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Writing Center: Experimental Research Papers

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FAQs About Experimental Research Papers (APA)

What is a research paper? 

A researcher uses a research paper to explain how they conducted a research study to answer a question or test a hypothesis. They explain why they conducted the study, the research question or hypothesis they tested, how they conducted the study, the results of their study, and the implications of these results. 

What is the purpose of an experimental research paper? 

A research paper is intended to inform others about advancement in a particular field of study. The researcher who wrote the paper identified a gap in the research in a field of study and used their research to help fill this gap. The researcher uses their paper to inform others about the knowledge that the results of their study contribute. 

What sections are included in an experimental research paper?

A typical research paper contains a Title Page, Abstract, Introduction, Methods, Results, Discussion, and References section. Some also contain a Table and Figures section and Appendix section. 

What citation style is used for experimental research papers? 

APA (American Psychological Association) style is most commonly used for research papers. 

Structure Of Experimental Research Papers (APA)

• Answers the question of “What is this paper about and who wrote it?”
• Located on the first page of the paper 
• The author’s note acknowledges any support that the authors received from others
• A student paper also includes the course number and name, instructor’s name, and assignment due date
• Contains a title that summarizes the purpose and content of the research study and engages the audience 
• No longer than 250 words
• Summarizes important background information, the research questions and/or hypothesis, methods, key findings, and implications of the findings
• Explains what the topic of the research is and why the topic is worth studying
• Summarizes and discusses prior research conducted on the topic 
• Identifies unresolved issues and gaps in past research that the current research will address
• Ends with an overview of the current research study, including how the independent and dependent variables, the research questions or hypotheses, and the objective of the research 
• Explains how the research study was conducted 
• Typically includes 3 sections: Participants, Materials, and Procedure
• Includes characteristics of the subjects, how the subjects were selected and recruited, how their anonymity was protected, and what feedback was provided to the participants
• Describes any equipment, surveys, tests, questionnaires, informed consent forms, and observational techniques 
• Describes the independent and dependent variables, the type of research design, and how the data was collected
• Explains what results were found in the research study 
• Describes the data that was collected and the results of statistical tests 
• Explains the significance of the results 
• Accepts or denies the hypotheses 
• Details the implications of these findings 
• Addresses the limitations of the study and areas for future research 
• Includes all sources that were mentioned in the research study 
• Adheres to APA citation styles
• Includes all tables and/or figures that were used in the research study 
• Each table and figure is placed on a separate page 
• Tables are included before figures
• Begins with a bolded, centered header such as “ Table 1 ”
• Appends all forms, surveys, tests, etc. that were used in the study 
• Only includes documents that were referenced in the Methods section 
• Each entry is placed on a separate page 
• Begins with a bolded, centered header such as “ Appendix A ”

Tips For Experimental Research Papers (APA)

• Initial interest will motivate you to complete your study 
• Your entire study will be centered around this question or statement 
• Use only verifiable sources that provide accurate information about your topic 
• You need to thoroughly understand the field of study your topic is on to help you recognize the gap your research will fill and the significance of your results
• This will help you identify what you should study and what the significance of your study will be 
• Create an outline before you begin writing to help organize your thoughts and direct you in your writing 
• This will prevent you from losing the source or forgetting to cite the source 
• Work on one section at a time, rather than trying to complete multiple sections at once
• This information can be easily referred to as your write your various sections 
• When conducting your research, working general to specific will help you narrow your topic and fully understand the field your topic is in 
• When writing your literature review, writing from general to specific will help the audience understand your overall topic and the narrow focus of your research 
• This will prevent you from losing sources you may need later 
• Incorporate correct APA formatting as you write, rather than changing the formatting at the end of the writing process 

Checklist For Experimental Research Papers (APA)

• If the paper is a student paper, it contains the title of the project, the author’s name(s), the instructor's name, course number and name, and assignment due date
• If the paper is a professional paper, it includes the title of the paper, the author’s name(s), the institutional affiliation, and the author note
• Begins on the first page of the paper
• The title is typed in upper and lowercase letters, four spaces below the top of the paper, and written in boldface 
• Other information is separated by a space from the title

Title (found on title page)

• Informs the audience about the purpose of the paper 
• Captures the attention of the audience 
• Accurately reflects the purpose and content of the research paper 

Abstract 

• Labeled as “ Abstract ”
• Begins on the second page 
• Provides a short, concise summary of the content of the research paper 
• Includes background information necessary to understand the topic 
• Background information demonstrates the purpose of the paper
• Contains the hypothesis and/or research questions addressed in the paper
• Has a brief description of the methods used 
• Details the key findings and significance of the results
• Illustrates the implications of the research study 
• Contains less than 250 words

Introduction 

• Starts on the third page 
• Includes the title of the paper in bold at the top of the page
• Contains a clear statement of the problem that the paper sets out to address 
• Places the research paper within the context of previous research on the topic 
• Explains the purpose of the research study and what you hope to find
• Describes the significance of the study 
• Details what new insights the research will contribute
• Concludes with a brief description of what information will be mentioned in the literature review

Literature Review

• Labeled as “ Literature Review”
• Presents a general description of the problem area 
• Defines any necessary terms 
• Discusses and summarizes prior research on the selected topic 
• Identifies any unresolved issues or gaps in research that the current research plans to address
• Concludes with a summary of the current research study, including the independent and dependent variables, the research questions or hypotheses, and the objective of the research  
• Labeled as “ Methods ”
• Efficiently explains how the research study was conducted 
• Appropriately divided into sections
• Describes the characteristics of the participants 
• Explains how the participants were selected 
• Details how the anonymity of the participants was protected 
• Notes what feedback the participants will be provided 
• Describes all materials and instruments that were used 
• Mentions how the procedure was conducted and data collected
• Notes the independent and dependent variables 
• Includes enough information that another researcher could duplicate the research 

Results 

• Labeled as “ Results ”
• Describes the data was collected
• Explains the results of statistical tests that were performed
• Omits any analysis or discussion of the implications of the study 

Discussion 

• Labeled as “ Discussion ”
• Describes the significance of the results 
• Relates the results to the research questions and/or hypotheses
• States whether the hypotheses should be rejected or accepted 
• Addresses limitations of the study, including potential bias, confounds, imprecision of measures, and limits to generalizability
• Explains how the study adds to the knowledge base and expands upon past research
• Labeled as “ References ”
• Correctly cites sources according to APA formatting 
• Orders sources alphabetically
• All sources included in the study are cited in the reference section 

Table and Figures (optional)

•  Each table and each figure is placed on a separate page 
• Tables and figures are included after the reference page
• Tables and figures are correctly labeled
• Each table and figure begins with a bolded, centered header such as “ Table 1 ,” “ Table 2 ,”

Appendix (optional) 

• Any forms, surveys, tests, etc. are placed in the Appendix
• All appendix entries are mentioned in the Methods section 
• Each appendix begins on a new page
• Each appendix begins with a bolded, centered header such as “ Appendix A, ” “ Appendix B ”

Additional Resources For Experimental Research Papers (APA)

• https://www.mcwritingcenterblog.org/single-post/how-to-conduct-research-using-the-library-s-resources
• https://www.mcwritingcenterblog.org/single-post/how-to-read-academic-articles
• https://researchguides.ben.edu/source-evaluation   
• https://researchguides.library.brocku.ca/external-analysis/evaluating-sources
• https://writing.wisc.edu/handbook/assignments/planresearchpaper/
• https://nmu.edu/writingcenter/tips-writing-research-paper
• https://writingcenter.gmu.edu/guides/how-to-write-a-research-question
• https://www.unr.edu/writing-speaking-center/student-resources/writing-speaking-resources/guide-to-writing-research-papers
• https://drive.google.com/drive/folders/1F4DFWf85zEH4aZvm10i8Ahm_3xnAekal?usp=sharing
• https://owl.purdue.edu/owl/research_and_citation/apa_style/apa_formatting_and_style_guide/general_format.html
• https://libguides.elmira.edu/research
• https://www.nhcc.edu/academics/library/doing-library-research/basic-steps-research-process
• https://libguides.wustl.edu/research
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• Beauty sleep:...

Beauty sleep: experimental study on the perceived health and attractiveness of sleep deprived people

• Related content
• Peer review
• John Axelsson , researcher 1 2 ,
• Tina Sundelin , research assistant and MSc student 2 ,
• Michael Ingre , statistician and PhD student 3 ,
• Eus J W Van Someren , researcher 4 ,
• Andreas Olsson , researcher 2 ,
• Mats Lekander , researcher 1 3
• 1 Osher Center for Integrative Medicine, Department of Clinical Neuroscience, Karolinska Institutet, 17177 Stockholm, Sweden
• 2 Division for Psychology, Department of Clinical Neuroscience, Karolinska Institutet
• 3 Stress Research Institute, Stockholm University, Stockholm
• 4 Netherlands Institute for Neuroscience, an Institute of the Royal Netherlands Academy of Arts and Sciences, and VU Medical Center, Amsterdam, Netherlands
• Correspondence to: J Axelsson john.axelsson{at}ki.se
• Accepted 22 October 2010

Objective To investigate whether sleep deprived people are perceived as less healthy, less attractive, and more tired than after a normal night’s sleep.

Design Experimental study.

Setting Sleep laboratory in Stockholm, Sweden.

Participants 23 healthy, sleep deprived adults (age 18-31) who were photographed and 65 untrained observers (age 18-61) who rated the photographs.

Intervention Participants were photographed after a normal night’s sleep (eight hours) and after sleep deprivation (31 hours of wakefulness after a night of reduced sleep). The photographs were presented in a randomised order and rated by untrained observers.

Main outcome measure Difference in observer ratings of perceived health, attractiveness, and tiredness between sleep deprived and well rested participants using a visual analogue scale (100 mm).

Results Sleep deprived people were rated as less healthy (visual analogue scale scores, mean 63 (SE 2) v 68 (SE 2), P<0.001), more tired (53 (SE 3) v 44 (SE 3), P<0.001), and less attractive (38 (SE 2) v 40 (SE 2), P<0.001) than after a normal night’s sleep. The decrease in rated health was associated with ratings of increased tiredness and decreased attractiveness.

Conclusion Our findings show that sleep deprived people appear less healthy, less attractive, and more tired compared with when they are well rested. This suggests that humans are sensitive to sleep related facial cues, with potential implications for social and clinical judgments and behaviour. Studies are warranted for understanding how these effects may affect clinical decision making and can add knowledge with direct implications in a medical context.

Introduction

The recognition [of the case] depends in great measure on the accurate and rapid appreciation of small points in which the diseased differs from the healthy state Joseph Bell (1837-1911)

Good clinical judgment is an important skill in medical practice. This is well illustrated in the quote by Joseph Bell, 1 who demonstrated impressive observational and deductive skills. Bell was one of Sir Arthur Conan Doyle’s teachers and served as a model for the fictitious detective Sherlock Holmes. 2 Generally, human judgment involves complex processes, whereby ingrained, often less consciously deliberated responses from perceptual cues are mixed with semantic calculations to affect decision making. 3 Thus all social interactions, including diagnosis in clinical practice, are influenced by reflexive as well as reflective processes in human cognition and communication.

Sleep is an essential homeostatic process with well established effects on an individual’s physiological, cognitive, and behavioural functionality 4 5 6 7 and long term health, 8 but with only anecdotal support of a role in social perception, such as that underlying judgments of attractiveness and health. As illustrated by the common expression “beauty sleep,” an individual’s sleep history may play an integral part in the perception and judgments of his or her attractiveness and health. To date, the concept of beauty sleep has lacked scientific support, but the biological importance of sleep may have favoured a sensitivity to perceive sleep related cues in others. It seems warranted to explore such sensitivity, as sleep disorders and disturbed sleep are increasingly common in today’s 24 hour society and often coexist with some of the most common health problems, such as hypertension 9 10 and inflammatory conditions. 11

To describe the relation between sleep deprivation and perceived health and attractiveness we asked untrained observers to rate the faces of people who had been photographed after a normal night’s sleep and after a night of sleep deprivation. We chose facial photographs as the human face is the primary source of information in social communication. 12 A perceiver’s response to facial cues, signalling the bearer’s emotional state, intentions, and potential mate value, serves to guide actions in social contexts and may ultimately promote survival. 13 14 15 We hypothesised that untrained observers would perceive sleep deprived people as more tired, less healthy, and less attractive compared with after a normal night’s sleep.

Using an experimental design we photographed the faces of 23 adults (mean age 23, range 18-31 years, 11 women) between 14.00 and 15.00 under two conditions in a balanced design: after a normal night’s sleep (at least eight hours of sleep between 23.00-07.00 and seven hours of wakefulness) and after sleep deprivation (sleep 02.00-07.00 and 31 hours of wakefulness). We advertised for participants at four universities in the Stockholm area. Twenty of 44 potentially eligible people were excluded. Reasons for exclusion were reported sleep disturbances, abnormal sleep requirements (for example, sleep need out of the 7-9 hour range), health problems, or availability on study days (the main reason). We also excluded smokers and those who had consumed alcohol within two days of the protocol. One woman failed to participate in both conditions. Overall, we enrolled 12 women and 12 men.

The participants slept in their own homes. Sleep times were confirmed with sleep diaries and text messages. The sleep diaries (Karolinska sleep diary) included information on sleep latency, quality, duration, and sleepiness. Participants sent a text message to the research assistant by mobile phone (SMS) at bedtime and when they got up on the night before sleep deprivation. They had been instructed not to nap. During the normal sleep condition the participants’ mean duration of sleep, estimated from sleep diaries, was 8.45 (SE 0.20) hours. The sleep deprivation condition started with a restriction of sleep to five hours in bed; the participants sent text messages (SMS) when they went to sleep and when they woke up. The mean duration of sleep during this night, estimated from sleep diaries and text messages, was 5.06 (SE 0.04) hours. For the following night of total sleep deprivation, the participants were monitored in the sleep laboratory at all times. Thus, for the sleep deprivation condition, participants came to the laboratory at 22.00 (after 15 hours of wakefulness) to be monitored, and stayed awake for a further 16 hours. We therefore did not observe the participants during the first 15 hours of wakefulness, when they had had a slightly restricted sleep, but had good control over the last 16 hours of wakefulness when sleepiness increased in magnitude. For the sleep condition, participants came to the laboratory at 12.00 (after five hours of wakefulness). They were kept indoors two hours before being photographed to avoid the effects of exposure to sunlight and the weather. We had a series of five or six photographs (resolution 3872×2592 pixels) taken in a well lit room, with a constant white balance (×900l; colour temperature 4200 K, Nikon D80; Nikon, Tokyo). The white balance was differently set during the two days of the study and affected seven photographs (four taken during sleep deprivation and three during a normal night’s sleep). Removing these participants from the analyses did not affect the results. The distance from camera to head was fixed, as was the focal length, within 14 mm (between 44 and 58 mm). To ensure a fixed surface area of each face on the photograph, the focal length was adapted to the head size of each participant.

For the photo shoot, participants wore no makeup, had their hair loose (combed backwards if long), underwent similar cleaning or shaving procedures for both conditions, and were instructed to “sit with a straight back and look straight into the camera with a neutral, relaxed facial expression.” Although the photographer was not blinded to the sleep conditions, she followed a highly standardised procedure during each photo shoot, including minimal interaction with the participants. A blinded rater chose the most typical photograph from each series of photographs. This process resulted in 46 photographs; two (one from each sleep condition) of each of the 23 participants. This part of the study took place between June and September 2007.

In October 2007 the photographs were presented at a fixed interval of six seconds in a randomised order to 65 observers (mainly students at the Karolinska Institute, mean age 30 (range 18-61) years, 40 women), who were unaware of the conditions of the study. They rated the faces for attractiveness (very unattractive to very attractive), health (very sick to very healthy), and tiredness (not at all tired to very tired) on a 100 mm visual analogue scale. After every 23 photographs a brief intermission was allowed, including a working memory task lasting 23 seconds to prevent the faces being memorised. To ensure that the observers were not primed to tiredness when rating health and attractiveness they rated the photographs for attractiveness and health in the first two sessions and tiredness in the last. To avoid the influence of possible order effects we presented the photographs in a balanced order between conditions for each session.

Statistical analyses

Data were analysed using multilevel mixed effects linear regression, with two crossed independent random effects accounting for random variation between observers and participants using the xtmixed procedure in Stata 9.2. We present the effect of condition as a percentage of change from the baseline condition as the reference using the absolute value in millimetres (rated on the visual analogue scale). No data were missing in the analyses.

Sixty five observers rated each of the 46 photographs for attractiveness, health, and tiredness: 138 ratings by each observer and 2990 ratings for each of the three factors rated. When sleep deprived, people were rated as less healthy (visual analogue scale scores, mean 63 (SE 2) v 68 (SE 2)), more tired (53 (SE 3) v 44 (SE 3)), and less attractive (38 (SE 2) v 40 (SE 2); P<0.001 for all) than after a normal night’s sleep (table 1 ⇓ ). Compared with the normal sleep condition, perceptions of health and attractiveness in the sleep deprived condition decreased on average by 6% and 4% and tiredness increased by 19%.

 Multilevel mixed effects regression on effect of how sleep deprived people are perceived with respect to attractiveness, health, and tiredness

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A 10 mm increase in tiredness was associated with a −3.0 mm change in health, a 10 mm increase in health increased attractiveness by 2.4 mm, and a 10 mm increase in tiredness reduced attractiveness by 1.2 mm (table 2 ⇓ ). These findings were also presented as correlation, suggesting that faces with perceived attractiveness are positively associated with perceived health (r=0.42, fig 1 ⇓ ) and negatively with perceived tiredness (r=−0.28, fig 1). In addition, the average decrease (for each face) in attractiveness as a result of deprived sleep was associated with changes in tiredness (−0.53, n=23, P=0.03) and in health (0.50, n=23, P=0.01). Moreover, a strong negative association was found between the respective perceptions of tiredness and health (r=−0.54, fig 1). Figure 2 ⇓ shows an example of observer rated faces.

 Associations between health, tiredness, and attractiveness

Fig 1  Relations between health, tiredness, and attractiveness of 46 photographs (two each of 23 participants) rated by 65 observers on 100 mm visual analogue scales, with variation between observers removed using empirical Bayes’ estimates

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Fig 2  Participant after a normal night’s sleep (left) and after sleep deprivation (right). Faces were presented in a counterbalanced order

To evaluate the mediation effects of sleep loss on attractiveness and health, tiredness was added to the models presented in table 1 following recommendations. 16 The effect of sleep loss was significantly mediated by tiredness on both health (P<0.001) and attractiveness (P<0.001). When tiredness was added to the model (table 1) with an estimated coefficient of −2.9 (SE 0.1; P<0.001) the independent effect of sleep loss on health decreased from −4.2 to −1.8 (SE 0.5; P<0.001). The effect of sleep loss on attractiveness decreased from −1.6 (table 1) to −0.62 (SE 0.4; P=0.133), with tiredness estimated at −1.1 (SE 0.1; P<0.001). The same approach applied to the model of attractiveness and health (table 2), with a decrease in the association from 2.4 to 2.1 (SE 0.1; P<0.001) with tiredness estimated at −0.56 (SE 0.1; P<0.001).

Sleep deprived people are perceived as less attractive, less healthy, and more tired compared with when they are well rested. Apparent tiredness was strongly related to looking less healthy and less attractive, which was also supported by the mediating analyses, indicating that a large part of the found effects and relations on appearing healthy and attractive were mediated by looking tired. The fact that untrained observers detected the effects of sleep loss in others not only provides evidence for a perceptual ability not previously subjected to experimental control, but also supports the notion that sleep history gives rise to socially relevant signals that provide information about the bearer. The adaptiveness of an ability to detect sleep related facial cues resonates well with other research, showing that small deviations from the average sleep duration in the long term are associated with an increased risk of health problems and with a decreased longevity. 8 17 Indeed, even a few hours of sleep deprivation inflict an array of physiological changes, including neural, endocrinological, immunological, and cellular functioning, that if sustained are relevant for long term health. 7 18 19 20 Here, we show that such physiological changes are paralleled by detectable facial changes.

These results are related to photographs taken in an artificial setting and presented to the observers for only six seconds. It is likely that the effects reported here would be larger in real life person to person situations, when overt behaviour and interactions add further information. Blink interval and blink duration are known to be indicators of sleepiness, 21 and trained observers are able to evaluate reliably the drowsiness of drivers by watching their videotaped faces. 22 In addition, a few of the people were perceived as healthier, less tired, and more attractive during the sleep deprived condition. It remains to be evaluated in follow-up research whether this is due to random error noise in judgments, or associated with specific characteristics of observers or the sleep deprived people they judge. Nevertheless, we believe that the present findings can be generalised to a wide variety of settings, but further studies will have to investigate the impact on clinical studies and other social situations.

Importantly, our findings suggest a prominent role of sleep history in several domains of interpersonal perception and judgment, in which sleep history has previously not been considered of importance, such as in clinical judgment. In addition, because attractiveness motivates sexual behaviour, collaboration, and superior treatment, 13 sleep loss may have consequences in other social contexts. For example, it has been proposed that facial cues perceived as attractive are signals of good health and that this recognition has been selected evolutionarily to guide choice of mate and successful transmission of genes. 13 The fact that good sleep supports a healthy look and poor sleep the reverse may be of particular relevance in the medical setting, where health estimates are an essential part. It is possible that people with sleep disturbances, clinical or otherwise, would be judged as more unhealthy, whereas those who have had an unusually good night’s sleep may be perceived as rather healthy. Compared with the sleep deprivation used in the present investigation, further studies are needed to investigate the effects of less drastic acute reductions of sleep as well as long term clinical effects.

Conclusions

People are capable of detecting sleep loss related facial cues, and these cues modify judgments of another’s health and attractiveness. These conclusions agree well with existing models describing a link between sleep and good health, 18 23 as well as a link between attractiveness and health. 13 Future studies should focus on the relevance of these facial cues in clinical settings. These could investigate whether clinicians are better than the average population at detecting sleep or health related facial cues, and whether patients with a clinical diagnosis exhibit more tiredness and are less healthy looking than healthy people. Perhaps the more successful doctors are those who pick up on these details and act accordingly.

Taken together, our results provide important insights into judgments about health and attractiveness that are reminiscent of the anecdotal wisdom harboured in Bell’s words, and in the colloquial notion of “beauty sleep.”

What is already known on this topic

Short or disturbed sleep and fatigue constitute major risk factors for health and safety

Complaints of short or disturbed sleep are common among patients seeking healthcare

The human face is the main source of information for social signalling

What this study adds

The facial cues of sleep deprived people are sufficient for others to judge them as more tired, less healthy, and less attractive, lending the first scientific support to the concept of “beauty sleep”

By affecting doctors’ general perception of health, the sleep history of a patient may affect clinical decisions and diagnostic precision

Cite this as: BMJ 2010;341:c6614

We thank B Karshikoff for support with data acquisition and M Ingvar for comments on an earlier draft of the manuscript, both without compensation and working at the Department for Clinical Neuroscience, Karolinska Institutet, Sweden.

Contributors: JA designed the data collection, supervised and monitored data collection, wrote the statistical analysis plan, carried out the statistical analyses, obtained funding, drafted and revised the manuscript, and is guarantor. TS designed and carried out the data collection, cleaned the data, drafted, revised the manuscript, and had final approval of the manuscript. JA and TS contributed equally to the work. MI wrote the statistical analysis plan, carried out the statistical analyses, drafted the manuscript, and critically revised the manuscript. EJWVS provided statistical advice, advised on data handling, and critically revised the manuscript. AO provided advice on the methods and critically revised the manuscript. ML provided administrative support, drafted the manuscript, and critically revised the manuscript. All authors approved the final version of the manuscript.

Funding: This study was funded by the Swedish Society for Medical Research, Rut and Arvid Wolff’s Memory Fund, and the Osher Center for Integrative Medicine.

Competing interests: All authors have completed the Unified Competing Interest form at www.icmje.org/coi_disclosure.pdf (available on request from the corresponding author) and declare: no support from any company for the submitted work; no financial relationships with any companies that might have an interest in the submitted work in the previous 3 years; no other relationships or activities that could appear to have influenced the submitted work.

Ethical approval: This study was approved by the Karolinska Institutet’s ethical committee. Participants were compensated for their participation.

Participant consent: Participant’s consent obtained.

Data sharing: Statistical code and dataset of ratings are available from the corresponding author at john.axelsson{at}ki.se .

This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is non commercial and is otherwise in compliance with the license. See: http://creativecommons.org/licenses/by-nc/2.0/ and http://creativecommons.org/licenses/by-nc/2.0/legalcode .

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Experimental Research Design — 6 mistakes you should never make!

Since school days’ students perform scientific experiments that provide results that define and prove the laws and theorems in science. These experiments are laid on a strong foundation of experimental research designs.

An experimental research design helps researchers execute their research objectives with more clarity and transparency.

In this article, we will not only discuss the key aspects of experimental research designs but also the issues to avoid and problems to resolve while designing your research study.

Table of Contents

What Is Experimental Research Design?

Experimental research design is a framework of protocols and procedures created to conduct experimental research with a scientific approach using two sets of variables. Herein, the first set of variables acts as a constant, used to measure the differences of the second set. The best example of experimental research methods is quantitative research .

Experimental research helps a researcher gather the necessary data for making better research decisions and determining the facts of a research study.

When Can a Researcher Conduct Experimental Research?

A researcher can conduct experimental research in the following situations —

• When time is an important factor in establishing a relationship between the cause and effect.
• When there is an invariable or never-changing behavior between the cause and effect.
• Finally, when the researcher wishes to understand the importance of the cause and effect.

Importance of Experimental Research Design

To publish significant results, choosing a quality research design forms the foundation to build the research study. Moreover, effective research design helps establish quality decision-making procedures, structures the research to lead to easier data analysis, and addresses the main research question. Therefore, it is essential to cater undivided attention and time to create an experimental research design before beginning the practical experiment.

By creating a research design, a researcher is also giving oneself time to organize the research, set up relevant boundaries for the study, and increase the reliability of the results. Through all these efforts, one could also avoid inconclusive results. If any part of the research design is flawed, it will reflect on the quality of the results derived.

Types of Experimental Research Designs

Based on the methods used to collect data in experimental studies, the experimental research designs are of three primary types:

1. Pre-experimental Research Design

A research study could conduct pre-experimental research design when a group or many groups are under observation after implementing factors of cause and effect of the research. The pre-experimental design will help researchers understand whether further investigation is necessary for the groups under observation.

Pre-experimental research is of three types —

• One-shot Case Study Research Design
• One-group Pretest-posttest Research Design
• Static-group Comparison

2. True Experimental Research Design

A true experimental research design relies on statistical analysis to prove or disprove a researcher’s hypothesis. It is one of the most accurate forms of research because it provides specific scientific evidence. Furthermore, out of all the types of experimental designs, only a true experimental design can establish a cause-effect relationship within a group. However, in a true experiment, a researcher must satisfy these three factors —

• There is a control group that is not subjected to changes and an experimental group that will experience the changed variables
• A variable that can be manipulated by the researcher
• Random distribution of the variables

This type of experimental research is commonly observed in the physical sciences.

3. Quasi-experimental Research Design

The word “Quasi” means similarity. A quasi-experimental design is similar to a true experimental design. However, the difference between the two is the assignment of the control group. In this research design, an independent variable is manipulated, but the participants of a group are not randomly assigned. This type of research design is used in field settings where random assignment is either irrelevant or not required.

The classification of the research subjects, conditions, or groups determines the type of research design to be used.

Advantages of Experimental Research

Experimental research allows you to test your idea in a controlled environment before taking the research to clinical trials. Moreover, it provides the best method to test your theory because of the following advantages:

• Researchers have firm control over variables to obtain results.
• The subject does not impact the effectiveness of experimental research. Anyone can implement it for research purposes.
• The results are specific.
• Post results analysis, research findings from the same dataset can be repurposed for similar research ideas.
• Researchers can identify the cause and effect of the hypothesis and further analyze this relationship to determine in-depth ideas.
• Experimental research makes an ideal starting point. The collected data could be used as a foundation to build new research ideas for further studies.

6 Mistakes to Avoid While Designing Your Research

There is no order to this list, and any one of these issues can seriously compromise the quality of your research. You could refer to the list as a checklist of what to avoid while designing your research.

1. Invalid Theoretical Framework

Usually, researchers miss out on checking if their hypothesis is logical to be tested. If your research design does not have basic assumptions or postulates, then it is fundamentally flawed and you need to rework on your research framework.

2. Inadequate Literature Study

Without a comprehensive research literature review , it is difficult to identify and fill the knowledge and information gaps. Furthermore, you need to clearly state how your research will contribute to the research field, either by adding value to the pertinent literature or challenging previous findings and assumptions.

3. Insufficient or Incorrect Statistical Analysis

Statistical results are one of the most trusted scientific evidence. The ultimate goal of a research experiment is to gain valid and sustainable evidence. Therefore, incorrect statistical analysis could affect the quality of any quantitative research.

4. Undefined Research Problem

This is one of the most basic aspects of research design. The research problem statement must be clear and to do that, you must set the framework for the development of research questions that address the core problems.

5. Research Limitations

Every study has some type of limitations . You should anticipate and incorporate those limitations into your conclusion, as well as the basic research design. Include a statement in your manuscript about any perceived limitations, and how you considered them while designing your experiment and drawing the conclusion.

6. Ethical Implications

The most important yet less talked about topic is the ethical issue. Your research design must include ways to minimize any risk for your participants and also address the research problem or question at hand. If you cannot manage the ethical norms along with your research study, your research objectives and validity could be questioned.

Experimental Research Design Example

In an experimental design, a researcher gathers plant samples and then randomly assigns half the samples to photosynthesize in sunlight and the other half to be kept in a dark box without sunlight, while controlling all the other variables (nutrients, water, soil, etc.)

By comparing their outcomes in biochemical tests, the researcher can confirm that the changes in the plants were due to the sunlight and not the other variables.

Experimental research is often the final form of a study conducted in the research process which is considered to provide conclusive and specific results. But it is not meant for every research. It involves a lot of resources, time, and money and is not easy to conduct, unless a foundation of research is built. Yet it is widely used in research institutes and commercial industries, for its most conclusive results in the scientific approach.

Have you worked on research designs? How was your experience creating an experimental design? What difficulties did you face? Do write to us or comment below and share your insights on experimental research designs!

Frequently Asked Questions

Randomization is important in an experimental research because it ensures unbiased results of the experiment. It also measures the cause-effect relationship on a particular group of interest.

Experimental research design lay the foundation of a research and structures the research to establish quality decision making process.

There are 3 types of experimental research designs. These are pre-experimental research design, true experimental research design, and quasi experimental research design.

The difference between an experimental and a quasi-experimental design are: 1. The assignment of the control group in quasi experimental research is non-random, unlike true experimental design, which is randomly assigned. 2. Experimental research group always has a control group; on the other hand, it may not be always present in quasi experimental research.

Experimental research establishes a cause-effect relationship by testing a theory or hypothesis using experimental groups or control variables. In contrast, descriptive research describes a study or a topic by defining the variables under it and answering the questions related to the same.

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Experimental Research on Dreaming: State of the Art and Neuropsychoanalytic Perspectives

Perrine m. ruby.

1 INSERM U1028, Lyon Neuroscience Research Center, Brain Dynamics and Cognition Team, Lyon, France

2 CNRS UMR5292, Lyon Neuroscience Research Center, Brain Dynamics and Cognition Team, Lyon, France

3 University Lyon 1, Lyon, France

Dreaming is still a mystery of human cognition, although it has been studied experimentally for more than a century. Experimental psychology first investigated dream content and frequency. The neuroscientific approach to dreaming arose at the end of the 1950s and soon proposed a physiological substrate of dreaming: rapid eye movement sleep. Fifty years later, this hypothesis was challenged because it could not explain all of the characteristics of dream reports. Therefore, the neurophysiological correlates of dreaming are still unclear, and many questions remain unresolved. Do the representations that constitute the dream emerge randomly from the brain, or do they surface according to certain parameters? Is the organization of the dream’s representations chaotic or is it determined by rules? Does dreaming have a meaning? What is/are the function(s) of dreaming? Psychoanalysis provides hypotheses to address these questions. Until now, these hypotheses have received minimal attention in cognitive neuroscience, but the recent development of neuropsychoanalysis brings new hopes of interaction between the two fields. Considering the psychoanalytical perspective in cognitive neuroscience would provide new directions and leads for dream research and would help to achieve a comprehensive understanding of dreaming. Notably, several subjective issues at the core of the psychoanalytic approach, such as the concept of personal meaning, the concept of unconscious episodic memory and the subject’s history, are not addressed or considered in cognitive neuroscience. This paper argues that the focus on singularity and personal meaning in psychoanalysis is needed to successfully address these issues in cognitive neuroscience and to progress in the understanding of dreaming and the psyche.

The word “dream” is commonly used to express an unattainable ideal or a very deep and strong desire:

I have a dream that my four little children will one day live in a nation where they will not be judged by the color of their skin, but by the content of their character. Martin Luther King

In dream reports, however, one often notices banal situations, strange scenes, or even frightening events. Why is there such a contrast between the popular meaning of the word “dream” and the content of dream reports? Why are some dream scenes so bizarre? Are dreams built from images that arise randomly from the sleeping brain? Or is the emergence and organization of dream images controlled by currently unknown parameters? Does dreaming have a function?

Answering these questions is not easy because dreaming is elusive. We still do not know when it happens during the night, how long it lasts, whether we can recall its entire content, or how to control it. For more than a century, such limited understanding of dreaming has seriously hampered experimental investigations. Nonetheless, scientific research has managed to produce considerable information about the phenomenology and physiology of dreaming and has improved our understanding of this fascinating phenomenon.

Experimental Research on Dreaming

Dreaming and experimental psychology, dream content.

Dreaming was first investigated on an experimental level in the nineteenth century. Calkins ( 1893 ) published the first statistical results about dreaming and argued that some aspects of dream content could be quantified. Later, questionnaires and automatic analysis of the lexical content of dream reports allowed psychologists to show that dream content has some precise phenomenological characteristics. According to psychological studies (Hall and Van de Castle, 1966 ; Schwartz, 1999 ), visual imagery occurs more frequently in dreams than imagery of other senses (audition, olfaction, touch, and taste); the dream drama is mostly lived by the dreamer from a first-person perspective; some elements of real-life events previously experienced by the dreamer often contribute to the scene of the dream; most often, the dream sequence is not within the dreamer’s voluntary control (i.e., the dreamer may be convinced during the dream that the dream’s story is really happening); temporal and spatial incoherencies can occur in the dream story; the dream report is often full of people interacting with each other (e.g., discussions, fights, pursuit, sexuality); and finally, the dream report often contains strong emotions.

Substantial variability of content exists, however, among the same individual’s dreams and among the dreams of different individuals. Further, psychological studies have shown that many internal and external parameters can influence dream content. For example, males report more aggression and violence in their dreams than do females (Nielsen et al., 2003 ; Schredl et al., 2004 ). External stimulation perceived by the dreamer can be incorporated into dreams (Koulack, 1969 ; Saint-Denys, 1867; Hoelscher et al., 1981 ), as illustrated by the famous Dali painting Dream Caused by the Flight of a Bee around a Pomegranate a Second before Awakening . The current concerns of the subject may also be found in the content of his/her dreams (Schwartz, 1999 ; Domhoff and Schneider, 2008 ), and many aspects of the subject’s daily life were found to influence dream content, including news events (Bulkeley and Kahan, 2008 ), musical practice (Uga et al., 2006 ), religious beliefs (Domhoff and Schneider, 2008 ), chronic pain (Raymond et al., 2002 ), mood (Cartwright et al., 1998a ), or a violent living environment (Valli et al., 2005 ). By contrast, congenital or acquired malformations do not seem to significantly influence dream content (Voss et al., 2010 ; Saurat et al., 2011 ).

Based on these results, two opposing hypotheses were formulated: the continuity hypothesis (Schredl and Hofmann, 2003 ) and the discontinuity hypothesis (Rechtschaffen, 1978 ; Kahn et al., 1997 ; Stickgold et al., 2001 ). The former relies on results showing that the themes of an individual’s thoughts during waking life and dreaming are similar; the latter focuses on the fundamentally different structures of thoughts during waking life and dreaming. Voss et al. ( 2010 ) stressed in their recent paper that these hypotheses represent oversimplified approaches to dream analysis and argued that waking and dreaming thoughts were related but structurally independent; in other words, she argued in favor of merging the continuity and discontinuity hypotheses.

Dream report frequency

Dream report frequency (DRF) can vary within subjects and varies substantially among subjects. In a study of 900 German subjects with a large age range from various socioprofessional categories, the mean DRF was approximately 1 dream report per week (Schredl, 2008 ). This result shows that the dream experience is common and familiar to everyone. Psychological studies have demonstrated that many parameters covary with DRF and may thus influence it.

Sleep parameters

First, DRF varies according to the sleep stage preceding awakening (e.g., Dement and Kleitman, 1957b ; Nielsen, 2000 , for a review). More dream reports are obtained after an awakening during rapid eye movement (REM) sleep than after an awakening during non-REM (NREM) sleep. These results inspired the REM sleep hypothesis of dreaming (see the section Dreaming and Neuroscience). Second, DRF increases with the number of awakenings during sleep, according to retrospective self-evaluations of awakenings (Cory and Ormiston, 1975 ; Schredl et al., 2003 ). Such studies showed that the more the subjects tended to awaken during sleep, the higher their DRF. These results support the hypothesis of Koulack and Goodenough ( 1976 ), which proposes that nocturnal awakenings facilitate the encoding of the dream in memory and thus facilitate dream recall upon awakening. However, this hypothesis has not been tested by measuring awakenings with polysomnographic recordings in healthy subjects with various DRFs. Finally, DRF varies according to the method of awakening. Abrupt awakenings lead to more dream reports than gradual awakenings (Shapiro et al., 1963 , 1965 ; Goodenough et al., 1965 ).

Physiological and environmental parameters

Dream report frequency deceases with age (e.g., Schredl, 2008 ) and tends to be slightly higher among females than males (e.g., Schredl, 2008 ; Schredl and Reinhard, 2008 ). Remarkably, Schredl’s ( 2008 ) results revealed that DRF also varied according to the size of the subject’s place of residence.

Psychological parameters

First, increased professional stress or interpersonal stress resulted in an increase in DRF (for a review, see Schredl, 1999 ). Second, an interest in dreams or a positive attitude toward dreams clearly covaries with DRF (Hill et al., 1997 ; Schredl, 1999 ; Schredl et al., 2003 ). The greater an individual’s interest in dreams, the higher his/her DRF. Third, several cognitive abilities have been found to covary with DRF. Contradictory results have been reported for the correlation between DRF and memory abilities (short-term, long-term, visual, verbal, implicit, and explicit; significant positive correlation: Cory and Ormiston, 1975 ; Belicki et al., 1978 ; Butler and Watson, 1985 ; Schredl et al., 1995 ; Solms, 1997 ; no significant correlation: Cohen, 1971 ; Belicki et al., 1978 ; Schredl et al., 1995 , 1997 , 2003 ; Solms, 1997 ) and the correlation between DRF and visual imagery ( significant positive correlation : Hiscock and Cohen, 1973 ; Richardson, 1979 ; Okada et al., 2000 ; no significant correlation : Hill et al., 1997 ; Okada et al., 2000 ). However, several studies have consistently shown that DRF is positively correlated with creativity (Fitch and Armitage, 1989 ; Schredl, 1999 ; Schredl et al., 2003 ) and intelligence scales (multiple-choice vocabulary test, Schonbar, 1959 ; Shipley Intelligence Scale, Connor and Boblitt, 1970 ). Finally, many authors have reported a correlation between DRF and personality traits. Subjects with a high DRF are more likely to have a personality with thinner boundaries (Hartmann described people with thin boundaries as being open, trustworthy, vulnerable, and sensitive; Hartmann, 1989 ; Hartmann et al., 1991 ; Schredl et al., 2003 ), to be more anxious (Schonbar, 1959 ; Tart, 1962 ), to have a higher level of absorption (the absorption scale measures the capacity to become absorptively involved in imaginative and esthetic experiences; Hill et al., 1997 ; Schredl, 1999 ; Schredl et al., 2003 ), to be more open to experience (Hill et al., 1997 ; Schredl et al., 2003 ), and to be less alexithymic (alexithymia is a personality variable that incorporates difficulty identifying and describing feelings, difficulty distinguishing between feelings and the physical sensation of emotional arousal, limited imaginative processes, and an externally oriented cognitive style; De Gennaro et al., 2003 ; Nielsen et al., 2011 ) compared to subjects with a low dream recall frequency. However, those results have not always been reproducible (e.g., Schredl, 2002 for openness to experience; Cory and Ormiston, 1975 ; Hill et al., 1997 for anxiety; Nielsen et al., 1997 for alexithymia) and, according to the recent review by Blagrove and Pace-Schott ( 2010 ), it is difficult to draw conclusions about a possible link between personality traits and DRF.

In conclusion, numerous parameters have been identified that covary with DRF. Schredl stressed in many of his papers that the studied parameters usually explain only a small percentage of the total variance (e.g., Schredl, 2008 ). Thus, the DRF variation profile suggests that the production, encoding and recall of dreams are influenced by numerous parameters that probably interact with each other.

Dreaming and neuroscience

The neuroscientific approach to dreaming arose at the end of the 1950s with the discovery of REM during human sleep by the American physiologist Nathaniel Kleitman and his team (Aserinsky and Kleitman, 1953 ; Dement and Kleitman, 1957a ). During these sleep episodes with saccades, the researchers noticed a decrease in voltage and an increase in frequency in the EEG, accompanied by an increase in cardiac frequency variability and a decrease in body movements. They concluded that these physiological modifications indicate a particular sleep stage, which they called REM sleep. A few years later, the French team led by neurobiologist Michel Jouvet discovered that the lack of movement during REM sleep in cats was due to a general muscular atonia, controlled notably by the locus coeruleus α in the brainstem (Jouvet and Michel, 1959 ; Berger, 1961 later showed that muscular atonia during REM sleep also occurs in humans). Interestingly, the inability to move during REM sleep indicates deep sleep and paradoxically, the fast EEG activity of REM sleep resembles EEG activity in wakefulness. Jouvet concluded that this particular physiological state is associated with a “third state” of the brain (in addition to the brain states associated with wakefulness and NREM sleep) which he called “paradoxical sleep” instead of “REM sleep” (Jouvet et al., 1959 ; Jouvet, 1992 ). Several years later, Fisher et al. ( 1965 ) discovered another physiological characteristic of REM sleep: the penile erection.

During the same period, the American team noticed that a subject awakened during REM sleep very often reported a dream (80% of awakenings in REM sleep vs. 6% of awakenings in NREM sleep are followed by a dream report, according to Dement and Kleitman, 1957b ). Researchers concluded that dreaming occurs during REM sleep. The eye movements of REM sleep would allow the dreamer to scan the imaginary scene of the dream (the scanning hypothesis); the cerebral cortex activation revealed by the rapid EEG would allow intense cognitive activity, creating the complex stories of a dream; and the lack of muscle tone would prevent the dreamer from acting out his dreams. From that time on, researchers investigated REM sleep to obtain answers about dreaming.

In the 1990s, researchers used functional neuroimaging techniques such as positron emission tomography (PET) to investigate brain activity during REM sleep in humans. This new approach enabled researchers to demonstrate that the functional organization of the brain during REM sleep is different from the functional organization of the brain during wakefulness (Maquet et al., 1996 ; Braun et al., 1998 ). In comparison to wakefulness, brain activity during REM sleep is decreased in some brain regions (e.g., in the dorsolateral prefrontal cortex; Braun et al., 1998 ) and increased in other regions (e.g., in the occipital and temporal cortex, the hippocampus and parahippocampus, the anterior cingulate, the precentral and postcentral gyri, the superior parietal cortex, and the pons; Braun et al., 1998 ; Maquet et al., 2000 ). Looking more generally for brain activity correlating with REM sleep (the vigilance states considered included wakefulness, slow-wave sleep, and REM sleep), Maquet et al. ( 1996 ) found negative correlations in the precuneus, posterior cingulate cortex, temporoparietal junction, and dorsolateral prefrontal cortex and positive correlations in the amygdala, anterior cingulate, postcentral gyrus, thalamus, and pons (see Schwartz and Maquet, 2002 ; Maquet et al., 2005 ; Nir and Tononi, 2010 for reviews). Based on these results, researchers argued that the particular functional organization of the brain during REM sleep could explain the phenomenological characteristics of dream reports (Hobson and Pace-Schott, 2002 ; Schwartz and Maquet, 2002 ; Maquet et al., 2005 ; Nir and Tononi, 2010 ). They considered that brain activity increases and decreases during REM sleep could be interpreted on the basis of what we know about brain activity during wakefulness. In this context, the increased occipital cortex activity during REM sleep could explain the visual component of dream reports because neuroimaging results during wakefulness showed that visual imagery with the eyes closed activates the occipital cortex (Kosslyn and Thompson, 2003 ). The decreased activity in the temporoparietal junction during REM sleep may explain why dreams are mainly experienced in the egocentric coordinates of the first-person; indeed, during wakefulness, activity in the temporoparietal junction was reported to be greater for allocentric vs. egocentric representation (e.g., Ruby and Decety, 2001 ; Zacks et al., 2003 ) and for third- vs. first-person perspective (e.g., Ruby and Decety, 2003 , 2004 ). The increased activity in the hippocampus during REM sleep could explain why dreams are often composed of known images or characters, as the hippocampus is known to be associated with the encoding and retrieval of lived events during wakefulness (e.g., Piolino et al., 2009 ). The decreased activity in the lateral prefrontal cortex during REM sleep could explain why dream stories lack consistency, why the dreamer’s perception of time is altered, why the dream story is beyond the control of the dreamer and why the dreamer is convinced that the dream story is really happening. Indeed, during wakefulness, the lateral prefrontal cortex is involved in executive function, cognitive control, and working memory (Petrides, 2005 ; Koechlin and Hyafil, 2007 ). The increased activity in the medial prefrontal cortex during REM sleep could explain the attribution of thoughts, beliefs, and emotions to the characters in the dream because, during wakefulness, the medial prefrontal cortex is known to participate in mind reading (Ruby et al., 2007 , 2009 ; Legrand and Ruby, 2009 ). The increased activity in the motor cortex (precentral gyrus) during REM sleep could explain the movements of the characters’ bodies in the dream because, during wakefulness, motor imagery, and the imagination of someone’s action from the third-person perspective involve the precentral gyrus (Decety et al., 1994 ; Ruby and Decety, 2001 ). Finally, the amygdala’s activity during REM sleep could explain why emotions, especially fear, are often mentioned in dream reports; indeed, the amygdala is involved in the processing of emotional stimuli during wakefulness (Adolphs, 2008 ).

In conclusion, results from experimental psychology and neuroscience allow us to better understand the phenomenology of dreaming and the cerebral correlates of some characteristics of dream reports. Still, what do they tell us about the role of dreaming? What are the current hypotheses about dream function(s)?

Hypotheses about dream function(s)

No function.

At the end of the twentieth century, the neurologist Alan Hobson, who was profoundly anti-psychoanalysis, proposed a theory that deprived dreaming of any function. Hobson argued that dreaming is an epiphenomenon of REM sleep: “Because dreams are so difficult to remember, it seems unlikely that attention to their content could afford much in the way of high-priority survival value. Indeed, it might instead be assumed that dreaming is an epiphenomenon of REM sleep whose cognitive content is so ambiguous as to invite misleading or even erroneous interpretation” (Hobson et al., 1998 ).

Psychological individualism

In contrast, other teams, like Michel Jouvet’s, believed that dreaming serves a vital function. In 1979, Jouvet’s team blocked muscular atonia during REM sleep in a cat by damaging the locus coeruleus α in its brainstem. This lesion resulted in the appearance of movements during REM sleep. Movies from the Jouvet lab show sleeping cats performing complex motor actions (with altered control and coordination) resembling those of wakefulness, such as fur licking, growling, chasing prey, mastication, and fighting. From these videos, the authors concluded that the cat was acting out its dream, and they called this non-physiological state “oneiric behavior” (Sastre and Jouvet, 1979 ). These results led Jouvet to propose that dreaming plays a role in reinforcing a species’ typical behavior. Later in his career, Jouvet moved toward a hypothesis focusing on the role of dreaming in the individual dimension. He speculated that dreams (note that, for Jouvet, dreams and paradoxical sleep were equivalent) could be involved in psychological individualism and in the stability of the dreamer’s personality (Jouvet, 1991 , 1992 , 1998 ). According to Jouvet, “the brain is the sole organ of homeotherms that do not undergo cell division. We thus have to explain how certain aspects of psychological heredity (found in homozygote twins raised in different surroundings) may persist for a whole life (psychological individuation). A definitive genetic programming during development (by neurogenesis) is unlikely due to the plasticity of the nervous system. That is why we have to consider the possibility of an iterative genetic programming. The internal mechanisms (synchronous) of paradoxical sleep (SP) are particularly adapted to such programming. This would activate an endogenous system of stimulation that would stimulate and stabilize receptors genetically programmed by DNA in some neuronal circuits. The excitation of these neurons during SP leads to oniric behaviors that could be experimentally revealed – the lists of these behaviors are specific to each individual and indirect data suggest a genetic component of this programming. Amongst the mechanisms allowing the iterative programming of SP, sleep is particularly important. Security – and hence the inhibition of the arousal system – is a sine qua non-condition for genetic programming to take place. In that sense, sleep could very well be the guardian of dreaming” (Jouvet, 1991 ). In other words, Jouvet’s hypothesis is that paradoxical sleep restores neuronal circuitry that was modified during the day to preserve the expression of the genetic program that codes for psychological characteristics. This process would ensure the stability of personality across time.

The threat simulation theory

The Finnish psychologist Antti Revonsuo recently proposed a hypothesis called threat simulation theory, which explains the fearful characteristics of dream content (Revonsuo, 2000 ; Valli and Revonsuo, 2009 ). According to this theory, dreams serve as virtual training places to improve threat avoidance or threat fighting ability. The theory postulates that such nocturnal training makes the dreamer more efficient at resolving threatening situations during wakefulness.

Emotional regulation

Cartwright et al. ( 1998a , b ) defended the idea that dreaming is involved in emotional regulation. Her team showed that, in healthy subjects, the depression level before sleep was significantly correlated with affect in the first REM report. Her team also observed that low scorers on the depression scale displayed a flat distribution of positive and negative affect in dreams, whereas those with a depressed mood before sleep showed a pattern of decreasing negative and increasing positive affect in dreams reported from successive REM periods (Cartwright et al., 1998a ). These results led Cartwright’s team to suggest that dreaming may actively moderate mood overnight in normal subjects. The team strengthened this hypothesis by showing that among subjects who were depressed because of a divorce, those who reported more negative dreams at the beginning of sleep and fewer at the night’s end were more likely to be in remission 1 year later than subjects who had fewer negative dreams at the beginning of sleep and more at the end of the night (Cartwright et al., 1998b ). The researchers concluded that negative dreams early in the night may reflect a within-sleep mood regulation process, whereas those that occur later may indicate a failure in the completion of this process.

Memory consolidation

Finally, a current mainstream hypothesis in cognitive neuroscience credits sleep and dreaming with a role in memory consolidation (for a recent review, see Diekelmann and Born, 2010 ). Numerous studies have shown that brain activity during training is replayed during post-training sleep (e.g., using a serial reaction time task Maquet et al., 2000 , demonstrated replay during REM sleep; using a maze exploration task Peigneux et al., 2004 , demonstrated replay during slow-wave sleep). Decreased performance during the post-training day in sleep-deprived subjects further suggested that the replay of brain activity at night contributes to memory consolidation (e.g., Maquet et al., 2003 ). Only recently, however, have experimental results in humans argued in favor of a role of dreaming per se in memory consolidation. In one study, subjects were trained on a virtual navigation task before taking a nap. Post-nap tests showed that subjects who dreamed about the task performed better than subjects who did not dream (note that only 4 out of 50 subjects dreamed about the task in this study; Wamsley et al., 2010 ). Using a different approach, Nielsen and colleagues provided additional arguments supporting a link between dreams and memory (Nielsen et al., 2004 ; Nielsen and Stenstrom, 2005 ). This team demonstrated that dreams preferably incorporate events that the dreamer lived the day before and events that the dreamer lived 7 days before the dream (U shaped curve). Animal studies have shown that after associative learning, the excitability of hippocampal cells increases (which leads to an increase in neuronal plasticity) and then returns to baseline 7 days after training (Thompson et al., 1996 ). The similarity between the delay of episodic event incorporation into dreams and the delay of post-training cellular plasticity in the hippocampus led the Canadian team to suggest a link between dreaming and episodic memory consolidation.

In summary, the preceding section describes the current state of the art on dreaming, its phenomenology and cerebral correlates and hypotheses about its functions. Some substantial advances have been made, but much remains to be understood.

Unresolved Issues

The link between oneiric behaviors and dream reports.

A piece of evidence in favor of a strong link between REM sleep and dreaming is the oneiric behavior (the appearance of complex motor behaviors when motor inhibition is suppressed during REM sleep) discovered by Sastre and Jouvet ( 1979 ) in cats and reproduced by Sanford et al. ( 2001 ) in rats. Researchers interpreted these results as the animal acting out its dream. However, as animals do not talk, the link between oneiric behavior and dream recall cannot be tested experimentally. This limitation seriously hampers our understanding of dreaming. In humans, complex motor behaviors (e.g., talking, grabbing, and manipulating imaginary objects, walking, and running) can also occur during REM sleep in a pathological context. This syndrome is called REM sleep behavior disorder (RBD). It can be caused by substance withdrawal (e.g., alcohol, Nitrazepam) or intoxication (e.g., caffeine, tricyclic antidepressants) or by various diseases (e.g., Parkinson’s and Alzheimer’s diseases, pontine neoplasms). According to physicians experts on this syndrome, some patients report dreams that are consistent with their behaviors in REM sleep (Mahowald and Schenck, 2000 ). According to the literature, however, such matches seem to be loose and not systematic. Only one study has tested whether observers can link dream content to sleep behaviors in RBD (Valli et al., 2011 ). In this study, each video recording of motor manifestations was combined with four dream reports, and seven judges had to match the video clip with the correctly reported dream content. The authors found that reported dream content can be linked to motor behaviors at a level better than chance. However, only 39.5% of video-dream pairs were correctly identified. Note, however, that because the authors obtained only movements and not behavioral episodes for many RBD patients, the link between videos and dream reports was unfairly difficult to make.

It is important to note that motor behavior during sleep can happen outside of REM sleep. Sleepwalking and sleep terrors, which occur during NREM sleep, are usually not considered dream enactments. However, we know that dreams can happen during NREM sleep, and many patients report dreamlike mentation after awakening from sleepwalking or sleep terrors (71%, according to Oudiette et al., 2009 ). In addition, Oudiette et al. ( 2009 ) reported that the dreamlike mentation can correspond with the sleep behavior in NREM sleep. Consequently, the authors concluded that sleepwalking may represent an acting out of corresponding dreamlike mentation.

Recent research suggests that any kind of motor behavior during sleep can be considered an oneiric behavior. One of the challenges for future research is to test the strength of the link between these oneiric behaviors and dream reports in a controlled and systematic way.

Neurophysiological correlates of dreaming

Despite the numerous neuroimaging studies of sleep in humans, the neurophysiological correlates of dreaming remain unclear.

Indeed, dreaming can happen during NREM sleep, and although NREM brain activity differs substantially from REM sleep brain activity (Maquet et al., 2000 ; Buchsbaum et al., 2001 ), some NREM dreams are phenomenologically indistinguishable from REM dreams (Hobson, 1988 ; Cavallero et al., 1992 ; Cicogna et al., 1998 ; Wittmann et al., 2004 ). This phenomenon is difficult to understand given what we currently know about the sleeping brain and about dreaming. One explanation may rely on the possibility that brain activity during sleep is not as stable as we think.

Brain activity during REM sleep in humans is considered to be well understood (Hobson and Pace-Schott, 2002 ; Schwartz and Maquet, 2002 ; Nir and Tononi, 2010 ), but several results question this notion. First, contrary to the common belief that dorsolateral prefrontal cortex activity decreases during REM sleep, several studies have reported increased activity in the dorsolateral prefrontal cortex during REM sleep (Hong et al., 1995 , 2009 ; Nofzinger et al., 1997 ; Kubota et al., 2011 ). Second, brain activity during REM sleep is heterogeneous. The mean regional cerebral blood flow during 1 min of REM sleep (e.g., as reported in Maquet et al., 1996 ) and the regional cerebral blood flow associated with the rapid eye movements of REM sleep (Hong et al., 2009 ; Miyauchi et al., 2009 ) highlight different brain regions. Finally, few congruencies have been noted in the results of studies investigating brain activity during REM sleep (Hong et al., 1995 , 2009 ; Maquet et al., 1996 , 2000 ; Braun et al., 1997 , 1998 ; Nofzinger et al., 1997 ; Peigneux et al., 2001 ; Wehrle et al., 2005 ; Miyauchi et al., 2009 ; Kubota et al., 2011 ), even between studies using the same technique and the same contrasts (e.g., Braun et al., 1998 ; Maquet et al., 2000 ), or between studies investigating the same REM event (e.g., brain activity associated with rapid eyes movements, as in Peigneux et al., 2001 ; Wehrle et al., 2005 ; Hong et al., 2009 ; Miyauchi et al., 2009 ). Furthermore, few brain regions are consistently reported across the majority of the studies. This inconsistency suggests great intra- and intersubject variability in brain activity during REM sleep in humans. A challenge for future research will be to find out whether the variability in brain activity during REM sleep can be explained by the variability in dream content.

Because dream reports can be collected after awakenings from any sleep stage, one may hypothesize that the brain activity that subserves dreaming (if such brain activity is reproducible across dreams) is quite constant throughout the night and can be observed during all sleep stages. Some results have supported this hypothesis and encouraged further attention in this direction. Buchsbaum et al. ( 2001 ), for example, reported that metabolism in the primary visual areas and certain parts of the lateral temporal cortex does not fluctuate much across REM and slow-wave sleep. Similarly, Nielsen’s team found that dream recall (vs. no dream recall) was associated with decreased alpha (8–12 Hz) power in the EEG preceding awakening, regardless of the sleep stage (Stage 2 or REM sleep; Esposito et al., 2004 ). Interestingly, some authors have suggested that decreased power in the alpha band during wakefulness reflects search and retrieval processes in long-term memory (for a review, see Klimesch, 1999 ).

Processes of selection and organization of dream representations

Nielsen’s team found that episodic events from the 1, 7, and 8 days before a dream were more often incorporated into the dream than were events from 2 or 6 days before the dream (Nielsen et al., 2004 ; results reproduced by Blagrove et al., 2011 ). This result tells us that internal processes control and shape dream content and thus help us to constrain and shape hypotheses about the function and biological basis of dreaming.

At the end of the nineteenth century, Saint-Denys (1867) showed that a sensory stimulus (e.g., the scent of lavender) presented to a sleeping subject without his or her knowledge could induce the incorporation of an event associated with the stimulus (e.g., holidays spent near a lavender field) into the dream, regardless of the delay between the dream and the association stimulus/events (lavender scent/holidays). The author demonstrated that the external world can influence dream content in a direct or indirect way.

Finally, it appears that both external and internal parameters can shape or govern dream content. Nonetheless, few of these parameters are known, and some regularities in the phenomenology of dreams suggest that more influencing parameters remain to be discovered. For example, some individuals experience recurring themes, characters, or places in their dreams. In line with this observation, Michael Schredl’s team showed that the content and style of a person’s life strongly influence dream content (Schredl and Hofmann, 2003 ). However, the rule(s) governing which lived events are incorporated into dreams remain unknown. Do the representations constituting the dream emerge randomly from the brain, or do they surface according to certain parameters? Similarly, is the organization of the dream’s representations chaotic, or is it determined by rules? Does dreaming have a meaning? What is/are the function(s) of dreaming?

Dreaming, Psychoanalysis, and Neuropsychoanalysis

Psychoanalysis, which was developed by the neurologist Sigmund Freud in the beginning of the twentieth century, proposes answers to the questions raised above. Indeed, his theory of the human mind comprises hypotheses about the rules of selection and organization of the representations that constitute dreams.

At the beginning of the twentieth century, Freud presented the concept of the unconscious. He proposed that a part of our mind is made up of thoughts, desires, emotions, and knowledge that we are not aware of, but that nevertheless profoundly influence and guide our behaviors. In his books (e.g., Freud, 1900, 1920 ), Freud proposes that the unconscious mind comes out in slips and dreams. Its expression, however, is coded within dreams (the work of dream), and unconscious thoughts are distorted before they emerge in the conscious mind of the sleeping subject (manifest content of the dream). As a consequence, the dreamer is not disturbed by repressed and unacceptable thoughts (latent content of the dream) and can continue sleeping (this is the reason why Freud considered dreams the guardians of sleep). Hence, according to Freud, decoding dreams’ latent content provides an access to the unconscious mind.

In Freud’s theory of the mind, unconscious thoughts and feelings may cause the patient to experience life difficulties and/or maladjustment, and free unconscious thoughts can help the patient gain insight into his/her situation. As a consequence, Freud developed techniques to decode dreams and provide a way for an analyst to look inside the words and unconscious images of the patient, and to free them through patient insight. One of these techniques is called free association, and is regarded as an essential part of the psychoanalytic therapy process. In order for an analyst to get to the latent content of a dream, he requires the patient to discuss the dream’s manifest content and encourage free association about the dream. Free association is the principle that the patient is to say anything and everything that comes to mind. This includes decensoring his/her own speech so that he/she truly expresses everything. Over time, the therapist or analyst will draw associations between the many trains of uncensored speech the patient shares during each session. This can lead to patient insight into their unconscious thoughts or repressed memories, and the accomplishment of their ultimate goal of “freedom from the oppression of the unconscious” (Trull, 2005 ).

Hence, Freud considered that dreams, as well as slips, have a meaning and can be interpreted, so that one is justified in inferring from them the presence of restrained or repressed intentions (Freud, 1900, 1920 ). Note that, in Freud’s theory of the mind, the words “meaning” and “intention” are closely linked: “Let us agree once more on what we understand by the ‘meaning’ of a psychic process. A psychic process is nothing more than the purpose which it serves and the position which it holds in a psychic sequence. We can also substitute the word ‘purpose’ or ‘intention’ for ‘meaning’ in most of our investigations” (Freud, 1920 ).

In other words, according to Freud, decoding dreams with the free association method provides an access to what makes each of us so special, uncorvering the forces that guide one’s behavior. It gives access to an unknown dimension of ourselves that is fundamental in understanding who we are. It provides access to personal meaning.

This hypothesis, attributing significant importance and meaning to dreams, has rarely been considered by neuroscientists who often consider Freud’s work and theory unscientific.

However, this situation may change as the relationship between psychoanalysis and neuroscience evolves. The starting point was the creation of the International Society for Neuropsychoanalysis in 2000. It was founded by neuropsychologist and psychoanalyst Mark Solms with the intention to promote interactions and collaborations between psychoanalysis and neuroscience. The challenge was serious, as illustrated by neuroscientist Alan Hobson’s aggressiveness in the famous dream debate (Alan Hobson vs. Mark Solms) entitled “Should Freud’s dream theory be abandoned?” held in Tucson, Arizona, in 2006 during the Towards a Science of Consciousness meeting (scientific arguments can be found in Solms, 2000 and Hobson et al., 2000 ). Alan Hobson tried to convince the assembly that Freud was 100% wrong and that Freud’s dream theory was misguided and misleading and should be abandoned. He aimed to demonstrate that Freud’s dream theory is incompatible with what we know about how the brain works. He added that Freud’s dream theory was not scientific because it was not testable or falsifiable. Finally, he presented his model of dreaming, the activation-synthesis hypothesis (Hobson and McCarley, 1977 ; Hobson et al., 2000 ): “The Activation-Synthesis model of dream construction proposed that the phasic signals arising in the pontine brainstem during REM sleep and impinging upon the cortex and limbic forebrain led directly to the visual and motor hallucinations, emotion, and distinctively bizarre cognition that characterize dream mentation. In doing so, these chaotically generated signals arising from the brain stem acted as a physiological Rorschach test, initiating a process of image and narrative synthesis involving associative and language regions of the brain and resulting in the construction of the dream scenarios.” In contrast, Mark Solms demonstrated that what is currently known about the dreaming brain is at least broadly consistent with Freud’s dream theory. He argued that it is generally accepted that brain stem activation is necessary, but not sufficient, to explain the particular characteristics of dream consciousness. What does explain the particular characteristics of dream consciousness, according to Solms, are the following features of brain activity during REM sleep (Braun et al., 1997 ): the activation of core forebrain emotion and instinctual drive mechanisms, i.e., the limbic and paralimbic brain areas (the anterior cingulate, insula, hippocampus, parahippocampal gyrus, and temporal pole), and of the posterior perceptual system (the fusiform gyrus, superior, inferior and middle temporal gyrus, and angular gyrus) and the deactivation of executive dorsolateral frontal control mechanisms (the dorsolateral prefrontal cortex). He further argued that his lesion studies (Solms, 1997 ) are congruent with neuroimaging results because they showed that a total cessation of dreaming results from lesions in the medial part of the frontal lobe and in the temporoparietal junction (whereas no cessation of dreaming was observed for core brainstem lesions or for dorsolateral prefrontal lesions). Finally he emphasized that the activation of motivational mechanisms (such as drives and basic emotions) and of posterior perceptual system associated with deactivation of the executive control (i.e., reality oriented regulatory mechanism) during REM sleep, is broadly consistent with Freud’s dream theory which claims that our instinctual drive states (notably appetitive and libidinal drive system) are relatively disinhibited during sleep. Note that experimental results demonstrating the existence of unconscious representations that guide behavior (e.g., Shevrin and Fritzler, 1968 ; Bunce et al., 1999 ; Arminjon, 2011 , for a review) could also have been cited in support of Freud’s dream theory. This debate was a success for Mark Solms and neuropsychoanalysis. Indeed, at the end of the debate, approximately 100 people voted “no” (i.e., “Freud’s dream theory should not be abandoned”), approximately 50 people voted “yes” and 50 voted “I don’t know”.

Solms’ ( 1997 , 2000 ) approach to dreaming and his experimental results fundamentally challenged our current understanding of dreaming. He proposes that dreaming and REM sleep are controlled by different brain mechanisms. According to Solms, REM sleep is controlled by cholinergic brain stem mechanisms, whereas dreaming is mediated by forebrain mechanisms that are probably dopaminergic. This implies that dreaming can be activated by a variety of NREM triggers. Several experimental results support this hypothesis.

First, behavioral studies have demonstrated that the link between REM sleep and dream reports is lax. Subjects awakened during NREM sleep can recall dreams at a high rate (Foulkes, 1962 : 74% of awakenings in NREM sleep were followed by dream reports; Cavallero et al., 1992 : 64%; Wittmann et al., 2004 : 60%); dreams can be recalled after a nap consisting only of NREM sleep (Salzarulo, 1971 ; Palagini et al., 2004 ); and some individuals never recall dreams, even when awakened from REM sleep (Pagel, 2003 ). In addition, in healthy subjects with a normal dream recall frequency (around 1 dream recall per week, Schredl, 2008 ), dream recall after an awakening during REM sleep is not systematic: 5–30% of awakenings in REM sleep are not followed by a dream recall, according to the literature (e.g., Dement and Kleitman, 1957a , b ; Foulkes, 1962 ; Hobson, 1988 ). Finally, 5–10% of NREM dreams cannot be distinguished from REM dreams based on their content (Hobson, 1988 ; Cavallero et al., 1992 ; Cicogna et al., 1998 ; Wittmann et al., 2004 ).

Second, as Solms ( 2000 ) argued, the amount of dream recall can be modulated by dopamine agonists (Scharf et al., 1978 ; Nausieda et al., 1982 ) without concomitant modification of the duration and frequency of REM sleep (Hartmann et al., 1980 ). Dream recall can be suppressed by focal brain lesions (at the temporo-parieto-occipital junction and ventromedial prefrontal cortex; Solms, 1997 , 2000 ). These lesions do not have any appreciable effects on REM frequency, duration, or density (Kerr et al., 1978 ; Michel and Sieroff, 1981 ). Finally, some clinical studies suggest that a dream can be triggered by nocturnal seizures in NREM sleep, i.e., by focal brain stimulation. Some cases of recurring nightmares caused by epileptiform activity in the temporal lobe have indeed been reported (Solms, 2000 ).

Conclusion: Collaboration between Neuroscience and Psychoanalysis Would Benefit Dream Research

Considering the issues that remain unresolved (e.g., neurophysiologic variability, parameter(s) influencing the emergence of representations in dreams, the meaning of dreams), a psychoanalytic perspective would certainly benefit dream research by providing new directions/leads and helping to reach a comprehensive understanding of dreaming.

On the one hand, psychological research has demonstrated that dream content is influenced by one’s personal life, especially personal concerns (Schwartz, 1999 ; Schwartz and Maquet, 2002 ; Schredl and Hofmann, 2003 ), and some neuroscientists have hypothesized that dreaming is involved in psychological individualism. Thus, both psychology and neuroscience have provided results and hypotheses that validate the possibility that dreaming has something to do with personal and meaningful issues. On the other hand, Freud argued that the unconscious, which guides behaviors and desires, express itself during dreams. The two disciplines’ (cognitive neuroscience and psychoanalysis) convergence on dreaming thus seems obvious; however, very little collaboration has occurred to date.

Note that some experimental studies in psychology have considered the psychoanalytic perspective. For example, Greenberg et al. ( 1992 ) attempted “a research-based reconsideration of the psychoanalytical theory of dreaming.” They evaluated the presence of problems (defined as an expression of negative feeling or any situation evoking such feeling or requiring some change or adaptation) during dreaming and pre- and post-sleep wakefulness in two subjects. They showed that problems occurred very frequently in the manifest dream content and that these problems were nearly systematically related to the problems noted during pre-sleep wakefulness. In addition, they observed that effective dreams (i.e., dreams that presented some solution to the individuals’ problems) were followed by a waking state in which the impact of the problems was diminished, whereas ineffective dreams were followed by the persistence of the problems. This study thus confirmed that personal concerns influence dream content. In addition it provided new results suggesting that dreaming may have some psychological problem-solving function (this result recalls the neuroscientific findings that sleep has a cognitive problem-solving function associated with brain reorganization; e.g., Wagner et al., 2004 ; Darsaud et al., 2011 ). Greenberg et al.’s ( 1992 ) study managed to quantify personal issues and clearly broadened the cognitive neuroscience perspective on dreaming. To proceed further, approaches integrating psychoanalysis and neuroscience must now be developed. Several subjective issues at the core of the psychoanalytic approach, such as the concept of personal meaning, the concept of unconscious episodic memory and the subject’s history, are not addressed or considered in cognitive neuroscience. This limitation hampers the understanding of psychological and neurophysiological functioning in humans. These issues must be addressed, and the expertise of psychoanalysts in singularity and personal meaning is needed to do so in neuroscience and to further the understanding of dreaming and of the psyche.

Conflict of Interest Statement

The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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A Complete Guide to Experimental Research

Published by Carmen Troy at August 14th, 2021 , Revised On August 25, 2023

A Quick Guide to Experimental Research

Experimental research refers to the experiments conducted in the laboratory or observation under controlled conditions. Researchers try to find out the cause-and-effect relationship between two or more variables. 

The subjects/participants in the experiment are selected and observed. They receive treatments such as changes in room temperature, diet, atmosphere, or given a new drug to observe the changes. Experiments can vary from personal and informal natural comparisons. It includes three  types of variables ;

• Independent variable
• Dependent variable
• Controlled variable

Before conducting experimental research, you need to have a clear understanding of the experimental design. A true experimental design includes  identifying a problem , formulating a  hypothesis , determining the number of variables, selecting and assigning the participants,  types of research designs , meeting ethical values, etc.

There are many  types of research  methods that can be classified based on:

• The nature of the problem to be studied
• Number of participants (individual or groups)
• Number of groups involved (Single group or multiple groups)
• Types of data collection methods (Qualitative/Quantitative/Mixed methods)
• Number of variables (single independent variable/ factorial two independent variables)
• The experimental design

Types of Experimental Research

Laboratory Experiment  

It is also called experimental research. This type of research is conducted in the laboratory. A researcher can manipulate and control the variables of the experiment.

Example: Milgram’s experiment on obedience.

Field Experiment

Field experiments are conducted in the participants’ open field and the environment by incorporating a few artificial changes. Researchers do not have control over variables under measurement. Participants know that they are taking part in the experiment.

Natural Experiments

The experiment is conducted in the natural environment of the participants. The participants are generally not informed about the experiment being conducted on them.

Examples: Estimating the health condition of the population. Did the increase in tobacco prices decrease the sale of tobacco? Did the usage of helmets decrease the number of head injuries of the bikers?

Quasi-Experiments

A quasi-experiment is an experiment that takes advantage of natural occurrences. Researchers cannot assign random participants to groups.

Example: Comparing the academic performance of the two schools.

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How to Conduct Experimental Research?

Step 1. identify and define the problem.

You need to identify a problem as per your field of study and describe your  research question .

Example: You want to know about the effects of social media on the behavior of youngsters. It would help if you found out how much time students spend on the internet daily.

Example: You want to find out the adverse effects of junk food on human health. It would help if you found out how junk food frequent consumption can affect an individual’s health.

Step 2. Determine the Number of Levels of Variables

You need to determine the number of  variables . The independent variable is the predictor and manipulated by the researcher. At the same time, the dependent variable is the result of the independent variable.

In the first example, we predicted that increased social media usage negatively correlates with youngsters’ negative behaviour.

In the second example, we predicted the positive correlation between a balanced diet and a good healthy and negative relationship between junk food consumption and multiple health issues.

Step 3. Formulate the Hypothesis

One of the essential aspects of experimental research is formulating a hypothesis . A researcher studies the cause and effect between the independent and dependent variables and eliminates the confounding variables. A  null hypothesis is when there is no significant relationship between the dependent variable and the participants’ independent variables. A researcher aims to disprove the theory. H0 denotes it.  The  Alternative hypothesis  is the theory that a researcher seeks to prove.  H1or HA denotes it. 

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Step 4. Selection and Assignment of the Subjects

It’s an essential feature that differentiates the experimental design from other research designs . You need to select the number of participants based on the requirements of your experiment. Then the participants are assigned to the treatment group. There should be a control group without any treatment to study the outcomes without applying any changes compared to the experimental group.

Randomisation:  The participants are selected randomly and assigned to the experimental group. It is known as probability sampling. If the selection is not random, it’s considered non-probability sampling.

Stratified sampling : It’s a type of random selection of the participants by dividing them into strata and randomly selecting them from each level. 

Matching:   Even though participants are selected randomly, they can be assigned to the various comparison groups. Another procedure for selecting the participants is ‘matching.’ The participants are selected from the controlled group to match the experimental groups’ participants in all aspects based on the dependent variables.  

What is Replicability?

When a researcher uses the same methodology  and subject groups to carry out the experiments, it’s called ‘replicability.’ The  results will be similar each time. Researchers usually replicate their own work to strengthen external validity.

Step 5. Select a Research Design

You need to select a  research design  according to the requirements of your experiment. There are many types of experimental designs as follows.

Step 6. Meet Ethical and Legal Requirements

• Participants of the research should not be harmed.
• The dignity and confidentiality of the research should be maintained.
• The consent of the participants should be taken before experimenting.
• The privacy of the participants should be ensured.
• Research data should remain confidential.
• The anonymity of the participants should be ensured.
• The rules and objectives of the experiments should be followed strictly.
• Any wrong information or data should be avoided.

Tips for Meeting the Ethical Considerations

To meet the ethical considerations, you need to ensure that.

• Participants have the right to withdraw from the experiment.
• They should be aware of the required information about the experiment.
• It would help if you avoided offensive or unacceptable language while framing the questions of interviews, questionnaires, or Focus groups.
• You should ensure the privacy and anonymity of the participants.
• You should acknowledge the sources and authors in your dissertation using any referencing styles such as APA/MLA/Harvard referencing style.

Step 7. Collect and Analyse Data.

Collect the data  by using suitable data collection according to your experiment’s requirement, such as observations,  case studies ,  surveys ,  interviews , questionnaires, etc. Analyse the obtained information.

Step 8. Present and Conclude the Findings of the Study.

Write the report of your research. Present, conclude, and explain the outcomes of your study .  

Frequently Asked Questions

What is the first step in conducting an experimental research.

The first step in conducting experimental research is to define your research question or hypothesis. Clearly outline the purpose and expectations of your experiment to guide the entire research process.

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What are the different research strategies you can use in your dissertation? Here are some guidelines to help you choose a research strategy that would make your research more credible.

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A survey includes questions relevant to the research topic. The participants are selected, and the questionnaire is distributed to collect the data.

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This glossary is intended to assist you in understanding commonly used terms and concepts when reading, interpreting, and evaluating scholarly research. Also included are common words and phrases defined within the context of how they apply to research in the social and behavioral sciences.

• Acculturation -- refers to the process of adapting to another culture, particularly in reference to blending in with the majority population [e.g., an immigrant adopting American customs]. However, acculturation also implies that both cultures add something to one another, but still remain distinct groups unto themselves.
• Accuracy -- a term used in survey research to refer to the match between the target population and the sample.
• Affective Measures -- procedures or devices used to obtain quantified descriptions of an individual's feelings, emotional states, or dispositions.
• Aggregate -- a total created from smaller units. For instance, the population of a county is an aggregate of the populations of the cities, rural areas, etc. that comprise the county. As a verb, it refers to total data from smaller units into a large unit.
• Anonymity -- a research condition in which no one, including the researcher, knows the identities of research participants.
• Baseline -- a control measurement carried out before an experimental treatment.
• Behaviorism -- school of psychological thought concerned with the observable, tangible, objective facts of behavior, rather than with subjective phenomena such as thoughts, emotions, or impulses. Contemporary behaviorism also emphasizes the study of mental states such as feelings and fantasies to the extent that they can be directly observed and measured.
• Beliefs -- ideas, doctrines, tenets, etc. that are accepted as true on grounds which are not immediately susceptible to rigorous proof.
• Benchmarking -- systematically measuring and comparing the operations and outcomes of organizations, systems, processes, etc., against agreed upon "best-in-class" frames of reference.
• Bias -- a loss of balance and accuracy in the use of research methods. It can appear in research via the sampling frame, random sampling, or non-response. It can also occur at other stages in research, such as while interviewing, in the design of questions, or in the way data are analyzed and presented. Bias means that the research findings will not be representative of, or generalizable to, a wider population.
• Case Study -- the collection and presentation of detailed information about a particular participant or small group, frequently including data derived from the subjects themselves.
• Causal Hypothesis -- a statement hypothesizing that the independent variable affects the dependent variable in some way.
• Causal Relationship -- the relationship established that shows that an independent variable, and nothing else, causes a change in a dependent variable. It also establishes how much of a change is shown in the dependent variable.
• Causality -- the relation between cause and effect.
• Central Tendency -- any way of describing or characterizing typical, average, or common values in some distribution.
• Chi-square Analysis -- a common non-parametric statistical test which compares an expected proportion or ratio to an actual proportion or ratio.
• Claim -- a statement, similar to a hypothesis, which is made in response to the research question and that is affirmed with evidence based on research.
• Classification -- ordering of related phenomena into categories, groups, or systems according to characteristics or attributes.
• Cluster Analysis -- a method of statistical analysis where data that share a common trait are grouped together. The data is collected in a way that allows the data collector to group data according to certain characteristics.
• Cohort Analysis -- group by group analytic treatment of individuals having a statistical factor in common to each group. Group members share a particular characteristic [e.g., born in a given year] or a common experience [e.g., entering a college at a given time].
• Confidentiality -- a research condition in which no one except the researcher(s) knows the identities of the participants in a study. It refers to the treatment of information that a participant has disclosed to the researcher in a relationship of trust and with the expectation that it will not be revealed to others in ways that violate the original consent agreement, unless permission is granted by the participant.
• Confirmability Objectivity -- the findings of the study could be confirmed by another person conducting the same study.
• Construct -- refers to any of the following: something that exists theoretically but is not directly observable; a concept developed [constructed] for describing relations among phenomena or for other research purposes; or, a theoretical definition in which concepts are defined in terms of other concepts. For example, intelligence cannot be directly observed or measured; it is a construct.
• Construct Validity -- seeks an agreement between a theoretical concept and a specific measuring device, such as observation.
• Constructivism -- the idea that reality is socially constructed. It is the view that reality cannot be understood outside of the way humans interact and that the idea that knowledge is constructed, not discovered. Constructivists believe that learning is more active and self-directed than either behaviorism or cognitive theory would postulate.
• Content Analysis -- the systematic, objective, and quantitative description of the manifest or latent content of print or nonprint communications.
• Context Sensitivity -- awareness by a qualitative researcher of factors such as values and beliefs that influence cultural behaviors.
• Control Group -- the group in an experimental design that receives either no treatment or a different treatment from the experimental group. This group can thus be compared to the experimental group.
• Controlled Experiment -- an experimental design with two or more randomly selected groups [an experimental group and control group] in which the researcher controls or introduces the independent variable and measures the dependent variable at least two times [pre- and post-test measurements].
• Correlation -- a common statistical analysis, usually abbreviated as r, that measures the degree of relationship between pairs of interval variables in a sample. The range of correlation is from -1.00 to zero to +1.00. Also, a non-cause and effect relationship between two variables.
• Covariate -- a product of the correlation of two related variables times their standard deviations. Used in true experiments to measure the difference of treatment between them.
• Credibility -- a researcher's ability to demonstrate that the object of a study is accurately identified and described based on the way in which the study was conducted.
• Critical Theory -- an evaluative approach to social science research, associated with Germany's neo-Marxist “Frankfurt School,” that aims to criticize as well as analyze society, opposing the political orthodoxy of modern communism. Its goal is to promote human emancipatory forces and to expose ideas and systems that impede them.
• Data -- factual information [as measurements or statistics] used as a basis for reasoning, discussion, or calculation.
• Data Mining -- the process of analyzing data from different perspectives and summarizing it into useful information, often to discover patterns and/or systematic relationships among variables.
• Data Quality -- this is the degree to which the collected data [results of measurement or observation] meet the standards of quality to be considered valid [trustworthy] and  reliable [dependable].
• Deductive -- a form of reasoning in which conclusions are formulated about particulars from general or universal premises.
• Dependability -- being able to account for changes in the design of the study and the changing conditions surrounding what was studied.
• Dependent Variable -- a variable that varies due, at least in part, to the impact of the independent variable. In other words, its value “depends” on the value of the independent variable. For example, in the variables “gender” and “academic major,” academic major is the dependent variable, meaning that your major cannot determine whether you are male or female, but your gender might indirectly lead you to favor one major over another.
• Deviation -- the distance between the mean and a particular data point in a given distribution.
• Discourse Community -- a community of scholars and researchers in a given field who respond to and communicate to each other through published articles in the community's journals and presentations at conventions. All members of the discourse community adhere to certain conventions for the presentation of their theories and research.
• Discrete Variable -- a variable that is measured solely in whole units, such as, gender and number of siblings.
• Distribution -- the range of values of a particular variable.
• Effect Size -- the amount of change in a dependent variable that can be attributed to manipulations of the independent variable. A large effect size exists when the value of the dependent variable is strongly influenced by the independent variable. It is the mean difference on a variable between experimental and control groups divided by the standard deviation on that variable of the pooled groups or of the control group alone.
• Emancipatory Research -- research is conducted on and with people from marginalized groups or communities. It is led by a researcher or research team who is either an indigenous or external insider; is interpreted within intellectual frameworks of that group; and, is conducted largely for the purpose of empowering members of that community and improving services for them. It also engages members of the community as co-constructors or validators of knowledge.
• Empirical Research -- the process of developing systematized knowledge gained from observations that are formulated to support insights and generalizations about the phenomena being researched.
• Epistemology -- concerns knowledge construction; asks what constitutes knowledge and how knowledge is validated.
• Ethnography -- method to study groups and/or cultures over a period of time. The goal of this type of research is to comprehend the particular group/culture through immersion into the culture or group. Research is completed through various methods but, since the researcher is immersed within the group for an extended period of time, more detailed information is usually collected during the research.
• Expectancy Effect -- any unconscious or conscious cues that convey to the participant in a study how the researcher wants them to respond. Expecting someone to behave in a particular way has been shown to promote the expected behavior. Expectancy effects can be minimized by using standardized interactions with subjects, automated data-gathering methods, and double blind protocols.
• External Validity -- the extent to which the results of a study are generalizable or transferable.
• Factor Analysis -- a statistical test that explores relationships among data. The test explores which variables in a data set are most related to each other. In a carefully constructed survey, for example, factor analysis can yield information on patterns of responses, not simply data on a single response. Larger tendencies may then be interpreted, indicating behavior trends rather than simply responses to specific questions.
• Field Studies -- academic or other investigative studies undertaken in a natural setting, rather than in laboratories, classrooms, or other structured environments.
• Focus Groups -- small, roundtable discussion groups charged with examining specific topics or problems, including possible options or solutions. Focus groups usually consist of 4-12 participants, guided by moderators to keep the discussion flowing and to collect and report the results.
• Framework -- the structure and support that may be used as both the launching point and the on-going guidelines for investigating a research problem.
• Generalizability -- the extent to which research findings and conclusions conducted on a specific study to groups or situations can be applied to the population at large.
• Grey Literature -- research produced by organizations outside of commercial and academic publishing that publish materials, such as, working papers, research reports, and briefing papers.
• Grounded Theory -- practice of developing other theories that emerge from observing a group. Theories are grounded in the group's observable experiences, but researchers add their own insight into why those experiences exist.
• Group Behavior -- behaviors of a group as a whole, as well as the behavior of an individual as influenced by his or her membership in a group.
• Hypothesis -- a tentative explanation based on theory to predict a causal relationship between variables.
• Independent Variable -- the conditions of an experiment that are systematically manipulated by the researcher. A variable that is not impacted by the dependent variable, and that itself impacts the dependent variable. In the earlier example of "gender" and "academic major," (see Dependent Variable) gender is the independent variable.
• Individualism -- a theory or policy having primary regard for the liberty, rights, or independent actions of individuals.
• Inductive -- a form of reasoning in which a generalized conclusion is formulated from particular instances.
• Inductive Analysis -- a form of analysis based on inductive reasoning; a researcher using inductive analysis starts with answers, but formulates questions throughout the research process.
• Insiderness -- a concept in qualitative research that refers to the degree to which a researcher has access to and an understanding of persons, places, or things within a group or community based on being a member of that group or community.
• Internal Consistency -- the extent to which all questions or items assess the same characteristic, skill, or quality.
• Internal Validity -- the rigor with which the study was conducted [e.g., the study's design, the care taken to conduct measurements, and decisions concerning what was and was not measured]. It is also the extent to which the designers of a study have taken into account alternative explanations for any causal relationships they explore. In studies that do not explore causal relationships, only the first of these definitions should be considered when assessing internal validity.
• Life History -- a record of an event/events in a respondent's life told [written down, but increasingly audio or video recorded] by the respondent from his/her own perspective in his/her own words. A life history is different from a "research story" in that it covers a longer time span, perhaps a complete life, or a significant period in a life.
• Margin of Error -- the permittable or acceptable deviation from the target or a specific value. The allowance for slight error or miscalculation or changing circumstances in a study.
• Measurement -- process of obtaining a numerical description of the extent to which persons, organizations, or things possess specified characteristics.
• Meta-Analysis -- an analysis combining the results of several studies that address a set of related hypotheses.
• Methodology -- a theory or analysis of how research does and should proceed.
• Methods -- systematic approaches to the conduct of an operation or process. It includes steps of procedure, application of techniques, systems of reasoning or analysis, and the modes of inquiry employed by a discipline.
• Mixed-Methods -- a research approach that uses two or more methods from both the quantitative and qualitative research categories. It is also referred to as blended methods, combined methods, or methodological triangulation.
• Modeling -- the creation of a physical or computer analogy to understand a particular phenomenon. Modeling helps in estimating the relative magnitude of various factors involved in a phenomenon. A successful model can be shown to account for unexpected behavior that has been observed, to predict certain behaviors, which can then be tested experimentally, and to demonstrate that a given theory cannot account for certain phenomenon.
• Models -- representations of objects, principles, processes, or ideas often used for imitation or emulation.
• Naturalistic Observation -- observation of behaviors and events in natural settings without experimental manipulation or other forms of interference.
• Norm -- the norm in statistics is the average or usual performance. For example, students usually complete their high school graduation requirements when they are 18 years old. Even though some students graduate when they are younger or older, the norm is that any given student will graduate when he or she is 18 years old.
• Null Hypothesis -- the proposition, to be tested statistically, that the experimental intervention has "no effect," meaning that the treatment and control groups will not differ as a result of the intervention. Investigators usually hope that the data will demonstrate some effect from the intervention, thus allowing the investigator to reject the null hypothesis.
• Ontology -- a discipline of philosophy that explores the science of what is, the kinds and structures of objects, properties, events, processes, and relations in every area of reality.
• Panel Study -- a longitudinal study in which a group of individuals is interviewed at intervals over a period of time.
• Participant -- individuals whose physiological and/or behavioral characteristics and responses are the object of study in a research project.
• Peer-Review -- the process in which the author of a book, article, or other type of publication submits his or her work to experts in the field for critical evaluation, usually prior to publication. This is standard procedure in publishing scholarly research.
• Phenomenology -- a qualitative research approach concerned with understanding certain group behaviors from that group's point of view.
• Philosophy -- critical examination of the grounds for fundamental beliefs and analysis of the basic concepts, doctrines, or practices that express such beliefs.
• Phonology -- the study of the ways in which speech sounds form systems and patterns in language.
• Policy -- governing principles that serve as guidelines or rules for decision making and action in a given area.
• Policy Analysis -- systematic study of the nature, rationale, cost, impact, effectiveness, implications, etc., of existing or alternative policies, using the theories and methodologies of relevant social science disciplines.
• Population -- the target group under investigation. The population is the entire set under consideration. Samples are drawn from populations.
• Position Papers -- statements of official or organizational viewpoints, often recommending a particular course of action or response to a situation.
• Positivism -- a doctrine in the philosophy of science, positivism argues that science can only deal with observable entities known directly to experience. The positivist aims to construct general laws, or theories, which express relationships between phenomena. Observation and experiment is used to show whether the phenomena fit the theory.
• Predictive Measurement -- use of tests, inventories, or other measures to determine or estimate future events, conditions, outcomes, or trends.
• Principal Investigator -- the scientist or scholar with primary responsibility for the design and conduct of a research project.
• Probability -- the chance that a phenomenon will occur randomly. As a statistical measure, it is shown as p [the "p" factor].
• Questionnaire -- structured sets of questions on specified subjects that are used to gather information, attitudes, or opinions.
• Random Sampling -- a process used in research to draw a sample of a population strictly by chance, yielding no discernible pattern beyond chance. Random sampling can be accomplished by first numbering the population, then selecting the sample according to a table of random numbers or using a random-number computer generator. The sample is said to be random because there is no regular or discernible pattern or order. Random sample selection is used under the assumption that sufficiently large samples assigned randomly will exhibit a distribution comparable to that of the population from which the sample is drawn. The random assignment of participants increases the probability that differences observed between participant groups are the result of the experimental intervention.
• Reliability -- the degree to which a measure yields consistent results. If the measuring instrument [e.g., survey] is reliable, then administering it to similar groups would yield similar results. Reliability is a prerequisite for validity. An unreliable indicator cannot produce trustworthy results.
• Representative Sample -- sample in which the participants closely match the characteristics of the population, and thus, all segments of the population are represented in the sample. A representative sample allows results to be generalized from the sample to the population.
• Rigor -- degree to which research methods are scrupulously and meticulously carried out in order to recognize important influences occurring in an experimental study.
• Sample -- the population researched in a particular study. Usually, attempts are made to select a "sample population" that is considered representative of groups of people to whom results will be generalized or transferred. In studies that use inferential statistics to analyze results or which are designed to be generalizable, sample size is critical, generally the larger the number in the sample, the higher the likelihood of a representative distribution of the population.
• Sampling Error -- the degree to which the results from the sample deviate from those that would be obtained from the entire population, because of random error in the selection of respondent and the corresponding reduction in reliability.
• Saturation -- a situation in which data analysis begins to reveal repetition and redundancy and when new data tend to confirm existing findings rather than expand upon them.
• Semantics -- the relationship between symbols and meaning in a linguistic system. Also, the cuing system that connects what is written in the text to what is stored in the reader's prior knowledge.
• Social Theories -- theories about the structure, organization, and functioning of human societies.
• Sociolinguistics -- the study of language in society and, more specifically, the study of language varieties, their functions, and their speakers.
• Standard Deviation -- a measure of variation that indicates the typical distance between the scores of a distribution and the mean; it is determined by taking the square root of the average of the squared deviations in a given distribution. It can be used to indicate the proportion of data within certain ranges of scale values when the distribution conforms closely to the normal curve.
• Statistical Analysis -- application of statistical processes and theory to the compilation, presentation, discussion, and interpretation of numerical data.
• Statistical Bias -- characteristics of an experimental or sampling design, or the mathematical treatment of data, that systematically affects the results of a study so as to produce incorrect, unjustified, or inappropriate inferences or conclusions.
• Statistical Significance -- the probability that the difference between the outcomes of the control and experimental group are great enough that it is unlikely due solely to chance. The probability that the null hypothesis can be rejected at a predetermined significance level [0.05 or 0.01].
• Statistical Tests -- researchers use statistical tests to make quantitative decisions about whether a study's data indicate a significant effect from the intervention and allow the researcher to reject the null hypothesis. That is, statistical tests show whether the differences between the outcomes of the control and experimental groups are great enough to be statistically significant. If differences are found to be statistically significant, it means that the probability [likelihood] that these differences occurred solely due to chance is relatively low. Most researchers agree that a significance value of .05 or less [i.e., there is a 95% probability that the differences are real] sufficiently determines significance.
• Subcultures -- ethnic, regional, economic, or social groups exhibiting characteristic patterns of behavior sufficient to distinguish them from the larger society to which they belong.
• Testing -- the act of gathering and processing information about individuals' ability, skill, understanding, or knowledge under controlled conditions.
• Theory -- a general explanation about a specific behavior or set of events that is based on known principles and serves to organize related events in a meaningful way. A theory is not as specific as a hypothesis.
• Treatment -- the stimulus given to a dependent variable.
• Trend Samples -- method of sampling different groups of people at different points in time from the same population.
• Triangulation -- a multi-method or pluralistic approach, using different methods in order to focus on the research topic from different viewpoints and to produce a multi-faceted set of data. Also used to check the validity of findings from any one method.
• Unit of Analysis -- the basic observable entity or phenomenon being analyzed by a study and for which data are collected in the form of variables.
• Validity -- the degree to which a study accurately reflects or assesses the specific concept that the researcher is attempting to measure. A method can be reliable, consistently measuring the same thing, but not valid.
• Variable -- any characteristic or trait that can vary from one person to another [race, gender, academic major] or for one person over time [age, political beliefs].
• Weighted Scores -- scores in which the components are modified by different multipliers to reflect their relative importance.
• White Paper -- an authoritative report that often states the position or philosophy about a social, political, or other subject, or a general explanation of an architecture, framework, or product technology written by a group of researchers. A white paper seeks to contain unbiased information and analysis regarding a business or policy problem that the researchers may be facing.

Elliot, Mark, Fairweather, Ian, Olsen, Wendy Kay, and Pampaka, Maria. A Dictionary of Social Research Methods. Oxford, UK: Oxford University Press, 2016; Free Social Science Dictionary. Socialsciencedictionary.com [2008]. Glossary. Institutional Review Board. Colorado College; Glossary of Key Terms. Writing@CSU. Colorado State University; Glossary A-Z. Education.com; Glossary of Research Terms. Research Mindedness Virtual Learning Resource. Centre for Human Servive Technology. University of Southampton; Miller, Robert L. and Brewer, John D. The A-Z of Social Research: A Dictionary of Key Social Science Research Concepts London: SAGE, 2003; Jupp, Victor. The SAGE Dictionary of Social and Cultural Research Methods . London: Sage, 2006.

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• 15 May 2024

‘Quantum internet’ demonstration in cities is most advanced yet

• Davide Castelvecchi

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A quantum network node at Delft University of Technology in the Netherlands. Credit: Marieke de Lorijn for QuTech

Three separate research groups have demonstrated quantum entanglement — in which two or more objects are linked so that they contain the same information even if they are far apart — over several kilometres of existing optical fibres in real urban areas. The feat is a key step towards a future quantum internet , a network that could allow information to be exchanged while encoded in quantum states.

Together, the experiments are “the most advanced demonstrations so far” of the technology needed for a quantum internet, says physicist Tracy Northup at the University of Innsbruck in Austria. Each of the three research teams — based in the United States, China and the Netherlands — was able to connect parts of a network using photons in the optical-fibre-friendly infrared part of the spectrum, which is a “major milestone”, says fellow Innsbruck physicist Simon Baier.

How to build a quantum internet

A quantum internet could enable any two users to establish almost unbreakable cryptographic keys to protect sensitive information . But full use of entanglement could do much more, such as connecting separate quantum computers into one larger, more powerful machine. The technology could also enable certain types of scientific experiment, for example by creating networks of optical telescopes that have the resolution of a single dish hundreds of kilometres wide.

Two of the studies 1 , 2 were published in Nature on 15 May. The third was described last month in a preprint posted on arXiv 3 , which has not yet been peer reviewed.

Impractical environment

Many of the technical steps for building a quantum internet have been demonstrated in the laboratory over the past decade or so. And researchers have shown that they can produce entangled photons using lasers in direct line of sight of each other, either in separate ground locations or on the ground and in space.

But going from the lab to a city environment is “a different beast”, says Ronald Hanson, a physicist who led the Dutch experiment 3 at the Delft University of Technology. To build a large-scale network, researchers agree that it will probably be necessary to use existing optical-fibre technology. The trouble is, quantum information is fragile and cannot be copied; it is often carried by individual photons, rather than by laser pulses that can be detected and then amplified and emitted again. This limits the entangled photons to travelling a few tens of kilometres before losses make the whole thing impractical. “They also are affected by temperature changes throughout the day — and even by wind, if they’re above ground,” says Northup. “That’s why generating entanglement across an actual city is a big deal.”

The three demonstrations each used different kinds of ‘quantum memory’ device to store a qubit, a physical system such as a photon or atom that can be in one of two states — akin to the ‘1’ or ‘0’ of ordinary computer bits — or in a combination, or ‘quantum superposition’, of the two possibilities.

The quantum internet has arrived (and it hasn’t)

In one of the Nature studies, led by Pan Jian-Wei at the University of Science and Technology of China (USTC) in Hefei, qubits were encoded in the collective states of clouds of rubidium atoms 1 . The qubits’ quantum states can be set using a single photon, or can be read out by ‘tickling’ the atomic cloud to emit a photon. Pan’s team had such quantum memories set up in three separate labs in the Hefei area. Each lab was connected by optical fibres to a central ‘photonic server’ around 10 kilometres away. Any two of these nodes could be put in an entangled state if the photons from the two atom clouds arrived at the server at exactly the same time.

By contrast, Hanson and his team established a link between individual nitrogen atoms embedded in small diamond crystals with qubits encoded in the electron states of the nitrogen and in the nuclear states of nearby carbon atoms 3 . Their optical fibre went from the university in Delft through a tortuous 25-kilometre path across the suburbs of The Hague to reach a second laboratory in the city.

In the US experiment, Mikhail Lukin, a physicist at Harvard University in Cambridge, Massachusetts, and his collaborators also used diamond-based devices, but with silicon atoms instead of nitrogen, making use of the quantum states of both an electron and a silicon nucleus 2 . Single atoms are less efficient than atomic ensembles at emitting photons on demand, but they are more versatile, because they can perform rudimentary quantum computations. “Basically, we entangled two small quantum computers,” says Lukin. The two diamond-based devices were in the same building at Harvard, but to mimic the conditions of a metropolitan network, the researchers used an optical fibre that snaked around the local Boston area. “It crosses the Charles River six times,” Lukin says.

Challenges ahead

The entanglement procedure used by the Chinese and the Dutch teams required photons to arrive at a central server with exquisite timing precision, which was one of the main challenges in the experiments. Lukin’s team used a protocol that does not require such fine-tuning: instead of entangling the qubits by getting them to emit photons, the researchers sent one photon to entangle itself with the silicon atom at the first node. The same photon then went around the fibre-optic loop and came back to graze the second silicon atom, thereby entangling it with the first.

Pan has calculated that at the current pace of advance, by the end of the decade his team should be able to establish entanglement over 1,000 kilometres of optical fibres using ten or so intermediate nodes, with a procedure called entanglement swapping . (At first, such a link would be very slow, creating perhaps one entanglement per second, he adds.) Pan is the leading researcher for a project using the satellite Micius , which demonstrated the first quantum-enabled communications in space, and he says there are plans for a follow-up mission.

“The step has now really been made out of the lab and into the field,” says Hanson. “It doesn’t mean it’s commercially useful yet, but it’s a big step.”

Nature 629 , 734-735 (2024)

doi: https://doi.org/10.1038/d41586-024-01445-2

Knaut, C. M. et al. Nature 629 , 573–578 (2024).

Article   PubMed   Google Scholar  

Liu, J. L. et al. Nature 629 , 579–585 (2024).

Stolk, A. J. et al. Preprint at arXiv https://doi.org/10.48550/arXiv.2404.03723 (2024).

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Title: chameleon: mixed-modal early-fusion foundation models.

Abstract: We present Chameleon, a family of early-fusion token-based mixed-modal models capable of understanding and generating images and text in any arbitrary sequence. We outline a stable training approach from inception, an alignment recipe, and an architectural parameterization tailored for the early-fusion, token-based, mixed-modal setting. The models are evaluated on a comprehensive range of tasks, including visual question answering, image captioning, text generation, image generation, and long-form mixed modal generation. Chameleon demonstrates broad and general capabilities, including state-of-the-art performance in image captioning tasks, outperforms Llama-2 in text-only tasks while being competitive with models such as Mixtral 8x7B and Gemini-Pro, and performs non-trivial image generation, all in a single model. It also matches or exceeds the performance of much larger models, including Gemini Pro and GPT-4V, according to human judgments on a new long-form mixed-modal generation evaluation, where either the prompt or outputs contain mixed sequences of both images and text. Chameleon marks a significant step forward in a unified modeling of full multimodal documents.

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• Open access
• Published: 21 May 2024

Mitochondrial transfer in tunneling nanotubes—a new target for cancer therapy

• Fan Guan 1   na1 ,
• Xiaomin Wu 1   na1 ,
• Jiatong Zhou 1 ,
• Yuzhe Lin 1 ,
• Yuqing He 1 ,
• Chunmei Fan 3 ,
• Zhaoyang Zeng 1 , 2 &
• Wei Xiong   ORCID: orcid.org/0000-0003-1635-8173 1 , 2  

Journal of Experimental & Clinical Cancer Research volume  43 , Article number:  147 ( 2024 ) Cite this article

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A century ago, the Warburg effect was first proposed, revealing that cancer cells predominantly rely on glycolysis during the process of tumorigenesis, even in the presence of abundant oxygen, shifting the main pathway of energy metabolism from the tricarboxylic acid cycle to aerobic glycolysis. Recent studies have unveiled the dynamic transfer of mitochondria within the tumor microenvironment, not only between tumor cells but also between tumor cells and stromal cells, immune cells, and others. In this review, we explore the pathways and mechanisms of mitochondrial transfer within the tumor microenvironment, as well as how these transfer activities promote tumor aggressiveness, chemotherapy resistance, and immune evasion. Further, we discuss the research progress and potential clinical significance targeting these phenomena. We also highlight the therapeutic potential of targeting intercellular mitochondrial transfer as a future anti-cancer strategy and enhancing cell-mediated immunotherapy.

Graphical Abstract

Mitochondrial Transfer in the Tumor Microenvironment. This review elaborates in detail on the molecular mechanisms and pathophysiological significance behind the mitochondrial transfer occurring between tumor cells and their microenvironment. This biological phenomenon of mitochondrial transfer is prevalent in a variety of cancers, including both solid tumors and hematologic malignancies, with a high incidence in acute myeloid leukemia (AML), breast cancer, and gliomas. The review also discusses therapeutic approaches targeting mitochondrial transfer, with a special focus on its application in immunotherapy, particularly in CAR-T cell therapy, where it has begun to show unique advantages

Unrestricted rapid proliferation is one of the most important biological characteristics of tumor cells [ 1 ]. To meet the substantial energy and nutritional needs for their rapid division, proliferation, and growth, tumor cells often exhibit a unique mode of energy metabolism. Even in the presence of sufficient oxygen, tumor cells prefer to metabolize glucose via glycolysis rather than through mitochondrial oxidative phosphorylation (OXPHOS); the latter produces more ATP. This phenomenon is known as aerobic glycolysis, also referred to as the Warburg effect, and is a main feature distinguishing tumor cells from normal cells [ 2 ]. Mitochondria are the centers of energy metabolism in all eukaryotes [ 3 ]. Studies have shown that some tumor cells indeed exhibit varying degrees of irreversible mitochondrial functional damage. For example, the activity of respiratory chain complex III in breast cancer cells is significantly lower compared to normal breast cells [ 4 ]. Other studies indicate that the main driving factor behind the high glycolysis of tumor cells is not mitochondrial dysfunction but rather an adaptive response to microenvironmental changes and genetic regulation. For instance, the activation of the c-Myc gene drives the increased expression of key glycolytic enzymes such as hexokinase (HK), pyruvate kinase M2 (PKM2), and glucose transporter 1 (GLUT-1). Meanwhile, the activation of protein kinase B (AKT) further triggers the activation of mTOR and the phosphorylation of HK and phosphofructokinase (PFK), while the inactivation of p53 upregulates the level of aerobic glycolysis [ 5 , 6 , 7 ]. Utilizing specific enzyme inhibitors, such as lactate dehydrogenase inhibitors, can slow down the conversion of pyruvate to lactate during aerobic glycolysis. When this conversion is reduced, the function of mitochondrial OXPHOS may be restored, suggesting that mitochondrial function has not been lost but has entered a specific "dormant" state.

However, recent studies have shown that mitochondria and the mitochondrial genome (mitochondrial DNA (mtDNA)) also play significant roles in tumor cells and their metabolic microenvironment. For instance, certain mitochondrial metabolites are sufficient to drive tumorigenesis [ 8 ]; some mitochondrial pathways adapt to the unique bioenergetic or biosynthetic metabolic functions of tumors, thereby endowing malignant cells with considerable metabolic plasticity [ 9 , 10 ]. Interestingly, it has been further discovered that mitochondria can undergo transfer within the tumor microenvironment [ 11 ], and this transfer is not only limited to tumor cells themselves [ 12 , 13 ], but also occurs between tumor cells and stromal cells [ 14 , 15 ], tumor cells and immune cells [ 16 , 17 ], tumor cells and endothelial cells [ 18 ], or between tumor cells and homologous normal cells [ 19 ]. Moreover, mitochondrial transfer occurs between tumor cells and platelets [ 20 ]. In most cases, tumor cells plunder mitochondria from other cells in the microenvironment to promote their own invasion and metastasis [ 20 , 21 ], chemotherapy resistance [ 22 ], and immune evasion [ 17 ]. In a few cases, tumor cells transfer mitochondria to stromal cells to resist oxidative stress [ 23 ]. High-metastasis tumor cells can also transfer mtDNA with metastatic mutations to low-metastasis cancer cells and stromal cells through small extracellular vesicles (s-EVs) [ 24 ]. In this review, we thoroughly explore the impact of the tumor microenvironment on mitochondrial dynamics and their transfer pathways and mechanisms, as well as the pathophysiological importance of these processes in the metabolic adaptation of tumor cells. Additionally, this article discusses potential clinical intervention strategies targeting the biological process of mitochondrial transfer and highlights its potential in future cancer treatments and enhancing the efficacy of cell-mediated immunotherapy.

Mechanisms of mitochondrial transfer

Tunneling nanotubes (tnts).

Tunneling nanotubes represent the most crucial pathway for mitochondrial transfer between tumor cells. TNTs are nano-scale membranous channels between cells, with diameters ranging from 50 to 1500 nm and lengths of 5–200 μm, with some TNTs reaching thicknesses up to 700 nm [ 25 ]. TNTs are not empty membranous tubes but are filled with cytoskeletal filaments. F-actin is present in most TNTs and is a critical structural component. On one hand, the cross-linking of F-actin ensures the rigidity of the TNT, ensuring its stability for outward growth [ 26 , 27 ]; on the other hand, the cross-linking of F-actin mediates the biosynthesis of TNTs and allows mitochondria to be transported along the cytoskeletal structures within TNTs [ 28 ].

Rustom and colleagues observed the ultrastructure of rat pheochromocytoma (PC) 12 cells, where they first discovered TNTs and observed intercellular material exchange via TNTs using organelle-specific fluorescent dyes [ 29 ]. Subsequently, studies using electron microscopy revealed that TNTs could transfer mitochondria from mesenchymal stem cells (MSCs) to cardiomyocytes, marking one of the earliest pieces of research to reveal TNT-mediated mitochondrial transfer between cells [ 11 , 30 ]. With the advancement of imaging technologies, scanning electron microscopy (SEM), atomic force microscopy (AFM), cryo-electron microscopy, and others have been widely applied to observe TNTs [ 31 ]. The challenges posed by the fragility and sensitivity of TNTs have been overcome, and TNTs are now extensively studied. Currently, TNT-mediated mitochondrial transfer is involved in various cellular microenvironments, including the cardiovascular system, immune system, respiratory system, corneal epithelium, tumors, and in neuronal injury and neurodegeneration within the central nervous system [ 11 ]. TNTs participate in a wide range of physiological and pathological events, such as immune responses, cell proliferation and apoptosis, substance transport, and angiogenesis. TNTs can transport a variety of materials over distances as long as 150 mm, including mitochondria and other organelles, lipid droplets, proteins, ions, RNA, and pathogens [ 29 , 32 ].

Two mechanisms of TNT formation have been extensively discussed [ 33 , 34 ]. In the actin-driven mechanism, a cell extends a pseudopod-like protrusion containing actin filaments that fuses with the edge of a neighboring cell, leading to TNT formation. This mechanism does not rely on cell motility or close contact. The other mechanism is the cell displacement mechanism, which occurs when two closely situated cells move in opposite directions. During this movement, the cells extend membrane protrusions that lead to TNT formation, thus it highly depends on cell movement. Since continuous cell contact occurs within minutes, this process can be temporarily regulated [ 30 , 35 ]. However, it is still unclear whether these two mechanisms lead to the same tubular structures and whether cells utilize both mechanisms simultaneously to form TNTs.

Specifically, the transport of mitochondria via TNTs involves mainly two mechanisms, one of which is primarily mediated by the mitochondrial Rho GTPase 1 (Miro1). Research has shown that TNTs mediate the transfer of mitochondria from MSCs to epithelial cells. If the Miro1 in MSCs is knocked out, mitochondria are unable to transfer to epithelial cells. This study confirmed that Miro1, acting as a motor protein-associated, calcium-sensitive linker protein, can mediate the transfer of mitochondria through TNTs from MSCs to epithelial cells, with Miro1 playing a role in regulating mitochondrial homeostasis and transport [ 36 ]. The specific mechanism involves Miro1, along with auxiliary proteins Miro2, transport associated protein 1 (TRAK1), TRAK2, and myosin XIX (Myo19), driving the mitochondria to bind with the Kruppel-like factor 5 (KLF5) driven proteins. When bound, they form a motor-adaptor complex, thereby facilitating the transport of mitochondria within TNTs and regulating their movement. At the same time, these structures stabilize and protect mitochondria from degradation.

Extracellular vesicles (EVs)

In addition to transport mediated by tunneling nanotubes, mitochondria can also be transferred between cells encapsulated within EVs. EVs are nano-sized bilayer vesicles secreted by cells, capable of carrying various lipids, proteins, RNA, microRNA (miRNA), and mitochondria [ 37 ]. EVs include exosomes with a diameter of 30–100 nm, microvesicles ranging from 100 nm to 1 μm, and apoptotic bodies sized from 1 μm to more than 2 μm [ 38 ]. Due to their smaller volume, exosomes can only carry mtDNA, miRNA, cytokines, chemokines, and other small molecular proteins, while microvesicles are capable of transporting entire mitochondria [ 39 ].

Artificial mechanisms of mitochondrial transfer

Aside from the physiological release and uptake of mitochondria, artificial transfer of mitochondria has also been achieved. Researchers have developed a technique called MitoCeption, which relies on the ability of recipient cells to internalize isolated mitochondria, a process associated with macropinocytosis [ 40 ]. Labeled mitochondria isolated from donor cells are centrifuged together with similarly labeled recipient cells, then co-cultured under normal conditions. During co-culture, the isolated mitochondria are internalized by the recipient cells, thereby allowing entry into the recipient cells [ 41 ]. The process of mitochondria entering recipient cells through internalization induced by centrifugation and heat shock during co-culture is referred to as MitoCeption. The researchers developed MitoCeption to achieve mitochondrial transfer from MSCs to cancer cells. They further validated the mitochondrial transfer process using microscopy imaging, fluorescence-activated cell sorting (FACS), real-time quantitative PCR (qPCR) and other techniques [ 42 ]. Techniques like MitoCeption, which represent artificial mitochondrial transfer, not only provide effective tools for studying intercellular mitochondrial transfer but also have significant implications for understanding cell interactions within the tumor microenvironment, developing new therapeutic strategies, and studying the role of mitochondria in diseases.

Cell fusion

Cell fusion can also mediate the transfer of mitochondria between cells. This process occurs both through partial cell fusion facilitated by TNTs and through complete cell fusion. Researchers co-cultured free mitochondria extracted from cervical cancer cells with cardiomyocytes and observed the mitochondria being endocytosed by the cardiomyocytes [ 43 ]. However, when the actin polymerization of cardiomyocytes was inhibited using cytochalasin D (CytoD), the transfer of mitochondria to cardiomyocytes was significantly reduced [ 44 ]. This study represents a process of partial cell fusion achieved through TNTs. In the case of complete cell fusion, mitochondrial transfer can be identified when MSCs are co-cultured with transgenic mouse cardiomyocytes and fully fuse with mitochondria-damaged cardiomyocytes. However, since cell fusion is rarely found in higher eukaryotes under normal physiological conditions, it is not the main mechanism for mitochondrial transfer.

Current research has revealed that cells release free mitochondria in a manner dependent on mitochondrial fission proteins, such as dynamin-related protein 1 (DRP1) and mitochondrial fission 1 protein (FIS1). However, more studies are needed to fully understand the specific mechanisms through which mitochondria are packaged and transported (Fig. 1 ).

Modes of mitochondrial transfer in the tumor microenvironment

Mitochondrial transfer in tumor dynamics

Mitochondrial transfer promotes tumor proliferation.

The earliest studies showed that ρ0 tumor cells, which lack mtDNA, divided more slowly [ 11 ], but could restore respiratory function by seizing whole mitochondria and associated mtDNA from neighboring cells [ 45 , 46 , 47 ], thereby achieving faster cell division and restoring their tumorigenic capacity [ 46 , 48 ]. Research indicates that unlike solid tumors, AML cells rely more on OXPHOS than on glycolysis [ 49 ]. In AML cells, NADPH oxidase 2 (NOX2) generates superoxides, stimulating bone marrow stromal cells (BMSCs) to transfer mitochondria to AML blast cells via TNTs derived from AML, thereby promoting AML cell proliferation. However, NOX2 has no detectable effect on the survival of non-malignant CD34 + cells, suggesting AML cells may specifically plunder mitochondria from stromal cells via NOX2 to meet their proliferation needs [ 50 ]. Interestingly, another study showed that transferred mitochondria are not in optimal condition but rather are dysfunctional with high Reactive Oxygen Species (ROS) content, and recipient tumor cells do not require these dysfunctional mitochondria to restore their respiratory function but rather stimulate other signaling pathways through ROS. For example, malignant breast cancer cells plunder dysfunctional mitochondria from macrophages in the microenvironment and accumulate ROS, which activates the ERK pathway thus promoting tumor proliferation [ 51 ] (Fig. 2 ). In gliomas, the tumor-associated stromal cells (TASCs) transfer mitochondria to glioblastoma (GBM) cells, thereby promoting tumor proliferation. This transfer occurs through structures such as TNTs, EVs, etc [ 52 ]. Studies have shown that lung cancer cells form cancer-initiating cell (CIC) structures to plunder lymphocyte mitochondria, thereby activating the mitogen-activated protein kinase (MAPK) and AKT signaling pathways, promoting their own proliferation [ 17 ]. The transfer of mitochondria from stem cells to immortalized cells rapidly induces tumorigenesis. For instance, the transfer of mitochondria from adipose stem cells to HEK293 cells not only makes them more tumorigenic but also enhances their aggressiveness [ 53 ]. In gliomas, the uptake of astrocyte mitochondria promotes cell cycle progression to the proliferative G2/M phase, enhancing self-renewal and tumorigenicity of GBM cells [ 54 , 55 ]. Some research teams have developed a tool, MitoCeption (as mentioned above), that enables the transfer of mitochondria in stromal cell to tumor cells, thereby restoring respiratory function and increasing proliferation rates [ 42 ]. In melanoma, tumor cells attract bone marrow-derived stromal cells (MSCs) to the primary tumor site, stimulate PGC-1α to promote the biogenesis of MSC mitochondria, and transfer these mitochondria to tumor cells to promote their proliferatio [ 56 ]. The mechanism by which exogenous mitochondria drive cancer cell proliferation is not clear but may be related to the production of ROS [ 51 ], and ROS can stimulate the transport of mitochondria to cancer cells [ 50 ].

Mitochondrial transfer from stromal cells to tumor cells. In AML cells, NOX2 in mitochondria can produce ROS to further promote tumor cell proliferation. The possible mechanism is that mitochondrial Reactive Oxygen Species (mtROS) stimulates ERK to further activate the AKT-mTOR signaling pathway. The mtROS generated by mitochondria can also activate the transforming growth factor- β (TGF-β) signaling pathway, thereby promoting tumor metastasis. In prostate cancer, tumor cells change the metabolic pattern of cancer-associated fibroblasts (CAFs), causing them to produce lactate. Then, through their own lactate receptor monocarboxylate transporter 1(MCT1), the lactate is received, further activating PKM2 into the nucleus, and enhancing the demand for CAF mitochondria through the downstream SIRT1-PGC-1α signaling pathway

Mitochondrial transfer promotes tumor invasion and metastasis

Increasing evidence indicates that mitochondrial transfer promotes the invasion and metastasis of tumor cells, which is one of the main hallmarks of tumors. In prostate cancer (PCa) research, it has been discovered that tumor cells and CAFs form a dual-compartment metabolic system that promotes the malignant progression of cancer [ 57 , 58 ]. In this interaction, CAFs change their metabolism to glycolysis after contact with PCa, producing lactate and releasing it into the surrounding microenvironment. PCa cells absorb these lactates through the MCT1 on their surface, further triggering the nuclear translocation of PKM2, which acts as a transcription factor participating in and activating OXPHOS [ 59 ], changing the intracellular NAD + /NADH ratio, and then enhancing mitochondrial activity in PCa cells through the SIRT1—PGC-1α pathway. To meet this increased energy demand, CAFs transfer mitochondria to PCa cells through TNTs. This metabolic mode is also known as the "Reverse Warburg Effect" [ 60 ]. In another study, overexpression of mitochondrial fission factor (MFF) in an hTERT-immortalized human fibroblast line led to oxidative stress, increased ROS production, NF-kB activation, driving autophagy, mitophagy, and ultimately glycolytic metabolism, resulting in mitochondrial dysfunction. MFF-overexpressing fibroblasts similarly exhibited increased ATP consumption and L-lactate production, thus promoting tumor development [ 61 ]. This metabolic symbiosis not only enhances the energy metabolism of PCa cells but also promotes tumor invasiveness and epithelial-mesenchymal transition (EMT) [ 14 ], which is an important step for cancer cells to increase mobility and invasiveness. Research shows that mitochondrial transfer occurs between tumor cells, and the core component of mitochondria, mtDNA, can also be transferred individually. The increase of extracellular glutamate through mGluR3 activation in MDA-MB-231 (a human breast cancer cell line) leads to the release of EVs dependent on Rab27. These EVs contain mtDNA packaged through a PTEN-induced putative kinase 1 (PINK1) -dependent manner, are transported to glutamate-starved MDA-MB-231 cells, and enhance their invasiveness and metastatic capacity through cell surface toll-like receptor 9 (TLR9) [ 13 ](Fig.  3 ). Direct transfer of mitochondria to MDA-MB-231 cells can enhance their proliferative and invasive capabilities [ 62 ], and also increase their sensitivity to cisplatin [ 63 ]. Studies have shown that melanoma cells plunder mtDNA from host cells to restore respiratory capacity, promoting their own invasion and metastasis. The inability of tumor cells to fully restore mitochondrial function during prolonged ex vivo maintenance highlights a crucial aspect. These cells require exposure to the microenvironment to regain their complete respiratory capacity. This underscores the significance of mitochondrial transfer and its components within the tumor microenvironment for tumor development and progression [ 48 ]. Subsequent studies by the same authors proved that tumor formation directly depends on the restoration of mitochondrial respiration [ 64 ]. Research found that high activity of the TCA cycle or electron transport chain (ETC) can activate the TGF-β pathway through mtROS, promoting cancer migration, invasion, and metastasis. This might be one of the important reasons why tumor cells plunder mitochondria to promote their invasion and metastasis [ 65 ]. In bladder cancer, mitochondrial transfer between heterogeneous tumor cells occurs (Fig. 4 ). Fluorescence imaging and flow cytometry detected the spontaneous unidirectional transfer of mitochondria from T24 to RT4 cells, and the AKT, mTOR, and downstream mediators were activated and increased in recipient cells. An increase in the invasiveness of bladder cancer cells was detected both in vitro and in vivo [ 12 ]. Other studies have shown that mitochondria from platelets transferred to tumor cells through the PINK1/Parkin-Mfn2 pathway, increasing their dependency on glycolytic metabolism to control intracellular ROS levels, and reducing their proliferation rate. However, this process promotes EMT in tumor cells, leading to metastasis [ 20 ].

Mitochondria and their mtDNA are transferred via EVs. A In the glutamate in MDA-MB-231 cells is encapsulated into EVs through the PINK1 pathway, leading to an increase in extracellular glutamate concentration which activates mGLUR3 on the cell membrane. This activation stimulates the downstream Rab, promoting the packaging and transport of mtDNA. The mtDNA released from cells is reuptaken by glutamate-hungry MDA-MB-231, which, by stimulating TLR9, enhances the invasive capability of glutamate-hungry MDA-MB-231. B In platelets transfer mitochondria to tumor cells via the PINK1/Parkin-Mfn2 pathway via EVs. The mitochondria from platelets promote an increase in glycolytic metabolism and a decrease in ROS levels in tumor cells, although their proliferation rate decreases. As a result, they are more susceptible to experiencing EMT, which can consequently lead to metastasis

Highly malignant tumor cells can transfer mitochondria to less malignant tumor cells. The transferred mitochondria increases the proliferation and metastatic capabilities of the less malignant tumor cells. Moreover, mtDNA can also be transferred, which restores the dysfunctional mitochondria in less malignant tumor cells, enabling them to regain respiratory function. In addition, tumor cells resistant to chemotherapy transfer mitochondria to chemotherapy-sensitive tumor cells, making them resistant to chemotherapy

Mitochondrial transfer helps tumor cells cope with oxidative stress

Whether mitochondria are transferred into or out of tumor cells, there are instances showing that this transfer reduces the oxidative stress faced by tumor cells, thereby aiding tumor development and progression. PC12 cells avoid apoptosis induced by ultraviolet (UV) radiation by plundering mitochondria from healthy cells [ 66 ]. The transfer of mitochondria from MSC cells to ALL cells reduces the mortality of ALL cells after treatment with ROS and subsequent treatment with cytarabine (AraC) and daunorubicin (DNR) [ 15 ]. Studies have shown that the transfer of mitochondria from platelets to tumor cells shifts their metabolic mode towards glycolysis, and by controlling the ratio of oxidized glutathione to ROS within tumor cells, it effectively protects them. Destroying platelet mitochondria or inhibiting this antioxidant pathway increases the apoptosis rate of tumor cells [ 20 ]. In response to oxidative stress, tumor cells can also transfer mitochondria to stromal cells. Research indicates that T-ALL cells transfer mitochondria to mesenchymal stem cells via cell adhesion to reduce the oxidative stress produced by chemotherapy, with few mitochondria being accepted from mesenchymal stem cells [ 23 ]. This demonstrates that the transfer of mitochondria between tumor cells and stromal cells is often bidirectional.

Mitochondrial transfer promotes tumor resistance to chemotherapy

Chemotherapy remains one of the most common means of controlling and treating cancer clinically, yet many cancers exhibit chemotherapy resistance during clinical treatment [ 67 , 68 ]. Interestingly, one of the most common phenotypes gained by tumor cells through mitochondrial transfer is chemotherapy resistance. This phenotype was first observed in 2013 when MCF-7 cancer cells, having acquired mitochondria from epithelial cells, gained resistance to doxorubicin [ 18 ]. Studies suggest that mitochondrial transfer may occur in response to chemical drugs posing a threat to tumor survival. For example, multiple myeloma cells primarily metabolize through glycolysis [ 69 ] and have been shown to be sensitive to glycolysis inhibitors [ 70 , 71 ]. However, it was found that multiple myeloma cells could perform functional OXPHOS after treatment with the glycolysis inhibitor ritonavir, and mitochondria were transferred from BMSCs to multiple myeloma cells when co-cultured together. Using a CD38-targeting agent (which inhibits the formation of TNTs) in combination with a glycolysis inhibitor led to extensive apoptosis of malignant plasma cells. This suggests that multiple myeloma cells resist chemical drugs by plundering mitochondria from stromal cells [ 72 , 73 ]. It has also been shown that multiple myeloma cells can resist belamaf (a monoclonal antibody conjugated with microtubule-disrupting agent monomethyl auristatin-F (MMAF)) through this mechanism, thus avoiding apoptosis [ 74 ].

In ALL, mitochondrial transfer occurs more frequently, and traditional chemotherapy drugs like AraC and DNR always fail to completely eliminate tumor cells [ 75 ]. A more thorough clearance of ALL cells was achieved by using microtubule inhibitors (e.g., vincristine (VCR)) to disrupt the formation of TNTs, which could hinder the transfer of mitochondria from MSCs to ALL cells [ 15 ]. Under chemotherapy pressure, tumor cells can also transfer mitochondria to stromal cells to avoid being killed [ 23 ]. Further research indicates that treating AML cells with OXPHOS inhibitors rapidly induces both the transfer of exogenous mitochondria from bone marrow (BM) stromal cells to AML cells and the internal mitochondrial fission and mitophagy. This spontaneous enhancement of mitochondrial quality and quantity in tumor cells plays a crucial role in the compensatory adaptation of AML cells to energy stress in the BM environment [ 76 , 77 , 78 ]. Mitochondrial transfer from mesenchymal stem cells through metabolic rewiring also endows glioblastoma stem cells with chemotherapy resistance [ 52 , 79 ]. Additionally, chemotherapy-resistant triple-negative breast cancer (TNBC) has been shown to transport mitochondria with mutant genes (mtND4) to ordinary TNBC cells via EVs, thereby conferring chemotherapy resistance [ 80 ]. The transfer of mtDNA levels from EVs also acts as a carcinogenic signal, promoting the exit of treatment-induced cancer stem-like cells from dormancy and leading to endocrine therapy resistance in OXPHOS-dependent breast cancer [ 81 ]. Mitochondrial transfer also occurs between tumor cells and endothelial cells, a pathway that is preferred over the formation between tumor cells and stromal cells, and also modulates chemotherapy resistance in tumor cells [ 18 ].

Mitochondrial transfer promotes tumor immune escape

Mitochondrial transfer, as a significant biological phenomenon, has recently been revealed to play a key role in promoting tumor immune evasion, offering a new perspective on how tumors evade immune surveillance. Cell-in-cell structures (CICs) is defined as the entry of living cells of one type into another type of cell [ 82 ], and studies have found that CICs between immune cells and tumor cells are associated with the malignancy of many cancers. It has been shown that lung cancer cells form CICs with infiltrating lymphocytes, and through these CICs, mitochondria are transferred from lymphocytes to tumor cells, promoting immune evasion by upregulating PD-L1 expression (Fig. 5 ). CICs also induce reprogramming of glucose metabolism in lung cancer cells by upregulating glucose intake and glycolytic enzymes, affecting the normal energy metabolism of lymphocytes and weakening their immune killing ability [ 17 ]. Further studies using emission scanning electron microscopy, fluorescently labeled mitochondrial transfer tracking, and metabolic quantification have directly demonstrated that mitochondrial transfer from immune cells to cancer cells mediated by TNTs metabolically enhances cancer cells and depletes immune cells. Inhibiting the assembly mechanism of nanotubes can significantly reduce mitochondrial transfer and prevent immune cell exhaustion [ 16 ]. In the latest research, single-cell RNA sequencing technology combined with mitochondrial-enabled reconstruction of cellular interactions (MERCI) was used to track and quantify mitochondrial traffic between cancer cells and T cells. The application of MERCI to human cancer samples identified recurrent phenotypes associated with mitochondrial transfer, with characteristic genes involved in cytoskeletal remodeling, energy production, and the tumor necrosis factor-α (TNF-α) signaling pathway [ 83 ], providing new insights for clinical cancer immunotherapy (Table  1 ).

Mitochondrial transfer from CD8 + T cells to tumor cells. A Tumor cells hijack mitochondria from immune cells to facilitate immune evasion. Tumor cells can engulf T cells into their cytoplasm to form heterotypic cell-in-cell structures (CICs). The mitochondria from T cells entering tumor cells can promote tumor cell proliferation through the AKT and MAPK signaling pathways and upregulate their glycolytic metabolism process. It can also activate c-Myc to increase the expression of GLUT-1, thereby enhancing glucose uptake. Most importantly, by hijacking mitochondria from T cells, tumor cells upregulate PD-L1 on the cell membrane. B T cells also transfer mitochondria to tumor cells through TNTs, leading to a reduction in their own OXPHOS levels, a decrease in anti-tumor immunity, and promoting tumor immune evasion

Clinical application of mitochondrial transplantation

With the revelation of intercellular mitochondrial transfer, mitochondrial transplantation based on this phenomenon is gradually increasing across various medical fields. Although mitochondrial transfer in the tumor microenvironment generally promotes tumor progression, introducing healthy mitochondria into cells exogenously can produce the opposite effect. At present, the first step in mitochondrial transplantation is to isolate functional mitochondria from cells and tissues. Several methods for mitochondrial transplantation in vitro already exist, with incubation being the most basic method, which involves co-culturing isolated mitochondria with recipient cells. However, this basic method is limited by the endocytosis capabilities of the recipient cells, so researchers have employed various methods to improve efficiency [ 85 ]. For example, MitoCeption mentioned before and Mitopunch, which uses a pressure-driven device to introduce isolated mitochondria into recipient cells lacking mtDNA (Fig.  6 ) [ 86 ]. Mitochondrial transplantation for oocytes can be done using autologous microinjection. Other than methods for mitochondrial transplantation in vitro , there are also methods for in vivo transplantation, including direct injection, intravenous injection, or intranasal injection [ 86 ].

The process of mitochondrial transplantation. The process of mitochondrial transplantation involves the isolation of healthy mitochondria from cells or tissues. In vitro mitochondrial transplantation usually co-incubates the isolated mitochondria with recipient cells, and techniques such as Mitoception or Mitopunch are used to increase efficiency. In vivo mitochondrial transplantation can be directly administered through in situ injection, intravenous injection, or intranasal injection

Apoptosis induced by mitochondrial transplantation

Although mitochondrial transfer within the tumor microenvironment generally accelerates tumor development, introducing healthy mitochondria into cells exogenously triggers the opposite effect. For instance, implanting foreign mitochondria into tumor cells induces apoptosis in these cells. Researchers have found that transplanting mitochondria into DU145, PC3, or SKOV3 cancer cells, in combination with low-dose chemotherapy, significantly increased apoptosis in these cells, enhancing the sensitivity of mice to chemotherapy [ 87 ]. In tumor cells, the mitochondrial apoptosis system is suppressed while the anti-apoptosis system is activated, preventing tumor cells from undergoing apoptosis [ 88 ]. However, multiple studies on mitochondrial transplantation have found that after the transplant, the mitochondrial apoptosis pathway in tumor cells is reactivated, also enhancing the sensitivity of corresponding tumors to chemotherapy [ 87 , 88 , 89 , 90 ]. The transplantation of healthy mitochondria into cancer cells can induce apoptosis based on the production of ROS [ 91 ]. This is because different types of cancer have different needs for ROS, and even within the same tumor type, the need for ROS varies at different stages [ 92 ]. Therefore, both an increase or a decrease in ROS may activate the apoptotic signaling pathways. Changes in ROS prompt mitochondrial pores to release cytochrome C (cytC), thereby activating apoptotic protease activating factor 1 (Apaf1) to induce the formation of the apoptosome, which then activates Caspase 9 and Caspase 3, triggering apoptosis [ 91 ] (Fig.  7 ). By co-culturing HuCCT1 cells and mitochondria isolated from 143Bρ0 cells, it was found that mitochondrial transplantation promoted apoptosis in cholangiocarcinoma (CCA) cells, thereby inhibiting CCA cell proliferation. This process relied on the phosphatase and tensin homolog (PTEN)/Phosphoinositide 3-Kinase (PI3K)/AKT signaling pathway, where the production of ROS and mtROS significantly decreased in CCA cells after transplantation from 143Bρ0 cells, and PTEN expression was activated. As PTEN is a negative regulator of PI3K, it inhibits the expression of PI3K and its downstream molecule AKT [ 93 ]. The PI3K/AKT signaling pathway itself inhibits apoptosis, so with the downregulation of PI3K and AKT, the inhibition of apoptosis is weakened, thus increasing apoptosis in cancer cells and achieving a tumor-suppressive effect [ 94 ]. In experiments on mitochondrial transplantation in hepatocellular carcinoma, healthy mitochondria were found to inhibit tumor cells from undergoing glycolysis, promoted dephosphorylation of p-Bad, downregulated the expression of Bcl-2, increased Bax, and finally induced tumor cell apoptosis in a Caspase-dependent manner [ 95 ]. Under the mediation of Pep-1, transporting mitochondria to MCF-7 breast cancer cells decreased the viability of MCF-7 cells and induced caspase-independent and apoptosis-inducing factor (AIF)-mediated cell death [ 96 ], proving that mitochondrial transplantation can also induce other forms of cell death besides apoptosis. Under the stimulation of mitochondrial transplantation, the permeability of outer mitochondrial membrane changes [ 97 ]. At this time, AIF is released from mitochondria into the cytosol and then transported into the cell nucleus, promoting chromatin condensation and DNA degradation in a caspase-independent manner, causing a form of death known as parthanatos [ 98 ]. Moreover, in melanoma mouse models, it was found that the tumor-suppressive effect produced by importing healthy mitochondria from female sources was stronger than that from male sources [ 88 ], potentially indicating the greater therapeutic value of female mitochondria over male mitochondria in treating melanoma.

Mitochondrial transplantation leads to apoptosis, parthanatos, and necroptosis. A If the transplanted mitochondria lead to an increase in intracellular ROS, it stimulates the release of TNF-α, which then binds to tumor necrosis factor receptor (TNFR), triggering the recruitment of related proteins to form complex I, subsequently forming complex IIa, and eventually leading to the formation of the necrosome, causing necroptosis. B Transplanted mitochondria cause changes in intracellular ROS. Whether an increase or a decrease level of ROS, induces apoptosis through the release of cytC. In addition, AIF might also be released from the mitochondria into the nucleus during this process, causing parthanatos

Necroptosis induced by mitochondrial transplantation

Mitochondrial transplantation, in addition to inducing cancer cell apoptosis, can also lead to necroptosis under certain conditions. When the transplanted mitochondria increase ROS within cancer cells, the excess ROS stimulates the release of TNF-α, which then activates its corresponding receptors, triggering the recruitment of related proteins to the cell membrane [ 91 ]. These proteins include receptor-interacting protein kinase 1 (RIPK1), TNFR-associated death domain (TRADD), TNFR-associated factor 2 (TRAF2), TRAF5, cellular inhibitor of apoptosis 1 (cIAP1), cIAP2, and linear ubiquitin chain assembly complex (LUBAC). These proteins form complex I, from which TRADD and RIPK1 dissociate and undergo different processes to form two types of complex II, with complex IIa composed of FADD, TRADD, RIPK1, and caspase 8. In complex IIa, when the levels of RIPK3 and mixed lineage kinase domain-like (MLKL) are sufficient and caspase 8 is inactivated, RIPK3 is recruited [ 99 ]. Recruited RIPK3, RIPK1, and MLKL proteins form the necrosome [ 100 ], after which MLKL forms pores in the cell membrane, ultimately leading to cell necroptosis [ 91 ]. It is noteworthy that the appearance of caspase 8 in the process of necrosis means that this signaling pathway can simultaneously induce apoptosis. This is closely related to the intracellular ATP content; high ATP levels convert the cell fate towards apoptosis, while necroptosis, which occurs without ATP, is more likely to happen in a low ATP cellular environment [ 91 ]. Therefore, the therapeutic effect of mitochondrial transplantation in cancer cells may not only solely rely on apoptosis but also be associated with necroptosis and parthanatos.

Blocking mitochondrial transfer with drugs

Although mitochondrial transplantation can exert a tumor-suppressing effect, a lot of work is needed before it can be practically applied in humans. Firstly, it concerns how to ensure that mitochondria overcome the assault of the high calcium environment outside the cell during transportation within the body [ 101 ], so as to target tumor tissues, and achieve an effective concentration that inhibits tumor growth within tumor cells. Secondly, whether different types of tumors can be treated with the same type of mitochondrial transplantation, or whether mitochondria transplanted to different types of tumors need to have relevant specificity [ 102 ]. In addition, if we want to apply this widely in clinical trials, effectively preserving mitochondria from degradation is also a challenge that must be overcome. Lastly, the safety issues of mitochondrial transplantation remain to be resolved; we still need more research to confirm the safety and feasibility of this treatment method.

Although the application of mitochondrial transplantation is currently limited, however, this does not mean we can not draw inspiration from mitochondrial transfer. As mentioned earlier, spontaneous mitochondrial transfer mostly promotes tumor development. Thus, designing drugs to reverse the transfer of mitochondria between tumor cells and their microenvironment could be a strategy to inhibit tumors [ 16 ]. Intercellular mitochondrial transfer is mediated by TNTs, extracellular vesicles, and gap junctions [ 103 ]. Inhibitors targeting gap junctions include 18-α-glycyrrhetinic acid, and for inhibiting vesicular endocytosis, dynasore, a dynamin inhibitor, can be used [ 23 ]. However, TNTs are the most common route for mitochondrial transfer [ 83 ], so blocking TNTs might be an effective therapeutic strategy. Taxanes and vinca alkaloids can inhibit mitochondrial transfer by preventing microtubule polymerization [ 34 ]. Additionally, actin polymerization inhibitors such as cytochalasin B (CytoB) [ 104 ], CytoD [ 23 ], and metformin also inhibit the formation of TNTs, thereby reducing mitochondrial transfer. In the experiment where tumor cells deprive T cells of mitochondria, researchers found that L-778,123 (an inhibitor of farnesyltransferase and geranylgeranyl transferase I) could inhibit the formation of nanotubes and mitochondrial transfer at non-cytotoxic concentrations [ 16 ]. Inhibiting nanotubes, which mediate tumor cells hijacking mitochondria of immune cells, is a new mechanism for tumor immune evasion. Therefore, using inhibitors of nanotubes to prevent tumor cells from hijacking T cell mitochondria can prevent immune cell exhaustion [ 16 ], which is crucial for restoring anti-tumor immunity. M-sec also serves as a therapeutic target. Inhibiting M-sec blocks the formation of TNTs [ 105 ]. Due to the lack of specific TNT markers, the inhibitors mentioned earlier, including L-778,123 and cytochalasins, only partially prohibit the formation of TNTs and have limited ability to inhibit tumor growth [ 83 ]. Future research should focus on specific inhibitors of TNTs as targets.

Mitochondrial retransfusion promotes anti-tumor immunity

Chimeric antigen receptor (CAR) T-cell therapy represents a groundbreaking innovation in immune cell therapy, offering a personalized cancer immunotherapy approach. By modifying patients' T cells to express CARs—composed of antibodies and T cell receptors—on their surface, these cells can recognize tumor-associated antigens (TAAs) in an MHC-independent manner, thereby inducing the identification and destruction of tumor cells [ 106 , 107 ]. While CAR-T cell therapy has shown good efficacy in treating hematological tumors, its effectiveness against solid tumors has been less satisfactory [ 108 , 109 ]. Moreover, treatment failures have also been observed in some patients with hematological malignancies following CAR-T cell therapy [ 110 ]. A major limiting factor in the therapeutic efficacy of CAR-T cell therapy is the early exhaustion of T cells, characterized by impaired mitochondrial function and dynamics [ 109 ].

T cells, as crucial players in the anti-tumor immune response, rely on their mitochondrial activity at various stages when generating an immune response. From T cell polarization and migration, the formation of immune synapses, to T cell activation, proliferation, and differentiation, mitochondria play an essential and diverse role. Mitochondria are not only producers of ATP but also participate in calcium homeostasis regulation, lipid synthesis, and cell apoptosis, and other processes [ 111 ]. Therefore, targeting mitochondria could be a strategy to avoid T cell exhaustion in CAR-T cell therapy. Mitochondrial transplantation increases the mitochondrial content in T cells, further enhancing T cell function. By serving as a positive regulator, "supercharging" T cells with mitochondria makes them more effective at attacking tumor cells [ 110 ]. Research has already demonstrated the feasibility of transplanting mitochondria from human dermal fibroblasts (NHDF Neo) to human Jurkat cells (immortalized T cells) [ 102 ]. Furthermore, researchers have transferred prepared Q-mitochondria into CAR-T cells. The results demonstrated that this led to improved metabolic adaptability, enhanced proliferation capacity and cytokine production ability, and strengthened anti-tumor capability in CAR-T cells [ 110 ], potentially boosting the therapeutic effects of CAR-T treatment. These findings suggest that mitochondrial transplantation has the potential to complement CAR-T cell therapy and can be combined with other pharmacological methods to further enhance the effectiveness of CAR-T cell therapy.

Conclusions

In modern oncology research, there is a pressing need to deepen our understanding on tumor metabolic reprogramming and the mechanisms behind mitochondrial transfer. This interest is not just about unraveling the fundamental mechanisms of tumor cell survival and proliferation; it also refers to the complexity of immunotherapy strategies and the challenges they face. Through metabolic reprogramming, tumor cells exhibit adaptability to internal and external environmental stresses, a capability that is particularly evident in their interactions with surrounding cells, especially during the process of mitochondrial transfer. This phenomenon not only adds complexity to the tumor metabolic network but also reveals the intricate interplay between the tumor and its microenvironment. Understanding this interplay is crucial for grasping how tumors survive and proliferate under adverse conditions.

Utilizing nanotechnology and single-cell analysis, scientists can now explore these biological processes with unprecedented precision, deepening our understanding on tumor cell metabolic pathways. This progress not only facilitates the study of intercellular interactions and communication mechanisms but also inspires the development of new therapeutic approaches. However, despite the new research directions opened by these technologies, our understanding of the molecular mechanisms behind mitochondrial transfer, particularly how they exhibit uniqueness across different tissues and cell types, remains limited. If the specific molecular mechanisms by which mitochondrial transfer promotes tumor development, including proliferation, invasion and metastasis, chemotherapy resistance, immune evasion and so on, could be clarified, it would provide numerous targets for drug research. Further research in this area will be key to achieving more personalized and precise cancer treatment strategies.

Mitochondrial transplantation therapy for tumor is still in the experimental stage, although showing potential therapeutic effects in animal models, yet it has not progressed to clinical use. The transition from laboratory research to clinical application presents multiple challenges, such as safety concerns, the targeting of mitochondria to tumor cells, and preservation issues. Future research must overcome these hurdles to successfully translate these findings into clinical benefits for cancer patients. Meanwhile, current research is focusing on how to block the pathways of mitochondrial transfer between tumor cells. The preliminary success of this strategy gives us hope, suggesting that by intervening in the metabolic interactions of tumor cells, we might develop new therapeutic approaches to inhibit tumor growth and spread.

The application of mitochondrial transfer in immunotherapy, especially in CAR-T cell therapy, has begun to show its unique advantages. By enhancing the metabolic capacity of T cells, mitochondrial transplantation not only increases the activity of CAR-T cells against tumors but also helps these cells survive in the inhibitory tumor microenvironment, thereby improving the effectiveness of the treatment. This progress not only brings new hope to the field of immunotherapy but also further emphasizes the importance of understanding and utilizing the metabolic checkpoints of tumor cells in cancer treatment.

Moreover, existing research has also demonstrated that transferring mitochondria into tumor cells artificially can promote tumor growth, a finding that seems contradictory to other studies where mitochondrial transplantation was shown to suppress tumor development. This raises the question: whether mitochondrial transplantation possesses a dual nature, or whether it only suppresses tumor growth under specific conditions? Additionally, the concentration of transferred mitochondria appears to influence the extent of tumor promotion. This relationship is not straightforwardly proportional; rather, it is when mitochondria are at moderate concentrations that tumor growth is most significantly enhanced. Could this imply that excessively high concentrations of mitochondria might inhibit tumor cells? These are crucial questions that merit further investigation.

In summary, the in-depth study of tumor cell metabolic reprogramming and the mechanisms of mitochondrial transfer not only showcases the adaptability and biological flexibility of tumors but also provides an important scientific foundation for overcoming the limitations of current treatment methods and designing new therapeutic strategies. Based on this, we have reason to believe that further exploration of these complex biological processes will be able to offer more personalized and precise treatment options for tumor patients.

Availability of data and materials

Not applicable.

Abbreviations

Acute myeloid leukemia

Pyruvate kinase M2

Glucose transporter 1

Protein kinase B

Phosphofructokinase

Mitochondrial DNA

Small extracellular vesicles

• Tunneling nanotubes

Pheochromocytoma

Mesenchymal stem cells

Scanning electron microscopy

Atomic force microscopy

Mitochondrial Rho GTPase 1

Transport associated protein 1

Kruppel-like factor 5

Extracellular vesicles

Fluorescence-activated cell sorting

Real-time quantitative PCR

Cytochalasin D

Dynamin-related protein 1

Fission 1 protein

NADPH oxidase 2

Bone marrow stromal cells

Reactive Oxygen Species

Tumor-associated stromal cells

Glioblastoma

Cancer-initiating cell

Mitogen-activated protein kinase

Marrow-derived stromal cells

Mitochondrial Reactive Oxygen Species

Transforming growth factor- β

Cancer-associated fibroblasts

Monocarboxylate transporter 1

• Oxidative phosphorylation

Mitochondrial fission factor

Epithelial-mesenchymal transition

PTEN-induced putative kinase 1

Toll-like receptor 9

Electron transport chain

Ultraviolet

Daunorubicin

Monomethyl auristatin-F

Vincristine

Bone marrow

Triple-negative breast cancer

Cell-in-cell structures

Mitochondrial-enabled reconstruction of cellular interactions

Tumor necrosis factor-α

Cytochrome C

Apoptotic protease activating factor 1

Cholangiocarcinoma

Phosphatase and tensin homolog

Phosphoinositide 3-Kinase

Apoptosis-inducing factor

Tumor necrosis factor receptor

Receptor-interacting protein kinase 1

TNFR-associated death domain

TNFR-associated factor 2

Cellular inhibitor of apoptosis 1

Linear ubiquitin chain assembly complex

Mixed lineage kinase domain-like

Cytochalasin B

Chimeric antigen receptor

Tumor-associated antigens

Wharton’s jelly mesenchymal stem cells

Membrane protrusions

Acute lymphoblastic leukemia

Laryngeal squamous cell carcinoma

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Acknowledgements

This work has been supported by the National Natural Science Foundation of China (82203163), the Natural Science Foundation of Hunan Province (2022JJ40660), and Young Elite Scientists Sponsorship Program by CAST (2022QNRC001).

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Fan Guan and Xiaomin Wu contributed equally to this work.

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NHC Key Laboratory of Carcinogenesis and Hunan Key Laboratory of Cancer Metabolism, Hunan Cancer Hospital and the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, China

Fan Guan, Xiaomin Wu, Jiatong Zhou, Yuzhe Lin, Yuqing He, Zhaoyang Zeng & Wei Xiong

Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of Education, Cancer Research Institute, Central South University, Changsha, China

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Fan Guan and Xiaomin Wu were primarily involved in literature search and the drafting of the manuscript. Fan Guan created  the Graphical Abstract, Figures 1-5, and Table 1 , while Xiaomin Wu created Figs.  6 and 7 . Jiatong Zhou, Yuzhe Lin, Yuqing He, Chunmei Fan, Zhaoyang Zeng, and Wei Xiong participated in the design of the review and drafting of the manuscript. All authors read and approved the final manuscript.

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Guan, F., Wu, X., Zhou, J. et al. Mitochondrial transfer in tunneling nanotubes—a new target for cancer therapy. J Exp Clin Cancer Res 43 , 147 (2024). https://doi.org/10.1186/s13046-024-03069-w

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DOI : https://doi.org/10.1186/s13046-024-03069-w

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How to Write an Experimental Research Paper

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The art and practice of academic neurosurgery are mastered by defining and learning the pertinent basic principles and skills. This article aims to present general guidelines to one of the many roles of a neurosurgeon: Writing an experimental research paper.

Every research report must use the “IMRAD formula: introduction, methods, results and discussion”. After the IMRAD is finished, abstract should be written and the title should be “created”. Your abstract should answer these questions: “Why did you start?, what did you do?, what answer did you get?, and what does it mean?”. Title of the research paper should be short enough to catch glance and memory of the reader and be long enough to give the essential information of what the paper is about.

Writing about the results of the experiment is no easier than the research itself. As surgery, writing a scientific paper is also an improvisation, but general principles should be learned and used in practice. The most effective style of learning basic skills to construct a research paper is the “trial and error” type.

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M. N. Pamir M.D.

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Pamir, M.N. (2002). How to Write an Experimental Research Paper. In: Kanpolat, Y. (eds) Research and Publishing in Neurosurgery. Acta Neurochirurgica Supplements, vol 83. Springer, Vienna. https://doi.org/10.1007/978-3-7091-6743-4_18

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Considerations Regarding Future Research on Use of Fees in Employment and Training Administration (ETA) Programs: Discussion Paper

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This paper explores ideas for future research on application or user fees in programs administered by the Employment and Training Administration (in the U.S. Department of Labor). The paper briefly reviews federal law and regulations, related research studies, and key factors that can be used to guide possible research. The paper focuses on research related to use of fees with employers who, under title I of the Workforce Innovation and Opportunity Act, can be charged fees at the local level for certain customized services (such as for recruitment events and human resource consultation services). Possible research studies identified in the paper include: 1) a descriptive study of current use of fees by local programs (as well as of comparable commercial services to which employers have access); 2) a pilot or demonstration to test use of fees for employers in different circumstances and different types of services, and 3) a feasibility study on use of more rigorous methods (such as a randomized controlled trial or a quasi-experimental design) to test use of fees with employers.

Final Report: Considerations Regarding Future Research on Use of Fees in Employment and Training Administration (ETA) Programs:  Discussion Paper

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