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Related Concept Videos

Correlations02:20

Correlations

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Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
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Ideally, the people who observe and record the children’s behavior are unaware of who was assigned to the experimental or control group, in order to control for experimenter bias. Experimenter bias refers to the possibility that a researcher’s expectations might skew the results of the study. Remember, conducting an experiment requires a lot of planning, and the people involved in the research project have a vested interest in supporting their hypotheses. If the observers knew which...
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The biological clock is involved in many aspects of regulating complex physiology in all animals. It was in 1935 when German zoologists, Hans Kalmus and Erwin Bünning, discovered the existence of circadian rhythm in Drosophila melanogaster. However, the internal molecular mechanisms behind the circadian clock remained a mystery until 1984, when Jeffrey C. Hall, Michael Rosbash, and Michael W. Young discovered the expression of the Per gene oscillating over a 24-hour cycle. In subsequent...
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While variables are sometimes correlated because one does cause the other, it could also be that some other factor, a confounding variable, is actually causing the systematic movement in our variables of interest. For instance, as sales in ice cream increase, so does the overall rate of crime. Is it possible that indulging in your favorite flavor of ice cream could send you on a crime spree? Or, after committing crime do you think you might decide to treat yourself to a cone?
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Substance use disorders involve a pattern of using drugs more extensively than intended and continuing use despite harmful consequences. This includes legal substances like alcohol and nicotine, as well as illegal drugs. These disorders often involve both physical and psychological dependence, reflecting compulsive use of substances that significantly alter thoughts, feelings, and behaviors, contributing to a major public health issue.
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Although digestion of proteins, carbohydrates, and lipids may begin in the stomach, it is completed in the intestine. The absorption of nutrients, water, and electrolytes from food and drink also occurs in the intestine. The intestines can be divided into two structurally distinct organs—the small and large intestines.
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A Method to Define the Effects of Environmental Enrichment on Colon Microbiome Biodiversity in a Mouse Colon Tumor Model
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Associations between gut microbiota and sleep: a two-sample, bidirectional Mendelian randomization study.

Jun Wu1, Baofu Zhang1, Shengjie Zhou2

  • 1Department of Vascular Surgery, The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.

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This study reveals a two-way link between gut bacteria and sleep. Changes in gut microbiota composition can affect sleep, and sleep disturbances can alter gut bacteria, highlighting a reciprocal relationship.

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Mendelian randomizationcausal relationshipgut microbiotainstrumental variablesleep

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Area of Science:

  • Microbiome research
  • Sleep science
  • Genetics

Background:

  • The gut microbiota plays a role in sleep via the microbiome-gut-brain axis.
  • A definitive causal link between gut microbiota and sleep is yet to be established.

Purpose of the Study:

  • To investigate the causal relationships between gut microbiota and sleep traits.
  • To explore bidirectional associations using Mendelian randomization.

Main Methods:

  • Two-sample, bidirectional Mendelian randomization (MR) analysis.
  • Utilized genome-wide association study data for 119 bacterial genera and seven sleep traits.
  • Employed multiple MR methods and assessed heterogeneity and pleiotropy.

Main Results:

  • Forward MR indicated causal effects of 42 bacterial genera on sleep-associated traits.
  • Reverse MR showed causal effects of sleep traits on 39 bacterial genera.
  • 13 bacterial genera showed overlap in both forward and reverse analyses.

Conclusions:

  • Gut microbiota composition is causally linked to sleep regulation.
  • Sleep traits can reciprocally influence gut microbiota abundance.
  • Evidence supports a bidirectional causal association between the gut microbiome and sleep.