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Record W1983115019 · doi:10.2478/s13380-013-0121-6

Serotonin transporter genotype by environment: Studies on alcohol use and misuse in non-human and human primates

2013· article· en· W1983115019 on OpenAlexaff
Aniruddha Todkar, Kent W. Nilsson, Lars Oreland, Sheilagh Hodgins, Erika Comasco

Bibliographic record

VenueTranslational Neuroscience · 2013
Typearticle
Languageen
FieldNeuroscience
TopicNeurotransmitter Receptor Influence on Behavior
Canadian institutionsUniversité de Montréal
FundersForskningsrådet för Arbetsliv och Socialvetenskap
KeywordsSerotonin transporter5-HTTLPRGene–environment interactionVulnerability (computing)AlcoholGenotypePsychologyHuman studiesPhenotypeClinical psychologyBiologyGeneticsGeneMedicineInternal medicineBiochemistry

Abstract

fetched live from OpenAlex

Abstract Much evidence indicates that gene-by-environment interactions (GxE) play a role in alcohol misuse. It has been proposed that interactions between serotonin and stress confer vulnerability for alcohol misuse. The present review examined studies of the interaction between the serotonin transporter linked polymorphic region (5-HTTLPR) genotype and stressful life events and alcohol-related phenotypes, in rhesus monkeys and humans. Ten studies were found that had investigated the interaction of 5-HTTLPR and various measures of stress and alcohol use or misuse, two studies of rhesus monkeys, and eight of humans. The results are contradictory. Important differences were reported in study samples, experimental designs, measures used to assess environmental variables, definitions and measurements of alcohol-related phenotypes, and in the statistical analyses. These differences may explain the contradictory results. Guidelines for future studies are suggested. Results are discussed in light of findings from molecular, non-human animal, and clinical studies. The review highlights the need for future studies examining associations of interactions between the serotonin transporter gene and environmental factors and alcohol misuse, especially in samples followed over time.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.627
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.076
GPT teacher head0.331
Teacher spread0.255 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2013
Admission routes1
Has abstractyes

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