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Record W2917062489 · doi:10.1249/mss.0b013e31828b28a3

Advances in Exercise, Fitness, and Performance Genomics in 2012

2013· review· en· W2917062489 on OpenAlexaff
Louis Përusse, Tuomo Rankinen, James M. Hagberg, Ruth J. F. Loos, Stephen M. Roth, Mark A. Sarzynski, Bernd Wolfarth, Claude Bouchard

Bibliographic record

VenueMedicine & Science in Sports & Exercise · 2013
Typereview
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsUniversité Laval
FundersNational Heart, Lung, and Blood Institute
KeywordsSingle-nucleotide polymorphismGenomicsObesityGeneticsSNPBiologyGenome-wide association studyHypertriglyceridemiaMedicineBioinformaticsInternal medicineGenotypeEndocrinologyGeneGenomeTriglyceride

Abstract

fetched live from OpenAlex

A small number of excellent articles on exercise genomics issues were published in 2012. A new PYGM knock-in mouse model will provide opportunities to investigate the exercise intolerance and very low activity level of people with McArdle disease. New reports on variants in ACTN3 and ACE have increased the level of uncertainty regarding their true role in skeletal muscle metabolism and strength traits. The evidence continues to accumulate on the positive effects of regular physical activity on body mass index or adiposity in individuals at risk of obesity as assessed by their FTO genotype or by the number of risk alleles they carry at multiple obesity-susceptibility loci. The serum levels of triglycerides and the risk of hypertriglyceridemia were shown to be influenced by the interactions between a single nucleotide polymorphism (SNP) in the NOS3 gene and physical activity level. Allelic variation at nine SNPs was shown to account for the heritable component of the changes in submaximal exercise heart rate induced by the HERITAGE Family Study exercise program. SNPs at the RBPMS, YWHAQ, and CREB1 loci were found to be particularly strong predictors of the changes in submaximal exercise heart rate. The 2012 review ends with comments on the importance of relying more on experimental data, the urgency of identifying panels of genomic predictors of the response to regular exercise and particularly of adverse responses, and the exciting opportunities offered by recent advances in our understanding of the global architecture of the human genome as reported by the Encyclopedia of DNA Elements project.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.971
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.004
Science and technology studies0.0000.003
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.001
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 head0.035
GPT teacher head0.316
Teacher spread0.281 · 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 designOther design
Domainnot available
GenreReview

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

Citations57
Published2013
Admission routes1
Has abstractyes

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