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Record W3162316168 · doi:10.1186/s13102-021-00266-4

The effect of omega3 fatty acid supplementation on PPARγ and UCP2 expressions, resting energy expenditure, and appetite in athletes

2021· article· en· W3162316168 on OpenAlexaff
Sara Moradi, Mohamadreza Alivand, Yaser Khajebishak, Maedeh Alipour, Philip D. Chilibeck, Beitullah Alipour

Bibliographic record

VenueBMC Sports Science Medicine and Rehabilitation · 2021
Typearticle
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsInternal medicineEndocrinologyAppetiteResting energy expenditurePeroxisome proliferator-activated receptorMedicineChemistryReceptorEnergy expenditure

Abstract

fetched live from OpenAlex

BACKGROUND: Omega3 fatty acids as a ligand of energy-related genes, have a role in metabolism, and energy expenditure. These effects are due to changes in the expression of peroxisome proliferator-activated receptor-gamma (PPARγ) and uncoupling protein2 (UCP2). This study evaluated the effect of omega3 supplements on PPARγ mRNA expression and UCP2 mRNA expression and protein levels, as regulators of energy metabolism, resting energy expenditure (REE), and appetite in athletes. METHODS: In a 3-week double-blind RCT in Tabriz, Iran, in 2019, 36 male athletes, age 21.86 (±3.15) y with 16.17 (±5.96)% body fat were randomized to either an intervention (2000 mg/day omega3; EPA: 360, DHA: 240) or placebo (2000 mg/day edible paraffin) groups. Appetite and REE were assessed before and after the intervention. PPARγ and UCP2 mRNA expression and UCP2 protein levels in blood were evaluated by standard methods. RESULTS: Results showed PPARγ mRNA levels, and UCP2 mRNA and protein levels increased in omega3 group (p < 0.05), as did REE (p < 0.05). Also, differences in the sensation of hunger or satiety were significant (p < 0.05). CONCLUSIONS: Our findings showed that omega3 supplementation leads to the up-regulation of PPARγ and UCP2 expressions as the indicators of metabolism in healthy athletes.

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)0.003
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.162
Threshold uncertainty score0.400

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.016
GPT teacher head0.333
Teacher spread0.317 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations16
Published2021
Admission routes1
Has abstractyes

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