MétaCan
Menu
Back to cohort
Record W3138694906 · doi:10.1039/d0fo02610g

Whey peptides exacerbate body weight gain and perturb systemic glucose and tissue lipid metabolism in male high-fat fed mice

2021· article· en· W3138694906 on OpenAlexafffund
Kenneth D’Souza, Caleb Acquah, Angella Mercer, Yadab Paudel, Thomas Pulinilkunnil, Chibuike C. Udenigwe, Petra C. Kienesberger

Bibliographic record

VenueFood & Function · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsUniversity of OttawaDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsWhey proteinMetabolismLipid metabolismCarbohydrate metabolismInsulinEndocrinologyChemistryBody weightInternal medicineBiochemistryBiologyFood scienceMedicine

Abstract

fetched live from OpenAlex

) throughout the diet regimen. Mice consuming WPH gained more body weight and were more glucose intolerant compared to those consuming WPI or water only. Despite increased body weight gain, perigonadal adipose tissue weight and lipid accumulation were unchanged. However, excess lipids accumulated ectopically in the liver and skeletal muscle in mice consuming WPH, which was associated with elevated inflammatory markers systemically and in adipose tissue, liver, and skeletal muscle. In skeletal muscle, mitochondrial fat oxidation and electron transport chain proteins were decreased with WPH consumption, indicative of mitochondrial dysfunction. Taken together, our results demonstrate that WPH, but not WPI, exacerbates HF-induced body weight gain and impairs glucose homeostasis, which is accompanied by increased inflammation, ectopic fat accumulation and mitochondrial dysfunction. Thus, our results argue against the use of dietary whey peptide supplementation as a preventative option against HF diet-induced metabolic dysfunction.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.173
Threshold uncertainty score0.741

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 studies0.0000.000
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 head0.006
GPT teacher head0.199
Teacher spread0.193 · 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 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

Citations1
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueFood & FunctionSame topicMuscle metabolism and nutritionFrench-language works237,207