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Record W2018664083 · doi:10.1038/oby.2010.209

Blood Gene Expression Reveal Pathway Differences Between Diet‐Sensitive and Resistant Obese Subjects Prior to Caloric Restriction

2010· article· en· W2018664083 on OpenAlexafffund
Sujoy Ghosh, Robert Dent, Mary‐Ellen Harper, Joan Stuart, Ruth McPherson

Bibliographic record

VenueObesity · 2010
Typearticle
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsUniversity of OttawaOttawa Hospital
FundersNational Heart, Lung, and Blood InstituteHeart and Stroke Foundation of CanadaGlaxoSmithKline
KeywordsCaloric theoryOxidative phosphorylationWeight lossMedicineEndocrinologyInternal medicineObesityGene expressionDownregulation and upregulationGeneBiologyGeneticsBiochemistry

Abstract

fetched live from OpenAlex

Weight loss in response to caloric restriction displays significant interindividual heterogeneity. To develop early predictors of weight-loss success, we have compared whole-blood gene expression profiles of obese, diet-sensitive vs. obese, diet-resistant subjects prior to the initiation of clinically supervised caloric restriction. Pathway enrichment analysis of gene expression profiles by multiple applications converged on the "oxidative phosphorylation" (OXPHOS) pathway, and to a lesser extent the "proteasome" pathway, as statistically significantly upregulated in obese, diet-sensitive subjects compared to the diet-resistant subjects. The finding of increased OXPHOS is consistent with earlier observations of increased proton leak, increased expression of OXPHOS genes, and increased oxidative muscle fibers in skeletal muscle of obese, diet-sensitive subjects. The current study further highlights the utility of blood as a sentinel tissue reflecting systemic states and provides a potential modality to predict future weight-loss success, relevant to the design of individualized bariatric treatment programs.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.017
GPT teacher head0.252
Teacher spread0.235 · 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 source (direct Gemma or distilled Codex), 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

Citations39
Published2010
Admission routes2
Has abstractyes

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