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Record W2027827990 · doi:10.1038/oby.2007.509

Awakening Cortisol Response in Lean, Obese, and Reduced Obese Individuals: Effect of Gender and Fat Distribution

2007· article· en· W2027827990 on OpenAlexaff
Fanny Therrien, Vicky Drapeau, Josée Lalonde, Sonia Lupien, Serge Beaulieu, Angelo Tremblay, Denis Richard

Bibliographic record

VenueObesity · 2007
Typearticle
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsMcGill UniversityDouglas Mental Health University InstituteUniversité Laval
Fundersnot available
KeywordsMedicineWaistInternal medicineEndocrinologyObesityAnthropometryFat distributionBlood samplingWeight lossCortisol awakening responseHydrocortisone

Abstract

fetched live from OpenAlex

OBJECTIVE: Our goal was to assess the awakening cortisol response (ACR) in obese and reduced obese men and women. RESEARCH METHODS AND PROCEDURES: Fifty-one men (16 lean, 19 abdominally obese, and 16 reduced obese) and 31 women (12 lean, 10 subcutaneously obese, and 9 reduced obese) were selected to participate to this study. Strict ranges of BMI and waist circumference were used to select the participants. Medical examination, psychological assessment, anthropometric measurements, and blood sampling were undergone at the laboratory. Cortisol response to awakening was determined with saliva cortisol sampling being taken immediately at the time of awakening and 30 minutes thereafter over 3 days within a period of 2 months. RESULTS: Men with visceral obesity exhibited an enhanced ACR, whereas this response tends to return to normal in a reduced obese state. In women, peripheral fat accumulation does not modify ACR, but weight loss increased the response. DISCUSSION: These results highlight gender effects on ACR of obese and reduced obese subjects, which could be accounted for by the different fat distribution profiles that characterize men and women. They also provide further support for the usefulness of ACR in assessing the hypothalamic-pituitary-adrenal axis activity status.

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)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.215
Threshold uncertainty score0.642

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.026
GPT teacher head0.296
Teacher spread0.270 · 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

Citations85
Published2007
Admission routes1
Has abstractyes

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