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Record W4415450350 · doi:10.1210/jendso/bvaf149.1922

MON-191 In Vivo Overexposure to Non-esterified Fatty Acids Increases Circulating Androgen Levels in Normal Mongrel Dogs

2025· article· en· W4415450350 on OpenAlexaff
CHRISTOPHE RICHER DIT LAFLÈCHE, Joanie Faubert, F. Naimi, Sylvain Bellanger, M.-C. Battista, Ouhida Benrezzak, André C. Carpentier, Jean‐Patrice Baillargeon

Bibliographic record

VenueJournal of the Endocrine Society · 2025
Typearticle
Languageen
FieldMedicine
TopicAdipose Tissue and Metabolism
Canadian institutionsCentre Hospitalier Universitaire de SherbrookeUniversité de Sherbrooke
Fundersnot available
KeywordsNEFAAndrogenLipotoxicityIn vivoPolycystic ovarySalineInsulin

Abstract

fetched live from OpenAlex

Abstract Disclosure: C. Richer dit Laflèche: None. J. Faubert: None. F. Naimi: None. S. Bellanger: None. M. Battista: None. O. Benrezzak: None. A. Carpentier: None. J. Baillargeon: None. Background. The exact etiology of polycystic ovary syndrome is poorly understood, but studies suggest that lipotoxicity may be an important contributor. The aim of this study was to evaluate the effects of an in vivo overexposure to non-esterified fatty acids (NEFA) on changes in circulating androgen levels in a dog model, which was selected for its similarities with humans in steroidogenesis and energy metabolism. Methods. Female mongrel dogs (27.6 ± 2.9 kg) underwent a 17.5-hour metabolic protocol. During the first 8 hours (night period), dogs (n=6/group) received either a Intralipid-heparin 20% (IH; 0.02 ml/kg/min+0.5 U/kg/min) or a saline infusion (control group), followed by a standard meal at 8:30. Blood samples were drawn every 60 minutes during the night period (8h) and for 9 hrs post-meal (day period). Only 2 dogs (1/group) were in estrus. Changes from baseline were calculated as the ratio of mean levels during the period to the level measured at baseline (before IH infusion initiation) and compared between groups using Wilcoxon tests. Associations of androgen (testosterone, androstenedione, 17-hydroxyprogesterone (17-OHP), and DHEA) ratios with insulin and NEFA ratios during each test phase were tested using Spearman’s correlations. In addition, NEFA or insulin ratios were correlated with 17-OHP ratios corrected for potential confounders (individually, by dividing 17-OHP ratios by either cortisol, ACTH, insulin or NEFA ratios). Results. Baseline androgen levels were comparable between experimental groups. NEFA levels nearly doubled during the nocturnal IH infusion compared with the saline group (1.77 vs. 0.93-fold increase, p=0.015) and rapidly returned to normal after discontinuation. 17-OHP level ratios were significantly increased 1.5-fold in the IH group compared to the saline group both at night (0.86 vs. 0.56, p=0.026) and more than doubled during the day (0.90 vs. 0.42, p=0.009), without significant changes in other androgens. Nocturnal NEFA ratios correlated with both the nocturnal and diurnal 17-OHP ratios (rho=0.783, p=0.003; and rho=0.755, p=0.005); and diurnal insulin ratios correlated with 17-OHP ratios (rho=0.615, p=0.03). Correcting for nocturnal insulin ratios weakened the correlation between nocturnal 17-OHP ratios and NEFA ratios (rho=0.434, p=0.159), indicating a confounding effect. Moreover, adjusting for diurnal insulin ratios decreased the correlation between diurnal 17-OHP ratios and nocturnal NEFA ratios (rho=0.378, p=0.226). The association between diurnal 17-OHP ratios and diurnal insulin ratios was partly confounded by both night and day NEFA ratios (rho=0.336; and rho=0.224). Associations were mostly independent of ACTH and cortisol ratios. Conclusion. An acute in vivo elevation of NEFA using an IH protocol induces a significant increase in androgen production through a mechanism that is partially dependent on insulin. Presentation: Monday, July 14, 2025

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: Bench or experimental · Consensus signal: Bench or experimental
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 integrity0.0000.001
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 head0.295
Teacher spread0.278 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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