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Record W2805224297 · doi:10.1155/2018/4315413

Role of Lipotoxicity and Contribution of the Renin-Angiotensin System in the Development of Polycystic Ovary Syndrome

2018· review· en· W2805224297 on OpenAlexaff
Alexandre Connolly, Samuel Leblanc, Jean‐Patrice Baillargeon

Bibliographic record

VenueInternational Journal of Endocrinology · 2018
Typereview
Languageen
FieldMedicine
TopicOvarian function and disorders
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsMedicinePolycystic ovaryLipotoxicityRenin–angiotensin systemInternal medicineEndocrinologyOvaryBlood pressure

Abstract

fetched live from OpenAlex

Polycystic ovary syndrome (PCOS) is a common and significant condition associated with hyperandrogenism, infertility, low quality of life, and metabolic comorbidities. One possible explanation of PCOS development is cellular dysfunction induced by nonesterified fatty acids (NEFAs), that is, lipotoxicity, which could explain both the hyperandrogenemia and insulin resistance that characterize women with PCOS. The literature suggests that androgen biosynthesis may be induced by overexposure of androgen-secreting tissues to NEFA and/or defective NEFA metabolism, leading to lipotoxic effects. Indeed, lipotoxicity could trigger androgenic hyperresponsiveness to insulin, LH, and ACTH. In most PCOS women, lipotoxicity also causes insulin resistance, inducing compensatory hyperinsulinemia, and may thus further increase hyperandrogenemia. Many approaches aimed at insulin sensitization also reduce lipotoxicity and have been shown to treat PCOS hyperandrogenemia. Furthermore, our group and others found that angiotensin II type 2 receptor (AT2R) activation is able to improve lipotoxicity. We provided evidence, using C21/M24, that AT2R activation improves adipocytes' size and insulin sensitivity in an insulin-resistant rat model, as well as androgen levels in a PCOS obese rat model. Taken together, these findings point toward the important role of lipotoxicity in PCOS development and of the RAS system as a new target for the treatment of PCOS.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.877
Threshold uncertainty score0.291

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.025
GPT teacher head0.306
Teacher spread0.281 · 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 designOther design
Domainnot available
GenreReview

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

Citations18
Published2018
Admission routes1
Has abstractyes

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