A Unique Rodent Model of Cardiometabolic Risk Associated with the Metabolic Syndrome and Polycystic Ovary Syndrome
Bibliographic record
Abstract
Polycystic ovary syndrome (PCOS) is characterized by hyperandrogenism, oligo-/anovulation, and polycystic ovarian morphology and is a complex endocrine disorder that also presents with features of the metabolic syndrome, including obesity, insulin resistance, and dyslipidemia. These latter symptoms form cardiometabolic risk factors predisposing individuals to the development of type 2 diabetes and cardiovascular disease (CVD). To date, animal models to study PCOS in the context of the metabolic syndrome and CVD risk have been lacking. The aim of this study was to investigate the JCR:LA-cp rodent as an animal model of PCOS associated with the metabolic syndrome. Metabolic indices were measured at 6 and 12 wk, and reproductive parameters including ovarian morphology and estrous cyclicity were assessed at 12 wk or adulthood. At 6 wk of age, the cp/cp genotype of the JCR:LA-cp strain developed visceral obesity, insulin resistance, and dyslipidemia (hypertriglyceridemia and hypercholesterolemia) compared with control animals. Serum testosterone concentrations were not significantly different between groups at 6 wk of age. However, at 12 wk, the cp/cp genotype had higher serum testosterone concentrations, compared with control animals, and presented with oligoovulation, a decreased number of corpora lutea, and an increased number of total follicles, in particular atretic and cystic follicles. The cardiometabolic risk factors in the cp/cp animals were exacerbated at 12 wk including obesity, insulin resistance, and dyslipidemia. The results of this study demonstrate that the JCR:LA-cp rodent may be a useful PCOS-like model to study early mechanisms involved in the etiology of cardiometabolic risk factors in the context of both PCOS and the metabolic syndrome.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".