Reproductive alterations in hyperinsulinemic but normoandrogenic MSG obese female rats
Bibliographic record
Abstract
Obesity and metabolic syndrome are the common causes of reproductive and fertility disorders in women. In particular, polycystic ovary syndrome, which is clinically characterized by hyperandrogenism, oligo/anovulation, and polycystic ovarian morphology, has been increasingly associated with metabolic disorders. However, given the broad interplay between metabolic and reproductive functions, this remains a field of intense research. In this study, we investigated the effect of monosodium l-glutamate (MSG)-induced obesity on reproductive biology of female rats. Newborn female rats were subcutaneously injected with MSG (4g/kg/day) or equiosmolar saline (CTR) each 2 days up to postnatal day (pnd) 10. On pnd 60, estrous cycle was evaluated using vaginal smears twice a day for 15 days, which showed MSG rats to be oligocyclic. Thereafter, animals were killed on estrous phase for blood and tissue collection. MSG rats had increased body mass, accumulation of retroperitoneal and visceral fat pads, and visceral adipocyte hypertrophy compared with CTR rats. MSG rats were also dyslipidemic and hyperinsulinemic but were normoglycemic and normoandrogenic. Ovarian morphology analysis showed that MSG rats had a two-fold decrease in oocyte count but a six-fold increase on ovarian follicular cysts, along with a higher number of total primordial and atretic follicles. Moreover, MSG rats had a four-fold increase in anti-Müllerian hormone immunohistochemical staining on antral follicles. Taken together, data presented here characterize MSG obesity as a unique model to study the metabolic pathways underlying reproductive disorders in the absence of overactivated hypothalamic-pituitary-gonadal axis.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".