Suppression of protein kinase RNA-like endoplasmic reticulum kinase by probiotics circumvents cardiovascular risk profile in experimentally induced PCOS model
Bibliographic record
Abstract
The present study was designed to investigate the role of PERK in CVD risk associated with polycystic ovarian syndrome (PCOS) in experimental rat model, and the therapeutic benefits of probiotics. Eight-weeks-old female Wistar rats were assigned into four groups ( n = 6): Control (CTRL), Probiotics (PROB), Letrozole (PCOS), and PCOS + PROB. Daily administration of letrozole (1 mg/kg) for 21 days was used to induce PCOS; thereafter, probiotics (3 × 10 9 CFU) was administered daily for 6 weeks. Biochemical parameters and histological evaluations were performed with appropriate techniques. The present findings revealed that animals with PCOS were characterized with phenotypic features such as hyperandrogenemia and multiple cysts in the ovaries. In addition, PCOS rats manifested insulin resistance and increase in glucose regulatory protein (GRP78), together with increased levels of circulating corticosterone, cardiac triglyceride, inflammatory mediators (NF-κB and TNF-α), TGF-β1, Caspase-6, and HDAC2, while a decrease in HIF-1α and NrF2 was observed when compared with control animals. These were accompanied by elevated level of PERK. However, treatment with probiotics reversed these systemic, endocrine, metabolic, and cardiac anomalies. The present study suggests that probiotics attenuates CVD risk profile in experimental PCOS rat model by suppression of PERK/HDAC2-dependent pathway.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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".