Neuropeptide Y directly reduced apoptosis of granulosa cells, and the expression of NPY and its receptors in PCOS subjects
Bibliographic record
Abstract
BACKGROUND: Most women with anovulatory infertility show polycystic ovarian syndrome (PCOS), and androgen excess is known as a key factor involved in pathogenicity of PCOS. However, the mechanism of follicular developmental arrest in PCOS is not completely understood. The reproductive function of Neuropeptide Y (NPY) in the ovary during folliculogenesis was previously reported; NPY function in apoptosis and proliferation of granulosa cells (GCs) is follicular-stage dependent. The objective of this study was to investigate the role of NPY in ovarian follicular development and the pathogenesis of PCOS. METHODS: To simulate the PCOS phenotype using a rat model, 21-day old Sprague Dawley rats were implanted with dihydrotestosterone (DHT) capsule (83 µg/day) and euthanized after 28 days. mRNA and protein content of NPY and its receptors were assessed in GCs from DHT treated rats using RT-qPCR and Western blot, respectively. Proliferation and apoptosis of GCs was assessed using Ki67- and TUNEL assays. Finally, NPY levels were measured in human follicular fluid (FF) from matched PCOS and non-PCOS patients using ELISA. RESULTS: GCs from DHT treated rats (PCOS-GCs) contained significantly less NPY protein and Npy mRNA by 0.16- and 0.56-fold, respectively, and more NPY receptor type 2 and 5 protein by 2.21- and 3.17-fold, respectively, when compared to sham control. Addition of recombinant NPY to PCOS-GCs culture did not alter Ki67-positive but significantly decreased TUNEL-positive cells by 0.65-fold, but not to baseline levels. There was no significant difference in NPY levels in FF between PCOS and non-PCOS subjects. CONCLUSIONS: These results indicate that DHT modulates expression of NPY and its receptors, NPY decreases DHT-induced GCs apoptosis. That alterations in NPY's function might be involved in follicular developmental failure of PCOS.
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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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".