Analysis of apoptosis levels and MMP7 gene expression in ovaries of postpartum female rabbits after long-term use of LHRH-A3
Bibliographic record
Abstract
Luteinizing hormone-releasing hormone A3 (LHRH-A3), a reproductive hormone analog, is widely used to stimulate ovulation in female rabbits. However, the long-term impact of sustained LHRH-A3 administration on the reproductive system, particularly ovarian health, remains unclear. In this study, we compared apoptosis levels in ovaries and molecular regulation between LHRH-A3-treated (A3 group) and untreated female rabbits (N group) after their 5th litter. Western blotting showed a significantly lower Bcl-2/Bax ratio in the A3 group compared with the N group ( P < 0.01), indicating higher ovarian apoptosis. Ovarian tissues from four rabbits per group were divided into the A3 group and the N group, and RNA-seq technology was then utilized to conduct transcriptome analysis on these two groups. This analysis revealed 220 differentially expressed genes (DEGs), including BMP6, BMP15, CYP1A1, and other reproductive-related genes. KEGG analysis of these DEGs showed their involvement in processes such as the cell cycle, PI3K-Akt signaling pathway, and ovarian steroidogenesis. Subsequently, we selected the key gene Matrix metallopeptidase 7 ( MMP7) for functional analysis using CCK8 and Annexin V-FITC/PI techniques. MMP7 was found to promote the proliferation of granulosa cells (GCs) and inhibit apoptosis ( P < 0.01). In conclusion, LHRH-A3 treatment can modulate ovarian molecular regulation, with the key gene MMP7 involved in the proliferation and apoptosis of GCs.
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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) | 0.001 | 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".