BPA Decreases PDCD4 in Bovine Granulosa Cells Independently of miR-21 Inhibition
Bibliographic record
Abstract
microRNAs (miRNAs) are susceptible to environmental factors that might affect cellular function and impose negative effects on female reproduction. miR-21 is the most abundant miRNA in bovine granulosa cells and is widely reported as affected by Bisphenol A (BPA) exposure, yet the cause and consequences are not entirely elucidated. BPA is a synthetic endocrine disruptor associated with poor fertility. miR-21 function in bovine granulosa cells is investigated utilizing locked nucleic acid (LNA) oligonucleotides to suppress miR-21. Before measuring apoptosis and quantifying miR-21 apoptotic targets PDCD4 and PTEN, transfection was optimized and validated. BPA was introduced to see how it affects miR-21 regulation and which BPA-mediated effects are influenced by miR-21. miR-21 knockdown and specificity against additional miRNAs were confirmed. miR-21 was found to have antiapoptotic effects, which could be explained by its effect on the proapoptotic target PDCD4, but not PTEN. Previous findings of miR-21 overexpression were validated using BPA treatments, and the temporal influence of BPA on miR-21 levels was addressed. Finally, BPA effects on upstream regulators, such as VMP1 and STAT3, explain the BPA-dependent upregulation of miR-21 expression. Overall, this research enhances our understanding of miR-21 function in granulosa cells and the mechanisms of BPA-induced reproductive impairment.
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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 | 0.001 |
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".