ERK1/2-dependent gene expression in the bovine ovulating follicle
Bibliographic record
Abstract
Ovulation is triggered by gonadotropin surge-induced signaling cascades. To study the role of extracellular signal-regulated kinase 1/2 (ERK1/2) in bovine ovulation, we administered the pharmacological inhibitor, PD0325901, into the preovulatory dominant follicle by intrafollicular injection. Four of five cows treated with 50 µM PD0325901 failed to ovulate. To uncover the molecular basis of anovulation in ERK1/2-inhibited cows, we collected granulosa and theca cells from Vehicle and PD0325901 treated follicles. Next-generation sequencing of granulosa cell RNA revealed 285 differentially expressed genes between Vehicle and PD0325901-treated granulosa cells at 6 h post-GnRH. Multiple inflammation-related pathways were enriched among the differentially expressed genes. The ERK1/2 dependent LH-induced genes in granulosa cells included EGR1, ADAMTS1, STAT3 and TNFAIP6. Surprisingly, PD0325901 treatment did not affect STAR expression in granulosa cells at 6 h post-GnRH. Granulosa cells had higher STAR protein and theca cells had higher levels of STAR mRNA in ERK1/2-inhibited follicles. Further, both granulosa and theca cells of ERK1/2-inhibited follicles had higher expression of SLC16A1, a monocarboxylate transporter, transporting substances including β-hydroxybutyrate across the plasma membrane. Taken together, ERK1/2 plays a significant role in mediating LH surge-induced gene expression in granulosa and theca cells of the ovulating follicle in cattle.
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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".