The mycotoxin metabolite deepoxy- deoxynivalenol increases apoptosis and decreases steroidogenesis in bovine ovarian theca cells†
Bibliographic record
Abstract
The mycotoxin deoxynivalenol (DON) has been shown to inhibit ovarian granulosa cell function in cattle in vitro, but it is not known whether DON or its metabolite deepoxy-DON (DOM-1) affects theca cell function. The objectives of this study were to determine the effects of DON and of DOM-1 on theca cell steroidogenesis and apoptosis, and to determine the main pathways through which they act. Bovine theca cells were cultured in a nonluteinizing serum-free culture system, and challenged with DON or DOM-1 for 4 days to measure steroidogenesis and apoptosis, for 1-8 h to measure immediate-early genes, and for 5-60 min to measure phosphorylation of intracellular signaling proteins. Addition of DON decreased progesterone secretion at doses as low as 0.5 ng/ml but had no effect on testosterone secretion. Addition of DOM-1 inhibited progesterone and testosterone secretion at 0.5 ng/ml. Treatment of cells with 1 ng/ml DOM-1 increased the proportion of apoptotic cells, whereas DON had no effect. Addition of DON or DOM-1 stimulated phosphorylation of EIF2AK2, MAPK3/1, and AKT. However, DON inhibited and DOM-1 stimulated MAPK14 phosphorylation. DON increased the levels of mRNA encoding early-immediate genes EGR1, EGR3, and FOS, whereas DOM-1 was without effect. DOM-1 but not DON increased abundance of mRNA of the endoplasmic reticulum (ER) stress-related proteins, PRKRA and ATF4. We conclude that DOM-1 has a major impact on theca function in cattle, and possibly induces theca cell apoptosis through ER stress.
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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".