Deoxynivalenol and Deepoxy-Deoxynivalenol- Induced Alterations in Theca Cell Function as a Major Cause of Infertility in Dairy Cows
Bibliographic record
Abstract
activate MAPKs [7].In ruminant species, ruminal microorganisms are able to detoxify DON by converting it to the DOM-1, however despite this biochemical degradation DON-associated subclinical health problems are still occurring in dairy cows [8].Nevertheless, the impact of DON and DOM-1 on reproductive system has not been well explored.This study for the first time investigated the effect of mycotoxins on ovarian theca cell function.Although theca cells consist major part of the follicular structure, their role in follicular function has not well studied, however there is no doubt about their contribution in coordinating some signaling networks between pituitary gland, oocyte, granulosa cells and endothelial cells within the ovary.They have receptor for LH and produce androgens that can be converted to estrogens by granulosa cells, thus any alteration in the normal physiologic function of these cells can have significant impact on follicular development and ovulation process resulting in infertility [9].Thus, the objective of the present study was to shed light on the mechanism of action of DON and DOM-1 in bovine theca cells by their effects in the phospho-proteome alterations.Therefore, we used mass spectrometry approach, to evaluate the intracellular pathways of bovine theca cells activated following exposure to the sub-toxic doses of mycotoxins-DON and DOM-1.
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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".