Low concentrations of the food contaminant Deoxynivalenol trigger apoptosis and impair GnRH-induced LH secretion in pituitary gonadotrope-like cells
Bibliographic record
Abstract
Abstract The Fusarium mycotoxin deoxynivalenol (DON) is one of the most frequently occurring food contaminants. Nearly all individuals are exposed to DON, due to it widespread presence in grains and grain-based products. Chronic DON poisoning is associated with growth retardation, immunotoxicity as well as impaired reproduction and fetal development. At the molecular level, DON alters intracellular signaling by activating mitogen-activated protein kinases (MAPKs) that modulate cell growth, differentiation, and apoptosis. Of note, these MAPKs are also critical mediators of gonadotrophin-releasing hormone (GnRH)-induced synthesis and secretion of follicle-stimulating hormone (FSH) and luteinizing hormone (LH) by pituitary gonadotrope cells. So far, no research has explored the potential endocrine-disrupting effects of DON on pituitary gonadotropins production. Herein, we show the first evidence that DON affects LH production by the immortalized gonadotrope-like cell line LβT2 in a concentration-dependent manner. Taken together, our experiments demonstrated that low concentrations of DON affect GnRH-induced signaling through a mechanism that, at least in part, involves apoptosis and inhibition of GnRH-induced phosphorylation of ERK-MAPK. Consequently, DON also affects the GnRH-induced expression of Cga and Lhb , two critical genes for LH synthesis and secretion by gonadotrope cells in mammals. This research broadens our knowledge of the toxicity of DON and brings a new depth to the potential neuroendocrine implications for reproduction. Graphical abstract
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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".