The effect of inflammation on the synthesis of luteinizing hormone and gonadotropin-releasing hormone receptor expression in the <i>pars tuberalis</i> of ewe during different photoperiodic conditions
Bibliographic record
Abstract
The study was designed to determine the effect of endotoxin-induced inflammation on luteinizing hormone (LH) synthesis and gonadotropin-releasing hormone (GnRH) receptor expression in the pars tuberalis (PT) of ewes during anestrous season and follicular phase taking into account the time of the day. Moreover, the effect of inflammation on the release of melatonin and its type I receptor gene expression in the PT was also determined. Lipopolysaccharide administration reduced nocturnal release of melatonin only during anestrous season, but it did not influence the gene expression of melatonin type I receptor in the PT. Inflammation inhibited nocturnal increase in the gene and protein expression of LH in the PT during the follicular phase. Since in day-active species nocturnal accumulation of LH protein in the pituitary precedes the LH surge, this lowering of LH content may delay or disturb the surge occurrence. Suppression of LH secretion could have resulted from the decreased sensitivity of the PT on the action of GnRH because inflammation reduced GnRH receptor expression. The study suggests that the ability of endotoxin to suppress LH synthesis in the PT may be another mechanism by which inflammation disturbs reproductive neuroendocrine axis in seasonal breeders.
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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".