Transcriptional changes in the hypothalamus, pituitary, and mammary gland underlying decreased lactation performance in mice under heat stress
Bibliographic record
Abstract
Because of climate change, heat stress (HS) causes more and more impacts on dairy animals to decrease lactation performance. The neuroendocrine system is key in regulating systemic physiological processes and milk synthesis. However, the hypothalamic-pituitary axis response to HS is still unclear. In this study, a group of lactating mice underwent a daily 2-h heat treatment (36°C) for 14 d to explore possible cross-talk between the hypothalamic-pituitary axis and mammary gland under HS. Transcriptome analyses by multitissue RNA-Seq indicated the possible mechanisms of reduced lactation performance in animals under HS. In the hypothalamus, the cAMP signaling pathway was activated to resist neuronal death, and the expression of downstream genes was increased to promote cell survival under HS. Reduced food intake might be caused by down-regulated appetite-related peptide, whereas up-regulated neuropeptide Y acted to attenuate reduced food intake. In pituitary, energy stress from lower food intake might result in reduced secretion of prolactin and growth hormone. Under HS, the mammary gland may undergo hypoxic stress, causing mammary epithelial cell apoptosis. Together, these data showed systemic changes in tissues to accommodate the effects of HS on lactation.-Han, J., Shao, J., Chen, Q., Sun, H., Guan, L., Li, Y., Liu, J., Liu, H. Transcriptional changes in the hypothalamus, pituitary, and mammary gland underlying decreased lactation performance in mice under heat 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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".