In vitro effects of 5-Hydroxy-L-tryptophan supplementation on primary bovine mammary epithelial cell gene expression under thermoneutral or heat shock conditions
Bibliographic record
Abstract
Serotonin (5-HT) is an autocrine-paracrine molecule within the mammary gland regulating homeostasis during lactation and triggering involution after milk stasis. Exposure of dairy cows to hyperthermia during the dry period alters mammary gland involution processes leading to reduced subsequent yields. Herein, primary bovine mammary epithelial cells (pBMEC) under thermoneutral (TN, 37 °C) or heat shock (HS, 41.5 °C) conditions were cultured with either 0, 50, 200, or 500 μM 5-Hydroxy-L-tryptophan (5-HTP; 5-HT precursor) for 8-, 12- or 24-h. Expression of 95 genes involved in 5-HT signaling, involution and tight junction regulation were evaluated using a Multiplex RT-qPCR BioMark Dynamic Array Circuit. Different sets of genes were impacted by 5-HTP or temperature, or by their interaction. All 5-HT signaling genes were downregulated after 8-h of HS and then upregulated after 12-h, relative to TN. After 24-h, apoptosis related gene, FASLG, was upregulated by all doses except TN-200 μM 5-HTP, and cell survival gene, FOXO3, was upregulated by HS-50, 200 and 500 μM 5-HTP, suggesting 5-HTP involvement in cell turnover under HS. Supplementing 5-HTP at various concentrations in vitro to pBMEC modulates the expression of genes that might aid in promoting epithelial cell turn-over during involution in dairy cattle under hyperthermia.
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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 | 0.001 |
| 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".