Selected pro-inflammatory factor transcripts in bovine endometrial epithelial cells are regulated during the oestrous cycle and elevated in case of subclinical or clinical endometritis
Bibliographic record
Abstract
Endometrial cells take part in embryo-maternal communication, as well as supporting the immune system in defending against invading pathogens. The aim of the present study was to examine the mRNA expression of factors that have been suggested to be involved in both events in the bovine endometrial epithelium, namely bovine granulocyte chemotactic protein 2 (CXCL5), interleukin-1 beta (IL1B), IL6, IL8, tumour necrosis factor (TNF), cyclooxygenase 2 (PTGS2) and haptoglobin (HP). Samples were collected in vivo from cows on Days 21-27 postpartum by the cytobrush method to evaluate the correlation between inflammatory factors and uterine health (cows with signs of clinical or subclinical endometritis and healthy cows). Bovine uteri were collected at the abattoir to investigate oestrous cycle-dependent mRNA expression patterns. Real-time reverse transcription-polymerase chain reaction revealed that the expression of CXCL5, IL1B, IL8 and TNF mRNA was significantly higher in cows with subclinical or clinical endometritis compared with healthy cows. The expression of CXCL5, IL1B and IL8 mRNA was increased around ovulation compared with the luteal phase. There was no indication of either oestrous cycle-dependent expression or a correlation with uterine health for IL6, PTGS2 and HP transcripts. These results suggest that CXCL5, IL1B, IL8 and TNF may represent potential marker genes for the detection of cows with subclinical endometritis and for monitoring new therapeutic approaches.
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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".