Effects of miR-98 in intrauterine extracellular vesicles on maternal immune regulation during the peri-implantation period in cattle
Bibliographic record
Abstract
Evidence accumulated suggests that extracellular vesicles (EVs) present in uterine lumen play a role in conceptus-endometrial cell interactions during peri-implantation periods. However, how intrauterine EVs function on endometrium have not been well characterized. To study how intrauterine EVs affect endometrial milieu in cattle, bovine endometrial epithelial cells (EECs) were treated with EVs isolated from uterine flushing fluids (UFs) on day 17 or 20 pregnancy (P17, P20, respectively; conceptus implantation to endometrium begins on days 19-19.5). RNA extracted from EECs were then subjected to RNA sequence analysis. The analysis revealed that transcripts related to immune system were down-regulated in EECs treated with EVs on P20 compared with those on P17. To investigate whether microRNAs (miRNAs) in EVs regulate maternal immune system in the endometrium during the peri-implantation, microRNA sequence and in silico analyses were performed, identifying bta-miR-98 in EVs as a potential miRNA to regulate maternal immune system. Furthermore, the treatment of EECs with bta-miR-98 negatively regulated several immune system-related genes, CTSC, IL6, CASP4 and IKBKE, in EECs. These results suggest that EVs containing bta-miR-98 is a regulator of maternal immune system, possibly allowing the conceptus attachment to the endometrial epithelium during the peri-implantation period.
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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 | 0.001 | 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".