Day 7 Embryos Change the Proteomics and Exosomal Micro-RNAs Content of Bovine Uterine Fluid: Involvement of Innate Immune Functions
Bibliographic record
Abstract
This study aimed to characterize proteins and exosomal microRNAs (miRNAs) in the uterine flushings (UF) of cows associated with Day 7 (D7) pregnancy using the embryo donor cows of the embryo transfer program. Superovulated cows either were inseminated (AI cows) or remained non-inseminated (Ctrl cows). UF was collected on D7 in the presence of multiple embryos (AI cows) or without embryos (Ctrl cows) and subjected to isobaric tags for relative and absolute quantification protein analysis. A total of 336 proteins were identified, of which 260 proteins were more than 2-fold higher in AI cows than Ctrl cows. Gene ontology analysis revealed that many differentially expressed proteins were involved in "neutrophil-related" and "extracellular vesicular exosome-related" terms. In silico analysis of proteins with higher concentrations in the UF of AI identified 18 uniquely expressed proteins. Exosomes were isolated from the UF, from which RNA was subjected to miRNA-seq, identifying 37 miRNAs. Of these, three miRNAs were lower, and six miRNAs were higher in the UF of AI cows than those of Ctrl ones. The principal component analysis displayed a close association in miRNA and protein between bta-miR-29a, bta-miR-199b, SUGT1, and PPID. In addition, the receiver operating characteristic curve analysis showed that SUGT1 was the best predictor for the presence of embryos in the uterus. These findings suggest that the presence of multiple D7 embryos in the uterus can lead to significant changes in the protein composition and exosomal miRNA contents of UF, which could mediate innate immunological interactions between the pre-hatching embryo and the uterus in cows.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".