46 Endometrial transcriptome profiles associated with bovine preimplantation pregnancy outcome and parity
Bibliographic record
Abstract
Abstract Pregnancy failure in dairy cattle appears to be attributable to losses during embryogenesis, mainly within the first month. Models have estimated that pregnancies lost after day 30 of fertilization cost producers US $550/cow. The reasons for these losses are not well understood, and the transcriptome profile of the reproductive tract during the establishment of pregnancy may point to mechanisms. Thirty-eight cows in lactations 1 to 3 were artificially inseminated, and endometrial biopsies were collected on day 15 after artificial insemination to investigate the effect of parity on the preimplantation pregnancy outcome. Pregnancy status was determined by the presence of interferon-tau in the uterine flushing, revealing 19 pregnant (P) and 19 non-pregnant (NP) cows. Nineteen biopsy samples [9 cows in lactation 1 (6 P and 3 NP), 4 in lactation 2 (2 P and 2 NP), and 6 in lactation 3 (3P and 3NP)] with an average RNA integrity number of 7 were selected for RNA sequencing with an Illumina HiSeq analyzer. Sequence reads were assembled to the ARS_USD1.2.99 bovine reference genome using the CLC genomics workbench software. On average, the samples generated ~56 million reads and 94.99% were mapped to the reference genome. Differential gene expression analysis between P and NP cows identified 187, 60, and 136 differentially expressed genes (DEG) in lactation 1, 2 and 3, respectively (P < 0.01, FDR < 0.05, FC > ±2). Metabolic pathway enrichment analysis identified several DEG upregulated in lactations 2 and 3 associated with IL-17 signaling pathway, although expression of IL-17 itself was not different. This pathway is part of the protective response against extracellular bacteria and likely participates in pregnancy maintenance through local regulation of immune function. Further functional genomic analyses will be performed to determine additional metabolic pathways, key regulator genes, and functional SNPs associated with the establishment of pregnancy.
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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".