Gene expression and maintenance of pregnancy in bovine: roles of trophoblastic binucleate cell-specific molecules
Bibliographic record
Abstract
Cell to cell interaction plays a pivotal role in the regulation of placentogenesis and exchange of stage-specific developmental signals between the fetal and maternal units. Specifically, these interactions are paramount for programmed fetal growth, maternal adaptation to pregnancy and coordination of parturition. However, little is known about the precise regulation of placentation and maintenance of gestation in cattle. Therefore, the aim of the present study was to decipher the complex networks ofcell communication to gain an insight into the multifaceted developmental process and understand the profound consequences of flawed communication. In the ruminant, the binucleate cell plays a central role in forming the structures and secretions at the fetomaternal interface that are crucial in establishing and maintaining pregnancy. Herein, we summarise differences in the abundance of specific RNA transcripts in the bovine cotyledon and caruncle using global gene expression profiling and further investigate the relationship of mRNA abundance for selected pregnancy-specific genes of interest (identified from microarray studies) that are localised exclusively to the binucleate cell, such as placental lactogen, prolactin-related proteins and pregnancy-associated glycoproteins. The results suggest that a well-orchestrated transcriptional command from binucleate cells is pivotal to the establishment and progression of pregnancy in cattle.
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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".