Somatic cell nuclear transfer alters peri-implantation trophoblast differentiation in bovine embryos
Bibliographic record
Abstract
Abnormal placental development limits success in ruminant pregnancies derived from somatic cell nuclear transfer (SCNT), due to reduction in placentome number and consequently, maternal/fetal exchange. In the primary stages of an epithelial-chorial association, the maternal/fetal interface is characterized by progressive endometrial invasion by specialized trophoblast binucleate/giant cells (TGC). We hypothesized that dysfunctional placentation in SCNT pregnancies results from aberration in expression of genes known to be necessary for trophoblast proliferation (Mash2), differentiation (Hand1), and function (IFN-tau and PAG-9). We, therefore, compared the expression of these factors in trophoblast from bovine embryos derived from artificial insemination (AI), in vitro fertilization (IVF), and SCNT prior to (day 17) and following (day 40 of gestation) implantation, as well as TGC densities and function. In preimplantation embryos, Mash2 mRNA was more abundant in SCNT embryos compared to AI, while Hand1 was highest in AI and IVF relative to SCNT embryos. IFN-tau mRNA abundance did not differ among groups. PAG-9 mRNA was undetectable in SCNT embryos, present in IVF embryos and highest in AI embryos. In postimplantation pregnancies, SCNT fetal cotyledons displayed higher Mash2 and Hand1 than AI and IVF tissues. Allelic expression of Mash2 was not different among the groups, which suggests that elevated mRNA expression was not due to altered imprinting status of Mash2. The day 40 SCNT cotyledons had the fewest number of TGC compared to IVF and AI controls. Thus, expression of genes critical to normal placental development is altered in SCNT bovine embryos, and this is expected to cause abnormal trophoblast differentiation and contribute to pregnancy loss.
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 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".