Expression of Vascular Endothelial Growth Factor Isoforms and Receptors Flt-1 and KDR During the Peri-Implantation Period in the Mink, Mustela vison1
Bibliographic record
Abstract
Expression of vascular endothelial growth factor (VEGF) isoforms and its receptors, Flt-1 and KDR, was investigated during the period of peri-implantation in mink, a species that displays obligate embryonic diapause. Uterine samples were collected during diapause, embryo activation, and implantation from pseudopregnant and anestrous animals and analyzed by semiquantitative reverse transcription polymerase chain reaction and immunohistochemistry. The abundance of mRNA of VEGF isoforms 120, 164, and 188 was highest during late embryo activation and at implantation. VEGF protein was localized to the glandular epithelium at all stages of peri-implantation, whereas the luminal epithelium lacked VEGF reactivity during diapause. Endometrial stroma and luminal and glandular epithelia were positive for VEGF in implanted uteri. The invasive trophoblast cells of the implanting embryo were intensively stained. High levels of VEGF mRNA in pseudopregnant uteri indicates that VEGF upregulation leading to implantation is dependent upon maternal rather than embryonic factors. The abundance of the two receptors, KDR and Flt-1, increased in the uterus during implantation. Low levels of the receptors in pseudopregnant uteri compared with those containing activated or implanted embryos indicates that the embryo regulates receptor expression. These results demonstrate VEGF and VEGF receptor expression during early gestation in mink and suggest that maternal and embryonic input regulates different aspects of the angiogenic process.
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".