Loss of Vascular Endothelial Growth Factor A (VEGFA) Isoforms in Granulosa Cells Using pDmrt-1-Cre or Amhr2-Cre Reduces Fertility by Arresting Follicular Development and by Reducing Litter Size in Female Mice
Bibliographic record
Abstract
Because VEGFA has been implicated in follicle development, the objective of this study was to determine the effects of granulosa- and germ cell-specific VEGFA loss on ovarian morphogenesis, function, and female fertility. pDmrt1-Cre mice were mated to floxed VEGFA mice to develop granulosa-/germ cell-specific knockouts (pDmrt1-Cre;Vegfa-/-). The time from mating to first parturition was increased when pDmrt1-Cre;Vegfa-/- females were mated to control males (P = 0.0008) and tended to be longer for heterozygous females (P < 0.07). Litter size was reduced for pDmrt1-Cre;Vegfa-/- females (P < 0.007). The time between the first and second parturitions was also increased for heterozygous females (P < 0.04) and tended to be increased for pDmrt1-Cre;Vegfa-/- females (P < 0.07). pDmrt1-Cre;Vegfa-/- females had smaller ovaries (P < 0.04), reduced plasma estradiol (P < 0.007), fewer developing follicles (P < 0.008) and tended to have fewer corpora lutea (P < 0.08). Expression of Igf1r was reduced (P < 0.05); expression of Foxo3a tended to be increased (P < 0.06); and both Fshr (P < 0.1) and Sirt6 tended to be reduced (P < 0.06) in pDmrt1-Cre;Vegfa-/- ovaries. To compare VEGFA knockouts, we generated Amhr2-Cre;Vegfa-/- mice that required more time from mating to first parturition (P < 0.003) with variable ovarian size. Both lines had more apoptotic granulosa cells, and vascular staining did not appear different. Taken together these data indicate that the loss of all VEGFA isoforms in granulosa/germ cells (proangiogenic and antiangiogenic) causes subfertility by arresting follicular development, resulting in reduced ovulation rate and fewer pups per litter.
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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".