Loss of Vascular Endothelial Growth Factor A (VEGFA) Isoforms in the Testes of Male Mice Causes Subfertility, Reduces Sperm Numbers, and Alters Expression of Genes That Regulate Undifferentiated Spermatogonia
Bibliographic record
Abstract
Vascular endothelial growth factor A (VEGFA) isoform treatment has been demonstrated to alter spermatogonial stem cell homeostasis. Therefore, we generated pDmrt1-Cre;Vegfa(-/-) (knockout, KO) mice by crossing pDmrt1-Cre mice to floxed Vegfa mice to test whether loss of all VEGFA isoforms in Sertoli and germ cells would impair spermatogenesis. When first mated, KO males took 14 days longer to get control females pregnant (P < .02) and tended to take longer for all subsequent parturition intervals (9 days; P < .07). Heterozygous males sired fewer pups per litter (P < .03) and after the first litter took 10 days longer (P < .05) to impregnate females, suggesting a more progressive loss of fertility. Reproductive organs were collected from 6-month-old male mice. There were fewer sperm per tubule in the corpus epididymides (P < .001) and fewer ZBTB16-stained undifferentiated spermatogonia (P < .003) in the testes of KO males. Testicular mRNA abundance for Bcl2 (P < .02), Bcl2:Bax (P < .02), Neurog3 (P < .007), and Ret was greater (P = .0005), tended to be greater for Sin3a and tended to be reduced for total Foxo1 (P < .07) in KO males. Immunofluorescence for CD31 and VE-Cadherin showed no differences in testis vasculature; however, CD31-positive staining was evident in undifferentiated spermatogonia only in KO testes. Therefore, loss of VEGFA isoforms in Sertoli and germ cells alters genes necessary for long-term maintenance of undifferentiated spermatogonia, ultimately reducing sperm numbers and resulting in subfertility.
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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 | 0.001 | 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) | 0.003 | 0.001 |
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".