Defects in de novo neoangiogenesis in CD34KO mice revealed in a Matrigel chamber model
Bibliographic record
Abstract
CD34 is a cell surface sialomucin widely used for hematopoietic stem cell (HSC) and endothelial progenitor cell (EPC) purification and as a marker of most vascular endothelial cells. Despite extensive research, the function of this sialomucin remains elusive. CD34‐deficient (CD34KO) strains of transgenic mice surprisingly have mild phenotypes, with no significant vascular defects. We took advantage of a subcutaneous in vivo Matrigel chamber model to systematically compare angiogenesis, endothelial, pericyte, white blood cell and adipocyte growth and migration in wild type and CD34KO mice. Using immunohistochemical staining for Hoechst 33342, CD31+, NG2+, F4/80, and perilipin, we revealed differences in the frequency of specific cell populations, rate of penetration and relative cell density. Endothelial cells appear to be defective in chambers grown within CD34KO mice. Chamber digestion and analysis of incoming cells by flow cytometry indicates Ter119+ cell numbers are elevated in chambers implanted in CD34KO mice for 6 weeks. Our data provide the first report of an endothelial phenotype in CD34KO mice. As well, the results illustrate how the chamber model of de novo tissue development may be an invaluable method for elucidating endothelial cell subsets that influence neoangiogenesis in vivo . This work is funded by the Canadian Institutes of Health Research. Grant Funding Source Canadian Institutes of Health Research
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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) | 0.001 | 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 | 0.001 | 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".