CD24 and CD49f expressions of E14.5 mouse mammary anlagen cells define putative distribution of earlier embryonic mammary stem cell activities
Bibliographic record
Abstract
Stem cell biology offers promise for understanding the origins of the mammary gland. However, the distribution of mammary stem cell (MaSC) activities at earlier embryonic stages has not been fully identified. The markers for sorting adult MaSC, CD24, CD29, and CD49f have been applied to analyze fetal MaSCs. Here we explored mammary anlagen MaSCs by investigating the expression of CD24 and CD49f. According to the comparative analysis between adult mammary gland and fetal mammary anlagen, we found that fetal mouse mammary anlagen may possess a high percentage of potential MaSCs. Flow cytometry analysis revealed 2 distinct mammary anlagen populations: Lin–CD24med and Lin–CD24high. Sphere-forming and mammary repopulating assays confirmed that the stem cell activity of E14.5 mouse mammary anlagen was restricted to the Lin–CD24med cell population. Furthermore, CD24med mammary anlagen cells were separated into Lin–CD24medCD49f+ and Lin–CD24medCD49f– populations and identified, respectively. The results proved that the mammary anlagen Lin–CD24medCD49f+ cell population possesses more stem cell activities than the Lin–CD24medCD49f– cell population. However, a limited numbers of stem cells and large numbers of stromal cells were identified in mammary anlagen in the Lin–CD24med cell population.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".