Basal Cells of Second Trimester Fetal Breasts: Immunohistochemical Study of Myoepithelial Precursors
Bibliographic record
Abstract
The molecular characterization of human mammary myoepithelial cells is incomplete, hindering our understanding of its importance in breast physiology and pathology. Because data on the precursors of this cell lineage remain scarce and often contradictory, basal epithelial cells of second trimester fetal breasts were studied by light microscopy (LM) and immunohistochemistry (IHC). Up to 20 wk of gestational age, the mammary rudiments only comprised roundish primary outgrowths, "primary buds," more likely to represent immature nipples than true mammary tissue. At 21 wk secondary outgrowths, "projections," extended from enlarged primary buds into well-vascularized layers of dense mesenchyme. Basal projection cells had a partial myoepithelial-like phenotype: they reacted with CD29, CD49f, CD104, keratin 14, vimentin, S100beta protein, and p63; furthermore, many became positive for keratin 17, alpha-smooth muscle actin, and CD10 (but not for keratin 19) between wk 21 and 25. The continuous basement membrane associated with the fetal mammary rudiments was strongly positive for collagens type IV and VII, and for laminin 5. Consistently strong and basally polarized staining for hemidesmosomal components suggested that although incompletely differentiated, most second trimester myoepithelial precursors might already mediate local epithelial-mesenchymal interactions, i.e., complex signaling pathways which are crucial for both orderly growth during development and maintenance of homeostasis during adult life. Because they are likely implicated in the phenomenon of menstrual cycle-related growth spurts in the adult resting breast, the strategically positioned cells of the myoepithelial lineage might constitute critical protagonists in defective epithelial-mesenchymal signaling associated with cancer progression.
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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) | 0.001 | 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".