Fluorescence activated cell sorting reveals heterogeneous and cell non‐autonomous osteoprogenitor differentiation in fetal rat calvaria cell populations
Bibliographic record
Abstract
Identification of osteoblast progenitors, with defined developmental capacity, would facilitate studies on a variety of parameters of bone development. We used expression of alkaline phosphatase (ALP) and the parathyroid hormone/parathyroid hormone-related protein receptor (PTH1R) as osteoblast markers in dual-color fluorescence activated cell sorting (FACS) to fractionate rat calvaria (RC) cells into ALP(-)PTH1R(-), ALP(+)PTH1R(-), ALP(-)PTH1R(+), and ALP(+)PTH1R(+) populations. These fractionated populations were seeded clonally (n = 96) or over a range of cell densities ( approximately 150-8,500 cell/cm(2); n = 3). Our results indicate that colony forming unit-osteoblast (CFU-O)/bone nodule-forming cells are found in all fractions, but the frequency of CFU-O and total mineralized area is different across fractions. Analysis of these differences suggests that ALP(-)PTH1R(-), ALP(-)PTH1R(+), ALP(+)PTH1R(-), and ALP(+)PTH1R(+) cell populations are separated in order of increasing bone formation capacity. Dexamethasone (dex) differentially increased the CFU-O number in the four fractions, with the largest stimulation in the ALP(-) cell populations. However, there was no significant difference in the number or size distribution of CFU-F (fibroblast) colonies that formed in vehicle versus dex. Finally, both cell autonomous and cell non-autonomous (i.e., inhibitory/stimulatory effects of cell neighbors) differentiation of osteoprogenitors was seen. Only the ALP(-)PTH1R(-) population was capable of forming nodules at the clonal level, at approximately 3- or 12-times the predicted frequency of unfractionated populations in dex or vehicle, respectively. These data suggest that osteoprogenitors can be significantly enriched by fractionation of RC populations, that assay conditions modify the osteoprogenitor frequencies observed and that fractionation of osteogenic populations is useful for interrogation of their developmental status and osteogenic capacity.
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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 | 0.000 | 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 | 0.000 |
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".