Number, frequency, self‐renewal, and expansion of osteoprogenitor cells (CFU‐O) in subcultured female rat vertebral cell populations
Bibliographic record
Abstract
The present study was undertaken to determine whether the frequency and/or number of dexamethasone- and progesterone-responsive osteoprogenitors in cell populations derived from vertebrae of 6-week-old female rats could be increased relative to that of other progenitors. Frequencies and numbers of both progenitor types were determined for up to six subcultures using continuous subculturing, limiting dilution analysis, and colony assays. In dexamethasone-containing medium, subculturing resulted in an eightfold increase in the total number of dexamethasone-responsive osteoprogenitors and a 14-fold increase in progesterone-responsive osteoprogenitors in second subculture cells over first subculture cells without a significant increase in the frequency of these progenitors. From the third subculture onward, the frequency of both classes of osteoprogenitors decreased in a linear manner and none were observed after six subcultures. Similar results were obtained in progesterone-containing medium. Limiting dilution analysis in the presence of dexamethasone indicated that 2.61 % of cells represented a colony forming unit-fibroblast and 0.28 % represented an osteoprogenitor in first subculture cells, while in second subculture cells, these frequencies increased to 5.56 % and 0.40 %, respectively. Results show that while the frequency of colony forming unit-osteoprogenitor is not increased in the second subculture over the first, the total number of osteoprogenitors is greatly increased because of expansion of the total progenitor cell pool.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".