Regulation of Skeletal Progenitor Differentiation by the Bmp and Retinoid Signaling Pathways
Bibliographic record
Abstract
The generation of the paraxial skeleton requires that commitment and differentiation of skeletal progenitors is precisely coordinated during limb outgrowth. Several signaling molecules have been identified that are important in specifying the pattern of these skeletal primordia. Very little is known, however, about the mechanisms regulating the differentiation of limb mesenchyme into chondrocytes. Overexpression of RARalpha in transgenic animals interferes with chondrogenesis and leads to appendicular skeletal defects (Cash, D.E., C.B. Bock, K. Schughart, E. Linney, and T.M. Underhill. 1997. J. Cell Biol. 136:445-457). Further analysis of these animals shows that expression of the transgene in chondroprogenitors maintains a prechondrogenic phenotype and prevents chondroblast differentiation even in the presence of BMPs, which are known stimulators of cartilage formation. Moreover, an RAR antagonist accelerates chondroblast differentiation as demonstrated by the emergence of collagen type II-expressing cells much earlier than in control or BMP-treated cultures. Addition of Noggin to limb mesenchyme cultures inhibits cartilage formation and the appearance of precartilaginous condensations. In contrast, abrogation of retinoid signaling is sufficient to induce the expression of the chondroblastic phenotype in the presence of Noggin. These findings show that BMP and RAR-signaling pathways appear to operate independently to coordinate skeletal development, and that retinoid signaling can function in a BMP-independent manner to induce cartilage formation. Thus, retinoid signaling appears to play a novel and unexpected role in skeletogenesis by regulating the emergence of chondroblasts from skeletal progenitors.
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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".