Biology and pathology of Rho GTPase, PI‐3 kinase‐Akt, and MAP kinase signaling pathways in chondrocytes
Bibliographic record
Abstract
Chondrocytes provide the framework for the developing skeleton and regulate long-bone growth through the activity of the growth plate. Chondrocytes in the articular cartilage, found at the ends of bones in diarthroidial joints, are responsible for maintenance of the tissue through synthesis and degradation of the extracellular matrix. The processes of growth, differentiation, cell death and matrix remodeling are regulated by a network of cell signaling pathways in response to a variety of extracellular stimuli. These stimuli consist of soluble ligands, including growth factors and cytokines, extracellular matrix proteins, and mechanical factors that act in concert to regulate chondrocyte function through a variety of canonical and non-canonical signaling pathways. Key chondrocyte signaling pathways include, but are not limited to, the p38, JNK and ERK MAP kinases, the PI-3 kinase-Akt pathway, the Jak-STAT pathway, Rho GTPases and Wnt-beta-catenin and Smad pathways. Modulation of the activity of any of these pathways has been associated with various pathological states in cartilage. This review focuses on the Rho GTPases, the PI-3 kinase-Akt pathway, and some selected aspects of MAP kinase signaling. Most studies to date have examined these pathways in isolation but it is becoming clear that there is significant cross-talk among the pathways and that the overall effects on chondrocyte function depend on the balance in activity of multiple signaling proteins.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".