Low-Frequency High-Magnitude Mechanical Strain of Articular Chondrocytes Activates p38 MAPK and Induces Phenotypic Changes Associated with Osteoarthritis and Pain
Bibliographic record
Abstract
Osteoarthritis (OA) is a debilitating joint disorder resulting from an incompletely understood combination of mechanical, biological, and biochemical processes. OA is often accompanied by inflammation and pain, whereby cytokines associated with chronic OA can up-regulate expression of neurotrophic factors such as nerve growth factor (NGF). Several studies suggest a role for cytokines and NGF in OA pain, however the effects of changing mechanical properties in OA tissue on chondrocyte metabolism remain unclear. Here, we used high-extension silicone rubber membranes to examine if high mechanical strain (HMS) of primary articular chondrocytes increases inflammatory gene expression and promotes neurotrophic factor release. HMS cultured chondrocytes displayed up-regulated NGF, TNFα and ADAMTS4 gene expression while decreasing TLR2 expression, as compared to static controls. HMS culture increased p38 MAPK activity compared to static controls. Conditioned medium from HMS dynamic cultures, but not static cultures, induced significant neurite sprouting in PC12 cells. The increased neurite sprouting was accompanied by consistent increases in PC12 cell death. Low-frequency high-magnitude mechanical strain of primary articular chondrocytes in vitro drives factor secretion associated with degenerative joint disease and joint pain. This study provides evidence for a direct link between cellular strain, secretory factors, neo-innervation, and pain in OA pathology.
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) | 0.002 | 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".