DDR1 associates with TRPV4 in cell‐matrix adhesions to enable calcium‐regulated myosin activity and collagen compaction
Bibliographic record
Abstract
Abstract Tissue fibrosis manifests as excessive deposition of compacted, highly aligned collagen fibrils, which interfere with organ structure and function. Cells in collagen‐rich lesions often exhibit marked overexpression of discoidin domain receptor 1 (DDR1), which is linked to increased collagen compaction through the association of DDR1 with the Ca2+‐dependent nonmuscle myosin IIA (NMIIA). We examined the functional relationship between DDR1 and the transient receptor potential vanilloid type 4 (TRPV4) channel, a Ca2+‐permeable ion channel that is implicated in collagen compaction. Fibroblasts expressing high levels of DDR1 were used to model cells in lesions with collagen compaction. In these cells, the expression of the β1 integrin was deleted to simplify studies of DDR1 function. Compared with DDR1 wild‐type cells, high DDR1 expression was associated with increased Ca2+ influx through TRPV4, enrichment of TRPV4 in collagen adhesions, and enhanced contractile activity mediated by NMIIA. At cell adhesion sites to collagen, DDR1 associated with TRPV4, which enhanced DDR1‐mediated collagen alignment and compaction. We conclude that DDR1 regulates Ca2+ influx through the TRPV4 channel to promote critical, DDR1‐mediated processes that are important in lesions with collagen compaction and alignment.
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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 | 0.001 |
| 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".