Platelet Polyphosphate Signals Through NFκB to Induce Myofibroblast Differentiation
Bibliographic record
Abstract
Myofibroblasts drive wound healing and fibrotic disease through generation of contractile force to promote wound closure and production of matrix proteins to generate scar tissue. Platelets secrete many pro-wound healing molecules, including cytokines and growth factors. We previously reported that inorganic polyphosphate, secreted by activated platelets, is chemotactic for fibroblasts and induces a myofibroblast phenotype. Using NIH-3T3 cells and primary human fibroblasts, we examined the impact of inhibitors of cell-surface receptors and intracellular signaling molecules on polyphosphate-induced myofibroblast differentiation. We now report that polyphosphate-induced differentiation of fibroblasts to myofibroblasts occurs through a signaling pathway mediated by the receptor for advanced glycation end products (RAGE) and nuclear factor kappa B (NFκB) transcription factor. Inhibition of these signaling components ablated the effects of polyphosphate on fibroblasts. Platelet releasates also induced NFκB signaling and myofibroblast differentiation. Blocking the polyphosphate content of platelet releasates with a biocompatible polyP inhibitor rendered the releasates unable to induce myofibroblast differentiation. These results identify a cell-surface receptor and intracellular transcription factor utilized by platelet polyphosphate to promote wound healing through myofibroblast differentiation and may provide targets for promoting wound healing or altering the disease progression of fibrosis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".