Complement factor D regulates collagen type I expression and fibroblast migration to enhance human tendon repair and healing outcomes
Bibliographic record
Abstract
Introduction: Dense connective tissues (DCTs) such as tendon, ligament, and cartilage are important stabilizers and force transmitters in the musculoskeletal system. The healing processes after DCT injuries are highly variable, often leading to degenerative changes and poor clinical outcome. Biomarkers in relation to repair quality for human DCTs, especially tendon are lacking. This study expands our previous findings and aimed to characterize the mechanisms by which a potential biomarker of good outcomes, complement factor D (CFD), regulates tendon healing. Methods: Quantitative mass spectrometry (QMS) profiling of tissue biopsies from the inflammatory phase of healing (n = 40 patients) and microdialysates from the proliferative phase of healing (n = 28 patients) were used to identify specific biomarkers for tendon healing. Further bioinformatic and experimental investigations based on primary fibroblasts and fibroblast cell line were used to confirm the identified biomarkers. Results: The QMS profiling of tissue biopsies from the inflammatory phase of healing identified 769 unique proteins, and microdialysates from the proliferative phase of healing identified 1423 unique proteins in Achilles tendon rupture patients. QMS-profiling showed that CFD expression was higher during the inflammatory- and lower during the proliferative healing phase in the good outcome patients. Further bioinformatic and experimental explorations based on both inflammatory and proliferative fibroblast models demonstrated that CFD potentially improved repair by regulating cell migration and modulating collagen type I (Col1a1) expression. Moreover, it was shown that the enhanced Col1a1 expression, through increased fibroblast migration, was correlated with the validated clinical outcome. Discussion: The results of the current studies characterized underlying inflammatory- and proliferative healing mechanisms by which CFD potentially improved tendon repair. These findings may lead to improved individualized treatment options, as well the development of effective therapies to promote good long-term clinical outcomes after tendon and other DCT injuries. Trial registration: http://clinicaltrials.gov, identifiers NCT02318472, NCT01317160.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".