Hypoxia-driven secretion of extracellular matrix proteins in the exosomes reflects the asymptomatic pathology of rotator cuff tendinopathies
Bibliographic record
Abstract
The major hallmark of rotator cuff tendinopathies (RCT) is the disorganization of the tendon extracellular matrix (ECM), which is due to a decrease in the ratio of collagen I to collagen III. In addition, the pathology of the tendon matrisome remains asymptomatic, and hypoxia has been identified to be the priming signal to initiate the molecular pathology of RCT. Also, the secretome content of hypoxia-challenged tendon cells (tenocytes) reflects the pathological status of RCT. With this background, the present study was designed to establish the expression status and molecular crosstalk of the ECM component proteins contained in the exosomes of the hypoxia-challenged swine tenocytes. The mass spectrometry analysis revealed the upregulation of COL1A2, P4HA1, PRDX2, P3H1, COL6A1, PPIB, LCN1, and COL3A1 and the downregulation of COLA12, PDIA4, COLG, FN1, CTSK, and TNC in the exosomes of hypoxic tenocytes. These proteins interact with diverse proteins and operate multiple pathways associated with ECM homeostasis and repair as determined by NetworkAnalyst. The functional analysis of these proteins reflects the pathology of tendon ECM, which is correlated with the asymptomatic phase of RCT. Understanding the signaling mediated by these proteins would reveal the underlying molecular pathology and offers translational significance in the diagnosis and management of RCT.
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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".