Defects in Tendon, Ligament, and Enthesis in Response to Genetic Alterations in Key Proteoglycans and Glycoproteins: A Review
Bibliographic record
Abstract
This review summarizes the genetic alterations and knockdown approaches published in the literature to assess the role of key proteoglycans and glycoproteins in the structural development, function, and repair of tendon, ligament, and enthesis. The information was collected from (i) genetically altered mice, (ii) in vitro knockdown studies, (iii) genetic variants predisposition to injury, and (iv) human genetic diseases. The genes reviewed are for small leucine-rich proteoglycans (lumican, fibromodulin, biglycan, decorin, and asporin); dermatan sulfate epimerase (Dse) that alters structure of glycosaminoglycan and hence the function of small leucine-rich proteoglycans by converting glucuronic to iduronic acid; matricellular proteins (thrombospondin 2, secreted phosphoprotein 1 (Spp1), secreted protein acidic and rich in cysteine (Sparc), periostin, and tenascin X) including human tenascin C variants; and others, such as tenomodulin, leukocyte cell derived chemotaxin 1 (chondromodulin-I, ChM-I), CD44 antigen (Cd44), lubricin (Prg4), and aggrecan degrading gene, a disintegrin-like and metallopeptidase (reprolysin type) with thrombospondin type 1 motif, 5 (Adamts5). Understanding these genes represents drug targets for disrupting pathological mechanisms that lead to tendinopathy, ligamentopathy, enthesopathy, enthesitis and tendon/ligament injury, that is, osteoarthritis and ankylosing spondylitis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".