Effects of Cysteine Proteases on the Structural and Mechanical Properties of Collagen Fibers
Bibliographic record
Abstract
Excessive cathepsin K (catK)-mediated turnover of fibrillar type I and II collagens in bone and cartilage leads to osteoporosis and osteoarthritis. However, little is known about how catK degrades compact collagen macromolecules. The present study is aimed to explore the structural and mechanical consequences of collagen fiber degradation by catK. Mouse tail type I collagen fibers were incubated with either catK or non-collagenase cathepsins. Methods used include scanning electron microscopy, protein electrophoresis, atomic force microscopy, and tensile strength testing. Our study revealed evidence of proteoglycan network degradation, followed by the progressive disassembly of macroscopic collagen fibers into primary structural elements by catK. Proteolytically released GAGs are involved in the generation of collagenolytically active catK-GAG complexes as shown by AFM. In addition to their structural disintegration, a decrease in the tensile properties of fibers was observed due to the action of catK. The Young's moduli of untreated collagen fibers versus catK-treated fibers in dehydrated conditions were 3.2 ± 0.68 GPa and 1.9 ± 0.65 GPa, respectively. In contrast, cathepsin L, V, B, and S revealed no collagenase activity, except the disruption of proteoglycan-GAG interfibrillar bridges, which slightly decreased the tensile strength of fibers. Background: Collagen macromolecules are biologically relevant substrates in tissue remodeling and bone-related diseases. Results: We investigated the action of cysteine proteases on the structural integrity and mechanical functionality of collagen fibers. Conclusion: Using ultrastructural and biochemical techniques, we present a model of collagen fiber degradation via cathepsin K. Significance: Our data provide new insights in matrix degradation and may allow new strategies to inhibit it.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".