A Comparative Study of the Effects of Different Crosslinking Methods on the Physicochemical Properties of Collagen Multifilament Bundles
Bibliographic record
Abstract
Crosslinking is usually required to improve the mechanical properties and stability of collagen-based scaffolds. Introducing exogenous crosslinks into collagen may however affect the collagen structure. Since the architecture of collagen is tied to its functionality, it is important to study the effect of crosslinking and to select a crosslinking method that preserves both the collagen structure and mechanical properties. The objective of this study is to compare the effect of various crosslinking methods on the structure and mechanical properties of bioartificial tendon-like materials (collagen multifilament bundles) fabricated by contact drawing. We examine both physical (ultraviolet light, UVC) and chemical (genipin, carbodiimide (EDC), and glutaraldehyde) crosslinking methods. The presence of collagen and the formation of well-ordered collagen structures are confirmed by attenuated total reflectance Fourier-transform infrared spectromicroscopy and wide-angle X-ray scattering for all crosslinking methods. The morphology of the collagen multifilament bundles is similar across crosslinking methods. Swelling of the multifilament bundles is dramatically reduced following crosslinking and varies by crosslinking method, with genipin- and carbodiimide-crosslinked specimens swelling the least. Ultimate tensile strength (UTS) and Young's modulus significantly improve for all crosslinked specimens compared to non-crosslinked specimens. Glutaraldehyde crosslinked collagen multifilament bundles display the highest UTS values ranging from 33.82±0.0 MPa to 45.59±0.76 MPa.
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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 | 0.000 |
| 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) | 0.000 | 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".