Modulation of the Biophysical and Biochemical Properties of Collagen by Glycation for Tissue Engineering Applications
Bibliographic record
Abstract
Abstract The structural and functional properties of collagen are modulated by the presence of intramolecular and intermolecular crosslinks. Advanced Glycation End-products (AGEs) can produce intermolecular crosslinks by bonding the free amino groups of neighboring proteins. In this research, the following hypothesis is explored: The accumulation of AGEs in collagen decreases its proteolytic degradation rates while increasing its stiffness. Fluorescence Lifetime Imaging (FLIM) and Fourier-transform infrared spectroscopy (FTIR) detect biochemical changes in collagen scaffolds during the glycation process. The accumulation of AGEs increases exponentially in the collagen scaffolds as a function of Methylglyoxal (MGO) concentration by performing autofluorescence measurement and competitive ELISA. Glycated scaffolds absorb water at a much higher rate confirming the direct affinity between AGEs and interstitial water within collagen fibrils. In addition, the topology of collagen fibrils as observed by Atomic Force Microscopy (AFM) is a lot more defined following glycation. The elastic modulus of collagen fibrils decreases as a function of glycation, whereas the elastic modulus of collagen scaffolds increases. Finally, the enzymatic degradation of collagen by bacterial collagenase shows a sigmoidal pattern with a much slower degradation rate in the glycated scaffolds. This study identifies unique variations in the properties of collagen following accumulation of AGEs.
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".