Nanomechanical and molecular characterization of aging in dentinal collagen
Bibliographic record
Abstract
Abstract Methylglyoxal (MGO) is an important molecule derived from glucose metabolism with the capacity of attaching to collagen and generating advanced glycation end-products (AGEs), which accumulate in tissues over time and are associated to aging and diseases. However, the accumulation of MGO-derived AGEs in dentin and their effect on the nanomechanical properties of dentinal collagen remain unknown. Thus, the aim of the present study was to quantify MGO-based AGEs in the organic matrix of human dentin as a function of age and associate these changes with alterations in the nanomechanical and ultrastructural properties of dentinal collagen. For this, twelve healthy teeth from <26 year-old and >50 year-old patients were collected and prepared to obtain crown and root dentin discs. Following demineralization, MGO-derived AGEs were quantified with a competitive ELISA assay. In addition, atomic force microscopy (AFM) nano-indentation was utilized to measure changes in elastic modulus in both peritubular (PT) and intertubular (IT) collagen fibrils. Finally, principal component analysis (PCA) was carried out to determine aging profiles for both crown and root dentin. Results showed increased presence of MGO AGEs in the organic matrix of dentin in the >50 year-old compared to <26 year-old samples in both crown and root. Furthermore, an overall increase in PT and IT collagen elasticity was observed in the >50 year-old group associated to ultrastructural changes in the organic matrix determined by AFM analysis. Furthermore, PCA loading plots suggested different ‘aging profiles’ in both crown and root dentin, which could potentially have important therapeutic implications in restorative and adhesive dentistry approaches. Overall, these results demonstrate that the organic matrix of human dentin undergoes aging-related changes due to MGO-derived AGEs with important changes in nanomechanical behavior of collagen that may impact diagnostic and restorative procedures in the elderly.
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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 | 0.001 | 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".