Ageing Changes in the Tensile Properties of Tendons: Influence of Collagen Fibril Volume Fraction
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Connective tissues are biological composites comprising of collagen fibrils embedded in (and reinforcing) the hydrated proteoglycan-rich (PG) gel within the extracellular matrices (ECMs). Age-related changes to the mechanical properties of tissues are often associated with changes to the structure of the ECM, namely, fibril diameter. However, quantitative attempts to correlate fibril diameter to mechanical properties have yielded inconclusive evidence. Here, we described a novel approach that was based on the rule of mixtures for fiber composites to evaluate the dependence of age-related changes in tendon tensile strength (sigma) and stiffness (E) on the collagen fibril cross-sectional area fraction (rho), which is related to the fibril volume fraction. Tail tendons from C57BL6 mice from age groups 1.6-35.3 months old were stretched to failure to determine sigma and E. Parallel measurements of rho as a function of age were made using transmission electron microscopy. Mathematical models (rule of mixtures) of fibrils reinforcing a PG gel in tendons were used to investigate the influence of rho on ageing changes in sigma and E. The magnitudes of sigma, E, and rho increased rapidly from 1.6 months to 4.0 months (P-values <0.05) before reaching a constant (age independent) from 4.0 months to 29.0 months (P-values >0.05); this trend continued for E and rho (P-values >0.05) from 29.0 months to 35.3 months, but not for sigma, which decreased gradually (P-values <0.05). Linear regression analysis revealed that age-related changes in sigma and E correlated positively to rho (P-values <0.05). Collagen fibril cross-sectional area fraction rho is a significant predictor of ageing changes in sigma and E in the tail tendons of C57BL6 mice.
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.
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 it