Nanomechanical mapping of single collagen fibrils under tension
Bibliographic record
Abstract
At the most fundamental level, collagen fibrils are rope-like structures assembled from triple-helical collagen molecules. One key structural characteristic of the fibril is the 67 nm D-band pattern arising from the quarter-stagger packing of the molecules. Our current understanding of the structural changes induced by tensile loading of collagen fibrils comes mostly from atomistic molecular dynamics simulations and tissue level experiments. Tensile testing of individual fibrils is an upcoming field of investigation, and thus far structural analysis has always taken place after the fibrils have been ruptured or strained and subsequently dried. There is therefore a gap in understanding how the structure of collagen fibrils transforms under tension, and how this reorganization affects the functionality of collagen fibrils within tissues. In this study, atomic force microscopy based nanomechanical mapping is introduced to image hydrated collagen fibrils absorbed to an elastic substrate. Upon stretching the substrate between 5 and 30%, we observe a radial stiffening consistent with the fibrils being under tension. This is associated with an increase in D-band length. In addition the indentation modulus contrast associated with the D-band pattern increases linearly with D-band strain. These results provide direct confirmation of, and new information on the axially inhomogeneous structural response of collagen fibrils to applied tension as previously proposed on the basis of X-ray scattering experiments on stretched tissues. Furthermore our approach opens the road for studying the structural impacts of tension on cell-matrix interactions at the molecular level.
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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 | 0.000 | 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".