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Record W4224124878 · doi:10.1016/j.jmbbm.2022.105220

Empirical evidence that bone collagen molecules denature as a result of bone fracture

2022· article· en· W4224124878 on OpenAlexafffund
Corin Seelemann, Thomas L. Willett

Bibliographic record

VenueJournal of the mechanical behavior of biomedical materials/Journal of mechanical behavior of biomedical materials · 2022
Typearticle
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsUniversity of Waterloo
FundersOntario Ministry of Research and InnovationCanadian Institutes of Health ResearchUniversity of WaterlooCanada Foundation for InnovationOntario Research FoundationUniversity of Guelph
KeywordsFracture (geology)Materials scienceChemistryComposite material

Abstract

fetched live from OpenAlex

Cortical bone tissue, primarily composed of collagen, hydroxyapatite, and water, is a strong and tough natural, structural biomaterial. The integrity of the collagenous phase (native triple helix vs. damaged/denatured coil) has previously been correlated via various means, including hydrothermal isometric tension testing and FTIR and Raman spectroscopy, with the capability of cortical bone to undergo stable fracture. Collagen is a relatively stable protein, requiring around 70 J/g to thermally denature its native triple helix structure, through the melting of hydrogen bonds. It is widely thought that bone collagen molecules denature (unravel) during fracture, acting as a molecular-scale mechanical toughening mechanism, but this has not been empirically demonstrated to date. A new technology, fluorescently-labeled collagen hybridizing peptides (F-CHP), enables imaging that specifically detects denatured collagen. This provides an opportunity to empirically test whether bone collagen molecules do denature during bone fracture. Here, F-CHP was used to stain fracture surfaces produced by transverse Mode-I fracture of chevron-notched bovine and human cortical bone beams. The fracture surfaces demonstrated increased staining, above the level of rigorous paired controls, and the staining directly correlated with the work-to-fracture (WFx) of bovine bone beams. This increased denaturation signal was also constrained to a rough textured region visible on the fracture surface, which is known to correspond with stable tearing. Similar staining was also detected on the fracture surfaces of human cortical bone. Increased staining was not detected on the fracture surfaces of specimens that were dehydrated prior to fracture, suggesting a role for water in the denaturation process. This study provides the first empirical evidence of bone collagen denaturation resulting from cortical bone fracture and extends our understanding of this mechanism towards the mechanical performance of cortical bone.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.056
GPT teacher head0.364
Teacher spread0.308 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueJournal of the mechanical behavior of biomedical materials/Journal of mechanical behavior of biomedical materials→Same topicBone health and osteoporosis research→French-language works237,207→