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Record W4214824138 · doi:10.1101/2022.03.03.482886

Modulation of the Biophysical and Biochemical Properties of Collagen by Glycation for Tissue Engineering Applications

2022· preprint· en· W4214824138 on OpenAlexafffund
Mina Vaez, Meisam Asgari, L Hirvonen, Görkem Bakir, Sebastián Aguayo, C. Schuh, Kathleen Gough, Laurent Bozec

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2022
Typepreprint
Languageen
FieldMaterials Science
TopicCollagen: Extraction and Characterization
Canadian institutionsUniversity of ManitobaMcGill UniversityUniversity of Toronto
FundersFaculty of Dentistry, University of TorontoNatural Sciences and Engineering Research Council of CanadaUniversity of Toronto
KeywordsGlycationChemistryBiophysicsCollagenaseType I collagenPentosidineAutofluorescenceFourier transform infrared spectroscopyFibrillogenesisElastic modulusFibrilBiochemistryChemical engineeringFluorescenceMaterials scienceEnzymeComposite material

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.012
Threshold uncertainty score0.632

Codex and Gemma teacher scores by category

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

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 head0.010
GPT teacher head0.205
Teacher spread0.195 · 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 teacher head, 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

Citations3
Published2022
Admission routes2
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)Same topicCollagen: Extraction and CharacterizationFrench-language works237,207