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Record W4400602137 · doi:10.1101/2024.07.09.602794

AGEing of Collagen: The Effects of Glycation on Collagen’s Stability, Mechanics and Assembly

2024· preprint· en· W4400602137 on OpenAlexaff
Daniel Sloseris, Nancy R. Forde

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldMaterials Science
TopicCollagen: Extraction and Characterization
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsGlycationAgeingChemistryBiophysicsBiochemistryInternal medicineMedicineBiologyReceptor

Abstract

fetched live from OpenAlex

ABSTRACT Advanced Glycation End Products (AGEs) are the end result of the irreversible, non-enzymatic glycation of proteins by reducing sugars. These chemical modifications accumulate with age and have been associated with various age-related and diabetic complications. AGEs predominantly accumulate on proteins with slow turnover rates, of which collagen is a prime example. Glycation has been associated with tissue stiffening and reduced collagen fibril remodelling. In this study, we investigate the effects of glycation on the stability of type I collagen, its molecular-level mechanics and its ability to perform its physiological role of self-assembly. Collagen AGEing is induced in vitro by incubation with ribose. We confirm and assess glycation using fluorescence measurements and changes in collagen’s electrophoretic mobility. Susceptibility to trypsin digestion and circular dichroism (CD) spectroscopy are used to probe changes in collagen’s triple helical stability, revealing decreased stability due to glycation. Atomic Force Microscopy (AFM) imaging is used to quantify how AGEing affects collagen flexibility, where we find molecular-scale stiffening. Finally we use microscopy to show that glycated collagen molecules are unable to self-assemble into fibrils. These findings shed light on the molecular mechanisms underlying AGE-induced tissue changes, offering insight into how glycation modifies protein structure and stability.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.011
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.012
GPT teacher head0.222
Teacher spread0.211 · 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.

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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

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