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Record W4386466687 · doi:10.1002/adma.202305964

Intrafibrillar Crosslinking Enables Decoupling of Mechanical Properties and Structure of a Composite Fibrous Hydrogel

2023· article· en· W4386466687 on OpenAlexafffund
Zhengkun Chen, Maya Ezzo, Benjamen Zondag, Faeze Rakhshani, Yingshan Ma, Boris Hinz, Eugenia Kumacheva

Bibliographic record

VenueAdvanced Materials · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular Mechanics and Interactions
Canadian institutionsSt. Michael's HospitalUniversity of Toronto
FundersCanadian Institutes of Health ResearchCanada Foundation for Innovation
KeywordsMaterials scienceSelf-healing hydrogelsGelatinFibroblastExtracellular matrixComposite numberTissue engineeringStiffnessNanotechnologyComposite materialBiomedical engineeringBiophysicsPolymer chemistryChemistry

Abstract

fetched live from OpenAlex

The fibrous network of an extracellular matrix (ECM) possesses mechanical properties that convey critical biological functions in cell mechanotransduction. Engineered fibrous hydrogels show promise in emulating key aspects of ECM structure and functions. However, varying hydrogel mechanics without changing its architecture remains a challenge. A composite fibrous hydrogel is developed to vary gel stiffness without affecting its structure by controlling intrafibrillar crosslinking. The hydrogel is formed from aldehyde-modified cellulose nanocrystals and gelatin methacryloyl that provide the capability of intrafibrillar photocrosslinking. By varying the degree of gelatin functionalization with methacryloyl groups and/or photoirradiation time, the hydrogel's elastic modulus is changed by more than an order of magnitude, while preserving the same fiber diameter and pore size. The hydrogel is used to seed primary mouse lung fibroblasts and test the role of ECM stiffness on fibroblast contraction and activation. Increasing hydrogel stiffness by stronger intrafibrillar crosslinking results in enhanced fibroblast activation and increased fibroblast contraction force, yet at a reduced contraction speed. The developed approach enables the fabrication of biomimetic hydrogels with decoupled structural and mechanical properties, facilitating studies of ECM mechanics on tissue development and disease progression.

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 score0.001
Threshold uncertainty score0.342

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 head0.012
GPT teacher head0.241
Teacher spread0.229 · 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

Citations43
Published2023
Admission routes2
Has abstractyes

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