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Development of a Collagen/Clay Nanocomposite Biomaterial

2012· article· en· W2033889405 on OpenAlexaff
Alejandra Reyna-Valencia, Pascale Chevallier, Diego Mantovani

Bibliographic record

VenueMaterials science forum · 2012
Typearticle
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsBiopolymerSelf-healing hydrogelsMaterials scienceNanocompositeNanoscopic scaleBiomaterialPolymerNanotechnologyChemical engineeringMoleculeComposite materialPolymer chemistryChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Collagen hydrogels are widely used as three-dimensional scaffolds for cells and tissue in culture environments. These materials, which consist of crosslinked biopolymer (protein-based) networks in aqueous media, are particularly suitable for recreating part of the extra-cellular matrix, but their poor mechanical properties represent a major limitation. One strategy to enhance the strength of this kind of hydrogels might be to incorporate clay nanoscopic particles. In fact, it has been observed that the charged surface of clay nanosheets can interact with certain functional groups belonging to polymer molecules, yielding stronger networks. Moreover, clay particles are recognized to be biocompatible. In the present work, the gelation process and the resulting morphological and mechanical properties of collagen/laponite clay nanocomposite hydrogels were invastigated. Upon gelation, the biopolymer molecules assemble into nanoscale fibrils, which bundle into fibers and entangle into a three-dimensional network. The network characteristics depend on tunable parameters such as pH and clay concentration.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.011
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 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

Citations7
Published2012
Admission routes1
Has abstractyes

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