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Record W2416341659

[Scaffolds based on collagen and chitosan for post-burn tissue engineering].

2009· article· en· W2416341659 on OpenAlexaboutno aff
Oana Sorina Năstăsescu, Ionel Marcel Popa, Liliana Vereștiuc, Maria Butnaru, Dana Baran

Bibliographic record

VenuePubMed · 2009
Typearticle
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsChitosanCollagenaseChemistryPolymerSwellingBiomaterialIsoelectric pointIn vitroBiochemistryMaterials scienceEnzymeOrganic chemistryComposite material
DOInot available

Abstract

fetched live from OpenAlex

UNLABELLED: Porous scaffolds based on collagen and chitosan have been obtained from mixed bio-polymeric solutions and mixture freeze-drying method in the purpose of using them as materials for post-burns tissue regeneration. MATERIAL AND METHOD: Soluble collagen from bovine leather was obtained by acid-base extraction (isoelectric pH = 4.82). Two types of chitosan (CS I, M(w) = 755.900, de-acetylating degree of 79.2% and CS II, M(w) = 309.900, de-acetylating degree of 79.7%), were provided by Vascon Co., Canada. Various compositions were prepared and then structurally and morphologically characterized. In vitro degradation studies were performed in buffered collagenase or chitosan solutions, respectively, and the kinetic data were analysed. Materials effect on the tissue regeneration was tested on heat-induced burns in Wistar rats by covering the damaged tissue with collagen-chitosan scaffolds for a period of 28 days. Materials were changed every 7 days. At the end of the follow-up period skin tissue samples were harvested for histological investigation. RESULTS: By freeze-drying of collagen-chitosan solutions porous scaffolds were obtained with a lamellar morphology and porosity closer to chitosan than to collagen. In vitro degradation tests in simulated body fluid with collagenase revealed a decrease of the degradation rate of the collagen by mixing with chitosan. By using chitosan with lower molecular weight the degradation rate of the materials was decreased too, and the influence of the proportion of chitosan in composition diminished; stronger interactions between polymers hinder the enzyme diffusion to the following amino-acids groups: glycine - leucine (Gly-Leu), glycine - isoleucine (Gly-Ile), alanine-proline-glycine/leucine (-Ala-Pro-Gly-/-Leu-). In vivo tests and histological examination revealed a differentiated repair process of the post-combustion wounds in accordance with the scaffold-type influence. CONCLUSION: Scaffolds based on collagen and chitosan are biocompatible materials with promising results for tissue regeneration of the wounds.

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 score0.003
Threshold uncertainty score0.010

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 integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.209
Teacher spread0.199 · 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

Citations2
Published2009
Admission routes1
Has abstractyes

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