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Record W2110198005 · doi:10.3109/15569527.2010.489307

Nanofibrous materials for wound care

2010· review· en· W2110198005 on OpenAlexaff
Wen Zhong, Malcolm Xing, Howard I. Maibach

Bibliographic record

VenueCutaneous and Ocular Toxicology · 2010
Typereview
Languageen
FieldMaterials Science
TopicElectrospun Nanofibers in Biomedical Applications
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsBiocompatibilityPolymerWound careMaterials scienceNatural polymersWound healingWound dressingSurface modificationSynthetic polymerMembraneNanofiberBiomedical engineeringNanotechnologyPolymer scienceComposite materialChemistrySurgeryMedicine

Abstract

fetched live from OpenAlex

Nanofibrous membranes are highly soft materials with high surface-to-volume ratios, and therefore can serve as excellent carriers for therapeutic agents that are antibacterial or accelerate wound healing. This article overviews research and development of nanofibrous dressing materials for wound care, in addition to a discussion of natural and synthetic polymers used in fabricating nanofibrous dressing materials, and a description of in vitro and in vivo evaluation methods for the performance and cytotoxicity of these materials. Natural polymers are usually believed to be less cytotoxic than synthetic polymer in wound care. However, most natural polymers exhibit relatively low mechanical strength than synthetic polymers. As a result, they are usually crosslinked or blended with synthetic polymers so as to somewhat affect their biocompatibility.

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 categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.987
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.017
GPT teacher head0.312
Teacher spread0.295 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations56
Published2010
Admission routes1
Has abstractyes

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