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Record W4376456304 · doi:10.1039/d3tb00639e

Recent advances in novel materials and techniques for developing transparent wound dressings

2023· review· en· W4376456304 on OpenAlexafffund
Muzammil Kuddushi, Aatif Ali Shah, Cagri Ayranci, Xuehua Zhang

Bibliographic record

VenueJournal of Materials Chemistry B · 2023
Typereview
Languageen
FieldMedicine
TopicWound Healing and Treatments
Canadian institutionsUniversity of Alberta
FundersCanada Research Chairs
KeywordsMaterials scienceWound healingNanotechnologyKey (lock)FabricationBiomedical engineeringComputer scienceMedicineSurgeryPathologyComputer security

Abstract

fetched live from OpenAlex

Optically transparent wound dressings offer a range of potential applications in biomedical fields, as they allow for the monitoring of wound-healing progress without having to replace the dressing. These dressings must be impermeable to water and bacteria, yet permeable to moisture vapor and atmospheric gases in order to maintain a moist environment at the wound site. This review article provides a comprehensive overview of the types of wound dressings, novel wound-dressing materials, advanced fabrication techniques for transparent wound-dressing materials, and the key features and applications of transparent dressings for the healing process, as well as how they can improve healing outcomes. This review mainly focuses on presenting specifications of transparent polymeric wound-dressing materials, such as transparent electrospun nanofibers, transparent crosslinked hydrogels, and transparent composite films/membranes. Due to the advanced properties of electrospun nanofibers, such as large surface area, efficient incorporation of antibacterial molecules, a structure similar to the extracellular matrix, and high mechanical stability, they are often used in wound-dressing applications. We also highlight hydrogels or films for wound-healing applications, and their promotion of the healing process, provision of a moist environment and pain relief through cooling and high-water content, excellent biocompatibility, and bio-biodegradability. But as hydrogels or films fabricated with a single component have low mechanical strength and stability, recent trends have offered composite or hybrid materials to achieve typical wound-dressing requirements. Advanced wound dressings with transparency, high mechanical stability, and antimicrobial functionality are becoming a popular research avenue in the wound-dressing research field. Finally, the developmental prospects of new transparent wound-dressing materials for future research are presented.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.139
GPT teacher head0.424
Teacher spread0.285 · 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 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

Citations75
Published2023
Admission routes2
Has abstractyes

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