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Record W4415943798 · doi:10.1016/j.jori.2025.100005

Advances in silkworm silk proteins: From textile to biomedical innovations

2025· article· en· W4415943798 on OpenAlexaff
Dingpei Long, Zhenlin Yang, Xiaojie Zhang, Subhas C. Kundu, Yin Du, Zhan Zhang, Chunhua Yang, Fangyin Dai

Bibliographic record

VenueJournal of Resource Insects · 2025
Typearticle
Languageen
FieldMaterials Science
TopicSilk-based biomaterials and applications
Canadian institutionsMinistry of Agriculture
FundersChongqing Graduate Student Research Innovation ProjectFundamental Research Funds for the Central UniversitiesNatural Science Foundation of ChongqingEuropean Regional Development FundFundação para a Ciência e a TecnologiaNational University's Basic Research Foundation of ChinaVenture and Innovation Support Program for Chongqing Overseas Returnees
KeywordsSericinFibroinBombyx moriSILK

Abstract

fetched live from OpenAlex

The domesticated silkworm ( Bombyx mori ) silk, an ancient and renewable natural protein fiber, has received renewed attention in biomedical materials research in recent years. B. mori silk consists mainly of fibroin (a type of fibrous protein) and sericin (a type of glue-like protein). Fibroin exhibits excellent biocompatibility, robust mechanical properties, and controllable degradability. In contrast, sericin is rich in hydrophilic amino acids and possesses biological activity. This review covers the extraction and modification methods for these two proteins and highlights their structural advantages. It systematically summarizes recent progress in silk-based materials for tissue engineering, controllable-release drug delivery, trauma hemostasis, antimicrobial applications, and smart medicine. Finally, the advantages and challenges of silk-based biomedical materials are discussed, and their prospects are explored.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.278
Teacher spread0.268 · 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

Citations4
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Resource InsectsSame topicSilk-based biomaterials and applicationsFrench-language works237,207