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Record W4384826348 · doi:10.3389/fbioe.2023.1255293

Editorial: Responsive biomaterials for controlled release and cancer theranostics

2023· editorial· en· W4384826348 on OpenAlexaff
Nansha Gao, Xiaowei Zeng, Hongzhong Chen, Guoqing Pan, Guojun Chen, Zhongjian Xie

Bibliographic record

VenueFrontiers in Bioengineering and Biotechnology · 2023
Typeeditorial
Languageen
FieldEngineering
TopicNanoplatforms for cancer theranostics
Canadian institutionsMcGill University
FundersNatural Science Foundation of Guangdong Province
KeywordsNanotechnologyChemistryMaterials science

Abstract

fetched live from OpenAlex

Editorial on the Research Topic Responsive biomaterials for controlled release and cancer theranosticsNowadays, cancer has become a major public health problem worldwide.Responsive biomaterials undergo changes specifically in response to specific environmental induction, providing potential clinical applications for controlled release, cancer therapeutics diagnostics and personalized medicine.The microenvironment of tumor site is significantly different from that of normal site, such as higher temperature, lower pH value or secretion of certain specific enzymes.Recently, a great quantity of stimuliresponsive biomaterials have been engineered for biomedical applications using different environment stimulus, which could be chemicals such as pH, glucose, enzymes, or physicals such as ultrasound, light, temperature, radiation, or their combinations.In this Research Topic, we consisted of 10 articles, including six articles, two review articles and two mini reviews, contributed by 67 researchers worldwide.The original research articles involved multiple delivery systems: nanohybrid hydrogels, nanoemulsions, microcapsules and other nanoparticles or nanosheets.These nanosystems were rationally designed and synthesized of novel responsive nanomaterials for controlled release and cancer theranostics or other disease treatments, providing enormous references for their clinical applications.There are two review articles on this Research Topic.In a review article, Ding et al. provided a systematic summary of photothermal nano hydrogels and discussed their biomedical applications.They noted that the preparation of photothermal nanohydrogels should focus on the photothermal nanomaterials, and summarized the most commonly used photothermal agents including nanomaterials made of metal, carbon based, metal sulfide/ oxide, polymer, black phosphorus, MXenes, organic dye and other composite nanomaterials.The authors highlighted the applications of photothermal nanocomposite hydrogel in drug release, photothermal anti-bacterial and wound repair, photothermal inhibition of cancer, bone tissue regeneration, and other aspects such as hydrogel eye piece or electric response hydrogel.In another review article, Qian et al. summarized the advantages and disadvantages of several widely used nanomaterials including mesoporous silica nanoparticles (MSNs),

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)0.004
metaresearch head score (Gemma)0.010
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.029
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0040.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.001
Science and technology studies0.0020.001
Scholarly communication0.0050.003
Open science0.0030.001
Research integrity0.0110.010
Insufficient payload (model declined to judge)0.0290.020

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 head0.005
GPT teacher head0.225
Teacher spread0.220 · 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
GenreEditorial

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
Published2023
Admission routes1
Has abstractyes

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