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Record W4407369788 · doi:10.1039/d4sc07198k

Engineering live cell surfaces with polyphenol-functionalized nanoarchitectures

2025· review· en· W4407369788 on OpenAlexaff
Yunxiang He, Qinling Liu, Yuanmeng He, Siqi Deng, Junling Guo

Bibliographic record

VenueChemical Science · 2025
Typereview
Languageen
FieldMaterials Science
TopicPolymer Surface Interaction Studies
Canadian institutionsUniversity of British Columbia
FundersNational Key Research and Development Program of ChinaState Key Laboratory of Polymer Materials EngineeringSichuan UniversityNational Natural Science Foundation of ChinaYoung Scientists FundKey Laboratory of Leather Chemistry and Engineering of Ministry of Education
KeywordsPolyphenolNanotechnologyChemistryMaterials scienceOrganic chemistryAntioxidant

Abstract

fetched live from OpenAlex

metal coordination or macromolecular self-assembly that can rapidly attach to cell surfaces in a cell-agnostic manner. Additionally, the cytoPNAs attached on the cell surface can also provide active sites for the conjunction of bioactive payloads, further expanding the structural repertoire and properties of engineered cells. This Perspective introduces the wide potential of cytoPNA-mediated cell engineering in three key applications: (1) creating inorganic-organic biohybrids as cell factories for efficient production of high-value chemicals, (2) constructing engineered cells for cell-based therapies with enhanced targeting specificity and nano-bio interactions, and (3) encapsulating microbes as biotherapeutics for the treatment of gastrointestinal tract-related diseases. Collectively, the rapid, versatile, and modular nature of cytoPNAs presents a promising platform for next-generation cell engineering and beyond.

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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.015
GPT teacher head0.284
Teacher spread0.269 · 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

Citations25
Published2025
Admission routes1
Has abstractyes

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