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Record W2366078744

Preparation and control release properties of chitosan electrostatic assembly with polyanion bearing phosphorylcholine groups

2015· article· en· W2366078744 on OpenAlexaff
Min Gong

Bibliographic record

VenueJournal of Functional Biomaterials · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHydrogels: synthesis, properties, applications
Canadian institutionsScience North
Fundersnot available
KeywordsSelf-healing hydrogelsPhosphorylcholinePolyelectrolyteMaterials scienceMethacrylic acidCationic polymerizationChitosanPoly(methacrylic acid)Fourier transform infrared spectroscopyPolymer chemistryPolymerizationDrug deliveryMethacrylateChemical engineeringNanotechnologyChemistryPolymerComposite material
DOInot available

Abstract

fetched live from OpenAlex

Novel polyelectrolyte hydrogels were prepared by polycation chitosan(CS)and polyanionic poly(2-methacryloyloxyethyl phosphorylcholine-co-methacrylic acid)(poly(MPC-co-MA),PMA30).The PMA30(the actual percentages of MPC unit in PMA30 determined by 1 H-NMR was 28%)was synthesized by free radical polymerization of 2-methacryloyloxyethyl phosphorylcholine(MPC)and methacrylic acid(MA).Fourier transform infrared spectra(FT-IR)and scanning electron microscopy(SEM)confirmed that the formation of the polyelectrolyte hydrogels was attributed to the strong electrostatic interaction between cationic groups in CS and anionic groups in PMA30.Potential applications of the hydrogels matrices in controlled drug delivery were also examined.In vitro release showed that neutral red release could be controlled by choosing the composition and pH.This facile method of fabricating CS/PMA30 hydrogels bearing phosphorylcholine groups may have potential applications in the fields of drug delivery,tissue engineering,and cell culture.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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

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 head0.019
GPT teacher head0.239
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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations0
Published2015
Admission routes1
Has abstractyes

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Same venueJournal of Functional BiomaterialsSame topicHydrogels: synthesis, properties, applicationsFrench-language works237,207