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Record W4412695610 · doi:10.1002/marc.202500419

Self‐Immolative Polyion Complexes

2025· article· en· W4412695610 on OpenAlexafffund
Xueli Mei, Elizabeth R. Gillies

Bibliographic record

VenueMacromolecular Rapid Communications · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Interference and Gene Delivery
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsDepolymerizationChemistryMicelleCationic polymerizationPolyelectrolyteBiophysicsPolymerAqueous solutionCytotoxicityCombinatorial chemistryPolymer chemistryIn vitroOrganic chemistryBiochemistry

Abstract

fetched live from OpenAlex

ABSTRACT Polyion complex (PICs) micelles are formed through the self‐assembly of polyelectrolytes bearing opposite charges. The ability to form PICs under fully aqueous conditions makes them attractive for the encapsulation of biopolymers such as proteins and nucleic acids for potential therapeutic applications. Stimuli‐responsive PIC micelles have the potential to release their cargo under specific biological conditions. We describe here the development of PIC micelles formed from two self‐immolative polymers (SIPs) with complementary charges. The polycationic SIP, having pendent ammonium groups, undergoes depolymerization in response to light. The polyanionic SIP, bearing pendent carboxylates and a stabilizing PEG block, undergoes depolymerization in response to a pH change from 7.4 to 6. SIP PICs composed of a 0.6 anion:cation ratio remain well dispersed at pH 7.4, but degrade at pH 6, primarily due to depolymerization of the anionic block. Irradiation with UV light leads primarily to depolymerization of the cationic block. In vitro cytotoxicity assays with C2C12 cells indicate that the PICs are quite well tolerated by the cells with low cytotoxicity up to about 0.5 mg mL −1 . Overall, these PICs are a new platform that can potentially be used for the encapsulation and stimulus‐mediated release of ionic cargo.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.573
Threshold uncertainty score0.661

Codex and Gemma teacher scores by category

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 science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.286
Teacher spread0.273 · 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 teacher head, 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

Citations1
Published2025
Admission routes2
Has abstractyes

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