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Record W2888626503 · doi:10.1039/c8tb01602j

Binding of an amphiphilic phthalocyanine to pre-formed liposomes confers light-triggered cargo release

2018· article· en· W2888626503 on OpenAlexaff
Miloslav Macháček, Kevin A. Carter, Filip Kostelanský, Dyego Miranda, Amal Seffouh, Joaquı́n Ortega, Tomáš Šimůnek, Petr Zimčík, Jonathan F. Lovell

Bibliographic record

VenueJournal of Materials Chemistry B · 2018
Typearticle
Languageen
FieldMaterials Science
TopicPorphyrin and Phthalocyanine Chemistry
Canadian institutionsMcGill University
FundersNational Institute of Biomedical Imaging and BioengineeringEuropean Regional Development FundEuropean Food Safety AuthorityNational Institutes of HealthNational Science Foundation
KeywordsAmphiphileLiposomePhthalocyanineMaterials scienceBiophysicsNanotechnologyCombinatorial chemistryChemistryPolymerComposite materialBiologyCopolymer

Abstract

fetched live from OpenAlex

Liposomes are able to load a range of cargos and have been used for drug delivery applications, including for stimuli-triggered drug release. Here, we describe an approach for imparting near infrared (NIR) light-triggered release to pre-formed liposomes, using a newly-synthesized cationic, amphiphilic phthalocyanine. When simply mixed in aqueous solution with cargo-loaded liposomes, the cationic amphiphilic phthalocyanine, but not a cationic hydrophilic azaphthalocyanine, spontaneously incorporates into the liposome bilayer. This enables subsequent release of loaded cargo (doxorubcin or basic orange) upon irradiation with NIR light. The rate of release could be altered by varying the amount of photosensitizer added to the liposomes. In the absence of NIR light exposure, stable cargo loading of the liposomes was maintained. Introduction.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.004
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.265
Teacher spread0.252 · 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.

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

Citations37
Published2018
Admission routes1
Has abstractyes

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