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Record W4230931225 · doi:10.1002/ange.201400133

An MRI‐Sensitive, Non‐Photobleachable Porphysome Photothermal Agent

2014· article· en· W4230931225 on OpenAlexafffund
Thomas D. MacDonald, Tracy Liu, Gang Zheng

Bibliographic record

VenueAngewandte Chemie · 2014
Typearticle
Languageen
FieldEngineering
TopicNanoplatforms for cancer theranostics
Canadian institutionsUniversity of TorontoOntario Institute for Cancer Research
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchPrincess Margaret Cancer Foundation
KeywordsPhotothermal therapyNanoparticleGadoliniumPhotothermal effectMaterials scienceNanotechnologyNanocrystalChemistry

Abstract

fetched live from OpenAlex

Abstract Photothermal therapy makes use of photothermal sensitizers and laser light to thermally ablate diseased tissues. Porphysome nanoparticles offer a nontoxic alternative to inorganic nanocrystals for the efficient conversion of light into heat. Mn 3+ ions were incorporated directly into the building blocks of our porphysome nanoparticles, thus imparting MRI sensitivity while simultaneously improving photostability and maintaining high photothermal efficiency. Mn porphysomes are as photothermally effective as free‐base porphysomes and can rival gadolinium diethylenetriaminepentaacetate (Gd‐DTPA) for MRI contrast generation. Their MRI contrast generation, photothermal efficiency, and photostability are unprecedented for an all‐organic nanoparticle composed of a single functional component.

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 categoriesMeta-epidemiology (narrow)
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 score0.050
Threshold uncertainty score1.000

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 science0.0000.000
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 head0.007
GPT teacher head0.204
Teacher spread0.197 · 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

Citations41
Published2014
Admission routes2
Has abstractyes

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