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Record W4234430285 · doi:10.1002/ange.201908664

A Nanoemulsion with A Porphyrin Shell for Cancer Theranostics

2019· article· en· W4234430285 on OpenAlexafffund
Wenxiu Hou, Jenny W. H. Lou, Jiachuan Bu, En-Ling Chang, Lili Ding, Michael S. Valic, Han Ho Jeon, Danielle M. Charron, Catherine Coolens, Daxiang Cui, Juan Chen, Gang Zheng

Bibliographic record

VenueAngewandte Chemie · 2019
Typearticle
Languageen
FieldEngineering
TopicNanoplatforms for cancer theranostics
Canadian institutionsUniversity of TorontoPrincess Margaret Cancer CentreUniversity Health Network
FundersCanadian Institutes of Health Research
KeywordsPorphyrinPhotodynamic therapyPhotochemistryAbsorbanceFluorescenceChemistryDissociation (chemistry)Photothermal therapyDrug deliveryMaterials scienceNanotechnologyOrganic chemistryChromatographyOptics

Abstract

fetched live from OpenAlex

Abstract A nanoemulsion with a porphyrin shell (NewPS) was created by the self‐assembly of porphyrin salt around an oil core. The NewPS system has excellent colloidal stability, is amenable to different porphyrin salts and oils, and is capable of co‐loading with chemotherapeutics. The porphyrin salt shell enables porphyrin‐dependent optical tunability. The NewPS consisting of pyropheophorbide a mono‐salt has a porphyrin shell of ordered J‐aggregates, which produced a narrow, red‐shifted Q‐band with increased absorbance. Upon nanostructure dissociation, the fluorescence and photodynamic reactivity of the porphyrin monomers are restored. The spectrally distinct photoacoustic imaging (at 715 nm by intact NewPS) and fluorescence increase (at 671 nm by disrupted NewPS) allow the monitoring of NewPS accumulation and disruption in mice bearing KB tumors to guide effective photodynamic therapy. Substituting the oil core with Lipiodol affords additional CT contrast, whereas loading paclitaxel into NewPS facilitates drug delivery.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.694

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 head0.009
GPT teacher head0.212
Teacher spread0.203 · 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

Citations29
Published2019
Admission routes2
Has abstractyes

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