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Record W2962717330 · doi:10.1002/anie.201907754

Stable J‐Aggregation of an aza‐BODIPY‐Lipid in a Liposome for Optical Cancer Imaging

2019· article· en· W2962717330 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAngewandte Chemie International Edition · 2019
Typearticle
Languageen
FieldEngineering
TopicNanoplatforms for cancer theranostics
Canadian institutionsUniversity of TorontoPrincess Margaret Cancer CentreUniversity Health Network
FundersNatural Sciences and Engineering Research Council of CanadaPrincess Margaret Cancer Foundation
KeywordsBODIPYLiposomeFluorescenceQuenching (fluorescence)NanoparticleMaterials scienceFluorescence-lifetime imaging microscopyBiophysicsPhotoacoustic imaging in biomedicineNanotechnologyChemistryOptics

Abstract

fetched live from OpenAlex

Abstract Organic building blocks are the centerpieces of “one‐for‐all” nanoparticle development. Herein, we report the synthesis of a novel aza‐BODIPY‐lipid building block and its self‐assembly into a liposomal nanoparticle (BODIPYsome). We observed optically stable NIR J‐aggregation within the BODIPYsome that is likely attributed to J‐dimerization. BODIPYsomes with cholesterol showed enhanced colloidal stability while maintaining a high extinction coefficient (128 m m −1 cm −1 ) and high fluorescence quenching (99.70±0.09 %), which enables photoacoustic (PA) properties from its intact structure and recovered NIR fluorescence properties when it is disrupted in cancer cells. Finally, its capabilities for optical imaging (PA/fluorescence) were observed in an orthotopic prostate tumor mouse model 24 h after intravenous administration. Overall, the BODIPYsome opens the door for engineering new building blocks in the design of optically stable biophotonic imaging agents.

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.

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 score0.019
Threshold uncertainty score0.486

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 communication0.0000.001
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 head0.247
Teacher spread0.238 · 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