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Record W2001942919 · doi:10.1021/bc5000725

Aggregate Enhanced Trimodal Porphyrin Shell Microbubbles for Ultrasound, Photoacoustic, and Fluorescence Imaging

2014· article· en· W2001942919 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

VenueBioconjugate Chemistry · 2014
Typearticle
Languageen
FieldEngineering
TopicUltrasound and Hyperthermia Applications
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
FundersCanadian Institutes of Health Research
KeywordsMicrobubblesChemistryPhotoacoustic imaging in biomedicinePorphyrinUltrasoundFluorescence-lifetime imaging microscopyMolecular imagingMagnetic resonance imagingFluorescenceDrug deliveryUltrasound imagingBiophysicsNuclear magnetic resonanceNanotechnologyBiomedical engineeringRadiologyIn vivoOpticsPhotochemistryMaterials science

Abstract

fetched live from OpenAlex

Microbubbles (MBs) are currently used as ultrasound (US) contrast agents and as delivery vehicles for site-specific US-triggered drug and gene delivery. Multimodal US-based imaging methods have been applied preclinically to assess and validate the effectiveness and fate of MBs in imaging and therapy. Here we present the first intrinsically trimodal MBs by incorporating a dense concentration of porphyrin molecules within a MB shell, enabled by the use of a single porphyrin-lipid component. These MBs possess US, photoacoustic, and fluorescence properties that are demonstrated in solution and in a mouse tumor xenograft model. They also have potential to be extended to other imaging modalities such as magnetic resonance imaging and nuclear imaging.

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 score0.022
Threshold uncertainty score0.942

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 head0.004
GPT teacher head0.184
Teacher spread0.181 · 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