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Record W1980785302 · doi:10.1021/ja305988f

Porphyrin Shell Microbubbles with Intrinsic Ultrasound and Photoacoustic Properties

2012· article· en· W1980785302 on OpenAlexafffund
Elizabeth Huynh, Jonathan F. Lovell, Brandon Helfield, Mansik Jeon, Chulhong Kim, David E. Goertz, Brian C. Wilson, Gang Zheng

Bibliographic record

VenueJournal of the American Chemical Society · 2012
Typearticle
Languageen
FieldEngineering
TopicPhotoacoustic and Ultrasonic Imaging
Canadian institutionsSunnybrook Health Science CentreUniversity Health NetworkUniversity of TorontoOntario Institute for Cancer Research
FundersCanadian Institutes of Health Research
KeywordsChemistryPhotoacoustic imaging in biomedicineMicrobubblesUltrasoundShell (structure)PorphyrinNanotechnologyPhotochemistryOpticsAcousticsComposite material

Abstract

fetched live from OpenAlex

Porphyrin-phospholipid conjugates were used to create photonic microbubbles (MBs) having a porphyrin shell ("porshe"), and their acoustic and photoacoustic properties were investigated. The inclusion of porphyrin-lipid in the MB shell increased the yield, improved the serum stability, and generated a narrow volumetric size distribution with a peak size of 2.7 ± 0.2 μm. Using an acoustic model, we calculated the porshe stiffness to be 3-5 times greater than that of commercial lipid MBs. Porshe MBs were found to be intrinsically suitable for both ultrasound and photoacoustic imaging with a resonance frequency of 9-10 MHz. The distinctive properties of porshe MBs make them potentially advantageous for a broad range of biomedical imaging and therapeutic applications.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.000
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.006
GPT teacher head0.182
Teacher spread0.176 · 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 source (direct Gemma or distilled Codex), 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

Citations185
Published2012
Admission routes2
Has abstractyes

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