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Record W4239019935 · doi:10.32920/ryerson.14647995

Synthesis and characterization of theranostic agents for photoacoustic imaging and therapy.

2021· preprint· en· W4239019935 on OpenAlexaff
Yan Jie Wang

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicPhotoacoustic and Ultrasonic Imaging
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsVaporizationPLGAMaterials scienceNanoparticleParticle (ecology)NanotechnologyIrradiationPhotoacoustic imaging in biomedicineFluenceParticle sizeLaserBiomedical engineeringChemical engineeringChemistryOpticsOrganic chemistryMedicine

Abstract

fetched live from OpenAlex

In this work, phase-change contrast agents were developed for photoacoustic (PA) imaging and therapy. They consist of superheated liquid perfluorocarbon and gold nanoparticles capped by a Poly-(Lactide-co-Glycolic Acid) (PLGA) polymer shell. The phase transition from liquid to gas bubble can be remotely triggered by a laser source. In their liquid state, upon laser irradiation, these agents generated strong PA signals which were proportional to the laser fluence and particle sizes. The vaporization threshold decreased with increasing particle size, and was 850, 670 and 420 mJ/cm2 for 2, 5, 10 μm-sized PLGA particles loaded with 35 nm GNPs, respectively. Cell culture studies, including passive uptake by the cancer cells and mechanical damage to the cancer cells caused by the vaporization inside the cells are also investigated. These agents show potential as photoacoustic imaging contrast and cancer therapy agents for clinical 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)0.000
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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)0.0010.001

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 head0.012
GPT teacher head0.219
Teacher spread0.207 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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Same topicPhotoacoustic and Ultrasonic ImagingFrench-language works237,207