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Record W2922436230 · doi:10.3390/pharmaceutics11030125

Spatially Specific Liposomal Cancer Therapy Triggered by Clinical External Sources of Energy

2019· review· en· W2922436230 on OpenAlexaff
Courtney van Ballegooie, Alice Man, Mi Win, Donald T. Yapp

Bibliographic record

VenuePharmaceutics · 2019
Typereview
Languageen
FieldMedicine
TopicRadiation Therapy and Dosimetry
Canadian institutionsSimon Fraser UniversityUniversity of British ColumbiaBC Cancer Agency
Fundersnot available
KeywordsLiposomeDrug deliveryClinical trialMedical physicsCancer therapyCancer treatmentMedicineCancerExternal beam radiationRadiation therapyComputer scienceNanotechnologyBiomedical engineeringSurgeryMaterials scienceInternal medicine

Abstract

fetched live from OpenAlex

This review explores the use of energy sources, including ultrasound, magnetic fields, and external beam radiation, to trigger the delivery of drugs from liposomes in a tumor in a spatially-specific manner. Each section explores the mechanism(s) of drug release that can be achieved using liposomes in conjunction with the external trigger. Subsequently, the treatment's formulation factors are discussed, highlighting the parameters of both the therapy and the medical device. Additionally, the pre-clinical and clinical trials of each triggered release method are explored. Lastly, the advantages and disadvantages, as well as the feasibility and future outlook of each triggered release method, are discussed.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.990
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.241
GPT teacher head0.484
Teacher spread0.244 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations21
Published2019
Admission routes1
Has abstractyes

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