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Record W4388571002 · doi:10.1177/15330338231211472

Integrating Therapeutic Ultrasound With Nanosized Drug Delivery Systems in the Battle Against Cancer

2023· review· en· W4388571002 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

VenueTechnology in Cancer Research & Treatment · 2023
Typereview
Languageen
FieldEngineering
TopicUltrasound and Hyperthermia Applications
Canadian institutionsSt. Michael's HospitalToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDrug deliveryMedicineDrugCancer therapyCancerCancer treatmentCancer drugsDrug carrierPharmacologyNanotechnologyInternal medicineMaterials science

Abstract

fetched live from OpenAlex

Controlled, localized, and timely activation of nanosized drug delivery systems (NSDDSs), using an external stimulus such as therapeutic ultrasound (TUS), can improve the efficacy of cancer treatments compared to either conventional chemotherapy methods or passive NSDDSs alone. Specifically, TUS induces thermal and mechanical effects that trigger drug release from NSDDSs and overcomes drug delivery barriers in tumor microenvironments to allow nanoparticle drug carriers to penetrate more deeply into tumor tissue while minimizing side effects. This review highlights recent advancements, contemplates future prospects, and addresses challenges in using TUS-mediated NSDDSs for cancer treatment, encompassing preclinical and 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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.111
GPT teacher head0.402
Teacher spread0.291 · 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