MétaCan
Menu
Back to cohort
Record W4404359355 · doi:10.1177/15330338241298864

Ultrasound-Based Radiation Enhancement: Concepts, Mechanisms and Therapeutic Applications

2024· editorial· en· W4404359355 on OpenAlexaff
Deepa Sharma, Gregory J. Czarnota

Bibliographic record

VenueTechnology in Cancer Research & Treatment · 2024
Typeeditorial
Languageen
FieldEngineering
TopicUltrasound and Hyperthermia Applications
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMicrobubblesCeramideRadiation therapyCancer researchUltrasoundAcid sphingomyelinaseEndothelial stem cellCell biologyMedicineChemistryBiologyApoptosisRadiologyBiochemistry

Abstract

fetched live from OpenAlex

Microbubbles have emerged as versatile carriers used both for cancer diagnosis and therapy. Microbubbles in the presence of ultrasound waves undergo cavitation, generating bioeffects near the cell's vicinity. Studies have shown ultrasound-stimulated microbubbles (USMB) to cause mechanical perturbation of endothelial cells, resulting in acid sphingomyelinase (ASMase)-induced ceramide production. Disruption of endothelial cells further causes vascular deterioration, leading to secondary tumor cell death. These effects are known to be synergistically higher when USMB is combined with radiation. This paper provides insight into the use of USMB as a potential radioenhancer. The possible underlying mechanism and therapeutic effects of combining USMB and radiation therapy are also presented.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0040.003
Open science0.0020.001
Research integrity0.0080.010
Insufficient payload (model declined to judge)0.0050.004

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 head0.023
GPT teacher head0.362
Teacher spread0.339 · 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 designNot applicable
Domainnot available
GenreEditorial

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

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueTechnology in Cancer Research & TreatmentSame topicUltrasound and Hyperthermia ApplicationsFrench-language works237,207