Vascular Disruption Therapy in Lung Cancer using Endobronchial Ultrasound and Ultrasound Active Agents
Bibliographic record
Abstract
Tumour vascular disruption therapy (VDT) hampers tumour growth by inhibiting its supply of oxygen and nutrients. One strategy in VDT is to use ultrasound and ultrasound active agents (UAAs) (i.e. microbubbles and nanodroplets) to locally damage tumour vessels. Despite pre-clinical successes, lung cancer VDT by ultrasound and UAAs remains challenging as conventional ultrasound cannot penetrate the lung. Diagnostic endobronchial ultrasound (EBUS) enables ultrasound access into the lung and have the potential to be combined with UAAs to implement lung cancer VDT. Here, UAAs were characterized for stability and acoustic response in vitro and employed in vivo with EBUS to examine their potential in VDT in a mouse tumour model. The in vivo pilot study revealed that while applying EBUS and microbubbles showed little tumour vascular disruption effect, a substantial effect in vascular disruption was demonstrated when nanodroplets were used with EBUS (73% decrease in tumour microbubble perfusion).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".