Optimizing Ultrasound Settings in Ultrasound and Microbubble Treatment of ARDS
Bibliographic record
Abstract
Acute respiratory distress syndrome (ARDS) is a severe disorder commonly found in intensive care units (ICUs) and results in high mortality. Characterized by fluid leakage into alveolar sacs, the heterogeneity of injury reduces effectiveness of current treatments. Ultrasoundmediated microbubble treatment has been used to successfully deliver cargo in a targeted manner to injured lung tissue. To further develop this method as a treatment, the optimal ultrasound settings for efficient cargo delivery need to be established. An ultrasound phantom model was used to correlate ultrasound settings with varying amounts of inertial cavitation. Three ultrasound settings corresponding to mostly inertial cavitation, mostly stable cavitation, and a mix of both were used to delivery cargo to adherent cells. Inertial cavitation induced more delivery and decreased cell viability compared to non-inertial cavitation. Further research using animal models is needed to optimize ultrasound settings for cargo delivery and develop USMB as a treatment for ARDS.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".