Relationship between salinity of the liquid and shell composition on the resonance frequency of the C3F8 lipid coated microbubbles
Bibliographic record
Abstract
Lipid-coated microbubbles (MBs) are used in contrast-enhanced ultrasound (CEUS) imaging and MB enhanced therapeutic ultrasound (US). Understanding the MB behavior and the influence of the surrounding medium on its response to the US is necessary to select the suitable US exposure parameters. The MB lipid coating is often charged, however the influence of the ions in the medium on MB behavior is not fully understood. In this work, the influence of the medium salinity on the pressure-dependent MB behavior is investigated for the first time. MBs of different lipid shell compositions are size isolated to achieve the same size distribution. The MBs linear and pressure-dependent attenuation are measured in deionized water, PBS 1×, PBS 2×, and PBS 10× using a system of aligned PVDF 100% bandwidth transducers with a center frequency of 10 MHz and exposures with peak to peak pressure range of 3–140 kPa. With increasing salinity, the linear resonance frequency decreases up to 50% for conventional lipid shell compositions, and the pressure dependence of the resonance frequency is inhibited. By modifying the shell PEG ratio, the salinity effects can significantly be altered. Moreover, the nonlinear pressure-dependent resonance frequency is restored with applications to increased CEUS.
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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 | 0.001 |
| 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".