Shear stress preconditioning and microbubble flow pattern modulate ultrasound-assisted plasma membrane permeabilization
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.
Bibliographic record
Abstract
The recent and exciting success of anti-inflammatory therapies for ischemic heart disease (e.g. atherosclerosis) is hindered by the lack of site-specific and targeted therapeutic deposition. Microbubble-mediated focused ultrasound, which uses circulating, lipid-encapsulated intravascular microbubbles to locally enhance endothelial permeability, offers an exciting approach. Atherosclerotic plaques preferentially develop in regions with disturbed blood flow, and microbubble-endothelial cell membrane interactions under such flow conditions are not well understood. Here, using an acoustically-coupled microscopy system, endothelial cells were sonicated (1 MHz, 20 cycle bursts, 1 ms PRI, 4 s duration, 300 kPa peak-negative pressure) under perfusion with Definity™ bubbles to examine microbubble-mediated endothelial permeabilization under a range of physiological conditions. Endothelial preconditioning under prolonged shear influenced physiology and the secretome, inducing increased expression of pro-angiogenesis analytes, decreasing levels of pro-inflammatory ones, and increasing the susceptibility of ultrasound therapy. Ultrasound treatment efficiency was positively correlated with concentrations of pro-angiogenic cytokines (e.g. VEGF-A, EGF, FGF-2), and negatively correlated with pro-inflammatory chemokines (e.g. MCP-1, GCP-2, SDF-1). Furthermore, ultrasound therapy under non-reversing pulsatile flow (∼4–8 dyne/cm2, 0.5–1 Hz) increased permeabilization up to 2.4-fold compared to shear-matched laminar flow, yet treatment under reversing oscillatory flow resulted in more heterogeneous modulation. This study provides insight into the role of vascular physiology, including endothelial biology, into the design of a localized ultrasound drug delivery system for ischemic heart disease.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| 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 it