Ultrasound Microbubble Treatment Enhances Clathrin-Mediated Endocytosis and Fluid-Phase Uptake through Distinct Mechanisms
Bibliographic record
Abstract
Drug delivery to tumors is limited by several factors, including drug permeability of the target cell plasma membrane. Ultrasound in combination with microbubbles (USMB) is a promising strategy to overcome these limitations. USMB treatment elicits enhanced cellular uptake of materials such as drugs, in part as a result of sheer stress and formation of transient membrane pores. Pores formed upon USMB treatment are rapidly resealed, suggesting that other processes such as enhanced endocytosis may contribute to the enhanced material uptake by cells upon USMB treatment. How USMB regulates endocytic processes remains incompletely understood. Cells constitutively utilize several distinct mechanisms of endocytosis, including clathrin-mediated endocytosis (CME) for the internalization of receptor-bound macromolecules such as Transferrin Receptor (TfR), and distinct mechanism(s) that mediate the majority of fluid-phase endocytosis. Tracking the abundance of TfR on the cell surface and the internalization of its ligand transferrin revealed that USMB acutely enhances the rate of CME. Total internal reflection fluorescence microscopy experiments revealed that USMB treatment altered the assembly of clathrin-coated pits, the basic structural units of CME. In addition, the rate of fluid-phase endocytosis was enhanced, but with delayed onset upon USMB treatment relative to the enhancement of CME, suggesting that the two processes are distinctly regulated by USMB. Indeed, vacuolin-1 or desipramine treatment prevented the enhancement of CME but not of fluid phase endocytosis upon USMB, suggesting that lysosome exocytosis and acid sphingomyelinase, respectively, are required for the regulation of CME but not fluid phase endocytosis upon USMB treatment. These results indicate that USMB enhances both CME and fluid phase endocytosis through distinct signaling mechanisms, and suggest that strategies for potentiating the enhancement of endocytosis upon USMB treatment may improve targeted drug delivery.
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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 | 0.001 | 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".