The effect of ultrasound pulse length on microbubble cavitation induced antibody accumulation and distribution in a mouse model of breast cancer
Bibliographic record
Abstract
In solid tumors, the limited diffusion of therapeutic molecules in the perivascular space is a known limitation impacting treatment efficacy.Ultrasound Targeted Microbubble Cavitation (UTMC) has been shown to increase vascular permeability and improve the delivery of therapeutic compounds including small molecules, antibodies (mAb), nanoparticles and even cells, notably across the blood-brain-barrier (BBB).In this study, we hypothesized that UTMC could improve the accumulation and biodistribution of mAb targeting the adenosinergic pathway (i.e.CD73) in mice bearing bilateral subcutaneous 4T1 mammary carcinoma.METHODS: A bolus of fluorescently labeled mAb was given intravenously, followed by a slow infusion of microbubbles.UTMC therapy (1 MHz, 850 kPa) was given under ultrasound image guidance for 5 minutes to the right side tumor only, using three different pulse lengths with identical ultrasound energy (5000cyc "long", 125x40cyc "mid" and 500x10cyc "short"), and leaving the left tumor as a paired control.Longitudinal accumulation at 0 h, 4 h and 24 h was measured using whole-body biofluorescence and confocal microscopy.RESULTS: Our data support an increase in antibody accumulation and extravasation (# extravasated vessels and extravasated signal intensity) at 0 h for all pulses and at 4 h for the mid and short pulses when compared to the control non treated side.However, this difference was not found at 24 h post UTMC, indicative of the transient nature of UTMC.Interestingly, confocal data supported that the highest extravasation range was obtained at 0 h with the long pulse and that the short pulse caused no increase in the extravasation range.Overall, the mid pulse was the only pulse to increase all our metrics (biofluorescence, fraction of extravasated vessels, amount of extravasated Ab, and extravasation range) at 0 h and 4 h time points.CONCLUSIONS: Our results support that UTMC can enhance antibody accumulation in solid tumors at the macroscopic and microscopic levels.This preferential accumulation was evident at early time points (0 h and 4 h) but had started to fade by 24 h, a time dependence that is consistent with the ultrasound blood brain barrier opening literature.Further development and optimization of this theranostic platform, such as repeated UTMC, could help improve antibody based therapies against solid cancer.
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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".