Targeted delivery of miR-1 to the heart using clinical contrast ultrasound
Bibliographic record
Abstract
Pathological left-ventricle hypertrophy is a cardiovascular disorder resulting in the thickening of the ventricle wall due to abnormal cardiomyocyte growth. The downregulation of miR-1 in hypertrophic cardiomyocytes has been identified as an early disease marker, with the delivery of miR-1 as a promising treatment strategy. Ultrasound and microbubbles offer an exciting approach to image-guided and site-specific cardiac gene delivery. The objective of this study is to show the feasibility of viable ultrasound and microbubble-mediated delivery of miR-1 in vivo. Sprague–Dawley rats were injected via tail vein with a suspension of miR-1 mimic (0.6 mg/kg) and Definity. The rats were then treated with a high MI (1.34) flash sequence for 20 min using a C5-2 probe with a Phillips iU22. Delivery was confirmed on isolated heart tissue with RT-qPCR and Western blots for miR-1 and protein expression, respectively. miR-1 delivery in healthy male rats resulted in a 1.33-fold (p = 0.05) increase in miR-1 as compared to sham controls. This resulted in a decrease in hypertrophic protein expression (1.18-fold in TWF1, p = 0.17; 1.23-fold in MEF2A, p = 0.07; 1.25-fold in CX43, p = 0.03). Our data demonstrate the feasibility of using ultrasound and microbubbles as an image-guided delivery method for molecular therapeutics in cardiovascular disorders.
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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".