Time course of the vasoactive response for sonoreperfusion therapy using long tone burst ultrasound
Bibliographic record
Abstract
We have previously shown that sonoreperfusion (SRP) using ultrasound (US) and microbubble (MB) can restore perfusion following microvascular obstruction and is mediated by nitric oxide vasodilation. Here, we compared the use of short (SP-10 cycles) and long (LP-5000 cycles) pulses for SRP and investigated the vasoactive response time-course and the downstream signaling 4 h post-treatment. In a rat hindlimb, we applied LP or SP (1 MHz,1.5 MPa) with the same number of acoustic cycles for 2 min during MB infusion. Both pulses affected the perfusion rate but with distinct temporal responses. For SP, the flow rate peaked (12.3±3.4 dB/s) at 15 min but returned to baseline (BL)(3.2±0.8 dB/s) after 60 min. Conversely, for LP, the flow rate also initially dropped but started to increase at 6 min and peaked (13.0±2.1 dB/s) at 15 min and was still high (8.3±2.0 dB/s) after 4 h compared to BL and SP. This sustained increase in flow rate, which was different from reactive hyperemia, was concordant with 2.5-fold increases in phosphorylated and total eNOS expression (Western blot) compared to untreated tissue, and consistent with a 2-fold increase in eNOS transcription (qPCR). These data support that long pulse SRP therapy increased in muscle perfusion for at least 4 h consistently with increased eNOS transcription and expression.
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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 | 0.000 | 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".