Assessment of Endogenous and Therapeutic Arteriogenesis by Contrast Ultrasound Molecular Imaging of Integrin Expression
Bibliographic record
Abstract
BACKGROUND: We hypothesized that molecular imaging with contrast-enhanced ultrasound (CEU) and microbubbles targeted to endothelial integrins could be used to noninvasively assess early angiogenic responses to ischemia and growth factor therapy. METHODS AND RESULTS: Hindlimb ischemia was produced in 48 rats by ligation of an iliac artery. Half of the animals received intramuscular sustained-release fibroblast growth factor-2 (FGF-2). Immediately after ligation and at subsequent intervals from 4 to 28 days, blood flow and oxygen tension in the proximal adductor muscles were measured by CEU perfusion imaging and phosphor quenching, respectively. Targeted CEU imaging of alpha(v)- and alpha5beta1-integrin expression was performed with microbubbles bearing the disintegrin echistatin. Iliac artery ligation produced a 65% to 70% reduction in blood flow and oxygen tension. In untreated ischemic muscle, muscle flow and oxygen tension partially recovered by days 14 to 28. In these animals, signal from integrin-targeted microbubbles was intense and peaked before flow increase (days 4 to 7). In comparison to untreated animals, FGF-2-treated muscle had a greater rate and extent of blood flow recovery and greater signal intensity from integrin-targeted microbubbles, which peaked before maximal recovery of flow. On immunohistology, arteriolar but not capillary density increased in the ischemic limb after ligation, the rate and degree of which were greater in FGF-2-treated rats. Immunofluorescence demonstrated intense staining for alpha(v) in arterioles, the temporal course of which correlated with targeted imaging. CONCLUSIONS: Targeted CEU can be used to assess endogenous and therapeutic arteriogenesis before recovery of tissue perfusion. These results suggest that molecular imaging of integrin expression may be useful for evaluating proangiogenic therapies.
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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 | 0.000 |
| 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 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".