Dual-Modal Magnetic Resonance and Fluorescence Imaging of Atherosclerotic Plaques in Vivo Using VCAM-1 Targeted Tobacco Mosaic Virus
Bibliographic record
Abstract
The underlying cause of major cardiovascular events, such as myocardial infarctions and strokes, is atherosclerosis. For accurate diagnosis of this inflammatory disease, molecular imaging is required. Toward this goal, we sought to develop a nanoparticle-based, high aspect ratio, molecularly targeted magnetic resonance (MR) imaging contrast agent. Specifically, we engineered the plant viral nanoparticle platform tobacco mosaic virus (TMV) to target vascular cell adhesion molecule (VCAM)-1, which is highly expressed on activated endothelial cells at atherosclerotic plaques. To achieve dual optical and MR imaging in an atherosclerotic ApoE(-/-) mouse model, TMV was modified to carry near-infrared dyes and chelated Gd ions. Our results indicate molecular targeting of atherosclerotic plaques. On the basis of the multivalency and multifunctionality, the targeted TMV-based MR probe increased the detection limit significantly; the injected dose of Gd ions could be further reduced 400x compared to the suggested clinical use, demonstrating the utility of targeted nanoparticle cargo 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".