Detection of atherosclerotic plaques with HDL-like porphyrin nanoparticles using an intravascular dual-modality optical coherence tomography and fluorescence system
Bibliographic record
Abstract
Abstract Atherosclerosis is the build-up of fatty plaques within blood vessel walls, which can occlude the vessels and cause strokes or heart attacks. It gives rise to both structural and biomolecular changes in the vessel walls. Current single-modality imaging techniques each measure one of these two aspects but fail to provide insight into the combined changes. To address this, our team has developed a dual-modality imaging system which combines optical coherence tomography (OCT) and fluorescence imaging that is optimized for a porphyrin lipid nanoparticle that emits fluorescence and targets atherosclerotic plaques. Atherosclerosis-prone apolipoprotein ( Apo ) e -/- mice were fed a high cholesterol diet to promote plaque development in descending thoracic aortas. Following infusion of porphyrin lipid nanoparticles in atherosclerotic mice, the fiber-optic probe was inserted into the aorta for imaging, and we were able to robustly detect a porphyrin lipid-specific fluorescence signal that was not present in saline-infused control mice. We observed that the nanoparticle fluorescence colocalized in areas of CD68 + macrophages. These results demonstrate that our system can detect the fluorescence from nanoparticles, providing complementary biological information to the structural information obtained from simultaneously acquired OCT.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".