<i>Ex Vivo</i>Evaluation of a Novel Polyiodinated Compound for Early Detection of Atherosclerosis
Bibliographic record
Abstract
Atherosclerosis is a primary cause of heart disease and stroke; it is the underlying cause of about 50% of all deaths in Western countries. It is known that early detection of atherosclerotic lesions would significantly reduce the risk of mortality. The objective of this study was to develop a radioimaging method for early detection of atherosclerotic plaques. A novel polyiodinated cholesterol analog, cholesteryl 1,3-diiopanoate glyceryl ether (C2I, patent pending), was synthesized and radiolabeled with 125I. 125I-C2I was incorporated into acetylated low-density lipoprotein (AcLDL), which is considered to be an atherosclerotic plaque-seeking carrier. 125I-C2I was also prepared as a chylomicron-like emulsion. Transgenic mice deficient in apoE and low-density lipoprotein receptors (LDLR), known as apoE/LDLR double knockout, were used as an animal model of early atherosclerosis. 125I-C2I/AcLDL or 125I-C2I emulsion was injected into the apoE/LDLR knockout mice via the tail vein, and the mice were killed humanely 24 h after injection. Various tissues including aorta were removed and radioactivity was determined. The aorta samples were also imaged to determine the accumulation of radioactivity from C2I. The images were compared to the atherosclerotic lesions revealed by histological studies. It was found that both 125I-C2I/AcLDL and 125I-C2I emulsion resulted in accumulation of radioactivity at the site of early atherosclerotic lesions, and they therefore may be useful for early detection of atherosclerosis.
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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".