Imaging-Based Biomarkers: Characterization of Post-Kawasaki Vasculitis in Infants and Hypertension Phenotype in Rat Model
Bibliographic record
Abstract
Background. Investigating the mechanical properties of the arteries is essential in cardiovascular diseases. Recent imaging modalities allow mapping mechanical properties within the arterial wall. Aims. We report the potential of imaging-based biomarker (ImBioMark) to investigate the effect of aging on the rat. We also present preliminary data with ImBioMark characterizing vascular sequelae of Kawasaki disease (KD) in young humans. Methods. We investigated in vivo the effect of aging on male Brown Norway (BN) rats' (n = 5) carotid stiffness. In a second experiment, the impact of KD on the ascending aorta (AA) was examined in KD children (n = 2) aged 13 ± 1.41 years old compared to KD-free children (n = 5) aged 13.13 ± 0.18 years old. Results. The stiffness of BN's carotid artery was three times stiffer in the old rats, with a turning point at 40 weeks old (P = 0.001). KD had a very significant impact on the AA stiffness with strain estimates of 2.39 ± 0.51% versus 4.24 ± 0.65% in controls (P < 0.001). Conclusion. ImBioMark phenotypes hypertension in rat models noninvasively in vivo without resorting to euthanasia. Quantifying aortic wall remodeling is also feasible in humans. Future investigations target human cardiovascular disease.
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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".