Assessment and pathophysiology of microvascular disease: recent progress and clinical implications
Bibliographic record
Abstract
The development of novel, non-invasive techniques and standardization of protocols to assess microvascular dysfunction have elucidated the key role of microvascular changes in the evolution of cardiovascular (CV) damage, and their capacity to predict an increased risk of adverse events. These technical advances parallel with the development of novel biological assays that enabled the ex vivo identification of pathways promoting microvascular dysfunction, providing novel potential treatment targets for preventing cerebral-CV disease. In this article, we provide an update of diagnostic testing strategies to detect and characterize microvascular dysfunction and suggestions on how to standardize and maximize the information obtained from each microvascular assay. We examine emerging data highlighting the significance of microvascular dysfunction in the development CV disease manifestations. Finally, we summarize the pathophysiology of microvascular dysfunction emphasizing the role of oxidative stress and its regulation by epigenetic mechanisms, which might represent potential targets for novel interventions beyond conventional approaches, representing a new frontier in CV disease reduction.
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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 | 0.000 | 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 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".