Fundamentals of Endothelial Function for the Clinical Cardiologist
Bibliographic record
Abstract
Mr Gundry is a 42-year-old construction worker who has had type II diabetes mellitus for the past 6 years.He has no other vascular risk factors and is currently asymptomatic.Is this patient at risk of developing endothelial dysfunction?Case presentation 2: Mr Sinha is a 64-year-old man who presents to your office for symptomatic intermittent claudication.Past medical history is unremarkable except for the presence of multiple vascular risk factors (smoking, hypertension, dyslipidemia, and obesity).How do vascular risk factors cause endothelial dysfunction?Is endothelial dysfunction treatable?A survey of medical history will reveal that major breakthroughs are often a result of simple and at times unexpected observations.Indeed, the era of endothelial biology was brought to the forefront through a simple pharmacological experiment conducted approximately 2 decades ago in Dr Furchgott's laboratory. 1 In this landmark study, the authors described the essential role of the endothelium in mediating the vasodilatory actions of acetylcholine, now known to be dependent on the release of nitric oxide (NO) from the endothelium.No one could have predicted that this observation would have the gargantuan impact on vascular biology that is evident today.Endothelial dysfunction now is implicated in the pathogenesis and clinical course of the majority of cardiovascular diseases.The purpose of this "Clinical Cardiology: Physician Update" is to provide the busy cardiovascular specialist with some of the fundamental principles of endothelial function as they relate to cardiovascular health and 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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".