The power of Pasteur's quadrant: cardiovascular disease at the turn of the century
Bibliographic record
Abstract
During the life span of The FASEB Journal, the decline in cardiovascular mortality was astonishing as the fundamental bases of the complex syndromes of cardiovascular disease were illuminated. In this Silver Anniversary Review, we highlight a few pivotal advances in the field and relate them to research in Pasteur's quadrant, the region of investigation driven by both a desire for fundamental understanding and the consideration of its use. In the second half of the 20th century, we advanced from little pathophysiologic understanding to a near-complete understanding and effective, evidence-based therapeutics for vascular disorders and a similar development of pharmacotherapy to address heart failure, primarily through agents that antagonize the excessive concentration of circulating neurohumoral agents. In the current era, we have witnessed "the rise of the machines," from stents to cardiac resynchronization therapy. The next wave of treatments will build on an increasingly sophisticated understanding of the molecular determinants of cardiovascular disorders. We briefly consider the promise of regenerative medicine and are intrigued by the possibility for the direct reprogramming of resident cardiac fibroblasts into cardiomyocytes. As for the future, genomic profiling should help physicians recommend individualized risk factor modification targeted to prevent specific manifestations of cardiovascular disease. Transcriptional and biomarker analyses will almost surely be used individually to tailor therapy for those at risk of or experiencing cardiovascular disease. Given the ongoing exponential expansion of scientific knowledge, all of human ingenuity will be needed to fully utilize the power of Pasteur's quadrant and to unleash another quarter century in cardiology as scientifically fruitful and effective on human health as the last.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.007 | 0.016 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".