Cardiovascular research and the arrival of circadian medicine
Bibliographic record
Abstract
Reinberg and Michael Smolensky as a visionary step forward for the emerging science of chronobiology (Reinberg and Smolensky 1984).The first issue included many studies relevant to human health including cardiovascular disease, neurobiology, cancer, bone growth, metabolic pathways, as well as cosinor bioinformatics programs for the Apple II microcomputer, and several papers on other organisms.Over the decades, it has become the leading journal of biological and medical rhythm research.As of 2023, there are now 40 volumes of Chronobiology International, and the importance of applying circadian biology to clinical medicine has become increasingly apparent.The published papers encompass a wide range of clinical conditions, incorporate the latest state-of the-art technologies, challenge us to better understand human physiology and pathophysiology, and apply our circadian research as a basis for new treatments for disease.Importantly, we now know that circadian rhythms are especially relevant to cardiovascular physiology.For example, circadian rhythms underlie our daily rhythmic variation in heart rate, blood pressure, and the day/night biases of our autonomic nervous system.Circadian rhythms also underlie the timing of the onset of adverse cardiovascular events such as myocardial infarction, ventricular tachyarrhythmias, sudden cardiac death, and dissection or rupture of aortic aneurysms (Martino and Sole 2009).Moreover, circadian rhythms are highly relevant to clinical cardiology therapies, such as chronotherapy for hypertension, (Mistry et al. 2017) circadian lighting in intensive care units (Alibhai et al. 2014), and can influence morbidity and mortality following surgical procedures such as percutaneous coronary intervention, or angioplasty, or aortic valve replacement.(Khaper et al. 2018).Recently the important role of biological sex and gender on chronobiology and chronotherapies (Glen Pyle and Martino 2018), and development of the novel field of rest for befitting cardiac repair have been discovered (Reitz et. al 2022).The idea for this special collection of articles in Chronobiology International was developed following an NIH workshop on Understanding the Circadian Mechanisms of Sudden Cardiac Death in Bethesda MD in 2019 (Delisle et al. 2021b , 2021a)).Building on this prestigious meeting, we reached out to Dr.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.011 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".