Bibliographic record
Abstract
Diurnal rhythms influence cardiovascular physiology such as heart rate and blood pressure and the incidence of adverse cardiac events such as heart attack and stroke. For example, shift workers and patients with sleep disturbances, such as obstructive sleep apnea, have an increased risk of heart attack, stroke, and sudden death. Diurnal variation is also evident at the molecular level, as gene expression in the heart and blood vessels is remarkably different in the day as compared to the night. Much of the evidence presented here indicates that growth and renewal (structural remodeling) are highly dependent on processes that occur during the subjective night. Myocardial metabolism is also dynamic with substrate preference also differing day from night. The risk/benefit ratio of some therapeutic strategies and the appearance of biomarkers also vary across the 24-hour diurnal cycle. Synchrony between external and internal diurnal rhythms and harmony among the molecular rhythms within the cell is essential for normal organ biology. Cell physiology is 4 dimensional; the substrate and enzymatic components of a given metabolic pathway must be present not only in the right compartmental space within the cell but also at the right time. As a corollary, we show disrupting this integral relationship has devastating effects on cardiovascular, renal and possibly other organ systems. Harmony between our biology and our environment is vital to good health.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.046 | 0.029 |
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".