Effect of circadian rhythm on NAD and other metabolites in human brain
Bibliographic record
Abstract
Nicotinamide Adenine Dinucleotide (NAD) plays a central role in the master circadian clock of the brain (the suprachiasmatic nuclei, SCN) as demonstrated in many model organisms. NAD acts as an enzyme co-factor and substrate and its modulation was found to be tightly regulated to the periodicity of the cycles. However, in human brain, the effect of the circadian rhythm (CR) on the metabolism of the SCN and other brain regions is poorly understood. We conducted a magnetic resonance spectroscopy (MRS) study at a high magnetic field, measuring the occipital brain NAD levels and other metabolites in two different morning and afternoon diurnal states in 25 healthy participants. Salivary cortisol levels were determined to confirm that the experiment was done in two chronologically different physiological conditions, and a behavioral test of risk-taking propensity was administered. Overall, we found that the CR did not significantly affect NAD levels in the occipital brain region. The other brain metabolites measured, including lactate, were not significantly affected by the CR either, except for taurine. The CR did impact risk-taking behavior and salivary cortisol level, confirming that the participants were in two circadian different behavioral and physiological states in the morning and in the afternoon. Measurement of the CR effect on NAD and taurine levels in other brain regions might provide stronger effects.
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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 | 0.000 | 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) | 0.001 | 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 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".