The role of dietary niacin intake and the adenosine-5′-diphosphate-ribosyl cyclase enzyme CD38 in spatial learning ability: is cyclic adenosine diphosphate ribose the link between diet and behaviour?
Bibliographic record
Abstract
The pyridine nucleotide NAD+ is derived from dietary niacin and serves as the substrate for the synthesis of cyclic ADP-ribose (cADPR), an intracellular Ca signalling molecule that plays an important role in synaptic plasticity in the hippocampus, a region of the brain involved in spatial learning. cADPR is formed in part via the activity of the ADP-ribosyl cyclase enzyme CD38, which is widespread throughout the brain. In the present review, current evidence of the relationship between dietary niacin and behaviour is presented following investigations of the effect of niacin deficiency, pharmacological nicotinamide supplementation and CD38 gene deletion on brain nucleotides and spatial learning ability in mice and rats. In young male rats, both niacin deficiency and nicotinamide supplementation significantly altered brain NAD+ and cADPR, both of which were inversely correlated with spatial learning ability. These results were consistent across three different models of niacin deficiency (pair feeding, partially restricted feeding and niacin recovery). Similar changes in spatial learning ability were observed in Cd38- / - mice, which also showed decreases in brain cADPR. These findings suggest an inverse relationship between spatial learning ability, dietary niacin intake and cADPR, although a direct link between cADPR and spatial learning ability is still missing. Dietary niacin may therefore play a role in the molecular events regulating learning performance, and further investigations of niacin intake, CD38 and cADPR may help identify potential molecular targets for clinical intervention to enhance learning and prevent or reverse cognitive decline.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".