Chronic dietary creatine enhances hippocampal-dependent spatial memory, bioenergetics, and levels of plasticity-related proteins associated with NF-κB
Bibliographic record
Abstract
The brain has a high demand for energy, of which creatine (Cr) is an important regulator. Studies document neurocognitive benefits of oral Cr in mammals, yet little is known regarding their physiological basis. This study investigated the effects of Cr supplementation (3%, w/w) on hippocampal function in male C57BL/6 mice, including spatial learning and memory in the Morris water maze and oxygen consumption rates from isolated mitochondria in real time. Levels of transcription factors and related proteins (CREB, Egr1, and IκB to indicate NF-κB activity), proteins implicated in cognition (CaMKII, PSD-95, and Egr2), and mitochondrial proteins (electron transport chain Complex I, mitochondrial fission protein Drp1) were probed with Western blotting. Dietary Cr decreased escape latency/time to locate the platform ( P < 0.05) and increased the time spent in the target quadrant ( P < 0.01) in the Morris water maze. This was accompanied by increased coupled respiration ( P < 0.05) in isolated hippocampal mitochondria. Protein levels of CaMKII, PSD-95, and Complex 1 were increased in Cr-fed mice, whereas IκB was decreased. These data demonstrate that dietary supplementation with Cr can improve learning, memory, and mitochondrial function and have important implications for the treatment of diseases affecting memory and energy homeostasis.
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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) | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".