Low-Dose Lithium Supplementation Influences GSK3β Activity in a Brain Region Specific Manner in C57BL6 Male Mice
Bibliographic record
Abstract
BACKGROUND: Lithium, a commonly used treatment for bipolar disorder, has been shown to have neuroprotective effects for other conditions including Alzheimer's disease via the inhibition of the enzyme glycogen synthase kinase-3 (GSK3). However, dose-dependent adverse effects of lithium are well-documented, highlighting the need to determine if low doses of lithium can reliably reduce GSK3 activity. OBJECTIVE: The purpose of this study was to evaluate the effects of a low-dose lithium supplementation on GSK3 activity in the brain of an early, diet-induced Alzheimer's disease model. METHODS: Male C57BL/6J mice were divided into either a 6-week or 12-week study. In the 6-week study, mice were fed a chow diet or a chow diet with lithium-supplemented drinking water (10 mg/kg/day) for 6 weeks. Alternatively, in the 12-week study, mice were fed a chow diet, a high-fat diet (HFD), or a HFD with lithium-supplemented drinking water for 12 weeks. Prefrontal cortex and hippocampal tissues were collected for analysis. RESULTS: Results demonstrated reduced GSK3 activity in the prefrontal cortex as early as 6 weeks of lithium supplementation, in the absence of inhibitory phosphorylation changes. Further, lithium supplementation in an obese model reduced prefrontal cortex GSK3 activity as well as improved insulin sensitivity. CONCLUSION: Collectively, these data provide evidence for low-dose lithium supplementation to inhibit GSK3 activity in the brain. Moreover, these results indicate that GSK3 activity can be inhibited despite any changes in phosphorylation. These findings contribute to an overall greater understanding of low-dose lithium's ability to influence GSK3 activity in the brain and its potential as an Alzheimer's disease prophylactic.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".