Looking at Lithium: Molecular Moods and Complex Behaviour
Bibliographic record
Abstract
Lithium and other mood-stabilizing drugs are used for the management of bipolar mood disorders and, to a lesser extent, for augmentation of other psychoactive drugs. Lithium also has neuroprotective properties that may be useful for treatment of neurodegenerative diseases such as Alzheimer's disease and amyotrophic lateral sclerosis. Over the years, lithium has been shown to inhibit inositol monophosphatases and glycogen synthase kinase 3, but the relevance of such enzyme inhibition to the therapeutic effects of lithium has remained difficult to assess. Here, we provide an overview of recent advances in the identification of molecular mechanisms involved in the regulation of behavior by lithium. We also highlight recent findings suggesting that lithium could exert some of its behavioral effects by acting on a dopamine receptor regulated signaling complex composed of Akt, protein phosphatase 2A, and the multifunctional protein scaffold beta-arrestin 2.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".