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Record W1969876744 · doi:10.1124/mi.8.5.8

Looking at Lithium: Molecular Moods and Complex Behaviour

2008· review· en· W1969876744 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMolecular Interventions · 2008
Typereview
Languageen
FieldMedicine
TopicBipolar Disorder and Treatment
Canadian institutionsUniversité Laval
FundersNational Institute on Drug AbuseNational Institute of Neurological Disorders and StrokeNational Institute of Mental Health
KeywordsLithium (medication)GSK-3Protein kinase BNeuroprotectionBipolar disorderNeuroscienceGSK3BMoodMood stabilizerSignal transductionPharmacologyChemistryMedicineBiologyCell biologyInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.967
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.075
GPT teacher head0.386
Teacher spread0.311 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it