A kinesin signaling complex mediates the ability of GSK-3β to affect mood-associated behaviors
Bibliographic record
Abstract
Lithium has been the gold standard in the treatment of bipolar disorder (BPD) for 60 y. Like lithium, glycogen synthase kinase 3 (GSK-3) inhibitors display both antimanic-like and antidepressant-like effects in some animal models. However, the molecular mechanisms of both lithium and GSK-3 inhibitors remain unclear. Here we show that the GSK-3 inhibitor AR-A014418 regulated alpha-amino-3-hydroxyl-5-methyl-4-isoxazole-propionate (AMPA)-induced GluR1 and GluR2 internalization via phosphorylation of kinesin light chain 2 (KLC2), the key molecule of the kinesin cargo delivery system. Specifically, AMPA stimulation triggered serine phosphorylation of KLC2 and, subsequently, the dissociation of the GluR1/KLC2 protein complex. This suggests that GSK-3 phosphorylation of KLC2 led to the dissociation of AMPA-containing vesicles from the kinesin cargo system. The peptide TAT-KLCpCDK, a specific inhibitor for KLC2 phosphorylation by GSK-3beta, reduced the formation of long-term depression. Furthermore, the TAT-KLCpCDK peptide showed antimanic-like effects similar to lithium's on amphetamine-induced hyperactivity, a frequently used animal model of mania. It also induced antidepressant-like effects in the tail suspension and forced swim tests, two commonly used animal models of depression. Taken together, the results demonstrated that KLC2 is a cellular target of GSK-3beta capable of regulating synaptic plasticity, particularly AMPA receptor trafficking, as well as mood-associated behaviors in animal models. The kinesin cargo system may provide valuable novel targets for the development of new therapeutics for mood disorders.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".