GSK3β: a plausible mechanism of cognitive and hippocampal changes induced by erythropoietin treatment in mood disorders?
Bibliographic record
Abstract
Mood disorders are associated with significant psychosocial and occupational disability. It is estimated that major depressive disorder (MDD) will become the second leading cause of disability worldwide by 2020. Existing pharmacological and psychological treatments are limited for targeting cognitive dysfunctions in mood disorders. However, growing evidence from human and animal studies has shown that treatment with erythropoietin (EPO) can improve cognitive function. A recent study involving EPO-treated patients with mood disorders showed that the neural basis for their cognitive improvements appeared to involve an increase in hippocampal volume. Molecular mechanisms underlying hippocampal changes have been proposed, including the activation of anti-apoptotic, antioxidant, pro-survival and anti-inflammatory signalling pathways. The aim of this review is to describe the potential importance of glycogen synthase kinase 3-beta (GSK3β) as a multi-potent molecular mechanism of EPO-induced hippocampal volume change in mood disorder patients. We first examine published associations between EPO administration, mood disorders, cognition and hippocampal volume. We then highlight evidence suggesting that GSK3β influences hippocampal volume in MDD patients, and how this could assist with targeting more precise treatments particularly for cognitive deficits in patients with mood disorders. We conclude by suggesting how this developing area of research can be further advanced, such as using pharmacogenetic studies of EPO treatment in patients with 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".