Brain-derived neurotrophic factor and neuroplasticity in bipolar disorder
Bibliographic record
Abstract
Initial descriptions of bipolar disorder (BD) emphasized that patients returned to a baseline condition after acute episodes. Such definitions were operational in teasing bipolar disorder apart from schizophrenia, where patients were described to be permanently impaired after the initial episodes. However, this view of BD as a disorder where cognition and overall functioning was spared has been changing after the scrutiny of new research. Currently, the cognitive impairment and neuroanatomical changes related to cumulative mood episodes, particularly manic episodes, are well described. In terms of neuropathological findings, recent data suggest that changes in neuronal plasticity, particularly in cell resilience and connectivity, are the main findings in BD. Data from differential lines of research converge to BDNF as an important contributor to the pathophysiology of BD. Serum BDNF levels have been shown to be decreased in depressive and manic episodes, returning to normal levels in euthymia. Moreover, factors that negatively influence the course of BD, such as life stress and trauma, have been shown to be associated with a decrease in serum BDNF levels among bipolar patients. These findings suggest that BDNF plays a central role in the transduction of psychosocial stress and recurrent episodes into the neurobiology of bipolar disorder. The present review discusses the role of BDNF as a mediator of the neuroplastic changes that occur in portion with mood episodes and the potential use of serum BDNF as a biomarker in BD.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".