Deficits in axon‐associated proteins in prefrontal white matter in bipolar disorder but not schizophrenia
Bibliographic record
Abstract
OBJECTIVES: Brain imaging studies have implicated white matter dysfunction in the pathophysiology of both bipolar disorder (BD) and schizophrenia (SCZ). However, the contribution of axons to white matter pathology in these disorders is not yet understood. Maintenance of neuronal function is dependent on the active transport of biological material, including synaptic proteins, along the axon. In this study, the expression of six proteins associated with axonal transport of synaptic cargoes was quantified in postmortem samples of prefrontal white matter in subjects with BD, those with SCZ, and matched controls, as a measure of axonal dysfunction in these disorders. METHODS: Levels of the microtubule-associated proteins β-tubulin and microtubule-associated protein 6 (MAP6), the motor and accessory proteins kinesin-1 and disrupted-in-schizophrenia 1 (DISC1), and the synaptic cargoes synaptotagmin and synaptosomal-associated protein-25 (SNAP-25) were quantified in white matter adjacent to the dorsolateral prefrontal cortex in subjects with BD (n = 34), subjects with SCZ (n = 35), and non-psychiatric controls (n = 35) using immunoblotting and an enzyme-linked immunosorbent assay (ELISA). RESULTS: Protein expression of β-tubulin, kinesin-1, DISC1, synaptotagmin, and SNAP-25 was significantly lower in subjects with BD compared to controls. Levels of axon-associated proteins were also lower in subjects with SCZ, but failed to reach statistical significance. CONCLUSIONS: These data provide evidence for deficits in axon-associated proteins in prefrontal white matter in BD. Findings are suggestive of decreased axonal density or dysregulation of axonal function in this disorder.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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 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".