The Role of Neuroglia in the Development and Progression of Schizophrenia
Bibliographic record
Abstract
Schizophrenia is a complex heterogenous disorder thought to be caused by interactions between genetic and environmental factors. The theories developed to explain the etiology of schizophrenia have focused largely on the dysfunction of neurotransmitters such as dopamine, serotonin and glutamate with their receptors, although research in the past several decades has indicated strongly that other factors are also involved and that the role of neuroglial cells in psychotic disorders including schizophrenia should be given more attention. Although glia were originally thought to be present in the brain only to support neurons in a physical, metabolic and nutritional capacity, it has become apparent that these cells have a variety of important physiological roles and that abnormalities in their function may make significant contributions to the symptoms of schizophrenia. In the present paper, we review the interactions of brain microglia, astrocytes and oligodendroglia with aspects such as transmitter dysregulation, neuro-inflammation, oxidative stress, synaptic function, the gut microbiome, myelination and the blood-brain barrier that appear to affect the cause, development and treatment of schizophrenia. We also review crosstalk between microglia, astrocytes and oligodendrocytes and the effects of antipsychotics on neuroglia. Problems associated with studies on specific biomarkers for glia in schizophrenia are discussed.
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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 | 0.001 |
| 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 | 0.001 |
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".