Neuroinflammation in Schizophrenia: A Critical Review and The Future
Bibliographic record
Abstract
Schizophrenia is a serious mental illness that affects approximately 1% of the population worldwide, with positive, negative and cognitive dysfunctions and a significant deterioration in psychosocial functioning. Interactions between genetic predisposition and environmental stressors at the early stages of life, and subsequently a molecular level neurodegeneration process are important in the development of schizophrenia. Current approaches suggest that cytokines-induced neuroinflammation might have a role in the development of several psychiatric disorders, including schizophrenia. Uncontrolled microglial activation, increase in pro-inflammatory cytokines, and subsequent neurotransmitter dysfunctions can induce schizophrenia. Microglial activation induced by pro-inflammatory cytokines in central nervous system is responsible for the initiation and proceeding of the inflammatory process and consequently developing neurodegeneration. Here in this review, we aimed to provide an overview to the latest findings related to the cytokines-mediated peripheral and central immune responses in the development of schizophrenia.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".