Autoimmunity and immune system dysregulation in schizophrenia: IgGs from sera of patients hydrolyze myelin basic protein
Bibliographic record
Abstract
Several different theories of schizophrenia (SCZ) were discussed; the causes of this disease are not yet clear. Using ELISA, it was shown that titers of autoantibodies against myelin basic protein (MBP) in SCZ patients are ~1.8-fold higher than in healthy individuals but 5.0-fold lower than in patients with multiple sclerosis. Several rigid criteria were checked to show that the MBP-hydrolyzing activity is an intrinsic property of SCZ IgGs. Approximately 82% electrophoretically homogeneous SCZ IgGs purified using several affinity sorbents including Sepharose with immobilized MBP hydrolyze specifically only MBP but not many other tested proteins. The average relative activity of IgGs from patients with negative symptoms was 2.5-fold higher than that of patients with positive symptoms of SCZ, and it increases with the duration of this pathology. It was shown that abzymes are the earliest statistically significant markers of many autoimmune pathologies. Our findings surmise that the immune systems of individual SCZ patients can generate a variety of anti-MBP abzymes with different catalytic properties, which can attack MBP of the myelin-proteolipid shell of axons. Therefore, autoimmune processes together with other mechanisms can play an important role in SCZ pathogenesis. MBP-hydrolyzing antibodies were previously detected in the blood of 80% to 90% of patients with systemic lupus erythematosus (SLE) and multiple sclerosis (MS). In addition, some similar neuropsychiatric indicators of disease common to SLE, MS, and SCZ were described in the literature. Thus, the destruction of the myelin sheath and the production of MBP-hydrolyzing antibodies can be a common phenomenon for some different diseases.
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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) | 0.001 | 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".