Type 17 Immune Response Facilitates Progression of Inflammation and Correlates with Cognition in Stable Schizophrenia
Bibliographic record
Abstract
Dysregulation of the type 17 immune pathway has already been considered in schizophrenia and we previously measured decreased sera values of interleukin (IL)-17 in early stages. We further explored the possible correlation of IL-17 systemic levels with proinflammatory cytokines and cognitive scores and additionally analyzed the percentage of IL-17 producing lymphocytes in peripheral blood of patients with stable schizophrenia. We included 27 patients diagnosed with schizophrenia (F20), after a three-month stable depot antipsychotic therapy (risperidone or paliperidone) and 18 healthy control subjects. Positive and Negative Syndrome Scale of Schizophrenia and the Montreal-Cognitive Assessment (MoCA) were conducted. Sera concentrations of IL-17, IL-6, tumor necrosis factor alpha (TNF-α) and soluble ST2 receptor (sST2) were measured. Flow cytometry and Natural Killer (NK) and T cell analyses were done in 10 patients and 10 healthy controls. Moderate positive correlation was established between IL-17 and TNF-α (r = 0.640; p = 0.001), IL-17 and IL-6 (r = 0.514; p = 0.006), IL-17 and sST2 (r = 0.394; p = 0.042). Furthermore, a positive correlation between the serum levels of IL-17 and MoCA scores was observed, especially with visuospatial and executive functioning, as well as language functioning and delayed recall (p < 0.05). Significantly higher percentage of IL-17 producing CD56+ NK cells was measured in peripheral blood of patients with schizophrenia in remission vs. healthy individuals (p = 0.001). The percentage of CD4+ T cells and CD4+ T cells that produce IL-17 was significantly increased in patients (p = 0.001). This study revealed the involvement of innate type 17 immune response in the progression of inflammation and this could be related to cognitive functioning in stable 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 | 0.000 | 0.001 |
| 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".