Do increased serum IL-12 and IL-23 levels affect cognitive function in patients with multiple sclerosis? A preliminary study
Bibliographic record
Abstract
Aim of the study: To compare the serum levels of IL-12 and IL-23 between healthy volunteers and patients with multiple sclerosis with regard to their cognitive function. Materials and methods: A total of 21 patients with multiple sclerosis and 21 healthy individuals were enrolled into the study. The individuals were age- and sex-matched. Each participant was evaluated using the Montreal Cognitive Assessment (MoCA), the Beck Depression Inventory (BDI), and the Pittsburgh Sleep Quality Index (PSQI). The enzyme-linked immunosorbent assay was performed to assess the serum levels of IL-12 and IL-23. Results: The concentration of IL-12 was 1.61 ± 4.61 pg/mL in the group of patients with multiple sclerosis and 1.78 ± 3.54 pg/mL in the control group, p = 0.5009. The concentration of IL-23 was 19.04 ± 75.50 pg/mL in the study group and 5.50 ± 14.4 pg/mL in the control group, p = 0.5170. A significant difference was found between the control and study groups in the MoCA cognitive test (28 vs. 24 points, respectively, p < 0.0001). There was no significant difference in the Beck Depression Inventory and PSQI between the control and study groups. No significant correlations were found between the IL-12/IL-23 serum levels and psychological evaluations. Conclusions and clinical implications: The results obtained indicate that IL-12 and IL-23 may not play a role in the development of cognitive impairment. The assessment of cognitive impairment in patients with multiple sclerosis may have a screening value in preventing their cognitive deterioration.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".