GR.2 Circulating plasma cytokines as biomarkers of inflammatory activity in radiologically isolated syndrome and Multiple Sclerosis
Bibliographic record
Abstract
Background: In multiple sclerosis (MS), soluble mediators of neuroinflammation are released by activated lymphocytes and resident immune cells, leading to demyelination and neurodegeneration. Radiologically isolated syndrome (RIS) is an entity in which white matter lesions fulfilling criteria for MS occur in individuals without any suggestive symptoms. The exact nature of pro- and anti-inflammatory cytokines in blood, and their association with disease activity in RIS/MS requires further clarification. Methods: Plasma was collected and cryopreserved from healthy controls (HCs), people with RIS and relapsing-remitting MS (RRMS) at the Barlo MS Centre. All samples were analyzed with OLink Target 96 Inflammation Multiplex Immunoassay Panel. Results: Individuals with RIS (p=0.0001; p= 0.0007; p= 0.0012) and RRMS (p<0.0001; p= 0.0003; p= 0.00112) had significantly higher concentrations of hepatocyte growth factor (HGF), interleukin-6 (IL-6), and chemokine ligand 23 (CCL23) in plasma compared to HCs, and patients with RRMS (p=0.0087) had significantly higher concentrations of HGF compared to individuals with RIS. Conclusions: Our study demonstrates that HGF, IL-6 and CCL23 are significantly increased in the plasma of patients with RIS and RRMS compared to HCs. Our observations suggest that the biology of MS is present in those with RIS, and these neuroinflammatory mediators may serve as a biomarker of disease activity.
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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".