Immune mechanisms in multiple sclerosis: CD3 levels on CD28+ CD4+ T cells link antibody responses to human herpesvirus 6
Bibliographic record
Abstract
Compelling evidence suggests a significant association between antibody-mediated immune responses and multiple sclerosis (MS). However, the exact causal relationships between these immune responses and MS remain unclear. In this study, we conducted a comprehensive examination of the link between antibody-mediated immune responses and MS via Mendelian randomization (MR) analysis to identify specific infectious pathogens potentially involved in the onset and progression of MS. We compared immune cell infiltration between MS patients and control subjects. Furthermore, single-cell sequencing was employed to conduct a comparative analysis of the marker genes associated with each cell subtype between individuals diagnosed with MS and the control cohort. We revealed connections between antibody-mediated immune responses and immune cells , as well as the associations between these immune cells and MS. We discovered that CD3 levels on CD28 + CD4 + T cells significantly influence MS progression by altering the ratio of human herpesvirus 6 (HHV-6). These findings provide novel insights into the biological mechanisms underlying HHV–6–mediated MS.
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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 | 0.000 | 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".