B Cell-Derived IL-15 Enhances CD8 T Cell Cytotoxicity and Is Increased in Multiple Sclerosis Patients
Bibliographic record
Abstract
Multiple lines of evidence suggest that CD8 T cells contribute to the pathogenesis of multiple sclerosis (MS). However, the sources and involvement of cytokines such as IL-15 in activating these cells is still unresolved. To investigate the role of IL-15 in enhancing the activation of CD8 T cells in the context of MS, we determined cell types expressing the bioactive surface IL-15 in the peripheral blood of patients and evaluated the impact of this cytokine on CD8 T cell cytotoxicity and migration. Flow cytometric analysis showed a significantly greater proportion of B cells and monocytes from MS patients expressing IL-15 relative to controls. We established that CD40L activation of B cells from healthy donors increased their IL-15 levels, reaching those of MS patients. We also demonstrated an enhanced cytotoxic profile in CD8 T cells from MS patients upon stimulation with IL-15. Furthermore, we showed that IL-15 expressed by B cells and monocytes is sufficient and functional, enhancing granzyme B production by CD8 T cells upon coculture. Exposure of CD8 T cells to this cytokine enhanced their ability to kill glial cells as well as to migrate across an in vitro inflamed human blood-brain barrier. The elevated levels of IL-15 in patients relative to controls, the greater susceptibility of CD8 T cells from patients to IL-15, in addition to the enhanced cytotoxic responses by IL-15-exposed CD8 T cells, stresses the potential of therapeutic strategies to reduce peripheral sources of IL-15 in 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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".