Type 2 Monocyte and Microglia Differentiation Mediated by Glatiramer Acetate Therapy in Patients with Multiple Sclerosis
Bibliographic record
Abstract
Glatiramer acetate (GA) therapy of patients with multiple sclerosis (MS) represents a unique setting in which in vivo Th2 deviation of T cells is consistently observed and associated with clinical benefit in a human autoimmune disease. We postulated that APCs are important targets of GA therapy and demonstrate that treatment of MS patients with GA reciprocally regulates the IL-10/IL-12 cytokine network of monocytes in vivo. We further show that Th1- or Th2-polarized GA-reactive T cells isolated from untreated or treated MS patients mediate type 1 and 2 APC differentiation of human monocytes, based on their ability to efficiently induce subsequent Th1 and Th2 deviation of naive T cells, respectively. These observations are extended to human microglia, providing the first demonstration of type 2 differentiation of CNS-derived APCs. Finally, we confirm that the fundamental capacity of polarized T cells to reciprocally modulate APC function is not restricted to GA-reactive T cells, thereby defining a novel and dynamic positive feedback loop between human T cell and APC responses. In the context of MS, we propose that GA therapy results in the generation of type 2 APCs, contributing to Th2 deviation both in the periphery and in the CNS of MS patients. In addition to extending insights into the therapeutic mode of action of GA, our findings revisit the concept of bystander suppression and underscore the potential of APCs as attractive targets for therapeutic immune modulation.
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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".