Adjuvant Immunotherapy of Experimental Autoimmune Encephalomyelitis: Immature Myeloid Cells Expressing CXCL10 and CXCL16 Attract CXCR3+CXCR6+ and Myelin-Specific T Cells to the Draining Lymph Nodes Rather Than the Central Nervous System
Bibliographic record
Abstract
CFA is a strong adjuvant capable of stimulating cellular immune responses. Paradoxically, adjuvant immunotherapy by prior exposure to CFA or live mycobacteria suppresses the severity of experimental autoimmune encephalomyelitis (EAE) and spontaneous diabetes in rodents. In this study, we investigated immune responses during adjuvant immunotherapy of EAE. Induction of EAE in CFA-pretreated mice resulted in a rapid influx into the draining lymph nodes (dLNs) of large numbers of CD11b(+)Gr-1(+) myeloid cells, consisting of immature cells with ring-shaped nuclei, macrophages, and neutrophils. Concurrently, a population of mycobacteria-specific IFN-γ-producing T cells appeared in the dLNs. Immature myeloid cells in dLNs expressed the chemokines CXCL10 and CXCL16 in an IFN-γ-dependent manner. Subsequently, CD4(+) T cells coexpressing the cognate chemokine receptors CXCR3 and CXCR6 and myelin oligodendrocyte glycoprotein (MOG)-specific CD4(+) T cells accumulated within the chemokine-expressing dLNs, rather than within the CNS. Migration of CD4(+) T cells toward dLN cells was abolished by depleting the CD11b(+) cells and was also mediated by the CD11b(+) cells alone. In addition to altering the distribution of MOG-specific T cells, adjuvant treatment suppressed development of MOG-specific IL-17. Thus, adjuvant immunotherapy of EAE requires IFN-γ, which suppresses development of the Th17 response, and diverts autoreactive T cells away from the CNS toward immature myeloid cells expressing CXCL10 and CXCL16 in the lymph nodes.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| 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".