Preferential recruitment of interferon‐γ–expressing T<sub>H</sub>17 cells in multiple sclerosis
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Bibliographic record
Abstract
OBJECTIVE: There is substantial evidence supporting the role of interferon (IFN)-gamma-producing T helper (T(H)) 1 and interleukin (IL)-17-expressing T(H)17 lymphocytes in multiple sclerosis (MS) and its animal model, experimental allergic encephalomyelitis (EAE). However, to date little is known about the potential cooperative interplay between these 2 cytokines. In the current study, we sought to evaluate the frequency of IFN-gamma-expressing T(H)17 lymphocytes in MS and EAE, and study their recruitment into the central nervous system (CNS). METHODS: Human T(H)17 lymphocytes were expanded in vitro from the blood of healthy controls and relapsing MS patients using IL-23. Immune cell migration to the CNS was assessed in vitro with primary cultures of human blood-brain barrier (BBB)-derived endothelial cells, and in vivo in EAE mice. RESULTS: We demonstrate that in response to IL-23, human memory lymphocytes expand into a T(H)17 phenotype, with a subpopulation of cells simultaneously expressing IFN-gamma and IL-17. We note that lymphocytes obtained from the blood of relapsing MS patients have an increased propensity to expand into IFN-gamma-producing T(H)17 cells and identify numerous T lymphocytes coexpressing IL-17 and IFN-gamma in brain tissue of MS patients. We also find lymphocytes expressing both the T(H)1- and the T(H)17-associated transcription factors ROR gamma t and T-bet, in situ and in vitro. We further provide in vitro and in vivo evidence that IFN-gamma(+) T(H)17 lymphocytes preferentially cross the human BBB and accumulate in the CNS of mice during the effector phase of EAE. INTERPRETATION: Our data underscore the involvement of IFN-gamma(+) T(H)17 lymphocytes in the pathology of MS and EAE and their preferential recruitment into the CNS during inflammatory events.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it