Altered naive CD4 and CD8 T cell homeostasis in patients with relapsing-remitting multiple sclerosis: thymic<i>versus</i>peripheral (non-thymic) mechanisms
Bibliographic record
Abstract
We have reported previously that naive T cells from relapsing-remitting multiple sclerosis (RRMS) patients have T cell receptor (TCR) repertoire shifts, but the basis of these TCR repertoire shifts was uncertain. Here, we questioned whether RRMS patients have altered naive CD4 and CD8 T cell homeostasis by studying homeostatic proliferation and thymic production in RRMS patients and healthy controls. We measured thymic production by quantifying signal joint T cell receptor excision circles (sjTRECs). Both naive T subsets from controls showed an age-associated decrease in sjTRECs, i.e. evidence of progressive thymic involution, but we detected no age-associated decrease in sjTRECs in RRMS patients. Instead, naive CD8 T cells from patients had lower sjTRECs (P = 0.012) and higher Ki-67 proliferation levels (P = 0.04) than controls. Naive CD4 T cell sjTRECs did not differ between patients and controls. However, in RRMS these sjTRECs correlated strongly with CD31, a marker expressed by newly generated CD4 T cells but not by naive CD4 T cells that have undergone homeostatic proliferation. HLA-DR2 positivity correlated negatively with naive CD4 T cell CD31 expression in RRMS (P = 0.002). We conclude in RRMS that naive T subsets have homeostatic abnormalities due probably to peripheral (non-thymic) mechanisms. These abnormalities could have relevance for MS pathogenesis, as naive T cell changes may precede MS onset.
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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 | 0.000 | 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".