Distribution of Th17 cells and Th1 cells in peripheral blood and cerebrospinal fluid in chronic inflammatory demyelinating polyradiculoneuropathy
Bibliographic record
Abstract
Chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) is an immune-mediated demyelinating disease of the peripheral nervous system. Th17 and Th1 cells contribute to the pathogenesis of most autoimmune diseases, but little is known about their distribution and reciprocal relationship in CIDP. In this study, we analyzed the distribution of Th17, Th1, and Th17/Th1 cells in the peripheral blood and cerebrospinal fluid (CSF). The results showed that the frequency of Th17 cells was significantly higher in the peripheral blood mononuclear cell (PBMCs) and CSF of active CIDP in comparison with remitting CIDP or to other non-inflammatory neurological diseases (ONDs), accompanied by similar findings for Th17/Th1 cells. Both active and remitting CIDP have higher percentage of Th1 cells in the CSF than OND. CSF protein levels positively correlated with the frequencies of Th17 cells either in the PBMCs or CSF of active CIDP, while there was no significant correlation with Th1 cells. In line with these observations, the levels of interleukin-17 (IL-17) in plasma and transcript factors retinoic acid receptor-related orphan receptor (ROR)γt expressed by PBMCs were significantly higher in the active CIDP than remitting CIDP or OND. In summary, our preliminary findings suggest that elevated numbers of inflammatory T cells, especially for Th17 cells, might be an important determinant in the evolution of CIDP.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".