Interleukin-26, preferentially produced by T <sub>H</sub> 17 lymphocytes, regulates CNS barrier function
Bibliographic record
Abstract
Objective To investigate the involvement of interleukin (IL)-26 in neuroinflammatory processes in multiple sclerosis (MS), in particular in blood-brain barrier (BBB) integrity. Methods Expression of IL-26 was measured in serum, CSF, in vitro differentiated T helper (TH) cell subsets, and postmortem brain tissue of patients with MS and controls by ELISA, quantitative PCR, and immunohistochemistry. Primary human and mouse BBB endothelial cells (ECs) were treated with IL-26 in vitro and assessed for BBB integrity. RNA sequencing was performed on IL-26–treated human BBB ECs. Myelin oligodendrocyte glycoprotein35–55 experimental autoimmune encephalomyelitis (EAE) mice were injected IP with IL-26. BBB leakage and immune cell infiltration were assessed in the CNS of these mice using immunohistochemistry and flow cytometry. Results IL-26 expression was induced in TH lymphocytes by TH17-inducing cytokines and was upregulated in the blood and CSF of patients with MS. CD4+IL-26+ T lymphocytes were found in perivascular infiltrates in MS brain lesions, and both receptor chains for IL-26 (IL-10R2 and IL-20R1) were detected on BBB ECs in vitro and in situ. In contrast to IL-17 and IL-22, IL-26 promoted integrity and reduced permeability of BBB ECs in vitro and in vivo. In EAE, IL-26 reduced disease severity and proinflammatory lymphocyte infiltration into the CNS, while increasing infiltration of Tregs. Conclusions Our study demonstrates that although IL-26 is preferentially expressed by TH17 lymphocytes, it promotes BBB integrity in vitro and in vivo and is protective in chronic EAE, highlighting the functional diversity of cytokines produced by TH17 lymphocytes.
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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 | 0.000 | 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) | 0.002 | 0.001 |
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".