Pro-inflammatory T helper 17 directly harms oligodendrocytes in neuroinflammation
Bibliographic record
Abstract
T helper (Th)17 cells are considered to contribute to inflammatory mechanisms in diseases such as multiple sclerosis (MS). However, the discussion persists regarding their true role in patients. Here, we visualized central nervous system (CNS) inflammatory processes in models of MS live in vivo and in MS brains and discovered that CNS-infiltrating Th17 cells form prolonged stable contact with oligodendrocytes. Strikingly, compared to Th2 cells, direct contact with Th17 worsened experimental demyelination, caused damage to human oligodendrocyte processes, and increased cell death. Importantly, we found that in comparison to Th2 cells, both human and murine Th17 cells express higher levels of the integrin CD29, which is linked to glutamate release pathways. Of note, contact of human Th17 cells with oligodendrocytes triggered release of glutamate, which induced cell stress and changes in biosynthesis of cholesterol and lipids, as revealed by single-cell RNA-sequencing analysis. Finally, exposure to glutamate decreased myelination, whereas blockade of CD29 preserved oligodendrocyte processes from Th17-mediated injury. Our data provide evidence for the direct and deleterious attack of Th17 cells on the myelin compartment and show the potential for therapeutic opportunities in MS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".