Interleukin‐1β promotes oligodendrocyte death through glutamate excitotoxicity
Bibliographic record
Abstract
Glutamate excitotoxicity is implicated in the progressive loss of oligodendrocytes in multiple sclerosis, but how glutamate metabolism is dysregulated in the disease remains unclear. Because there is microglia activation in all stages of multiple sclerosis, we determined whether a microglia product, interleukin-1beta, could provide the mechanism for glutamate excitotoxicity. We found that whereas interleukin-1beta did not kill oligodendrocytes in pure culture, it produced apoptosis of oligodendrocytes in coculture with astrocytes and microglia. This requirement for a mixed glia environment suggests that interleukin-1beta impairs the well-described glutamate-buffering capacity of astrocytes. In support, antagonists at AMPA/kainate glutamate receptors, NBQX and CNQX, blocked the interleukin-1beta toxicity to oligodendrocytes. Another microglia/macrophage cytokine, tumor necrosis factor-alpha, also evoked apoptosis of oligodendrocytes in a mixed glia environment in an NBQX-blockable manner. These results provide a mechanistic link between the persistent and insidious microglia activation that is evident in all stages of multiple sclerosis, with the recent appreciation that glutamate excitotoxicity leads to the destruction of oligodendrocytes in the disease.
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 | 0.000 | 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".