Tumor Necrosis Factor α But Not Interleukin 1β Mediates Neuroprotection in Response to Acute Nitric Oxide Excitotoxicity
Bibliographic record
Abstract
Neurodegenerative processes in the brain are accompanied by activation of innate immunity, which involves the release of proinflammatory cytokines by microglia and infiltrating macrophages. The beneficial or detrimental roles of these cytokines, including interleukin 1beta (IL-1beta) and tumor necrosis factor alpha (TNF-alpha), remain to be clarified. These cytokines have numerous overlapping activities that make it difficult to interpret data generated by mice that have a mutation in the gene encoding either TNF-alpha or IL-1beta. To remediate the problem, we generated a mouse that bears a mutation in both genes and exposed them to an acute neurotoxic insult. Intracerebral infusion with the nitric oxide donor sodium nitroprusside (SNP) caused neurodegeneration and demyelination that were markedly increased in the brain of TNF-alpha- and IL-1beta/TNF-alpha-deficient mice compared with IL-1beta-deficient and wild-type mice. Surprisingly, TNF and double mutants exhibited an early (6 h after SNP injections) blunted microglial activation followed by an exaggerated response later on (4 d later). No differences were found in the brain of the IL-1beta knock-out and wild-type groups. This suggests a crucial role for TNF-alpha in mediating microglial reactivity to acute injury. An immediate response clearly helps eliminate cell debris, restrict subsequent damages, and restore homeostasis. These findings may have direct implications for the use anti-inflammatory drugs in acute neurodegenerative and demyelinating disorders.
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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) | 0.001 | 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 | 0.001 |
| 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".