Tumor Necrosis Factor–α and Interleukin‐1β Play a Critical Role in the Resistance against Lethal Herpes Simplex Virus Encephalitis
Bibliographic record
Abstract
BACKGROUND: The innate immune response after herpes simplex type 1 (HSV-1) encephalitis could be protective or, paradoxically, implicated in neuronal damage. We investigated the role of the innate immune response in such infection using a C57BL/6 mouse knockout (KO) model for tumor necrosis factor (TNF)-alpha and/or interleukin (IL)-1beta. METHODS: Encephalitis was induced by intranasal infection with a clinical strain of HSV-1 in 1-month-old KO or wild-type (WT) mice. Mice were monitored for survival, brain viral load was quantified by real-time polymerase chain reaction, and the inflammatory response was assessed by in situ hybridization in groups of mice killed on days 3-7. RESULTS: WT mice had a significantly higher mean life expectancy (P=.0001, log-rank test) than other groups. IL-1beta and TNF-alpha KO mice had a similar mean life expectancy, and encephalitis was lethal to all TNF-alpha /IL-1beta-deficient mice. Brain viral loads were lower in WT than in KO mice that had disseminated viral replication in the pons and medulla. Moreover, TNF- alpha and IL-1beta KO mice failed to initiate an adequate immune response, as shown by the virtual absence of expression of proinflammatory molecules in the brain. CONCLUSION: These data clearly demonstrate the importance of TNF-alpha and IL-1beta in protection against HSV-1 encephalitis in this mouse model.
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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 | 0.001 |
| 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".