Effect of Pretreatment with Toll‐like Receptor Agonists in a Mouse Model of Herpes Simplex Virus Type 1 Encephalitis
Bibliographic record
Abstract
BACKGROUND: We evaluated the effect of pretreatment with Toll-like receptor (TLR) agonists in a mouse model of herpes simplex virus type 1 (HSV-1) encephalitis. METHODS: BALB/c mice received a single intraperitoneal or intranasal injection of polyinosinic:polycytidylic acid (poly I:C), a TLR3 agonist; lipopolysaccharide (LPS), a TLR4 agonist; oligodeoxynucleotide (ODN), a TLR9 agonist; or control vehicle. Twenty-four hours later, animals were infected with 5000 plaque-forming units of HSV-1. RESULTS: Mice that received intraperitoneal pretreatment with vehicle, LPS, and poly I:C had survival rates of 7%, 13%, and 56%, respectively, and mean life expectancies of 156.80+/-9.56, 176.00+/-9.24, and 213.00+/-7.71 h, respectively (p< .05, poly I:C group vs. other groups). Similarly, intranasal pretreatment with vehicle, LPS, ODN, and poly I:C were associated with survival rates of 20%, 47%, 60%, and 94%, respectively, and mean life expectancies of 153.60+/-11.71, 188.80+/-12.97, 204.80+/-11.73, and 234.00+/-5.81 h, respectively (p< .05, ODN and poly I:C groups vs. vehicle group). Pretreatment with intranasal poly I:C induced early expression of several immune genes in the brain and resulted in a significantly lower virus load. CONCLUSION: TLR3 stimulation by poly I:C 24 h before infection reinforces a natural innate immune mechanism of neuroprotection against HSV-1.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".