Leukotriene B4 Protects Latently Infected Mice against Murine Cytomegalovirus Reactivation following Allogeneic Transplantation
Bibliographic record
Abstract
Human CMV is often associated with transplant rejection and opportunistic infections such as pneumonia in immunosuppressed patients. Current anti-CMV therapies, although effective, show relatively high toxicity, which seriously limits their long-term use. In this study, we provide evidence that leukotriene B(4) (LTB(4)) plays an important role in the fight against murine CMV (MCMV) infection in vivo. Intravenous administration of 50 and 500 ng/kg/day of LTB(4) to mice infected with a lethal dose of MCMV significantly increases their survival (50 and 70%, respectively), compared with the placebo-treated group (10% of survival). In mice infected with a sublethal dose of MCMV and treated daily with 50 ng/kg/day of LTB(4), the salivary gland viral loads were found to be reduced by 66% compared with the control group. Furthermore, using an allogeneic bone marrow transplantation mouse model, the frequency of MCMV reactivation from latently infected mice was much lower (38%) in LTB(4) (500 ng/kg)-treated mice than in the placebo-treated group (78%). Finally, in experiments using 5-lipoxygenase-deficient mice, MCMV viral loads in salivary glands were found to be higher in animals unable to produce leukotrienes than in the control groups, supporting a role of endogenous 5-lipoxygenase products, possibly LTB(4), in host defense against CMV infection.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".