Immunoregulatory Role of Nitric Oxide in Kilham Rat Virus-Induced Autoimmune Diabetes in DR-BB Rats
Bibliographic record
Abstract
Macrophages play a critical role in the pathogenesis of Kilham rat virus (KRV)-induced autoimmune diabetes in diabetes-resistant BioBreeding (DR-BB) rats. This investigation was initiated to determine the role of macrophage-derived soluble mediators, particularly NO, in the pathogenesis of KRV-induced diabetes in DR-BB rats. We found that the expression of inducible NO synthase (iNOS), an enzyme responsible for NO production, was significantly increased during the early phase of KRV infection. Inhibition of iNOS by aminoguanidine (AG) treatment resulted in the prevention of diabetes in KRV-infected animals. The expression of IL-1beta, TNF-alpha, and IL-12 was significantly decreased in the spleen of AG-treated, KRV-infected DR-BB rats compared with PBS-treated, KRV-infected control rats. Subsequent experiments revealed that AG treatment exerted its preventive effect in KRV-infected rats by maintaining the finely tuned immune balance normally disrupted by KRV, evidenced by a significant decrease in the expression of IFN-gamma, but not IL-4, and a decrease in Th1-type chemokine receptors CCR5, CXCR3, and CXCR4. We also found that iNOS inhibition by AG decreased the KRV-induced expression of MHC class II molecules and IL-2R alpha-chain, resulting in the suppression of T cell activation, evidenced by the decreased cytolytic activity of CD8(+) T cells. We conclude that NO plays a critical immunoregulatory role by up-regulating macrophage-derived proinflammatory cytokines, up-regulating the Th1 immune response, and activating T cells, leading to type 1 diabetes after KRV infection, whereas suppression of NO production by AG treatment prevents KRV-induced autoimmune diabetes in DR-BB rats.
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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 | 0.001 | 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".