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Here, we sought to explore the underlying role of interleukin (IL)-8 in neutrophil extracellular traps (NETs) formation during atherosclerosis (AS). The concentration of pro-inflammatory cytokines IL-8, IL-6 and IL-1β was determined by enzyme-linked immunosorbent assay (ELISA). NETs formation was evaluated by immunofluorescence and myeloperoxidase (MPO)-DNA complex ELISA. The mRNA levels of IL-8 and Toll-like receptor 9 (TLR9) were measured by quantitative real-time PCR (qRT-PCR). The phosphorylation levels of NF-κB p65 were detected by western blotting. The hematoxylin and eosin (H&E) staining of atherosclerotic lesion areas was performed in ApoE-deficiency mice. Results showed that patients with AS showed higher serum levels of IL-8, a pro-inflammatory cytokine and NETs. IL-8 interacted with its receptor CXC chemokine receptor 2 (CXCR2) on neutrophils, leading to the formation of NETs via Src and extracellular signal-regulated kinase (ERK) and p38 mitogen-activated protein kinases (MAPK) signaling to aggravate AS progression in vivo. PMA-induced NETosis directly upregulated the TLR9/NF-κB pathway in macrophages and subsequently initiated the release of IL-8. Our data reveal a neutrophil-macrophage interaction in AS progression, and indicate that NETs represent as a novel therapeutic target in treatment of AS and other cardiovascular diseases (CVD).

Crescentic IgA nephropathy (IgAN), defined as .50% crescentic glomeruli on kidney biopsy, is one of the most common causes of rapidly progressive GN. However, few studies have characterized this condition. To identify risk factors and develop a prediction model, we assessed data from patients$14 years old with crescentic IgAN who were followed $12 months. The discovery cohort comprised 52 patients from one kidney center, and the validation cohort comprised 61 patients from multiple centers. At biopsy, the mean serum creatinine (SCr) level 6 SD was 4.363.4 mg/dl, and the mean percentage of crescents was 66.4%615.8%. The kidney survival rates at years 1, 3, and 5 after biopsy were 57.4%64.7%, 45.8%65.1%, and 30.4%66.6%, respectively. Multivariate Cox regression revealed initial SCr as the only independent risk factor for ESRD (hazard ratio [HR], 1.32; 95% confidence interval [CI], 1.10 to 1.57; P=0.002). Notably, the percentage of crescents did not associate independently with ESRD. Logistic regression showed that the risk of ESRD at 1 year after biopsy increased rapidly at SCr.2.7 mg/dl and reached 90% at SCr.6.8 mg/dl (specificity=98.5%, sensitivity=64.6% for combined cohorts). In both cohorts, patients with SCr.6.8 mg/dl were less likely to recover from dialysis. Analyses in additional cohorts revealed a similar association between initial SCr and ESRD in patients with antiglomerular basement membrane disease but not ANCA-associated systemic vasculitis. In conclusion, crescentic IgAN has a poor prognosis, and initial SCr concentration may predict kidney failure in patients with this disease.

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The Dempster-Shafer (DS) theory is a powerful tool for probabilistic reasoning based on a formal calculus for combining evidence. DS theory has been widely used in computer science and engineering applications, but has yet to reach the statistical mainstream, perhaps because the DS belief functions do not satisfy long-run frequency properties. Recently, two of the authors proposed an extension of DS, called the weak belief (WB) approach, that can incorporate desirable frequency properties into the DS framework by systematically enlarging the focal elements. The present paper reviews and extends this WB approach. We present a general description of WB in the context of inferential models, its interplay with the DS calculus, and the maximal belief solution. New applications of the WB method in two high-dimensional hypothesis testing problems are given. Simulations show that the WB procedures, suitably calibrated, perform well compared to popular classical methods. Most importantly, the WB approach combines the probabilistic reasoning of DS with the desirable frequency properties of classical statistics.