Dijiao Tang; Qi Tang; Long Zhang; Hongxu Wang
Abstract
Background: Lupus nephritis (LN) is one of the most serious complications of systemic lupus erythematosus (SLE).The neutrophil to lymphocyte ratio (NLR) is a promising predictor and prognostic factor. An increased NLR is associated with a poor prognosis of several inflammatory diseases. Objective: ...
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Background: Lupus nephritis (LN) is one of the most serious complications of systemic lupus erythematosus (SLE).The neutrophil to lymphocyte ratio (NLR) is a promising predictor and prognostic factor. An increased NLR is associated with a poor prognosis of several inflammatory diseases. Objective: To evaluate the value of NLR in the diagnosis and pre-assessment of the disease severity of LN. Methods: This retrospective study included 88 patients with LN, 51 SLE patients without kidney involvement, 79 patients with primary chronic nephritis (CN), and 52 healthy controls (HC). The differences among these four groups and diagnostic value of NLR for patients with LN were evaluated. Results: The NLR of patients with LN before treatment was significantly higher than that of the other three groups. NLR positively correlated with C-reactive protein (CRP), complement 3(C3), C4, and serum creatinine (SCr) (CRP: r=0.337, p=0.007; C3: r=0.222, p=0.042; C4: r=0.230, p=0.035; SCr: r=0.408, p <0.0001) but negatively correlated with total serum IgG (r=-0.226, p=0.041). The level of NLR increased with the severity of renal dysfunction NLR (area under the curve: 0.785, 95% CI: 0.708-0.862) was useful for the diagnosis of LN, and its optimal cut-off value was 5.44 (sensitivity: 65.9%, specificity: 86.3%). Conclusions: NLR would be useful for the diagnosis of LN and reflects the severity of renal dysfunction Therefore, evaluating NLR before treatment could help clinicians to identify potential renal involvement in patients with SLE and distinguish LN from CN.
Weidong Xu; Zheng Chen; Xiaodong Shen; Chiheng Pi
Abstract
Background: Realgar, an arsenic tetrasulfide compound, is a highly recognized traditional Chinese medicinal prescription that has been widely used to treat various diseases such as inflammatory diseases. However, there are still some problems in the clinical treatment of Realgar, such as large oral dose ...
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Background: Realgar, an arsenic tetrasulfide compound, is a highly recognized traditional Chinese medicinal prescription that has been widely used to treat various diseases such as inflammatory diseases. However, there are still some problems in the clinical treatment of Realgar, such as large oral dose and high potential toxicity. Objective: To evaluate effects of Realgar nanoparticles on lupus nephritis (LN) in vivo in MRL/lpr mice. Methods: Ten-week mice were orally administered every day for eight consecutive weeks except the mice of normal model groups. The serum levels of anti-ds-DNA antibody IgG, IgM, IFN-γ, Creatinine (Cr), and blood urea nitrogen (BUN) were determined, and 24-hour urine protein was also measured. Renal inflammatory pathology analysis was assessed by hematoxylin-eosin (H&E) staining. The expression of phosphorylated signal transducer and activator of transcription 1 (p-STAT 1) and Janus Kinase 1 (JAK 1) in kidney tissue was determined by direct reverse transcriptase-polymerase chain reaction (RT-PCR) and immunohistochemistry (IHC). Results: The mice treated with Realgar nanoparticle in the high dose-treated (Realgar HD, 0.03 g/kg/d) group exhibited significantly reduced serum levels of anti-dsDNA (p<0.01), IgG (p<0.01), IgM (p<0.01), BUN (p<0.01), Cr (p<0.01), and inflammatory cytokine IFN-γ (p<0.01) as well as proteinuria (p<0.01) compared to the untreated model MRL/lpr mice. Additionally, high doses of Realgar nanoparticles significantly suppressed the phosphorylations of STAT 1 (p<0.01) and the renal pathological changes. Conclusions: The study indicates that Realgar nanoparticles may be a potential agent to treat LN, and the down-regulated p-STAT1 expression suggests that it may be one of the LN treatment targets for Realgar nanoparticles.
Jian-Ping Xiao; Xue-Rong Wang; Sen Zhang; Jun Wang; Chao Zhang; De-Guang Wang
