BackgroundChronic kidney disease (CKD) leads to end-stage renal failure and cardiovascular events. An attribute to these progressions is abnormalities in inflammation, which can be evaluated using the neutrophil-to-lymphocyte ratio (NLR). We aimed to investigate the association of NLR with the progression of end stage of renal disease (ESRD), cardiovascular disease (CVD) and all-cause mortality in Chinese patients with stages 1–4 CKD.MethodsPatients with stages 1–4 CKD (18–74 years of age) were recruited at 39 centers in 28 cities across 22 provinces in China since 2011. A total of 938 patients with complete NLR and other relevant clinical variables were included in the current analysis. Cox regression analysis was used to estimate the association between NLR and the outcomes including ESRD, CVD events or all-cause mortality.ResultsBaseline NLR was related to age, hypertension, serum triglycerides, total serum cholesterol, CVD history, urine albumin to creatinine ratio (ACR), chronic kidney disease-mineral and bone disorder (CKD-MBD), hyperlipidemia rate, diabetes, and estimated glomerular filtration rate (eGFR). The study duration was 4.55 years (IQR 3.52–5.28). Cox regression analysis revealed an association of NLR and the risk of ESRD only in patients with stage 4 CKD. We did not observe any significant associations between abnormal NLR and the risk of either CVD or all-cause mortality in CKD patients in general and CKD patients grouped according to the disease stages in particular.ConclusionOur results suggest that NLR is associated with the risk of ESRD in Chinese patients with stage 4 CKD. NLR can be used in risk assessment for ESRD among patients with advanced CKD; this application is appealing considering NLR being a routine test.Trial registration ClinicalTrials.gov Identifier NCT03041987. Registered January 1, 2012. (retrospectively registered) (https://www.clinicaltrials.gov/ct2/show/NCT03041987?term=Chinese+Cohort+Study+of+Chronic+Kidney+Disease+%28C-STRIDE%29&rank=1)Electronic supplementary materialThe online version of this article (10.1186/s12967-019-1808-4) contains supplementary material, which is available to authorized users.

Krüppel-like factor 4 (KLF4) is a transcription factor which plays divergent roles in a number of physiological or pathological process. However, the expression and role of KLF4 in renal fibrosis remain undetermined. The aim of the present study was to determine the epigenetic alterations of KLF4 and its potential role and mechanisms of action in epithelial-to-mesenchymal transition (EMT) in renal fibrosis. The hypermethylation of the KLF4 promoter accompanied by a decrease in KLF4 expression were observed in mice subjected to unilateral ureteral obstruction (UUO) and in HK-2 cells stimulated with transforming growth factor (TGF)-β1. However, treatment with 5-aza-2′-deoxycytidine attenuated the TGF-β1-induced downregulation of KLF4 and E-cadherin and the upregulation of α-smooth muscle actin (α-SMA) in the HK-2 cells. DNA methyltransferase 1 (Dnmt1) participated in the TGF-β1-mediated hypermethylation of the KLF4 promoter in the HK-2 cells. In addition, functional analysis demonstrated that the overexpression of KLF4 led to an increase in the expression of E-cadherin and zonula occludens-l (ZO-1), and a decrease in the expression of α-SMA and fibroblast-specific protein 1 (FSP-1), thus reversing the effects of the suppression of KLF4. These data suggest that KLF4 inhibits the progression of EMT in renal epithelial cells. In conclusion, our findings demonstrate that KLF4 is downregulated during EMT in renal fibrosis in vivo and in vitro; thus, KLF4 functions as a suppressor of renal fibrogenesis. The hypermethylation of KLF4 directly mediated by Dnmt1 contributes to the progression of EMT in renal epithelial cells. KLF4 promoter methylation may thus be a promising diagnostic marker or therapeutic target in renal fibrosis.

In situ combustion (ISC) is an important thermal recovery technique. Significant open ISC questions include the effect of coke formation on the pore structure and permeability. In the study, an experimental apparatus was constructed to not only physically simulate coke formation similar to the crude oil ISC process but also to in situ measure postdeposition permeability. Effects on coke deposition with the Xinjiang crude oil were studied, including reaction atmosphere, temperature, and time. The results indicate that the critical coking temperature differs significantly by at least 200 °C between low-temperature oxidation (LTO) runs with air flow and coking runs with nitrogen flow for the Xinjiang crude oil. The coke generation promoted by LTO and the coke consumption via high-temperature oxidation (HTO) result in a maximum coke production with temperature in the LTO runs. In addition, the study found that many resins and the small amount of asphaltenes in the Xinjiang crude oil prolonged the induction coking period in the coking runs. This understanding of the coke deposition process led to the production of core samples with different amounts of coke deposition for selected reaction conditions. The pore structure of the coked grain clusters was viewed with a scanning electron microscopy (SEM) and mercury porosimeters. The results showed the complicated pore structure and increasing number of micropores with increasing coke deposition, which not only reduced the permeability rapidly so that it deviated from the Kozeny–Carman relationship at the Darcy scale but also further promoted the Klinkenberg effect. In addition, the global permeability damage would be further underestimated regardless of the coke concentration heterogeneity in the core samples. The permeability change was then correlated with coke deposition for numerical simulations of ISC or ToeHeel Air Injection (THAI) processes in sandstone reservoirs.

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Background. microRNA (miRNA, miR) are thought to interact with multiple mRNAs which are involved in the EMT process. But the role of miRNAs in peritoneal fibrosis has remained unknown. Objective. To determine if miRNA589 regulates the EMT induced by TGFβ1 in human peritoneal mesothelial cell line (HMrSV5 cells). Methods. 1. Level of miR589 was detected in both human peritoneal mesothelial cells (HPMCs) isolated from continuous ambulatory peritoneal dialysis (CAPD) patients' effluent and HMrSV5 cells treated with or without TGFβ1. 2. HMrSV5 cells were divided into three groups: control group, TGFβ1 group, and pre-miR-589+TGFβ1 group. The level of miRNA589 was determined by realtime PCR. The expressions of ZO-1, vimentin, and E-cadherin in HPMCs were detected, respectively. Results. Decreased level of miRNA589 was obtained in either HPMCs of long-term CAPD patients or HMrSV5 cells treated with TGFβ1. In vitro, TGFβ1 led to upregulation of vimentin and downregulation of ZO-1 as well as E-cadherin in HMrSV5 cells, which suggested EMT, was induced. The changes were accompanied with notably decreased level of miRNA589 in HMrSV5 cells treated with TGFβ1. Overexpression of miRNA589 by transfection with pre-miRNA589 partially reversed these EMT changes. Conclusion. miRNA589 mediates TGFβ1 induced EMT in human peritoneal mesothelial cells.

Artificial intelligence (AI), as an advanced science technology, has been widely used in medical fields to promote medical development, mainly applied to early detections, disease diagnoses, and management. Owing to the huge number of patients, kidney disease remains a global health problem. Challenges remain in its diagnosis and treatment. AI could take individual conditions into account, produce suitable decisions and promise to make great strides in kidney disease management. Here, we review the current studies of AI applications in kidney disease in alerting systems, diagnostic assistance, guiding treatment and evaluating prognosis. Although the number of studies related to AI applications in kidney disease is small, the potential of AI in the management of kidney disease is well recognized by clinicians; AI will greatly enhance clinicians' capacity in their clinical practice in the future.

Trajectory data are prevalent in systems that monitor the locations of moving objects. In a location-based service, for instance, the positions of vehicles are continuously monitored through GPS; the trajectory of each vehicle describes its movement history. We study joins on two sets of trajectories, generated by two sets M and R of moving objects. For each entity in M , a join returns its k nearest neighbors from R. We examine how this query can be evaluated in cloud environments. This problem is not trivial, due to the complexity of the trajectory, and the fact that both the spatial and temporal dimensions of the data have to be handled. To facilitate this operation, we propose a parallel solution framework based on MapReduce. We also develop a novel bounding technique, which enables trajectories to be pruned in parallel. Our approach can be used to parallelize existing single-machine trajectory join algorithms. To evaluate the efficiency and the scalability of our solutions, we have performed extensive experiments on a real dataset.