Risk factors for non-diabetic renal disease in diabetic patients

Background. Diabetic patients with kidney disease have a high prevalence of non-diabetic renal disease (NDRD). Renal and patient survival regarding the diagnosis of diabetic nephropathy (DN) or NDRD have not been widely studied. The aim of our study is to evaluate the prevalence of NDRD in patients with diabetes and to determine the capacity of clinical and analytical data in the prediction of NDRD. In addition, we will study renal and patient prognosis according to the renal biopsy findings in patients with diabetes. Methods. Retrospective multicentre observational study of renal biopsies performed in patients with diabetes from 2002 to 2014. Results. In total, 832 patients were included: 621 men (74.6%), mean age of 61.7 6 12.8 years, creatinine was 2.8 6 2.2 mg/dL and proteinuria 2.7 (interquartile range: 1.2–5.4) g/24 h. About 39.5% (n ¼ 329) of patients had DN, 49.6% (n ¼ 413) NDRD and 10.8% (n ¼ 90) mixed forms. The most frequent NDRD was nephroangiosclerosis (NAS) (n ¼ 87, 9.3%). In the multivariate logistic regression analysis, older age [odds ratio (OR) ¼ 1.03, 95% CI: 1.02–1.05, P < 0.001], microhaematuria (OR ¼ 1.51, 95% CI: 1.03–2.21, P ¼ 0.033) and absence of diabetic retinopathy (DR) (OR ¼ 0.28, 95% CI: 0.19–0.42, P < 0.001) were independently associated with NDRD. Kaplan–Meier analysis showed that patients with DN or mixed forms presented worse renal prognosis than NDRD (P < 0.001) and higher mortality (P ¼ 0.029). In multivariate Cox analyses, older age (P < 0.001), higher serum creatinine (P < 0.001), higher proteinuria (P < 0.001), DR (P ¼ 0.007) and DN (P < 0.001) were independent risk factors for renal replacement therapy. In addition, older age (P < 0.001), peripheral vascular disease (P ¼ 0.002), higher creatinine (P ¼ 0.01) and DN (P ¼ 0.015) were independent risk factors for mortality. Conclusions. The most frequent cause of NDRD is NAS. Elderly patients with microhaematuria and the absence of DR are the ones at risk for NDRD. Patients with DN presented worse renal prognosis and higher mortality than those with NDRD. These results suggest that in some patients with diabetes, kidney biopsy may be useful for an accurate renal diagnosis and subsequently treatment and prognosis

A multilayered post-GWAS assessment on genetic susceptibility to pancreatic cancer

Funder: Fundación Científica Asociación Española Contra el Cáncer (ES)Funder: Cancer Focus Northern Ireland and Department for Employment and LearningFunder: Intramural Research Program of the Division of Cancer Epidemiology and Genetics, National Cancer Institute, USAAbstract: Background: Pancreatic cancer (PC) is a complex disease in which both non-genetic and genetic factors interplay. To date, 40 GWAS hits have been associated with PC risk in individuals of European descent, explaining 4.1% of the phenotypic variance. Methods: We complemented a new conventional PC GWAS (1D) with genome spatial autocorrelation analysis (2D) permitting to prioritize low frequency variants not detected by GWAS. These were further expanded via Hi-C map (3D) interactions to gain additional insight into the inherited basis of PC. In silico functional analysis of public genomic information allowed prioritization of potentially relevant candidate variants. Results: We identified several new variants located in genes for which there is experimental evidence of their implication in the biology and function of pancreatic acinar cells. Among them is a novel independent variant in NR5A2 (rs3790840) with a meta-analysis p value = 5.91E−06 in 1D approach and a Local Moran’s Index (LMI) = 7.76 in 2D approach. We also identified a multi-hit region in CASC8—a lncRNA associated with pancreatic carcinogenesis—with a lowest p value = 6.91E−05. Importantly, two new PC loci were identified both by 2D and 3D approaches: SIAH3 (LMI = 18.24), CTRB2/BCAR1 (LMI = 6.03), in addition to a chromatin interacting region in XBP1—a major regulator of the ER stress and unfolded protein responses in acinar cells—identified by 3D; all of them with a strong in silico functional support. Conclusions: This multi-step strategy, combined with an in-depth in silico functional analysis, offers a comprehensive approach to advance the study of PC genetic susceptibility and could be applied to other diseases

Artificial vision wireless PV system to efficiently track the MPP under partial shading

The solar photovoltaic industry is booming and the achievement of high efficiency in this kind of systems is crucial. Partial shading conditions complicate the search of the maximum power point (MPP) of the installations due to the existence of multiple peaks in the P-V curve. In addition, these photovoltaic (PV) systems require monitoring and control in real-time to guarantee the correct operation. Thus, this paper proposes a novel system to track the maximum power point through artificial vision, under partial shading conditions controlled and monitored by a wireless sensor network based on IEEE 802.15.4 technology. The infrastructure consists of a wireless distributed photovoltaic system (WDPS) where the power converter is connected to a sensor node that sends the information to the coordinator node. The coordinator node is connected to a webcam and a Raspberry Pi. This part of the system is called wireless webcam centralized control (WWCC) and is responsible for processing the sensors information and the images. Besides, the WWCC sends the control signal. The wireless communication is set in beacon-enabled mode allowing synchronization between the sensor nodes and the coordinator node. Moreover, the guaranteed time slot mechanism provides the correct transmission of data with low latency, ensuring the stability of the controller. Experimental tests have been carried out to validate the artificial vision wireless PV system. The results prove an appropriate operation, achieving an MPP tracking higher than 99%, even in partial shading conditions.Departamento de Ingeniería Eléctrica y TérmicaDepartamento de Ingeniería Electrónica, de Sistemas Informáticos y Automátic