Association between serum resistin level and outcomes in kidney transplant recipients.

Resistin is an adipocytokine that is associated with inflammation, coronary artery disease, and other types of cardiovascular disease among patients with normal kidney function. However, little is known about the association of resistin with outcomes in kidney transplant recipients. We collected socio-demographic and clinical parameters, medical and transplant history, and laboratory data from 988 prevalent kidney transplant recipients enrolled in the Malnutrition-Inflammation in Transplant-Hungary Study (MINIT-HU study). Serum resistin levels were measured at baseline. Associations between serum resistin level and death with a functioning graft over a 6-year follow-up period were examined in unadjusted and adjusted models. The mean±SD age of the study population was 51 ± 13 years, among whom 57% were men and 21% were diabetics. Median serum resistin concentrations were significantly higher in patients who died with a functioning graft as compared to those who did not die during the follow-up period (median [IQR]: 22[15-26] vs. 19[14-22] ng/ml, respectively; P < 0.001). Higher serum resistin level was associated with higher mortality risk in both unadjusted and fully adjusted models: HRs (95% CI): 1.33(1.16-1.54) and 1.21(1.01-1.46), respectively. In prevalent kidney transplant recipients, serum resistin was an independent predictor of death with a functioning graft

A multi-chanel electrical impedance meter based on digital lock-in technology

Abstract The presented multichannel measuring system working on various frequencies is suitable either for electrical impedance spectroscopy or tomography. The authors of this paper have developed the complete measurement system and a graphical user interface platform. The accuracy of impedance amplitude and phase are 1 ppm and 0.01°, respectively. The basic instrument works with 8 channels and can be expanded to 64 channels with the application of multiplexing or multiple parallel connected instruments in the same system

nucleAIzer : A Parameter-free Deep Learning Framework for Nucleus Segmentation Using Image Style Transfer

Single-cell segmentation is typically a crucial task of image-based cellular analysis. We present nucleAIzer, a deep-learning approach aiming toward a truly general method for localizing 2D cell nuclei across a diverse range of assays and light microscopy modalities. We outperform the 739 methods submitted to the 2018 Data Science Bowl on images representing a variety of realistic conditions, some of which were not represented in the training data. The key to our approach is that during training nucleAIzer automatically adapts its nucleus-style model to unseen and unlabeled data using image style transfer to automatically generate augmented training samples. This allows the model to recognize nuclei in new and different experiments efficiently without requiring expert annotations, making deep learning for nucleus segmentation fairly simple and labor free for most biological light microscopy experiments. It can also be used online, integrated into CellProfiler and freely downloaded at www.nucleaizer.org. A record of this paper's transparent peer review process is included in the Supplemental Information.Peer reviewe

Firefighter Safety for PV Systems:A Solution for the Protection of Emergency Responders from Hazardous dc Voltage

An important and highly discussed safety issue for photovoltaic (PV) systems is that as long as the PV panels are illuminated, a high voltage is present at the PV string terminals and cables between the string and inverters that is independent of the state of the inverter's dc disconnection switch. The presence of these energized conductors on the dc side of the PV system can pose a danger to anyone performing maintenance or firefighting.</p