Erythroferrone (ERFE) is a hepcidin inhibitor whose synthesis is stimulated by erythropoietin, which increases iron absorption and mobilization. We studied the association between serum ERFE and mortality and non-fatal cardiovascular (CV) events in a cohort of 1123 hemodialysis patients and in a cohort of 745 stage 1–5 chronic kidney disease (CKD) patients. Erythroferrone was measured by a validated enzyme-linked immunosorbent assay (ELISA). In the hemodialysis cohort, serum ERFE associated directly with erythropoiesis stimulating agents (ESA) dose (p < 0.001) and inversely with serum iron and ferritin (p < 0.001). Erythroferrone associated with the combined outcome in an analysis adjusting for traditional risk factors, factors peculiar to end-stage kidney disease, serum ferritin, inflammation, and nutritional status (HR, hazard ratio, (5 ng/mL increase: 1.04, 95% confidence interval, CI: 1.01–1.08, p = 0.005). Furthermore, treatment with ESA modified the relationship between ERFE and the combined end-point in adjusted analyses (p for the effect modification = 0.018). Similarly, in CKD patients there was a linear increase in the risk for the same outcome in adjusted analyses (HR (2 ng/mL increase): 1.04, 95% CI: 1.0–1.07, p = 0.015). Serum ERFE is associated with mortality and CV events in CKD and in HD patients, and treatment by ESA amplifies the risk for this combined end-point in HD patients.

Endothelial dysfunction (ED) starts early in chronic kidney disease (CKD) and is the hallmark of atherosclerosis in these patients. During recent years, numerous markers have emerged, aiming to predict the onset of ED in CKD patients. Therefore, there is a need to evaluate and assess the discriminatory ability (or diagnostic accuracy) of such a marker (i.e., the ability to correctly classify individuals as having a given disease or not) and identify the optimal cut-off value. A receiver operating characteristic (ROC) curve analysis has been used in the majority of the research papers evaluating the predictive ability of a marker of ED. It is a graphical plot combining pairs of sensitivity (true positive rate) on the y axis and the complement of specificity (1—specificity, false positive rate) in the x axis, corresponding to several of the cut-off values covering the complete range of possible values that this test/marker might take. Herein, using a series of practical examples derived from clinical studies on ED in the special population of CKD, we address the principles, fundamentals, advantages and limitations regarding the interpretation of the ROC analysis.

A known issue in teleoperation concerns dexterity in grasping objects, which can be severely limited if not properly coupled with perfect stereoscopic vision and force/tactile feedback. This work presents the development and testing of a subsystem used for a virtual dashboard within the Sully teleoperation system, with hardware and software components. It is used to capture images, gather object information, and display a virtual dashboard that provides the operator with information about the distance and reachability of objects, to support stereoscopic vision visualized through a virtual reality headset. The hardware consists of two front cameras, used as eyes for the teleoperated robot, and two Time-of-Flight (ToF) sensors to estimate the distance between the teleoperated robot and the Object of Interest (OoI). The software processes images captured by cameras to identify the objects, detects the OoI, and estimates its distance from the robot using the measurements of ToF sensors. Performance results showed an optimal trade-off between image quality, frame rate, and use experience. Indeed, a mean accuracy of 88% was achieved in identifying and detecting OoIs, and an average mean absolute percentage error (MAPE) of 1.40% to estimate the distance from the robot to the OoI at 120 cm.

Introduction and Aims: To examine the relationship of birthweight, and prematurity, to risk factors and markers for chronic kidney disease (CKD) in postnatal life.

This research study proposes a new method to improve robotic teleoperation during grasping tasks. In particular, the target is to reduce the operator's mental burden in grasping tasks, ensuring that the robotic grasping task is simplified for the operator. This simplification aims to improve the task grasping execution time and, in the meantime, increase its grasping success rate. The method is based on an adaptive 3D Virtual Activation Volume (VaV), which acts as a dynamic constraint to support the operator in the grasping task. This volume is centered around the object to grasp and leverages advanced 3D modeling and active control techniques by using machine learning algorithms. In conclusion, the experimental results demonstrate that the proposed method enhances the precision of Human-Robot Interaction (HRI), resulting in a more intuitive teleoperation experience, with a 24% decrease in grasping execution time and a 26.4% increase in grasping success rate.