Reply to "The incidence of cisplatin nephrotoxicity post hyperthermic intraperitoneal chemotherapy (HIPEC) and cytoreductive surgery".

We read an article by Hakeam, Breakiet, Azzam, Nadeem, and Amin, with interest and would like to congratulate the authors for the effort that they have put in a field so challenging.Cytoreductive S..

A Real-Time Service-Oriented Architecture for Industrial Automation

Industrial automation platforms are experiencing a paradigm shift. New technologies are making their way in the area, including embedded real-time systems, standard local area networks like Ethernet, Wi-Fi and ZigBee, IP-based communication protocols, standard service oriented architectures (SOAs) and Web services. An automation system will be composed of flexible autonomous components with plug & play functionality, self configuration and diagnostics, and autonomic local control that communicate through standard networking technologies. However, the introduction of these new technologies raises important problems that need to be properly solved, one of these being the need to support real-time and quality-of-service (QoS) for real-time applications. This paper describes a SOA enhanced with real-time capabilities for industrial automation. The proposed architecture allows for negotiation of the QoS requested by clients from Web services, and provides temporal encapsulation of individual activities. This way, it is possible to perform an a priori analysis of the temporal behavior of each service, and to avoid unwanted interference among them. After describing the architecture, experimental results gathered on a real implementation of the framework (which leverages a soft real-time scheduler for the Linux kernel) are presented, showing the effectiveness of the proposed solution. The experiments were performed on simple case studies designed in the context of industrial automation applications

SOM-based behavioral analysis for virtualized network functions

In this paper, we propose a mechanism based on Self-Organizing Maps for analyzing the resource consumption behaviors and detecting possible anomalies in data centers for Network Function Virtualization (NFV). Our approach is based on a joint analysis of two historical data sets available through two separate monitoring systems: system-level metrics for the physical and virtual machines obtained from the monitoring infrastructure, and application-level metrics available from the individual virtualized network functions. Experimental results, obtained by processing real data from one of the NFV data centers of the Vodafone network operator, highlight some of the capabilities of our system to identify interesting points in space and time of the evolution of the monitored infrastructure

Behavioral Analysis for Virtualized Network Functions : A SOM-based Approach

In this paper, we tackle the problem of detecting anomalous behaviors in a virtualized infrastructure for network function virtualization, proposing to use self-organizing maps for analyzing historical data available through a data center. We propose a joint analysis of system-level metrics, mostly related to resource consumption patterns of the hosted virtual machines, as available through the virtualized infrastructure monitoring system, and the application-level metrics published by individual virtualized network functions through their own monitoring subsystems. Experimental results, obtained by processing real data from one of the NFV data centers of the Vodafone network operator, show that our technique is able to identify specific points in space and time of the recent evolution of the monitored infrastructure that are worth to be investigated by a human operator in order to keep the system running under expected conditions

Very early onset of ATTRE89Q amyloidosis in a homozygous patient

Case Presentarion: Hereditary transthyretin amyloidosis is a progressive, fatal disease that generally involves the peripheral nervous system, the autonomic nervous system, and the heart. It is autosomal dominant with different penetrance depending on the mutation and the genetic background. Many other missense mutations of the TTR gene may cause the disease. Being an overall rare disease is very rare to observe the condition of homozygosity. In particular, cases of homozygosity have been described in patients with ATTRV30M and ATTRV122I amyloidosis. In the former, the phenotype does not seem to be aggravated, having an age of onset and disease course that does not appear to differ from those of heterozygotes, while in the latter, the onset appears to be earlier. Conclusion: We report the first case of ATTRE89Q amyloidosis in a patient that was homozygous for the E89Q mutation in the TTR gene. The clinical phenotype resulted in the earlier disease onset reported in this form of amyloidosis, suggesting that the homozygous condition may be prognostically negative

The Burden of Structured Self-Monitoring of Blood Glucose on Diabetes-Specific Quality of Life and Locus of Control in Patients with Noninsulin-Treated Type 2 Diabetes: The PRISMA Study

Background: To evaluate whether structured self-monitoring of blood glucose (SMBG) is associated with changes in diabetes-specific quality of life (DSQoL) and locus of control (LOC) in patients with noninsulin-treated type 2 diabetes (T2DM). Study Design and Methods: In this analysis of the PRISMA (Prospective Randomized Trial on Intensive SMBG Management Added Value in Noninsulin-Treated T2DM Patients) Study psychosocial data, we evaluated the impact of 12 months of structured SMBG on the individual domains of DSQoL and LOC questionnaires, including the role of selected confounders. Results: The score for Satisfaction, Impact, and Worry domains (DSQoL) improved when compared with baseline, without significant differences between structured SMBG regimen (intervention group, n = 501) and active control group (n = 523). Scores for Internal, Chance, and Powerful Others domains (LOC) improved compared with baseline, with a significant between-group change in Chance (P = 0.0309). For DSQoL domain score, improvements were associated with higher number of SMBG measurements (P = 0.007), older age (P = 0.013), and male sex (P = 0.0133) for Satisfaction and with male sex (P < 0.0001) for Worry. Concerning LOC domain score, improvements were associated with longer diabetes duration (P = 0.0084) and younger age (P < 0.0001) for Chance and total number of SMBG measurements (P = 0.0036) for Internal, with the intervention group close to being significant (P = 0.06). Conclusions: Our analysis demonstrates that in patients with noninsulin-treated T2DM, structured SMBG is not associated with a deterioration of quality of life and LOC, which is strongly predicted by demographics and diabetes-related variables. These findings should be considered when tailoring educational support to SMBG for these patients

Forecasting Operation Metrics for Virtualized Network Functions

Network Function Virtualization (NFV) is the key technology that allows modern network operators to provide flexible and efficient services, by leveraging on general-purpose private cloud infrastructures. In this work, we investigate the performance of a number of metric forecasting techniques based on machine learning and artificial intelligence, and provide insights on how they can support the decisions of NFV operation teams. Our analysis focuses on both infrastructure-level and service-level metrics. The former can be fetched directly from the monitoring system of an NFV infrastructure, whereas the latter are typically provided by the monitoring components of the individual virtualized network functions. Our selected forecasting techniques are experimentally evaluated using real-life data, exported from a production environment deployed within some Vodafone NFV data centers. The results show what the compared techniques can achieve in terms of the forecasting accuracy and computational cost required to train them on production data

Diabetic kidney disease in the elderly: Prevalence and clinical correlates

Background: Diabetic kidney disease (DKD) is a major burden in elderly patients with type 2 diabetes (T2DM). Low estimated glomerular filtration rate (eGFR+, < 60 mL/min/1.73 m2) and albuminuria (Alb+) are essential for the diagnosis of DKD, but their association with clinical variables and quality of care may be influenced by ageing. Methods: Here we investigated the association of clinical variables and quality of care measures with eGFR+ and Alb+ in 157,595 T2DM individuals participating to the Italian Association of Clinical Diabetologists (AMD) Annals Initiative, stratified by age. Results: The prevalence of eGFR+ and Alb+ increased with ageing, although this increment was more pronounced for low eGFR. Irrespective of age, both the eGFR+ and Alb + groups had the worst risk factors profile when compared to subjects without renal disease, showing a higher prevalence of out-of target values of HbA1c, BMI, triglycerides, HDL-C, blood pressure and more complex cardiovascular (CVD) and anti-diabetic therapies, including a larger use of insulin In all age groups, these associations differed according to the specific renal outcome examined: male sex and smoking were positively associated with Alb+ and negatively with eGFR+; age and anti-hypertensive therapies were more strongly associated with eGFR+, glucose control with Alb+, whereas BMI, and lipid-related variables with both abnormalities. All these associations were attenuated in the older (> 75 years) as compared to the younger groups (< 65 years; 65-75 years), and they were confirmed by multivariate analysis. Notably, Q-score values < 15, indicating a low quality of care, were strongly associated with Alb+ (OR 8.54; P < 0.001), but not with eGFR+. Conclusions: In T2DM patients, the prevalence of both eGFR and Albuminuria increase with age. DKD is associated with poor cardiovascular risk profile and a lower quality of care, although these associations are influenced by the type of renal abnormality and by ageing. These data indicate that clinical surveillance of DKD should not be unerestimated in old T2DM patients

Green and scalable synthesis of nanocrystalline kuramite

The new generation of solar cells aims to overcome many of the issues created by silicon-based devices (e.g., decommissioning, flexibility and high-energy production costs). Due to the scarcity of the resources involved in the process and the need for the reduction of potential pollution, a greener approach to solar cell material production is required. Among others, the solvothermal approach for the synthesis of nanocrystalline Cu-Sn-S (CTS) materials fulfils all of these requirements. The material constraints must be considered, not only for the final product, but for the whole production process. Most works reporting the successful synthesis of CTS have employed surfactants, high pressure or noxious solvents. In this paper, we demonstrate the synthesis of nanocrystalline kuramite by means of a simpler, greener and scalable solvothermal synthesis. We exploited a multianalytical characterization approach (X-ray diffraction, extended X-ray absorption fine structure, field emission scanning electron microscopy, Raman spectroscopy and electronic microprobe analysis (EMPA) to discriminate kuramite from other closely related polymorphs. Moreover, we confirmed the presence of structural defects due to a relevant antisite population