Lab-on-a-chip: Emerging analytical platforms for immune-mediated diseases

Miniaturization of analytical procedures has a significant impact on diagnostic testing since it provides several advantages such as: reduced sample and reagent consumption, shorter analysis time and less sample handling. Lab-on-a-chip (LoC), usually silicon, glass, or silicon-glass, or polymer disposable cartridges, which are produced using techniques inherited from the microelectronics industry, could perform and integrate the operations needed to carry out biochemical analysis through the mechanical realization of a dedicated instrument.Analytical devices based on miniaturized platforms like LoC may provide an important contribution to the diagnosis of high prevalence and rare diseases. In this paper we review some of the uses of Lab-on-a-chip in the clinical diagnostics of immune-mediated diseases and we provide an overview of how specific applications of these technologies could improve and simplify several complex diagnostic procedures.     

A decomposition approach for the combined master surgical schedule and surgical case assignment problems

This research aims at supporting hospital management in making prompt Operating Room (OR) planning decisions, when either unpredicted events occur or alternative scenarios or configurations need to be rapidly evaluated. We design and test a planning tool enabling managers to efficiently analyse several alternatives to the current OR planning and scheduling. To this aim, we propose a decomposition approach. More specifically, we first focus on determining the Master Surgical Schedule (MSS) on a weekly basis, by assigning the different surgical disciplines to the available sessions. Next, we allocate surgeries to each session, focusing on elective patients only. Patients are selected from the waiting lists according to several parameters, including surgery duration, waiting time and priority class of the operations. We performed computational experiments to compare the performance of our decomposition approach with an (exact) integrated approach. The case study selected for our simulations is based on the characteristics of the operating theatre (OT) of a medium-size public Italian hospital. Scalability of the method is tested for different OT sizes. A pilot example is also proposed to highlight the usefulness of our approach for decision support. The proposed decomposition approach finds satisfactory solutions with significant savings in computation time.     

Long QT Syndrome in Pregnancy: Are Vaginal Delivery and Use of Oxytocin Permitted? A Case Report

BackgroundPatients with congenital long QT syndrome (LQTS) are at increased risk of ventricular arrhythmia, particularly during labour and the puerperium.CaseA 28-year-old primigravida with known LQTS underwent induction of labour at 41 weeks’ gestation using a Foley catheter balloon and IV oxytocin. Vaginal delivery with passive second stage and outlet forceps was undertaken with early epidural analgesia to prevent tachycardia and psychological stress. The patient gave birth to a healthy female, and had an uncomplicated postpartum period under continuous electrocardiogram monitoring.ConclusionVaginal delivery with use of oxytocin for the induction of labour can be safely undertaken in patients with LQTS.     

GMAC: A Matlab toolbox for spectral Granger causality analysis of fMRI data

Investigation of causal interactions within brain networks using Granger causality analysis (GCA) is a key challenge in studying neural activity on the basis of functional magnetic resonance imaging (fMRI). The article describes an open-source software toolbox GMAC (Granger multivariate autoregressive connectivity) implementing multivariate spectral GCA. Available features are: fMRI data importing/exporting, network nodes definition, time series preprocessing, multivariate autoregressive modeling, spectral Granger causality indexes estimation, statistical significance assessment using surrogate data, network analysis and visualization of connectivity results. All functions have been integrated into a user-friendly graphical interface developed in the Matlab environment, easily accessible to both technical and clinical users.     

High-level language ability in healthy individuals and its relationship with verbal working memory

The aims of the study were to investigate healthy subjects’ performance on a clinical test of high-level language (HLL) and how it is related to demographic characteristics and verbal working memory (VWM). One hundred healthy subjects (20–79 years old) were assessed with the Swedish BeSS test (Laakso, Brunnegård, Hartelius, & Ahlsén, 2000) and two digit span tasks. Relationships between the demographic variables, VWM and BeSS were investigated both with bivariate correlations and multiple regression analysis. The results present the norms for BeSS. The correlations and multiple regression analysis show that demographic variables had limited influence on test performance. Measures of VWM were moderately related to total BeSS score and weakly to moderately correlated with five of the seven subtests. To conclude, education has an influence on the test as a whole but measures of VWM stood out as the most robust predictor of HLL.