Ontology Based Statistical Automated Inference - New Approach to Artificial Intelligence

Statistical analysis requires understanding the nature of the phenomenon under study, as well as understanding sense of mathematical statistics. Bridging the gap between semantic web based on knowledge representation languages, and concepts described by mathematical formula is a challenge for AI. In order to overcome this gap the ontology language P-ONT (based on directed graph) has been invented. To illustrate the capabilities of the P-ONT language, semantic web (built on the P-ONT ontology) OLAP cube, relational data bases and generalized hierarchical statistical regression models are presented

Functional Neuroanatomy of Dynamic Visuo-Spatial Imagery

The aim of this thesis was the examination of the neural bases of dynamic visuo-spatial imagery. In addition to the assessment of brain activity during dy-namic visuo-spatial imagery using single-trial functional magnetic resonance im-aging (fMRI) and slow cortical potentials (SCPs), several methodological issues have been investigated. The theoretical part of this thesis consists of a selective overview of fMRI and SCPs, and of the advantages of their combination for functional neuroimaging (chapter 2). The methodological and empirical chapters include: Ø the presentation of a new, highly accurate and practicable method for the co-registration of MRI- and EEG-data (chapter 3), Ø the description of the increase in the accuracy of SCP mapping resulting from the use of individual electrode coordinates and realistic head models (chapter 4), Ø the description of regional differences in the consistency of brain activity across several executions of the same task type, as assessed by a new analysis con-cept based on single-trial fMRI data (chapter 5), Ø the demonstration of the involvement of premotor regions in dynamic visuo-spatial imagery, as assessed via a combination of single-trial fMRI and SCPs (chapter 6), Ø the description of a combined fMRI-SCP investigation in which earlier findings concerning individual differences in neural efficiency during dynamic imagery could not be replicated (chapter 7)

The VESPA Project: Virtual Reality Interventions for Neurocognitive and Developmental Disorders

VESPA is a financed project supported by the Sicilian Regional Research and Development funds, and it is structured by the development, research and validation of Virtual Reality (VR) based application for the diagnosis and treatment of neurocognitive conditions. In particular, this article presents its characteristics, referred to as the first (2013-2015) and second (2021-ongoing) generations of VESPA, with particular reference to literature regarding the VR technology application and development, the VR treatment of neurocognitive conditions and prior versions of this intervention. Through a comprehensive review of the research conducted over the last 5 years, evidence has emerged supporting VESPA’s aim and scopes, highlighting how the application of VR can be considered to add value to typical rehabilitation/therapeutic paths. VESPA project generations are then presented in detail, including specific session/task battery characteristics, 2.5D, 3D and 5D typologies, system usability and architecture and pathological domain-based dynamics and features. The discussion about VESPA will highlight the current advantages along with limitations and future directions

Spectral imaging in preclinical research and clinical pathology.

Spectral imaging methods are attracting increased interest from researchers and practitioners in basic science, pre-clinical and clinical arenas. A combination of better labeling reagents and better optics creates opportunities to detect and measure multiple parameters at the molecular and cellular level. These tools can provide valuable insights into the basic mechanisms of life, and yield diagnostic and prognostic information for clinical applications. There are many multispectral technologies available, each with its own advantages and limitations. This chapter will present an overview of the rationale for spectral imaging, and discuss the hardware, software and sample labeling strategies that can optimize its usefulness in clinical settings

On-site customer analytics and reporting (OSCAR):a portable clinical data warehouse for the in-house linking of hospital and telehealth data

This document conveys the results of the On-Site Customer Analytics and Reporting (OSCAR) project. This nine-month project started on January 2014 and was conducted at Philips Research in the Chronic Disease Management group as part of the H2H Analytics Project. Philips has access to telehealth data from their Philips Motiva tele-monitoring and other services. Previous projects within Philips Re-search provided a data warehouse for Motiva data and a proof-of-concept (DACTyL) solution that demonstrated the linking of hospital and Motiva data and subsequent reporting. Severe limitations with the DACTyL solution resulted in the initiation of OSCAR. A very important one was the unwillingness of hospitals to share personal patient data outside their premises due to stringent privacy policies, while at the same time patient personal data is required in order to link the hospital data with the Motiva data. Equally important is the fact that DACTyL considered the use of only Motiva as a telehealth source and only a single input interface for the hospitals. OSCAR was initiated to propose a suitable architecture and develop a prototype solution, in contrast to the proof-of-concept DACTyL, with the twofold aim to overcome the limitations of DACTyL in order to be deployed in a real-life hospital environment and to expand the scope to an extensible solution that can be used in the future for multiple telehealth services and multiple hospital environments. In the course of the project, a software solution was designed and consequently deployed in the form of a virtual machine. The solution implements a data warehouse that links and hosts the collected hospital and telehealth data. Hospital data are collected with the use of a modular service oriented data collection component by exposing web services described in WSDL that accept configurable XML data messages. ETL processes propagate the data, link, and load it on the OS-CAR data warehouse. Automated reporting is achieved using dash-boards that provide insight into the data stored in the data warehouse. Furthermore, the linked data is available for export to Philips Re-search in de-identified format

The design, development and application of novel, screen-printed amperometric glutamate biosensors

The aim of the studies presented in this thesis was to develop a screen-printed electrochemical biosensor for the measurement of glutamate and to apply this device to the determination of the analyte in food, serum and toxicity studies.Chapter 1 serves as an introduction to both the physiological significance of glutamate and the fundamental principles underpinning the electrochemical techniques used throughout this thesis.Chapter 2 is a review chapter, separated into two main sections. The first section details glutamate biosensors fabricated with glutamate oxidase (GluOx), the second section details biosensors fabricated with glutamate dehydrogenase (GLDH). The immobilization techniques, ease of fabrication and sample preparation techniques employed are compared. Biosensor characteristics such as sensitivity, limit of detection and linear range are summarised within a table.The studies described in Chapter 3 focus on the development of a non-reagentless glutamate biosensor. A Meldola’s Blue screen-printed carbon electrode (MB-SPCE) was employed as the base transducer. The biosensor was constructed by drop coating the biopolymer chitosan (CHIT) and GLDH onto the surface of the MB-SPCE. For this study, NAD+ was present in free solution. Meldola’s Blue served as the electrocatalyst, whereby NADH produced by the GLDH/NAD+ reaction, was electrocatalytically oxidised at a low operating potential (+0.1V (vs. Ag/AgCl)). The applied potential, temperature, pH and concentration of the co-factors required for the biosensor operation were optimised in this study. The assay exhibited a linear range of 12.5 µM to 150 µM, limit of detection of 1.5 µM, response time of 2s and a sensitivity of 0.44 nA/ µM. The optimised biosensor was subsequently applied to the determination of endogenous and fortified concentrations of glutamate in both serum and food samples (OXO cubes). The serum was fortified with and the resulting mean recovery was 96% with a CV of 3.3% (n = 6). For the food sample, an unfiltered beef OXO cube was analysed for monosodium glutamate (MSG) content. The endogenous content of MSG was 125.43 mg/g, with a CV of 8.98% (n = 6). The solution was fortified with 100mM of glutamate and a resulting mean recovery of 91% with a CV of 6.39% (n = 6) was determined.In Chapter 4, the glutamate biosensor was further developed in order to produce a reagentless device whereby the cofactor NAD+ and GLDH were immobilized on to the surface of the electrode utilising CHIT. The reagentless device was developed in order to monitor glutamate release from human liver carcinoma cells (HepG2) as a result of cell toxicity from exposure to paracetamol. The biosensor was miniaturised in the form of a microband biosensor, whereby one dimension of the electrode is of micrometre size and the other millimetre size. Micro bands exhibit unique diffusion properties in comparison to conventional sized electrodes. Calibration studies were carried out with an applied potential of +0.1V (vs. Ag/AgCl) using both phosphate buffer and cell media. In phosphate buffer the following microband biosensor characteristics were determined: linear range; 25 - 125µM, sensitivity; 0.0636 nA/µM and a theoretical limit of detection of 1.20µM. In cell media; linear range; 25 – 150 µM, sensitivity; 0.128 nA/µM and a theoretical limit of detection of 4.2µM. As the HepG2 cells were grown in an incubator at a fixed temperature and pH, studies were carried out at pH 7, 37ºC, in a 5% CO2 atmosphere. The miniaturised biosensor was applied to the determination of glutamate and the quantification was done by standard addition in cell media after 24 hours exposure to various concentrations of paracetamol. The average endogenous concentrations for glutamate released from the HepG2 cells was 52.07µM (CoV: 13.74%, n = 3), 93.30µM (CoV: 18.41%, n = 3) and 177.14µM (CoV: 14.54% n = 3) for 1mM, 5mM, 10mM doses of paracetamol respectively. The microband biosensor was also applied to the real time monitoring of glutamate over 8 hours. The standard deviations for the final current generated after eight hours are as follows; 1mM (coefficient of variation (CoV): 3.3%), 5mM (CoV: 9.056%) and 10mM (CoV: 13.18%). The study showed that the magnitudes of the steady state currents increased in proportion to the concentration of added paracetamol. The study also demonstrated the possibility of applying microband biosensors, over extended time periods, for toxicity studies; there is no significant removal of analyte owning to the small biosensor dimensions.Chapter 5 describes the development of a reagentless conventional sized glutamate biosensor whereby the cofactor NAD+ and GLDH were immobilized using a combination of multi-walled carbon nanotubes (MWCNT), CHIT and additional water based MB in a layer-by-layer fashion. The MWCNT/CHIT/MB combination facilitates electron transfer to the surface of working electrode. The MWCNT/CHIT also entraps GLDH and the NAD+ on the surface of the electrode. The pH, temperature, optimum applied potential, concentrations of NAD+, CHIT and the addition of water-based MB were optimised. The electrocatalyst MB allowed a operating potential of +0.1V (vs. Ag/AgCl) to be utilised. The biosensor was examined with standard glutamate solutions and the following biosensor characteristics were determined; linear range; 7 - 105µM, LOD; 3 µM, sensitivity; 0.39 nA/µM, response time 20-30s. A food sample was analysed for MSG and found to contain 90.56 mg/g with a CV of 7.52% (n = 5). The reagentless biosensor was also applied to the determination of glutamate in serum. The endogenous concentration was found to be 1.44mM (n = 5), CV: 8.54%. The recovery of glutamate in fortified serum was 104% (n = 5), CV of 2.91%. The results indicate that the new biosensor holds promise for food and biomedical studies