Artificial neural network-statistical approach for PET volume analysis and classification

Copyright © 2012 The Authors. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.This article has been made available through the Brunel Open Access Publishing Fund.The increasing number of imaging studies and the prevailing application of positron emission tomography (PET) in clinical oncology have led to a real need for efficient PET volume handling and the development of new volume analysis approaches to aid the clinicians in the clinical diagnosis, planning of treatment, and assessment of response to therapy. A novel automated system for oncological PET volume analysis is proposed in this work. The proposed intelligent system deploys two types of artificial neural networks (ANNs) for classifying PET volumes. The first methodology is a competitive neural network (CNN), whereas the second one is based on learning vector quantisation neural network (LVQNN). Furthermore, Bayesian information criterion (BIC) is used in this system to assess the optimal number of classes for each PET data set and assist the ANN blocks to achieve accurate analysis by providing the best number of classes. The system evaluation was carried out using experimental phantom studies (NEMA IEC image quality body phantom), simulated PET studies using the Zubal phantom, and clinical studies representative of nonsmall cell lung cancer and pharyngolaryngeal squamous cell carcinoma. The proposed analysis methodology of clinical oncological PET data has shown promising results and can successfully classify and quantify malignant lesions.This study was supported by the Swiss National Science Foundation under Grant SNSF 31003A-125246, Geneva Cancer League, and the Indo Swiss Joint Research Programme ISJRP 138866. This article is made available through the Brunel Open Access Publishing Fund

Uniform generation in trace monoids

We consider the problem of random uniform generation of traces (the elements of a free partially commutative monoid) in light of the uniform measure on the boundary at infinity of the associated monoid. We obtain a product decomposition of the uniform measure at infinity if the trace monoid has several irreducible components-a case where other notions such as Parry measures, are not defined. Random generation algorithms are then examined.Comment: Full version of the paper in MFCS 2015 with the same titl

Matching pursuit-based compressive sensing in a wearable biomedical accelerometer fall diagnosis device

There is a significant high fall risk population, where individuals are susceptible to frequent falls and obtaining significant injury, where quick medical response and fall information are critical to providing efficient aid. This article presents an evaluation of compressive sensing techniques in an accelerometer-based intelligent fall detection system modelled on a wearable Shimmer biomedical embedded computing device with Matlab. The presented fall detection system utilises a database of fall and activities of daily living signals evaluated with discrete wavelet transforms and principal component analysis to obtain binary tree classifiers for fall evaluation. 14 test subjects undertook various fall and activities of daily living experiments with a Shimmer device to generate data for principal component analysis-based fall classifiers and evaluate the proposed fall analysis system. The presented system obtains highly accurate fall detection results, demonstrating significant advantages in comparison with the thresholding method presented. Additionally, the presented approach offers advantageous fall diagnostic information. Furthermore, transmitted data accounts for over 80% battery current usage of the Shimmer device, hence it is critical the acceleration data is reduced to increase transmission efficiency and in-turn improve battery usage performance. Various Matching pursuit-based compressive sensing techniques have been utilised to significantly reduce acceleration information required for transmission.Scopu

Toward a Framework for Improving the Execution of the Big Data Applications

AbstractIn this paper, we propose a new framework based on learning techniques to improve the execution of a cloud application, especially the big-data application that requires significant computing capacity. We propose a new metric to detect the available capacity in the cloud client

Thermo-physical properties of paraffin wax with iron oxide nanoparticles as phase change material for heat storage applications

Phase change materials (PCMs) are growing in importance in many thermal applications as heat storage or to smooth the energy peak demand in many technological fields in industrial as well as in civil applications. Conductive nanoparticles can be added to phase change material to improve their thermo-physical properties. In this work, Iron oxide nanoparticles (IOx-NPs) were synthesized using a simple and green synthesis method, free of toxic and harmful solvents, using the extract of a plant as a reducer and stabilizer at two different temperatures of calcination 500°C and 750°C. The metallic oxide was used as an additive with 2% wt. compositions to paraffin wax to prepare a nanocomposite. The variation in thermal properties of paraffin wax in the composite was experimentally investigated. The biosynthesized IOx-NPs were characterized by X-ray diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR) and Scanning Electron Microscope (SEM) and Thermal Gravimetric Analysis (TGA) techniques. The thermal properties of the synthesized nanocomposites were characterized by a thermal conductivity analyzer and differential scanning calorimetry (DSC). The FTIR spectra showed a bond at 535 cm-1, which confirms the Fe-O vibration. The XRD powder analysis revealed the formation of the cubic phase of Fe3O4 with an average particle size of 11 nm at 500°C and the presence of the phase α-Fe2O3 with Fe3O4 at 750°C. Scanning Electron Microscopy (SEM) showed that the obtained oxide was made up of particles of nanoscale size. Experimental measurements showed that the presence of nanoparticles can improve the latent heat capacity by a maximum of 16.16 % and the thermal conductivity of the nanocomposites by a maximum of 16.99%

Retrospective study of epidemiological, clinicopathological and biological profils of 62 colorectal cancers cases in Jijel provence (Algeria)

In Algeria, the CRC wing and become the first digestive cancer in both sexes,  outperforming stomach cancer. To enrich the Algerian cancer registries, we analyzed the profiles of patients with these cancers in Jijel Willaya. This was a retrospective and descriptive analysis of epidemiological, clinicopathological and biological profiles of 62 CRC cases. We found that the CRC represented the first type of digestive cancers in which the three quarters were colon cancers. The most affected age group was 60-70 years with a male predominance and an average age of 56.20 years. The bleeding and abdominal pain were the majority telltale signs. The combined chemotherapy has been standardized with all patients and the Lieberkühnien adenocarcinoma was the major histological form. The disease issue and the choice of therapy depended on the K-RAS gene mutations. Our results were often compatible with the available literature and may provide reliable and relevant data on this disease.Key words: Colorectal cancer; Epidemiology; Therapy; Adenocarcinoma; K-RAS gen

Real-time ECG Monitoring using Compressive sensing on a Heterogeneous Multicore Edge-Device

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.In a typical ambulatory health monitoring systems, wearable medical sensors are deployed on the human body to continuously collect and transmit physiological signals to a nearby gateway that forward the measured data to the cloud-based healthcare platform. However, this model often fails to respect the strict requirements of healthcare systems. Wearable medical sensors are very limited in terms of battery lifetime, in addition, the system reliance on a cloud makes it vulnerable to connectivity and latency issues. Compressive sensing (CS) theory has been widely deployed in electrocardiogramme ECG monitoring application to optimize the wearable sensors power consumption. The proposed solution in this paper aims to tackle these limitations by empowering a gatewaycentric connected health solution, where the most power consuming tasks are performed locally on a multicore processor. This paper explores the efficiency of real-time CS-based recovery of ECG signals on an IoT-gateway embedded with ARM’s big.littleTM multicore for different signal dimension and allocated computational resources. Experimental results show that the gateway is able to reconstruct ECG signals in real-time. Moreover, it demonstrates that using a high number of cores speeds up the execution time and it further optimizes energy consumption. The paper identifies the best configurations of resource allocation that provides the optimal performance. The paper concludes that multicore processors have the computational capacity and energy efficiency to promote gateway-centric solution rather than cloud-centric platforms

Biological properties of carotenoids extracted from Halobacterium halobium isolated from a Tunisian solar saltern

Background: Bioactive molecules have received increasing attention due to their nutraceutical attributes and anticancer, antioxidant, antiproliferative and apoptosis-inducing properties. This study aimed to investigate the biological properties of carotenoids extracted from Archaea. Methods: Halophilic Archaea strains were isolated from the brine of a local crystallizer pond (TS7) of a solar saltern at Sfax, Tunisia. The most carotenoid-producing strain (M8) was investigated on heptoma cell line (HepG2), and its viability was assessed by the MTT-test. The cells were incubated with different sub-lethal extract rates, with carotenoid concentrations ranging from 0.2 to 1.5 μM. Antioxidant activity was evaluated through exposing the cells to sub-lethal extract concentrations for 24 hours and then to oxidative stress induced by 60 μM arachidonic acid and 50 μM H2O2. Results: Compared to non-treated cells, bacterial carotenoid extracts inhibited HepG2 cell viability (50%). A time and dose effect was observed, with cell viability undergoing a significant (P < 0.05) decrease with extract concentration. After exposure to oxidative stress, control cells underwent a significant (P < 0.05) decrease in viability as compared to the non-treated cells. Conclusions: The bacterial extracts under investigation were noted to exhibit the strongest free radical scavenging activity with high carotenoid concentrations. The carotenoid extract also showed significant antiproliferative activity against HepG2 human cancer cell lines

Metabolite modifications in Solanum lycopersicum roots and leaves under cadmium stress

The effects of cadmium (Cd) were investigated on growth and metabolite profiling in roots and leaves of tomato (Solanum lycopersicum L., Var. Ibiza F1) plants exposed for 3 and 10 days to various CdCl2 concentrations (0 - 300 ìM). The aim of this study was to describe metabolite modifications in response to Cd stress and to identify Cd stress markers in the roots and leaves of tomato plants. During the treatment, Cd accumulated  significantly in the roots compared to stems and leaves. Plant growth (root, stem and leaf) decreased when Cd concentration increased. The analysis of 1H-NMR spectra of polar extracts showed clear differences between metabolites amounts (soluble sugars, organic and amino acids) in 30 and 300 ìM Cd-treated plants versus control ones. Among soluble sugars and organic acids, glucose, fructose and citrate contents significantly increased, by a factor 2 to 5 in both leaves and roots of Cd treated plants during the first three days of the treatment and then only in roots. In addition, Cd induced qualitative and quantitative changes in amino acid contents in the roots. Asparagine, glutamine and branched chain amino acids (valine, isoleucine, phenylalanine and tryptophane) significantly accumulated after 10 days of Cd exposure. Asparagine content which increased by 26 fold in the roots of 300 ìM Cd treated plants when compared with control ones, was found to be a good marker for Cd stress. In contrast, few modifications occurred in the leaves in response to Cd, except for tyrosine which content was highly increased (by 10 fold) after three days of treatment with 30 ìM. Taken together, our results show that, the exposure of tomato plants to various Cd concentrations results in significant changes in primary metabolism compounds, especially in the accumulation of some amino and organic acids involved in cellular compartmentation and detoxification of Cd.Key words: Cadmium, sugars, organic acids, amino acids, tomato (Solanum lycopersicum)