The correlation between the mutation of protein kinase genes and the clinical characteristics of breast cancer progression

It is accepted that breast cancer (BC) is a heterogeneous disease. In order to investigate BC as a group of disease sub-types, the varying clinical characteristics of BC patients must be considered. In this project a series of clinical, pathological, genetic and genomic data, retrieved from multiple data repositories, will be reviewed for selection in a large-scale meta-analysis and then categorised into 5 sub-groups (Luminal A, Luminal B, Basal, HER2 and Normal). The meta-analysis is primarily designed to ascertain if a correlation exists between the mutation of protein kinase (PK) genes and BC progression. As PK genes play important roles in regulating most cellular processes (e.g. cell proliferation, differentiation and apoptosis), it is no surprise that deregulated PK activity is a frequent cause of disease, and that PK genes are often oncogenes. The meta-analysis objectives are two-fold: 1. To conduct an integrative meta-analysis of the differential gene expression of the PK gene family between clinical categories of BC progression (low vs high proliferation; luminal vs basal tissue; and grade 1 vs grade 3 tumours). Results from the meta-analysis will generate a ranked list of PK gene expression profiles observed in BC progression. 2. Through the use of powerful bioinformatics tools and sequence analysis interfaces the ranked PK list will be used to direct investigations into the correlations between: codon usage bias; aberrant epigenetic factors; somatic mutations; and observed structural/functional changes of deregulated PK genes in different BC progression categories. To address these objectives a series of in silico bioinformatics experiments have been designed. A software program (MYGEO) has been specifically written for: multiple dataset download; calculation of p-values between BC progression groups; finding Q-values to control for the false discovery rate over multiple dataset comparisons; and to perform permutation testing on the ranked PK gene list; and 2D/3D sequence analysis functions for the analysis of structure/function relationships in significantly differentiated PK genes in BC progression. This project will benefit our understanding of the complex system of BC biology by identifying significantly deregulated PK genes in BC progression. The results will identify BC biomarkers and structural/functional locations within PK genes not yet elucidated, thus providing new directions for the development of PK inhibitors and improving the effectiveness of current BC treatment strategies

Fog Computing in Medical Internet-of-Things: Architecture, Implementation, and Applications

In the era when the market segment of Internet of Things (IoT) tops the chart in various business reports, it is apparently envisioned that the field of medicine expects to gain a large benefit from the explosion of wearables and internet-connected sensors that surround us to acquire and communicate unprecedented data on symptoms, medication, food intake, and daily-life activities impacting one's health and wellness. However, IoT-driven healthcare would have to overcome many barriers, such as: 1) There is an increasing demand for data storage on cloud servers where the analysis of the medical big data becomes increasingly complex, 2) The data, when communicated, are vulnerable to security and privacy issues, 3) The communication of the continuously collected data is not only costly but also energy hungry, 4) Operating and maintaining the sensors directly from the cloud servers are non-trial tasks. This book chapter defined Fog Computing in the context of medical IoT. Conceptually, Fog Computing is a service-oriented intermediate layer in IoT, providing the interfaces between the sensors and cloud servers for facilitating connectivity, data transfer, and queryable local database. The centerpiece of Fog computing is a low-power, intelligent, wireless, embedded computing node that carries out signal conditioning and data analytics on raw data collected from wearables or other medical sensors and offers efficient means to serve telehealth interventions. We implemented and tested an fog computing system using the Intel Edison and Raspberry Pi that allows acquisition, computing, storage and communication of the various medical data such as pathological speech data of individuals with speech disorders, Phonocardiogram (PCG) signal for heart rate estimation, and Electrocardiogram (ECG)-based Q, R, S detection.Comment: 29 pages, 30 figures, 5 tables. Keywords: Big Data, Body Area Network, Body Sensor Network, Edge Computing, Fog Computing, Medical Cyberphysical Systems, Medical Internet-of-Things, Telecare, Tele-treatment, Wearable Devices, Chapter in Handbook of Large-Scale Distributed Computing in Smart Healthcare (2017), Springe

Developing the Quantitative Histopathology Image Ontology : A case study using the hot spot detection problem

Interoperability across data sets is a key challenge for quantitative histopathological imaging. There is a need for an ontology that can support effective merging of pathological image data with associated clinical and demographic data. To foster organized, cross-disciplinary, information-driven collaborations in the pathological imaging field, we propose to develop an ontology to represent imaging data and methods used in pathological imaging and analysis, and call it Quantitative Histopathological Imaging Ontology – QHIO. We apply QHIO to breast cancer hot-spot detection with the goal of enhancing reliability of detection by promoting the sharing of data between image analysts

Assessment of the volume of intraorbital structures using the numerical segmentation image technique (NSI): the extraocular muscles

Wstęp: Stosowane współczeœnie układy obliczeniowe i ich oprogramowanie pozwalają na analizę obrazów medycznych i znaczne przyspieszenie przetwarzania danych liczbowych w informacje użyteczne klinicznie. Realne jest stworzenie aplikacji automatycznie obliczających objętość struktur obrazowanych w badaniu MR. Celem pracy była ocena przydatności klinicznej metody cyfrowej segmentacji objętościowej (NSI, numerical segmentation image) w określaniu objętości mięśni wewnątrzgałkowych. Materiał i metody: Do badania włączono 45 chorych (90 oczodołów). Wszyscy pacjenci zostali podani badaniu metodą rezonansu magnetycznego oczodołów w skanerze 1,5 T przy użyciu cewki głowowej. Stopień wytrzeszczu określono klinicznie, jak i radiologicznie w stosunku do linii międzyjarzmowej. Ocenę ilościową wszystkich mięśni zewnątrzgałkowych przeprowadzono przy użyciu aplikacji NSI, stanowiącej nowy program komputerowy opracowany przez autorów. Wyniki: Stwierdzono silną korelację statystyczną pomiędzy objętością mięśni gałkoruchowych a stopniem wytrzeszczu (r = 0,543, p = 3,13396E-08), co jest zgodne z innymi doniesieniami. Wnioski: Program NSI jest aplikacją umożliwiającą wiarygodną i precyzyjną ocenę objętości mięśni zewnątrzgałkowych. Jest tym samym użyteczny w diagnozowaniu procesów patologicznych prowadzących do wytrzeszczu. Technika NSI może być przydatna zwłaszcza w monitorowaniu dyskretnych zmian objętoœci mięśni w trakcie leczenia.Introduction: In recent years the use of computer systems has allowed numerical analysis of medical images to be introduced and has speeded up the conversion of numerical data into clinically valuable information. The creation of a software application that could almost automatically calculate the volume of anatomical structures imaged by MRI has seemed possible. The aim of our study was to determine the clinical usefulness of an numerical segmentation image technique (NSI) software application in estimating the volume of extraocular muscles. Material and methods: The study group was formed of 45 patients (90 orbits). All the patients underwent MRI examinations of the orbits by a 1.5 T scanner using a head coil. The degree of exophthalmos was determined clinically and radiologically in relation to the interzygomaticus line. The quantitative assessment of all eye muscles was carried out using the NSI application, a new software program introduced by the authors. Results: A close correlation between muscle volume and the degree of exophthalmos was revealed and confirmed by statistical analysis (r = 0.543, p = 3.13396E-08) in agreement with other papers. Conclusions: The NSI software program is an application which offers a reliable and precise estimation of eye muscle volume. It is therefore useful in the diagnosis of the pathological processes leading to exophthalmos. It has special clinical value for monitoring discrete volume changes of muscles during treatment

A Computer Aided Detection system for mammographic images implemented on a GRID infrastructure

The use of an automatic system for the analysis of mammographic images has proven to be very useful to radiologists in the investigation of breast cancer, especially in the framework of mammographic-screening programs. A breast neoplasia is often marked by the presence of microcalcification clusters and massive lesions in the mammogram: hence the need for tools able to recognize such lesions at an early stage. In the framework of the GPCALMA (GRID Platform for Computer Assisted Library for MAmmography) project, the co-working of italian physicists and radiologists built a large distributed database of digitized mammographic images (about 5500 images corresponding to 1650 patients) and developed a CAD (Computer Aided Detection) system, able to make an automatic search of massive lesions and microcalcification clusters. The CAD is implemented in the GPCALMA integrated station, which can be used also for digitization, as archive and to perform statistical analyses. Some GPCALMA integrated stations have already been implemented and are currently on clinical trial in some italian hospitals. The emerging GRID technology can been used to connect the GPCALMA integrated stations operating in different medical centers. The GRID approach will support an effective tele- and co-working between radiologists, cancer specialists and epidemiology experts by allowing remote image analysis and interactive online diagnosis.Comment: 5 pages, 5 figures, to appear in the Proceedings of the 13th IEEE-NPSS Real Time Conference 2003, Montreal, Canada, May 18-23 200

A new complimentary web-based tool for manual analysis of microcirculation videos: validation of the capillary mapper against the current gold standard AVA 3.2

OBJECTIVE: The aim of the current study was to compare a newly developed web-based freely accessible software program for manual analysis of the microcirculation, the Capillary Mapper (CM), with AVA 3.2 software (AVA; MicroVision Medical B.V., Amsterdam, The Netherlands), which is the current gold standard for analysis of microcirculation videos. METHODS: A web-based software program was developed, which enables manual analysis of videos of the microcirculation to be carried out according to recommendations of the 2018 consensus conference. A set of 50 high quality microcirculation videos was analyzed with AVA and CM with respect to total vessel density, perfused vessel density, proportion of perfused vessels, and the microvascular flow index. RESULTS: Comparison of the mean values derived from manual analysis with CM and AVA revealed no significant differences in microcirculatory variables. Analysis according to Bland and Altman revealed an acceptable bias between manual analysis with the CM and AVA for all variables tested with sufficient limits of agreement. The analysis of intraclass correlation showed "excellent" agreement for all microcirculatory variables analyzed. CONCLUSIONS: The newly developed CM was successfully validated for manual analyses of microcirculation videos against the current gold standard, the software AVA 3.2

Deletion of low molecular weight protein tyrosine phosphatase (Acp1) protects against stress-induced cardiomyopathy.

The low molecular weight protein tyrosine phosphatase (LMPTP), encoded by the ACP1 gene, is a ubiquitously expressed phosphatase whose in vivo function in the heart and in cardiac diseases remains unknown. To investigate the in vivo role of LMPTP in cardiac function, we generated mice with genetic inactivation of the Acp1 locus and studied their response to long-term pressure overload. Acp1(-/-) mice develop normally and ageing mice do not show pathology in major tissues under basal conditions. However, Acp1(-/-) mice are strikingly resistant to pressure overload hypertrophy and heart failure. Lmptp expression is high in the embryonic mouse heart, decreased in the postnatal stage, and increased in the adult mouse failing heart. We also show that LMPTP expression increases in end-stage heart failure in humans. Consistent with their protected phenotype, Acp1(-/-) mice subjected to pressure overload hypertrophy have attenuated fibrosis and decreased expression of fibrotic genes. Transcriptional profiling and analysis of molecular signalling show that the resistance of Acp1(-/-) mice to pathological cardiac stress correlates with marginal re-expression of fetal cardiac genes, increased insulin receptor beta phosphorylation, as well as PKA and ephrin receptor expression, and inactivation of the CaMKIIδ pathway. Our data show that ablation of Lmptp inhibits pathological cardiac remodelling and suggest that inhibition of LMPTP may be of therapeutic relevance for the treatment of human heart failure

Novel mutations in TARDBP (TDP-43) in patients with familial amyotrophic lateral sclerosis.

The TAR DNA-binding protein 43 (TDP-43) has been identified as the major disease protein in amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration with ubiquitin inclusions (FTLD-U), defining a novel class of neurodegenerative conditions: the TDP-43 proteinopathies. The first pathogenic mutations in the gene encoding TDP-43 (TARDBP) were recently reported in familial and sporadic ALS patients, supporting a direct role for TDP-43 in neurodegeneration. In this study, we report the identification and functional analyses of two novel and one known mutation in TARDBP that we identified as a result of extensive mutation analyses in a cohort of 296 patients with variable neurodegenerative diseases associated with TDP-43 histopathology. Three different heterozygous missense mutations in exon 6 of TARDBP (p.M337V, p.N345K, and p.I383V) were identified in the analysis of 92 familial ALS patients (3.3%), while no mutations were detected in 24 patients with sporadic ALS or 180 patients with other TDP-43-positive neurodegenerative diseases. The presence of p.M337V, p.N345K, and p.I383V was excluded in 825 controls and 652 additional sporadic ALS patients. All three mutations affect highly conserved amino acid residues in the C-terminal part of TDP-43 known to be involved in protein-protein interactions. Biochemical analysis of TDP-43 in ALS patient cell lines revealed a substantial increase in caspase cleaved fragments, including the approximately 25 kDa fragment, compared to control cell lines. Our findings support TARDBP mutations as a cause of ALS. Based on the specific C-terminal location of the mutations and the accumulation of a smaller C-terminal fragment, we speculate that TARDBP mutations may cause a toxic gain of function through novel protein interactions or intracellular accumulation of TDP-43 fragments leading to apoptosis