Multiplex real-time PCR for the diagnosis of malaria: correlation with microscopy.

Malaria is generally diagnosed by microscopy and rapid antigen testing. Molecular methods become more widely used. In the present study, the contribution of a quantitative multiplex malaria PCR was investigated. We assessed: (i) the agreement between PCR-based identification and microscopy and (ii) the correlation between the parasite load as determined by quantitative PCR and by microscopy. For 83 patients positive by microscopy for Plasmodium spp., the first EDTA-blood sample was tested by multiplex PCR to confirm smear-based species identification. Parasite load was assessed daily using both microscopy and PCR. Among the 83 patients tested, one was positive by microscopy only and 82 were positive by microscopy and PCR. Agreement between microscopy and PCR for the identification at the species level was 89% (73/82). Six of the nine discordant results corresponded to co-infections by two or three species and were attributed to inaccurate morphological identification of mixed cases. The parasite load generally decreased rapidly after treatment had been started, with similar decay curves being obtained using both microscopy and PCR. Our PCR proved especially useful for identifying mixed infections. The quantification obtained by PCR closely correlated with microscopy-based quantification and could be useful for monitoring treatment efficacy, at least in clinical trials.

Fast test for assessing the susceptibility of Mycobacterium tuberculosis to isoniazid and rifampin by real-time PCR

Mycobacterium tuberculosis is the bacterium that causes tuberculosis (TB), a leading cause of death from infectious disease worldwide. Rapid diagnosis of resistant strains is important for the control of TB. Real-time polymerase chain reaction (RT-PCR) assays may detect all of the mutations that occur in the M. tuberculosis 81-bp core region of the rpoB gene, which is responsible for resistance to rifampin (RIF) and codon 315 of the katG gene and the inhA ribosomal binding site, which are responsible for isoniazid (INH). The goal of this study was to assess the performance of RT-PCR compared to traditional culture-based methods for determining the drug susceptibility of M. tuberculosis. BACTEC TM MGIT TM 960 was used as the gold standard method for phenotypic drug susceptibility testing. Susceptibilities to INH and RIF were also determined by genotyping of katG, inhA and rpoB genes. RT-PCR based on molecular beacons probes was used to detect specific point mutations associated with resistance. The sensitivities of RT-PCR in detecting INH resistance using katG and inhA targets individually were 55% and 25%, respectively and 73% when combined. The sensitivity of the RT-PCR assay in detecting RIF resistance was 99%. The median time to complete the RT-PCR assay was three-four hours. The specificities for tests were both 100%. Our results confirm that RT-PCR can detect INH and RIF resistance in less than four hours with high sensitivity.

First detection of Waddlia chondrophila in Africa using SYBR Green real-time PCR on veterinary samples.

Waddlia chondrophila is a strict intracellular microorganism belonging to the order Chlamydiales that has been isolated twice from aborted bovine fetuses, once in USA and once in Germany. This bacterium is now considered as an abortigenic agent in cattle. However, no information is available regarding the presence of this bacterium in Africa. Given the low sensitivity of cell culture to recover such an obligate intracellular bacterium, molecular-based diagnostic approaches are warranted. This report describes the development of a quantitative SYBR Green real-time PCR assay targeting the recA gene of W. chondrophila. Analytical sensitivity was 10 copies of control plasmid DNA per reaction. No cross-amplification was observed when testing pathogens that can cause abortion in cattle. The PCR exhibited a good intra-run and inter-run reproducibility. This real-time PCR was then applied to 150 vaginal swabs taken from Tunisian cows that have aborted. Twelve samples revealed to be Waddlia positive, suggesting a possible role of this bacterium in this setting. This new real-time PCR assay represents a diagnostic tool that may be used to further study the prevalence of Waddlia infection.

Navigator-gated and real-time motion corrected free-breathing MR Imaging of myocardial late enhancement.

PURPOSE: A new magnetic resonance imaging approach for detection of myocardial late enhancement during free-breathing was developed. METHODS AND RESULTS: For suppression of respiratory motion artifacts, a prospective navigator technology including real-time motion correction and a local navigator restore was implemented. Subject specific inversion times were defined from images with incrementally increased inversion times acquired during a single dynamic scout navigator-gated and real-time motion corrected free-breathing scan. Subsequently, MR-imaging of myocardial late enhancement was performed with navigator-gated and real-time motion corrected adjacent short axis and long axis (two, three and four chamber) views. This alternative approach was investigated in 7 patients with history of myocardial infarction 12 min after i. v. administration of 0.2 mmol/kg body weight gadolinium-DTPA. CONCLUSION: With the presented navigator-gated and real-time motion corrected sequence for MR-imaging of myocardial late enhancement data can be completely acquired during free-breathing. Time constraints of a breath-hold technique are abolished and optimized patient specific inversion time is ensured.

Development of a duplex real-time PCR for the detection of Rickettsia spp. and typhus group rickettsia in clinical samples.

Molecular diagnosis using real-time polymerase chain reaction (PCR) may allow earlier diagnosis of rickettsiosis. We developed a duplex real-time PCR that amplifies (1) DNA of any rickettsial species and (2) DNA of both typhus group rickettsia, that is, Rickettsia prowazekii and Rickettsia typhi. Primers and probes were selected to amplify a segment of the 16S rRNA gene of Rickettsia spp. for the pan-rickettsial PCR and the citrate synthase gene (gltA) for the typhus group rickettsia PCR. Analytical sensitivity was 10 copies of control plasmid DNA per reaction. No cross-amplification was observed when testing human DNA and 22 pathogens or skin commensals. Real-time PCR was applied to 16 clinical samples. Rickettsial DNA was detected in the skin biopsies of three patients. In one patient with severe murine typhus, the typhus group PCR was positive in a skin biopsy from a petechial lesion and seroconversion was later documented. The two other patients with negative typhus group PCR suffered from Mediterranean and African spotted fever, respectively; in both cases, skin biopsy was performed on the eschar. Our duplex real-time PCR showed a good analytical sensitivity and specificity, allowing early diagnosis of rickettsiosis among three patients, and recognition of typhus in one of them.

Role of MT1-MMP in cancer dissemination : insights from the real time imaging of tumors

Abstract : Matrix metalloproteinases (MMPs) are thought to play a major role in the tumor dissemination process as they degrade all components of the extracellular matrix. However, failure of clinical trials testing broad MMP inhibitors in cancer led to the consensus that a better understanding of the MMP biology was required. Using intravital multiphoton laser scanning microscopy, we developed an in vivo model to observe tumor dissemination and extracellular matrix remodeling in real time. We show that the matrix-modifying hormone relaxin increases tumor associated fibroblast interaction with collagen fibers by inducing integrin beta-1 expression. This causes changes in the collagen network that are mediated by MMP-8 and MT1-MMP. Also, we show that MMP-mediated collagen remodeling in vivo requires a direct contact between stationary tumor associated fibroblasts (TAFs) and collagen fibers. As MMPs are expressed in the tumor and stromal compartment of breast cancers we determined the importance of Membrane-type 1 MMP (MT1-MMP) from each compartment for cancer progression. We find that tumor-MT1-MMP promotes the invasion of the blood vasculature and blood-borne metastasis in vivo by enhancing tumor cell migration and endothelial basement membrane degradation. Interestingly, stromal-MT1-MMP cannot compensate for the lack of tumor-MT1-MMP but promotes peritumor collagen I remodeling. Thus, the function of MT1-MMP is context dependent and we identify the different but complementary roles of tumor and stromal MT1-MMP for tumor dissemination. Finally, we translate our preclinical findings in to human breast cancer samples. We show that tumor-MT1-MMP expression correlates with tumor invasion of the blood vasculature in ER-PR-HER2- breast cancers and that MT1-MMP expression increases with cancer progression. MT1-MMP could thus represent an interesting therapeutic target for the prevention of blood vasculature invasion in these tumors. Resumé : Les matrix metalloproteinases (MMPs) semblent jouer un rôle majeur pour la dissémination tumorale en raison de leur capacité à dégrader l'ensemble des composants de la matrice extracellulaire (MEC). Néanmoins, les résultats décevants des études cliniques testant les inhibiteurs des MMP ont conduit à la notion qu'une compréhension plus précise de la biologie des MMP était requise. Dans ce travail de thèse, nous avons développé un modèle murin qui permet d'observer simultanément la dissémination tumorale ainsi que les modifications de la MEC en temps réel. Nous démontrons que le traitement de tumeurs par l'hormone relaxin augmente l'interaction des fibroblastes tumoraux avec les fibres de collagène via l'intégrine beta-1. Nous montrons que cette interaction favorise et est nécessaire à la dégradation des fibres de collagène par MMP-8 et MT1-MMP. Ensuite, étant donné que les MMPs sont exprimées dans les cellules tumorales et stromales des cancers du sein, nous nous sommes intéressés au rôle de la MMP membranaire type 1 (MT1-MMP) exprimée dans chacun de ces compartiments. Nous démontrons que MT1-MMP dérivant des cellules tumorales favorise leur invasion dans les vaisseaux sanguins par la dégradation de la membrane basale vasculaire. De manière inattendue, nous montrons que l'expression de MT1-MMP par le compartiment stromal ne peut compenser le manque de MT1-MMP dans le compartiment tumoral. Néanmoins, nos résultats prouvent que MT1-MMP dérivant du compartiment stromal est impliqué dans la dégradation de collagène peritumorale. La fonction de la protéine MT1-MMP varie donc selon le compartiment tumoral d'origine. Finalement, nous avons testé nos résultats pré cliniques chez l'humain. Dans des biopsies de cancer du sein nous montrons une corrélation entre l'expression de MT1-MMP dans les cellules tumorales et l'invasion de vaisseaux sanguins par des tumeurs ER-PR-HER2-. MT1-MMP pourrait donc être une cible intéressante pour la prévention de dissémination vasculaire de ces tumeurs

Discovery of a 29-gene panel in peripheral blood mononuclear cells for the detection of colorectal cancer and adenomas using high throughput real-time PCR.

Colorectal cancer (CRC) is the second leading cause of cancer-related death in developed countries. Early detection of CRC leads to decreased CRC mortality. A blood-based CRC screening test is highly desirable due to limited invasiveness and high acceptance rate among patients compared to currently used fecal occult blood testing and colonoscopy. Here we describe the discovery and validation of a 29-gene panel in peripheral blood mononuclear cells (PBMC) for the detection of CRC and adenomatous polyps (AP). Blood samples were prospectively collected from a multicenter, case-control clinical study. First, we profiled 93 samples with 667 candidate and 3 reference genes by high throughput real-time PCR (OpenArray system). After analysis, 160 genes were retained and tested again on 51 additional samples. Low expressed and unstable genes were discarded resulting in a final dataset of 144 samples profiled with 140 genes. To define which genes, alone or in combinations had the highest potential to discriminate AP and/or CRC from controls, data were analyzed by a combination of univariate and multivariate methods. A list of 29 potentially discriminant genes was compiled and evaluated for its predictive accuracy by penalized logistic regression and bootstrap. This method discriminated AP >1cm and CRC from controls with a sensitivity of 59% and 75%, respectively, with 91% specificity. The behavior of the 29-gene panel was validated with a LightCycler 480 real-time PCR platform, commonly adopted by clinical laboratories. In this work we identified a 29-gene panel expressed in PBMC that can be used for developing a novel minimally-invasive test for accurate detection of AP and CRC using a standard real-time PCR platform.

Real-Time Simulation of Mobile and Industrial Machines Using the Multibody Simulation Approach

This thesis introduces a real-time simulation environment based on the multibody simulation approach. The environment consists of components that are used in conventional product development, including computer aided drawing, visualization, dynamic simulation and finite element software architecture, data transfer and haptics. These components are combined to perform as a coupled system on one platform. The environment is used to simulate mobile and industrial machines at different stages of a product life time. Consequently, the demands of the simulated scenarios vary. In this thesis, a real-time simulation environment based on the multibody approach is used to study a reel mechanism of a paper machine and a gantry crane. These case systems are used to demonstrate the usability of the real-time simulation environment for fault detection purposes and in the context of a training simulator. In order to describe the dynamical performance of a mobile or industrial machine, the nonlinear equations of motion must be defined. In this thesis, the dynamical behaviour of machines is modelled using the multibody simulation approach. A multibody system may consist of rigid and flexible bodies which are joined using kinematic joint constraints while force components are used to describe the actuators. The strength of multibody dynamics relies upon its ability to describe nonlinearities arising from wearing of the components, friction, large rotations or contact forces in a systematic manner. For this reason, the interfaces between subsystems such as mechanics, hydraulics and control systems of the mechatronic machine can be defined and analyzed in a straightforward manner.

Novel virtual environment and real-time simulation based methods for improving life-cycle efficiency of non-road mobile machinery

Virtual environments and real-time simulators (VERS) are becoming more and more important tools in research and development (R&D) process of non-road mobile machinery (NRMM). The virtual prototyping techniques enable faster and more cost-efficient development of machines compared to use of real life prototypes. High energy efficiency has become an important topic in the world of NRMM because of environmental and economic demands. The objective of this thesis is to develop VERS based methods for research and development of NRMM. A process using VERS for assessing effects of human operators on the life-cycle efficiency of NRMM was developed. Human in the loop simulations are ran using an underground mining loader to study the developed process. The simulations were ran in the virtual environment of the Laboratory of Intelligent Machines of Lappeenranta University of Technology. A physically adequate real-time simulation model of NRMM was shown to be reliable and cost effective in testing of hardware components by the means of hardware-in-the-loop (HIL) simulations. A control interface connecting integrated electro-hydraulic energy converter (IEHEC) with virtual simulation model of log crane was developed. IEHEC consists of a hydraulic pump-motor and an integrated electrical permanent magnet synchronous motorgenerator. The results show that state of the art real-time NRMM simulators are capable to solve factors related to energy consumption and productivity of the NRMM. A significant variation between the test drivers is found. The results show that VERS can be used for assessing human effects on the life-cycle efficiency of NRMM. HIL simulation responses compared to that achieved with conventional simulation method demonstrate the advances and drawbacks of various possible interfaces between the simulator and hardware part of the system under study. Novel ideas for arranging the interface are successfully tested and compared with the more traditional one. The proposed process for assessing the effects of operators on the life-cycle efficiency will be applied for wider group of operators in the future. Driving styles of the operators can be analysed statistically from sufficient large result data. The statistical analysis can find the most life-cycle efficient driving style for the specific environment and machinery. The proposed control interface for HIL simulation need to be further studied. The robustness and the adaptation of the interface in different situations must be verified. The future work will also include studying the suitability of the IEHEC for different working machines using the proposed HIL simulation method.

Evaluation Of A Novel Method Of Real Time Computer Assisted Spine Surgery

In this paper the effectiveness of a novel method of computer assisted pedicle screw insertion was studied using testing of hypothesis procedure with a sample size of 48. Pattern recognition based on geometric features of markers on the drill has been performed on real time optical video obtained from orthogonally placed CCD cameras. The study reveals the exactness of the calculated position of the drill using navigation based on CT image of the vertebra and real time optical video of the drill. The significance value is 0.424 at 95% confidence level which indicates good precision with a standard mean error of only 0.00724. The virtual vision method is less hazardous to both patient and the surgeon

Adaptive Real-time Anomaly-based Intrusion Detection using Data Mining and Machine Learning Techniques

Die zunehmende Vernetzung der Informations- und Kommunikationssysteme führt zu einer weiteren Erhöhung der Komplexität und damit auch zu einer weiteren Zunahme von Sicherheitslücken. Klassische Schutzmechanismen wie Firewall-Systeme und Anti-Malware-Lösungen bieten schon lange keinen Schutz mehr vor Eindringversuchen in IT-Infrastrukturen. Als ein sehr wirkungsvolles Instrument zum Schutz gegenüber Cyber-Attacken haben sich hierbei die Intrusion Detection Systeme (IDS) etabliert. Solche Systeme sammeln und analysieren Informationen von Netzwerkkomponenten und Rechnern, um ungewöhnliches Verhalten und Sicherheitsverletzungen automatisiert festzustellen. Während signatur-basierte Ansätze nur bereits bekannte Angriffsmuster detektieren können, sind anomalie-basierte IDS auch in der Lage, neue bisher unbekannte Angriffe (Zero-Day-Attacks) frühzeitig zu erkennen. Das Kernproblem von Intrusion Detection Systeme besteht jedoch in der optimalen Verarbeitung der gewaltigen Netzdaten und der Entwicklung eines in Echtzeit arbeitenden adaptiven Erkennungsmodells. Um diese Herausforderungen lösen zu können, stellt diese Dissertation ein Framework bereit, das aus zwei Hauptteilen besteht. Der erste Teil, OptiFilter genannt, verwendet ein dynamisches "Queuing Concept", um die zahlreich anfallenden Netzdaten weiter zu verarbeiten, baut fortlaufend Netzverbindungen auf, und exportiert strukturierte Input-Daten für das IDS. Den zweiten Teil stellt ein adaptiver Klassifikator dar, der ein Klassifikator-Modell basierend auf "Enhanced Growing Hierarchical Self Organizing Map" (EGHSOM), ein Modell für Netzwerk Normalzustand (NNB) und ein "Update Model" umfasst. In dem OptiFilter werden Tcpdump und SNMP traps benutzt, um die Netzwerkpakete und Hostereignisse fortlaufend zu aggregieren. Diese aggregierten Netzwerkpackete und Hostereignisse werden weiter analysiert und in Verbindungsvektoren umgewandelt. Zur Verbesserung der Erkennungsrate des adaptiven Klassifikators wird das künstliche neuronale Netz GHSOM intensiv untersucht und wesentlich weiterentwickelt. In dieser Dissertation werden unterschiedliche Ansätze vorgeschlagen und diskutiert. So wird eine classification-confidence margin threshold definiert, um die unbekannten bösartigen Verbindungen aufzudecken, die Stabilität der Wachstumstopologie durch neuartige Ansätze für die Initialisierung der Gewichtvektoren und durch die Stärkung der Winner Neuronen erhöht, und ein selbst-adaptives Verfahren eingeführt, um das Modell ständig aktualisieren zu können. Darüber hinaus besteht die Hauptaufgabe des NNB-Modells in der weiteren Untersuchung der erkannten unbekannten Verbindungen von der EGHSOM und der Überprüfung, ob sie normal sind. Jedoch, ändern sich die Netzverkehrsdaten wegen des Concept drif Phänomens ständig, was in Echtzeit zur Erzeugung nicht stationärer Netzdaten führt. Dieses Phänomen wird von dem Update-Modell besser kontrolliert. Das EGHSOM-Modell kann die neuen Anomalien effektiv erkennen und das NNB-Model passt die Änderungen in Netzdaten optimal an. Bei den experimentellen Untersuchungen hat das Framework erfolgversprechende Ergebnisse gezeigt. Im ersten Experiment wurde das Framework in Offline-Betriebsmodus evaluiert. Der OptiFilter wurde mit offline-, synthetischen- und realistischen Daten ausgewertet. Der adaptive Klassifikator wurde mit dem 10-Fold Cross Validation Verfahren evaluiert, um dessen Genauigkeit abzuschätzen. Im zweiten Experiment wurde das Framework auf einer 1 bis 10 GB Netzwerkstrecke installiert und im Online-Betriebsmodus in Echtzeit ausgewertet. Der OptiFilter hat erfolgreich die gewaltige Menge von Netzdaten in die strukturierten Verbindungsvektoren umgewandelt und der adaptive Klassifikator hat sie präzise klassifiziert. Die Vergleichsstudie zwischen dem entwickelten Framework und anderen bekannten IDS-Ansätzen zeigt, dass der vorgeschlagene IDSFramework alle anderen Ansätze übertrifft. Dies lässt sich auf folgende Kernpunkte zurückführen: Bearbeitung der gesammelten Netzdaten, Erreichung der besten Performanz (wie die Gesamtgenauigkeit), Detektieren unbekannter Verbindungen und Entwicklung des in Echtzeit arbeitenden Erkennungsmodells von Eindringversuchen.

Incremental Verification of Timing Constraints for Real-Time Systems

Testing constraints for real-time systems are usually verified through the satisfiability of propositional formulae. In this paper, we propose an alternative where the verification of timing constraints can be done by counting the number of truth assignments instead of boolean satisfiability. This number can also tell us how “far away” is a given specification from satisfying its safety assertion. Furthermore, specifications and safety assertions are often modified in an incremental fashion, where problematic bugs are fixed one at a time. To support this development, we propose an incremental algorithm for counting satisfiability. Our proposed incremental algorithm is optimal as no unnecessary nodes are created during each counting. This works for the class of path RTL. To illustrate this application, we show how incremental satisfiability counting can be applied to a well-known rail-road crossing example, particularly when its specification is still being refined.

The Benefits of Re-Evaluating Real-Time Fulfillment Decisions

At the time of a customer order, the e-tailer assigns the order to one or more of its order fulfillment centers, and/or to drop shippers, so as to minimize procurement and transportation costs, based on the available current information. However this assignment is necessarily myopic as it cannot account for all future events, such as subsequent customer orders or inventory replenishments. We examine the potential benefits from periodically re-evaluating these real-time order-assignment decisions. We construct near-optimal heuristics for the re-assignment for a large set of customer orders with the objective to minimize the total number of shipments. We investigate how best to implement these heuristics for a rolling horizon, and discuss the effect of demand correlation, customer order size, and the number of customer orders on the nature of the heuristics. Finally, we present potential saving opportunities by testing the heuristics on sets of order data from a major e-tailer.

A modular head/eye platform for real-time reactive vision

This paper describes the design, implementation and testing of a high speed controlled stereo “head/eye” platform which facilitates the rapid redirection of gaze in response to visual input. It details the mechanical device, which is based around geared DC motors, and describes hardware aspects of the controller and vision system, which are implemented on a reconfigurable network of general purpose parallel processors. The servo-controller is described in detail and higher level gaze and vision constructs outlined. The paper gives performance figures gained both from mechanical tests on the platform alone, and from closed loop tests on the entire system using visual feedback from a feature detector.

From saccades to smooth pursuit: real-time gaze control using motion feedback

The authors present an active vision system which performs a surveillance task in everyday dynamic scenes. The system is based around simple, rapid motion processors and a control strategy which uses both position and velocity information. The surveillance task is defined in terms of two separate behavioral subsystems, saccade and smooth pursuit, which are demonstrated individually on the system. It is shown how these and other elementary responses to 2D motion can be built up into behavior sequences, and how judicious close cooperation between vision and control results in smooth transitions between the behaviors. These ideas are demonstrated by an implementation of a saccade to smooth pursuit surveillance system on a high-performance robotic hand/eye platform.