Accuracy of LightCycler SeptiFast for the detection and identification of pathogens in the blood of patients with suspected sepsis: a systematic review and meta-analysis

Purpose: There is an urgent need to develop diagnostic tests to improve the detection of pathogens causing life-threatening infection (sepsis). SeptiFast is a CE-marked multi-pathogen real-time PCR system capable of detecting DNA sequences of bacteria and fungi present in blood samples within a few hours. We report here a systematic review and meta-analysis of diagnostic accuracy studies of SeptiFast in the setting of suspected sepsis.

Methods: A comprehensive search strategy was developed to identify studies that compared SeptiFast with blood culture in suspected sepsis. Methodological quality was assessed using QUADAS. Heterogeneity of studies was investigated using a coupled forest plot of sensitivity and specificity and a scatter plot in receiver operator characteristic space. Bivariate model method was used to estimate summary sensitivity and specificity.

Results: From 41 phase III diagnostic accuracy studies, summary sensitivity and specificity for SeptiFast compared with blood culture were 0.68 (95 % CI 0.63–0.73) and 0.86 (95 % CI 0.84–0.89) respectively. Study quality was judged to be variable with important deficiencies overall in design and reporting that could impact on derived diagnostic accuracy metrics.

Conclusions: SeptiFast appears to have higher specificity than sensitivity, but deficiencies in study quality are likely to render this body of work unreliable. Based on the evidence presented here, it remains difficult to make firm recommendations about the likely clinical utility of SeptiFast in the setting of suspected sepsis.

A Game-Theoretic Approach for Threats Detection and Intervention in Surveillance

Threat prevention with limited security resources is a challenging problem. An optimal strategy is to eectively predict attackers' targets (or goals) based on current available information, and use such predictions to prevent (or disrupt) their planned attacks. In this paper, we propose a game-theoretic framework to address this challenge which encompasses the following three elements. First, we design a method to analyze an attacker's types in order to determine the most plausible type of an attacker. Second, we propose an approach to predict possible targets of an attack and the course of actions that the attackers may take even when the attackers' types are ambiguous. Third, a game-theoretic based strategy is developed to determine the best protection actions for defenders (security resources).

Strategies for detection and quantification of cysteine cathepsins-evolution from bench to bedside

The cysteine cathepsins are a family of closely related thiol proteases, normally found in the endosomal and lysosomal compartments of cells. A growing body of evidence has clearly linked the dysregulated activity of these proteases with many diseases and pathological conditions, offering therapeutic, prognostic and diagnostic potential. However, these proteases are synthesised as inactive precursors and once activated, are controlled by factors such as pH and presence of endogenous inhibitors, meaning that overall protein and activity levels do not necessarily correlate. In order to fully appreciate the role and potential of these proteases, tools are required that can detect and quantify overall cathepsin activity. Two main strategies have evolved; synthetic substrates and protease-labelling with affinity-binding probes (or activity-based probes). This review examines recent innovations in these approaches as the field moves towards developing tools that could ultimately be used in patients for diagnostic or prognostic applications.

Mixed chimaerism; detection and significance following BMT

Residual recipient haematopoietic cells may coexist with donor haemopoietic tissue following BMT. This is known as mixed chimaerism. The incidence of mixed chimaerism varies with the sensitivity of the detection system used; DNA based methodologies are the most sensitive. The influence of mixed chimaerism on leukaemia relapse and graft rejection is unclear. The lineages in which mixed chimaerism occurs may affect outcome.

A novel fluorescence-based assay for the rapid detection and quantification of cellular deoxyribonucleoside triphosphates

Current methods for measuring deoxyribonucleoside triphosphates (dNTPs) employ reagent and labor-intensive assays utilizing radioisotopes in DNA polymerase-based assays and/or chromatography-based approaches. We have developed a rapid and sensitive 96-well fluorescence-based assay to quantify cellular dNTPs utilizing a standard real-time PCR thermocycler. This assay relies on the principle that incorporation of a limiting dNTP is required for primer-extension and Taq polymerase-mediated 5-3' exonuclease hydrolysis of a dual-quenched fluorophore-labeled probe resulting in fluorescence. The concentration of limiting dNTP is directly proportional to the fluorescence generated. The assay demonstrated excellent linearity (R(2) > 0.99) and can be modified to detect between ∼0.5 and 100 pmol of dNTP. The limits of detection (LOD) and quantification (LOQ) for all dNTPs were defined as <0.77 and <1.3 pmol, respectively. The intra-assay and inter-assay variation coefficients were determined to be <4.6% and <10%, respectively with an accuracy of 100 ± 15% for all dNTPs. The assay quantified intracellular dNTPs with similar results obtained from a validated LC-MS/MS approach and successfully measured quantitative differences in dNTP pools in human cancer cells treated with inhibitors of thymidylate metabolism. This assay has important application in research that investigates the influence of pathological conditions or pharmacological agents on dNTP biosynthesis and regulation.

Real-Time Multiple Event Detection and Classification Using Moving Window PCA

This paper proposes a method for the detection and classification of multiple events in an electrical power system in real-time, namely; islanding, high frequency events (loss of load) and low frequency events (loss of generation). This method is based on principal component analysis of frequency measurements and employs a moving window approach to combat the time-varying nature of power systems, thereby increasing overall situational awareness of the power system. Numerical case studies using both real data, collected from the UK power system, and simulated case studies, constructed using DigSilent PowerFactory, for islanding events, as well as both loss of load and generation dip events, are used to demonstrate the reliability of the proposed method.

Improved line/edge detection and visual reconstruction

Lines and edges provide important information for object categorization and recognition. In addition, one brightness model is based on a symbolic interpretation of the cortical multi-scale line/edge representation. In this paper we present an improved scheme for line/edge extraction from simple and complex cells and we illustrate the multi-scale representation. This representation can be used for visual reconstruction, but also for nonphotorealistic rendering. Together with keypoints and a new model of disparity estimation, a 3D wireframe representation of e.g. faces can be obtained in the future.

Locally Periodic Signal Estimation and Pitch Detection, and Acoustic Communication in American and Northwestern Crows

Thesis (Ph.D.)--University of Washington, 2016-03

The Discrimination of Colored Acrylic, Cotton, and Wool Textile Fibers Using Micro-Raman Spectroscopy. Part 1 : In Situ Detection and Characterization of Dyes

Raman spectroscopy has been applied to characterize fiber dyes and determine the discriminating ability of the method. Black, blue, and red acrylic, cotton, and wool samples were analyzed. Four excitation sources were used to obtain complementary responses in the case of fluorescent samples. Fibers that did not provide informative spectra using a given laser were usually detected using another wavelength. For any colored acrylic, the 633-nm laser did not provide Raman information. The 514-nm laser provided the highest discrimination for blue and black cotton, but half of the blue cottons produced noninformative spectra. The 830-nm laser exhibited the highest discrimination for red cotton. Both visible lasers provided the highest discrimination for black and blue wool, and NIR lasers produced remarkable separation for red and black wool. This study shows that the discriminating ability of Raman spectroscopy depends on the fiber type, color, and the laser wavelength.

Multi-scale support vector algorithms for hot spot detection and modelling

The algorithmic approach to data modelling has developed rapidly these last years, in particular methods based on data mining and machine learning have been used in a growing number of applications. These methods follow a data-driven methodology, aiming at providing the best possible generalization and predictive abilities instead of concentrating on the properties of the data model. One of the most successful groups of such methods is known as Support Vector algorithms. Following the fruitful developments in applying Support Vector algorithms to spatial data, this paper introduces a new extension of the traditional support vector regression (SVR) algorithm. This extension allows for the simultaneous modelling of environmental data at several spatial scales. The joint influence of environmental processes presenting different patterns at different scales is here learned automatically from data, providing the optimum mixture of short and large-scale models. The method is adaptive to the spatial scale of the data. With this advantage, it can provide efficient means to model local anomalies that may typically arise in situations at an early phase of an environmental emergency. However, the proposed approach still requires some prior knowledge on the possible existence of such short-scale patterns. This is a possible limitation of the method for its implementation in early warning systems. The purpose of this paper is to present the multi-scale SVR model and to illustrate its use with an application to the mapping of Cs137 activity given the measurements taken in the region of Briansk following the Chernobyl accident.

Molecular detection and identification of zygomycetes species from paraffin-embedded tissues in a murine model of disseminated zygomycosis: a collaborative European Society of Clinical Microbiology and Infectious Diseases (ESCMID) Fungal Infection Study Group (EFISG) evaluation.

The present study was performed to assess the interlaboratory reproducibility of the molecular detection and identification of species of Zygomycetes from formalin-fixed paraffin-embedded kidney and brain tissues obtained from experimentally infected mice. Animals were infected with one of five species (Rhizopus oryzae, Rhizopus microsporus, Lichtheimia corymbifera, Rhizomucor pusillus, and Mucor circinelloides). Samples with 1, 10, or 30 slide cuts of the tissues were prepared from each paraffin block, the sample identities were blinded for analysis, and the samples were mailed to each of seven laboratories for the assessment of sensitivity. A protocol describing the extraction method and the PCR amplification procedure was provided. The internal transcribed spacer 1 (ITS1) region was amplified by PCR with the fungal universal primers ITS1 and ITS2 and sequenced. As negative results were obtained for 93% of the tissue specimens infected by M. circinelloides, the data for this species were excluded from the analysis. Positive PCR results were obtained for 93% (52/56), 89% (50/56), and 27% (15/56) of the samples with 30, 10, and 1 slide cuts, respectively. There were minor differences, depending on the organ tissue, fungal species, and laboratory. Correct species identification was possible for 100% (30 cuts), 98% (10 cuts), and 93% (1 cut) of the cases. With the protocol used in the present study, the interlaboratory reproducibility of ITS sequencing for the identification of major Zygomycetes species from formalin-fixed paraffin-embedded tissues can reach 100%, when enough material is available.

Detection and measurement of paracaspase MALT1 activity.

The paracaspase MALT1 is a Cys-dependent, Arg-specific protease that plays an essential role in the activation and proliferation of lymphocytes during the immune response. Oncogenic activation of MALT1 is associated with the development of specific forms of B-cell lymphomas. Through specific cleavage of its substrates, MALT1 controls various aspects of lymphocyte activation, including the activation of transcriptional pathways, the stabilization of mRNAs, and an increase in cellular adhesion. In lymphocytes, the activity of MALT1 is tightly controlled by its inducible monoubiquitination, which promotes the dimerization of MALT1. Here, we describe both in vitro and in vivo assays that have been developed to assess MALT1 activity.

Towards high-quality simultaneous EEG-fMRI at 7T: Detection and reduction of EEG artifacts due to head motion.

The enhanced functional sensitivity offered by ultra-high field imaging may significantly benefit simultaneous EEG-fMRI studies, but the concurrent increases in artifact contamination can strongly compromise EEG data quality. In the present study, we focus on EEG artifacts created by head motion in the static B0 field. A novel approach for motion artifact detection is proposed, based on a simple modification of a commercial EEG cap, in which four electrodes are non-permanently adapted to record only magnetic induction effects. Simultaneous EEG-fMRI data were acquired with this setup, at 7T, from healthy volunteers undergoing a reversing-checkerboard visual stimulation paradigm. Data analysis assisted by the motion sensors revealed that, after gradient artifact correction, EEG signal variance was largely dominated by pulse artifacts (81-93%), but contributions from spontaneous motion (4-13%) were still comparable to or even larger than those of actual neuronal activity (3-9%). Multiple approaches were tested to determine the most effective procedure for denoising EEG data incorporating motion sensor information. Optimal results were obtained by applying an initial pulse artifact correction step (AAS-based), followed by motion artifact correction (based on the motion sensors) and ICA denoising. On average, motion artifact correction (after AAS) yielded a 61% reduction in signal power and a 62% increase in VEP trial-by-trial consistency. Combined with ICA, these improvements rose to a 74% power reduction and an 86% increase in trial consistency. Overall, the improvements achieved were well appreciable at single-subject and single-trial levels, and set an encouraging quality mark for simultaneous EEG-fMRI at ultra-high field.

Early detection and intervention for infants at risk of autism spectrum disorders

Autism is a developmental disorder that is characterized by abnonnal social interactions and communications as well as repetitive and restricted activities and interests. There is evidence of a genetic component, as 5% of younger siblings are diagnosed if their older sibling has been diagnosed. Autism is generally not diagnosed until age 3 at the earliest, yet it has been shown that early intervention for children with autism can greatly increase their functioning. Because of this, it is important that symptoms of autism are identified as early as possible so that diagnosis can occur as soon as possible to allow these children the earliest intervention. This thesis was divided into two parts. The first looked at the psychometrics of two proposed measures, the Parent Observation Checklist (POC), administered monthly, and the Infant Behavior Summary Evaluation (mSE), administered bimonthly, to see if they can be used with the infant population to identify autistic symptoms in infants who are at high risk for autism or related problems because they have an older sibling with autism. Study 1 reported acceptable psychometric properties of both the POC and IBSE in terms of test-retest reliability, internal consistency, construct validity and predictive validity. These results provide preliminary evidence that parent report measures can help to detect early symptoms of ASD in infants. The POC was shown to differentiate infants who were diagnosed from a matched group that was not diagnosed by 3 years of age. The second part of this thesis involved a telephone interview of parents who reported developmental and/or behavior problems in their high-risk infants that may be early signs of Autism Spectrum Disorder (ASD). During the interview, a service questionnaire was administered to see what interventions (including strategies recommended by the researchers) their at risk infants and affected older siblings were receiving, how satisfied the parents were with them and how effective they felt the interventions were. 3 Study 2 also yielded promising results. Parents utilized a variety of services for at risk infants and children with ASD. The interventions included empirically validated early intervention (e.g., ABA) to non-empirically validated treatments (e.g., diet therapy). The large number of nonempirically validated treatments parents used was surprising, yet parents reported being involved and satisfied, and thought that the services were effective. Parents' perceptions of their stress levels went down slightly and feelings of competence rose when they accessed services for their infants. Overall, the results of this thesis provide new evidence that parent-report methods hold promise as early detection instruments for ASD in at-risk infants. More research is needed to further validate these instruments as well as to understand the variables related to the parents' choice of early intervention for their at risk and affected children.

Buried Treasure: The Economics of Leak Detection and Water Loss Prevention in Ontario

On average approximately 13% of the water that is withdrawn by Canadian municipal water suppliers is lost before it reaches final users. This is an important topic for several reasons: water losses cost money, losses force water agencies to draw more water from lakes and streams thereby putting more stress on aquatic ecosystems, leaks reduce system reliability, leaks may contribute to future pipe failures, and leaks may allow contaminants to enter water systems thereby reducing water quality and threatening the health of water users. Some benefits of leak detection fall outside water agencies’ accounting purview (e.g. reduced health risks to households connected to public water supply systems) and, as a result, may not be considered adequately in water agency decision-making. Because of the regulatory environment in which Canadian water agencies operate, some of these benefits-especially those external to the agency or those that may accrue to the agency in future time periods- may not be fully counted when agencies decide on leak detection efforts. Our analysis suggests potential reforms to promote increased efforts for leak detection: adoption of a Canada-wide goal of universal water metering; development of full-cost accounting and, pricing for water supplies; and co-operation amongst the provinces to promulgate standards for leak detection efforts and provide incentives to promote improved efficiency and rational investment decision-making.