Accurate PCR detection of influenza A/B and respiratory syncytial viruses by use of Cepheid Xpert Flu+RSV Xpress Assay in point-of-care settings: Comparison to Prodesse ProFlu+

ABSTRACT The Xpert Flu+RSV Xpress Assay is a fast, automated in vitro diagnostic test for qualitative detection and differentiation of influenza A and B viruses and respiratory syncytial virus (RSV) performed on the Cepheid GeneXpert Xpress System. The objective of this study was to establish performance characteristics of the Xpert Flu+RSV Xpress Assay compared to those of the Prodesse ProFlu+ real-time reverse transcription-PCR (RT-PCR) assay (ProFlu+) for the detection of influenza A and B viruses as well as RSV in a Clinical Laboratory Improvement Amendments (CLIA)-waived (CW) setting. Overall, the assay, using fresh and frozen nasopharyngeal (NP) swabs, demonstrated high concordance with results of the ProFlu+ assay in the combined CW and non-CW settings with positive percent agreements (PPA) (100%, 100%, and 97.1%) and negative percent agreements (NPA) (95.2%, 99.5%, and 99.6%) for influenza A and B viruses and RSV, respectively. In conclusion, this multicenter study using the Cepheid Xpert Flu+RSV Xpress Assay demonstrated high sensitivities and specificities for influenza A and B viruses and RSV in ∼60 min for use at the point-of-care in the CW setting. </jats:p

Effects of Test-Driven Development : A Comparative Analysis of Empirical Studies

Test-driven development is a software development practice where small sections of test code are used to direct the development of program units. Writing test code prior to the production code promises several positive effects on the development process itself and on associated products and processes as well. However, there are few comparative studies on the effects of test-driven development. Thus, it is difficult to assess the potential process and product effects when applying test-driven development. In order to get an overview of the observed effects of test-driven development, an in-depth review of existing empirical studies was carried out. The results for ten different internal and external quality attributes indicate that test-driven development can reduce the amount of introduced defects and lead to more maintainable code. Parts of the implemented code may also be somewhat smaller in size and complexity. While maintenance of test-driven code can take less time, initial development may last longer. Besides the comparative analysis, this article sketches related work and gives an outlook on future research.Peer reviewe

A Multidisciplinary survey on controversies in the use of EUS-guided FNA: assessing perspectives of surgeons, oncologists and gastroenterologists

<p>Abstract</p> <p>Background</p> <p>EUS-guided FNA can help diagnose and differentiate between various pancreatic and other lesions.</p> <p>The aim of this study was to compare approaches among involved/relevant physicians to the controversies surrounding the use of FNA in EUS.</p> <p>Methods</p> <p>A five-case survey was developed, piloted, and validated. It was collected from a total of 101 physicians, who were all either gastroenterologists (GIs), surgeons or oncologists. The survey compared the management strategies chosen by members of these relevant disciplines regarding EUS-guided FNA.</p> <p>Results</p> <p>For CT operable T2NOM0 pancreatic tumors the research demonstrated variance as to whether to undertake EUS-guided FNA, at p < 0.05. For inoperable pancreatic tumors 66.7% of oncologists, 62.2% of surgeons and 79.1% of GIs opted for FNA (p < 0.05). For cystic pancreatic lesions, oncologists were more likely to send patients to surgery without FNA. For stable simple pancreatic cysts (23 mm), most physicians (66.67%) did not recommend FNA. For a submucosal gastric 19 mm lesion, 63.2% of surgeons recommended FNA, vs. 90.0% of oncologists (p < 0.05).</p> <p>Conclusions</p> <p>Controversies as to ideal application of EUS-FNA persist. Optimal guidelines should reflect the needs and concerns of the multidisciplinary team who treat patients who need EUS-FNA. Multi-specialty meetings assembled to manage patients with these disorders may be enlightening and may help develop consensus.</p

Use of smokeless tobacco among groups of Pakistani medical students – a cross sectional study

<p>Abstract</p> <p>Background</p> <p>Use of smokeless tobacco is common in South Asia. Tobacco is a major preventable cause of morbidity and mortality. Doctors make one of the best avenues to influence patients' tobacco use. However, medical students addicted to tobacco are likely to retain this habit as physicians and are unlikely to counsel patients against using tobacco. With this background, this study was conducted with the objective of determining the prevalence of smokeless tobacco among Pakistani medical students.</p> <p>Methods</p> <p>A cross sectional study was carried out in three medical colleges of Pakistan – one from the north and two from the southern region. 1025 students selected by convenient sampling completed a peer reviewed, pre-tested, self-administered questionnaire. Questions were asked regarding lifetime use (at least once or twice in their life), current use (at least once is the last 30 days), and established use (more than 100 times in their life) of smokeless tobacco. Chi square and logistic regression analyses were used.</p> <p>Results</p> <p>Two hundred and twenty (21.5%) students had used tobacco in some form (smoked or smokeless) in their lifetime. Sixty six (6.4%) students were lifetime users of smokeless tobacco. Thirteen (1.3%) were daily users while 18 (1.8%) fulfilled the criterion for established users. Niswar was the most commonly used form of smokeless tobacco followed by paan and nass. Most naswar users belonged to NWFP while most paan users studied in Karachi. On univariate analysis, lifetime use of smokeless tobacco showed significant associations with the use of cigarettes, student gender (M > F), student residence (boarders > day scholars) and location of the College (NWFP > Karachi). Multivariate analysis showed independent association of lifetime use of smokeless tobacco with concomitant cigarette smoking, student gender and location of the medical college.</p> <p>Conclusion</p> <p>The use of smokeless tobacco among medical students cannot be ignored. The governments should add the goal of eliminating smokeless tobacco to existing drives against cigarette smoking. Drives in Karachi should focus more on eliminating paan usage while those in NWFP should focus more on the use of naswar. Medical colleges should provide greater education about the myths and hazards of smokeless tobacco.</p

Design and construction of the MicroBooNE Cosmic Ray Tagger system

The MicroBooNE detector utilizes a liquid argon time projection chamber (LArTPC) with an 85 t active mass to study neutrino interactions along the Booster Neutrino Beam (BNB) at Fermilab. With a deployment location near ground level, the detector records many cosmic muon tracks in each beam-related detector trigger that can be misidentified as signals of interest. To reduce these cosmogenic backgrounds, we have designed and constructed a TPC-external Cosmic Ray Tagger (CRT). This sub-system was developed by the Laboratory for High Energy Physics (LHEP), Albert Einstein center for fundamental physics, University of Bern. The system utilizes plastic scintillation modules to provide precise time and position information for TPC-traversing particles. Successful matching of TPC tracks and CRT data will allow us to reduce cosmogenic background and better characterize the light collection system and LArTPC data using cosmic muons. In this paper we describe the design and installation of the MicroBooNE CRT system and provide an overview of a series of tests done to verify the proper operation of the system and its components during installation, commissioning, and physics data-taking

Ionization Electron Signal Processing in Single Phase LArTPCs II. Data/Simulation Comparison and Performance in MicroBooNE

The single-phase liquid argon time projection chamber (LArTPC) provides a large amount of detailed information in the form of fine-grained drifted ionization charge from particle traces. To fully utilize this information, the deposited charge must be accurately extracted from the raw digitized waveforms via a robust signal processing chain. Enabled by the ultra-low noise levels associated with cryogenic electronics in the MicroBooNE detector, the precise extraction of ionization charge from the induction wire planes in a single-phase LArTPC is qualitatively demonstrated on MicroBooNE data with event display images, and quantitatively demonstrated via waveform-level and track-level metrics. Improved performance of induction plane calorimetry is demonstrated through the agreement of extracted ionization charge measurements across different wire planes for various event topologies. In addition to the comprehensive waveform-level comparison of data and simulation, a calibration of the cryogenic electronics response is presented and solutions to various MicroBooNE-specific TPC issues are discussed. This work presents an important improvement in LArTPC signal processing, the foundation of reconstruction and therefore physics analyses in MicroBooNE.Comment: 54 pages, 36 figures; the first part of this work can be found at arXiv:1802.0870

A Deep Neural Network for Pixel-Level Electromagnetic Particle Identification in the MicroBooNE Liquid Argon Time Projection Chamber

We have developed a convolutional neural network (CNN) that can make a pixel-level prediction of objects in image data recorded by a liquid argon time projection chamber (LArTPC) for the first time. We describe the network design, training techniques, and software tools developed to train this network. The goal of this work is to develop a complete deep neural network based data reconstruction chain for the MicroBooNE detector. We show the first demonstration of a network's validity on real LArTPC data using MicroBooNE collection plane images. The demonstration is performed for stopping muon and a $\nu_\mu$ charged current neutral pion data samples

Ionization Electron Signal Processing in Single Phase LArTPCs I. Algorithm Description and Quantitative Evaluation with MicroBooNE Simulation

We describe the concept and procedure of drifted-charge extraction developed in the MicroBooNE experiment, a single-phase liquid argon time projection chamber (LArTPC). This technique converts the raw digitized TPC waveform to the number of ionization electrons passing through a wire plane at a given time. A robust recovery of the number of ionization electrons from both induction and collection anode wire planes will augment the 3D reconstruction, and is particularly important for tomographic reconstruction algorithms. A number of building blocks of the overall procedure are described. The performance of the signal processing is quantitatively evaluated by comparing extracted charge with the true charge through a detailed TPC detector simulation taking into account position-dependent induced current inside a single wire region and across multiple wires. Some areas for further improvement of the performance of the charge extraction procedure are also discussed.Comment: 60 pages, 36 figures. The second part of this work can be found at arXiv:1804.0258

Convolutional Neural Networks Applied to Neutrino Events in a Liquid Argon Time Projection Chamber

We present several studies of convolutional neural networks applied to data coming from the MicroBooNE detector, a liquid argon time projection chamber (LArTPC). The algorithms studied include the classification of single particle images, the localization of single particle and neutrino interactions in an image, and the detection of a simulated neutrino event overlaid with cosmic ray backgrounds taken from real detector data. These studies demonstrate the potential of convolutional neural networks for particle identification or event detection on simulated neutrino interactions. We also address technical issues that arise when applying this technique to data from a large LArTPC at or near ground level

The Pandora multi-algorithm approach to automated pattern recognition of cosmic-ray muon and neutrino events in the MicroBooNE detector

The development and operation of Liquid-Argon Time-Projection Chambers for neutrino physics has created a need for new approaches to pattern recognition in order to fully exploit the imaging capabilities offered by this technology. Whereas the human brain can excel at identifying features in the recorded events, it is a significant challenge to develop an automated, algorithmic solution. The Pandora Software Development Kit provides functionality to aid the design and implementation of pattern-recognition algorithms. It promotes the use of a multi-algorithm approach to pattern recognition, in which individual algorithms each address a specific task in a particular topology. Many tens of algorithms then carefully build up a picture of the event and, together, provide a robust automated pattern-recognition solution. This paper describes details of the chain of over one hundred Pandora algorithms and tools used to reconstruct cosmic-ray muon and neutrino events in the MicroBooNE detector. Metrics that assess the current pattern-recognition performance are presented for simulated MicroBooNE events, using a selection of final-state event topologies.Comment: Preprint to be submitted to The European Physical Journal