Effect of reconstruction methods and x-ray tube current-time product on nodule detection in an anthropomorphic thorax phantom : a crossed-modality JAFROC observer study

Purpose: To evaluate nodule detection in an anthropomorphic chest phantom in computed tomography (CT) images reconstructed with adaptive iterative dose reduction 3D (AIDR3D) and filtered back projection (FBP) over a range of tube current-time product (mAs). Methods: Two phantoms were used in this study: (i) an anthropomorphic chest phantom was loaded with spherical simulated nodules of 5, 8, 10 and 12mm in diameter and +100, -630 and -800 Hounsfied Units electron density; this would generate CT images for the observer study; (ii) a whole-body dosimetry verification phantom was used to ultimately estimate effective dose and risk according to the model of the BEIR VII committee. Both phantoms were scanned over a mAs range (10, 20, 30, and 40) while all other acquisition parameters remained constant. Images were reconstructed with both AIDR3D and FBP. 34 normal cases (no nodules) and 34 abnormal cases (containing 1-3 nodules, mean 1.35±0.54) cases were chosen for the observer study. Eleven observers evaluated images from all tube current-time product and reconstruction methods under the free-response paradigm. A crossed-modality jackknife alternative free-response operating characteristic (JAFROC) analysis method was developed for data analysis, averaging data over the two factors influencing nodule detection in this study: mAs and image reconstruction (AIDR3D or FBP). A Bonferroni correction was applied and the threshold for declaring significance was set at 0.025 to maintain the overall probability of Type I error at α = 0.05. Contrast-to-noise (CNR) was also measured for all nodules and evaluated by a linear least squares analysis. Results: For random-reader fixed-case crossed-modality JAFROC analysis there was no significant difference in nodule detection between AIDR3D and FBP when data was averaged over mAs (F(1,10) = 0.08, p = 0.789). However, when data was averaged over reconstruction methods, a significant difference was seen between multiple pairs of mAs settings (F(3,30) = 15.96, p<0.001). Measurements of effective dose and effective risk showed the expected linear dependence on mAs. Nodule CNR was statistically higher for simulated nodules on images reconstructed with AIDR3D (p<0.001). Conclusion: No significant difference in nodule detection performance was demonstrated between images reconstructed with FBP and AIDR3D. Tube current-time product was found to influence nodule detection, though further work is required for dose optimisation

A Deep Learning based Explainable Control System for Reconfigurable Networks of Edge Devices

Edge devices that operate in real-world environments are subjected to unpredictable conditions caused by environmental forces such as wind and uneven surfaces. Since most edge systems exhibit dynamic properties, reinforcement learning can be a powerful tool for improving system accuracy. Successful maintenance of the position of a vehicle in such environments can be achieved with the aid of Deep Reinforcement Learning (DRL) that dynamically adjusts the Reconfigurable Wireless Network (RWN) response. Deep Neural Networks (DNNs) is often seen as black boxes, as neither the acquired knowledge nor the decision rationale can be explained. In this paper, we explain the process of a DNN on an autonomous dynamic positioning system by gauging reactions of the DNN to predefined constraints. We introduce a novel digitisation technique that reduces interesting patterns of time series data into single digits to obtain a cross comparable view of the conditions. By analysing the clusters formed on this cross comparable view, we discovered multiple intensities of environmental conditions spanning across 44\% of moderate conditions and 33\% and 23\% of harsh and mild conditions, respectively. Our analysis showed that the proposed system can provide stable responses to uncertain conditions by predicting randomness

Random Numbers Certified by Bell's Theorem

Randomness is a fundamental feature in nature and a valuable resource for applications ranging from cryptography and gambling to numerical simulation of physical and biological systems. Random numbers, however, are difficult to characterize mathematically, and their generation must rely on an unpredictable physical process. Inaccuracies in the theoretical modelling of such processes or failures of the devices, possibly due to adversarial attacks, limit the reliability of random number generators in ways that are difficult to control and detect. Here, inspired by earlier work on nonlocality based and device independent quantum information processing, we show that the nonlocal correlations of entangled quantum particles can be used to certify the presence of genuine randomness. It is thereby possible to design of a new type of cryptographically secure random number generator which does not require any assumption on the internal working of the devices. This strong form of randomness generation is impossible classically and possible in quantum systems only if certified by a Bell inequality violation. We carry out a proof-of-concept demonstration of this proposal in a system of two entangled atoms separated by approximately 1 meter. The observed Bell inequality violation, featuring near-perfect detection efficiency, guarantees that 42 new random numbers are generated with 99% confidence. Our results lay the groundwork for future device-independent quantum information experiments and for addressing fundamental issues raised by the intrinsic randomness of quantum theory.Comment: 10 pages, 3 figures, 16 page appendix. Version as close as possible to the published version following the terms of the journa

The application of multiplex PCR to detect seven different DNA targets in group B streptococci

Group B Streptococcus (GBS) causes severe infections in infants and in immunocompromised adults. GBS pathogenicity varies between and within serotypes, with considerable variation in genetic content between strains. For this reason, it is important to be able to carry out immediate and comprehensive diagnostics of these infections. Seven genes important for screening of GBS infection were detected: cfb gene encoding the CAMP factor presented in every GBS; the cps operon genes such as cps1aH, cps1a/2/3IJ, and cps5O specific for capsular polysaccharide types Ia, III, and V, respectively; macrolide resistance genes ermB and mefA/E; and the gbs2018 S10 region specific for ST17 hypervirulent clone. Standardization of multiplex PCR with the use of seven primer pairs was performed on 81 bacterial strains representing different GBS isolates (n = 75) and other Gram-positive cocci (n = 10). Multiplex PCR can be used as an effective screening method to detect different sequences important for the screening of GBS infection

Routes for breaching and protecting genetic privacy

We are entering the era of ubiquitous genetic information for research, clinical care, and personal curiosity. Sharing these datasets is vital for rapid progress in understanding the genetic basis of human diseases. However, one growing concern is the ability to protect the genetic privacy of the data originators. Here, we technically map threats to genetic privacy and discuss potential mitigation strategies for privacy-preserving dissemination of genetic data.Comment: Draft for comment

Perspectives on the Trypanosoma cruzi-host cell receptor interaction

Chagas disease is caused by the parasite Trypanosoma cruzi. The critical initial event is the interaction of the trypomastigote form of the parasite with host receptors. This review highlights recent observations concerning these interactions. Some of the key receptors considered are those for thromboxane, bradykinin, and for the nerve growth factor TrKA. Other important receptors such as galectin-3, thrombospondin, and laminin are also discussed. Investigation into the molecular biology and cell biology of host receptors for T. cruzi may provide novel therapeutic targets

Nomograms of Iranian fetal middle cerebral artery Doppler waveforms and uniformity of their pattern with other populations' nomograms

<p>Abstract</p> <p>Background</p> <p>Doppler flow velocity waveform analysis of fetal vessels is one of the main methods for evaluating fetus health before labor. Doppler waves of middle cerebral artery (MCA) can predict most of the at risk fetuses in high risk pregnancies. In this study, we tried to obtain normal values and their nomograms during pregnancy for Doppler flow velocity indices of MCA in 20 – 40 weeks of normal pregnancies in Iranian population and compare their pattern with other countries' nomograms.</p> <p>Methods</p> <p>During present descriptive cross-sectional study, 1037 normal pregnant women with 20^th–40^thweek gestational age were underwent MCA Doppler study. All cases were studied by gray scale ultrasonography initially and Doppler of MCA afterward. Resistive Index (RI), Pulsative Index (PI), Systolic/Diastolic ratio (S/D ratio), and Peak Systolic Velocity (PSV) values of MCA were determined for all of the subjects.</p> <p>Results</p> <p>Results of present study showed that RI, PI, S/D ratio values of MCA decreased with parabolic pattern and PSV value increased with simple pattern, as gestational age progressed. These changes were statistically significant (P = 0.000 for all of indices) and more characteristic during late weeks of pregnancy.</p> <p>Conclusion</p> <p>Values of RI, PI and S/D ratio indices reduced toward the end of pregnancy, but PSV increased. Despite the trivial difference, nomograms of various Doppler indices in present study have similar pattern with other studies.</p

The minimal kinome of Giardia lamblia illuminates early kinase evolution and unique parasite biology

Background: The major human intestinal pathogen Giardia lamblia is a very early branching eukaryote with a minimal genome of broad evolutionary and biological interest. Results: To explore early kinase evolution and regulation of Giardia biology, we cataloged the kinomes of three sequenced strains. Comparison with published kinomes and those of the excavates Trichomonas vaginalis and Leishmania major shows that Giardia's 80 core kinases constitute the smallest known core kinome of any eukaryote that can be grown in pure culture, reflecting both its early origin and secondary gene loss. Kinase losses in DNA repair, mitochondrial function, transcription, splicing, and stress response reflect this reduced genome, while the presence of other kinases helps define the kinome of the last common eukaryotic ancestor. Immunofluorescence analysis shows abundant phospho-staining in trophozoites, with phosphotyrosine abundant in the nuclei and phosphothreonine and phosphoserine in distinct cytoskeletal organelles. The Nek kinase family has been massively expanded, accounting for 198 of the 278 protein kinases in Giardia. Most Neks are catalytically inactive, have very divergent sequences and undergo extensive duplication and loss between strains. Many Neks are highly induced during development. We localized four catalytically active Neks to distinct parts of the cytoskeleton and one inactive Nek to the cytoplasm. Conclusions: The reduced kinome of Giardia sheds new light on early kinase evolution, and its highly divergent sequences add to the definition of individual kinase families as well as offering specific drug targets. Giardia's massive Nek expansion may reflect its distinctive lifestyle, biphasic life cycle and complex cytoskeleton

Depression diagnoses following the identification of bipolar disorder: costly incongruent diagnoses

<p>Abstract</p> <p>Background</p> <p>Previous research has documented that the symptoms of bipolar disorder are often mistaken for unipolar depression prior to a patient's first bipolar diagnosis. The assumption has been that once a patient receives a bipolar diagnosis they will no longer be given a misdiagnosis of depression. The objectives of this study were 1) to assess the rate of subsequent unipolar depression diagnosis in individuals with a history of bipolar disorder and 2) to assess the increased cost associated with this potential misdiagnosis.</p> <p>Methods</p> <p>This study utilized a retrospective cohort design using administrative claims data from 2002 and 2003. Patient inclusion criteria for the study were 1) at least 2 bipolar diagnoses in 2002, 2) continuous enrollment during 2002 and 2003, 3) a pharmacy benefit, and 4) age 18 to 64. Patients with at least 2 unipolar depression diagnoses in 2003 were categorized as having an incongruent diagnosis of unipolar depression. We used propensity scoring to control for selection bias. Utilization was evaluated using negative binomial models. We evaluated cost differences between patient cohorts using generalized linear models.</p> <p>Results</p> <p>Of the 7981 patients who met all inclusion criteria for the analysis, 17.5% (1400) had an incongruent depression diagnosis (IDD). After controlling for background differences, individuals who received an IDD had higher rates of inpatient and outpatient psychiatric utilization and cost, on average, an additional $1641 per year compared to individuals without an IDD.</p> <p>Conclusions</p> <p>A strikingly high proportion of bipolar patients are given the differential diagnosis of unipolar depression <it>after </it>being identified as having bipolar disorder. Individuals with an IDD had increased acute psychiatric care services, suggesting higher levels of relapses, and were at risk for inappropriate treatment, as antidepressant therapy without a concomitant mood-stabilizing medication is contraindicated in bipolar disorder. Further prospective research is needed to validate the findings from this retrospective administrative claims-based analysis.</p

Testing the role of predicted gene knockouts in human anthropometric trait variation

National Heart, Lung, and Blood Institute (NHLBI) S.L. is funded by a Canadian Institutes of Health Research Banting doctoral scholarship. G.L. is funded by Genome Canada and Génome Québec; the Canada Research Chairs program; and the Montreal Heart Institute Foundation. C.M.L. is supported by Wellcome Trust (grant numbers 086596/Z/08/Z, 086596/Z/08/A); and the Li Ka Shing Foundation. N.S. is funded by National Institutes of Health (grant numbers HL088456, HL111089, HL116747). The Mount Sinai BioMe Biobank Program is supported by the Andrea and Charles Bronfman Philanthropies. GO ESP is supported by NHLBI (RC2 HL-103010 to HeartGO, RC2 HL-102923 to LungGO, RC2 HL-102924 to WHISP). The ESP exome sequencing was performed through NHLBI (RC2 HL-102925 to BroadGO, RC2 HL- 102926 to SeattleGO). EGCUT work was supported through the Estonian Genome Center of University of Tartu by the Targeted Financing from the Estonian Ministry of Science and Education (grant number SF0180142s08); the Development Fund of the University of Tartu (grant number SP1GVARENG); the European Regional Development Fund to the Centre of Excellence in Genomics (EXCEGEN) [grant number 3.2.0304.11-0312]; and through FP7 (grant number 313010). EGCUT were further supported by the US National Institute of Health (grant number R01DK075787). A.K.M. was supported by an American Diabetes Association Mentor-Based Postdoctoral Fellowship (#7-12-MN- 02). The BioVU dataset used in the analyses described were obtained from Vanderbilt University Medical Centers BioVU which is supported by institutional funding and by the Vanderbilt CTSA grant ULTR000445 from NCATS/NIH. Genome-wide genotyping was funded by NIH grants RC2GM092618 from NIGMS/OD and U01HG004603 from NHGRI/NIGMS. Funding to pay the Open Access publication charges for this article was provided by a block grant from Research Councils UK to the University of Cambridge