Study protocol and design for the assessment of paediatric pneumonia from X-ray images using deep learning

Introduction In low-income and middle-income countries, pneumonia remains the leading cause of illness and death in children<5 years. The recommended tool for diagnosing paediatric pneumonia is the interpretation of chest X-ray images, which is difficult to standardise and requires trained clinicians/radiologists. Current automated computational tools have primarily focused on assessing adult pneumonia and were trained on images evaluated by a single specialist. We aim to provide a computational tool using a deep-learning approach to diagnose paediatric pneumonia using X-ray images assessed by multiple specialists trained by the WHO expert X-ray image reading panel.Methods and analysis Approximately 10 000 paediatric chest X-ray images are currently being collected from an ongoing WHO-supported surveillance study in Bangladesh. Each image will be read by two trained clinicians/radiologists for the presence or absence of primary endpoint pneumonia (PEP) in each lung, as defined by the WHO. Images whose PEP labels are discordant in either lung will be reviewed by a third specialist and the final assignment will be made using a majority vote. Convolutional neural networks will be used for lung segmentation to align and scale the images to a reference, and for interpretation of the images for the presence of PEP. The model will be evaluated against an independently collected and labelled set of images from the WHO. The study outcome will be an automated method for the interpretation of chest radiographs for diagnosing paediatric pneumonia.Ethics and dissemination All study protocols were approved by the Ethical Review Committees of the Bangladesh Institute of Child Health, Bangladesh. The study sponsor deemed it unnecessary to attain ethical approval from the Academic and Clinical Central Office for Research and Development of University of Edinburgh, UK. The study uses existing X-ray images from an ongoing WHO-coordinated surveillance. All findings will be published in an open-access journal. All X-ray labels and statistical code will be made openly available. The model and images will be made available on request

Inhibition of Fungi and Gram-Negative Bacteria by Bacteriocin BacTN635 Produced by Lactobacillus plantarum sp. TN635

The aim of this study was to evaluate 54 lactic acid bacteria (LAB) strains isolated from meat, fermented vegetables and dairy products for their capacity to produce antimicrobial activities against several bacteria and fungi. The strain designed TN635 has been selected for advanced studies. The supernatant culture of this strain inhibits the growth of all tested pathogenic including the four Gram-negative bacteria (Salmonella enterica ATCC43972, Pseudomonas aeruginosa ATCC 49189, Hafnia sp. and Serratia sp.) and the pathogenic fungus Candida tropicalis R2 CIP203. Based on the nucleotide sequence of the 16S rRNA gene of the strain TN635 (1,540 pb accession no FN252881) and the phylogenetic analysis, we propose the assignment of our new isolate bacterium as Lactobacillus plantarum sp. TN635 strain. Its antimicrobial compound was determined as a proteinaceous substance, stable to heat and to treatment with surfactants and organic solvents. Highest antimicrobial activity was found between pH 3 and 11 with an optimum at pH = 7. The BacTN635 was purified to homogeneity by a four-step protocol involving ammonium sulfate precipitation, centrifugal microconcentrators with a 10-kDa membrane cutoff, gel filtration Sephadex G-25, and C18 reverse-phase HPLC. SDS-PAGE analysis of the purified BacTN635, revealed a single band with an estimated molecular mass of approximately 4 kDa. The maximum bacteriocin production (5,000 AU/ml) was recorded after a 16-h incubation in Man, Rogosa, and Sharpe (MRS) medium at 30 °C. The mode of action of the partial purified BacTN635 was identified as bactericidal against Listeria ivanovii BUG 496 and as fungistatic against C. tropicalis R2 CIP203

Theory and Phenomenology of mu in M theory

We consider a solution to the mu-problem within M theory on a G2-manifold. Our study is based upon the discrete symmetry proposed by Witten that forbids the mu-term and solves the doublet-triplet splitting problem. We point out that the symmetry must be broken by moduli stabilization, describing in detail how this can occur. The mu-term is generated via Kahler interactions after strong dynamics in the hidden sector generate a potential which stabilizes all moduli and breaks supersymmetry with m_{3/2} ~ 20 - 30 TeV. We show that mu is suppressed relative to the gravitino mass, by higher dimensional operators, mu ~ 0.1 m_{3/2} ~ 2-3 TeV. This necessarily gives a Higgsino component to the (mostly Wino) LSP, and a small but non-negligible LSP-nucleon scattering cross-section. The maximum, spin-independent cross-sections are not within reach of the current XENON100 experiment, but are within reach of upcoming runs and upgrades.Comment: 34 pages, 3 figure

Evaluation of the stopping angiotensin converting enzyme inhibitor compared to angiotensin receptor blocker (STOP ACEi trial) in advanced and progressive chronic kidney disease

In the STOP-ACEi trial, the outcome was similar whether or not renin–angiotensin system inhibitors (RASi) were discontinued. We now investigate whether the effect of withdrawing angiotensin converting enzyme inhibitors (ACEi) or angiotensin-receptor blockers (ARBs) differed. In this open label trial patients with estimated glomerular filtration rates (eGFR) under 30ml/min per 1.73 m2 and progressive chronic kidney disease (CKD) were randomized to stop or continue RASi. The primary outcome was eGFR at three years. The composite of kidney failure, over 50% fall in eGFR, or kidney replacement therapy (KRT) was also assessed. Of patients randomized, 99 stopped and 123 patients continued ACEi while 104 stopped and 77 continued ARB at baseline. At three years, the eGFR was similar whether or not patients were withdrawn from ACEi or from ARB. Kidney failure or initiation of KRT occurred in 65% of those stopping and 54% continuing ACEi (hazard ratio if stopped, 1.52; 95% Confidence Interval, 1.07 to 2.16) and in 60% on an ARB regardless of randomized group (hazard ratio if stopped, 1.23; 0.83 to 1.81). Kidney failure/Initiation of KRT with over 50% decline in eGFR occurred in 71% of those stopping and 59% continuing ACEi (relative risk if stopped, 1.19; 95% CI, 1.00 to 1.41) and in 65% stopping and 69% continuing ARB (relative risk if stopped, 0.96; 0.79 to 1.16). Thus, neither discontinuing ACEi nor ARB slowed the rate of decline in eGFR. Although discontinuation of ACEi appeared to have more unfavorable effects on kidney outcomes than stopping ARB, the trial was neither designed nor powered to show differences between agents