An image classification approach to analyze the suppression of plant immunity by the human pathogen <it>Salmonella</it> Typhimurium

<p>Abstract</p> <p>Background</p> <p>The enteric pathogen <it>Salmonella</it> is the causative agent of the majority of food-borne bacterial poisonings. Resent research revealed that colonization of plants by <it>Salmonella</it> is an active infection process. <it>Salmonella</it> changes the metabolism and adjust the plant host by suppressing the defense mechanisms. In this report we developed an automatic algorithm to quantify the symptoms caused by <it>Salmonella</it> infection on <it>Arabidopsis</it>.</p> <p>Results</p> <p>The algorithm is designed to attribute image pixels into one of the two classes: healthy and unhealthy. The task is solved in three steps. First, we perform segmentation to divide the image into foreground and background. In the second step, a support vector machine (SVM) is applied to predict the class of each pixel belonging to the foreground. And finally, we do refinement by a neighborhood-check in order to omit all falsely classified pixels from the second step. The developed algorithm was tested on infection with the non-pathogenic <it>E. coli</it> and the plant pathogen <it>Pseudomonas syringae</it> and used to study the interaction between plants and <it>Salmonella</it> wild type and T3SS mutants. We proved that T3SS mutants of <it>Salmonella</it> are unable to suppress the plant defenses. Results obtained through the automatic analyses were further verified on biochemical and transcriptome levels.</p> <p>Conclusion</p> <p>This report presents an automatic pixel-based classification method for detecting “unhealthy” regions in leaf images. The proposed method was compared to existing method and showed a higher accuracy. We used this algorithm to study the impact of the human pathogenic bacterium <it>Salmonella</it> Typhimurium on plants immune system. The comparison between wild type bacteria and T3SS mutants showed similarity in the infection process in animals and in plants. Plant epidemiology is only one possible application of the proposed algorithm, it can be easily extended to other detection tasks, which also rely on color information, or even extended to other features.</p

Dysregulated IER3 Expression is Associated with Enhanced Apoptosis in Titin-Based Dilated Cardiomyopathy

Apoptosis (type I programmed cell death) of cardiomyocytes is a major process that plays a role in the progression of heart failure. The early response gene IER3 regulates apoptosis in a wide variety of cells and organs. However, its role in heart failure is largely unknown. Here, we investigate the role of IER3 in an inducible heart failure mouse model. Heart failure was induced in a mouse model that imitates a human titin truncation mutation we found in a patient with dilated cardiomyopathy (DCM). Transferase dUTP nick end labeling (TUNEL) and ssDNA stainings showed induction of apoptosis in titin-deficient cardiomyocytes during heart failure development, while IER3 response was dysregulated. Chromatin immunoprecipitation and knock-down experiments revealed that IER3 proteins target the promotors of anti-apoptotic genes and act as an anti-apoptotic factor in cardiomyocytes. Its expression is blunted during heart failure development in a titin-deficient mouse model. Targeting the IER3 pathway to reduce cardiac apoptosis might be an effective therapeutic strategy to combat heart failure

Dengue: Rapid Diagnostic Testing in a Tertiary Care Setting in Butwal, Nepal

Dengue virus (DENV) is spread mostly by biting by the infected female mosquitoes of the species Aedes aegypti, that are commonly found in tropical and subtropical zones of globe. Some studies have shown that nearly fifty percent of the globe are susceptible to DENV. Most infections by DENV are asymptomatic. Clinical infections vary from mild fever to serious diseases including hemorrhagic fever and shock syndrome. The main objective of this study was to estimate DENV infection by rapid diagnostic (RDTs) kit methods in a tertiary care setting. This retrospective study was done at Crimson Hospital, Butwal, Nepal from June to November 2019. Serum samples of all dengue fever suspected patients were tested for DENV antigen as Dengue nonstructural protein 1(NS1) and DENV specific antibodies as IgM and IgG by using World Health Organization Good Manufacturing Practices (GMP) certified rapid solid phase immunochromatographic method. All laboratory test results were tabulated by using MS-Excel and analyzed by statistical package for the Social Sciences software version 20. Out of 821 samples tested, 518 were positive, including 322 (62.16%) reactive for dengue NS1 Protein, 121 (23.35%) for IgM, 62 (11.96%) for IgG and 13 (2.50%) were positive for both IgG and IgM antibodies. Our study showed high prevalence of dengue infection during monsoon to post-monsoon and the infection rate was higher in males (71.72%) than in females (53.36%). According to our findings, DENV infection is prevalent in Butwal, Nepal. Early diagnosis, better case management, faster public health response and effective health policy towards the control of mosquito vectors may reduce the dengue burden and must be implemented in Nepal