The Type VI Secretion System Plays a Role in Type 1 Fimbria Expression and Pathogenesis of an Avian Pathogenic Escherichia coli Strain

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Avian pathogenic Escherichia coli (APEC) strains frequently cause extraintestinal infections and are responsible for significant economic losses in the poultry industry worldwide. APEC isolates are closely related to human extraintestinal pathogenic E. coli (ExPEC) strains and may also act as pathogens for humans. Known APEC virulence factors include adhesins such as type 1 fimbriae and curli, iron acquisition systems, and cytotoxins. Here we show that APEC strain SEPT362, isolated from a septicemic hen, expresses a type VI secretion system (T6SS); causes cytoskeleton rearrangements; and invades epithelial cells, replicates within macrophages, and causes lethal disease in chicks. To assess the contribution of the T6SS to SEPT362 pathogenesis, we generated two mutants, hcp (which encodes a protein suggested to be both secreted and a structural component of the T6SS) and clpV (encoding the T6SS ATPase). Both mutants showed decreased adherence and actin rearrangement on epithelial cells. However, only the hcp mutant presented a mild decrease in its ability to invade epithelial cells, and none of these mutants were defective for intramacrophage replication. Transcriptome studies showed that the level of expression of type 1 fimbriae was decreased in these mutants, which may account for the diminished adhesion and invasion of epithelial cells. The T6SS seems to be important for the disease process, given that both mutants were attenuated for infection in chicks. These results suggest that the T6SS influences the expression of type 1 fimbriae and contributes to APEC pathogenesis.781249904998NIH [AI053067]Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)NIH [AI053067]FAPESP [2008/56739-6, 07/50432-3]CAPES [4062086

Improving the Generalizability of Convolutional Neural Network-Based Segmentation on CMR Images

Background: Convolutional neural network (CNN) based segmentation methods provide an efficient and automated way for clinicians to assess the structure and function of the heart in cardiac MR images. While CNNs can generally perform the segmentation tasks with high accuracy when training and test images come from the same domain (e.g., same scanner or site), their performance often degrades dramatically on images from different scanners or clinical sites. / Methods: We propose a simple yet effective way for improving the network generalization ability by carefully designing data normalization and augmentation strategies to accommodate common scenarios in multi-site, multi-scanner clinical imaging data sets. We demonstrate that a neural network trained on a single-site single-scanner dataset from the UK Biobank can be successfully applied to segmenting cardiac MR images across different sites and different scanners without substantial loss of accuracy. Specifically, the method was trained on a large set of 3,975 subjects from the UK Biobank. It was then directly tested on 600 different subjects from the UK Biobank for intra-domain testing and two other sets for cross-domain testing: the ACDC dataset (100 subjects, 1 site, 2 scanners) and the BSCMR-AS dataset (599 subjects, 6 sites, 9 scanners). / Results: The proposed method produces promising segmentation results on the UK Biobank test set which are comparable to previously reported values in the literature, while also performing well on cross-domain test sets, achieving a mean Dice metric of 0.90 for the left ventricle, 0.81 for the myocardium, and 0.82 for the right ventricle on the ACDC dataset; and 0.89 for the left ventricle, 0.83 for the myocardium on the BSCMR-AS dataset. / Conclusions: The proposed method offers a potential solution to improve CNN-based model generalizability for the cross-scanner and cross-site cardiac MR image segmentation task

Improving the Generalizability of Convolutional Neural Network-Based Segmentation on CMR Images

Convolutional neural network (CNN) based segmentation methods provide an efficient and automated way for clinicians to assess the structure and function of the heart in cardiac MR images. While CNNs can generally perform the segmentation tasks with high accuracy when training and test images come from the same domain (e.g. same scanner or site), their performance often degrades dramatically on images from different scanners or clinical sites. We propose a simple yet effective way for improving the network generalization ability by carefully designing data normalization and augmentation strategies to accommodate common scenarios in multi-site, multi-scanner clinical imaging data sets. We demonstrate that a neural network trained on a single-site single-scanner dataset from the UK Biobank can be successfully applied to segmenting cardiac MR images across different sites and different scanners without substantial loss of accuracy. Specifically, the method was trained on a large set of 3,975 subjects from the UK Biobank. It was then directly tested on 600 different subjects from the UK Biobank for intra-domain testing and two other sets for cross-domain testing: the ACDC dataset (100 subjects, 1 site, 2 scanners) and the BSCMR-AS dataset (599 subjects, 6 sites, 9 scanners). The proposed method produces promising segmentation results on the UK Biobank test set which are comparable to previously reported values in the literature, while also performing well on cross-domain test sets, achieving a mean Dice metric of 0.90 for the left ventricle, 0.81 for the myocardium and 0.82 for the right ventricle on the ACDC dataset; and 0.89 for the left ventricle, 0.83 for the myocardium on the BSCMR-AS dataset. The proposed method offers a potential solution to improve CNN-based model generalizability for the cross-scanner and cross-site cardiac MR image segmentation task

Tear fluid biomarkers in ocular and systemic disease: potential use for predictive, preventive and personalised medicine

In the field of predictive, preventive and personalised medicine, researchers are keen to identify novel and reliable ways to predict and diagnose disease, as well as to monitor patient response to therapeutic agents. In the last decade alone, the sensitivity of profiling technologies has undergone huge improvements in detection sensitivity, thus allowing quantification of minute samples, for example body fluids that were previously difficult to assay. As a consequence, there has been a huge increase in tear fluid investigation, predominantly in the field of ocular surface disease. As tears are a more accessible and less complex body fluid (than serum or plasma) and sampling is much less invasive, research is starting to focus on how disease processes affect the proteomic, lipidomic and metabolomic composition of the tear film. By determining compositional changes to tear profiles, crucial pathways in disease progression may be identified, allowing for more predictive and personalised therapy of the individual. This article will provide an overview of the various putative tear fluid biomarkers that have been identified to date, ranging from ocular surface disease and retinopathies to cancer and multiple sclerosis. Putative tear fluid biomarkers of ocular disorders, as well as the more recent field of systemic disease biomarkers, will be shown

Preclinical Evaluation of Caprylic Acid-Fractionated IgG Antivenom for the Treatment of Taipan (Oxyuranus scutellatus) Envenoming in Papua New Guinea

articulo (arbitrado) -- Universidad de Costa Rica, Instituto de Investigaciones Clodomiro Picado, 2011Background: Snake bite is a common medical emergency in Papua New Guinea (PNG). The taipan, Oxyuranus scutellatus, inflicts a large number of bites that, in the absence of antivenom therapy, result in high mortality. Parenteral administration of antivenoms manufactured in Australia is the current treatment of choice for these envenomings. However, the price of these products is high and has increased over the last 25 years; consequently the country can no longer afford all the antivenom it needs. This situation prompted an international collaborative project aimed at generating a new, low-cost antivenom against O. scutellatus for PNG. Methodology/Principal Findings: A new monospecific equine whole IgG antivenom, obtained by caprylic acid fractionation of plasma, was prepared by immunising horses with the venom of O. scutellatus from PNG. This antivenom was compared with the currently used F(ab’)2 monospecific taipan antivenom manufactured by CSL Limited, Australia. The comparison included physicochemical properties and the preclinical assessment of the neutralisation of lethal neurotoxicity and the myotoxic, coagulant and phospholipase A2 activities of the venom of O. scutellatus from PNG. The F(ab’)2 antivenom had a higher protein concentration than whole IgG antivenom. Both antivenoms effectively neutralised, and had similar potency, against the lethal neurotoxic effect (both by intraperitoneal and intravenous routes of injection), myotoxicity, and phospholipase A2 activity of O. scutellatus venom. However, the whole IgG antivenom showed a higher potency than the F(ab’)2 antivenom in the neutralisation of the coagulant activity of O. scutellatus venom from PNG. Conclusions/Significance: The new whole IgG taipan antivenom described in this study compares favourably with the currently used F(ab’)2 antivenom, both in terms of physicochemical characteristics and neutralising potency. Therefore, it should be considered as a promising low-cost candidate for the treatment of envenomings by O. scutellatus in PNG, and is ready to be tested in clinical trials.This study was supported by Vicerrectoría de Investigación, Universidad de Costa Rica (project 741-A9-003); the PNG Office of Higher Education, CTP Limited (Milne Bay Estates), and the Australian Venom Research Unit (University of Melbourne), which is funded by the Australian Government Department of Health and Ageing, the Australia Pacific Science Foundation and Snowy Nominees. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.UCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias de la Salud::Instituto Clodomiro Picado (ICP