149 research outputs found

    Joint Segmentation and Uncertainty Visualization of Retinal Layers in Optical Coherence Tomography Images using Bayesian Deep Learning

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    Optical coherence tomography (OCT) is commonly used to analyze retinal layers for assessment of ocular diseases. In this paper, we propose a method for retinal layer segmentation and quantification of uncertainty based on Bayesian deep learning. Our method not only performs end-to-end segmentation of retinal layers, but also gives the pixel wise uncertainty measure of the segmentation output. The generated uncertainty map can be used to identify erroneously segmented image regions which is useful in downstream analysis. We have validated our method on a dataset of 1487 images obtained from 15 subjects (OCT volumes) and compared it against the state-of-the-art segmentation algorithms that does not take uncertainty into account. The proposed uncertainty based segmentation method results in comparable or improved performance, and most importantly is more robust against noise

    Combined systems approaches reveal highly plastic responses to antimicrobial peptide challenge in Escherichia coli

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    Obtaining an in-depth understanding of the arms races between peptides comprising the innate immune response and bacterial pathogens is of fundamental interest and will inform the development of new antibacterial therapeutics. We investigated whether a whole organism view of antimicrobial peptide (AMP) challenge on Escherichia coli would provide a suitably sophisticated bacterial perspective on AMP mechanism of action. Selecting structurally and physically related AMPs but with expected differences in bactericidal strategy, we monitored changes in bacterial metabolomes, morphological features and gene expression following AMP challenge at sub-lethal concentrations. For each technique, the vast majority of changes were specific to each AMP, with such a plastic response indicating E. coli is highly capable of discriminating between specific antibiotic challenges. Analysis of the ontological profiles generated from the transcriptomic analyses suggests this approach can accurately predict the antibacterial mode of action, providing a fresh, novel perspective for previous functional and biophysical studies

    Silent cerebral infarct after cardiac catheterization as detected by diffusion weighted Magnetic Resonance Imaging: a randomized comparison of radial and femoral arterial approaches

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    Background and objective: Cerebral microembolism detected by transcranial Doppler (TCD) occurs systematically during cardiac catheterization, but its clinical relevance, remains unknown. Studies suggest that asymptomatic embolic cerebral infarction detectable by diffusion-weighted (DW) MRI might exist after percutaneous cardiac interventions with a frequency as high as 15 to 22% of cases. We have set up, for the first time, a prospective multicenter trial to assess the rate of silent cerebral infarction after cardiac catheterization and to compare the impact of the arterial access site, comparing radial and femoral access, on this phenomenon. Study design: This prospective study will be performed in patients with severe aortic valve stenosis. To assess the occurrence of cerebral infarction, all patients will undergo cerebral DW-MRI and neurological assessment within 24 hours before, and 48 hours after cardiac catheterization and retrograde catheterization of the aortic valve. Randomization for the access site will be performed before coronary angiography. A subgroup will be monitored by transcranial power M-mode Doppler during cardiac catheterization to observe cerebral blood flow and track emboli. Neuropsychological tests will also be recorded in a subgroup of patients before and after the interventional procedures to assess the impact of silent brain injury on potential cognitive decline. The primary end-point of the study is a direct comparison of ischemic cerebral lesions as detected by serial cerebral DW-MRI between patients explored by radial access and patients explored by femoral access. Secondary end-points include comparison of neuropsychological test performance and number of microembolism signals observed in the two groups. Implications: Using serial DW-MRI, silent cerebral infarction rate will be defined and the potential influence of vascular access site will be evaluated. Silent cerebral infarction might be a major concern during cardiac catheterization and its potential relationship to cognitive decline needs to be assessed. Study registration: The SCIPION study is registered through National Institutes of Health-sponsored clinical trials registry and has been assigned the Identifier: NCT 00329979

    ErbB2, EphrinB1, Src Kinase and PTPN13 Signaling Complex Regulates MAP Kinase Signaling in Human Cancers

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    In non-cancerous cells, phosphorylated proteins exist transiently, becoming de-phosphorylated by specific phosphatases that terminate propagation of signaling pathways. In cancers, compromised phosphatase activity and/or expression occur and contribute to tumor phenotype. The non-receptor phosphatase, PTPN13, has recently been dubbed a putative tumor suppressor. It decreased expression in breast cancer correlates with decreased overall survival. Here we show that PTPN13 regulates a new signaling complex in breast cancer consisting of ErbB2, Src, and EphrinB1. To our knowledge, this signaling complex has not been previously described. Co-immunoprecipitation and localization studies demonstrate that EphrinB1, a PTPN13 substrate, interacts with ErbB2. In addition, the oncogenic V660E ErbB2 mutation enhances this interaction, while Src kinase mediates EphrinB1 phosphorylation and subsequent MAP Kinase signaling. Decreased PTPN13 function further enhances signaling. The association of oncogene kinases (ErbB2, Src), a signaling transmembrane ligand (EphrinB1) and a phosphatase tumor suppressor (PTPN13) suggest that EphrinB1 may be a relevant therapeutic target in breast cancers harboring ErbB2-activating mutations and decreased PTPN13 expression

    Differential Response to Soil Salinity in Endangered Key Tree Cactus: Implications for Survival in a Changing Climate

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    Understanding reasons for biodiversity loss is essential for developing conservation and management strategies and is becoming increasingly urgent with climate change. Growing at elevations <1.4 m in the Florida Keys, USA, the endangered Key tree cactus (Pilosocereus robinii) experienced 84 percent loss of total stems from 1994 to 2007. The most severe losses of 99 and 88 percent stems occurred in the largest populations in the Lower Keys, where nine storms with high wind velocities and storm surges, occurred during this period. In contrast, three populations had substantial stem proliferation. To evaluate possible mortality factors related to changes in climate or forest structure, we examined habitat variables: soil salinity, elevation, canopy cover, and habitat structure near 16 dying or dead and 18 living plants growing in the Lower Keys. Soil salinity and elevation were the preliminary factors that discriminated live and dead plants. Soil salinity was 1.5 times greater, but elevation was 12 cm higher near dead plants than near live plants. However, distribution-wide stem loss was not significantly related to salinity or elevation. Controlled salinity trials indicated that salt tolerance to levels above 40 mM NaCl was related to maternal origin. Salt sensitive plants from the Lower Keys had less stem growth, lower root:shoot ratios, lower potassium: sodium ratios and lower recovery rate, but higher δ 13C than a salt tolerant lineage of unknown origin. Unraveling the genetic structure of salt tolerant and salt sensitive lineages in the Florida Keys will require further genetic tests. Worldwide rare species restricted to fragmented, low-elevation island habitats, with little or no connection to higher ground will face challenges from climate change-related factors. These great conservation challenges will require traditional conservation actions and possibly managed relocation that must be informed by studies such as these

    Investigating Tissue Optical Properties and Texture Descriptors of the Retina in Patients with Multiple Sclerosis

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    PURPOSE: To assess the differences in texture descriptors and optical properties of retinal tissue layers in patients with multiple sclerosis (MS) and to evaluate their usefulness in the detection of neurodegenerative changes using optical coherence tomography (OCT) image segmentation. PATIENTS AND METHODS: 38 patients with MS were examined using Stratus OCT. The raw macular OCT data were exported and processed using OCTRIMA software. The enrolled eyes were divided into two groups, based on the presence of optic neuritis (ON) in the history (MSON+ group, n = 36 and MSON- group, n = 31). Data of 29 eyes of 24 healthy subjects (H) were used as controls. A total of seven intraretinal layers were segmented and thickness as well as optical parameters such as contrast, fractal dimension, layer index and total reflectance were measured. Mixed-model ANOVA analysis was used for statistical comparisons. RESULTS: Significant thinning of the retinal nerve fiber layer (RNFL), ganglion cell/inner plexiform layer complex (GCL+IPL) and ganglion cell complex (GCC, RNFL+GCL+IPL) was observed between study groups in all comparisons. Significant difference was found in contrast in the RNFL, GCL+IPL, GCC, inner nuclear layer (INL) and outer plexiform layer when comparing MSON+ to the other groups. Higher fractal dimension values were observed in GCL+IPL and INL layers when comparing H vs. MSON+ groups. A significant difference was found in layer index in the RNFL, GCL+IPL and GCC layers in all comparisons. A significant difference was observed in total reflectance in the RNFL, GCL+IPL and GCC layers between the three examination groups. CONCLUSION: Texture and optical properties of the retinal tissue undergo pronounced changes in MS even without optic neuritis. Our results may help to further improve the diagnostic efficacy of OCT in MS and neurodegeneration

    Fast Retinal Vessel Detection and Measurement Using Wavelets and Edge Location Refinement

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    The relationship between changes in retinal vessel morphology and the onset and progression of diseases such as diabetes, hypertension and retinopathy of prematurity (ROP) has been the subject of several large scale clinical studies. However, the difficulty of quantifying changes in retinal vessels in a sufficiently fast, accurate and repeatable manner has restricted the application of the insights gleaned from these studies to clinical practice. This paper presents a novel algorithm for the efficient detection and measurement of retinal vessels, which is general enough that it can be applied to both low and high resolution fundus photographs and fluorescein angiograms upon the adjustment of only a few intuitive parameters. Firstly, we describe the simple vessel segmentation strategy, formulated in the language of wavelets, that is used for fast vessel detection. When validated using a publicly available database of retinal images, this segmentation achieves a true positive rate of 70.27%, false positive rate of 2.83%, and accuracy score of 0.9371. Vessel edges are then more precisely localised using image profiles computed perpendicularly across a spline fit of each detected vessel centreline, so that both local and global changes in vessel diameter can be readily quantified. Using a second image database, we show that the diameters output by our algorithm display good agreement with the manual measurements made by three independent observers. We conclude that the improved speed and generality offered by our algorithm are achieved without sacrificing accuracy. The algorithm is implemented in MATLAB along with a graphical user interface, and we have made the source code freely available

    Non-Steroidal Anti-Inflammatory Drugs and Cognitive Function: Are Prostaglandins at the Heart of Cognitive Impairment in Dementia and Delirium ?

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    Studies of non-steroidal anti-inflammatory drugs (NSAIDs) in rheumatoid arthritis imply that inflammation is important in the development of Alzheimer’s disease (AD). However, these drugs have not alleviated the symptoms of AD in those who have already developed dementia. This suggests that the primary mediator targeted by these drugs, PGE2, is not actively suppressing memory function in AD. Amyloid-β oligomers appear to be important for the mild cognitive changes seen in AD transgenic mice, yet amyloid immunotherapy has also proven unsuccessful in clinical trials. Collectively, these findings indicate that NSAIDs may target a prodromal process in mice that has already passed in those diagnosed with AD, and that synaptic and neuronal loss are key determinants of cognitive dysfunction in AD. While the role of inflammation has not yet become clear, inflammatory processes definitely have a negative impact on cognitive function during episodes of delirium during dementia. Delirium is an acute and profound impairment of cognitive function frequently occurring in aged and demented patients exposed to systemic inflammatory insults, which is now recognised to contribute to long-term cognitive decline. Recent work in animal models is beginning to shed light on the interactions between systemic inflammation and CNS pathology in these acute exacerbations of dementia. This review will assess the role of prostaglandin synthesis in the memory impairments observed in dementia and delirium and will examine the relative contribution of amyloid, synaptic and neuronal loss. We will also discuss how understanding the role of inflammatory mediators in delirious episodes will have major implications for ameliorating the rate of decline in the demented population
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