Search results for "itt"

Posterior reversible encephalopathy syndrome revealing acute intermittent porphyria

2016

Microbial diversity along a gradient in peatlands treating mining-affected waters.

2018

Peatlands are used for the purification of mining-affected waters in Northern Finland. In Northern climate, microorganisms in treatment peatlands (TPs) are affected by long and cold winters, but studies about those microorganisms are scarce. Thus, the bacterial, archaeal and fungal communities along gradients of mine water influence in two TPs were investigated. The TPs receive waters rich in contaminants, including arsenic (As), sulfate (SO42-) and nitrate (NO3-). Microbial diversity was high in both TPs, and microbial community composition differed between the studied TPs. Bacterial communities were dominated by Proteobacteria, Actinobacteria, Chloroflexi and Acidobacteria, archaeal commu…

2019

Background: Network science provides powerful access to essential organizational principles of the brain. The aim of this study was to investigate longitudinal evolution of gray matter networks in early relapsing–remitting MS (RRMS) compared with healthy controls (HCs) and contrast network dynamics with conventional atrophy measurements. Methods: For our longitudinal study, we investigated structural cortical networks over 1 year derived from 3T MRI in 203 individuals (92 early RRMS patients with mean disease duration of 12.1 ± 14.5 months and 101 HCs). Brain networks were computed based on cortical thickness inter-regional correlations and fed into graph theoretical analysis. Network conne…

State transition identification in multivariate time series (STIMTS) applied to rotational jump trajectories from single molecules

2018

Time resolved data from single molecule experiments often suffer from contamination with noise due to a low signal level. Identifying a proper model to describe the data thus requires an approach with sufficient model parameters without misinterpreting the noise as relevant data. Here, we report on a generalized data evaluation process to extract states with piecewise constant signal level from simultaneously recorded multivariate data, typical for multichannel single molecule experiments. The method employs the minimum description length principle to avoid overfitting the data by using an objective function, which is based on a tradeoff between fitting accuracy and model complexity. We val…

Molecular detection of Borrelia burgdorferi sensu lato – An analytical comparison of real-time PCR protocols from five different Scandinavian laborat…

2017

Introduction Lyme borreliosis (LB) is the most common tick transmitted disease in Europe. The diagnosis of LB today is based on the patient A s medical history, clinical presentation and laboratory findings. The laboratory diagnostics are mainly based on antibody detection, but in certain conditions molecular detection by polymerase chain reaction (PCR) may serve as a complement. Aim The purpose of this study was to evaluate the analytical sensitivity, analytical specificity and concordance of eight different real-time PCR methods at five laboratories in Sweden, Norway and Denmark. Method Each participating laboratory was asked to analyse three different sets of samples (reference panels; a…

Automatic sleep scoring: A deep learning architecture for multi-modality time series

2020

Background: Sleep scoring is an essential but time-consuming process, and therefore automatic sleep scoring is crucial and urgent to help address the growing unmet needs for sleep research. This paper aims to develop a versatile deep-learning architecture to automate sleep scoring using raw polysomnography recordings. Method: The model adopts a linear function to address different numbers of inputs, thereby extending model applications. Two-dimensional convolution neural networks are used to learn features from multi-modality polysomnographic signals, a “squeeze and excitation” block to recalibrate channel-wise features, together with a long short-term memory module to exploit long-range co…

The IASLC Lung Cancer Staging Project: Proposals for Revision of the TNM Stage Groupings in the Forthcoming (Eighth) Edition of the TNM Classificatio…

2016

AbstractThe IASLC Staging and Prognostic Factors Committee has collected a new database of 94,708 cases donated from 35 sources in 16 countries around the globe. This has now been analysed by our statistical partners at Cancer Research And Biostatistics and, in close collaboration with the members of the committee proposals have been developed for the T, N, and M categories of the 8th edition of the TNM Classification for lung cancer due to be published late 2016. In this publication we describe the methods used to evaluate the resultant Stage groupings and the proposals put forward for the 8th edition.

Ortervirales: New Virus Order Unifying Five Families of Reverse-Transcribing Viruses

2018

International audience; Reverse-transcribing viruses, which synthesize a copy of genomic DNA from an RNA template, are widespread in animals, plants, algae, and fungi (1, 2). This broad distribution suggests the ancient origin(s) of these viruses, possibly [...]

Visual Working Memory Requires Permissive and Instructive NO/cGMP Signaling at Presynapses in the Drosophila Central Brain.

2017

The gaseous second messenger nitric oxide (NO) has been shown to regulate memory formation by activating retrograde signaling cascades from post- to presynapse that involve cyclic guanosine monophosphate (cGMP) production to induce synaptic plasticity and transcriptional changes. In this study, we analyzed the role of NO in the formation of a visual working memory that lasts only a few seconds. This memory is encoded in a subset of ring neurons that form the ellipsoid body in the Drosophila brain. Using genetic and pharmacological manipulations, we show that NO signaling is required for cGMP-mediated CREB activation, leading to the expression of competence factors like the synaptic homer pr…

Clustering of low-correlated spatial gene expression patterns in the mouse brain in the Allen Brain Atlas

2018

In this paper, clustering techniques are applied to spatial gene expression patterns with a low genomic correlation between the sagittal and coronal projections. The data analysed here are hosted on an available public DB named ABA (Allen Brain Atlas). The results are compared to those obtained by Bohland et al. on the complementary dataset (high correlation values). We prove that, by analysing a reduced dataset,hence reducing the computational burden, we get the same accuracy in highlighting different neuroanatomical region.