Creating the Workforce of the Future: A Requirements Analysis

This paper focuses on the theme of workforce preparation

Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: The CADDementia challenge

Algorithms for computer-aided diagnosis of dementia based on structural MRI have demonstrated high performance in the literature, but are difficult to compare as different data sets and methodology were used for evaluation. In addition, it is unclear how the algorithms would perform on previously unseen data, and thus, how they would perform in clinical practice when there is no real opportunity to adapt the algorithm to the data at hand. To address these comparability, generalizability and clinical applicability issues, we organized a grand challenge that aimed to objectively compare algorithms based on a clinically representative multi-center data set. Using clinical practice as the starting point, the goal was to reproduce the clinical diagnosis. Therefore, we evaluated algorithms for multi-class classification of three diagnostic groups: patients with probable Alzheimer's disease, patients with mild cognitive impairment and healthy controls. The diagnosis based on clinical criteria was used as reference standard, as it was the best available reference despite its known limitations. For evaluation, a previously unseen test set was used consisting of 354 T1-weighted MRI scans with the diagnoses blinded. Fifteen research teams participated with a total of 29 algorithms. The algorithms were trained on a small training set (n = 30) and optionally on data from other sources (e.g., the Alzheimer's Disease Neuroimaging Initiative, the Australian Imaging Biomarkers and Lifestyle flagship study of aging). The best performing algorithm yielded an accuracy of 63.0% and an area under the receiver-operating-characteristic curve (AUC) of 78.8%. In general, the best performances were achieved using feature extraction based on voxel-based morphometry or a combination of features that included volume, cortical thickness, shape and intensity. The challenge is open for new submissions via the web-based framework: http://caddementia.grand-challenge.org

MERS-CoV 4b protein interferes with the NF-κB-dependent innate immune response during infection

This work is licensed under a Creative Commons Attribution 4.0 International License.Middle East respiratory syndrome coronavirus (MERS-CoV) is a novel human coronavirus that emerged in 2012, causing severe pneumonia and acute respiratory distress syndrome (ARDS), with a case fatality rate of ~36%. When expressed in isolation, CoV accessory proteins have been shown to interfere with innate antiviral signaling pathways. However, there is limited information on the specific contribution of MERS-CoV accessory protein 4b to the repression of the innate antiviral response in the context of infection. We found that MERS-CoV 4b was required to prevent a robust NF-κB dependent response during infection. In wild-type virus infected cells, 4b localized to the nucleus, while NF-κB was retained in the cytoplasm. In contrast, in the absence of 4b or in the presence of cytoplasmic 4b mutants lacking a nuclear localization signal (NLS), NF-κB was translocated to the nucleus leading to the expression of pro-inflammatory cytokines. This indicates that NF-κB repression required the nuclear import of 4b mediated by a specific NLS. Interestingly, we also found that both in isolation and during infection, 4b interacted with α-karyopherin proteins in an NLS-dependent manner. In particular, 4b had a strong preference for binding karyopherin-α4 (KPNA4), which is known to translocate the NF-κB protein complex into the nucleus. Binding of 4b to KPNA4 during infection inhibited its interaction with NF-κB-p65 subunit. Thereby we propose a model where 4b outcompetes NF-κB for KPNA4 binding and translocation into the nucleus as a mechanism of interference with the NF-κB-mediated innate immune response

Severe Acute Respiratory Syndrome Coronavirus Envelope Protein Regulates Cell Stress Response and Apoptosis

Severe acute respiratory syndrome virus (SARS-CoV) that lacks the envelope (E) gene (rSARS-CoV-ΔE) is attenuated in vivo. To identify factors that contribute to rSARS-CoV-ΔE attenuation, gene expression in cells infected by SARS-CoV with or without E gene was compared. Twenty-five stress response genes were preferentially upregulated during infection in the absence of the E gene. In addition, genes involved in signal transduction, transcription, cell metabolism, immunoregulation, inflammation, apoptosis and cell cycle and differentiation were differentially regulated in cells infected with rSARS-CoV with or without the E gene. Administration of E protein in trans reduced the stress response in cells infected with rSARS-CoV-ΔE or with respiratory syncytial virus, or treated with drugs, such as tunicamycin and thapsigargin that elicit cell stress by different mechanisms. In addition, SARS-CoV E protein down-regulated the signaling pathway inositol-requiring enzyme 1 (IRE-1) of the unfolded protein response, but not the PKR-like ER kinase (PERK) or activating transcription factor 6 (ATF-6) pathways, and reduced cell apoptosis. Overall, the activation of the IRE-1 pathway was not able to restore cell homeostasis, and apoptosis was induced probably as a measure to protect the host by limiting virus production and dissemination. The expression of proinflammatory cytokines was reduced in rSARS-CoV-ΔE-infected cells compared to rSARS-CoV-infected cells, suggesting that the increase in stress responses and the reduction of inflammation in the absence of the E gene contributed to the attenuation of rSARS-CoV-ΔE

Preparing for the Challenge of a Global Workforce: A Study of Training and Enterprise Councils in Wales

Abstract not available

The Role of Knowledge Management in Balancing Exploration and Exploitation in E-Commerce Firms

This article focuses on the role of knowledge management and organizational learning in e-commerce firms as they develop and prosper; theoretical and applied issues of balancing exploration and exploitation for their survival, growth, and profitability are discussed. Knowledge management is presented as central to learning that facilitates long-term success. The concept of micro-formalization related to Agile management practices is proposed as an approach that allows young companies in dynamic sectors to implement learning systems with an adequate but minimal level of formalization without experiencing crises inherent to traditional life-cycle models, and without resorting to rigid procedures which stifle creativity