7,555 research outputs found
FoxM1B regulates NEDD4-1 expression, leading to cellular transformation and full malignant phenotype in immortalized human astrocytes.
Our recent studies have shown that the FoxM1B transcription factor is overexpressed in human glioma tissues and that the level of its expression correlates directly with glioma grade. However, whether FoxM1B plays a role in the early development of glioma (i.e., in transformation) is unknown. In this study, we found that the FoxM1B molecule causes cellular transformation and tumor formation in normal human astrocytes (NHA) immortalized by p53 and pRB inhibition. Moreover, brain tumors that arose from intracranial injection of FoxM1B-expressing immortalized NHAs displayed glioblastoma multiforme (GBM) phenotypes, suggesting that FoxM1B overexpression in immortalized NHAs not only transforms the cells but also leads to GBM formation. Mechanistically, our results showed that overexpression of FoxM1B upregulated NEDD4-1, an E3 ligase that mediates the degradation and downregulation of phosphatase and tensin homologue (PTEN) in multiple cell lines. Decreased PTEN in turn resulted in the hyperactivation of Akt, which led to phosphorylation and cytoplasmic retention of FoxO3a. Blocking Akt activation with phosphoinositide 3-kinase/Akt inhibitors inhibited the FoxM1B-induced transformation of immortalized NHAs. Furthermore, overexpression of FoxM1B in immortalized NHAs increased the expression of survivin, cyclin D1, and cyclin E, which are important molecules for tumor growth. Collectively, these results indicate that overexpression of FoxM1B, in cooperation with p53 and pRB inhibition in NHA cells, promotes astrocyte transformation and GBM formation through multiple mechanisms
Neurological Soft Signs Are Not "Soft" in Brain Structure and Functional Networks: Evidence From ALE Meta-Analysis
Background: Neurological soft signs (NSS) are associated with schizophrenia and related psychotic disorders. NSS have been conventionally considered as clinical neurological signs without localized brain regions. However, recent brain imaging studies suggest that NSS are partly localizable and may be associated with deficits in specific brain areas. Method: We conducted an activation likelihood estimation meta-analysis to quantitatively review structural and functional imaging studies that evaluated the brain correlates of NSS in patients with schizophrenia and other psychotic disorders. Six structural magnetic resonance imaging (sMRI) and 15 functional magnetic -resonance imaging (fMRI) studies were included. Results: The results from meta-analysis of the sMRI studies-indicated that NSS were associated with atrophy of the precentral gyrus, the cerebellum, the inferior frontal gyrus, and the thalamus. The results from meta-analysis of the fMRI studies demonstrated that the NSS-related task was significantly associated with altered brain activation in the inferior frontal gyrus, bilateral putamen, the cerebellum, and the superior temporal gyrus. Conclusions: Ourfindings from both sMRI and fMRI meta-analyses further support the conceptualization of NSS as a manifestation of the "cerebello-thalamo-prefrontal" brain network model of schizophrenia and related psychotic disorders
A hierarchical key pre-distribution scheme for fog networks
Security in fog computing is multi-faceted, and one particular challenge is establishing a secure communication channel between fog nodes and end devices. This emphasizes the importance of designing efficient and secret key distribution scheme to facilitate fog nodes and end devices to establish secure communication channels. Existing secure key distribution schemes designed for hierarchical networks may be deployable in fog computing, but they incur high computational and communication overheads and thus consume significant memory. In this paper, we propose a novel hierarchical key pre-distribution scheme based on âResidual Designâ for fog networks. The proposed key distribution scheme is designed to minimize storage overhead and memory consumption, while increasing network scalability. The scheme is also designed to be secure against node capture attacks. We demonstrate that in an equal-size network, our scheme achieves around 84% improvement in terms of node storage overhead, and around 96% improvement in terms of network scalability. Our research paves the way for building an efficient key management framework for secure communication within the hierarchical network of fog nodes and end devices.
KEYWORDS: Fog Computing, Key distribution, Hierarchical Networks
Are Foreign Firms Privileged By Their Host Governments? Evidence From The 2000 World Business Environment Survey
Using the data from World Business Environment Survey (WBES) on over 10,000 firms across eighty one countries, this paper finds preliminary evidence that foreign firms enjoy significant regulatory advantages - as perceived by the firms themselves - over domestic firms. The findings on regulatory advantages of foreign firms hold with a variety of alternative measures of regulations and with or without firm- and country-level attributes and industry and country controls. There is also evidence that foreign firms' regulatory advantages are especially substantial vis-a-vis the politically weak domestic firms. Furthermore, the regulatory advantages of foreign firms appear stronger in corrupt countries than in non-corrupt countries
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Defining language networks from resting-state fMRI for surgical planning-a feasibility study
Presurgical language mapping for patients with lesions close to language areas is critical to neurosurgical decision-making for preservation of language function. As a clinical noninvasive imaging technique, functional MRI (fMRI) is used to identify language areas by measuring blood-oxygen-level dependent (BOLD) signal change while patients perform carefully timed language vs. control tasks. This task-based fMRI critically depends on task performance, excluding many patients who have difficulty performing language tasks due to neurologic deficits. On the basis of recent discovery of resting-state fMRI (rs-fMRI), we propose a âtask-freeâ paradigm acquiring fMRI data when patients simply are at rest. This paradigm is less demanding for patients to perform and easier for technologists to administer. We investigated the feasibility of this approach in right-handed healthy control subjects. First, group independent component analysis (ICA) was applied on the training group (14 subjects) to identify group level language components based on expert rating results. Then, four empirically and structurally defined language network templates were assessed for their ability to identify language components from individuals' ICA output of the testing group (18 subjects) based on spatial similarity analysis. Results suggest that it is feasible to extract language activations from rs-fMRI at the individual subject level, and two empirically defined templates (that focuses on frontal language areas and that incorporates both frontal and temporal language areas) demonstrated the best performance. We propose a semi-automated language component identification procedure and discuss the practical concerns and suggestions for this approach to be used in clinical fMRI language mapping
Expert-centered Evaluation of Deep Learning Algorithms for Brain Tumor Segmentation
Purpose To present results from a literature survey on practices in deep learning segmentation algorithm evaluation and perform a study on expert quality perception of brain tumor segmentation. Materials and Methods A total of 180 articles reporting on brain tumor segmentation algorithms were surveyed for the reported quality evaluation. Additionally, ratings of segmentation quality on a four-point scale were collected from medical professionals for 60 brain tumor segmentation cases. Results Of the surveyed articles, Dice score, sensitivity, and Hausdorff distance were the most popular metrics to report segmentation performance. Notably, only 2.8% of the articles included clinical experts\u27 evaluation of segmentation quality. The experimental results revealed a low interrater agreement (Krippendorff Îą, 0.34) in experts\u27 segmentation quality perception. Furthermore, the correlations between the ratings and commonly used quantitative quality metrics were low (Kendall tau between Dice score and mean rating, 0.23; Kendall tau between Hausdorff distance and mean rating, 0.51), with large variability among the experts. Conclusion The results demonstrate that quality ratings are prone to variability due to the ambiguity of tumor boundaries and individual perceptual differences, and existing metrics do not capture the clinical perception of segmentation quality
Magnetic Field and Pressure Phase Diagrams of Uranium Heavy-Fermion Compound UZn
We have performed magnetization measurements at high magnetic fields of up to
53 T on single crystals of a uranium heavy-fermion compound UZn
grown by the Bridgman method. In the antiferromagnetic state below the N\'{e}el
temperature = 9.7 K, a metamagnetic transition is found at
32 T for the field along the [110] direction (-axis). The
magnetic phase diagram for the field along the [110] direction is
given. The magnetization curve shows a nonlinear increase at 35
T in the paramagnetic state above up to a characteristic
temperature where the magnetic susceptibility or
electrical resistivity shows a maximum value. This metamagnetic behavior of the
magnetization at is discussed in comparison with the metamagnetic
magnetism of the heavy-fermion superconductors UPt, URuSi, and
UPdAl. We have also carried out high-pressure resistivity measurement
on UZn using a diamond anvil cell up to 8.7 GPa. Noble gas argon was
used as a pressure-transmitting medium to ensure a good hydrostatic
environment. The N\'{e}el temperature is almost
pressure-independent up to 4.7 GPa and starts to increase in the
higher-pressure region. The pressure dependences of the coefficient of the
term in the electrical resistivity , the antiferromagnetic gap
, and the characteristic temperature are
discussed. It is found that the effect of pressure on the electronic states in
UZn is weak compared with those in the other heavy fermion
compounds
The molecular characterisation of Escherichia coli K1 isolated from neonatal nasogastric feeding tubes
Background: The most common cause of Gram-negative bacterial neonatal meningitis is E. coli K1. It has a mortality rate of 10â15%, and neurological sequelae in 30â 50% of cases. Infections can be attributable to nosocomial sources, however the pre-colonisation of enteral feeding tubes has not been considered as a specific risk factor. Methods: Thirty E. coli strains, which had been isolated in an earlier study, from the residual lumen liquid and biofilms of neonatal nasogastric feeding tubes were genotyped using pulsed-field gel electrophoresis, and 7-loci multilocus sequence typing. Potential pathogenicity and biofilm associated traits were determined using specific PCR probes, genome analysis, and in vitro tissue culture assays. Results: The E. coli strains clustered into five pulsotypes, which were genotyped as sequence types (ST) 95, 73, 127, 394 and 2076 (Achman scheme). The extra-intestinal pathogenic E. coli (ExPEC) phylogenetic group B2 ST95 serotype O1:K1:NM strains had been isolated over a 2 week period from 11 neonates who were on different feeding regimes. The E. coli K1 ST95 strains encoded for various virulence traits associated with neonatal meningitis and extracellular matrix formation. These strains attached and invaded intestinal, and both human and rat brain cell lines, and persisted for 48 h in U937 macrophages. E. coli STs 73, 394 and 2076 also persisted in macrophages and invaded Caco-2 and human brain cells, but only ST394 invaded rat brain cells. E. coli ST127 was notable as it did not invade any cell lines. Conclusions: Routes by which E. coli K1 can be disseminated within a neonatal intensive care unit are uncertain, however the colonisation of neonatal enteral feeding tubes may be one reservoir source which could constitute a serious health risk to neonates following ingestion
Joint EANM/EANO/RANO/SNMMI practice guideline/procedure standards for diagnostics and therapy (theranostics) of meningiomas using radiolabeled somatostatin receptor ligands:version 1.0
Purpose To provide practice guideline/procedure standards for diagnostics and therapy (theranostics) of meningiomas using radiolabeled somatostatin receptor (SSTR) ligands.Methods This joint practice guideline/procedure standard was collaboratively developed by the European Association of Nuclear Medicine (EANM), the Society of Nuclear Medicine and Molecular Imaging (SNMMI), the European Association of Neurooncology (EANO), and the PET task force of the Response Assessment in Neurooncology Working Group (PET/RANO).Results Positron emission tomography (PET) using somatostatin receptor (SSTR) ligands can detect meningioma tissue with high sensitivity and specificity and may provide clinically relevant information beyond that obtained from structural magnetic resonance imaging (MRI) or computed tomography (CT) imaging alone. SSTR-directed PET imaging can be particularly useful for differential diagnosis, delineation of meningioma extent, detection of osseous involvement, and the differentiation between posttherapeutic scar tissue and tumour recurrence. Moreover, SSTR-peptide receptor radionuclide therapy (PRRT) is an emerging investigational treatment approach for meningioma.Conclusion These practice guidelines will define procedure standards for the application of PET imaging in patients with meningiomas and related SSTR-targeted PRRTs in routine practice and clinical trials and will help to harmonize data acquisition and interpretation across centers, facilitate comparability of studies, and to collect larger databases. The current document provides additional information to the evidence-based recommendations from the PET/RANO Working Group regarding the utilization of PET imaging in meningiomas Galldiks (Neuro Oncol. 2017;19(12):1576-87). The information provided should be considered in the context of local conditions and regulations
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