Advanced Magnetic Resonance Imaging in Glioblastoma: A Review

INTRODUCTION In 2017, it is estimated that 26,070 patients will be diagnosed with a malignant primary brain tumor in the United States, with more than half having the diagnosis of glioblas- toma (GBM).1 Magnetic resonance imaging (MRI) is a widely utilized examination in the diagnosis and post-treatment management of patients with glioblastoma; standard modalities available from any clinical MRI scanner, including T1, T2, T2-FLAIR, and T1-contrast-enhanced (T1CE) sequences, provide critical clinical information. In the last decade, advanced imaging modalities are increasingly utilized to further charac- terize glioblastomas. These include multi-parametric MRI sequences, such as dynamic contrast enhancement (DCE), dynamic susceptibility contrast (DSC), diffusion tensor imaging (DTI), functional imaging, and spectroscopy (MRS), to further characterize glioblastomas, and significant efforts are ongoing to implement these advanced imaging modalities into improved clinical workflows and personalized therapy approaches. A contemporary review of standard and advanced MR imaging in clinical neuro-oncologic practice is presented

DeltaPhish: Detecting Phishing Webpages in Compromised Websites

The large-scale deployment of modern phishing attacks relies on the automatic exploitation of vulnerable websites in the wild, to maximize profit while hindering attack traceability, detection and blacklisting. To the best of our knowledge, this is the first work that specifically leverages this adversarial behavior for detection purposes. We show that phishing webpages can be accurately detected by highlighting HTML code and visual differences with respect to other (legitimate) pages hosted within a compromised website. Our system, named DeltaPhish, can be installed as part of a web application firewall, to detect the presence of anomalous content on a website after compromise, and eventually prevent access to it. DeltaPhish is also robust against adversarial attempts in which the HTML code of the phishing page is carefully manipulated to evade detection. We empirically evaluate it on more than 5,500 webpages collected in the wild from compromised websites, showing that it is capable of detecting more than 99% of phishing webpages, while only misclassifying less than 1% of legitimate pages. We further show that the detection rate remains higher than 70% even under very sophisticated attacks carefully designed to evade our system.Comment: Preprint version of the work accepted at ESORICS 201

Unsupervised Polygonal Reconstruction of Noisy Contours by a Discrete Irregular Approach

International audienceIn this paper, we present an original algorithm to build a polygonal reconstruction of noisy digital contours. For this purpose, we first improve an algorithm devoted to the vectorization of discrete irregular isothetic objects. Afterwards we propose to use it to define a reconstruction process of noisy digital contours. More precisely, we use a local noise detector, introduced by Kerautret and Lachaud in IWCIA 2009, that builds a multi-scale representation of the digital contour, which is composed of pixels of various size depending of the local amount of noise. Finally, we compare our approach with previous works, by con- sidering the Hausdorff distance and the error on tangent orientations of the computed line segments to the original perfect contour. Thanks to both synthetic and real noisy objects, we show that our approach has interesting performance, and could be applied in document analysis systems

An MPEG-7 scheme for semantic content modelling and filtering of digital video

Abstract Part 5 of the MPEG-7 standard specifies Multimedia Description Schemes (MDS); that is, the format multimedia content models should conform to in order to ensure interoperability across multiple platforms and applications. However, the standard does not specify how the content or the associated model may be filtered. This paper proposes an MPEG-7 scheme which can be deployed for digital video content modelling and filtering. The proposed scheme, COSMOS-7, produces rich and multi-faceted semantic content models and supports a content-based filtering approach that only analyses content relating directly to the preferred content requirements of the user. We present details of the scheme, front-end systems used for content modelling and filtering and experiences with a number of users

NRG/RTOG 0837: Randomized, Phase II, Double-Blind, Placebo-Controlled Trial of Chemoradiation With or Without Cediranib in Newly Diagnosed Glioblastoma

BACKGROUND: A randomized, phase II, placebo-controlled, and blinded clinical trial (NCT01062425) was conducted to determine the efficacy of cediranib, an oral pan-vascular endothelial growth factor receptor tyrosine kinase inhibitor, versus placebo in combination with radiation and temozolomide in newly diagnosed glioblastoma. METHODS: Patients with newly diagnosed glioblastoma were randomly assigned 2:1 to receive (1) cediranib (20 mg) in combination with radiation and temozolomide; (2) placebo in combination with radiation and temozolomide. The primary endpoint was 6-month progression-free survival (PFS) based on blinded, independent radiographic assessment of postcontrast T1-weighted and noncontrast T2-weighted MRI brain scans and was tested using a 1-sided RESULTS: One hundred and fifty-eight patients were randomized, out of which 9 were ineligible and 12 were not evaluable for the primary endpoint, leaving 137 eligible and evaluable. 6-month PFS was 46.6% in the cediranib arm versus 24.5% in the placebo arm ( CONCLUSIONS: This study met its primary endpoint of prolongation of 6-month PFS with cediranib in combination with radiation and temozolomide versus placebo in combination with radiation and temozolomide. There was no difference in overall survival between the 2 arms

Identification, Expression and Target Gene Analyses of MicroRNAs in Spodoptera litura

MicroRNAs (miRNAs) are small RNAs widely present in animals and plants and involved in post-transcriptional regulation of gene transcripts. In this study we identified and validated 58 miRNAs from an EST dataset of Spodoptera litura based on the computational and experimental analysis of sequence conservation and secondary structure of miRNA by comparing the miRNA sequences in the miRbase. RT-PCR was conducted to examine the expression of these miRNAs and stem-loop RT-PCR assay was performed to examine expression of 11 mature miRNAs (out of the 58 putative miRNA) that showed significant changes in different tissues and stages of the insect development. One hundred twenty eight possible target genes against the 11 miRNAs were predicted by using computational methods. Binding of one miRNA (sli-miR-928b) with the three possible target mRNAs was confirmed by Southern blotting, implying its possible function in regulation of the target genes

Exploration and characterization of the antimalarial activity of cyclopropyl carboxamides that target the mitochondrial protein, cytochrome b.

Drug resistance against antimalarials is rendering them increasingly ineffective and so there is a need for the development of new antimalarials. To discover new antimalarial chemotypes a phenotypic screen of the Janssen Jumpstarter library against the P. falciparum asexual stage was undertaken, uncovering the cyclopropyl carboxamide structural hit class. Structure-activity analysis revealed that each structural moiety was largely resistant to change, although small changes led to the frontrunner compound, WJM280, which has potent asexual stage activity (EC50 40 nM) and no human cell cytotoxicity. Forward genetics uncovered that cyclopropyl carboxamide resistant parasites have mutations and an amplification in the cytochrome b gene. Cytochrome b was then verified as the target with profiling against cytochrome b drug-resistant parasites and a mitochondrial oxygen consumption assay. Accordingly, the cyclopropyl carboxamide class was shown to have slow-acting asexual stage activity and activity against male gametes and exoerythrocytic forms. Enhancing metabolic stability to attain efficacy in malaria mouse models remains a challenge in the future development of this antimalarial chemotype

Short text similarity based on probabilistic topics

In this paper, we propose a new method for measuring the similarity between two short text snippets by comparing each of them with the probabilistic topics. Specifically, our method starts by firstly finding the distinguishing terms between the two short text snippets and comparing them with a series of probabilistic topics, extracted by Gibbs sampling algorithm. The relationship between the distinguishing terms of the short text snippets can be discovered by examining their probabilities under each topic. The similarity between two short text snippets is calculated based on their common terms and the relationship of their distinguishing terms. Extensive experiments on paraphrasing and question categorization show that the proposed method can calculate the similarity of short text snippets more accurately than other methods including the pure TF-IDF measure.Xiaojun Quan, Gang Liu, Zhi Lu, Xingliang Ni, Liu Wenyi