Face processing in adolescents with positive and negative threat bias

BackgroundIndividuals with anxiety disorders exhibit a ‘vigilance-avoidance’ pattern of attention to threatening stimuli when threatening and neutral stimuli are presented simultaneously, a phenomenon referred to as ‘threat bias’. Modifying threat bias through cognitive retraining during adolescence reduces symptoms of anxiety, and so elucidating neural mechanisms of threat bias during adolescence is of high importance. We explored neural mechanisms by testing whether threat bias in adolescents is associated with generalized or threat-specific differences in the neural processing of faces.MethodSubjects were categorized into those with (n = 25) and without (n = 27) threat avoidance based on a dot-probe task at average age 12.9 years. Threat avoidance in this cohort has previously been shown to index threat bias. Brain response to individually presented angry and neutral faces was assessed in a separate session using functional magnetic resonance imaging.ResultsAdolescents with threat avoidance exhibited lower activity for both angry and neutral faces relative to controls in several regions in the occipital, parietal, and temporal lobes involved in early visual and facial processing. Results generalized to happy, sad, and fearful faces. Adolescents with a prior history of depression and/or an anxiety disorder had lower activity for all faces in these same regions. A subset of results replicated in an independent dataset.ConclusionsThreat bias is associated with generalized, rather than threat-specific, differences in the neural processing of faces in adolescents. Findings may aid in the development of novel treatments for anxiety disorders that use attention training to modify threat bias.</jats:sec

Collaborative project to identify direct and distant pedigree relationships in apple

Pedigree information is fundamentally important in breeding programs, enabling breeders to know the source of valuable attributes and underlying alleles and to enlarge genetic diversity in a directed way. Many apple cultivars are related to each other through both recent and distant common ancestors. As apple trees are clonally propagated, long-lived, and widely adapted, many of the ancestors of modern cultivars are still present in global germplasm collections. Use of apple SNP arrays enables identification of direct and distant pedigree relationships with precision. An example is the elucidation of the \u27Honeycrisp\u27 pedigree using the 8K SNP array, which enabled further findings regarding the inheritance of important alleles for traits including scab resistance and soft scald susceptibility. To facilitate more discoveries across apple germplasm, a large-scale collaborative apple pedigree reconstruction project has been initiated. This project utilizes output from the Illumina Infinium 20K and Affymetrix Axiom 480K apple SNP arrays, a high quality genetic linkage map for the 20K array SNPs, and a data curation pipeline developed through the FruitBreedomics and RosBREED projects. Techniques using shared haplotype length statistics will be used alongside historical information to deduce distant pedigree relationships. The project involves various experts, germplasm collections, and academic institutions around the world and is open for further extension. It will provide findings useful for breeding programs, germplasm collections, geneticists, and historians

Multi-center prediction of hemorrhagic transformation in acute ischemic stroke using permeability imaging features

Permeability images derived from magnetic resonance (MR) perfusion images are sensitive to blood–brain barrier derangement of the brain tissue and have been shown to correlate with subsequent development of hemorrhagic transformation (HT) in acute ischemic stroke. This paper presents a multi-center retrospective study that evaluates the predictive power in terms of HT of six permeability MRI measures including contrast slope (CS), final contrast (FC), maximum peak bolus concentration (MPB), peak bolus area (PB), relative recirculation (rR), and percentage recovery (%R). Dynamic T2*-weighted perfusion MR images were collected from 263 acute ischemic stroke patients from four medical centers. An essential aspect of this study is to exploit a classifier-based framework to automatically identify predictive patterns in the overall intensity distribution of the permeability maps. The model is based on normalized intensity histograms that are used as input features to the predictive model. Linear and nonlinear predictive models are evaluated using a cross-validation to measure generalization power on new patients and a comparative analysis is provided for the different types of parameters. Results demonstrate that perfusion imaging in acute ischemic stroke can predict HT with an average accuracy of more than 85% using a predictive model based on a nonlinear regression model. Results also indicate that the permeability feature based on the percentage of recovery performs significantly better than the other features. This novel model may be used to refine treatment decisions in acute stroke

hctr: a variable-input-length enciphering mode

State Key Lab Informat Secur, Chinese Acad SciThis paper proposes a blockcipher mode of operation, HCTR, which is a length-preserving encryption mode. HCTR turns an n-bit blockcipher into a tweakable blockcipher that supports arbitrary variable input length which is no less than n bits.

Acute Stroke Imaging Research Roadmap II.

The Stroke Imaging Research (STIR) Group, the American Society of Neuroradiology, and the Foundation of the American Society of Neuroradiology sponsored a series of working group meetings >12 months, with the final meeting occurring during the Stroke Treatment Academy Industry Roundtable (STAIR) on March 9 to 10, 2013, in Washington, DC. This process brought together vascular neurologists, neuroradiologists, neuroimaging research scientists, members of the National Institute of Neurological Disorders and Stroke, industry representatives, and members of the US Food and Drug Administration to discuss stroke imaging research priorities, especially in the light of the recent negative results of acute stroke clinical trials that tested the concept of penumbral imaging selection. The goal of this process was to propose a research roadmap for the next 5 years. STIR recommendations include (1) the use of standard terminology, aligned with the National Institute of Neurological Disorders and Stroke Common Data Elements. ; (2) a standardized imaging assessment of revascularization in acute ischemic stroke trials, including a modified Treatment In Cerebral Ischemia (mTICI) score. ; (3) a standardized process to assess whether ischemic core and penumbral imaging methods meet the requirements to be considered as an acceptable selection tool in acute ischemic stroke trials. ; (4) the characteristics of a clinical and imaging data repository to facilitate the development and testing process described in recommendation no. 3. ; (5) the optimal study design for a clinical trial to evaluate whether advanced imaging adds value in selecting acute ischemic stroke patients for revascularization therapy. ; (6) the structure of a stroke neuroimaging network to implement and coordinate the recommendations listed above. All of these recommendations pertain to research, not to clinical care