A clinical tool that can diagnose psychiatric illness using functional or structural magnetic resonance (MR) brain images has the potential to greatly assist physicians and improve treatment ...efficacy. Working toward the goal of automated diagnosis, we propose an approach for automated classification of ADHD and autism based on histogram of oriented gradients (HOG) features extracted from MR brain images, as well as personal characteristic data features. We describe a learning algorithm that can produce effective classifiers for ADHD and autism when run on two large public datasets. The algorithm is able to distinguish ADHD from control with hold-out accuracy of 69.6% (over baseline 55.0%) using personal characteristics and structural brain scan features when trained on the ADHD-200 dataset (769 participants in training set, 171 in test set). It is able to distinguish autism from control with hold-out accuracy of 65.0% (over baseline 51.6%) using functional images with personal characteristic data when trained on the Autism Brain Imaging Data Exchange (ABIDE) dataset (889 participants in training set, 222 in test set). These results outperform all previously presented methods on both datasets. To our knowledge, this is the first demonstration of a single automated learning process that can produce classifiers for distinguishing patients vs. controls from brain imaging data with above-chance accuracy on large datasets for two different psychiatric illnesses (ADHD and autism). Working toward clinical applications requires robustness against real-world conditions, including the substantial variability that often exists among data collected at different institutions. It is therefore important that our algorithm was successful with the large ADHD-200 and ABIDE datasets, which include data from hundreds of participants collected at multiple institutions. While the resulting classifiers are not yet clinically relevant, this work shows that there is a signal in the (f)MRI data that a learning algorithm is able to find. We anticipate this will lead to yet more accurate classifiers, over these and other psychiatric disorders, working toward the goal of a clinical tool for high accuracy differential diagnosis.
The spread of the Omicron SARS-CoV-2 variant underscores the importance of analyzing the cross-protection from previous non-Omicron infection. We have developed a high-throughput neutralization assay ...for Omicron SARS-CoV-2 by engineering the Omicron spike gene into an mNeonGreen USA-WA1/2020 SARS-CoV-2 (isolated in January 2020). Using this assay, we determine the neutralization titers (defined as the maximal serum dilution that inhibited 50% of infectious virus) of patient sera collected at 1- or 6-months after infection with non-Omicron SARS-CoV-2. From 1- to 6-month post-infection, the neutralization titers against USA-WA1/2020 decrease from 601 to 142 (a 4.2-fold reduction), while the neutralization titers against Omicron-spike SARS-CoV-2 remain low at 38 and 32, respectively. Thus, at 1- and 6-months after non-Omicron SARS-CoV-2 infection, the neutralization titers against Omicron are 15.8- and 4.4-fold lower than those against USA-WA1/2020, respectively. The low cross-neutralization against Omicron from previous non-Omicron infection supports vaccination of formerly infected individuals to mitigate the health impact of the ongoing Omicron surge.
Abstract
Antiferromagnetic insulators are a ubiquitous class of magnetic materials, holding the promise of low-dissipation spin-based computing devices that can display ultra-fast switching and are ...robust against stray fields. However, their imperviousness to magnetic fields also makes them difficult to control in a reversible and scalable manner. Here we demonstrate a novel proof-of-principle ionic approach to control the spin reorientation (Morin) transition reversibly in the common antiferromagnetic insulator α-Fe
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(haematite) – now an emerging spintronic material that hosts topological antiferromagnetic spin-textures and long magnon-diffusion lengths. We use a low-temperature catalytic-spillover process involving the post-growth incorporation or removal of hydrogen from α-Fe
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thin films. Hydrogenation drives pronounced changes in its magnetic anisotropy, Néel vector orientation and canted magnetism via electron injection and local distortions. We explain these effects with a detailed magnetic anisotropy model and first-principles calculations. Tailoring our work for future applications, we demonstrate reversible control of the room-temperature spin-state by doping/expelling hydrogen in Rh-substituted α-Fe
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Brain expression of CB2 cannabinoid receptors has been much less well established and characterized in comparison to the expression of brain CB1 receptors. Since CB2 receptors are intensely expressed ...in peripheral and immune tissues, expression in brain microglia has been anticipated. Nevertheless, we now describe expression of CB2-receptor-like immunoreactivity in brain in neuronal patterns that support broader CNS roles for this receptor. Two anti-CB2 affinity purified polyclonal antibodies were raised in rabbits immunized with peptide conjugates that corresponded to amino acids 1–33 and 20–33. Western blot analyses revealed specific bands that were identified using these sera and were absent when the sera were preadsorbed with 8.3 μg/ml of the immunizing peptides. These studies, and initial RT-PCR analyses of brain CB1 and CB2 mRNAs, also support the expression of brain CB2 receptor transcripts at levels much lower than those of CB1 receptors. CB2 cannabinoid receptor mRNA was clearly expressed in the cerebellum of wild type but not in CB2 knockout mice. CB2 immunostaining was detected in the interpolar part of spinal 5th nucleus of wild type but not in CB2 knockout mice, using a mouse C-terminal CB2 receptor antibody. Immunohistochemical analyses revealed abundant immunostaining for CB2 receptors in apparent neuronal and glial processes in a number of rat brain areas. Cerebellar Purkinje cells and hippocampal pyramidal cells revealed substantial immunoreactivity that was absent when sections were stained with preadsorbed sera. CB2 immunoreactivity was also observed in olfactory tubercle, islands of Calleja, cerebral cortex, striatum, thalamic nuclei, hippocampus, amygdala, substantia nigra, periaqueductal gray, paratrochlear nucleus, paralemniscal nucleus, red nucleus, pontine nuclei, inferior colliculus and the parvocellular portion of the medial vestibular nucleus. In-vitro, CB2 immunoreactivity was also present in hippocampal cell cultures. The multifocal expression of CB2 immunoreactivity in glial and neuronal patterns in a number of brain regions suggests reevaluation of the possible roles that CB2 receptors may play in the brain.
We make use of a catalog of 1600 Pan-STARRS1 groups produced by the probability friends-of-friends algorithm to explore how the galaxy properties, i.e., the specific star formation rate (SSFR) and ...quiescent fraction, depend on stellar mass and group-centric radius. The work is the extension of Lin et al. In this work, powered by a stacking technique plus a background subtraction for contamination removal, a finer correction and more precise results are obtained than in our previous work. We find that while the quiescent fraction increases with decreasing group-centric radius, the median SSFRs of star-forming galaxies in groups at fixed stellar mass drop slightly from the field toward the group center. This suggests that the main quenching process in groups is likely a fast mechanism. On the other hand, a reduction in SSFRs by ∼0.2 dex is seen inside clusters as opposed to the field galaxies. If the reduction is attributed to the slow quenching effect, the slow quenching process acts dominantly in clusters. In addition, we also examine the density-color relation, where the density is defined by using a sixth-nearest-neighbor approach. Comparing the quiescent fractions contributed from the density and radial effect, we find that the density effect dominates the massive group or cluster galaxies, and the radial effect becomes more effective in less massive galaxies. The results support mergers and/or starvation as the main quenching mechanisms in the group environment, while harassment and/or starvation dominate in clusters.
Bladder cancer is associated with high recurrence and mortality rates due to metastasis. The elucidation of metastasis suppressors may offer therapeutic opportunities if their mechanisms of action ...can be elucidated and tractably exploited. In this study, we investigated the clinical and functional significance of the transcription factor activating transcription factor 3 (ATF3) in bladder cancer metastasis. Gene expression analysis revealed that decreased ATF3 was associated with bladder cancer progression and reduced survival of patients with bladder cancer. Correspondingly, ATF3 overexpression in highly metastatic bladder cancer cells decreased migration in vitro and experimental metastasis in vivo. Conversely, ATF3 silencing increased the migration of bladder cancer cells with limited metastatic capability in the absence of any effect on proliferation. In keeping with their increased motility, metastatic bladder cancer cells had increased numbers of actin filaments. Moreover, ATF3 expression correlated with expression of the actin filament severing protein gelsolin (GSN). Mechanistic studies revealed that ATF3 upregulated GSN, whereas ATF3 silencing reduced GSN levels, concomitant with alterations in the actin cytoskeleton. We identified six ATF3 regulatory elements in the first intron of the GSN gene confirmed by chromatin immunoprecipitation analysis. Critically, GSN expression reversed the metastatic capacity of bladder cancer cells with diminished levels of ATF3. Taken together, our results indicate that ATF3 suppresses metastasis of bladder cancer cells, at least in part through the upregulation of GSN-mediated actin remodeling. These findings suggest ATF3 coupled with GSN as prognostic markers for bladder cancer metastasis.
Ghrelin, neuropeptide Y (NPY) and cholecystokinin (CCK) all have important roles in the regulation of feeding in fish and mammals. To better understand the role of the three peptides in appetite ...regulation in the early developmental stages of blunt snout bream (Megalobrama amblycephala), partial cDNA sequences of ghrelin, NPY and CCK genes were cloned. And then, real‐time quantitative PCR and RT‐PCR were used to detect and quantify the mRNA expressions of these genes from zygotes to larvae of 50 days after hatching (DAH). Ghrelin, NPY and CCK were all expressed throughout the embryonic and larval development stages, and the expression levels were higher in larval stages than in embryonic stages. Ghrelin and NPY mRNA expressions were upregulated at 1, 3, 5 DAH, while CCK mRNA expression was reduced significantly at 3 DAH. The mRNA expression levels of three genes in larvae varied significantly until 30 DAH. In adult fish, all three peptides were detected to be expressed in brain and several peripheral tissues. Ghrelin mRNA was mainly expressed in the intestine, whereas NPY and CCK mRNAs were mainly expressed in the brain. Taken together, these results indicate that ghrelin, NPY and CCK may have roles in early development and participate in the regulation of feeding of larvae in blunt snout bream and will be helpful for further investigation into feed intake regulation in adults of this species.
The Periodontal Ligament (PDL) plays a very important role in load transmission between the teeth and alveolar bone. To capture biomechanical responses of Orthodontics, numerical analysis need to ...consider multiple types of materials: incompressible visco-hyperelastic for the PDL and compressible elastic for teeth. This article proposes a unified-implementation of smoothed finite element methods (UI-SFEM), which enables the use of different types of smoothing domains for different materials. It has several important properties: (1) A UI-SFEM model can use any types of smoothing domains in a combination as desired for complex systems. (2) The choice of the smoothing domain types can be done in a single model based on the user needs (material properties, incompressible numerical problems). (3) It provides a framework for designing models with different solution properties. Numerical experiments show that the UI-SFEM is efficient and robust against mesh distortion, which is works particularity well for complex biological systems.
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