6-[(E)-2-Phenyl­vin­yl]-1H-indole

The title compound, C16H13N, is essentially planar [maximum deviation from the least-squares plane = 0.081 (3) Å], with a dihedral angle of 1.65 (13)° between the planes of the indole and benzene rings. In the crystal, there are no significant inter­molecular π–π inter­actions [minimum ring centroid–centroid separation = 4.217 (5) Å]

4-(1H-Tetra­zol-5-yl)-1H-indole

There are two mol­ecules with similar configurations in the asymmetric unit of the title compound, C9H7N5, which are linked by inter­molecular N—H⋯N hydrogen bonds into chains with graph-set motif C 2 2(8) along the b axis. The indole core has the expected planar geometry in the two mol­ecules, with a maximum deviation of 0.008 (8) Å from the least-squares plane defined by the nine constituent atoms, and the dihedral angles between the indole and tetra­zole rings are similar [42.4 (2) and 42.7 (2)°]

Enlarged Training Dataset by Pairwise GANs for Molecular-Based Brain Tumor Classification

This paper addresses issues of brain tumor subtype classification using Magnetic Resonance Images (MRIs) from different scanner modalities like T1 weighted, T1 weighted with contrast-enhanced, T2 weighted and FLAIR images. Currently most available glioma datasets are relatively moderate in size,and often accompanied with incomplete MRIs in different modalities. To tackle the commonly encountered problems of insufficiently large brain tumor datasets and incomplete modality of image for deep learning, we propose to add augmented brain MR images to enlarge the training dataset by employing a pairwise Generative Adversarial Network (GAN) model. The pairwise GAN is able to generate synthetic MRIs across different modalities. To achieve the patient-level diagnostic result, we propose a post-processing strategy to combine the slice-level glioma subtype classification results by majority voting. A two-stage course-to-fine training strategy is proposed to learn the glioma feature using GAN-augmented MRIs followed by real MRIs. To evaluate the effectiveness of the proposed scheme, experiments have been conducted on a brain tumor dataset for classifying glioma molecular subtypes: isocitrate dehydrogenase 1 (IDH1) mutation and IDH1 wild-type. Our results on the dataset have shown good performance (with test accuracy 88.82%). Comparisons with several state-of-the-art methods are also included

Impact of high-frequency pumping on anomalous finite-size effects in three-dimensional topological insulators

Lowering of the thickness of a thin-film three-dimensional topological insulator down to a few nanometers results in the gap opening in the spectrum of topologically protected two-dimensional surface states. This phenomenon, which is referred to as the anomalous finite-size effect, originates from hybridization between the states propagating along the opposite boundaries. In this work, we consider a bismuth-based topological insulator and show how the coupling to an intense high-frequency linearly polarized pumping can further be used to manipulate the value of a gap. We address this effect within recently proposed Brillouin-Wigner perturbation theory that allows us to map a time-dependent problem into a stationary one. Our analysis reveals that both the gap and the components of the group velocity of the surface states can be tuned in a controllable fashion by adjusting the intensity of the driving field within an experimentally accessible range and demonstrate the effect of light-induced band inversion in the spectrum of the surface states for high enough values of the pump.Comment: 6 pages, 3 figure

A gene catalogue for post-diapause development of an anhydrobiotic arthropod Artemia franciscana

<p>Abstract</p> <p>Background</p> <p>Diapause is a reversible state of developmental suspension and found among diverse taxa, from plants to animals, including marsupials and some other mammals. Although previous work has accumulated ample data, the molecular mechanism underlying diapause and reactivation from it remain elusive.</p> <p>Results</p> <p>Using <it>Artemia franciscana</it>, a model organism to study the development of post-diapause embryos in Arthropod, we sequenced random clones up to a total of 28,039 ESTs from four cDNA libraries made from dehydrated cysts and three time points after rehydration/reactivation, which were assembled into 8,018 unigene clusters. We identified 324 differentially-expressed genes (DEGs, <it>P </it>< 0.05) based on pairwise comparisons of the four cDNA libraries. We identified a group of genes that are involved in an anti-water-deficit system, including proteases, protease inhibitors, heat shock proteins, and several novel members of the late embryogenesis abundant (LEA) protein family. In addition, we classified most of the up-regulated genes after cyst reactivation into metabolism, biosynthesis, transcription, and translation, and this result is consistent with the rapid development of the embryo. Some of the specific expressions of DEGs were confirmed experimentally based on quantitative real-time PCR.</p> <p>Conclusion</p> <p>We found that the first 5-hour period after rehydration is most important for embryonic reactivation of <it>Artemia</it>. As the total number of expressed genes increases significantly, the majority of DEGs were also identified in this period, including a group of water-deficient-induced genes. A group of genes with similar functions have been described in plant seeds; for instance, one of the novel LEA members shares ~70% amino-acid identity with an <it>Arabidopsis </it>EM (embryonic abundant) protein, the closest animal relative to plant LEA families identified thus far. Our findings also suggested that not only nutrition, but also mRNAs are produced and stored during cyst formation to support rapid development after reactivation.</p

(5-Meth­oxy-1H-indol-3-yl)acetonitrile

In the title compound, C11H10N2O, the O atom and the C atom of the methyl­ene group deviate only slightly [0.029 (3) and 0.055 (3) Å, respectively] from the approximately planar ring system (r.m.s. deviation = 0.013 Å). In the crystal, N—H⋯O hydrogen bonds link the mol­ecules into zigzag chains running along the b axis

Deep semi-supervised learning for brain tumor classification

Background: This paper addresses issues of brain tumor, glioma, classification from four modalities of Magnetic Resonance Image (MRI) scans (i.e., T1 weighted MRI, T1 weighted MRI with contrast-enhanced, T2 weighted MRI and FLAIR). Currently, many available glioma datasets often contain some unlabeled brain scans, and many datasets are moderate in size. Methods: We propose to exploit deep semi-supervised learning to make full use of the unlabeled data. Deep CNN features were incorporated into a new graph-based semi-supervised learning framework for learning the labels of the unlabeled data, where a new 3D-2D consistent constraint is added to make consistent classifications for the 2D slices from the same 3D brain scan. A deep-learning classifier is then trained to classify different glioma types using both labeled and unlabeled data with estimated labels. To alleviate the overfitting caused by moderate-size datasets, synthetic MRIs generated by Generative Adversarial Networks (GANs) are added in the training of CNNs. Results: The proposed scheme has been tested on two glioma datasets, TCGA dataset for IDH-mutation prediction (molecular-based glioma subtype classification) and MICCAI dataset for glioma grading. Our results have shown good performance (with test accuracies 86.53% on TCGA dataset and 90.70% on MICCAI dataset). Conclusions: The proposed scheme is effective for glioma IDH-mutation prediction and glioma grading, and its performance is comparable to the state-of-the-art

Lattice and QR decomposition-based algorithms for recursive least squares adaptive nonlinear filters

Journal ArticleThis paper presents a lattice structure for adaptive Volterra systems. The stucture is applicable to arbitrary planes of support of the Volterra kernels. A fast least squares lattice and a fast QR-lattice adaptive nonlinear filtering algorithms based on the lattice structure are also presented. These algorithms share the fast convergence property of fast least squares transversal Volterra filters; however, unlike the transversal filters they do not suffer from numerical instability

Effects of methylphenidate on attentional set-shifting in a genetic model of attention-deficit/hyperactivity disorder

Abstract Background Although deficits of attentional set-shifting have been reported in individuals with attention deficit/hyperactivity disorder (ADHD), it is rarely examined in animal models. Methods This study compared spontaneously hypertensive rats (SHRs; a genetic animal model of ADHD) and Wistar-Kyoto (WKY) and Sprague-Dawley (SD) rats (normoactive control strains), on attentional set-shifting task (ASST) performance. Furthermore, the dose-effects of methylphenidate (MPH) on attentional set-shifting of SHR were investigated. In experiment 1, ASST procedures were conducted in SHR, WKY and SD rats of 8 each at the age of 5 weeks. Mean latencies at the initial phase, error types and numbers, and trials to criteria at each stage were recorded. In experiment 2, 24 SHR rats were randomly assigned to 3 groups of 8 each-- MPH-L (lower dose), MPH-H (higher dose), and SHR-vehicle groups. From 3 weeks, they were administered 2.5 mg/kg or 5 mg/kg MPH or saline respectively for 14 consecutive days. All rats were tested in the ASST at the age of 5 weeks. Results The SHRs generally exhibited poorer performance on ASST than the control WKY and SD rats. Significant strain effects on mean latency [F (2, 21) = 639.636, p p p p p Conclusions The SHR may be impaired in discrimination learning, reversal learning and attentional set-shifting. Our study provides evidence that MPH may improve the SHR's performance on attentional set-shifting and lower dose is more effective than higher dose.</p

Oxonium picrate

The title compound, H3O+·C6H2N3O7 −, consists of one picrate anion and one oxonium cation. The oxonium cation is located on a crystallographic twofold axis and both its H atoms are disordered, each over two symmetry-equivalent positions with occupancy ratios of 0.75. The picrate anions are also located on twofold axes bis­ecting the phenolate and p-nitro groups. π–π inter­actions between the rings of the picrates [centroid-to-centroid distances of 3.324 (2) Å] connect the anions to form stacks along the a-axis direction. The stacks are further joined together by the protonated water mol­ecules through hydrogen bonds to form two-dimensional sheets extending parallel to the ab plane. The sheets are stacked on top of each other along the c-axis direction and connected through C—H⋯O inter­actions between the CH groups of the benzene rings and the picrate nitro groups, with C⋯O distances of 3.450 (2) Å