The anti-melanoma activity of dinaciclib, a cyclin-dependent kinase inhibitor, is dependent on p53 signaling.

Although cyclin dependent kinase (CDK)-2 is known to be dispensable for the growth of most tumors, it is thought to be important for the proliferation of melanoma cells, where its expression is controlled by the melanocyte-lineage specific transcription factor MITF. Treatment of a panel of melanoma cells with the CDK inhibitor dinaciclib led to a concentration-dependent inhibition of growth under both 2D adherent and 3D organotypic cell culture conditions. Dinaciclib targeted melanoma cell lines regardless of cdk2 or MITF levels.

Transcriptome analysis of Nicotiana tabacum infected by Cucumber mosaic virus during systemic symptom development.

Virus infection of plants may induce a variety of disease symptoms. However, little is known about the molecular mechanism of systemic symptom development in infected plants. Here we performed the first next-generation sequencing study to identify gene expression changes associated with disease development in tobacco plants (Nicotiana tabacum cv.

Identification of miRNA signatures during the differentiation of hESCs into retinal pigment epithelial cells.

Retinal pigment epithelium (RPE) cells can be obtained through in vitro differentiation of both embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs). We have previously identified 87 signature genes relevant to RPE cell differentiation and function through transcriptome analysis of both human ESC- and iPSC-derived RPE as well as normal fetal RPE. Here, we profile miRNA expression through small RNA-seq in human ESCs and their RPE derivatives.

2,3-Bis(thio-phen-2-yl)pyrazine-[2,3-f][1,10]phenanthroline.

The mol-ecule of the title compound, C(22)H(12)N(4)S(2), shows no crystallographic symmetry. The thiophene rings form different dihedral angles [40.15 (9) and 15.

Accelerating Large Scale Image Analyses on Parallel, CPU-GPU Equipped Systems.

The past decade has witnessed a major paradigm shift in high performance computing with the introduction of accelerators as general purpose processors. These computing devices make available very high parallel computing power at low cost and power consumption, transforming current high performance platforms into heterogeneous CPU-GPU equipped systems. Although the theoretical performance achieved by these hybrid systems is impressive, taking practical advantage of this computing power remains a very challenging problem.

Digital Pathology: Data-Intensive Frontier in Medical Imaging: Health-information sharing, specifically of digital pathology, is the subject of this paper which discusses how sharing the rich images in pathology can stretch the capabilities of all otherwise well-practiced disciplines.

Pathology is a medical subspecialty that practices the diagnosis of disease. Microscopic examination of tissue reveals information enabling the pathologist to render accurate diagnoses and to guide therapy. The basic process by which anatomic pathologists render diagnoses has remained relatively unchanged over the last century, yet advances in information technology now offer significant opportunities in image-based diagnostic and research applications.

The tumor microenvironment strongly impacts master transcriptional regulators and gene expression class of glioblastoma.

The Cancer Genome Atlas (TCGA) project has generated gene expression data that divides glioblastoma (GBM) into four transcriptional classes: proneural, neural, classical, and mesenchymal. Because transcriptional class is only partially explained by underlying genomic alterations, we hypothesize that the tumor microenvironment may also have an impact. In this study, we focused on necrosis and angiogenesis because their presence is both prognostically and biologically significant.

Integrated morphologic analysis for the identification and characterization of disease subtypes.

Background And Objective: Morphologic variations of disease are often linked to underlying molecular events and patient outcome, suggesting that quantitative morphometric analysis may provide further insight into disease mechanisms. In this paper a methodology for the subclassification of disease is developed using image analysis techniques. Morphologic signatures that represent patient-specific tumor morphology are derived from the analysis of hundreds of millions of cells in digitized whole slide images.

Towards building computerized image analysis framework for nucleus discrimination in microscopy images of diffuse glioma.

As an effort to build an automated and objective system for pathologic image analysis, we present, in this paper, a computerized image processing method for identifying nuclei, a basic biological unit of diagnostic utility, in microscopy images of glioma tissue samples. The complete analysis includes multiple processing steps, involving mode detection with color and spatial information for pixel clustering, background normalization leveraging morphological operations, boundary refinement with deformable models, and clumped nuclei separation using watershed. In aggregate, our validation dataset includes 220 nuclei from 11 distinct tissue regions selected at random by an experienced neuropathologist.

In silico analysis of nuclei in glioblastoma using large-scale microscopy images improves prediction of treatment response.

In this paper, we present a complete and novel workflow for quantitative nuclear feature analysis of glioblastoma using high-throughput whole-slide microscopy image processing as it relates to treatment response and patient survival. With a complete suite of computer algorithms, large numbers of micro-anatomical structures, in this case nuclei, are analyzed and represented efficiently from whole-slide digitized images with numerical features. With regard to endpoints of treatment response, the computerized analysis presents a better discrimination than traditional neuropathologic review.

A COMPREHENSIVE FRAMEWORK FOR CLASSIFICATION OF NUCLEI IN DIGITAL MICROSCOPY IMAGING: AN APPLICATION TO DIFFUSE GLIOMAS.

In this paper, we present a comprehensive framework to support classification of nuclei in digital microscopy images of diffuse gliomas. This system integrates multiple modules designed for convenient human annotations, standard-based data management, efficient data query and analysis. In our study, 2770 nuclei of six types are annotated by neuropathologists from 29 whole-slide images of glioma biopsies.

IVSPlat 1.0: an integrated virtual screening platform with a molecular graphical interface.

Background: The virtual screening (VS) of lead compounds using molecular docking and pharmacophore detection is now an important tool in drug discovery. VS tasks typically require a combination of several software tools and a molecular graphics system. Thus, the integration of all the requisite tools in a single operating environment could reduce the complexity of running VS experiments.

MORPHOLOGICAL SIGNATURES AND GENOMIC CORRELATES IN GLIOBLASTOMA.

Large multimodal datasets such as The Cancer Genome Atlas present an opportunity to perform correlative studies of tissue morphology and genomics to explore the morphological phenotypes associated with gene expression and genetic alterations. In this paper we present an investigation of Cancer Genome Atlas data that correlates morphology with recently discovered molecular subtypes of glioblastoma. Using image analysis to segment and extract features from millions of cells, we calculate high-dimensional morphological signatures to describe trends of nuclear morphology and cytoplasmic staining in whole-slide images.

[The analysis of axial length changes in the phakic eyes after posterior chamber implantation of lens to correct high myopia].

Objective: To definitive axial length measuring mode of the phakic eyes after posterior chamber implantation of lens.

Methods: All patients came from the Ophthalmology Hospital of China Medical University. Seventy patients with 135 eyes, aged 21 - 48 years old.

Integrative, multimodal analysis of glioblastoma using TCGA molecular data, pathology images, and clinical outcomes.

Multimodal, multiscale data synthesis is becoming increasingly critical for successful translational biomedical research. In this letter, we present a large-scale investigative initiative on glioblastoma, a high-grade brain tumor, with complementary data types using in silico approaches. We integrate and analyze data from The Cancer Genome Atlas Project on glioblastoma that includes novel nuclear phenotypic data derived from microscopic slides, genotypic signatures described by transcriptional class and genetic alterations, and clinical outcomes defined by response to therapy and patient survival.

A data model and database for high-resolution pathology analytical image informatics.

Background: The systematic analysis of imaged pathology specimens often results in a vast amount of morphological information at both the cellular and sub-cellular scales. While microscopy scanners and computerized analysis are capable of capturing and analyzing data rapidly, microscopy image data remain underutilized in research and clinical settings. One major obstacle which tends to reduce wider adoption of these new technologies throughout the clinical and scientific communities is the challenge of managing, querying, and integrating the vast amounts of data resulting from the analysis of large digital pathology datasets.

Modeling the evolution of ETV6-RUNX1-induced B-cell precursor acute lymphoblastic leukemia in mice.

The t(12;21) translocation that generates the ETV6-RUNX1 (TEL-AML1) fusion gene, is the most common chromosomal rearrangement in childhood cancer and is exclusively associated with B-cell precursor acute lymphoblastic leukemia (BCP-ALL). The translocation arises in utero and is necessary but insufficient for the development of leukemia. Single-nucleotide polymorphism array analysis of ETV6-RUNX1 patient samples has identified multiple additional genetic alterations; however, the role of these lesions in leukemogenesis remains undetermined.

Slingshot: a PiggyBac based transposon system for tamoxifen-inducible 'self-inactivating' insertional mutagenesis.

We have developed a self-inactivating PiggyBac transposon system for tamoxifen inducible insertional mutagenesis from a stably integrated chromosomal donor. This system, which we have named 'Slingshot', utilizes a transposon carrying elements for both gain- and loss-of-function screens in vitro. We show that the Slingshot transposon can be efficiently mobilized from a range of chromosomal loci with high inducibility and low background generating insertions that are randomly dispersed throughout the genome.

An integrative approach for in silico glioma research.

The integration of imaging and genomic data is critical to forming a better understanding of disease. Large public datasets, such as The Cancer Genome Atlas, present a unique opportunity to integrate these complementary data types for in silico scientific research. In this letter, we focus on the aspect of pathology image analysis and illustrate the challenges associated with analyzing and integrating large-scale image datasets with molecular characterizations.

Prediction of Microporous Aluminophosphate AlPO4 -5 Based on Resampling Using Partial Least Squares and Logistic Discrimination.

In this paper, Partial Least Squares (PLS) regression and Logistic Discrimination (LD) are employed to predict the formation of microporous aluminophosphate AlPO4 -5 based on the database of AlPO synthesis, which aims to provide a useful guidance to the rational synthesis of microporous materials as well as other inorganic crystalline materials. To deal with the problem of class imbalance, four guided resampling methods considering not only the between-class imbalance but also the within-class imbalance are proposed. Experimental results indicate that the presented methods are competent for predicting the formation of microporous aluminophosphate AlPO4 -5.

Human dermal stem cells differentiate into functional epidermal melanocytes.

Melanocytes sustain a lifelong proliferative potential, but a stem cell reservoir in glabrous skin has not yet been found. Here, we show that multipotent dermal stem cells isolated from human foreskins lacking hair follicles are able to home to the epidermis to differentiate into melanocytes. These dermal stem cells, grown as three-dimensional spheres, displayed a capacity for self-renewal and expressed NGFRp75, nestin and OCT4, but not melanocyte markers.

A new model-based estimation of ellipses for object representation.

Fitting geometric models to objects of interest in images is one of the most classical problems studied in computer vision field. As a result of its strong representation power and flexibility, conic is one of the geometric primitives widely used in a large number of image analysis applications, in practice. As opposed to most existing conic fitting methods minimizing the fitting error with the use of the second order polynomial representation, in this paper, we propose a new method that formulates the geometric fitting problem as a process of seeking for the optimal mapping to a bivariate normal distribution model.

Application of problem-based learning in a large class in stomatology course.

Purpose: To determine the feasibility of implementing problem-based learning (PBL) in a large class and whether previous PBL experience is necessary.

Materials And Methods: A total of 236 students from 2 large classes at China Medical University were enrolled. One class (118 students) had had a previous small-group PBL experience and another class (113 students) had not.

Studies of alpha-helicity and intersegmental interactions in voltage-gated Na+ channels: S2D4.

Much data, including crystallographic, support structural models of sodium and potassium channels consisting of S1-S4 transmembrane segments (the "voltage-sensing domain") clustered around a central pore-forming region (S5-S6 segments and the intervening loop). Voltage gated sodium channels have four non-identical domains which differentiates them from the homotetrameric potassium channels that form the basis for current structural models. Since potassium and sodium channels also exhibit many different functional characteristics and the fourth domain (D4) of sodium channels differs in function from other domains (D1-D3), we have explored its structure in order to determine whether segments in D4 of sodium channels differ significantly from that determined for potassium channels.