Cardiac metabolomics and autopsy in a patient with early diffuse systemic sclerosis presenting with dyspnea: A case report

Introduction: Diffuse systemic sclerosis is associated with high mortality; however, the pathogenesis of cardiac death in these patients is not clear. Case presentation: A 56-year-old Caucasian female patient presented with dyspnea and requested to donate her body to science in order to improve understanding of diffuse systemic sclerosis pathogenesis. She had extensive testing for dyspnea including pulmonary function tests, an echocardiogram, cardiac magnetic resonance imaging, and right heart catheterization to characterize her condition. Her case highlights the morbidity seen in this disease, including the presence of extensive skin thickening, digital ulcerations, and scleroderma renal crisis. Conclusion: In this case report, we present the finding of cardiac tissue metabolomics, which may indicate a problem with vasodilation as a contributor to cardiac death in diffuse systemic sclerosis. The use of autopsy and tissue metabolomics in rare disease may help clarify disease pathogenesis

Detection, Isolation and Confirmation of Crimean-Congo Hemorrhagic Fever Virus in Human, Ticks and Animals in Ahmadabad, India, 2010–2011

A nosocomial outbreak of CCHFV occurred in January 2011, in a tertiary care hospital in Ahmadabad, Gujarat State in western India. Out of a total five cases reported, contact transmission occurred to three treating medical professionals, all of whom succumbed to the disease. The only survivor was the husband of the index case. These results highlight the importance of considering CCHFV as a potential aetiology for Hemorrhagic fever (HF) cases in India. This also underlines the need for strict barrier nursing and patient isolation while managing these patients. During the investigation presence of CCHFV RNA in Hyalomma anatolicum ticks and livestock were detected in the village from where the primary case (case A) was reported. Further retrospective investigation confirmed two CCHF human cases in Rajkot village 20 kilometres to the west of Ahmadabad in 2010, and CCHFV presence in the livestock 200 kilometres to the north in the neighbouring State Rajasthan. This report shows the presence of CCHFV in human, ticks and animals in Gujarat, India. The fact of concern is the spread of this disease from one state to another due to trading of livestock

A quick guide for building a successful bioinformatics community

“Scientific community” refers to a group of people collaborating together on scientific-research-related activities who also share common goals, interests, and values. Such communities play a key role in many bioinformatics activities. Communities may be linked to a specific location or institute, or involve people working at many different institutions and locations. Education and training is typically an important component of these communities, providing a valuable context in which to develop skills and expertise, while also strengthening links and relationships within the community. Scientific communities facilitate: (i) the exchange and development of ideas and expertise; (ii) career development; (iii) coordinated funding activities; (iv) interactions and engagement with professionals from other fields; and (v) other activities beneficial to individual participants, communities, and the scientific field as a whole. It is thus beneficial at many different levels to understand the general features of successful, high-impact bioinformatics communities; how individual participants can contribute to the success of these communities; and the role of education and training within these communities. We present here a quick guide to building and maintaining a successful, high-impact bioinformatics community, along with an overview of the general benefits of participating in such communities. This article grew out of contributions made by organizers, presenters, panelists, and other participants of the ISMB/ECCB 2013 workshop “The ‘How To Guide’ for Establishing a Successful Bioinformatics Network” at the 21st Annual International Conference on Intelligent Systems for Molecular Biology (ISMB) and the 12th European Conference on Computational Biology (ECCB)

Measurement of the Bottom-Strange Meson Mixing Phase in the Full CDF Data Set

We report a measurement of the bottom-strange meson mixing phase \beta_s using the time evolution of B0_s -> J/\psi (->\mu+\mu-) \phi (-> K+ K-) decays in which the quark-flavor content of the bottom-strange meson is identified at production. This measurement uses the full data set of proton-antiproton collisions at sqrt(s)= 1.96 TeV collected by the Collider Detector experiment at the Fermilab Tevatron, corresponding to 9.6 fb-1 of integrated luminosity. We report confidence regions in the two-dimensional space of \beta_s and the B0_s decay-width difference \Delta\Gamma_s, and measure \beta_s in [-\pi/2, -1.51] U [-0.06, 0.30] U [1.26, \pi/2] at the 68% confidence level, in agreement with the standard model expectation. Assuming the standard model value of \beta_s, we also determine \Delta\Gamma_s = 0.068 +- 0.026 (stat) +- 0.009 (syst) ps-1 and the mean B0_s lifetime, \tau_s = 1.528 +- 0.019 (stat) +- 0.009 (syst) ps, which are consistent and competitive with determinations by other experiments.Comment: 8 pages, 2 figures, Phys. Rev. Lett 109, 171802 (2012

Prognostic Significance and Gene Expression Profiles of p53 Mutations in Microsatellite-Stable Stage III Colorectal Adenocarcinomas

Although the prognostic value of p53 abnormalities in Stage III microsatellite stable (MSS) colorectal cancers (CRCs) is known, the gene expression profiles specific to the p53 status in the MSS background are not known. Therefore, the current investigation has focused on identification and validation of the gene expression profiles associated with p53 mutant phenotypes in MSS Stage III CRCs. Genomic DNA extracted from 135 formalin-fixed paraffin-embedded tissues, was analyzed for microsatellite instability (MSI) and p53 mutations. Further, mRNA samples extracted from five p53-mutant and five p53-wild-type MSS-CRC snap-frozen tissues were profiled for differential gene expression by Affymetrix Human Genome U133 Plus 2.0 arrays. Differentially expressed genes were further validated by the high-throughput quantitative nuclease protection assay (qNPA), and confirmed by quantitative real-time polymerase chain reaction (qRT-PCR) and by immunohistochemistry (IHC). Survival rates were estimated by Kaplan-Meier and Cox regression analyses. A higher incidence of p53 mutations was found in MSS (58%) than in MSI (30%) phenotypes. Both univariate (log-rank, P = 0.025) and multivariate (hazard ratio, 2.52; 95% confidence interval, 1.25–5.08) analyses have demonstrated that patients with MSS-p53 mutant phenotypes had poor CRC-specific survival when compared to MSS-p53 wild-type phenotypes. Gene expression analyses identified 84 differentially expressed genes. Of 49 down-regulated genes, LPAR6, PDLIM3, and PLAT, and, of 35 up-regulated genes, TRIM29, FUT3, IQGAP3, and SLC6A8 were confirmed by qNPA, qRT-PCR, and IHC platforms. p53 mutations are associated with poor survival of patients with Stage III MSS CRCs and p53-mutant and wild-type phenotypes have distinct gene expression profiles that might be helpful in identifying aggressive subsets

Evaluation of lymph node numbers for adequate staging of Stage II and III colon cancer

<p>Abstract</p> <p>Background</p> <p>Although evaluation of at least 12 lymph nodes (LNs) is recommended as the minimum number of nodes required for accurate staging of colon cancer patients, there is disagreement on what constitutes an adequate identification of such LNs.</p> <p>Methods</p> <p>To evaluate the minimum number of LNs for adequate staging of Stage II and III colon cancer, 490 patients were categorized into groups based on 1-6, 7-11, 12-19, and ≥ 20 LNs collected.</p> <p>Results</p> <p>For patients with Stage II or III disease, examination of 12 LNs was not significantly associated with recurrence or mortality. For Stage II (HR = 0.33; 95% CI, 0.12-0.91), but not for Stage III patients (HR = 1.59; 95% CI, 0.54-4.64), examination of ≥20 LNs was associated with a reduced risk of recurrence within 2 years. However, examination of ≥20 LNs had a 55% (Stage II, HR = 0.45; 95% CI, 0.23-0.87) and a 31% (Stage III, HR = 0.69; 95% CI, 0.38-1.26) decreased risk of mortality, respectively. For each six additional LNs examined from Stage III patients, there was a 19% increased probability of finding a positive LN (parameter estimate = 0.18510, p < 0.0001). For Stage II and III colon cancers, there was improved survival and a decreased risk of recurrence with an increased number of LNs examined, regardless of the cutoff-points. Examination of ≥7 or ≥12 LNs had similar outcomes, but there were significant outcome benefits at the ≥20 cutoff-point only for Stage II patients. For Stage III patients, examination of 6 additional LNs detected one additional positive LN.</p> <p>Conclusions</p> <p>Thus, the 12 LN cut-off point cannot be supported as requisite in determining adequate staging of colon cancer based on current data. However, a minimum of 6 LNs should be examined for adequate staging of Stage II and III colon cancer patients.</p

Dissection of the Transformation of Primary Human Hematopoietic Cells by the Oncogene NUP98-HOXA9

NUP98-HOXA9 is the prototype of a group of oncoproteins associated with acute myeloid leukemia. It consists of an N-terminal portion of NUP98 fused to the homeodomain of HOXA9 and is believed to act as an aberrant transcription factor that binds DNA through the homeodomain. Here we show that NUP98-HOXA9 can regulate transcription without binding to DNA. In order to determine the relative contributions of the NUP98 and HOXA9 portions to the transforming ability of NUP98-HOXA9, the effects of NUP98-HOXA9 on primary human CD34+ cells were dissected and compared to those of wild-type HOXA9. In contrast to previous findings in mouse cells, HOXA9 had only mild effects on the differentiation and proliferation of primary human hematopoietic cells. The ability of NUP98-HOXA9 to disrupt the differentiation of primary human CD34+ cells was found to depend primarily on the NUP98 portion, whereas induction of long-term proliferation required both the NUP98 moiety and an intact homeodomain. Using oligonucleotide microarrays in primary human CD34+ cells, a group of genes was identified whose dysregulation by NUP98-HOXA9 is attributable primarily to the NUP98 portion. These include RAP1A, HEY1, and PTGS2 (COX-2). Their functions may reflect the contribution of the NUP98 moiety of NUP98-HOXA9 to leukemic transformation. Taken together, these results suggest that the effects of NUP98-HOXA9 on gene transcription and cell transformation are mediated by at least two distinct mechanisms: one that involves promoter binding through the homeodomain with direct transcriptional activation, and another that depends predominantly on the NUP98 moiety and does not involve direct DNA binding

Why High-Performance Modelling and Simulation for Big Data Applications Matters

Modelling and Simulation (M&S) offer adequate abstractions to manage the complexity of analysing big data in scientific and engineering domains. Unfortunately, big data problems are often not easily amenable to efficient and effective use of High Performance Computing (HPC) facilities and technologies. Furthermore, M&S communities typically lack the detailed expertise required to exploit the full potential of HPC solutions while HPC specialists may not be fully aware of specific modelling and simulation requirements and applications. The COST Action IC1406 High-Performance Modelling and Simulation for Big Data Applications has created a strategic framework to foster interaction between M&S experts from various application domains on the one hand and HPC experts on the other hand to develop effective solutions for big data applications. One of the tangible outcomes of the COST Action is a collection of case studies from various computing domains. Each case study brought together both HPC and M&S experts, giving witness of the effective cross-pollination facilitated by the COST Action. In this introductory article we argue why joining forces between M&S and HPC communities is both timely in the big data era and crucial for success in many application domains. Moreover, we provide an overview on the state of the art in the various research areas concerned

Transcriptomic alterations in the heart of non-obese type 2 diabetic Goto-Kakizaki rats

BACKGROUND: There is a spectacular rise in the global prevalence of type 2 diabetes mellitus (T2DM) due to the worldwide obesity epidemic. However, a significant proportion of T2DM patients are non-obese and they also have an increased risk of cardiovascular diseases. As the Goto-Kakizaki (GK) rat is a well-known model of non-obese T2DM, the goal of this study was to investigate the effect of non-obese T2DM on cardiac alterations of the transcriptome in GK rats. METHODS: Fasting blood glucose, serum insulin and cholesterol levels were measured at 7, 11, and 15 weeks of age in male GK and control rats. Oral glucose tolerance test and pancreatic insulin level measurements were performed at 11 weeks of age. At week 15, total RNA was isolated from the myocardium and assayed by rat oligonucleotide microarray for 41,012 genes, and then expression of selected genes was confirmed by qRT-PCR. Gene ontology and protein-protein network analyses were performed to demonstrate potentially characteristic gene alterations and key genes in non-obese T2DM. RESULTS: Fasting blood glucose, serum insulin and cholesterol levels were significantly increased, glucose tolerance and insulin sensitivity were significantly impaired in GK rats as compared to controls. In hearts of GK rats, 204 genes showed significant up-regulation and 303 genes showed down-regulation as compared to controls according to microarray analysis. Genes with significantly altered expression in the heart due to non-obese T2DM includes functional clusters of metabolism (e.g. Cyp2e1, Akr1b10), signal transduction (e.g. Dpp4, Stat3), receptors and ion channels (e.g. Sln, Chrng), membrane and structural proteins (e.g. Tnni1, Mylk2, Col8a1, Adam33), cell growth and differentiation (e.g. Gpc3, Jund), immune response (e.g. C3, C4a), and others (e.g. Lrp8, Msln, Klkc1, Epn3). Gene ontology analysis revealed several significantly enriched functional inter-relationships between genes influenced by non-obese T2DM. Protein-protein interaction analysis demonstrated that Stat is a potential key gene influenced by non-obese T2DM. CONCLUSIONS: Non-obese T2DM alters cardiac gene expression profile. The altered genes may be involved in the development of cardiac pathologies and could be potential therapeutic targets in non-obese T2DM