Benchmark datasets for 3D MALDI- and DESI-imaging mass spectrometry

BACKGROUND: Three-dimensional (3D) imaging mass spectrometry (MS) is an analytical chemistry technique for the 3D molecular analysis of a tissue specimen, entire organ, or microbial colonies on an agar plate. 3D-imaging MS has unique advantages over existing 3D imaging techniques, offers novel perspectives for understanding the spatial organization of biological processes, and has growing potential to be introduced into routine use in both biology and medicine. Owing to the sheer quantity of data generated, the visualization, analysis, and interpretation of 3D imaging MS data remain a significant challenge. Bioinformatics research in this field is hampered by the lack of publicly available benchmark datasets needed to evaluate and compare algorithms. FINDINGS: High-quality 3D imaging MS datasets from different biological systems at several labs were acquired, supplied with overview images and scripts demonstrating how to read them, and deposited into MetaboLights, an open repository for metabolomics data. 3D imaging MS data were collected from five samples using two types of 3D imaging MS. 3D matrix-assisted laser desorption/ionization imaging (MALDI) MS data were collected from murine pancreas, murine kidney, human oral squamous cell carcinoma, and interacting microbial colonies cultured in Petri dishes. 3D desorption electrospray ionization (DESI) imaging MS data were collected from a human colorectal adenocarcinoma. CONCLUSIONS: With the aim to stimulate computational research in the field of computational 3D imaging MS, selected high-quality 3D imaging MS datasets are provided that could be used by algorithm developers as benchmark datasets

Genome-Scale Reconstruction of Escherichia coli's Transcriptional and Translational Machinery: A Knowledge Base, Its Mathematical Formulation, and Its Functional Characterization

Metabolic network reconstructions represent valuable scaffolds for ‘-omics’ data integration and are used to computationally interrogate network properties. However, they do not explicitly account for the synthesis of macromolecules (i.e., proteins and RNA). Here, we present the first genome-scale, fine-grained reconstruction of Escherichia coli's transcriptional and translational machinery, which produces 423 functional gene products in a sequence-specific manner and accounts for all necessary chemical transformations. Legacy data from over 500 publications and three databases were reviewed, and many pathways were considered, including stable RNA maturation and modification, protein complex formation, and iron–sulfur cluster biogenesis. This reconstruction represents the most comprehensive knowledge base for these important cellular functions in E. coli and is unique in its scope. Furthermore, it was converted into a mathematical model and used to: (1) quantitatively integrate gene expression data as reaction constraints and (2) compute functional network states, which were compared to reported experimental data. For example, the model predicted accurately the ribosome production, without any parameterization. Also, in silico rRNA operon deletion suggested that a high RNA polymerase density on the remaining rRNA operons is needed to reproduce the reported experimental ribosome numbers. Moreover, functional protein modules were determined, and many were found to contain gene products from multiple subsystems, highlighting the functional interaction of these proteins. This genome-scale reconstruction of E. coli's transcriptional and translational machinery presents a milestone in systems biology because it will enable quantitative integration of ‘-omics’ datasets and thus the study of the mechanistic principles underlying the genotype–phenotype relationship

Tumor classification: molecular analysis meets Aristotle

BACKGROUND: Traditionally, tumors have been classified by their morphologic appearances. Unfortunately, tumors with similar histologic features often follow different clinical courses or respond differently to chemotherapy. Limitations in the clinical utility of morphology-based tumor classifications have prompted a search for a new tumor classification based on molecular analysis. Gene expression array data and proteomic data from tumor samples will provide complex data that is unobtainable from morphologic examination alone. The growing question facing cancer researchers is, "How can we successfully integrate the molecular, morphologic and clinical characteristics of human cancer to produce a helpful tumor classification?" DISCUSSION: Current efforts to classify cancers based on molecular features ignore lessons learned from millennia of experience in biological classification. A tumor classification must include every type of tumor and must provide a unique place for each tumor within the classification. Groups within a classification inherit the properties of their ancestors and impart properties to their descendants. A classification was prepared grouping tumors according to their histogenetic development. The classification is simple (reducing the complexity of information received from the molecular analysis of tumors), comprehensive (providing a place for every tumor of man), and consistent with recent attempts to characterize tumors by cytogenetic and molecular features. The clinical and research value of this historical approach to tumor classification is discussed. SUMMARY: This manuscript reviews tumor classification and provides a new and comprehensive classification for neoplasia that preserves traditional nomenclature while incorporating information derived from the molecular analysis of tumors. The classification is provided as an open access XML document that can be used by cancer researchers to relate tumor classes with heterogeneous experimental and clinical tumor databases

Cardiovascular magnetic resonance myocardial feature tracking detects quantitative wall motion during dobutamine stress

Contains fulltext : 96698.pdf (publisher's version ) (Open Access)BACKGROUND: Dobutamine stress cardiovascular magnetic resonance (DS-CMR) is an established tool to assess hibernating myocardium and ischemia. Analysis is typically based on visual assessment with considerable operator dependency. CMR myocardial feature tracking (CMR-FT) is a recently introduced technique for tissue voxel motion tracking on standard steady-state free precession (SSFP) images to derive circumferential and radial myocardial mechanics.We sought to determine the feasibility and reproducibility of CMR-FT for quantitative wall motion assessment during intermediate dose DS-CMR. METHODS: 10 healthy subjects were studied at 1.5 Tesla. Myocardial strain parameters were derived from SSFP cine images using dedicated CMR-FT software (Diogenes MRI prototype; Tomtec; Germany). Right ventricular (RV) and left ventricular (LV) longitudinal strain (EllRV and EllLV) and LV long-axis radial strain (ErrLAX) were derived from a 4-chamber view at rest. LV short-axis circumferential strain (EccSAX) and ErrSAX; LV ejection fraction (EF) and volumes were analyzed at rest and during dobutamine stress (10 and 20 mug . kg(1). min(1)). RESULTS: In all volunteers strain parameters could be derived from the SSFP images at rest and stress. EccSAX values showed significantly increased contraction with DSMR (rest: -24.1 +/- 6.7; 10 mug: -32.7 +/- 11.4; 20 mug: -39.2 +/- 15.2; p < 0.05). ErrSAX increased significantly with dobutamine (rest: 19.6 +/- 14.6; 10 mug: 31.8 +/- 20.9; 20 mug: 42.4 +/- 25.5; p < 0.05). In parallel with these changes; EF increased significantly with dobutamine (rest: 56.9 +/- 4.4%; 10 mug: 70.7 +/- 8.1; 20 mug: 76.8 +/- 4.6; p < 0.05). Observer variability was best for LV circumferential strain (EccSAX ) and worst for RV longitudinal strain (EllRV) as determined by 95% confidence intervals of the difference. CONCLUSIONS: CMR-FT reliably detects quantitative wall motion and strain derived from SSFP cine imaging that corresponds to inotropic stimulation. The current implementation may need improvement to reduce observer-induced variance. Within a given CMR lab; this novel technique holds promise of easy and fast quantification of wall mechanics and strain

Tissue-Autonomous Function of Drosophila Seipin in Preventing Ectopic Lipid Droplet Formation

Obesity is characterized by accumulation of excess body fat, while lipodystrophy is characterized by loss or absence of body fat. Despite their opposite phenotypes, these two conditions both cause ectopic lipid storage in non-adipose tissues, leading to lipotoxicity, which has health-threatening consequences. The exact mechanisms underlying ectopic lipid storage remain elusive. Here we report the analysis of a Drosophila model of the most severe form of human lipodystrophy, Berardinelli-Seip Congenital Lipodystrophy 2, which is caused by mutations in the BSCL2/Seipin gene. In addition to reduced lipid storage in the fat body, dSeipin mutant flies accumulate ectopic lipid droplets in the salivary gland, a non-adipose tissue. This phenotype was suppressed by expressing dSeipin specifically within the salivary gland. dSeipin mutants display synergistic genetic interactions with lipogenic genes in the formation of ectopic lipid droplets. Our data suggest that dSeipin may participate in phosphatidic acid metabolism and subsequently down-regulate lipogenesis to prevent ectopic lipid droplet formation. In summary, we have demonstrated a tissue-autonomous role of dSeipin in ectopic lipid storage in lipodystrophy

Investigating the metabolic capabilities of Mycobacterium tuberculosis H37Rv using the in silico strain iNJ661 and proposing alternative drug targets

<p>Abstract</p> <p>Background:</p> <p><it>Mycobacterium tuberculosis </it>continues to be a major pathogen in the third world, killing almost 2 million people a year by the most recent estimates. Even in industrialized countries, the emergence of multi-drug resistant (MDR) strains of tuberculosis hails the need to develop additional medications for treatment. Many of the drugs used for treatment of tuberculosis target metabolic enzymes. Genome-scale models can be used for analysis, discovery, and as hypothesis generating tools, which will hopefully assist the rational drug development process. These models need to be able to assimilate data from large datasets and analyze them.</p> <p>Results:</p> <p>We completed a bottom up reconstruction of the metabolic network of <it>Mycobacterium tuberculosis </it>H37Rv. This functional <it>in silico </it>bacterium, <it>iNJ</it>661, contains 661 genes and 939 reactions and can produce many of the complex compounds characteristic to tuberculosis, such as mycolic acids and mycocerosates. We grew this bacterium <it>in silico </it>on various media, analyzed the model in the context of multiple high-throughput data sets, and finally we analyzed the network in an 'unbiased' manner by calculating the Hard Coupled Reaction (HCR) sets, groups of reactions that are forced to operate in unison due to mass conservation and connectivity constraints.</p> <p>Conclusion:</p> <p>Although we observed growth rates comparable to experimental observations (doubling times ranging from about 12 to 24 hours) in different media, comparisons of gene essentiality with experimental data were less encouraging (generally about 55%). The reasons for the often conflicting results were multi-fold, including gene expression variability under different conditions and lack of complete biological knowledge. Some of the inconsistencies between <it>in vitro </it>and <it>in silico </it>or <it>in vivo </it>and <it>in silico </it>results highlight specific loci that are worth further experimental investigations. Finally, by considering the HCR sets in the context of known drug targets for tuberculosis treatment we proposed new alternative, but equivalent drug targets.</p

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

CMR for Assessment of Diastolic Function

Prevalence of heart failure with preserved left ventricular ejection fraction amounts to 50% of all cases with heart failure. Diagnosis assessment requires evidence of left ventricular diastolic dysfunction. Currently, echocardiography is the method of choice for diastolic function testing in clinical practice. Various applications are in use and recommended criteria are followed for classifying the severity of dysfunction. Cardiovascular magnetic resonance (CMR) offers a variety of alternative applications for evaluation of diastolic function, some superior to echocardiography in accuracy and reproducibility, some being complementary. In this article, the role of the available CMR applications for diastolic function testing in clinical practice and research is reviewed and compared to echocardiography

Intracoronary versus intravenous abciximab in ST-segment elevation myocardial infarction: rationale and design of the CICERO trial in patients undergoing primary percutaneous coronary intervention with thrombus aspiration

<p>Abstract</p> <p>Background</p> <p>Administration of abciximab during primary percutaneous coronary intervention is an effective adjunctive therapy in the treatment of patients with ST-segment elevation myocardial infarction. Recent small-scaled studies have suggested that intracoronary administration of abciximab during primary percutaneous coronary intervention is superior to conventional intravenous administration. This study has been designed to investigate whether intracoronary bolus administration of abciximab is more effective than intravenous bolus administration in improving myocardial perfusion in patients with ST-segment elevation myocardial infarction undergoing primary percutaneous coronary intervention with thrombus aspiration.</p> <p>Methods/Design</p> <p>The Comparison of IntraCoronary versus intravenous abciximab administration during Emergency Reperfusion Of ST-segment elevation myocardial infarction (CICERO) trial is a single-center, prospective, randomized open-label trial with blinded evaluation of endpoints. A total of 530 patients with STEMI undergoing primary percutaneous coronary intervention are randomly assigned to either an intracoronary or intravenous bolus of weight-adjusted abciximab. The primary end point is the incidence of >70% ST-segment elevation resolution. Secondary end points consist of post-procedural residual ST-segment deviation, myocardial blush grade, distal embolization, enzymatic infarct size, in-hospital bleeding, and clinical outcome at 30 days and 1 year.</p> <p>Discussion</p> <p>The CICERO trial is the first clinical trial to date to verify the effect of intracoronary versus intravenous administration of abciximab on myocardial perfusion in patients with ST-segment elevation myocardial infarction undergoing primary percutaneous coronary intervention with thrombus aspiration.</p> <p>Trial registration</p> <p>ClinicalTrials.gov NCT00927615</p