Direct and inverse scattering problems for quasi-linear biharmonic operator in 3D

Abstract. We consider direct and inverse scattering problems for three-dimensional biharmonic operator $Hu = ∆^2u + Vu$, where $∆$ is the Laplacian and $V$ is a scalar valued perturbation. The scattering problem for this operator is given as a partial differential equation $Hu = k^4u$, with a parameter $k$. In the direct scattering problem, our goal is to find the solution $u$ while the perturbation (V\) is known. We also assume that the solution $u$ can be written as a sum of two functions $u_{0}$ and $u_{sc}$, where $u_{0}$ is a plane wave and $u_{sc}$ is an outgoing wave in the sense that it satisfies to the Sommerfeld radiation conditions at the infinity. Our approach in this text is to first modify the partial differential equation into an integral equation by using the fundamental solution. Next, we show that this integral equation is solvable, and it has a unique solution. Finally, we prove two main results of this text; an asymptotic formula for the solution with large values of $x ∈ \mathbb{R}^3$ and Saito’s formula. The asymptotic behaviour of the solution leads us to defining the scattering amplitude. In the inverse scattering problem, the goal is to gather some information about the unknown perturbation V while the behaviour of the function u is known. With Saito’s formula we obtain two corollaries regarding the inverse scattering problem, namely uniqueness and a representation formula for the function $V(x, 1)$, when the scattering amplitude is known. We end the text by first defining the inverse Born approximation for both full scattering data and backscattering data. We also discuss some results that have been obtained previously with this approach

genoPlotR: comparative gene and genome visualization in R

Summary: The amount of gene and genome data obtained by next-generation sequencing technologies generates a need for comparative visualization tools. Complementing existing software for comparison and exploration of genomics data, genoPlotR automatically creates publication-grade linear maps of gene and genomes, in a highly automatic, flexible and reproducible way

MOCAT2: a metagenomic assembly, annotation and profiling framework

MOCAT2 is a software pipeline for metagenomic sequence assembly and gene prediction with novel features for taxonomic and functional abundance profiling. The automated generation and efficient annotation of non-redundant reference catalogs by propagating pre-computed assignments from 18 databases covering various functional categories allows for fast and comprehensive functional characterization of metagenomes. Availability and Implementation: MOCAT2 is implemented in Perl 5 and Python 2.7, designed for 64-bit UNIX systems and offers support for high-performance computer usage via LSF, PBS or SGE queuing systems; source code is freely available under the GPL3 license at http://mocat.embl.de. Contact: [email protected]

Proteomics-Based Characterization of miR-574-5p Decoy to CUGBP1 Suggests Specificity for mPGES-1 Regulation in Human Lung Cancer Cells

MicroRNAs (miRs) are one of the most important post-transcriptional repressors of gene expression. However, miR-574-5p has recently been shown to positively regulate the expression of microsomal prostaglandin E-synthase-1 (mPGES-1), a key enzyme in the prostaglandin E2 (PGE2) biosynthesis, by acting as decoy to the RNA-binding protein CUG-RNA binding protein 1 (CUGBP1) in human lung cancer. miR-574-5p exhibits oncogenic properties and promotes lung tumor growth in vivo via induction of mPGES-1-derived PGE2 synthesis. In a mass spectrometry-based proteomics study, we now attempted to characterize this decoy mechanism in A549 lung cancer cells at a cellular level. Besides the identification of novel CUGBP1 targets, we identified that the interaction between miR-574-5p and CUGBP1 specifically regulates mPGES-1 expression. This is supported by the fact that CUGBP1 and miR-574-5p are located in the nucleus, where CUGBP1 regulates alternative splicing. Further, in a bioinformatical approach we showed that the decoy-dependent mPGES-1 splicing pattern is unique. The specificity of miR-574-5p/CUGBP1 regulation on mPGES-1 expression supports the therapeutic strategy of pharmacological inhibition of PGE2 formation, which may provide significant therapeutic value for NSCLC patients with high miR-574-5p levels

Potential of fecal microbiota for early-stage detection of colorectal cancer

Several bacterial species have been implicated in the development of colorectal carcinoma (CRC), but CRC-associated changes of fecal microbiota and their potential for cancer screening remain to be explored. Here, we used metagenomic sequencing of fecal samples to identify taxonomic markers that distinguished CRC patients from tumor-free controls in a study population of 156 participants. Accuracy of metagenomic CRC detection was similar to the standard fecal occult blood test (FOBT) and when both approaches were combined, sensitivity improved > 45% relative to the FOBT, while maintaining its specificity. Accuracy of metagenomic CRC detection did not differ significantly between early- and late-stage cancer and could be validated in independent patient and control populations (N = 335) from different countries. CRC-associated changes in the fecal microbiome at least partially reflected microbial community composition at the tumor itself, indicating that observed gene pool differences may reveal tumor-related host-microbe interactions. Indeed, we deduced a metabolic shift from fiber degradation in controls to utilization of host carbohydrates and amino acids in CRC patients, accompanied by an increase of lipopolysaccharide metabolism

Current challenges in software solutions for mass spectrometry-based quantitative proteomics

This work was in part supported by the PRIME-XS project, grant agreement number 262067, funded by the European Union seventh Framework Programme; The Netherlands Proteomics Centre, embedded in The Netherlands Genomics Initiative; The Netherlands Bioinformatics Centre; and the Centre for Biomedical Genetics (to S.C., B.B. and A.J.R.H); by NIH grants NCRR RR001614 and RR019934 (to the UCSF Mass Spectrometry Facility, director: A.L. Burlingame, P.B.); and by grants from the MRC, CR-UK, BBSRC and Barts and the London Charity (to P.C.

Improved Differential Diagnosis of Alzheimer’s Disease by Integrating ELISA and Mass Spectrometry-Based Cerebrospinal Fluid Biomarkers

BACKGROUND: Alzheimer’s disease (AD) is diagnosed based on a clinical evaluation as well as analyses of classical biomarkers: Aβ₄₂, total tau (t-tau), and phosphorylated tau (p-tau) in cerebrospinal fluid (CSF). Although the sensitivities and specificities of the classical biomarkers are fairly good for detection of AD, there is still a need to develop novel biochemical markers for early detection of AD. OBJECTIVE: We explored if integration of novel proteins with classical biomarkers in CSF can better discriminate AD from non-AD subjects. METHODS: We applied ELISA, mass spectrometry, and multivariate modeling to investigate classical biomarkers and the CSF proteome in subjects (n = 206) with 76 AD patients, 74 mild cognitive impairment (MCI) patients, 11 frontotemporal dementia (FTD) patients, and 45 non-dementia controls. The MCI patients were followed for 4–9 years and 21 of these converted to AD, whereas 53 remained stable. RESULTS: By combining classical CSF biomarkers with twelve novel markers, the area of the ROC curves (AUROCS) of distinguishing AD and MCI/AD converters from non-AD were 93% and 96%, respectively. The FTDs and non-dementia controls were identified versus all other groups with AUROCS of 96% and 87%, respectively. CONCLUSIONS: Integration of new and classical CSF biomarkers in a model-based approach can improve the identification of AD, FTD, and non-dementia control subjects

Targeted resequencing of candidate genes using selector probes

Targeted genome enrichment is a powerful tool for making use of the massive throughput of novel DNA-sequencing instruments. We herein present a simple and scalable protocol for multiplex amplification of target regions based on the Selector technique. The updated version exhibits improved coverage and compatibility with next-generation-sequencing (NGS) library-construction procedures for shotgun sequencing with NGS platforms. To demonstrate the performance of the technique, all 501 exons from 28 genes frequently involved in cancer were enriched for and sequenced in specimens derived from cell lines and tumor biopsies. DNA from both fresh frozen and formalin-fixed paraffin-embedded biopsies were analyzed and 94% specificity and 98% coverage of the targeted region was achieved. Reproducibility between replicates was high (R2 = 0, 98) and readily enabled detection of copy-number variations. The procedure can be carried out in <24 h and does not require any dedicated instrumentation

Striatal Proteomic Analysis Suggests that First L-Dopa Dose Equates to Chronic Exposure

L-3,4-dihydroxypheylalanine (L-dopa)-induced dyskinesia represent a debilitating complication of therapy for Parkinson's disease (PD) that result from a progressive sensitization through repeated L-dopa exposures. The MPTP macaque model was used to study the proteome in dopamine-depleted striatum with and without subsequent acute and chronic L-dopa treatment using two-dimensional difference in-gel electrophoresis (2D-DIGE) and mass spectrometry. The present data suggest that the dopamine-depleted striatum is so sensitive to de novo L-dopa treatment that the first ever administration alone would be able (i) to induce rapid post-translational modification-based proteomic changes that are specific to this first exposure and (ii), possibly, lead to irreversible protein level changes that would be not further modified by chronic L-dopa treatment. The apparent equivalence between first and chronic L-dopa administration suggests that priming would be the direct consequence of dopamine loss, the first L-dopa administrations only exacerbating the sensitization process but not inducing it

Interoperable and scalable data analysis with microservices: applications in metabolomics.

Developing a robust and performant data analysis workflow that integrates all necessary components whilst still being able to scale over multiple compute nodes is a challenging task. We introduce a generic method based on the microservice architecture, where software tools are encapsulated as Docker containers that can be connected into scientific workflows and executed using the Kubernetes container orchestrator. We developed a Virtual Research Environment (VRE) which facilitates rapid integration of new tools and developing scalable and interoperable workflows for performing metabolomics data analysis. The environment can be launched on-demand on cloud resources and desktop computers. IT-expertise requirements on the user side are kept to a minimum, and workflows can be re-used effortlessly by any novice user. We validate our method in the field of metabolomics on two mass spectrometry, one nuclear magnetic resonance spectroscopy and one fluxomics study. We showed that the method scales dynamically with increasing availability of computational resources. We demonstrated that the method facilitates interoperability using integration of the major software suites resulting in a turn-key workflow encompassing all steps for mass-spectrometry-based metabolomics including preprocessing, statistics and identification. Microservices is a generic methodology that can serve any scientific discipline and opens up for new types of large-scale integrative science. The PhenoMeNal consortium maintains a web portal (https://portal.phenomenal-h2020.eu) providing a GUI for launching the Virtual Research Environment. The GitHub repository https://github.com/phnmnl/ hosts the source code of all projects. Supplementary data are available at Bioinformatics online