Hybrid Session Verification through Endpoint API Generation

© Springer-Verlag Berlin Heidelberg 2016.This paper proposes a new hybrid session verification methodology for applying session types directly to mainstream languages, based on generating protocol-specific endpoint APIs from multiparty session types. The API generation promotes static type checking of the behavioural aspect of the source protocol by mapping the state space of an endpoint in the protocol to a family of channel types in the target language. This is supplemented by very light run-time checks in the generated API that enforce a linear usage discipline on instances of the channel types. The resulting hybrid verification guarantees the absence of protocol violation errors during the execution of the session. We implement our methodology for Java as an extension to the Scribble framework, and use it to specify and implement compliant clients and servers for real-world protocols such as HTTP and SMTP

Detailed evaluation of data analysis tools for subtyping of bacterial isolates based on whole genome sequencing : Neisseria meningitidis as a proof of concept

Whole genome sequencing is increasingly recognized as the most informative approach for characterization of bacterial isolates. Success of the routine use of this technology in public health laboratories depends on the availability of well-characterized and verified data analysis methods. However, multiple subtyping workflows are now often being used for a single organism, and differences between them are not always well described. Moreover, methodologies for comparison of subtyping workflows, and assessment of their performance are only beginning to emerge. Current work focuses on the detailed comparison of WGS-based subtyping workflows and evaluation of their suitability for the organism and the research context in question. We evaluated the performance of pipelines used for subtyping of Neisseria meningitidis, including the currently widely applied cgMLST approach and different SNP-based methods. In addition, the impact of the use of different tools for detection and filtering of recombinant regions and of different reference genomes were tested. Our benchmarking analysis included both assessment of technical performance of the pipelines and functional comparison of the generated genetic distance matrices and phylogenetic trees. It was carried out using replicate sequencing datasets of high- and low-coverage, consisting mainly of isolates belonging to the clonal complex 269. We demonstrated that cgMLST and some of the SNP-based subtyping workflows showed very good performance characteristics and highly similar genetic distance matrices and phylogenetic trees with isolates belonging to the same clonal complex. However, only two of the tested workflows demonstrated reproducible results for a group of more closely related isolates. Additionally, results of the SNP-based subtyping workflows were to some level dependent on the reference genome used. Interestingly, the use of recombination-filtering software generally reduced the similarity between the gene-by-gene and SNP-based methodologies for subtyping of N. meningitidis. Our study, where N. meningitidis was taken as an example, clearly highlights the need for more benchmarking comparative studies to eventually contribute to a justified use of a specific WGS data analysis workflow within an international public health laboratory context

Utilizing Mass Spectrometry Imaging to Correlate N-Glycosylation of Hepatocellular Carcinoma with Tumor Subtypes for Biomarker Discovery

Hepatocellular carcinoma (HCC) is a leading cause of cancer deaths globally and is a growing clinical problem with poor survival outcomes beyond early-stage disease. Surveillance for HCC has primarily relied on ultrasound and serum α-fetoprotein (AFP), but combined they only have a sensitivity of 63% for early-stage HCC tumors, suggesting a need for improved diagnostic strategies. Alterations to N-glycan expression are relevant to the progression of cancer, and there a multitude of N-glycan-based cancer biomarkers that have been identified with sensitivity for various cancer types including HCC. Spatial HCC tissue profiling of N-linked glycosylation by matrix-assisted laser desorption ionization imaging mass spectrometry (MALDI-IMS) serves as a new method to evaluate tumor-correlated N-glycosylation and thereby identify potential HCC biomarkers. Previous work has identified significant changes in the N-linked glycosylation of HCC tumors, but has not accounted for the heterogeneous genetic and molecular nature of HCC, which has led to inadequate sensitivity of N-glycan biomarkers. Therefore, we hypothesized that the incorporation of genetic/molecular information into N-glycan-based biomarker development would result in improved sensitivity for HCC. To determine the correlation between HCC-specific N-glycosylation and genetic/molecular tumor features, we profiled HCC tissue samples with MALDI-IMS and correlated the spatial N-glycosylation with a widely used HCC molecular classification that utilizes histological, genetic, and clinical tumor features (Hoshida subtypes). MALDI-IMS data displayed trends that could approximately distinguish between subtypes, with Subtype 1 demonstrating significantly dysregulated N-glycosylation compared to Subtypes 2 and 3, particularly in regard to fucosylation. In order to further the clinical relevance of subtype-dependent N-glycosylation, we analyzed patient-matching HCC tumor tissue, background liver tissue and serum samples through MALDI-IMS. Results showed a N-glycan based model capable of differentiating tumor tissue from background liver tissue with an AUC of 0.9842. When analyzing the associated serum, 24.7% of detected N-glycans were significantly positively correlated between tumor tissue and serum, suggesting that N-glycosylation trends translate from tissue to serum. Additionally, a serum N-glycan-based model was capable of distinguishing Subtype 1/Subtype 2 tumors from Subtype 3 tumors with an AUC of 0.881. Through the utilization of MALDI-IMS, subtype-dependent N-glycosylation trends were identified in both tissue and serum, which can significantly further the development of HCC biomarkers for clinical application

Explicit connection actions in multiparty session types

This work extends asynchronous multiparty session types (MPST) with explicit connection actions to support protocols with op- tional and dynamic participants. The actions by which endpoints are connected and disconnected are a key element of real-world protocols that is not treated in existing MPST works. In addition, the use cases motivating explicit connections often require a more relaxed form of mul- tiparty choice: these extensions do not satisfy the conservative restric- tions used to ensure safety in standard syntactic MPST. Instead, we de- velop a modelling-based approach to validate MPST safety and progress for these enriched protocols. We present a toolchain implementation, for distributed programming based on our extended MPST in Java, and a core formalism, demonstrating the soundness of our approach. We discuss key implementation issues related to the proposed extensions: a practi- cal treatment of choice subtyping for MPST progress, and multiparty correlation of dynamic binary connections

Ferrets exclusively synthesize Neu5Ac and express naturally humanized influenza A virus receptors

Mammals express the sialic acids ​N-acetylneuraminic acid (​Neu5Ac) and ​N-glycolylneuraminic acid (​Neu5Gc) on cell surfaces, where they act as receptors for pathogens, including influenza A virus (IAV). ​Neu5Gc is synthesized from ​Neu5Ac by the enzyme cytidine monophosphate-N-acetylneuraminic acid hydroxylase (CMAH). In humans, this enzyme is inactive and only ​Neu5Ac is produced. Ferrets are susceptible to human-adapted IAV strains and have been the dominant animal model for IAV studies. Here we show that ferrets, like humans, do not synthesize ​Neu5Gc. Genomic analysis reveals an ancient, nine-exon deletion in the ferret CMAH gene that is shared by the Pinnipedia and Musteloidia members of the Carnivora. Interactions between two human strains of IAV with the sialyllactose receptor (sialic acid—α2,6Gal) confirm that the type of terminal sialic acid contributes significantly to IAV receptor specificity. Our results indicate that exclusive expression of ​Neu5Ac contributes to the susceptibility of ferrets to human-adapted IAV strains

National Outbreak of Salmonella Serotype Saintpaul Infections: Importance of Texas Restaurant Investigations in Implicating Jalapeño Peppers

BACKGROUND: In May 2008, PulseNet detected a multistate outbreak of Salmonella enterica serotype Saintpaul infections. Initial investigations identified an epidemiologic association between illness and consumption of raw tomatoes, yet cases continued. In mid-June, we investigated two clusters of outbreak strain infections in Texas among patrons of Restaurant A and two establishments of Restaurant Chain B to determine the outbreak's source. METHODOLOGY/PRINCIPAL FINDINGS: We conducted independent case-control studies of Restaurant A and B patrons. Patients were matched to well controls by meal date. We conducted restaurant environmental investigations and traced the origin of implicated products. Forty-seven case-patients and 40 controls were enrolled in the Restaurant A study. Thirty case-patients and 31 controls were enrolled in the Restaurant Chain B study. In both studies, illness was independently associated with only one menu item, fresh salsa (Restaurant A: matched odds ratio [mOR], 37; 95% confidence interval [CI], 7.2-386; Restaurant B: mOR, 13; 95% CI 1.3-infinity). The only ingredient in common between the two salsas was raw jalapeño peppers. Cultures of jalapeño peppers collected from an importer that supplied Restaurant Chain B and serrano peppers and irrigation water from a Mexican farm that supplied that importer with jalapeño and serrano peppers grew the outbreak strain. CONCLUSIONS/SIGNIFICANCE: Jalapeño peppers, contaminated before arrival at the restaurants and served in uncooked fresh salsas, were the source of these infections. Our investigations, critical in understanding the broader multistate outbreak, exemplify an effective approach to investigating large foodborne outbreaks. Additional measures are needed to reduce produce contamination

Isoform-level gene signature improves prognostic stratification and accurately classifies glioblastoma subtypes.

Molecular stratification of tumors is essential for developing personalized therapies. Although patient stratification strategies have been successful; computational methods to accurately translate the gene-signature from high-throughput platform to a clinically adaptable low-dimensional platform are currently lacking. Here, we describe PIGExClass (platform-independent isoform-level gene-expression based classification-system), a novel computational approach to derive and then transfer gene-signatures from one analytical platform to another. We applied PIGExClass to design a reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) based molecular-subtyping assay for glioblastoma multiforme (GBM), the most aggressive primary brain tumors. Unsupervised clustering of TCGA (the Cancer Genome Altas Consortium) GBM samples, based on isoform-level gene-expression profiles, recaptured the four known molecular subgroups but switched the subtype for 19% of the samples, resulting in significant (P = 0.0103) survival differences among the refined subgroups. PIGExClass derived four-class classifier, which requires only 121 transcript-variants, assigns GBM patients' molecular subtype with 92% accuracy. This classifier was translated to an RT-qPCR assay and validated in an independent cohort of 206 GBM samples. Our results demonstrate the efficacy of PIGExClass in the design of clinically adaptable molecular subtyping assay and have implications for developing robust diagnostic assays for cancer patient stratification

Systematic Evaluation of Serotypes Causing Invasive Pneumococcal Disease among Children Under Five: The Pneumococcal Global Serotype Project

Hope Johnson and colleagues calculate the global and regional burden of serotype-specific pneumococcal disease in children under the age of five