Enterprise 2.0: Research challenges and opportunities

© Springer International Publishing Switzerland 2015. Blending Web 2.0 technologies with enterprise information systems is setting up the stage for a new generation of information systems that will help enterprises open up new communication channels with their stakeholders. Contrary to traditional enterprises with top-down command flow and bottom-up feedback flow, the same flows in Enterprise 2.0 cross all levels and in all directions bringing people together in the development of creative and innovative ideas. The power of Web 2.0 technologies stems from their ability to capture real-world phenomena such as collaboration, competition, and partnership that can be converted into useful and structured information sources from which enterprises can draw information about markets’ trends, consumers’ habits, suppliers’ strategies, etc. This paper discusses the research efforts that our international research group has put into the topic of Enterprise 2.0 (aka Social Enterprise). In particular, our research group advocates that existing practices for managing enterprise information systems need to be re-visited in a way that permits to capture social relations that arise inside and outside the enterprise, to establish guidelines and techniques to assist IT practitioners integrate social relations into their design, development, and maintenance efforts of these information systems, and last but not least to identify and tackle challenges that prevent capturing social relations

Type 2 diabetes, glucose, insulin, BMI, and ischemic stroke subtypes: Mendelian randomization study

$\textbf{Objective:}$ To implement a mendelian randomization (MR) approach to determine whether type 2 diabetes mellitus (T2D), fasting glucose, fasting insulin, and body mass index (BMI) are causally associated with specific ischemic stroke subtypes. $\textbf{Methods:}$ MR estimates of the association between each possible risk factor and ischemic stroke subtypes were calculated with inverse-variance weighted (conventional) and weighted median approaches, and MR-Egger regression was used to explore pleiotropy. The number of single nucleotide polymorphisms (SNPs) used as instrumental variables was 49 for T2D, 36 for fasting glucose, 18 for fasting insulin, and 77 for BMI. Genome-wide association study data of SNP-stroke associations were derived from METASTROKE and the Stroke Genetics Network (n = 18,476 ischemic stroke cases and 37,296 controls). $\textbf{Results:}$ Conventional MR analysis showed associations between genetically predicted T2D and large artery stroke (odds ratio [OR] 1.28, 95% confidence interval [CI] 1.16-1.40, p = 3.3 × 10(-7)) and small vessel stroke (OR 1.21, 95% CI 1.10-1.33, p = 8.9 × 10(-5)) but not cardioembolic stroke (OR 1.06, 95% CI 0.97-1.15, p = 0.17). The association of T2D with large artery stroke but not small vessel stroke was consistent in a sensitivity analysis using the weighted median method, and there was no evidence of pleiotropy. Genetically predicted fasting glucose and fasting insulin levels and BMI were not statistically significantly associated with any ischemic stroke subtype. $\textbf{Conclusions:}$ This study provides support that T2D may be causally associated with large artery stroke.Hugh S Markus is supported by a National Institute for Health Research (NIHR) Senior Investigator award, and his work is supported by the Cambridge Universities NIHR Comprehensive Biomedical Research Centre. See also article

Epigenetic Differences in Cortical Neurons from a Pair of Monozygotic Twins Discordant for Alzheimer's Disease

DNA methylation [1], [2] is capable of modulating coordinate expression of large numbers of genes across many different pathways, and may therefore warrant investigation for their potential role between genes and disease phenotype. In a rare set of monozygotic twins discordant for Alzheimer's disease (AD), significantly reduced levels of DNA methylation were observed in temporal neocortex neuronal nuclei of the AD twin. These findings are consistent with the hypothesis that epigenetic mechanisms may mediate at the molecular level the effects of life events on AD risk, and provide, for the first time, a potential explanation for AD discordance despite genetic similarities

COMPASS identifies T-cell subsets correlated with clinical outcomes.

Advances in flow cytometry and other single-cell technologies have enabled high-dimensional, high-throughput measurements of individual cells as well as the interrogation of cell population heterogeneity. However, in many instances, computational tools to analyze the wealth of data generated by these technologies are lacking. Here, we present a computational framework for unbiased combinatorial polyfunctionality analysis of antigen-specific T-cell subsets (COMPASS). COMPASS uses a Bayesian hierarchical framework to model all observed cell subsets and select those most likely to have antigen-specific responses. Cell-subset responses are quantified by posterior probabilities, and human subject-level responses are quantified by two summary statistics that describe the quality of an individual's polyfunctional response and can be correlated directly with clinical outcome. Using three clinical data sets of cytokine production, we demonstrate how COMPASS improves characterization of antigen-specific T cells and reveals cellular 'correlates of protection/immunity' in the RV144 HIV vaccine efficacy trial that are missed by other methods. COMPASS is available as open-source software

Key Concepts for Estimating the Burden of Surgical Conditions and the Unmet Need for Surgical Care

Background: Surgical care is emerging as a crucial issue in global public health. Methodology is needed to assess the impact of surgical care from a public health perspective. Methods: A consensus opinion of a group of surgeons, anesthesiologists, and public health experts was established regarding the methodology for estimating the burden of surgical conditions and the unmet need for surgical care. Results: For purposes of analysis, we define surgical conditions as any disease state requiring the expertise of a surgically trained provider. Abnormalities resulting from a surgical condition or its treatment are termed surgical sequelae. Surgical care is defined as any measure that reduces the rates of physical disability or premature death associated with a surgical condition. To measure the burden of surgical conditions and unmet need for surgical care we propose using cumulative disability-adjusted life-year (DALY) curves generated from age-specific population-based data. This conceptual framework is based on the premise that surgically associated disability and death is determined by the incidence of surgical conditions and the quantity and quality of surgical care. The burden of surgical conditions is defined as the total disability and premature deaths that would occur in a population should there be no surgical care; the unmet need for surgical care is defined as the potentially treatable disability and premature deaths due to surgical conditions. Burden of surgical conditions should be expressed as DALYs and unmet need as potential DALYs avertable. Conclusions: Methodology is described for estimating the burden of surgical conditions and unmet need for surgical care. Using this approach it will be feasible to estimate the global burden of surgical conditions and help clarify where surgery fits among other global health priorities. These methods need to be validated using population-based data

Skewed genomic variability in strains of the toxigenic bacterial pathogen, Clostridium perfringens

Clostridium perfringens is a Gram-positive, anaerobic spore-forming bacterium commonly found in soil, sediments, and the human gastrointestinal tract. C. perfringens is responsible for a wide spectrum of disease, including food poisoning, gas gangrene (clostridial myonecrosis), enteritis necroticans, and non-foodborne gastrointestinal infections. The complete genome sequences of Clostridium perfringens strain ATCC 13124, a gas gangrene isolate and the species type strain, and the enterotoxin-producing food poisoning strain SM101, were determined and compared with the published C. perfringens strain 13 genome. Comparison of the three genomes revealed considerable genomic diversity with >300 unique "genomic islands" identified, with the majority of these islands unusually clustered on one replichore. PCR-based analysis indicated that the large genomic islands are widely variable across a large collection of C. perfringens strains. These islands encode genes that correlate to differences in virulence and phenotypic characteristics of these strains. Significant differences between the strains include numerous novel mobile elements and genes encoding metabolic capabilities, strain-specific extracellular polysaccharide capsule, sporulation factors, toxins, and other secreted enzymes, providing substantial insight into this medically important bacterial pathogen. ©2006 by Cold Spring Harbor Laboratory Press

New Insights into the Diversity of Marine Picoeukaryotes

Over the last decade, culture-independent surveys of marine picoeukaryotic diversity based on 18S ribosomal DNA clone libraries have unveiled numerous sequences of novel high-rank taxa. This newfound diversity has significantly altered our understanding of marine microbial food webs and the evolution of eukaryotes. However, the current picture of marine eukaryotic biodiversity may be significantly skewed by PCR amplification biases, occurrence of rDNA genes in multiple copies within a single cell, and the capacity of DNA to persist as extracellular material. In this study we performed an analysis of the metagenomic dataset from the Global Ocean Survey (GOS) expedition, seeking eukaryotic ribosomal signatures. This PCR-free approach revealed similar phylogenetic patterns to clone library surveys, suggesting that PCR steps do not impose major biases in the exploration of environmental DNA. The different cell size fractions within the GOS dataset, however, displayed a distinct picture. High protistan diversity in the <0.8 µm size fraction, in particular sequences from radiolarians and ciliates (and their absence in the 0.8–3 µm fraction), suggest that most of the DNA in this fraction comes from extracellular material from larger cells. In addition, we compared the phylogenetic patterns from rDNA and reverse transcribed rRNA 18S clone libraries from the same sample harvested in the Mediterranean Sea. The libraries revealed major differences, with taxa such as pelagophytes or picobiliphytes only detected in the 18S rRNA library. MAST (Marine Stramenopiles) appeared as potentially prominent grazers and we observed a significant decrease in the contribution of alveolate and radiolarian sequences, which overwhelmingly dominated rDNA libraries. The rRNA approach appears to be less affected by taxon-specific rDNA copy number and likely better depicts the biogeochemical significance of marine protists

Endophyte Microbiome Diversity in Micropropagated Atriplex canescens and Atriplex torreyi var griffithsii

Microbial diversity associated with micropropagated Atriplex species was assessed using microscopy, isolate culturing, and sequencing. Light, electron, and confocal microscopy revealed microbial cells in aseptically regenerated leaves and roots. Clone libraries and tag-encoded FLX amplicon pyrosequencing (TEFAP) analysis amplified sequences from callus homologous to diverse fungal and bacterial taxa. Culturing isolated some seed borne endophyte taxa which could be readily propagated apart from the host. Microbial cells were observed within biofilm-like residues associated with plant cell surfaces and intercellular spaces. Various universal primers amplified both plant and microbial sequences, with different primers revealing different patterns of fungal diversity. Bacterial and fungal TEFAP followed by alignment with sequences from curated databases revealed 7 bacterial and 17 ascomycete taxa in A. canescens, and 5 bacterial taxa in A. torreyi. Additional diversity was observed among isolates and clone libraries. Micropropagated Atriplex retains a complex, intimately associated microbiome which includes diverse strains well poised to interact in manners that influence host physiology. Microbiome analysis was facilitated by high throughput sequencing methods, but primer biases continue to limit recovery of diverse sequences from even moderately complex communities