Metamodel-based model conformance and multiview consistency checking

Model-driven development, using languages such as UML and BON, often makes use of multiple diagrams (e.g., class and sequence diagrams) when modeling systems. These diagrams, presenting different views of a system of interest, may be inconsistent. A metamodel provides a unifying framework in which to ensure and check consistency, while at the same time providing the means to distinguish between valid and invalid models, that is, conformance. Two formal specifications of the metamodel for an object-oriented modeling language are presented, and it is shown how to use these specifications for model conformance and multiview consistency checking. Comparisons are made in terms of completeness and the level of automation each provide for checking multiview consistency and model conformance. The lessons learned from applying formal techniques to the problems of metamodeling, model conformance, and multiview consistency checking are summarized

Aperiodicity in one-way Markov cycles and repeat times of large earthquakes in faults

A common use of Markov Chains is the simulation of the seismic cycle in a fault, i.e. as a renewal model for the repetition of its characteristic earthquakes. This representation is consistent with Reid's elastic rebound theory. Here it is proved that in {\it any} one-way Markov cycle, the aperiodicity of the corresponding distribution of cycle lengths is always lower than one. This fact concurs with observations of large earthquakes in faults all over the world

HIV-1 immune activation induces Siglec-1 expression and enhances viral trans-infection in blood and tissue myeloid cells

Background: Myeloid cells are key players in the recognition and response of the host against invading viruses. Paradoxically, upon HIV-1 infection, myeloid cells might also promote viral pathogenesis through trans-infection, a mechanism that promotes HIV-1 transmission to target cells via viral capture and storage. The receptor Siglec-1 (CD169) potently enhances HIV-1 trans-infection and is regulated by immune activating signals present throughout the course of HIV-1 infection, such as interferon α (IFNα). Results: Here we show that IFNα-activated dendritic cells, monocytes and macrophages have an enhanced ability to capture and trans-infect HIV-1 via Siglec-1 recognition of viral membrane gangliosides. Monocytes from untreated HIV-1-infected individuals trans-infect HIV-1 via Siglec-1, but this capacity diminishes after effective antiretroviral treatment. Furthermore, Siglec-1 is expressed on myeloid cells residing in lymphoid tissues, where it can mediate viral trans-infection. Conclusions: Siglec-1 on myeloid cells could fuel novel CD4+ T-cell infections and contribute to HIV-1 dissemination in vivo

The Interplay Between Host Genetic Variation, Viral Replication, and Microbial Translocation in Untreated HIV-Infected Individuals

Systemic immune activation, a major determinant of human immunodeficiency virus (HIV) disease progression, is the result of a complex interplay between viral replication, dysregulation of the immune system, and microbial translocation due to gut mucosal damage. Although human genetic variants influencing HIV load have been identified, it is unknown how much the host genetic background contributes to interindividual differences in other determinants of HIV pathogenesis such as gut damage and microbial translocation. Using samples and data from 717 untreated participants in the Swiss HIV Cohort Study and a genome-wide association study design, we searched for human genetic determinants of plasma levels of intestinal fatty acid-binding protein (I-FABP/FABP2), a marker of gut damage, and of soluble CD14 (sCD14), a marker of lipopolysaccharide bioactivity and microbial translocation. We also assessed the correlations between HIV load, sCD14, and I-FABP. Although we found no genome-wide significant determinant of the tested plasma markers, we observed strong associations between sCD14 and both HIV load and I-FABP, shedding new light on the relationships between processes that drive progression of untreated HIV infectio

Association Study of Common Genetic Variants and HIV- 1 Acquisition in 6,300 Infected Cases and 7,200 Controls

Multiple genome-wide association studies (GWAS) have been performed in HIV-1 infected individuals, identifying common genetic influences on viral control and disease course. Similarly, common genetic correlates of acquisition of HIV-1 after exposure have been interrogated using GWAS, although in generally small samples. Under the auspices of the International Collaboration for the Genomics of HIV, we have combined the genome-wide single nucleotide polymorphism (SNP) data collected by 25 cohorts, studies, or institutions on HIV-1 infected individuals and compared them to carefully matched population-level data sets (a list of all collaborators appears in Note S1 in Text S1). After imputation using the 1,000 Genomes Project reference panel, we tested approximately 8 million common DNA variants (SNPs and indels) for association with HIV-1 acquisition in 6,334 infected patients and 7,247 population samples of European ancestry. Initial association testing identified the SNP rs4418214, the C allele of which is known to tag the HLA-B*57:01 and B*27:05 alleles, as genome-wide significant (p = 3.6×10−11). However, restricting analysis to individuals with a known date of seroconversion suggested that this association was due to the frailty bias in studies of lethal diseases. Further analyses including testing recessive genetic models, testing for bulk effects of non-genome-wide significant variants, stratifying by sexual or parenteral transmission risk and testing previously reported associations showed no evidence for genetic influence on HIV-1 acquisition (with the exception ofCCR5Δ32 homozygosity). Thus, these data suggest that genetic influences on HIV acquisition are either rare or have smaller effects than can be detected by this sample size

Contribution of Genetic Background, Traditional Risk Factors, and HIV-Related Factors to Coronary Artery Disease Events in HIV-Positive Persons

We show in human immunodeficiency virus-positive persons that the coronary artery disease effect of an unfavorable genetic background is comparable to previous studies in the general population, and comparable in size to traditional risk factors and antiretroviral regimens known to increase cardiovascular ris

Long-term hydroxyurea in combination with didanosine and stavudine for the treatment of HIV-1 infection

Objective and methods: In 1998 we reported on a randomized comparison between stavudine plus didanosine plus placebo versus stavudine plus didanosine plus hydroxyurea (HU), in patients with a CD4 count of 200±500 3 10 6 cells/l. After 3 months, the HU group had a higher proportion of patients with viral load , 200 3 10 6 cells/l. At the end of the 3 months blinded period, patients in the placebo group had the option to add HU if their viral load remained . 200 3 10 6 cells/l. We report results after 24 months. Results: Seventy-two patients were randomized to the HU arm, and a further 30 elected to add HU after 12 weeks. Twenty-four months after the start of the trial, only 25% of the 72 patients originally randomized to HU, and 20% of the 30 who added HU after week 12, were still taking it. The reasons for stopping HU were: lack of ef®cacy (45%), adverse events (37%) and patient or physician preference (18%). Side effects were more frequent in the didanosine/stavudine/HU group than in the didanosine/stavudine group: neuropathy (35 versus 15%, P , 0.02), fatigue (22 versus 7%, P , 0.01), and nausea or vomiting (26 versus 9%, P ,0.01). Of those who had discontinued HU, 73% were taking three drugs including a protease inhibitor. Patients who had started HU were compared with similar patients who had started protease inhibitors in the Swiss cohort. The probability of stopping HU was higher than the probability of stopping nel®navir or indinavir, and similar to the probability of stopping ritonavir. Conclusion: HU increased the antiviral effect of stavudine plus didanosine. However, side effects were more frequent, and after 24 months the majority of patients had switched to protease inhibitor regimens

The fecal metabolome as a functional readout of the gut microbiome

The human gut microbiome plays a key role in human health1, but 16S characterization lacks quantitative functional annotation2. The fecal metabolome provides a functional readout of microbial activity and can be used as an intermediate phenotype mediating host–microbiome interactions3. In this comprehensive description of the fecal metabolome, examining 1,116 metabolites from 786 individuals from a population-based twin study (TwinsUK), the fecal metabolome was found to be only modestly influenced by host genetics (heritability (H2) = 17.9%). One replicated locus at the NAT2 gene was associated with fecal metabolic traits. The fecal metabolome largely reflects gut microbial composition, explaining on average 67.7% (±18.8%) of its variance. It is strongly associated with visceral-fat mass, thereby illustrating potential mechanisms underlying the well-established microbial influence on abdominal obesity. Fecal metabolic profiling thus is a novel tool to explore links among microbiome composition, host phenotypes, and heritable complex traits

Host and Viral Genetic Correlates of Clinical Definitions of HIV-1 Disease Progression

BACKGROUND: Various patterns of HIV-1 disease progression are described in clinical practice and in research. There is a need to assess the specificity of commonly used definitions of long term non-progressor (LTNP) elite controllers (LTNP-EC), viremic controllers (LTNP-VC), and viremic non controllers (LTNP-NC), as well as of chronic progressors (P) and rapid progressors (RP). METHODOLOGY AND PRINCIPAL FINDINGS: We re-evaluated the HIV-1 clinical definitions, summarized in Table 1, using the information provided by a selected number of host genetic markers and viral factors. There is a continuous decrease of protective factors and an accumulation of risk factors from LTNP-EC to RP. Statistical differences in frequency of protective HLA-B alleles (p-0.01), HLA-C rs9264942 (p-0.06), and protective CCR5/CCR2 haplotypes (p-0.02) across groups, and the presence of viruses with an ancestral genotype in the "viral dating" (i.e., nucleotide sequences with low viral divergence from the most recent common ancestor) support the differences among principal clinical groups of HIV-1 infected individuals. CONCLUSIONS: A combination of host genetic and viral factors supports current clinical definitions that discriminate among patterns of HIV-1 progression. The study also emphasizes the need to apply a standardized and accepted set of clinical definitions for the purpose of disease stratification and research