Should We Learn Probabilistic Models for Model Checking? A New Approach and An Empirical Study

Many automated system analysis techniques (e.g., model checking, model-based testing) rely on first obtaining a model of the system under analysis. System modeling is often done manually, which is often considered as a hindrance to adopt model-based system analysis and development techniques. To overcome this problem, researchers have proposed to automatically "learn" models based on sample system executions and shown that the learned models can be useful sometimes. There are however many questions to be answered. For instance, how much shall we generalize from the observed samples and how fast would learning converge? Or, would the analysis result based on the learned model be more accurate than the estimation we could have obtained by sampling many system executions within the same amount of time? In this work, we investigate existing algorithms for learning probabilistic models for model checking, propose an evolution-based approach for better controlling the degree of generalization and conduct an empirical study in order to answer the questions. One of our findings is that the effectiveness of learning may sometimes be limited.Comment: 15 pages, plus 2 reference pages, accepted by FASE 2017 in ETAP

Learning deterministic probabilistic automata from a model checking perspective

Probabilistic automata models play an important role in the formal design and analysis of hard- and software systems. In this area of applications, one is often interested in formal model-checking procedures for verifying critical system properties. Since adequate system models are often difficult to design manually, we are interested in learning models from observed system behaviors. To this end we adopt techniques for learning finite probabilistic automata, notably the Alergia algorithm. In this paper we show how to extend the basic algorithm to also learn automata models for both reactive and timed systems. A key question of our investigation is to what extent one can expect a learned model to be a good approximation for the kind of probabilistic properties one wants to verify by model checking. We establish theoretical convergence properties for the learning algorithm as well as for probability estimates of system properties expressed in linear time temporal logic and linear continuous stochastic logic. We empirically compare the learning algorithm with statistical model checking and demonstrate the feasibility of the approach for practical system verification

Extreme genetic fragility of the HIV-1 capsid

Genetic robustness, or fragility, is defined as the ability, or lack thereof, of a biological entity to maintain function in the face of mutations. Viruses that replicate via RNA intermediates exhibit high mutation rates, and robustness should be particularly advantageous to them. The capsid (CA) domain of the HIV-1 Gag protein is under strong pressure to conserve functional roles in viral assembly, maturation, uncoating, and nuclear import. However, CA is also under strong immunological pressure to diversify. Therefore, it would be particularly advantageous for CA to evolve genetic robustness. To measure the genetic robustness of HIV-1 CA, we generated a library of single amino acid substitution mutants, encompassing almost half the residues in CA. Strikingly, we found HIV-1 CA to be the most genetically fragile protein that has been analyzed using such an approach, with 70% of mutations yielding replication-defective viruses. Although CA participates in several steps in HIV-1 replication, analysis of conditionally (temperature sensitive) and constitutively non-viable mutants revealed that the biological basis for its genetic fragility was primarily the need to coordinate the accurate and efficient assembly of mature virions. All mutations that exist in naturally occurring HIV-1 subtype B populations at a frequency >3%, and were also present in the mutant library, had fitness levels that were >40% of WT. However, a substantial fraction of mutations with high fitness did not occur in natural populations, suggesting another form of selection pressure limiting variation in vivo. Additionally, known protective CTL epitopes occurred preferentially in domains of the HIV-1 CA that were even more genetically fragile than HIV-1 CA as a whole. The extreme genetic fragility of HIV-1 CA may be one reason why cell-mediated immune responses to Gag correlate with better prognosis in HIV-1 infection, and suggests that CA is a good target for therapy and vaccination strategies

Self-Reported Health Status in Primary Health Care: The Influence of Immigration and Other Associated Factors

OBJECTIVE: The aims of this study are to compare self-reported health status between Spanish-born and Latin American-born Spanish residents, adjusted by length of residence in the host country; and additionally, to analyse sociodemographic and psychosocial variables associated with a better health status. DESIGN: This is a cross-sectional population based study of Latin American-born (n = 691) and Spanish-born (n = 903) in 15 urban primary health care centres in Madrid (Spain), carried out between 2007 and 2009. The participants provided information, through an interview, about self-reported health status, socioeconomic characteristics, psychosocial factors and migration conditions. Descriptive and multiple logistic regression analyses were conducted. RESULTS: The Spanish-born participants reported a better health status than the Latin America-born participants (79.8% versus 69.3%, p<0.001). Different patterns of self-reported health status were observed depending on the length of residence in the host country. The proportion of immigrants with a better health status is greater in those who have been in Spain for less than five years compared to those who have stayed longer. Better health status is significantly associated with being men, under 34 years old, being Spanish-born, having a monthly incomes of over 1000 euros, and having considerable social support and low stress. CONCLUSIONS: Better self-reported health status is associated with being Spanish-born, men, under 34 years old, having an uppermiddle-socioeconomic status, adequate social support, and low stress. Additionally, length of residence in the host country is seen as a related factor in the self-reported health status of immigrants

Epidemiological risk factors for adult dengue in Singapore: an 8-year nested test negative case control study

10.1186/s12879-016-1662-4BMC Infectious Diseases16132

The Multi-Regge limit of NMHV Amplitudes in N=4 SYM Theory

We consider the multi-Regge limit for N=4 SYM NMHV leading color amplitudes in two different formulations: the BFKL formalism for multi-Regge amplitudes in leading logarithm approximation, and superconformal N=4 SYM amplitudes. It is shown that the two approaches agree to two-loops for the 2->4 and 3->3 six-point amplitudes. Predictions are made for the multi-Regge limit of three loop 2->4 and 3->3 NMHV amplitudes, as well as a particular sub-set of two loop 2 ->2 +n N^kMHV amplitudes in the multi-Regge limit in the leading logarithm approximation from the BFKL point of view.Comment: 28 pages, 3 figure

Phylogenomic Analysis of Odyssella thessalonicensis Fortifies the Common Origin of Rickettsiales, Pelagibacter ubique and Reclimonas americana Mitochondrion

Background: The evolution of the Alphaproteobacteria and origin of the mitochondria are topics of considerable debate. Most studies have placed the mitochondria ancestor within the Rickettsiales order. Ten years ago, the bacterium Odyssella thessalonicensis was isolated from Acanthamoeba spp., and the 16S rDNA phylogeny placed it within the Rickettsiales. Recently, the whole genome of O. thessalonicensis has been sequenced, and 16S rDNA phylogeny and more robust and accurate phylogenomic analyses have been performed with 65 highly conserved proteins. Methodology/Principal Findings: The results suggested that the O. thessalonicensis emerged between the Rickettsiales and other Alphaproteobacteria. The mitochondrial proteins of the Reclinomonas americana have been used to locate the phylogenetic position of the mitochondrion ancestor within the Alphaproteobacteria tree. Using the K tree score method, nine mitochondrion-encoded proteins, whose phylogenies were congruent with the Alphaproteobacteria phylogenomic tree, have been selected and concatenated for Bayesian and Maximum Likelihood phylogenies. The Reclinomonas americana mitochondrion is a sister taxon to the free-living bacteria Candidatus Pelagibacter ubique, and together, they form a clade that is deeply rooted in the Rickettsiales clade. Conclusions/Significance: The Reclinomonas americana mitochondrion phylogenomic study confirmed that mitochondri

The COMT Val158 Met polymorphism as an associated risk factor for Alzheimer disease and mild cognitive impairment in APOE 4 carriers

<p>Abstract</p> <p>Background</p> <p>The aim of this study is to examine the influence of the <it>catechol-O-methyltranferase (COMT) </it>gene (polymorphism Val158 Met) as a risk factor for Alzheimer's disease (AD) and mild cognitive impairment of amnesic type (MCI), and its synergistic effect with the <it>apolipoprotein E gene (APOE)</it>.</p> <p>A total of 223 MCI patients, 345 AD and 253 healthy controls were analyzed. Clinical criteria and neuropsychological tests were used to establish diagnostic groups.</p> <p>The DNA Bank of the University of the Basque Country (UPV-EHU) (Spain) determined <it>COMT </it>Val158 Met and <it>APOE </it>genotypes using real time polymerase chain reaction (rtPCR) and polymerase chain reaction (PCR), and restriction fragment length polymorphism (RFLPs), respectively. Multinomial logistic regression models were used to determine the risk of AD and MCI.</p> <p>Results</p> <p>Neither <it>COMT </it>alleles nor genotypes were independent risk factors for AD or MCI. The high activity genotypes (GG and AG) showed a synergistic effect with <it>APOE ε4 </it>allele, increasing the risk of AD (OR = 5.96, 95%CI 2.74-12.94, p < 0.001 and OR = 6.71, 95%CI 3.36-13.41, p < 0.001 respectivily). In AD patients this effect was greater in women.</p> <p>In MCI patients such as synergistic effect was only found between AG and <it>APOE ε4 </it>allele (OR = 3.21 95%CI 1.56-6.63, p = 0.02) and was greater in men (OR = 5.88 95%CI 1.69-20.42, p < 0.01).</p> <p>Conclusion</p> <p><it>COMT </it>(Val158 Met) polymorphism is not an independent risk factor for AD or MCI, but shows a synergistic effect with <it>APOE ε4 </it>allele that proves greater in women with AD.</p

The Chemotherapeutic Drug 5-Fluorouracil Promotes PKR-Mediated Apoptosis in a p53- Independent Manner in Colon and Breast Cancer Cells

The chemotherapeutic drug 5-FU is widely used in the treatment of a range of cancers, but resistance to the drug remains a major clinical problem. Since defects in the mediators of apoptosis may account for chemo-resistance, the identification of new targets involved in 5-FU-induced apoptosis is of main clinical interest. We have identified the ds-RNA-dependent protein kinase (PKR) as a key molecular target of 5-FU involved in apoptosis induction in human colon and breast cancer cell lines. PKR distribution and activation, apoptosis induction and cytotoxic effects were analyzed during 5-FU and 5-FU/IFNα treatment in several colon and breast cancer cell lines with different p53 status. PKR protein was activated by 5-FU treatment in a p53-independent manner, inducing phosphorylation of the protein synthesis translation initiation factor eIF-2α and cell death by apoptosis. Furthermore, PKR interference promoted a decreased response to 5-FU treatment and those cells were not affected by the synergistic antitumor activity of 5-FU/IFNα combination. These results, taken together, provide evidence that PKR is a key molecular target of 5-FU with potential relevance in the clinical use of this drug