Petri Net Siphon Analysis and Network Centrality Measures for Identifying Combination Therapies in Signaling Pathways

Aberrant behavior of biological signaling pathways has been implicated in diseases such as cancers. Therapies have been developed to target proteins in these networks in the hope of curing the illness or bringing about remission. However, identifying targets for drug inhibition that exhibit good therapeutic index has proven to be challenging since signaling pathways have a large number of components and many interconnections such as feedback, crosstalk, and divergence. Unfortunately, some characteristics of these pathways such as redundancy, feedback, and drug resistance reduce the efficacy of single drug target therapy and necessitate the employment of more than one drug to target multiple nodes in the system. However, choosing multiple targets with high therapeutic index poses more challenges since the combinatorial search space could be huge. To cope with the complexity of these systems, computational tools such as ordinary differential equations have been used to successfully model some of these pathways. Regrettably, for building these models, experimentally-measured initial concentrations of the components and rates of reactions are needed which are difficult to obtain, and in very large networks, they may not be available at the moment. Fortunately, there exist other modeling tools, though not as powerful as ordinary differential equations, which do not need the rates and initial conditions to model signaling pathways. Petri net and graph theory are among these tools. In this thesis, we introduce a methodology based on Petri net siphon analysis and graph network centrality measures for identifying prospective targets for single and multiple drug therapies. In this methodology, first, potential targets are identified in the Petri net model of a signaling pathway using siphon analysis. Then, the graph-theoretic centrality measures are employed to prioritize the candidate targets. Also, an algorithm is developed to check whether the candidate targets are able to disable the intended outputs in the graph model of the system or not. We implement structural and dynamical models of ErbB1-Ras-MAPK pathways and use them to assess and evaluate this methodology. The identified drug-targets, single and multiple, correspond to clinically relevant drugs. Overall, the results suggest that this methodology, using siphons and centrality measures, shows promise in identifying and ranking drugs. Since this methodology only uses the structural information of the signaling pathways and does not need initial conditions and dynamical rates, it can be utilized in larger networks.

Discrimination of honey of different floral origins by a combination of various chemical parameters

Abstract Honey is a high value food commodity with recognized nutraceutical properties. A primary driver of the value of honey is its floral origin. The feasibility of applying multivariate data analysis to various chemical parameters for the discrimination of honeys was explored. This approach was applied to four authentic honeys with different floral origins (rata, kamahi, clover and manuka) obtained from producers in New Zealand. Results from elemental profiling, stable isotope analysis, metabolomics (UPLC-QToF MS), and NIR, FT-IR, and Raman spectroscopic fingerprinting were analyzed. Orthogonal partial least square discriminant analysis (OPLS-DA) was used to determine which technique or combination of techniques provided the best classification and prediction abilities. Good prediction values were achieved using metabolite data (for all four honeys, Q² = 0.52; for manuka and clover, Q² = 0.76) and the trace element/isotopic data (for manuka and clover, Q² = 0.65), while the other chemical parameters showed promise when combined (for manuka and clover, Q² = 0.43).

Efficacy and safety of lumacaftor/ivacaftor combination therapy in patients with cystic fibrosis homozygous for Phe508del CFTR by pulmonary function subgroup

Background Lumacaftor/ivacaftor combination therapy demonstrated clinical benefits inpatients with cystic fibrosis homozygous for the Phe508del CFTR mutation.Pretreatment lung function is a confounding factor that potentially impacts the efficacyand safety of lumacaftor/ivacaftor therapy. Methods Two multinational, randomised, double-blind, placebo-controlled, parallelgroupPhase 3 studies randomised patients to receive placebo or lumacaftor (600 mgonce daily [qd] or 400 mg every 12 hours [q12h]) in combination with ivacaftor (250 mgq12h) for 24 weeks. Prespecified analyses of pooled efficacy and safety data by lungfunction, as measured by percent predicted forced expiratory volume in 1 second(ppFEV1), were performed for patients with baseline ppFEV1 <40 (n=81) and ≥40(n=1016) and screening ppFEV1 <70 (n=730) and ≥70 (n=342). These studies wereregistered with ClinicalTrials.gov (NCT01807923 and NCT01807949). Findings The studies were conducted from April 2013 through April 2014.Improvements in the primary endpoint, absolute change from baseline at week 24 inppFEV1, were observed with both lumacaftor/ivacaftor doses in the subgroup withbaseline ppFEV1 <40 (least-squares mean difference versus placebo was 3∙7 and 3.3percentage points for lumacaftor 600 mg qd/ivacaftor 250 mg q12h and lumacaftor 400mg q12h/ivacaftor 250 mg q12h, respectively [p<0∙05] and in the subgroup with baselineppFEV1 ≥40 (3∙3 and 2∙8 percentage points, respectively [p<0∙001]). Similar absoluteimprovements versus placebo in ppFEV1 were observed in subgroups with screening 4ppFEV1 <70 (3∙3 and 3∙3 percentage points for lumacaftor 600 mg qd/ivacaftor 250 mgq12h and lumacaftor 400 mg q12h/ivacaftor 250 mg q12h, respectively [p<0∙001]) and≥70 (3∙3 and 1∙9 percentage points, respectively [p=0.002] and [p=0∙079]). Increases inBMI and reduction in number of pulmonary exacerbation events were observed in bothLUM/IVA dose groups vs placebo across all lung function subgroups. Treatment wasgenerally well tolerated, although the incidence of some respiratory adverse events washigher with active treatment than with placebo. Interpretation Lumacaftor/ivacaftor combination therapy benefits patients homozygousfor Phe508del CFTR who have varying degrees of lung function impairment. Funding Vertex Pharmaceuticals Incorporated.

Features combination for art authentication studies: brushstroke and materials analysis of Amadeo de Souza-Cardoso

This work presents a tool to support authentication studies of paintings attributed to the modernist Portuguese artist Amadeo de Souza-Cardoso (1887-1918). The strategy adopted was to quantify and combine the information extracted from the analysis of the brushstroke with information on the pigments present in the paintings. The brushstroke analysis was performed combining Gabor filter and Scale Invariant Feature Transform. Hyperspectral imaging and elemental analysis were used to compare the materials in the painting with those present in a database of oil paint tubes used by the artist. The outputs of the tool are a quantitative indicator for authenticity, and a mapping image that indicates the areas where materials not coherent with Amadeo's palette were detected, if any. This output is a simple and effective way of assessing the results of the system. The method was tested in twelve paintings obtaining promising results.

A signaling visualization toolkit to support rational design of combination therapies and biomarker discovery: SiViT

Targeted cancer therapy aims to disrupt aberrant cellular signalling pathways. Biomarkers are surrogates of pathway state, but there is limited success in translating candidate biomarkers to clinical practice due to the intrinsic complexity of pathway networks. Systems biology approaches afford better understanding of complex, dynamical interactions in signalling pathways targeted by anticancer drugs. However, adoption of dynamical modelling by clinicians and biologists is impeded by model inaccessibility. Drawing on computer games technology, we present a novel visualisation toolkit, SiViT, that converts systems biology models of cancer cell signalling into interactive simulations that can be used without specialist computational expertise. SiViT allows clinicians and biologists to directly introduce for example loss of function mutations and specific inhibitors. SiViT animates the effects of these introductions on pathway dynamics, suggesting further experiments and assessing candidate biomarker effectiveness. In a systems biology model of Her2 signalling we experimentally validated predictions using SiViT, revealing the dynamics of biomarkers of drug resistance and highlighting the role of pathway crosstalk. No model is ever complete: the iteration of real data and simulation facilitates continued evolution of more accurate, useful models. SiViT will make accessible libraries of models to support preclinical research, combinatorial strategy design and biomarker discovery.

Identifying treatment effects and counterfactual distributions using data combination with unobserved heterogeneity

This paper considers identification of treatment effects when the outcome variables and covari-ates are not observed in the same data sets. Ecological inference models, where aggregate out-come information is combined with individual demographic information, are a common example of these situations. In this context, the counterfactual distributions and the treatment effects are not point identified. However, recent results provide bounds to partially identify causal effects. Unlike previous works, this paper adopts the selection on unobservables assumption, which means that randomization of treatment assignments is not achieved until time fixed unobserved heterogeneity is controlled for. Panel data models linear in the unobserved components are con-sidered to achieve identification. To assess the performance of these bounds, this paper provides a simulation exercise.

A combination of amino acids and caffeine enhances sprint running capacity in a hot, hypoxic environment.

Quercetin in Cancer Treatment, Alone or in Combination with Conventional Therapeutics?

Cancer is a problem of global importance, since the incidence is increasing worldwide and therapeutic options are generally limited. Thus, it becomes imperative to find new therapeutic targets as well as new molecules with therapeutic potential for tumors. Flavonoids are polyphenolic compounds that may be potential therapeutic agents. Several studies have shown that these compounds have a higher anticancer potential. Among the flavonoids in the human diet, quercetin is one of the most important. In the last decades, several anticancer properties of quercetin have been described, such as cell signaling, pro-apoptotic, anti-proliferative and anti-oxidant effects, growth suppression. In fact, it is now well known that quercetin has diverse biological effects, inhibiting multiple enzymes involved in cell proliferation, as well as, in signal transduction pathways. On the other hand, there are also studies reporting potential synergistic effects when combined quercetin with chemotherapeutic agents or radiotherapy. In fact, several studies which aim to explore the anticancer potential of these combined treatments have already been published, the majority with promising results. Actually it is well known that quercetin can act on the chemosensitization and radiosensitization but also as chemoprotective and radioprotective, protecting normal cells of the side effects that results from chemotherapy and radiotherapy, which obviously provides notable advantages in their use in anticancer treatment. Thus, all these data indicate that quercetin may have a key role in anticancer treatment. In this context, this review is focused on the relationship between flavonoids and cancer, with special emphasis on the role of quercetin.

Magnetic carbon xerogels for the catalytic wet peroxide oxidation of sulfamethoxazole in environmentally relevant water matrices

Novel magnetic carbon xerogels consisting of interconnected carbon microspheres with iron and/or cobalt microparticles embedded in their structure were developed by a simple route. As inferred from the characterization data, materials with distinctive properties may be directly obtained upon inclusion of iron and/or cobalt precursors during the sol-gel polymerization of resorcinol and formaldehyde, followed by thermal annealing. The unique properties of these magnetic carbon xerogels were explored in the catalytic wet peroxide oxidation (CWPO) of an antimicrobial agent typically found throughout the urban water cycle – sulfamethoxazole (SMX). A clear synergistic effect arises from the inclusion of cobalt and iron in carbon xerogels (CX/CoFe),the resulting magnetic material revealing a better performance in the CWPO of SMX at the ppb level(500 microg L−1) when compared to that of monometallic carbon xerogels containing only iron or cobalt.This effect was ascribed to the increased accessibility of highly active iron species promoted by the simultaneous incorporation of cobalt.The performance of the CWPO process in the presence of CX/CoFe was also evaluated in environmentally relevant water matrices, namely in drinking water and secondary treated wastewater, considered in addition to ultrapure water. It was found that the performance decreases when applied to more complex water and wastewater samples. Nevertheless, the ability of the CWPO technology for the elimination of SMX in secondary treated wastewater was unequivocally shown, with 96.8% of its initial content being removed after 6 h of reaction in the presence of CX/CoFe, at atmospheric pressure, room temperature(T = 25◦C), pH = 3, [H2O2]0= 500 mg L−1and catalyst load = 80 mg L−1. A similar performance (97.8% SMX removal) is obtained in 30 min when the reaction temperature is slightly increased up to 60◦C in an ultra-pure water matrix. Synthetic water containing humic acid, bicarbonate, sulphate or chloride, was also tested. The results suggest the scavenging effect of the different anions considered, as well as the negative impact of dissolved organic matter typically found in secondary treated wastewater, as simulated by the presence of humic acid.An in-situ magnetic separation procedure was applied for catalyst recovery and re-use during reusability cycles performed to mimic real-scale applications. CWPO runs performed with increased SMX concentration (10 mg L−1), under a water treatment process intensification approach, allowed to evalu-ate the mineralization levels obtained, the antimicrobial activity of the treated water, and to propose adegradation mechanism for the CWPO of SMX.

Combination of Evolutionary Algorithms with Experimental Design, Traditional Optimization and Machine Learning

Evolutionary algorithms alone cannot solve optimization problems very efficiently since there are many random (not very rational) decisions in these algorithms. Combination of evolutionary algorithms and other techniques have been proven to be an efficient optimization methodology. In this talk, I will explain the basic ideas of our three algorithms along this line (1): Orthogonal genetic algorithm which treats crossover/mutation as an experimental design problem, (2) Multiobjective evolutionary algorithm based on decomposition (MOEA/D) which uses decomposition techniques from traditional mathematical programming in multiobjective optimization evolutionary algorithm, and (3) Regular model based multiobjective estimation of distribution algorithms (RM-MEDA) which uses the regular property and machine learning methods for improving multiobjective evolutionary algorithms.

Robust Stereo Visual Odometry through a Probabilistic Combination of Points and Line Segments

Most approaches to stereo visual odometry reconstruct the motion based on the tracking of point features along a sequence of images. However, in low-textured scenes it is often difficult to encounter a large set of point features, or it may happen that they are not well distributed over the image, so that the behavior of these algorithms deteriorates. This paper proposes a probabilistic approach to stereo visual odometry based on the combination of both point and line segment that works robustly in a wide variety of scenarios. The camera motion is recovered through non-linear minimization of the projection errors of both point and line segment features. In order to effectively combine both types of features, their associated errors are weighted according to their covariance matrices, computed from the propagation of Gaussian distribution errors in the sensor measurements. The method, of course, is computationally more expensive that using only one type of feature, but still can run in real-time on a standard computer and provides interesting advantages, including a straightforward integration into any probabilistic framework commonly employed in mobile robotics.

EACS: Effective Avoidance Combination Strategy

International audience

HBsAg seroclearance or seroconversion induced by peg-interferon alpha and lamivudine or adefovir combination therapy in chronic hepatitis B treatment: a meta-analysis and systematic review

Background and aims: Seroclearance or seroconversion of hepatitis B surface antigen (HBsAg) is generally considered as a clinical endpoint. The purpose of the present meta-analysis was to evaluate the effect of combined therapy with pegylated interferon alpha (PEG-IFNα) with or without lamivudine (LAM) or adefovir (ADV) on HBsAg seroclearance or seroconversion in subjects with chronic hepatitis B (CHB). Methods: Randomized controlled trials performed through May 30th 2015 in adults with CHB receiving PEG-IFNα and LAM or ADV combination therapy or monotherapy for 48-52 weeks were included. The Review Manager Software 5.2.0 was used for the meta-analysis. Results: No statistical differences in HBsAg seroclearance (9.9% vs. 7.1%, OR = 1.47, 95% CI: 0.75, 2.90; p = 0.26) or HBsAg seroconversion (4.2% vs. 3.7%, OR = 1.17, 95% CI: 0.57, 2.37; p = 0.67) rates were noticed between PEG-IFNα + LAM and PEG-IFN α + placebo during post-treatment follow-up for 24-26-weeks in subjects with hepatitis Be antigen (HBeAg)-positive CHB. No statistical differences in HBsAg clearance (10.5% vs. 6.4%, OR = 1.68, 95% CI: 0.75, 3.76; p = 0.21) were seen, but statistical differences in HBsAg seroconversion (6.3% vs. 0%, OR = 7.22, 95% CI: 1.23, 42.40; p = 0.03) were observed, between PEG-IFNα + ADV and PEG-IFNα for 48-52 weeks of treatment in subjects with HBeAg-positive CHB. A systematic evaluation showed no differences in HBsAg disappearance and seroconversion rates between PEG-IFNα + placebo and PEG-IFNα + LAM for 48-52 weeks in subjects with HBeAg-positive CHB. A systematic assessment found no differences in HBsAg disappearance and seroconversion rates between PEG-IFNα + placebo and PEG-IFNα + LAM during 24 weeks' to 3 years' follow-up after treatment in subjects with HBeAg-negative CHB. Conclusion: Combined therapy with PEG-IFNα and LAM or ADV was not superior to monotherapy with PEG-IFNα in terms of HBsAg seroclearance or seroconversion.

Using a Combination of Phylogenetic Comparative and Paleobotanical Methods to Elucidate Patterns of Lineage Selection in Rosales (Plantae: Anthophyta)

An increasing focus in evolutionary biology is on the interplay between mesoscale ecological and evolutionary processes such as population demographics, habitat tolerance, and especially geographic distribution, as potential drivers responsible for patterns of diversification and extinction over geologic time. However, few studies to date connect organismal processes such as survival and reproduction through mesoscale patterns to long-term macroevolutionary trends. In my dissertation, I investigate how mechanism of seed dispersal, mediated through geographic range size, influences diversification rates in the Rosales (Plantae: Anthophyta). In my first chapter, I validate the phylogenetic comparative methods that I use in my second and third chapters. Available state speciation and extinction (SSE) models assumptions about evolution known to be false through fossil data. I show, however, that as long as net diversification rates remain positive – a condition likely true for the Rosales – these violations of SSE’s assumptions do not cause significantly biased results. With SSE methods validated, my second chapter reconstructs three associations that appear to increase diversification rate for Rosalean genera: (1) herbaceous habit; (2) a three-way interaction combining animal dispersal, high within-genus species richness, and geographic range on multiple continents; (3) a four-way interaction combining woody habit with the other three characteristics of (2). I suggest that the three- and four-way interactions represent colonization ability and resulting extinction resistance in the face of late Cenozoic climate change; however, there are other possibilities as well that I hope to investigate in future research. My third chapter reconstructs the phylogeographic history of the Rosales using both non-fossil-assisted SSE methods as well as fossil-informed traditional phylogeographic analysis. Ancestral state reconstructions indicate that the Rosaceae diversified in North America while the other Rosalean families diversified elsewhere, possibly in Eurasia. SSE is able to successfully identify groups of genera that were likely to have been ancestrally widespread, but has poorer taxonomic resolution than methods that use fossil data. In conclusion, these chapters together suggest several potential causal links between organismal, mesoscale, and geologic scale processes, but further work will be needed to test the hypotheses that I raise here.

EFFECT OF BAP, NAA AND GA3, EITHER ALONE OR IN COMBINATION, ON MERISTEM CULTURE AND PLANTLET ESTABLISHMENT IN SWEET POTATO (CV BRONDAL)

In Zimbabwe, the average sweet potato yield (6 t/ha) is relatively low when compared to Asian counterparts (17 t/ha). These low crop yields have been blamed on weevil infestations and viral infections which account for 60-90% of sweet potato yield losses in Africa. Meristem tip culture, a Centre for Potato Improvement (CIP) initiated tissue culture technique, has been widely used to eradicate viruses from clonally propagated crops and has been noted to be one of the instrumental techniques that helped China to increase sweet potato yields. In an effort to adopt the meristem tip culture technique for the production of virus-free planting material of a local sweet potato (cv Brondal), a study was conducted to evaluate the effect of Benzylamino purine (BAP), 1-Naphthaleneacetic acid (NAA) and Gibberellic acid (GA3) (either alone or in combination) on cultured Brondal meristems. The different hormonal treatments were assessed on the following parameters: plantlet regenerative capacity, multiple plantlet production, shoot height, average leaf number per shoot and average node number per shoot, ten weeks after meristem culture. All treatments containing a combination of BAP (1 mg-L) and GA3 (at either 5 mg-L, 10 mg-L, or 20 mg-L) had a significantly (p<0.01) higher plantlet regenerative capacity of 33-66% when compared to other treatment combinations. Only treatments, 10 mg-L GA3 + 1 mg-L BAP and 20 mg-L GA3 + 1 mg-L BAP were capable of inducing multiple plantlet formation, producing an average of three plantlets/meristem and two plantlets/meristem respectively. Overall, treatment 10 mg-L GA3 + 1 mg-L BAP gave rise to significantly (p<0.01) taller shoots (20 mm) compared to the rest of the treatments used. For average leaf number per shoot, all GA3 treatments (5 mg-L, 10 mg-L, or 20 mg-L) supplemented with 1 mg-L BAP gave significantly (p<0.01) higher numbers of leaves (six leaves/shoot) than the rest of the treatments. Treatments 10 mg-L GA3 + 1 mg-L BAP and 20 mg-L GA3 + 1 mg-L BAP gave rise to the highest number of nodes per shoot, producing an average of three nodes per shoot. In sharp contrast to treatments containing a combination of BAP and GA3, all treatments containing a combination of BAP and NAA performed poorly in all parameters tested for plant regeneration of Brondal sweet potato variety. In conclusion, the best hormonal treatment for culturing Brondal meristems proved to be 10 mg-L GA3 + 1 mg-L BAP.