Combination of 16S rRNA variable regions provides a detailed analysis of bacterial community dynamics in the lungs of cystic fibrosis patients

Chronic bronchopulmonary bacterial infections remain the most common cause of morbidity and mortality among patients with cystic fibrosis (CF). Recent community sequencing work has now shown that the bacterial community in the CF lung is polymicrobial. Identifying bacteria in the CF lung through sequencing can be costly and is not practical for many laboratories. Molecular techniques such as terminal restriction fragment length polymorphism or amplicon length heterogeneity-polymerase chain reaction (LH-PCR) can provide many laboratories with the ability to study CF bacterial communities without costly sequencing. The aim of this study was to determine if the use of LH-PCR with multiple hypervariable regions of the 16S rRNA gene could be used to identify organisms found in sputum DNA. This work also determined if LH-PCR could be used to observe the dynamics of lung infections over a period of time. Nineteen samples were analysed with the V1 and the V1_V2 region of the 16S rRNA gene. Based on the amplicon size present in the V1_V2 region, Pseudomonas aeruginosa was confirmed to be in all 19 samples obtained from the patients. The V1 region provided a higher power of discrimination between bacterial profiles of patients. Both regions were able to identify trends in the bacterial population over a period of time. LH profiles showed that the CF lung community is dynamic and that changes in the community may in part be driven by the patient's antibiotic treatment. LH-PCR is a tool that is well suited for studying bacterial communities and their dynamics.

A Review of Merger and Acquisition Wave Literature: Proposing Future Research in the Restaurant Industry

The purpose of this study is to identify research trends in Merger and Acquisition waves in the restaurant industry and propose future research directions by thoroughly reviewing existing Merger and Acquisition related literature. Merger and Acquisition has been extensively used as a strategic management tool for fast growth in the restaurant industry. However, there has been a very limited amount of literature that focuses on Merger & Acquisition in the restaurant industry. Particular, no known study has been identified that examined M&A wave and its determinants. A good understanding of determinants of M&A wave will help practitioners identify important factors that should be considered before making M&A decisions and predict the optimal timing for successful M&A transactions. This study examined literature on six U.S M&A waves and their determinants and summarized main explanatory factors examined, statistical methods, and theoretical frameworks. Inclusion of unique macroeconomic factors of the restaurant industry and the use of factor analysis are suggested for future research.

Screening of pharmaceuticals and other pollutants of concern by a combination of chemical and biological methods

This study examined the occurrence of pharmaceuticals and personal care products (PPCP's) in surface waters of Florida and their potential to be use as indicators of wastewater contamination. Previous studies have shown that elimination of pharmaceuticals in municipal sewage treatment plants is often incomplete. Aquatic ecosystems are under increased stress from human activities, particularly in heavily populated areas. The purpose of this study was to find an ideal indicator for wastewater. The applied methods, GC/MS and LC/MS, were suitable for the determination of pharmaceuticals and personal care products in aqueous environmental samples to the lower parts-per-trillion (ng/L) level. As a result of this study a snapshot view of the occurrence of pharmaceuticals and personal care products in south Florida was produced. PPCP's were commonly detected in coastal environments of South Florida at relatively low concentrations. In general, PPCP's were higher inside the canals and contained bodies of water than in open water systems. Caffeine was successfully used to describe impacted versus pristine locations. However, no particular correlation was observed among caffeine and other traditional water quality parameters.

Processing of highly porous titanium parts by metal injection moulding in combination with innovative plasma treatment

A combinação da Moldagem por Injeção de pós Metálicos (Metal Injection Moulding MIM) e o Método do Retentor Espacial (Space Holder Method - SHM) é uma técnica promissora para fabricação de peças porosas de titânio com porosidade bem definida como implantes biomédicos, uma vez que permite um alto grau de automatização e redução dos custos de produção em larga escala quando comparado a técnica tradicional (SHM e usinagem a verde). Contudo a aplicação desta técnica é limitada pelo fato que há o fechamento parcial da porosidade na superfície das amostras, levando ao deterioramento da fixação do implante ao osso. E além disso, até o presente momento não foi possível atingir condições de processamento estáveis quando a quantidade de retentor espacial excede 50 vol. %. Entretanto, a literatura descreve que a melhor faixa de porosidade para implantes de titânio para coluna vertebral está entre 60 - 65 vol. %. Portanto, no presente estudo, duas abordagens foram conduzidas visando a produção de amostras altamente porosas através da combinação de MIM e SHM com o valor constante de retentor espacial de 70 vol. % e uma porosidade aberta na superfície. Na primeira abordagem, a quantidade ótima de retentor espacial foi investigada, para tal foram melhorados a homogeneização do feedstock e os parâmetros de processo com o propósito de permitir a injeção do feedstock. Na segunda abordagem, tratamento por plasma foi aplicado nas amostras antes da etapa final de sinterização. Ambas rotas resultaram na melhoria da estabilidade dimensional das amostras durante a extração térmica do ligante e sinterização, permitindo a sinterização de amostras de titânio altamente porosas sem deformação da estrutura.

Long-Acting b-Agonist in Combination or Separate Inhaler as Step-Up Therapy for Children with Uncontrolled Asthma Receiving Inhaled Corticosteroids

Acknowledgments The authors thank Prof. Stanley Szefler for his comments on the paper and Lisa Law for help with editing

Persistence and adherence of combination therapy among adult asthmatic patients

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Source apportionment of PM2.5 in Cork Harbour, Ireland using a combination of single particle mass spectrometry and quantitative semi-continuous measurements

An aerosol time-of-flight mass spectrometer (ATOFMS) was deployed for the measurement of the size resolved chemical composition of single particles at a site in Cork Harbour, Ireland for three weeks in August 2008. The ATOFMS was co-located with a suite of semi-continuous instrumentation for the measurement of particle number, elemental carbon (EC), organic carbon (OC), sulfate and particulate matter smaller than 2.5 μm in diameter (PM2.5). The temporality of the ambient ATOFMS particle classes was subsequently used in conjunction with the semi-continuous measurements to apportion PM2.5 mass using positive matrix factorisation. The synergy of the single particle classification procedure and positive matrix factorisation allowed for the identification of six factors, corresponding to vehicular traffic, marine, long-range transport, various combustion, domestic solid fuel combustion and shipping traffic with estimated contributions to the measured PM2.5 mass of 23%, 14%, 13%, 11%, 5% and 1.5% respectively. Shipping traffic was found to contribute 18% of the measured particle number (20–600 nm mobility diameter), and thus may have important implications for human health considering the size and composition of ship exhaust particles. The positive matrix factorisation procedure enabled a more refined interpretation of the single particle results by providing source contributions to PM2.5 mass, while the single particle data enabled the identification of additional factors not possible with typical semi-continuous measurements, including local shipping traffic.

Persistence and adherence of combination therapy among adult asthmatic patients

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

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).

The peculiar Type Ia supernova iPTF14atg: Chandrasekhar-mass explosion or violent merger?

iPTF14atg, a subluminous peculiar Type Ia supernova (SN Ia) similar to SN 2002es, is the first SN Ia for which a strong UV flash was observed in the early-time light curves. This has been interpreted as evidence for a single-degenerate (SD) progenitor system, where such a signal is expected from interactions between the SN ejecta and the non-degenerate companion star. Here, we compare synthetic observables of multidimensional state-of-the-art explosion models for different progenitor scenarios to the light curves and spectra of iPTF14atg. From our models, we have difficulties explaining the spectral evolution of iPTF14atg within the SD progenitor channel. In contrast, we find that a violent merger of two carbon-oxygen white dwarfs with 0.9 and 0.76 M⊙, respectively, provides an excellent match to the spectral evolution of iPTF14atg from 10 d before to several weeks after maximum light. Our merger model does not naturally explain the initial UV flash of iPTF14atg. We discuss several possibilities like interactions of the SN ejecta with the circumstellar medium and surface radioactivity from an He-ignited merger that may be able to account for the early UV emission in violent merger models.

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.