Spirometric values in elderly asthmatic patients are not influenced by obesity

Background Studies have suggested that asthma in obese individuals differs from the classic asthma phenotype, presenting as a disease that is more difficult to control. Objective The objective of the present study was to determine whether obesity, age or a combination of the two are associated with worse spirometry parameters in patients with asthma. Methods This was an observational cross-sectional study involving patients over 18 years of age who had been diagnosed with asthma (allergic or nonallergic). We evaluated the results of their spirometric tests. The patients were classified in accordance with two criteria: body mass index (BMI) and age. Based on their BMIs, the patients were divided into three groups: normal weight, overweight and obese. Patients were also separated into two categories by age: 18-59 years of age; and >= 60 years of age. Results We evaluated 451 patients with asthma and their spirometry tests. In the present study, the pulmonary function parameters were negatively correlated with BMI and age (P < 0.05). We found that there was a statistically significant correlation between spirometric values and BMI among patients 18-59 years of age (P < 0.001), however, among patients over 60, we did not observe this negative association. Conclusions and Clinical Relevance The spirometric values decreased significantly in proportion to the increase of BMI and age in patients with asthma, especially among young adults. There was no negative correlation between BMI and FEV1 in the group >= 60 years of age, suggesting that perhaps the time of disease is a major factor in the loss of lung function than weight gain in the elderly.

Decreasing the number of false positives in sequence classification

Abstract Background A large number of probabilistic models used in sequence analysis assign non-zero probability values to most input sequences. To decide when a given probability is sufficient the most common way is bayesian binary classification, where the probability of the model characterizing the sequence family of interest is compared to that of an alternative probability model. We can use as alternative model a null model. This is the scoring technique used by sequence analysis tools such as HMMER, SAM and INFERNAL. The most prevalent null models are position-independent residue distributions that include: the uniform distribution, genomic distribution, family-specific distribution and the target sequence distribution. This paper presents a study to evaluate the impact of the choice of a null model in the final result of classifications. In particular, we are interested in minimizing the number of false predictions in a classification. This is a crucial issue to reduce costs of biological validation. Results For all the tests, the target null model presented the lowest number of false positives, when using random sequences as a test. The study was performed in DNA sequences using GC content as the measure of content bias, but the results should be valid also for protein sequences. To broaden the application of the results, the study was performed using randomly generated sequences. Previous studies were performed on aminoacid sequences, using only one probabilistic model (HMM) and on a specific benchmark, and lack more general conclusions about the performance of null models. Finally, a benchmark test with P. falciparum confirmed these results. Conclusions Of the evaluated models the best suited for classification are the uniform model and the target model. However, the use of the uniform model presents a GC bias that can cause more false positives for candidate sequences with extreme compositional bias, a characteristic not described in previous studies. In these cases the target model is more dependable for biological validation due to its higher specificity.

Clinical judgment to estimate pretest probability in the diagnosis of Cushing's syndrome under a Bayesian perspective

OBJECTIVE: To estimate the pretest probability of Cushing's syndrome (CS) diagnosis by a Bayesian approach using intuitive clinical judgment. MATERIALS AND METHODS: Physicians were requested, in seven endocrinology meetings, to answer three questions: "Based on your personal expertise, after obtaining clinical history and physical examination, without using laboratorial tests, what is your probability of diagnosing Cushing's Syndrome?"; "For how long have you been practicing Endocrinology?"; and "Where do you work?". A Bayesian beta regression, using the WinBugs software was employed. RESULTS: We obtained 294 questionnaires. The mean pretest probability of CS diagnosis was 51.6% (95%CI: 48.7-54.3). The probability was directly related to experience in endocrinology, but not with the place of work. CONCLUSION: Pretest probability of CS diagnosis was estimated using a Bayesian methodology. Although pretest likelihood can be context-dependent, experience based on years of practice may help the practitioner to diagnosis CS. Arq Bras Endocrinol Metab. 2012;56(9):633-7

Spatio-temporal patterns of tuberculosis incidence in Ribeirão Preto, State of São Paulo, southeast Brazil, and their relationship with social vulnerability: a Bayesian analysis

INTRODUCTION: The purpose of this ecological study was to evaluate the urban spatial and temporal distribution of tuberculosis (TB) in Ribeirão Preto, State of São Paulo, southeast Brazil, between 2006 and 2009 and to evaluate its relationship with factors of social vulnerability such as income and education level. METHODS: We evaluated data from TBWeb, an electronic notification system for TB cases. Measures of social vulnerability were obtained from the SEADE Foundation, and information about the number of inhabitants, education and income of the households were obtained from Brazilian Institute of Geography and Statistics. Statistical analyses were conducted by a Bayesian regression model assuming a Poisson distribution for the observed new cases of TB in each area. A conditional autoregressive structure was used for the spatial covariance structure. RESULTS: The Bayesian model confirmed the spatial heterogeneity of TB distribution in Ribeirão Preto, identifying areas with elevated risk and the effects of social vulnerability on the disease. We demonstrated that the rate of TB was correlated with the measures of income, education and social vulnerability. However, we observed areas with low vulnerability and high education and income, but with high estimated TB rates. CONCLUSIONS: The study identified areas with different risks for TB, given that the public health system deals with the characteristics of each region individually and prioritizes those that present a higher propensity to risk of TB. Complex relationships may exist between TB incidence and a wide range of environmental and intrinsic factors, which need to be studied in future research.

Comparison between the complete Bayesian method and empirical Bayesian method for ARCH models using Brazilian financial time series

In this work we compared the estimates of the parameters of ARCH models using a complete Bayesian method and an empirical Bayesian method in which we adopted a non-informative prior distribution and informative prior distribution, respectively. We also considered a reparameterization of those models in order to map the space of the parameters into real space. This procedure permits choosing prior normal distributions for the transformed parameters. The posterior summaries were obtained using Monte Carlo Markov chain methods (MCMC). The methodology was evaluated by considering the Telebras series from the Brazilian financial market. The results show that the two methods are able to adjust ARCH models with different numbers of parameters. The empirical Bayesian method provided a more parsimonious model to the data and better adjustment than the complete Bayesian method.

One-repetition maximum test and isokinetic leg extension and flexion: correlations and predicted values

The most typical maximum tests for measuring leg muscle performance are the one-repetition maximum leg press test (1RMleg) and the isokinetic knee extension/flexion (IKEF) test. Nevertheless, their inter-correlations have not been well documented, mainly the predicted values of these evaluations. This correlational and regression analysis study involved 30 healthy young males aged 18-24y, who have performed both tests. Pearson's product moment correlation between 1RMleg and IKEF varied from 0.20 to 0.69 and the more exact predicted test was to 1RMleg (R2 = 0.71). The study showed correlations between 1RMleg and IKEF although these tests are different (isotonic vs. isokinetic) and provided further support for cross determination of 1RMleg and IKEF by linear and multiple linear regression analysis.

Essays on Bayesian Inference for Social Networks

This thesis presents Bayesian solutions to inference problems for three types of social network data structures: a single observation of a social network, repeated observations on the same social network, and repeated observations on a social network developing through time. A social network is conceived as being a structure consisting of actors and their social interaction with each other. A common conceptualisation of social networks is to let the actors be represented by nodes in a graph with edges between pairs of nodes that are relationally tied to each other according to some definition. Statistical analysis of social networks is to a large extent concerned with modelling of these relational ties, which lends itself to empirical evaluation. The first paper deals with a family of statistical models for social networks called exponential random graphs that takes various structural features of the network into account. In general, the likelihood functions of exponential random graphs are only known up to a constant of proportionality. A procedure for performing Bayesian inference using Markov chain Monte Carlo (MCMC) methods is presented. The algorithm consists of two basic steps, one in which an ordinary Metropolis-Hastings up-dating step is used, and another in which an importance sampling scheme is used to calculate the acceptance probability of the Metropolis-Hastings step. In paper number two a method for modelling reports given by actors (or other informants) on their social interaction with others is investigated in a Bayesian framework. The model contains two basic ingredients: the unknown network structure and functions that link this unknown network structure to the reports given by the actors. These functions take the form of probit link functions. An intrinsic problem is that the model is not identified, meaning that there are combinations of values on the unknown structure and the parameters in the probit link functions that are observationally equivalent. Instead of using restrictions for achieving identification, it is proposed that the different observationally equivalent combinations of parameters and unknown structure be investigated a posteriori. Estimation of parameters is carried out using Gibbs sampling with a switching devise that enables transitions between posterior modal regions. The main goal of the procedures is to provide tools for comparisons of different model specifications. Papers 3 and 4, propose Bayesian methods for longitudinal social networks. The premise of the models investigated is that overall change in social networks occurs as a consequence of sequences of incremental changes. Models for the evolution of social networks using continuos-time Markov chains are meant to capture these dynamics. Paper 3 presents an MCMC algorithm for exploring the posteriors of parameters for such Markov chains. More specifically, the unobserved evolution of the network in-between observations is explicitly modelled thereby avoiding the need to deal with explicit formulas for the transition probabilities. This enables likelihood based parameter inference in a wider class of network evolution models than has been available before. Paper 4 builds on the proposed inference procedure of Paper 3 and demonstrates how to perform model selection for a class of network evolution models.

Bayesian Analysis of Linear Inverse Problems with Applications in Economics and Finance

In my PhD thesis I propose a Bayesian nonparametric estimation method for structural econometric models where the functional parameter of interest describes the economic agent's behavior. The structural parameter is characterized as the solution of a functional equation, or by using more technical words, as the solution of an inverse problem that can be either ill-posed or well-posed. From a Bayesian point of view, the parameter of interest is a random function and the solution to the inference problem is the posterior distribution of this parameter. A regular version of the posterior distribution in functional spaces is characterized. However, the infinite dimension of the considered spaces causes a problem of non continuity of the solution and then a problem of inconsistency, from a frequentist point of view, of the posterior distribution (i.e. problem of ill-posedness). The contribution of this essay is to propose new methods to deal with this problem of ill-posedness. The first one consists in adopting a Tikhonov regularization scheme in the construction of the posterior distribution so that I end up with a new object that I call regularized posterior distribution and that I guess it is solution of the inverse problem. The second approach consists in specifying a prior distribution on the parameter of interest of the g-prior type. Then, I detect a class of models for which the prior distribution is able to correct for the ill-posedness also in infinite dimensional problems. I study asymptotic properties of these proposed solutions and I prove that, under some regularity condition satisfied by the true value of the parameter of interest, they are consistent in a "frequentist" sense. Once I have set the general theory, I apply my bayesian nonparametric methodology to different estimation problems. First, I apply this estimator to deconvolution and to hazard rate, density and regression estimation. Then, I consider the estimation of an Instrumental Regression that is useful in micro-econometrics when we have to deal with problems of endogeneity. Finally, I develop an application in finance: I get the bayesian estimator for the equilibrium asset pricing functional by using the Euler equation defined in the Lucas'(1978) tree-type models.

Messung des Wirkungsquerschnitts der Reaktion d(e,e'p)n für fehlende Impulse bis 950 MeV/c und Trennung der longitudinalen und transversalen Reaktionsanteile für fehlende Impulse bis 350 MeV/c

Die Dreispektrometeranlage der A1-Kollaboration am MainzerElektronenbeschleuniger MAMI wurde im Rahmen dieser Arbeitverwendet, um die Elektrodisintegration des Deuteronsmit Hilfe der Reaktion d(e,e'p)n zu untersuchen. Im ersten Teil der Untersuchungen wurde die longitudinaleund transversale Strukturfunktion aus denWirkungsquerschnitten extrahiert. Die Zentralwerte derkinematischen Parameter waren dabei wie folgt eingestellt:1) Der Impulsübertrag wurde für alle Messungen auf 450 MeV/c festgelegt.2) Das Proton wurde in Richtung des Impulsübertrags nachgewiesen (parallele Kinematik).3) Vier Einstellungen des Energieübertrags, und damit korrespondierend des fehlenden Impulses, wurden gemessen: Energieübertrag / MeV : 128, 226, 289, 360. Fehlender Impuls / (MeV/c): 50, 200, 275, 350.4) Für jede dieser vier Kinematiken wurden mindestens drei verschiedene Einschußenergien bzw. Elektronenstreuwinkel eingestellt, um die Strukturfunktionen mit Hilfe der Rosenbluth-Separation zu bestimmen. Im zweiten Teil der Untersuchungen wurde derWirkungsquerschnitt für hohe fehlende Impulse bestimmt.Dessen Zentralwerte wurden von 30 MeV/c bis 906 MeV/cvariiert, wobei für die hohen fehlenden Impulse das Protonweit außerhalb der Richtung des Impulsübertragesnachzuweisen war. Der Energieübertrag lag dabei zwischen180 MeV und 600 MeV und der Impulsübertrag zwischen608 MeV/c und 698 MeV/c.

The impact of polymorphisms in P-gp, DNA repair and folic acid metabolism genes in newly diagnosed multiple myeloma patients treated with thalidomide plus dexamethasone, with or without bortezomib

The principle aim of this study was to investigate biological predictors of response and resistance to multiple myeloma treatment. Two hypothesis had been proposed as responsible of responsiveness: SNPs in DNA repair and Folate pathway, and P-gp dependent efflux. As a first objective, panel of SNPs in DNA repair and Folate pathway genes, were analyzed. It was a retrospective study in a group of 454, previously untreated, MM patients enrolled in a randomized phase III open-label study. Results show that some SNPs in Folate pathway are correlated with response to MM treatment. MTR genotype was associated with favorable response in the overall population of MM patients. However, this relation, disappear after adjustment for treatment response. When poor responder includes very good partial response, partial response and stable/progressive disease MTFHR rs1801131 genotype was associated with poor response to therapy. This relation - unlike in MTR – was still significant after adjustment for treatment response. Identification of this genetic variant in MM patients could be used as an independent prognostic factor for therapeutic outcome in the clinical practice. In the second objective, basic disposition characteristics of bortezomib was investigated. We demonstrated that bortezomib is a P-gp substrate in a bi-directional transport study. We obtain apparent permeability rate values that together with solubility values can have a crucial implication in better understanding of bortezomib pharmacokinetics with respect to the importance of membrane transporters. Subsequently, in view of the importance of P-gp for bortezomib responsiveness a panel of SNPs in ABCB1 gene - coding for P-gp - were analyzed. In particular we analyzed five SNPs, none of them however correlated with treatment responsiveness. However, we found a significant association between ABCB1 variants and cytogenetic abnormalities. In particular, deletion of chromosome 17 and t(4;14) translocation were present in patients harboring rs60023214 and rs2038502 variants respectively.

In-vivo-Tumorbiologie mittels 68 Ga-PET: Beurteilung der p-Glykoprotein-Aktivität in Weichgewebe-Tumoren sowie Diagnose und Therapie von Knochenmetastasen

Krebs ist eine der häufigsten Krankheiten und stellt eine der wichtigsten medizinischen Herausforderungen des 21. Jahrhunderts dar. Eine frühzeitige Diagnose ist dabei essentiell für eine individuell angepasste Therapie zur Verbesserung der Lebensqualität und -erwartung der Patienten. Hierbei kommen der 68Ge/68Ga-Generator und das daraus resultierende PET-Nuklid 68Ga immer stärker in den Fokus von Wissenschaft und Medizin. rnrnFür eine erfolgreiche Therapie stellt die Chemoresistenz (Multi-Drug-Resistance) zahlreicher Tumore eine schwerwiegende Komplikation dar. Für das Therapieversagen ist die Aktivierung des Transportproteins p-Glykoprotein (pGP) maßgeblich mit verantwortlich. Mit Hilfe der Schiff’schen Base [68Ga]MFL6.MZ konnte die Aktivitätsänderung von pGP unter verschiedener Beeinflussung erstmals in vivo beobachtet werden. So zeigte sich, dass sich unter azidotischen Bedingungen in Tumoren die Aktivität des pGP erhöht und somit vermehrt auch Zytostatika, die pGP-Substrate sind, aus den Tumoren transportiert werden. Durch Aufklärung der Abhängigkeit der pGP-Aktivität von dessen Signalkaskade konnte gezeigt werden, dass durch eine Blockade der MAP-Kinase p38 eine Erniedrigung der pGP-Aktivität zu verzeichnen ist. Die ebenfalls in der Signalkaskade eingebundene MAP-Kinase ERK1/2 hingegen spielt hier nur eine untergeordnete Rolle.rnrnNeben dem Versagen der Chemotherapie stellt auch die Metastasierung eines Malignoms massive Einschnitte in die Lebensqualität von Erkrankten dar. Befallen die Metastasen das Skelett eines Menschen, wird dies zumeist erst spät registriert. 68Ga-markierte Bisphosphonate bieten nun die Möglichkeit, Patienten quantitativ auf Knochenmetastasen hin untersuchen zu können. So konnten zu Beginn einfache Phosphonate wie EDTMP und DOTP nicht die nötige in vivo Stabilität bzw. hohe radiochemische Ausbeuten liefern und sind damit für die Anwendung am Menschen uninteressant. Jedoch die DOTA-basierten Bisphosphonate allen voran der Ligand BPAMD zeigen ein großes Potential. In vivo-Versuche an Ratten mit Knochenmetastasen zeigten, dass sich [68Ga]BPAMD an den Metastasen anreichert und einen sehr guten Kontrast zum gesunden Knochen darstellt. Der Tracer konnte erstmals am Menschen angewendet werden und zeigte in ausgewählten Regionen eine höhere Anreicherung als eine zuvor durchgeführte PET-Aufnahme mit [18F]Fluorid. Der Ligand BPAMD bietet außerdem den Vorteil, neben 68Ga auch andere dreiwertige Radionuklide wie das therapeutische 177Lu komplexieren zu können. Durch Studien zur Komplexbildung und Stabilität konnte auch [177Lu]BPAMD in der klinischen Anwendung erprobt werden und zeigte eine Anreicherung an den Knochenmetastasen. So ist es nun möglich, Knochenmetastasen mittels 68Ga-PET zu diagnostizieren, eine entsprechende Dosisberechnung anzustellen und anschließend mit dem gleichen Liganden eine Therapie mit [177Lu]BPAMD durchzuführen.

Synthese von polymergebundenen Sialyl-Lewis x-Strukturen und deren Mimetika als Zelladhäsionsinhibitoren für E-, L- und P-Selektin

Kohlenhydrate dienen nicht nur der Ernährung oder der Stabilisierung von Zellwänden, sondern sie sind auch von essentieller Bedeutung für Zell-Zell-Wechselwirkungen im Organismus. Damit sind sie von besonderem Interesse für die Behandlung von Entzündungen sowie tumorösen Erkrankungen, die auf Wechselwirkungen zwischen bestimmten Kohlenhydraten und Rezeptoren, Selektine genannt, basieren. Die vorliegende Dissertation mit dem Titel „Synthese von polymergebundenen Sialyl-Lewis x-Strukturen und deren Mimetika als Zelladhäsionsinhibitoren für E-, L- und P-Selektin“ befasst sich mit der Synthese und der Modifizierung des natürlich vorkommenden Selektin-Liganden Sialyl-Lewisx und seinen potentiell mimetischen Strukturen auf Basis von Gemischen der an der Bindung beteiligten Kohlenhydrate sowie von sulfatierten Einheiten. Um im Organismus eine verstärkte Bindung an die zu adressierenden Rezeptoren und eine erhöhte Zirkulationsdauer zu erreichen, wurden die geeignet funktionalisierten Liganden mittels reaktiver Polymere auf Basis von Pentafluorphenyl-Reaktivestern im Rahmen einer polymeranalogen Umsetzung an ein definiertes Methacrylamid-Polymer gebunden.Um die biologische Wirksamkeit der synthetisierten Polymere zu überprüfen, wurden Oberflächenplasmonenresonanz-Messungen (SPR-Messungen) durchgeführt. Dabei zeigte sich bei den verschiedenen Selektinen eine unterschiedlich hohe Affinität der Sialyl-Lewis x sowie der mimetischen Polymere. Es konnten bei E-Selektin die geringsten, bei L-Selektin mittlere und bei P-Selektin die höchsten Affinitäten im unteren nanomolaren Bereich festgestellt werden.

Cytotoxicity and P-glycoprotein inhibition by cardiotonic steroids

Herzwirksame Glykoside sind in der Natur sowohl im Tier- als auch im Pflanzenreich zu finden und werden regelmäßig zur Therpaie von Herzinsuffizienz eingesetzt. In letzter Zeit belegten viele Studien, dass herzwirksame Glykoside vielversprechende Substanzen für die Behandlung von Krebs darstellen. Ihr Wirkmechanismus basiert auf der Hemmung der Na+/K+-ATPase. Die Na+/K+-ATPase spielt neuerdings eine wichtige Rolle in der Krebsbiologie, da sie viele relevante Signalwege beeinflusst. Multiresistenzen gegen Arzneimittel sind oftmals verantwortlich für das Scheitern einer Chemotherapie. Bei multi-drug-resistenten Tumoren erfolgt ein Transport der Chemotherapeutika aus der Krebszelle hinaus durch das Membranprotein P-Glykoprotein. In der vorliegenden Arbeit wurde die Zytotoxizität von 66 herzwirksamen Glykosiden und ihren Derivaten in sensitiven und resistenten Leukämie-Zellen getestet. Die Ergebnisse zeigen, dass diese Naturstoffe die Zell-Linien in verschiedenen molaren Bereichen abtöten. Allerdings waren die Resistenz-Indizes niedrig (d. h. die IC50 Werte waren in beiden Zell-Linien ähnlich). Die untersuchten 66 Substanzen besitzen eine große Vielfalt an chemischen Substituenten. Die Wirkung dieser Substituenten auf die Zytotoxizität wurde daher durch Struktur-Aktivitäts-Beziehung (SAR) erforscht. Des Weiteren wiesen quantitative Struktur-Aktivitäts-Beziehung (QSAR) und molekulares Docking darauf hin, dass die Na+/K+-ATPase in sensitiven und resistenten Zellen unterschiedlich stark exprimiert wird. Eine Herunterregulation der Na+/K+-ATPase in multi-drug-resistenten Zellen wurde durch Western Blot bestätigt und die Wirkung dieser auf relevante Signalwege durch Next-Generation-Sequenzierung weiter verfolgt. Dadurch konnte eine Verbindung zwischen der Überexpression von P-Glykoprotein und der Herunterregulation der Na+/K+-ATPase hergestellt werden. Der zweite Aspekt der Arbeit war die Hemmung von P-Glykoprotein durch herzwirksame Glykoside, welche durch Hochdurchsatz-Durchflusszytometrie getestet wurde. Sechs wirksame Glykoside konnten den P-Glykoprotein-vermittelten Transport von Doxorubicin inhibieren. Zudem konnte die Zytotoxität von Doxorubicin in multi-drug-resistenten Zellen teilweise wieder zurück erlangt werden. Unabhängig von herzwirksamen Glykosiden war die Bewertung der Anwendung von molekularem Docking in der P-Glykoprotein Forschung ein weiterer Aspekt der Arbeit. Es ließ sich schlussfolgern, dass molekulares Docking fähig ist, zwischen den verschiedenen Molekülen zu unterscheiden, die mit P-Glykoprotein interagieren. Die Anwendbarkeit von molekularem Docking in Bezug auf die Bestimmung der Bindestelle einer Substanz wurde ebenfalls untersucht.

ABCtoolbox: a versatile toolkit for approximate Bayesian computations

Background The estimation of demographic parameters from genetic data often requires the computation of likelihoods. However, the likelihood function is computationally intractable for many realistic evolutionary models, and the use of Bayesian inference has therefore been limited to very simple models. The situation changed recently with the advent of Approximate Bayesian Computation (ABC) algorithms allowing one to obtain parameter posterior distributions based on simulations not requiring likelihood computations. Results Here we present ABCtoolbox, a series of open source programs to perform Approximate Bayesian Computations (ABC). It implements various ABC algorithms including rejection sampling, MCMC without likelihood, a Particle-based sampler and ABC-GLM. ABCtoolbox is bundled with, but not limited to, a program that allows parameter inference in a population genetics context and the simultaneous use of different types of markers with different ploidy levels. In addition, ABCtoolbox can also interact with most simulation and summary statistics computation programs. The usability of the ABCtoolbox is demonstrated by inferring the evolutionary history of two evolutionary lineages of Microtus arvalis. Using nuclear microsatellites and mitochondrial sequence data in the same estimation procedure enabled us to infer sex-specific population sizes and migration rates and to find that males show smaller population sizes but much higher levels of migration than females. Conclusion ABCtoolbox allows a user to perform all the necessary steps of a full ABC analysis, from parameter sampling from prior distributions, data simulations, computation of summary statistics, estimation of posterior distributions, model choice, validation of the estimation procedure, and visualization of the results.