Antismooth Muscle and Antiactin Antibodies Are Indirect Markers of Histological and Biochemical Activity of Autoimmune Hepatitis

Reactivity and titers of autoantibodies vary during the course of autoimmune hepatitis (AIH), and some autoantibodies have been associated with disease activity and adverse outcomes after treatment. The aim of this study was to assess the autoantibody behavior in AIH and its significance as predictors of biochemical and histological remission. A total of 117 patients with AIH (mean age 18.6 [4-69] years) were evaluated and tested for auto- antibodies at disease onset and successively (mean 3.2 [2-6] times) after a mean follow-up evaluation of 70 [20-185] months. Antismooth muscle (ASMA), antiliver kidney micro- some type 1 (anti-LKM1), antiliver cytosol type 1 (anti-LC1), antimitochondrial, antinu- clear (ANA), and antiactin antibodies (AAA) were determined at disease onset and 379 other times during the follow-up evaluation through indirect immunofluorescence in rodent tissues, HEp-2 cells, and human fibroblasts. Anti-SLA/LP were assessed 45 times in the follow-up evaluation of 19 patients using enzyme-linked immunosorbent assay (ELISA). Upon admission, AIH types 1 and 2 were observed in 95 and 17 patients, respectively. Five subjects had AIH with anti-SLA/LP as the sole markers. Patients initially negative for AAA did not develop these antibodies thereafter. ANA were detected de novo in six and three subjects with AIH types 1 and 2, respectively. After treatment, only ASMA ( > 1:80) and AAA ( > 1:40) were significantly associated with biochemical (76.9% and 79.8%) and histological features (100% and 100%) of disease activity ( P < 0.001). Conclusion: With the exception of ANA, the autoantibody profile does not markedly vary in the course of AIH. The persistence of high titers of ASMA and/or AAA in patients with AIH is associated with disease activity.

Comparison of flow cytometry and indirect immunofluorescence assay in the diagnosis and cure criterion after therapy of American tegumentary leishmaniasis by anti-live Leishmania (Viannia) braziliensis immunoglobulin G

The aim of this study was to compare the techniques of indirect immunofluorescence assay (IFA) and flow cytometry to clinical and laboratorial evaluation of patients before and after clinical cure and to evaluate the applicability of flow cytometry in post-therapeutic monitoring of patients with American tegumentary leishmaniasis (ATL). Sera from 14 patients before treatment (BT), 13 patients 1 year after treatment (AT), 10 patients 2 and 5 years AT were evaluated. The results from flow cytometry were expressed as levels of IgG reactivity, based on the percentage of positive fluorescent parasites (PPFP). The 1:256 sample dilution allowed us to differentiate individuals BT and AT. Comparative analysis of IFA and flow cytometry by ROC (receiver operating characteristic curve) showed, respectively, AUC (area under curve) = 0.8 (95% CI = 0.64–0.89) and AUC = 0.90 (95% CI = 0.75–0.95), demonstrating that the flow cytometry had equivalent accuracy. Our data demonstrated that 20% was the best cut-off point identified by the ROC curve for the flow cytometry assay. This test showed a sensitivity of 86% and specificity of 77% while the IFA had a sensitivity of 78% and specificity of 85%. The after-treatment screening, through comparative analysis of the technique performance indexes, 1, 2 and 5 years AT, showed an equal performance of the flow cytometry compared with the IFA. However, flow cytometry shows to be a better diagnostic alternative when applied to the study of ATL in the cure criterion. The information obtained in this work opens perspectives to monitor cure after treatment of ATL.

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.

Indagini in Deep Inference

La tesi è uno studio di alcuni aspetti della nuova metodologia “deep inference”, abbinato ad una rivisitazione dei concetti classici di proof theory, con l'aggiunta di alcuni risultati originali orientati ad una maggior comprensione dell'argomento, nonché alle applicazioni pratiche. Nel primo capitolo vengono introdotti, seguendo un approccio di stampo formalista (con alcuni spunti personali), i concetti base della teoria della dimostrazione strutturale – cioè quella che usa strumenti combinatoriali (o “finitistici”) per studiare le proprietà delle dimostrazioni. Il secondo capitolo focalizza l'attenzione sulla logica classica proposizionale, prima introducendo il calcolo dei sequenti e dimostrando il Gentzen Hauptsatz, per passare poi al calcolo delle strutture (sistema SKS), dimostrando anche per esso un teorema di eliminazione del taglio, appositamente adattato dall'autore. Infine si discute e dimostra la proprietà di località per il sistema SKS. Un percorso analogo viene tracciato dal terzo ed ultimo capitolo, per quanto riguarda la logica lineare. Viene definito e motivato il calcolo dei sequenti lineari, e si discute del suo corrispettivo nel calcolo delle strutture. L'attenzione qui è rivolta maggiormente al problema di definire operatori non-commutativi, che mettono i sistemi in forte relazione con le algebre di processo.

Inference on copula-based correlation structures

We propose an extension of the approach provided by Kluppelberg and Kuhn (2009) for inference on second-order structure moments. As in Kluppelberg and Kuhn (2009) we adopt a copula-based approach instead of assuming normal distribution for the variables, thus relaxing the equality in distribution assumption. A new copula-based estimator for structure moments is investigated. The methodology provided by Kluppelberg and Kuhn (2009) is also extended considering the copulas associated with the family of Eyraud-Farlie-Gumbel-Morgenstern distribution functions (Kotz, Balakrishnan, and Johnson, 2000, Equation 44.73). Finally, a comprehensive simulation study and an application to real financial data are performed in order to compare the different approaches.

Partial reconstruction of the trajectories of a discretely observed branching diffusion with immigration and an application to inference

In this treatise we consider finite systems of branching particles where the particles move independently of each other according to d-dimensional diffusions. Particles are killed at a position dependent rate, leaving at their death position a random number of descendants according to a position dependent reproduction law. In addition particles immigrate at constant rate (one immigrant per immigration time). A process with above properties is called a branching diffusion withimmigration (BDI). In the first part we present the model in detail and discuss the properties of the BDI under our basic assumptions. In the second part we consider the problem of reconstruction of the trajectory of a BDI from discrete observations. We observe positions of the particles at discrete times; in particular we assume that we have no information about the pedigree of the particles. A natural question arises if we want to apply statistical procedures on the discrete observations: How can we find couples of particle positions which belong to the same particle? We give an easy to implement 'reconstruction scheme' which allows us to redraw or 'reconstruct' parts of the trajectory of the BDI with high accuracy. Moreover asymptotically the whole path can be reconstructed. Further we present simulations which show that our partial reconstruction rule is tractable in practice. In the third part we study how the partial reconstruction rule fits into statistical applications. As an extensive example we present a nonparametric estimator for the diffusion coefficient of a BDI where the particles move according to one-dimensional diffusions. This estimator is based on the Nadaraya-Watson estimator for the diffusion coefficient of one-dimensional diffusions and it uses the partial reconstruction rule developed in the second part above. We are able to prove a rate of convergence of this estimator and finally we present simulations which show that the estimator works well even if we leave our set of assumptions.

Phage therapy: A software system for phage quantification and kinetic model inference.

One of the most serious problems of the modern medicine is the growing emergence of antibiotic resistance among pathogenic bacteria. In this circumstance, different and innovative approaches for treating infections caused by multidrug-resistant bacteria are imperatively required. Bacteriophage Therapy is one among the fascinating approaches to be taken into account. This consists of the use of bacteriophages, viruses that infect bacteria, in order to defeat specific bacterial pathogens. Phage therapy is not an innovative idea, indeed, it was widely used around the world in the 1930s and 1940s, in order to treat various infection diseases, and it is still used in Eastern Europe and the former Soviet Union. Nevertheless, Western scientists mostly lost interest in further use and study of phage therapy and abandoned it after the discovery and the spread of antibiotics. The advancement of scientific knowledge of the last years, together with the encouraging results from recent animal studies using phages to treat bacterial infections, and above all the urgent need for novel and effective antimicrobials, have given a prompt for additional rigorous researches in this field. In particular, in the laboratory of synthetic biology of the department of Life Sciences at the University of Warwick, a novel approach was adopted, starting from the original concept of phage therapy, in order to study a concrete alternative to antibiotics. The innovative idea of the project consists in the development of experimental methodologies, which allow to engineer a programmable synthetic phage system using a combination of directed evolution, automation and microfluidics. The main aim is to make “the therapeutics of tomorrow individualized, specific, and self-regulated” (Jaramillo, 2015). In this context, one of the most important key points is the Bacteriophage Quantification. Therefore, in this research work, a mathematical model describing complex dynamics occurring in biological systems involving continuous growth of bacteriophages, modulated by the performance of the host organisms, was implemented as algorithms into a working software using MATLAB. The developed program is able to predict different unknown concentrations of phages much faster than the classical overnight Plaque Assay. What is more, it gives a meaning and an explanation to the obtained data, making inference about the parameter set of the model, that are representative of the bacteriophage-host interaction.

Inference of Raja miraletus population structure using mitochondrial and nuclear DNA: comparing the resolution power of molecular markers in exploring species and population boundaries

This study focused on the role of oceanographic discontinuities and the presence of transitional areas in shaping the population structure and the phylogeography of the Raja miraletus species complex, coupled with the test of the effective occurrence of past speciation events. The comparisons between the Atlantic African and the North-Eastern Atlantic-Mediterranean geographic populations were unravelled using both Cytochrome Oxidase I and eight microsatellite loci. This approach guaranteed a robust dataset for the identification of a speciation event between the Atlantic African clade, corresponding to the ex Raja ocellifera nominal species, and the NE Atlantic-Mediterranean R. miraletus clade. As a matter of fact, the origin of the Atlantic Africa and the NE Atlantic-Mediterranean deep split dated about 11.74MYA and was likely due to the synergic influence currents and two upwelling areas crossing the Western African Waters. Within the Mediterranean Sea, particular attention was also paid to the transitional area represented by Adventura and Maltese Bank, that might have contributed in sustaining the connectivity of the Western and the Eastern Mediterranean geographical populations. Furthermore, the geology of the easternmost part of Sicily and the geo-morphological depression of the Calabrian Arc could have driven the differentiation of the Eastern Mediterranean Sea. Although bathymetric and oceanographic discontinuity could represent barriers to dispersal and migration between Eastern and Western Mediterranean samples, a clear and complete genetic separation among them was not detected. Results produced by this work identified a speciation event defining Raja ocellifera and R. miraletus as two different species, and describing the R. miraletus species complex as the most ancient cryptic speciation event in the family Rajidae, representing another example of how strictly connected the environment, the behavioural habits and the evolutionary and ecologic drivers are.

Inhibition of direct and indirect TLR-mediated activation of human NK cells by low molecular weight dextran sulfate

NK cells express toll-like receptors (TLR) that recognize conserved pathogen or damage associated molecular patterns and play a fundamental role in innate immunity. Low molecular weight dextran sulfate (DXS), known to inhibit the complement system, has recently been reported by us to inhibit TLR4-induced maturation of human monocyte-derived dendritic cells (MoDC). In this study, we investigated the capability of DXS to interfere with human NK cell activation triggered directly by TLR2 agonists or indirectly by supernatants of TLR4-activated MoDC. Both TLR2 agonists and supernatants of TLR4-activated MoDC activated NK cells phenotypically, as demonstrated by the analysis of NK cell activation markers (CD56, CD25, CD69, NKp30, NKp44, NKp46, DNAM-1 and NKG2D), and functionally as shown by increased NK cell degranulation (CD107a surface expression) and IFN-gamma secretion. DXS prevented the up-regulation of NK cell activation markers triggered by TLR2 ligands or supernatants of TLR4-activated MoDC and dose-dependently abrogated NK cell degranulation and IFN-gamma secretion. In summary our results suggest that DXS may be a useful reagent to inhibit the direct and indirect TLR-mediated activation of NK cells.

Sonographic Assessment of Fetal Cardiac Function: Indirect Measurements of Fetal Cardiac Function, Newer Techniques and Clinical Applications

Noninvasive blood flow measurements based on Doppler ultrasound studies are the main clinical tool for studying the cardiovascular status of fetuses at risk for circulatory compromise. Usually, qualitative analysis of peripheral arteries and in particular clinical situations such as severe growth restriction or volume overload also of venous vessels close to the heart or of flow patterns in the heart is being used to gauge the level of compensation in a fetus. However, quantitative assessment of the driving force of the fetal circulation, the cardiac output remains an elusive goal in fetal medicine. This article reviews the methods for direct and indirect assessment of cardiac function and explains new clinical applications. Part 1 of this review describes the concept of cardiac function and cardiac output and the techniques that have been used to quantify output. Part 2 summarizes the use of arterial and venous Doppler studies in the fetus and gives a detailed description of indirect measurements of cardiac function (like indices derived from the duration of segments of the cardiac cycle) with current examples of their application.