Pro-inflammatory flagellin proteins of prevalent motile commensal bacteria are variably abundant in the intestinal microbiome of elderly humans

Some Eubacterium and Roseburia species are among the most prevalent motile bacteria present in the intestinal microbiota of healthy adults. These flagellate species contribute "cell motility" category genes to the intestinal microbiome and flagellin proteins to the intestinal proteome. We reviewed and revised the annotation of motility genes in the genomes of six Eubacterium and Roseburia species that occur in the human intestinal microbiota and examined their respective locus organization by comparative genomics. Motility gene order was generally conserved across these loci. Five of these species harbored multiple genes for predicted flagellins. Flagellin proteins were isolated from R. inulinivorans strain A2-194 and from E. rectale strains A1-86 and M104/1. The amino-termini sequences of the R. inulinivorans and E. rectale A1-86 proteins were almost identical. These protein preparations stimulated secretion of interleukin-8 (IL-8) from human intestinal epithelial cell lines, suggesting that these flagellins were pro-inflammatory. Flagellins from the other four species were predicted to be pro-inflammatory on the basis of alignment to the consensus sequence of pro-inflammatory flagellins from the beta- and gamma-proteobacteria. Many fliC genes were deduced to be under the control of sigma(28). The relative abundance of the target Eubacterium and Roseburia species varied across shotgun metagenomes from 27 elderly individuals. Genes involved in the flagellum biogenesis pathways of these species were variably abundant in these metagenomes, suggesting that the current depth of coverage used for metagenomic sequencing (3.13-4.79 Gb total sequence in our study) insufficiently captures the functional diversity of genomes present at low (<= 1%) relative abundance. E. rectale and R. inulinivorans thus appear to synthesize complex flagella composed of flagellin proteins that stimulate IL-8 production. A greater depth of sequencing, improved evenness of sequencing and improved metagenome assembly from short reads will be required to facilitate in silico analyses of complete complex biochemical pathways for low-abundance target species from shotgun metagenomes.

MicroRNA expression and function in neonatal hypoxic ischaemic encephalopathy

Hypoxic ischaemic encephalopathy (HIE) is a devastating neonatal condition which affects 2-3 per 1000 infants annually. The current gold standard of treatment - induced hypothermia, has the ability to reduce neonatal mortality and improve neonatal morbidity. However, to be effective it needs to be initiated within the therapeutic window which exists following initial insult until approximately 6 hours after birth. Current methods of assessment which are relied upon to identify infants with HIE are subjective and unreliable. To overcome this issue, an early and reliable biomarker of HIE severity must be identified. MicroRNA (miRNA) are a class of small non-coding RNA molecules which have potential as biomarkers of disease state and potential therapeutic targets. These tiny molecules can modulate gene expression by inhibiting translation of messenger RNA (mRNA) and as a result, can regulate protein synthesis. These miRNA are understood to be released into the circulation during cellular stress, where they are highly stable and relatively easy to quantify. Therefore, these miRNAs may be ideal candidates for biomarkers of HIE severity and may aid in directing the clinical management of these infants. By using both transcriptomic and proteomic approaches to analyse the expression of miRNAs and their potential targets in the umbilical cord blood, I have confirmed that infants with perinatal asphyxia and HIE have a significantly different UCB miRNA signature compared to UCB samples from healthy controls. Finally, I have identified and investigated 2 individual miRNAs; both of which show some potential as classifiers of HIE severity and predictors of long term outcome, particularly when coupled with their downstream targets. While this work will need to be validated and expanded in a new and larger cohort of infants, it suggests the potential of miRNA as biomarkers of neonatal pathological conditions such as HIE.

Genome analysis and characterisation of the exopolysaccharide produced by Bifidobacterium longum subsp. longum 35624™

The Bifibobacterium longum subsp. longum 35624™ strain (formerly named Bifidobacterium longum subsp. infantis) is a well described probiotic with clinical efficacy in Irritable Bowel Syndrome clinical trials and induces immunoregulatory effects in mice and in humans. This paper presents (a) the genome sequence of the organism allowing the assignment to its correct subspeciation longum; (b) a comparative genome assessment with other B. longum strains and (c) the molecular structure of the 35624 exopolysaccharide (EPS624). Comparative genome analysis of the 35624 strain with other B. longum strains determined that the sub-speciation of the strain is longum and revealed the presence of a 35624-specific gene cluster, predicted to encode the biosynthetic machinery for EPS624. Following isolation and acid treatment of the EPS, its chemical structure was determined using gas and liquid chromatography for sugar constituent and linkage analysis, electrospray and matrix assisted laser desorption ionization mass spectrometry for sequencing and NMR. The EPS consists of a branched hexasaccharide repeating unit containing two galactose and two glucose moieties, galacturonic acid and the unusual sugar 6-deoxy-L-talose. These data demonstrate that the B. longum 35624 strain has specific genetic features, one of which leads to the generation of a characteristic exopolysaccharide.

Accélérer l'entraînement d'un modèle non-paramétrique de densité non normalisée par échantillonnage aléatoire

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

The Rotational Evolution and Magnetospheric Emission of the Magnetic Early B-type Stars

How do the magnetic fields of massive stars evolve over time? Are their gyrochronological ages consistent with ages inferred from evolutionary tracks? Why do most stars predicted to host Centrifugal Magnetospheres (CMs) display no H$\alpha$ emission? Does plasma escape from CMs via centrifugal breakout events, or by a steady-state leakage mechanism? This thesis investigates these questions via a population study with a sample of 51 magnetic early B-type stars. The longitudinal magnetic field \bz~was measured from Least Squares Deconvolution profiles extracted from high-resolution spectropolarimetric data. New rotational periods $P_{\rm rot}$ were determined for 15 stars from \bz, leaving only 3 stars for which $P_{\rm rot}$ is unknown. Projected rotational velocities \vsini~were measured from multiple spectral lines. Effective temperatures and surface gravities were measured via ionization balances and line profile fitting of H Balmer lines. Fundamental physical parameters, \bz, \vsini, and $P_{\rm rot}$ were then used to determine radii, masses, ages, dipole oblique rotator model, stellar wind, magnetospheric, and spindown parameters using a Monte Carlo approach that self-consistently calculates all parameters while accounting for all available constraints on stellar properties. Dipole magnetic field strengths $B_{\rm d}$ follow a log-normal distribution similar to that of Ap stars, and decline over time in a fashion consistent with the expected conservation of fossil magnetic flux. $P_{\rm rot}$ increases with fractional main sequence age, mass, and $B_{\rm d}$, as expected from magnetospheric braking. However, comparison of evolutionary track ages to maximum spindown ages $t_{\rm S,max}$ shows that initial rotation fractions may be far below critical for stars with $M_*>10 M_\odot$. Computing $t_{\rm S,max}$ with different mass-loss prescriptions indicates that the mass-loss rates of B-type stars are likely much lower than expected from extrapolation from O-type stars. Stars with H$\alpha$ in emission and absorption occupy distinct regions in the updated rotation-magnetic confinement diagram: H$\alpha$-bright stars are found to be younger, more rapidly rotating, and more strongly magnetized than the general population. Emission strength is sensitive both to the volume of the CM and to the mass-loss rate, favouring leakage over centrifugal breakout.

Communication-efficient decentralized sequential detection

The problem of decentralized sequential detection is studied in this thesis, where local sensors are memoryless, receive independent observations, and no feedback from the fusion center. In addition to traditional criteria of detection delay and error probability, we introduce a new constraint: the number of communications between local sensors and the fusion center. This metric is able to reflect both the cost of establishing communication links as well as overall energy consumption over time. A new formulation for communication-efficient decentralized sequential detection is proposed where the overall detection delay is minimized with constraints on both error probabilities and the communication cost. Two types of problems are investigated based on the communication-efficient formulation: decentralized hypothesis testing and decentralized change detection. In the former case, an asymptotically person-by-person optimum detection framework is developed, where the fusion center performs a sequential probability ratio test based on dependent observations. The proposed algorithm utilizes not only reported statistics from local sensors, but also the reporting times. The asymptotically relative efficiency of proposed algorithm with respect to the centralized strategy is expressed in closed form. When the probabilities of false alarm and missed detection are close to one another, a reduced-complexity algorithm is proposed based on a Poisson arrival approximation. In addition, decentralized change detection with a communication cost constraint is also investigated. A person-by-person optimum change detection algorithm is proposed, where transmissions of sensing reports are modeled as a Poisson process. The optimum threshold value is obtained through dynamic programming. An alternative method with a simpler fusion rule is also proposed, where the threshold values in the algorithm are determined by a combination of sequential detection analysis and constrained optimization. In both decentralized hypothesis testing and change detection problems, tradeoffs in parameter choices are investigated through Monte Carlo simulations.

MiRNA 34a: a therapeutic target for castration-resistant prostate cancer

INTRODUCTION: Development of a therapy for bone metastases is of paramount importance for castration-resistant prostate cancer (CRPC). The osteomimetic properties of CRPC confer a propensity to metastasize to osseous sites. Micro-ribonucleic acid (miRNA) is non-coding RNA that acts as a post-transcriptional regulator of multiple proteins and associated pathways. Therefore identification of miRNAs could reveal a valid third generation therapy for CRPC. Areas covered: miR34a has been found to play an integral role in the progression of prostate cancer, particularly in the regulation of metastatic genes involved in migration, intravasation, extravasation, bone attachment and bone homeostasis. The correlation between miR34a down-regulation and metastatic progression has generated substantial interest in this field. Expert opinion: Examination of the evidence reveals that miR34a is an ideal target for gene therapy for metastatic CRPC. We also conclude that future studies should focus on the effects of miR34a upregulation in CRPC with respect to migration, translocation to bone micro-environment and osteomimetic phenotype development. The success of miR34a as a therapeutic is reliant on the development of appropriate delivery systems and targeting to the bone micro-environment. In tandem with any therapeutic studies, biomarker serum levels should also be ascertained as an indicator of successful miR34a delivery.

Hmx1 Function In Lateral Facial Development

Thesis (Master's)--University of Washington, 2016-08

The Use of Multi-Criteria Decision Analysis in Performing Alternatives Assessment and Comparative Risk Analysis: The Case Study of Codling Moth Pesticides

Thesis (Ph.D.)--University of Washington, 2016-08

Exploring social representations of adapting to climate change using topic modeling and Bayesian networks

When something unfamiliar emerges or when something familiar does something unexpected people need to make sense of what is emerging or going on in order to act. Social representations theory suggests how individuals and society make sense of the unfamiliar and hence how the resultant social representations (SRs) cognitively, emotionally, and actively orient people and enable communication. SRs are social constructions that emerge through individual and collective engagement with media and with everyday conversations among people. Recent developments in text analysis techniques, and in particular topic modeling, provide a potentially powerful analytical method to examine the structure and content of SRs using large samples of narrative or text. In this paper I describe the methods and results of applying topic modeling to 660 micronarratives collected from Australian academics / researchers, government employees, and members of the public in 2010-2011. The narrative fragments focused on adaptation to climate change (CC) and hence provide an example of Australian society making sense of an emerging and conflict ridden phenomena. The results of the topic modeling reflect elements of SRs of adaptation to CC that are consistent with findings in the literature as well as being reasonably robust predictors of classes of action in response to CC. Bayesian Network (BN) modeling was used to identify relationships among the topics (SR elements) and in particular to identify relationships among topics, sentiment, and action. Finally the resulting model and topic modeling results are used to highlight differences in the salience of SR elements among social groups. The approach of linking topic modeling and BN modeling offers a new and encouraging approach to analysis for ongoing research on SRs.

Asymptotic Change-Point Analysis of the Dependencies in Time Series

In recent papers, Wied and his coauthors have introduced change-point procedures to detect and estimate structural breaks in the correlation between time series. To prove the asymptotic distribution of the test statistic and stopping time as well as the change-point estimation rate, they use an extended functional Delta method and assume nearly constant expectations and variances of the time series. In this thesis, we allow asymptotically infinitely many structural breaks in the means and variances of the time series. For this setting, we present test statistics and stopping times which are used to determine whether or not the correlation between two time series is and stays constant, respectively. Additionally, we consider estimates for change-points in the correlations. The employed nonparametric statistics depend on the means and variances. These (nuisance) parameters are replaced by estimates in the course of this thesis. We avoid assuming a fixed form of these estimates but rather we use "blackbox" estimates, i.e. we derive results under assumptions that these estimates fulfill. These results are supplement with examples. This thesis is organized in seven sections. In Section 1, we motivate the issue and present the mathematical model. In Section 2, we consider a posteriori and sequential testing procedures, and investigate convergence rates for change-point estimation, always assuming that the means and the variances of the time series are known. In the following sections, the assumptions of known means and variances are relaxed. In Section 3, we present the assumptions for the mean and variance estimates that we will use for the mean in Section 4, for the variance in Section 5, and for both parameters in Section 6. Finally, in Section 7, a simulation study illustrates the finite sample behaviors of some testing procedures and estimates.

A Política Externa da União Europeia no Ártico

É através da política externa que os atores das relações internacionais procuram concretizar os seus objetivos além das suas fronteiras. O Ártico é atualmente uma região alvo da política externa de atores das relações internacionais, entre eles Estados,organizações internacionais, multinacionais, entre outros. Sendo um território quase inexplorado, sabe-se que é extremamente rico em recursos naturais e energéticose que,com as alterações climáticas, estes recursos podem ser explorados. Com o derretimento da camada de gelo, o Oceano Ártico torna-se também uma rota de navegação rápida, o que intensificará o comércio internacional. No entanto, não são apenas oportunidades de crescimento económico que surgem do degelo do Ártico, mas também sérios riscos económicos, ambientais e securitários, aos quais a União Europeia não está alheia. Neste sentido, a organização europeia tem vindo a aplicar os seus esforços de política externa para desenvolver uma política que vá ao encontro dos seus objetivos na região, salvaguardando assim a sua segurança e também os seus interesses. Numa análise teórica, este trabalho procura previamente entender o que é a política externa, qual o papel da União Europeianesse âmbitoe quais as motivações para uma política externa europeia para o Ártico. Também se pretende mostrar a crescente importância da região do Ártico, e como este crescimento está fortemente ligado ao fenómeno das alterações climáticas. Sob a análise empírica, procura-se evidenciar a forma como a União Europeia está a desenvolver a sua política orientada para a região, para que no final do trabalho, cruzando a teoria com a parte empírica, fazer uma leitura da política europeia de acordo com as teorias das relações internacionais. Para dar forma ao trabalho, a metodologia utilizada foi a consulta de fontes académicas, a partir de centros de investigação ligados ao Ártico,como o Smithsonian Arctic Studies Center, o International Arctic Research Center eo Arctic Centre da Universidade da Lapónia, além de fontes documentais de diferentes organizações internacionais e documentos oficiais da União Europeia. Pode concluir-se que a União Europeia tem desenvolvido uma estratégia tendencialmente realista, pois procura sobretudo obter a sua segurança em relação às consequências do degelo do Árticoe limitar as oportunidades de crescimento dos restantes atores da região, apesar de o fazer utilizando políticas e estratégias de caráter pluralista.

MicroRNAs

Os microRNAs (miRNAs) são curtas cadeias de RNA não codificante, com cerca de 18 a 25 nucleotídeos, que regulam os níveis de mRNAs que são produzidos a partir de genes codificantes de proteínas. A descoberta dos miRNAs e a sua subsequente caracterização estrutural e funcional revelou a existência de um novo processo de regulação pós-transcricional da expressão génica em células eucarióticas que afeta uma grande variedade de funções celulares. A senescência acompanha o processo de evelhecimento dos organismos e é manifestada pela perda da capacidade proliferativa das células em resposta a diversos fatores de stress que desencadeiam alterações moleculares específicas. Na última década foram identificados e caracterizados vários miRNAs que participam na regulação do fenótipo da senescência celular, quer através da modulação de vias de sinalização endógenas que controlam a progressão do ciclo celular, quer através da secreção de factores de sinalização. Vários estudos têm também revelado a enorme potencialidade dos miRNAs como biomarcadores e alvos moleculares de novas abordagens terapêuticas. No futuro, é expectável que os avanços científicos possam ser transferidos para a prática clínica com vista a uma efetiva prevenção, vigilância e tratamento do envelhecimento prematuro e de doenças associadas ao envelhecimento.

Rice-Infecting Pseudomonas Genomes Are Highly Accessorized and Harbor Multiple Putative Virulence Mechanisms to Cause Sheath Brown Rot

Sheath rot complex and seed discoloration in rice involve a number of pathogenic bacteria that cannot be associated with distinctive symptoms. These pathogens can easily travel on asymptomatic seeds and therefore represent a threat to rice cropping systems. Among the rice-infecting Pseudomonas, P. fuscovaginae has been associated with sheath brown rot disease in several rice growing areas around the world. The appearance of a similar Pseudomonas population, which here we named P. fuscovaginae-like, represents a perfect opportunity to understand common genomic features that can explain the infection mechanism in rice. We showed that the novel population is indeed closely related to P. fuscovaginae. A comparative genomics approach on eight rice-infecting Pseudomonas revealed heterogeneous genomes and a high number of strain-specific genes. The genomes of P. fuscovaginae-like harbor four secretion systems (Type I, II, III, and VI) and other important pathogenicity machinery that could probably facilitate rice colonization. We identified 123 core secreted proteins, most of which have strong signatures of positive selection suggesting functional adaptation. Transcript accumulation of putative pathogenicity-related genes during rice colonization revealed a concerted virulence mechanism. The study suggests that rice-infecting Pseudomonas causing sheath brown rot are intrinsically diverse and maintain a variable set of metabolic capabilities as a potential strategy to occupy a range of environments.

Exact Solution of Bayes and Minimax Change-Detection Problems

The challenge of detecting a change in the distribution of data is a sequential decision problem that is relevant to many engineering solutions, including quality control and machine and process monitoring. This dissertation develops techniques for exact solution of change-detection problems with discrete time and discrete observations. Change-detection problems are classified as Bayes or minimax based on the availability of information on the change-time distribution. A Bayes optimal solution uses prior information about the distribution of the change time to minimize the expected cost, whereas a minimax optimal solution minimizes the cost under the worst-case change-time distribution. Both types of problems are addressed. The most important result of the dissertation is the development of a polynomial-time algorithm for the solution of important classes of Markov Bayes change-detection problems. Existing techniques for epsilon-exact solution of partially observable Markov decision processes have complexity exponential in the number of observation symbols. A new algorithm, called constellation induction, exploits the concavity and Lipschitz continuity of the value function, and has complexity polynomial in the number of observation symbols. It is shown that change-detection problems with a geometric change-time distribution and identically- and independently-distributed observations before and after the change are solvable in polynomial time. Also, change-detection problems on hidden Markov models with a fixed number of recurrent states are solvable in polynomial time. A detailed implementation and analysis of the constellation-induction algorithm are provided. Exact solution methods are also established for several types of minimax change-detection problems. Finite-horizon problems with arbitrary observation distributions are modeled as extensive-form games and solved using linear programs. Infinite-horizon problems with linear penalty for detection delay and identically- and independently-distributed observations can be solved in polynomial time via epsilon-optimal parameterization of a cumulative-sum procedure. Finally, the properties of policies for change-detection problems are described and analyzed. Simple classes of formal languages are shown to be sufficient for epsilon-exact solution of change-detection problems, and methods for finding minimally sized policy representations are described.