Influenza is a severe disease in humans and animals, causing upwards of 40,000 deaths every year in America alone. Influenza A virus (IAV) also causes periodic pandemics every 10 to 50 years, killing millions of people. Despite this, very few effective therapies are available. All strains of IAV are prone to developing resistance to antibodies due to the high mutation rate in the viral genome. Because of this mutation rate, a yearly vaccine must be generated before every flu season, and efficacy varies year to year. IAV has also mutated to escape several of the clinically-approved small molecule inhibitors. A therapeutic agent that targets a highly conserved region of the virus could bypass resistance and also be effective against multiple strains of IAV. IAV attachment is mediated by many individually weak hemagglutinin–sialic acid interactions that all together make a strong attachment to a host cell. Polymerized sialic acid analogs can recreate these interactions and block infection. However, they are not ideal therapeutics due to solubility issues and in vivo toxicity. We used liposomes as a novel means for delivery of the sialic acid-containing glycan, sialylneolacto-N-tetraose c (LSTc). LSTcbearing decoy liposomes form multivalent, polymer-like interactions with IAV. Decoy liposomes competitively bind IAV in hemagglutination inhibition assays and inhibit infection of target cells in a dose-dependent manner. LSTc decoy liposomes co-localize with IAV, while control liposomes do not. Inhibition is specific, as inhibition of Sendai virus and respiratory syncytial virus is not observed. In contrast, monovalent LSTc does not bind IAV or inhibit infectivity. LSTc decoy liposomes prevent the spread of IAV during multiple rounds of replication in vitro and extend survival of mice challenged with a lethal dose of virus. Considering the conservation of the hemagglutinin binding pocket and the ability of decoy liposomes to form high-avidity interactions with IAV hemagglutinin, our decoy liposomes have potential as a new therapeutic agent against emerging strains.

While memory CD4 T cells are critical for effective immunity to pathogens, the mechanisms underlying their generation are poorly defined. Although extensive work has been done to examine the role of antigen (Ag) in shaping memory formation, most studies focus on the requirements during the first few days of the response known as the priming phase. Little is known about whether or not Ag re-encounter by effector T cells (late Ag) alters CD4 memory T cell formation. Since influenza infection produces a large, heterogeneous, protective CD4 memory T cell population, I used this model to examine the role of late Ag in promoting CD4 memory T cell formation. In the experiments presented in this thesis, I demonstrate that late Ag is required to rescue responding CD4 T cells from default apoptosis and to program the transition to long-lived memory. Responding cells that failed to re-encounter Ag had decreased memory marker expression and failed to produce multiple cytokines upon re-stimulation. Ag recognition is required at a defined stage, as short-term Ag presentation provided 6 days after infection is able to restore canonical memory formation even in the absence of viral infection. Finally, I find that memory CD4 T cell formation following cold-adapted influenza vaccination is boosted when Ag is administered at this stage. These findings imply that persistence of viral Ag presentation into the effector phase is the key factor that determines the efficiency of memory generation. They also suggest that administering Ag during the effector stage may improve vaccine efficacy.

Le virus Influenza de type A (IAV) est un agent pathogène hypervariable responsable d’une infection respiratoire aiguë appelée la grippe. L’hyper-variabilité de ce virus IAV lui permet d’être résistant aux traitements antiviraux et est responsable de l’apparition des épidémies de grippe saisonnières. Il est donc essentiel d’établir de nouveaux traitements curatifs « à spectre large » insensibles aux variations du virus de la grippe. Les nanoparticules d’argent (NPs-Ag) sont les nanomatériaux métalliques les plus présents dans le secteur de la santé. En effet, leurs propriétés physico-chimiques leur confèrent de nombreuses capacités telles que la modulation des réponses immunitaires au niveau du poumon et des effets antimicrobiens. Quelques études ont démontré le potentiel anti-IAV des NPs-Ag lorsqu’elles sont placées directement en contact avec le virus IAV. Cependant, aucune de ces études ne porte sur les effets des NPs-Ag dans un contexte physiologique constitué d’une infection grippale suivie d’un traitement. D’autre part, au jour d’aujourd’hui, on ignore les mécanismes d’action mis en place par ces NPs-Ag et les effets induits par l’interaction de ces NPs-Ag avec le système immunitaire dans le contexte d’une infection par l’IAV. Dans ce travail de thèse, l’objectif est d’identifier les mécanismes d’action mis en place par les NPs-Ag au cours de l’infection par le virus IAV et également d’identifier si ces NPs-Ag pourraient être utilisées comme traitement curatif.Dans ce manuscrit de thèse, nous avons pu identifier, dans les cellules épithéliales pulmonaires, un nouveau mécanisme de modulation des NPs-Ag sur la réponse anti-IAV précoce médiée, entre autres, par la sécrétion de la chimiokine CCL5 et de l’IFN-. En effet, les NPs-Ag ciblent spécifiquement la voie de signalisation RIG-I-MAVS-IRFs, activée suite à l’infection par l’IAV et qui est liée à la mitochondrie. Ces NPs-Ag ciblent également en parallèle, à la fois le réseau mitochondrial et le flux autophagique. L’ensemble de ces effets conduit à une redistribution des facteurs de régulation des IFNs (IRFs), les empêchant potentiellement d’interagir avec d’autres facteurs de la voie de signalisation RIG-I/MAVS, ce qui pourrait expliquer l’inhibition de la sécrétion de CCL5 et de l’IFN-b, induite par le virus influenza de type A, par les nanoparticules d’argent. / The Influenza A virus (IAV) is a hyper-variable pathogen causing acute respiratory infection known as Flu. Its hyper-variability allows it to be resistant to antiviral treatment. It is therefore essential to establish new curative "broad spectrum" treatments. Silver nanoparticles (NPs-Ag) are the most metallic nanomaterials present in the health sector and are potent microbicidal agents with major concerns about their use on humans because of their toxicity. Some studies have shown the antiviral effect of NPs-Ag against IAV, but not in a physiological context of Flu. Moreover, the antiviral and immunomodulation mechanisms of NPs-Ag during infection by IAV is still unclear. Here, we show that intra-tracheal administration of AgNPs to influenza infected mice or treatment of human lung epithelial cells with AgNPs resulted in exacerbated inflammation, reduced viral clearance and enhanced mortality associated to different regulation of KC (pro-inflammatory cytokine functionally homologue to human IL-8) and CCL-5 (interferon-related cytokine) in the lung. In this PhD thesis, we identified in lung epithelial cells, a new mechanism explaining dampening of mitochondrial antiviral immunity by AgNPs through alteration of the mitochondrial network leading to redistribution of IFNs regulatory factors 7, which prevents nuclear translocation of these factors. Finally, AgNPs increased LC3 positive vesicles and p62 expression, indicating that AgNPs modify the autophagy flux in lung epithelial cells. Thus, the NPs-Ag Ag inhibited the early anti-IAV response by specifically targeting the RIG-I/MAVS/IRFs signaling pathway resulting in down- regulation of CCL-5 and IFN-ß expression induced by IAV.

No description available.

Activation of the innate immune system via pattern recognition receptors (PRRs) is key to generate lasting adaptive immunity. PRRs detect unique chemical patterns associated with invading microorganisms, but whether and how the physical properties of PRR ligands influence the development of the immune response remains unknown. Through the study of fungal mannans, we show that the physical form of PRR ligands dictates the immune response. Soluble mannans are immunosilent in the periphery but elicit a potent pro-inflammatory response in the draining lymph node (dLN). By modulating the physical form of mannans, we developed a formulation that targets both the periphery and the dLN. When combined with viral glycoprotein antigens, this mannan formulation broadens epitope recognition, elicits potent antigen-specific neutralizing antibodies, and confers protection against viral infections of the lung. Thus, the physical properties of microbial ligands determine the outcome of the immune response and can be harnessed for vaccine development.

No description available.

我們身處於一個充滿風險的社會。金融海嘯、核能危機、全球暖化、食品問題等，在說明社會步向現代化的後遺症，正如何為人類帶來更難預測的風險，並無孔不入般影響我們的日常生活(Beck, 1992)。在這理論基礎上，本文將探究新聞製作於建構風險的角色，並提出一個名為「客觀化」(objectification) 的過程---新聞媒體如何在科學專家的意見眾說紛紜、對風險難有最終定案之下，把有關社會風險的新聞論述詮釋為客觀的社會事實。我尤其探討風險範例的建構---一些有關風險的新聞事件其後演變為重要範例，並影響日後類似事件的新聞論述。 / 為求以實證方法探究風險「合理化」的過程，我將以香港(中華人民共和國的特別行政區) 的新聞論述如何回應2009年全球豬流感危機作為案例。豬流感是香港經歷2003年非典型肺炎危機(又稱「沙士」) 的重創後，首次面對的全球疫症危機。香港新聞如何呈現豬流感疫情，亦深受「沙士」時的歷史回憶、經驗及後遺所影響。故此，這案例有助我研究風險範例於風險「合理化」時的作用。我從香港報章隨機抽樣出有關豬流感的新聞論述的樣本，並透過內容分析和文本分析，研究香港新聞如何敍述豬流感危機，以及相關敍述所包含的意識形態。我亦走訪了當年採訪豬流感新聞的新聞工作者、有份向傳媒提供專家意見的醫學專家、以及負責制定香港政府防控豬流感政策的官員，以了解建構豬流感風險背後的社會互動。 / 本文的研究顯示，香港有關豬流感危機的新聞論述，是如何奠基於「沙士」這風險範例而建構。豬流感起來襲初時，新聞論述廣泛地藉「沙士」的經驗去詮釋豬流感可能帶給香港的後果。新聞工作者於「沙士」時的採訪經歷，亦成為他們報道豬流感新聞時尋找醫學專家意見的參照經驗，尤其是當醫學專家意見紛紜、新聞工作者要判斷誰人的意見較有權威去界定健康風險之時。本文主要闡述新聞的建構於社會回應風險時所起的關鍵作用，從而帶出這於風險社會理論、以及當我們探究新聞媒體及傳播於現代風險社會的角色時，仍未受足夠重視的重要層面。 / We are witnessing the formation of a risk society, with financial instability, nuclear catastrophes, global warming, and food crises, and just to give a few examples, becoming parts of our everyday life in an age of risk characterized by uncertainties stemming from system failure of modernization (Beck, 1992). In the light of this theoretical concern, in this study I shall scrutinize how news making plays its role in the construction of risk. This, I suggest, is a process of risk objectification ---how news media justifies its discourse of social risk by making social facts upon uncertainties and inconclusive scientific opinions. Specifically, I shall focus on the creation of risk exemplar. That is, some news events become critical exemplar that would shape the news construction of subsequent crises of similar sources. / To look into the process of risk objectification empirically, I shall examine what were the main features of the news discourse in Hong Kong, a Special Administrative Region of China, in reaction to the global health crisis of Swine Flu in 2009. Swine Flu was the first pandemic crisis encountered by Hong Kong after its devastating suffering from the epidemic of Severe Acute Respiratory Syndrome (SARS) in 2003. The news representation of Swine Flu was influenced by the historical memory, experience and legacies of SARS and this helps illustrate how risk exemplar contributes to risk legitimization. I carried out content and textual analysis respectively on a random sample of Hong Kong’s newspapers for the purpose of analyzing the key narrations of Swine Flu and the underlying ideological packages of such narrations. I also conducted in-depth interviews with journalists, medical experts and public officials who were deeply involved in the news making of Swine Flu so as to uncover the social dynamics in the process of risk construction. / Key findings of this thesis highlight how the health crisis of Swine Flu was staged by the risk exemplar of SARS. Experience of SARS was widely drawn upon for making sense of the potential impacts of Swine Flu when it first broke out. It was also the key reference for journalists when seeking expert advices, particularly when identifying those who are more authoritative among different opinions in defining the nature of the risk. It is my argument that news making plays a critical role in the shaping of the social reactions to a risk. My analysis thus adds an important, but somehow unduly neglected, dimension to theory of risk society and our understanding of the role of news media and communication in contemporary risk society. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Chan, Chi Kit. / Thesis (Ph.D.) Chinese University of Hong Kong, 2014. / Includes bibliographical references (leaves 240-250). / Abstracts also in Chinese. / Chan, Chi Kit.

Introduction: Epidemiological studies have indicated that 5-38% of influenza like illnesses (ILI) develop into severe disease due to, among others, factors such as; underlying chronic diseases, age, pregnancy, and viral mutations. There are suggestions that dual or multiple virus infections may affect disease severity. This study investigated the association between co-infection between influenza A viruses and other respiratory viruses and disease severity. Methodology: Datum for samples from North West England tested between January 2007 and June 2012 was analysed for patterns of co-infection between influenza A viruses and ten respiratory viruses. Risk of hospitalization to a general ward ICU or death in single versus mixed infections was assessed using multiple logistic regression models. Results: One or more viruses were identified in 37.8% (11,715/30,975) of samples, of which 10.4% (1,214) were mixed infections and 89.6% (10,501) were single infections. Among patients with influenza A(H1N1)pdm09, co-infections occurred in 4.7% (137⁄2,879) vs. 6.5% (59⁄902) in those with seasonal influenza A virus infection. In general, patients with mixed respiratory virus infections had a higher risk of admission to a general ward (OR: 1.43, 95% CI: 1.2 – 1.7, p = <0.0001) than those with a single infection. Co-infection between seasonal influenza A viruses and influenza B virus was associated with a significant increase in the risk of admission to ICU/ death (OR: 22.0, 95% CI: 2.21 – 219.8 p = 0.008). RSV/seasonal influenza A viruses co-infection also associated with increased risk but this was not statistically significant. For the pandemic influenza A(H1N1)pdm09 virus, RSV and AdV co-infection increased risk of hospitalization to a general ward, whereas Flu B increased risk of admission to ICU/ death, but none of these were statistically significant. Considering only single infections, RSV and hPIV1-3 increased risk of admission to a general ward (OR: 1.49, 95% CI: 1.28 – 1.73, p = <0.0001 and OR: 1.34, 95% CI: 1.003 – 1.8, p = 0.05) and admission to ICU/ death (OR: 1.5, 95% CI: 1.20 – 2.0, p = <0.0001 and OR: 1.60, 95% CI: 1.02 – 2.40, p = 0.04). Conclusion: Co-infection is a significant predictor of disease outcome; there is insufficient public health data on this subject as not all samples sent for investigation of respiratory virus infection are tested for all respiratory viruses. Integration of testing for respiratory viruses’ co-infections into routine clinical practice and R&D on integrated drugs and vaccines for influenza A&B, RSV, and AdV, and development of multi-target diagnostic tests is encouraged.

Protein sequencing has produced overwhelming amount of protein sequences, especially in the last decade. Nevertheless, the majority of the proteins' functional and structural classes are still unknown, and experimental methods currently used to determine these properties are very expensive, laborious and time consuming. Therefore, automated computational methods are urgently required to accurately and reliably predict functional and structural classes of the proteins. Several bioinformatics methods have been developed to determine such properties of the proteins directly from their sequence information. Such methods that involve signal processing methods have recently become popular in the bioinformatics area and been investigated for the analysis of DNA and protein sequences and shown to be useful and generally help better characterise the sequences. However, there are various technical issues that need to be addressed in order to overcome problems associated with the signal processing methods for the analysis of the proteins sequences. Amino acid indices that are used to transform the protein sequences into signals have various applications and can represent diverse features of the protein sequences and amino acids. As the majority of indices have similar features, this project proposes a new set of computationally derived indices that better represent the original group of indices. A study is also carried out that resulted in finding a unique and universal set of best discriminating amino acid indices for the characterisation of allergenic proteins. This analysis extracts features directly from the protein sequences by using Discrete Fourier Transform (DFT) to build a classification model based on Support Vector Machines (SVM) for the allergenic proteins. The proposed predictive model yields a higher and more reliable accuracy than those of the existing methods. A new method is proposed for performing a multiple sequence alignment. For this method, DFT-based method is used to construct a new distance matrix in combination with multiple amino acid indices that were used to encode protein sequences into numerical sequences. Additionally, a new type of substitution matrix is proposed where the physicochemical similarities between any given amino acids is calculated. These similarities were calculated based on the 25 amino acids indices selected, where each one represents a unique biological protein feature. The proposed multiple sequence alignment method yields a better and more reliable alignment than the existing methods. In order to evaluate complex information that is generated as a result of DFT, Complex Informational Spectrum Analysis (CISA) is developed and presented. As the results show, when protein classes present similarities or differences according to the Common Frequency Peak (CFP) in specific amino acid indices, then it is probable that these classes are related to the protein feature that the specific amino acid represents. By using only the absolute spectrum in the analysis of protein sequences using the informational spectrum analysis is proven to be insufficient, as biologically related features can appear individually either in the real or the imaginary spectrum. This is successfully demonstrated over the analysis of influenza neuraminidase protein sequences. Upon identification of a new protein, it is important to single out amino acid responsible for the structural and functional classification of the protein, as well as the amino acids contributing to the protein's specific biological characterisation. In this work, a novel approach is presented to identify and quantify the relationship between individual amino acids and the protein. This is successfully demonstrated over the analysis of influenza neuraminidase protein sequences. Characterisation and identification problem of the Influenza A virus protein sequences is tackled through a Subgroup Discovery (SD) algorithm, which can provide ancillary knowledge to the experts. The main objective of the case study was to derive interpretable knowledge for the influenza A virus problem and to consequently better describe the relationships between subtypes of this virus. Finally, by using DFT-based sequence-driven features a Support Vector Machine (SVM)-based classification model was built and tested, that yields higher predictive accuracy than that of SD. The methods developed and presented in this study yield promising results and can be easily applied to proteomic fields.

\\OBJETIVOS: Avaliar a imunogenicidade e a segurança a curto prazo da vacina H1N1 pandêmica em pacientes com artrite reumatóide (AR) e espondiloartrites [ESa - artrite psoriática (AP) e espondilite anquilosante (EA)] recebendo classes distintas de terapia anti-TNF, assim como comparação com pacientes que receberam drogas modificadoras de doenças reumáticas (DMARDs) e controles saudáveis. MÉTODOS: Cento e vinte pacientes (AR, n=41; EA, n=57 e artrite psoriática - AP, n=22) em uso de agentes anti-TNF (monoclonal, n=94 e receptor solúvel, n=26) foram comparados com 116 pacientes com artrite inflamatórias em uso de DMARDs e 117 controles saudáveis. Soroproteção (SP), soroconversão (SC), médias geométricas dos títulos (MGTs), fator de aumento (FI) das MGT e eventos adversos foram avaliados 21 dias após a vacinação. RESULTADOS: Após a imunização, as taxas de SC (58,2% vs 74,3%, p=0,017) foram significativamente menores nos pacientes com espondiloartrites que receberam a terapia anti-TNF, enquanto nenhuma diferença foi observada em pacientes com AR que recebem esta terapia, em comparação com controles saudáveis (p=0,067). Pacientes com espondiloartrites que receberam anticorpos monoclonais (infliximabe/adalimumabe) tiveram uma taxa de SC significativamente menor em comparação com controles saudáveis (51,6% vs. 74,3%, p=0,002) ou para aqueles em uso de DMARDs (51,6% vs. 74,7%, p=0,005), por sua vez não houve diferença para pacientes em uso de etanercepte (86,7% vs. 74,3%, p=0,091). Uma análise dos pacientes com espondiloartrites que apresentaram SC e os que não apresentaram SC revelou que o primeiro grupo teve maior média de idade (p=0,003), maior frequência de anti-TNF (p=0,031) e anticorpos monoclonais (p=0,001), e uma menor frequência de metotrexate (p=0,028). Na regressão logística multivariada, apenas a idade avançada (p=0,015) e tratamento anticorpos monoclonais (p=0,023) permaneceram fatores importantes para a não SC em pacientes com espondiloartrites. CONCLUSÕES: Este estudo mostrou um padrão distinto da resposta imune à vacina contra a gripe pandêmica em pacientes com artrite inflamatória que receberam agentes anti-TNF, com uma imunogenicidade reduzida apenas em pacientes com espondiloartrites usando anticorpos monoclonais / OBJECTIVES: To evaluate the immunogenicity of the anti-influenza A H1N1/2009 vaccine in rheumatoid arthritis (RA) and spondyloarthritis patients receiving distinct classes of anti-TNF agents compared with patients receiving DMARDs and healthy controls. METHODS: One hundred and twenty patients (RA, n=41; ankylosing spondylitis - AS, n=57 and psoriatic arthritis - PsA, n=22) under anti-TNF agents (monoclonal, n=94 and soluble receptor, n=26) were compared to 116 inflammatory arthritis patients under DMARDs and 117 healthy controls. Seroprotection (SP), seroconversion (SC), geometric mean titre (GMT), factor increase (FI) in GMT and adverse events were evaluated 21 days after vaccination. RESULTS: After immunisation, SC rates (58.2% vs. 74.3%, p=0.017) were significantly lower in spondyloarthritis patients receiving anti-TNF therapy, whereas no difference was observed in RA patients receiving this therapy compared to healthy controls (p=0.067). Spondyloarthritis patients receiving monoclonal antibodies (infliximab/adalimumab) had a significantly lower seroconversion rate compared to healthy controls (51.6% vs. 74.3%, p=0.002) or to those under DMARDs (51.6% vs. 74.7%, p=0.005), whereas no difference was observed for patients under etanercept (86.7% vs. 74.3%, p=0.091). Further analysis of non-seroconverting and seronconverting spondyloarthritis patients revealed that the former group had a higher mean age (p=0.003), a higher frequency of anti-TNF (p=0.031) and monoclonal antibodies (p=0.001), and a lower frequency of methotrexate (p=0.028). In multivariate logistic regression, only older age (p=0.015) and monoclonal antibodies treatment (p=0.023) remained significant factors for nonseroconversion in spondyloarthritis patients. CONCLUSIONS: This study revealed a distinct disease pattern of immune response to the pandemic influenza vaccine in inflammatory arthritis patients receiving anti-TNF agents, illustrated by a reduced immunogenicity solely in spondyloarthritis patients using monoclonal antibodies