296 research outputs found

    The values and limitations of mathematical modelling to COVID-19 in the world: a follow up report

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    We previously described a mathematical model to simulate the course of the COVID-19 pandemic and try to predict how this outbreak might evolve in the following two months when the pandemic cases will drop significantly. Our original paper prepared in March 2020 analyzed the outbreaks of COVID-19 in the US and its selected states to identify the rise, peak, and decrease of cases within a given geographic population, as well as a rough calculation of accumulated total cases in this population from the beginning to the end of June 2020. The current report will describe how well the later actual trend from March to June fit our model and prediction. Similar analyses are also conducted to include countries other than the US. From such a wide global data analysis, our results demonstrated that different US states and countries showed dramatically different patterns of pandemic trend. The values and limitations of our modelling are discussed

    DNA Immunization for HIV Vaccine Development

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    DNA vaccination has been studied in the last 20 years for HIV vaccine research. Significant experience has been accumulated in vector design, antigen optimization, delivery approaches and the use of DNA immunization as part of a prime-boost HIV vaccination strategy. Key historical data and future outlook are presented. With better understanding on the potential of DNA immunization and recent progress in HIV vaccine research, it is anticipated that DNA immunization will play a more significant role in the future of HIV vaccine development

    Visual analysis of discrimination in machine learning

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    The growing use of automated decision-making in critical applications, such as crime prediction and college admission, has raised questions about fairness in machine learning. How can we decide whether different treatments are reasonable or discriminatory? In this paper, we investigate discrimination in machine learning from a visual analytics perspective and propose an interactive visualization tool, DiscriLens, to support a more comprehensive analysis. To reveal detailed information on algorithmic discrimination, DiscriLens identifies a collection of potentially discriminatory itemsets based on causal modeling and classification rules mining. By combining an extended Euler diagram with a matrix-based visualization, we develop a novel set visualization to facilitate the exploration and interpretation of discriminatory itemsets. A user study shows that users can interpret the visually encoded information in DiscriLens quickly and accurately. Use cases demonstrate that DiscriLens provides informative guidance in understanding and reducing algorithmic discrimination

    The dynamics of immunoglobulin V-gene usage and clonotype expansion in mice after prime and boost immunizations as analyzed by NGS

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    In the current study, an improved NGS approach was developed to study the B-cell repertoire evolution in a simple mouse immunization model including only two DNA immunizations. The combination of 5\u27RACE and Ion Torrent long reads enabled unbiased immunoglobulin repertoire analysis even from small amounts of peripheral mouse blood. The B-cell population expanded by the vaccine displayed a relatively strong clonality. Upon priming with the first vaccine dose, we observed a consistent pattern of V-segment gene and CDR3 usage (public specificities). Interestingly, this pattern diversified with the second dose of immunization -it was relatively different in individual mice in spite of having received the same vaccine regimen (private specificities). Nevertheless, there were several instances in which the same public V-segment genes and CDR3s that were expanded after the first dose were further amplified after the second immunization. Taken together, it appears that the major clonotypes expanded by vaccination were originally a homogeneous subset that later diversified after a second dose leading to diverse private clonal compositions in different mice. These results established a new platform valuable to perform longitudinal analyses of the Ig germline gene usage and clonotype evolution throughout an immunization regimen in a commonly used animal model

    Select gp120 V2 domain specific antibodies derived from HIV and SIV infection and vaccination inhibit gp120 binding to alpha4beta7

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    The GI tract is preferentially targeted during acute/early HIV-1 infection. Consequent damage to the gut plays a central role in HIV pathogenesis. The basis for preferential targeting of gut tissues is not well defined. Recombinant proteins and synthetic peptides derived from HIV and SIV gp120 bind directly to integrin alpha4beta7, a gut-homing receptor. Using both cell-surface expressed alpha4beta7 and a soluble alpha4beta7 heterodimer we demonstrate that its specific affinity for gp120 is similar to its affinity for MAdCAM (its natural ligand). The gp120 V2 domain preferentially engages extended forms of alpha4beta7 in a cation -sensitive manner and is inhibited by soluble MAdCAM. Thus, V2 mimics MAdCAM in the way that it binds to alpha4beta7, providing HIV a potential mechanism to discriminate between functionally distinct subsets of lymphocytes, including those with gut-homing potential. Furthermore, alpha4beta7 antagonists developed for the treatment of inflammatory bowel diseases, block V2 binding to alpha4beta7. A 15-amino acid V2 -derived peptide is sufficient to mediate binding to alpha4beta7. It includes the canonical LDV/I alpha4beta7 binding site, a cryptic epitope that lies 7-9 amino acids amino terminal to the LDV/I, and residues K169 and I181. These two residues were identified in a sieve analysis of the RV144 vaccine trial as sites of vaccine -mediated immune pressure. HIV and SIV V2 mAbs elicited by both vaccination and infection that recognize this peptide block V2-alpha4beta7 interactions. These mAbs recognize conformations absent from the beta- barrel presented in a stabilized HIV SOSIP gp120/41 trimer. The mimicry of MAdCAM-alpha4beta7 interactions by V2 may influence early events in HIV infection, particularly the rapid seeding of gut tissues, and supports the view that HIV replication in gut tissue is a central feature of HIV pathogenesis

    Considerable MHC Diversity Suggests That the Functional Extinction of Baiji Is Not Related to Population Genetic Collapse

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    To further extend our understanding of the mechanism causing the current nearly extinct status of the baiji (Lipotes vexillifer), one of the most critically endangered species in the world, genetic diversity at the major histocompatibility complex (MHC) class II DRB locus was investigated in the baiji. Nine highly divergent DRB alleles were identified in 17 samples, with an average of 28.4 (13.2%) nucleotide difference and 16.7 (23.5%) amino acid difference between alleles. The unexpectedly high levels of DRB allelic diversity in the baiji may partly be attributable to its evolutionary adaptations to the freshwater environment which is regarded to have a higher parasite diversity compared to the marine environment. In addition, balancing selection was found to be the main mechanisms in generating sequence diversity at baiji DRB gene. Considerable sequence variation at the adaptive MHC genes despite of significant loss of neutral genetic variation in baiji genome might suggest that intense selection has overpowered random genetic drift as the main evolutionary forces, which further suggested that the critically endangered or nearly extinct status of the baiji is not an outcome of genetic collapse

    Adaptive evolution and functional constraint at TLR4 during the secondary aquatic adaptation and diversification of cetaceans

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    <p>Abstract</p> <p>Background</p> <p>Cetaceans (whales, dolphins and porpoises) are a group of adapted marine mammals with an enigmatic history of transition from terrestrial to full aquatic habitat and rapid radiation in waters around the world. Throughout this evolution, the pathogen stress-response proteins must have faced challenges from the dramatic change of environmental pathogens in the completely different ecological niches cetaceans occupied. For this reason, cetaceans could be one of the most ideal candidate taxa for studying evolutionary process and associated driving mechanism of vertebrate innate immune systems such as Toll-like receptors (TLRs), which are located at the direct interface between the host and the microbial environment, act at the first line in recognizing specific conserved components of microorganisms, and translate them rapidly into a defense reaction.</p> <p>Results</p> <p>We used TLR4 as an example to test whether this traditionally regarded pattern recognition receptor molecule was driven by positive selection across cetacean evolutionary history. Overall, the lineage-specific selection test showed that the <it>dN/dS </it>(ω) values along most (30 out of 33) examined cetartiodactylan lineages were less than 1, suggesting a common effect of functional constraint. However, some specific codons made radical changes, fell adjacent to the residues interacting with lipopolysaccharides (LPS), and showed parallel evolution between independent lineages, suggesting that TLR4 was under positive selection. Especially, strong signatures of adaptive evolution on TLR4 were identified in two periods, one corresponding to the early evolutionary transition of the terrestrial ancestors of cetaceans from land to semi-aquatic (represented by the branch leading to whale + hippo) and from semi-aquatic to full aquatic (represented by the ancestral branch leading to cetaceans) habitat, and the other to the rapid diversification and radiation of oceanic dolphins.</p> <p>Conclusions</p> <p>This is the first study thus far to characterize the TLR gene in cetaceans. Our data present evidences that cetacean TLR4 has undergone adaptive evolution against the background of purifying selection in response to the secondary aquatic adaptation and rapid diversification in the sea. It is suggested that microbial pathogens in different environments are important factors that promote adaptive changes at cetacean TLR4 and new functions of some amino acid sites specialized for recognizing pathogens in dramatically contrasted environments to enhance the fitness for the adaptation and survival of cetaceans.</p

    A Novel DNA and Protein Combination COVID-19 Vaccine Formulation Provides Full Protection against SARS-CoV-2 in Rhesus Macaques

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    The current study aims to develop a safe and highly immunogenic COVID-19 vaccine. The novel combination of a DNA vaccine encoding the full-length Spike (S) protein of SARS-CoV-2 and a recombinant S1 protein vaccine induced high level neutralizing antibody and T cell immune responses in both small and large animal models. More significantly, the co-delivery of DNA and protein components at the same time elicited full protection against intratracheal challenge of SARS-CoV-2 viruses in immunized rhesus macaques. As both DNA and protein vaccines have been proven safe in previous human studies, and DNA vaccines are capable of eliciting germinal center B cell development, which is critical for high -affinity memory B cell responses, the DNA and protein co-delivery vaccine approach has great potential to serve as a safe and effective approach to develop COVID-19 vaccines that provide long-term protection

    Visual diagnosis of tree boosting methods

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    Tree boosting, which combines weak learners (typically decision trees) to generate a strong learner, is a highly effective and widely used machine learning method. However, the development of a high performance tree boosting model is a time-consuming process that requires numerous trial-and-error experiments. To tackle this issue, we have developed a visual diagnosis tool, BOOSTVis, to help experts quickly analyze and diagnose the training process of tree boosting. In particular, we have designed a temporal confusion matrix visualization, and combined it with a t-SNE projection and a tree visualization. These visualization components work together to provide a comprehensive overview of a tree boosting model, and enable an effective diagnosis of an unsatisfactory training process. Two case studies that were conducted on the Otto Group Product Classification Challenge dataset demonstrate that BOOSTVis can provide informative feedback and guidance to improve understanding and diagnosis of tree boosting algorithms
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