Quantitative Phenotype Analysis to Identify, Validate and Compare Rat Disease Models

Introduction The laboratory rat has been widely used as an animal model in biomedical research. There are many strains exhibiting a wide variety of phenotypes. Capturing these phenotypes in a centralized database provides researchers with an easy method for choosing the appropriate strains for their studies. Current resources such as NBRP and PhysGen provided some preliminary work in rat phenotype databases. However, there are drawbacks in both projects: (1) small number of animals (6 rats) used by NBRP; (2) NBRP project is a one-time effort for each strain; (3) PhysGen web interface only enables queries within a single study – data comparison and integration not possible; (4) PhysGen lacks a data standardization process so that the measurement method, experimental condition, and age of rats used are hidden. Therefore, there is a need for a better data integration and visualization method in order to provide users with more insights about phenotype differences across rat strains. The Rat Genome Database (RGD) PhenoMiner tool has provided the first step in this effort by standardizing and integrating data from individual studies as well as NBRP and PhysGen. Methods Our work involved the following key steps: (1) we developed a meta-analysis pipeline to automatically integrate data from heterogeneous sources and to produce expected ranges (standardized phenotype ranges) for different strains, and different phenotypes under different experimental conditions; (2) we created tools to visualize expected ranges for individual strains and strain groups; (3) we clustered substrains into different sub-populations according to phenotype correlations. Results We developed a meta-analysis pipeline and an interactive web interface that summarizes and visualizes expected ranges produced from the meta-analysis pipeline. Automation of the pipeline allows for updates as additional data becomes available. The interactive web interface provides the researchers with a platform for identifying and validating expected ranges for a variety of quantitative phenotypes. In addition, we performed a preliminary cluster analysis that enables researchers to examine similarities of strains, substrains, and different sex or age groups of strains on a multi-dimensional scale by using multiple phenotype features. Conclusion The data resources and the data mining and visualization tools will promote an understanding of rat disease models, guide researchers to choose optimal strains for their research needs, and encourage data sharing from different research hubs. Such resources also help to promote research reproducibility. Data produced and interactive platforms created in this project will continue to provide a valuable resource for Translational Research efforts

Enriching Step-Based Product Information Models to Support Product Life-Cycle Activities

The representation and management of product information in its life-cycle requires standardized data exchange protocols. Standard for Exchange of Product Model Data (STEP) is such a standard that has been used widely by the industries. Even though STEP-based product models are well defined and syntactically correct, populating product data according to these models is not easy because they are too big and disorganized. Data exchange specifications (DEXs) and templates provide re-organized information models required in data exchange of specific activities for various businesses. DEXs show us it would be possible to organize STEP-based product models in order to support different engineering activities at various stages of product life-cycle. In this study, STEP-based models are enriched and organized to support two engineering activities: materials information declaration and tolerance analysis. Due to new environmental regulations, the substance and materials information in products have to be screened closely by manufacturing industries. This requires a fast, unambiguous and complete product information exchange between the members of a supply chain. Tolerance analysis activity, on the other hand, is used to verify the functional requirements of an assembly considering the worst case (i.e., maximum and minimum) conditions for the part/assembly dimensions. Another issue with STEP-based product models is that the semantics of product data are represented implicitly. Hence, it is difficult to interpret the semantics of data for different product life-cycle phases for various application domains. OntoSTEP, developed at NIST, provides semantically enriched product models in OWL. In this thesis, we would like to present how to interpret the GD & T specifications in STEP for tolerance analysis by utilizing OntoSTEP

Textual Information Extraction

Material completo EI

Products and Services

Today’s global economy offers more opportunities, but is also more complex and competitive than ever before. This fact leads to a wide range of research activity in different fields of interest, especially in the so-called high-tech sectors. This book is a result of widespread research and development activity from many researchers worldwide, covering the aspects of development activities in general, as well as various aspects of the practical application of knowledge

Developing a Framework for Stigmergic Human Collaboration with Technology Tools: Cases in Emergency Response

Information and Communications Technologies (ICTs), particularly social media and geographic information systems (GIS), have become a transformational force in emergency response. Social media enables ad hoc collaboration, providing timely, useful information dissemination and sharing, and helping to overcome limitations of time and place. Geographic information systems increase the level of situation awareness, serving geospatial data using interactive maps, animations, and computer generated imagery derived from sophisticated global remote sensing systems. Digital workspaces bring these technologies together and contribute to meeting ad hoc and formal emergency response challenges through their affordances of situation awareness and mass collaboration. Distributed ICTs that enable ad hoc emergency response via digital workspaces have arguably made traditional top-down system deployments less relevant in certain situations, including emergency response (Merrill, 2009; Heylighen, 2007a, b). Heylighen (2014, 2007a, b) theorizes that human cognitive stigmergy explains some self-organizing characteristics of ad hoc systems. Elliott (2007) identifies cognitive stigmergy as a factor in mass collaborations supported by digital workspaces. Stigmergy, a term from biology, refers to the phenomenon of self-organizing systems with agents that coordinate via perceived changes in the environment rather than direct communication. In the present research, ad hoc emergency response is examined through the lens of human cognitive stigmergy. The basic assertion is that ICTs and stigmergy together make possible highly effective ad hoc collaborations in circumstances where more typical collaborative methods break down. The research is organized into three essays: an in-depth analysis of the development and deployment of the Ushahidi emergency response software platform, a comparison of the emergency response ICTs used for emergency response during Hurricanes Katrina and Sandy, and a process model developed from the case studies and relevant academic literature is described

Identification of Prognostic Cancer Biomarkers through the Application of RNA-Seq Technologies and Bioinformatics

MicroRNAs (miRNAs) are short single-stranded RNAs that function as the guide sequence of the post-transcriptional regulatory process known as the RNA-induced silencing complex (RISC), which targets mRNA sequences for degradation through complementary binding to the guide miRNA. Changes in miRNA expression have been reported as correlated with numerous biological processes, including embryonic development, cellular differentiation, and disease manifestation. In the latter case, dysregulation has been observed in response to infection by human papillomavirus (HPV), which has also been established as both oncogenic in cervical cancers and oropharyngeal cancers and favorable for overall patient survival after tumor formation. The identification of dysregulated miRNAs associated with both HPV infection and cancer survival requires large datasets of high-throughput sequencing data, which were obtained through The Cancer Genome Atlas. By analyzing this public data, we have identified a series of proposed mechanisms for cancer formation and survival that is mediated through the miRNA-RISC regulatory mechanism in response to HPV infection. We have also identified a diverse set of miRNA biomarkers that have been incorporated into linear expression-based risk signatures that are prognostic for overall patient survival after tumor diagnosis in HPV-related cancers. The tools that were used to identify both miRNA biomarkers and proposed targets in public datasets, such as The Cancer Genome Atlas, have since been incorporated into an web-accessible resource, OncomiR.org, to streamline the process of biomarker identification for the cancer research community

AIUCD2016 - Book of Abstracts

Questo volume raccoglie gli abstract dei contributi accolti al convegno AIUCD 2016, dal titolo "Edizioni digitali: rappresentazione, interoperabilità, analisi del testo e infrastrutture" (Digital editions: representation, interoperability, text analysis and infrastructures). Si tratta del quinto convegno dell'Associazione di Informatica Umanistica e Cultura Digitale (AIUCD), tenutosi a Venezia dal 7 al 9 Settembre 2016, che è stato infatti dedicato alla rappresentazione e allo studio del testo sotto vari punti di vista (risorse, analisi, infrastrutture di pubblicazione), con lo scopo di far dialogare intorno al testo filologi, storici, umanisti digitali, linguisti computazionali, logici, informatici e ingegneri informatici. Il presente volume raccoglie dunque gli abstract dei soli interventi accettati al convegno, che hanno ottenuto il parere favorevole da parte di valutatori esperti della materia, attraverso un processo di revisione anonima sotto la responsabilità del Comitato Scientifico di AIUCD 2016

Emerging environmental contaminants and human health : risk assessment of dietary exposure to microplastics

Microplastics (MPs) are an emerging contaminant ubiquitous in the environment. There is growing concern regarding potential human health effects. A major human exposure route is hypothesised to be the dietary pathway via ingestion of contaminated food. A risk assessment perspective was employed, which is the standard approach for human health protection regarding food safety. It is comprised of the four interconnected evidence-based steps of hazard identification, hazard characterization, exposure assessment and risk characterization. Existing scientific data were collected via the execution of scoping, systematic and rapid reviews, using state of the art, robust methodology. Quantitative meta- analysis and meta-regression analyses were also employed. Two bespoke novel risk-of-bias tools were developed and implemented in the execution of the reviews for the standardized quality appraisal of the studies.Seventy-two studies were included in the systematic reviews on food contamination from three categories. The majority of the samples were contaminated in varying levels: 0-4889 MPs/L in drinking water, 0–10.5 MPs/g in seafood and 0–1674 MPs/kg in salt, thus establishing the dietary ingestion route for MP human exposures. According to the exposure assessment modelling, the estimated levels for MP dietary aggregate exposures could be as high as 3.6 million MPs per year.Seventeen studies were included in a rapid review focusing on human cell in vitro MP toxicological effects. Four biological endpoints displayed MP-associated effects: cytotoxicity, immune response, oxidative stress and barrier attributes. Irregular shape was found to be the only MP characteristic predicting cell death, along with the duration of exposure and MP concentration (μg/mL). Minimum concentrations of 10 μg/mL (5– 200 μm), had an adverse effect on cell viability, and 20 μg/mL (0.4 μm) on cytokine release, effectively constituting thresholds of adverse effects. The preliminary comparison of the levels of the thresholds and the exposures reveals that human health could be at risk due to MP dietary exposures.Further high-quality research using standardized methods is needed to cement the scientific evidence on MP contamination and human exposures. On the other hand, serious data gaps exist regarding toxicodynamics and toxicokinetics which are necessary for a complete toxicological profile

Understanding of the underlying resistance mechanism of the Kat-G protein against isoniazid in Mycobacterium tuberculosis using bioinformatics approaches

Tuberculosis (TB) is a multi-organ infection caused by rod-shaped acid-fast Mycobacterium tuberculosis. The World Health Organization (WHO) ranks TB among the top 10 fatal infections and the leading the cause of death from a single infection. In 2017, TB was responsible for an estimated 1.3 million deaths among both the HIV negative and positive populations worldwide (WHO, 2018). Approximately 23% (roughly 1.7 billion) of the world’s population is estimated to have latent TB with a high risk of reverting to active TB infection. In 2017, an estimated 558,000 people developed drug resistant TB worldwide with 82% of the cases being multi-drug resistant TB (WHO, 2018). South Africa is ranked among the 30 high TB burdened countries with a TB incidence of 322,000 cases in 2017 accounting for 3% of the world’s TB cases. TB is curable and is clinically managed through a combination of intensive and continuation phases of first-line drugs (isoniazid, rifampicin, ethambutol, and pyrazinamide). Second-line drugs which include fluoroquinolones, injectable aminoglycoside and injectable polypeptides are used in cases of first line drug resistance. The third-line drugs include amoxicillin, clofazimine, linezolid and imipenem. These have variable but unproven efficacy to TB and are the last resort in cases of total drug resistance (Jilani et al., 2019). TB drug resistance to first-line drugs especially isoniazid in M. tuberculosis has been attributed to single nucleotide polymorphisms (SNPs) in the catalase peroxidase enzyme (katG), a protein important in the activation of the pro-drug isoniazid. The SNPs especially at position 315 of the katG enzyme are believed to reduce the sensitivity of the M. tuberculosis to isoniazid while still maintaining the enzyme’s catalytic activity - a mechanism not completely understood. KatG protein is important for protecting the bacteria from hydro peroxides and hydroxyl radicals present in an aerobic environment. This study focused on understanding the mechanism of isoniazid drug resistance in M. tuberculosis as a result of high confidence mutations in the katG through modelling the enzyme with its respective variants, performing MD simulations to explore the protein behaviour, calculating the dynamic residue network analysis (DRN) of the variants in respect to the wild type katG and finally performing alanine scanning. From the MD simulations, it was observed that the high confidence mutations i.e. S140R, S140N, G279D, G285D, S315T, S315I, S315R, S315N, G316D, S457I and G593D were not only reducing the backbone flexibility of the protein but also reducing the protein’s conformational variation and space. All the variant protein structures were observed to be more compact compared to the wild type. Residue fluctuation results indicated reduced residue flexibility across all variants in the loop region (position 26-110) responsible for katG dimerization. In addition, mutation S315T is believed to reduce the size of the active site access channel in the protein. From the DRN data, residues in the interface region between the N and C-terminal domains were observed to gain importance in the variants irrespective of the mutation location indicating an allosteric effect of the mutations on the interface region. Alanine scanning results established that residue Leucine at position 48 was not only important in the protein communication but also a destabilizing residue across all the variants. The study not only demonstrated change in the protein behaviour but also showed allosteric effect of the mutations in the katG protein

AIUCD2016 - Book of Abstracts

Questo volume raccoglie gli abstract dei contributi accolti al convegno AIUCD 2016, dal titolo "Edizioni digitali: rappresentazione, interoperabilità, analisi del testo e infrastrutture" (Digital editions: representation, interoperability, text analysis and infrastructures). Si tratta del quinto convegno dell'Associazione di Informatica Umanistica e Cultura Digitale (AIUCD), tenutosi a Venezia dal 7 al 9 Settembre 2016, che è stato infatti dedicato alla rappresentazione e allo studio del testo sotto vari punti di vista (risorse, analisi, infrastrutture di pubblicazione), con lo scopo di far dialogare intorno al testo filologi, storici, umanisti digitali, linguisti computazionali, logici, informatici e ingegneri informatici. Il presente volume raccoglie dunque gli abstract dei soli interventi accettati al convegno, che hanno ottenuto il parere favorevole da parte di valutatori esperti della materia, attraverso un processo di revisione anonima sotto la responsabilità del Comitato Scientifico di AIUCD 2016