24 research outputs found
Genome-guided bioprospecting for novel antibiotic lead compounds.
Antimicrobial resistance continues to pose a threat to health and wellbeing. Unmitigated, it is predicted to be the leading cause of death by 2050. Hence, the sustained development of novel antibiotics is crucial. As over 60% of licensed antibiotics are based on scaffolds derived from less than 1% of all known bacterial species, bacterial secondary metabolites constitute an untapped source of novel antibiotics. The aim of this project therefore was to expand the chemical space of bacteria-derived antibiotic lead compounds, using genomics approach. To that end, a topsoil sample was collected from the rhizosphere in which antibiosis occurs naturally. Using starvation stress, sixty-five isolates were recovered from the sample, out of which four were selected based on morphology and designated A13BB, A23BA, A13AA and A23AA. A13BB was identified by 16S rRNA gene sequence comparison as a Pseudomonas spp. and the other three isolates as Hafnia/Obesumbacterium spp. A database search showed that species belonging to these genera have genomes larger than the 3 Mb size above which an increasing proportion of a bacterial genome is dedicated to secondary metabolism. Given their ecological origin, expected genome size and ability to withstand starvation stress, these four isolates were presumed to harbour antibiotic-encoding gene clusters. Isolates A13BB and A23BA were therefore selected for genome mining in the first instance. Illumina and GridION/MinION sequencing data were obtained for both isolates and assembled into high-quality genomes. Isolates' identities were confirmed by FastANI analysis as strains of P. fragi and H. alvei, with 4.94 and 4.77 Mb genomes, respectively. Assembled genomes were mined with antiSMASH. Amongst other secondary metabolite biosynthetic gene clusters (smBGCs) detected, the β-lactone smBGCs in both genomes were selected for activation as their end products bear the hallmarks of an 'ideal antibiotic' that can inhibit several bacteria-specific enzymes simultaneously. Analysis of these smBGCs revealed genes encoding two core enzymes: 2-isopropylmalate synthase (2-IPMS) and acyl CoA ligase homologues. In the biosynthetic pathway, 2-IPMS catalyses the condensation of acetyl CoA with the degradation product of valine or isoleucine to form 2-IPM. 2-IPM is isomerised to 3-IPM which then forms the β-lactone warhead through reactions catalysed by acyl CoA ligase. It was speculated that the β-lactone compound is biosynthesised to efficiently rid the organism of potentially harmful metabolic intermediates as it grows on poor carbon and nitrogen sources. Strain fermentation was therefore performed with 10.8 mM acetate as the main carbon source, and 5 mM L-valine or L-isoleucine as the nitrogen source. Fermentation extracts were analysed by LC-MS with at least thirty-seven metabolite ions detected. Many of these ions have masses in the range m/z 230-750, which is an ideal mass range for antibiotic molecules. As β-lactone compounds are difficult to identify in crude extracts, especially when utilising single-stage mass spectrometry, reactivity-guided screening of extracts with cysteine thiol probe was performed as the probe forms UV- and MS-visible adducts with β-lactone compounds. However, complete dimerization of probe at a faster-than-expected rate in extract matrices hindered successful screening. This meant that it was not possible to determine if any crude extract components were β-lactone compounds without further analysis. Measures to limit or eliminate probe dimerization are proposed, together with molecular networking strategies that can afford global visualisation and rapid dereplication of extract components, using tandem mass spectrometry fragmentation patterns of parent ions. This project provides an original and robust workflow that serves as a strong starting point in the isolation of novel β-lactone compounds from crude extracts, followed by structural optimisation and bioactivity profiling. The hitherto unrecognised potential of β-lactone natural compounds as 'ideal antibiotics' is highlighted, and several structural optimisation strategies required to harness this potential are proposed. The genomes assembled here, and associated data have been deposited in the repositories of the International Nucleotide Sequence Database Collaboration for repurposing by other researchers. Likewise, the hidden metabolic and biosynthetic potentials of P. fragi and H. alvei species uncovered by RASTtk and antiSMASH analyses have been catalogued and placed in the public domain, with many of these attributes reported for the first time
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Exploring a capability-demand interaction model for inclusive design evaluation
Designers are required to evaluate their designs against the needs and capabilities of their target user groups in order to achieve successful, inclusive products. This dissertation presents exploratory research into the specific problem of supporting analytical design evaluation for Inclusive Design. The analytical evaluation process involves evaluating products with user data rather than testing with actual users. The work focuses on the exploration of a capability-demand model of product interaction as the basis for analytical inclusive evaluation. This model suggests that by comparing the measured sensory, cognitive and motor capabilities of a user population to the corresponding product demands, the degree of fit between users and products can be assessed.
The research problem was addressed by firstly examining theories of human function and performance together with existing sources of user capability data. It was found that user capability data was fragmented and lacking in terms of predicting design exclusion and difficulty at the population level. More fundamentally, however, it was found that the relationships between measured capability in populations with low functional capacity and real world task performance with products (such as errors, times and difficulty) were not well understood. Given that an understanding of these relationships are necessary to guide capability data collection and to drive valid and robust analytical evaluation methods, the research effort focused on exploring these relationships via empirical and analytical studies.
The research process culminated in an experimental study with nineteen users of various functional capability profiles performing tasks with four consumer products (a clock radio, a mobile phone, a blender and a vacuum cleaner). Measures of user capability were related to corresponding product demands (on those capabilities) and task outcome measures. A complex picture emerged, where linear relationships did not generally account for significant variance in task outcome measures. Further, it appeared that multiple capabilities were possibly interacting in unknown ways to support real world interaction. These indicative results point to the further investigation of multivariate and non-linear models for describing capability-demand relationships, and also the replication of similar studies with larger sample sizes to confirm the relationships observed. The resulting overall recommendation, therefore, is that there is a need to direct research efforts in this critical but largely unexplored area of capability-demand model building for Inclusive Design evaluation
Personalizing online reviews for better customer decision making
Online consumer reviews have become an important source of information for understanding
markets and customer preferences. When making purchase decisions, customers
increasingly rely on user-generated online reviews; some even consider the information
in online reviews more credible and trustworthy than information provided
by vendors. Many studies have revealed that online reviews influence demand and
sales. Others have shown the possibility of identifying customer interest in product
attributes. However, little work has been done to address customer and review diversity
in the process of examining reviews. This research intends to answer the research
question: how can we solve the problem of customer and review diversity in the context
of online reviews to recommend useful reviews based on customer preferences and
improve product recommendation? Our approach to the question is through personalization.
Similar to other personalization research, we use an attribute-based model
to represent products and customer preferences. Unlike existing personalization research
that uses a set of pre-defined product attributes, we explore the possibility of a
data-driven approach for identifying more comprehensive product attributes from online
reviews to model products and customer preferences. Specifically, we introduce
a new topic model for product attribute identification and sentiment analysis. By
differentiating word co-occurrences at the sentence level from at the document level,
the model better identifies interpretable topics. The use of an inference network with
shared structure enables the model to predict product attribute ratings accurately.
Based on this topic model, we develop attribute-based representations of products,
reviews and customer preferences and use them to construct the personalization of online reviews. We examine personalization from the lens of consumer search theory
and human information processing theory and test the hypotheses with an experiment.
The personalization of online reviews can 1) recommend products matching
customer's preferences; 2) improve custom's intention towards recommended products;
3) best distinguish recommended products from products that do not match
customer's preferences; and 4) reduce decision effort
Proceedings, MSVSCC 2015
The Virginia Modeling, Analysis and Simulation Center (VMASC) of Old Dominion University hosted the 2015 Modeling, Simulation, & Visualization Student capstone Conference on April 16th. The Capstone Conference features students in Modeling and Simulation, undergraduates and graduate degree programs, and fields from many colleges and/or universities. Students present their research to an audience of fellow students, faculty, judges, and other distinguished guests. For the students, these presentations afford them the opportunity to impart their innovative research to members of the M&S community from academic, industry, and government backgrounds. Also participating in the conference are faculty and judges who have volunteered their time to impart direct support to their students’ research, facilitate the various conference tracks, serve as judges for each of the tracks, and provide overall assistance to this conference. 2015 marks the ninth year of the VMASC Capstone Conference for Modeling, Simulation and Visualization. This year our conference attracted a number of fine student written papers and presentations, resulting in a total of 51 research works that were presented. This year’s conference had record attendance thanks to the support from the various different departments at Old Dominion University, other local Universities, and the United States Military Academy, at West Point. We greatly appreciated all of the work and energy that has gone into this year’s conference, it truly was a highly collaborative effort that has resulted in a very successful symposium for the M&S community and all of those involved. Below you will find a brief summary of the best papers and best presentations with some simple statistics of the overall conference contribution. Followed by that is a table of contents that breaks down by conference track category with a copy of each included body of work. Thank you again for your time and your contribution as this conference is designed to continuously evolve and adapt to better suit the authors and M&S supporters.
Dr.Yuzhong Shen Graduate Program Director, MSVE Capstone Conference Chair
John ShullGraduate Student, MSVE Capstone Conference Student Chai
Advancement in Dietary Assessment and Self-Monitoring Using Technology
Although methods to assess or self-monitor intake may be considered similar, the intended function of each is quite distinct. For the assessment of dietary intake, methods aim to measure food and nutrient intake and/or to derive dietary patterns for determining diet-disease relationships, population surveillance or the effectiveness of interventions. In comparison, dietary self-monitoring primarily aims to create awareness of and reinforce individual eating behaviours, in addition to tracking foods consumed. Advancements in the capabilities of technologies, such as smartphones and wearable devices, have enhanced the collection, analysis and interpretation of dietary intake data in both contexts. This Special Issue invites submissions on the use of novel technology-based approaches for the assessment of food and/or nutrient intake and for self-monitoring eating behaviours. Submissions may document any part of the development and evaluation of the technology-based approaches. Examples may include: web adaption of existing dietary assessment or self-monitoring tools (e.g., food frequency questionnaires, screeners) image-based or image-assisted methods mobile/smartphone applications for capturing intake for assessment or self-monitoring wearable cameras to record dietary intake or eating behaviours body sensors to measure eating behaviours and/or dietary intake use of technology-based methods to complement aspects of traditional dietary assessment or self-monitoring, such as portion size estimation
Customer Relationship Management : Concept, Strategy, and Tools -3/E
Customer relationship management
(CRM) as a strategy and as a technology
has gone through an amazing evolutionary
journey. After the initial technological
approaches, this process has matured considerably – both from a conceptual and
from an applications point of view. Of
course this evolution continues, especially
in the light of the digital transformation.
Today, CRM refers to a strategy, a set of
tactics, and a technology that has become
indispensable in the modern economy.
Based on both authors’ rich academic and
managerial experience, this book gives a
unified treatment of the strategic and
tactical aspects of customer relationship
management as we know it today. It
stresses developing an understanding of
economic customer value as the guiding
concept for marketing decisions. The goal
of this book is to be a comprehensive and
up-to-date learning companion for
advanced undergraduate students, master
students, and executives who want a
detailed and conceptually sound insight
into the field of CRM