Wang Z.,Center for Bio Molecular Science and Engineering |
Malanoski A.P.,Center for Bio Molecular Science and Engineering |
Lin B.,Center for Bio Molecular Science and Engineering |
Long N.C.,Nova Research Inc. |
And 10 more authors.
Microbial Ecology | Year: 2010
Military recruits experience a high incidence of febrile respiratory illness (FRI), leading to significant morbidity and lost training time. Adenoviruses, group A Streptococcus pyogenes, and influenza virus are implicated in over half of the FRI cases reported at recruit training center clinics, while the etiology of the remaining cases is unclear. In this study, we explore the carriage rates and disease associations of adenovirus, enterovirus, rhinovirus, Streptococcus pneumoniae, Haemophilus influenzae, and Neisseria meningitidis in military recruits using high-density resequencing microarrays. The results showed that rhinoviruses, adenoviruses, S. pneumoniae, H. influenzae, and N. meningitidis were widely distributed in recruits. Of these five agents, only adenovirus showed significant correlation with illness. Among the samples tested, only pathogens associated with FRI, such as adenovirus 4 and enterovirus 68, revealed strong temporal and spatial clustering of specific strains, indicating that they are transmitted primarily within sites. The results showed a strong negative association between adenoviral FRI and the presence of rhinoviruses in recruits, suggesting some form of viral interference. © 2010 Springer Science+Business Media, LLC. Source
Abd Rahman S.,University of Queensland |
Schirra H.J.,University of Queensland |
Lichanska A.M.,University of Queensland |
Lichanska A.M.,Tessarae, Llc |
And 2 more authors.
Growth Hormone and IGF Research | Year: 2013
Objective: Growth hormone (GH) is a protein hormone with important roles in growth and metabolism. The objective of this study was to investigate the metabolism of a human subject with severe GH deficiency (GHD) due to a PIT-1 gene mutation and the metabolic effects of GH therapy using Nuclear Magnetic Resonance (NMR)-based metabonomics. NMR-based metabonomics is a platform that allows the metabolic profile of biological fluids such as urine to be recorded, and any alterations in the profile modulated by GH can potentially be detected. Design: Urine samples were collected from a female subject with severe GHD before, during and after GH therapy, and from healthy age- and sex-matched controls and analysed with NMR-based metabonomics. Setting: The samples were collected at a hospital and the study was performed at a research facility. Participants: We studied a 17. year old female adolescent with severe GHD secondary to PIT-1 gene mutation who had reached final adult height and who had ceased GH therapy for over 3. years. The subject was subsequently followed for 5. years with and without GH therapy. Twelve healthy age-matched female subjects acted as control subjects. Intervention: The GH-deficient subject re-commenced GH therapy at a dose of 1. mg/day to normalise serum IGF-1 levels. Main outcome measures: Urine metabolic profiles were recorded using NMR spectroscopy and analysed with multivariate statistics to distinguish the profiles at different time points and identify significant metabolites affected by GH therapy. Results: NMR-based metabonomics revealed that the metabolic profile of the GH-deficient subject altered with GH therapy and that her profile was different from healthy controls before, and during withdrawal of GH therapy. Conclusion: This study illustrates the potential use of NMR-based metabonomics for monitoring the effects of GH therapy on metabolism by profiling the urine of GH-deficient subjects. Further controlled studies in larger numbers of GH-deficient subjects are required to determine the clinical benefits of NMR-based metabonomics in subjects receiving GH therapy. © 2012 Elsevier Ltd. Source
Agency: Department of Agriculture | Branch: | Program: SBIR | Phase: Phase II | Award Amount: 460.00K | Year: 2011
The primary objectives of this Phase II project are to 1) validate performance of the prototype resequencing pathogen microarray application for detection and identification of selected food-borne pathogens, including varieties of viruses, bacteria and eukaryotic agents; 2) iterate and port the prototype application to a more practical, "market-friendly" product form factor that requires less expensive capital equipment to use, and that anticipates significantly lower operating cost per assay, without compromise of assay multiplicity, sensitivity or specificity; and 3) perform limited additional performance validation of the product application to enable initial commercial marketing to government and private sector, domestic and international laboratories that provide food-safety testing services.
Agency: Department of Agriculture | Branch: | Program: SBIR | Phase: Phase I | Award Amount: 89.65K | Year: 2010
National swine health statistics indicate a growing death rate due to respiratory disease in both the nursery and grower/finished phases in swine (Swine 2006, APHIS, USDA). In 2006, veterinary diagnostic testing revealed that Porcine Reproductive and Respiratory Syndrome was the most prevalent of the diagnosed diseases in breeding herd and nursery pigs (Swine 2006, APHIS, USDA). Additional diseases that contribute to the swine morbidity and mortality rate include Porcine Circovirus 2 associated diseases, swine influenza, foot and mouth disease, classic swine fever and swine vesicular disease. The proposed TessArray RPM assay is a simultaneously differential diagnosis platform for these and other targeted pathogens of the assay. The single test result can establish cause of infectious disease in individual animals as well as outbreaks of infectious disease in local herds or across swine production communities. No existing test other than RPM can enable rapid differential diagnosis, determine presence of multiple infectious agents co-infecting individual animals, or support epidemiological tracking in epidemic outbreaks to minimize effective response times.
Tessarae, Llc and The Regents Of The University Of California | Date: 2013-02-21
A robust, automated computational pipeline was used to design a system comprising a microarray for the identification of microorganisms and their antibiotic resistance profiles. This system and methods will facilitate the study of the epidemiology and microbial ecology of antibiotic resistance and be an invaluable tool to rapidly and simultaneously identify organisms and their antimicrobial resistance elements in environmental, food and clinical samples.