Cyanide poisoning in cattle from Dysphania glomulifera (red crumbweed): Using the internet for rapid plant identification and diagnostic advice: Case Report

A 300-strong Angus-Brahman cattle herd near Springsure, central Queensland, was being fed Acacia shirleyi (lancewood) browse during drought and crossed a 5-hectare, previously burnt area with an almost pure growth of Dysphania glomulifera subspecies glomulifera (red crumbweed) on their way to drinking water. Forty cows died of cyanide poisoning over 2 days before further access to the plant was prevented. A digital image of a plant specimen made on a flat-bed scanner and transmitted by email was used to identify D glomulifera. Specific advice on the plant's poisonous properties and management of the case was then provided by email within 2 hours of an initial telephone call by the field veterinarian to the laboratory some 600 km away. The conventional method using physical transport of a pressed dried plant specimen to confirm the identification took 5 days. D glomulifera was identified in the rumen of one of two cows necropsied. The cyanogenic potential of D glomulifera measured 4 days after collection from the site of cattle deaths was 18,600 mg HCN/kg in dry matter. The lethal dose of D glomulifera for a 420 kg cow was estimated as 150 to 190 g wet weight. The plant also contained 4.8% KNO3 equivalent in dry matter, but nitrate-nitrite poisoning was not involved in the deaths.

Complete and interpretable conformance checking of business processes

This article presents a method for checking the conformance between an event log capturing the actual execution of a business process, and a model capturing its expected or normative execution. Given a business process model and an event log, the method returns a set of statements in natural language describing the behavior allowed by the process model but not observed in the log and vice versa. The method relies on a unified representation of process models and event logs based on a well-known model of concurrency, namely event structures. Specifically, the problem of conformance checking is approached by folding the input event log into an event structure, unfolding the process model into another event structure, and comparing the two event structures via an error-correcting synchronized product. Each behavioral difference detected in the synchronized product is then verbalized as a natural language statement. An empirical evaluation shows that the proposed method scales up to real-life datasets while producing more concise and higher-level difference descriptions than state-of-the-art conformance checking methods.

Enhanced diagnostic platforms for Post Entry Quarantine (PEQ)

Enhanced diagnostic platforms for Post Entry Quarantine (PEQ) and market access (Phase 1).

CRC27012 A National Diagnostic Database for Emergency Plant Pests

Development of a national diagnostic database for Emergency Plant Pests which will be web-accessible.

Diagnostic Agronomy

Develop and implement a diagnostic framework designed to help advisors and farmers identify the causes of poor crop performance and implement appropriate remedial measures.

CRC20093 Increasing Diagnostic Capacity in Thailand

Accurate identification of pests is essential for practically all aspects of agricultural development and is critical to the operations of biosecurity that safeguard agricultural integrity and facilitate trade. Diagnostic capability is at the forefront of and complementary to, activities such as border protection, incursion management, surveillance and pest and disease certification. The efficiency of a biosecurity system therefore depends largely on the feedback between these activities and diagnostics. Australian scientists will train Thai scientists in diagnostics and surveillance to provide the Thai DOA with skills that will aid in the development of a Thai Diagnostic Network. The skills will be taught using a range of pests, including some which have particular biosecurity importance for both Australia and Thailand such as citrus canker, potato viruses and fruit flies.

CRC20080 Diagnostic technologies for phosphine resistance management

Development of molecular markers for rapid diagnosis of phosphine resistance in insects.

The current status of heart failure diagnostic biomarkers

Heart failure (HF) affects approximately 23 million individuals worldwide and this number is increasing, due to an aging and growing population. Early detection of HF is crucial in the management of this debilitating disease. Current diagnostic methods for HF rely heavily on clinical imaging techniques and blood analysis, which makes them less than ideal for population-based screening purposes. Studies focusing on developing novel biomarkers for HF have utilized various techniques and biological fluids, including urine and saliva. Promising results from these studies imply that these body fluids can be used in evaluating the clinical manifestation of HF and will one day be integrated into a clinical workflow and facilitate HF management.

Diagnostic Molecular Markers for Phosphine Resistance in U.S. Populations of Tribolium castaneum and Rhyzopertha dominica

Stored product beetles that are resistant to the fumigant pesticide phosphine (hydrogen phosphide) gas have been reported for more than 40 years in many places worldwide. Traditionally, determination of phosphine resistance in stored product beetles is based on a discriminating dose bioassay that can take up to two weeks to evaluate. We developed a diagnostic cleaved amplified polymorphic sequence method, CAPS, to detect individuals with alleles for strong resistance to phosphine in populations of the red flour beetle, Tribolium castaneum, and the lesser grain borer, Rhyzopertha dominica, according to a single nucleotide mutation in the dihydrolipoamide dehydrogenase (DLD) gene. We initially isolated and sequenced the DLD genes from susceptible and strongly resistant populations of both species. The corresponding amino acid sequences were then deduced. A single amino acid mutation in DLD in populations of T.castaneum and R.dominica with strong resistance was identified as P45S in T.castaneum and P49S in R.dominica, both collected from northern Oklahoma, USA. PCR products containing these mutations were digested by the restriction enzymes MboI and BstNI, which revealed presence or absence, respectively of the resistant (R) allele and allowed inference of genotypes with that allele. Seven populations of T.castaneum from Kansas were subjected to discriminating dose bioassays for the weak and strong resistance phenotypes. Application of CAPS to these seven populations confirmed the R allele was in high frequency in the strongly resistant populations, and was absent or at a lower frequency in populations with weak resistance, which suggests that these populations with a low frequency of the R allele have the potential for selection of the strong resistance phenotype. CAPS markers for strong phosphine resistance will help to detect and confirm resistant beetles and can facilitate resistance management actions against a given pest population.

Investigation of an emerging bacterial disease in wild Queensland groper, marine fish and stingrays with production of diagnostic tools to reduce the spread of disease to other states of Australia : final report

This project describes how Streptococcus agalactiae can be transmitted experimentally in Queensland grouper. The implications of this research furthers the relatedness between Australian S. agalactiae strains from animals and humans. Additionally, this research has developed diagnostic tools for Australian State Veterinary Laboratories and Universities, which will assist in State and National aquatic animal disease detection, surveillance, disease monitoring and reporting

Diagnostic values for skin temperature assessment to detect diabetes-related foot complications

Background Skin temperature assessment is a promising modality for early detection of diabetic foot problems, but its diagnostic value has not been studied. Our aims were to investigate the diagnostic value of different cutoff skin temperature values for detecting diabetes-related foot complications such as ulceration, infection, and Charcot foot and to determine urgency of treatment in case of diagnosed infection or a red-hot swollen foot. Materials and Methods The plantar foot surfaces of 54 patients with diabetes visiting the outpatient foot clinic were imaged with an infrared camera. Nine patients had complications requiring immediate treatment, 25 patients had complications requiring non-immediate treatment, and 20 patients had no complications requiring treatment. Average pixel temperature was calculated for six predefined spots and for the whole foot. We calculated the area under the receiver operating characteristic curve for different cutoff skin temperature values using clinical assessment as reference and defined the sensitivity and specificity for the most optimal cutoff temperature value. Mean temperature difference between feet was analyzed using the Kruskal–Wallis tests. Results The most optimal cutoff skin temperature value for detection of diabetes-related foot complications was a 2.2°C difference between contralateral spots (sensitivity, 76%; specificity, 40%). The most optimal cutoff skin temperature value for determining urgency of treatment was a 1.35°C difference between the mean temperature of the left and right foot (sensitivity, 89%; specificity, 78%). Conclusions Detection of diabetes-related foot complications based on local skin temperature assessment is hindered by low diagnostic values. Mean temperature difference between two feet may be an adequate marker for determining urgency of treatment.

Formal network behaviour analysis using model checking

In this research we modelled computer network devices to ensure their communication behaviours meet various network standards. By modelling devices as finite-state machines and examining their properties in a range of configurations, we discovered a flaw in a common network protocol and produced a technique to improve organisations' network security against data theft.

Characterization of genomic diversity in extraintestinal pathogenic Escherichia coli (ExPEC) and development of a diagnostic DNA microarray for the differentiation of ExPEC isolates causing urinary tract infections

Extraintestinal pathogenic Escherichia coli (ExPEC) represent a diverse group of strains of E. coli, which infect extraintestinal sites, such as the urinary tract, the bloodstream, the meninges, the peritoneal cavity, and the lungs. Urinary tract infections (UTIs) caused by uropathogenic E. coli (UPEC), the major subgroup of ExPEC, are among the most prevalent microbial diseases world wide and a substantial burden for public health care systems. UTIs are responsible for serious morbidity and mortality in the elderly, in young children, and in immune-compromised and hospitalized patients. ExPEC strains are different, both from genetic and clinical perspectives, from commensal E. coli strains belonging to the normal intestinal flora and from intestinal pathogenic E. coli strains causing diarrhea. ExPEC strains are characterized by a broad range of alternate virulence factors, such as adhesins, toxins, and iron accumulation systems. Unlike diarrheagenic E. coli, whose distinctive virulence determinants evoke characteristic diarrheagenic symptoms and signs, ExPEC strains are exceedingly heterogeneous and are known to possess no specific virulence factors or a set of factors, which are obligatory for the infection of a certain extraintestinal site (e. g. the urinary tract). The ExPEC genomes are highly diverse mosaic structures in permanent flux. These strains have obtained a significant amount of DNA (predictably up to 25% of the genomes) through acquisition of foreign DNA from diverse related or non-related donor species by lateral transfer of mobile genetic elements, including pathogenicity islands (PAIs), plasmids, phages, transposons, and insertion elements. The ability of ExPEC strains to cause disease is mainly derived from this horizontally acquired gene pool; the extragenous DNA facilitates rapid adaptation of the pathogen to changing conditions and hence the extent of the spectrum of sites that can be infected. However, neither the amount of unique DNA in different ExPEC strains (or UPEC strains) nor the mechanisms lying behind the observed genomic mobility are known. Due to this extreme heterogeneity of the UPEC and ExPEC populations in general, the routine surveillance of ExPEC is exceedingly difficult. In this project, we presented a novel virulence gene algorithm (VGA) for the estimation of the extraintestinal virulence potential (VP, pathogenicity risk) of clinically relevant ExPECs and fecal E. coli isolates. The VGA was based on a DNA microarray specific for the ExPEC phenotype (ExPEC pathoarray). This array contained 77 DNA probes homologous with known (e.g. adhesion factors, iron accumulation systems, and toxins) and putative (e.g. genes predictably involved in adhesion, iron uptake, or in metabolic functions) ExPEC virulence determinants. In total, 25 of DNA probes homologous with known virulence factors and 36 of DNA probes representing putative extraintestinal virulence determinants were found at significantly higher frequency in virulent ExPEC isolates than in commensal E. coli strains. We showed that the ExPEC pathoarray and the VGA could be readily used for the differentiation of highly virulent ExPECs both from less virulent ExPEC clones and from commensal E. coli strains as well. Implementing the VGA in a group of unknown ExPECs (n=53) and fecal E. coli isolates (n=37), 83% of strains were correctly identified as extraintestinal virulent or commensal E. coli. Conversely, 15% of clinical ExPECs and 19% of fecal E. coli strains failed to raster into their respective pathogenic and non-pathogenic groups. Clinical data and virulence gene profiles of these strains warranted the estimated VPs; UPEC strains with atypically low risk-ratios were largely isolated from patients with certain medical history, including diabetes mellitus or catheterization, or from elderly patients. In addition, fecal E. coli strains with VPs characteristic for ExPEC were shown to represent the diagnostically important fraction of resident strains of the gut flora with a high potential of causing extraintestinal infections. Interestingly, a large fraction of DNA probes associated with the ExPEC phenotype corresponded to novel DNA sequences without any known function in UTIs and thus represented new genetic markers for the extraintestinal virulence. These DNA probes included unknown DNA sequences originating from the genomic subtractions of four clinical ExPEC isolates as well as from five novel cosmid sequences identified in the UPEC strains HE300 and JS299. The characterized cosmid sequences (pJS332, pJS448, pJS666, pJS700, and pJS706) revealed complex modular DNA structures with known and unknown DNA fragments arranged in a puzzle-like manner and integrated into the common E. coli genomic backbone. Furthermore, cosmid pJS332 of the UPEC strain HE300, which carried a chromosomal virulence gene cluster (iroBCDEN) encoding the salmochelin siderophore system, was shown to be part of a transmissible plasmid of Salmonella enterica. Taken together, the results of this project pointed towards the assumptions that first, (i) homologous recombination, even within coding genes, contributes to the observed mosaicism of ExPEC genomes and secondly, (ii) besides en block transfer of large DNA regions (e.g. chromosomal PAIs) also rearrangements of small DNA modules provide a means of genomic plasticity. The data presented in this project supplemented previous whole genome sequencing projects of E. coli and indicated that each E. coli genome displays a unique assemblage of individual mosaic structures, which enable these strains to successfully colonize and infect different anatomical sites.