Preference for and performance of some Australian native plants grown as hedges

Indigenous and other native plants are commonly restricted to informal or naturalistic designed landscapes. This research project investigates the use of native plants as a formal landscape element – the hedge. A multidisciplinary approach was used with distinct horticultural and social science components. The first study explored the response of 14 native and one exotic species to hedging every 4 months. Digital imaging techniques were used to measure changes in growth, density and canopy distribution. All species responded well to hedging, greatly increasing in density. Significant differences in growth rates and shoot regrowth patterns were recorded between the species. Some hedges grown from genetically diverse plant material had noticeable morphological variations and would be more suited to use as informal hedges, however growth rates were found to be a much better predictor of hedging performance than genetic uniformity. A second study explored gardeners’ (n=162) preference for these native hedges. Photomontages were created of the hedges grown in the horticultural experiment and a photo-questionnaire distributed to several groups of gardeners. The preference results showed that many gardeners did like some Australian plants used as hedges. Significant differences in preference were found between species. A principal components analysis found that factors positively affecting preference for hedges included neatness, foliage colour (green and grey), presence of flowers and the absence of visible woody stems. In general, genetically diverse hedges were slightly less preferred than genetically uniform hedges, but some genetically diverse hedges were highly preferred. Personal style preferences based on gardeners’ expressed gardening behaviour were also observed, with grey and softer hedges preferred by those participants with low-maintenance, drought tolerant or native gardens.     

Three‐dimensional T1‐weighted gradient echo is a suitable alternative to two‐dimensional T1‐weighted spin echo for imaging the canine brain

Volumetric imaging (VOL), a three‐dimensional magnetic resonance imaging (MRI) technique, has been described in the literature for evaluation of the human brain. It offers several advantages over conventional two‐dimensional (2D) spin echo (SE), allowing rapid, whole‐brain, isotropic imaging with submillimeter voxels. This retrospective, observational study compares the use of 2D T1‐weighted SE (T1W SE), with T1W VOL, for the evaluation of dogs with clinical signs of intracranial disease. Brain MRI images from 160 dogs who had T1W SE and T1W VOL sequences acquired pre‐ and postcontrast, were reviewed for presence and characteristics of intracranial lesions. Twenty‐nine of 160 patients were found to have intracranial lesions, all visible on both sequences. Significantly better grey‐white matter (GWM) differentiation was identified with T1W VOL (P < .001), with fair agreement between the two sequences (weighted κ = 0.35). Excluding a mild reduction in lesion intensity in three dogs precontrast on the T1W VOL images compared to T1W SE, and meningeal enhancement noted on the T1W VOL images in one dog, not identified on T1W SE, there was otherwise complete agreement between the two sequences. The T1W VOL sequence provided equivalent lesion evaluation and significantly improved GWM differentiation. Images acquired were of comparable diagnostic quality to those produced using a conventional T1W SE technique, for assessment of lesion appearance, number, location, mass effect, and postcontrast enhancement. T1W VOL, therefore, provides a suitable alternative T1W sequence for canine brain evaluation and can facilitate a reduction in total image acquisition time.     

Spatial epidemiological approaches to inform leptospirosis surveillance and control: A systematic review and critical appraisal of methods

Leptospirosis is a global zoonotic disease that the transmission is driven by complex geographical and temporal variation in demographics, animal hosts and socioecological factors. This results in complex challenges for the identification of high‐risk areas. Spatial and temporal epidemiological tools could be used to support leptospirosis control programs, but the adequacy of its application has not been evaluated. We searched literature in six databases including PubMed, Web of Science, EMBASE, Scopus, SciELO and Zoological Record to systematically review and critically assess the use of spatial and temporal analytical tools for leptospirosis and to provide general framework for its application in future studies. We reviewed 115 articles published between 1930 and October 2018 from 41 different countries. Of these, 65 (56.52%) articles were on human leptospirosis, 39 (33.91%) on animal leptospirosis and 11 (9.5%) used data from both human and animal leptospirosis. Spatial analytical (n = 106) tools were used to describe the distribution of incidence/prevalence at various geographical scales (96.5%) and to explored spatial patterns to detect clustering and hot spots (33%). A total of 51 studies modelled the relationships of various variables on the risk of human (n = 31), animal (n = 17) and both human and animal infection (n = 3). Among those modelling studies, few studies had generated spatially structured models and predictive maps of human (n = 2/31) and animal leptospirosis (n = 1/17). In addition, nine studies applied time‐series analytical tools to predict leptospirosis incidence. Spatial and temporal analytical tools have been greatly utilized to improve our understanding on leptospirosis epidemiology. Yet the quality of the epidemiological data, the selection of covariates and spatial analytical techniques should be carefully considered in future studies to improve usefulness of evidence as tools to support leptospirosis control. A general framework for the application of spatial analytical tools for leptospirosis was proposed.     

Standing in the canine precision medicine knowledge gap: Improving annotation of canine cancer genomic biomarkers through systematic comparative analysis of human cancer mutations in COSMIC

The accrual of cancer mutation data and related functional and clinical associations have revolutionised human oncology, enabling the advancement of precision medicine and biomarker-guided clinical management. The catalogue of cancer mutations is also growing in canine cancers. However, without direct high-powered functional data in dogs, it remains challenging to interpret and utilise them in research and clinical settings. It is well-recognised that canine and human cancers share genetic, molecular and phenotypic similarities. Therefore, leveraging the massive wealth of human mutation data may help advance canine oncology. Here, we present a structured analysis of sequence conservation and conversion of human mutations to the canine genome through a ‘caninisation’ process. We applied this analysis to COSMIC, the Catalogue of Somatic Mutations in Cancer, the most prominent human cancer mutation database. For the project's initial phase, we focused on the subset of the COSMIC data corresponding to Cancer Gene Census (CGC) genes. A total of 670 canine orthologs were found for 721 CGC genes. In these genes, 365 K unique mutations across 160 tumour types were converted successfully to canine coordinates. We identified shared putative cancer-driving mutations, including pathogenic and hotspot mutations and mutations bearing similar biomarker associations with diagnostic, prognostic and therapeutic utility. Thus, this structured caninisation of human cancer mutations facilitates the interpretation and annotation of canine mutations and helps bridge the knowledge gap to enable canine precision medicine.