Backyard poultry cases in UK small animal practices: Demographics, health conditions and pharmaceutical prescriptions.

BACKGROUND: Backyard poultry ownership is of keen interest in the United Kingdom. However, despite this, little is known about veterinary care engagement and outcomes of visits in this group of species. METHODS: This study described and characterised veterinary practice-visiting backyard poultry, utilising electronic health record data supplied by veterinary practices voluntarily participating in the Small Animal Veterinary Surveillance Network between 1st April 2014 and 31st March 2019. RESULTS: In total, 4424 recorded poultry consultations originating from 197 veterinary practices (352 sites) were summarised. Chicken consultation (n = 3740) peak incidence was in early summer (April-June), relative to all recorded species. More chickens resided in rural (incident rate ratio = 2.5, confidence interval [CI] 2.3-2.6, p <0.001) or less deprived areas. Non-specific clinical signs were commonly recorded (17.6% of chicken consultations, CI 15.9-19.2), as were those indicative of advanced disease. This latter finding was reflected in prescribed management strategies, with euthanasia comprising 29.8% (CI 27.0-32.6) of consultations. Antimicrobials were commonly prescribed (33.0% of consultations, CI 29.8-36.2), 43.8% of which included antimicrobials considered 'highest priority critically important' by the World Health Organisation. CONCLUSION: Our findings indicate a need to tailor antimicrobial prescription guidance to the backyard poultry setting. In addition, late presentation of disease, vague clinical descriptions in clinical narratives and high euthanasia rates show that disease identification, management and knowledge of poultry health and welfare among owners and veterinary surgeons can be improved.

Exploring semantic deep learning for building reliable and reusable one health knowledge from PubMed systematic reviews and veterinary clinical notes.

BACKGROUND: Deep Learning opens up opportunities for routinely scanning large bodies of biomedical literature and clinical narratives to represent the meaning of biomedical and clinical terms. However, the validation and integration of this knowledge on a scale requires cross checking with ground truths (i.e. evidence-based resources) that are unavailable in an actionable or computable form. In this paper we explore how to turn information about diagnoses, prognoses, therapies and other clinical concepts into computable knowledge using free-text data about human and animal health. We used a Semantic Deep Learning approach that combines the Semantic Web technologies and Deep Learning to acquire and validate knowledge about 11 well-known medical conditions mined from two sets of unstructured free-text data: 300 K PubMed Systematic Review articles (the PMSB dataset) and 2.5 M veterinary clinical notes (the VetCN dataset). For each target condition we obtained 20 related clinical concepts using two deep learning methods applied separately on the two datasets, resulting in 880 term pairs (target term, candidate term). Each concept, represented by an n-gram, is mapped to UMLS using MetaMap; we also developed a bespoke method for mapping short forms (e.g. abbreviations and acronyms). Existing ontologies were used to formally represent associations. We also create ontological modules and illustrate how the extracted knowledge can be queried. The evaluation was performed using the content within BMJ Best Practice. RESULTS: MetaMap achieves an F measure of 88% (precision 85%, recall 91%) when applied directly to the total of 613 unique candidate terms for the 880 term pairs. When the processing of short forms is included, MetaMap achieves an F measure of 94% (precision 92%, recall 96%). Validation of the term pairs with BMJ Best Practice yields precision between 98 and 99%. CONCLUSIONS: The Semantic Deep Learning approach can transform neural embeddings built from unstructured free-text data into reliable and reusable One Health knowledge using ontologies and content from BMJ Best Practice.

Demographics of dogs, cats, and rabbits attending veterinary practices in Great Britain as recorded in their electronic health records.

BACKGROUND: Understanding the distribution and determinants of disease in animal populations must be underpinned by knowledge of animal demographics. For companion animals, these data have been difficult to collect because of the distributed nature of the companion animal veterinary industry. Here we describe key demographic features of a large veterinary-visiting pet population in Great Britain as recorded in electronic health records, and explore the association between a range of animal's characteristics and socioeconomic factors. RESULTS: Electronic health records were captured by the Small Animal Veterinary Surveillance Network (SAVSNET), from 143 practices (329 sites) in Great Britain. Mixed logistic regression models were used to assess the association between socioeconomic factors and species and breed ownership, and preventative health care interventions. Dogs made up 64.8% of the veterinary-visiting population, with cats, rabbits and other species making up 30.3, 2.0 and 1.6% respectively. Compared to cats, dogs and rabbits were more likely to be purebred and younger. Neutering was more common in cats (77.0%) compared to dogs (57.1%) and rabbits (45.8%). The insurance and microchipping relative frequency was highest in dogs (27.9 and 53.1%, respectively). Dogs in the veterinary-visiting population belonging to owners living in least-deprived areas of Great Britain were more likely to be purebred, neutered, insured and microchipped. The same association was found for cats in England and for certain parameters in Wales and Scotland. CONCLUSIONS: The differences we observed within these populations are likely to impact on the clinical diseases observed within individual veterinary practices that care for them. Based on this descriptive study, there is an indication that the population structures of companion animals co-vary with human and environmental factors such as the predicted socioeconomic level linked to the owner's address. This 'co-demographic' information suggests that further studies of the relationship between human demographics and pet ownership are warranted.

The human squamous oesophagus has widespread capacity for clonal expansion from cells at diverse stages of differentiation.

OBJECTIVE: Knowledge of the cellular mechanisms involved in homeostasis of human squamous oesophagus in the steady state and following chronic injury is limited. We aimed to better understand these mechanisms by using a functional 3D approach. DESIGN: Proliferation, mitosis and the expression of progenitor lineage markers were assessed in normal squamous oesophagus from 10 patients by immunofluorescence on 3D epithelial whole mounts. Cells expressing differential levels of epithelial and progenitor markers were isolated using flow cytometry sorting and characterised by qPCR and IF. Their self-renewing potential was investigated by colony forming cells assays and in vitro organotypic culture models. RESULTS: Proliferation and mitotic activity was highest in the interpapillary basal layer and decreased linearly towards the tip of the papilla (p<0.0001). The orientation of mitosis was random throughout the basal layer, and asymmetric divisions were not restricted to specific cell compartments. Cells sorted into distinct populations based on the expression of epithelial and progenitor cell markers (CD34 and EpCAM) showed no difference in self-renewal in 2D culture, either as whole populations or as single cells. In 3D organotypic cultures, all cell subtypes were able to recapitulate the architecture of the tissue of origin and the main factor determining the success of the 3D culture was the number of cells plated, rather than the cell type. CONCLUSIONS: Oesophageal epithelial cells demonstrate remarkable plasticity for self-renewal. This situation could be viewed as an ex vivo wounding response and is compatible with recent findings in murine models.

High grade glioma: imaging combined with pathological grade defines management and predicts prognosis.

INTRODUCTION: There is ambiguity in pathological grading of high grade gliomas within the WHO 2000 classification, especially those with predominant oligodendroglial differentiation. PATIENTS AND METHODS: All adult high grade gliomas treated radically, 1996-2005, were assessed. Cases in which pathology was grade III but radiology suggested glioblastoma (GBM) were classified as 'grade III/IV'; their pathology was reviewed. RESULTS: Data from 245 patients (52 grade III, 18 grade III/IV, 175 GBM) were analysed using a Cox Proportional Hazards model. On pathology review, features suggestive of more aggressive behaviour were found in all 18 grade III/IV tumours. Oligodendroglial components with both necrosis and microvascular proliferation were present in 7. MIB-1 counts for the last 8 were all above 14%, mean 27%. Median survivals were: grade III 34 months, grade III/IV 10 months, GBM 11 months. Survival was not significantly different between grade III/IV and GBM. Patients with grade III/IV tumours had significantly worse outcome than grade III, with a hazard of death 3.7 times higher. CONCLUSIONS: The results highlight the current inconsistency in pathological grading of high grade tumours, especially those with oligodendroglial elements. Patients with histological grade III tumours but radiological appearances suggestive of GBM should be managed as glioblastoma.