Work-type influences perceived livestock herding success in Australian Working Kelpies

Background Working dog handlers and breeders have very different behavioural requirements in the animals that they employ for managing livestock. The Australian Working Kelpie breed may be used in several working contexts, notably yards, paddocks and a combination of both. The working context influences the skillsets required and gives rise to three corresponding work-types: Yard, Paddock and Utility Kelpies. In particular, dogs used for working stock in the confines of yards and trucks interact with stock more forcefully than those mustering in larger areas (paddocks) where they can herd stock effectively from a greater distance. This article explores owner assessments of dog working quality and assessment of genomic similarity by multidimensional scaling, to ask whether it is sufficient for breeders to aim for a multipurpose breeding objective, or whether breeding only specialist lines maximises user satisfaction for yard and paddock work. Results Reported owner perceptions of 298 dogs assessed with the Livestock Herding Dog assessment tool showed that dog handlers across all working types were very happy with their dogs’ level of general skills. Compared with both Yard and Utility Kelpies, Paddock Kelpies had significantly lower trait scores for force(pressure applied by the dog to move livestock), willingness to back the stock (run along a sheep’s dorsum) and bite (frequency of using the mouth to grab or bite the livestock). Meanwhile, compared with both Paddock and Utility Kelpies, the Yard Kelpies had significantly higher scores for hyperactivity and excitability (both with and without stock) and impulsiveness without stock. As one would predict for all-rounders, Utility Kelpies had intermediate scores for all behaviours and working traits. Conclusions Specialist characteristics were displayed by dogs in the Yard Kelpie and Paddock Kelpie groups. In particular, Yard Kelpies demonstrate higher excitability, willingness to back the stock, and a higher tendency to bark and bite the stock. Conversely, Paddock Kelpies rarely display these characteristics. Utility Kelpies, as the name suggests, are intermediate between the other two groups and display the characteristics of both. Genetic analysis suggests that the Yard, Utility and Paddock Kelpies are not distinguishable at a DNA level. In conclusion, at this time there is no suggestion of a breed split in the Australian Working Kelpie generated by selection for work type. A common breeding objective should enable dogs to be produced that fulfil all potential working requirements. This reinforces the importance of breeder skill in recognising the phenotypic potential of pups in order to place them in appropriate working contexts

Constrained Willmore Surfaces

Constrained Willmore surfaces are conformal immersions of Riemann surfaces that are critical points of the Willmore energy $W=\int H^2$ under compactly supported infinitesimal conformal variations. Examples include all constant mean curvature surfaces in space forms. In this paper we investigate more generally the critical points of arbitrary geometric functionals on the space of immersions under the constraint that the admissible variations infinitesimally preserve the conformal structure. Besides constrained Willmore surfaces we discuss in some detail examples of constrained minimal and volume critical surfaces, the critical points of the area and enclosed volume functional under the conformal constraint.Comment: 17 pages, 8 figures; v2: Hopf tori added as an example, minor changes in presentation, numbering changed; v3: new abstract and appendix, several changes in presentatio

Pulmonary rehabilitation referral and uptake from primary care for people living with COPD: a mixed-methods study.

Healthcare service and patient barriers contribute to low referral to and uptake of pulmonary rehabilitation (PR). Solutions should support skilled clinician-patient conversations and span primary care-PR boundaries to prevent disjointed working. http://bit.ly/2PVKHZf

Overlapping genetic susceptibility variants between three autoimmune disorders: rheumatoid arthritis, type 1 diabetes and coeliac disease

INTRODUCTION: Genome wide association studies, replicated by numerous well powered validation studies, have revealed a large number of loci likely to play a role in susceptibility to many multifactorial diseases. It is now well established that some of these loci are shared between diseases with similar aetiology. For example, a number of autoimmune diseases have been associated with variants in the PTPN22, TNFAIP3 and CTLA4 genes. Here we have attempted to define overlapping genetic variants between rheumatoid arthritis (RA), type 1 diabetes (T1D) and coeliac disease (CeD). METHODS: We selected eight SNPs previously identified as being associated with CeD and six T1D-associated SNPs for validation in a sample of 3,962 RA patients and 3,531 controls. Genotyping was performed using the Sequenom MassArray platform and comparison of genotype and allele frequencies between cases and controls was undertaken. A trend test P-value < 0.004 was regarded as significant. RESULTS: We found statistically significant evidence for association of the TAGAP locus with RA (P = 5.0 × 10-4). A marker at one other locus, C1QTNF6, previously associated with T1D, showed nominal association with RA in the current study but did not remain statistically significant at the corrected threshold. CONCLUSIONS: In exploring the overlap between T1D, CeD and RA, there is strong evidence that variation within the TAGAP gene is associated with all three autoimmune diseases. Interestingly a number of loci appear to be specific to one of the three diseases currently studied suggesting that they may play a role in determining the particular autoimmune phenotype at presentation

An updated PREDICT breast cancer prognostication and treatment benefit prediction model with independent validation

BACKGROUND PREDICT is a breast cancer prognostic and treatment benefit model implemented online. The overall fit of the model has been good in multiple independent case series, but PREDICT has been shown to underestimate breast cancer specific mortality in women diagnosed under the age of 40. Another limitation is the use of discrete categories for tumour size and node status resulting in 'step' changes in risk estimates on moving between categories. We have refitted the PREDICT prognostic model using the original cohort of cases from East Anglia with updated survival time in order to take into account age at diagnosis and to smooth out the survival function for tumour size and node status. METHODS Multivariable Cox regression models were used to fit separate models for ER negative and ER positive disease. Continuous variables were fitted using fractional polynomials and a smoothed baseline hazard was obtained by regressing the baseline cumulative hazard for each patients against time using fractional polynomials. The fit of the prognostic models were then tested in three independent data sets that had also been used to validate the original version of PREDICT. RESULTS In the model fitting data, after adjusting for other prognostic variables, there is an increase in risk of breast cancer specific mortality in younger and older patients with ER positive disease, with a substantial increase in risk for women diagnosed before the age of 35. In ER negative disease the risk increases slightly with age. The association between breast cancer specific mortality and both tumour size and number of positive nodes was non-linear with a more marked increase in risk with increasing size and increasing number of nodes in ER positive disease. The overall calibration and discrimination of the new version of PREDICT (v2) was good and comparable to that of the previous version in both model development and validation data sets. However, the calibration of v2 improved over v1 in patients diagnosed under the age of 40. CONCLUSIONS The PREDICT v2 is an improved prognostication and treatment benefit model compared with v1. The online version should continue to aid clinical decision making in women with early breast cancer

Postoperative serum proteomic profiles may predict recurrence-free survival in high-risk primary breast cancer

Item does not contain fulltextPURPOSE: Better breast cancer prognostication may improve selection of patients for adjuvant therapy. We conducted a retrospective longitudinal study in which we investigated sera of high-risk primary breast cancer patients, to search for proteins predictive of recurrence-free survival. METHODS: Sera of 82 breast cancer patients obtained after surgery, but prior to the administration of adjuvant therapy, were fractionated using anion-exchange chromatography, to facilitate the detection of the low-abundant serum peptides. Selected fractions were subsequently analysed by surface-enhanced laser desorption/ionisation time-of-flight mass spectrometry (SELDI-TOF MS), and the resulting protein profiles were searched for prognostic markers by appropriate bioinformatics tools. RESULTS: Four peak clusters (i.e. m/z 3073, m/z 3274, m/z 4405 and m/z 7973) were found to bear significant prognostic value (P </= 0.01). The m/z 3274 candidate marker was structurally identified as inter-alpha-trypsin inhibitor heavy chain 4 fragment(658-688) in serum. Except for the m/z 7973 peak cluster, these peaks remained independently associated with recurrence-free survival upon multivariate Cox regression analysis, including clinical parameters of known prognostic value in this study population. CONCLUSION: Investigation of the postoperative serum proteome by, e.g., anion-exchange fractionation followed by SELDI-TOF MS analysis is promising for the detection of novel prognostic factors. However, regarding the rather limited study population, validation of these results by analysis of independent study populations is warranted to assess the true clinical applicability of discovered prognostic markers. In addition, structural identification of the other markers will aid in elucidation of their role in breast cancer prognosis, as well as enable development of absolute quantitative assays

Phocine distemper Virus: Current knowledge and future directions

Phocine distemper virus (PDV) was first recognized in 1988 following a massive epidemic in harbor and grey seals in north-western Europe. Since then, the epidemiology of infection in North Atlantic and Arctic pinnipeds has been investigated. In the western North Atlantic endemic infection in harp and grey seals predates the European epidemic, with relatively small, localized mortality events occurring primarily in harbor seals. By contrast, PDV seems not to have become established in European harbor seals following the 1988 epidemic and a second event of similar magnitude and extent occurred in 2002. PDV is a distinct species within the Morbillivirus genus with minor sequence variation between outbreaks over time. There is now mounting evidence of PDV-like viruses in the North Pacific/Western Arctic with serological and molecular evidence of infection in pinnipeds and sea otters. However, despite the absence of associated mortality in the region, there is concern that the virus may infect the large Pacific harbor seal and northern elephant seal populations or the endangered Hawaiian monk seals. Here, we review the current state of knowledge on PDV with particular focus on developments in diagnostics, pathogenesis, immune response, vaccine development, phylogenetics and modeling over the past 20 years

Determinants of expression of SARS-CoV-2 entry-related genes in upper and lower airways.

Funder: Dutch Research Council (NWO)Funder: Cancer Research UK Cambridge CentreFunder: ATS Foundation/Boehringer Ingelheim Pharmaceuticals Inc. Research FellowshipFunder: The Netherlands Ministry of Spatial Planning, Housing, and the EnvironmentFunder: Chan Zuckerberg InitiativeFunder: The Netherlands Ministry of Health, Welfare, and SportFunder: Longfonds Junior FellowshipFunder: Cambridge BioresourceFunder: The Netherlands Organization for Health Research and DevelopmentFunder: Cambridge NIHR Biomedical Research CentreFunder: Parker B. Francis FellowshipFunder: China Scholarship Counci