Results from a randomized, controlled trial on efficacy and tolerability of a 5% Lidocaine-Medicated Plaster vs. Pregabalin in patients with Post-Herpetic Neuralgia (PHN) and Painful Diabetic Polyneuropathy (DPN) [poster]

No abstract available

An artificial intelligence approach to predicting personality types in dogs

Canine personality and behavioural characteristics have a significant influence on relationships between domestic dogs and humans as well as determining the suitability of dogs for specific working roles. As a result, many researchers have attempted to develop reliable personality assessment tools for dogs. Most previous work has analysed dogs’ behavioural patterns collected via questionnaires using traditional statistical analytic approaches. Artificial Intelligence has been widely and successfully used for predicting human personality types. However, similar approaches have not been applied to data on canine personality. In this research, machine learning techniques were applied to the classification of canine personality types using behavioural data derived from the C-BARQ project. As the dataset was not labelled, in the first step, an unsupervised learning approach was adopted and K-Means algorithm was used to perform clustering and labelling of the data. Five distinct categories of dogs emerged from the K-Means clustering analysis of behavioural data, corresponding to five different personality types. Feature importance analysis was then conducted to identify the relative importance of each behavioural variable’s contribution to each cluster and descriptive labels were generated for each of the personality traits based on these associations. The five personality types identified in this paper were labelled: “Excitable/Hyperattached”, “Anxious/Fearful”, “Aloof/Predatory”, “Reactive/Assertive”, and “Calm/Agreeable”. Four machine learning models including Support Vector Machine (SVM), K-Nearest Neighbour (KNN), Naïve Bayes, and Decision Tree were implemented to predict the personality traits of dogs based on the labelled data. The performance of the models was evaluated using fivefold cross validation method and the results demonstrated that the Decision Tree model provided the best performance with a substantial accuracy of 99%. The novel AI-based methodology in this research may be useful in the future to enhance the selection and training of dogs for specific working and non-working roles

Results from a randomized, controlled trial on efficacy and tolerability of a 5% Lidocaine-Medicated Plaster vs. Pregabalin in patients with Post-Herpetic Neuralgia (PHN) and Painful Diabetic Polyneuropathy (DPN) [poster]

No abstract available

Building bridges between theory and practice: how citizen science can bring equine researchers and practitioners together

Over the last decade, equitation scientists have increasingly relied on online survey tools to gather information on horse training, management, behaviour and other equine-related subjects. With a detailed knowledge of their animals, horse owners and riders are ideally placed to contribute to research but are sometimes reluctant to engage with and devote time to surveys. The current article reveals, through consultation with stakeholder groups, the potential of a range of motivational items to boost horse-owner participation. A short, three-question inquiry was developed to rank respondents’ (n=747) preferred survey tools and other items designed to engage the equestrian community with the donation of data. Respondents were asked to assign themselves to one of four categories: academics/researchers, professionals, practitioners and enthusiasts. The inquiry offered respondents the choice of three hypothetical tools: a standardized tool to measure behaviour over time; a logbook tool to record training and behaviour on a regular basis; and a chart to compare an individual horse’s behaviour with that of the general horse population. While analysis revealed that stakeholders considered at least one of the tools to be useful, it also exposed significant differences among the perceived usefulness of the various tools themselves. Using free-text responses, participants described the challenges faced when gathering information on horse training, management and behaviour. Qualitative analysis of these data revealed the need to improve the current dissemination of scientific findings to bridge various knowledge gaps. The Equine Behavior Assessment and Research Questionnaire (E-BARQ) is a longitudinal instrument that investigates horse training and management practices and permits an analysis of their relationship with behaviour. The current stakeholder consultation contributed to the final version of the E-BARQ questionnaire, identified incentivizing items that can be offered to putative E-BARQ respondents, guided the eventual selection of a Share-&-Compare feedback chart, and reinforced the need for open-access dissemination of findings

The Development of a Novel Questionnaire Approach to the Investigation of Horse Training, Management, and Behaviour.

The Equine Behaviour Assessment and Research Questionnaire (E-BARQ) is a questionnaire instrument developed to obtain quantitative data on the domestic equine triad of training, management, and behaviour of horses. The E-BARQ was developed to identify how changes in training and management impact behaviour over time, to define normal behaviour in horses, and to discover how to improve rider safety and horse welfare, leading to ethical equitation. During the development of the E-BARQ, we also investigated how best to motivate stakeholders to engage with this citizen science project. The pilot version of the E-BARQ collected qualitative data on respondents' experience of the questionnaire. The pilot questionnaire was developed with the assistance of an international panel (with professional expertise in horse training, equitation science, veterinary science, equestrian coaching, welfare, animal behaviour, and elite-level riding), and was used to collect data on 1320 horses from approximately 1194 owner/caregiver respondents, with an option for respondents to provide free-text feedback. A Rotated Principal Component Analysis of the 218 behavioural, management, and training questionnaire items extracted a total of 65 rotated components. Thirty-six of the 65 rotated components demonstrated high internal reliability. Of the 218 questionnaire items, 43 items failed to reach the Rotated Principal Component Analysis criteria and were not included in the final version of the E-BARQ. Survey items that failed the Rotated Principal Component Analysis inclusion criteria were discarded if found to have a less than 85% response rate, or a variance of less than 1.3. Of those that survived the Rotated Principal Component Analysis, items were further assigned to horse temperament (17 rotated components), equitation (11 rotated components), and management and equipment (8 rotated components) groups. The feedback from respondents indicated the need for further items to be added to the questionnaire, resulting in a total of 214 items for the final E-BARQ survey. Many of these items were further grouped into question matrices, and the demographic items for horse and handler included, giving a final total of 97 questions on the E-BARQ questionnaire. These results provided content validity, showing that the questionnaire items were an acceptable representation of the entire horse training, management, and behavioural domain for the development of the final E-BARQ questionnaire

Improving the estimation of deep-sea megabenthos biomass: dimension to wet weight conversions for abyssal invertebrates

Deep-sea megafaunal biomass has typically been assessed by sampling with benthic sledges and trawls, but non-destructive methods, particularly photography, are becoming increasingly common. Estimation of individual wet weight in seabed photographs has been achieved using equations obtained from measured trawl-caught specimens for a limited number of taxa. However, a lack of appropriate conversion factors has limited estimation across taxa encompassing whole communities. Here we compile relationships between measured body dimensions and preserved wet weights for a comprehensive catalogue of abyssal epibenthic megafauna, using ~47,000 specimens from the Porcupine Abyssal Plain (NE Atlantic) housed in the Discovery Collections. The practical application of the method is demonstrated using an extremely large dataset of specimen measurements from seabed photographs taken in the same location. We also collate corresponding field data on fresh wet weight, to estimate the impact of fixation in formalin and preservation in industrial denatured alcohol on the apparent biomass. Taxa with substantial proportions of soft tissues lose 35 to 60% of their wet weight during preservation, while those with greater proportions of hard tissues lose 10 to 20%. Our total estimated fresh wet weight biomass of holothurians and cnidarians in the photographic survey was ~20 times the previous estimates of total invertebrate biomass based on trawl catches. This dramatic uplift in megabenthic biomass has significant implications for studies of standing stocks, community metabolism, and numerical modelling of benthic carbon flows

First evidence for an association between joint hypermobility and excitability in a non-human species, the domestic dog

There is a well-established relationship between joint hypermobility and anxiety in humans, that has not previously been investigated in other species. A population of 5575 assistance dogs were scored for both hip hypermobility and 13 behaviour characteristics using previously validated methods. Our results suggest a positive association between hip joint hypermobility and emotional arousal in domestic dogs, which parallel results found in people

Gaia on-board metrology: basic angle and best focus

The Gaia payload ensures maximum passive stability using a single material, SiC, for most of its elements. Dedicated metrology instruments are, however, required to carry out two functions: monitoring the basic angle and refocusing the telescope. Two interferometers fed by the same laser are used to measure the basic angle changes at the level of $\mu$as (prad, micropixel), which is the highest level ever achieved in space. Two Shack-Hartmann wavefront sensors, combined with an ad-hoc analysis of the scientific data are used to define and reach the overall best-focus. In this contribution, the systems, data analysis, procedures and performance achieved during commissioning are presentedComment: 18 pages, 14 figures. To appear in SPIE proceedings 9143-30. Space Telescopes and Instrumentation 2014: Optical, Infrared, and Millimeter Wav

Association of opioid prescribing practices with chronic pain and benzodiazepine co-prescription:a primary care data linkage study

Background: Opioid prescribing is increasing worldwide with associated increases in misuse and other harms. We studied variations in national opioid prescription rates, indicators of prescribing quality, co-prescribing of benzodiazepines and relationship with pain severity in Scotland. Methods: Electronic linkages of opioid prescribing in Scotland were determined from: (i) national data from Information Services Division, NHS Scotland (2003–2012); and (ii) individual data from Generation Scotland: Scottish Family Health Study. Descriptive analyses were conducted on national data, multilevel modelling to examine factors associated with variations in prescribing rates. χ2 tests examined associations between individual pain severity and opioid prescriptions. Results: The number of strong opioid prescriptions more than doubled from 474 385 in 2003 to 1 036 446 in 2012, and weak opioid prescribing increased from 3 261 547 to 4 852 583. In Scotland, 938 674 individuals were prescribed an opioid in 2012 (18% of the population). Patients in the most deprived areas were 3.5 times more likely to receive a strong opioid than patients in the least deprived. There was significant variation in prescribing rates between geographical areas, with much of this explained by deprivation. Of women aged 25–40 yr prescribed a strong opioid, 40% were also prescribed a benzodiazepine. There was significant association between pain severity and receipt of opioid prescription. Over 50% of people reporting severe pain were not prescribed an opioid analgesic. Conclusions: We found opioid prescribing in primary care to be common and increasing in Scotland, particularly for severe pain. Co-prescribing of opioids and benzodiazepines was common

Protofilaments, filaments, ribbons, and fibrils from peptidomimetic self-assembly: Implications for amyloid fibril formation and materials science

Deciphering the mechanism(s) of beta-sheet mediated self-assembly is essential for understanding amyloid fibril formation and for the fabrication of polypeptide materials. Herein, we report a simple peptidomimetic that self-assembles into polymorphic beta-sheet quaternary structures including protofilaments, filaments, fibrils, and ribbons that are reminiscent of the highly ordered structures displayed by the amyloidogenic peptides A beta, calcitonin, and amylin. The distribution of quaternary structures can be controlled by and in some cases specified by manipulating the pH, buffer composition, and the ionic strength. The ability to control beta-sheet-mediated assembly takes advantage of quaternary structure dependent pK(a) perturbations. Biophysical methods including analytical ultracentrifugation studies as well as far-UV circular dichroism and FT-IR spectroscopy demonstrate that linked secondary and quaternary structural changes mediate peptidomimetic self-assembly. Electron and atomic force microscopy reveal that peptidomimetic assembly involves numerous quaternary structural intermediates that appear to self-assemble in a convergent fashion affording quaternary structures of increasing complexity. The ability to control the assembly pathway(s) and the final quaternary structure(s) afforded should prove to be particularly useful in deciphering the quaternary structural requirements for amyloid fibril formation and for the construction of noncovalent macromolecular structure