Quantification of Respirable Aerosol Particles from Speech and Language Therapy Exercises

INTRODUCTION

Voice assessment and treatment involve the manipulation of all the subsystems of voice production, and may lead to production of respirable aerosol particles that pose a greater risk of potential viral transmission via inhalation of respirable pathogens (eg, SARS-CoV-2) than quiet breathing or conversational speech.

OBJECTIVE

To characterise the production of respirable aerosol particles during a selection of voice assessment therapy tasks.

METHODS

We recruited 23 healthy adult participants (12 males, 11 females), 11 of whom were speech-language pathologists specialising in voice disorders. We used an aerodynamic and an optical particle sizer to measure the number concentration and particle size distributions of respirable aerosols generated during a variety of voice assessment and therapy tasks. The measurements were carried out in a laminar flow operating theatre, with a near-zero background aerosol concentration, allowing us to quantify the number concentration and size distributions of respirable aerosol particles produced from assessment/therapy tasks studied.

RESULTS

Aerosol number concentrations generated while performing assessment/therapy tasks were log-normally distributed among individuals with no significant differences between professionals (speech-language pathologists) and non-professionals or between males and females. Activities produced up to 32 times the aerosol number concentration of breathing and 24 times that of speech at 70-80 dBA. In terms of aerosol mass, activities produced up to 163 times the mass concentration of breathing and up to 36 times the mass concentration of speech. Voicing was a significant factor in aerosol production; aerosol number/mass concentrations generated during the voiced activities were 1.1-5 times higher than their unvoiced counterpart activities. Additionally, voiced activities produced bigger respirable aerosol particles than their unvoiced variants except the trills. Humming generated higher aerosol concentrations than sustained /a/, fricatives, speaking (70-80 dBA), and breathing. Oscillatory semi-occluded vocal tract exercises (SOVTEs) generated higher aerosol number/mass concentrations than the activities without oscillation. Water resistance therapy (WRT) generated the most aerosol of all activities, ∼10 times higher than speaking at 70-80 dBA and >30 times higher than breathing.

CONCLUSIONS

All activities generated more aerosol than breathing, although a sizeable minority were no different to speaking. Larger number concentrations and larger particle sizes appear to be generated by activities with higher suspected airflows, with the greatest involving intraoral pressure oscillation and/or an oscillating oral articulation (WRT or trilling).

Comparing aerosol number and mass exhalation rates from children and adults during breathing, speaking and singing

Aerosol particles of respirable size are exhaled when individuals breathe, speak and sing and can transmit respiratory pathogens between infected and susceptible individuals. The COVID-19 pandemic has brought into focus the need to improve the quantification of the particle number and mass exhalation rates as one route to provide estimates of viral shedding and the potential risk of transmission of viruses. Most previous studies have reported the number and mass concentrations of aerosol particles in an exhaled plume. We provide a robust assessment of the absolute particle number and mass exhalation rates from measurements of minute ventilation using a non-invasive Vyntus Hans Rudolf mask kit with straps housing a rotating vane spirometer along with measurements of the exhaled particle number concentrations and size distributions. Specifically, we report comparisons of the number and mass exhalation rates for children (12–14 years old) and adults (19–72 years old) when breathing, speaking and singing, which indicate that child and adult cohorts generate similar amounts of aerosol when performing the same activity. Mass exhalation rates are typically 0.002–0.02 ng s −1 from breathing, 0.07–0.2 ng s −1 from speaking (at 70–80 dBA) and 0.1–0.7 ng s −1 from singing (at 70–80 dBA). The aerosol exhalation rate increases with increasing sound volume for both children and adults when both speaking and singing.

What's Stopping Knowledge Synthesis? A Systematic Review of Recent Practices in Research on Smallholder Diversity

A systematic review of recent publications was conducted to assess the extent to which contemporary micro-level research on smallholders facilitates data re-use and knowledge synthesis. Following PRISMA standards for systematic review, 1,182 articles were identified (published between 2018 and 2020), and 261 articles were selected for review in full. The themes investigated were: (i) data management, including data source, variables collected, granularity, and availability of the data; (ii) the statistical methods used, including analytical approach and reproducibility; and (iii) the interpretation of results, including the scope and objectives of the study, development issues addressed, scale of recommendations made relative to the scale of the sample, and the audience for recommendations. It was observed that household surveys were the most common data source and tended to be representative at the local (community) level. There was little harmonization of the variables collected between studies. Over three quarters of the studies (77%) drew on data which was not in the public domain, 14% published newly open data, and 9% drew on datasets which were already open. Other than descriptive statistics, linear and logistic regression methods were the most common analytical method used (64% of articles). In the vast majority of those articles, regression was used as an explanatory tool, as opposed to a predictive tool. More than half of the articles (59%) made claims or recommendations which extended beyond the coverage of their datasets. In combination these two common practices may lead to erroneous understanding: the tendency to rely upon simple regressions to explain context-specific and complex associations; and the tendency to generalize beyond the remit of the data collected. We make four key recommendations: (1) increased data sharing and variable harmonization would enable data to be re-used between studies; (2) providing detailed meta-data on sampling frames and study-context would enable more powerful meta-analyses; (3) methodological openness and predictive modeling could help test the transferability of approaches; (4) more precise language in study conclusions could help decision makers understand the relevance of findings for policy planning. Following these practices could leverage greater benefits from the substantial investment already made in data collection on smallholder farms.

The ARRIVE guidelines 2.0: Updated guidelines for reporting animal research

Reproducible science requires transparent reporting. The ARRIVE guidelines (Animal Research: Reporting of In Vivo Experiments) were originally developed in 2010 to improve the reporting of animal research. They consist of a checklist of information to include in publications describing in vivo experiments to enable others to scrutinise the work adequately, evaluate its methodological rigour, and reproduce the methods and results. Despite considerable levels of endorsement by funders and journals over the years, adherence to the guidelines has been inconsistent, and the anticipated improvements in the quality of reporting in animal research publications have not been achieved. Here, we introduce ARRIVE 2.0. The guidelines have been updated and information reorganised to facilitate their use in practice. We used a Delphi exercise to prioritise and divide the items of the guidelines into 2 sets, the "ARRIVE Essential 10," which constitutes the minimum requirement, and the "Recommended Set," which describes the research context. This division facilitates improved reporting of animal research by supporting a stepwise approach to implementation. This helps journal editors and reviewers verify that the most important items are being reported in manuscripts. We have also developed the accompanying Explanation and Elaboration document, which serves (1) to explain the rationale behind each item in the guidelines, (2) to clarify key concepts, and (3) to provide illustrative examples. We aim, through these changes, to help ensure that researchers, reviewers, and journal editors are better equipped to improve the rigour and transparency of the scientific process and thus reproducibility.

The ARRIVE guidelines 2.0: updated guidelines for reporting animal research

Reproducible science requires transparent reporting. The ARRIVE guidelines (Animal Research: Reporting of In Vivo Experiments) were originally developed in 2010 to improve the reporting of animal research. They consist of a checklist of information to include in publications describing in vivo experiments to enable others to scrutinise the work adequately, evaluate its methodological rigour, and reproduce the methods and results. Despite considerable levels of endorsement by funders and journals over the years, adherence to the guidelines has been inconsistent, and the anticipated improvements in the quality of reporting in animal research publications have not been achieved. Here, we introduce ARRIVE 2.0. The guidelines have been updated and information reorganised to facilitate their use in practice. We used a Delphi exercise to prioritise and divide the items of the guidelines into 2 sets, the 'ARRIVE Essential 10,' which constitutes the minimum requirement, and the 'Recommended Set,' which describes the research context. This division facilitates improved reporting of animal research by supporting a stepwise approach to implementation. This helps journal editors and reviewers verify that the most important items are being reported in manuscripts. We have also developed the accompanying Explanation and Elaboration document, which serves (1) to explain the rationale behind each item in the guidelines, (2) to clarify key concepts, and (3) to provide illustrative examples. We aim, through these changes, to help ensure that researchers, reviewers, and journal editors are better equipped to improve the rigour and transparency of the scientific process and thus reproducibility.

The ARRIVE guidelines 2.0: Updated guidelines for reporting animal research

Reproducible science requires transparent reporting. The ARRIVE guidelines (Animal Research: Reporting of In Vivo Experiments) were originally developed in 2010 to improve the reporting of animal research. They consist of a checklist of information to include in publications describing in vivo experiments to enable others to scrutinise the work adequately, evaluate its methodological rigour, and reproduce the methods and results. Despite considerable levels of endorsement by funders and journals over the years, adherence to the guidelines has been inconsistent, and the anticipated improvements in the quality of reporting in animal research publications have not been achieved. Here, we introduce ARRIVE 2.0. The guidelines have been updated and information reorganised to facilitate their use in practice. We used a Delphi exercise to prioritise and divide the items of the guidelines into 2 sets, the "ARRIVE Essential 10," which constitutes the minimum requirement, and the "Recommended Set," which describes the research context. This division facilitates improved reporting of animal research by supporting a stepwise approach to implementation. This helps journal editors and reviewers verify that the most important items are being reported in manuscripts. We have also developed the accompanying Explanation and Elaboration document, which serves (1) to explain the rationale behind each item in the guidelines, (2) to clarify key concepts, and (3) to provide illustrative examples. We aim, through these changes, to help ensure that researchers, reviewers, and journal editors are better equipped to improve the rigour and transparency of the scientific process and thus reproducibility.

The ARRIVE guidelines 2.0: Updated guidelines for reporting animal research

Reproducible science requires transparent reporting. The ARRIVE guidelines (Animal Research: Reporting of In Vivo Experiments) were originally developed in 2010 to improve the reporting of animal research. They consist of a checklist of information to include in publications describing in vivo experiments to enable others to scrutinise the work adequately, evaluate its methodological rigour, and reproduce the methods and results. Despite considerable levels of endorsement by funders and journals over the years, adherence to the guidelines has been inconsistent, and the anticipated improvements in the quality of reporting in animal research publications have not been achieved. Here, we introduce ARRIVE 2.0. The guidelines have been updated and information reorganised to facilitate their use in practice. We used a Delphi exercise to prioritise and divide the items of the guidelines into 2 sets, the "ARRIVE Essential 10," which constitutes the minimum requirement, and the "Recommended Set," which describes the research context. This division facilitates improved reporting of animal research by supporting a stepwise approach to implementation. This helps journal editors and reviewers verify that the most important items are being reported in manuscripts. We have also developed the accompanying Explanation and Elaboration (E&E) document, which serves (1) to explain the rationale behind each item in the guidelines, (2) to clarify key concepts, and (3) to provide illustrative examples. We aim, through these changes, to help ensure that researchers, reviewers, and journal editors are better equipped to improve the rigour and transparency of the scientific process and thus reproducibility.

The ARRIVE guidelines 2.0: updated guidelines for reporting animal research

Reproducible science requires transparent reporting. The ARRIVE guidelines (Animal Research: Reporting of In Vivo Experiments) were originally developed in 2010 to improve the reporting of animal research. They consist of a checklist of information to include in publications describing in vivo experiments to enable others to scrutinise the work adequately, evaluate its methodological rigour and reproduce the methods and results. Despite considerable levels of endorsement by funders and journals over the years, adherence to the guidelines has been inconsistent, and the anticipated improvements in the quality of reporting in animal research publications have not been achieved. Here, we introduce ARRIVE 2.0. The guidelines have been updated and information reorganised to facilitate their use in practice. We used a Delphi exercise to prioritise and divide the items of the guidelines into two sets, the 'ARRIVE Essential 10', which constitutes the minimum requirement, and the 'Recommended Set', which describes the research context. This division facilitates improved reporting of animal research by supporting a stepwise approach to implementation. This helps journal editors and reviewers verify that the most important items are being reported in manuscripts. We have also developed the accompanying Explanation and Elaboration document, which serves (1) to explain the rationale behind each item in the guidelines, (2) to clarify key concepts and (3) to provide illustrative examples. We aim, through these changes, to help ensure that researchers, reviewers and journal editors are better equipped to improve the rigour and transparency of the scientific process and thus reproducibility.

The ARRIVE guidelines 2.0: Updated guidelines for reporting animal research

Reproducible science requires transparent reporting. The ARRIVE guidelines (Animal Research: Reporting of In Vivo Experiments) were originally developed in 2010 to improve the reporting of animal research. They consist of a checklist of information to include in publications describing in vivo experiments to enable others to scrutinise the work adequately, evaluate its methodological rigour, and reproduce the methods and results. Despite considerable levels of endorsement by funders and journals over the years, adherence to the guidelines has been inconsistent, and the anticipated improvements in the quality of reporting in animal research publications have not been achieved. Here, we introduce ARRIVE 2.0. The guidelines have been updated and information reorganised to facilitate their use in practice. We used a Delphi exercise to prioritise and divide the items of the guidelines into 2 sets, the "ARRIVE Essential 10," which constitutes the minimum requirement, and the "Recommended Set," which describes the research context. This division facilitates improved reporting of animal research by supporting a stepwise approach to implementation. This helps journal editors and reviewers verify that the most important items are being reported in manuscripts. We have also developed the accompanying Explanation and Elaboration document, which serves (1) to explain the rationale behind each item in the guidelines, (2) to clarify key concepts, and (3) to provide illustrative examples. We aim, through these changes, to help ensure that researchers, reviewers, and journal editors are better equipped to improve the rigour and transparency of the scientific process and thus reproducibility.

Reporting animal research: Explanation and elaboration for the ARRIVE guidelines 2.0

Improving the reproducibility of biomedical research is a major challenge. Transparent and accurate reporting is vital to this process; it allows readers to assess the reliability of the findings and repeat or build upon the work of other researchers. The ARRIVE guidelines (Animal Research: Reporting In Vivo Experiments) were developed in 2010 to help authors and journals identify the minimum information necessary to report in publications describing in vivo experiments. Despite widespread endorsement by the scientific community, the impact of ARRIVE on the transparency of reporting in animal research publications has been limited. We have revised the ARRIVE guidelines to update them and facilitate their use in practice. The revised guidelines are published alongside this paper. This explanation and elaboration document was developed as part of the revision. It provides further information about each of the 21 items in ARRIVE 2.0, including the rationale and supporting evidence for their inclusion in the guidelines, elaboration of details to report, and examples of good reporting from the published literature. This document also covers advice and best practice in the design and conduct of animal studies to support researchers in improving standards from the start of the experimental design process through to publication.

The ARRIVE guidelines 2.0: Updated guidelines for reporting animal research

Reproducible science requires transparent reporting. The ARRIVE guidelines (Animal Research: Reporting of In Vivo Experiments) were originally developed in 2010 to improve the reporting of animal research. They consist of a checklist of information to include in publications describing in vivo experiments to enable others to scrutinise the work adequately, evaluate its methodological rigour, and reproduce the methods and results. Despite considerable levels of endorsement by funders and journals over the years, adherence to the guidelines has been inconsistent, and the anticipated improvements in the quality of reporting in animal research publications have not been achieved. Here, we introduce ARRIVE 2.0. The guidelines have been updated and information reorganised to facilitate their use in practice. We used a Delphi exercise to prioritise and divide the items of the guidelines into 2 sets, the "ARRIVE Essential 10," which constitutes the minimum requirement, and the "Recommended Set," which describes the research context. This division facilitates improved reporting of animal research by supporting a stepwise approach to implementation. This helps journal editors and reviewers verify that the most important items are being reported in manuscripts. We have also developed the accompanying Explanation and Elaboration (E&E) document, which serves (1) to explain the rationale behind each item in the guidelines, (2) to clarify key concepts, and (3) to provide illustrative examples. We aim, through these changes, to help ensure that researchers, reviewers, and journal editors are better equipped to improve the rigour and transparency of the scientific process and thus reproducibility.

Quantifying defence cascade responses as indicators of pig affect and welfare using computer vision methods

Affective states are key determinants of animal welfare. Assessing such states under field conditions is thus an important goal in animal welfare science. The rapid Defence Cascade (DC) response (startle, freeze) to sudden unexpected stimuli is a potential indicator of animal affect; humans and rodents in negative affective states often show potentiated startle magnitude and freeze duration. To be a practical field welfare indicator, quick and easy measurement is necessary. Here we evaluate whether DC responses can be quantified in pigs using computer vision. 280 video clips of induced DC responses made by 12 pigs were analysed by eye to provide 'ground truth' measures of startle magnitude and freeze duration which were also estimated by (i) sparse feature tracking computer vision image analysis of 200 Hz video, (ii) load platform, (iii) Kinect depth camera, and (iv) Kinematic data. Image analysis data strongly predicted ground truth measures and were strongly positively correlated with these and all other estimates of DC responses. Characteristics of the DC-inducing stimulus, pig orientation relative to it, and 'relaxed-tense' pig behaviour prior to it moderated DC responses. Computer vision image analysis thus offers a practical approach to measuring pig DC responses, and potentially pig affect and welfare, under field conditions.

Partitioning variation in multilevel models for count data

A first step when fitting multilevel models to continuous responses is to explore the degree of clustering in the data. Researchers fit variance-component models and then report the proportion of variation in the response that is due to systematic differences between clusters. Equally they report the response correlation between units within a cluster. These statistics are popularly referred to as variance partition coefficients (VPCs) and intraclass correlation coefficients (ICCs). When fitting multilevel models to categorical (binary, ordinal, or nominal) and count responses, these statistics prove more challenging to calculate. For categorical response models, researchers appeal to their latent response formulations and report VPCs/ICCs in terms of latent continuous responses envisaged to underly the observed categorical responses. For standard count response models, however, there are no corresponding latent response formulations. More generally, there is a paucity of guidance on how to partition the variation. As a result, applied researchers are likely to avoid or inadequately report and discuss the substantive importance of clustering and cluster effects in their studies. A recent article drew attention to a little-known exact algebraic expression for the VPC/ICC for the special case of the two-level random-intercept Poisson model. In this article, we make a substantial new contribution. First, we derive exact VPC/ICC expressions for more flexible negative binomial models that allows for overdispersion, a phenomenon which often occurs in practice. Then we derive exact VPC/ICC expressions for three-level and random-coefficient extensions to these models. We illustrate our work with an application to student absenteeism. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

State-dependent judgement bias in Drosophila: evidence for evolutionarily primitive affective processes

Affective states influence decision-making under ambiguity in humans and other animals. Individuals in a negative state tend to interpret ambiguous cues more negatively than individuals in a positive state. We demonstrate that the fruit fly, Drosophila melanogaster, also exhibits state-dependent changes in cue interpretation. Drosophila were trained on a Go/Go task to approach a positive (P) odour associated with a sugar reward and actively avoid a negative (N) odour associated with shock. Trained flies were then either shaken to induce a purported negative state or left undisturbed (control), and given a choice between: air or P; air or N; air or ambiguous odour (1 : 1 blend of P : N). Shaken flies were significantly less likely to approach the ambiguous odour than control flies. This ‘judgement bias’ may be mediated by changes in neural activity that reflect evolutionarily primitive affective states. We cannot say whether such states are consciously experienced, but use of this model organism's versatile experimental tool kit may facilitate elucidation of their neural and genetic basis.

Experimentally manipulating light spectra reveals the importance of dark corridors for commuting bats

The rapid global spread of artificial light at night is causing unprecedented disruption to ecosystems. In otherwise dark environments, street lights restrict the use of major flight routes by some bats, including the threatened lesser horseshoe bat Rhinolophus hipposideros, and may disrupt foraging. Using radio tracking, we examined the response of individual female R. hipposideros to experimental street lights placed on hedgerows used as major flight routes. Hedgerows were illuminated on one side over four nights using lights with different emission spectra, while the opposite side of the hedge was not illuminated. Automated bat detectors were used to examine changes in overall bat activity by R. hipposideros and other bat species present. R. hipposideros activity reduced significantly under all light types, including red light, challenging a previously held assumption that red light is safe for bats. Despite this, R. hipposideros rapidly adapted to the presence of lights by switching their flight paths to the dark side of the hedgerow, enabling them to reach foraging sites without restriction. Red light had no effect on the activity of the other species present. Slow-flying Myotis spp. avoided orange, white and green light, while more agile Pipistrellus spp. were significantly more active at these light types compared to dark controls, most probably in response to accumulations of insect prey. No effect of any light type was found for Nyctalus or Eptesicus spp. Our findings demonstrate that caution must be used when promoting forms of lighting that are thought to be safe for wildlife before they are tested more widely. We argue that it is essential to preserve dark corridors to mitigate the impacts of artificial light at night on bat activity and movements.

Early-life risk factors identified for owner-reported feline overweight and obesity at around two years of age

Obesity is considered the second most common health problem in pet cats in developed countries. This study used prospective data from a longitudinal study of pet cats ('C.L.A.W.S.', www.bristol.ac.uk/vetscience/claws) to identify early-life risk factors for feline overweight/obesity occurring at around two years of age. Data were collected via five owner-completed questionnaires (for cats aged two-six months, six months, 12 months, 18 months and two years respectively) completed between May 2011 and April 2015. Owner-reported body condition scores (BCS) of cats at age two years, assessed using images from the 9-point BCS system (Laflamme, 1997), were categorised into a dichotomous variable: overweight/obese (BCS 6-9) and not overweight (BCS 1-5) and used as the dependent variable. Of the 375 cats with owner-reported BCS, 25.3% were overweight or obese at two years of age. Multivariable logistic regression models were built using stepwise forward-selection. To account for potential hierarchical clustering due to multi-cat households two-level random intercept models were considered but clustering had no impact on the analysis. Models were compared using Wald tests. Six factors were significantly associated with overweight/obesity at two years of age: being overweight or obese at one year of age (OR=10.6, 95%CI 4.4-25.3); owner belief that BCS 7 was the ideal weight (OR=33.2, 95%CI 8.5-129.4), or that BCS represented overweight cats but they would not be concerned if their cat were classified in this category (OR=2.7, 95%CI 1.2-6.2), at questionnaire five completion; vets advising owners that the cat should lose weight, or making no comment on their weight, between one and two years of age (OR=12.1, 95%CI 3.2-44.9 and OR=3.9, 95%CI 1.5-10.3 respectively); owners giving their cat treats when they "felt happy" with them at 18 months of age (OR=2.7, 95%CI 1.0 - 7.3); feeding ≥250g wet food daily between two and six months of age (OR=2.7, 95%CI 1.2-5.9), and feeding dry food as the only or major part (>50%) of the diet at two years of age (OR=2.1, 95%CI 1.0-4.2). These findings have the potential to reduce the current high prevalence of a widespread problem by informing preventive advice, and as such improving the health and welfare of pet cats.

A Bayesian micro-simulation to evaluate the cost-effectiveness of interventions for mastitis control during the dry period in UK dairy herds

Importance of the dry period with respect to mastitis control is now well established although the precise interventions that reduce the risk of acquiring intramammary infections during this time are not clearly understood. There are very few intervention studies that have measured the clinical efficacy of specific mastitis interventions within a cost-effectiveness framework so there remains a large degree of uncertainty about the impact of a specific intervention and its costeffectiveness. The aim of this study was to use a Bayesian framework to investigate the cost-effectiveness of mastitis controls during the dry period. Data were assimilated from 77 UK dairy farms that participated in a British national mastitis control programme during 2009-2012 in which the majority of intramammary infections were acquired during the dry period. The data consisted of clinical mastitis (CM) and somatic cell count (SCC) records, herd management practices and details of interventions that were implemented by the farmer as part of the control plan. The outcomes used to measure the effectiveness of the interventions were i) changes in the incidence rate of clinical mastitis during the first 30days after calving and ii) the rate at which cows gained new infections during the dry period (measured by SCC changes across the dry period from <200,000cells/ml to >200,000cells/ml). A Bayesian one-step microsimulation model was constructed such that posterior predictions from the model incorporated uncertainty in all parameters. The incremental net benefit was calculated across 10,000 Markov chain Monte Carlo iterations, to estimate the cost-benefit (and associated uncertainty) of each mastitis intervention. Interventions identified as being cost-effective in most circumstances included selecting dry-cow therapy at the cow level, dry-cow rations formulated by a qualified nutritionist, use of individual calving pens, first milking cows within 24h of calving and spreading bedding evenly in dry-cow yards. The results of this study highlighted the efficacy of specific mastitis interventions in UK conditions which, when incorporated into a costeffectiveness framework, can be used to optimize decision making in mastitis control. This intervention study provides an example of how an intuitive and clinically useful Bayesian approach can be used to form the basis of an on-farm decision support tool.

Multiple membership multiple classification (MMMC) models

In the social and other sciences many data are collected with a known but complex underlying structure. Over the past two decades there has been an increase in the use of multilevel modelling techniques that account for nested data structures. Often however the underlying data structures are more complex and cannot be fitted into a nested structure. First, there are cross-classified models where the classifications in the data are not nested. Secondly, we consider multiple membership models where an observation does not belong simply to one member of a classification. These two extensions when combined allow us to fit models to a large array of underlying structures. Existing frequentist modelling approaches to fitting such data have some important computational limitations. In this paper we consider ways of overcoming such limitations using Bayesian methods, since Bayesian model fitting is easily accomplished using Monte Carlo Markov chain (MCMC) techniques. In examples where we have been able to make direct comparisons, Bayesian methods in conjunction with suitable ‘diffuse’ prior distributions lead to similar inferences to existing frequentist techniques. In this paper we illustrate our techniques with examples in the fields of education, veterinary epidemiology, demography, and public health illustrating the diversity of models that fit into our framework.

Using cross-classified multivariate mixed response models with application to life history traits in great tits (Parus major)

Longitudinal observations on known individuals are an important source of data with which to test evolutionary theory within natural populations, in particular, the evolution and maintenance of life-history traits. In this paper, we concentrate on the reproductive behaviour and survival of a small passerine bird, the great tit ( Parus major). The dataset we consider is taken from the long-term study of great tits in Wytham Woods in Oxfordshire. The models we consider are designed to relate variation in several phenotypic response variables that are linked to evolutionary fitness, alongside the correlations between them, to both general environmental and individual-specific factors. We fit multivariate cross-classified random effects models using a Markov chain Monte Carlo (MCMC) estimation algorithm described in the paper. Our results show for which traits variability is influenced by environmental factors and for which traits individual bird factors are more important. The partitioning of correlations is particularly illuminating, producing some pairs of ‘antagonistic’ correlations which are biologically meaningful.

Temperament, age and weather predict social interaction in the sheep flock

The aim of the current study was to investigate the social relationships between individual sheep, and factors that influence this, through the novel application of the statistical multiple membership multiple classification (MMMC) model. In study one 49 ewes (ranging between 1 and 8 years old) were fitted with data loggers, which recorded when pairs of sheep were within 4m or less of each other, within a social group, for a total of 6days. In study two proximity data were collected from 45 ewes over 17days, as were measures of ewe temperament, weight and weather. In study 1 age difference significantly influenced daily contact time, with sheep of the same age spending an average of 20min 43s together per day, whereas pairs with the greatest difference in age spent 16min 33s together. Maximum daily temperature also significantly affected contact time, being longer on hotter days (34min 40s hottest day vs. 18min 17s coolest day), as did precipitation (29min 33s wettest day vs. 10min 32s no rain). Vocalisation in isolation, as a measure of temperament, also affected contacts, with sheep with the same frequency of vocalisations spending more time together (27min 16s) than those with the greatest difference in vocalisations (19min 36s). Sheep behaviour in the isolation box test (IBT) was also correlated over time, but vocalisations and movement were not correlated. Influences of age, temperature and rain on social contact are all well-established and so indicate that MMMC modelling is a useful way to analyse social structures of the flock. While it has been demonstrated that personality factors affect social relationships in non-human animals, the finding that vocalisation in isolation influences pair social contact in sheep is a novel one.

A Screen-Peck Task for Investigating Cognitive Bias in Laying Hens

Affect-induced cognitive judgement biases occur in both humans and animals. Animals in a more negative affective state tend to interpret ambiguous cues more negatively than animals in a more positive state and vice versa. Investigating animals’ responses to ambiguous cues can therefore be used as a proxy measure of affective state. We investigated laying hens’ responses to ambiguous stimuli using a novel cognitive bias task. In the ‘screen-peck’ task, hens were trained to peck a high/low saturation orange circle presented on a computer screen (positive cue–P) to obtain a mealworm reward, and to not peck when the oppositely saturated orange circle was presented (negative cue–N) to avoid a one second air puff. Ambiguous cues were orange circles of intermediate saturation between the P and N cue (near-positive–NP; middle–M; near-negative–NN), and were unrewarded. Cue pecking showed a clear generalisation curve from P through NP, M, NN to N suggesting that hens were able to associate colour saturation with reward or punishment, and could discriminate between stimuli that were more or less similar to learnt cues. Across six test sessions, there was no evidence for extinction of pecking responses to ambiguous cues. We manipulated affective state by changing temperature during testing to either ~20°C or ~29°C in a repeated measures cross-over design. Hens have been shown to prefer temperatures in the higher range and hence we assumed that exposure to the higher temperature would induce a relatively positive affective state. Hens tested under warmer conditions were significantly more likely to peck the M probe than those tested at cooler temperatures suggesting that increased temperature in the ranges tested here may have some positive effect on hens, inducing a positive cognitive bias.

The place of experimental design and statistics in the 3Rs

The 3Rs--replacement, reduction, and refinement--can be applied to any animal experiment by researchers and other bodies seeking to conduct those studies in as humane a manner as possible. Key to the success of this endeavor is an appreciation of the principles of good experimental design and analysis; these need to be considered in concert before any data is collected. Indeed, many of the principles central to helping achieve the objectives of the 3Rs-such as conducting valid, reliable, and efficient experiments; clearly and transparently reporting findings; and ensuring that an appreciation and understanding of animal welfare plays a central role in laboratory practice-are to the betterment of research per se.

Managing Conflict between Bats and Humans: The Response of Soprano Pipistrelles (Pipistrellus pygmaeus) to Exclusion from Roosts in Houses

Conflict can arise when bats roost in human dwellings and householders are affected adversely by their presence. In the United Kingdom, the exclusion of bats from roosts can be licensed under exceptional circumstances to alleviate conflict, but the fate of excluded bats and the impact on their survival and reproduction is not well understood. Using radio-tracking, we investigated the effects of exclusion on the soprano pipistrelle Pipistrellus pygmaeus, a species that commonly roosts in buildings in Europe. Exclusions were performed under licence at five roosts in England in spring, when females were in the early stages of pregnancy. Following exclusion, all bats found alternative roosts and colonies congregated in nearby known roosts that had been used by radio-tagged bats prior to exclusion. We found no difference in roosting behaviour before and after exclusion. Both the frequency of roost switching and the type of roosts used by bats remained unchanged. We also found no change in foraging behaviour. Bats foraged in the same areas, travelled similar distances to reach foraging areas and showed similar patterns of habitat selection before and after exclusion. Population modelling suggested that any reduction in survival following exclusion could have a negative impact on population growth, whereas a reduction in productivity would have less effect. While the number of soprano pipistrelle exclusions currently licensed each year is likely to have little effect on local populations, the cumulative impacts of licensing the destruction of large numbers of roosts may be of concern.

Scientific rigor and the art of motorcycle maintenance

The reliability of scientific research is under scrutiny. A recently convened working group proposes cultural adjustments to incentivize better research practices.

Elastography of the normal canine liver, spleen and kidneys

Elastography is a simple, expedient and noninvasive technique that may be used to assess the elasticity or stiffness of a tissue, in conjunction with traditional B-mode ultrasonography. Quantitative assessment of tissue stiffness can be made which involves measurement of the shear wave velocity within the tissue of interest. The goal of this study was to assess the feasibility of elastography for clinical use in the abdomen of conscious small animals and to investigate factors that affect shear wave velocity measurement. Elastography was performed on the liver, spleen, and kidneys of 15 dogs at predefined depths within the parenchyma. Breed, age, gender, neuter status, and weight were documented for each animal. Depth at which measurements were taken had a significant negative relationship with the shear wave velocity value obtained. Individual dog effects, such as weight and gender, also appeared to have a significant effect on the shear wave velocity measurement for specific organs; weight had a significant positive effect on the shear wave velocity for each of the organs examined, whereas the effect of gender was inconsistent between organs (having a positive effect for the liver and a negative effect for the spleen). It is hoped that these results may act as a baseline to guide further work into the field of elastography in companion animals.

Improving Bioscience Research Reporting: The ARRIVE Guidelines for Reporting Animal Research

In the last decade the number of bioscience journals has increased enormously, with many filling specialised niches reflecting new disciplines and technologies. The emergence of open-access journals has revolutionised the publication process, maximising the availability of research data. Nevertheless, a wealth of evidence shows that across many areas, the reporting of biomedical research is often inadequate, leading to the view that even if the science is sound, in many cases the publications themselves are not “fit for purpose”, meaning that incomplete reporting of relevant information effectively renders many publications of limited value as instruments to inform policy or clinical and scientific practice [1–21]. A recent review of clinical research showed that there is considerable cumulative waste of financial resources at all stages of the research process, including as a result of publications that are unusable due to poor reporting [22]. It is unlikely that this issue is confined to clinical research [2–14,16–20].

Multiple-membership multiple-classification models for social network and group dependences

The social network literature on network dependences has largely ignored other sources of dependence, such as the school that a student attends, or the area in which an individual lives. The multilevel modelling literature on school and area dependences has, in turn, largely ignored social networks. To bridge this divide, a multiple-membership multiple-classification modelling approach for jointly investigating social network and group dependences is presented. This allows social network and group dependences on individual responses to be investigated and compared. The approach is used to analyse a subsample of the Adolescent Health Study data set from the USA, where the response variable of interest is individual level educational attainment, and the three individual level covariates are sex, ethnic group and age. Individual, network, school and area dependences are accounted for in the analysis. The network dependences can be accounted for by including the network as a classification in the model, using various network configurations, such as ego-nets and cliques. The results suggest that ignoring the network affects the estimates of variation for the classifications that are included in the random part of the model (school, area and individual), as well as having some influence on the point estimates and standard errors of the estimates of regression coefficients for covariates in the fixed part of the model. From a substantive perspective, this approach provides a flexible and practical way of investigating variation in an individual level response due to social network dependences, and estimating the share of variation of an individual response for network, school and area classifications.

Male mice housed in groups engage in frequent fighting and show a lower response to additional bone loading than females or individually housed males that do not fight

Experiments to investigate bone's physiological adaptation to mechanical loading frequently employ models that apply dynamic loads to bones in vivo and assess the changes in mass and architecture that result. It is axiomatic that bones will only show an adaptive response if the applied artificial loading environment differs in a significant way from that to which the bones have been habituated by normal functional loading. It is generally assumed that this normal loading is similar between experimental groups. In the study reported here we found that this was not always the case. Male and female 17-week-old C57BL/6 mice were housed in groups of six, and a single episode (40 cycles) of non-invasive axial loading, engendering 2,200 με on the medial surface of the proximal tibiae in sample mice, was applied to right tibiae on alternate days for two weeks. This engendered an adaptive increase in bone mass in females, but not males. Observation revealed the main difference in behaviour between males and females was that males were involved in fights 1.3 times per hour, whereas the females never fought. We therefore housed all mice individually. In females, there was a similar significant osteogenic response to loading in cortical and trabecular bone of both grouped and individual mice. In contrast, in males, adaptive increases in the loaded compared with non-loaded control bones was only apparent in animals housed individually. Our interpretation of these findings is that the frequent vigorous fighting that occurs between young adult males housed in groups could be sufficient to engender peak strains and strain rates that equal or exceed the stimulus derived from artificial loading. This indicates the importance of ensuring that physical activity is consistent between groups. Reducing the background level of the naturally engendered strain environment allows adaptive responses to artificial loading to be demonstrated at lower loads.

Factors associated with herd restriction and de-restriction with bovine tuberculosis in British cattle herds

The incidence of herd breakdown (HBD) with bovine tuberculosis (bTB) has continued to increase year on year since the 1980s in Great Britain. The management of bTB constitutes a major challenge for government and the cattle industry. Whilst various factors have been implicated with the risk of HBD with bTB, factors involved in recovery are less well described. In this paper, we used a multilevel multistate model to identify the factors affecting the probability of a herd being placed under restriction following a bTB outbreak and the factors involved in those restrictions being lifted. By modelling both transitions within the same model, we control for unobserved herd-specific characteristics, and investigate the frequency of change between the restricted and derestricted states. There were two patterns of herd breakdown: transient (characterised by fast cycling between restricted and derestricted states) and continuous (characterised by rare changes between the two states). The risk of a herd being placed under restriction was dominated by predictors related to cattle movements. The probability of derestriction increased with more regular testing. Some risks affected both transitions, namely loge mean size of neighbouring herds in the test-year, whether the herd bred its own replacements and the foot and mouth disease indicator of whether a bTB test was done between February 2002 and January 2003, possibly because the underlying true state of the herd, as infected or not, meant that these factors increased or reduced the risk of HBD. These results highlight that management of bTB is dependent on the true underlying herd status of bTB infection and that some confusion of the benefits or otherwise of some management practices, e.g. using home bred replacements can be explained by this underlying status.

Impact of imperfect test sensitivity on determining risk factors: the case of bovine tuberculosis

BACKGROUND

Imperfect diagnostic testing reduces the power to detect significant predictors in classical cross-sectional studies. Assuming that the misclassification in diagnosis is random this can be dealt with by increasing the sample size of a study. However, the effects of imperfect tests in longitudinal data analyses are not as straightforward to anticipate, especially if the outcome of the test influences behaviour. The aim of this paper is to investigate the impact of imperfect test sensitivity on the determination of predictor variables in a longitudinal study.

METHODOLOGY/PRINCIPAL FINDINGS

To deal with imperfect test sensitivity affecting the response variable, we transformed the observed response variable into a set of possible temporal patterns of true disease status, whose prior probability was a function of the test sensitivity. We fitted a Bayesian discrete time survival model using an MCMC algorithm that treats the true response patterns as unknown parameters in the model. We applied our approach to epidemiological data of bovine tuberculosis outbreaks in England and investigated the effect of reduced test sensitivity in the determination of risk factors for the disease. We found that reduced test sensitivity led to changes to the collection of risk factors associated with the probability of an outbreak that were chosen in the 'best' model and to an increase in the uncertainty surrounding the parameter estimates for a model with a fixed set of risk factors that were associated with the response variable.

CONCLUSIONS/SIGNIFICANCE

We propose a novel algorithm to fit discrete survival models for longitudinal data where values of the response variable are uncertain. When analysing longitudinal data, uncertainty surrounding the response variable will affect the significance of the predictors and should therefore be accounted for either at the design stage by increasing the sample size or at the post analysis stage by conducting appropriate sensitivity analyses.

Bones' adaptive response to mechanical loading is essentially linear between the low strains associated with disuse and the high strains associated with the lamellar/woven bone transition

There is a widely held view that the relationship between mechanical loading history and adult bone mass/strength includes an adapted state or "lazy zone" where the bone mass/strength remains constant over a wide range of strain magnitudes. Evidence to support this theory is circumstantial. We investigated the possibility that the "lazy zone" is an artifact and that, across the range of normal strain experience, features of bone architecture associated with strength are linearly related in size to their strain experience. Skeletally mature female C57BL/6 mice were right sciatic neurectomized to minimize natural loading in their right tibiae. From the fifth day, these tibiae were subjected to a single period of external axial loading (40, 10-second rest interrupted cycles) on alternate days for 2 weeks, with a peak dynamic load magnitude ranging from 0 to 14 N (peak strain magnitude: 0-5000 µε) and a constant loading rate of 500 N/s (maximum strain rate: 75,000 µε/s). The left tibiae were used as internal controls. Multilevel regression analyses suggest no evidence of any discontinuity in the progression of the relationships between peak dynamic load and three-dimensional measures of bone mass/strength in both cortical and cancellous regions. These are essentially linear between the low-peak locomotor strains associated with disuse (∼300 µε) and the high-peak strains derived from artificial loading and associated with the lamellar/woven bone transition (∼5000 µε). The strain:response relationship and minimum effective strain are site-specific, probably related to differences in the mismatch in strain distribution between normal and artificial loading at the locations investigated.

Surface shape analysis with an application to brain surface asymmetry in schizophrenia

Some methods for the statistical analysis of surface shapes and asymmetry are introduced. We focus on a case study where magnetic resonance images of the brain are available from groups of 30 schizophrenia patients and 38 controls, and we investigate large-scale brain surface shape differences. Key aspects of shape analysis are to remove nuisance transformations by registration and to identify which parts of one object correspond with the parts of another object. We introduce maximum likelihood and Bayesian methods for registering brain images and providing large-scale correspondences of the brain surfaces. Brain surface size-and-shape analysis is considered using random field theory, and also dimension reduction is carried out using principal and independent components analysis. Some small but significant differences are observed between the the patient and control groups. We then investigate a particular type of asymmetry called torque. Differences in asymmetry are observed between the control and patient groups, which add strength to other observations in the literature. Further investigations of the midline plane location in the 2 groups and the fitting of nonplanar curved midlines are also considered.

Feline extranodal lymphoma: response to chemotherapy and survival in 110 cats

OBJECTIVE

To determine response to treatment, survival and prognostic factors for feline extranodal lymphoma in the UK.

METHODS

Records of cats diagnosed with lymphoma of extranodal sites at seven referral centres were reviewed and information on signalment, tumour location, prior treatment and chemotherapy protocol recorded. Factors influencing response to treatment and survival were assessed.

RESULTS

One hundred and forty-nine cases met inclusion criteria. Sixty-nine cats had nasal lymphoma, 35 renal, 15 central nervous system, 11 laryngeal and 19 miscellaneous locations. Sixty-six cats received cyclophosphamide, vincristine, prednisolone, 25 Wisconsin-Madison doxorubicin-containing multi-agent protocol, 10 prednisolone alone and nine other combinations. The response rate for the 110 treated cats was 85.5 per cent. Of cyclophosphamide, vincristine, prednisolone treated cats 72.7 per cent achieved complete remission, median survival 239 days. Sixty-four per cent of Wisconsin-Madison treated cats achieved complete remission, median survival 563 days. Cats with nasal lymphoma achieving complete remission had the longest survival (749 days) and cats with central nervous system lymphoma the shortest (70 days). If complete remission was achieved, prior treatment with corticosteroids significantly reduced survival time.

CLINICAL SIGNIFICANCE

Cats with extranodal lymphoma respond to chemotherapy and achieve survival times comparable to other locations. Corticosteroid pretreatment reduced survival time in cats achieving complete remission.