Assessment of the wintering area of Red Knots in Maranhão, northern Brazil, in February 2005

To assess population size and the conservation status of the Red Knot Calidris canutus rufa population in Maranhão, N Brazil, an aerial census and field studies were conducted in February 2005. The aerial count showed a population of 7,575 Knots, which is down about 600 from a previous census in the 1980s. However, the count for all shorebird species combined was only 24,000 compared to 198,600 in the 1980s, paralleling a world-wide trend of population decline in shorebirds. Resightings of colour-banded knots confirmed that this is a separate population from the larger wintering population in Tierra del Fuego. All species of shorebirds captured in Maranhão were found to be infested with feather lice and mites. Body masses of knots in Maranhão were significantly lower than in Tierra del Fuego, and about half the birds were below the hypothesized fat-free mass of the species. Blood and feather samples were taken from 38 Knots for subsequent assessment of virus loads, and for detecting sites where primary feather moult had occurred. This will enable us to establish whether significant mortality is associated with pathogen loads and the energetic demands of delayed moulting. The small size of the Maranhão population and the loss of another 13,000 knots this winter from the Tierra del Fuego population means that both are now endangered. Brochures on the need for Red Knot conservation were designed and printed, and have been circulated among fishing communities and school classes in Maranhão.Fil: Baker,Allan J.. Royal Ontario Museum; CanadáFil: González, Patricia M.. Fundación Inalafquen; ArgentinaFil: Serrano, Ines L.. CEMAVE, Centro Nacional de Pesquisa para Conservação das Aves Silvestres; BrasilFil: Júnior, Wallace R. T.. CEMAVE, Centro Nacional de Pesquisa para Conservação das Aves Silvestres; BrasilFil: Efe, Marcio A.. Universidade Federal de Alagoas; BrasilFil: Rice, Susan. Eastern Shore of Virginia National Wildlife Refuge; Estados UnidosFil: D'amico, Veronica Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico; ArgentinaFil: Rocha, Marcia C.. Belém, Pará; BrasilFil: Echave, María Eugenia. Fundación Inalafquen; Argentin

Patterns of mortality in domesticated ruminants in Ethiopia

BACKGROUND: Premature death of livestock is a problem in all ruminant production systems. While the number of premature ruminant deaths in a country is a reasonable indicator for the nation's health, few data sources exist in a country like Ethiopia that can be used to generate valid estimates. The present study aimed to establish if three different data sets, each with imperfect information on ruminant mortality, including abortions, could be combined into improved estimates of nationwide mortality in Ethiopia. METHODS: We combined information from a recent survey of ruminant mortality with information from the Living Standards Measurement Study and the Disease Outbreak and Vaccination Reporting dataset. Generalized linear mixed and hurdle models were used for data analysis, with results summarized using predicted outcomes. RESULTS: Analyses indicated that most herds experienced zero mortality and reproductive losses, with rare occasions of larger losses. Diseases causing deaths varied greatly both geographically and over time. There was little agreement between the different datasets. While the models aid the understanding of patterns of mortality and reproductive losses, the degree of variation observed limited the predictive scope. CONCLUSIONS: The models revealed some insight into why mortality rates are variable over time and are therefore less useful in measuring production or health status, and it is suggested that alternative measures of productivity, such as number of offspring raised to 1 year old per dam, would be more stable over time and likely more indicative

The effect of a peer-led problem-support mentor intervention on self-harm and violence in prison : an interrupted time series analysis using routinely collected prison data

Background: Levels of mental disorder, self-harm and violent behaviour are higher in prisons than in the community. The purpose of this study was to determine whether a brief peer-led problem-support mentor intervention could reduce the incidence of self-harm and violence in an English prison. Methods: An existing intervention was adapted using a theory of change model and eligible prisoners were trained to become problem-support mentors. Delivery of the intervention took two forms: (i) promotion of the intervention to fellow prisoners, offering support and raising awareness of the intervention but not delivering the skills and (ii) delivery of the problem-solving therapy skills to selected individual prisoners. Training and intervention adherence was measured using mentor log books. We used an Interrupted Time Series (ITS) design utilizing prison data over a 31 month period. Three ITS models and sensitivity analyses were used to address the impact across the whole prison and in the two groups by intervention delivery. Outcomes included self-harm and violent behaviour. Routine data were collected at monthly intervals 16 months pre-, 10 months during and six months post-intervention. Qualitative data measured the acceptability, feasibility, impact and sustainability of the intervention. A matched case-control study followed people after release to assess the feasibility of formal evaluation of the impact on re-offending up to 16 months. Findings: Our causal map identified that mental health and wellbeing in the prison were associated with environmental and social factors. We found a significant reduction in the incidence of self-harm for those receiving the full problem-solving therapy skills. No significant reduction was found for incidence of violent behaviour. Interpretation: Universal prison-wide strategies should consider a series of multi-level interventions to address mental health and well-being in prisons

Agreement Between Experts and an Untrained Crowd for Identifying Dermoscopic Features Using a Gamified App: Reader Feasibility Study

Background Dermoscopy is commonly used for the evaluation of pigmented lesions, but agreement between experts for identification of dermoscopic structures is known to be relatively poor. Expert labeling of medical data is a bottleneck in the development of machine learning (ML) tools, and crowdsourcing has been demonstrated as a cost- and time-efficient method for the annotation of medical images. Objective The aim of this study is to demonstrate that crowdsourcing can be used to label basic dermoscopic structures from images of pigmented lesions with similar reliability to a group of experts. Methods First, we obtained labels of 248 images of melanocytic lesions with 31 dermoscopic “subfeatures” labeled by 20 dermoscopy experts. These were then collapsed into 6 dermoscopic “superfeatures” based on structural similarity, due to low interrater reliability (IRR): dots, globules, lines, network structures, regression structures, and vessels. These images were then used as the gold standard for the crowd study. The commercial platform DiagnosUs was used to obtain annotations from a nonexpert crowd for the presence or absence of the 6 superfeatures in each of the 248 images. We replicated this methodology with a group of 7 dermatologists to allow direct comparison with the nonexpert crowd. The Cohen κ value was used to measure agreement across raters. Results In total, we obtained 139,731 ratings of the 6 dermoscopic superfeatures from the crowd. There was relatively lower agreement for the identification of dots and globules (the median κ values were 0.526 and 0.395, respectively), whereas network structures and vessels showed the highest agreement (the median κ values were 0.581 and 0.798, respectively). This pattern was also seen among the expert raters, who had median κ values of 0.483 and 0.517 for dots and globules, respectively, and 0.758 and 0.790 for network structures and vessels. The median κ values between nonexperts and thresholded average–expert readers were 0.709 for dots, 0.719 for globules, 0.714 for lines, 0.838 for network structures, 0.818 for regression structures, and 0.728 for vessels. Conclusions This study confirmed that IRR for different dermoscopic features varied among a group of experts; a similar pattern was observed in a nonexpert crowd. There was good or excellent agreement for each of the 6 superfeatures between the crowd and the experts, highlighting the similar reliability of the crowd for labeling dermoscopic images. This confirms the feasibility and dependability of using crowdsourcing as a scalable solution to annotate large sets of dermoscopic images, with several potential clinical and educational applications, including the development of novel, explainable ML tools

Interspecies Translation of Disease Networks Increases Robustness and Predictive Accuracy

Gene regulatory networks give important insights into the mechanisms underlying physiology and pathophysiology. The derivation of gene regulatory networks from high-throughput expression data via machine learning strategies is problematic as the reliability of these models is often compromised by limited and highly variable samples, heterogeneity in transcript isoforms, noise, and other artifacts. Here, we develop a novel algorithm, dubbed Dandelion, in which we construct and train intraspecies Bayesian networks that are translated and assessed on independent test sets from other species in a reiterative procedure. The interspecies disease networks are subjected to multi-layers of analysis and evaluation, leading to the identification of the most consistent relationships within the network structure. In this study, we demonstrate the performance of our algorithms on datasets from animal models of oculopharyngeal muscular dystrophy (OPMD) and patient materials. We show that the interspecies network of genes coding for the proteasome provide highly accurate predictions on gene expression levels and disease phenotype. Moreover, the cross-species translation increases the stability and robustness of these networks. Unlike existing modeling approaches, our algorithms do not require assumptions on notoriously difficult one-to-one mapping of protein orthologues or alternative transcripts and can deal with missing data. We show that the identified key components of the OPMD disease network can be confirmed in an unseen and independent disease model. This study presents a state-of-the-art strategy in constructing interspecies disease networks that provide crucial information on regulatory relationships among genes, leading to better understanding of the disease molecular mechanisms

A systematic review of intrapersonal coach development programs: Examining the development and evaluation of programs to elicit coach reflection

The current approaches used to develop coaches within many sport organisations extend beyond merely the professional knowledge related to sport-specific aspects. Effective coaching notably entails intrapersonal skills related to learning through experience and developing one’s own approach, and these skills are often targeted in coach development. Recognising that researchers have delivered Coach Development Programs (CDPs) that use strategies like reflective practice to foster coaches’ strategies and attitudes toward reflection, reviewing research in this domain could inform the development of our field. We conducted the current review to examine nonformal intrapersonal CDPs within the academic literature with goals of summarising existing CDPs, while also identifying factors related to their implementation. Method: The PRISMA guidelines informed our search strategy, including a database search along with supplemental strategies to identify studies. In addition to describing the CDPs generally, each study was also coded for: (a) potential to be implemented and maintained in sport contexts, (b) behaviour change techniques (BCTs), and (c) risk of bias. Results: After screening the full-texts of studies, we identified 10 unique intrapersonal CDPs. Most CDPs entailed pilot investigations of small samples, involving both qualitative and quantitative methods focused on coaches’ experiences when using reflective strategies. The majority of CDPs were conducted in-person and in one-on-one contexts. The most frequently used BCT was self-monitoring of behaviour, and low-to-moderate information was reported regarding internal and external validity. Conclusions: Whereas reflective practice may enable coach development, researchers must seek opportunities to design higher-quality intervention studies that are designed to enhance both internal and external validity