Can sleep and resting behaviours be used as indicators of welfare in shelter dogs (Canis lupusfamiliaris)?

Previous research on humans and animals suggests that the analysis of sleep patterns may reliably inform us about welfare status, but little research of this kind has been carried out for non-human animals in an applied context. This study explored the use of sleep and resting behaviour as indicators of welfare by describing the activity patterns of dogs (Canis lupus familiaris) housed in rescue shelters, and comparing their sleep patterns to other behavioural and cognitive measures of welfare. Sleep and activity patterns were observed over five non-consecutive days in a population of 15 dogs. Subsequently, the characteristics of sleep and resting behaviour were described and the impact of activity on patterns of sleep and resting behaviour analysed. Shelter dogs slept for 2.8% of the day, 14.3% less than previously reported and experienced less sleep fragmentation at night (32 sleep bouts). There were no statistically significant relationships between behaviours exhibited during the day and sleep behaviour. A higher proportion of daytime resting behaviour was significantly associated with a positive judgement bias, less repetitive behaviour and increased time spent coded as ‘relaxed’ across days by shelter staff. These results suggest that, in the context of a busy shelter environment, the ability to rest more during the day could be a sign of improved welfare. Considering the non-linear relationship between sleep and welfare in humans, the relationship between sleep and behavioural indicators of welfare, including judgement bias, in shelter dogs may be more complex than this study could detect

Neuropathology in Mouse Models of Mucopolysaccharidosis Type I, IIIA and IIIB

Mucopolysaccharide diseases (MPS) are caused by deficiency of glycosaminoglycan (GAG) degrading enzymes, leading to GAG accumulation. Neurodegenerative MPS diseases exhibit cognitive decline, behavioural problems and shortened lifespan. We have characterised neuropathological changes in mouse models of MPSI, IIIA and IIIB to provide a better understanding of these events

Systematic screening for unsafe driving due to medical conditions: Still debatable

<p>Abstract</p> <p>Background</p> <p>Assessing people's ability to drive has become a public health concern in most industrialized countries. Although age itself is not a predictive factor of an increased risk for dangerous driving, the prevalence of medical conditions that may impair driving increases with age. Because the implementation of a screening for unsafe driving due to medical conditions is a public health issue, its usefulness should be judged using standardised criteria already proposed for screening for chronic disease. The aim of this paper is to propose standardised criteria suitable to assess the scientific validity of screening for unsafe driving due to medical conditions, and identify potential issues to be clarified before screening can be implemented and effective.</p> <p>Discussion</p> <p>Using criteria developed for screening for chronic diseases and published studies on driving with medical conditions, we specify six criteria to judge the opportunity of screening for unsafe driving due to medical conditions. This adaptation was needed because of the complexity of the natural history of medical conditions and their potential consequences on driving and road safety. We then illustrate that published studies pleading for or against screening for unsafe driving due to medical conditions fail to provide the needed documentation. Individual criteria were mentioned in 3 to 72% of 36 papers pleading for or against screening. Quantitative estimates of relevant indicators were provided in at most 42% of papers, and some data, such as the definition of an appropriate unsafe driving period were never provided.</p> <p>Summary</p> <p>The standardised framework described in this paper provides a template for assessing the effectiveness (or lack of effectiveness) of proposed measures for screening for unsafe driving due to medical conditions. Even if most criteria were mentioned in the published literature pleading for or against such a screening, the failure to find quantitative and evidence-based estimates of relevant indicators provides useful insight for further research.</p

A multi-omics machine learning classifier for outgrowth of cow\u27s milk allergy in children

\ua9 The Royal Society of Chemistry 2025.Cow’s milk protein allergy (CMA) is one of the most common food allergies in children worldwide. However, it is still not well understood why certain children outgrow their CMA and others do not. While there is increasing evidence for a link of CMA with the gut microbiome, it is still unclear how the gut microbiome and metabolome interact with the immune system. Integrating data from different omics platforms and clinical data can help to unravel these interactions. In this study, we integrate clinical, microbial, (meta)proteomics, immune and metabolomics data into machine learning (ML) classification, using multi-view learning by late integration. The aim is to group infants into those that outgrew their CMA and those that did not. The results show that integration of microbiome data with clinical, immune, (meta)proteomics and metabolomics data could considerably improve classification of infants on outgrowth of CMA, compared to only considering one type of data. Moreover, pathways previously linked to development of CMA could also be related to outgrowth of this allergy

Optimizing the Temperature Sensitivity of the Isoprene Emission Model MEGAN in Different Ecosystems Using a Metropolis-Hastings Markov Chain Monte Carlo Method

Isoprene is a reactive hydrocarbon emitted to the atmosphere in large quantities by terrestrial vegetation. Annual total isoprene emissions exceed 300 Tg a−1, but emission rates vary widely among plant species and are sensitive to meteorological and environmental conditions including temperature, sunlight, and soil moisture. Due to its high reactivity, isoprene has a large impact on air quality and climate pollutants such as ozone and aerosols. It is also an important sink for the hydroxyl radical which impacts the lifetime of the important greenhouse gas methane along with many other trace gas species. Modeling the impacts of isoprene emissions on atmospheric chemistry and climate requires accurate isoprene emission estimates. These can be obtained using the empirical Model of Emissions of Gases and Aerosols from Nature (MEGAN), but the parameterization of this model is uncertain due in part to limited field observations. In this study, we use ground-based measurements of isoprene concentrations and fluxes from 11 field sites to assess the variability of the isoprene emission temperature response across ecosystems. We then use these observations in a Metropolis-Hastings Markov Chain Monte Carlo (MHMCMC) data assimilation framework to optimize the MEGAN temperature response function. We find that the performance of MEGAN can be significantly improved at several high-latitude field sites by increasing the modeled sensitivity of isoprene emissions to past temperatures. At some sites, the optimized model was nearly four times more sensitive to temperature than the unoptimized model. This has implications for air quality modeling in a warming climate

The potential impacts of changes in bear hunting policy for hunting organisations in Croatia

The brown bear (Ursus arctos) in Croatia is currently being managed through trophy hunting, with quotas allocated to local hunting organisations. Human-bear conflict is present at a low level, but any losses are compensated by the hunting organisations that benefit from bear hunting. Attitudes towards bears are generally positive, and the bear population appears stable, or even increasing. Croatia's current bear hunting policy relies upon both the ecological sustainability of the quotas and the economic sustainability of the hunting organisations. To address the first of these pillars of current policy, we used a two-sex matrix model of the bear population to investigate the biological sustainability of current hunting levels. The model suggests that if the annual allocated quota were fully realised, the population would suffer a considerable decrease over 10 years. A likely explanation for the mismatch between this result and the observed stability of the population is that the bear population size is underestimated. To address the second pillar, we quantified the current structure, costs and benefits of bear hunting to hunting organisations through an interview survey with hunting managers. We found that bear hunting is a substantial component of hunting organisations' income, supporting the other activities of the organisation. Croatia's recent accession to the EU will require changes in their bear management system, potentially stopping bear trophy hunting. Therefore, we assessed the changes in hunting organisations' budgets in the absence of bear hunting. Our results demonstrate that a loss of bear trophy hunting would result in a substantial loss of income to the hunting organisations. Moving bear hunting and compensation mechanisms from local management and responsibility to a more centralised system without trophy hunting, as suggested by EU legislation, will lead to considerable uncertainties. These include how to make centralised decisions on population targets and offtake levels for population control, given the uncertainty around population estimates, and on compensation payments given the loss of the current system which relies heavily on local income from trophy hunting, local relationships and informal monetary and non-monetary compensation

Social media for health promotion and weight management: A critical debate

© 2018 The Author(s). Background: In 2016 an estimated 1.9 billion adults world-wide were either overweight or obese. The health consequences of obesity are responsible for 2.8 million preventable deaths per year. The WHO now considers obesity as a global epidemic and recommends population-wide health promotion strategies to address this issue. Weight gain is caused by increased energy intake and physical inactivity, so treatment should focus on changes to behaviour regarding diet and physical activity. Discussion: The WHO has also recognised the importance of social resources as a valuable agent for behaviour change in health promotion. Social resources are translated at the community level as support provided by significant others such as family, partners and peers, in the form of information, material aid and encouragement. Social support has been shown to improve health and well-being, whereas social isolation has been shown to have a negative impact on health outcomes. Social support provided by peers has been shown to be a useful strategy to employ in weight management programmes. The documented increased use of ICT and social media has presented health promoters with a potentially useful medium to increase social support for weight management. Conclusion: While the use of social media for health promotion is an emerging field of investigation, preliminary research suggests that it increases participant engagement, and may provide a cost-effective tool to provide social support for individuals participating in weight management programmes. With stringent privacy protocols in place, social media may be a useful, cost-effective accompaniment to multifactorial weight management programmes. However more research is needed to identify how to make the best use of social media as health promotion tool

Nuclear Factor-Kappa B Family Member RelB Inhibits Human Immunodeficiency Virus-1 Tat-Induced Tumor Necrosis Factor-Alpha Production

Human Immunodeficiency Virus-1 (HIV-1)-associated neurocognitive disorder (HAND) is likely neuroinflammatory in origin, believed to be triggered by inflammatory and oxidative stress responses to cytokines and HIV protein gene products such as the HIV transactivator of transcription (Tat). Here we demonstrate increased messenger RNA for nuclear factor-kappa B (NF-κB) family member, transcription factor RelB, in the brain of doxycycline-induced Tat transgenic mice, and increased RelB synthesis in Tat-exposed microglial cells. Since genetic ablation of RelB in mice leads to multi-organ inflammation, we hypothesized that Tat-induced, newly synthesized RelB inhibits cytokine production by microglial cells, possibly through the formation of transcriptionally inactive RelB/RelA complexes. Indeed, tumor necrosis factor-alpha (TNFα) production in monocytes isolated from RelB deficient mice was significantly higher than in monocytes isolated from RelB expressing controls. Moreover, RelB overexpression in microglial cells inhibited Tat-induced TNFα synthesis in a manner that involved transcriptional repression of the TNFα promoter, and increased phosphorylation of RelA at serine 276, a prerequisite for increased RelB/RelA protein interactions. The Rel-homology-domain within RelB was necessary for this interaction. Overexpression of RelA itself, in turn, significantly increased TNFα promoter activity, an effect that was completely blocked by RelB overexpression. We conclude that RelB regulates TNFα cytokine synthesis by competitive interference binding with RelA, which leads to downregulation of TNFα production. Moreover, because Tat activates both RelB and TNFα in microglia, and because Tat induces inflammatory TNFα synthesis via NF-κB, we posit that RelB serves as a cryoprotective, anti-inflammatory, counter-regulatory mechanism for pathogenic NF-κB activation. These findings identify a novel regulatory pathway for controlling HIV-induced microglial activation and cytokine production that may have important therapeutic implications for the management of HAND