144 research outputs found

    Preoperative localization techniques during thoracoscopic operations

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    A computational approach to managing coupled human–environmental systems: the POSEIDON model of ocean fisheries

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    Sustainable management of complex human–environment systems, and the essential services they provide, remains a major challenge, felt from local to global scales. These systems are typically highly dynamic and hard to predict, particularly in the context of rapid environmental change, where novel sets of conditions drive coupled socio-economic-environmental responses. Faced with these challenges, our tools for policy development, while informed by the past experience, must not be unduly constrained; they must allow equally for both the fine-tuning of successful existing approaches and the generation of novel ones in unbiased ways. We study ocean fisheries as an example class of complex human–environmental systems, and present a new model (POSEIDON) and computational approach to policy design. The model includes an adaptive agent-based representation of a fishing fleet, coupled to a simplified ocean ecology model. The agents (fishing boats) do not have programmed responses based on empirical data, but respond adaptively, as a group, to their environment (including policy constraints). This conceptual model captures qualitatively a wide range of empirically observed fleet behaviour, in response to a broad set of policies. Within this framework, we define policy objectives (of arbitrary complexity) and use Bayesian optimization over multiple model runs to find policy parameters that best meet the goals. The trade-offs inherent in this approach are explored explicitly. Taking this further, optimization is used to generate novel hybrid policies. We illustrate this approach using simulated examples, in which policy prescriptions generated by our computational methods are counterintuitive and thus unlikely to be identified by conventional frameworks

    Genetic and pharmacological regulation of the endocannabinoid CB1 receptor in Duchenne muscular dystrophy

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    The endocannabinoid system refers to a widespread signaling system and its alteration is implicated in a growing number of human diseases. However, the potential role of endocannabinoids in skeletal muscle disorders remains unknown. Here we report the role of the endocannabinoid CB1 receptors in Duchenne's muscular dystrophy. In murine and human models, CB1 transcripts show the highest degree of expression at disease onset, and then decline overtime. Similar changes are observed for PAX7, a key regulator of muscle stem cells. Bioinformatics and biochemical analysis reveal that PAX7 binds and upregulates the CB1 gene in dystrophic more than in healthy muscles. Rimonabant, an antagonist of CB1, promotes human satellite cell differentiation in vitro, increases the number of regenerated myofibers, and prevents locomotor impairment in dystrophic mice. In conclusion, our study uncovers a PAX7-CB1 cross talk potentially exacerbating DMD and highlights the role of CB1 receptors as target for potential therapies

    Continuous population-level monitoring of SARS-CoV-2 seroprevalence in a large European metropolitan region.

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    Effective public health measures against SARS-CoV-2 require granular knowledge of population-level immune responses. We developed a Tripartite Automated Blood Immunoassay (TRABI) to assess the IgG response against three SARS-CoV-2 proteins. We used TRABI for continuous seromonitoring of hospital patients and blood donors (n = 72'250) in the canton of Zurich from December 2019 to December 2020 (pre-vaccine period). We found that antibodies waned with a half-life of 75 days, whereas the cumulative incidence rose from 2.3% in June 2020 to 12.2% in mid-December 2020. A follow-up health survey indicated that about 10% of patients infected with wildtype SARS-CoV-2 sustained some symptoms at least twelve months post COVID-19. Crucially, we found no evidence of a difference in long-term complications between those whose infection was symptomatic and those with asymptomatic acute infection. The cohort of asymptomatic SARS-CoV-2-infected subjects represents a resource for the study of chronic and possibly unexpected sequelae
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