DISC1-dependent Regulation of Mitochondrial Dynamics Controls the Morphogenesis of Complex Neuronal Dendrites

The DISC1 protein is implicated in major mental illnesses including schizophrenia, depression, bipolar disorder, and autism. Aberrant mitochondrial dynamics are also associated with major mental illness. DISC1 plays a role in mitochondrial transport in neuronal axons, but its effects in dendrites have yet to be studied. Further, the mechanisms of this regulation and its role in neuronal development and brain function are poorly understood. Here we have demonstrated that DISC1 couples to the mitochondrial transport and fusion machinery via interaction with the outer mitochondrial membrane GTPase proteins Miro1 and Miro2, the TRAK1 and TRAK2 mitochondrial trafficking adaptors, and the mitochondrial fusion proteins (mitofusins). Using live cell imaging, we show that disruption of the DISC1-Miro-TRAK complex inhibits mitochondrial transport in neurons. We also show that the fusion protein generated from the originally described DISC1 translocation (DISC1-Boymaw) localizes to the mitochondria, where it similarly disrupts mitochondrial dynamics. We also show by super resolution microscopy that DISC1 is localized to endoplasmic reticulum contact sites and that the DISC1-Boymaw fusion protein decreases the endoplasmic reticulum-mitochondria contact area. Moreover, disruption of mitochondrial dynamics by targeting the DISC1-Miro-TRAK complex or upon expression of the DISC1-Boymaw fusion protein impairs the correct development of neuronal dendrites. Thus, DISC1 acts as an important regulator of mitochondrial dynamics in both axons and dendrites to mediate the transport, fusion, and cross-talk of these organelles, and pathological DISC1 isoforms disrupt this critical function leading to abnormal neuronal development

Structure and Dynamics of Sheep Systems in Bosnia and Herzegovina

The paper presents the analysis of dynamics and structure of the sheep systems in Bosnia and Herzegovina assuming that they suffered a decrease of animal and farms consistency in the last 6 decades. Since 1991 neither a general nor agricultural censuses were made to provide information about the present state of sheep farming in the country. An analysis of the available statistical records of agricultural trends related to the sheep sector was performed. In addition, a depth questionnaire by consulting national experts was performed in order to obtain relevant information on the spatial distribution, consistency, feeding management, production and environmental impact on the present structure of sheep production systems. A decrease in sheep number was observed over the last six decades, but less than in other species. Six main sheep systems in three biogeographical regions were identified. Differences in animal spatial distribution, production purpose and other characteristics of the systems indicate that the environmental and socio-economic factors throughout the country strongly influence the choice of breeding methods and management. All consulted experts indicated the lack of support for sheep systems in relation to agro environmental management, landscape conservation and biodiversity preservation

Extending classical planning with state constraints: Heuristics and search for optimal planning

We present a principled way of extending a classical AI planning formalism with systems of state constraints, which relate - sometimes determine - the values of variables in each state traversed by the plan. This extension occupies an attractive middle ground between expressivity and complexity. It enables modelling a new range of problems, as well as formulating more efficient models of classical planning problems. An example of the former is planning-based control of networked physical systems - power networks, for example - in which a local, discrete control action can have global effects on continuous quantities, such as altering flows across the entire network. At the same time, our extension remains decidable as long as the satisfiability of sets of state constraints is decidable, including in the presence of numeric state variables, and we demonstrate that effective techniques for cost-optimal planning known in the classical setting - in particular, relaxation-based admissible heuristics - can be adapted to the extended formalism. In this paper, we apply our approach to constraints in the form of linear or non-linear equations over numeric state variables, but the approach is independent of the type of state constraints, as long as there exists a procedure that decides their consistency. The planner and the constraint solver interact through a well-defined, narrow interface, in which the solver requires no specialisation to the planning contextThis work was supported by ARC project DP140104219, “Robust AI Planning for Hybrid Systems”, and in part by ARO grant W911NF1210471 and ONR grant N000141210430

Miro clusters regulate ER-mitochondria contact sites and link cristae organization to the mitochondrial transport machinery

Mitochondrial Rho (Miro) GTPases localize to the outer mitochondrial membrane and are essential machinery for the regulated trafficking of mitochondria to defined subcellular locations. However, their sub-mitochondrial localization and relationship with other critical mitochondrial complexes remains poorly understood. Here, using super-resolution fluorescence microscopy, we report that Miro proteins form nanometer-sized clusters along the mitochondrial outer membrane in association with the Mitochondrial Contact Site and Cristae Organizing System (MICOS). Using knockout mouse embryonic fibroblasts we show that Miro1 and Miro2 are required for normal mitochondrial cristae architecture and Endoplasmic Reticulum-Mitochondria Contacts Sites (ERMCS). Further, we show that Miro couples MICOS to TRAK motor protein adaptors to ensure the concerted transport of the two mitochondrial membranes and the correct distribution of cristae on the mitochondrial membrane. The Miro nanoscale organization, association with MICOS complex and regulation of ERMCS reveal new levels of control of the Miro GTPases on mitochondrial functionality

Managing COVID-19 within and across health systems:why we need performance intelligence to coordinate a global response

Background The COVID-19 pandemic is a complex global public health crisis presenting clinical, organisational and system-wide challenges. Different research perspectives on health are needed in order to manage and monitor this crisis. Performance intelligence is an approach that emphasises the need for different research perspectives in supporting health systems’ decision-makers to determine policies based on well-informed choices. In this paper, we present the viewpoint of the Innovative Training Network for Healthcare Performance Intelligence Professionals (HealthPros) on how performance intelligence can be used during and after the COVID-19 pandemic. Discussion A lack of standardised information, paired with limited discussion and alignment between countries contribute to uncertainty in decision-making in all countries. Consequently, a plethora of different non-data-driven and uncoordinated approaches to address the outbreak are noted worldwide. Comparative health system research is needed to help countries shape their response models in social care, public health, primary care, hospital care and long-term care through the different phases of the pandemic. There is a need in each phase to compare context-specific bundles of measures where the impact on health outcomes can be modelled using targeted data and advanced statistical methods. Performance intelligence can be pursued to compare data, construct indicators and identify optimal strategies. Embracing a system perspective will allow countries to take coordinated strategic decisions while mitigating the risk of system collapse.A framework for the development and implementation of performance intelligence has been outlined by the HealthPros Network and is of pertinence. Health systems need better and more timely data to govern through a pandemic-induced transition period where tensions between care needs, demand and capacity are exceptionally high worldwide. Health systems are challenged to ensure essential levels of healthcare towards all patients, including those who need routine assistance. Conclusion Performance intelligence plays an essential role as part of a broader public health strategy in guiding the decisions of health system actors on the implementation of contextualised measures to tackle COVID-19 or any future epidemic as well as their effect on the health system at large. This should be based on commonly agreed-upon standardised data and fit-for-purpose indicators, making optimal use of existing health information infrastructures. The HealthPros Network can make a meaningful contribution