73 research outputs found

    Functional Integration of Grafted Neural Stem Cell-Derived Dopaminergic Neurons Monitored by Optogenetics in an In Vitro Parkinson Model

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    Intrastriatal grafts of stem cell-derived dopamine (DA) neurons induce behavioral recovery in animal models of Parkinson's disease (PD), but how they functionally integrate in host neural circuitries is poorly understood. Here, Wnt5a-overexpressing neural stem cells derived from embryonic ventral mesencephalon of tyrosine hydroxylase-GFP transgenic mice were expanded as neurospheres and transplanted into organotypic cultures of wild type mouse striatum. Differentiated GFP-labeled DA neurons in the grafts exhibited mature neuronal properties, including spontaneous firing of action potentials, presence of post-synaptic currents, and functional expression of DA D2 autoreceptors. These properties resembled those recorded from identical cells in acute slices of intrastriatal grafts in the 6-hydroxy-DA-induced mouse PD model and from DA neurons in intact substantia nigra. Optogenetic activation or inhibition of grafted cells and host neurons using channelrhodopsin-2 (ChR2) and halorhodopsin (NpHR), respectively, revealed complex, bi-directional synaptic interactions between grafted cells and host neurons and extensive synaptic connectivity within the graft. Our data demonstrate for the first time using optogenetics that ectopically grafted stem cell-derived DA neurons become functionally integrated in the DA-denervated striatum. Further optogenetic dissection of the synaptic wiring between grafted and host neurons will be crucial to clarify the cellular and synaptic mechanisms underlying behavioral recovery as well as adverse effects following stem cell-based DA cell replacement strategies in PD

    State–Space Forecasting of Schistosoma haematobium Time-Series in Niono, Mali

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    Adequate forecasting and early warning systems are based upon observations of human behavior, population, disease time-series, climate, environment, and/or a combination thereof, whichever option best compromises among realism, feasibility, robustness, and parsimony. Fully automatic and user-friendly state–space forecasting frameworks, incorporating myriad options (e.g., expert opinion, univariate, multivariate, and spatial-temporal), could considerably enhance disease control and hazard mitigation efforts in regions where vulnerability to neglected tropical diseases is pervasive and statistical expertise is scarce. The operational simplicity, generality, and flexibility of state–space frameworks, encapsulating multiple methods, could conveniently allow for 1) unsupervised model selection without disease-specific methodological tailoring, 2) on-line adaptation to disease time-series fluctuations, and 3) automatic switches between distinct forecasting methods as new time-series perturbations dictate. In this investigation, a univariate state–space framework with the aforementioned properties was successfully applied to the Schistosoma haematobium time-series for the district of Niono, Mali, to automatically generate contemporaneous on-line forecasts and hence, providing a basis for local re-organization and strengthening public health programs in this and potentially other Sahelian districts

    Evidence-Based PET for Neurological Diseases

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    Over the past two decades, one of the major breakthroughs for the approach to neurological diseases both in the clinical and research settings has been represented by the validation of diagnostic biomarkers able to demonstrate the presence of pathological mechanisms, alteration in neurotransmission as well as to predict disease progression [1, 2]. The use of PET with different tracers as well as other imaging biomarkers support the etiological diagnosis of neurological disorders in vivo. This approach is particularly relevant in the field of neurodegenerative diseases. In fact, neurodegenerative diseases are characterized by the progressive degeneration and death of neurons. They represent a heterogeneous group of conditions characterized by different etiologies, different neuropathological and neurochemical alterations leading to different clinical pictures and courses [3]. Indeed, an early accurate diagnosis allows to tackle the disease with available or experimental intervention, lifestyle changes, or logistical arrangements, before disability has developed. Early intervention is expected to have greater clinical impact, extend independent and active life, improve its quality, and decrease the burden and costs of the disease [4]. However, the validation of PET tracers in neurological disease is still ongoing, and evidence on its comparative and combined diagnostic value with respect to other biomarkers is incomplete [4, 5]. As a matter of fact, the increasing pressure for cost-effectiveness requires systematic assessment and validation of all biomarker performance in the clinical settings. Similarly only an evidence-based approach to new PET tracers can allow to select the most promising tracers for PET imaging in the research field both for pathophysiological investigations and for upcoming diagnostic approaches
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