227 research outputs found

    An efficient computing strategy for prediction in mixed linear models

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    After estimation of effects from a linear mixed model, it is often useful to form predicted values for certain factor/variate combinations. This process has been well-defined for linear models, but the introduction of random effects means that a decision has to be made about the inclusion or exclusion of random model terms from the predictions, including the residual error. For spatially correlated data, kriging then becomes prediction from the fitted model. In many cases, the size of the matrices required to calculate predictions and their covariance matrix directly can be prohibitive. An efficient computational strategy for calculating predictions and their standard errors is given, which includes the ability to detect the invariance of predictions to the parameterisation used in the model

    Size and shape constancy in consumer virtual reality

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    With the increase in popularity of consumer virtual reality headsets, for research and other applications, it is important to understand the accuracy of 3D perception in VR. We investigated the perceptual accuracy of near-field virtual distances using a size and shape constancy task, in two commercially available devices. Participants wore either the HTC Vive or the Oculus Rift and adjusted the size of a virtual stimulus to match the geometric qualities (size and depth) of a physical stimulus they were able to refer to haptically. The judgments participants made allowed for an indirect measure of their perception of the egocentric, virtual distance to the stimuli. The data show under-constancy and are consistent with research from carefully calibrated psychophysical techniques. There was no difference in the degree of constancy found in the two headsets. We conclude that consumer virtual reality headsets provide a sufficiently high degree of accuracy in distance perception, to allow them to be used confidently in future experimental vision science, and other research applications in psychology

    Mesenchymal stem cells secretome-induced axonal outgrowth is mediated by BDNF

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    Mesenchymal stem cells (MSCs) have been used for cell-based therapies in regenerative medicine, with increasing importance in central and peripheral nervous system repair. However, MSCs grafting present disadvantages, such as, a high number of cells required for transplantation and low survival rate when transplanted into the central nervous system (CNS). In line with this, MSCs secretome which present on its composition a wide range of molecules (neurotrophins, cytokines) and microvesicles, can be a solution to surpass these problems. However, the effect of MSCs secretome in axonal elongation is poorly understood. In this study, we demonstrate that application of MSCs secretome to both rat cortical and hippocampal neurons induces an increase in axonal length. In addition, we show that this growth effect is axonal intrinsic with no contribution from the cell body. To further understand which are the molecules required for secretome-induced axonal outgrowth effect, we depleted brain-derived neurotrophic factor (BDNF) from the secretome. Our results show that in the absence of BDNF, secretome-induced axonal elongation effect is lost and that axons present a reduced axonal growth rate. Altogether, our results demonstrate that MSCs secretome is able to promote axonal outgrowth in CNS neurons and this effect is mediated by BDNF.European Regional Development Fund (ERDF), through the Centro 2020 Regional Operational Programme under project CENTRO-01–0145-FEDER-000008:BrainHealth 2020, and through the COMPETE 2020 - Operational Programme for Competitiveness and Internationalisation and Portuguese national funds via FCT – Fundação para a Ciência e a Tecnologia, I.P., under projects PTDC/SAU-NEU/104100/2008, EXPL/NEU-NMC/0541/2012 and UID/NEU/04539/2013. This work was also funded by Marie Curie Actions - International reintegration grant #249288, 7th Framework programme, EU. Partially funded by Prémios Santa Casa Neurociências - Prize Melo e Castro for Spinal Cord Injury Research; Portuguese Foundation for Science and Technology (IF Development Grant to A.J.S.); NORTE-01-0145-FEDER-000013, supported by the Northern Portugal Regional Operational Programme; by FEDER funds, through the Competitiveness Factors Operational Programme (COMPETE), and by national funds, through the Foundation for Science and Technology (FCT), under the scope of the project POCI-01-0145-FEDER-007038. The authors would also like to acknowledge Prof. J.E. Davies from the Institute of Biomaterials and Biomedical Engineering at the University of Toronto, Canada, for kindly providing some of the HUCPVCs lots used in the present workinfo:eu-repo/semantics/publishedVersio

    Clonal human fetal ventral mesencephalic dopaminergic neuron precursors for cell therapy research

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    A major challenge for further development of drug screening procedures, cell replacement therapies and developmental studies is the identification of expandable human stem cells able to generate the cell types needed. We have previously reported the generation of an immortalized polyclonal neural stem cell (NSC) line derived from the human fetal ventral mesencephalon (hVM1). This line has been biochemically, genetically, immunocytochemically and electrophysiologically characterized to document its usefulness as a model system for the generation of A9 dopaminergic neurons (DAn). Long-term in vivo transplantation studies in parkinsonian rats showed that the grafts do not mature evenly. We reasoned that diverse clones in the hVM1 line might have different abilities to differentiate. In the present study, we have analyzed 9 hVM1 clones selected on the basis of their TH generation potential and, based on the number of v-myc copies, v-myc down-regulation after in vitro differentiation, in vivo cell cycle exit, TH+ neuron generation and expression of a neuronal mature marker (hNSE), we selected two clones for further in vivo PD cell replacement studies. The conclusion is that homogeneity and clonality of characterized NSCs allow transplantation of cells with controlled properties, which should help in the design of long-term in vivo experimentsThis work was supported by grants from the Spanish Ministry of Economy and Competitiveness (formerly Science and Innovation; PLE2009-0101, SAF2010-17167), Comunidad Autónoma Madrid (S2011-BMD-2336), Instituto Salud Carlos III (RETICS TerCel, RD06/0010/0009) and European Union (Excell, NMP4-SL-2008-214706). This work was also supported by an institutional grant from Foundation Ramón Areces to the Center of Molecular Biology Severo Ocho

    How Haptic Size Sensations Improve Distance Perception

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    Determining distances to objects is one of the most ubiquitous perceptual tasks in everyday life. Nevertheless, it is challenging because the information from a single image confounds object size and distance. Though our brains frequently judge distances accurately, the underlying computations employed by the brain are not well understood. Our work illuminates these computions by formulating a family of probabilistic models that encompass a variety of distinct hypotheses about distance and size perception. We compare these models' predictions to a set of human distance judgments in an interception experiment and use Bayesian analysis tools to quantitatively select the best hypothesis on the basis of its explanatory power and robustness over experimental data. The central question is: whether, and how, human distance perception incorporates size cues to improve accuracy. Our conclusions are: 1) humans incorporate haptic object size sensations for distance perception, 2) the incorporation of haptic sensations is suboptimal given their reliability, 3) humans use environmentally accurate size and distance priors, 4) distance judgments are produced by perceptual “posterior sampling”. In addition, we compared our model's estimated sensory and motor noise parameters with previously reported measurements in the perceptual literature and found good correspondence between them. Taken together, these results represent a major step forward in establishing the computational underpinnings of human distance perception and the role of size information.National Institutes of Health (U.S.) (NIH grant R01EY015261)University of Minnesota (UMN Graduate School Fellowship)National Science Foundation (U.S.) (Graduate Research Fellowship)University of Minnesota (UMN Doctoral Dissertation Fellowship)National Institutes of Health (U.S.) (NIH NRSA grant F32EY019228-02)Ruth L. Kirschstein National Research Service Awar
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