Plos One
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Gene therapy model of X-linked severe combined immunodeficiency using a modified foamy virus vector.
X-linked severe combined immunodeficiency (SCID-X1) is an inherited genetic immunodeficiency associated with mutations in the common cytokine receptor γ chain (γc) gene, and characterized by a complete defect of T and natural killer (NK) cells. Gene therapy for SCID-X1 using conventional retroviral (RV) vectors carrying the γc gene results in the successful reconstitution of T cell immunity. However, the high incidence of vector-mediated T cell leukemia, caused by vector insertion near or within cancer-related genes has been a serious problem. ⋯ To evaluate the therapeutic efficacy, bone marrow cells from γc-knockout (γc-KO) mice were infected with the FV vector and transplanted into γc-KO mice. Transplantation of the FV-treated cells resulted in the successful reconstitution of functionally active T and B cells. These data suggest that FV vectors can be effective and may be safer than conventional RV vectors for gene therapy for SCID-X1.
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Renal interstitial fibrosis (RIF) is the common pathological process of chronic kidney diseases leading inevitably to renal function deterioration. RIF and its preceding epithelial-mesenchymal transition (EMT) are commonly triggered by an early occurring renal inflammation. However, an effective approach to prevent EMT and RIF is still lacking and of urgent need. ⋯ Our data demonstrated that activation of A2AR significantly suppressed the deposition of collagen types I and III, reduced the infiltration of CD4+ T lymphocytes, and attenuated the expression of TGF-β1 and ROCK1, which in turn inhibited and postponed the EMT progress. Conversely, genetic inactivation of A2AR exacerbated the aforementioned pathological processes of UUO-induced RIF. Together, activation of A2AR effectively alleviated EMT and RIF in mice, suggesting A2AR as a potential therapeutic target for the treatment of RIF.
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Physical exercise promotes neural plasticity in the brain of healthy subjects and modulates pathophysiological neural plasticity after sensorimotor loss, but the mechanisms of this action are not fully understood. After spinal cord injury, cortical reorganization can be maximized by exercising the non-affected body or the residual functions of the affected body. However, exercise per se also produces systemic changes - such as increased cardiovascular fitness, improved circulation and neuroendocrine changes - that have a great impact on brain function and plasticity. ⋯ Using western blot analysis, we found that the level of proteins associated with plasticity - specifically ADCY1 and BDNF - increased in the somatosensory cortex of transected animals that received passive bike exercise compared to transected animals that received sham exercise. Using electrophysiological techniques, we then verified that neurons in the deafferented hindlimb cortex increased their responsiveness to tactile stimuli delivered to the forelimb in transected animals that received passive bike exercise compared to transected animals that received sham exercise. Passive exercise below the level of the lesion, therefore, promotes cortical reorganization after spinal cord injury, uncovering a brain-body interaction that does not rely on intact sensorimotor pathways connecting the exercised body parts and the brain.
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The assumption that a name uniquely identifies an entity introduces two types of errors: splitting treats one entity as two or more (because of name variants); lumping treats multiple entities as if they were one (because of shared names). Here we investigate the extent to which splitting and lumping affect commonly-used measures of large-scale named-entity networks within two disambiguated bibliographic datasets: one for co-author names in biomedicine (PubMed, 2003-2007); the other for co-inventor names in U. S. patents (USPTO, 2003-2007). ⋯ This effect of lumping is much less dramatic but persists with measures that give less weight to high-degree vertices, such as the mean local clustering coefficient and log-based degree assortativity. Furthermore, the log-log distribution of collaborator counts follows a much straighter line (power law) with splitting and lumping errors than without, particularly at the low and the high counts. This suggests that part of the power law often observed for collaborator counts in science and technology reflects an artifact: name ambiguity.
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Neuroimaging activation maps typically color voxels to indicate whether the blood oxygen level-dependent (BOLD) signals measured among two or more experimental conditions differ significantly at that location. This data presentation, however, omits information critical for interpretation of experimental results. First, no information is represented about trends at voxels that do not pass the statistical test. ⋯ Here, we first document the prevalence of the fundamental error of interpretation, and then present a method for solving it by depicting confidence intervals in fMRI activation maps. Presenting images where the bounds of confidence intervals at each voxel are coded as color allows readers to visually test for differences between "active" and "inactive" voxels, and permits for more proper interpretation of neuroimaging data. Our specific graphical methods are intended as initial proposals to spur broader discussion of how to present confidence intervals for fMRI data.