Into the Square and out of the Box: The effects of Quadrato Motor Training on Creativity and Alpha Coherence

The objective of the present study was to investigate the body-cognitive relationship through behavioral and electrophysiological measures in an attempt to uncover the underlying mediating neuronal mechanism for movement-induced cognitive change. To this end we examined the effects of Quadrato Motor Training (QMT), a new whole-body training paradigm on cognitive performance, including creativity and reaction time tasks, and electrophysiological change, using a within-subject pre-post design. Creativity was studied by means of the Alternate Uses Task, measuring ideational fluency and ideational flexibility. Electrophysiological effects were measured in terms of alpha power and coherence. In order to determine whether training-induced changes were driven by the cognitive or the motor aspects of the training, we used two control groups: Verbal Training (VT, identical cognitive training with verbal response) and Simple Motor Training (SMT, similar motor training with reduced choice requirements). Twenty-seven participants were randomly assigned to one of the groups. Following QMT, we found enhanced inter-hemispheric and intra-hemispheric alpha coherence, and increased ideational flexibility, which was not the case for either the SMT or VT groups. These findings indicate that it is the combination of the motor and cognitive aspects embedded in the QMT which is important for increasing ideational flexibility and alpha coherence.     

Reconstructing Roma History from Genome-Wide Data

The Roma people, living throughout Europe and West Asia, are a diverse population linked by the Romani language and culture. Previous linguistic and genetic studies have suggested that the Roma migrated into Europe from South Asia about 1,000–1,500 years ago. Genetic inferences about Roma history have mostly focused on the Y chromosome and mitochondrial DNA. To explore what additional information can be learned from genome-wide data, we analyzed data from six Roma groups that we genotyped at hundreds of thousands of single nucleotide polymorphisms (SNPs). We estimate that the Roma harbor about 80% West Eurasian ancestry–derived from a combination of European and South Asian sources–and that the date of admixture of South Asian and European ancestry was about 850 years before present. We provide evidence for Eastern Europe being a major source of European ancestry, and North-west India being a major source of the South Asian ancestry in the Roma. By computing allele sharing as a measure of linkage disequilibrium, we estimate that the migration of Roma out of the Indian subcontinent was accompanied by a severe founder event, which appears to have been followed by a major demographic expansion after the arrival in Europe.     

Identification of novel Xanthomonas euvesicatoria type III effector proteins by a machine‐learning approach

The Gram‐negative bacterium Xanthomonas euvesicatoria (Xcv) is the causal agent of bacterial spot disease in pepper and tomato. Xcv pathogenicity depends on a type III secretion (T3S) system that delivers effector proteins into host cells to suppress plant immunity and promote disease. The pool of known Xcv effectors includes approximately 30 proteins, most identified in the 85‐10 strain by various experimental and computational techniques. To identify additional Xcv 85‐10 effectors, we applied a genome‐wide machine‐learning approach, in which all open reading frames (ORFs) were scored according to their propensity to encode effectors. Scoring was based on a large set of features, including genomic organization, taxonomic dispersion, hypersensitive response and pathogenicity (hrp)‐dependent expression, 5′ regulatory sequences, amino acid composition bias and GC content. Thirty‐six predicted effectors were tested for translocation into plant cells using the hypersensitive response (HR)‐inducing domain of AvrBs2 as a reporter. Seven proteins (XopAU, XopAV, XopAW, XopAP, XopAX, XopAK and XopAD) harboured a functional translocation signal and their translocation relied on the HrpF translocon, indicating that they are bona fide T3S effectors. Remarkably, four belong to novel effector families. Inactivation of the xopAP gene reduced the severity of disease symptoms in infected plants. A decrease in cell death and chlorophyll content was observed in pepper leaves inoculated with the xopAP mutant when compared with the wild‐type strain. However, populations of the xopAP mutant in infected leaves were similar in size to those of wild‐type bacteria, suggesting that the reduction in virulence was not caused by impaired bacterial growth.     

Parametric analysis of the biomechanical response of head subjected to the primary blast loading – a data mining approach

Traumatic brain injury due to primary blast loading has become a signature injury in recent military conflicts and terrorist activities. Extensive experimental and computational investigations have been conducted to study the interrelationships between intracranial pressure response and intrinsic or ‘input’ parameters such as the head geometry and loading conditions. However, these relationships are very complicated and are usually implicit and ‘hidden’ in a large amount of simulation/test data. In this study, a data mining method is proposed to explore such underlying information from the numerical simulation results. The heads of different species are described as a highly simplified two-part (skull and brain) finite element model with varying geometric parameters. The parameters considered include peak incident pressure, skull thickness, brain radius and snout length. Their interrelationship and coupling effect are discovered by developing a decision tree based on the large simulation data-set. The results show that the proposed data-driven method is superior to the conventional linear regression method and is comparable to the nonlinear regression method. Considering its capability of exploring implicit information and the relatively simple relationships between response and input variables, the data mining method is considered to be a good tool for an in-depth understanding of the mechanisms of blast-induced brain injury. As a general method, this approach can also be applied to other nonlinear complex biomechanical systems.     

Enhanced generation of intraluminal vesicles in neuronal late endosomes in the brain of a Down syndrome mouse model with endosomal dysfunction

Down syndrome (DS) is a human genetic disease caused by trisomy of chromosome 21 and characterized by early developmental brain abnormalities. Dysfunctional endosomal pathway in neurons is an early event of DS and Alzheimer's disease. Recently, we have demonstrated that exosome secretion is upregulated in human DS postmortem brains, in the brain of the trisomic mouse model Ts[Rb(12.17¹⁶)]2Cje (Ts2) and by DS fibroblasts as compared with disomic controls. High levels of the tetraspanin CD63, a regulator of exosome biogenesis, were observed in DS brains. Partially blocking exosome secretion by DS fibroblasts exacerbated a pre‐existing early endosomal pathology. We thus hypothesized that enhanced CD63 expression induces generation of intraluminal vesicles (ILVs) in late endosomes/multivesicular bodies (MVBs), increasing exosome release as an endogenous mechanism to mitigate endosomal abnormalities in DS. Herein, we show a high‐resolution electron microscopy analysis of MVBs in neurons of the frontal cortex of 12‐month‐old Ts2 mice and littermate diploid controls. Our quantitative analysis revealed that Ts2 MVBs are larger, more abundant, and contain a higher number of ILVs per neuron compared to controls. These findings were further corroborated biochemically by Western blot analysis of purified endosomal fractions showing higher levels of ILVs proteins in the same fractions containing endosomal markers in the brain of Ts2 mice compared to controls. These data suggest that upregulation of ILVs production may be a key homeostatic mechanism to alleviate endosomal dysregulation via the endosomal–exosomal pathway.     

Modeling Patient-Derived Glioblastoma with Cerebral Organoids

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Sensitive detection of GFP utilizing tyramide signal amplification to overcome gene silencing

The green fluorescent protein (GFP) is among the most commonly used expression markers in biology. GFP-tagged cells have played a particularly important role in studies of cell lineage. Sensitive detection of GFP is crucially important for such studies to be successful, and problems with detection may account for discrepancies in the literature regarding the possible fate choices of stem cells. Here we describe a very sensitive technique for visualization of GFP. Using it we can detect about 90% of cells of donor origin while we could only see about 50% of these cells when we employ the methods that are in general use in other laboratories. In addition, we provide evidence that some cells permanently silence GFP expression. In the case of the progeny of bone marrow stem cells, it appears that the more distantly related they are to their precursors, the more likely it is that they will turn off the lineage marker.