Characterizing Spatiotemporal Transcriptome of the Human Brain Via Low-Rank Tensor Decomposition

Statistics in Biosciences - Spatiotemporal gene expression data of the human brain offer insights on the spatial and temporal patterns of gene regulation during brain development. Most existing...     

Characterizing Behavioral and Brain Changes Associated with Practicing Reasoning Skills

We have reported previously that intensive preparation for a standardized test that taxes reasoning leads to changes in structural and functional connectivity within the frontoparietal network. Here, we investigated whether reasoning instruction transfers to improvement on unpracticed tests of reasoning, and whether these improvements are associated with changes in neural recruitment during reasoning task performance. We found behavioral evidence for transfer to a transitive inference task, but no evidence for transfer to a rule generation task. Across both tasks, we observed reduced lateral prefrontal activation in the trained group relative to the control group, consistent with other studies of practice-related changes in brain activation. In the transitive inference task, we observed enhanced suppression of task-negative, or default-mode, regions, consistent with work suggesting that better cognitive skills are associated with more efficient switching between networks. In the rule generation task, we found a pattern consistent with a training-related shift in the balance between phonological and visuospatial processing. Broadly, we discuss general methodological considerations related to the analysis and interpretation of training-related changes in brain activation. In summary, we present preliminary evidence for changes in brain activation associated with practice of high-level cognitive skills.     

Characterizing Deep Brain Stimulation effects in computationally efficient neural network models

Background  

Recent studies on the medical treatment of Parkinson's disease (PD) led to the introduction of the so called Deep Brain Stimulation (DBS) technique. This particular therapy allows to contrast actively the pathological activity of various Deep Brain structures, responsible for the well known PD symptoms. This technique, frequently joined to dopaminergic drugs administration, replaces the surgical interventions implemented to contrast the activity of specific brain nuclei, called Basal Ganglia (BG). This clinical protocol gave the possibility to analyse and inspect signals measured from the electrodes implanted into the deep brain regions. The analysis of these signals led to the possibility to study the PD as a specific case of dynamical synchronization in biological neural networks, with the advantage to apply the theoretical analysis developed in such scientific field to find efficient treatments to face with this important disease. Experimental results in fact show that the PD neurological diseases are characterized by a pathological signal synchronization in BG. Parkinsonian tremor, for example, is ascribed to be caused by neuron populations of the Thalamic and Striatal structures that undergo an abnormal synchronization. On the contrary, in normal conditions, the activity of the same neuron populations do not appear to be correlated and synchronized.     

Pericyte ALK5/TIMP3 Axis Contributes to Endothelial Morphogenesis in the Developing Brain

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Psychopathological Profiles in Transsexuals and the Challenge of Their Special Status among the Sexes

Objective

Investigating psychopathological profiles of transsexuals raises a very basic methodological question: are control groups, which represent the biological or the phenotypic sex, most suited for an optimal evaluation of psychopathology of transsexuals?

Method

Male-to-female (MtF) (n=52) and female-to-male transsexuals (FtM) (n=32), receiving cross-sex hormone treatment, were compared with age matched healthy subjects of the same genetic sex (n=178) and with the same phenotypic sex (n=178) by means of the Symptom Check List-90-Revisited instrument (SCL-90-R). We performed analyses of covariance (ANCOVA) to test for group and sex effects. Furthermore, we used a profile analysis to determine if psychopathological symptom profiles of transsexuals more closely resemble genotypic sex or phenotypic sex controls.

Results

Transsexual patients reported more symptoms of psychopathological distress than did healthy control subjects in all subscales of the SCL-90-R (all p<0.001), regardless of whether they were compared with phenotype or genotype matched controls. Depressive symptoms were more pronounced in MtF than in FtM (SCL-90-R score 0.85 vs. 0.45, p = 0.001). We could demonstrate that FtM primarily reflect the psychopathological profile of biological males rather than that of biological females (r = 0.945), while MtF showed a slightly higher profile similarity with biological females than with biological males (r = 0.698 vs. r = 0.685).

Conclusion

Our findings suggest that phenotypic sex matched controls are potentially more appropriate for comparison with the psychopathology of transsexual patients than are genetic sex matched controls.     

Molecular Mechanisms of Actions of Interleukin-6 on the Brain,with Special Reference to Serotonin and the Hypothalamo-Pituitary-Adrenocortical Axis

Biological activities of the multifunctional cytokine, interleukin-6 (IL-6) include stimulation of B cell proliferation, immunoglobulin production, and initiation of the acute-phase response. IL-6 affects the CNS in that it activates the hypothalamo-pituitary-adrenocortical (HPA) axis and increases brain tryptophan and serotonin metabolism. IL-6 has been proposed as an important mediator of interaction between the neuroendocrine and immune systems. The peripheral and central effects of IL-6 are presumably mediated through its membrane receptor (IL-6R). IL-6, IL-6R and their respective mRNAs have been detected in several brain regions. Although the functions of cytokines overlap considerably, each displays its own characteristic properties. Expression of IL-6 in the brain has been observed in several CNS disorders, some of which have been associated with disorders of serotonin metabolism. It is proposed that interactions between IL-6 and brain serotonin is a complex process which involves corticotropin-releasing factor (CRF) and opioid peptides. It is likely that the molecular mechanisms underlying the actions of IL-6 on the HPA axis and its other brain functions involve the integrated effects of glutamate, Ca²⁺, 3,5-cyclic AMP, protein kinase C, and other metabolic pathways.     

Gut,Microbiome, and Brain Regulatory Axis: Relevance to Neurodegenerative and Psychiatric Disorders

It has become apparent that the molecular and biochemical integrity of interactive families, genera, and species of human gut microflora is critically linked to maintaining complex metabolic and behavioral processes mediated by peripheral organ systems and central nervous system neuronal groupings. Relatively recent studies have established intrinsic ratios of enterotypes contained within the human microbiome across demographic subpopulations and have empirically linked significant alterations in the expression of bacterial enterotypes with the initiation and persistence of several major metabolic and psychiatric disorders. Accordingly, the goal of our review is to highlight potential thematic/functional linkages of pathophysiological alterations in gut microbiota and bidirectional gut–brain signaling pathways with special emphasis on the potential roles of gut dysbiosis on the pathophysiology of psychiatric illnesses. We provide critical discussion of putative thematic linkages of Parkinson’s disease (PD) data sets to similar pathophysiological events as potential causative factors in the development and persistence of diverse psychiatric illnesses. Finally, we include a concise review of preclinical paradigms that involve immunologically–induced GI deficits and dysbiosis of maternal microflora that are functionally linked to impaired neurodevelopmental processes leading to affective behavioral syndromes in the offspring.     

Neural Network of Body Representation Differs between Transsexuals and Cissexuals

Body image is the internal representation of an individual’s own physical appearance. Individuals with gender identity disorder (GID), commonly referred to as transsexuals (TXs), are unable to form a satisfactory body image due to the dissonance between their biological sex and gender identity. We reasoned that changes in the resting-state functional connectivity (rsFC) network would neurologically reflect such experiential incongruence in TXs. Using graph theory-based network analysis, we investigated the regional changes of the degree centrality of the rsFC network. The degree centrality is an index of the functional importance of a node in a neural network. We hypothesized that three key regions of the body representation network, i.e., the primary somatosensory cortex, the superior parietal lobule and the insula, would show a higher degree centrality in TXs. Twenty-three pre-treatment TXs (11 male-to-female and 12 female-to-male TXs) as one psychosocial group and 23 age-matched healthy cissexual control subjects (CISs, 11 males and 12 females) were recruited. Resting-state functional magnetic resonance imaging was performed, and binarized rsFC networks were constructed. The TXs demonstrated a significantly higher degree centrality in the bilateral superior parietal lobule and the primary somatosensory cortex. In addition, the connectivity between the right insula and the bilateral primary somatosensory cortices was negatively correlated with the selfness rating of their desired genders. These data indicate that the key components of body representation manifest in TXs as critical function hubs in the rsFC network. The negative association may imply a coping mechanism that dissociates bodily emotion from body image. The changes in the functional connectome may serve as representational markers for the dysphoric bodily self of TXs.     

Characterizing the phylogenetic tree-search problem

Phylogenetic trees are important in many areas of biological research, ranging from systematic studies to the methods used for genome annotation. Finding the best scoring tree under any optimality criterion is an NP-hard problem, which necessitates the use of heuristics for tree-search. Although tree-search plays a major role in obtaining a tree estimate, there remains a limited understanding of its characteristics and how the elements of the statistical inferential procedure interact with the algorithms used. This study begins to answer some of these questions through a detailed examination of maximum likelihood tree-search on a wide range of real genome-scale data sets. We examine all 10,395 trees for each of the 106 genes of an eight-taxa yeast phylogenomic data set, then apply different tree-search algorithms to investigate their performance. We extend our findings by examining two larger genome-scale data sets and a large disparate data set that has been previously used to benchmark the performance of tree-search programs. We identify several broad trends occurring during tree-search that provide an insight into the performance of heuristics and may, in the future, aid their development. These trends include a tendency for the true maximum likelihood (best) tree to also be the shortest tree in terms of branch lengths, a weak tendency for tree-search to recover the best tree, and a tendency for tree-search to encounter fewer local optima in genes that have a high information content. When examining current heuristics for tree-search, we find that nearest-neighbor-interchange performs poorly, and frequently finds trees that are significantly different from the best tree. In contrast, subtree-pruning-and-regrafting tends to perform well, nearly always finding trees that are not significantly different to the best tree. Finally, we demonstrate that the precise implementation of a tree-search strategy, including when and where parameters are optimized, can change the character of tree-search, and that good strategies for tree-search may combine existing tree-search programs.     

Characterizing the silica deposition vesicle of diatoms

Summary The present study on a centric diatom,Ditylum brightwellii, includes two parts: detection of sugars in the silica deposition vesicle (SDV) with lectins and labeling the developing siliceous cell wall in the SDV with rhodamine 123. Cells with developing valves are treated with SDS to remove all the cytoplasmic contents, then either stained with fluorescein labeled lectins or thin-sectioned and stained with colloidal gold labeled lectins. The results show that mannose is part of the organic matrix in the SDV. Rhodamine 123, a non-toxic fluorescent laser dye, enters the cell immediately and is trapped in the SDV probably by the high reducing potential of the SDV. Silica is co-deposited with rhodamine 123 in the SDV, and the resulting valves and girdle bands become fluorescent. Implications of this study for the mechanism of silicification are discussed.Abbreviation SDV Silica deposition vesicle     

Characterizing the Community Structure of Complex Networks

Background

Community structure is one of the key properties of complex networks and plays a crucial role in their topology and function. While an impressive amount of work has been done on the issue of community detection, very little attention has been so far devoted to the investigation of communities in real networks.

Methodology/Principal Findings

We present a systematic empirical analysis of the statistical properties of communities in large information, communication, technological, biological, and social networks. We find that the mesoscopic organization of networks of the same category is remarkably similar. This is reflected in several characteristics of community structure, which can be used as “fingerprints” of specific network categories. While community size distributions are always broad, certain categories of networks consist mainly of tree-like communities, while others have denser modules. Average path lengths within communities initially grow logarithmically with community size, but the growth saturates or slows down for communities larger than a characteristic size. This behaviour is related to the presence of hubs within communities, whose roles differ across categories. Also the community embeddedness of nodes, measured in terms of the fraction of links within their communities, has a characteristic distribution for each category.

Conclusions/Significance

Our findings, verified by the use of two fundamentally different community detection methods, allow for a classification of real networks and pave the way to a realistic modelling of networks'' evolution.     

Characterizing the conformational ensemble of monomeric polyglutamine

Studies of synthetic polyglutamine peptides in vitro have established that polyglutamine peptides aggregate via a classic nucleation and growth mechanism. Chen and colleagues [Proc Natl Acad Sci U S A 2002;99:11884-11889] have found that monomeric polyglutamine, which is a disordered statistical coil in solution, is the critical nucleus for aggregation. Therefore, nucleation of beta-sheet-rich aggregates requires an initial disorder to order transition, which is a highly unfavorable thermodynamic reaction. The questions of interest to us are as follows: What are the statistical fluctuations that drive beta-sheet formation in monomeric polyglutamine? How do these fluctuations vary with chain length? And why is this process thermodynamically unfavorable, that is, why is monomeric polyglutamine disordered? To answer these questions we use multiple molecular dynamics simulations to provide quantitative characterization of conformational ensembles for two short polyglutamine peptides. We find that the ensemble for polyglutamine is indeed disordered. However, the disorder is inherently different from that of denatured proteins and the average compactness and magnitude of conformational fluctuations increase with chain length. Most importantly, the effective concentration of sidechain primary amides around backbone units is inherently high and peptide units are solvated either by hydrogen bonds to sidechains or surrounding water molecules. Due to the multiplicity of backbone solvation modes the probability associated with any specific backbone conformation is small, resulting in a conformational entropy bottleneck which makes beta-sheet formation in monomeric polyglutamine thermodynamically unfavorable.     

Characterizing the three-dimensional organization of telomeres.

BACKGROUND: Quantitative analysis can be used in combination with fluorescence microscopy. Although the human eye is able to obtain good qualitative results, when analyzing the spatial organization of telomeres in interphase nuclei, there is a need for quantitative results based on image analysis. METHODS: We developed a tool for analyzing three-dimensional images of telomeres stained by fluorescence in situ hybridization in interphase nuclei with DNA counterstained with 4',6-diamidino-2-phenylindole. After deconvolution of the image, we segmented individual telomeres. From the location of the telomeres we derived a distribution parameter rhoT, which indicated whether the telomeres were in a disk (rhoT > 1) or not (rhoT approximately 1). We sorted mouse lymphocyte nuclei and measured rhoT. We also performed a bromodeoxyuridine synchronous cell sorting experiment on live cells and measured rhoT at several instances. RESULTS: Measuring rhoT for nuclei in G0/G1, S, and G2 produced 1.4 +/- 0.1, 1.5 +/- 0.2, and 14 +/- 2, respectively, showing a significant difference between G2 and G0/G1 or S. For the bromodeoxyuridine synchronous cell sorting experiment, we found a cell cycle dependency of rhoT and a correlation between rhoT and an observer. CONCLUSIONS: In this study we present a quantitative method to characterize the organization of telomeres using three-dimensional imaging, image processing, and image analysis.