Neuronal K-Cl Cotransporter : Transcriptional Mechanisms of KCC2 Gene Regulation

K-Cl cotransporter 2 (KCC2) maintains a low intracellular Cl concentration required for fast hyperpolarizing responses of neurons to classical inhibitory neurotransmitters γ-aminobutyric acid (GABA) and glycine. Decreased Cl extrusion observed in genetically modified KCC2-deficient mice leads to depolarizing GABA responses, impaired brain inhibition, and as a consequence to epileptic seizures. Identification of mechanisms regulating activity of the SLC12A5 gene, which encodes the KCC2 cotransporter, in normal and pathological conditions is, thus, of extreme importance. Multiple reports have previously elucidated in details a spatio-temporal pattern of KCC2 expression. Among the characteristic features are an exclusive neuronal specificity, a dramatic upregulation during embryonic and early postnatal development, and a significant downregulation by neuronal trauma. Numerous studies confirmed these expressional features, however transcriptional mechanisms predetermining the SLC12A5 gene behaviour are still unknown. The aim of the presented thesis is to recognize such transcriptional mechanisms and, on their basis, to create a transcriptional model that would explain the established SLC12A5 gene behaviour. Up to recently, only one KCC2 transcript has been thought to exist. A particular novelty of the presented work is the identification of two SLC12A5 gene promoters (SLC12A5-1a and SLC12A5-1b) that produce at least two KCC2 isoforms (KCC2a and KCC2b) differing by their N-terminal parts. Even though a functional 86Rb+ assay reveals no significant difference between transport activities of the isoforms, consensus sites for several protein kinases, found in KCC2a but not in KCC2b, imply a distinct kinetic regulation. As a logical continuation, the current work presents a detailed analysis of the KCC2a and KCC2b expression patterns. This analysis shows an exclusively neuron-specific pattern and similar expression levels for both isoforms during embryonic and neonatal development in rodents. During subsequent postnatal development, the KCC2b expression dramatically increases, while KCC2a expression, depending on central nervous system (CNS) area, either remains at the same level or moderately decreases. In an attempt to explain both the neuronal specificity and the distinct expressional kinetics of the KCC2a and KCC2b isoforms during postnatal development, the corresponding SLC12A5-1a and SLC12A5-1b promoters have been subjected to a comprehensive bioinformatical analysis. Binding sites of several transcription factors (TFs), conserved in the mammalian SLC12A5 gene orthologs, have been identified that might shed light on the observed behaviour of the SLC12A5 gene. Possible roles of these TFs in the regulating of the SLC12A5 gene expression have been elucidated in subsequent experiments and are discussed in the current thesis.

RF Sputtered Er2O3 Thin Films as High-k Gate Dielectrics for Germanium MOS Devices

We report the material and electrical properties of Erbium Oxide (Er2O3) thin films grown on n-Ge (100) by RF sputtering. The properties of the films are correlated with the processing conditions. The structural characterization reveals that the films annealed at 550 degrees C, has densified as compared to the as-grown ones. Fixed oxide charges and interface charges, both of the order of 10(13)/cm(2) is observed.

Soft gluon k(t)-resummation and the Froissart bound

We study soft gluon k(t)-resurnmation and the relevance of InfraRed (IR) gluons for the energy dependence of total hadronic cross-sections. In our model, consistency with the Froissart bound is directly related to the ansatz that the IR behaviour of the QCD coupling constant follows an inverse power law.

Nonspecifically bound proteins spin while diffusing along DNA

It is known that DNA-binding proteins can slide along the DNA helix while searching for specific binding sites, but their path of motion remains obscure. Do these proteins undergo simple one-dimensional (1D) translational diffusion, or do they rotate to maintain a specific orientation with respect to the DNA helix? We measured 1D diffusion constants as a function of protein size while maintaining the DNA-protein interface. Using bootstrap analysis of single-molecule diffusion data, we compared the results to theoretical predictions for pure translational motion and rotation-coupled sliding along the DNA. The data indicate that DNA-binding proteins undergo rotation-coupled sliding along the DNA helix and can be described by a model of diffusion along the DNA helix on a rugged free-energy landscape. A similar analysis including the 1D diffusion constants of eight proteins of varying size shows that rotation-coupled sliding is a general phenomenon. The average free-energy barrier for sliding along the DNA was 1.1 +/- 0.2 k(B)T. Such small barriers facilitate rapid search for binding sites.

On the Structure of Contractible Edges in k-connected Partial k-trees

Contraction of an edge e merges its end points into a new single vertex, and each neighbor of one of the end points of e is a neighbor of the new vertex. An edge in a k-connected graph is contractible if its contraction does not result in a graph with lesser connectivity; otherwise the edge is called non-contractible. In this paper, we present results on the structure of contractible edges in k-trees and k-connected partial k-trees. Firstly, we show that an edge e in a k-tree is contractible if and only if e belongs to exactly one (k + 1) clique. We use this characterization to show that the graph formed by contractible edges is a 2-connected graph. We also show that there are at least |V(G)| + k - 2 contractible edges in a k-tree. Secondly, we show that if an edge e in a partial k-tree is contractible then e is contractible in any k-tree which contains the partial k-tree as an edge subgraph. We also construct a class of contraction critical 2k-connected partial 2k-trees.

STEM education K-12: perspectives on integration

This commentary was stimulated by Yeping Li's first editorial (2014) citing one of the journal's goals as adding multidisciplinary perspectives to current studies of single disciplines comprising the focus of other journals. In this commentary I argue for a greater focus on STEM integration, with a more equitable representation of the four disciplines in studies purporting to advance STEM learning. The STEM acronym is often used in reference to just one of the disciplines, commonly science. Although the integration of STEM disciplines is increasingly advocated in the literature, studies that address multiple disciplines appear scant with mixed findings and inadequate directions for STEM advancement. Perspectives on how discipline integration can be achieved are varied, with reference to multidisciplinary, interdisciplinary, and transdisciplinary approaches adding to the debates. Such approaches include core concepts and skills being taught separately in each discipline but housed within a common theme; the introduction of closely linked concepts and skills from two or more disciplines with the aim of deepening understanding and skills; and the adoption of a transdisciplinary approach, where knowledge and skills from two or more disciplines are applied to real-world problems and projects with the aim of shaping the total learning experience. Research that targets STEM integration is an embryonic field with respect to advancing curriculum development and various student outcomes. For example, we still need more studies on how student learning outcomes arise not only from different forms of STEM integration but also from the particular disciplines that are being integrated. As noted in this commentary, it seems that mathematics learning benefits less than the other disciplines in programs claiming to focus on STEM integration. Factors contributing to this finding warrant more scrutiny. Likewise, learning outcomes for engineering within K-12 integrated STEM programs appear under-researched. This commentary advocates a greater focus on these two disciplines within integrated STEM education research. Drawing on recommendations from the literature, suggestions are offered for addressing the challenges of integrating multiple disciplines faced by the STEM community.

Two-level k-means clustering algorithm for k-tau relationship establishment and linear-time classification

Partitional clustering algorithms, which partition the dataset into a pre-defined number of clusters, can be broadly classified into two types: algorithms which explicitly take the number of clusters as input and algorithms that take the expected size of a cluster as input. In this paper, we propose a variant of the k-means algorithm and prove that it is more efficient than standard k-means algorithms. An important contribution of this paper is the establishment of a relation between the number of clusters and the size of the clusters in a dataset through the analysis of our algorithm. We also demonstrate that the integration of this algorithm as a pre-processing step in classification algorithms reduces their running-time complexity.

[B4O9H2] Cyclic Borate Units as the Building Unit in a Family of Zinc Borate Structures

A solvothermal reaction of ZnO, boric acid (B(OH)(3)), and aliphatic airlines in a water-pyridine mixture gave four zinc borate phases of different dimensionalities: [Zn(B4O8H2)(C3H10N2)], I (one-dimensional); [Zn(B4O8H2)(C3H10N2)] H2O, II (two-dimensional); [Zn(B5O10H3)(C10H24N4)]center dot H2O, III (two-dimensional): and [Zn-2(B8O15H2)(C3H10N2)(2)], IV (three-dimensional). The structures are formed by the connectivity involving polyborate chains and layers with Zn2+ species. In all the compounds, the amine molecules act its file ligand binding either the same or different zn centers. The formation of two different structures, II and IV, from the same amine by varying the reaction time is noteworthy. Transformation studies on II indicate that the formation of IV. from II, is facile and has been investigated for the first time. Two of file compounds, I and III, exhibit activity for second-order nonlinear optical behavior. The UV exposure of the sample indicates the absorption of all the UV radiation suggesting that the zinc borate compounds could be exploited for UV-blocking applications. The compounds have been characterized by powder X-ray diffraction, infrared spectroscopy, thermogravimetric analysis, UV-vis, photoluminescence, and NMR studies.

Prediction of individual genetic risk to prostate cancer using a polygenic score

BACKGROUND Polygenic risk scores comprising established susceptibility variants have shown to be informative classifiers for several complex diseases including prostate cancer. For prostate cancer it is unknown if inclusion of genetic markers that have so far not been associated with prostate cancer risk at a genome-wide significant level will improve disease prediction. METHODS We built polygenic risk scores in a large training set comprising over 25,000 individuals. Initially 65 established prostate cancer susceptibility variants were selected. After LD pruning additional variants were prioritized based on their association with prostate cancer. Six-fold cross validation was performed to assess genetic risk scores and optimize the number of additional variants to be included. The final model was evaluated in an independent study population including 1,370 cases and 1,239 controls. RESULTS The polygenic risk score with 65 established susceptibility variants provided an area under the curve (AUC) of 0.67. Adding an additional 68 novel variants significantly increased the AUC to 0.68 (P = 0.0012) and the net reclassification index with 0.21 (P = 8.5E-08). All novel variants were located in genomic regions established as associated with prostate cancer risk. CONCLUSIONS Inclusion of additional genetic variants from established prostate cancer susceptibility regions improves disease prediction. Prostate 75:1467–1474, 2015. © 2015 Wiley Periodicals, Inc.

Directional dominance on stature and cognition in diverse human populations

Homozygosity has long been associated with rare, often devastating, Mendelian disorders1, and Darwin was one of the first to recognize that inbreeding reduces evolutionary fitness2. However, the effect of the more distant parental relatedness that is common in modern human populations is less well understood. Genomic data now allow us to investigate the effects of homozygosity on traits of public health importance by observing contiguous homozygous segments (runs of homozygosity), which are inferred to be homozygous along their complete length. Given the low levels of genome-wide homozygosity prevalent in most human populations, information is required on very large numbers of people to provide sufficient power3, 4. Here we use runs of homozygosity to study 16 health-related quantitative traits in 354,224 individuals from 102 cohorts, and find statistically significant associations between summed runs of homozygosity and four complex traits: height, forced expiratory lung volume in one second, general cognitive ability and educational attainment (P < 1 × 10−300, 2.1 × 10−6, 2.5 × 10−10 and 1.8 × 10−10, respectively). In each case, increased homozygosity was associated with decreased trait value, equivalent to the offspring of first cousins being 1.2 cm shorter and having 10 months’ less education. Similar effect sizes were found across four continental groups and populations with different degrees of genome-wide homozygosity, providing evidence that homozygosity, rather than confounding, directly contributes to phenotypic variance. Contrary to earlier reports in substantially smaller samples5, 6, no evidence was seen of an influence of genome-wide homozygosity on blood pressure and low density lipoprotein cholesterol, or ten other cardio-metabolic traits. Since directional dominance is predicted for traits under directional evolutionary selection7, this study provides evidence that increased stature and cognitive function have been positively selected in human evolution, whereas many important risk factors for late-onset complex diseases may not have been.

Worldwide outdoor round robin study of organic photovoltaic devices and modules

Accurate characterization and reporting of organic photovoltaic (OPV) device performance remains one of the important challenges in the field. The large spread among the efficiencies of devices with the same structure reported by different groups is significantly caused by different procedures and equipment used during testing. The presented article addresses this issue by offering a new method of device testing using “suitcase sample” approach combined with outdoor testing that limits the diversity of the equipment, and a strict measurement protocol. A round robin outdoor characterization of roll-to-roll coated OPV cells and modules conducted among 46 laboratories worldwide is presented, where the samples and the testing equipment were integrated in a compact suitcase that served both as a sample transportation tool and as a holder and test equipment during testing. In addition, an internet based coordination was used via plasticphotovoltaics.org that allowed fast and efficient communication among participants and provided a controlled reporting format for the results that eased the analysis of the data. The reported deviations among the laboratories were limited to 5% when compared to the Si reference device integrated in the suitcase and were up to 8% when calculated using the local irradiance data. Therefore, this method offers a fast, cheap and efficient tool for sample sharing and testing that allows conducting outdoor measurements of OPV devices in a reproducible manner.

DMT of Multi-hop Cooperative Networks-Part I: K-Parallel-Path Networks

We consider single-source, single-sink multi-hop relay networks, with slow-fading Rayleigh fading links and single-antenna relay nodes operating under the half-duplex constraint. While two hop relay networks have been studied in great detail in terms of the diversity-multiplexing tradeoff (DMT), few results are available for more general networks. In this two-part paper, we identify two families of networks that are multi-hop generalizations of the two hop network: K-Parallel-Path (KPP) networks and Layered networks. In the first part, we initially consider KPP networks, which can be viewed as the union of K node-disjoint parallel paths, each of length > 1. The results are then generalized to KPP(I) networks, which permit interference between paths and to KPP(D) networks, which possess a direct link from source to sink. We characterize the optimal DMT of KPP(D) networks with K >= 4, and KPP(I) networks with K >= 3. Along the way, we derive lower bounds for the DMT of triangular channel matrices, which are useful in DMT computation of various protocols. As a special case, the DMT of two-hop relay network without direct link is obtained. Two key implications of the results in the two-part paper are that the half-duplex constraint does not necessarily entail rate loss by a factor of two, as previously believed and that, simple AF protocols are often sufficient to attain the best possible DMT.

Heritability of the network architecture of intrinsic brain functional connectivity

The brain's functional network exhibits many features facilitating functional specialization, integration, and robustness to attack. Using graph theory to characterize brain networks, studies demonstrate their small-world, modular, and "rich-club" properties, with deviations reported in many common neuropathological conditions. Here we estimate the heritability of five widely used graph theoretical metrics (mean clustering coefficient (γ), modularity (Q), rich-club coefficient (ϕnorm), global efficiency (λ), small-worldness (σ)) over a range of connection densities (k=5-25%) in a large cohort of twins (N=592, 84 MZ and 89 DZ twin pairs, 246 single twins, age 23±2.5). We also considered the effects of global signal regression (GSR). We found that the graph metrics were moderately influenced by genetic factors h2 (γ=47-59%, Q=38-59%, ϕnorm=0-29%, λ=52-64%, σ=51-59%) at lower connection densities (≤15%), and when global signal regression was implemented, heritability estimates decreased substantially h2 (γ=0-26%, Q=0-28%, ϕnorm=0%, λ=23-30%, σ=0-27%). Distinct network features were phenotypically correlated (|r|=0.15-0.81), and γ, Q, and λ were found to be influenced by overlapping genetic factors. Our findings suggest that these metrics may be potential endophenotypes for psychiatric disease and suitable for genetic association studies, but that genetic effects must be interpreted with respect to methodological choices.