Main assumptions for energy pathways

© The Author(s) 2019. The aim of this chapter is to make the scenario calculations fully transparent and comprehensible to the scientific community. It provides the scenario narratives for the reference case (5.0 °C) as well as for the 2.0 °C and 1.5 °C on a global and regional basis. Cost projections for all fossil fuels and renewable energy technologies until 2050 are provided. Explanations are given for all relevant base year data for the modelling and the main input parameters such as GDP, population, renewable energy potentials and technology parameters

Explaining disparities in colorectal cancer screening among five Asian ethnic groups: A population-based study in California

<p>Abstract</p> <p>Background</p> <p>Data from the California Health Interview Survey (CHIS) indicate that levels and temporal trends in colorectal cancer (CRC) screening prevalence vary among Asian American groups; however, the reasons for these differences have not been fully investigated.</p> <p>Methods</p> <p>Using CHIS 2001, 2003 and 2005 data, we conducted hierarchical regression analyses progressively controlling for demographic characteristics, English proficiency and access to care in an attempt to identify factors explaining differences in screening prevalence and trends among Chinese, Filipino, Vietnamese, Korean and Japanese Americans (N = 4,188).</p> <p>Results</p> <p>After controlling for differences in gender and age, all Asian subgroups had significantly lower odds of having ever received screening in 2001 than the reference group of Japanese Americans. In addition, Korean Americans were the only subgroup that had a statistically significant decline in screening prevalence from 2001 to 2005 compared to the trend among Japanese Americans. After controlling for differences in education, marital status, employment status and federal poverty level, Korean Americans were the only group that had significantly lower screening prevalence than Japanese Americans in 2001, and their trend to 2005 remained significantly depressed. After controlling for differences in English proficiency and access to care, screening prevalences in 2001 were no longer significantly different among the Asian subgroups, but the trend among Korean Americans from 2001 to 2005 remained significantly depressed. Korean and Vietnamese Americans were less likely than other groups to report a recent doctor recommendation for screening and more likely to cite a lack of health problems as a reason for not obtaining screening.</p> <p>Conclusions</p> <p>Differences in CRC screening trends among Asian ethnic groups are not entirely explained by differences in demographic characteristics, English proficiency and access to care. A better understanding of mutable factors such as rates of doctor recommendation and health beliefs will be crucial for designing culturally appropriate interventions to promote CRC screening.</p

Absence of Positive Selection on Centromeric Histones in Tetrahymena Suggests Unsuppressed Centromere-Drive in Lineages Lacking Male Meiosis

Centromere-drive is a process where centromeres compete for transmission through asymmetric "female" meiosis for inclusion into the oocyte. In symmetric "male" meiosis, all meiotic products form viable germ cells. Therefore, the primary incentive for centromere-drive, a potential transmission bias, is believed to be missing from male meiosis. In this article, we consider whether male meiosis also bears the primary cost of centromere-drive. Because different taxa carry out different combinations of meiotic programs (symmetric + asymmetric, symmetric only, asymmetric only), it is possible to consider the evolutionary consequences of centromere-drive in the context of these differing systems. Groups with both types of meiosis have large, rapidly evolving centromeric regions, and their centromeric histones (CenH3s) have been shown to evolve under positive selection, suggesting roles as suppressors of centromere-drive. In contrast, taxa with only symmetric male meiosis have shown no evidence of positive selection in their centromeric histones. In this article, we present the first evolutionary analysis of centromeric histones in ciliated protozoans, a group that only undergoes asymmetric "female" meiosis. We find no evidence of positive selection acting on CNA1, the CenH3 of Tetrahymena species. Cytological observations of a panel of Tetrahymena species are consistent with dynamic karyotype evolution in this lineage. Our findings suggest that defects in male meiosis, and not mitosis or female meiosis, are the primary selective force behind centromere-drive suppression. Our study raises the possibility that taxa like ciliates, with only female meiosis, may therefore undergo unsuppressed centromere drive

Rationalization and Design of the Complementarity Determining Region Sequences in an Antibody-Antigen Recognition Interface

Protein-protein interactions are critical determinants in biological systems. Engineered proteins binding to specific areas on protein surfaces could lead to therapeutics or diagnostics for treating diseases in humans. But designing epitope-specific protein-protein interactions with computational atomistic interaction free energy remains a difficult challenge. Here we show that, with the antibody-VEGF (vascular endothelial growth factor) interaction as a model system, the experimentally observed amino acid preferences in the antibody-antigen interface can be rationalized with 3-dimensional distributions of interacting atoms derived from the database of protein structures. Machine learning models established on the rationalization can be generalized to design amino acid preferences in antibody-antigen interfaces, for which the experimental validations are tractable with current high throughput synthetic antibody display technologies. Leave-one-out cross validation on the benchmark system yielded the accuracy, precision, recall (sensitivity) and specificity of the overall binary predictions to be 0.69, 0.45, 0.63, and 0.71 respectively, and the overall Matthews correlation coefficient of the 20 amino acid types in the 24 interface CDR positions was 0.312. The structure-based computational antibody design methodology was further tested with other antibodies binding to VEGF. The results indicate that the methodology could provide alternatives to the current antibody technologies based on animal immune systems in engineering therapeutic and diagnostic antibodies against predetermined antigen epitopes

Normal radial migration and lamination are maintained in dyslexia-susceptibility candidate gene homolog Kiaa0319 knockout mice

AbstractDevelopmental dyslexia is a common disorder with a strong genetic component, but the underlying molecular mechanisms are still unknown. Several candidate dyslexia-susceptibility genes, including KIAA0319, DYX1C1, and DCDC2, have been identified in humans. RNA interference experiments targeting these genes in rat embryos have shown impairments in neuronal migration, suggesting that defects in radial cortical migration could be involved in the disease mechanism of dyslexia. Here we present the first characterisation of a Kiaa0319 knockout mouse line. Animals lacking KIAA0319 protein do not show anatomical abnormalities in any of the layered structures of the brain. Neurogenesis and radial migration of cortical projection neurons are not altered, and the intrinsic electrophysiological properties of Kiaa0319-deficient neurons do not differ from those of wild-type neurons. Kiaa0319 overexpression in cortex delays radial migration, but does not affect final neuronal position. However, knockout animals show subtle differences suggesting possible alterations in anxiety-related behaviour and in sensorimotor gating. Our results do not reveal a migration disorder in the mouse model, adding to the body of evidence available for Dcdc2 and Dyx1c1 that, unlike in the rat in utero knockdown models, the dyslexia-susceptibility candidate mouse homolog genes do not play an evident role in neuronal migration. However, KIAA0319 protein expression seems to be restricted to the brain, not only in early developmental stages but also in adult mice, indicative of a role of this protein in brain function. The constitutive and conditional knockout lines reported here will be useful tools for further functional analyses of Kiaa0319

Intramolecular Cohesion of Coils Mediated by Phenylalanine–Glycine Motifs in the Natively Unfolded Domain of a Nucleoporin

The nuclear pore complex (NPC) provides the sole aqueous conduit for macromolecular exchange between the nucleus and the cytoplasm of cells. Its diffusion conduit contains a size-selective gate formed by a family of NPC proteins that feature large, natively unfolded domains with phenylalanine–glycine repeats (FG domains). These domains of nucleoporins play key roles in establishing the NPC permeability barrier, but little is known about their dynamic structure. Here we used molecular modeling and biophysical techniques to characterize the dynamic ensemble of structures of a representative FG domain from the yeast nucleoporin Nup116. The results showed that its FG motifs function as intramolecular cohesion elements that impart order to the FG domain and compact its ensemble of structures into native premolten globular configurations. At the NPC, the FG motifs of nucleoporins may exert this cohesive effect intermolecularly as well as intramolecularly to form a malleable yet cohesive quaternary structure composed of highly flexible polypeptide chains. Dynamic shifts in the equilibrium or competition between intra- and intermolecular FG motif interactions could facilitate the rapid and reversible structural transitions at the NPC conduit needed to accommodate passing karyopherin–cargo complexes of various shapes and sizes while simultaneously maintaining a size-selective gate against protein diffusion

Genomic Organization of H2Av Containing Nucleosomes in Drosophila Heterochromatin

H2Av is a versatile histone variant that plays both positive and negative roles in transcription, DNA repair, and chromatin structure in Drosophila. H2Av, and its broader homolog H2A.Z, tend to be enriched toward 5′ ends of genes, and exist in both euchromatin and heterochromatin. Its organization around euchromatin genes and other features have been described in many eukaryotic model organisms. However, less is known about H2Av nucleosome organization in heterochromatin. Here we report the properties and organization of individual H2Av nucleosomes around genes and transposable elements located in Drosophila heterochromatic regions. We compare the similarity and differences with that found in euchromatic regions. Our analyses suggest that nucleosomes are intrinsically positioned on inverted repeats of DNA transposable elements such as those related to the “1360” element, but are not intrinsically positioned on retrotransposon-related elements

Prodepth: Predict Residue Depth by Support Vector Regression Approach from Protein Sequences Only

Residue depth (RD) is a solvent exposure measure that complements the information provided by conventional accessible surface area (ASA) and describes to what extent a residue is buried in the protein structure space. Previous studies have established that RD is correlated with several protein properties, such as protein stability, residue conservation and amino acid types. Accurate prediction of RD has many potentially important applications in the field of structural bioinformatics, for example, facilitating the identification of functionally important residues, or residues in the folding nucleus, or enzyme active sites from sequence information. In this work, we introduce an efficient approach that uses support vector regression to quantify the relationship between RD and protein sequence. We systematically investigated eight different sequence encoding schemes including both local and global sequence characteristics and examined their respective prediction performances. For the objective evaluation of our approach, we used 5-fold cross-validation to assess the prediction accuracies and showed that the overall best performance could be achieved with a correlation coefficient (CC) of 0.71 between the observed and predicted RD values and a root mean square error (RMSE) of 1.74, after incorporating the relevant multiple sequence features. The results suggest that residue depth could be reliably predicted solely from protein primary sequences: local sequence environments are the major determinants, while global sequence features could influence the prediction performance marginally. We highlight two examples as a comparison in order to illustrate the applicability of this approach. We also discuss the potential implications of this new structural parameter in the field of protein structure prediction and homology modeling. This method might prove to be a powerful tool for sequence analysis

Protein docking prediction using predicted protein-protein interface

<p>Abstract</p> <p>Background</p> <p>Many important cellular processes are carried out by protein complexes. To provide physical pictures of interacting proteins, many computational protein-protein prediction methods have been developed in the past. However, it is still difficult to identify the correct docking complex structure within top ranks among alternative conformations.</p> <p>Results</p> <p>We present a novel protein docking algorithm that utilizes imperfect protein-protein binding interface prediction for guiding protein docking. Since the accuracy of protein binding site prediction varies depending on cases, the challenge is to develop a method which does not deteriorate but improves docking results by using a binding site prediction which may not be 100% accurate. The algorithm, named PI-LZerD (using Predicted Interface with Local 3D Zernike descriptor-based Docking algorithm), is based on a pair wise protein docking prediction algorithm, LZerD, which we have developed earlier. PI-LZerD starts from performing docking prediction using the provided protein-protein binding interface prediction as constraints, which is followed by the second round of docking with updated docking interface information to further improve docking conformation. Benchmark results on bound and unbound cases show that PI-LZerD consistently improves the docking prediction accuracy as compared with docking without using binding site prediction or using the binding site prediction as post-filtering.</p> <p>Conclusion</p> <p>We have developed PI-LZerD, a pairwise docking algorithm, which uses imperfect protein-protein binding interface prediction to improve docking accuracy. PI-LZerD consistently showed better prediction accuracy over alternative methods in the series of benchmark experiments including docking using actual docking interface site predictions as well as unbound docking cases.</p