Introduction: Educational attainment, widely used in epidemiologic studies as a surrogate for socioeconomic status, is a predictor of cardiovascular health outcomes.Methods: A two-stage genome-wide... Show moreIntroduction: Educational attainment, widely used in epidemiologic studies as a surrogate for socioeconomic status, is a predictor of cardiovascular health outcomes.Methods: A two-stage genome-wide meta-analysis of low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL), and triglyceride (TG) levels was performed while accounting for gene-educational attainment interactions in up to 226,315 individuals from five population groups. We considered two educational attainment variables: "Some College" (yes/no, for any education beyond high school) and "Graduated College" (yes/no, for completing a 4-year college degree). Genome-wide significant (p < 5 x 10(-8)) and suggestive (p < 1 x 10(-6)) variants were identified in Stage 1 (in up to 108,784 individuals) through genome-wide analysis, and those variants were followed up in Stage 2 studies (in up to 117,531 individuals).Results: In combined analysis of Stages 1 and 2, we identified 18 novel lipid loci (nine for LDL, seven for HDL, and two for TG) by two degree-of-freedom (2 DF) joint tests of main and interaction effects. Four loci showed significant interaction with educational attainment. Two loci were significant only in cross-population analyses. Several loci include genes with known or suggested roles in adipose (FOXP1, MBOAT4, SKP2, STIM1, STX4), brain (BRI3, FILIP1, FOXP1, LINC00290, LMTK2, MBOAT4, MYO6, SENP6, SRGAP3, STIM1, TMEM167A, TMEM30A), and liver (BRI3, FOXP1) biology, highlighting the potential importance of brain-adipose-liver communication in the regulation of lipid metabolism. An investigation of the potential druggability of genes in identified loci resulted in five gene targets shown to interact with drugs approved by the Food and Drug Administration, including genes with roles in adipose and brain tissue.Discussion: Genome-wide interaction analysis of educational attainment identified novel lipid loci not previously detected by analyses limited to main genetic effects. Show less
Cluster inference based on spatial extent thresholding is a popular analysis method multiple testing in spatial data, and is frequently used for finding activated brain areas in neuroimaging.... Show moreCluster inference based on spatial extent thresholding is a popular analysis method multiple testing in spatial data, and is frequently used for finding activated brain areas in neuroimaging. However, the method has several well-known issues. While powerful for finding regions with some activation, the method as currently defined does not allow any further quantification or localisation of signal. In this paper, we repair this gap. We show that cluster-extent inference can be used (1) to infer the presence of signal in any region of interest and (2) to quantify the percentage of activation in such regions. These additional inferences come for free, i.e. they do not require any further adjustment of the alpha-level of tests, while retaining full family-wise error control. We achieve this extension of the possibilities of cluster inference by embedding the method into a closed testing procedure, and solving the graph-theoretic k-separator problem that results from this embedding. We demonstrate the usefulness of the improved method in a large-scale application to neuroimaging data from the Neurovault database. Show less
The spread of antibiotic resistant bacteria (ARB) in the environment poses a potential threat to human health, and the reactivation of inactivated ARB accelerated the spread of ARB. However, little... Show moreThe spread of antibiotic resistant bacteria (ARB) in the environment poses a potential threat to human health, and the reactivation of inactivated ARB accelerated the spread of ARB. However, little is known about the reactivation of sunlight-inactivated ARB in natural waters. In this study, the reactivation of sunlight-inactivated ARB in dark conditions was investigated with tetracycline-resistant E. coli (Tc-AR E. coli) as a representative. Results showed that sunlight-inactivated Tc-AR E. coli underwent dark repair to regain tetracycline resistance with dark repair ratios increasing from (0.124 ± 0.012)‱ within 24 h dark treatment to (0.891 ± 0.033)‱ within 48 h. The presence of Suwannee River fulvic acid (SRFA) promoted the reactivation of sunlight-inactivated Tc-AR E. coli and tetracycline inhibited their reactivation. The reactivation of sunlight-inactivated Tc-AR E. coli is mainly attributed to the repair of the tetracycline-specific efflux pump in the cell membrane. Tc-AR E. coli in a viable but non-culturable (VBNC) state was observed and dominated the reactivation as the inactivated ARB remain present in the dark for more than 20 h. These results explained the reason for distribution difference of Tc-ARB at different depths in natural waters, which are of great significance for understanding the environmental behavior of ARB. Show less
Cluster inference based on spatial extent thresholding is a popular analysis method multiple testing in spatial data, and is frequently used for finding activated brain areas in neuroimaging.... Show moreCluster inference based on spatial extent thresholding is a popular analysis method multiple testing in spatial data, and is frequently used for finding activated brain areas in neuroimaging. However, the method has several well-known issues. While powerful for finding regions with some activation, the method as currently defined does not allow any further quantification or localisation of signal. In this paper, we repair this gap. We show that cluster-extent inference can be used (1) to infer the presence of signal in any region of interest and (2) to quantify the percentage of activation in such regions. These additional inferences come for free, i.e. they do not require any further adjustment of the alpha-level of tests, while retaining full family-wise error control. We achieve this extension of the possibilities of cluster inference by embedding the method into a closed testing procedure, and solving the graph-theoretic k-separator problem that results from this embedding. We demonstrate the usefulness of the improved method in a large-scale application to neuroimaging data from the Neurovault database. Show less
The Angstrom-scale space between graphene and its substrate provides an attractive playground for scientific exploration and can lead to breakthrough applications. Here, we report the energetics... Show moreThe Angstrom-scale space between graphene and its substrate provides an attractive playground for scientific exploration and can lead to breakthrough applications. Here, we report the energetics and kinetics of hydrogen electrosorption on a graphene-covered Pt(111) electrode using electrochemical experiments, in situ spectroscopy, and density functional theory calculations. The graphene overlayer influences the hydrogen adsorption on Pt(111) by shielding the ions from the interface and weakening the Pt-H bond energy. Analysis of the proton permeation resistance with controlled graphene defect density proves that the domain boundary defects and point defects are the pathways for proton permeation in the graphene layer, in agreement with density functional theory (DFT) calculations of the lowest energy proton permeation pathways. Although graphene blocks the interaction of anions with the Pt(111) surfaces, anions do adsorb near the defects: the rate constant for hydrogen permeation is sensitively dependent on anion identity and concentration. Show less
Amaro-Seoane, P.; Andrews, J.; Arca Sedda, M.; Askar, A.; Baghi, Q.; Balasov, R.; ... ; Vigna-Gómez, A. 2023
With the emergence of online social networks (OSNs), the way people create and share information has changed, which becomes faster and broader than traditional social media. Understanding how... Show moreWith the emergence of online social networks (OSNs), the way people create and share information has changed, which becomes faster and broader than traditional social media. Understanding how information (both good and harmful) spreads through OSNs, as well as what elements drive the success of information diffusion, has significant implications for a wide range of real-world applications. In this thesis, we conduct research to analysis the diffusion of information in OSNs via using deep representation learning. Specifically, we aim to develop deep learning- based models to solve two specific tasks, i.e., information cascades modeling and rumor detection. Show less
Existing methods for differential network analysis could only infer whether two networks of interest have differences between two groups of samples, but could not quantify and localize network... Show moreExisting methods for differential network analysis could only infer whether two networks of interest have differences between two groups of samples, but could not quantify and localize network differences. In this work, a novel method, permutation-based Network True Discovery Proportions (NetTDP), is proposed to quantify the number of edges (correlations) or nodes (genes) for which the co-expression networks are different. In the NetTDP method, we propose an edge-level statistic and a node-level statistic, and detect true discoveries of edges and nodes in the sense of differential co-expression network, respectively, by the permutation-based sumSome method. Furthermore, the NetTDP method could further localize the differences by inferring the TDPs for edge or gene subsets of interest, which can be selected post hoc. Our NetTDP method allows inference on data-driven modules or biology-driven gene sets, and remains valid even when these sub-networks are optimized using the same data. Experimental results on both simulation data sets and five real data sets show the effectiveness of the proposed method in inferring the quantification and localization of differential co-expression networks. The R code is available at hrips://github.com/LiminLi-xjtu/NetTDP. Show less
Simultaneous inference allows for the exploration of data while deciding on criteria for proclaiming discoveries. It was recently proved that all admissible post hoc inference methods for the true... Show moreSimultaneous inference allows for the exploration of data while deciding on criteria for proclaiming discoveries. It was recently proved that all admissible post hoc inference methods for the true discoveries must employ closed testing. In this paper, we investigate efficient closed testing with local tests of a special form: thresholding a function of sums of test scores for the individual hypotheses. Under this special design, we propose a new statistic that quantifies the cost of multiplicity adjustments, and we develop fast (mostly linear-time) algorithms for post hoc inference. Paired with recent advances in global null tests based on generalized means, our work instantiates a series of simultaneous inference methods that can handle many dependence structures and signal compositions. We provide guidance on the method choices via theoretical investigation of the conservativeness and sensitivity for different local tests, as well as simulations that find analogous behavior for local tests and full closed testing. Show less
Ye, C.; Raaijman, S.J.; Chen, X.; Koper, M.T.M. 2022
Developing active and selective catalysts that convert CO2 into valuable products remains a critical challenge for further application of the electrochemical CO2 reduction reaction (CO2RR).... Show moreDeveloping active and selective catalysts that convert CO2 into valuable products remains a critical challenge for further application of the electrochemical CO2 reduction reaction (CO2RR). Catalytic tuning with organic additives/films has emerged as a promising strategy to tune CO2RR activity and selectivity. Herein, we report a facile method to significantly change CO2RR selectivity and activity of copper and gold electrodes. We found improved selectivity toward HCOOH at low overpotentials on both polycrystalline Cu and Au electrodes after chemical modification with a poly(4-vinylpyridine) (P4VP) layer. In situ attenuated total reflection surface-enhanced infrared reflection-adsorption spectroscopy and contact angle measurements indicate that the hydrophobic nature of the P4VP layer limits mass transport of HCO3- and H2O, whereas it has little influence on CO2 mass transport. Moreover, the early onset of HCOOH formation and the enhanced formation of HCOOH over CO suggest that P4VP modification promotes a surface hydride mechanism for HCOOH formation on both electrodes. Show less
Jong, T.A. de; Chen, X.; Jobst, J.; Krasovskii, E.E.; Tromp, R.M.; Molen, S.J. van der 2022
Stacking domain boundaries occur in Van der Waals heterostacks whenever there is a twist angle or lattice mismatch between subsequent layers. Not only can these domain boundaries host topological... Show moreStacking domain boundaries occur in Van der Waals heterostacks whenever there is a twist angle or lattice mismatch between subsequent layers. Not only can these domain boundaries host topological edge states, imaging them has been instrumental to determine local variations in twisted bilayer graphene. Here, we analyse the mechanisms causing stacking domain boundary contrast in Bright Field Low-Energy Electron Microscopy (BF-LEEM) for both graphene on SiC, where domain boundaries are caused by strain and for twisted few layer graphene. We show that when domain boundaries are between the top two graphene layers, BF-LEEM contrast is observed due to amplitude contrast and corresponds well to calculations of the contrast based purely on the local stacking in the domain boundary. Conversely, for deeper-lying domain boundaries, amplitude contrast only provides a weak distinction between the inequivalent stackings in the domains themselves. However, for small domains phase contrast, where electrons from different parts of the unit cell interfere causes a very strong contrast. We derive a general rule-of-thumb of expected BF-LEEM contrast for domain boundaries in Van der Waals materials. Show less
Chen, X.; Granda Marulanda, L.P.; McCrum, I.T.; Koper, M.T.M. 2022
