bluuebunny/crossref_metadata_2025_split huggingface dataset:
Variability in Sea Surface pCO2 and Controlling Factors in the Bay of Bengal Based on buoy Observations at 15°N, 90°E
Authors: Ye Haijun , Tang Shilin , Morozov Evgeny 
Published: September 2022

AbstractDiurnal variability of the CO2 partial pressure (pCO2) at the sea surface (pCO2sea) and its impact on air‐sea CO2 flux estimations are currently poorly understood. In this work, diurnal variations in pCO2sea were examined in the Bay of Bengal (BoB) based on 3‐hourly observations collected at the BoB Ocean Acidification moored buoy between November 2013 and November 2018 by a moored autonomous pCO2 system. Significant mean diurnal pCO2sea cycles and a mean diurnal amplitude of 11 ± 9 μatm were observed based on 1215 complete diurnal cycles. One‐dimensional mass budget model calculations suggest that temperature was responsible for these mean diurnal variations in pCO2sea and that these variations were intensified by biological activity. The effects of air‐sea gas fluxes and mixing on the mean diurnal pCO2sea variability were very low. A weak annual net source of 12.1 mmol m−2 year−1 was estimated at this site. The sampling frequency greatly impacted the annual air‐sea CO2 flux estimations. Compared to the 3‐hr sampling frequency, random daily sampling resulted in a bias of ±7.7 mmol m−2 year−1 or 64%, and regular daily sampling resulted in a maximum bias of 400%. Factorial experiments showed that wind speed had the largest impact on the air‐sea CO2 flux estimations, followed by pCO2sea and atmospheric pCO2 (pCO2air). These findings indicate the importance of obtaining continuous pCO2 measurements to accurately estimate air‐sea CO2 flux; additionally, pCO2 and wind speed measurements should be obtained at frequencies higher than 6 hr.
Evaluation of Soil Moisture in CMIP6 Multimodel Simulations Over Conterminous China
Authors: Wang Aihui , Kong Xianghui , Chen Yue , Ma Xin 
Published: September 2022

AbstractThe Sixth Phase of the Coupled Model Intercomparison Project (CMIP6) provides the long‐term soil moisture (SM) products and this study conducts a comprehensive assessment of SM products of multiple CMIP6 model simulations over conterminous China. Both near‐surface (0–10 cm) SM simulations from 40 models and root‐zone (0–100 cm) SM from 25 models are compared with a set of in situ and a satellite‐based data set in the growing season for 1992–2013. The long‐term trend and interannual variability of near‐surface SM for 1961–2014 are further evaluated with an offline land surface modeling data set. Simulations from most models broadly capture the spatial characteristics of observation, and the multimodel mean (MME) well reproduces seasonal variations over the majority of regions, regardless of the large spread across models. SM from CMIP6 models from the same institution likely manifests similar performances, which indicates that the land‐surface scheme plays a dominant role in the CMIP6 SM reproduction. The majority of CMIP6 models well simulate the overall drying trend in China as a whole and the signs of a SM trend are highly consistent across different models, but the areas with significant wetting/drying trends vary with models. The spatial patterns of SM interannual variability are model‐dependent. MME is overall superior to the simulation of individual model and may have potential applications in future research. The heterogeneity of SM performances across CMIP6 models reveals the complexity and uncertainty in modeling land surface variables, suggesting the need for improving representations of land surface processes in the coupled models.
Heritability of REM sleep neurophysiology in adolescence
Authors: Markovic Andjela , Kaess Michael , Tarokh Leila 
Published: September 2022

AbstractAlterations of rapid eye movement (REM) sleep have long been observed in patients with psychiatric disorders and proposed as an endophenotype—a link between behavior and genes. Recent experimental work has shown that REM sleep plays an important role in the emotional processing of memories, emotion regulation, and is altered in the presence of stress, suggesting a mechanism by which REM sleep may impact psychiatric illness. REM sleep shows a developmental progression and increases during adolescence—a period of rapid maturation of the emotional centers of the brain. This study uses a behavioral genetics approach to understand the relative contribution of genes, shared environmental and unique environmental factors to REM sleep neurophysiology in adolescents. Eighteen monozygotic (MZ; n = 36; 18 females) and 12 dizygotic (DZ; n = 24; 12 females) same-sex twin pairs (mean age = 12.46; SD = 1.36) underwent whole-night high-density sleep EEG recordings. We find a significant genetic contribution to REM sleep EEG power across frequency bands, explaining, on average, between 75 to 88% of the variance in power, dependent on the frequency band. In the lower frequency bands between delta and sigma, however, we find an additional impact of shared environmental factors over prescribed regions. We hypothesize that these regions may reflect the contribution of familial and environmental stress shared amongst the twins. The observed strong genetic contribution to REM sleep EEG power in early adolescence establish REM sleep neurophysiology as a potentially strong endophenotype, even in adolescence—a period marked by significant brain maturation.
From concepts to treatment: a dialog between a preclinical researcher and a clinician in addiction medicine
Authors: Vandaele Youna , Daeppen Jean-Bernard 
Published: September 2022

AbstractThe debate surrounding the brain disease model and the associated questioning of the relevance of animal models is polarizing the field of addiction, and tends to widen the gap between preclinical research and addiction medicine. Here, we aimed at bridging this gap by establishing a dialog between a preclinical researcher and a clinician in addiction medicine. Our objective was to evaluate animal models and the neuroscientific conceptualization of addiction in light of alcohol or drug dependence and treatment in patients struggling with an addiction. We sought to determine how preclinical research influenced addiction medicine over past decades, and reciprocally, what can preclinical researchers learn from addiction medicine that could lead to more effective approaches. In this dialog, we talk about the co-evolution of addiction concepts and treatments from neuroscientific and medical perspectives. This dialog illustrates the reciprocal influences and mutual enrichment between the two disciplines and reveals that, although preclinical research might not produce new pharmacotherapies, it does shape the theoretical conceptualization of addiction and could thereby contribute to the implementation of therapeutic approaches.
Intrinsic bias estimation for improved analysis of bulk and single-cell chromatin accessibility profiles using SELMA
Authors: Hu Shengen Shawn , Liu Lin , Li Qi , Ma Wenjing , Guertin Michael J. , Meyer Clifford A. , Deng Ke , Zhang Tingting , Zang Chongzhi 
Published: September 2022

AbstractGenome-wide profiling of chromatin accessibility by DNase-seq or ATAC-seq has been widely used to identify regulatory DNA elements and transcription factor binding sites. However, enzymatic DNA cleavage exhibits intrinsic sequence biases that confound chromatin accessibility profiling data analysis. Existing computational tools are limited in their ability to account for such intrinsic biases and not designed for analyzing single-cell data. Here, we present Simplex Encoded Linear Model for Accessible Chromatin (SELMA), a computational method for systematic estimation of intrinsic cleavage biases from genomic chromatin accessibility profiling data. We demonstrate that SELMA yields accurate and robust bias estimation from both bulk and single-cell DNase-seq and ATAC-seq data. SELMA can utilize internal mitochondrial DNA data to improve bias estimation. We show that transcription factor binding inference from DNase footprints can be improved by incorporating estimated biases using SELMA. Furthermore, we show strong effects of intrinsic biases in single-cell ATAC-seq data, and develop the first single-cell ATAC-seq intrinsic bias correction model to improve cell clustering. SELMA can enhance the performance of existing bioinformatics tools and improve the analysis of both bulk and single-cell chromatin accessibility sequencing data.
Observation of spin-glass-like characteristics in ferrimagnetic TbCo through energy-level-selective approach
Authors: Park Ji-Ho , Kim Won Tae , Won Woonjae , Kang Jun-Ho , Lee Soogil , Park Byong-Guk , Ham Byoung S. , Jo Younghun , Rotermund Fabian , Kim Kab-Jin 
Published: September 2022

AbstractRare earth (RE)–transition metal (TM) ferrimagnetic alloys are gaining increasing attention because of their potential use in the field of antiferromagnetic spintronics. The moment from RE sub-lattice primarily originates from the 4f-electrons located far below the Fermi level (EF), and the moment from TM sub-lattice arises from the 3d-electrons across the EF. Therefore, the individual magnetic moment configurations at different energy levels must be explored to clarify the microscopic mechanism of antiferromagnetic spin dynamics. Considering these issues, here we investigate the energy-level-selective magnetic moment configuration in ferrimagnetic TbCo alloy. We reveal that magnetic moments at deeper energy levels are more easily altered by the external magnetic field than those near the EF. More importantly, we find that the magnetic moments at deeper energy levels exhibit a spin-glass-like characteristics such as slow dynamics and magnetic moment freezing whereas those at EF do not. These unique energy-level-dependent characteristics of RE-TM ferrimagnet may provide a better understanding of ferrimagnet, which could be useful in spintronic applications as well as in spin-glass studies.
Atomistic deformation mechanism of silicon under laser-driven shock compression
Authors: Pandolfi Silvia , Brown S. Brennan , Stubley P. G. , Higginbotham Andrew , Bolme C. A. , Lee H. J. , Nagler B. , Galtier E. , Sandberg R. L. , Yang W. , Mao W. L. , Wark J. S. , Gleason A. E. 
Published: September 2022

AbstractSilicon (Si) is one of the most abundant elements on Earth, and it is the most widely used semiconductor. Despite extensive study, some properties of Si, such as its behaviour under dynamic compression, remain elusive. A detailed understanding of Si deformation is crucial for various fields, ranging from planetary science to materials design. Simulations suggest that in Si the shear stress generated during shock compression is released via a high-pressure phase transition, challenging the classical picture of relaxation via defect-mediated plasticity. However, direct evidence supporting either deformation mechanism remains elusive. Here, we use sub-picosecond, highly-monochromatic x-ray diffraction to study (100)-oriented single-crystal Si under laser-driven shock compression. We provide the first unambiguous, time-resolved picture of Si deformation at ultra-high strain rates, demonstrating the predicted shear release via phase transition. Our results resolve the longstanding controversy on silicon deformation and provide direct proof of strain rate-dependent deformation mechanisms in a non-metallic system.
Metabolic pathway assembly using docking domains from type I cis-AT polyketide synthases
Authors: Sun Xixi , Yuan Yujie , Chen Qitong , Nie Shiqi , Guo Jiaxuan , Ou Zutian , Huang Min , Deng Zixin , Liu Tiangang , Ma Tian 
Published: September 2022

AbstractEngineered metabolic pathways in microbial cell factories often have no natural organization and have challenging flux imbalances, leading to low biocatalytic efficiency. Modular polyketide synthases (PKSs) are multienzyme complexes that synthesize polyketide products via an assembly line thiotemplate mechanism. Here, we develop a strategy named mimic PKS enzyme assembly line (mPKSeal) that assembles key cascade enzymes to enhance biocatalytic efficiency and increase target production by recruiting cascade enzymes tagged with docking domains from type I cis-AT PKS. We apply this strategy to the astaxanthin biosynthetic pathway in engineered Escherichia coli for multienzyme assembly to increase astaxanthin production by 2.4-fold. The docking pairs, from the same PKSs or those from different cis-AT PKSs evidently belonging to distinct classes, are effective enzyme assembly tools for increasing astaxanthin production. This study addresses the challenge of cascade catalytic efficiency and highlights the potential for engineering enzyme assembly.
Physics-embedded graph network for accelerating phase-field simulation of microstructure evolution in additive manufacturing
Authors: Xue Tianju , Gan Zhengtao , Liao Shuheng , Cao Jian 
Published: September 2022

AbstractThe phase-field (PF) method is a physics-based computational approach for simulating interfacial morphology. It has been used to model powder melting, rapid solidification, and grain structure evolution in metal additive manufacturing (AM). However, traditional direct numerical simulation (DNS) of the PF method is computationally expensive due to sufficiently small mesh size. Here, a physics-embedded graph network (PEGN) is proposed to leverage an elegant graph representation of the grain structure and embed the classic PF theory into the graph network. By reformulating the classic PF problem as an unsupervised machine learning task on a graph network, PEGN efficiently solves temperature field, liquid/solid phase fraction, and grain orientation variables to minimize a physics-based loss/energy function. The approach is at least 50 times faster than DNS in both CPU and GPU implementation while still capturing key physical features. Hence, PEGN allows to simulate large-scale multi-layer and multi-track AM build effectively.
Tracking SARS-COV-2 variants using Nanopore sequencing in Ukraine in 2021
Authors: Yakovleva Anna , Kovalenko Ganna , Redlinger Matthew , Liulchuk Mariia G. , Bortz Eric , Zadorozhna Viktoria I. , Scherbinska Alla M. , Wertheim Joel O. , Goodfellow Ian , Meredith Luke , Vasylyeva Tetyana I. 
Published: September 2022

AbstractThe use of real-time genomic epidemiology has enabled the tracking of the global spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), informing evidence-based public health decision making. Ukraine has experienced four waves of the Coronavirus Disease 2019 (COVID-19) between spring 2020 and spring 2022. However, insufficient capacity for local genetic sequencing limited the potential application of SARS-CoV-2 genomic surveillance for public health response in the country. Herein, we report local sequencing of 103 SARS-CoV-2 genomes from patient samples collected in Kyiv in July-December 2021 using Oxford Nanopore technology. Together with other published Ukrainian SARS-CoV-2 genomes, our data suggest that the third wave of the epidemic in Ukraine (June-December 2021) was dominated by the Delta Variant of Concern (VOC). Our phylogeographic analysis revealed that in summer 2021 Delta VOC was introduced into Ukraine from multiple locations worldwide, with most introductions coming from Central and Eastern European countries. The wide geographic range of Delta introductions coincides with increased volume of travel to Ukraine particularly from locations outside of Europe in summer 2021. This study highlights the need to urgently integrate affordable and easily scaled pathogen sequencing technologies in locations with less developed genomic infrastructure, in order to support local public health decision making.
Depression and bipolar disorder subtypes differ in their genetic correlations with biological rhythms
Authors: Sirignano Lea , Streit Fabian , Frank Josef , Zillich Lea , Witt Stephanie H. , Rietschel Marcella , Foo Jerome C. 
Published: September 2022

AbstractMajor Depression and Bipolar Disorder Type I (BIP-I) and Type II (BIP-II), are characterized by depressed, manic, and hypomanic episodes in which specific changes of physical activity, circadian rhythm, and sleep are observed. It is known that genetic factors contribute to variation in mood disorders and biological rhythms, but unclear to what extent there is an overlap between their underlying genetics. In the present study, data from genome-wide association studies were used to examine the genetic relationship between mood disorders and biological rhythms. We tested the genetic correlation of depression, BIP-I, and BIP-II with physical activity (overall physical activity, moderate activity, sedentary behaviour), circadian rhythm (relative amplitude), and sleep features (sleep duration, daytime sleepiness). Genetic correlations of depression, BIP-I, and BIP-II with biological rhythms were compared to discover commonalities and differences. A gene-based analysis tested for associations of single genes and common circadian genes with mood disorders. Depression was negatively correlated with overall physical activity and positively with sedentary behaviour, while BIP-I showed associations in the opposite direction. Depression and BIP-II had negative correlations with relative amplitude. All mood disorders were positively correlated with daytime sleepiness. Overall, we observed both genetic commonalities and differences across mood disorders in their relationships with biological rhythms: depression and BIP-I differed the most, while BIP-II was in an intermediate position. Gene-based analysis suggested potential targets for further investigation. The present results suggest shared genetic underpinnings for the clinically observed associations between mood disorders and biological rhythms. Research considering possible joint mechanisms may offer avenues for improving disease detection and treatment.
China’s LNG import risk assessment based on the perspective of global governance
Authors: Zeng Weijing , Zhang Xianfeng , Li Na , Wang Xiaobo , Wang Xiaolin 
Published: September 2022

AbstractThe uncertainty of LNG import risks will have a significant impact on China's energy security. This paper establishes a multi-agent game model based on the current LNG transportation network and global LNG supply and demand pattern, evaluates the LNG import risks faced by China under the global governance model, and simulates and predicts the optimal LNG import strategy of China in 2030. The research results show that between 2007 and 2020, China’s LNG import risks increased rapidly compared with political risks and national risks. From the perspective of risk identification, the comprehensive risk of China's imports from Southeast Asia and Australia is lower. However, due to the increasing demand gap for LNG, the Middle East, and Africa are still necessary supply sources. It is estimated that by 2030, the future LNG market will be oversupplied, and the United States is expected to become the world's top LNG supplier. China will reduce its dependence on Africa and the Middle East, and import a large amount of natural gas from the United States, Australia, Qatar, and Russia to reduce supply risks. From the perspective of import market competition, the new analysis model proposed in this article provides an effective tool for exploring the optimal strategy for LNG import.
Novel method for detecting complement C3 deposition on Staphylococcus aureus
Authors: Wonfor Toska , Li Shuxian , Dunphy Rhys W. , Macpherson Alex , van den Elsen Jean , Laabei Maisem 
Published: September 2022

AbstractThe primary host response to Staphylococcus aureus infection occurs via complement. Complement is an elegant evolutionarily conserved system, playing essential roles in early defences by working in concert with immune cells to survey, label and destroy microbial intruders and coordinate inflammation. Currently the exact mechanisms employed by S. aureus to manipulate and evade complement is not clear and is hindered by the lack of accurate molecular tools that can report on complement deposition on the bacterial surface. Current gold-standard detection methods employ labelled complement-specific antibodies and flow cytometry to determine complement deposited on bacteria. These methods are restricted by virtue of the expression of the S. aureus immunoglobulin binding proteins, Protein A and Sbi. In this study we describe the use of a novel antibody-independent C3 probe derived from the staphylococcal Sbi protein, specifically Sbi-IV domain. Here we show that biotin-labelled Sbi-IV interacts specifically with deposited C3 products on the staphylococcal surface and thus can be used to measure complement fixation on wild-type cells expressing a full repertoire of immune evasion proteins. Lastly, our data indicates that genetically diverse S. aureus strains restrict complement to different degrees suggesting that complement evasion is a variable virulence trait among S. aureus isolates.
Updated reference ranges for aminotransferase levels of Korean children and young adolescents based on the risk factors for metabolic syndrome
Authors: Seo Young-Jun , Shim Young Suk , Lee Hae Sang , Hwang Jin Soon 
Published: September 2022

AbstractWe investigated the reference values of liver enzymes based on cardiometabolic risks among children and adolescents using the Korea National Health and Nutrition Examination Survey. A total of 8091 subjects aged 10–18 years were included from the data from 2007–2017. Overall, aspartate aminotransferase (AST), alanine aminotransferase (ALT), and the AST/ALT ratio varied with sex and age. AST levels tended to decrease with age, but ALT levels had a U-shaped curve, which resulted in a gradual increase in the AST/ALT ratio after age 13. The prevalence of MetS was strongly associated with elevated AST or ALT and a decreased AST/ALT ratio. The prevalence ratios of the development of MetS were also elevated in groups with high levels of AST and ALT and a low AST/ALT ratio. Particularly in the combined ALT and AST/ALT analyses, borderline-high levels also showed a high prevalence ratio of MetS. Liver enzymes were also involved in the increase in the adjusted mean values for each risk factor for MetS. Here, we provided updated reference values for liver enzymes based on the analysis between population-based data and cardiometabolic risk factors; AST, ALT and the AST/ALT ratio might be useful in the early diagnosis and treatment of MetS.