bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Integrative Model for Soil Biogeochemistry and Methane Processes. II: Warming and Elevated CO2 Effects on Peatland CH4 Emissions
Authors: Yuan Fenghui , Wang Yihui , Ricciuto Daniel M. , Shi Xiaoying , Yuan Fengming , Hanson Paul J. , Bridgham Scott , Keller Jason , Thornton Peter E. , Xu Xiaofeng 
Published: July 2021

AbstractPeatlands are one of the largest natural sources for atmospheric methane (CH4), a potent greenhouse gas. Climate warming and elevated atmospheric carbon dioxide (CO2) are two important environmental factors that have been confirmed to stimulate peatland CH4 emissions; however, the mechanisms underlying enhanced emissions remain elusive. A data‐model integration approach was applied to understand the CH4 processes in a northern temperate peatland under a gradient of warming and doubled atmospheric CO2 concentration. We found that warming and elevated CO2 stimulated CH4 emissions through different mechanisms. Warming initially stimulated but then suppressed vegetative productivity while stimulating soil organic matter (SOM) mineralization and dissolved organic carbon (DOC) fermentation, which led to higher acetate production and enhanced acetoclastic and hydrogenotrophic methanogenesis. Warming also enhanced surface CH4 emissions, which combined with warming‐caused decreases in CH4 solubility led to slightly lower dissolved CH4 concentrations through the soil profiles. Elevated CO2 enhanced ecosystem productivity and SOM mineralization, resulting in higher DOC and acetate concentrations. Higher DOC and acetate concentrations increased acetoclastic and hydrogenotrophic methanogenesis and led to higher dissolved CH4 concentrations and CH4 emissions. Both warming and elevated CO2 had minor impacts on CH4 oxidation. A meta‐analysis of warming and elevated CO2 impacts on carbon cycling in wetlands agreed well with a majority of the modeled mechanisms. This mechanistic understanding of the stimulating impacts of warming and elevated CO2 on peatland CH4 emissions enhances our predictability on the climate‐ecosystem feedback.
Metabolic flexibility of aerobic methanotrophs under anoxic conditions in Arctic lake sediments
Authors: He Ruo , Wang Jing , Pohlman John W , Jia Zhongjun , Chu Yi-Xuan , Wooller Matthew J , Leigh Mary Beth 
Published: July 2021

Abstract
Methane (CH4) emissions from Arctic lakes are a large and growing source of greenhouse gas to the atmosphere with critical implications for global climate. Because Arctic lakes are ice covered for much of the year, understanding the metabolic flexibility of methanotrophs under anoxic conditions would aid in characterizing the mechanisms responsible for limiting CH4 emissions from high-latitude regions. Using sediments from an active CH4 seep in Lake Qalluuraq, Alaska, we conducted DNA-based stable isotope probing (SIP) in anoxic mesocosms and found that aerobic Gammaproteobacterial methanotrophs dominated in assimilating CH4. Aerobic methanotrophs were also detected down to 70 cm deep in sediments at the seep site, where anoxic conditions persist. Metagenomic analyses of the heavy DNA from 13CH4-SIP incubations showed that these aerobic methanotrophs had the capacity to generate intermediates such as methanol, formaldehyde, and formate from CH4 oxidation and to oxidize formaldehyde in the tetrahydromethanopterin (H4MPT)-dependent pathway under anoxic conditions. The high levels of Fe present in sediments, combined with Fe and CH4 profiles in the persistent CH4 seep site, suggested that oxidation of CH4, or, more specifically, its intermediates such as methanol and formaldehyde might be coupled to iron reduction. Aerobic methanotrophs also possessed genes associated with nitrogen and hydrogen metabolism, which might provide potentially alternative energy conservation options under anoxic conditions. These results expand the known metabolic spectrum of aerobic methanotrophs under anoxic conditions and necessitate the re-assessment of the mechanisms underlying CH4 oxidation in the Arctic, especially under lakes that experience extended O2 limitations during ice cover.
Taurodontism in dental genetics
Authors: Chetty Manogari , Roomaney Imaan A. , Beighton Peter 
Published: July 2021

AbstractTaurodontism is a dental anomaly defined by enlargement of the pulp chamber of multirooted teeth with apical displacement of the pulp floor and bifurcation of the roots. Taurodontism can be an isolated trait or part of a syndrome. A study was conducted to document the dental and craniofacial aspects of genetic thin bone disorders in South Africa. Sixty-four individuals with Osteogenesis imperfecta (OI), one individual with Pyle disease and one with Torg-Winchester syndrome respectively, were assessed clinically, radiographically and at a molecular level. Ten patients with OI XI and those with Pyle disease and Torg-Winchester syndrome had taurodontism. Taurodontism has been identified in several genetic disorders necessitating cognizance of the possible existence and implications of this characteristic when managing patients in the dental environment. Further studies should be directed toward identifying the incidence, etiology, and molecular pathways leading to taurodontism and its relationship to genetic syndromes.
In situ XRD and operando spectra-electrochemical investigation of tetragonal WO3-x nanowire networks for electrochromic supercapacitors
Authors: Wang Shen , Xu Hongbo , Hao Tingting , Wang Peiyuan , Zhang Xiang , Zhang Hongming , Xue Junying , Zhao Jiupeng , Li Yao 
Published: July 2021

AbstractElectrochromic supercapacitors (ESCs) are appealing for smart electronic device applications due to their advantages of dual-function integration. Unfortunately, the synchronous dual-function evaluation and the essential reaction mechanism are ambiguous. Herein, we constructed a 3D WO3-x nanowire networks/fluorine-doped tin oxide (WO3-x NWNs/FTO) bifunctional electrode for ESCs by a solvothermal self-crystal seeding method. The synchronous correspondence relationship between the optical and electrochemical performances of the WO3-x NWNs/FTO electrode was explored using an operando spectra-electrochemical characterization method. It reveals an excellent areal capacity of 57.57 mF cm−2 with a high corresponding optical modulation (ΔT) of 85.05% and high optical-electrochemical cycling stability. Furthermore, the synergistic reaction mechanism between the Al3+ ion intercalation behavior and the surface pseudocapacitance reaction during electrochemical cycling is revealed utilizing in situ X-ray diffraction. Based on these results, an ESC device was constructed by pairing WO3-x/FTO as the cathode with V2O5 nanoflowers/FTO (V2O5 NFs/FTO) as the anode, which simultaneously deliver high capacity and large optical modulation. Moreover, the energy storage level of the ESC device could be visually monitored by rapid and reversible color transitions in real time. This work provides a promising pathway to developing multi-functional integrated smart supercapacitors.
Mating can initiate stable RNA silencing that overcomes epigenetic recovery
Authors: Devanapally Sindhuja , Raman Pravrutha , Chey Mary , Allgood Samual , Ettefa Farida , Diop Maïgane , Lin Yixin , Cho Yongyi E. , Jose Antony M. 
Published: July 2021

AbstractStable epigenetic changes appear uncommon, suggesting that changes typically dissipate or are repaired. Changes that stably alter gene expression across generations presumably require particular conditions that are currently unknown. Here we report that a minimal combination of cis-regulatory sequences can support permanent RNA silencing of a single-copy transgene and its derivatives in C. elegans simply upon mating. Mating disrupts competing RNA-based mechanisms to initiate silencing that can last for >300 generations. This stable silencing requires components of the small RNA pathway and can silence homologous sequences in trans. While animals do not recover from mating-induced silencing, they often recover from and become resistant to trans silencing. Recovery is also observed in most cases when double-stranded RNA is used to silence the same coding sequence in different regulatory contexts that drive germline expression. Therefore, we propose that regulatory features can evolve to oppose permanent and potentially maladaptive responses to transient change.
Extracellular matrix protein-1 secretory isoform promotes ovarian cancer through increasing alternative mRNA splicing and stemness
Authors: Yin Huijing , Wang Jingshu , Li Hui , Yu Yinjue , Wang Xiaoling , Lu Lili , Lv Cuiting , Chang Bin , Jin Wei , Guo Wenwen , Ren Chunxia , Yang Gong 
Published: July 2021

AbstractExtracellular matrix protein-1 (ECM1) promotes tumorigenesis in multiple organs but the mechanisms associated to ECM1 isoform subtypes have yet to be clarified. We report in this study that the secretory ECM1a isoform induces tumorigenesis through the GPR motif binding to integrin αXβ2 and the activation of AKT/FAK/Rho/cytoskeleton signaling. The ATP binding cassette subfamily G member 1 (ABCG1) transduces the ECM1a-integrin αXβ2 interactive signaling to facilitate the phosphorylation of AKT/FAK/Rho/cytoskeletal molecules and to confer cancer cell cisplatin resistance through up-regulation of the CD326-mediated cell stemness. On the contrary, the non-secretory ECM1b isoform binds myosin and blocks its phosphorylation, impairing cytoskeleton-mediated signaling and tumorigenesis. Moreover, ECM1a induces the expression of the heterogeneous nuclear ribonucleoprotein L like (hnRNPLL) protein to favor the alternative mRNA splicing generating ECM1a. ECM1a, αXβ2, ABCG1 and hnRNPLL higher expression associates with poor survival, while ECM1b higher expression associates with good survival. These results highlight ECM1a, integrin αXβ2, hnRNPLL and ABCG1 as potential targets for treating cancers associated with ECM1-activated signaling.
Uncovering the eruptive patterns of the 2019 double paroxysm eruption crisis of Stromboli volcano
Authors: Andronico Daniele , Del Bello Elisabetta , D’Oriano Claudia , Landi Patrizia , Pardini Federica , Scarlato Piergiorgio , de’ Michieli Vitturi Mattia , Taddeucci Jacopo , Cristaldi Antonino , Ciancitto Francesco , Pennacchia Francesco , Ricci Tullio , Valentini Federico 
Published: July 2021

AbstractIn 2019, Stromboli volcano experienced one of the most violent eruptive crises in the last hundred years. Two paroxysmal explosions interrupted the ‘normal’ mild explosive activity during the tourist season. Here we integrate visual and field observations, textural and chemical data of eruptive products, and numerical simulations to analyze the eruptive patterns leading to the paroxysmal explosions. Heralded by 24 days of intensified normal activity and 45 min of lava outpouring, on 3 July a paroxysm ejected ~6 × 107 kg of bombs, lapilli and ash up to 6 km high, damaging the monitoring network and falling towards SW on the inhabited areas. Intensified activity continued until the less energetic, 28 August paroxysm, which dispersed tephra mainly towards NE. We argue that all paroxysms at Stromboli share a common pre-eruptive weeks-to months-long unrest phase, marking the perturbation of the magmatic system. Our analysis points to an urgent implementation of volcanic monitoring at Stromboli to detect such long-term precursors.
An adaptive threshold neuron for recurrent spiking neural networks with nanodevice hardware implementation
Authors: Shaban Ahmed , Bezugam Sai Sukruth , Suri Manan 
Published: July 2021

AbstractWe propose a Double EXponential Adaptive Threshold (DEXAT) neuron model that improves the performance of neuromorphic Recurrent Spiking Neural Networks (RSNNs) by providing faster convergence, higher accuracy and a flexible long short-term memory. We present a hardware efficient methodology to realize the DEXAT neurons using tightly coupled circuit-device interactions and experimentally demonstrate the DEXAT neuron block using oxide based non-filamentary resistive switching devices. Using experimentally extracted parameters we simulate a full RSNN that achieves a classification accuracy of 96.1% on SMNIST dataset and 91% on Google Speech Commands (GSC) dataset. We also demonstrate full end-to-end real-time inference for speech recognition using real fabricated resistive memory circuit based DEXAT neurons. Finally, we investigate the impact of nanodevice variability and endurance illustrating the robustness of DEXAT based RSNNs.
Practical iridium-catalyzed direct α-arylation of N-heteroarenes with (hetero)arylboronic acids by H2O-mediated H2 evolution
Authors: Cao Liang , Zhao He , Guan Rongqing , Jiang Huanfeng , Dixneuf Pierre. H. , Zhang Min 
Published: July 2021

AbstractDespite the widespread applications of 2-(hetero)aryl N-heteroarenes in numerous fields of science and technology, universal access to such compounds is hampered due to the lack of a general method for their synthesis. Herein, by a H2O-mediated H2-evolution cross-coupling strategy, we report an iridium(III)-catalyzed facile method to direct α-arylation of N-heteroarenes with both aryl and heteroaryl boronic acids, proceeding with broad substrate scope and excellent functional compatibility, oxidant and reductant-free conditions, operational simplicity, easy scalability, and no need for prefunctionalization of N-heteroarenes. This method is applicable for structural modification of biomedical molecules, and offers a practical route for direct access to 2-(hetero)aryl N-heteroarenes, a class of potential cyclometalated C^N ligands and N^N bidentate ligands that are difficult to prepare with the existing α-C-H arylation methods, thus filling an important gap in the capabilities of synthetic organic chemistry.
Potent and protective IGHV3-53/3-66 public antibodies and their shared escape mutant on the spike of SARS-CoV-2
Authors: Zhang Qi , Ju Bin , Ge Jiwan , Chan Jasper Fuk-Woo , Cheng Lin , Wang Ruoke , Huang Weijin , Fang Mengqi , Chen Peng , Zhou Bing , Song Shuo , Shan Sisi , Yan Baohua , Zhang Senyan , Ge Xiangyang , Yu Jiazhen , Zhao Juanjuan , Wang Haiyan , Liu Li , Lv Qining , Fu Lili , Shi Xuanling , Yuen Kwok Yung , Liu Lei , Wang Youchun , Chen Zhiwei , Zhang Linqi , Wang Xinquan , Zhang Zheng 
Published: July 2021

AbstractNeutralizing antibodies (nAbs) to SARS-CoV-2 hold powerful potentials for clinical interventions against COVID-19 disease. However, their common genetic and biologic features remain elusive. Here we interrogate a total of 165 antibodies from eight COVID-19 patients, and find that potent nAbs from different patients have disproportionally high representation of IGHV3-53/3-66 usage, and therefore termed as public antibodies. Crystal structural comparison of these antibodies reveals they share similar angle of approach to RBD, overlap in buried surface and binding residues on RBD, and have substantial spatial clash with receptor angiotensin-converting enzyme-2 (ACE2) in binding to RBD. Site-directed mutagenesis confirms these common binding features although some minor differences are found. One representative antibody, P5A-3C8, demonstrates extraordinarily protective efficacy in a golden Syrian hamster model against SARS-CoV-2 infection. However, virus escape analysis identifies a single natural mutation in RBD, namely K417N found in B.1.351 variant from South Africa, abolished the neutralizing activity of these public antibodies. The discovery of public antibodies and shared escape mutation highlight the intricate relationship between antibody response and SARS-CoV-2, and provide critical reference for the development of antibody and vaccine strategies to overcome the antigenic variation of SARS-CoV-2.
Arginine methylation promotes siRNA-binding specificity for a spermatogenesis-specific isoform of the Argonaute protein CSR-1
Authors: Nguyen Dieu An H. , Phillips Carolyn M. 
Published: July 2021

AbstractCSR-1 is an essential Argonaute protein that binds to a subclass of 22G-RNAs targeting most germline-expressed genes. Here we show that the two isoforms of CSR-1 have distinct expression patterns; CSR-1B is ubiquitously expressed throughout the germline and during all stages of development while CSR-1A expression is restricted to germ cells undergoing spermatogenesis. Furthermore, CSR-1A associates preferentially with 22G-RNAs mapping to spermatogenesis-specific genes whereas CSR-1B-bound small RNAs map predominantly to oogenesis-specific genes. Interestingly, the exon unique to CSR-1A contains multiple dimethylarginine modifications, which are necessary for the preferential binding of CSR-1A to spermatogenesis-specific 22G-RNAs. Thus, we have discovered a regulatory mechanism for C. elegans Argonaute proteins that allows for specificity of small RNA binding between similar Argonaute proteins with overlapping temporal and spatial localization.
Graph neural networks for an accurate and interpretable prediction of the properties of polycrystalline materials
Authors: Dai Minyi , Demirel Mehmet F. , Liang Yingyu , Hu Jia-Mian 
Published: July 2021

AbstractVarious machine learning models have been used to predict the properties of polycrystalline materials, but none of them directly consider the physical interactions among neighboring grains despite such microscopic interactions critically determining macroscopic material properties. Here, we develop a graph neural network (GNN) model for obtaining an embedding of polycrystalline microstructure which incorporates not only the physical features of individual grains but also their interactions. The embedding is then linked to the target property using a feed-forward neural network. Using the magnetostriction of polycrystalline Tb0.3Dy0.7Fe2 alloys as an example, we show that a single GNN model with fixed network architecture and hyperparameters allows for a low prediction error of ~10% over a group of remarkably different microstructures as well as quantifying the importance of each feature in each grain of a microstructure to its magnetostriction. Such a microstructure-graph-based GNN model, therefore, enables an accurate and interpretable prediction of the properties of polycrystalline materials.
Optimal supply chains and power sector benefits of green hydrogen
Authors: Stöckl Fabian , Schill Wolf-Peter , Zerrahn Alexander 
Published: July 2021

AbstractGreen hydrogen can help to decarbonize parts of the transportation sector, but its power sector interactions are not well understood so far. It may contribute to integrating variable renewable energy sources if production is sufficiently flexible in time. Using an open-source co-optimization model of the power sector and four options for supplying hydrogen at German filling stations, we find a trade-off between energy efficiency and temporal flexibility. For lower shares of renewables and hydrogen, more energy-efficient and less flexible small-scale on-site electrolysis is optimal. For higher shares of renewables and/or hydrogen, more flexible but less energy-efficient large-scale hydrogen supply chains gain importance, as they allow to temporally disentangle hydrogen production from demand via storage. Liquid hydrogen emerges as particularly beneficial, followed by liquid organic hydrogen carriers and gaseous hydrogen. Large-scale hydrogen supply chains can deliver substantial power sector benefits, mainly through reduced renewable curtailment. Energy modelers and system planners should consider the distinct flexibility characteristics of hydrogen supply chains in more detail when assessing the role of green hydrogen in future energy transition scenarios. We also propose two alternative cost and emission metrics which could be useful in future analyses.
A novel bidirectional clustering algorithm based on local density
Authors: Lyu Baicheng , Wu Wenhua , Hu Zhiqiang 
Published: July 2021

AbstractWith the widely application of cluster analysis, the number of clusters is gradually increasing, as is the difficulty in selecting the judgment indicators of cluster numbers. Also, small clusters are crucial to discovering the extreme characteristics of data samples, but current clustering algorithms focus mainly on analyzing large clusters. In this paper, a bidirectional clustering algorithm based on local density (BCALoD) is proposed. BCALoD establishes the connection between data points based on local density, can automatically determine the number of clusters, is more sensitive to small clusters, and can reduce the adjusted parameters to a minimum. On the basis of the robustness of cluster number to noise, a denoising method suitable for BCALoD is proposed. Different cutoff distance and cutoff density are assigned to each data cluster, which results in improved clustering performance. Clustering ability of BCALoD is verified by randomly generated datasets and city light satellite images.
The stability of paintings and the molecular structure of the oil paint polymeric network
Authors: Nardelli Francesca , Martini Francesca , Lee Judith , Lluvears-Tenorio Anna , La Nasa Jacopo , Duce Celia , Ormsby Bronwyn , Geppi Marco , Bonaduce Ilaria 
Published: July 2021

AbstractA molecular-level understanding of the structure of the polymeric network formed upon the curing of air-drying artists’ oil paints still represents a challenge. In this study we used a set of analytical methodologies classically employed for the characterisation of a paint film—based on infrared spectroscopy and mass spectrometry—in combination with solid state NMR (SSNMR), to characterise model paint layers which present different behaviours towards surface cleaning with water, a commonly applied procedure in art conservation. The study demonstrates, with the fundamental contribution of SSNMR, a relationship between the painting stability and the chemical structure of the polymeric network. In particular, it is demonstrated for the first time that a low degree of cross-linking in combination with a high degree of oxidation of the polymeric network render the oil paint layer sensitive to water.
Rotational-invariant speckle-scanning ultrasonography through thick bones
Authors: Liang Siyi , Wang Lidai 
Published: July 2021

AbstractUltrasonography is a major medical imaging technique that has been broadly applied in many disease diagnoses. However, due to strong aberration and scattering in the human skull, high-resolution transcranial ultrasonic imaging remains a grand challenge. Here, we explore the rotational-invariant property of ultrasonic speckle and develop high-resolution speckle-scanning ultrasonography to image sub-millimeter-sized features through thick bones. We experimentally validate the rotational invariance of ultrasonic speckle. Based on this property, we scan a random ultrasonic speckle pattern across an object sandwiched between two thick bones so that the object features can be encoded to the ultrasonic waves. After receiving the transmitted ultrasonic waves, we reconstruct the image of the object using an iterative phase retrieval algorithm. We successfully demonstrate imaging of hole and tube features sized as fine as several hundreds of microns between two 0.5 ~ 1-cm-thick bones. With 2.5-MHz excitation and the third-harmonic detection, we measure the spatial resolution as 352 µm. Rotational-invariant speckle-scanning ultrasonography offers a new approach to image through thick bones and paves an avenue towards high-resolution ultrasonic imaging of the human brain.