bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tidal and Nontidal Marsh Restoration: A Trade‐Off Between Carbon Sequestration, Methane Emissions, and Soil Accretion
Authors: Arias‐Ortiz Ariane , Oikawa Patricia Y. , Carlin Joseph , Masqué Pere , Shahan Julie , Kanneg Sadie , Paytan Adina , Baldocchi Dennis D. 
Published: November 2021

AbstractSupport for coastal wetland restoration projects that consider carbon (C) storage as a climate mitigation benefit is growing as coastal wetlands are sites of substantial C sequestration. However, the climate footprint of wetland restoration remains controversial as wetlands can also be large sources of methane (CH4). We quantify the vertical fluxes of C in restored fresh and oligohaline nontidal wetlands with managed hydrology and a tidal euhaline marsh in California's San Francisco Bay‐Delta. We combine the use of eddy covariance atmospheric flux measurements with 210Pb‐derived soil C accumulation rates to quantify the C sequestration efficiency of restored wetlands and their associated climate mitigation service. Nontidal managed wetlands were the most efficient in burying C on‐site, with soil C accumulation rates as high as their net atmospheric C uptake (−280 ± 90 and −350 ± 150 g C m−2 yr−1). In contrast, the restored tidal wetland exhibited lower C burial rates over decadal timescales (70 ± 19 g C m−2 yr−1) that accounted for ∼13%–23% of its annual C uptake, suggesting that the remaining fraction is exported via lateral hydrologic flux. From an ecosystem radiative balance perspective, the restored tidal wetland showed a > 10 times higher CO2‐sequestration to CH4‐emission ratio than the nontidal managed wetlands. Thus overall, tidal wetland restoration resulted in a negative radiative forcing (cooling) through increased soil C accumulation, while nontidal wetland restoration led to an early positive forcing (warming) through increased CH4 emissions potentially lasting between 2.1 ± 2.0 to 8 ± 4 decades.
Explore Spatio‐Temporal Learning of Large Sample Hydrology Using Graph Neural Networks
Authors: Sun Alexander Y. , Jiang Peishi , Mudunuru Maruti K. , Chen Xingyuan 
Published: November 2021

AbstractStreamflow forecasting over gauged and ungauged basins play a vital role in water resources planning, especially under the changing climate. Increased availability of large sample hydrology data sets, together with recent advances in deep learning techniques, has presented new opportunities to explore temporal and spatial patterns in hydrological signatures for improving streamflow forecasting. The purpose of this study is to adapt and benchmark several state‐of‐the‐art graph neural network (GNN) architectures, including ChebNet, Graph Convolutional Network (GCN), and GraphWaveNet, for end‐to‐end graph learning. We explicitly represent river basins as nodes in a graph, learn the spatiotemporal nodal dependencies, and then use the learned relations to predict streamflow simultaneously across all nodes in the graph. The efficacy of the developed GNN models is investigated using the Catchment Attributes and MEteorology for Large‐sample Studies (CAMELS) data set under two settings, fixed graph topology (transductive learning), and variable graph topology (inductive learning), with the latter applicable to prediction in ungauged basins (PUB). Results indicate that GNNs are generally robust and computationally efficient, achieving similar or better performance than a baseline model trained using the long short‐term memory (LSTM) network. Further analyses are conducted to interpret the graph learning process at the edge and node levels and to investigate the effect of different model configurations. We conclude that graph learning constitutes a viable machine learning‐based method for aggregating spatiotemporal information from a multitude of sources for streamflow forecasting
General dental practitioners' knowledge and opinions of snoring and sleep-related breathing disorders
Authors: Leigh Charlotte , Faigenblum Maurice , Fine Peter , Blizard Robert , Leung Albert 
Published: November 2021

AbstractAimsThere is increasing recognition that sleep disturbances can affect lifestyle, economy and health. General dental practitioners (GDPs) can play a vital role in helping to identify at-risk patients through screening as well as aid in the management of these conditions. The aim of this study was to assess the knowledge of UK-based GDPs in relation to sleep-related breathing disorders (SRBDs).Material and methodsA questionnaire was developed to assess GDPs' knowledge of SRBDs and their current practice in relation to the management of SRBDs, and identify the factors associated with improved knowledge and management. A volunteer sample was recruited from social media platforms and conference attendees.ResultsIn total, 152 GDPs completed the questionnaire; 101 (66% [95% CI 59%,74%]) agreed that GDPs should ask their patients about sleep disorders, while only 82 (54% [95% CI 46%,62%]) confirmed that they actually asked their patients about the problem. On a 22-point knowledge scale, the mean score was 12.93 (95%CI 12.23, 13.63). Postgraduate education (F = 5.47; p = 0.001), increasing age (r = 0.23; p = 0.005) and GDP workplace (F = 4.98; p = 0.008) contributed to a higher knowledge score. GDPs were strongly in favour of having more information (N = 141; 93% [95% CI 87%,97%]).ConclusionAlthough GDPs' knowledge of SRBDs was better than anticipated, they clearly felt a need for further information and training. There is a compelling case to include this subject in the undergraduate dental curriculum.
Ionizing irradiation-induced Fgr in senescent cells mediates fibrosis
Authors: Mukherjee Amitava , Epperly Michael W. , Shields Donna , Hou Wen , Fisher Renee , Hamade Diala , Wang Hong , Saiful Huq M. , Bao Riyue , Tabib Tracy , Monier Daisy , Watkins Simon , Calderon Michael , Greenberger Joel S. 
Published: November 2021

AbstractThe role of cellular senescence in radiation-induced pulmonary fibrosis (RIPF) and the underlying mechanisms are unknown. We isolated radiation-induced senescent tdTOMp16 positive mesenchymal stem cells, established their absence of cell division, then measured levels of irradiation-induced expression of biomarkers of senescence by RNA-seq analysis. We identified a Log2 6.17-fold upregulation of tyrosine kinase Fgr, which was a potent inducer of biomarkers of fibrosis in target cells in non-contact co-cultures. Inhibition of Fgr by shRNA knockdown did not block radiation-induced senescence in vitro; however, both shRNA knockdown, or addition of a specific small-molecule inhibitor of Fgr, TL02-59, abrogated senescent cell induction of profibrotic genes in transwell-separated target cells. Single-cell RNA-seq (scRNAseq) analysis of mouse lungs at day 150 after 20 Gy thoracic irradiation revealed upregulation of Fgr in senescent neutrophils, and macrophages before detection of lung fibrosis. Thus, upregulated Fgr in radiation-induced senescent cells mediates RIPF and is a potential therapeutic target for the prevention of this radiation late effect.
Spectral analysis of climate dynamics with operator-theoretic approaches
Authors: Froyland Gary , Giannakis Dimitrios , Lintner Benjamin R. , Pike Maxwell , Slawinska Joanna 
Published: November 2021

AbstractThe Earth’s climate system is a classical example of a multiscale, multiphysics dynamical system with an extremely large number of active degrees of freedom, exhibiting variability on scales ranging from micrometers and seconds in cloud microphysics, to thousands of kilometers and centuries in ocean dynamics. Yet, despite this dynamical complexity, climate dynamics is known to exhibit coherent modes of variability. A primary example is the El Niño Southern Oscillation (ENSO), the dominant mode of interannual (3–5 yr) variability in the climate system. The objective and robust characterization of this and other important phenomena presents a long-standing challenge in Earth system science, the resolution of which would lead to improved scientific understanding and prediction of climate dynamics, as well as assessment of their impacts on human and natural systems. Here, we show that the spectral theory of dynamical systems, combined with techniques from data science, provides an effective means for extracting coherent modes of climate variability from high-dimensional model and observational data, requiring no frequency prefiltering, but recovering multiple timescales and their interactions. Lifecycle composites of ENSO are shown to improve upon results from conventional indices in terms of dynamical consistency and physical interpretability. In addition, the role of combination modes between ENSO and the annual cycle in ENSO diversity is elucidated.
Mesmerize is a dynamically adaptable user-friendly analysis platform for 2D and 3D calcium imaging data
Authors: Kolar Kushal , Dondorp Daniel , Zwiggelaar Jordi Cornelis , Høyer Jørgen , Chatzigeorgiou Marios 
Published: November 2021

AbstractCalcium imaging is an increasingly valuable technique for understanding neural circuits, neuroethology, and cellular mechanisms. The analysis of calcium imaging data presents challenges in image processing, data organization, analysis, and accessibility. Tools have been created to address these problems independently, however a comprehensive user-friendly package does not exist. Here we present Mesmerize, an efficient, expandable and user-friendly analysis platform, which uses a Findable, Accessible, Interoperable and Reproducible (FAIR) system to encapsulate the entire analysis process, from raw data to interactive visualizations for publication. Mesmerize provides a user-friendly graphical interface to state-of-the-art analysis methods for signal extraction & downstream analysis. We demonstrate the broad scientific scope of Mesmerize’s applications by analyzing neuronal datasets from mouse and a volumetric zebrafish dataset. We also applied contemporary time-series analysis techniques to analyze a novel dataset comprising neuronal, epidermal, and migratory mesenchymal cells of the protochordate Ciona intestinalis.
Cell cycle arrest determines adult neural stem cell ontogeny by an embryonic Notch-nonoscillatory Hey1 module
Authors: Harada Yujin , Yamada Mayumi , Imayoshi Itaru , Kageyama Ryoichiro , Suzuki Yutaka , Kuniya Takaaki , Furutachi Shohei , Kawaguchi Daichi , Gotoh Yukiko 
Published: November 2021

AbstractQuiescent neural stem cells (NSCs) in the adult mouse brain are the source of neurogenesis that regulates innate and adaptive behaviors. Adult NSCs in the subventricular zone are derived from a subpopulation of embryonic neural stem-progenitor cells (NPCs) that is characterized by a slower cell cycle relative to the more abundant rapid cycling NPCs that build the brain. Yet, how slow cell cycle can cause the establishment of adult NSCs remains largely unknown. Here, we demonstrate that Notch and an effector Hey1 form a module that is upregulated by cell cycle arrest in slowly dividing NPCs. In contrast to the oscillatory expression of the Notch effectors Hes1 and Hes5 in fast cycling progenitors, Hey1 displays a non-oscillatory stationary expression pattern and contributes to the long-term maintenance of NSCs. These findings reveal a novel division of labor in Notch effectors where cell cycle rate biases effector selection and cell fate.
Apoptotic stress-induced FGF signalling promotes non-cell autonomous resistance to cell death
Authors: Bock Florian J. , Sedov Egor , Koren Elle , Koessinger Anna L. , Cloix Catherine , Zerbst Désirée , Athineos Dimitris , Anand Jayanthi , Campbell Kirsteen J. , Blyth Karen , Fuchs Yaron , Tait Stephen W. G. 
Published: November 2021

AbstractDamaged or superfluous cells are typically eliminated by apoptosis. Although apoptosis is a cell-autonomous process, apoptotic cells communicate with their environment in different ways. Here we describe a mechanism whereby cells under apoptotic stress can promote survival of neighbouring cells. We find that upon apoptotic stress, cells release the growth factor FGF2, leading to MEK-ERK-dependent transcriptional upregulation of pro-survival BCL-2 proteins in a non-cell autonomous manner. This transient upregulation of pro-survival BCL-2 proteins protects neighbouring cells from apoptosis. Accordingly, we find in certain cancer types a correlation between FGF-signalling, BCL-2 expression and worse prognosis. In vivo, upregulation of MCL-1 occurs in an FGF-dependent manner during skin repair, which regulates healing dynamics. Importantly, either co-treatment with FGF-receptor inhibitors or removal of apoptotic stress restores apoptotic sensitivity to cytotoxic therapy and delays wound healing. These data reveal a pathway by which cells under apoptotic stress can increase resistance to cell death in surrounding cells. Beyond mediating cytotoxic drug resistance, this process also provides a potential link between tissue damage and repair.
Zinc finger protein ZNF384 is an adaptor of Ku to DNA during classical non-homologous end-joining
Authors: Singh Jenny Kaur , Smith Rebecca , Rother Magdalena B. , de Groot Anton J. L. , Wiegant Wouter W. , Vreeken Kees , D’Augustin Ostiane , Kim Robbert Q. , Qian Haibin , Krawczyk Przemek M. , González-Prieto Román , Vertegaal Alfred C. O. , Lamers Meindert , Huet Sébastien , van Attikum Haico 
Published: November 2021

AbstractDNA double-strand breaks (DSBs) are among the most deleterious types of DNA damage as they can lead to mutations and chromosomal rearrangements, which underlie cancer development. Classical non-homologous end-joining (cNHEJ) is the dominant pathway for DSB repair in human cells, involving the DNA-binding proteins XRCC6 (Ku70) and XRCC5 (Ku80). Other DNA-binding proteins such as Zinc Finger (ZnF) domain-containing proteins have also been implicated in DNA repair, but their role in cNHEJ remained elusive. Here we show that ZNF384, a member of the C2H2 family of ZnF proteins, binds DNA ends in vitro and is recruited to DSBs in vivo. ZNF384 recruitment requires the poly(ADP-ribosyl) polymerase 1 (PARP1)-dependent expansion of damaged chromatin, followed by binding of its C2H2 motifs to the exposed DNA. Moreover, ZNF384 interacts with Ku70/Ku80 via its N-terminus, thereby promoting Ku70/Ku80 assembly and the accrual of downstream cNHEJ factors, including APLF and XRCC4/LIG4, for efficient repair at DSBs. Altogether, our data suggest that ZNF384 acts as a ‘Ku-adaptor’ that binds damaged DNA and Ku70/Ku80 to facilitate the build-up of a cNHEJ repairosome, highlighting a role for ZNF384 in DSB repair and genome maintenance.
Precise visuomotor transformations underlying collective behavior in larval zebrafish
Authors: Harpaz Roy , Nguyen Minh Nguyet , Bahl Armin , Engert Florian 
Published: November 2021

AbstractComplex schooling behaviors result from local interactions among individuals. Yet, how sensory signals from neighbors are analyzed in the visuomotor stream of animals is poorly understood. Here, we studied aggregation behavior in larval zebrafish and found that over development larvae transition from overdispersed groups to tight shoals. Using a virtual reality assay, we characterized the algorithms fish use to transform visual inputs from neighbors into movement decisions. We found that young larvae turn away from virtual neighbors by integrating and averaging retina-wide visual occupancy within each eye, and by using a winner-take-all strategy for binocular integration. As fish mature, their responses expand to include attraction to virtual neighbors, which is based on similar algorithms of visual integration. Using model simulations, we show that the observed algorithms accurately predict group structure over development. These findings allow us to make testable predictions regarding the neuronal circuits underlying collective behavior in zebrafish.
A Deep Gravity model for mobility flows generation
Authors: Simini Filippo , Barlacchi Gianni , Luca Massimilano , Pappalardo Luca 
Published: November 2021

AbstractThe movements of individuals within and among cities influence critical aspects of our society, such as well-being, the spreading of epidemics, and the quality of the environment. When information about mobility flows is not available for a particular region of interest, we must rely on mathematical models to generate them. In this work, we propose Deep Gravity, an effective model to generate flow probabilities that exploits many features (e.g., land use, road network, transport, food, health facilities) extracted from voluntary geographic data, and uses deep neural networks to discover non-linear relationships between those features and mobility flows. Our experiments, conducted on mobility flows in England, Italy, and New York State, show that Deep Gravity achieves a significant increase in performance, especially in densely populated regions of interest, with respect to the classic gravity model and models that do not use deep neural networks or geographic data. Deep Gravity has good generalization capability, generating realistic flows also for geographic areas for which there is no data availability for training. Finally, we show how flows generated by Deep Gravity may be explained in terms of the geographic features and highlight crucial differences among the three considered countries interpreting the model’s prediction with explainable AI techniques.
The phosphoinositide coincidence detector Phafin2 promotes macropinocytosis by coordinating actin organisation at forming macropinosomes
Authors: Schink Kay Oliver , Tan Kia Wee , Spangenberg Hélène , Martorana Domenica , Sneeggen Marte , Stévenin Virginie , Enninga Jost , Campsteijn Coen , Raiborg Camilla , Stenmark Harald 
Published: November 2021

AbstractUptake of large volumes of extracellular fluid by actin-dependent macropinocytosis has an important role in infection, immunity and cancer development. A key question is how actin assembly and disassembly are coordinated around macropinosomes to allow them to form and subsequently pass through the dense actin network underlying the plasma membrane to move towards the cell center for maturation. Here we show that the PH and FYVE domain protein Phafin2 is recruited transiently to newly-formed macropinosomes by a mechanism that involves coincidence detection of PtdIns3P and PtdIns4P. Phafin2 also interacts with actin via its PH domain, and recruitment of Phafin2 coincides with actin reorganization around nascent macropinosomes. Moreover, forced relocalization of Phafin2 to the plasma membrane causes rearrangement of the subcortical actin cytoskeleton. Depletion of Phafin2 inhibits macropinosome internalization and maturation and prevents KRAS-transformed cancer cells from utilizing extracellular protein as an amino acid source. We conclude that Phafin2 promotes macropinocytosis by controlling timely delamination of actin from nascent macropinosomes for their navigation through the dense subcortical actin network.
A viral genome packaging ring-ATPase is a flexibly coordinated pentamer
Authors: Dai Li , Singh Digvijay , Lu Suoang , Kottadiel Vishal I. , Vafabakhsh Reza , Mahalingam Marthandan , Chemla Yann R. , Ha Taekjip , Rao Venigalla B. 
Published: November 2021

AbstractMulti-subunit ring-ATPases carry out a myriad of biological functions, including genome packaging in viruses. Though the basic structures and functions of these motors have been well-established, the mechanisms of ATPase firing and motor coordination are poorly understood. Here, using single-molecule fluorescence, we determine that the active bacteriophage T4 DNA packaging motor consists of five subunits of gp17. By systematically doping motors with an ATPase-defective subunit and selecting single motors containing a precise number of active or inactive subunits, we find that the packaging motor can tolerate an inactive subunit. However, motors containing one or more inactive subunits exhibit fewer DNA engagements, a higher failure rate in encapsidation, reduced packaging velocity, and increased pausing. These findings suggest a DNA packaging model in which the motor, by re-adjusting its grip on DNA, can skip an inactive subunit and resume DNA translocation, suggesting that strict coordination amongst motor subunits of packaging motors is not crucial for function.
SARS-CoV-2 B.1.1.7 (alpha) and B.1.351 (beta) variants induce pathogenic patterns in K18-hACE2 transgenic mice distinct from early strains
Authors: Radvak Peter , Kwon Hyung-Joon , Kosikova Martina , Ortega-Rodriguez Uriel , Xiang Ruoxuan , Phue Je-Nie , Shen Rong-Fong , Rozzelle James , Kapoor Neeraj , Rabara Taylor , Fairman Jeff , Xie Hang 
Published: November 2021

AbstractSARS-CoV-2 variants of concern (VOC) B.1.1.7 (alpha) and B.1.351 (beta) show increased transmissibility and enhanced antibody neutralization resistance. Here we demonstrate in K18-hACE2 transgenic mice that B.1.1.7 and B.1.351 are 100-fold more lethal than the original SARS-CoV-2 bearing 614D. B.1.1.7 and B.1.351 cause more severe organ lesions in K18-hACE2 mice than early SARS-CoV-2 strains bearing 614D or 614G, with B.1.1.7 and B.1.351 infection resulting in distinct tissue-specific cytokine signatures, significant D-dimer depositions in vital organs and less pulmonary hypoxia signaling before death. However, K18-hACE2 mice with prior infection of early SARS-CoV-2 strains or intramuscular immunization of viral spike or receptor binding domain are resistant to the lethal reinfection of B.1.1.7 or B.1.351, despite having reduced neutralization titers against these VOC than early strains. Our results thus distinguish pathogenic patterns in K18-hACE2 mice caused by B.1.1.7 and B.1.351 infection from those induced by early SARS-CoV-2 strains, and help inform potential medical interventions for combating COVID-19.
Selective cobalt and nickel electrodeposition for lithium-ion battery recycling through integrated electrolyte and interface control
Authors: Kim Kwiyong , Raymond Darien , Candeago Riccardo , Su Xiao 
Published: November 2021

AbstractMolecularly-selective metal separations are key to sustainable recycling of Li-ion battery electrodes. However, metals with close reduction potentials present a fundamental challenge for selective electrodeposition, especially for critical elements such as cobalt and nickel. Here, we demonstrate the synergistic combination of electrolyte control and interfacial design to achieve molecular selectivity for cobalt and nickel during potential-dependent electrodeposition. Concentrated chloride allows for the speciation control via distinct formation of anionic cobalt chloride complex (CoCl42-), while maintaining nickel in the cationic form ([Ni(H2O)5Cl]+). Furthermore, functionalizing electrodes with a positively charged polyelectrolyte (i.e., poly(diallyldimethylammonium) chloride) changes the mobility of CoCl42- by electrostatic stabilization, which tunes cobalt selectivity depending on the polyelectrolyte loading. This strategy is applied for the multicomponent metal recovery from commercially-sourced lithium nickel manganese cobalt oxide electrodes. We report a final purity of 96.4 ± 3.1% and 94.1 ± 2.3% for cobalt and nickel, respectively. Based on a technoeconomic analysis, we identify the limiting costs arising from the background electrolyte, and provide a promising outlook of selective electrodeposition as an efficient separation approach for battery recycling.