bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gene expression and target-site mutations are associated with resistance to ALS inhibitors in annual sedge (Cyperus compressus) biotypes from Georgia
Authors: Yu Jialin , McCullough Patrick E. , McElroy J. Scott , Jespersen David , Shilling Donn G. 
Published: August 2020

AbstractAnnual sedge (Cyperus compressus L.) populations with resistance to halosulfuron were identified in turfgrass at two new locations in Georgia. Research was conducted to evaluate (1) resistance levels to two acetolactate synthase (ALS) inhibitors, (2) ALS enzyme susceptibility, (3) genetic differences associated with resistance, and (4) differential levels of ALS gene expression in these biotypes. In dose–response experiments, the biotypes were >160 times resistant to halosulfuron but only 12 times more resistant to imazaquin compared with a susceptible biotype. In vitro enzyme assays indicated that resistant (R) biotypes required 6.1-fold greater concentrations of imazaquin to reduce ALS activity 50% compared with the susceptible (S) biotype. Both R biotypes had a similar Pro-197-Ser amino acid substitution in the ALS gene that confers resistance to sulfonylureas. Compared with the S biotype, R biotypes had 4.4 times higher ALS gene expression than the S biotype. No differences in gene copy number were found between any biotypes for the ALS gene. Overall, ALS-resistant C. compressus selected by halosulfuron use in turfgrass may be exhibiting partial susceptibility to imazaquin but complete resistance to sulfonylureas. Differential levels of susceptibility to ALS inhibitors for these biotypes are associated with the Pro-197-Ser substitution and enhanced expression of the ALS gene.
The problem of Orobanche spp. and Phelipanche spp. and their management in Iran
Authors: Nosratti Iraj , Mobli Ahmadreza , Mohammadi Gholamreza , Yousefi Ali Reza , Sabeti Peyman , Chauhan Bhagirath S. 
Published: August 2020

AbstractBroomrape species (Orobanche spp. and Phelipanche spp.) pose a tremendous threat to economically important crops in Iran; however, there is little information on the country’s major broomrape species, their distribution and host ranges, and the subsequent crop losses they cause. The literature from Iran describes Egyptian broomrape (Orobanche aegyptiaca Pers.), hemp broomrape (Orobanche ramosa L.), Phelipanche nana (Reut.) Beck, and Orobanche cumana Wallr. as the major species of broomrape infesting agricultural fields. Solanaceae crops are among the most susceptible crops to infestation by broomrape in the country, and farmers are either shifting production to crops with lesser value or abandoning crop production entirely. Among infested crops, tomato (Solanum lycopersicum L.) is the most susceptible and widely infested, resulting in annual crop yield reductions of up to 40%. Chick pea (Cicer arietinum L.) and canola (Brassica napus L.) are also highly susceptible to broomrape infestation. Current control methods (physical, agronomical, biological, and chemical) have not proven to be effective or economic. The microscopic size of broomrape seeds and the presence of a wide range of host plants (weeds and crops) have promoted the spread of broomrape to new areas of Iran. Hence, the familiarization of farmers with the biology of broomrape would be highly effective in finding suitable control measures and in preventing its further distribution.
What Configuration of the Atmospheric Circulation Drives Extreme Net and Total Moisture Transport Into the Arctic
Authors: Papritz L. , Dunn‐Sigouin E. 
Published: August 2020

AbstractPrevious work highlighted different configurations of the atmospheric circulation causing moisture transport into the Arctic and contributing to surface warming. Here, we clarify the configurations leading to extreme wintertime events of zonal‐mean net and total (sum of absolute values of poleward and equatorward) moisture transports by comparing feature‐based weather system diagnostics with zonal‐wavenumber decomposition of moisture transport in reanalysis data. Results show that extreme Arctic moisture transport events are attributable to individual weather systems, where cyclones favor net transport and blocks favor total transport. Zonal‐wavenumber decomposition reveals that net moisture transport is dominated by planetary scales (zonal‐wavenumbers k ≤ 3). Comparison between the two diagnostics suggests that blocks account for planetary scale contributions to net transport by interacting with cyclones rather than driving the transport themselves. Finally, net and total moisture transport events result in Arctic surface warming via different underlying processes related to cyclones and blocks, respectively.
Slab Rollback Orogeny Model: A Test of Concept
Authors: Dal Zilio Luca , Kissling Edi , Gerya Taras , van Dinther Ylona 
Published: August 2020

AbstractBuoyancy forces associated with subducting lithosphere control the dynamics of convergent margins. In the postcollisional stage these forces are significantly reduced, yet mountain building and seismicity are ongoing, albeit at lower rates. We leverage advances of a newly developed seismo‐thermo‐mechanical modeling approach to simulate tectonic and seismicity processes in a self‐driven subduction and continental collision setting. We demonstrate that the rearrangement of forces due to slab breakoff, in the postcollisional stage, causes bending and rollback of the residual slab, suction forces, and mantle traction at the base of the upper plate, while stress coupling transfers to the shallow crust. Our results provide an explanation for the postcollisional evolution of the Central Alps, where the so‐called Slab Rollback Orogeny model explains the slow yet persistent upper plate advance, the height of the mountain range, and a seismicity pattern consistent with the different tectonic regimes throughout the orogen.
Spatial Footprints of Storm Surges Along the Global Coastlines
Authors: Enríquez Alejandra R. , Wahl Thomas , Marcos Marta , Haigh Ivan D. 
Published: August 2020

AbstractWe perform the first global analysis of the spatial footprints of storm surges, using observed and simulated storm surge data. Three different techniques are applied to quantify the spatial footprints: clustering analysis, percentage of co‐occurrence, and joint probability analysis. The capability of the simulated data to represent the observed storm surge footprints is demonstrated. Results lead to the identification of coastline stretches prone to be impacted simultaneously by the same storm surge events. The spatial footprint sizes differ around the globe, partially conditioned by the geography of the coastline, that is, more irregular coastlines consist of a larger number of different storm surge clusters with varying footprint sizes. For the northwestern Atlantic, spatial footprints of storm surges vary when specifically accounting for tropical cyclones, using storm track information in the storm surge simulations. Our results provide important new insights into the spatial footprints of storm surges at the global scale and will help to facilitate improvements in how coastal flood risk is identified, assessed, and managed, by taking these spatial features into account.
Nutrient Uptake in the Supraglacial Stream Network of an Antarctic Glacier
Authors: Bergstrom A. , Gooseff M. N. , Singley J. G. , Cohen M. J. , Welch K. A. 
Published: August 2020

AbstractIn polar regions, where many glaciers are cold based (frozen to their beds), biological communities on the glacier surface can modulate and transform nutrients, controlling downstream delivery. However, it remains unclear whether supraglacial streams are nutrient sinks or sources and the rates of nutrient processing. In order to test this, we conducted tracer injections in three supraglacial streams (62 to 123 m long) on Canada Glacier in the Taylor Valley, of the McMurdo Dry Valleys, Antarctica. We conducted a series of additions including nitrate (N), N + phosphate (P), N + P + glucose (C), and N + C. In two reaches, N‐only additions resulted in N uptake. The third reach showed net N release during the N‐only addition, but high N uptake in the N + P addition, indicating P‐limitation or N + P colimitation. Coinjecting C did not increase N‐uptake. Additionally, in these systems at low N concentrations the streams can be a net source of nitrogen. We confirmed these findings using laboratory‐based nutrient incubation experiments on sediment collected from stream channels on Canada Glacier and two other glaciers in the Taylor Valley. Together, these results suggest there is active biological processing of nutrients occurring in these supraglacial streams despite low sediment cover, high flow velocities, and cold temperatures, modifying the input signals to proglacial streams. As glaciers worldwide undergo rapid change, these findings further our understanding of how melt generated on glacier surfaces set the initial nutrient signature for subglacial and downstream environments.
A Machine‐Learning‐Based Model for Water Quality in Coastal Waters, Taking Dissolved Oxygen and Hypoxia in Chesapeake Bay as an Example
Authors: Yu Xin , Shen Jian , Du Jiabi 
Published: August 2020

AbstractHypoxia is a big concern in coastal waters as it affects ecosystem health, fishery yield, and marine water resources. Accurately modeling coastal hypoxia is still very challenging even with the most advanced numerical models. A data‐driven model for coastal water quality is proposed in this study and is applied to predict the temporal‐spatial variations of dissolved oxygen (DO) and hypoxic condition in Chesapeake Bay, the largest estuary in the United States with mean summer hypoxic zone extending about 150 km along its main axis. The proposed model has three major components including empirical orthogonal functions analysis, automatic selection of forcing transformation, and neural network training. It first uses empirical orthogonal functions to extract the principal components, then applies neural network to train models for the temporal variations of principal components, and finally reconstructs the three‐dimensional temporal‐spatial variations of the DO. Using the first 75% of the 32‐year (1985–2016) data set for training, the model shows good performance for the testing period (the remaining 25% data set). Selection of forcings for the first mode points to the dominant role of streamflow in controlling interannual variability of bay‐wide DO condition. Different from previous empirical models, the approach is able to simulate three‐dimensional variations of water quality variables and it does not use in situ measured water quality variables but only external forcings as model inputs. Even though the approach is used for the hypoxia problem in Chesapeake Bay, the methodology is readily applicable to other coastal systems that are systematically monitored.
Bowel inflammation in cancer patients: the microbiome, antibiotics and interleukin-9
Authors: Halama Niels 
Published: August 2020

SummaryMicrobiome composition can impact disease courses and also immunotherapy outcomes in solid tumours. It is still unclear how the microbiome might impact treatments in oncology, but also how modulation via antibiotics might interfere. Elegant work now identified interleukin-9 and dysbiosis as relevant factors, providing some answers for these questions.
LncRNA Hoxaas3 promotes lung fibroblast activation and fibrosis by targeting miR-450b-5p to regulate Runx1
Authors: Lin Shuang , Zhang Rui , Xu Lei , Ma Rui , Xu Liming , Zhu Linghua , Hu Jian , An Xiaoxia 
Published: August 2020

AbstractLong noncoding RNAs (lncRNAs) participate in organ fibrosis and various pulmonary diseases, but its role in idiopathic pulmonary fibrosis (IPF) is not fully understood. In this study, we found lncRNA Hoxaas3 (Hoxaas3) was up-regulated in the mice model of BLM-induced PF and TGF-β1-induced fibrogenesis in lung fibroblasts (LF). Overexpression of Hoxaas3 promoted fibrogenesis, whereas Hoxaas3 inhibition attenuated lung fibrosis both in vitro and in vivo, through regulation of miR-450b-5p. Furthermore, miR-450b-5p inhibition stimulated fibrogenesis by regulating runt-related transcription factor 1 (Runx1), whereas up-regulation of miR-450b-5p alleviated fibrogenesis in LF. Mechanistically, our study showed that Hoxaas3 regulated lung fibroblast activation and fibrogenesis by acting as a competing endogenous RNA for miR-450b-5p: Hoxaas3 decreased the expression of miR-450b-5p to stimulate level and activity of Runx1 and induced fibrotic LF, whereas Runx1 inhibition alleviated the pro-fibrotic effect of Hoxaas3. In addition, Hoxaas3 was regulated by TGF-β1/Smad4 pathway as its transcriptional target. In conclusion, our study showed the role and mechanism of the TGF-β1/Smad4- Hoxaas3–miR-450b-5p–Runx1 axis for a better understanding of PF, demonstrated Hoxaas3 maybe a new diagnostic biomarker or potential therapeutic target for IPF.
ATAC-seq footprinting unravels kinetics of transcription factor binding during zygotic genome activation
Authors: Bentsen Mette , Goymann Philipp , Schultheis Hendrik , Klee Kathrin , Petrova Anastasiia , Wiegandt René , Fust Annika , Preussner Jens , Kuenne Carsten , Braun Thomas , Kim Johnny , Looso Mario 
Published: August 2020

AbstractWhile footprinting analysis of ATAC-seq data can theoretically enable investigation of transcription factor (TF) binding, the lack of a computational tool able to conduct different levels of footprinting analysis has so-far hindered the widespread application of this method. Here we present TOBIAS, a comprehensive, accurate, and fast footprinting framework enabling genome-wide investigation of TF binding dynamics for hundreds of TFs simultaneously. We validate TOBIAS using paired ATAC-seq and ChIP-seq data, and find that TOBIAS outperforms existing methods for bias correction and footprinting. As a proof-of-concept, we illustrate how TOBIAS can unveil complex TF dynamics during zygotic genome activation in both humans and mice, and propose how zygotic Dux activates cascades of TFs, binds to repeat elements and induces expression of novel genetic elements.
Fibroblast-enriched endoplasmic reticulum protein TXNDC5 promotes pulmonary fibrosis by augmenting TGFβ signaling through TGFBR1 stabilization
Authors: Lee Tzu-Han , Yeh Chih-Fan , Lee Ying-Tung , Shih Ying-Chun , Chen Yen-Ting , Hung Chen-Ting , You Ming-Yi , Wu Pei-Chen , Shentu Tzu-Pin , Huang Ru-Ting , Lin Yu-Shan , Wu Yueh-Feng , Lin Sung-Jan , Lu Frank-Leigh , Tsao Po-Nien , Lin Tzu-Hung , Lo Shen-Chuan , Tseng Yi-Shuan , Wu Wan-Lin , Chen Chiung-Nien , Wu Chau-Chung , Lin Shuei-Liong , Sperling Anne I. , Guzy Robert D. , Fang Yun , Yang Kai-Chien 
Published: August 2020

AbstractPulmonary fibrosis (PF) is a major public health problem with limited therapeutic options. There is a clear need to identify novel mediators of PF to develop effective therapeutics. Here we show that an ER protein disulfide isomerase, thioredoxin domain containing 5 (TXNDC5), is highly upregulated in the lung tissues from both patients with idiopathic pulmonary fibrosis and a mouse model of bleomycin (BLM)-induced PF. Global deletion of Txndc5 markedly reduces the extent of PF and preserves lung function in mice following BLM treatment. Mechanistic investigations demonstrate that TXNDC5 promotes fibrogenesis by enhancing TGFβ1 signaling through direct binding with and stabilization of TGFBR1 in lung fibroblasts. Moreover, TGFβ1 stimulation is shown to upregulate TXNDC5 via ER stress/ATF6-dependent transcriptional control in lung fibroblasts. Inducing fibroblast-specific deletion of Txndc5 mitigates the progression of BLM-induced PF and lung function deterioration. Targeting TXNDC5, therefore, could be a novel therapeutic approach against PF.
Structural mechanism for replication origin binding and remodeling by a metazoan origin recognition complex and its co-loader Cdc6
Authors: Schmidt Jan Marten , Bleichert Franziska 
Published: August 2020

AbstractEukaryotic DNA replication initiation relies on the origin recognition complex (ORC), a DNA-binding ATPase that loads the Mcm2–7 replicative helicase onto replication origins. Here, we report cryo-electron microscopy (cryo-EM) structures of DNA-bound Drosophila ORC with and without the co-loader Cdc6. These structures reveal that Orc1 and Orc4 constitute the primary DNA binding site in the ORC ring and cooperate with the winged-helix domains to stabilize DNA bending. A loop region near the catalytic Walker B motif of Orc1 directly contacts DNA, allosterically coupling DNA binding to ORC’s ATPase site. Correlating structural and biochemical data show that DNA sequence modulates DNA binding and remodeling by ORC, and that DNA bending promotes Mcm2–7 loading in vitro. Together, these findings explain the distinct DNA sequence-dependencies of metazoan and S. cerevisiae initiators in origin recognition and support a model in which DNA geometry and bendability contribute to Mcm2–7 loading site selection in metazoans.
Directed manipulation of membrane proteins by fluorescent magnetic nanoparticles
Authors: Li Jia Hui , Santos-Otte Paula , Au Braedyn , Rentsch Jakob , Block Stephan , Ewers Helge 
Published: August 2020

AbstractThe plasma membrane is the interface through which cells interact with their environment. Membrane proteins are embedded in the lipid bilayer of the plasma membrane and their function in this context is often linked to their specific location and dynamics within the membrane. However, few methods are available to manipulate membrane protein location at the single-molecule level. Here, we use fluorescent magnetic nanoparticles (FMNPs) to track membrane molecules and to control their movement. FMNPs allow single-particle tracking (SPT) at 10 nm and 5 ms spatiotemporal resolution, and using a magnetic needle, we pull membrane components laterally with femtonewton-range forces. In this way, we drag membrane proteins over the surface of living cells. Doing so, we detect barriers which we could localize to the submembrane actin cytoskeleton by super-resolution microscopy. We present here a versatile approach to probe membrane processes in live cells via the magnetic control of membrane protein motion.
Reconciling qualitative, abstract, and scalable modeling of biological networks
Authors: Paulevé Loïc , Kolčák Juri , Chatain Thomas , Haar Stefan 
Published: August 2020

AbstractPredicting biological systems’ behaviors requires taking into account many molecular and genetic elements for which limited information is available past a global knowledge of their pairwise interactions. Logical modeling, notably with Boolean Networks (BNs), is a well-established approach that enables reasoning on the qualitative dynamics of networks. Several dynamical interpretations of BNs have been proposed. The synchronous and (fully) asynchronous ones are the most prominent, where the value of either all or only one component can change at each step. Here we prove that, besides being costly to analyze, these usual interpretations can preclude the prediction of certain behaviors observed in quantitative systems. We introduce an execution paradigm, the Most Permissive Boolean Networks (MPBNs), which offers the formal guarantee not to miss any behavior achievable by a quantitative model following the same logic. Moreover, MPBNs significantly reduce the complexity of dynamical analysis, enabling to model genome-scale networks.
Time-resolved photoemission of infinitely periodic atomic arrangements: correlation-dressed excited states of solids
Authors: Kim Youngjae , Lee JaeDong 
Published: August 2020

AbstractA theory of the time-resolved photoemission spectroscopy (TRPES) is developed, which enables to explore the real-time electron dynamics of infinitely periodic crystalline solids. In the strongly correlated electron systems NiO and CuO, the early-stage dynamics of the valence band edge are found to be sharply contrasted between those in the spectra of TRPES. This provides a new dynamical insight to the Zaanen–Sawatzky–Allen (ZSA) classification scheme of correlated insulators and makes us assert that NiO dynamically behaves like the Mott–Hubbard insulator (MHI) and CuO like the charge transfer insulator (CTI). In the two-dimensional carbon layer graphene, the real-time electron dynamics of quantum-phase-dressed excited states, i.e., due to the Berry phase and the pseudospin correlation, are investigated in an unprecedented way through the time-resolved angle-resolved photoemission spectroscopy (TR-ARPES). In particular, the dephasing dynamics of optically doped electrons and holes in the massless Dirac band, accompanying a field-induced gliding of the Dirac cone, are discovered.
Machine-learned metrics for predicting the likelihood of success in materials discovery
Authors: Kim Yoolhee , Kim Edward , Antono Erin , Meredig Bryce , Ling Julia 
Published: August 2020

AbstractMaterials discovery is often compared to the challenge of finding a needle in a haystack. While much work has focused on accurately predicting the properties of candidate materials with machine learning (ML), which amounts to evaluating whether a given candidate is a piece of straw or a needle, less attention has been paid to a critical question: are we searching in the right haystack? We refer to the haystack as the design space for a particular materials discovery problem (i.e., the set of possible candidate materials to synthesize), and thus frame this question as one of design space selection. In this paper, we introduce two metrics, the predicted fraction of improved candidates (PFIC), and the cumulative maximum likelihood of improvement (CMLI), which we demonstrate can identify discovery-rich and discovery-poor design spaces, respectively. A combined classification system, composed of the CMLI and PFIC metrics, is then used to identify optimal design spaces with high precision, and thus show the potential to significantly accelerate ML-driven materials discovery.
Objective function estimation for solving optimization problems in gate-model quantum computers
Authors: Gyongyosi Laszlo 
Published: August 2020

AbstractQuantum computers provide a valuable resource to solve computational problems. The maximization of the objective function of a computational problem is a crucial problem in gate-model quantum computers. The objective function estimation is a high-cost procedure that requires several rounds of quantum computations and measurements. Here, we define a method for objective function estimation of arbitrary computational problems in gate-model quantum computers. The proposed solution significantly reduces the costs of the objective function estimation and provides an optimized estimate of the state of the quantum computer for solving optimization problems.