bluuebunny/crossref_metadata_2025_split huggingface dataset:
Calibration of the HP3 Radiometer on InSight
Authors: Mueller N. T. , Knollenberg J. , Grott M. , Kopp E. , Walter I. , Krause C. , Hudson T. , Spohn T. , Smrekar S. 
Published: March 2020

AbstractThe Heatflow and Physical Properties Package (HP3) radiometer is currently operating on Mars, observing two spots approximately 1 and 3 m north‐north‐west of the InSight lander. The instrument has primary sensors that are sensitive in the range of 8 to 14 μm and two more sensors with more narrow spectral ranges per field of view. The radiometer underwent radiometric and geometric calibration at DLR—Berlin; and on Mars radiometric self‐calibration is performed regularly. The self‐calibration confirms that one of the two primary sensors has been stable since the ground calibration, but environmental parameters that are likely associated with the thermal contact of sensor and instrument main body may have slightly changed. The other primary sensor has increased in sensitivity for an unknown reason but is still within expectation from the sensor design. The uncertainty of the two primary sensors is approximately 3 K at night, with somewhat larger errors in the late afternoon. This estimate includes the effect of sensitivity changes that would be too small to be reliably detected by the self‐calibration.
Is the River a Chemostat?: Scale Versus Land Use Controls on Nitrate Concentration‐Discharge Dynamics in the Upper Mississippi River Basin
Authors: Marinos Richard E. , Van Meter Kimberly J. , Basu Nandita B. 
Published: March 2020

AbstractThe Upper Mississippi River Basin is the largest source of reactive nitrogen (N) to the Gulf of Mexico. Concentration‐discharge (C‐Q) relationships offer a means to understand both the terrestrial sources that generate this reactive N and the in‐stream processes that transform it. Progress has been made on identifying land use controls on C‐Q dynamics. However, the impact of basin size and river network structure on C‐Q relationships is not well characterized. Here, we show, using high‐resolution nitrate concentration data, that tile drainage is a dominant control on C‐Q dynamics, with increasing drainage density contributing to more chemostatic C‐Q behavior. We further find that concentration variability increases, relative to discharge variability, with increasing basin size across six orders of magnitude, and this pattern is attributed to different spatial correlation structures for C and Q. Our results show how land use and river network structure jointly control riverine N export.
Plant Water Uptake Thresholds Inferred From Satellite Soil Moisture
Authors: Bassiouni Maoya , Good Stephen P. , Still Christopher J. , Higgins Chad W. 
Published: March 2020

AbstractEmpirical functions are widely used in hydrological, agricultural, and Earth system models to parameterize plant water uptake. We infer soil water potentials at which uptake is downregulated from its well‐watered rate and at which uptake ceases, in biomes with <60% woody vegetation at 36‐km grid resolution. We estimate thresholds through Bayesian inference using a stochastic soil water balance framework to construct theoretical soil moisture probability distributions consistent with empirical distributions derived from satellite soil moisture observations. The global median Nash–Sutcliffe efficiency between empirical soil moisture distributions and theoretical distributions using reference constants, inferred median parameters per biome, and spatially variable inferred parameters are 0.38, 0.59, and 0.8, respectively. Spatially variable thresholds capture location‐specific vegetation and climate characteristics and can be connected to biome‐level water uptake strategies. Results demonstrate that satellite soil moisture probability distributions encode information, valuable to understanding biome‐level ecohydrological adaptation and resistance to climate variability.
Nonenzymatic function of Aldolase A downregulates miR-145 to promote the Oct4/DUSP4/TRAF4 axis and the acquisition of lung cancer stemness
Authors: Chang Yu-Chan , Yang Yi-Fang , Chiou Jean , Tsai Hsing-Fang , Fang Chih-Yeu , Yang Chih-Jen , Chen Chi-Long , Hsiao Michael 
Published: March 2020

AbstractDrug resistance remains a serious issue of clinical importance and is a consequence of cancer stemness. In this study, we showed that the level of Aldolase A (ALDOA) expression is significantly associated with the IC50 value of chemotherapy drugs in lung cancer. Our data revealed that ALDOA overexpression resulted in a significant increase of lung tumor spheres. The use of ingenuity pathway analysis (IPA) resulted in the identification of POU5F1 (Oct4) as the leading transcription factor of ALDOA. We observed high expression of ALDOA, Oct4 and stemness markers in collected spheroid cells. DUSP4 and TRAF4 were confirmed as major downstream targets of the ALDOA-Oct4 axis. Knockdown of these molecules significantly decreased the stemness ability of cells. In addition, we investigated whether miR-145 targets the 3′-UTR of Oct4 and is regulated by ALDOA due to the involvement of ALDOA in glycolysis and metabolic reprogramming. Furthermore, we constructed several mutant forms of ALDOA that disrupted its enzymatic activity and showed that they still induced significant in vitro sphere formation and in vivo tumorigenicity. These results demonstrated that ALDOA-mediated spheroid formation is independent of its enzymatic activity. In the clinical component, we also showed that the combination of ALDOA and TRAF4 or DUSP4 is positively correlated with poor overall survival in a xenograft model and cancer patients through immunohistochemical analyses. The results of our study revealed novel functional roles of ALDOA in inducing cancer stemness via the inhibition of miR-145 expression and the activation of Oct4 transcription. These findings offer new therapeutic strategies for modulation of lung cancer stemness to enhance chemotherapeutic responses in lung cancer patients.
Cx43 channels and signaling via IP3/Ca2+, ATP, and ROS/NO propagate radiation-induced DNA damage to non-irradiated brain microvascular endothelial cells
Authors: Hoorelbeke Delphine , Decrock Elke , De Smet Maarten , De Bock Marijke , Descamps Benedicte , Van Haver Valérie , Delvaeye Tinneke , Krysko Dmitri V. , Vanhove Christian , Bultynck Geert , Leybaert Luc 
Published: March 2020

AbstractRadiotherapeutic treatment consists of targeted application of radiation beams to a tumor but exposure of surrounding healthy tissue is inevitable. In the brain, ionizing radiation induces breakdown of the blood–brain barrier by effects on brain microvascular endothelial cells. Damage from directly irradiated cells can be transferred to surrounding non-exposed bystander cells, known as the radiation-induced bystander effect. We investigated involvement of connexin channels and paracrine signaling in radiation-induced bystander DNA damage in brain microvascular endothelial cells exposed to focused X-rays. Irradiation caused DNA damage in the directly exposed area, which propagated over several millimeters in the bystander area. DNA damage was significantly reduced by the connexin channel-targeting peptide Gap26 and the Cx43 hemichannel blocker TAT-Gap19. ATP release, dye uptake, and patch clamp experiments showed that hemichannels opened within 5 min post irradiation in both irradiated and bystander areas. Bystander signaling involved cellular Ca2+ dynamics and IP3, ATP, ROS, and NO signaling, with Ca2+, IP3, and ROS as crucial propagators of DNA damage. We conclude that bystander effects are communicated by a concerted cascade involving connexin channels, and IP3/Ca2+, ATP, ROS, and NO as major contributors of regenerative signal expansion.
Conversionless efficient and broadband laser light diffusers for high brightness illumination applications
Authors: Schütt Fabian , Zapf Maximilian , Signetti Stefano , Strobel Julian , Krüger Helge , Röder Robert , Carstensen Jürgen , Wolff Niklas , Marx Janik , Carey Tian , Schweichel Marleen , Terasa Maik-Ivo , Siebert Leonard , Hong Hyo-Ki , Kaps Sören , Fiedler Bodo , Mishra Yogendra Kumar , Lee Zonghoon , Pugno Nicola M. , Kienle Lorenz , Ferrari Andrea C. , Torrisi Felice , Ronning Carsten , Adelung Rainer 
Published: March 2020

AbstractLaser diodes are efficient light sources. However, state-of-the-art laser diode-based lighting systems rely on light-converting inorganic phosphor materials, which strongly limit the efficiency and lifetime, as well as achievable light output due to energy losses, saturation, thermal degradation, and low irradiance levels. Here, we demonstrate a macroscopically expanded, three-dimensional diffuser composed of interconnected hollow hexagonal boron nitride microtubes with nanoscopic wall-thickness, acting as an artificial solid fog, capable of withstanding ~10 times the irradiance level of remote phosphors. In contrast to phosphors, no light conversion is required as the diffuser relies solely on strong broadband (full visible range) lossless multiple light scattering events, enabled by a highly porous (>99.99%) non-absorbing nanoarchitecture, resulting in efficiencies of ~98%. This can unleash the potential of lasers for high-brightness lighting applications, such as automotive headlights, projection technology or lighting for large spaces.
GenomeScope 2.0 and Smudgeplot for reference-free profiling of polyploid genomes
Authors: Ranallo-Benavidez T. Rhyker , Jaron Kamil S. , Schatz Michael C. 
Published: March 2020

AbstractAn important assessment prior to genome assembly and related analyses is genome profiling, where the k-mer frequencies within raw sequencing reads are analyzed to estimate major genome characteristics such as size, heterozygosity, and repetitiveness. Here we introduce GenomeScope 2.0 (https://github.com/tbenavi1/genomescope2.0), which applies combinatorial theory to establish a detailed mathematical model of how k-mer frequencies are distributed in heterozygous and polyploid genomes. We describe and evaluate a practical implementation of the polyploid-aware mixture model that quickly and accurately infers genome properties across thousands of simulated and several real datasets spanning a broad range of complexity. We also present a method called Smudgeplot (https://github.com/KamilSJaron/smudgeplot) to visualize and estimate the ploidy and genome structure of a genome by analyzing heterozygous k-mer pairs. We successfully apply the approach to systems of known variable ploidy levels in the Meloidogyne genus and the extreme case of octoploid Fragaria × ananassa.
Environmental remodeling of human gut microbiota and antibiotic resistome in livestock farms
Authors: Sun Jian , Liao Xiao-Ping , D’Souza Alaric W. , Boolchandani Manish , Li Sheng-Hui , Cheng Ke , Luis Martínez José , Li Liang , Feng You-Jun , Fang Liang-Xing , Huang Ting , Xia Jing , Yu Yang , Zhou Yu-Feng , Sun Yong-Xue , Deng Xian-Bo , Zeng Zhen-Ling , Jiang Hong-Xia , Fang Bing-Hu , Tang You-Zhi , Lian Xin-Lei , Zhang Rong-Min , Fang Zhi-Wei , Yan Qiu-Long , Dantas Gautam , Liu Ya-Hong 
Published: March 2020

AbstractAnthropogenic environments have been implicated in enrichment and exchange of antibiotic resistance genes and bacteria. Here we study the impact of confined and controlled swine farm environments on temporal changes in the gut microbiome and resistome of veterinary students with occupational exposure for 3 months. By analyzing 16S rRNA and whole metagenome shotgun sequencing data in tandem with culture-based methods, we show that farm exposure shapes the gut microbiome of students, resulting in enrichment of potentially pathogenic taxa and antimicrobial resistance genes. Comparison of students’ gut microbiomes and resistomes to farm workers’ and environmental samples revealed extensive sharing of resistance genes and bacteria following exposure and after three months of their visit. Notably, antibiotic resistance genes were found in similar genetic contexts in student samples and farm environmental samples. Dynamic Bayesian network modeling predicted that the observed changes partially reverse over a 4-6 month period. Our results indicate that acute changes in a human’s living environment can persistently shape their gut microbiota and antibiotic resistome.
Latent periodic process inference from single-cell RNA-seq data
Authors: Liang Shaoheng , Wang Fang , Han Jincheng , Chen Ken 
Published: March 2020

AbstractThe development of a phenotype in a multicellular organism often involves multiple, simultaneously occurring biological processes. Advances in single-cell RNA-sequencing make it possible to infer latent developmental processes from the transcriptomic profiles of cells at various developmental stages. Accurate characterization is challenging however, particularly for periodic processes such as cell cycle. To address this, we develop Cyclum, an autoencoder approach identifying circular trajectories in the gene expression space. Cyclum substantially improves the accuracy and robustness of cell-cycle characterization beyond existing approaches. Applying Cyclum to removing cell-cycle effects substantially improves delineations of cell subpopulations, which is useful for establishing various cell atlases and studying tumor heterogeneity.
FHIR Genomics: enabling standardization for precision medicine use cases
Authors: Alterovitz Gil , Heale Bret , Jones James , Kreda David , Lin Fan , Liu Lei , Liu Xin , Mandl Kenneth D. , Poloway David W. , Ramoni Rachel , Wagner Alex , Warner Jeremy L. 
Published: March 2020

AbstractThe development of Fast Healthcare Interoperability Resources (FHIR) Genomics, a feasible and efficient method for exchanging complex clinical genomic data and interpretations, is described. FHIR Genomics is a subset of the emerging Health Level 7 FHIR standard and targets data from increasingly available technologies such as next-generation sequencing. Much care and integration of feedback have been taken to ease implementation, facilitate wide-scale interoperability, and enable modern app development toward a complete precision medicine standard. A new use case, the integration of the Variant Interpretation for Cancer Consortium (VICC) “meta-knowledgebase” into a third-party application, is described.
The retrospective analysis of Antarctic tracking data project
Authors: Ropert-Coudert Yan , Van de Putte Anton P. , Reisinger Ryan R. , Bornemann Horst , Charrassin Jean-Benoît , Costa Daniel P. , Danis Bruno , Hückstädt Luis A. , Jonsen Ian D. , Lea Mary-Anne , Thompson David , Torres Leigh G. , Trathan Philip N. , Wotherspoon Simon , Ainley David G. , Alderman Rachael , Andrews-Goff Virginia , Arthur Ben , Ballard Grant , Bengtson John , Bester Marthán N. , Blix Arnoldus Schytte , Boehme Lars , Bost Charles-André , Boveng Peter , Cleeland Jaimie , Constantine Rochelle , Crawford Robert J. M. , Dalla Rosa Luciano , Nico de Bruyn P. J. , Delord Karine , Descamps Sébastien , Double Mike , Emmerson Louise , Fedak Mike , Friedlaender Ari , Gales Nick , Goebel Mike , Goetz Kimberly T. , Guinet Christophe , Goldsworthy Simon D. , Harcourt Rob , Hinke Jefferson T. , Jerosch Kerstin , Kato Akiko , Kerry Knowles R. , Kirkwood Roger , Kooyman Gerald L. , Kovacs Kit M. , Lawton Kieran , Lowther Andrew D. , Lydersen Christian , Lyver Phil O’B. , Makhado Azwianewi B. , Márquez Maria E. I. , McDonald Birgitte I. , McMahon Clive R. , Muelbert Monica , Nachtsheim Dominik , Nicholls Keith W. , Nordøy Erling S. , Olmastroni Silvia , Phillips Richard A. , Pistorius Pierre , Plötz Joachim , Pütz Klemens , Ratcliffe Norman , Ryan Peter G. , Santos Mercedes , Southwell Colin , Staniland Iain , Takahashi Akinori , Tarroux Arnaud , Trivelpiece Wayne , Wakefield Ewan , Weimerskirch Henri , Wienecke Barbara , Xavier José C. , Raymond Ben , Hindell Mark A. 
Published: March 2020

AbstractThe Retrospective Analysis of Antarctic Tracking Data (RAATD) is a Scientific Committee for Antarctic Research project led jointly by the Expert Groups on Birds and Marine Mammals and Antarctic Biodiversity Informatics, and endorsed by the Commission for the Conservation of Antarctic Marine Living Resources. RAATD consolidated tracking data for multiple species of Antarctic meso- and top-predators to identify Areas of Ecological Significance. These datasets and accompanying syntheses provide a greater understanding of fundamental ecosystem processes in the Southern Ocean, support modelling of predator distributions under future climate scenarios and create inputs that can be incorporated into decision making processes by management authorities. In this data paper, we present the compiled tracking data from research groups that have worked in the Antarctic since the 1990s. The data are publicly available through biodiversity.aq and the Ocean Biogeographic Information System. The archive includes tracking data from over 70 contributors across 12 national Antarctic programs, and includes data from 17 predator species, 4060 individual animals, and over 2.9 million observed locations.
Helical tomotherapy: Comparison of Hi-ART and Radixact clinical patient treatments at the Technical University of Munich
Authors: Kraus K. M. , Kampfer S. , Wilkens J. J. , Schüttrumpf L. , Combs S. E. 
Published: March 2020

AbstractThe helical tomotherapy (HT) Hi-ART system was installed at our department in April 2007. In July 2018 the first Radixact system in Germany has been launched for clinical use. We present differences, advantages and disadvantages and show future perspectives in patient treatment using two HT devices. We investigate patient characteristics, image quality, radiotherapy treatment specifications and analyze the time effort for treatments with the Hi-ART system from April 2010 until May 2017 and compare it to the data acquired in the first nine months of usage of the Radixact system. Comparing the Hi-ART and Radixact system, the unique option of integrated MVCT image acquisition has experienced distinct improvement in image quality. Time effort for irradiation treatment could be improved resulting in a mean beam on time for craniospinal axis treatment of 636.2 s for the Radixact system compared to 915.9 s for the Hi-ART system. The beneficial use of tomotherapy for complex target volumes is demonstrated by a head and neck tumor case and craniospinal axis treatment. With the Radixact system MVCT image quality has been improved allowing for fast and precise interfraction dose adaptation. The improved time effort for patient treatment could increase the accessibility for clinical usage.
SAEROF: an ensemble approach for large-scale drug-disease association prediction by incorporating rotation forest and sparse autoencoder deep neural network
Authors: Jiang Han-Jing , Huang Yu-An , You Zhu-Hong 
Published: March 2020

AbstractDrug-disease association is an important piece of information which participates in all stages of drug repositioning. Although the number of drug-disease associations identified by high-throughput technologies is increasing, the experimental methods are time consuming and expensive. As supplement to them, many computational methods have been developed for an accurate in silico prediction for new drug-disease associations. In this work, we present a novel computational model combining sparse auto-encoder and rotation forest (SAEROF) to predict drug-disease association. Gaussian interaction profile kernel similarity, drug structure similarity and disease semantic similarity were extracted for exploring the association among drugs and diseases. On this basis, a rotation forest classifier based on sparse auto-encoder is proposed to predict the association between drugs and diseases. In order to evaluate the performance of the proposed model, we used it to implement 10-fold cross validation on two golden standard datasets, Fdataset and Cdataset. As a result, the proposed model achieved AUCs (Area Under the ROC Curve) of Fdataset and Cdataset are 0.9092 and 0.9323, respectively. For performance evaluation, we compared SAEROF with the state-of-the-art support vector machine (SVM) classifier and some existing computational models. Three human diseases (Obesity, Stomach Neoplasms and Lung Neoplasms) were explored in case studies. As a result, more than half of the top 20 drugs predicted were successfully confirmed by the Comparative Toxicogenomics Database(CTD database). This model is a feasible and effective method to predict drug-disease correlation, and its performance is significantly improved compared with existing methods.
Origin of Rashba Spin-Orbit Coupling in 2D and 3D Lead Iodide Perovskites
Authors: Pham Minh T. , Amerling Eric , Luong Hoang M. , Pham Huy T. , Larsen George K. , Whittaker-Brooks Luisa , Nguyen Tho D. 
Published: March 2020

AbstractWe studied spin dynamics of charge carriers in the superlattice-like Ruddlesden-Popper hybrid lead iodide perovskite semiconductors, 2D (BA)2(MA)Pb2I7 (with MA = CH3NH3, and BA = CH3(CH2)3NH3), and 3D MAPbI3 using the magnetic field effect (MFE) on conductivity and electroluminescence in their light emitting diodes (LEDs) at cryogenic temperatures. The semiconductors with distinct structural/bulk inversion symmetry breaking, when combined with colossal intrinsic spin–orbit coupling (SOC), theoretically give rise to giant Rashba-type SOC. We found that the magneto-conductance (MC) magnitude increases monotonically with the emission intensity and saturates at ≈0.05% and 0.11% for the MAPbI3 and (BA)2(MA)Pb2I7, respectively. The magneto-electroluminescence (MEL) response with similar line shapes as the MC response has a significantly larger magnitude, and essentially stays constant at ≈0.22% and ≈0.20% for MAPbI3 and (BA)2(MA)Pb2I7, respectively. The sign and magnitude of the MC and MEL responses can be quantitatively explained in the framework of the Δg-based excitonic model using rate equations. Remarkably, the width of the MEL response in those materials linearly increases with increasing the applied electric field, where the Rashba coefficient in (BA)2(MA)Pb2I7 is estimated to be about 7 times larger than that in MAPbI3. Our studies might have significant impact on future development of electrically-controlled spin logic devices via Rashba-like effects.
Persistent metallic Sn-doped In2O3 epitaxial ultrathin films with enhanced infrared transmittance
Authors: Kim Dongha , Lee Shinbuhm 
Published: March 2020

AbstractInfrared transparent electrodes (IR-TEs) have recently attracted much attention for industrial and military applications. The simplest method to obtain high IR transmittance is to reduce the electrode film thickness. However, for films several tens of nanometres thick, this approach unintentionally suppresses conduction due to surface electron scattering. Here, we demonstrate low sheet resistance (<400 Ω □−1 at room temperature) and high IR transmittance (>65% at the 2.5-μm wavelength) in Sn-doped In2O3 (ITO) epitaxial films for the thickness range of 17−80 nm. A combination of X-ray spectroscopy and ellipsometry measurements reveals a persistent electronic bandstructure in the 8-nm-thick film compared to much thicker films. This indicates that the metallicity of the film is preserved, despite the ultrathin film configuration. The high carrier mobility in the ITO epitaxial films further confirms the film’s metallicity as a result of the improved crystallinity of the film and the resulting reduction in the scattering defect concentration. Thus, ITO shows great potential for IR-TE applications of transparent photovoltaic and optoelectronic devices.