bluuebunny/crossref_metadata_2025_split huggingface dataset:
A novel pathway for the photooxidation of catechin in relation to its prooxidative activity
Authors: Shishido Shunichi , Miyano Rei , Nakashima Takuji , Matsuo Hirotaka , Iwatsuki Masato , Nakamura Keisuke , Kanno Taro , Egusa Hiroshi , Niwano Yoshimi 
Published: August 2018

AbstractIn the present study, we evaluated the prooxidative mode of action of photoirradiated (+)-catechin at 400 nm in relation to reactive oxygen species generation and its possible application to disinfection. Photoirradiation of (+)-catechin at a concentration of 1 mg/mL yielded not only hydrogen peroxide (H2O2) but hydroxyl radical (·OH) in a total amount of approximately 20 μM in 10 min. As a result, photoirradiated catechin killed Staphylococcus aureus, and a > 5-log reduction in viable bacteria counts was observed within 20 min. Liquid chromatography-high-resolution-electrospray ionization-mass spectrometry showed that photoirradiation decreased the (+)-catechin peak (molecular formula C15H14O6) whilst it increased two peaks of a substance with the molecular formula C15H12O6 with increasing irradiation time. Nuclear magnetic resonance analysis revealed that the two C15H12O6 peaks were allocated to intramolecular cyclization products that are enantiomers of each other. These results suggest that photoirradiation induces oxidation of (+)-catechin resulting in the reduction of oxygen to generate H2O2. This H2O2 is then homolytically cleaved to ·OH, and alongside this process, (+)-catechin is finally converted to two intramolecular cyclization products that are different from the quinone structure of the B ring, as proposed previously for the autoxidation and enzymatic oxidation of catechins.
Detection of pathogenic microorganisms from bloodstream infection specimens using TaqMan array card technology
Authors: Zhang Chao , Zheng Xin , Zhao Chengna , Li Yan , Chen Shuiping , Liu Gang , Wang Chengbin , Lv Qingyu , Liu Peng , Zheng Yuling , Kong Decong , Jiang Hua , Jiang Yongqiang 
Published: August 2018

AbstractBloodstream infections (BSIs) are often life-threatening, and rapid identification is critical. Here, we developed a TaqMan array card (TAC) assay to detect pathogens in BSI specimens. The TAC included 30 primer/probe pairs targeting 27 species and 3 controls. Reverse transcription and 0.1% blue dextran 2000 increased the TAC assay efficiency. The primer/probe pairs had a limit of detection of 100–102 CFU/mL and a specificity of 100%. For whole blood specimens, the TAC assay showed a sensitivity and specificity of 79.4% and 99.69%, respectively. For blood culture samples, the TAC assay showed a sensitivity and specificity of 100% and 99.67%, respectively. The TAC assay could be a promising method for early detection of bloodstream infection.
Spontaneous light-induced Turing patterns in a dye-doped twisted nematic layer
Authors: Andrade-Silva Ignacio , Bortolozzo Umberto , Clerc Marcel G. , González-Cortés Gregorio , Residori Stefania , Wilson Mario 
Published: August 2018

AbstractOptical pattern formation is usually due either to the combination of diffraction and nonlinearity in a Kerr medium or to the temporal modulation of light in a photosensitive chemical reaction. Here, we show a different mechanism by which light spontaneously induces stripe domains between nematic states in a twisted nematic liquid crystal layer doped with azo-dyes. Thanks to the photoisomerization process of the dopants, light in the absorption band of the dopants creates spontaneous patterns without the need of temporal modulation, diffraction, Kerr or other optical nonlinearity, but based on the different scales for dopant transport processes and nematic order parameter, which identifies a genuine Turing mechanism for this instability. Theoretically, the emergence of the stripe patterns is described on the basis of a model for the dopant concentration coupled with the nematic order parameter.
Projecting groundwater storage changes in California’s Central Valley
Authors: Massoud Elias C. , Purdy Adam J. , Miro Michelle E. , Famiglietti James S. 
Published: August 2018

AbstractAccurate and detailed knowledge of California’s groundwater is of paramount importance for statewide water resources planning and management, and to sustain a multi-billion-dollar agriculture industry during prolonged droughts. In this study, we use water supply and demand information from California’s Department of Water Resources to develop an aggregate groundwater storage model for California’s Central Valley. The model is evaluated against 34 years of historic estimates of changes in groundwater storage derived from the United States Geological Survey’s Central Valley Hydrologic Model (USGS CVHM) and NASA’s Gravity Recovery and Climate Experiment (NASA GRACE) satellites. The calibrated model is then applied to predict future changes in groundwater storage for the years 2015–2050 under various precipitation scenarios from downscaled climate projections. We also discuss and project potential management strategies across different annual supply and demand variables and how they affect changes in groundwater storage. All simulations support the need for collective statewide management intervention to prevent continued depletion of groundwater availability.
Two-Dimensional MoxW1−xS2 Graded Alloys: Growth and Optical Properties
Authors: Bogaert Kevin , Liu Song , Liu Tao , Guo Na , Zhang Chun , Gradečak Silvija , Garaj Slaven 
Published: August 2018

AbstractTwo-dimensional (2D) transition metal dichalcogenides can be alloyed by substitution at the metal atom site with negligible effect on lattice strain, but with significant influence on optical and electrical properties. In this work, we establish the relationship between composition and optical properties of the MoxW1−xS2 alloy by investigating the effect of continuously-varying composition on photoluminescence intensity. We developed a new process for growth of two-dimensional MoxW1−xS2 alloys that span nearly the full composition range along a single crystal, thus avoiding any sample-related heterogeneities. The graded alloy crystals were grown using a diffusion-based chemical vapor deposition (CVD) method that starts by synthesizing a WS2 crystal with a graded point defect distribution, followed by Mo alloying in the second stage. We show that point defects promote the diffusion and alloying, as confirmed by Raman and photoluminescence measurements, density functional theory calculations of the reaction path, and observation that no alloying occurs in CVD-treated exfoliated crystals with low defect density. We observe a significant dependence of the optical quantum yield as a function of the alloy composition reaching the maximum intensity for the equicompositional Mo0.5W0.5S2 alloy. Furthermore, we map the growth-induced strain distribution within the alloyed crystals to decouple composition and strain effects on optical properties: at the same composition, we observe significant decrease in quantum yield with induced strain. Our approach is generally applicable to other 2D materials as well as the optimization of other composition-dependent properties within a single crystal.
Neural Evidence of Cross-domain Structural Interaction between Language and Arithmetic
Authors: Nakai Tomoya , Okanoya Kazuo 
Published: August 2018

AbstractThe presence of a shared neural system for the syntactic processing in language and arithmetic is controversial. Recent behavioral studies reported a cross-domain structural priming between language and arithmetic. Using functional magnetic resonance imaging, we examined whether the neural activation reflects the structural interaction between language and arithmetic. We prepared sentences and arithmetic expressions (A-expressions) with same and different syntactic structures and presented structurally congruent/incongruent pairs consecutively. By directly comparing activations in the congruent and incongruent conditions, we observed significant repetition suppression effect in the regions including the bilateral inferior frontal gyrus, i.e., neural activation with an A-expression decreased after a sentence with the same syntactic structure (and vice versa). The results strongly support the idea that arithmetic and language share the neural basis for processing syntactic structures.
A deep convolutional neural network approach for astrocyte detection
Authors: Suleymanova Ilida , Balassa Tamas , Tripathi Sushil , Molnar Csaba , Saarma Mart , Sidorova Yulia , Horvath Peter 
Published: August 2018

AbstractAstrocytes are involved in various brain pathologies including trauma, stroke, neurodegenerative disorders such as Alzheimer’s and Parkinson’s diseases, or chronic pain. Determining cell density in a complex tissue environment in microscopy images and elucidating the temporal characteristics of morphological and biochemical changes is essential to understand the role of astrocytes in physiological and pathological conditions. Nowadays, manual stereological cell counting or semi-automatic segmentation techniques are widely used for the quantitative analysis of microscopy images. Detecting astrocytes automatically is a highly challenging computational task, for which we currently lack efficient image analysis tools. We have developed a fast and fully automated software that assesses the number of astrocytes using Deep Convolutional Neural Networks (DCNN). The method highly outperforms state-of-the-art image analysis and machine learning methods and provides precision comparable to those of human experts. Additionally, the runtime of cell detection is significantly less than that of other three computational methods analysed, and it is faster than human observers by orders of magnitude. We applied our DCNN-based method to examine the number of astrocytes in different brain regions of rats with opioid-induced hyperalgesia/tolerance (OIH/OIT), as morphine tolerance is believed to activate glia. We have demonstrated a strong positive correlation between manual and DCNN-based quantification of astrocytes in rat brain.
Role of solvent accessibility for aggregation-prone patches in protein folding
Authors: Mishra Avinash , Ranganathan Shoba , Jayaram B. , Sattar Abdul 
Published: August 2018

AbstractThe arrangement of amino acids in a protein sequence encodes its native folding. However, the same arrangement in aggregation-prone regions may cause misfolding as a result of local environmental stress. Under normal physiological conditions, such regions congregate in the protein’s interior to avoid aggregation and attain the native fold. We have used solvent accessibility of aggregation patches (SAAPp) to determine the packing of aggregation-prone residues. Our results showed that SAAPp has low values for native crystal structures, consistent with protein folding as a mechanism to minimize the solvent accessibility of aggregation-prone residues. SAAPp also shows an average correlation of 0.76 with the global distance test (GDT) score on CASP12 template-based protein models. Using SAAPp scores and five structural features, a random forest machine learning quality assessment tool, SAAP-QA, showed 2.32 average GDT loss between best model predicted and actual best based on GDT score on independent CASP test data, with the ability to discriminate native-like folds having an AUC of 0.94. Overall, the Pearson correlation coefficient (PCC) between true and predicted GDT scores on independent CASP data was 0.86 while on the external CAMEO dataset, comprising high quality protein structures, PCC and average GDT loss were 0.71 and 4.46 respectively. SAAP-QA can be used to detect the quality of models and iteratively improve them to native or near-native structures.
Na1−xSn2P2 as a new member of van der Waals-type layered tin pnictide superconductors
Authors: Goto Yosuke , Miura Akira , Moriyoshi Chikako , Kuroiwa Yoshihiro , Matsuda Tatsuma D. , Aoki Yuji , Mizuguchi Yoshikazu 
Published: August 2018

AbstractSuperconductors with a van der Waals (vdW) structure have attracted a considerable interest because of the possibility for truly two-dimensional (2D) superconducting systems. We recently reported NaSn2As2 as a novel vdW-type superconductor with transition temperature (Tc) of 1.3 K. Herein, we present the crystal structure and superconductivity of new material Na1−xSn2P2 with Tc = 2.0 K. Its crystal structure consists of two layers of a buckled honeycomb network of SnP, bound by the vdW forces and separated by Na ions, as similar to that of NaSn2As2. Amount of Na deficiency (x) was estimated to be 0.074(18) using synchrotron X-ray diffraction. Bulk nature of superconductivity was confirmed by the measurements of electrical resistivity, magnetic susceptibility, and specific heat. First-principles calculation using density functional theory shows that Na1−xSn2P2 and NaSn2As2 have comparable electronic structure, suggesting higher Tc of Na1−xSn2P2 resulted from increased density of states at the Fermi level due to Na deficiency. Because there are various structural analogues with tin-pnictide (SnPn) conducting layers, our results indicate that SnPn-based layered compounds can be categorized into a novel family of vdW-type superconductors, providing a new platform for studies on physics and chemistry of low-dimensional superconductors.
A Kelch domain-containing KLHDC7B and a long non-coding RNA ST8SIA6-AS1 act oppositely on breast cancer cell proliferation via the interferon signaling pathway
Authors: Jeong Gookjoo , Bae Hansol , Jeong Dawoon , Ham Juyeon , Park Sungbin , Kim Hyeon Woo , Kang Han-Sung , Kim Sun Jung 
Published: August 2018

AbstractIn our previous study, the Kelch domain-containing 7B (KLHDC7B) was revealed to be hypermethylated at the promoter but upregulated in breast cancer. In this study, we identified a long non-coding RNA, ST8SIA6-AS1 (STAR1), whose expression was significantly associated with KLHDC7B in breast cancer (R2 = 0.3466, P < 0.01). Involvement of the two genes in tumorigenesis was examined via monitoring their effect on cellular as well as molecular events after each gene dysregulation in cultured mammary cell lines. Apoptosis of MCF-7 decreased by 49.5% and increased by 33.1%, while proliferation noted increase and decrease by up- and downregulation of KLHDC7B, respectively, suggesting its oncogenic property. STAR1, however, suppressed cell migration and increased apoptosis. Network analysis identified many target genes that appeared to have similar regulation, especially in relation to the interferon signaling pathway. Concordantly, expression of genes such as IFITs, STATs, and IL-29 in that pathway was affected by KLHDC7B and STAR1. Taken together, KLHDC7B and STAR1 are both overexpressed in breast cancer and significantly associated with gene modulation activity in the interferon signaling pathway during breast tumorigenesis.
Identification of a Novel Clinical Phenotype of Severe Malaria using a Network-Based Clustering Approach
Authors: Cominetti Ornella , Smith David , Hoffman Fred , Jallow Muminatou , Thézénas Marie L. , Huang Honglei , Kwiatkowski Dominic , Maini Philip K. , Casals-Pascual Climent 
Published: August 2018

AbstractThe parasite Plasmodium falciparum is the main cause of severe malaria (SM). Despite treatment with antimalarial drugs, more than 400,000 deaths are reported every year, mainly in African children. The diversity of clinical presentations associated with SM highlights important differences in disease pathogenesis that often require specific therapeutic options. The clinical heterogeneity of SM is largely unresolved. Here we report a network-based analysis of clinical phenotypes associated with SM in 2,915 Gambian children admitted to hospital with Plasmodium falciparum malaria. We used a network-based clustering method which revealed a strong correlation between disease heterogeneity and mortality. The analysis identified four distinct clusters of SM and respiratory distress that departed from the WHO definition. Patients in these clusters characteristically presented with liver enlargement and high concentrations of brain natriuretic peptide (BNP), giving support to the potential role of circulatory overload and/or right-sided heart failure as a mechanism of disease. The role of heart failure is controversial in SM and our work suggests that standard clinical management may not be appropriate. We find that our clustering can be a powerful data exploration tool to identify novel disease phenotypes and therapeutic options to reduce malaria-associated mortality.
The Importance of Signal Strength in Quantitative Assessment of Retinal Vessel Density Using Optical Coherence Tomography Angiography
Authors: Lim Hyung Bin , Kim Yong Woo , Kim Ju Mi , Jo Young Joon , Kim Jung Yeul 
Published: August 2018

AbstractThe quality of the scan image is important in microvascular circulation analysis using optical coherence tomography (OCTA). We aimed to investigate the effect of signal strength (SS) on OCTA metrics and minimum SS level that could be considered optimal. Macular 6 × 6 mm angiography images were acquired, and all subjects were divided into four groups according to the SS (SS 7, SS 8, SS 9, and SS 10) of the OCTA image. Vessel density (VD), perfusion density (PD), and foveal avascular zone (FAZ) metrics of the superficial capillary plexus were compared. In total, 446 eyes from young healthy subjects were included. As the SS increased from 7 to 10, the VD and PD of the total area, and the FAZ area increased significantly (all, p < 0.001), but there were no significant difference between SS 9 and SS 10 in all metrics. Correlation analysis between the SS and each parameter showed a high correlation coefficient (VD, r = 0.668; PD, r = 0.671; FAZ area, r = 0.570; all, p < 0.001). The measurements of VD, PD, and FAZ using OCTA varied significantly with the SS, and at least 9 of SS is recommended. The physician should be careful in the analyses of OCTA measurements showing different values of the SS.
Anatomical features of the incisivus labii superioris muscle and its relationships with the upper mucolabial fold, labial glands, and modiolar area
Authors: Hur Mi-Sun 
Published: August 2018

AbstractThe current study examined the incisivus labii superioris muscle (ILS) and its morphologic and spatial relationships with the surrounding structures, especially focusing on the upper mucolabial fold, labial glands, and modiolar area. ILSs were investigated in 52 specimens obtained from formalin-fixed Korean adult cadavers (26 left sides, 26 right sides of the face; 15 men, 11 women; mean age, 70.8 years). ILSs were observed in all specimens (100%). The ILS has an oblique and linear origin from the incisive fossa of the maxilla to the point just medial to the origin of the levator anguli oris muscle (LAO). The arising fibers of the ILS arched and covered the prominent labial glands at the superior margin of the orbicularis oris muscle (OOr). After the ILS coursed laterally along the anterior part of the upper mucolabial fold, it divided into superficial and deep inserting fibers in 48 specimens (92.3%) and it did not divide in 4 specimens (7.7%). The superficial inserting ILS fibers and the ILS fibers that did not divide blended with the medial fibers of the LAO to converge toward the modiolus. The deep inserting fibers of the ILS blended with the lateral deep fibers of the OOr in the 48 specimens (92.3%), and the deep inserting fibers continued to descend to converge toward the modiolus in 20 of those specimens (38.5%). These observations indicate that the ILS may assist to compress the labial glands and the upper oral vestibule, controlling modiolar movements and thereby integrating the movements of the mouth and lips.
Pivotal trial of an autonomous AI-based diagnostic system for detection of diabetic retinopathy in primary care offices
Authors: Abràmoff Michael D. , Lavin Philip T. , Birch Michele , Shah Nilay , Folk James C. 
Published: August 2018

AbstractArtificial Intelligence (AI) has long promised to increase healthcare affordability, quality and accessibility but FDA, until recently, had never authorized an autonomous AI diagnostic system. This pivotal trial of an AI system to detect diabetic retinopathy (DR) in people with diabetes enrolled 900 subjects, with no history of DR at primary care clinics, by comparing to Wisconsin Fundus Photograph Reading Center (FPRC) widefield stereoscopic photography and macular Optical Coherence Tomography (OCT), by FPRC certified photographers, and FPRC grading of Early Treatment Diabetic Retinopathy Study Severity Scale (ETDRS) and Diabetic Macular Edema (DME). More than mild DR (mtmDR) was defined as ETDRS level 35 or higher, and/or DME, in at least one eye. AI system operators underwent a standardized training protocol before study start. Median age was 59 years (range, 22–84 years); among participants, 47.5% of participants were male; 16.1% were Hispanic, 83.3% not Hispanic; 28.6% African American and 63.4% were not; 198 (23.8%) had mtmDR. The AI system exceeded all pre-specified superiority endpoints at sensitivity of 87.2% (95% CI, 81.8–91.2%) (>85%), specificity of 90.7% (95% CI, 88.3–92.7%) (>82.5%), and imageability rate of 96.1% (95% CI, 94.6–97.3%), demonstrating AI’s ability to bring specialty-level diagnostics to primary care settings. Based on these results, FDA authorized the system for use by health care providers to detect more than mild DR and diabetic macular edema, making it, the first FDA authorized autonomous AI diagnostic system in any field of medicine, with the potential to help prevent vision loss in thousands of people with diabetes annually. ClinicalTrials.gov NCT02963441
In situ serial crystallography for rapid de novo membrane protein structure determination
Authors: Huang Chia-Ying , Olieric Vincent , Howe Nicole , Warshamanage Rangana , Weinert Tobias , Panepucci Ezequiel , Vogeley Lutz , Basu Shibom , Diederichs Kay , Caffrey Martin , Wang Meitian 
Published: August 2018

AbstractDe novo membrane protein structure determination is often limited by the availability of large crystals and the difficulties in obtaining accurate diffraction data for experimental phasing. Here we present a method that combines in situ serial crystallography with de novo phasing for fast, efficient membrane protein structure determination. The method enables systematic diffraction screening and rapid data collection from hundreds of microcrystals in in meso crystallization wells without the need for direct crystal harvesting. The requisite data quality for experimental phasing is achieved by accumulating diffraction signals from isomorphous crystals identified post-data collection. The method works in all experimental phasing scenarios and is particularly attractive with fragile, weakly diffracting microcrystals. The automated serial data collection approach can be readily adopted at most microfocus macromolecular crystallography beamlines.