bluuebunny/crossref_metadata_2025_split huggingface dataset:
Decadal Delays in Groundwater Recovery from Nitrate Contamination Caused by Low O2 Reduction Rates
Authors: Wild Lisa M. , Mayer Bernhard , Einsiedl Florian 
Published: November 2018

AbstractNitrate (NO
) is one of the main pollutants in agriculturally impacted groundwater systems. The availability and reactivity of electron donors control the prevalent redox conditions in aquifers and past nitrate contamination of groundwater can be ameliorated if denitrification occurs. Using aqueous geochemistry data and the stable isotope composition of dissolved nitrate (δ15N and δ18O), we found that nitrate concentrations above the World Health Organization drinking water guideline were caused predominantly by manure and to a lesser extent by synthetic fertilizer applications and that denitrification was not a significant nitrate removal process in an aquifer in southern Germany underlying agricultural land with intensive hog farming. We also applied environmental isotopes (δ2H and δ18O, 3H/3He, and 14C) linked with a lumped parameter approach to determine apparent mean transit times (MTT) of groundwater that ranged from <5 years to >100 years. Furthermore, we determined low reduction rates of dissolved oxygen (O2) of 0.015 1/year for first‐order kinetics. By extrapolating the O2 reduction rates beyond the apparent MTT ranges of sampled groundwater, denitrification lag times (time prior to commencement of denitrification) of approximately 114 years were determined. This suggests that it will take many decades to significantly reduce nitrate concentrations in the porous aquifer via denitrification, even if future nitrate inputs were significantly reduced.
Low loss photonic nanocavity via dark magnetic dipole resonant mode near metal
Authors: Liu Ning , Silien Christophe , Sun Greg , Corbett Brian 
Published: November 2018

AbstractThe dielectric-semiconductor-dielectric-metal 4 layered structure is a well-established configuration to support TM hybrid plasmonic modes, which have demonstrated significant advantages over pure photonic modes in structures without metal to achieve low loss resonant cavities at sub-diffraction limited volumes. The photonic modes with TE characteristics supported by the same 4 layered structure, on the other hand, are less studied. Here we show that a low loss photonic mode with TE01 characteristics exists in the dielectric-semiconductor-dielectric-metal 4 layered structure if a truncated cylindrical disk is chosen as the semiconductor core. This mode exhibits the lowest cavity loss among all resonant modes, including both pure photonic and hybrid plasmonic modes, at cavity radius <150 nm and within the wavelength range 620 nm to 685 nm, with a footprint ~0.83 (λ/2neff)2, physical size ~0.47 (λ/2neff)3 and a mode volume down to 0.3 (λ/2neff)3. The low cavity loss of this TE01 mode is attributed to its substantially reduced radiation loss to the far field by the creation of image charges through the metal response. Because of the low mode penetration in the metal, this photonic mode show equally low cavity loss near industry relevant metals such as Cu. Our study demonstrates an alternative to hybrid plamonic modes and metallo-dielectric modes to achieve low loss cavities with extremely small footprints.
Phosphorescent Energy Downshifting for Diminishing Surface Recombination in Silicon Nanowire Solar Cells
Authors: Kim Hyun-Tak , Lee Kangmin , Jin Wonjoo , Um Han-Don , Lee Minsoo , Hwang Eunhye , Kwon Tae-Hyuk , Seo Kwanyong 
Published: November 2018

AbstractMolecularly engineered Ir(III) complexes can transfer energy from short-wavelength photons (λ < 450 nm) to photons of longer wavelength (λ > 500 nm), which can enhance the otherwise low internal quantum efficiency (IQE) of crystalline Si (c-Si) nanowire solar cells (NWSCs) in the short-wavelength region. Herein, we demonstrate a phosphorescent energy downshifting system using Ir(III) complexes at short wavelengths (300–450 nm) to diminish the severe surface recombination that occurs in c-Si NWSCs. The developed Ir(III) complexes can be considered promising energy converters because they exhibit superior intrinsic properties such as a high quantum yield, a large Stokes shift, a long exciton diffusion length in crystalline film, and a reproducible synthetic procedure. Using the developed Ir(III) complexes, highly crystalline energy downshifting layers were fabricated by ultrasonic spray deposition to enhance the photoluminescence efficiency by increasing the radiative decay. With the optimized energy downshifting layer, our 1 cm2 c-Si NWSCs with Ir(III) complexes exhibited a higher IQE value for short-wavelength light (300–450 nm) compared with that of bare Si NWSCs without Ir(III) complexes, resulting in a notable increase in the short-circuit current density (from 34.4 mA·cm−2 to 36.5 mA·cm−2).
Superhydrophobic lab-on-chip measures secretome protonation state and provides a personalized risk assessment of sporadic tumour
Authors: Malara N. , Gentile F. , Coppedè N. , Coluccio M. L. , Candeloro P. , Perozziello G. , Ferrara L. , Giannetto M. , Careri M. , Castellini A. , Mignogna C. , Presta I. , Pirrone C. K. , Maisano D. , Donato A. , Donato G. , Greco M. , Scumaci D. , Cuda G. , Casale F. , Ferraro E. , Bonacci S. , Trunzo V. , Mollace V. , Onesto V. , Majewska R. , Amato F. , Renne M. , Innaro N. , Sena G. , Sacco R. , Givigliano F. , Voci C. , Volpentesta G. , Guzzi G. , Lavano A. , Scali E. , Bottoni U. , Di Fabrizio E. 
Published: November 2018

AbstractSecretome of primary cultures is an accessible source of biological markers compared to more complex and less decipherable mixtures such as serum or plasma. The protonation state (PS) of secretome reflects the metabolism of cells and can be used for cancer early detection. Here, we demonstrate a superhydrophobic organic electrochemical device that measures PS in a drop of secretome derived from liquid biopsies. Using data from the sensor and principal component analysis (PCA), we developed algorithms able to efficiently discriminate tumour patients from non-tumour patients. We then validated the results using mass spectrometry and biochemical analysis of samples. For the 36 patients across three independent cohorts, the method identified tumour patients with high sensitivity and identification as high as 100% (no false positives) with declared subjects at-risk, for sporadic cancer onset, by intermediate values of PS. This assay could impact on cancer risk management, individual’s diagnosis and/or help clarify risk in healthy populations.
In vivo multiphoton microscopy detects longitudinal metabolic changes associated with delayed skin wound healing
Authors: Jones Jake D. , Ramser Hallie E. , Woessner Alan E. , Quinn Kyle P. 
Published: November 2018

AbstractChronic wounds are difficult to diagnose and characterize due to a lack of quantitative biomarkers. Label-free multiphoton microscopy has emerged as a useful imaging modality capable of quantifying changes in cellular metabolism using an optical redox ratio of FAD/(NADH+FAD) autofluorescence. However, the utility of an optical redox ratio for long-term in vivo monitoring of tissue metabolism has not been robustly evaluated. In this study, we demonstrate how multiphoton microscopy can be used to monitor changes in the metabolism of individual full-thickness skin wounds in vivo. 3D optical redox ratio maps and NADH fluorescence lifetime images identify differences between diabetic and control mice during the re-epithelialization of wounds. These metabolic changes are associated with a transient increase in keratinocyte proliferation at the wound edge. Our study demonstrates that high-resolution, non-invasive autofluorescence imaging can be performed in vivo and that optical redox ratios can serve as quantitative optical biomarkers of impaired wound healing.
High content organelle trafficking enables disease state profiling as powerful tool for disease modelling
Authors: Pal Arun , Glaß Hannes , Naumann Marcel , Kreiter Nicole , Japtok Julia , Sczech Ronny , Hermann Andreas 
Published: November 2018

AbstractNeurodegenerative diseases pose a complex field with various neuronal subtypes and distinct differentially affected intra-neuronal compartments. Modelling of neurodegeneration requires faithful in vitro separation of axons and dendrites, their distal and proximal compartments as well as organelle tracking with defined retrograde versus anterograde directionality. We use microfluidic chambers to achieve compartmentalization and established high throughput live organelle imaging at standardized distal and proximal axonal readout sites in iPSC-derived spinal motor neuron cultures from human amyotrophic lateral sclerosis patients to study trafficking phenotypes of potential disease relevance. Our semi-automated pipeline of organelle tracking with FIJI and KNIME yields quantitative, multiparametric high content phenotypic signatures of organelle morphology and their trafficking in axons. We provide here the resultant large datasets to enable systemic signature interrogations for comprehensive and predictive disease modelling, mechanistic dissection and secondary hit validation (e.g. drug screens, genetic screens). Due to the nearly complete coverage of analysed motility events, our quantitative method yields a bias-free statistical power superior over common analyses of a handful of manual kymographs.
RNA-seq transcriptomic profiling of crassulacean acid metabolism pathway in Dendrobium catenatum
Authors: Zou Long-Hai , Wan Xiao , Deng Hua , Zheng Bao-Qiang , Li Bai-Jun , Wang Yan 
Published: November 2018

AbstractThe regulation of crassulacean acid metabolism (CAM) pathway has recently become a topic of intensive research and has been explored in terms of several aspects, including phylogenetics, genomics, and transcriptomics. Orchidaceae, which contains approximately 9,000 CAM species, is one of the largest lineages using this special photosynthetic pathway. However, no comprehensive transcriptomic profiling focused on CAM regulation in orchid species had previously been performed. In this report, we present two Illumina RNA-seq datasets, including a total of 24 mature leaf samples with 844.4 million reads, from Dendrobium catenatum (Orchidaceae), a facultative CAM species. The first dataset was generated from a time-course experiment based on the typical CAM phases in a diel. The second was derived from an experiment on drought stress and stress removal. A series of quality assessments were conducted to verify the reliability of the datasets. These transcriptomic profiling datasets will be useful to explore and understand the essence of CAM regulation.
PaleoClim, high spatial resolution paleoclimate surfaces for global land areas
Authors: Brown Jason L. , Hill Daniel J. , Dolan Aisling M. , Carnaval Ana C. , Haywood Alan M. 
Published: November 2018

AbstractHigh-resolution, easily accessible paleoclimate data are essential for environmental, evolutionary, and ecological studies. The availability of bioclimatic layers derived from climatic simulations representing conditions of the Late Pleistocene and Holocene has revolutionized the study of species responses to Late Quaternary climate change. Yet, integrative studies of the impacts of climate change in the Early Pleistocene and Pliocene – periods in which recent speciation events are known to concentrate – have been hindered by the limited availability of downloadable, user-friendly climatic descriptors. Here we present PaleoClim, a free database of downscaled paleoclimate outputs at 2.5-minute resolution (~5 km at equator) that includes surface temperature and precipitation estimates from snapshot-style climate model simulations using HadCM3, a version of the UK Met Office Hadley Centre General Circulation Model. As of now, the database contains climatic data for three key time periods spanning from 3.3 to 0.787 million years ago: the Marine Isotope Stage 19 (MIS19) in the Pleistocene (~787 ka), the mid-Pliocene Warm Period (~3.264–3.025 Ma), and MIS M2 in the Late Pliocene (~3.3 Ma).
Characterizing young protostellar disks with the CALYPSO IRAM-PdBI survey: large Class 0 disks are rare
Authors: Maury A. J. , André Ph. , Testi L. , Maret S. , Belloche A. , Hennebelle P. , Cabrit S. , Codella C. , Gueth F. , Podio L. , Anderl S. , Bacmann A. , Bontemps S. , Gaudel M. , Ladjelate B. , Lefèvre C. , Tabone B. , Lefloch B. 
Published: November 2018

Context.Understanding the formation mechanisms of protoplanetary disks and multiple systems and also their pristine properties are key questions for modern astrophysics. The properties of the youngest disks, embedded in rotating infalling protostellar envelopes, have largely remained unconstrained up to now.Aims.We aim to observe the youngest protostars with a spatial resolution that is high enough to resolve and characterize the progenitors of protoplanetary disks. This can only be achieved using submillimeter and millimeter interferometric facilities. In the framework of the IRAM Plateau de Bure Interferometer survey CALYPSO, we have obtained subarcsecond observations of the dust continuum emission at 231 and 94 GHz for a sample of 16 solar-type Class 0 protostars.Methods.In an attempt to identify disk-like structures embedded at small scales in the protostellar envelopes, we modeled the dust continuum emission visibility profiles using Plummer-like envelope models and envelope models that include additional Gaussian disk-like components.Results.Our analysis shows that in the CALYPSO sample, 11 of the 16 Class 0 protostars are better reproduced by models including a disk-like dust continuum component contributing to the flux at small scales, but less than 25% of these candidate protostellar disks are resolved at radii >60 au. Including all available literature constraints on Class 0 disks at subarcsecond scales, we show that our results are representative: most (>72% in a sample of 26 protostars) Class 0 protostellar disks are small and emerge only at radii <60 au. We find a multiplicity fraction of the CALYPSO protostars ≲57% ± 10% at the scales 100–5000 au, which generally agrees with the multiplicity properties of Class I protostars at similar scales.Conclusions.We compare our observational constraints on the disk size distribution in Class 0 protostars to the typical disk properties from protostellar formation models. If Class 0 protostars contain similar rotational energy as is currently estimated for prestellar cores, then hydrodynamical models of protostellar collapse systematically predict a high occurrence of large disks. Our observations suggest that these are rarely observed, however. Because they reduce the centrifugal radius and produce a disk size distribution that peaks at radii <100 au during the main accretion phase, magnetized models of rotating protostellar collapse are favored by our observations.
A Retrospective Comparative Study of Different Methods of Blood Management in Total Knee Replacement
Authors: Pappa Eleni , Vergados Nikolaos , Spiridakis Emanouil , Chountas George , Apostolopoulou Anna , Sourmelis Savas 
Published: November 2018

AbstractPerioperative blood management is essential to minimize allogeneic blood transfusion in total knee replacement. The effect of preoperative administration of erythropoietin, intraoperative cell saver, tranexamic acid, and restrictive transfusion strategies on allogeneic transfusion is studied in total knee replacement. A retrospective comparative study of 106 patients who underwent total knee replacement in different time periods was performed. Group A (n
1 = 45) underwent restrictive strategies of transfusion between 2009 and 2010. Group B (n
2 = 24) includes patients where erythropoietin of either 10.000 IU or 20.000 IU was given preoperatively. Patients of Group C (n
3 = 21) underwent autologous washed erythrocytes transfusion through a cell saver. Lastly, in Group D (n
4 = 15) tranexamic acid dose of 1 gr IV was given intraoperatively. The preoperative and discharge hemoglobin together with total units of blood transfusion and creatinine levels was studied. Tranexamic acid noted the least units of blood transfusion (mean = 0.82 units/patient, p < 0.001, CI 95%) in contrast to the two regimens of erythropoietin (1.16 units/patient) OrthoPAT (1.43 units/patient) and restrictive strategies (1.92 units/patient). The mean preoperative hemoglobin was 13.37 g/dL with no statistical difference among the groups of patients. The postoperative mean hemoglobin was 10.59 with no statistical difference among the groups of patients too. Additionally, the mean creatinine level was 0.93 mg/dL; however, no statistical difference among the groups of patients was noted. Finally, tranexamic acid seemed to be the most cost-effective regime. In our study, tranexamic acid proved its superiority concerning the postoperative blood transfusion on patients undergoing total knee replacement, in comparison with the other existing methods of perioperative blood management. This is a Level III, retrospective comparative study.
Schmerztherapeutische Aspekte bei Tumoroperationen
Authors: Wirz Stefan , Schenk Michael , Kieselbach Kristin 
Published: November 2018

ZusammenfassungTrotz einer Vielzahl von Therapieoptionen wird die Akutschmerztherapie nach onkologischen Operationen häufig als unzureichend beschrieben. Neben einer unzureichenden Akutschmerztherapie können weitere Faktoren eine Hypersensitivierung und Chronifizierung sowie den Verlauf der Tumorerkrankung beeinflussen. Dieser Beitrag erklärt pathophysiologische Hintergründe und erläutert geeignete Therapiemodalitäten.
Double dissociation of single-interval and rhythmic temporal prediction in cerebellar degeneration and Parkinson’s disease
Authors: Breska Assaf , Ivry Richard B. 
Published: November 2018

Significance
The brain uses temporal regularities to anticipate the timing of future events, and adjust attention and action accordingly. We investigated whether subsecond temporal predictions formed in two distinct predictive contexts, when the stream of events is rhythmic or when the specific interval between two events is known, are functionally and neurally distinct. We show that individuals with cerebellar dysfunction were impaired in forming temporal predictions based on single intervals, but not in rhythmic contexts. In contrast, individuals with basal ganglia dysfunction resulting from Parkinson’s disease showed the reverse pattern. This double dissociation constitutes causal evidence in favor of distinct computational and neural mechanisms for interval- and rhythm-based temporal prediction, and highlights the contribution of these subcortical structures to attentional orienting.
What’s political Twitter talking about?
Authors: Hedding Kylah J. , Ripka Kevin 
Published: November 2018

Abstract
This study explicates the concept of news media agendamelding. While only one-quarter of U.S. adults are on Twitter, it remains a
popular platform among news media and political elites who often still set the public agenda for political discourse. Twitter
provides insights into the issues that are at the top of the media and policy agendas, as well as how social media might influence
the way journalists approach political issues. At the same time, there is concern about the influence of social media on political
polarization. This study uses a specific set of influential Twitter users to examine one main question: Were there differences
between right, left, and center political media reactions during the 2016 presidential debates? This study provides further
evidence that there is, in fact, a conservative political Twitter media agenda that exists separately from liberal or nonpartisan
media outlets.
Patient-centred cognition metrology
Authors: Cano S J , Melin J , Fisher WP , Stenner AJ , Pendrill LR 
Published: November 2018

Abstract
We have yet to realise reconciliation between metrology in the physical sciences and measurement practices in the social sciences. Here, we build on our previous arguments by proposing a psychometric methodology to support metrology in the social sciences. This will be exemplified in the European EMPIR NeuroMet 15HLT04 project, part of which exploits causal Rasch models, novel construct specification equations, and subsequent improved patient centred cognition measurement in support of healthcare and policy decision-making in Alzheimer’s disease. In addition, the programme’s goal of forming key stakeholder networks, including clinicians, instrument manufactures, biopharma, national and international organisations, will ensure consistent uptake of the new measurement methods.
A Drug-Side Effect Context-Sensitive Network approach for drug target prediction
Authors: Zhou Mengshi , Chen Yang , Xu Rong 
Published: November 2018

AbstractSummaryComputational drug target prediction has become an important process in drug discovery. Network-based approaches are commonly used in computational drug–target interaction (DTI) prediction. Existing network-based approaches are limited in capturing the contextual information on how diseases, drugs and genes are connected. Here, we proposed a context-sensitive network (CSN) model for DTI prediction by modeling contextual drug phenotypic relationships. We constructed a Drug-Side Effect Context-Sensitive Network (DSE-CSN) of 139 760 drug-side effect pairs, representing 1480 drugs and 5868 side effects. We also built a protein–protein interaction network (PPIN) of 15 267 gene nodes and 178 972 weighted edges. A heterogeneous network was built by connecting the DSE-CSN and the PPIN through 3684 known DTIs. For each drug on the DSE-CSN, its genetic targets were predicted and prioritized using a network-based ranking algorithm. Our approach was evaluated in both de novo and leave-one-out cross-validation analysis using known DTIs as the gold standard. We compared our DSE-CSN-based model to the traditional similarity-based network (SBN)-based prediction model. The results suggested that the DSE-CSN-based model was able to rank known DTIs highly. In a de novo cross-validation, the area under the receiver operating characteristic (ROC) curve was 0.95. In a leave-one-out cross-validation, the average rank was top 3.2% for known DTIs. When it was compared to the SBN-based model using the Precision-Recall curve, our CSN-based model achieved a higher mean average precision (MAP) (0.23 versus 0.19, P-value&lt;1e−4) in a de novo cross-validation analysis. We further improved the CSN-based DTI prediction by differentially weighting the drug-side effect pairs on the network and showed a significant improvement of the MAP (0.29 versus 0.23, P-value&lt;1e−4). We also showed that the CSN-based model consistently achieved better performances than the traditional SBN-based model across different drug classes. Moreover, we demonstrated that our novel DTI predictions can be supported by published literature. In summary, the CSN-based model, by modeling the context-specific inter-relationships among drugs and side effects, has a high potential in drug target prediction.Availability and implementationnlp/case/edu/public/data/DSE/CSN_DTI.
SeQuiLa: an elastic, fast and scalable SQL-oriented solution for processing and querying genomic intervals
Authors: Wiewiórka Marek , Leśniewska Anna , Szmurło Agnieszka , Stępień Kacper , Borowiak Mateusz , Okoniewski Michał , Gambin Tomasz 
Published: November 2018

Abstract

Summary
Efficient processing of large-scale genomic datasets has recently become possible due to the application of ‘big data’ technologies in bioinformatics pipelines. We present SeQuiLa—a distributed, ANSI SQL-compliant solution for speedy querying and processing of genomic intervals that is available as an Apache Spark package. Proposed range join strategy is significantly (∼22×) faster than the default Apache Spark implementation and outperforms other state-of-the-art tools for genomic intervals processing.

Availability and implementation
The project is available at http://biodatageeks.org/sequila/.

Supplementary information
Supplementary data are available at Bioinformatics online.