bluuebunny/crossref_metadata_2025_split huggingface dataset:
Virus genotyping by massive parallel amplicon sequencing: adenovirus and enterovirus in the Norwegian MIDIA study
Authors: Cinek Ondrej , Kramna Lenka , Mazankova Karla , Kunteová Kateřina , Chudá Kateřina , C. J. Claas Eric , Stene Lars C. , Tapia German 
Published: December 2018

ObjectivesDirect genotyping of adenovirus or enterovirus from clinical material using polymerase chain reaction (PCR) followed by Sanger sequencing is often difficult due to the presence of multiple virus types in a sample, or due to varying efficacy of PCR amplifying the capsid gene on the background of foreign nucleic acids. Here we present a simple protocol for virus genotyping using massive parallel amplicon sequencing.MethodsThe protocol utilized a set of 16 tailed degenerate primers flanking the seventh hypervariable region of the adenovirus hexon gene and 9 tailed degenerate primers targeted to the proximal portion of the enterovirus VP1 gene. Subsequent addition of dual indices enabled simultaneous sequencing of 384 different samples on an Illumina MiSeq instrument. Downstream bioinformatic analysis was based on remapping to a set of references representative of the presently known repertoire of virus types.ResultsAfter validation with known virus types, the sequencing method was applied on 301 adenovirus‐positive samples and 350 enterovirus‐positive samples from a longitudinally collected series of stools from 83 children aged 3 to 36 months. We detected 7 different adenovirus types and 27 different enterovirus types. There were 37 (6.2%) samples containing more than one genotype of the same viral genus. At least one dual infection was experienced by 23 of 83 (28%) of the children observed over the 3 years' observation period.ConclusionsAmplicon sequencing with a multiplex set of degenerate primers seems to be a rapid and reliable technical solution for genotyping of large collections of samples where simultaneous infections with multiple strains can be expected.
Evaluation of enamel demineralization and fluorine uptake caused by gustatory stimulants of salivary secretion (GSSS) using Raman spectroscopy and proton induced gamma‐ray emission (PIGE)
Authors: Luís Gonçalo , Silva Hugo , Silveira João , Manteigas Vasco , Mata António , Marques Duarte , Jesus Adelaide , Fonseca Micaela , Pessanha Sofia 
Published: December 2018

AbstractIn this work, two gustatory stimulants of salivary secretion (GSSS) were studied using Raman microscopy to evaluate their potential demineralization effect in human enamel samples and proton induced gamma‐ray emission (PIGE) to quantify fluorine uptake. These pharmaceutical products are usually administrated to patients who have revealed xerostomia, namely, caused by radiation therapy, chemotherapy, or diseases such as Sjögren's Syndrome. Traditional GSSS are composed of citric or malic acids that can promote enamel erosion by decreasing salivary pH below the critical level of hydroxyapatite demineralization (pH = 5.5). Recently, new GSSS composed of malic acid, fluorine, and xylitol were developed, which are supposed to decrease erosion potential risk and uptake fluorine in dental enamel. In this, in vitro study, 16 specimens of human enamel were randomized in two different groups exposed to two different GSSS: S group—SST® (with citric and malic acids, without fluorine) and X group—Xeros™ (with malic acid, fluorine, and xylitol) and analysed before and after treatment. The treatment simulated administration of four tablets per day during eight consecutive days. Statistically, significant increase in fluorine concentration was found in samples treated by Xeros™, whereas no significant differences were found in fluorine concentration for the ones treated using SST® treatment. No demineralization was found in dental enamel samples treated with either Xeros™ or SST®.
Aptamer‐modified magnetic metal‐organic framework MIL‐101 for highly efficient and selective enrichment of ochratoxin A
Authors: Zhang Qianchun , Yang Yanqun , Zhi Yongzhi , Wang Xingyi , Wu Yun , Zheng Yuguo 
Published: December 2018

AbstractA facile and efficient strategy is developed to modify aptamers on the surface of the magnetic metal‐organic framework MIL‐101 for the rapid magnetic solid‐phase extraction of ochratoxin A. To the best of our knowledge, this is the first attempt to create a robust aptamer‐modified magnetic MIL‐101 with covalent bonding for the magnetic separation and enrichment of ochratoxin A. The saturated adsorption of ochratoxin A by aptamer‐modified magnetic MIL‐101 was 7.9 times greater than that by magnetic metal‐organic framework MIL‐101 due to the former's high selective recognition as well as good stability. It could be used for extraction more than 12 times with no significant changes in the extraction efficiency. An aptamer‐modified magnetic MIL‐101‐based method of magnetic solid‐phase extraction combined with ultra high performance liquid chromatography with tandem mass spectrometry was developed for the determination of trace ochratoxin A with limit of detection of 0.067 ng/L. Ochratoxin A of 4.53–13.7 ng/kg was determined in corn and peanut samples. The recoveries were in the range 82.8–108% with a relative standard deviation (n = 5) of 4.5–6.5%. These results show that aptamer‐modified magnetic MIL‐101 exhibits selective and effective enrichment performance and have excellent potential for the analysis of ultra‐trace targets from complex matrices.
Age hardening behaviour of semi‐solid squeeze cast A319 aluminium alloy
Authors: Wang Q.F. , Wang L.D. , Zhu D.Y. , Lin Z. , Chen X. , Sheng B. 
Published: December 2018

AbstractThe influence of age hardening treatment on the hardness and microstructure of semi‐solid squeeze cast A319 alloy is investigated. At 175 °C, the age‐hardening curve of the alloy shows two peaks between which there was an apparent valley. Analyses by transmission electron microscopy, selected area electron diffraction and energy‐dispersive X‐ray detection suggest that the first peak is caused by formation of G.P.2 zones while the second peak can be related to formation of the metastable θ′‐ and Q′‐phases. Compared with gravity die cast A319 the semi‐solid squeeze cast A319 shows a larger increase and a higher peak in hardness during the age hardening process. Additionally, the latter requires another 32 h to reach the first hardness peak while it reaches the second hardness peak about 24 h earlier than the former.
Impact of Oxidative Metabolism on the Cytotoxic and Genotoxic Potential of Genistein in Human Colon Cancer Cells
Authors: Schroeter Anika , Aichinger Georg , Stornig Karin , Marko Doris 
Published: December 2018

ScopeGenistein (GEN) is known to be genotoxic via targeting topoisomerase‐II (TOPII). Oxidative metabolism of GEN is shown to generate hydroxylated metabolites with catecholic structures. The present study focuses on the impact of oxidative metabolism of GEN, exemplified for 3′‐hydroxygenistein (3′‐OH‐GEN) and 6‐hydroxygenistein (6‐OH‐GEN), on topoisomerase interference and the resulting genotoxic potential in HT‐29 human colon carcinoma cells.Methods and resultsIn a cell‐free decatenation assay, 3′‐OH‐GEN slightly exceeds the TOPII‐inhibiting potential of GEN. In HT‐29 cells, its inhibitory action on TOPII does not differ from GEN, but it has greater activity with respect to causing DNA damage (measured by the comet assay), p53 activation (Western blot), apoptosis induction (ELISA), and cytotoxicity (WST‐1 assay). This may to some extent be related to a stronger pro‐oxidative potential of 3′‐OH‐GEN in comparison to GEN, as observed for the highest concentrations (DCF assay).6‐OH‐GEN exerts much weaker toxic effects than GEN in cell‐based assays, including TOPII poisoning, DNA strand‐breaking potential, and ROS generation. This might in part arise from decreased cellular uptake of the metabolite, as measured by HPLC–DAD.ConclusionOxidative metabolism alters the toxicological potential of GEN. Depending on the site of oxidation, the toxicity of the parent compound is exceeded (3′‐OH‐GEN) or attenuated (6‐OH‐GEN).
Dosimetric features‐driven machine learning model for DVH prediction in VMAT treatment planning
Authors: Ma Ming , Kovalchuk Nataliya , Buyyounouski Mark K. , Xing Lei , Yang Yong 
Published: December 2018

PurposeFew features characterizing the dosimetric properties of the patients are included in currently available dose‐volume histogram (DVH) prediction models, making it intractable to build a correlative relationship between the input and output parameters. Here, we use planning target volume (PTV)‐only treatment plans of the patients (i.e., the achievable dose distribution in the absence of organs‐at‐risk (OAR) constraints) to estimate the potentially achievable quality of treatment plans and establish a machine learning‐based DVH prediction framework with the use of the dosimetric metric as model input parameters.MethodsA support vector regression (SVR) approach was used as the backbone of our machine learning model. A database containing volumetric modulated arc therapy (VMAT) plans of 63 prostate cancer patients were used. For each patient, the PTV‐only plan was generated first. A correlative relationship between the OAR DVH of the PTV‐only plan (model input) and the corresponding DVH of the clinical treatment plan (CTP) (model output) was then established with the 53 training cases. The prediction model was tested by the validation cohort of ten cases.ResultsFor the training cohort, the checks of dosimetric endpoints (DEs) indicated that 52 of 53 plans (98%) were within the 10% error bound for bladder, and 45 of 53 plans (85%) were within the 10% error bound for rectum. In the validation tests, 92% and 96% of the DEs were within the 10% error bounds for bladder and rectum, respectively, and eight of ten validation plans (80%) were within the 10% error bound for both the bladder and rectum. The sum of absolute residuals (SAR) achieved a mean of 0.034 ± 0.028 and 0.046 ± 0.021 for the bladder and rectum, respectively.ConclusionsA novel dosimetric features‐driven machine learning model with the use of PTV‐only plan has been established for DVH prediction. The framework is capable of efficiently generating best achievable DVHs for VMAT planning.
Association between obesity in 4‐ to 7‐year‐old children and eight types of crime: a hierarchical linear modelling approach
Authors: Benzies K. M. , Yates M. T. , Patel A. B. , Afzal A. R. , Kurilova J. , McNeil D. A. 
Published: December 2018

SummaryObjectiveEvidence of the association between childhood obesity and neighbourhood crime is inconclusive. Most previous studies have included children of all ages, and few have examined different types of crime. The objective of this study was to investigate the association between obesity and eight different types of crime (i.e. commercial robbery, street robbery, assault, other violence, commercial break and enter, residential break and enter, theft of vehicle and theft from vehicle) among 4‐ to 7‐year‐old children in a large western Canadian city.MethodsCross‐sectional, epidemiological study (N = 10,069) using spatial analysis and hierarchical generalized linear modelling. The outcome variable was normal weight or obesity. The exposure variable was the distance between the child's residential postal code and the closest occurrence of each type of crime.ResultsControlling for distance to the closest park, frequency of each type of crime in the child's neighbourhood and neighbourhood factors (proportion of visible minorities, education and median family income), there was no association between any of the crime types and childhood obesity.ConclusionsCrime did not contribute to obesity in this sample of 4‐ to 7‐year‐old children. Replication of this study in other jurisdictions would increase confidence in these results.
Structures and activities of widely conserved small prokaryotic aminopeptidases‐P clarify classification of M24B peptidases
Authors: Are Venkata N. , Kumar Ashwani , Goyal Venuka Durani , Gotad Siddhant S. , Ghosh Biplab , Gadre Rekha , Jamdar Sahayog N. , Makde Ravindra D. 
Published: December 2018

AbstractM24B peptidases cleaving Xaa‐Pro bond in dipeptides are prolidases whereas those cleaving this bond in longer peptides are aminopeptidases‐P. Bacteria have small aminopeptidases‐P (36‐39 kDa), which are diverged from canonical aminopeptidase‐P of Escherichia coli (50 kDa). Structure‐function studies of small aminopeptidases‐P are lacking. We report crystal structures of small aminopeptidases‐P from E. coli and Deinococcus radiodurans, and report substrate‐specificities of these proteins and their ortholog from Mycobacterium tuberculosis. These are aminopeptidases‐P, structurally close to small prolidases except for absence of dipeptide‐selectivity loop. We noticed absence of this loop and conserved arginine in canonical archaeal prolidase (Maher et al., Biochemistry. 43, 2004, 2771‐2783) and questioned its classification. Our enzymatic assays show that this enzyme is an aminopeptidase‐P. Further, our mutagenesis studies illuminate importance of DXRY sequence motif in bacterial small aminopeptidases‐P and suggest common evolutionary origin with human XPNPEP1/XPNPEP2. Our analyses reveal sequence/structural features distinguishing small aminopeptidases‐P from other M24B peptidases.
Mass defect filtering for suspect screening of halogenated environmental chemicals: A case study of chlorinated organophosphate flame retardants
Authors: Dolios Georgia , Patel Dhavalkumar , Arora Manish , Andra Syam S. 
Published: December 2018

RationaleOrganophosphate flame retardants (OPFRs) are a class of flame retardants widely found in environmental and biological matrices that have been extensively studied due to their adverse health effects in humans. OPFRs are loosely bound chemicals that can detach from treated products and be released into indoor and outdoor environments, where they have the potential to further undergo transformation and degradation processes, in particular the chlorinated OPFRs (Cl‐PFRs). Their detection remains a moving target for analysts, and traditional targeted mass spectrometry methods are suitable only for those compounds with authentic standards.MethodsMass defect filter (MDF) is a strategy to filter molecular features using thresholds applied to the mass defect value of a target ion or molecular feature of interest. We have developed an MDF strategy for the detection and tentative identification of twelve potential Cl‐PFR transformation products in a study mixture of six known Cl‐PFRs using MS/MS data acquired on a high‐resolution mass spectrometer. Most compounds in the Cl‐PFRs family share a ClO4P group as a core structure, of which modification results in a significant shift in the exact masses of the resulting compounds but show only a minimal shift in their mass defects. Subsequently, the MDF strategy was employed to tentatively identify Cl‐PFRs retrospectively in six human urine samples that had previously been analyzed.ResultsMDF in combination with product ion filtering for the characteristic [H2O3P]+ and [H4O4P]+ ions and neutral loss filtering for the characteristic CnH2n‐xClx group resulted in revealing suspects and homologues in the Cl‐PFRs family. Furthermore, the MDF of the product ions detected additional Cl‐PFR‐related compounds that differed significantly in the exact masses of both precursor and product ions but had minimal shift in the mass defects of product ions. The mass defect of one or more common product ions helped to detect a few Cl‐PFR analogs that had not been identified by MDF of the core structure precursor ion.ConclusionsMDF helped to detect some Cl‐PFRs present in lower concentrations, which went undetected without data filters. MDF also helped to detect chromatographic peaks for Cl‐PFR homologues that are likely structural analogs that resulted from impurities and/or derivatives and transformation products. The methodology was applied to demonstrate and tentatively detect known and suspect Cl‐PFRs in human urine samples retrospectively.
A comparison of satellite remote sensing data fusion methods to map peat swamp forest loss in Sumatra, Indonesia
Authors: Crowson Merry , Warren‐Thomas Eleanor , Hill Jane K. , Hariyadi Bambang , Agus Fahmuddin , Saad Asmadi , Hamer Keith C. , Hodgson Jenny A. , Kartika Winda D. , Lucey Jennifer , McClean Colin , Nurida Neneng Laela , Pratiwi Etty , Stringer Lindsay C. , Ward Caroline , Pettorelli Nathalie 
Published: December 2018

AbstractThe loss of huge areas of peat swamp forest in Southeast Asia and the resulting negative environmental effects, both local and global, have led to an increasing interest in peat restoration in the region. Satellite remote sensing offers the potential to provide up‐to‐date information on peat swamp forest loss across large areas, and support spatial explicit conservation and restoration planning. Fusion of optical and radar remote sensing data may be particularly valuable in this context, as most peat swamp forests are in areas with high cloud cover, which limits the use of optical data. Radar data can ‘see through’ cloud, but experience so far has shown that it doesn't discriminate well between certain types of land cover. Various approaches to fusion exist, but there is little information on how they compare. To assess this untapped potential, we compare three different classification methods with Sentinel‐1 and Sentinel‐2 images to map the remnant distribution of peat swamp forest in the area surrounding Sungai Buluh Protection Forest, Sumatra, Indonesia. Results show that data fusion increases overall accuracy in one of the three methods, compared to the use of optical data only. When data fusion was used with the pixel‐based classification using the original pixel values, overall accuracy increased by a small, but statistically significant amount. Data fusion was not beneficial in the case of object‐based classification or pixel‐based classification using principal components. This indicates optical data are still the main source of information for land cover mapping in the region. Based on our findings, we provide methodological recommendations to help those involved in peatland restoration capitalize on the potential of big data.
Biodegradable Thermogelling Polymers
Authors: Loh Xian Jun , Chee Pei Lin , Owh Cally 
Published: December 2018

AbstractThermogelling materials are envisioned as smart biomaterials with significant potential in the biomedical field. Their importance lies at the intersection between two highly medically relevant classes of materials: hydrogels and smart materials. They possess high water content and tunable properties of hydrogels and the ability to respond to external temperature variations with a simple, physical, and reversible sol‐to‐gel phase transition. Thermogels are proposed for many uses including drug delivery, gene delivery, and scaffolding for tissue engineering. Recent developments of biodegradable thermogelling polymers are reviewed, focusing on the properties of different thermogel systems and how those properties correlate with biomaterials behavior with the goal of providing safe and effective treatment for the treatment of diseases such as diabetes, glaucoma, and cancer.
Internal Coherence
Authors: Elleström Lars 
Published: December 2018

AbstractThis chapter offers a semiotically colored model for interrogating meaningfully interrelated events in narratives. Based on our minds’ inclination to perceive gestalts (i.e., intraconnected wholes), it is suggested that meaningful temporal interrelations among represented events be understood in terms of internal coherence. It is also put forward that the internal connections in narratives can be analyzed in terms of various sorts of contiguity, forming the basis for indices that bind together the numerous parts of narratives. Several theoretical perspectives and concepts, such as narrativization, are discussed. Finally, the results are demonstrated to be valid for the phenomenon of multimodal narration, which is central for understanding transmedial narration.
Decision level ensemble method for classifying multi-media data
Authors: Alyahyan Saleh , Wang Wenjia 
Published: December 2018

AbstractIn the digital era, the data, for a given analytical task, can be collected in different formats, such as text, images and audio etc. The data with multiple formats are called multimedia data. Integrating and fusing multimedia datasets has become a challenging task in machine learning and data mining.
In this paper, we present heterogeneous ensemble method that combines multi-media datasets at the decision level. Our method consists of several components, including extracting the features from multimedia datasets that are not represented by features, modelling independently on each of multimedia datasets, selecting models based on their accuracy and diversity and building the ensemble at the decision level. Hence our method is called decision level ensemble method (DLEM). The method is tested on multimedia data and compared with other heterogeneous ensemble based methods. The results show that the DLEM outperformed these methods significantly.
Interventions to improve healthcare workers’ hand hygiene compliance: A systematic review of systematic reviews
Authors: Price Lesley , MacDonald Jennifer , Gozdzielewska Lucyna , Howe Tracey , Flowers Paul , Shepherd Lesley , Watt Yvonne , Reilly Jacqui 
Published: December 2018

AbstractObjectiveTo synthesize the existing evidence base of systematic reviews of interventions to improve healthcare worker (HCW) hand hygiene compliance (HHC).MethodsPRISMA guidelines were followed, and 10 information sources were searched in September 2017, with no limits to language or date of publication, and papers were screened against inclusion criteria for relevance. Data were extracted and risk of bias was assessed.ResultsOverall, 19 systematic reviews (n=20 articles) were included. Only 1 article had a low risk of bias. Moreover, 15 systematic reviews showed positive effects of interventions on HCW HHC, whereas 3 reviews evaluating monitoring technology did not. Findings regarding whether multimodal rather than single interventions are preferable were inconclusive. Targeting social influence, attitude, self-efficacy, and intention were associated with greater effectiveness. No clear link emerged between how educational interventions were delivered and effectiveness.ConclusionsThis is the first systematic review of systematic reviews of interventions to improve HCW HHC. The evidence is sufficient to recommend the implementation of interventions to improve HCW HHC (except for monitoring technology), but it is insufficient to make specific recommendations regarding the content or how the content should be delivered. Future research should rigorously apply behavior change theory, and recommendations should be clearly described with respect to intervention content and how it is delivered. Such recommendations should be tested for longer terms using stronger study designs with clearly defined outcomes.