bluuebunny/crossref_metadata_2025_split huggingface dataset:
Simultaneous quantification of serum monounsaturated and polyunsaturated phosphatidylcholines as potential biomarkers for diagnosing non-small cell lung cancer
Authors: Chen Yingrong , Ma Zhihong , Zhong Jing , Li Liqin , Min Lishan , Xu Limin , Li Hongwei , Zhang Jianbin , Wu Wei , Dai Licheng 
Published: May 2018

AbstractNon-small cell lung cancer (NSCLC) is one of the most common malignancies worldwide. In this study, we investigated Ultrahigh Performance Liquid Chromatography-Quadrupole Time-of-Flight Mass Spectrometry and Gas Chromatography Time-of-Flight/Mass Spectrometry-based non-targeted metabolomic profiles of serum samples obtained from early-stage NSCLC patients and healthy controls (HC). Metabolic pathways and the biological relevance of potential biomarkers were extensively studied to gain insights into dysregulated metabolism in NSCLC. The identified biomarker candidates were further externally validated via a targeted metabolomics analysis. The global metabolomics profiles could clearly distinguish NSCLC patients from HC. Phosphatidylcholine (PC) levels were found to be dysregulated in glycerophospholipid (GPL) metabolism, which was the top altered pathway in early-stage NSCLC. Compared with those in HC, significant increases in the levels of saturated and monounsaturated PCs such as PC (15:0/18:1), PC (18:0/16:0) and PC (18:0/20:1) were observed in NSCLC. Additionally, relative to those in HC, the levels of 9 polyunsaturated PCs, namely, PC (17:2/2:0), PC (18:4/3:0), and PC (15:0/18:2), and so on were significantly decreased in NSCLC patients. A panel of 12 altered PCs had good diagnostic performance in differentiating early-stage NSCLC patients from HC, and these PCs may thus be used as serum biomarkers for the early diagnosis of NSCLC.
CTmax is repeatable and doesn’t reduce growth in zebrafish
Authors: Morgan Rachael , Finnøen Mette H. , Jutfelt Fredrik 
Published: May 2018

AbstractCritical thermal maximum (CTmax) is a commonly and increasingly used measure of an animal’s upper thermal tolerance limit. However, it is unknown how consistent CTmax is within an individual, and how physiologically taxing such experiments are. We addressed this by estimating the repeatability of CTmax in zebrafish, and measured how growth and survival were affected by multiple trials. The repeatability of CTmax over four trials was 0.22 (0.07–0.43). However, CTmax increased from the first to the second trial, likely because of thermal acclimation triggered by the heat shock. After this initial acclimation response individuals became more consistent in their CTmax, reflected in a higher repeatability measure of 0.45 (0.28–0.65) for trials 2–4. We found a high innate thermal tolerance led to a lower acclimation response, whereas a high acclimation response was present in individuals that displayed a low initial CTmax. This could indicate that different strategies for thermal tolerance (i.e. plasticity vs. high innate tolerance) can co-exist in a population. Additionally, repeated CTmax trials had no effect on growth, and survival was high (99%). This validates the method and, combined with the relatively high repeatability, highlights the relevance of CTmax for continued use as a metric for acute thermal tolerance.
Early events during human coronavirus OC43 entry to the cell
Authors: Owczarek Katarzyna , Szczepanski Artur , Milewska Aleksandra , Baster Zbigniew , Rajfur Zenon , Sarna Michal , Pyrc Krzysztof 
Published: May 2018

AbstractThe Coronaviridae family clusters a number of large RNA viruses, which share several structural and functional features. However, members of this family recognize different cellular receptors and exploit different entry routes, what affects their species specificity and virulence. The aim of this study was to determine how human coronavirus OC43 enters the susceptible cell. Using confocal microscopy and molecular biology tools we visualized early events during infection. We found that the virus employs caveolin-1 dependent endocytosis for the entry and the scission of virus-containing vesicles from the cell surface is dynamin-dependent. Furthermore, the vesicle internalization process requires actin cytoskeleton rearrangements. With our research we strove to broaden the understanding of the infection process, which in future may be beneficial for the development of a potential therapeutics.
Genetic alterations analysis in prognostic stratified groups identified TP53 and ARID1A as poor clinical performance markers in intrahepatic cholangiocarcinoma
Authors: Simbolo Michele , Vicentini Caterina , Ruzzenente Andrea , Brunelli Matteo , Conci Simone , Fassan Matteo , Mafficini Andrea , Rusev Borislav , Corbo Vincenzo , Capelli Paola , Bria Emilio , Pedron Serena , Turri Giona , Lawlor Rita T. , Tortora Giampaolo , Bassi Claudio , Guglielmi Alfredo , Scarpa Aldo 
Published: May 2018

AbstractThe incidence and mortality rates of intrahepatic cholangiocarcinoma have been rising worldwide. Few patients present an early-stage disease that is amenable to curative surgery and after resection, high recurrence rates persist. To identify new independent marker related to aggressive behaviour, two prognostic groups of patient were selected and divided according to prognostic performance. All patients alive at 36 months were included in good prognostic performers, while all patients died due to disease within 36 months in poor prognostic performers. Using high-coverage target sequencing we analysed principal genetic alterations in two groups and compared results to clinical data. In the 33 cases included in poor prognosis group, TP53 was most mutated gene (p = 0.011) and exclusively present in these cases. Similarly, ARID1A was exclusive of this group (p = 0.024). TP53 and ARID1A are mutually exclusive in this study. Statistical analysis showed mutations in TP53 and ARID1A genes and amplification of MET gene as independent predictors of poor prognosis (TP53, p = 0.0031, ARID1A, p = 0.0007, MET, p = 0.0003 in Cox analysis). LOH in PTEN was also identified as marker of disease recurrence (p = 0.04) in univariate analysis. This work improves our understanding of aggressiveness related to this tumour type and has identified novel prognostic markers of clinical outcome.
Online videos indicate human and dog behaviour preceding dog bites and the context in which bites occur
Authors: Owczarczak-Garstecka Sara C. , Watkins Francine , Christley Rob , Westgarth Carri 
Published: May 2018

AbstractYouTube videos of dog bites present an unexplored opportunity to observe dog bites directly. We recorded the context of bites, bite severity, victim and dog characteristics for 143 videos and for 56 videos we coded human and dog behaviour before the bite. Perceived bite severity was derived from visual aspects of the bite. Associations between bite severity and victim, dog and context characteristics were analysed using a Bayesian hierarchical regression model. Human and dog behaviour before the bite were summarised with descriptive statistics. No significant differences in bite severity were observed between contexts. Only age of the victim was predictive of bite severity: adults were bitten more severely than infants and infants more severely than children. Non-neutral codes describing dog body posture and some displacement and appeasement behaviours increased approximately 20 seconds before the bite and humans made more tactile contacts with dogs 21 seconds before the bite. This analysis can help to improve understanding of context in which bites occur and improve bite prevention by highlighting observable human and dog behaviours occurring before the bite.
Perfect meta-absorber by using pod-like nanostructures with ultra-broadband, omnidirectional, and polarization-independent characteristics
Authors: Lin Yu-Sheng , Chen Wenjun 
Published: May 2018

AbstractThe on-chip perfect meta-absorber (PMA) is an important optical and thermal energy component in photovoltaics, thermal emitters, and energy harvesting applications. However, most reported PMAs rely on the complicated lithography techniques, which imposed a serious cost barrier on the development of practical applications, especially in the visible to near-infrared (NIR) wavelength range and at very large scales. Importantly, it is hard to realize PMA in the UV wavelength range by using current lithography techniques. In this article, we develop an ultra-broadband PMA by using natural lithography (NL) technique. The morphology of proposed PMA is randomly distributed pod-like nanostructures composed of a nanocomposite (Au/SiO2) covered a gold layer. It can be formed easily on Si substrate to function as an ultra-broadband, omnidirectional, and polarization-independent PMA by controlling the conditions of sputtering deposition and thermal annealing treatment. We experimentally realized an on-chip ultra-broadband PMA with almost 100% absorption spanned from UV-visible to NIR wavelength ranges. This cost-effective and high-efficiency approach would release the manufacturing barrier for previously reported PMAs and therefore open an avenue to the development of effectively energy harvesting, energy recycling, and heat liberation applications.
Big-data and machine learning to revamp computational toxicology and its use in risk assessment
Authors: Luechtefeld Thomas , Rowlands Craig , Hartung Thomas 
Published: May 2018

AbstractThe creation of large toxicological databases and advances in machine-learning techniques have empowered computational approaches in toxicology. Work with these large databases based on regulatory data has allowed reproducibility assessment of animal models, which highlight weaknesses in traditional in vivo methods. This should lower the bars for the introduction of new approaches and represents a benchmark that is achievable for any alternative method validated against these methods. Quantitative Structure Activity Relationships (QSAR) models for skin sensitization, eye irritation, and other human health hazards based on these big databases, however, also have made apparent some of the challenges facing computational modeling, including validation challenges, model interpretation issues, and model selection issues. A first implementation of machine learning-based predictions termed REACHacross achieved unprecedented sensitivities of &gt;80% with specificities &gt;70% in predicting the six most common acute and topical hazards covering about two thirds of the chemical universe. While this is awaiting formal validation, it demonstrates the new quality introduced by big data and modern data-mining technologies. The rapid increase in the diversity and number of computational models, as well as the data they are based on, create challenges and opportunities for the use of computational methods.
Probabilistic–possibilistic model for a parking lot in the smart distribution network expansion planning
Authors: Nasri Amirhossein , Abdollahi Amir , Rashidinejad Masoud , Hadi Amini M. 
Published: May 2018

Conventional distribution network departs to the smart grid. The parking lot will have an important role in the smart grid as a distributed generation. Due to the output power of parking lots is uncertain, More accurate modeling of parking lot output power is necessary for the future of distribution network studies such as Distribution Network Expansion Planning (DNEP). In this paper, a systematic method based on the Z ‐number concept is utilized to represent the uncertainty of Vehicle to Grid's (V2G's) presence. In order to investigate the impact of V2Gs uncertainty on the DNEP, we proposed a Probabilistic–Possibilistic DNEP in the presence of V2Gs referred to as P‐PDNEPV2G. If the V2Gs historical data is incomplete, the proposed structure can significantly consider the effects of V2G on the DNEP. In P‐PDNEPV2G, parking lots output power is described as a probabilistic–possibilistic variable by Z ‐number method. The optimization of P‐PDNEPV2G is executed by the Non‐Dominated Sorting Genetic Algorithm (NSGA‐II). A 24‐bus test system and the real 20 kV distribution network of Ghale‐Ganj city of Kerman province in Iran are used to demonstrate the effectiveness of the proposed methodology. Eventually, several analyses are conducted to investigate the impact of probabilistic–possibilistic V2G model on the DNEP problem.
Using duobinary with first‐ and second‐order optical equalisers for extending transmission distance of optical access networks
Authors: Dong‐Nhat Nguyen , Nguyen Lim , Malekmohammadi Amin 
Published: May 2018

This study presents the external modulation and direct detection of duobinary signal in optical access networks at 25 and 50 Gb/s with the use of first‐order optical equaliser at the transmitter output (pre‐equalisation) to compensate the waveform distortion induced by fibre dispersion. The first‐order optical equaliser is then replaced by second‐order optical equaliser to further improve the bit error rate (BER) performance and extend the maximum transmission distance by compensating the residual dispersion for the first time. The authors explain the enhancement in the BER by analysing the eye diagrams and optical spectra. The authors also investigate non‐return‐to‐zero signal with similar setup parameters for reference.
Leaves on trees: identifying halo stars with extreme gradient boosted trees
Authors: Veljanoski Jovan , Helmi Amina , Breddels Maarten , Posti Lorenzo 
Published: May 2018

Context. Extended stellar haloes are a natural by-product of the hierarchical formation of massive galaxies like the Milky Way. If merging is a non-negligible factor in the growth of our Galaxy, evidence of such events should be encoded in its stellar halo. The reliable identification of genuine halo stars is a challenging task, however.
Aims. With the advent of the Gaia space telescope, we are ushered into a new era of Galactic astronomy. The first Gaia data release contains the positions, parallaxes, and proper motions for over two million stars, mostly in the solar neighbourhood. The second Gaia data release will enlarge this sample to over 1.5 billion stars, the brightest ~ 5 million of which will have full phase-space information. Our aim for this paper is to develop a machine learning model for reliably identifying halo stars, even when their full phase-space information is not available.
Methods. We use the Gradient Boosted Trees algorithm to build a supervised halo star classifier. The classifier is trained on a sample of stars extracted from the Gaia Universe Model Snapshot, which is also convolved with the errors of the public TGAS data, which is a subset of Gaia DR1, as well as with the expected uncertainties for the upcoming Gaia DR2 catalogue. We also trained our classifier on a dataset resulting from the cross-match between the TGAS and RAVE catalogues, where the halo stars are labelled in an entirely model-independent way. We then use this model to identify halo stars in TGAS.
Results. When full phase-space information is available and for Gaia DR2-like uncertainties, our classifier is able to recover 90% of the halo stars with at most 30% distance errors, in a completely unseen test set and with negligible levels of contamination. When line-of-sight velocity is not available, we recover ~ 60% of such halo stars, with less than 10% contamination. When applied to the TGAS catalogue, our classifier detects 337 high confidence red giant branch halo stars. At first glance this number may seem small, however, it is consistent with the expectation from the models, given the uncertainties in the data. The large parallax errors are in fact the biggest limitation in our ability to identify a large number of halo stars in all the cases studied.
Dust modelling and a dynamical study of comet 41P/Tuttle–Giacobini–Kresak during its 2017 perihelion passage
Authors: Pozuelos F. J. , Jehin E. , Moulane Y. , Opitom C. , Manfroid J. , Benkhaldoun Z. , Gillon M. 
Published: May 2018

Context. Thanks to the Rosetta mission, our understanding of comets has greatly improved. A very good opportunity to apply this knowledge appeared in early 2017 with the appearance of the Jupiter family comet 41P/Tuttle–Giacobini–Kresak. The comet was only 0.15 au from the Earth as it passed through perihelion on April 12, 2017. We performed an observational campaign with the TRAPPIST telescopes that covered almost the entire period of time when the comet was active.Aims. In this work we present a comprehensive study of the evolution of the dust environment of 41P based on observational data from January to July, 2017. In addition, we performed numerical simulations to constrain its origin and dynamical nature.Methods. To model the observational data set we used a Monte Carlo dust tail model, which allowed us to derive the dust parameters that best describe its dust environment as a function of heliocentric distance: its dust production rate, the size distribution and ejection velocities of the dust particles, and its emission pattern. In order to study its dynamical evolution, we completed several experiments to evaluate the degree of stability of its orbit, its life time in its current region close to Earth, and its future behaviour.Results. From the dust analysis, we found that comet 41P is a dust-poor comet compared to other comets of the same family, with a complex emission pattern that shifted from full isotropic to anisotropic ejection sometime during February 24–March 14 in 2017, and then from anisotropic to full isotropic again between June 7 and 28. During the anisotropic period, the emission was controlled by two strongly active areas, where one was located in the southern and one in the northern hemisphere of the nucleus. The total dust mass loss is estimated to be ~7.5 × 108kg. From the dynamical simulations we estimate that ~3600 yr is the period of time during which 41P will remain in a similar orbit. Taking into account the estimated mass loss per orbit, after 3600 yr, the nucleus may lose about 30% of its mass. However, based on its observed dust-to-water mass ratio and its propensity to outbursts, the lifetime of this comet could be much shorter.
Analysis of an augmented fully-mixed formulation for the coupling of the Stokes and heat equations
Authors: Caucao Sergio , Gatica Gabriel N. , Oyarzúa Ricardo 
Published: May 2018

We introduce and analyse an augmented mixed variational formulation for the coupling of the Stokes and heat equations. More precisely, the underlying model consists of the Stokes equation suggested by the Oldroyd model for viscoelastic flow, coupled with the heat equation through a temperature-dependent viscosity of the fluid and a convective term. The original unknowns are the polymeric part of the extra-stress tensor, the velocity, the pressure, and the temperature of the fluid. In turn, for convenience of the analysis, the strain tensor, the vorticity, and an auxiliary symmetric tensor are introduced as further unknowns. This allows to join the polymeric and solvent viscosities in an adimensional viscosity, and to eliminate the polymeric part of the extra-stress tensor and the pressure from the system, which, together with the solvent part of the extra-stress tensor, are easily recovered later on through suitable postprocessing formulae. In this way, a fully mixed approach is applied, in which the heat flux vector is incorporated as an additional unknown as well. Furthermore, since the convective term in the heat equation forces both the velocity and the temperature to live in a smaller space than usual, we augment the variational formulation by using the constitutive and equilibrium equations, the relation defining the strain and vorticity tensors, and the Dirichlet boundary condition on the temperature. The resulting augmented scheme is then written equivalently as a fixed-point equation, so that the well-known Schauder and Banach theorems, combined with the Lax-Milgram theorem and certain regularity assumptions, are applied to prove the unique solvability of the continuous system. As for the associated Galerkin scheme, whose solvability is established similarly to the continuous case by using the Brouwer fixed-point and Lax–Milgram theorems, we employ Raviart–Thomas approximations of orderkfor the stress tensor and the heat flux vector, continuous piecewise polynomials of order ≤k+ 1 for velocity and temperature, and piecewise polynomials of order ≤ k for the strain tensor and the vorticity. Finally, we derive optimala priorierror estimates and provide several numerical results illustrating the good performance of the scheme and confirming the theoretical rates of convergence.
Influence of coronal mass ejections on parameters of high-speed solar wind: a case study
Authors: Shugay Yulia , Slemzin Vladimir , Rodkin Denis , Yermolaev Yuri , Veselovsky Igor 
Published: May 2018

We investigate the case of disagreement between predicted and observed in-situ parameters of the recurrent high-speed solar wind streams (HSSs) existing for Carrington rotation (CR) 2118 (December 2011) in comparison with CRs 2117 and 2119. The HSSs originated at the Sun from a recurrent polar coronal hole (CH) expanding to mid-latitudes, and its area in the central part of the solar disk increased with the rotation number. This part of the CH was responsible for the equatorial flank of the HSS directed to the Earth. The time and speed of arrival for this part of the HSS to the Earth were predicted by the hierarchical empirical model based on EUV-imaging and the Wang-Sheeley-Arge ENLIL semi-empirical replace model and compared with the parameters measured in-situ by model. The predicted parameters were compared with those measured in-situ. It was found, that for CR 2117 and CR 2119, the predicted HSS speed values agreed with the measured ones within the typical accuracy of ±100 km s−1. During CR 2118, the measured speed was on 217 km s−1 less than the value predicted in accordance with the increased area of the CH. We suppose that at CR 2118, the HSS overtook and interacted with complex ejecta formed from three merged coronal mass ejections (CMEs) with a mean speed about 400 km s−1. According to simulations of the Drag-based model, this complex ejecta might be created by several CMEs starting from the Sun in the period between 25 and 27 December 2011 and arriving to the Earth simultaneously with the HSS. Due to its higher density and magnetic field strength, the complex ejecta became an obstacle for the equatorial flank of the HSS and slowed it down. During CR 2117 and CR 2119, the CMEs appeared before the arrival of the HSSs, so the CMEs did not influence on the HSSs kinematics.
Updates on Translational Research on Prevention of Polyps and Colorectal Cancer
Authors: Stoffel Elena 
Published: May 2018

AbstractMorbidity and mortality from colorectal cancer (CRC) can be effectively reduced through early detection and prevention. To date, strategies for managing CRC risk have focused primarily on secondary prevention, through screening asymptomatic individuals for colorectal neoplasia. In the United States, implementation of screening among individuals age ≥50 has led to not only decreased CRC-related mortality but also reduced CRC incidence through colonoscopic removal of precancerous polyps. In contrast to screening's endpoint of early detection, the goal of primary prevention of CRC is to arrest and/or reverse colorectal carcinogenesis. Observational studies and randomized clinical trials continue to examine effects of specific pharmacologic agents (chemoprevention) and dietary interventions on development of advanced colorectal neoplasia. This review will present an overview of strategies for primary and secondary prevention of CRC, including endoscopic, pharmacologic, and dietary interventions.