bluuebunny/crossref_metadata_2025_split huggingface dataset:
Antifungal drugs: What brings the future?
Authors: Van Daele Ruth , Spriet Isabel , Wauters Joost , Maertens Johan , Mercier Toine , Van Hecke Sam , Brüggemann Roger 
Published: February 2019

AbstractThe high burden and growing prevalence of invasive fungal infections (IFIs), the toxicity and interactions associated with current antifungal drugs, as well as the increasing resistance, ask for the development of new antifungal drugs, preferably with a novel mode of action. Also, the availability of oral or once-weekly alternatives would enable ambulatory treatment resulting in an improved patient's comfort and therapy adherence. However, only one new azole and two new posaconazole-formulations were marketed over the last decade. This review focuses on the antifungal drugs in the pipeline undergoing clinical evaluation. First, the newest azole, isavuconazole, with its improved safety profile and reduction in DDIs, will be discussed. Moreover, there are two glucan synthase inhibitors (GSIs) in the antifungal pipeline: rezafungin (CD101), a long-acting echinocandin with an improved stability that enables once weekly administration, and SCY-078, an orally available GSI with efficacy against azole- and echinocandin resistant isolates. A new oral formulation of amphotericin B will also be presented. Moreover, the first representative of a new antifungal class, the orotomides, with a broad spectrum and no cross-resistance with current antifungal classes, will be discussed. Finally, an overview of other antifungals that are still in earlier clinical development phases, is provided.
Recognition of M-type stars in the unclassified spectra of LAMOST DR5 using a hash-learning method
Authors: Guo Y-X , Luo A-L , Zhang S , Du B , Wang Y-F , Chen J-J , Zuo F , Kong X , Hou Y-H 
Published: February 2019

ABSTRACT
Our study aims to recognize M-type stars which are classified as ‘UNKNOWN’ due to poor quality in the Large sky Area Multi-Object fiber Spectroscopic Telescope (LAMOST) DR5 V1. A binary nonlinear hashing algorithm based on Multi-Layer Pseudo-Inverse Learning (ML-PIL) is proposed to effectively learn spectral features for M-type-star detection, which can overcome the bad fitting problem of template matching, particularly for low S/N spectra. The key steps and the performance of the search scheme are presented. A positive data set is obtained by clustering the existing M-type spectra to train the ML-PIL networks. By employing this new method, we find 11 410 M-type spectra out of 642 178 ‘UNKNOWN’ spectra, and provide a supplemental catalogue. Both the supplemental objects and released M-type stars in DR5 V1 are composed of a whole M-type sample, which will be released in the official DR5 to the public in June 2019. All the M-type stars in the data set are classified as giants and dwarfs by two suggested separators: (1) a colour diagram of H versus J − K from 2MASS, (2) line indices CaOH versus CaH1, and the separation is validated with the Hertzsprung–Russell diagram (HRD) derived from Gaia DR2. The magnetic activities and kinematics of M dwarfs are also provided with the equivalent width (EW) of the Hα emission line and the astrometric data from Gaia DR2 respectively.
Patterns and Mechanisms of Diminishing Returns from Beneficial Mutations
Authors: Wei Xinzhu , Zhang Jianzhi 
Published: February 2019

AbstractDiminishing returns epistasis causes the benefit of the same advantageous mutation smaller in fitter genotypes and is frequently observed in experimental evolution. However, its occurrence in other contexts, environment dependence, and mechanistic basis are unclear. Here, we address these questions using 1,005 sequenced segregants generated from a yeast cross. Under each of 47 examined environments, 66–92% of tested polymorphisms exhibit diminishing returns epistasis. Surprisingly, improving environment quality also reduces the benefits of advantageous mutations even when fitness is controlled for, indicating the necessity to revise the global epistasis hypothesis. We propose that diminishing returns originates from the modular organization of life where the contribution of each functional module to fitness is determined jointly by the genotype and environment and has an upper limit, and demonstrate that our model predictions match empirical observations. These findings broaden the concept of diminishing returns epistasis, reveal its generality and potential cause, and have important evolutionary implications.
Tobacco Use and Subsequent Cessation Among Hospitalized Patients in Mumbai, India: A Longitudinal Study
Authors: Kruse Gina R , Thawal Vaibhav , Gupte Himanshu A , Chaudhuri Leni , Pradhan Sultan , Howard Sydney , Rigotti Nancy A 
Published: February 2019

Abstract

Introduction
Hospitalization is an important setting to address tobacco use. Little is known about post-discharge cessation and treatment use in low- and middle-income countries. Our objective was to assess tobacco use after hospital discharge among patients in Mumbai, India.

Methods
Longitudinal observational study of inpatients (≥15 years) admitted at one hospital from November 2015 to October 2016. Patients reporting current tobacco use were surveyed by telephone after discharge.

Results
Of 2894 inpatients approached, 2776 participated and 15.7% (N = 437) reported current tobacco use, including 5.3% (N = 147) smokers, 9.1% (N = 252) smokeless tobacco (SLT) users, and 1.4% (N = 38) dual users. Excluding dual users, SLT users, compared to smokers, were less likely to report a plan to quit after discharge (42.6% vs. 54.2%, p = .04), a past-year quit attempt (38.1% vs. 52.7%, p = .004), to agree that tobacco has harmed them (57.9% vs. 70.3%, p = .02) or caused their hospitalization (43.4% vs. 61.4%, p &lt; .001). After discharge, 77.6% of smokers and 78.6% of SLT users reported trying to quit (p = .81). Six-month continuous abstinence after discharge was reported by 27.2% of smokers and 24.6% of SLT users (p = .56). Nearly all relapses to tobacco use after discharge occurred within 30 days and did not differ by tobacco type (log-rank p = .08). Use of evidence-based cessation treatment was reported by 6.5% (N = 26).

Conclusions
Three-quarters of tobacco users in a Mumbai hospital attempted to quit after discharge. One-quarter reported continuous tobacco abstinence for 6 months despite little use of cessation treatment. Increasing post-discharge cessation support could further increase cessation rates and improve patient outcomes.

Implications
No prior study has measured the patterns of tobacco use and cessation among hospitalized tobacco users in India. Three-quarters of tobacco users admitted to a hospital in Mumbai attempted to quit after discharge, and one-quarter remained tobacco-free for 6 months, indicating that hospitalization may be an opportune time to offer a cessation intervention. Although smokers and SLT users differed in socioeconomic status, perceived risks and interest in quitting, they did not differ in their ability to stay abstinent after hospital discharge.
A guide to methods for estimating phago-mixotrophy in nanophytoplankton
Authors: Beisner Beatrix E , Grossart Hans-Peter , Gasol Josep M 
Published: February 2019

Abstract
Growing attention to phytoplankton mixotrophy as a trophic strategy has led to significant revisions of traditional pelagic food web models and ecosystem functioning. Although some empirical estimates of mixotrophy do exist, a much broader set of in situ measurements are required to (i) identify which organisms are acting as mixotrophs in real time and to (ii) assess the contribution of their heterotrophy to biogeochemical cycling. Estimates are needed through time and across space to evaluate which environmental conditions or habitats favour mixotrophy: conditions still largely unknown. We review methodologies currently available to plankton ecologists to undertake estimates of plankton mixotrophy, in particular nanophytoplankton phago-mixotrophy. Methods are based largely on fluorescent or isotopic tracers, but also take advantage of genomics to identify phylotypes and function. We also suggest novel methods on the cusp of use for phago-mixotrophy assessment, including single-cell measurements improving our capacity to estimate mixotrophic activity and rates in wild plankton communities down to the single-cell level. Future methods will benefit from advances in nanotechnology, micromanipulation and microscopy combined with stable isotope and genomic methodologies. Improved estimates of mixotrophy will enable more reliable models to predict changes in food web structure and biogeochemical flows in a rapidly changing world.
Antecedents and outcome of entrepreneurial identification: The moderating effect of role orientation
Authors: Zou Bo , Li Yanxia , Guo Jinyu , Guo Feng 
Published: February 2019

AbstractThis article focuses on the entrepreneurial identification (EI), through the perspectives of social identity theory and identity theory. Using an empirical method, we investigate factors that affect the formation of EI. Results show that academic entrepreneurs’ multiple identities (MI) and role conflict (RC) influence such type of formation. Moreover, we use role orientation (RO) as a moderating variable and find that, although RO of academic entrepreneurs can moderate the relationship between RC and EI, the effect of MI on EI cannot be moderated by ROin a significant way. We also discuss and validate the relationship between EI and academic entrepreneurial performance. These findings highlight the importance of certain factors in forming anEI, thus providing theoretical contributions of RO moderation in the relationship between RC and EI, as well as insights into the integration of social identity theory with identity theory.
Predicting queue wait time probabilities for multi-scale computing
Authors: Jancauskas Vytautas , Piontek Tomasz , Kopta Piotr , Bosak Bartosz 
Published: February 2019

We describe a method for queue wait time prediction in supercomputing clusters. It was designed for use as a part of multi-criteria brokering mechanisms for resource selection in a multi-site High Performance Computing environment. The aim is to incorporate the time jobs stay queued in the scheduling system into the selection criteria. Our method can also be used by the end users to estimate the time to completion of their computing jobs. It uses historical data about the particular system to make predictions. It returns a list of probability estimates of the form (
t

i

,
p

i

), where
p

i

is the probability that the job will start before time
t

i

. Times
t

i

can be chosen more or less freely when deploying the system. Compared to regression methods that only return a single number as a queue wait time estimate (usually without error bars) our prediction system provides more useful information. The probability estimates are calculated using the Bayes theorem with the naive assumption that the attributes describing the jobs are independent. They are further calibrated to make sure they are as accurate as possible, given available data. We describe our service and its REST API and the underlying methods in detail and provide empirical evidence in support of the method's efficacy.

This article is part of the theme issue ‘Multiscale modelling, simulation and computing: from the desktop to the exascale’.
Multiscale modelling, simulation and computing: from the desktop to the exascale
Authors: Hoekstra Alfons G. , Portegies Zwart Simon , Coveney Peter V. 
Published: February 2019

This short contribution introduces a theme issue dedicated to ‘Multiscale modelling, simulation and computing: from the desktop to the exascale’. It holds a collection of articles presenting cutting-edge research in generic multiscale modelling and multiscale computing, and applications thereof on high-performance computing systems. The special issue starts with a position paper to discuss the paradigm of multiscale computing in the face of the emerging exascale, followed by a review and critical assessment of existing multiscale computing environments. This theme issue provides a state-of-the-art account of generic multiscale computing, as well as exciting examples of applications of such concepts in domains ranging from astrophysics, via material science and fusion, to biomedical sciences.
This article is part of the theme issue ‘Multiscale modelling, simulation and computing: from the desktop to the exascale’.
I believe, therefore I am: Effects of self-control beliefs on behavioral and electrophysiological markers of inhibitory and emotional attention control
Authors: Vanlessen Naomi , Rigoni Davide , Schettino Antonio , Brass Marcel 
Published: February 2019

AbstractIn this study, a placebo/nocebo neuro-stimulation procedure was employed to investigate if expectations about self-control can influence self-control exertion. More specifically, we recorded behavioral and electrophysiological responses in an emotional antisaccade task in a between-subjects design, in which one group was led to believe that self-control was enhanced (MSC group) and the other that self-control was weakened (LSC group). This set-up allowed to investigate both response and emotional inhibition, as well as different stages at which control can be exerted during task performance, using Event-Related Potential (ERP) methods. Results showed that the bogus neuro-stimulation indeed installed the expectation of respectively better or worse self-control capacity, as well as the retrospective evaluation at the end of the experiment that the neuro-stimulation changed their self-control in that direction. Participants in the MSC compared to the LSC group showed higher accuracy in trials in which inhibitory control was necessary (antisaccade trials). ERP results showed no effect of the placebo/nocebo manipulation at the level of attention and inhibitory control. In sum, this study showed that high-order cognitive processes are not immune to the influence of expectations induced by a placebo/nocebo procedure, and shows that instructions alone can induce a placebo/nocebo effect in cognitive functioning.
Comparison of SVM and Spectral Embedding in Promoter Biobricks’ Categorizing and Clustering
Authors: Zou Shangjie 
Published: February 2019

AbstractBackgroundIn organisms’ genomes, promoters are short DNA sequences on the upstream of structural genes, with the function of controlling genes’ transcription. Promoters can be roughly divided into two classes: constitutive promoters and inducible promoters. Promoters with clear functional annotations are practical synthetic biology biobricks. Many statistical and machine learning methods have been introduced to predict the functions of candidate promoters. Spectral Eigenmap has been proved to be an effective clustering method to classify biobricks, while support vector machine (SVM) is a powerful machine learning algorithm, especially when dataset is small.MethodsThe two algorithms: spectral embedding and SVM are applied to the same dataset with 375 prokaryotic promoters. For spectral embedding, a Laplacian matrix is built with edit distance, followed by K-Means Clustering. The sequences are represented by numeric vector to serve as dataset for SVM trainning.ResultsSVM achieved a high predicting accuracy of 93.07% in 10-fold cross validation for classification of promoters’ transcriptional functions. Laplacian eigenmap (spectral embedding) based on editing distance may not be capable for extracting discriminative features for this task.AvailabilityCodes, datasets and some important matrices are available on github https://github.com/shangjieZou/Promoter-transcriptional-predictor/tree/source-code
2-Cl-C.OXT-A Stimulates Contraction through the Suppression of Phosphodiesterase Activity in Human Induced Pluripotent Stem Cell-derived Cardiac Organoids
Authors: Kitsuka Takahiro , Itoh Manabu , Amamoto Sojiro , Arai Ken-ichi , Oyama Junichi , Node Koichi , Toda Shuji , Morita Shigeki , Nishida Takahiro , Nakayama Koichi 
Published: February 2019

AbstractBackground2-Cl-C.OXT-A (COA-Cl) is a novel synthesized adenosine analog that activates S1P1 receptor (S1P1R) and combines with adenosine A1 receptor (A1R) in G proteins and was shown to enhance angiogenesis and improve the brain function in rat stroke models. However, the role of COA-Cl in hearts remains unclear. COA-Cl, which has a similar structure to xanthine derivatives, has the potential to suppress phosphodiesterase (PDE), which is an important factor involved in the beating of heart muscle.Methods and resultsCardiac organoids with fibroblasts, human induced pluripotent stem cell-derived cardiac myocytes (hiPSC-CMs), and hiPSC-derived endothelial cells (hiPSC-ECs) were cultured until they started beating. The beating and contraction of organoids were observed before and after the application of COA-Cl. COA-Cl significantly increased the beating rate and fractional area change in organoids. To elucidate the mechanism underlying these effects of COA-Cl on cardiac myocytes, pure hiPSC-CM spheroids were evaluated in the presence/absence of Suramin (antagonist of A1R). The effects of COA-Cl, SEW2871 (direct stimulator of S1P1R), two positive inotropes (Isoproterenol [ISO] and Forskolin [FSK]), and negative inotrope (Propranolol [PRP]) on spheroids were assessed based on the beating rates and cAMP levels. COA-Cl stimulated the beating rates about 1.5-fold compared with ISO and FSK, while PRP suppressed the beating rate. However, no marked changes were observed with SEW2871. COA-Cl, ISO, and FSK increased the cAMP level. In contrast, the level of cAMP did not change with PRP or SEW2871 treatment. The results were the same in the presence of Suramin as absence. Furthermore, an enzyme analysis showed that COA-Cl suppressed the PDE activity by half.ConclusionsCOA-Cl, which has neovascularization effects, suppressed PDE and increased the contraction of cardiac organoids, independent of S1P1R and A1R. These findings suggest that COA-Cl may be useful as an inotropic agent for promoting angiogenesis in the future.
Skin transcriptome reveals the Periodic changes in genes underlying hair follicle cycling in Cashmere goats
Authors: Liu Zhihong , Yang Feng , Zhao Meng , Mu Qing , Che Tianyu , Xie Yuchun , Ma Lina , Mi Lu , Su Rui , Zhang Yanjun , Wang Ruijun , Wang Zhiying , Yanhong Zhao , Li Jinquan 
Published: February 2019

AbstractCashmere goats, as an important part of animal husbandry production, make outstanding contributions to animal fiber industry. In recent years, a great deal of research has been done on the molecular regulation mechanism of hair follicle cycle growth. However, there are few reports on the molecular regulation mechanisms of secondary hair follicle growth cycle in cashmere goats. In this study, we used transcriptome sequencing technique to sequence the skin of Inner Mongolia cashmere goats in different periods, Analyze the variation and difference of genes in the whole hair follicle cycle. And then, we verified the regulation mechanism of cashmere goat secondary hair follicle growth cycle by fluorescence quantitative PCR. As the result shows: The results of tissue section showed that the growth cycle of cashmere hair could be divided into three distinct periods: growth period (March-September), regression period (September-December) and resting period (December-March). The results of differential gene analysis showed that March was considered the beginning of the cycle, and the difference of gene expression was the most significant. Cluster analysis of gene expression in the whole growth cycle further supported the key nodes of the three periods of villus growth, and the differential gene expression of keratin corresponding to the villus growth cycle further supported the results of tissue slices. Quantitative fluorescence analysis showed that KAP3.1, KRTAP 8-1 and KRTAP 24-1 genes had close positive correlation with the growth cycle of cashmere, and their regulation was consistent with the growth cycle of cashmere. However, there was a sequence of expression time, indicating that the results of cycle regulation made the growth of cashmere change.
On the importance of service performance and customer satisfaction in third-party logistics selection
Authors: Asian Sobhan , Pool Javad Khazaei , Nazarpour Ali , Tabaeeian Reihaneh Alsadat 
Published: February 2019

Purpose
Developing strategic relationships with third-party logistics (3PL) providers has long been one of the key challenges in automotive supply chains. The purpose of this paper is to propose a new approach for evaluation and indexing 3PL providers using the Kano model.

Design/methodology/approach
The statistical population used in this research comprises managers from the Iranian automotive industry. The Kano evaluation approach is used to analyze the data collected and to classify the criteria used in selection of the preferred 3PL providers.

Findings
The results suggest that the proposed framework, based on the Kano classification, can be a powerful tool for the automotive industry in evaluating 3PL providers. Moreover, the analyses indicate that 3PL providers need to improve their service offering in aspects that are to be found in the Kano model’s requirements, namely, must-be, one-dimensional and attractive.

Originality/value
This study contributes to the supply chain management literature by being the first to classify selection indices of 3PL providers in the automotive industry using the Kano model.
Effects of wave breaking on the oceanic boundary layer in hurricane conditions
Authors: Wan Zhanhong , Lü Xiuyang , Jiawang Chen , Song Tianyu , Luo Shizhu 
Published: February 2019

Purpose
Wave breaking significantly affects the exchange process between ocean and atmosphere. This paper aims to simulate the upper ocean dynamics under the influence of wave breaking, which may help to figure out the transport of energy by these breakers.

Design/methodology/approach
The authors use a breaker-LES model to simulate the oceanic boundary layer in hurricane conditions, in which breakers become the main source of momentum and energy instead of traditional wind stress.

Findings
The mean horizontal velocities and energy increase rapidly with wind speed, reflecting that input from atmosphere dominates the coherent structure in the upper ocean. The penetration ability of a breaker limits its effective depth and thus the total turbulent kinetic energy (TKE) decreases sharply near the surface. Langmuir circulation is the main source of TKE in deeper water. The authors compared the dissipation rate (e) in the simulations with two estimates and found that the model tends to the scaling of ε∼z–3.4 at extreme wind speeds.

Originality/value
The probability distribution of breakers is also discussed based on the balance between the input from atmosphere and output by wave breaking. The authors considered the contribution of micro-scale breakers and revaluated the probability density function. The results show stability in hurricane conditions.