bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of AXIN1 and AXIN2 as targets of tankyrase inhibition in hepatocellular carcinoma cell lines
Authors: Wang Wenhui , Liu Pengyu , Lavrijsen Marla , Li Shan , Zhang Ruyi , Li Shanshan , van de Geer Wesley S. , van de Werken Harmen J. G. , Peppelenbosch Maikel P. , Smits Ron 
Published: April 2021

AbstractAXIN1 mutations are observed in 8–10% of hepatocellular carcinomas (HCCs) and originally were considered to support tumor growth by aberrantly enhancing β-catenin signaling. This view has however been challenged by reports showing neither a clear nuclear β-catenin accumulation nor clearly enhanced expression of β-catenin target genes. Here, using nine HCC lines, we show that AXIN1 mutation or siRNA mediated knockdown contributes to enhanced β-catenin signaling in all AXIN1-mutant and non-mutant lines, also confirmed by reduced signaling in AXIN1-repaired SNU449 cells. Both AXIN1 and AXIN2 work synergistically to control β-catenin signaling. While in the AXIN1-mutant lines, AXIN2 is solely responsible for keeping signaling in check, in the non-mutant lines both AXIN proteins contribute to β-catenin regulation to varying levels. The AXIN proteins have gained substantial interest in cancer research for a second reason. Their activity in the β-catenin destruction complex can be increased by tankyrase inhibitors, which thus may serve as a therapeutic option to reduce the growth of β-catenin-dependent cancers. At concentrations that inhibit tankyrase activity, some lines (e.g. HepG2, SNU398) were clearly affected in colony formation, but in most cases apparently independent from effects on β-catenin signaling. Overall, our analyses show that AXIN1 inactivation leads to enhanced β-catenin signaling in HCC cell lines, questioning the strong statements that have been made in this regard. Enhancing AXIN activity by tankyrase monotherapy provides however no effective treatment to affect their growth exclusively through reducing β-catenin signaling.
Baseline low-density lipoprotein cholesterol predicts the benefit of adding ezetimibe on statin in statin-naïve acute coronary syndrome
Authors: Im Jihaeng , Kawada-Watanabe Erisa , Yamaguchi Junichi , Arashi Hiroyuki , Otsuki Hisao , Matsui Yuko , Sekiguchi Haruki , Fujii Shinya , Mori Fumiaki , Ogawa Hiroshi , Hagiwara Nobuhisa 
Published: April 2021

AbstractWe aimed to evaluate the effect of baseline low-density lipoprotein cholesterol (LDL-C) on the outcomes of patients with the acute coronary syndrome (ACS) receiving pitavastatin monotherapy or the combination of pitavastatin + ezetimibe. In the HIJ-PROPER study, 1734 ACS patients with dyslipidemia were randomly assigned to receive pitavastatin or pitavastatin + ezetimibe therapy. Statin-naïve participants (n = 1429) were divided into two groups based on the median LDL-C level (131 mg/dL) at enrollment. The primary endpoint was a composite of all-cause death, non-fatal myocardial infarction, non-fatal stroke, unstable angina, and ischemia-driven coronary revascularization. The median follow-up was 3.2 years. In the < 131 mg/dL group (n = 686), LDL-C changes were − 34.0% and − 49.8% in the pitavastatin monotherapy and pitavastatin + ezetimibe-treated groups (P < 0.0001), respectively; in the ≥ 131 mg/dL group (n = 743), LDL-C changes were − 42.9% and − 56.4% (P < 0.0001, respectively. Kaplan–Meier analyses revealed that the primary endpoint was not significantly different between the treatment groups for the < 131 mg/dL group, however, it was significantly lower in patients treated with pitavastatin + ezetimibe in the ≥ 131 mg/dL group (Hazard ratio = 0.72, 95% confidence interval = 0.56–0.91, P = 0.007, P value for interaction = 0.012). Statin-naïve ACS patients with baseline LDL-C < 131 mg/dL did not clinically benefit from pitavastatin + ezetimibe, while patients with baseline LDL-C ≥ 131 mg/dL treated with pitavastatin + ezetimibe showed better clinical results than those treated with pitavastatin monotherapy.Clinical Trial Registration: Original HIJ PROPER study; URL: http://www.umin.ac.jp/ctr. Unique Identifier; UMIN000002742, registered as an International Standard Randomized Controlled Trial.
Asset management and maintenance programming for power distribution systems: A review
Authors: Mirhosseini Mina , Keynia Farshid 
Published: April 2021

AbstractSecurity and continuous proper functioning of the power system is a vital issue for supplying demands. Providing an acceptable level of reliability and necessity of that in all parts of the power system, from generation to distribution, has always been, and remains a major concern for network managers. Asset management and performing regular and routine maintenance activities has a considerable impact on ensuring system reliability, reducing expensive crashes, and preventing shutdowns. Up to now, much research has been done on the proper planning of maintenance in different parts of the network with a focus on cost savings, improved system performance and reliability, and reduced shutdowns. The purpose of this article is to review the findings of the study and to provide a more comprehensive view of the maintenance planning issue.
Goal oriented image quality assessment
Authors: S. Kiruthika , V. Masilamani 
Published: April 2021

AbstractThe area of image quality assessment(IQA) is an active research area in image processing and computer vision. All IQA algorithms reported in literature are attempting to quantify only the visual quality of the images/videos. An interesting question to be answered is that given a goal (task) and an image (with good visual quality), is the image good to achieve the goal by the best possible algorithm. In an attempt to spur the research community to answer this question, a new paradigm of IQA, called goal oriented IQA (GO‐IQA), is introduced. GO‐IQA is defined as given an image and a goal, predicting how good the image is to achieve that goal by the best possible algorithm. The need for GO‐IQA is that if GO‐IQA score is less, then any arbitrary algorithm attempting to achieve the goal will eventually fail. In this paper, considering segmentation as goal, a GO‐IQA algorithm is proposed to predict how good the image is to do accurate segmentation by the best possible segmentation algorithm. A support vector regression model has been trained with features related to image segmentation along with the accuracies of a class of well‐known image segmentation algorithms. In the process, we have obtained encouraging results in terms of the Pearson linear correlation coefficient and mean squared error. The predictions given by the proposed model have been validated with the scores of state of the art segmentation algorithm.
Measuring the electron temperature and identifying plasma detachment using machine learning and spectroscopy
Authors: Samuell C. M. , Mclean A. G. , Johnson C. A. , Glass F. , Jaervinen A. E. 
Published: April 2021

A machine learning approach has been implemented to measure the electron temperature directly from the emission spectra of a tokamak plasma. This approach utilized a neural network (NN) trained on a dataset of 1865 time slices from operation of the DIII-D tokamak using extreme ultraviolet/vacuum ultraviolet emission spectroscopy matched with high-accuracy divertor Thomson scattering measurements of the electron temperature, Te. This NN is shown to be particularly good at predicting Te at low temperatures (Te &lt; 10 eV) where the NN demonstrated a mean average error of less than 1 eV. Trained to detect plasma detachment in the tokamak divertor, a NN classifier was able to correctly identify detached states (Te &lt; 5 eV) with a 99% accuracy (an F1 score of 0.96) at an acquisition rate 10× faster than the Thomson scattering measurement. The performance of the model is understood by examining a set of 4800 theoretical spectra generated using collisional radiative modeling that was also used to predict the performance of a low-cost spectrometer viewing nitrogen emission in the visible wavelengths. These results provide a proof-of-principle that low-cost spectrometers leveraged with machine learning can be used to boost the performance of more expensive diagnostics on fusion devices and be used independently as a fast and accurate Te measurement and detachment classifier.
Effect of thickness on metal-to-semiconductor transition in 2-dimensional TiN thin films
Authors: Roy Manosi , Mucha Nikhil Reddy , Fialkova Svitlana , Kumar Dhananjay 
Published: April 2021

Titanium nitride thin films have been grown on c-plane sapphire substrates using a pulsed laser deposition technique in the thickness range of 6–45 nm. X-ray diffraction (XRD) analysis has demonstrated TiN (111) as the preferred orientation of growth on the sapphire substrates. The XRD measurements have also indicated that orientational alignment between the TiN and the sapphire improved with an increase in the TiN film thickness. A change in the resistivity behavior of the TiN thin films from metallic to semiconducting has been observed as the TiN film thickness is reduced below 15 nm. Analyzing and fitting of TiN films’ conductivity data have shown that while the Arrhenius law governs their conductivity in the temperature range of 300–350 K, conductivity values of the films follow the variable range hopping mechanism below 300 K.
Measuring voluntary and policy-induced social distancing behavior during the COVID-19 pandemic
Authors: Yan Youpei , Malik Amyn A. , Bayham Jude , Fenichel Eli P. , Couzens Chandra , Omer Saad B. 
Published: April 2021

Significance
Early in the US COVID-19 epidemic, Americans spent substantially more time at home to reduce cases. Disentangling voluntary from policy-induced behavioral changes is critical for governments grappling with relaxing or renewing restrictions. We estimate the number of additional reported cases that would have been needed to elicit a voluntary behavioral response equivalent to the behavioral response to policy. A substantial share of the observed behavioral response was voluntary. Stay-at-home orders increased the time people spent at home by replacing voluntary actions that likely would have emerged as cases rose. Our analysis is an initial step in answering the critical policy question as to whether fast forwarding the response provides sufficient public health benefits to justify the mandates.
Myristoylation alone is sufficient for PKA catalytic subunits to associate with the plasma membrane to regulate neuronal functions
Authors: Xiong Wei-Hong , Qin Maozhen , Zhong Haining 
Published: April 2021

Significance
Myristoylation is a major type of cotranslational lipid modification to many proteins that play important roles in numerous cell biology processes. Myristoylation serves diverse roles in protein–membrane association, protein structure, protein stability, and protein–protein interaction. With regard to protein–membrane association, it is believed that myristoylation alone does not confer sufficient energy to associate a protein to the membrane unless assisted by a second membrane-affinity motif. We find that the myristoylation on the PKA catalytic subunit (PKA-C) is sufficient to associate a fraction of PKA-C molecules to the plasma membrane in neuronal dendrites in a functionally significant manner without a canonical second motif. Our results remove a conceptual constraint for understanding myristoylated proteins and their function.
Outcomes of an Interprofessional SBIRT Training Program: Knowledge Attainment and Perceived Competence for Practice
Authors: Acquavita Shauna P. , Richardson George B. , Smith Rachel , Van Loon Ruth Anne , Brehm Bonnie , Kim Karissa , Diers Tiffiny 
Published: April 2021

Background One way to address substance misuse is to train health professional students in Screening, Brief Intervention, and Referral to Treatment (SBIRT), an early intervention strategy. This study evaluated a semester-long, 50-hour elective SBIRT training that blended online coursework with interprofessional experiences. Medicine, nursing, pharmacy, and social work students completed an interprofessional standardized patient experience and completed a minimum of two interprofessional SBIRT experiences at community agencies. Methods We analyzed longitudinal data from 197 students using structural equation modeling to examine gains in knowledge and perceived competence, as well as to test if background variables predicted 30-day application of SBIRT knowledge and skills, 30-day satisfaction’ 12-month frequencies of care for performing SBIRT; and number of SBIRT clients/patients served directly. Results Overall, student SBIRT knowledge and perceived competence both increased by more than a standard deviation during the course. Students who experienced larger gains in perceived competence rated the course significantly higher in terms of relevance and usefulness and, in turn, served significantly more SBIRT clients/patients during the following year. We did not find evidence that intra-individual growth in knowledge impacted the degree to which students ultimately applied SBIRT components. Finally, students who had more previous training and experience related to substance abuse ultimately reported greater application of SBIRT knowledge and skills. Interprofessional differences included: At baseline, medicine students had significantly lower substance abuse education knowledge as compared to the other disciplines. Pharmacy and social work students were more likely to have had previous experience with motivational interviewing. Baseline perceived competence in applying SBIRT was higher in social work and nursing. Upon completion, pharmacy and medicine students had lower satisfaction with the course. Conclusions These findings suggest that SBIRT courses can increase knowledge and perceived competence; moreover, student background characteristics, work settings, and experiences may have important effects on learning SBIRT.
Recent and Active Problematic Substance use among Primary Care Patients: Results from the Alcohol, Smoking, and Substance Involvement Screening Test in a Multisite Study
Authors: John William S. , Zhu He , Greenblatt Lawrence H. , Wu Li-Tzy 
Published: April 2021

Background Primary care settings provide salient opportunities for identifying patients with problematic substance use and addressing unmet treatment need. The aim of this study was to examine the extent and correlates of problematic substance use by substance-specific risk categories among primary care patients to inform screening/intervention efforts. Methods Data were analyzed from 2000 adult primary care patients aged ≥18 years (56% female) across 5 clinics in the eastern U.S. Participants completed the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST). Prevalence and ASSIST-defined risk-level of tobacco use, alcohol use, and nonmedical/illicit drug use was examined. Multinomial logistic regression models analyzed the demographic correlates of substance use risk-levels. Results Among the total sample, the prevalence of any past 3-month use was 53.9% for alcohol, 42.0% for tobacco, 24.2% for any illicit/Rx drug, and 5.3% for opioids; the prevalence of ASSIST-defined moderate/high-risk use was 45.1% for tobacco, 29.0% for any illicit/Rx drug, 14.2% for alcohol, and 9.1% for opioids. Differences in the extent and risk-levels of substance use by sex, race/ethnicity, and age group were observed. Adjusted logistic regression showed that male sex, white race, not being married, and having less education were associated with increased odds of moderate/high-risk use scores for each substance category; older ages (versus ages 18–25 years) were associated with increased odds of moderate/high-risk opioid use. Conclusions Intervention need for problematic substance use was prevalent in this sample. Providers should maintain awareness and screen for problematic substance use more consistently in identified high risk populations.
Covid 19 Impact Screening of Patients Undergoing Medication Treatment for Opioid use Disorder
Authors: Manzardo Ann M. , Sethi Roopa 
Published: April 2021

Background Populations with addiction are considered at-risk for both medical and financial effects of the COVID19 outbreak. Patients receiving medication treatment for opioid use disorder (MOUD) were screened to assess need, vulnerability factors and potential clinical impact of the pandemic for referral and allocation of resources. Methods A 31-item quality improvement survey of COVID19-related factors (e.g. engagement in social distancing, food and financial security) and clinical benchmarks of anxiety, craving, and treatment response was administered between March 24 and April 29, 2020. Anonymized data were compiled for study. Frequencies and means were evaluated for gender, age and financial effects on anxiety and craving ratings. Results A total of 200 ( N = 117 male; N = 80 female; N = 1 transgender) patients (age 42 ± 13 years) were screened. Medical risk factors known to predict severe COVID19 reactions reported in 33% of patients did not contribute significantly to distress. While 95% of patients reported stable food and housing, personal financial and employment instability reported in 40% of patients was associated with significantly increased anxiety and craving rating, particularly for women. Conclusions Financial ramifications of the COVID19 pandemic were the most salient concerns reported by patients engaged in MOUD in the early phases of the outbreak, particularly for women.
Experimental study of core and edge fluctuations by reflectometry on EAST tokamak
Authors: ZHOU Zhen , ZHANG Tao , WU Mingfu , YE Kaixuan , ZHONG Fubin , HUANG Jia , GENG Kangning , LIU Yukai , LI Gongshun , XIANG Haoming , WANG Yumin , WEN Fei , LIU Sanqiu 
Published: April 2021

Abstract
An eight-channel poloidal correlation reflectometer (PCR) with O-mode polarization has been installed in the EAST tokamak to measure the fluctuations from core to edge. The PCR launches eight different frequency microwaves (20.4, 24.8, 33, 40, 42.4, 48, 52.6, 57.2 GHz) into the plasma from the low field side and two poloidally separated antennae are used to receive the reflected waves. As a result, the diagnostic can measure fluctuations in eight (radial)× two (poloidal) spatial positions. The diagnostic has been applied to study the core and edge pedestal fluctuations during an inter-ELM phase in H-mode plasma. This inter-ELM phase can be divided into two stages. In the first stage, a low frequency (<50 kHz) broadband fluctuation dominates in the pedestal gradient region. In the second stage, this fluctuation is strongly suppressed and quasi-coherent fluctuations (QCFs) appear. The QCF’s amplitude increases with the pedestal density gradient, implying density gradient driven instabilities. But the core fluctuations inside the pedestal show no evident changes during the inter-ELM phase.
Simple and projective correspondence functors
Authors: Bouc Serge , Thévenaz Jacques 
Published: April 2021

A correspondence functor is a functor from the category of finite sets and correspondences to the category of

k
k

-modules, where

k
k

is a commutative ring. We determine exactly which simple correspondence functors are projective. We also determine which simple modules are projective for the algebra of all relations on a finite set. Moreover, we analyze the occurrence of such simple projective functors inside the correspondence functor

F
F

associated with a finite lattice and we deduce a direct sum decomposition of

F
F

.
Determination of Fucoxanthin in Bloom-Forming Macroalgae by HPLC–UV
Authors: Li Minlan , Feng Haozhan , Ouyang Xiaokun , Ling Junhong 
Published: April 2021

Abstract
Fucoxanthin is a carotenoid natural product with extensive biological activities and offers a variety of health benefits. Brown algae and diatoms are known producers of this compound as an important component of their light-harvesting complexes. Considering its important function in algal photosynthesis, we assume that the massive biomass from macroalgal blooms is potential bioresources of this compound. Accordingly, a high-performance liquid chromatography–ultra-violet (HPLC–UV) method was developed and validated for quantitation of fucoxanthin in bloom-forming macroalgal species from coastal waters of north China. The linear regression was acquired with r = 0.9991. The precisions were evaluated by intra- and inter-day tests, and the relative standard deviation (RSD) values were within the range of 0.59 and 2.30%, respectively. The recoveries for the method were observed over the range of 99.3–100.4% with RSD values &lt; 2.6%. Our results showed that fucoxanthin occurs in all the tested algae including red and green algal species, which are not generally considered as fucoxanthin producers. Application of HPLC–time-of-flight mass spectrometry for the qualitative analysis further confirmed the production of fucoxanthin in these species. The developed method provided an insight into the potential of the macroalgal biomass commercial production of fucoxanthin.
Rapid Determination of Metronidazole and 2-Hydroxymetronidazole in Murine Blood Plasma
Authors: Zemanová Nina , Anzenbacher Pavel , Hudcovic Tomáš , Anzenbacherová Eva 
Published: April 2021

Abstract
Metronidazole is a drug used to treat bacterial and protozoan infections. Nowadays, it is one of the most frequently prescribed drugs worldwide. The main aim of this paper is to present a rapid, reliable and simple high-performance liquid chromatography (HPLC) method to determine metronidazole along with its primary metabolite, 2-hydroxymetronidazole, in plasma or serum using paracetamol as an internal standard. A total of 100% methanol was used to denature plasma proteins. After centrifugation, the supernatant was evaporated under nitrogen flow. The samples were dissolved in the mobile phase and injected into a Li-Chrospher RP-18 column. A total of 10 mmol/L NaH2PO4: acetonitrile (90:10, v/v) solution with a flow rate of 1 mL/min was used as the mobile phase. Metronidazole and 2-hydroxymetronidazole were detected at two different wavelengths at 320 nm and 311 nm, respectively. The method is characterized by high precision (relative standard deviation % &lt; 6). The method was used for the determination of metronidazole and 2-hydroxymetronidazole in murine blood using small amounts of plasma (≤100 μL).