bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Sequential Machine Learning Model for Identifying At-risk NASH by Combining Liver Stiffness Measurement and Protein Biomarkers
Authors: Li Guanlin , Wong Grace Lai-Hung , Yip Terry Cheuk-Fung , Tan Qingxiong , Lin Huapeng , Wilson Jonathan Matthew , Bowsman Lenden M , Haas Joseph V , Chan Anthony Wing-Hung , Leung Howard Ho-Wai , Zhang Xinrong , Tse Yee-Kit , Shu Sally She-Ting , Chim Angel Mei-Ling , Chan Henry Lik-Yuen , Yuen Pong Chi , Wong Vincent Wai-Sun , Duffin Kevin L. , Chen Yu 
Published: October 2022

Abstract
Background: A number of protein biomarkers have been proposed for the assessment of non-alcoholic fatty liver disease (NAFLD), but few have been externally validated and directly compared. The aim of this study was to compare the diagnostic accuracies of 13 protein biomarkers and develop a biomarker-based machine learning algorithm to predict at-risk non-alcoholic steatohepatitis (NASH) in patients with NAFLD.
Methods: 281 NAFLD patients had blood biomarker tested within one week before liver biopsy. We used three machine learning methods to select biomarkers in training (70%) and testing (30%) datasets, and then input selected features into a logistic regression model to predict at-risk NASH (NAFLD activity score ≥4 with at least 1 point in each component and fibrosis stage ≥2).
Results: Among 13 protein biomarkers tested, growth differentiation factor-15 (GDF-15) and Pro-C3 had the highest accuracy for at-risk NASH and advanced fibrosis (F3-4), respectively. All three machine learning models selected GDF-15, Pro-C3, and tissue inhibitor matrix metalloproteinase 1 as the best predictors of at-risk NASH, and the logistic regression FibNASH-3 model had an area under receiver-operating characteristics curve of 0.784. Using LSM ≥8kPa as the first step, the sequential model had a 79.2% positive predictive value for at-risk NASH. During a mean follow-up of 9.7 years, 3% and 16.7% of patients with low and high sequential model score developed hepatocellular carcinoma and cirrhotic complications, respectively (P<0.01).
Conclusions: The study provides a head-to-head comparison of 13 protein biomarkers. FibNASH-3 has the ability to accurately identify at-risk NASH in NAFLD patients and predict the development of liver-related events.
Preclinical evaluation of pentagamavunone-1 as monotherapy and combination therapy for pancreatic cancer in multiple xenograft models
Authors: Kamitani Naoki , Nakamae Ikuko , Yoneda-Kato Noriko , Kato Jun-ya , Sho Masayuki 
Published: October 2022

Abstract
We previously reported that pentagamavunone-1 (PGV-1) effectively inhibited cell proliferation in many types of human tumors, including pancreatic cancer, by inducing M phase (prometaphase) arrest, senescence, and apoptosis with few side effects. However, a detailed evaluation of the effects of PGV-1 on pancreatic cancer cells in an in vivo setting has not yet been conducted. The present study investigated the potential efficacy of PGV-1 as both monotherapy and combination therapy for pancreatic cancer using multiple xenograft mouse assays. A cell-line derived xenograft model (CDX-M) with pancreatic cancer cell line and a patient-derived xenograft mouse model (PDX-M) using resected pancreatic cancer samples without neoadjuvant chemotherapy were established in both heterotopic and orthotopic manners. PGV-1 effectively suppressed tumor formation at the heterotopic and orthotopic sites in CDX-M than in untreated mice. Combination therapy with PGV-1 and gemcitabine more effectively suppressed tumor formation than monotherapy with PGV-1 or gemcitabine when administered after tumor formation. Monotherapy with PGV-1 or gemcitabine less effectively suppressed tumor formation in PDX-M than in CDX-M, whereas combination therapy with PGV-1 and gemcitabine more effectively suppressed tumor formation. PGV-1 as monotherapy and combination therapy with gemcitabine effectively inhibited tumor formation and has potential as an anticancer candidate for pancreatic cancer.
CO2 capture-driven thermal and electric energy harvesting using amine-functionalized solvents with a poly(amidoamine) impregnated membrane
Authors: Kim Seonggon , Kim Minjae , Kang Yong Tae 
Published: October 2022

Abstract
The energy consumed for CO2 capture in processes that capture, store, and utilize carbon frequently approaches 80% of the total energy consumed, and its reduction is a major area of focus. Herein, a system that captures CO2 from flue gas to produce electricity is proposed. The exothermic reaction heat of amine-CO2 in the point-source CO2 capture process is harvested and converted into electricity using a thermoelectric (TE) device. The reaction heat of synthesized amine-functionalized mixtures (TEPA@SBA/MEA+PZ) is 52% higher compared with that obtained from the primary amine absorbent. The flue gas channel and solvent reservoir are separated using a membrane composed of tetraethylenepentamine-impregnated poly (ethylene glycol) dimethacrylate that selectively permeates CO2, to minimize heat loss due to mass transfer. The CO2 working capacity of TEPA@SBA/MEA+PZ is 6.6 mmol/g, which is defined as the capture capacity under steady-state conditions of 15 mol% CO2 and 85 mol% N2. Simultaneously, electricity can be harvested at a rate of 7.5 kJ/kg with a TE device composed of Bi2Te3. When put to industrial use, the proposed system can reduce the CO2 emission of power plants from 0.8 ton/MWh to 0.25 ton/MWh, while simultaneously generating an additional 0.6% of the total electricity production.
Computation of Randić and Sum-Connectivity Indices for H3BO3 Layer Structure’s Derivatives
Authors: Hussain Muhammad , Rehman Atiq ur , Inc Mustafa , Iqbal Muhammad Sajid , Muhammad Alizeh 
Published: October 2022

Abstract
Chemical compounds have variety of physicochemical, toxicological and pharmacological properties which predict their nature and how they will react. But the study of these properties requires Herculean and laborious experimentation so its alternative, topological indices were invented about 150 years ago. In this research paper, miscellaneous mathematical and computational methods are applied for the calculation of two versions of Randić index and two versions of sum-connectivity index for the subdivision n S(H3BO3), line graph L(H3BO3) and caged chain C(H3BO3) of H3BO3 layer structure.
Bright Semiconductor Single-Photon Sources Pumped by Heterogeneously Integrated Micropillar lasers with Electrical Injections
Authors: Li Xueshi , Liu Shunfa , Wei Yuming , Ma Jiantao , Song Changkun , Yu Ying , Su Rongbin , Geng Wei , Chen You-Ling , ni haiqiao , Liu Hanqing , Su Xiangbin , Niu Zhichuan , Liu Jin 
Published: October 2022

Abstract
The emerging hybrid integrated quantum photonics combines advantages of different functional components into a single chip to meet the stringent requirements for quantum information processing. Despite the tremendous progress in hybrid integrations of III-V quantum emitters with silicon-based photonic circuits and superconducting single-photon detectors, on-chip optical excitations of quantum emitters via miniaturized lasers towards single-photon sources (SPSs) with low power consumptions, small device footprints and excellent coherence properties is highly desirable yet illusive. In this work, we present realizations of bright semiconductor singe-photon sources heterogeneously integrated with on-chip electrically-injected microlasers. Different from previous one-by-one transfer printing technique implemented in hybrid quantum dot (QD) photonic devices, multiple deterministically coupled QD-circular Bragg Grating (CBG) SPSs were integrated with electrically-injected micropillar lasers at one time via a potentially scalable transfer printing process assisted by the wide-field photoluminescence (PL) imaging technique. Optically pumped by electrically-injected microlasers, pure single photons are generated with a high-brightness of a count rate of 3.8 M/s and an extraction efficiency of 21.5%. Such a high-brightness is due to the enhancement by the cavity mode of the CBG, which is confirmed by a Purcell factor of 2.5. Our work provides a powerful tool for advancing hybrid integrated quantum photonics in general and boosts the developments for realizing highly-compact, energy-efficient and coherent SPSs in particular.
Solvent-free synthesis and characterization of bimetallic UiO-66(Zr/Sn) heterogeneous catalyst for biodiesel production
Authors: Aresha Ahmed , Shaban Ebtehal A. , Sun Yinyong , El-Nahas Ahmed M. , Kashar Tahani I. 
Published: October 2022

Abstract
UiO-66(Zr) has been demonstrated to be an efficient heterogeneous catalyst in the esterification of oleic acid and methanol for biodiesel production. For the development of multi-functional sites in the structure of UiO-66(Zr), direct synthesis of UiO-66(Zr) with extra metal centers is a challenge. Based on our previous work of solvent-free synthesis, tin-doped UiO-66(Zr) was prepared under solvent-free conditions. The produced materials were analyzed by scanning electron microscopy (SEM), X-ray diffraction (XRD), N2 sorption technique, Fourier transform infrared (FT-IR) spectroscopy, X-ray photoelectron spectroscopy (XPS) and temperature-programmed desorption (TPD) analysis of NH3. The results indicate that UiO-66(Zr/Sn)-green with bimetal centers exhibits superior catalytic performance in the esterification of oleic acid. Additionally, the influence of tin integration on the structure and reactivity of UiO-66(Zr) significantly accelerates the esterification process at room temperature. Such catalyst could easily be recycled and reused.
Location prediction model of zero value insulator based on PNN
Authors: He Baina , Wu Shuo , Wang Lemiao , Zhang Jingru , Lin Xin , Meng Fantao , Liu Yang 
Published: October 2022

Abstract
Zero insulators directly reduce the electrical performance of insulator strings, affecting the safe and reliable operation of transmission lines. The grounding current of the insulator string contains the characteristic information of insulator electrical performance. Extracting the characteristic information of grounding current can realize the detection of zero value insulator, which is of great significance to ensure the safe operation of transmission lines. In this paper, the composite insulator used on ultra high voltage (UHV) lines is studied to analyze the influence of zero insulators on the electric field distribution. Furthermore, the corresponding characteristics of the zero insulators at different locations are extracted. The fitting relationship between the characteristic quantity and the zero-insulator position is analyzed. The effective characteristics of grounding current are selected as training sample to establish the zero-insulator position prediction model based on probabilistic neural network (PNN). The research result is meaningful for the detection of zero insulators.
Hydrochemical characteristics of the Ramsar-listed Koshi Tappu Wetland, Nepal
Authors: Neupane Shristi , Pant Ramesh Raj , Thapa Lal B , Shah Deep Narayan , Gautam Birendra , Adhikari Barsha , Khanal Barsha , Acharya Anueva , Adhikari Saroj 
Published: October 2022

Abstract
Nepal abounds a vast array of freshwater bodies, from sub-tropical lowlands to glacier-fed highlands with varying water quality. This study evaluated the spatial variations in water quality at the Koshi Tappu Wetland, the first Ramsar site of Nepal, located in the eastern Tarai region within the Koshi Tappu Wildlife Reserve. Nineteen water quality parameters were chosen and analyzed from twenty-one different sampling points within the wetland. Parameters including pH, EC, TDS, turbidity, and DO were analyzed on-site, whereas HCO3−, Cl−, NH4+, NO3−, SO42− PO43−, K+, TH, Ca2+, Mg2+, CaH, MgH, Na+, and Fe3+ were analyzed in the laboratory. Multivariate methods such as hierarchical agglomerative cluster analysis (CA) and principal component analysis (PCA), and geochemical indices such as Piper and mixing diagrams were applied to assess the spatial variation in water quality. Findings indicated Ca2+ as the principal cation and HCO3− as the principal anion regulating the hydrochemistry of the wetland. Based on CA, three spatial clusters were observed, which depicted variations in chemical composition with the PCA results highlighting the primary contamination sources and controlling factors of the sampling locations with 84.13% of the total variance. Findings from the PCA and ionic relationship analyses elucidated that the hydrochemistry of the Koshi Tappu wetland is mainly controlled by carbonate weathering processes with minor contribution of silicate weathering and anthropogenic activities.
Dutch Pharmacogenetics Working Group Guideline for the Gene-Drug Interaction of CYP2D6 and COMT with Atomoxetine, Methylphenidate and Clonidine
Authors: Nijenhuis Marga , Soree Bianca , Jama Wafa , de Boer-Veger Nienke , Buunk Anne Marie , Guchelaar Henk-Jan , Houwink Isa , Rongen Gerard , Schaik Ron van , Swen Jesse , Touw Daan , Weide Jan van der , Westrhenen Roos van , Deneer Vera , Risselada Arne 
Published: October 2022

Abstract
Pharmacogenetics (PGx) studies the effect of heritable genetic variation on drug response. Clinical adoption of PGx has remained limited, despite progress in the field. To promote implementation, the Dutch Pharmacogenetics Working Group (DPWG) develops evidence-based guidelines on how to optimize pharmacotherapy based on PGx test results. This guideline describes optimization of atomoxetine therapy based on genetic variation in the CYP2D6 gene. The CYP2D6 enzyme is involved in conversion of atomoxetine into the metabolite 4-hydroxyatomoxetine. With decreasing CYP2D6 enzyme activity, the exposure to atomoxetine and the risk of atomoxetine induced side effects increases. So, for patients with genetically absent CYP2D6 enzyme activity (CYP2D6 poor metabolisers), the DPWG recommends to start with the normal initial dose, bearing in mind that increasing this dose probably will not be required. In case of side effects and/or a late response, the DPWG recommends to reduce the dose and check for sustained effectiveness for both poor metabolisers and patients with genetically reduced CYP2D6 enzyme activity (CYP2D6 intermediate metabolisers). Extra vigilance for ineffectiveness is required in patients with genetically increased CYP2D6 enzyme activity (CYP2D6 ultra-rapid metabolisers). No interaction was found between the CYP2D6 and COMT genes and methylphenidate. In addition, no interaction was found between CYP2D6 and clonidine, confirming the suitability of clonidine as a possible alternative for atomoxetine in variant CYP2D6 metabolisers. The DPWG classifies CYP2D6 genotyping as being “potentially beneficial” for atomoxetine. CYP2D6 testing prior to treatment can be considered on an individual patient basis.
Synthesis, characterization and evaluation the performance of some novel pyridinone derivatives as corrosion inhibitors in some petroleum applications
Authors: Darwish Gehad A. , Ammar Yousry A. , Al-Sharbasy S. , Migahed M. A. 
Published: October 2022

Abstract
In this paper, newly synthesized pyridinone derivatives namely; 6-amino-2-oxo-1-(((1-phenyl-3-(p-tolyl)-1H-pyrazol-4-yl) methylene) amino)-4-(thiophen-2-yl)-1,2-dihydropyridine-3,5-dicarbo- nitrile (II) and 6-amino-1-(((2-chloro-7-ethoxyquinnolin-3-yl) methylene) amino)-2-oxo-4-(thiophen-2-yl)-1,2-dihydropyridine-3,5-dicarbonitrile (III) were synthesized in laboratory and their chemical structure were characterized via elemental analysis, FTIR, 1H- and 13C -NMR spectroscopic analysis tools. The performance of the newly synthesized pyridinone derivatives as anticorrosion for carbon steel alloys in 2 M HCl aggressive medium were carried out using weight loss measurement as chemical testing method, in addition to PDP and EIS as electrochemical measurements. The collected data revealed that these pyridinone derivatives operated as excellent anticorrosion for metallic structures. PDP results revealed that these pyridinone derivatives behave as mixed type inhibitors. The adsorption isotherm revealed that undertaken compounds obeyed Langmuir adsorption isotherm. EIS data confirmed that the values charge transfer resistance (Rct) was increased by increasing the concentration of the injected inhibitor molecules, while the electrochemical double layer (Cdl) was dramatically decreased. The work was supported by two surface analysis methods such as SEM and EDX. Finally, a suitable inhibition mechanism was assumed and discussed in details.
Functional connectivity discriminates epileptogenic states and predicts surgical outcome in children with drug resistant epilepsy
Authors: Rijal Sakar , Corona Ludovica , Perry M Scott , Tamilia Eleonora , Madsen Joseph , Stone Scellig , Bolton Jeffrey , Pearl Phillip L , Papadelis Christos 
Published: October 2022

Abstract
Normal brain functioning emerges from a complex interplay among regions forming networks. In epilepsy, these networks are disrupted causing seizures. Nodes of these networks are the target of epilepsy surgery. Here, we assess whether functional connectivity (FC) using intracranial electroencephalography (iEEG) can quantify epileptogenicity and predict surgical outcome in children with drug-resistant epilepsy (DRE). We computed Amplitude Envelope Correlation (AEC) and Phase Locking Value (PLV) for different states (i.e., interictal with no spikes, interictal with spikes, pre-ictal, ictal, and post-ictal) and for different frequency bands. We then computed each node’s strength (i.e., AEC or PLV at iEEG electrodes). We observed differences in nodal strength among the different states following a hierarchical epileptogenic organization: lower FC in interictal and pre-ictal states followed by higher FC values in ictal and post-ictal states (p < 0.05). We also observed higher nodal strength within resection for patients with good outcome (n = 22, Engel I), but not for poor outcome (n = 9, Engel II-IV), for all states (except ictal) and all bands (p < 0.05). Resection of hubs with high nodal strength was predictive of outcome (75–92% positive and 47–63% negative predictive values). Our findings suggest that FC can discriminate epileptogenic states and predict outcome in children with DRE.
Social distancing and mental health among pregnant women during the coronavirus pandemic
Authors: Harville Emily W. , Wood Moira E. , Sutton Elizabeth 
Published: October 2022

Abstract
Background
The effect of social distancing due to the COVID-19 pandemic on the mental health of pregnant women is of particular concern, given potential effects on physical health, family functioning, and child development.
Methods
Pregnant women were recruited for the “Implications of and Experiences Surrounding being Pregnant during the COVID-19 Pandemic” study at Woman’s Hospital in Baton Rouge, Louisiana. Participants enrolled at any point during their pregnancy and surveys were delivered weekly until the participant indicated that she had delivered her baby; a postpartum survey followed four weeks after delivery. This analysis includes 1037 participants with baseline, 596 with follow-up, and 302 with postpartum surveys. Questions on social distancing behaviors were asked at baseline and grouped based on whether they involved social distancing from work, friends and family, or public places. Symptoms of anxiety, stress, depression, and pregnancy-related anxiety were measured. Each type of social distancing was examined as a predictor of mental health using linear model with control for confounders.
Results
The study population was largely white, married, and educated. Women who were younger, Black, single, or had less education or income reported fewer social distancing behaviors. After controlling for covariates, anxiety was associated with social distancing from friends and family and public events, while perceived stress postpartum and pregnancy-related stress were not associated with social distancing. Associations were substantially diminished when controlled for baseline levels of anxiety symptoms.
Conclusions
Greater social distancing was associated with more mental health symptoms, but worse mental health, particularly anxiety, may also have contributed to greater social distancing behaviors.
Morphological Analysis of Blue Swimming Crab (Portunus pelagicus) Populations From Nine Fishing Grounds in the Philippines through Landmark-based Geometric Morphometrics
Authors: Abesamis Juan Gabriel T. , Tengco Maria Theresa T. , Santos Brian S. 
Published: October 2022

Abstract

The blue swimming crab (BSC) is one of the Philippines’ major fishery exports. It is a highly valued commodity, having an annual yield of 27,500 metric tons from 2010-2019. The discovery of a putative cryptic species of Portunus pelagicus in previous studies based on cytochrome c oxidase subunit 1 (COI) sequences complicates the assessment of its genetic diversity, which is of importance in designing effective and efficient management plans for this economically-important species. In this study, landmark-based geometric morphometrics was used to examine shape variation between two pre-identified clades of the blue swimming crab Portunus pelagicus. Samples were obtained from various fishing grounds in the Philippines. Shape differences between clades were significant based on multivariate analysis of variance. The distinction was not clear though due to overlaps observed in the canonical variate analysis plot and the considerable misclassification rate. This was attributed to possible effects of sexual dimorphism on morphological analysis of the clades. Although shape variation was observed, the protocols will have to be refined further to effectively diagnose the different clades based on morphology.
Improving the Performance of NSGA III using Latin Hypercube Sampling
Authors: Jain Shilpi , Dubey Kamlesh Kumar 
Published: October 2022

Abstract
Performance of multi-objective optimization techniques mainly depends on the convergence and the diversity of obtained Pareto-optimal solutions. A well-known non-dominated sorting genetic algorithm-III (NSGA-III) is a meta-heuristic multi-objective optimization technique which generates the Pareto-optimal solutions through various steps such as population initialization and genetic operations including the crossover, mutation, non-dominated sorting and selection on the basis of generated reference points. The core objective of presented paper is to integrate the Latin hypercube sampling (LHS) in NSGA-III as population initialization method for improving the performance of NSGA-III. LHS has the ability to produce a clear depiction of each input distribution, devoid of sampling artifacts. To reveal the applicability of LHS-NSGA-III algorithm, a construction case study is solved for time-cost-safety-quality trade-off optimization. 13 performance metrics were selected and measured to compare the convergence and diversity of Pareto-optimal solutions generated by original NSGA-III and LHS-NSGA-III. Results of the paper indicate that the LHS based NSGA-III provides better Pareto-optimal solutions than original NSGA-III.