bluuebunny/crossref_metadata_2025_split huggingface dataset:
Endothelin receptor B enhances liver injury and pro-inflammatory responses by increasing G-protein-coupled receptor kinase-2 expression in primary biliary cholangitis
Authors: Xu Guoxin , Gong Yanping , Lu Fenying , Wang Bin , Yang Zaixing , Chen Long , Min Jingyu , Cheng Cuie , Jiang Tingwang 
Published: November 2022

AbstractSevere diseases like cirrhosis and liver failure can be developed from primary biliary cholangitis (PBC). Endothelin-2 (EDN2) and endothelin receptor B (EDNRB) are related to the pathogenesis of PBC. However, the roles of EDN2 and EDNRB in PBC-related liver injury and inflammation along with molecular mechanisms are poorly defined. In this study, histopathologic alterations of liver tissues were assessed through hematoxylin–eosin staining. Alanine transaminase (ALT), alkaline phosphatase (ALP), aspartate transaminase (AST), and γ-Glutamyltranspetidase (GGT) (4 liver function indexes) serum levels were detected with corresponding activity assay kits. Also, we determined the levels of M2 subtype anti-mitochondrial antibody (AMA-M2), interferon-gamma (IFN-γ), and tumor-necrosis factor alpha (TNFα) in serum with ELISA assay. Later, RT-qPCR assay was used to measure the expression of genes at mRNA levels, while western blotting and immunohistochemical techniques were used to detect protein levels of genes. Our results showed that the liver tissues of PBC patients and mice presented with severe hepatocyte injury and inflammatory cell infiltration as well as destruction of intrahepatic small bile ducts. ALP, AST, ALT, GGT, AMA-M2, IFN-γ, and TNF-α serum levels were higher in PBC patients and mice. Besides, EDN2 and EDNRB were highly expressed in serums and livers of PBC patients and mice. EDNRB potentiated PBC-related liver injury and pro-inflammatory responses, as evidenced by observation of serious liver pathologic injury and increased serum levels of ALP, AST, ALT, AMA-M2, IFN-γ, and TNF-α in PBC mice following EDNRB overexpression. EDNRB overexpression or activation via its agonist IRL-1620 TFA triggered liver injury and pro-inflammatory responses, increased GRK2 expression and induced NF-κB expression and activation in wild-type mice. EDNRB knockdown or inhibition by Bosentan alleviated liver damage and inflammation, reduced GRK2 expression, and inhibited NF-κB in PBC mice. These findings suggested EDNRB loss or inhibition weakened liver injury and pro-inflammatory responses by down-regulating GRK2 and inhibiting the NF-κB pathway in PBC mice.
A shared tissue transcriptome signature and pathways in psoriasis and ulcerative colitis
Authors: Xi Li , Garcet Sandra , Ye Zhan , Hung Kenneth , Hassan-Zahraee Mina , Kieras Elizabeth , Krueger James G. , Hyde Craig , Peeva Elena 
Published: November 2022

AbstractDespite multiple efficacious therapies in common between psoriasis (PS) and Ulcerative Colitis (UC), mechanisms underlying their common pathophysiology remain largely unclear. Here we sought to establish a link by evaluating expression differences and pathway alterations in diseased tissues. We identified two sets of differentially expressed genes (DEGs) between lesional and nonlesional tissues in meta-analyses of data collected from baseline samples in 3 UC and then 3 PS available clinical studies from Pfizer. A shared gene signature was defined by 190 DEGs common to both diseases. Commonly dysregulated pathways identified via enrichment analysis include interferon signaling, partly driven by genes IFI6, CXCL9, CXCL10 and CXCL11, which may attract chemotaxis of Th1 cells to inflammatory sites; IL-23 pathway (IL-23A, CCL20, PI3, CXCL1, LCN2); and Th17 pathway except IL-17A. Elevated expression of costimulatory molecules ICOS and CTLA4 suggests ongoing T-cell activation in both diseases. The clinical value of the shared signature is demonstrated by a gene set improvement score reflecting post-treatment molecular improvement for each disease. This is the first study using transcriptomic meta-analysis to define a tissue gene signature and pathways dysregulated in both PS and UC. These findings suggest immune mechanisms may initiate and sustain inflammation similarly in the two diseases.
Influence of urbanisation on phytodiversity and some soil properties in riverine wetlands of Bamenda municipality, Cameroon
Authors: Asongwe Godswill A. , Bame Irene B. , Ndam Lawrence M. , Orock Ayuk E. , Tellen Valantine A. , Bumtu Kamah P. , Tening Aaron S. 
Published: November 2022

AbstractIn urban areas, human activities result in the discharge of a variety of chemical substances into the environment. This affects soil quality, plant species diversity and human security. To suggest appropriate management strategies that ensure soil quality and human security amid urbanization, this study assessed the relationship between macrophyte diversity and some soil characteristics of wetlands that are adjacent to urban, peri-urban and rural areas in Bamenda Municipality, Cameroon. Plant communities were sampled for species composition and relative abundance, using the Braun-banquet method. Species richness was evaluated using Simpson’s diversity index. Twenty-one soil samples (0–25 cm depth) were randomly collected within the wetlands and analyzed for their physicochemical characteristics using standard methods. The hierarchical cluster analysis (HCA) was used to group the wetlands under managing units. The dominant species ranked in order of abundance in the rural wetland were Raphia farinifera > Ludwigia hexandra > Coix spp. > Leersia hexandra > Ehchinochloa paramidelis. The Peri-urban wetland dominant species stood at Commelina bengalensis > Leersia hexandra > Cyperus distance > Ehchinochloa pyramidalis. In the Urban segment, Pennisetum purpureum > Echinochloa pyramidalis > Tithonia diversifolia > Leersia hexandra were the abundant species. The Simpson index of diversity was 0.94 for the urban and 0.96 for the peri-urban and rural sites respectively. The soils were slightly acidic with pH KCl ranging from 4.87 to 5.41. From the coefficient of variability classes, Sand, pH-H2O, pH-KCl, and Na consistently varied slightly across the three sites. Two significant clusters (management units) representing a combination of urban, and peri-urban/rural were formed from the hierarchical dendrograms. The Mann–Whitney U test revealed a significant (P < 0.05) lower exchange acidity in the rural than the urban sites indicating contamination of the urban site, reducing its macrophyte diversity. Intensification and extension of urbanisation are gradually reducing the macrophyte diversity and also contaminating the soils of the wetlands of the Bamenda municipality in Cameroon, warranting monitoring. The chemical composition of soils in the urban cluster needs early remediation by encouraging the planting and monitoring of certain plants that can already take up the elements.
Machine learning of pair-contact process with diffusion
Authors: Shen Jianmin , Li Wei , Deng Shengfeng , Xu Dian , Chen Shiyang , Liu Feiyi 
Published: November 2022

AbstractThe pair-contact process with diffusion (PCPD), a generalized model of the ordinary pair-contact process (PCP) without diffusion, exhibits a continuous absorbing phase transition. Unlike the PCP, whose nature of phase transition is clearly classified into the directed percolation (DP) universality class, the model of PCPD has been controversially discussed since its infancy. To our best knowledge, there is so far no consensus on whether the phase transition of the PCPD falls into the unknown university classes or else conveys a new kind of non-equilibrium phase transition. In this paper, both unsupervised and supervised learning are employed to study the PCPD with scrutiny. Firstly, two unsupervised learning methods, principal component analysis (PCA) and autoencoder, are taken. Our results show that both methods can cluster the original configurations of the model and provide reasonable estimates of thresholds. Therefore, no matter whether the non-equilibrium lattice model is a random process of unitary (for instance the DP) or binary (for instance the PCP), or whether it contains the diffusion motion of particles, unsupervised learning can capture the essential, hidden information. Beyond that, supervised learning is also applied to learning the PCPD at different diffusion rates. We proposed a more accurate numerical method to determine the spatial correlation exponent $$\nu _{\perp }$$

ν
⊥

, which, to a large degree, avoids the uncertainty of data collapses through naked eyes.
Social media enables people-centric climate action in the hard-to-decarbonise building sector
Authors: Debnath Ramit , Bardhan Ronita , Shah Darshil U. , Mohaddes Kamiar , Ramage Michael H. , Alvarez R. Michael , Sovacool Benjamin K. 
Published: November 2022

AbstractThe building and construction sector accounts for around 39% of global carbon dioxide emissions and remains a hard-to-abate sector. We use a data-driven analysis of global high-level climate action on emissions reduction in the building sector using 256,717 English-language tweets across a 13-year time frame (2009–2021). Using natural language processing and network analysis, we show that public sentiments and emotions on social media are reactive to these climate policy actions. Between 2009–2012, discussions around green building-led emission reduction efforts were highly influential in shaping the online public perceptions of climate action. From 2013 to 2016, communication around low-carbon construction and energy efficiency significantly influenced the online narrative. More significant interactions on net-zero transition, climate tech, circular economy, mass timber housing and climate justice in 2017–2021 shaped the online climate action discourse. We find positive sentiments are more prominent and recurrent and comprise a larger share of the social media conversation. However, we also see a rise in negative sentiment by 30–40% following popular policy events like the IPCC report launches, the Paris Agreement and the EU Green Deal. With greater online engagement and information diffusion, social and environmental justice topics emerge in the online discourse. Continuing such shifts in online climate discourse is pivotal to a more just and people-centric transition in such hard-to-decarbonise sectors.
Multifrequency nonlinear model of magnetic material with artificial intelligence optimization
Authors: Pawłowski J. , Kutorasiński K. , Szewczyk M. 
Published: November 2022

AbstractMagnetic rings are extensively used in power products where they often operate in high frequency and high current conditions, such as for mitigation of excessive voltages in high-power switchgear equipment. We provide a general model of a magnetic ring that reproduces both frequency and current dependencies with the use of artificial intelligence (AI) optimization methods. The model has a form of a lumped element equivalent circuit that is suitable for power system transient studies. A previously published conventional (non-AI) model, which we take as a starting point, gives a good fit of parameters but uneven characteristics as a function of current, which pose numerical instabilities in transient simulations. We first enforce the Langevin function relationship to obtain smooth characteristics of parameters, which reduces the number of parameters and ensures their even characteristics, however, compromises fit quality. We then use AI metaheuristic optimization methods that give a perfect fit for the model in the whole range of frequency up to 100 MHz and current up to saturation, with smooth characteristics of its parameters. Additionally, for such fitted parameters, we show that it is feasible to find a frequency dependence for the magnetic saturation parameter of the Jiles-Atherton (JA) model, thus enabling frequency-dependent JA.
Regression analysis for predicting the elasticity of liquid crystal elastomers
Authors: Doi Hideo , Takahashi Kazuaki Z. , Yasuoka Haruka , Fukuda Jun-ichi , Aoyagi Takeshi 
Published: November 2022

AbstractIt is highly desirable but difficult to understand how microscopic molecular details influence the macroscopic material properties, especially for soft materials with complex molecular architectures. In this study we focus on liquid crystal elastomers (LCEs) and aim at identifying the design variables of their molecular architectures that govern their macroscopic deformations. We apply the regression analysis using machine learning (ML) to a database containing the results of coarse grained molecular dynamics simulations of LCEs with various molecular architectures. The predictive performance of a surrogate model generated by the regression analysis is also tested. The database contains design variables for LCE molecular architectures, system and simulation conditions, and stress–strain curves for each LCE molecular system. Regression analysis is applied using the stress–strain curves as objective variables and the other factors as explanatory variables. The results reveal several descriptors governing the stress–strain curves. To test the predictive performance of the surrogate model, stress–strain curves are predicted for LCE molecular architectures that were not used in the ML scheme. The predicted curves capture the characteristics of the results obtained from molecular dynamics simulations. Therefore, the ML scheme has great potential to accelerate LCE material exploration by detecting the key design variables in the molecular architecture and predicting the LCE deformations.
Vocal imprecision as a universal constraint on the structure of musical scales
Authors: Phillips Elizabeth , Brown Steven 
Published: November 2022

AbstractTheories of the origin of musical scales from the ancient Greeks to the present day have assumed that the intervals comprising scales are defined by specific mathematical ratios. Such theories are predicated on pre-tunable instruments, and yet the voice is almost certainly the original musical instrument. Therefore, the analysis of vocal scales offers a more naturalistic approach to understanding the origin of musical scales. In the present study, we conducted a large-scale computational analysis of vocal pitch-class properties and their implications for scale structure. We analyzed 418 field recordings of solo, unaccompanied songs from across 10 principal musical-style regions of the world. The results revealed a mean vocal pitch-class imprecision of approximately 1.5 semitones, and comparable results were obtained across all regions. These results suggest that vocal imprecision is universal and is mainly derived from the physiological limitations of the voice. Such vocal imprecision fundamentally constrains the formation of musical scale structure: it provides a lower limit on the spacing between adjacent scale tones and thus an upper limit on the number of scale tones that an octave can contain. We discuss these results in terms of an Interval Spacing model of the evolution of musical scales.
Lateral double magnetic tunnel junction device with orthogonal polarizer for high-performance magnetoresistive memory
Authors: Sin Stanislav , Oh Saeroonter 
Published: November 2022

AbstractMagnetic tunnel junction (MTJ)-based memory devices have larger switching delay and energy consumption, compared to cache or dynamic random access memory. In order to broaden the applications of the magnetoresistive random access memory, reducing the switching time and energy consumption of the MTJ is required. Here, a novel lateral double MTJ with an orthogonal polarizer is proposed. The proposed device consists of three ferromagnetic regions: the first pinned region (PR1) with perpendicular magnetic anisotropy (PMA), a free region (FR) with PMA, and the second pinned region (PR2) with in-plane magnetic anisotropy (IMA). PR1 and PR2 are placed on top of the oxide barrier, which separates them from the FR, comprising a lateral double MTJ structure. The current pulse through PR2 helps to perturb the magnetization of the FR. Since the angle between PR2 and FR is 90°, the initial torque increases significantly, decreasing switching delay by 4.02 times and energy-delay product by 7.23 times. It is also shown, that the area of the access transistor can be reduced by approximately 10%, while maintaining the same energy-delay product and reducing gate RC delay.
Measuring the effect of COVID-19-related night curfews in a bundled intervention within Germany
Authors: de Haas Samuel , Götz Georg , Heim Sven 
Published: November 2022

AbstractWe estimate the impact of local night curfews in Hesse, the fifth most populous federal state in Germany, on the growth of incidences of COVID-19 cases residing within the “second wave” of the pandemic. Thereby, we take advantage of the fact that all counties had the same measures in place with the only difference that some additionally had to implement night curfews due to state regulations. This allows us to identify the effect of night curfews as a salient part of a bundled intervention. In our case where different other measures are already in place, night curfews had at best a limited effect in slowing down the spread of the pandemic. The effect is not significantly different from zero.
Original study on mathematical models for analysis of cellulose water content from absorbance/wavenumber shifts in ATR FT-IR spectrum
Authors: Cichosz Stefan , Masek Anna , Dems-Rudnicka Katarzyna 
Published: November 2022

AbstractThe aim of this research was to evaluate the applicability of the attenuated total reflectance Fourier-transform infrared (ATR FT-IR) spectroscopy in the quantitative analysis of the moisture content in cellulose (from 0.5 to 11.0 wt.%). Innovatively, this work describes the variations in both absorbance and wavenumber of 16 absorption bands plotted as a function of cellulose water amount measured with Karl-Fischer titration. Different regression models were investigated (simple linear, semilogarithmic, power) and the adjusted coefficient of determination (R2) was given for each calculation. While model exhibited R2 > 90%, the standard error of calibration (SEC) was presented and an external validation has been performed. Regarding the absorbance-water content relationship, data recorded for sixteen peaks was successfully fitted with linear functions exhibiting R2 > 90%. The highest value of R2 = 98.7% and standard error of prediction SEP = 0.3wt.% have been assigned to the maximum from 3339 to 3327 cm−1 (–OH), proving ATR FT-IR usefulness in quantitative analysis.
Association of macular structure, function, and vessel density with foveal threshold in advanced glaucoma
Authors: Song Woo Keun , Kim Ko Eun , Yoon Joo Young , Lee Anna , Kook Michael S. 
Published: November 2022

AbstractIdentifying new biomarkers associated with central visual function impairment is important in advanced glaucoma patients. This retrospective cross-sectional study enrolled 154 eyes from 154 subjects, consisting of 86 patients with advanced open-angle glaucoma (mean deviation of 24-2 visual field [VF] tests < − 15 dB) and 68 healthy controls. Structure, function, and vessel density (VD) parameters were obtained using optical coherence tomography (OCT), 24-2 standard automated perimetry, and OCT angiography, respectively. The relationships of macular thickness, central 5° and 10° VF mean sensitivity (MS), and macular VD parameters with foveal threshold (FT), representing central visual function, were investigated using partial correlation analyses and linear regression analyses, with age adjustment. Superficial and deep layer macular VD, central 5° and 10° VF MS, and best corrected visual acuity (BCVA) correlated significantly with FT after age adjustment (P < 0.05). In multivariate linear regression analyses, FT associated significantly with BCVA (β = − 8.80, P < 0.001), central 5° MS (β = 0.30, P = 0.037), and deep-layer global parafoveal VD (β = 0.37, P = 0.037). Thus, deep-layer parafoveal VD is an independent predictor of FT and may be a potential biomarker for central visual function in advanced glaucoma.
Characterization of HCI-EC-23 a novel estrogen- and progesterone-responsive endometrial cancer cell line
Authors: Rush Craig M. , Blanchard Zannel , Polaski Jacob T. , Osborne Kyle S. , Osby Krystle , Vahrenkamp Jeffery M. , Yang Chieh-Hsiang , Lum David H. , Hagan Christy R. , Leslie Kimberly K. , Pufall Miles A. , Thiel Kristina W. , Gertz Jason 
Published: November 2022

AbstractMost endometrial cancers express the hormone receptor estrogen receptor alpha (ER) and are driven by excess estrogen signaling. However, evaluation of the estrogen response in endometrial cancer cells has been limited by the availability of hormonally responsive in vitro models, with one cell line, Ishikawa, being used in most studies. Here, we describe a novel, adherent endometrioid endometrial cancer (EEC) cell line model, HCI-EC-23. We show that HCI-EC-23 retains ER expression and that ER functionally responds to estrogen induction over a range of passages. We also demonstrate that this cell line retains paradoxical activation of ER by tamoxifen, which is also observed in Ishikawa and is consistent with clinical data. The mutational landscape shows that HCI-EC-23 is mutated at many of the commonly altered genes in EEC, has relatively few copy-number alterations, and is microsatellite instable high (MSI-high). In vitro proliferation of HCI-EC-23 is strongly reduced upon combination estrogen and progesterone treatment. HCI-EC-23 exhibits strong estrogen dependence for tumor growth in vivo and tumor size is reduced by combination estrogen and progesterone treatment. Molecular characterization of estrogen induction in HCI-EC-23 revealed hundreds of estrogen-responsive genes that significantly overlapped with those regulated in Ishikawa. Analysis of ER genome binding identified similar patterns in HCI-EC-23 and Ishikawa, although ER exhibited more bound sites in Ishikawa. This study demonstrates that HCI-EC-23 is an estrogen- and progesterone-responsive cell line model that can be used to study the hormonal aspects of endometrial cancer.
Correlation analysis of human upper arm parameters to oscillometric signal in automatic blood pressure measurement
Authors: Lee Bomi , Jeong Jae-Hak , Hong Junki , Park Yong-Hwa 
Published: November 2022

AbstractCardiovascular diseases are the leading cause of global deaths, making cardiovascular health monitoring important. Measuring blood pressure using an automatic sphygmomanometer is the most widely used method to monitor cardiovascular health due to its accessibility, convenience, and strong correlation with cardiovascular diseases. In this work, in order to estimate brachial artery diameter, stiffness, or thickness using an automatic sphygmomanometer, the correlation between upper arm parameters and the oscillometric signal was intensively investigated through analytical, numerical, and experimental approaches. The parametric studies commonly revealed that the inner radius of the brachial artery is the most influential parameter in determining the amplitude of the oscillometric signal. The experimental results of using a cardiovascular simulator (avirtual patient) combined with upper arm phantoms with various inner radii of the brachial artery showed a 6.5% change in the oscillometric signal amplitude with a 10% artery radius variation. It was concluded that the oscillometric signal can be used to evaluate brachial artery diameter. Based on the clinical relationship between brachial artery diameter and cardiovascular risk factors such as hypertension, diabetes, and obesity, this study showed and verified a novel method to monitor brachial artery diameter and hence, cardiovascular risks while measuring blood pressure.