bluuebunny/crossref_metadata_2025_split huggingface dataset:
Relationship between CDX2 rs11568820 and EcoRV rs4516035 polymorphisms on the vitamin D receptor gene with susceptibility to different SARS‐CoV‐2 variants
Authors: Al‐Mohammedawi Abed K. K. , Anvari Enayat , Fateh Abolfazl 
Published: June 2023

AbstractSeveral studies have revealed that vitamin D deficiency is linked to an increased risk of developing coronavirus disease 19 (COVID‐19). In individuals with the severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infections, vitamin D receptor activation is required to decrease acute respiratory distress syndrome. The purpose of this study was to examine the genotypic distribution and allelic frequencies of CDX2 rs11568820 and EcoRV rs4516035 polymorphisms in COVID‐19 patients with various SARS‐CoV‐2 variants. For genotyping of CDX2 rs11568820 and EcoRV rs4516035 polymorphisms, we used the polymerase chain reaction‐restriction fragment length polymorphism technique in 1734 and 1450 recovered and deceased patients, respectively. The results indicated the rate of COVID‐19 mortality was associated with CDX2 rs11568820 AA and GA genotypes in the Delta variant and with CDX2 rs11568820 AA in the Omicron BA.5 variant, while no association was shown in the Alpha variant. Therefore, the rate of COVID‐19 mortality was associated with EcoRV rs4516035 TC and CC genotypes in the Delta variant, while no association was shown in the Alpha and Omicron BA.5 variants. According to our analysis, the T‐G haplotype was more common in all SARS‐CoV‐2 variants. The C‐A haplotype was associated with COVID‐19 mortality in the Delta and Omicron BA.5 variants, and the T‐A haplotype was related to the Alpha variant. In conclusion, the genotype frequencies of the CDX2 rs11568820 and EcoRV rs4516035 polymorphisms between SARS‐CoV‐2 variants were significantly different between the deceased patients and recovered patients. However, more studies should be done to confirm the results.
Maximizing winter wheat yield through planting date and seeding rate management
Authors: Copeland J. Patrick , Pennington Dennis , Singh Maninder P. 
Published: June 2023

AbstractPlanting date and seeding rate are two of the most basic and important factors in determining yield potential in winter wheat (Triticum aestivum L.) due to their impact on stand establishment. Timely planting of winter wheat (within a few days after the Hessian fly free date) ensures sufficient time for fall growth and tillering, which are critical for maximizing yield, while adequate seeding rate is necessary to optimize the number of heads per unit area. Field experiments were conducted in Mason, MI during three growing seasons (2020–2022) utilizing five planting dates, ranging from mid‐September to mid‐November, and five seeding rates ranging from 0.8 to 2.4 million seeds acre−1. There was no interaction between planting date and seeding rate in determining yield. Yields declined by 22–48% from the earliest to the latest planting dates in response to a 33–47% reduction in the number of heads acre−1. Seeding rate did not significantly impact yield except at low seeding rates under delayed planting. Maximum yield was achieved with a seeding rate of 0.93, 1.37, 1.47, 1.54, and 1.85 million seeds acre−1 during the mid‐September, late September, mid‐October, late October, and mid‐November plantings, respectively. Overall, results demonstrated that timely planting of wheat is critical for maximizing yield, with significant yield reductions occurring when planting is delayed, regardless of the seeding rate used. Furthermore, while low seeding rates may be used within the optimal planting window without yield penalty, seeding rates should be progressively increased as planting is delayed to diminish yield loss.
Organoselenium Compounds: Chemistry and Applications in Organic Synthesis
Authors: Sonego Juan M. , de Diego Sheila I. , Szajnman Sergio H. , Gallo‐Rodriguez Carola , Rodriguez Juan B. 
Published: June 2023

AbstractSelenium, originally described as a toxin, turns out to be a crucial trace element for life that appears as selenocysteine and its dimer, selenocystine. From the point of view of drug developments, selenium‐containing drugs are isosteres of sulfur and oxygen with the advantage that the presence of the selenium atom confers antioxidant properties and high lipophilicity, which would increase cell membrane permeation leading to better oral bioavailability. In this article, we have focused on the relevant features of the selenium atom, above all, the corresponding synthetic approaches to access a variety of organoselenium molecules along with the proposed reaction mechanisms. The preparation and biological properties of selenosugars, including selenoglycosides, selenonucleosides, selenopeptides, and other selenium‐containing compounds will be treated. We have attempted to condense the most important aspects and interesting examples of the chemistry of selenium into a single article.
Synthesis and Biological Activity of 2‐Benzo[b]thienyl and 2‐Bithienyl Amidino‐Substituted Benzothiazole and Benzimidazole Derivatives
Authors: Racané Livio , Zlatić Katarina , Cindrić Maja , Mehić Emina , Karminski‐Zamola Grace , Taylor Martin C. , Kelly John M. , Malić Silvana Raić , Stojković Marijana Radić , Kralj Marijeta , Hranjec Marijana 
Published: June 2023

AbstractNovel benzo[b]thienyl‐ and 2,2′‐bithienyl‐derived benzothiazoles and benzimidazoles were synthesized to study their antiproliferative and antitrypanosomal activities in vitro. Specifically, we assessed the impact that amidine group substitutions and the type of thiophene backbone have on biological activity. In general, the benzothiazole derivatives were more active than their benzimidazole analogs as both antiproliferative and antitrypanosomal agents. The 2,2′‐bithienyl‐substituted benzothiazoles with unsubstituted and 2‐imidazolinyl amidine showed the most potent antitrypanosomal activity, and the greatest selectivity was observed for the benzimidazole derivatives bearing isopropyl, unsubstituted and 2‐imidazolinyl amidine. The 2,2′‐bithiophene derivatives showed most selective antiproliferative activity. Whereas the all 2,2′‐bithienyl‐substituted benzothiazoles were selectively active against lung carcinoma, the benzimidazoles were selective against cervical carcinoma cells. The compounds with an unsubstituted amidine group also produced strong antiproliferative effects. The more pronounced antiproliferative activity of the benzothiazole derivatives was attributed to different cytotoxicity mechanisms. Cell cycle analysis, and DNA binding experiments provide evidence that the benzimidazoles target DNA, whereas the benzothiazoles have a different cellular target because they are localized in the cytoplasm and do not interact with DNA.
Giant component for the supercritical level‐set percolation of the Gaussian free field on regular expander graphs
Authors: Černý Jiří 
Published: June 2023

AbstractWe consider the zero‐average Gaussian free field on a certain class of finite d‐regular graphs for fixed . This class includes d‐regular expanders of large girth and typical realisations of random d‐regular graphs. We show that the level set of the zero‐average Gaussian free field above level h has a giant component in the whole supercritical phase, that is for all , with probability tending to one as the size of the graphs tends to infinity. In addition, we show that this component is unique. This significantly improves the result of [4], where it was shown that a linear fraction of vertices is in mesoscopic components if , and together with the description of the subcritical phase from [4] establishes a fully‐fledged percolation phase transition for the model.
Experimental and Theoretical Studies of the HeICl Van der Waals Complexes in the Valence and Ion‐pair States
Authors: Lukashov Sergei S. , Martynov Ivan I. , Poretsky Sergey A. , Pravilov Anatoly M. , Sivokhina Mariia M. 
Published: June 2023

AbstractThe article presents results of experimental and theoretical analysis of the T‐shaped and linear HeICl van der Waals complexes in the valence A1 and ion‐pair β1 states as well as the HeICl(A1,vA,nA←X0+,vX=0,nx and β1,vβ,nβ←A1,vA,nA) optical transitions (ni are quantum numbers of the vdW) modes). The HeICl(β1,vβ,nβ)→He+ICl(E0+,
, β1) decay are also studied. Luminescence spectra of the HeICl(β1,vβ=0–3,nβ) complex electronic (ICl(E0+,vE,
) and vibrational ICl(β1,vβ) predissociation products are measured, and branching ratios of decay channels are determined. To construct potential energy surfaces for the HeICl(A1, β1) states, we utilized the intermolecular diatomic‐in‐molecule perturbation theory first order method. Experimental and calculated spectroscopic characteristics of the A1 and β1 states agree well. Comparison of the experimental and calculated pump‐probe, action and excitation spectra shows that the calculated spectra describe the experimental spectra adequately.
Machine Learning Guided Cobalt‐doping Strategy for Solid‐state NASICON Electrolytes
Authors: Zhou Pengfei , Zhao Zirui , Sun Kaitong , Zhao Qian , Xiao Fangyuan , Fu Ying , Li Hai‐Feng 
Published: June 2023

AbstractThe solid‐state battery (SSB) is a promising direction to address the inherent safety problems in commercial batteries and energy storage systems. However, the development of SSBs is still hider of the low ionic conductivity of solid‐state electrolytes. Based on a machine learning (ML) method, a cobalt‐doping strategy was developed for the Na3.2Zr2Si2.2P0.8O12 (NASICON) compound by training on NASICON‐type solid electrolyte data. The cobalt‐doping strategy efficiently improves the NASICONs’ ionic conductivity to ~2.63 mS/cm with low activation energy at ~0.245 eV. The grain‐boundary ionic conductivity reaches ~11.00 mS/cm without extra densification of the pellet. The NASICON's structures were studied by the Rietveld and the bond‐valence methods. The calculations and observed structural transitions confirm that the cobalt‐doping strategy promotes the structural transition and adjusts the structure to a better performance state. The doping strategy predicted by the ML model is consistent with our experimental results, providing very useful guidance for improving ionic conductivity of NASICON electrolytes.
Toward reliable fusion object detection based on dilated pyramid and semantic attention
Authors: Chang Rong , Gao Shan , Li Hao , Zhao Shan , Yang Yang 
Published: June 2023

AbstractObject detection on fused images of visible and infrared modals is of great importance for many applications, for example, surveillance and rescue at low‐light conditions. However, current detectors have difficulty for robust fused image detection for mainly two reasons. First, objects are presented in various shapes and sizes, making some hard samples cannot be localized accurately. Second, the same object category in the fused images will have different appearance due to changing weather condition, temperature and intrinsic heat. Such a contradiction will degrade the classification task of a detection network, since it cannot merge commonalities and distinguish differences well. In this paper, we propose to reconstruct the detection pipeline of current detectors, and enhance the detection ability on difficult samples in fused images. Specifically, a Dilation Pyramid Network (DPN) is designed at the lateral connection to generate and aggregate features of various receptive field, without increasing pyramid layers. To strengthen the classification, a Semantic Category Attention Module (SCAM) is proposed to capture attention centers of semantics in fused images, rather than object centers. Abundant experiments on two fusion datasets show that the proposed method achieves a satisfying performance, and both modules can greatly improve current generic detectors on fused images.
Solar drying process for sewage sludge in a drying bed: A case study in Tunisia
Authors: Masmoudi Azza , Ben Sik Ali Ahlem , Dhaouadi Hatem , Mhiri Hatem 
Published: June 2023

AbstractThe aim of this work is to investigate and model the sewage sludge drying kinetics in a lab‐scale drying bed by varying the sludge layer thickness during winter and summer. During each season, five experiments were carried out with increasing the sludge thickness by 0.5 cm each time. To achieve moisture content on a dry basis of 12%, the sludge drying period varied between 120 and 312 h in winter and between 72 and 168 h in summer. Thus, by increasing the sludge thickness, the drying time increased. The different curves of the moisture content evolution and the drying rates were analyzed. The drying curves show that the warm‐up phase (phase 0) and the constant rate phase (phase 1) are absent during the winter and summer seasons. Regardless of the sludge thickness, only the falling rate period was observed. In addition, the moisture content dropped quickly throughout the first 24 h because of the elimination of interstitial water. The drying characteristic curve has been represented by a 3rd degree polynomial. Mathematical equations were used to describe the experimental curves of drying kinetics. The logarithmic model was the most reliable for simulating the changes of reduced moisture content versus drying time in winter and summer.
Development of a Machine Learning Model to Estimate the Biotic Ligand Model–Based Predicted No-Effect Concentrations for Copper in Freshwater
Authors: Chung Jiwoong , Yoo Geonwoo , Jo Jae-Seong , Choi Jinhee , Lee Jong-Hyeon 
Published: June 2023

Abstract
The copper (Cu) biotic ligand model (BLM) has been used for ecological risk assessment by taking into account the bioavailability of Cu in freshwater. The Cu BLM requires data for many water chemistry variables, such as pH, major cations, and dissolved organic carbon, which can be difficult to obtain from water quality monitoring programs. To develop an optimized predicted no-effect concentration (PNEC) estimation model based on an available monitoring dataset, we proposed an initial model that considers all BLM variables, a second model that requires variables excluding alkalinity, and a third model using electrical conductivity as a surrogate for the major cations and alkalinity. Furthermore, deep neural network (DNN) models have been used to predict the nonlinear relationships between the PNEC (outcome variable) and the required input variables (explanatory variables). The predictive capacity of DNN models was compared with the results of other existing PNEC estimation tools using a look-up table and multiple linear and multivariate polynomial regression methods. Three DNN models, using different input variables, provided better predictions of the Cu PNECs compared with the existing tools for the following four test datasets: Korean, United States, Swedish, and Belgian freshwaters. Consequently, it is expected that Cu BLM–based risk assessment can be applied to various monitoring datasets, and that the most applicable model among the three different types of DNN models could be selected according to data availability for a given monitoring database. Environ Toxicol Chem 2023;42:2271–2283. © 2023 SETAC
Software defined network‐based multipath state‐aware routing with traffic prediction in satellite network
Authors: Luo Yonghua , Ning Qian , Chen Bingcai , Zhou Xinzhi , Huang Linyu 
Published: June 2023

AbstractUneven traffic demand in satellite networks can lead to link congestion and influence network communication quality. To tackle this problem, we propose a state‐aware routing algorithm based on traffic prediction to disperse network traffic. Reducing the onboard processing requirements, the routing algorithm in this paper introduces a software‐defined network to decouple the control plane and data plane of the satellite network. Also, to better sense the trend of network state, the routing algorithm devises a Spatial‐Temporal Attention Fusion Graph Neural Network (STAFGNN) to predict the future network state by capturing the spatial‐temporal correlation of satellite network traffic. In the control plane, the routing algorithm senses the network state by predicting the future satellite traffic and aggregates the real‐time states of neighboring satellites to identify the load level of the zone. The data plane forwards data based on the control information. Based on the routing algorithm in this paper, multipath routing is designed to reduce the probability of link congestion by dispersing each end‐to‐end traffic. The simulation results demonstrate that the routing algorithm in this paper reduces the number of congestion links and balances the load distribution. The proposed algorithm provides an idea to introduce deep learning to solve the load balancing problem in satellite networks.
In vitro development of gametophytes and sporophytes of critically endangered fern Christella kendujharensis S.K. Behera & S.K. Barik (Thelypteridaceae)
Authors: Mishra Niranjan , Behera Sandip Kumar , Barik Saroj Kanta 
Published: June 2023

AbstractChristella kendujharensis S.K. Behera & S.K. Barik (family: Thelypteridaceae) is a critically endangered fern endemic to India. We developed its mass propagation protocol through in vitro spore culture in a liquid suspended medium for germination of gametophytes that produced sporophytes subsequently. The spores were monolete, reniform (mean length 36.49 ± 3.6 × breadth 25.67 ± 4.2 μm) to spheroidal with fimbriate and broad‐winged perispore. The maximum germination was in the Parker's and Thompson's (P&TV) medium with 0.1 mg L−1 thiamin, 0.1 mg L−1 riboflavin, 0.1 mg L−1 biotin, 0.1 mg L−1 pyridoxin, 0.5 mg L−1 nicotinic acid, 100 mg L−1 myoinositol, 0.01 mg L−1 folic acid, and 3 mg L−1 glycine. Spore germination was Vittaria type and gametophyte development was Aspidium type. The cordate gametophyte developed archegonia on the 38th day and antheridia on the 42nd day of spore sowing. Both isolate and composite cultures developed sporophytes indicating the presence of intra‐gametophytic selfing. Based on the maximum number of regenerated gametophytes, two combinations, that is, (i) 2 mg L−1 kinetin, and 0.01 mg L−1 2,4‐dichlorophenoxyacetic acid, and (ii) 0.1 mg L−1 naphthaleneacetic acid and 2 mg L−1 kinetin in P&TV media were recommended for mass propagation of C. kendujharensis.
Combined antifungal effects of the vapor phases of Zataria multiflora and Cinnamomum zeylanicum essential oils against Aspergillus flavus and Penicillium citrinum in vitro and cheese
Authors: Imaz Loqman , Aliakbarlu Javad , Lin Lin 
Published: June 2023

AbstractThe objective of this study was to evaluate the antifungal effects of Zataria multiflora (ZEO) and Cinnamomum zeylanicum (CEO) essential oils in the vapor phase against Aspergillus flavus and Penicillium citrinum in vitro and cheese. The antifungal activities of the vapors of ZEO and CEO were assessed by determining the minimum inhibitory concentration (MIC), fractional inhibitory concentration (FIC) index, and inhibition zone diameters. Thymol (51.10%) and cinnamaldehyde (77.82%) were the main constituents of ZEO and CEO, respectively. The MIC values of the vapors of ZEO and CEO against A. flavus were 25 and 12.5 μL/L and against P. citrinum were 800 and 400 μL/L, respectively. The in vitro results showed that the combination of the vapor phases of ZEO and CEO could synergistically inhibit the growth of A. flavus (FIC index = 0.75). In the cheese, the growth of P. citrinum was entirely inhibited by the combination of ZEO and CEO vapors, even at very low concentrations (1/16 MIC). In conclusion, the vapor phases of ZEO and CEO showed the potential to be applied as effective natural antifungals and alternatives to synthetic preservatives in cheese.
Detection of laryngeal carcinoma during endoscopy using artificial intelligence
Authors: Wellenstein David J. , Woodburn Jonathan , Marres Henri A. M. , van den Broek Guido B. 
Published: June 2023

AbstractBackgroundThe objective of this study was to assess the performance and application of a self‐developed deep learning (DL) algorithm for the real‐time localization and classification of both vocal cord carcinoma and benign vocal cord lesions.MethodsThe algorithm was trained and validated upon a dataset of videos and photos collected from our own department, as well as an open‐access dataset named “Laryngoscope8”.ResultsThe algorithm correctly localizes and classifies vocal cord carcinoma on still images with a sensitivity between 71% and 78% and benign vocal cord lesions with a sensitivity between 70% and 82%. Furthermore, the best algorithm had an average frame per second rate of 63, thus making it suitable to use in an outpatient clinic setting for real‐time detection of laryngeal pathology.ConclusionWe have demonstrated that our developed DL algorithm is able to localize and classify benign and malignant laryngeal pathology during endoscopy.
The role and mechanism of circ‐BNC2 on the malignant progression of oral squamous cell carcinoma
Authors: Xia Yingjie , Hei Naiheng , Peng Shixiong , Cui Zifeng 
Published: June 2023

AbstractBackgroundCircular RNAs (circRNAs) play a key part in the progression of oral squamous cell carcinoma (OSCC). However, the role of circ‐BNC2 (circRNA ID hsa_circ_0086414) in OSCC progression is still unclear.MethodsPlasmid transfection was used to induce overexpression of circ‐BNC2. RNA expression of circ‐BNC2, microRNA‐142‐3p (miR‐142‐3p) and GNAS complex locus (GNAS) was detected by quantitative real‐time polymerase chain reaction. Protein expression was assessed by western blot assay or immunohistochemistry assay. Cell proliferation was investigated by 3‐(4,5‐dimethylthazol‐2‐yl)‐2,5‐diphenyltetrazolium bromide (MTT) assay, colony formation assay and flow cytometry analysis. Cell migratory and invasive abilities and cell apoptosis were assessed by transwell assay and flow cytometry analysis, respectively. Oxidative stress was evaluated by superoxide dismutase activity detection assay, lipid peroxidation malondialdehyde assay and cellular reactive oxygen species assay. The binding relationship between miR‐142‐3p and circ‐BNC2 or GNAS was proved by dual‐luciferase reporter assay and RNA immunoprecipitation assay. The impacts of circ‐BNC2 overexpression on tumor growth in vivo were unveiled by a xenograft mouse model assay.ResultsCirc‐BNC2 expression was downregulated in OSCC tissues and cells when compared with adjacent healthy tissues and normal human oral keratinocytes. Circ‐BNC2 overexpression repressed the proliferation, migration and invasion of OSCC cells but induced cell apoptosis and oxidative stress. Additionally, circ‐BNC2 overexpression inhibited tumor growth in vivo. Furthermore, circ‐BNC2 bound to miR‐142‐3p, and miR‐142‐3p targeted GNAS. MiR‐142‐3p mimic attenuated circ‐BNC2 overexpression‐mediated effects on the proliferation, migration, invasion, apoptosis and oxidative stress of OSCC cells. The regulation of miR‐142‐3p in OSCC cell tumor properties involved GNAS. Further, circ‐BNC2 introduction promoted GNAS expression by inhibiting miR‐142‐3p.ConclusionCirc‐BNC2 suppressed OSCC malignant progression by upregulating GNAS expression in a miR‐142‐3p‐dependent manner, which suggested that circ‐BNC2 might be a novel target for OSCC therapy.