bluuebunny/crossref_metadata_2025_split huggingface dataset:
Astaxanthin and DHA supplementation ameliorates the proteomic profile of perinatal undernutrition-induced adipose tissue dysfunction in adult life
Authors: Ranade Anu V. , Hegde Pramukh Subrahmanya , Bhat Megha Agni , Rai Praveen , Vinodini N. A. , Aravind Anjana , Prasad Thottethodi Subrahmanya Keshava , Damodara Gowda K. M. 
Published: July 2023

AbstractMaternal diet is an essential factor that directly and indirectly regulates fetal growth. Exposure to certain environmental conditions substantially impacts an individual's short- and long-term health. Adipose tissue dysfunction is a worldwide chronic disease caused by improper lipid build-up in adipose tissue leading to obesity. Therefore, it is the need of the hour to invent anti-obesity agents. As a keto–carotenoid, Astaxanthin (AsX) has been shown to have preventive effects against problems associated with obesity. A crucial role in the pathogenesis of obesity has been attributed to dietary polyunsaturated fatty acids. Adipose tissue plays a vital role in maintaining overall body homeostasis. Metabolic dysfunction of white adipocytes forms a critical step in the emergence of insulin resistance and related diseases. Here we aim to investigate the effect of AsX and Docosahexaenoic acid (DHA) supplementation on the proteomic profile of perinatal undernutrition-induced adipose tissue dysfunction in adult life using a rat model. The LC–MS/MS quantitative proteomics enabled us to identify differentially expressed proteins in perinatal undernourished but AsX and DHA-supplemented animal models. Data are available via ProteomeXchange with identifier PXD041772.This study explored biological roles, molecular functions of differentially expressed proteins, and pathways related to adipose tissue dysfunction induced by undernutrition and its effective modulation by AsX and DHA.
Understanding fluoride adsorption from groundwater by alumina modified with alum using PHREEQC surface complexation model
Authors: Adu-Boahene Francis , Boakye Patrick , Agyemang Frank Ofori , Kanjua Jolly , Oduro‑Kwarteng Sampson 
Published: July 2023

AbstractFluoride is recognized as a vital ion for human and animal growth because of the critical role it plays in preventing skeletal and dental problems. However, when it is ingested at a higher concentration it can cause demineralization of teeth and bones resulting in fluorosis, therefore, the production of high-adsorptive capacity material which is also cost-effective is necessary for the treatment of fluorides. In this study, aluminium foil is valorised into alumina nanoparticles. The as-prepared alumina was modified with alum in two different ratios of 1:0.5 and 1:1 (alumina to alum w/w%) and later used as adsorbents for the removal of fluoride from groundwater. The adsorbents were characterized by Fourier transform infrared spectroscopy, point of zero charge and X-ray diffraction. Different factors that influence the removal efficiency of fluorides such as pH, initial concentrations, contact time and adsorbent dosage were studied and optimized using a simulated fluoride solution. The optimum conditions obtained were used to test real groundwater. The static experiment conditions were used to calibrate a PHREEQC geochemical model which was later used to simulate the fluoride sorption onto the modified alumina at different conditions. PHREEQC was also coupled with parameter estimation software to determine equilibrium constants for the surface reactions between the fluoride species and the adsorbent in a way that the simulations accurately reflect the outcomes of laboratory experiments. Isotherm studies were carried out on the adsorbents. Both Langmuir and Freundlich's non-linear models fitted well for the equilibrium data. However, with a higher coefficient of regression and low chi-square test values, the adsorption process was more of chemisorption on a monolayer surface. Kinetic studies were also carried out by using the non-linear equations from the pseudo-first-order and pseudo-second-order models. The pseudo-second-order model fitted well for the equilibrium data. The mechanism for the fluoride ion adsorption was also studied by the intraparticle (IP) diffusion model and was found that IP was not the rate-determining factor, and therefore the most plausible mechanism for the sorption process was ion exchange or attraction of fluoride ions to the sorbent surface. The findings obtained from this research show that readily available aluminium waste could be valorised into a useful product that could be employed in the removal of fluoride from water samples, including groundwater, that may contain too much fluoride and pose a risk to the general public's health.
Externally validated deep learning model to identify prodromal Parkinson’s disease from electrocardiogram
Authors: Karabayir Ibrahim , Gunturkun Fatma , Butler Liam , Goldman Samuel M. , Kamaleswaran Rishikesan , Davis Robert L. , Colletta Kalea , Chinthala Lokesh , Jefferies John L. , Bobay Kathleen , Ross G. Webster , Petrovitch Helen , Masaki Kamal , Tanner Caroline M. , Akbilgic Oguz 
Published: July 2023

AbstractLittle is known about electrocardiogram (ECG) markers of Parkinson’s disease (PD) during the prodromal stage. The aim of the study was to build a generalizable ECG-based fully automatic artificial intelligence (AI) model to predict PD risk during the prodromal stage, up to 5 years before disease diagnosis. This case–control study included samples from Loyola University Chicago (LUC) and University of Tennessee-Methodist Le Bonheur Healthcare (MLH). Cases and controls were matched according to specific characteristics (date, age, sex and race). Clinical data were available from May, 2014 onward at LUC and from January, 2015 onward at MLH, while the ECG data were available as early as 1990 in both institutes. PD was denoted by at least two primary diagnostic codes (ICD9 332.0; ICD10 G20) at least 30 days apart. PD incidence date was defined as the earliest of first PD diagnostic code or PD-related medication prescription. ECGs obtained at least 6 months before PD incidence date were modeled to predict a subsequent diagnosis of PD within three time windows: 6 months–1 year, 6 months–3 years, and 6 months–5 years. We applied a novel deep neural network using standard 10-s 12-lead ECGs to predict PD risk at the prodromal phase. This model was compared to multiple feature engineering-based models. Subgroup analyses for sex, race and age were also performed. Our primary prediction model was a one-dimensional convolutional neural network (1D-CNN) that was built using 131 cases and 1058 controls from MLH, and externally validated on 29 cases and 165 controls from LUC. The model was trained on 90% of the MLH data, internally validated on the remaining 10% and externally validated on LUC data. The best performing model resulted in an external validation AUC of 0.67 when predicting future PD at any time between 6 months and 5 years after the ECG. Accuracy increased when restricted to ECGs obtained within 6 months to 3 years before PD diagnosis (AUC 0.69) and was highest when predicting future PD within 6 months to 1 year (AUC 0.74). The 1D-CNN model based on raw ECG data outperformed multiple models built using more standard ECG feature engineering approaches. These results demonstrate that a predictive model developed in one cohort using only raw 10-s ECGs can effectively classify individuals with prodromal PD in an independent cohort, particularly closer to disease diagnosis. Standard ECGs may help identify individuals with prodromal PD for cost-effective population-level early detection and inclusion in disease-modifying therapeutic trials.
Structural and expression analysis of polyphenol oxidases potentially involved in globe artichoke (C. cardunculus var. scolymus L.) tissue browning
Authors: Pompili Valerio , Mazzocchi Elena , Moglia Andrea , Acquadro Alberto , Comino Cinzia , Rotino Giuseppe Leonardo , Lanteri Sergio 
Published: July 2023

AbstractGlobe artichoke capitula are susceptible to browning due to oxidation of phenols caused by the activity of polyphenol oxidases (PPOs), this reduces their suitability for fresh or processed uses. A genome-wide analysis of the globe artichoke PPO gene family was performed. Bioinformatics analyses identified eleven PPOs and their genomic and amino acidic features were annotated. Cis-acting element analysis identified a gene regulatory and functional profile associated to plant growth and development as well as stress response. For some PPOs, phylogenetic analyses revealed a structural and functional conservation with different Asteraceae PPOs, while the allelic variants of the eleven PPOs investigated across four globe artichoke varietal types identified several SNP/Indel variants, some of which having impact on gene translation. By RTqPCR were assessed the expression patterns of PPOs in plant tissues and in vitro calli characterized by different morphologies. Heterogeneous PPO expression profiles were observed and three of them (PPO6, 7 and 11) showed a significant increase of transcripts in capitula tissues after cutting. Analogously, the same three PPOs were significantly up-regulated in calli showing a brown phenotype due to oxidation of phenols. Our results lay the foundations for a future application of gene editing aimed at disabling the three PPOs putatively involved in capitula browning.
The effectiveness of the puncture channel plugging for reduction of complications after CT-guided percutaneous transthoracic needle biopsy
Authors: Wang Dong-xu , Wang Yu-guang , Ding Guo-xu , Li Bo , Liu Rui-nan , Ai Zhong-wei , Wang Yang 
Published: July 2023

AbstractThe effect of plugging the puncture channel with a mixture of hemocoagulase injection on the complications of CT-guided percutaneous transthoracic need biopsy (PTNB) was discussed. The medical records of PTNB were retrospectively studied from June 2017 to May 2022. In the study, the puncture channel of 626 patients were blocked, while remain 681 patients’ were not. The Mantel Haenszel method performed layered analysis and evaluated the correlation of adjusted confounding factors. The Odds Ratio and its 95% confidence interval were calculated using the Woof method. The incidence of high-level pulmonary hemorrhage was significantly reduced in patients with lesions ≤ 2 cm and different needle lengths. Patients with different pleural-needle tip angle and perineedle emphysema were blocked, and the incidence of pneumothorax and thoracic implants was significantly reduced. Through puncture channel plugging, the incidence of pulmonary hemorrhage, pneumothorax and thoracic catheterization of PTNB under CT guidance was reduced.
Water and oil-grease barrier properties of PVA/CNF/MBP/AKD composite coating on paper
Authors: Huang Shancong , Wang Xiyun , Zhang Yu , Meng Yu , Hua Feiguo , Xia Xinxing 
Published: July 2023

AbstractIn this paper, three kinds of micro-nano bamboo powder (MBP) and alkyl ketene dimer (AKD) were added to the polyvinyl alcohol/cellulose nanofiber (PVA/CNF) coating to prepare PVA/CNF/MBP coated paper and PVA/CNF/M-MBP/AKD coated paper. The results showed that MBP improved the oleophobicity of PVA/CNF coating, and the grease resistance grade of PVA/CNF/B-MBP and PVA/CNF/M-MBP coated papers reached the highest level, with a kit number of 12. Among the PVA/CNF/MBP coated papers, the PVA/CNF/M-MBP coated paper has the best hydrophobic properties, with the water contact angle and Cobb value of 74° and 21.3 g/m2, respectively. In addition, when the AKD dosage was 0.2% in the PVA/CNF/M-MBP/AKD coating, the kit number of the coated paper was 11, the Cobb value was 15.2 g/m2, the water contact angle was 103°, and the tensile strength was found to increase slightly. Therefore, compared with PVA/CNF coated paper, PVA/CNF/M-MBP/AKD coated paper has good strength and excellent hydrophobic and oleophobic properties.
Monitoring and simulation of the fuel irradiation behavior in nuclear reactors based on phononic crystal structure
Authors: Sayed Fatma A. , Elsayed Hussein A. , Eissa M. F. , Aly Arafa H. , Mehaney Ahmed 
Published: July 2023

AbstractWe have presented in the current work a novel idea for simulating the irradiation behaviors of the nuclear fuel pellets in nuclear reactors by using a one-dimensional defective phononic crystal (1D-DPnC) design was presented. The transmission spectra of the incident mechanical waves were considered basic data for expressing the characteristics of different nuclear fuel-pellets. Herein, the density, sound speed, and Young’s modulus of the fuel-pellets represent the key parameters that are influenced by the irradiation behaviors of these pallets. Mixed plutonium–uranium oxide (MOX) nuclear fuel is considered the main fuel in the present study. In addition, a comparison is performed for this fuel with other types of nuclear fuels. Moreover, the mechanical properties of these MOX-pellets are dependent on the porosity, the ratio of oxygen-to-metal (O/M), and the plutonium (Pu-content). The theoretical treatments depend on the transfers matrix method to compute the transmission spectra through the 1D-DPnC. The numerical findings provided that the MOX-pellet has the highest performance compared to other fuel pellets and with sensitivity equal to 59.388 × 103 Hz s/m. It was also reported that the effects of the percentage of the O/M and Pu- content in MOX had a minor effect in a comparison with the impact of porosity. The theoretical simulation agreed extremely with the experimental data reported for these nuclear fuels. Because of the close relationship between sound speed and density, this sensor can be utilized to monitor the porosity, O/M, Pu-content, and density of fuel-pellets as a quick and non-destructive evaluation technique in a nuclear fuel fabrication laboratory. This article has proven theoretically that MOX fuel produced from nuclear waste of uranium dioxide and plutonium dioxide gives excellent results compared to other types of nuclear fuels, and this agrees with experimental researches. Thus, it may contribute in preserving the environment from nuclear waste, and this can be considered a novel kind of purification of environmental pollution treatment.
TwinPort: 5G drone-assisted data collection with digital twin for smart seaports
Authors: Yigit Yagmur , Nguyen Long D. , Ozdem Mehmet , Kinaci Omer Kemal , Hoang Trang , Canberk Berk , Duong Trung Q. 
Published: July 2023

AbstractNumerous ports worldwide are adopting automation to boost productivity and modernize their operations. At this point, smart ports become a more important paradigm for handling increasing cargo volumes and increasing operational efficiency. In fact, as ports become more congested and cargo volumes increase, the need for accurate navigation through seaports is more pronounced to avoid collisions and the resulting consequences. To this end, digital twin (DT) technology in the fifth-generation (5G) networks and drone-assisted data collection can be combined to provide precise ship maneuvering. In this paper, we propose a DT model using drone-assisted data collection architecture, called TwinPort, to offer a comprehensive port management system for smart seaports. We also present a recommendation engine to ensure accurate ship navigation within a smart port during the docking process. The experimental results reveal that our solution improves the trajectory performance by approaching the desired shortest path. Moreover, our solution supports significantly reducing financial costs and protecting the environment by reducing fuel consumption.
Fabrication and testing of a multifunctional SiO2@ZnO core–shell nanospheres incorporated polymer coating for sustainable marine transport
Authors: Verma Jaya , Geng Yanquan , Wang Jiqiang , Goel Saurav 
Published: July 2023

AbstractWe report the development of a coating system relying on the incorporation of SiO2@ZnO core–shell nanospheres in polyurethane media as a novel approach to achieve longevity and sustainability in marine transport. This polymeric coating showed significant improvement in surface abrasion resistance, the transition from a hydrophilic state to a hydrophobic state (~ 125.2° ± 2°), improved antifungal, antibacterial and antialgae effects which make the proposed coating ideal to protect steel surfaces against biofouling. To substantiate our claims, we performed X-ray diffraction, Transmission electron microscopy, Fourier transform infrared spectroscopy, scanning acoustic microscopy, Thermogravimetric analysis (TGA), contact angle measurements, antimicrobial (antialgal, antibacterial, antifungal) tests and Taber abrasion tests (ASTM D1044 and D4060) to highlight the mechanical and biological functionality as well as the bonding configuration of this coating. The wear analysis of the Taber abraded coating using SEM and optical microscopy showed significant improvement in the adhesion and shear resistance achieved by the SiO2@ZnO core–shell nanospheres incorporated PU coating which was a contrasting feature compared to using PU alone. The overall investigations we performed led us to find out that the addition of 4% (wt.) SiO2@ZnO core–shell nanoparticles to the PU media deposited on the low carbon steel surface demonstrated remarkable antimicrobial performance with almost no bacterial growth, significant reductions in growth for algae to about 90% and fungus to about 95%.
In vitro infection efficiency of nervous necrosis virus alters depending on amount of viral particles adsorbed onto cells
Authors: Lee Han Sol , Gye Hyun Jung , Nishizawa Toyohiko 
Published: July 2023

AbstractNervous necrosis virus (NNV) in the family Nodaviridae is one of the simplest spherical RNA viruses and is pathogenic to many fish species. We investigated the effect of purified NNV on striped snakehead cells (SSN-1) in terms of adsorption ratio and infection efficiency using the 96-well titration system. The proportion of cytopathic effect (CPE)-positive wells among total number of wells inoculated with the virus (CPE appearance ratio) reduced by 17% each time the NNV infectivity dose was halved (y = 55.7x + 50.6). Thus, subtle differences in NNV infectivity could be accurately detected using this system. Experiments performed to observe alteration of CPE appearance ratio with changing viral doses and adsorption times showed that NNV particles introduced into microplate wells as suspensions in ≤ 100 µl inoculum were adsorbed almost completely onto cells seeded on the wells within 4 days of incubation. Density profile analysis of NNV coat proteins revealed that the NNV suspension at 1 50% tissue culture infectious dose (TCID50) contained 60 particles. Infection efficiency/NNV peaked at 20 particles (1.20%/particle) and then declined gradually with increasing NNV doses. Therefore, in vitro infection efficiency of NNV may alter depending on the quantity of viral particles adsorbed onto cells.
End fire linear antenna array synthesis using differential evolution inspired Adaptive Naked Mole Rat Algorithm
Authors: Singh Harbinder , Mittal Nitin , Gupta Amit , Singh Pratap , Gared Fikreselam 
Published: July 2023

AbstractLinear antenna arrays (LAAs) play a critical role in smart system communication applications such as the Internet of Things (IoT), mobile communication and beamforming. However, minimizing secondary lobes while maintaining a low beamwidth remains challenging. This study presents an enhanced synthesis methodology for LAAs using the Adaptive Naked Mole Rat Algorithm (ANMRA). ANMRA, inspired by mole-rat mating habits, improves exploration and exploitation capabilities for directive LAA applications. The performance of ANMRA is assessed using the CEC 2019 benchmark test functions, a widely adopted standard for statistical evaluation in optimization algorithms. The proposed methodology results are also benchmarked against state-of-the-art algorithms, including the Salp Swarm Algorithm (SSA), Cuckoo Search (CS), Artificial Hummingbird Algorithm (AHOA), Chimp Optimization Algorithm (ChOA), and Naked Mole Rat Algorithm (NMRA). The results demonstrate that ANMRA achieves superior performance among the benchmarked algorithms by successfully minimizing secondary lobes and obtaining a narrow beamwidth. The ANMRA controlled design achieves the lowest Side Lobe Level (SLL) of − 37.08 dB and the smallest beamwidth of 74.68°. The statistical assessment using the benchmark test functions further confirms the effectiveness of ANMRA. By optimizing antenna element magnitude and placement control, ANMRA enables precise primary lobe placement, grating lobe elimination, and high directivity in LAAs. This research contributes to advancing smart system communication technologies, particularly in the context of IoT and beamforming applications, by providing an enhanced synthesis methodology for LAAs that offers improved performance in terms of secondary lobe reduction and beamwidth optimization.
Assessing causal relationship between circulating cytokines and age-related neurodegenerative diseases: a bidirectional two-sample Mendelian randomization analysis
Authors: Yin Zihan , Chen Jiao , Xia Manze , Zhang Xinyue , Li Yaqin , Chen Zhenghong , Bao Qiongnan , Zhong Wanqi , Yao Jin , Wu Kexin , Zhao Ling , Liang Fanrong 
Published: July 2023

AbstractNumerous studies have reported that circulating cytokines (CCs) are linked to age-related neurodegenerative diseases (ANDDs); however, there is a lack of systematic investigation for the causal association. A two-sample bidirectional Mendelian Randomisation (MR) method was utilized to evaluate the causal effect. We applied genetic variants correlated with concentrations of CCs from a genome-wide association study meta-analysis (n = 8293) as instrumental variables. Summary data of three major ANDDs [Alzheimer’s disease (AD), Parkinson’s disease (PD), and Amyotrophic lateral sclerosis (ALS)] were identified from the IEU OpenGWAS platform (n = 627, 266). Inverse-variance weighted method is the main approach to analyse causal effect, and MR results are verified by several sensitivity and pleiotropy analyses. In directional MR, it suggested that several CCs were nominally correlated with the risk of ANDDs, with a causal odds ratio (OR) of Interleukin (IL)-5 of 0.909 for AD; OR of IL-2 of 1.169 for PD; and OR of Beta nerve growth factor of 1.142 for ALS). In reverse MR, there were some suggestively causal effects of ANDDs on CCs (AD on increased Basic fibroblast growth factor and IL-12 and decreased Stem cell growth factor beta; PD on decreased Monokine induced by interferon-gamma; ALS on decreased Basic fibroblast growth factor and IL-17). The findings were stable across sensitivity and pleiotropy analyses. However, after Bonferroni correction, there is no statistically significant association between CCs and ANDDs. Through the genetic epidemiological approach, our study assessed the role and presented possible causal associations between CCs and ANDDs. Further studies are warranted to verify the causal associations.