bluuebunny/crossref_metadata_2025 huggingface dataset:
Data-Driven Global Subseasonal Forecast for Intraseasonal Oscillation Components
Authors: Shen Yichen , Lu Chuhan , Wang Yihan , Huang Dingan , Xin Fei
Published: November 2023

As a challenge in the construction of a “seamless forecast” system, improving the prediction skills of subseasonal forecasts is a key issue for meteorologists. In view of the evolution characteristics of numerical models and deep-learning models for subseasonal forecasts, as forecast times increase, the prediction skill for high-frequency components will decrease, as the lead time is already far beyond the predictability. Meanwhile, intraseasonal low-frequency components are essential to the change in general circulation on subseasonal timescales. In this paper, the Global Subseasonal Forecast Model (GSFM v1.0) first extracted the intraseasonal oscillation (ISO) components of atmospheric signals and used an improved deep-learning model (SE-ResNet) to train and predict the ISO components of geopotential height at 500 hPa (Z500) and temperature at 850 hPa (T850). The results show that the 10–30 day prediction performance of the SE-ResNet model is better than that of the model trained directly with original data. Compared with other models/methods, this model has a good ability to depict the subseasonal evolution of the ISO components of Z500 and T850. In particular, although the prediction results from the Climate Forecast System Version 2 have better performance through 10 days, the SE-ResNet model is substantially superior to CFSv2 through 10–30 days, especially in the middle and high latitudes. The SE-ResNet model also has a better effect in predicting planetary waves with wavenumbers of 3–8. Thus, the application of data-driven subseasonal forecasts of atmospheric ISO components may shed light on improving the skill of seasonal forecasts.
Multi-Objective Non-Linear Programming Problems in Linear Diophantine Fuzzy Environment
Authors: Iqbal Salma , Yaqoob Naveed , Gulistan Muhammad
Published: November 2023

Due to various unpredictable factors, a decision maker frequently experiences uncertainty and hesitation when dealing with real-world practical optimization problems. At times, it’s necessary to simultaneously optimize a number of non-linear and competing objectives. Linear Diophantine fuzzy numbers are used to address the uncertain parameters that arise in these circumstances. The objective of this manuscript is to present a method for solving a linear Diophantine fuzzy multi-objective nonlinear programming problem (LDFMONLPP). All the coefficients of the nonlinear multi-objective functions and the constraints are linear Diophantine fuzzy numbers (LDFNs). Here we find the solution of the nonlinear programming problem by using Karush-Kuhn-Tucker condition. A numerical example is presented.
Antibacterial Aerogels-Based Membranes by Customized Colloidal Functionalization of TEMPO-Oxidized Cellulose Nanofibers Incorporating CuO
Authors: Usala Elena , Espinosa Eduardo , El Arfaoui Wasim , Morcillo-Martín Ramón , Ferrari Begoña , González Zoilo
Published: November 2023

An innovative colloidal approach is proposed here to carry out the customized functionalization of TEMPO-Oxidized Cellulose Nanofibers (CNF) incorporating non-noble inorganic nanoparticles. A heterocoagulation process is applied between the delignified CNF and as-synthetized CuO nanoparticles (CuO NPs) to formulate mixtures which are used in the preparation of aerogels with antibacterial effect, which could be used to manufacture membranes, filters, foams, etc. The involved components of formulated blending, CNF and CuO NPs, were individually obtained by using a biorefinery strategy for agricultural waste valorization, together with an optimized chemical precipitation, assisted by ultrasounds. The optimization of synthesis parameters for CuO NPs has avoided the presence of undesirable species, which usually requires later thermal treatment with associated costs. The aerogels-based structure, obtained by conventional freeze-drying, acted as 3D support for CuO NPs, providing a good dispersion within the cross-linked structure of the nanocellulose and facilitating direct contact of the antibacterial phase against undesirable microorganisms. All samples showed a positive response against Escherichia coli and Staphylococcus aureus. An increase of the antibacterial response of the aerogels, measured by agar disk diffusion test, has been observed with the increase of CuO NPs incorporated, obtaining the width of the antimicrobial “halo” (nwhalo) from 0 to 0.6 and 0.35 for S. aureus and E. coli, respectively. Furthermore, the aerogels have been able to deactivate S. aureus and E. coli in less than 5 h when the antibacterial assays have been analyzed by a broth dilution method. From CNF-50CuO samples, an overlap in the nanoparticle effect produced a decrease of the antimicrobial kinetic.
Time-Dependent Fluid-Structure Interaction Simulations of a Simplified Human Soft Palate
Authors: Li Peng , Laudato Marco , Mihaescu Mihai
Published: November 2023

Obstructive Sleep Apnea Syndrome (OSAS) is a common sleep-related disorder. It is characterized by recurrent partial or total collapse of pharyngeal upper airway accompanied by induced vibrations of the soft tissues (e.g., soft palate). The knowledge of the tissue behavior subject to a particular airflow is relevant for realistic clinic applications. However, in-vivo measurements are usually impractical. The goal of the present study is to develop a 3D fluid-structure interaction model for the human uvulopalatal system relevant to OSA based on simplified geometries under physiological conditions. Numerical simulations are performed to assess the influence of the different breathing conditions on the vibrational dynamics of the flexible structure. Meanwhile, the fluid patterns are investigated for the coupled fluid-structure system as well. Increasing the respiratory flow rate is shown to induce larger structural deformation. Vortex shedding induced resonance is not observed due to the large discrepancy between the flow oscillatory frequency and the natural frequency of the structure. The large deformation for symmetric breathing case under intensive respiration is mainly because of the positive feedback from the pressure differences on the top and the bottom surfaces of the structure.
COVID-19 Detection via Ultra-Low-Dose X-ray Images Enabled by Deep Learning
Authors: Ahmad Isah Salim , Li Na , Wang Tangsheng , Liu Xuan , Dai Jingjing , Chan Yinping , Liu Haoyang , Zhu Junming , Kong Weibin , Lu Zefeng , Xie Yaoqin , Liang Xiaokun
Published: November 2023

The detection of Coronavirus disease 2019 (COVID-19) is crucial for controlling the spread of the virus. Current research utilizes X-ray imaging and artificial intelligence for COVID-19 diagnosis. However, conventional X-ray scans expose patients to excessive radiation, rendering repeated examinations impractical. Ultra-low-dose X-ray imaging technology enables rapid and accurate COVID-19 detection with minimal additional radiation exposure. In this retrospective cohort study, ULTRA-X-COVID, a deep neural network specifically designed for automatic detection of COVID-19 infections using ultra-low-dose X-ray images, is presented. The study included a multinational and multicenter dataset consisting of 30,882 X-ray images obtained from approximately 16,600 patients across 51 countries. It is important to note that there was no overlap between the training and test sets. The data analysis was conducted from 1 April 2020 to 1 January 2022. To evaluate the effectiveness of the model, various metrics such as the area under the receiver operating characteristic curve, receiver operating characteristic, accuracy, specificity, and F1 score were utilized. In the test set, the model demonstrated an AUC of 0.968 (95% CI, 0.956–0.983), accuracy of 94.3%, specificity of 88.9%, and F1 score of 99.0%. Notably, the ULTRA-X-COVID model demonstrated a performance comparable to conventional X-ray doses, with a prediction time of only 0.1 s per image. These findings suggest that the ULTRA-X-COVID model can effectively identify COVID-19 cases using ultra-low-dose X-ray scans, providing a novel alternative for COVID-19 detection. Moreover, the model exhibits potential adaptability for diagnoses of various other diseases.
Prediction of Ross River Virus Incidence Using Mosquito Data in Three Cities of Queensland, Australia
Authors: Qian Wei , Viennet Elvina , Glass Kathryn , Harley David , Hurst Cameron
Published: November 2023

Ross River virus (RRV) is the most common mosquito-borne disease in Australia, with Queensland recording high incidence rates (with an annual average incidence rate of 0.05% over the last 20 years). Accurate prediction of RRV incidence is critical for disease management and control. Many factors, including mosquito abundance, climate, weather, geographical factors, and socio-economic indices, can influence the RRV transmission cycle and thus have potential utility as predictors of RRV incidence. We collected mosquito data from the city councils of Brisbane, Redlands, and Mackay in Queensland, together with other meteorological and geographical data. Predictors were selected to build negative binomial generalised linear models for prediction. The models demonstrated excellent performance in Brisbane and Redlands but were less satisfactory in Mackay. Mosquito abundance was selected in the Brisbane model and can improve the predictive performance. Sufficient sample sizes of continuous mosquito data and RRV cases were essential for accurate and effective prediction, highlighting the importance of routine vector surveillance for disease management and control. Our results are consistent with variation in transmission cycles across different cities, and our study demonstrates the usefulness of mosquito surveillance data for predicting RRV incidence within small geographical areas.
Lenvatinib-Loaded Poly(lactic-co-glycolic acid) Nanoparticles with Epidermal Growth Factor Receptor Antibody Conjugation as a Preclinical Approach to Therapeutically Improve Thyroid Cancer with Aggressive Behavior
Authors: Revilla Giovanna , Al Qtaish Nuseibah , Caruana Pablo , Sainz-Ramos Myriam , Lopez-Mendez Tania , Rodriguez Francisco , Paez-Espinosa Verónica , Li Changda , Vallverdú Núria Fucui , Edwards Maria , Moral Antonio , Pérez José Ignacio , Escolà-Gil Juan Carlos , Pedraz José Luis , Gallego Idoia , Corcoy Rosa , Céspedes María Virtudes , Puras Gustavo , Mato Eugènia
Published: November 2023

Background: Lenvatinib, a tyrosine kinase inhibitor (TKI) approved for the treatment of progressive and radioactive iodine (RAI)-refractory differentiated thyroid cancer (DTC), is associated with significant adverse effects that can be partially mitigated through the development of novel drug formulations. The utilization of nanoparticles presents a viable option, as it allows for targeted drug delivery, reducing certain side effects and enhancing the overall quality of life for patients. This study aimed to produce and assess, both in vitro and in vivo, the cytotoxicity, biodistribution, and therapeutic efficacy of lenvatinib-loaded PLGA nanoparticles (NPs), both with and without decoration using antibody conjugation (cetuximab), as a novel therapeutic approach for managing aggressive thyroid tumors. Methods: Poly(lactic-co-glycolic acid) nanoparticles (NPs), decorated with or without anti-EGFR, were employed as a lenvatinib delivery system. These NPs were characterized for size distribution, surface morphology, surface charge, and drug encapsulation efficiency. Cytotoxicity was evaluated through MTT assays using two cellular models, one representing normal thyroid cells (Nthy-ori 3-1) and the other representing anaplastic thyroid cells (CAL-62). Additionally, an in vivo xenograft mouse model was established to investigate biodistribution and therapeutic efficacy following intragastric administration. Results: The NPs demonstrated success in terms of particle size, polydispersity index (PDI), zeta potential, morphology, encapsulation efficiency, and cetuximab distribution across the surface. In vitro analysis revealed cytotoxicity in both cellular models with both formulations, but only the decorated NPs achieved an ID50 value in CAL-62 cells. Biodistribution analysis following intragastric administration in xenografted thyroid mice demonstrated good stability in terms of intestinal barrier function and tumor accumulation. Both formulations were generally well tolerated without inducing pathological effects in the examined organs. Importantly, both formulations increased tumor necrosis; however, decorated NPs exhibited enhanced parameters related to apoptotic/karyolytic forms, mitotic index, and vascularization compared with NPs without decoration. Conclusions: These proof-of-concept findings suggest a promising strategy for administering TKIs in a more targeted and effective manner.
Gibberellic Acid Inhibits Dendrobium nobile—Piriformospora Symbiosis by Regulating the Expression of Cell Wall Metabolism Genes
Authors: Chen Hong , Li Yefei , Yin Yuying , Li Ji , Li Lin , Wu Kunlin , Fang Lin , Zeng Songjun
Published: November 2023

Orchid seeds lack endosperms and depend on mycorrhizal fungi for germination and nutrition acquisition under natural conditions. Piriformospora indica is a mycorrhizal fungus that promotes seed germination and seedling development in epiphytic orchids, such as Dendrobium nobile. To understand the impact of P. indica on D. nobile seed germination, we examined endogenous hormone levels by using liquid chromatography–mass spectrometry. We performed transcriptomic analysis of D. nobile protocorm at two developmental stages under asymbiotic germination (AG) and symbiotic germination (SG) conditions. The result showed that the level of endogenous IAA in the SG protocorm treatments was significantly higher than that in the AG protocorm treatments. Meanwhile, GA3 was only detected in the SG protocorm stages. IAA and GA synthesis and signaling genes were upregulated in the SG protocorm stages. Exogenous GA3 application inhibited fungal colonization inside the protocorm, and a GA biosynthesis inhibitor (PAC) promoted fungal colonization. Furthermore, we found that PAC prevented fungal hyphae collapse and degeneration in the protocorm, and differentially expressed genes related to cell wall metabolism were identified between the SG and AG protocorm stages. Exogenous GA3 upregulated SRC2 and LRX4 expression, leading to decreased fungal colonization. Meanwhile, GA inhibitors upregulated EXP6, EXB16, and EXP10-2 expression, leading to increased fungal colonization. Our findings suggest that GA regulates the expression of cell wall metabolism genes in D. nobile, thereby inhibiting the establishment of mycorrhizal symbiosis.
Recent Advances in Effector Research of Magnaporthe oryzae
Authors: Wei Yun-Yun , Liang Shuang , Zhu Xue-Ming , Liu Xiao-Hong , Lin Fu-Cheng
Published: November 2023

Recalcitrant rice blast disease is caused by Magnaporthe oryzae, which has a significant negative economic reverberation on crop productivity. In order to induce the disease onto the host, M. oryzae positively generates many types of small secreted proteins, here named as effectors, to manipulate the host cell for the purpose of stimulating pathogenic infection. In M. oryzae, by engaging with specific receptors on the cell surface, effectors activate signaling channels which control an array of cellular activities, such as proliferation, differentiation and apoptosis. The most recent research on effector identification, classification, function, secretion, and control mechanism has been compiled in this review. In addition, the article also discusses directions and challenges for future research into an effector in M. oryzae.
Linking Adiponectin and Its Receptors to Age-Related Macular Degeneration (AMD)
Authors: Choubey Mayank , Tirumalasetty Munichandra B. , Bora Nalini S. , Bora Puran S.
Published: November 2023

In recent years, there has been a captivating focus of interest in elucidating the intricate crosstalk between adiponectin (APN), a versatile fat-associated adipokine and ocular pathologies. Unveiling the intricate relationship between adipocytokine APN and its receptors (AdipoRs) with aging eye disorders has emerged as a fascinating frontier in medical research. This review article delves into this connection, illuminating the hidden influence of APN on retinal health. This comprehensive review critically examines the latest findings and breakthroughs that underscore the pivotal roles of APN/AdipoRs signaling in maintaining ocular homeostasis and protecting against eye ailments. Here, we meticulously explore the intriguing mechanisms by which APN protein influences retinal function and overall visual acuity. Drawing from an extensive array of cutting-edge studies, the article highlights APN’s multifaceted functions, ranging from anti-inflammatory properties and oxidative stress reduction to angiogenic regulation within retinal and macula tissues. The involvement of APN/AdipoRs in mediating these effects opens up novel avenues for potential therapeutic interventions targeting prevalent aging eye conditions. Moreover, this review unravels the interplay between APN signaling pathways and age-related macular degeneration (AMD). The single-cell RNA-seq results validate the expression of both the receptor isoforms (AdipoR1/R2) in retinal cells. The transcriptomic analysis showed lower expression of AdipoR1/2 in dry AMD pathogenesis compared to healthy subjects. The inhibitory adiponectin peptide (APN1) demonstrated over 75% suppression of CNV, whereas the control peptide did not exert any inhibitory effect on choroidal neovascularization (CNV). The elucidation of these relationships fosters a deeper understanding of adipose tissue’s profound influence on ocular health, presenting new prospects for personalized treatments and preventative measures. Because APN1 inhibits CNV and leakage, it can be used to treat human AMD, although the possibility to treat human AMD is in the early stage and more clinical research is needed. In conclusion, this review provides a captivating journey into the enthralling world of APN, intertwining the realms of adipose biology and ophthalmology in aging.
DDX3X Syndrome Behavioral Manifestations with Particular Emphasis on Psycho-Pathological Symptoms—A Review
Authors: Stefaniak Urszula , Malak Roksana , Kaczmarek Ada , Samborski Włodzimierz , Mojs Ewa
Published: November 2023

(1) Background: Identification of typical behavioral manifestations in patients with DEAD-Box Helicase 3 X-linked gene (DDX3X) variants plays a crucial role in accurately diagnosing and managing the syndrome. The objective of this paper was to carry out a review of medical and public databases and assess the behavioral features of the DDX3X syndrome (DDX3X), with a particular focus on psycho-pathological symptoms. (2) Methods: An extensive computerized search was conducted in various databases, including PubMed, Medline Complete, Science Direct, Scopus, and Web of Science. Specific keywords and Medical Subject Headings were used to ensure the inclusion of relevant studies. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were applied to assess the methodological quality of the manuscripts. (3) Results: Only nine papers out of the 272 assessed met the inclusion criteria. These articles revealed various psycho-pathological manifestations in patients with the DDX3X syndrome. Intellectual disability (ID) or developmental disability (DD), speech delay, autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), generalized anxiety disorder (GAD), self-injurious behaviors (SIBs), sensory symptoms and sleep disturbance were demonstrated to be the most common psycho-pathological behavior manifestations. (4) Conclusions: Patients with the DDX3X syndrome manifest a wide spectrum of psycho-pathological symptoms. A comprehensive investigation of these symptoms in patients is essential for early diagnosis and effective therapy.
Transient Expression in HEK-293 Cells in Suspension Culture as a Rapid and Powerful Tool: SARS-CoV-2 N and Chimeric SARS-CoV-2N-CD154 Proteins as a Case Study
Authors: Lao Thailin , Farnos Omar , Bueno Alexi , Alvarez Anays , Rodríguez Elsa , Palacios Julio , Luz Kathya Rashida de la , Kamen Amine , Carpio Yamila , Estrada Mario Pablo
Published: November 2023

In a previous work, we proposed a vaccine chimeric antigen based on the fusion of the SARS-CoV-2 N protein to the extracellular domain of the human CD40 ligand (CD154). This vaccine antigen was named N-CD protein and its expression was carried out in HEK-293 stably transfected cells, grown in adherent conditions and serum-supplemented medium. The chimeric protein obtained in these conditions presented a consistent pattern of degradation. The immunization of mice and monkeys with this chimeric protein was able to induce a high N-specific IgG response with only two doses in pre-clinical experiments. In order to explore ways to diminish protein degradation, in the present work, the N and N-CD proteins were produced in suspension cultures and serum-free media following transient transfection of the HEK-293 clone 3F6, at different scales, including stirred-tank controlled bioreactors. The results showed negligible or no degradation of the target proteins. Further, clones stably expressing N-CD were obtained and adapted to suspension culture, obtaining similar results to those observed in the transient expression experiments in HEK-293-3F6. The evidence supports transient protein expression in suspension cultures and serum-free media as a powerful tool to produce in a short period of time high levels of complex proteins susceptible to degradation, such as the SARS-CoV-2 N protein.
Large-Strain Nonlinear Consolidation of Sand-Drained Foundations Considering Vacuum Preloading and the Variation in Radial Permeability Coefficient
Authors: Xu Zan , Cui Penglu , Cao Wengui , Zhang Xingyi , Zhang Jiachao
Published: November 2023

The vacuum preloading method effectively strengthens soft soil foundations with vertical drainage, which produces a smear effect when laying sand drains. Meanwhile, the seepage of pore water and soil deformation during consolidation exhibit nonlinear characteristics. Therefore, based on Gibson’s 1D large-strain consolidation theory, this paper developed a more generalized large-strain radical consolidation model of sand-drained soft foundations under free-strain assumptions. In this system, the double logarithmic compression permeability relationships for soft soils with large-strain properties, the variation in the radical permeability coefficient in the smear zone, and the effect of the non-Darcy flow were all included. Then, the partial differential control equations were numerically solved by the finite difference method and validated with existing radical consolidation test results and derived analytical solutions. Finally, the influences of relevant model parameters on consolidation are discussed. The analysis shows that the greater the maximum dimensionless vacuum negative pressure P0, the faster the consolidation rate of sand-drained foundations. Meanwhile, the decrease in the negative pressure transfer coefficient k1 will result in a decreasing final settlement amount. Moreover, the consolidation rate of sand-drained foundations is slower considering the non-Darcy flow, but the final settlement is unaffected.
Evaluation of Shear Stress in Soils Stabilized with Biofuel Co-Products via Regression Analysis Methods
Authors: Uzer Ali Ulvi
Published: November 2023

In recent years, the employment of artificial neural networks (ANNs) has risen in various engineering fields. ANNs have been applied to a range of geotechnical engineering problems and have shown promising outcomes. The aim of this article is to enhance the effectiveness of estimating unfamiliar intermediate values from existing shear stress data by employing ANNs. Artificial neural network modelling was undertaken through the Regression Learner program that is integrated with the Matlab 2023a software package. This program offers a user-friendly graphical interface for developing AI models absent of the need for any coding. The validation and training of the ANNs were executed by relying on shear box test data which had been conducted at the Geotechnical Laboratory situated at Iowa State University. The objective of these experiments was to explore the potential of biofuel co-products (BCPs) in soil stabilization. The data should be structured with input and output parameters in columns and samples in rows. The dataset comprises a 216 × 6 matrix. The data columns provide information on soil type (pure soil—unadulterated; and 12% BCP-adulterated soil), time (1, 7, and 28 days), normal stress (0.069-DS10, 0.138-DS20, and 0.207-DS30 MPa), moisture content (OMC−4%, OMC%, and OMC+4%), and corresponding shear stress (σ, MPa) values. The AI predictions for the test data output provide an outstanding R2 score of 0.94. This indicates that employing ANN to teach shear test data facilitates gaining a large quantity of data more efficiently, with fewer experiments and in less time. Such an approach seems encouraging for geotechnical engineering.
Optimizing Window Glass Design for Energy Efficiency in South Korean Office Buildings: A Hierarchical Analysis Using Energy Simulation
Authors: Lee Yu-Jeong , Kim Sang-Hee , Ryu Ji-Hye , Lee Kweon-Hyoung
Published: November 2023

The world is emphasizing the need for building design that considers energy performance to deal with climate problems. South Korea has constantly been tightening the design standards for saving building energy but with a focus on thermal performance and equipment systems. Accordingly, this study conducted an energy simulation experiment on office buildings with different window-to-wall ratios (WWRs) to propose a smart glazing plan to improve energy performance. An energy simulation experiment was performed on office buildings with varying WWRs to hierarchically analyze the influence of building window performance elements, including the heat transmission coefficient (U-value), visible light transmittance (VLT), and solar heat gain coefficient (SHGC), on building energy performance. The analysis showed that SHGC had the most significant impact on the heating and cooling load, by 22.13%, with the influences of the variables being 12.4% for the U-value, 4.78% for VLT, and 82.83% for SHGC. The results showed that the solar heat gain coefficient (SHGC) had the greatest impact on energy performance among window performance elements, and the effect increased significantly in certain WWRs. Moreover, to improve the energy performance of buildings with higher WWRs, it is essential to reflect the optimum composition of the U-value and SHGC on the window plan. This study’s findings propose measures to supplement existing window plans focusing on thermal performance. Furthermore, these results hold academic value in providing concrete grounds for that.
Ultrasound Patterns of Hepatocellular Carcinoma and Their Prognostic Impact: A Retrospective Study
Authors: Barteselli Chiara , Mazza Stefano , Ravetta Valentina , Viera Francesca Torello , Veronese Letizia , Frigerio Chiara , Gori Giulia , Bergamaschi Gaetano , Sgarlata Carmelo , Facciorusso Antonio , Maestri Marcello , Di Sabatino Antonio , Anderloni Andrea
Published: November 2023

Background: Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death. Abdominal ultrasound (US) is by far the most widely used first-level exam for the diagnosis of HCC. We aimed to assess whether different ultrasound patterns were related to tumor prognosis. Methods: We retrospectively reviewed all patients with a new diagnosis of HCC (single nodule) and undergoing radiofrequency thermal ablation (RFTA) at our clinic between January 2009 and December 2021. Patients were classified according to four HCC ultrasound patterns: 1A, single capsulated nodule; 1B, well capsulated intra-node nodule; 1C, cluster consisting of capsulated nodules; and 2, non-capsulated nodule. Results: 149 patients were analysed; median follow-up time was 43 months. US patterns 1A (32.9%) and 1B (61.1%) were the most commonly seen. Median overall survival (OS) and recurrence-free survival (RFS) from RFTA were 54 months (95% CI, 42–66) and 22 months (95% CI, 12–32), respectively. Pattern 1A showed the best OS. Compared to pattern 1A, 1B was independently associated with worse OS (51 months (95% CI, 34–68) vs. 46 months (95% CI, 18–62)) and RFS (34 months (95% CI, 27–41) vs. 18 months (95% CI, 12–24)). Patterns 1C and 2 were associated with worse RFS compared to 1A, while no difference was seen for OS. Among baseline clinical variables, pattern 1B exhibited higher histological grade (p = 0.048) and tumor dimension (p = 0.034) compared to pattern 1A. Conclusions: Our findings demonstrate that different US patterns correlate with different survival outcomes and tumor behavior in patients with HCC. Prospective studies are needed to confirm these results.
A Novel Strategy for the Preparation of Supported Pd as an Efficient Catalyst for the Hydrogenation of Nitrobenzene in Mild Conditions
Authors: Hu Zhi , Cheng Yiyi , Wu Meng , Duan Ying , Yang Yanliang , Lu Tianliang
Published: November 2023

An advanced strategy was developed for the synthesis of molecular sieve-supported Pd catalysts. In this method, reductant containing C=C was in-situ prepared and pre-dispersed in the pore of the zeolites. The C=C group in the reductant can reduce the Pd2+ to Pd0 efficiently, leading to the formation of small and uniform Pd nanoparticles (~2 nm). The physical and chemical properties of the catalyst were characterized by XRD, TEM, XPS (ICP-OES), N2 isothermal adsorption-desorption, and H2-TPR. These catalysts showed high catalytic performance for the hydrogenation of nitrobenzene to aniline. All the TOFs for 1.5 Pd/Y, 1.5 Pd/ZSM-5, and 1.5 Pd/MOR with 1.5 wt% Pd loading are higher than 1000 h−1 at 30 °C and 0.1 MPa H2. Meanwhile, kinetic analysis for 2.0 Pd/Y was carried out, and an apparent activation energy of 28.88 kJ mol−1 was obtained, which is lower than most of the reported values in the literature. Furthermore, these catalysts were stable and recyclable.
Recent Developments in Lignocellulosic Biofuel Production with Nanotechnological Intervention: An Emphasis on Ethanol
Authors: Dutta Swagata , Saravanabhupathy Sarveshwaran , Anusha  , Rajak Rajiv Chandra , Banerjee Rintu , Dikshit Pritam Kumar , Padigala Chandra Tejaswi , Das Amit K. , Kim Beom Soo
Published: November 2023

Biofuel, an inexhaustible fuel source, plays a pivotal role in the contemporary era by diminishing the dependence on non-renewable energy sources and facilitating the mitigation of CO2 emissions. Due to the many constraints in existing technology and the resulting increased costs, the production of biofuels on a large scale is a laborious process. Furthermore, the methods used to convert varied feedstock into the intended biofuel may vary based on the specific techniques and materials involved. The demand for bioethanol is increasing worldwide due to the implementation of regulations by world nations that mandates the blending of bioethanol with petrol. In this regard, second-generation bioethanol made from lignocellulosic biomass is emerging at a rapid rate. Pre-treatment, hydrolysis, and fermentation are some of the technical, practical, and economic hurdles that the biochemical conversion method must overcome. Nanoparticles (NPs) provide a very effective approach to address the present obstacles in using biomass, due to their selectivity, energy efficiency, and time management capabilities, while also reducing costs. NPs smaller dimensions allow them to be more effective at interacting with lignocellulosic components at low concentrations to release carbohydrates that can be utilized to produce bioethanol. This article provides a concise overview of various biofuels and the nanotechnological advancements in producing it, with a particular emphasis on ethanol. It provides a detailed discussion on the application of nanotechnology at each stage of ethanol production, with a particular emphasis on understanding the mechanism of how nanoparticles interact with lignocellulose.
Proximity Interactome Analysis of Super Conserved Receptors Expressed in the Brain Identifies EPB41L2, SLC3A2, and LRBA as Main Partners
Authors: Kaafarani Abeer , Darche-Gabinaud Romain , Bisteau Xavier , Imbault Virginie , Wittamer Valérie , Parmentier Marc , Pirson Isabelle
Published: November 2023

The Super-Conserved Receptors Expressed in the Brain (SREBs) form a subfamily of orphan G protein-coupled receptors, highly conserved in evolution and characterized by a predominant expression in the brain. The signaling pathways activated by these receptors (if any) are presently unclear. Given the strong conservation of their intracellular loops, we used a BioID2 proximity-labeling assay to identify protein partners of SREBs that would interact with these conserved domains. Using streptavidin pull-down followed by mass spectrometry analysis, we identified the amino acid transporter SLC3A2, the AKAP protein LRBA, and the 4.1 protein EPB41L2 as potential interactors of these GPCRs. Using co-immunoprecipitation experiments, we confirmed the physical association of these proteins with the receptors. We then studied the functional relevance of the interaction between EPB41L2 and SREB1. Immunofluorescence microscopy revealed that SREB1 and EPB41L2 co-localize at the plasma membrane and that SREB1 is enriched in the β-catenin-positive cell membranes. siRNA knockdown experiments revealed that EPB41L2 promotes the localization of SREB1 at the plasma membrane and increases the solubilization of SREB1 when using detergents, suggesting a modification of its membrane microenvironment. Altogether, these data suggest that EPB41L2 could regulate the subcellular compartmentalization of SREBs and, as proposed for other GPCRs, could affect their stability or activation.
Chemistry, Synthesis, and Structure Activity Relationship of Anticancer Quinoxalines
Authors: Zayed Mohamed F.
Published: November 2023

Quinoxaline is a fused heterocycle system of a benzene ring and pyrazine ring. It has earned considerable attention due to its importance in the field of medicinal chemistry. The system is of extensive importance due to its comprehensive array of biological activities. Quinoxaline derivatives have been used as anticancer, anticonvulsant, anti-inflammatory, antidiabetic, antioxidant, antibacterial, anti-TB, antimalarial, antiviral, anti-HIV, and many other uses. Variously substituted quinoxalines are significant therapeutic agents in the pharmaceutical industry. This review spotlights on the chemistry, physiochemical characters, synthesis, pharmaceutical products, and medicinal chemistry of various anticancer quinoxaline derivatives that were developed in the last period. It covers the period from 2016 to 2023.
Quantitative Determination of Fluoride Mass Concentration in Beers Produced in Croatia Using the Standard Addition Method in Potentiometry
Authors: Buljac Maša , Bralić Marija , Vladislavić Nives , Dugeč Josipa , Radić Josip
Published: November 2023

It is well known that beer is more than 90% water, and therefore, water can be one of the main sources of fluoride in beers. With this in mind, the goal of the present study was to determine the mass concentration of fluoride in 53 beer samples. Using the recently published standard addition method in potentiometry, the fluoride content of 28 samples of the most consumed beers in the Republic of Croatia was determined. The remaining 25 beer samples tested came from so-called microbreweries, which together account for less than 10% of the Croatian market. Fluoride concentrations in light beers ranged from 49 to 180 μg L−1, with a mean value of 95 ± 34 μg L−1, and from 52 to 164 μg L−1, with a mean value of 89 ± 29 μg L−1 in dark beers. The mean value of fluoride content in beers from large producers was 100 ± 38 μg L−1 and 89 ± 38 μg L−1 in beers from small producers. All values are within the recommended range and thus do not pose a risk to human health. The statistical analysis showed no correlation between the mass concentration of fluoride and pH, i.e., alcohol content in beers.
Parylene-AlOx Stacks for Improved 3D Encapsulation Solutions
Authors: Buchwalder Sébastien , Bourgeois Florian , Leon Juan J. Diaz , Hogg Andreas , Burger Jürgen
Published: November 2023

The demand for ultra-tight encapsulation solutions with excellent barrier and high conformality properties has increased in recent years. To meet these challenges, thin-film barrier coatings have emerged as a promising solution. In this study, we investigate well-established silicon-based plasma-enhanced chemical vapor deposition (PECVD) and metal oxide atomic layer deposition (ALD) barrier coatings deposited at low temperatures (≤100 °C) regarding their abilities to address high-level 3D encapsulation applications. Various combinations of such layers are evaluated by measuring the water vapor transmission rate (WVTR) and considering the conformality properties. The impact and the benefits of the organic film integration, namely parylene VT4 grade, on the barrier performances is assessed. Among these combinations, parylene-AlOx stack emerges as one of the most effective solutions, obtaining a WVTR of 3.1 × 10−4 g m−2 day−1 at 38 °C and 90% relative humidity conditions.
Composition of the Scent in Some Ophrys Orchids Growing in Basilicata (Southern Italy): A Solid-Phase Microextraction Study Coupled with Gas Chromatography and Mass Spectrometry
Authors: D’Auria Maurizio , Lorenz Richard , Mecca Marisabel , Racioppi Rocco , Romano Vito Antonio
Published: November 2023

Several methods have been used to determine the volatile organic compounds emitted by Ophrys orchids. The use of different methods results in incomparable data. Solid-phase microextraction (SPME) has not been used extensively on Ophrys orchids. The main components found in the SPME analysis of the scent in Ophrys orchids were as follows: O. apifera: benzyl benzoate and α-copaene; O. crabronifera subsp. biscutella: pentadecane, heptadecane, and nonadecane; O. bertolonii subsp. bertolonii: pentadecane and heptadecane; O. passionis subsp. garganica: i-propyl palmitate and heptadecane; O. holosericea subsp. apulica: α-copaene, pentadecane, and heptadecane; O. lacaitae: α-copaene, pentadecane, and heptadecane; O. bombyliflora: cyclosativene, pentadecane, and ethyl dodecanoate; O. insectifera: 8-heptadecene and pentadecane; O. lutea: heptadecane and docosane; O. tenthredinifera subsp. neglecta: α-copaene, caryophyllene, and i-propyl palmitate.
Utilizing an Attention-Based LSTM Model for Detecting Sarcasm and Irony in Social Media
Authors: Olaniyan Deborah , Ogundokun Roseline Oluwaseun , Bernard Olorunfemi Paul , Olaniyan Julius , Maskeliūnas Rytis , Akande Hakeem Babalola
Published: November 2023

Sarcasm and irony represent intricate linguistic forms in social media communication, demanding nuanced comprehension of context and tone. In this study, we propose an advanced natural language processing methodology utilizing long short-term memory with an attention mechanism (LSTM-AM) to achieve an impressive accuracy of 99.86% in detecting and interpreting sarcasm and irony within social media text. Our approach involves innovating novel deep learning models adept at capturing subtle cues, contextual dependencies, and sentiment shifts inherent in sarcastic or ironic statements. Furthermore, we explore the potential of transfer learning from extensive language models and integrating multimodal information, such as emojis and images, to heighten the precision of sarcasm and irony detection. Rigorous evaluation against benchmark datasets and real-world social media content showcases the efficacy of our proposed models. The outcomes of this research hold paramount significance, offering a substantial advancement in comprehending intricate language nuances in digital communication. These findings carry profound implications for sentiment analysis, opinion mining, and an enhanced understanding of social media dynamics.
X-ray Diffraction, Spectroscopy, Optical Properties, NPA, NBO, FMO, and Hirshfeld Surface Analyses of Two Newly Synthesized Piperidinium Ionic Liquids
Authors: El Bakri Youness , Mohamed Shaaban K. , Ahsin Atazaz , Bakhite Etify A. , Marae Islam S. , A. H. Al-waleedy Safiyyah , Mague Joel T. , Al-Salahi Rashad
Published: November 2023

The present study elaborates on the synthesis, crystal structure, and computational studies of two new ionic liquids. In the crystal structure, [C5H12N][C21H14ClN2O2S] (4a), the anions form chains along the a-axis direction through C—H···π(ring) interactions. These are connected into layers that run approximately parallel to the ac plane by a variety of hydrogen bonds. In the compound structure, [C5H12N][C18H15N2O2S] (4b), the two ions are primarily associated by an N—H···N hydrogen bond. In the crystal structure, layers parallel to the bc plane are formed by pairs of C—H···O and N—H···S hydrogen bonds and by C—H···π(ring) interactions. A theoretical study reveals that 4a has lower energy than 4b and is more stable. The NBO and DOS studies further confine the liquids’ structural reactivity and electronic properties. The quantum theory of atoms in a molecule (QTAIM) analysis reveals the important non-covalent interactions among the fragments and charge transfer. The global reactivity descriptors indicate their molecular reactivity relationship with the presence of functional groups. The remarkable polarizability (αo) and hyperpolarizability (βo) values indicate their optical and nonlinear optical (NLO) properties. Furthermore, the analysis performed by CrystalExplorer shows the intermolecular interactions and reactive sites between cations and anions in ionic liquids. The 2D fingerprint plots and Hirshfeld surfaces indicate the major interactions of crystals with neighboring elements in crystal packing. For both compounds, the H···H interactions are significantly higher than the other element interactions.
Designing Selection Indices for the Florida Dairy Goat Breeding Program
Authors: Ziadi Chiraz , Sánchez Manuel , Muñoz-Mejías Eva , Molina Antonio
Published: November 2023

The aim of this study was to compare selection indices for important traits in intensive Spanish goat breeds in four economic scenarios, using the Florida as most representative breed of this production system in Spain. For this analysis, we considered the following traits: milk yield (MY), fat plus protein yields (FPY), casein yield (CY), somatic cell score (SCS), reproductive efficiency (RE), litter size (LS), mammary system (MS), final score (FS), body capacity index (BCI), and length of productive life (LPL). We estimated the genetic parameters and EBVs of most of these traits with REML methodology, while LPL was modeled through survival analysis. Four scenarios were proposed, depending on the overall objective for improvement: (1) milk production, (2) milk production and cheese extract, (3) cheese extract, and (4) milk production, cheese extract and sale of animals. Then, within each scenario, three different types of indices were designed using the different primary and secondary objectives/criteria considered suitable to improve the overall objective. The results indicated that selecting only for primary traits yielded the highest genetic response for all the scenarios. Including secondary traits led to positive correlated responses in those traits, but a decrease in the responses in the primary criteria.
Crucial Role of Foxp3 Gene Expression and Mutation in Systemic Lupus Erythematosus, Inferred from Computational and Experimental Approaches
Authors: Birjan Zahra , Khashei Varnamkhasti Khalil , Parhoudeh Sara , Naeimi Leila , Naeimi Sirous
Published: November 2023

The impaired suppressive function of regulatory T cells is well-understood in systemic lupus erythematosus. This is likely due to changes in Foxp3 expression that are crucial for regulatory T-cell stability and function. There are a few reports on the correlation between the Foxp3 altered expression level and single-nucleotide polymorphisms within the Foxp3 locus. Moreover, some studies showed the importance of Foxp3 expression in the same diseases. Therefore, to explore the possible effects of single-nucleotide polymorphisms, here, we evaluated the association of IVS9+459/rs2280883 (T>C) and −2383/rs3761549 (C>T) Foxp3 polymorphisms with systemic lupus erythematosus. Moreover, through machine-learning and deep-learning methods, we assessed the connection of the expression level of the gene with the disease. Single-nucleotide polymorphisms of Foxp3 (IVS9+459/rs2280883 (T>C) and −2383/rs3761549 (C>T)) were, respectively, genotyped using allele-specific PCR and direct sequencing and polymerase chain reaction-restriction fragment length polymorphism, in 199 systemic lupus erythematosus patients and 206 healthy age- and sex-matched controls. The Statistical Package for the Social Sciences version 19 and Fisher’s exact and chi-square tests were used to analyze the data. Moreover, six machine-learning models and two sequential deep-learning models were designed to classify patients from normal people in the E-MTAB-11191 dataset through the expression level of Foxp3 and its correlated genes. The allele and genotype frequencies of both polymorphisms in question were found to be significantly associated with an increased risk of systemic lupus erythematosus. Furthermore, both of the two single-nucleotide polymorphisms were associated with some systemic-lupus-erythematosus-related risk factors. Three SVM models and the logistic regression model showed an 81% accuracy in classification problems. In addition, the first deep-learning model showed an 83% and 89% accuracy for the training and validation data, respectively, while the second model had an 85% and 79% accuracy for the training and validation datasets. In this study, we are prompted to represent the predisposing loci for systemic lupus erythematosus pathogenesis and strived to provide evidence-based support to the application of machine learning for the identification of systemic lupus erythematosus. It is predicted that the recruiting of machine-learning algorithms with the simultaneous measurement of the applied single nucleotide polymorphisms will increased the diagnostic accuracy of systemic lupus erythematosus, which will be very helpful in providing sufficient predictive value about individual subjects with systemic lupus erythematosus.
Vision-Based Deep Reinforcement Learning of UAV-UGV Collaborative Landing Policy Using Automatic Curriculum
Authors: Wang Chang , Wang Jiaqing , Wei Changyun , Zhu Yi , Yin Dong , Li Jie
Published: November 2023

Collaborative autonomous landing of a quadrotor Unmanned Aerial Vehicle (UAV) on a moving Unmanned Ground Vehicle (UGV) presents challenges due to the need for accurate real-time tracking of the UGV and the adjustment for the landing policy. To address this challenge, we propose a progressive learning framework for generating an optimal landing policy based on vision without the need of communication between the UAV and the UGV. First, we propose the Landing Vision System (LVS) to offer rapid localization and pose estimation of the UGV. Then, we design an Automatic Curriculum Learning (ACL) approach to learn the landing tasks under different conditions of UGV motions and wind interference. Specifically, we introduce a neural network-based difficulty discriminator to schedule the landing tasks according to their levels of difficulty. Our method achieves a higher landing success rate and accuracy compared with the state-of-the-art TD3 reinforcement learning algorithm.