bluuebunny/crossref_metadata_2025 huggingface dataset:
Construction of Fractional Pseudospectral Differentiation Matrices with Applications
Authors: Li Wenbin , Ma Hongjun , Zhao Tinggang
Published: May 2024

Differentiation matrices are an important tool in the implementation of the spectral collocation method to solve various types of problems involving differential operators. Fractional differentiation of Jacobi orthogonal polynomials can be expressed explicitly through Jacobi–Jacobi transformations between two indexes. In the current paper, an algorithm is presented to construct a fractional differentiation matrix with a matrix representation for Riemann–Liouville, Caputo and Riesz derivatives, which makes the computation stable and efficient. Applications of the fractional differentiation matrix with the spectral collocation method to various problems, including fractional eigenvalue problems and fractional ordinary and partial differential equations, are presented to show the effectiveness of the presented method.
Ionic Conductivity Analysis of NASICON Solid Electrolyte Coated with Polyvinyl-Based Polymers
Authors: Salgueiro Tiago Afonso , Veloso Rita Carvalho , Ventura João , Danzi Federico , Oliveira Joana
Published: May 2024

The global environmental crisis necessitates reliable, sustainable, and safe energy storage solutions. The current systems are nearing their capacity limits due to the reliance on conventional liquid electrolytes, which are fraught with stability and safety concerns, prompting the exploration of solid-state electrolytes, which enable the integration of metal electrodes. Solid-state sodium-ion batteries emerge as an appealing option by leveraging the abundance, low cost, and sustainability of sodium. However, low ionic conductivity and high interfacial resistance currently prevent their widespread adoption. This study explores polyvinyl-based polymers as wetting agents for the NASICON-type NZSP (Na3Zr2Si2PO12) solid electrolyte, resulting in a combined system with enhanced ionic conductivity suitable for Na-ion solid-state full cells. Electrochemical impedance spectroscopy (EIS) performed on symmetric cells employing NZSP paired with different wetting agent compositions demonstrates a significant reduction in interfacial resistance with the use of poly(vinyl acetate)—(PVAc-) based polymers, achieving an impressive ionic conductivity of 1.31 mS cm−1 at room temperature, 63.8% higher than the pristine material, notably reaching 7.36 mS cm−1 at 90 °C. These results offer valuable insights into the potential of PVAc-based polymers for advancing high-performance solid-state sodium-ion batteries by reducing their total internal resistance.
Toe Box Shape of Running Shoes Affects In-Shoe Foot Displacement and Deformation: A Randomized Crossover Study
Authors: Zhu Chengyuan , Song Yang , Xu Yufan , Zhu Aojie , Baker Julien S. , Liu Wei , Gu Yaodong
Published: May 2024

Background: Long-distance running is popular but associated with a high risk of injuries, particularly toe-related injuries. Limited research has focused on preventive measures, prompting exploration into the efficacy of raised toe box running shoes. Purpose: This study aimed to investigate the effect of running shoes with raised toe boxes on preventing toe injuries caused by distance running. Methods: A randomized crossover design involved 25 male marathon runners (height: 1.70 ± 0.02 m, weight: 62.6 + 4.5 kg) wearing both raised toe box (extended by 8 mm along the vertical axis and 3 mm along the sagittal axis) and regular toe box running shoes. Ground reaction force (GRF), in-shoe displacement, and degree of toe deformation (based on the distance change between the toe and the metatarsal head) were collected. Results: Wearing raised toe box shoes resulted in a significant reduction in vertical (p = 0.001) and antero–posterior (p = 0.015) ground reaction forces during the loading phase, with a notable increase in vertical ground reaction force during the toe-off phase (p < 0.001). In-shoe displacement showed significant decreased movement in the forefoot medial (p < 0.001) and rearfoot (medial: p < 0.001, lateral: p < 0.001) and significant increased displacement in the midfoot (medial: p = 0.002, lateral: p < 0.001). Impact severity on the hallux significantly decreased (p < 0.001), while impact on the small toes showed no significant reduction (p = 0.067). Conclusions: Raised toe box running shoes offer an effective means of reducing toe injuries caused by long-distance running.
Mycobacterium tuberculosis PE_PGRS38 Enhances Intracellular Survival of Mycobacteria by Inhibiting TLR4/NF-κB-Dependent Inflammation and Apoptosis of the Host
Authors: Ullah Hayan , Shi Xiaoxia , Taj Ayaz , Cheng Lin , Yan Qiulong , Sha Shanshan , Ahmad  , Kang Jian , Haris Muhammad , Ma Xiaochi , Ma Yufang
Published: May 2024

Mycobacterium tuberculosis (Mtb) ranks as the most lethal human pathogen, able to fend off repeated attacks by the immune system or medications. PE_PGRS proteins are hallmarks of the pathogenicity of Mtb and contribute to its antigenic diversity, virulence, and persistence during infection. M. smegmatis is a nonpathogenic mycobacterium that naturally lacks PE_PGRS and is used as a model to express Mtb proteins. PE_PGRS has the capability to evade host immune responses and enhance the intracellular survival of M. smegmatis. Despite the intense investigations into PE_PGRS proteins, their role in tuberculosis remains elusive. We engineered the recombinant M. smegmatis strain Ms-PE_PGRS38. The result shows that PE_PGRS38 is expressed in the cell wall of M. smegmatis. PE_PGRS38 contributes to biofilm formation, confers permeability to the cell wall, and shows variable responses to exogenous stresses. PE_PGRS38 downregulated TLR4/NF-κB signaling in RAW264.7 macrophages and lung tissues of infected mice. In addition, PE_PGRS38 decreased NLRP3-dependent IL-1β release and limited pathogen-mediated inflammasome activity during infection. Moreover, PE_PGRS38 inhibited the apoptosis of RAW264.7 cells by downregulating the expression of apoptotic markers including Bax, cytochrome c, caspase-3, and caspase-9. In a nutshell, our findings demonstrate that PE_PGRS38 is a virulence factor for Mtb that enables recombinant M. smegmatis to survive by resisting and evading the host’s immune responses during infection.
Functional Genomics and Insights into the Pathogenesis and Treatment of Psoriasis
Authors: Shellard Elan May , Rane Shraddha S. , Eyre Stephen , Warren Richard B.
Published: May 2024

Psoriasis is a lifelong, systemic, immune mediated inflammatory skin condition, affecting 1–3% of the world’s population, with an impact on quality of life similar to diseases like cancer or diabetes. Genetics are the single largest risk factor in psoriasis, with Genome-Wide Association (GWAS) studies showing that many psoriasis risk genes lie along the IL-23/Th17 axis. Potential psoriasis risk genes determined through GWAS can be annotated and characterised using functional genomics, allowing the identification of novel drug targets and the repurposing of existing drugs. This review is focused on the IL-23/Th17 axis, providing an insight into key cell types, cytokines, and intracellular signaling pathways involved. This includes examination of currently available biological treatments, time to relapse post drug withdrawal, and rates of primary/secondary drug failure, showing the need for greater understanding of the underlying genetic mechanisms of psoriasis and how they can impact treatment. This could allow for patient stratification towards the treatment most likely to reduce the burden of disease for the longest period possible.
Molecular Evolution of RAMOSA1 (RA1) in Land Plants
Authors: Bellino Carolina , Herrera Fernando E. , Rodrigues Daniel , Garay A. Sergio , Huck Sofía V. , Reinheimer Renata
Published: May 2024

RAMOSA1 (RA1) is a Cys2-His2-type (C2H2) zinc finger transcription factor that controls plant meristem fate and identity and has played an important role in maize domestication. Despite its importance, the origin of RA1 is unknown, and the evolution in plants is only partially understood. In this paper, we present a well-resolved phylogeny based on 73 amino acid sequences from 48 embryophyte species. The recovered tree topology indicates that, during grass evolution, RA1 arose from two consecutive SUPERMAN duplications, resulting in three distinct grass sequence lineages: RA1-like A, RA1-like B, and RA1; however, most of these copies have unknown functions. Our findings indicate that RA1 and RA1-like play roles in the nucleus despite lacking a traditional nuclear localization signal. Here, we report that copies diversified their coding region and, with it, their protein structure, suggesting different patterns of DNA binding and protein–protein interaction. In addition, each of the retained copies diversified regulatory elements along their promoter regions, indicating differences in their upstream regulation. Taken together, the evidence indicates that the RA1 and RA1-like gene families in grasses underwent subfunctionalization and neofunctionalization enabled by gene duplication.
Circulating Biomarkers in Pulmonary Arterial Hypertension: An Update
Authors: Correale Michele , Tricarico Lucia , Bevere Ester Maria Lucia , Chirivì Francesco , Croella Francesca , Severino Paolo , Mercurio Valentina , Magrì Damiano , Dini Frank , Licordari Roberto , Beltrami Matteo , Dattilo Giuseppe , Salzano Andrea , Palazzuoli Alberto
Published: May 2024

Pulmonary arterial hypertension (PAH) is a rare subtype of group 1 pulmonary hypertension (PH) diseases, characterized by high pulmonary artery pressure leading to right ventricular dysfunction and potential life-threatening consequences. PAH involves complex mechanisms: vasoconstriction, vascular remodeling, endothelial dysfunction, inflammation, oxidative stress, fibrosis, RV remodeling, cellular hypoxia, metabolic imbalance, and thrombosis. These mechanisms are mediated by several pathways, involving molecules like nitric oxide and prostacyclin. PAH diagnosis requires clinical evaluation and right heart catheterization, confirming a value of mPAP ≥ 20 mmHg at rest and often elevated pulmonary vascular resistance (PVR). Even if an early and accurate diagnosis is crucial, PAH still lacks effective biomarkers to assist in its diagnosis and prognosis. Biomarkers could contribute to arousing clinical suspicion and serve for prognosis prediction, risk stratification, and dynamic monitoring in patients with PAH. The aim of the present review is to report the main novelties on new possible biomarkers for the diagnosis, prognosis, and treatment monitoring of PAH.
Proteomic Insights into Osteoporosis: Unraveling Diagnostic Markers of and Therapeutic Targets for the Metabolic Bone Disease
Authors: Wang Jihan , Xue Mengju , Hu Ya , Li Jingwen , Li Zhenzhen , Wang Yangyang
Published: May 2024

Osteoporosis (OP), a prevalent skeletal disorder characterized by compromised bone strength and increased susceptibility to fractures, poses a significant public health concern. This review aims to provide a comprehensive analysis of the current state of research in the field, focusing on the application of proteomic techniques to elucidate diagnostic markers and therapeutic targets for OP. The integration of cutting-edge proteomic technologies has enabled the identification and quantification of proteins associated with bone metabolism, leading to a deeper understanding of the molecular mechanisms underlying OP. In this review, we systematically examine recent advancements in proteomic studies related to OP, emphasizing the identification of potential biomarkers for OP diagnosis and the discovery of novel therapeutic targets. Additionally, we discuss the challenges and future directions in the field, highlighting the potential impact of proteomic research in transforming the landscape of OP diagnosis and treatment.
Bone and Extracellular Signal-Related Kinase 5 (ERK5)
Authors: Wen Lei , Liu Zirui , Zhou Libo , Liu Zhongcheng , Li Qingda , Geng Bin , Xia Yayi
Published: May 2024

Bones are vital for anchoring muscles, tendons, and ligaments, serving as a fundamental element of the human skeletal structure. However, our understanding of bone development mechanisms and the maintenance of bone homeostasis is still limited. Extracellular signal-related kinase 5 (ERK5), a recently identified member of the mitogen-activated protein kinase (MAPK) family, plays a critical role in the pathogenesis and progression of various diseases, especially neoplasms. Recent studies have highlighted ERK5’s significant role in both bone development and bone-associated pathologies. This review offers a detailed examination of the latest research on ERK5 in different tissues and diseases, with a particular focus on its implications for bone health. It also examines therapeutic strategies and future research avenues targeting ERK5.
Bioarchitectural Design of Bioactive Biopolymers: Structure–Function Paradigm for Diabetic Wound Healing
Authors: Sharma Shivam , Kishen Anil
Published: May 2024

Chronic wounds such as diabetic ulcers are a major complication in diabetes caused by hyperglycemia, prolonged inflammation, high oxidative stress, and bacterial bioburden. Bioactive biopolymers have been found to have a biological response in wound tissue microenvironments and are used for developing advanced tissue engineering strategies to enhance wound healing. These biopolymers possess innate bioactivity and are biodegradable, with favourable mechanical properties. However, their bioactivity is highly dependent on their structural properties, which need to be carefully considered while developing wound healing strategies. Biopolymers such as alginate, chitosan, hyaluronic acid, and collagen have previously been used in wound healing solutions but the modulation of structural/physico-chemical properties for differential bioactivity have not been the prime focus. Factors such as molecular weight, degree of polymerization, amino acid sequences, and hierarchical structures can have a spectrum of immunomodulatory, anti-bacterial, and anti-oxidant properties that could determine the fate of the wound. The current narrative review addresses the structure–function relationship in bioactive biopolymers for promoting healing in chronic wounds with emphasis on diabetic ulcers. This review highlights the need for characterization of the biopolymers under research while designing biomaterials to maximize the inherent bioactive potency for better tissue regeneration outcomes, especially in the context of diabetic ulcers.
Research on Economic Load Dispatch Problem of Microgrid Based on an Improved Pelican Optimization Algorithm
Authors: Zhang Yi , Li Haoxue
Published: May 2024

This paper presents an improved pelican optimization algorithm (IPOA) to solve the economic load dispatch problem. The vertical crossover operator in the crisscross optimization algorithm is integrated to expand the diversity of the population in the local search phase. The optimal individual is also introduced to enhance its ability to guide the whole population and add disturbance factors to enhance its ability to jump out of the local optimal. The dimensional variation strategy is adopted to improve the optimal individual and speed up the algorithm’s convergence. The results of the IPOA showed that coal consumption was reduced by 0.0292%, 2.7273%, and 3.6739%, respectively, when tested on 10, 40, and 80-dimensional thermal power plant units compared to POA. The IPOA can significantly reduce the fuel cost of power plants.
Kiwi 4.0: In Vivo Real-Time Monitoring to Improve Water Use Efficiency in Yellow Flesh Actinidia chinensis
Authors: Vurro Filippo , Manfrini Luigi , Boini Alexandra , Bettelli Manuele , Buono Vito , Caselli Stefano , Gioli Beniamino , Zappettini Andrea , Palermo Nadia , Janni Michela
Published: May 2024

This manuscript reports the application of sensors for water use efficiency with a focus on the application of an in vivo OECT biosensor. In two distinct experimental trials, the in vivo sensor bioristor was applied in yellow kiwi plants to monitor, in real-time and continuously, the changes in the composition and concentration of the plant sap in an open field during plant growth and development. The bioristor response and physiological data, together with other fruit sensor monitoring data, were acquired and combined in both trials, giving a complete picture of the biosphere conditions. A high correlation was observed between the bioristor index (ΔIgs), the canopy cover expressed as the fraction of intercepted PAR (fi_PAR), and the soil water content (SWC). In addition, the bioristor was confirmed to be a good proxy for the occurrence of drought in kiwi plants; in fact, a period of drought stress was identified within the month of July. A novelty of the bioristor measurements was their ability to detect in advance the occurrence of defoliation, thereby reducing yield and quality losses. A plant-based irrigation protocol can be achieved and tailored based on real plant needs, increasing water use sustainability and preserving high-quality standards.
The Use of Generative Adversarial Network and Graph Convolution Network for Neuroimaging-Based Diagnostic Classification
Authors: Huynh Nguyen , Yan Da , Ma Yueen , Wu Shengbin , Long Cheng , Sami Mirza Tanzim , Almudaifer Abdullateef , Jiang Zhe , Chen Haiquan , Dretsch Michael N. , Denney Thomas S. , Deshpande Rangaprakash , Deshpande Gopikrishna
Published: May 2024

Functional connectivity (FC) obtained from resting-state functional magnetic resonance imaging has been integrated with machine learning algorithms to deliver consistent and reliable brain disease classification outcomes. However, in classical learning procedures, custom-built specialized feature selection techniques are typically used to filter out uninformative features from FC patterns to generalize efficiently on the datasets. The ability of convolutional neural networks (CNN) and other deep learning models to extract informative features from data with grid structure (such as images) has led to the surge in popularity of these techniques. However, the designs of many existing CNN models still fail to exploit the relationships between entities of graph-structure data (such as networks). Therefore, graph convolution network (GCN) has been suggested as a means for uncovering the intricate structure of brain network data, which has the potential to substantially improve classification accuracy. Furthermore, overfitting in classifiers can be largely attributed to the limited number of available training samples. Recently, the generative adversarial network (GAN) has been widely used in the medical field for its generative aspect that can generate synthesis images to cope with the problems of data scarcity and patient privacy. In our previous work, GCN and GAN have been designed to investigate FC patterns to perform diagnosis tasks, and their effectiveness has been tested on the ABIDE-I dataset. In this paper, the models will be further applied to FC data derived from more public datasets (ADHD, ABIDE-II, and ADNI) and our in-house dataset (PTSD) to justify their generalization on all types of data. The results of a number of experiments show the powerful characteristic of GAN to mimic FC data to achieve high performance in disease prediction. When employing GAN for data augmentation, the diagnostic accuracy across ADHD-200, ABIDE-II, and ADNI datasets surpasses that of other machine learning models, including results achieved with BrainNetCNN. Specifically, in ADHD, the accuracy increased from 67.74% to 73.96% with GAN, in ABIDE-II from 70.36% to 77.40%, and in ADNI, reaching 52.84% and 88.56% for multiclass and binary classification, respectively. GCN also obtains decent results, with the best accuracy in ADHD datasets at 71.38% for multinomial and 75% for binary classification, respectively, and the second-best accuracy in the ABIDE-II dataset (72.28% and 75.16%, respectively). Both GAN and GCN achieved the highest accuracy for the PTSD dataset, reaching 97.76%. However, there are still some limitations that can be improved. Both methods have many opportunities for the prediction and diagnosis of diseases.
Study on the Failure Process and Acoustic Emission Characteristics of Freeze–Thawed Sandstone under Cyclic Loading and Unloading
Authors: Yu Chaoyun , Huang Shenghui , Li Junkun , Wu Xiangye , Tian Yuhang , Bao Xiankai
Published: May 2024

In order to investigate freeze–thawed red sandstone failure processes under cyclic loading and unloading conditions, real-time acoustic emission (AE) and scanning electron microscopy (SEM) techniques were used to reveal the fracture process of the saturated red sandstone after cyclic loading and unloading tests using uniaxial compression. The results show that the stress–strain curves of the freeze–thawed sandstones show signs of hysteresis and exhibit a two-stage evolution of “sparse → dense”. In the cyclic loading and unloading process, the modulus of elasticity in the loading process is always larger than that in the unloading process, while the Poisson’s ratio is the opposite, and the radial irreversible strain and cumulative irreversible strain are larger than those in the axial direction. As the number of freeze–thaw cycles increases, the rock specimens need more cycles of loading and unloading to make the crack volume compressive strain Δεcv+ reach the maximum value and tend to stabilize, while the crack volume extensional strain Δεcv− tends to decrease gradually. This study also shows that the growth phase of the cyclic loading and unloading process has more ringing counts and a shorter duration, while the slow degradation phase has more ringing counts with loading and less with unloading. In addition, the F-T cycle gradually changes the internal microcracks of the red sandstone from shear damage, which is dominated by shear cracks, to tensile damage, which is dominated by tensile cracks. This study’s findings contribute to our knowledge of the mechanical characteristics and sandstone’s degradation process following F-T treatment, and also serve as a guide for engineering stability analyses conducted in the presence of multiphysical field coupling.
High-Resolution Mapping of Urban Residential Building Stock Using Multisource Geographic Data
Authors: Shen Lina , Wang Lei , Yang Qi , Ma Min
Published: May 2024

The rapid pace of urbanization and the increasing concentration of populations in urban areas have generated a substantial demand for architectural structures, resulting in a significant increase in building stock and continuous material flows that interact with the environment. This study emphasizes the importance of high-spatial-resolution mapping of residential building stock for effective urban-construction resource management, planning, and waste management. Focusing on Xi’an as a case study, the research develops a comprehensive framework for mapping urban residential building stock by integrating diverse data dimensions, including temporal, spatial, network, and multi-attribute aspects. The findings indicate that between 1990 and 2020, approximately 4758 residential communities were established in central Xi’an. The analysis of seven key residential construction materials revealed that the building stock escalated from 1.53 million tons to 731.12 million tons, with a steady spatial expansion of material distribution. The study attributes this growth to factors such as population increase, economic advancement, and policy initiatives, which, in turn, have driven the demand for residential building materials and reinforced the interdependence between urban expansion and residential construction development. Remarkably, from 1990 to 2020, the population surged by 2.1-fold, the economy by 66-fold, and the stock of residential building materials by 477-fold, indicating that the growth rate of material stock consistently outpaced that of both population and economic growth. Over the past three decades, the rapid expansion of residential buildings has led to the encroachment of urban ecological spaces by concrete structures. The methodology proposed in this study for quantifying building material offers valuable insights for policymakers and urban and environmental planners to foster responsible resource consumption and supports component-level circularity in the built environment.
Architectural Neuroimmunology: A Pilot Study Examining the Impact of Biophilic Architectural Design on Neuroinflammation
Authors: Valentine Cleo , Steffert Tony , Mitcheltree Heather , Steemers Koen
Published: May 2024

Recent research in architectural neuroscience has found that visual exposure to biophilic design may help reduce occupant physiological stress responses. However, there are still significant gaps in our understanding of the complex ways in which biophilic design impacts on building occupant neurophysiology. The relationship between visual exposure to biophilic design and neurophysiological responses such as neuroinflammation have yet to be directly investigated. This paper examines the results of a pilot study that was established to investigate the relationship between visual exposure to biophilic design and neuroinflammation, as mediated by physiological stress responses. The pilot study utilised a 32-channel quantitative electroencephalograph (qEEG) to assess the relative changes in neuroinflammatory markers (relative alpha and relative delta power band activity) of 10 participants while they were exposed to 2D digital images of buildings that visually expressed varying degrees of biophilic design. Participants exhibited a decrease in relative delta power when exposed to higher levels of biophilic design. No statistically significant changes in relative alpha power were observed. These findings suggest that exposure to buildings with higher degrees of biophilia may result in decreased neuroinflammatory activity. In doing so, this research works to further develop our understanding of the complex ways in which the built environment impacts on occupant neuroinflammation and physiological stress.
Calculation of Characteristic Point Parameters for Restoring Model of Corroded Short-Pier RC Shear Walls
Authors: Qin Qing , Cheng Haojie , Zhang Chenghua , Ding Sha
Published: May 2024

Based on the quasi-static tests of 12 corroded RC (reinforced concrete) shear walls, it was found that reinforcement corrosion has a great influence on the skeleton curve of RC shear walls. With an increase in the degree of corrosion, the bearing capacity of specimens decreases, and the deformation capacity worsens. Increasing the diameter of longitudinal reinforcements can significantly improve the bearing capacity of corroded RC shear walls, while the deformation capacity of corroded specimens can be improved by increasing the lateral distributed reinforcement or the transverse reinforcement in the embedded column. In order to accurately evaluate the seismic performance of corroded RC shear walls, we considered descent segments of four broken-line models to estimate the skeleton curve. After considering the influence of corrosion on the parameters of the characteristic point for the skeleton curve, the calculation formulas of the characteristic point parameters of the skeleton curve for the corroded RC shear wall were determined based on the test data fitting. It was proven that the formula for the characteristic point parameters for the skeleton curve of corroded RC shear walls has good applicability. This study lays a theoretical foundation for the seismic performance evaluation of an RC shear wall structure in a salt fog environment. It provides a theoretical basis for further improving the life-cycle seismic capacity evaluation system for RC structures.
Flexural Performance of Steel–Normal Concrete–Ultra-High-Performance Concrete Composite Slabs with Steel Ribs
Authors: Guo Songsong , Liu Chao , Ma Xiaogang
Published: May 2024

For steel–concrete composite bridges, the cracking of concrete in the tensile zone influences the serviceability of bridges and decreases their durability. UHPC, as a high-tensile and -durability material, is used to replace a part of the concrete to enhance the tensile performance. Thus, the steel–normal concrete–UHPC composite slab, as a new composite structure, is formed. This paper investigates the flexural behaviours of steel–normal concrete–UHPC composite slabs through a full-scale experiment, numerical simulation, and theoretical analysis. The research results indicate that (1) UHPC enhances the flexural performance of the tensile zone and delays the development of cracks. The initial cracking force of concrete increases from 44 kN to 91 kN. (2) UHPC effectively enhances the carrying capacity of composite slabs. A 50 mm UHPC layer makes the flexural bearing capacity of steel–concrete composite slabs increase by 13.51%. (3) The construction methods influence the initial cracking force of composite slabs. For full-span scaffolding construction, the initial cracking force decreases from 91 kN to 69 kN compared with construction without brackets. (4) The theoretical model considering the tensile contribution of cracking UHPC can accurately predict the bearing capacity of the composite slabs. And the theoretical values of the bearing capacity are lower than the experimental values, which makes the composite slabs safer in service.
The Role of Digital Inclusive Finance in Weakening Real Estate Market Speculation
Authors: Zhang Ruiwen , Pang Yiran
Published: May 2024

A multitude of studies have extensively examined strategies for achieving sustainable development in the real estate market. As the pivotal component of land economy, the real estate market plays a crucial role in ensuring its sound operation. However, it is currently undergoing significant adjustments and grappling with rampant speculative activities, resulting in an alarming bubble. By scrutinizing the speculative motivations of different entities, we present a novel perspective on mitigating speculation. Our analysis reveals that digital inclusive finance effectively curbs residents’ and enterprises’ speculative behavior, as evidenced by diminished prevention motivation and investment substitution motivation. Utilizing data from 280 cities, this study measures real estate market speculation by establishing a model that the volatility of the housing market turnover, as a proportion of GDP, deviates from the actual housing demand transactions based on economic fundamentals. Furthermore, it investigates the relationship between digital inclusive finance and real estate market speculation, along with its spatial effects. The findings indicate that digital inclusive finance significantly curbs real estate market speculation and has a negative spatial spillover effect. This research provides a novel model and perspective for exploring real estate market speculation while positively impacting sustainable development within the real estate market.
MIF and CD74 as Emerging Biomarkers for Immune Checkpoint Blockade Therapy
Authors: Fey Rosalyn M. , Nichols Rebecca A. , Tran Thuy T. , Vandenbark Arthur A. , Kulkarni Rajan P.
Published: May 2024

Immune checkpoint blockade (ICB) therapy is used to treat a wide range of cancers; however, some patients are at risk of developing treatment resistance and/or immune-related adverse events (irAEs). Thus, there is a great need for the identification of reliable predictive biomarkers for response and toxicity. The cytokine MIF (macrophage migration inhibitory factor) and its cognate receptor CD74 are intimately connected with cancer progression and have previously been proposed as prognostic biomarkers for patient outcome in various cancers, including solid tumors such as malignant melanoma. Here, we assess their potential as predictive biomarkers for response to ICB therapy and irAE development. We provide a brief overview of their function and roles in the context of cancer and autoimmune disease. We also review the evidence showing that MIF and CD74 may be of use as predictive biomarkers of patient response to ICB therapy and irAE development. We also highlight that careful consideration is required when assessing the potential of serum MIF levels as a biomarker due to its reported circadian expression in human plasma. Finally, we suggest future directions for the establishment of MIF and CD74 as predictive biomarkers for ICB therapy and irAE development to guide further research in this field.
Recent Advances in the Development of Nanocarbon-Based Electrocatalytic/Electrode Materials for Proton Exchange Membrane Fuel Cells: A Review
Authors: Zasypkina Adelina A. , Ivanova Nataliya A. , Spasov Dmitry D. , Mensharapov Ruslan M. , Sinyakov Matvey V. , Grigoriev Sergey A.
Published: May 2024

The global issue for proton exchange membrane fuel cell market development is a reduction in the device cost through an increase in efficiency of the oxygen reduction reaction occurring at the cathode and an extension of the service life of the electrochemical device. Losses in the fuel cell performance are due to various degradation mechanisms in the catalytic layers taking place under conditions of high electric potential, temperature, and humidity. This review is devoted to recent advances in the field of increasing the efficiency and durability of electrocatalysts and other electrode materials by introducing structured carbon components into their composition. The main synthesis methods, physicochemical and electrochemical properties of materials, and performance of devices on their basis are presented. The main correlations between the composition and properties of structured carbon electrode materials, which can provide successful solutions to the highlighted issues, are revealed.
Functionalized Chitosan and Alginate Composite Hydrogel-Immobilized Laccase with Sustainable Biocatalysts for the Effective Removal of Organic Pollutant Bisphenol A
Authors: Zhang Hong , Zhang Xin , Wang Lei , Wang Bo , Zeng Xu , Ren Bo
Published: May 2024

The immobilization of enzymes is an important strategy to improve their stability and reusability. Enzyme immobilization technology has broad application prospects in biotechnology, biochemistry, environmental remediation, and other fields. In this study, composites of chitosan (CS) and sodium alginate (SA) with Cu2+ forming a double-network crosslinked structure of hydrogels were prepared and used for the immobilization of laccase. Fourier infrared spectroscopy, scanning electron microscopy, and X-ray photoelectron spectroscopy tests revealed that laccase molecules were immobilized on the composite hydrogel surface by a covalent bonding method. Compared to free laccase, the pH, temperature, and storage stability of the immobilized laccase were markedly improved. In addition, the immobilized laccase could be easily separated from the reaction system and reused, and it maintained 81.6% of its initial viability after six cycles of use. Bisphenol A (BPA) in polluted water was efficiently degraded using immobilized laccase, and the factors affecting the degradation efficiency were analyzed. Under the optimal conditions, the BPA removal was greater than 82%, and the addition of a small amount of ABTS had a significant effect on BPA degradation, with a removal rate of up to 99.1%. Experimental results indicated that immobilized laccases had enormous potential in actual industrial applications.
Nuclear mTOR Signaling Orchestrates Transcriptional Programs Underlying Cellular Growth and Metabolism
Authors: Zhao Tinghan , Fan Jialin , Abu-Zaid Ahmed , Burley Stephen , Zheng X.F.
Published: May 2024

mTOR is a central regulator of cell growth and metabolism in response to mitogenic and nutrient signals. Notably, mTOR is not only found in the cytoplasm but also in the nucleus. This review highlights direct involvement of nuclear mTOR in regulating transcription factors, orchestrating epigenetic modifications, and facilitating chromatin remodeling. These effects intricately modulate gene expression programs associated with growth and metabolic processes. Furthermore, the review underscores the importance of nuclear mTOR in mediating the interplay between metabolism and epigenetic modifications. By integrating its functions in nutrient signaling and gene expression related to growth and metabolism, nuclear mTOR emerges as a central hub governing cellular homeostasis, malignant transformation, and cancer progression. Better understanding of nuclear mTOR signaling has the potential to lead to novel therapies against cancer and other growth-related diseases.
Comprehensive Analysis of CXCR4, JUNB, and PD-L1 Expression in Circulating Tumor Cells (CTCs) from Prostate Cancer Patients
Authors: Roumeliotou Argyro , Strati Areti , Chamchougia Foteini , Xagara Anastasia , Tserpeli Victoria , Smilkou Stavroula , Lagopodi Elina , Christopoulou Athina , Kontopodis Emmanouil , Drositis Ioannis , Androulakis Nikolaos , Georgoulias Vassilis , Koinis Filippos , Kotsakis Athanasios , Lianidou Evi , Kallergi Galatea
Published: May 2024

CXCR4, JUNB and PD-L1 are implicated in cancer progression and metastasis. The current study investigated these biomarkers in CTCs isolated from metastatic prostate cancer (mPCa) patients at the RNA and protein levels. CTCs were isolated from 48 mPCa patients using the Ficoll density gradient and ISET system (17 out of 48). The (CK/PD-L1/CD45) and (CK/CXCR4/JUNB) phenotypes were identified using two triple immunofluorescence stainings followed by VyCAP platform analysis. Molecular analysis was conducted with an EpCAM-dependent method for 25/48 patients. CK-8, CK-18, CK-19, JUNB, CXCR4, PD-L1, and B2M (reference gene) were analyzed with RT-qPCR. The (CK+/PD-L1+/CD45-) and the (CK+/CXCR4+/JUNB+) were the most frequent phenotypes (61.1% and 62.5%, respectively). Furthermore, the (CK+/CXCR4+/JUNB-) phenotype was correlated with poorer progression-free survival [(PFS), HR: 2.5, p = 0.049], while the (CK+/PD-L1+/CD45-) phenotype was linked to decreased overall survival [(OS), HR: 262.7, p = 0.007]. Molecular analysis revealed that 76.0% of the samples were positive for CK-8,18, and 19, while 28.0% were positive for JUNB, 44.0% for CXCR4, and 48.0% for PD-L1. Conclusively, CXCR4, JUNB, and PD-L1 were highly expressed in CTCs from mPCa patients. The CXCR4 protein expression was associated with poorer PFS, while PD-L1 was correlated with decreased OS, providing new biomarkers with potential clinical relevance.
Mechanical Dewatering of Homogeneous and Segregated Filter Cakes by Vibration Compaction
Authors: Yildiz Tolga , Stankovic Una , Zolg Julius , Gleiß Marco , Nirschl Hermann
Published: May 2024

The solid volume fraction of a slurry requiring solid–liquid separation often fluctuates in industrial cake filtration processes. For low solid volume fractions, particle segregation arises, resulting in an inhomogeneous filter cake structure. Particle segregation has significant impacts on cake formation such as a longer cake formation time compared to homogeneous cakes. This work addresses the impact of this effect on vibration compaction, which is an alternative deliquoring method applying oscillatory shears to the filter cake. The dewatering results of homogeneous and segregated cakes made of the same material with a broad particle size distribution are compared. Although cake deliquoring is achievable despite particle segregation, vibration compaction is more effective for homogeneous cakes. The reason is that no particle size homogenization within segregated cakes occurs due to oscillatory shear, as particle size analyses indicate. The particle size measurements of cakes before and after vibration compaction reveal that the material’s particle size distribution is preserved despite vibration application. Vibration compaction achieves higher deliquoring than the common compaction method by squeezing, as elastic recovery effects after squeezing lead to the reabsorbing of liquid, already expressed and stored in the filter cloth. This demonstrates that vibration compaction is a real alternative for cake deliquoring.
A High-Precision Monitoring Method Based on SVM Regression for Multivariate Quantitative Analysis of PID Response to VOC Signals
Authors: Feng Xiujuan , Liu Zengyuan , Ren Yongjun , Dong Chengliang
Published: May 2024

In the moist environment of soil-water-air, there is a problem of low accuracy in monitoring volatile organic compounds (VOCs) using a photoionization detector (PID). This study is based on the PID water-soil-gas VOC online monitor developed by this group, online monitoring of the concentration of different constituents of VOCs in different production enterprises of the petroleum and chemical industries in Shandong Province, with the concentration of the laboratory test, to build a relevant model. The correlation coefficient about the PID test concentration and the actual concentration correlation coefficient was obtained through the collection of a large number of data trainings. Based on the application of PID in VOC monitoring, the establishment of a PID high-precision calibration model is important for the precise monitoring of VOCs. In this paper, multiple quantitative analyses were conducted, based on SVM regression of PID response to VOC signals, to study the high-precision VOC monitoring method. To select the response signals of PID under different concentrations of environmental VOCs measured by the research group, first, the PID response to VOC signals was modeled using the support vector machine principle to verify the effect of traditional SVM regression. For the problem of raw data redundancy, calculate the time-domain and frequency-domain characteristics of the PID signal, and conduct the principal component analysis of the time-domain of the PID signal. In order to make the SVM regression more generalized and robust, the selection of kernel function parameters and penalty factor of SVM is optimized by genetic algorithm. By comparing the accuracy of PID calibration models such as PID signal feature extraction, SVM regression, and principal component analysis SVM regression, the superiority of photoionization detector using the signal feature extraction PCA-GA-SVM method to monitor VOCs is verified.
A Tissue Engineered 3D Model of Cancer Cell Invasion for Human Head and Neck Squamous-Cell Carcinoma
Authors: Stöth Manuel , Mineif Anna Teresa , Sauer Fabian , Meyer Till Jasper , Mueller-Diesing Flurin , Haug Lukas , Scherzad Agmal , Steinke Maria , Rossi Angela , Hackenberg Stephan
Published: May 2024

Head and neck squamous-cell carcinoma (HNSCC) is associated with aggressive local invasiveness, being a main reason for its poor prognosis. The exact mechanisms underlying the strong invasive abilities of HNSCC remain to be elucidated. Therefore, there is a need for in vitro models to study the interplay between cancer cells and normal adjacent tissue at the invasive tumor front. To generate oral mucosa tissue models (OMM), primary keratinocytes and fibroblasts from human oral mucosa were isolated and seeded onto a biological scaffold derived from porcine small intestinal submucosa with preserved mucosa. Thereafter, we tested different methods (single tumor cells, tumor cell spots, spheroids) to integrate the human cancer cell line FaDu to generate an invasive three-dimensional model of HNSCC. All models were subjected to morphological analysis by histology and immunohistochemistry. We successfully built OMM tissue models with high in vivo–in vitro correlation. The integration of FaDu cell spots and spheroids into the OMM failed. However, with the integration of single FaDu cells into the OMM, invasive tumor cell clusters developed. Between segments of regular epithelial differentiation of the OMM, these clusters showed a basal membrane penetration and lamina propria infiltration. Primary human fibroblasts and keratinocytes seeded onto a porcine carrier structure are suitable to build an OMM. The HNSCC model with integrated FaDu cells could enable subsequent investigations into cancer cell invasiveness.
Structural and Dynamic Features of the Recognition of 8-oxoguanosine Paired with an 8-oxoG-clamp by Human 8-oxoguanine-DNA Glycosylase
Authors: Lukina Maria V. , Zhdanova Polina V. , Koval Vladimir V.
Published: May 2024

8-oxoguanine (oxoG) is formed in DNA by the action of reactive oxygen species. As a highly mutagenic and the most common oxidative DNA lesion, it is an important marker of oxidative stress. Human 8-oxoguanine-DNA glycosylase (OGG1) is responsible for its prompt removal in human cells. OGG1 is a bifunctional DNA glycosylase with N-glycosylase and AP lyase activities. Aspects of the detailed mechanism underlying the recognition of 8-oxoguanine among numerous intact bases and its subsequent interaction with the enzyme’s active site amino acid residues are still debated. The main objective of our work was to determine the effect (structural and thermodynamic) of introducing an oxoG-clamp in model DNA substrates on the process of 8-oxoG excision by OGG1. Towards that end, we used DNA duplexes modeling OGG1-specific lesions: 8-oxoguanine or an apurinic/apyrimidinic site with either cytidine or the oxoG-clamp in the complementary strand opposite to the lesion. It was revealed that there was neither hydrolysis of the N-glycosidic bond at oxoG nor cleavage of the sugar–phosphate backbone during the reaction between OGG1 and oxoG-clamp-containing duplexes. Possible structural reasons for the absence of OGG1 enzymatic activity were studied via the stopped-flow kinetic approach and molecular dynamics simulations. The base opposite the damage was found to have a critical effect on the formation of the enzyme–substrate complex and the initiation of DNA cleavage. The oxoG-clamp residue prevented the eversion of the oxoG base into the OGG1 active site pocket and impeded the correct convergence of the apurinic/apyrimidinic site of DNA and the attacking nucleophilic group of the enzyme. An obtained three-dimensional model of the OGG1 complex with DNA containing the oxoG-clamp, together with kinetic data, allowed us to clarify the role of the contact of amino acid residues with DNA in the formation of (and rearrangements in) the enzyme–substrate complex.
Colorectal Cancer Detection via Metabolites and Machine Learning
Authors: Yang Rachel , Tsigelny Igor F. , Kesari Santosh , Kouznetsova Valentina L.
Published: May 2024

Today, colorectal cancer (CRC) diagnosis is performed using colonoscopy, which is the current, most effective screening method. However, colonoscopy poses risks of harm to the patient and is an invasive process. Recent research has proven metabolomics as a potential, non-invasive detection method, which can use identified biomarkers to detect potential cancer in a patient’s body. The aim of this study is to develop a machine-learning (ML) model based on chemical descriptors that will recognize CRC-associated metabolites. We selected a set of metabolites found as the biomarkers of CRC, confirmed that they participate in cancer-related pathways, and used them for training a machine-learning model for the diagnostics of CRC. Using a set of selective metabolites and random compounds, we developed a range of ML models. The best performing ML model trained on Stage 0–2 CRC metabolite data predicted a metabolite class with 89.55% accuracy. The best performing ML model trained on Stage 3–4 CRC metabolite data predicted a metabolite class with 95.21% accuracy. Lastly, the best-performing ML model trained on Stage 0–4 CRC metabolite data predicted a metabolite class with 93.04% accuracy. These models were then tested on independent datasets, including random and unrelated-disease metabolites. In addition, six pathways related to these CRC metabolites were also distinguished: aminoacyl-tRNA biosynthesis; glyoxylate and dicarboxylate metabolism; glycine, serine, and threonine metabolism; phenylalanine, tyrosine, and tryptophan biosynthesis; arginine biosynthesis; and alanine, aspartate, and glutamate metabolism. Thus, in this research study, we created machine-learning models based on metabolite-related descriptors that may be helpful in developing a non-invasive diagnosis method for CRC.