bluuebunny/crossref_metadata_2025 huggingface dataset:
Molecular Basis of Energy Crops Functioning in Bioremediation of Heavy Metal Pollution
Authors: Huang Shuoqi , Lu Zhenqiang , Zhao Xiaoxin , Tan Wenbo , Wang Hao , Liu Dali , Xing Wang
Published: June 2024

Heavy metal pollution is a gradually growing environmental issue that hinders the growth and development of plants, and also destabilizes soil. Consequently, eco-friendly phytoremediation methods have gained traction, with energy crops emerging as a particularly effective solution. Energy crops not only provide high-quality plant materials for detoxification and remediation of heavy metal pollution, but also possess energy properties conducive to biofuel production. Therefore, this paper delves into the tolerance mechanism of energy crops towards heavy metal toxicity, elucidating processes such as root complex-mediated inhibition of metal migration and response to reactive oxygen species (ROS) through heavy metal-related proteins, enzyme systems, reactive nitrogen species (RNS), and hormones. Moreover, it summarizes the heavy metals remediation mechanisms of energy crops, including uptake, translocation, chelation, immobilization, and sequestration. This paper explores applications of energy crops in heavy metal pollution remediation, emphasizing the methods for efficient biochar remediation and biofuel generation. Furthermore, potential challenges in using energy crops for heavy metal pollution remediation are outlined. By systematically examining the function mechanisms and prospective applications of energy crops in heavy metal pollution bioremediation, this paper serves as a valuable reference for both research and practical implementation in this field.
The Lifting Performance and Experimental Study of a Variable Spiral Spike-Toothed Crop Divider
Authors: Bai Jing , Ma Shaochun , Cheng Chao
Published: June 2024

The contact between a traditional crop divider and sugarcane is unstable, and the sugarcane easily slides off of its surface. By analyzing the movement process of sugarcane, the influence of traditional spiral flightings on lifting performance was studied, and shortcomings were also found. Based on previous research and analysis, the variable spiral spike-toothed crop divider was designed by research groups. For sugarcane with different lodging states, the contact separation rule between the sugarcane and the spike tooth was studied, and the action time and angle of the spike tooth on sugarcane were obtained. At the same time, the interaction mechanism between sugarcane and the spike tooth was analyzed, and the conditions for lodged canes to be lifted were obtained. The influence of the spike tooth on the lifting performance was explored, and the working advantages were found for the spike-toothed crop divider. Then, a simulation test was conducted to obtain the contact force between the sugarcane and the crop divider. Finally, the crop divider was optimized and integrated into the harvester, and a field harvesting test was carried out to verify the working performance of the crop divider. This study was expected to provide a reference for the design of crop dividers and a theoretical basis for the analysis of the lifting process.
Effect of Application of a Cactus Pear Mucilage-Based Edible Coating Enriched with Glycerol and L-Glutamine on Minimally Processed White-Flesh Loquats
Authors: Greco Giuseppe , Gargano Francesco , Motta Miriam La , Gugino Ignazio Maria , Liguori Giorgia
Published: June 2024

Loquat (Eriobotrya japonica Lindl.), a non-climacteric fruit, is susceptible to physical and mechanical damage, as well as decay, especially after minimal processing, resulting in a short postharvest lifespan The objective of our study was to evaluate the impact of a cactus pear (OFI) mucilage-based edible coating enriched with glycerol and l-glutamine on the quality and nutraceutical value of minimally processed white-flesh Martorana loquat fruits during cold storage. After washing and processing the cladodes, mucilage was extracted, and two different coatings (EC1: 60% OFI mucilage, 40% glycerol; EC2: 67% OFI mucilage, 30% glycerol, 3% glutamine) were formulated and compared with an untreated sample (CTR). Our analyses covered various parameters, including color, total soluble solid content, titratable acidity, antioxidant activity, and total phenols. Additionally, sensory analysis was conducted and visual scores were obtained. The results suggest that the application of a cactus pear mucilage-based edible coating, supplemented with glycerol and L-glutamine, effectively preserves the quality attributes of minimally processed loquat fruits.
Recognition Model for Tea Grading and Counting Based on the Improved YOLOv8n
Authors: Xia Yuxin , Wang Zejun , Cao Zhiyong , Chen Yaping , Li Limei , Chen Lijiao , Zhang Shihao , Wang Chun , Li Hongxu , Wang Baijuan
Published: June 2024

Grading tea leaves efficiently in a natural environment is a crucial technological foundation for the automation of tea-picking robots. In this study, to solve the problems of dense distribution, limited feature-extraction ability, and false detection in the field of tea grading recognition, an improved YOLOv8n model for tea grading and counting recognition was proposed. Firstly, the SPD-Conv module was embedded into the backbone of the network model to enhance the deep feature-extraction ability of the target. Secondly, the Super-Token Vision Transformer was integrated to reduce the model’s attention to redundant information, thus improving its perception ability for tea. Subsequently, the loss function was improved to MPDIoU, which accelerated the convergence speed and optimized the performance. Finally, a classification-positioning counting function was added to achieve the purpose of classification counting. The experimental results showed that, compared to the original model, the precision, recall and average precision improved by 17.6%, 19.3%, and 18.7%, respectively. The average precision of single bud, one bud with one leaf, and one bud with two leaves were 88.5%, 89.5% and 89.1%. In this study, the improved model demonstrated strong robustness and proved suitable for tea grading and edge-picking equipment, laying a solid foundation for the mechanization of the tea industry.
Mechanisms of Embryonic Stem Cell Pluripotency Maintenance and Their Application in Livestock and Poultry Breeding
Authors: Wang Ziyu , Gong Wei , Yao Zeling , Jin Kai , Niu Yingjie , Li Bichun , Zuo Qisheng
Published: June 2024

Embryonic stem cells (ESCs) are remarkably undifferentiated cells that originate from the inner cell mass of the blastocyst. They possess the ability to self-renew and differentiate into multiple cell types, making them invaluable in diverse applications such as disease modeling and the creation of transgenic animals. In recent years, as agricultural practices have evolved from traditional to biological breeding, it has become clear that pluripotent stem cells (PSCs), either ESCs or induced pluripotent stem cells (iPSCs), are optimal for continually screening suitable cellular materials. However, the technologies for long-term in vitro culture or establishment of cell lines for PSCs in livestock are still immature, and research progress is uneven, which poses challenges for the application of PSCs in various fields. The establishment of a robust in vitro system for these cells is critically dependent on understanding their pluripotency maintenance mechanisms. It is believed that the combined effects of pluripotent transcription factors, pivotal signaling pathways, and epigenetic regulation contribute to maintaining their pluripotent state, forming a comprehensive regulatory network. This article will delve into the primary mechanisms underlying the maintenance of pluripotency in PSCs and elaborate on the applications of PSCs in the field of livestock.
Duration of Protection and Humoral Immune Response in Nile Tilapia (Oreochromis niloticus L.) Vaccinated against Streptococcus agalactiae
Authors: Queiróz Guilherme Alves de , Silva Tarcísio Martins França e , Leal Carlos Augusto Gomes
Published: June 2024

Streptococcosis caused by Streptococcus agalactiae (S. agalactiae) is a major bacterial disease affecting the production of Nile tilapia (Oreochromis niloticus L.), causing significant economic losses due to mortality in the growing phase. Vaccination is the most effective method for preventing streptococcosis on Nile tilapia farms. In Brazil, the major tilapia-producing regions have long production cycles (6–10 months) and harvest tilapias weighing over 900 g for fillet production. Thus, data on the duration of the humoral immune response and protection in farmed tilapia have not been reported or are poorly described. Furthermore, the efficiency of serological testing for the long-term monitoring of immune responses induced by vaccination against S. agalactiae has never been addressed. This study evaluated the duration of protection and humoral immune response induced in Nile tilapia vaccinated against S. agalactiae until 300 days post-vaccination (dpv). The immunization trial was composed of two groups: vaccinated (Vac), vaccinated intraperitoneally with a commercial vaccine, and unvaccinated (NonVac) group, injected fish with sterile saline solution. At 15, 30, 150, 180, 210, and 300 dpv, blood sampling was conducted to detect anti-S. agalactiae IgM antibodies using indirect Enzyme-Linked Immunosorbent Assay (ELISA), and the fish were challenged with pathogenic S. agalactiae to determine the duration of vaccine protection through relative percentage survival (RPS). Spearman’s rank correlation was performed between the ELISA optical density (OD) of vaccinated tilapia and the duration of vaccine protection (RPS). The mean cumulative mortality in NonVac and Vac groups ranged from 65 to 90% and less than 35%, respectively. The average RPS was 71, 93, 94, 70, 86, and 67% at 15, 30, 150, 180, 210, and 300 dpv, respectively. RPS revealed that the vaccine provided protection from 15 to 300 dpv. The specific anti-S. agalactiae IgM antibody levels were significantly higher in the Vac group than that non-Vac group up to 180 dpv. The vaccinated fish exhibited significant protection for up to 10 months after vaccination. There was a positive correlation between the antibody response and RPS. This study revealed that a single dose of commercial vaccine administered to Nile tilapia can confer long-term protection against S. agalactiae and that indirect ELISA can monitor the duration of the humoral immune response for up to six months following vaccination. Finally, vaccine protection over six months can be associated with other components of the fish immune system beyond the humoral immune response by IgM antibodies.
Hypothalamic Neuromodulation and Control of the Dermal Surface Temperature of Livestock during Hyperthermia
Authors: Sarubbi Juliana , Martínez-Burnes Julio , Ghezzi Marcelo Daniel , Olmos-Hernandez Adriana , Lendez Pamela Anahí , Ceriani María Carolina , Hernández-Avalos Ismael
Published: June 2024

Hyperthermia elicits several physiological and behavioral responses in livestock to restore thermal neutrality. Among these responses, vasodilation and sweating help to reduce core body temperature by increasing heat dissipation by radiation and evaporation. Thermoregulatory behaviors such as increasing standing time, reducing feed intake, shade-seeking, and limiting locomotor activity also increase heat loss. These mechanisms are elicited by the connection between peripheral thermoreceptors and cerebral centers, such as the preoptic area of the hypothalamus. Considering the importance of this thermoregulatory pathway, this review aims to discuss the hypothalamic control of hyperthermia in livestock, including the main physiological and behavioral changes that animals adopt to maintain their thermal stability.
Do High Doses of Multiple Antibiotics Loaded into Bone Cement Spacers Improve the Success Rate in Staphylococcal Periprosthetic Joint Infection When Rifampicin Cannot Be Employed?
Authors: Prats-Peinado Lourdes , Fernández-Fernández Tanya , Márquez-Gómez Miguel , Matas-Diaz José Antonio , Sánchez-Somolinos Mar , de la Villa-Martínez Sofía , Vaquero-Martín Javier , Sanz-Ruiz Pablo
Published: June 2024

Rifampicin is one of the mainstays in treating staphylococcal prosthetic joint infection (PJI). However, discontinuation due to intolerance, drug interactions, and adverse events is common. Two-stage revision surgery remains the gold standard, with the number of revision arthroplasties steadily increasing. This study aims to evaluate the effectiveness and safety of a novel two-stage revision protocol for staphylococcal prosthetic joint infection (PJI) utilizing bone cement spacers loaded with multiple high doses of antibiotics. Additionally, it seeks to analyze outcomes in patients ineligible for rifampicin treatment. A retrospective review of 43 cases of staphylococcal hip and knee prosthetic joint infections (PJIs) from 2012 to 2020 was conducted. In all instances, a commercial cement containing 1 g of gentamicin and 1 g of clindamycin, augmented with 4 g of vancomycin and 2 g of ceftazidime, was employed to cast a spacer manually after thorough surgical debridement. We report an eradication rate of 82%, with no significant differences observed (p = 0.673) between patients treated with (84%, n = 19) and without rifampicin (79%, n = 24). There were no disparities in positive culture rates (7%), spacer replacement (18%), or survival analysis (p = 0.514) after an average follow-up of 68 months (range 10–147) in the absence of systemic toxicity and surgical complications superimposable to those previously reported. In conclusion, two-stage revision with local high doses of ceftazidime, vancomycin, gentamicin, and clindamycin demonstrates high effectiveness in treating staphylococcal PJIs. Notably, systemic rifampicin does not influence the outcomes. This protocol, with multiple high doses of antibiotics loaded into the bone cement spacer, is presented as a viable and safe alternative for patients unsuitable for rifampicin treatment.
Environmentally Relevant Antibiotic Concentrations Exert Stronger Selection Pressure on River Biofilm Resistomes than AMR-Reservoir Effluents
Authors: Flores-Vargas Gabriela , Bergsveinson Jordyn , Korber Darren R.
Published: June 2024

Freshwater environments are primary receiving systems of wastewater and effluents, which carry low concentrations of antibiotics and antimicrobial-resistant (AMR) bacteria and genes. Aquatic microbial communities are thus exposed to environmentally relevant concentrations of antibiotics (ERCA) that presumably influence the acquisition and spread of environmental AMR. Here, we analyzed ERCA exposure with and without the additional presence of municipal wastewater treatment plant effluent (W) and swine manure run-off (M) on aquatic biofilm resistomes. Microscopic analyses revealed decreased taxonomic diversity and biofilm structural integrity, while metagenomic analysis revealed an increased abundance of resistance, virulence, and mobile element-related genes at the highest ERCA exposure levels, with less notable impacts observed when solely exposed to W or M effluents. Microbial function predictions indicated increased gene abundance associated with energy and cell membrane metabolism and heavy metal resistance under ERCA conditions. In silico predictions of increased resistance mechanisms did not correlate with observed phenotypic resistance patterns when whole communities were exposed to antimicrobial susceptibility testing. This reveals important insight into the complexity of whole-community coordination of physical and genetic responses to selective pressures. Lastly, the environmental AMR risk assessment of metagenomic data revealed a higher risk score for biofilms grown at sub-MIC antibiotic conditions.
Linear Contact Load Law of an Elastic–Perfectly Plastic Half-Space vs. Sphere under Low Velocity Impact
Authors: Yuan Hao , Yin Xiaochun , Wang Hui , Guo Yuanyuan , Wang Changliang , Zhou Hao , Gao Cheng , Ding Huaiping , Deng Xiaokai
Published: June 2024

The impact of contact between two elastic–plastic bodies is highly complex, with no established theoretical contact model currently available. This study investigates the problem of an elastic–plastic sphere impacting an elastic–plastic half-space at low speed and low energy using the finite element method (FEM). Existing linear contact loading laws exhibit significant discrepancies as they fail to consider the impact of elasticity and yield strength on the elastic–plastic sphere. To address this limitation, a novel linear contact loading law is proposed in this research, which utilizes the concept of equivalent contact stiffness rather than the conventional linear contact stiffness. The theoretical expressions of this new linear contact loading law are derived through FEM simulations of 150 sphere and half-space impact cases. The segmental linear characteristics of the equivalent contact stiffness are identified and fitted to establish the segmental expressions of the equivalent contact stiffness. The new linear contact loading law is dependent on various factors, including the yield strain of the half-space, the ratio of elastic moduli between the half-space and sphere, and the ratio of yield strengths between the half-space and sphere. The accuracy of the proposed linear contact loading law is validated through extensive Finite Element Method simulations, which involve an elastic–plastic half-space being struck by elastic–plastic spheres with varying impact energies, sizes, and material combinations.
Multi-Feature-Enhanced Academic Paper Recommendation Model with Knowledge Graph
Authors: Wang Le , Du Wenna , Chen Zehua
Published: June 2024

This paper addresses the challenges of data sparsity and personalization limitations inherent in current recommendation systems when processing extensive academic paper datasets. To overcome these issues, the present work introduces an innovative recommendation model that integrates the wealth of structured information from knowledge graphs and refines the amalgamation of temporal and relational data. By applying attention mechanisms and neural network technologies, the model thoroughly explores the text characteristics of papers and the evolving patterns of user behaviors. Additionally, the model elevates the accuracy and personalization of recommendations by meticulously examining citation patterns among papers and the networks of author collaboration. The experimental findings show that the present model surpasses baseline models on all evaluation metrics, thereby enhancing the precision and personalization of academic paper recommendations.
Vessel Segmentation in Fundus Images with Multi-Scale Feature Extraction and Disentangled Representation
Authors: Zhong Yuanhong , Chen Ting , Zhong Daidi , Liu Xiaoming
Published: June 2024

Vessel segmentation in fundus images is crucial for diagnosing eye diseases. The rapid development of deep learning has greatly improved segmentation accuracy. However, the scale of the retinal blood-vessel structure varies greatly, and there is a lot of noise unrelated to blood-vessel segmentation in fundus images, which increases the complexity and difficulty of the segmentation algorithm. Comprehensive consideration of factors like scale variation and noise suppression is imperative to enhance segmentation accuracy and stability. Therefore, we propose a retinal vessel segmentation method based on multi-scale feature extraction and decoupled representation. Specifically, we design a multi-scale feature extraction module at the skip connections, utilizing dilated convolutions to capture multi-scale features and further emphasizing crucial information through channel attention modules. Additionally, to separate useful spatial information from redundant information and enhance segmentation performance, we introduce an image reconstruction branch to assist in the segmentation task. The specific approach involves using a disentangled representation method to decouple the image into content and style, utilizing the content part for segmentation tasks. We conducted experiments on the DRIVE, STARE, and CHASE_DB1 datasets, and the results showed that our method outperformed others, achieving the highest accuracy across all three datasets (DRIVE:0.9690, CHASE_DB1:0.9757, and STARE:0.9765).
Currents’-Physical-Component-Based Reactive Power Compensation Optimization in Three-Phase, Four-Wire Systems
Authors: Zhao Xiaoying , Bian Dunxin
Published: June 2024

In this paper, we aim to address the limited capacity of compensation devices by enhancing their utilization rate by applying the currents’ physical component (CPC) theory for reactive power optimization in three-phase four-wire systems. When reactive currents cannot be fully compensated for, we propose using CPC theory to generate reference currents for the compensation devices. Weight coefficients associated with different reactive current components are introduced, enabling flexible combinations of these independent current components. The maximum output amplitude of the three-phase current from the compensation device serves as a constraint condition, allowing for the calculation of reference currents under various compensation targets. Additionally, a reactive current optimization compensation scheme focusing on loss reduction is selected. The simulated annealing–particle swarm optimization (SA-PSO) hybrid algorithm is employed to solve the optimization mathematical model. The discussed calculations, current waveforms, and voltage waveforms are generated using the constructed mathematical model and then used for a theoretical explanation. The simulation verifies the feasibility of the proposed method.
Combining Transformer, Convolutional Neural Network, and Long Short-Term Memory Architectures: A Novel Ensemble Learning Technique That Leverages Multi-Acoustic Features for Speech Emotion Recognition in Distance Education Classrooms
Authors: Alkhamali Eman Abdulrahman , Allinjawi Arwa , Ashari Rehab Bahaaddin
Published: June 2024

Speech emotion recognition (SER) is a technology that can be applied to distance education to analyze speech patterns and evaluate speakers’ emotional states in real time. It provides valuable insights and can be used to enhance students’ learning experiences by enabling the assessment of their instructors’ emotional stability, a factor that significantly impacts the effectiveness of information delivery. Students demonstrate different engagement levels during learning activities, and assessing this engagement is important for controlling the learning process and improving e-learning systems. An important aspect that may influence student engagement is their instructors’ emotional state. Accordingly, this study used deep learning techniques to create an automated system for recognizing instructors’ emotions in their speech when delivering distance learning. This methodology entailed integrating transformer, convolutional neural network, and long short-term memory architectures into an ensemble to enhance the SER. Feature extraction from audio data used Mel-frequency cepstral coefficients; chroma; a Mel spectrogram; the zero-crossing rate; spectral contrast, centroid, bandwidth, and roll-off; and the root-mean square, with subsequent optimization processes such as adding noise, conducting time stretching, and shifting the audio data. Several transformer blocks were incorporated, and a multi-head self-attention mechanism was employed to identify the relationships between the input sequence segments. The preprocessing and data augmentation methodologies significantly enhanced the precision of the results, with accuracy rates of 96.3%, 99.86%, 96.5%, and 85.3% for the Ryerson Audio–Visual Database of Emotional Speech and Song, Berlin Database of Emotional Speech, Surrey Audio–Visual Expressed Emotion, and Interactive Emotional Dyadic Motion Capture datasets, respectively. Furthermore, it achieved 83% accuracy on another dataset created for this study, the Saudi Higher-Education Instructor Emotions dataset. The results demonstrate the considerable accuracy of this model in detecting emotions in speech data across different languages and datasets.
On Modulus Statistical Convergence in Partial Metric Spaces
Authors: García-Pacheco Francisco Javier , Kama Ramazan
Published: June 2024

Modulus statistical convergence has been studied in very different general settings such as topological spaces and uniform spaces. In this manuscript, modulus statistical convergence is defined and studied in partial metric spaces.
A Traditional Chinese Medicine, Zhenqi Granule, Potentially Alleviates Dextran Sulfate Sodium-Induced Mouse Colitis Symptoms
Authors: Qiu Xiuxiu , Luo Wentao , Li Haotian , Li Tingting , Huang Yaxue , Huang Qi , Zhou Rui
Published: June 2024

Ulcerative colitis (UC) is an inflammatory bowel disease that causes chronic inflammation in the large intestine. The etiology of UC is complex and incompletely understood, with potential contributing factors including genetic susceptibility, environmental influences, immune dysregulation, and gut barrier dysfunction. Despite available therapeutic drugs, the suboptimal cure rate for UC emphasizes the necessity of developing novel therapeutics. Traditional Chinese Medicine (TCM) has attracted great interest in the treatment of such chronic inflammatory diseases due to its advantages, such as multi-targets and low side effects. In this study, a mouse model of Dextran Sulfate Sodium (DSS)-induced acute colitis was established and the efficacy of Zhenqi Granule, a TCM preparation composed of the extractives from Astragali Radix and Fructus Ligustri Lucidi, was evaluated. The results showed that treatment with Zhenqi Granule prior to or post-DSS induction could alleviate the symptoms of colitis, including weight loss, diarrhea, hematochezia, colon length shortening, and pathological damage of colon tissues of the DSS-treated mice. Further, network pharmacology analysis showed that there were 98 common targets between the active components of Zhenqi Granule and the targets of UC, and the common targets were involved in the regulation of inflammatory signaling pathways. Our results showed that Zhenqi Granule had preventive and therapeutic effects on acute colitis in mice, and the mechanism may be that the active components of Zhenqi Granule participated in the regulation of inflammatory response. This study provided data reference for further exploring the mechanism of Zhenqi Granule and also provided potential treatment strategies for UC.
Anti-Inflammatory Responses Produced with Nippostrongylus brasiliensis-Derived Uridine via the Mitochondrial ATP-Sensitive Potassium Channel and Its Anti-Atherosclerosis Effect in an Apolipoprotein E Gene Knockout Mouse Model
Authors: Zhang Yingshu , Ding Xin , Yuan Caiyi , Yang Yougui , Zhang Qiang , Yao Jiakai , Zhang Ying , Wang Junhong , Dai Yang
Published: June 2024

Atherosclerosis (AS) has become the leading cause of cardiovascular disease worldwide. Our previous study had observed that Nippostrongylus brasiliensis (Nb) infection or its derived products could inhibit AS development by inducing an anti-inflammatory response. We performed a metabolic analysis to screen Nb-derived metabolites with anti-inflammation activity and evaluated the AS-prevention effect. We observed that the metabolite uridine had higher expression levels in mice infected with the Nb and ES (excretory–secretory) products and could be selected as a key metabolite. ES and uridine interventions could reduce the pro-inflammatory responses and increase the anti-inflammatory responses in vitro and in vivo. The apolipoprotein E gene knockout (ApoE−/−) mice were fed with a high-fat diet for the AS modeling. Following the in vivo intervention, ES products or uridine significantly reduced serum and liver lipid levels, alleviated the formation of atherosclerosis, and reduced the pro-inflammatory responses in serum or plaques, while the anti-inflammatory responses showed opposite trends. After blocking with 5-HD (5-hydroxydecanoate sodium) in vitro, the mRNA levels of M2 markers were significantly reduced. When blocked with 5-HD in vivo, the degree of atherosclerosis was worsened, the pro-inflammatory responses were increased compared to the uridine group, while the anti-inflammatory responses decreased accordingly. Uridine, a key metabolite from Nippostrongylus brasiliensis, showed anti-inflammatory and anti-atherosclerotic effects in vitro and in vivo, which depend on the activation of the mitochondrial ATP-sensitive potassium channel.
Accurate Identification of Spatial Domain by Incorporating Global Spatial Proximity and Local Expression Proximity
Authors: Yu Yuanyuan , He Yao , Xie Zhi
Published: June 2024

Accurate identification of spatial domains is essential in the analysis of spatial transcriptomics data in order to elucidate tissue microenvironments and biological functions. However, existing methods only perform domain segmentation based on local or global spatial relationships between spots, resulting in an underutilization of spatial information. To this end, we propose SECE, a deep learning-based method that captures both local and global relationships among spots and aggregates their information using expression similarity and spatial similarity. We benchmarked SECE against eight state-of-the-art methods on six real spatial transcriptomics datasets spanning four different platforms. SECE consistently outperformed other methods in spatial domain identification accuracy. Moreover, SECE produced spatial embeddings that exhibited clearer patterns in low-dimensional visualizations and facilitated a more accurate trajectory inference.
Perimenopause Decreases SERCA2a Activity in the Hearts of a Mouse Model of Ovarian Failure
Authors: Barry Ciara , Rouhana Sarah , Braun Jessica L. , Geromella Mia S. , Fajardo Val A. , Pyle W. Glen
Published: June 2024

Risk of cardiovascular disease mortality rises in women after menopause. While increased cardiovascular risk is largely attributed to postmenopausal declines in estrogens, the molecular changes in the heart that contribute to risk are poorly understood. Disruptions in intracellular calcium handling develop in ovariectomized mice and have been implicated in cardiac dysfunction. Using a mouse model of menopause in which ovarian failure occurs over 120 days, we sought to determine if perimenopause impacted calcium removal mechanisms in the heart and identify the molecular mechanisms. Mice were injected with 4-vinylcyclohexene diepoxide (VCD) to induce ovarian failure over 120 days, mimicking perimenopause. Hearts were removed at 60 and 120 days after VCD injections, representing the middle and end of perimenopause. SERCA2a function was significantly diminished at the end of perimenopause. Neither SERCA2a nor phospholamban expression changed at either time point, but phospholamban phosphorylation at S16 and T17 was dynamically altered. Intrinsic SERCA inhibitors sarcolipin and myoregulin increased >4-fold at day 60, as did the native activator DWORF. At the end of perimenopause, sarcolipin and myoregulin returned to baseline levels while DWORF was significantly reduced below controls. Sodium–calcium exchanger expression was significantly increased at the end of perimenopause. These results show that the foundation for increased cardiovascular disease mortality develops in the heart during perimenopause and that regulators of calcium handling exhibit significant fluctuations over time. Understanding the temporal development of cardiovascular risk associated with menopause and the underlying mechanisms is critical to developing interventions that mitigate the rise in cardiovascular mortality that arises after menopause.
Understanding the Molecular Actions of Spike Glycoprotein in SARS-CoV-2 and Issues of a Novel Therapeutic Strategy for the COVID-19 Vaccine
Authors: Matsuzaka Yasunari , Yashiro Ryu
Published: June 2024

In vaccine development, many use the spike protein (S protein), which has multiple “spike-like” structures protruding from the spherical structure of the coronavirus, as an antigen. However, there are concerns about its effectiveness and toxicity. When S protein is used in a vaccine, its ability to attack viruses may be weak, and its effectiveness in eliciting immunity will only last for a short period of time. Moreover, it may cause “antibody-dependent immune enhancement”, which can enhance infections. In addition, the three-dimensional (3D) structure of epitopes is essential for functional analysis and structure-based vaccine design. Additionally, during viral infection, large amounts of extracellular vesicles (EVs) are secreted from infected cells, which function as a communication network between cells and coordinate the response to infection. Under conditions where SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) molecular vaccination produces overwhelming SARS-CoV-2 spike glycoprotein, a significant proportion of the overproduced intracellular spike glycoprotein is transported via EVs. Therefore, it will be important to understand the infection mechanisms of SARA-CoV-2 via EV-dependent and EV-independent uptake into cells and to model the infection processes based on 3D structural features at interaction sites.
Long COVID in Brain Health Research: A Call to Action
Authors: Rudroff Thorsten
Published: June 2024

The COVID-19 pandemic has brought attention to the long-term consequences of the virus, particularly the persistent symptoms that characterize long COVID. This syndrome, which can last for months after the initial infection, includes a range of neurological and neuropsychiatric manifestations that have significant implications for brain health and dementia research. This review explores the current understanding of long COVID’s cognitive, neurological, and psychiatric symptoms and their potential impact on brain stimulation and neuroimaging studies. It argues that researchers must adapt their study designs and screening processes to account for the confounding effects of long COVID and ensure the accuracy and reliability of their findings. To advance the understanding of this condition and its long-term effects on brain health, the review proposes a series of strategies, including the development of standardized screening tools, the investigation of underlying mechanisms, and the identification of risk factors and protective factors. It also emphasizes the importance of collaborative research efforts and international data sharing platforms in accelerating the pace of discovery and developing targeted interventions for individuals with long COVID. As the prevalence of this condition continues to grow, it is imperative that the neuroscience community comes together to address this challenge and support those affected by long COVID.
Employing Metal-Enriched Polymeric Composites: An Innovative Approach for Combatting Microbes and Bacteria in Building Components in Public Places
Authors: Agarwalla Aaruci , Ahmed Waleed , Al-Marzouqi Ali H. , Rizvi Tahir A. , Zaneldin Essam , Khan Mushtaq
Published: June 2024

The escalating occurrence of hospital-associated infections globally, compounded by the ongoing pandemic, has spurred researchers to delve into innovative approaches for combating pathogens and overcoming their resistance to commonly used materials. One of the most important concerns is frequently touched building components in public places and hospitals, which serve as potential sources of infection transmission, prompting a pressing need for effective antimicrobial solutions. This research developed antimicrobial polymeric composites comprising Copper (Cu), Aluminum (Al), and Stainless Steel (SS) particles incorporated into Polylactic Acid (PLA) via injection molding as a commercial method for the production of building components, to investigate the antimicrobial properties. The study aims at increasing the antimicrobial efficiency of polymeric composites with different metallic particles and tests the prepared polymeric composites (two sets of Cu-enriched composites, i.e., Cu–PLA–SS, by mixing Al–PLA with Cu–PLA, and Cu–PLA–Al, by mixing SS–PLA with Cu–PLA) against various bacteria. The results demonstrate that the samples prepared with Cu-PLA mixed with SS and Al exhibited the best antibacterial activity (98.6%) after 20 min of exposure to all bacteria, notably against Staphylococcus aureus and Enterococci. In addition, the hybrid composites Cu–PLA–SS and Cu–PLA–Al, prepared using injection molding, showed similar antimicrobial activity against all bacteria compared to those prepared using 3D printing. Therefore, polymeric composites enriched with metallic particles such as Cu, Al, and SS prepared via injection molding show potential in biomedical applications, food packaging, tissue engineering, and various technological industries, offering viable solutions for environments where risks from contact with infected surfaces are a concern.
Spatial Pattern, Quality Evaluation, and Implications of Preschool Education Facilities in New Urban Areas Using Multi-Source Data: A Case Study from Lingui New District in West China
Authors: Wang Xiao , Zhao Jiaying , Lu Yuxi , Li Xiang
Published: June 2024

Currently, China has entered the development stage of a “low birth rate” demographically. There is a huge contradiction between the unbalanced and inadequate distribution of preschool education facilities (PEFs) and the people’s expectations for “full and good education for children”. This study took the Lingui New District, a typical new urban area in West China as the research area, and through the introduction of POI big data and GIS analysis methods, supplemented by GeoDA Bivariate Moran index analyses, established a kindergarten spatial database. The study found that preschool education facilities have problems such as insufficient quantity, uneven quality, low service coverage, poor accessibility, etc. Therefore, it is suggested to increase the proportion of public affordable preschool education facilities including kindergartens and nurseries, optimize the spatial distribution of preschool education, and improve the accessibility of preschool services to promote affordable, safe, and high-quality development of preschool education and to provide reference suggestions for the revision of relevant standards and the adjustment of the layout of preschool education in undeveloped regions of China.
Research on the Propagation Model of Unsafe Behaviors among Construction Workers Based on a Two-Layer NAN-SIRS Network
Authors: Hou Yunfei , Zhao Qi
Published: June 2024

Unsafe behaviors among construction workers are a leading cause of safety accidents in the construction industry, and studying the mechanism of unsafe behavior propagation among construction workers is essential for reducing the occurrence of safety accidents. Safety attitude plays a pivotal role in predicting workers’ behavioral intentions. We propose a propagation model of unsafe behaviors based on a two-layer complex network, in which the upper layer depicts the change in construction workers’ safety attitudes, and the lower layer represents the propagation of unsafe behaviors. In this model, we consider the impact of individual heterogeneity and herd mentality on the transmission rate, establishing a partial mapping relationship based on behavioral feedback. After that, by building a probability transition tree, we establish the risk state transition equation in detail using the microscopic Markov chain approach (MMCA) and analyze the established equations to deduce the propagation threshold of unsafe behaviors analytically. The results show that enhancing the influence of individual heterogeneity and behavioral feedback increases the threshold for the spread of unsafe behaviors, thereby reducing its scale, while herd mentality amplifies the spread. Furthermore, the coexistence of safety education and behavioral feedback may lead to one of the mechanisms fails. This research enhances understanding of the propagation mechanism of unsafe behaviors and provides a foundation for managers to implement effective measures to suppress the propagation of unsafe behaviors among construction workers.
Effects of Aging on Rheological Properties and Microstructural Evolution of SBS Modified Asphalt and Crumb Rubber Modified Asphalt Binders
Authors: Zhang Honggang , Lv Songtao , Pang Jinsong , Chen Jie , Xuan Wei’an
Published: June 2024

Focusing on the comparison of aging resistance between styrene-butadiene-styrene (SBS) modified asphalt (SBSMA) and crumb rubber modified asphalt binders (CRMA), the influences of aging on rheological properties and microstructural characteristics of different modified asphalts were investigated in this work. Dynamic Shear Rheometer (DSR) and Bending Beam Rheometer (BBR) tests were carried out, and the variations in rheological properties for different modified asphalts after the rotating thin film oven test (RTFOT) were analyzed with the rutting factor aging index (RAI) and creep rate aging index (CAI). By using Fluorescence microscopy (FM) and Fourier transform infrared (FTIR) spectroscopy, the evolutions of microstructure and chemical composition for two modified asphalts were analyzed with carbonyl index growth rate (CIR) and sulfoxide index growth rate (SIR). Then, The relationships between CIR/SIR and RAI/CAI were established to show the correlation between the deterioration of macroscopic performance and the evolution of micro-structure. The results indicated that the aging degree of asphalt increases with elevated temperatures, leading to decreasing low-temperature performance while improving high-temperature performance. Nevertheless, SBSMA exhibited strong sensitivity to aging temperature. Under thermo-oxidative aging, the RAI and CAI of SBSMA were lower than those of CRMA, whereas the regularities of CIR and SIR were opposite, indicating that CRMA was superior to SBSMA in terms of anti-aging properties due to the rupture of the cross-linked network structure of SBSMA. However, CRMA experienced aging accompanied by full swelling, and thus, relatively minor performance declined. The CIR and SIR exhibited a better correlation with the RAI and CAI, illustrating that both CIR and SIR could characterize the aging degree of modified asphalts well.
Finite-Element Analysis of Temperature Field and Effect on Steel-Concrete Composite Pylon of Cable-Stayed Bridge without Backstays
Authors: Gong Boxu , Feng Lianjun , Liu Jiang , Liu Shiming , Wang Zhuang , Liu Yongjian
Published: June 2024

The backless cable-stayed bridge has the advantages of beautiful shape and reasonable force, but due to the low overall stiffness of the bridge pylon during cantilever construction, it is susceptible to the effect of solar temperature. To reveal the temperature deformation laws and achieve accurate alignment prediction during the installation process of steel–concrete composite pylons in complex environments, a refined numerical simulation model for the 3D bridge temperature field was established based on the proposed automatic sunshine-shadow recognition method. Subsequently, the optimal time periods for construction control are provided. The results of the study show that, during the cantilever construction of the bridge pylon, one pylon column will shade the other pylon column, resulting in asynchronous deformation that can reach 7.6 mm. The effect of solar temperature on the displacement of the bridge pylon is significant, where the maximum daily change in transverse displacement in the cantilevered state of the pylon can reach 33.6 mm, and the maximum change in cable force value can reach 52 kN. In order to mitigate the effect of solar radiation, the best construction time for the bridge pylon is 19:30~9:30, while the tensioning and measurement of the cable should be avoided from 6:00~18:00. This strategy ensures that the control of the pylon top displacement is maintained within 1/4000 of the pylon height, and the error in cable force is kept within 5%.
A Study on the Spatial Structures and Mechanisms of Intangible Cultural Heritage and Traditional Villages in the Dongting Lake Basin
Authors: He Chuan , Liang You-Wang , Zhang Shi-Yu
Published: June 2024

This study focuses on 1209 national and provincial intangible cultural heritage items and 1234 traditional Chinese villages within the Dongting Lake Basin. Using kernel density analysis, centroid models, coupling models, and quantitative spatial–structural models, the present research analyzes the spatial–structural characteristics and formation mechanisms of intangible cultural heritage and traditional villages to provide scientific support for their preservation, inheritance, and effective utilization. The results revealed the following: (1) Intangible cultural heritage and traditional villages in the Dongting Lake Basin exhibit a very concentrated spatial distribution, with similar spatial–structural characteristics. (2) High spatial coupling of intangible cultural heritage and traditional villages is observable in the sub-basins of Dongting Lake, such as the Yuanjiang, Zishui, and Lishui basins, whereas the Xiangjiang Basin and Dongting Lake area present relatively lower levels of spatial coupling. In terms of the categories of intangible cultural heritage, four of them—cultural heritage, folk literature, traditional music, traditional dance, and traditional drama—have the smallest deviation distance and index values from traditional villages. The coupling degree was higher than 0.70, and there were some differences in the coupling degree between the other six categories of intangible cultural heritage and traditional villages. (3) The spatial–structural characteristics of intangible cultural heritage and traditional villages in the Dongting Lake Basin emerged from the combined effects of multiple factors, including internal connections between the two, as well as external factors such as the natural environment, socio-economic conditions, and cultural policies, all of which play crucial roles in the formation processes of these characteristics.
Anogenital HPV-Related Cancers in Women: Investigating Trends and Sociodemographic Risk Factors
Authors: Lupi Micol , Tsokani Sofia , Howell Ann-Marie , Ahmed Mosab , Brogden Danielle , Tekkis Paris , Kontovounisios Christos , Mills Sarah
Published: June 2024

The incidences of anogenital HPV-related cancers in women are on the rise; this is especially true for anal cancer. Medical societies are now beginning to recommend anal cancer screening in certain high-risk populations, including high-risk women with a history of genital dysplasia. The aim of this study is to investigate national anogenital HPV cancer trends as well as the role of demographics, deprivation, and ethnicity on anogenital cancer incidence in England, in an attempt to better understand this cohort of women which is increasingly affected by anogenital HPV-related disease. Demographic data from the Clinical Outcomes and Services Dataset (COSD) were extracted for all patients diagnosed with anal, cervical, vulval and vaginal cancer in England between 2014 and 2020. Outcomes included age, ethnicity, deprivation status and staging. An age over 55 years, non-white ethnicity and high deprivation are significant risk factors for late cancer staging, as per logistic regression. In 2019, the incidences of anal and vulval cancer in white women aged 55–74 years surpassed that of cervical cancer. More needs to be done to educate women on HPV-related disease and their lifetime risk of these conditions.