bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation and Optimization Strategies of the Living Environment in One Resettlement Area of the South-to-North Water Diversion Project
Authors: Yan Dong , Zhao Jingxin , Chen Ran , Wang Biao
Published: December 2024

Taking Yunyu New Village in Nanyang City, a typical newly built resettlement area of the South-to-North Water Diversion Project of China, as an example, this paper tries to construct a health environment evaluation index system for the resettlement area and determines the priority and content of residential environment renovation in the resettlement area through residents’ health satisfaction evaluation and IPA analysis. The results revealed that six factors, namely, winter insulation, summer heat insulation, quality of domestic drinking water, indoor natural light environment, humanized design, and architectural plane function design, need to be renovated first. For the indoor environment, which is the focus of renovation, the light and heat environments were evaluated via field measurements and simulation experiments. The results show that the indoor comfort, daylighting, and energy savings of the surveyed buildings all fail to meet Chinese building design standards. Corresponding optimization strategies for indoor ventilation, thermal insulation performance of the envelope structure, and window wall ratio are proposed and verified via relevant software simulations and immigrants’ wishes. For the outdoor environment, we investigate the living habits and renovation needs of immigrants from the aspects of public space and courtyard space in the resettlement area and propose corresponding optimization strategies. The results of this research can help enhance the sense of gain and happiness of immigrants in the resettlement and provide a reference for improving the living environment of the same type of immigrant resettlement area.
Proposal for a Circular Product Development Model Applied to Packaging
Authors: João Samuel , Maceno Marcell Mariano Corrêa , Antonelo Aliny Kelly
Published: December 2024

Adopting the circular economy can drive significant cultural and organizational changes, providing important benefits such as cost improvement, innovation, new market opportunities, quality improvement, market acceptance, and legal compliance. This paper proposes a circular product development model for packaging to integrate circular economy principles into the traditional product development process. Firstly, a systematic literature review was made to identify relevant guidelines, strategies, practices, and initiatives related to circular economy and product development and understand how they could be integrated into the stages of the product development process. These circular practices, initiatives, and strategies were incorporated into the Rozenfeld model, creating a Circular Product Development Model proposed in this study (C-PDM). This model was tested through a case study in the packaging industry located in the Curitiba region—Brazil, identifying the opportunity to incorporate 18 circular practices into the product development process. The study concludes by highlighting the potential contribution of this model to the packaging market, particularly in supporting the circular development of products, thus aligning with the broader goals of sustainability and economic efficiency.
Operational Efficiency of Pharmaceutical Companies in China: Based on Three-Stage DEA with Undesirable Outputs
Authors: Sun Jiaqiang , Rosli Anita Binti , Daud Adrian
Published: December 2024

After a period of rapid growth, China’s pharmaceutical industry is facing multiple challenges, including insufficient innovation and severe pollution. Current research on the efficiency of pharmaceutical companies in China primarily focuses on financial or innovation aspects. Therefore, a holistic approach to operational efficiency is needed. To measure the operational efficiency of pharmaceutical companies in China more accurately and holistically, while accounting for environmental pollution, this study employs a three-stage Data Envelopment Analysis (DEA) model with undesirable outputs to evaluate efficiency across five dimensions: market performance, profitability, financial risk control, innovation, and sustainability. This approach integrates financial, innovation, and sustainability indicators to provide a more industry-specific framework for efficiency measurement. Furthermore, integrating with Stochastic Frontier Analysis (SFA) allows for revealing the impact of environmental factors on efficiency. The results show that both technical efficiency (TE) and pure technical efficiency (PTE) are relatively low in the first and third stages, with significant regional disparities. After excluding environmental factors, some regions—typically economically developed areas—showed improved overall efficiency. This indicates that the local environment in these regions is not conducive to the development of pharmaceutical enterprises. The SFA results further demonstrate that investments in education and high-level talent significantly enhance efficiency, whereas pollutant emissions and per capita income reduce operational efficiency. The findings suggest that local governments should enhance the operational efficiency of pharmaceutical enterprises by investing in education, attracting skilled talent, and improving waste infrastructure. Additionally, less efficient firms are encouraged to optimize resource allocation to achieve higher efficiency.
Risk Challenges and Their Impact on the Sustainable Food Security System: Lessons Learned from the COVID-19 Pandemic
Authors: Boratyńska Katarzyna
Published: December 2024

The aim of this study is to indicate and evaluate the main risk challenges for the food security system from the perspective of a sustainability and adaptation pillar of the Global Food Security Index (GFSI) in the COVID-19 pandemic. The study contributes to both theory and practice in addressing contemporary global challenges. The study systematically identifies and evaluates the multidimensional risks to sustainable food security systems caused by the COVID-19 pandemic, emphasizing the role of Sustainable Development Goals (SDGs). It employs innovative methodologies such as the integration of the Global Food Security Index (GFSI) and the PESTLE framework, extending the latter with governance considerations within the ESG concept, a novel approach in this context. The findings provide actionable insights into building resilience in food supply chains and adapting policies for future crises, thereby filling critical gaps in the literature. Moreover, the study focuses on the intersection of sustainability, risk challenges, and well-being, fostering research that drives sustainable development globally.
Impact of Professional Competency on Occupational Identity of Preschool Education Publicly Funded Teacher Trainees: The Moderating Role of Support from Significant Others
Authors: Li Zhangpei , Liu Mengfan , Zhu Junxiang
Published: December 2024

This study investigates the impact of professional competencies (moral, knowledge, and skill) on the occupational identity of government-supported preschool teacher trainees and examines the moderating role of support from significant others, including family, peers, and mentors. A quantitative research methodology was employed, involving a cross-sectional survey of 193 publicly funded teacher trainees. Validated scales were used to measure professional competencies, occupational identity, and perceived support. The results revealed a strong positive correlation between professional competencies and occupational identity (r = 0.61, p < 0.01), supporting the hypothesis that higher competency levels enhance trainees’ professional identity. Furthermore, support from significant others moderated this relationship, with a higher level of support amplifying the positive association (β = 1.412, p < 0.01). These findings highlight the interconnected nature of professional competencies and social support in shaping occupational identity. Based on these results, it is recommended that teacher training programs integrate targeted competency-building strategies alongside structured support systems to enhance professional identity formation. These initiatives are critical for fostering sustainable professional development and improving the quality and stability of preschool education.
Deep Learning for Automated Kellgren–Lawrence Grading in Knee Osteoarthritis Severity Assessment
Authors: Nasef Daniel , Nasef Demarcus , Sawiris Viola , Girgis Peter , Toma Milan
Published: December 2024

Background: This study evaluated the performance of machine learning models trained on two different datasets of knee X-ray images annotated with Kellgren–Lawrence grades. Methods: Learning curves indicated that one model experienced poor training, characterized by underfitting, while the other model demonstrated effective training with proper convergence. The poorly trained model appeared to perform adequately on its internal test set but failed to generalize to an external dataset, yielding suboptimal results. Results: In contrast, the well-trained model not only performed well on its internal validation but also showed adequate performance when tested on the external dataset. Conclusions: These findings highlight the importance of examining learning curves to assess model training quality and the critical necessity of external testing to evaluate generalizability. Most existing studies lack external validation, raising concerns about the reliability of their reported performance. This study emphasizes that without external testing, models may not perform as expected in real-world clinical settings, potentially impacting clinical decision-making for surgical interventions. The results advocate for the inclusion of external validation in model evaluation and the assessment of model convergence using learning curves to ensure the development of robust and generalizable tools for knee osteoarthritis severity assessment and other applications.
Design of Ranging Communication Coding and Noise Suppression Methods in Space Gravitational Wave Detection
Authors: Long Hongyu , Yu Tao , Xue Ke , Wang Zhi
Published: December 2024

A ranging communication system is a key technology for achieving precise ranging and scientific data exchange in space gravitational wave detection, with the aim of realizing the symmetry of interferometer arms. This system is integrated into the phase measurement payload, the ’phasemeter’. Achieving high-ranging accuracy and low-bit error rate communication while mitigating the impact of phase noise has become a focus of current research. This paper starts with the coding methods for ranging communication and analyzes phase modulation noise based on Binary Phase Shift Keying (BPSK). The study found that the main lobe phase noise caused by BPSK modulation is approximately 158 μrad/Hz, which is two orders of magnitude higher than the phase-tracking criteria for gravitational wave detection. To address this, this paper proposes a Bit-Balanced Code (BBC) sequence design and optimization method aimed at eliminating main lobe noise. The experimental results show that the optimized BBC sequence improves the metrics of even autocorrelation, odd autocorrelation, maximum spectral amplitude, and even cross-correlation by 7.17, 2.83, 1.22, and 7.16, respectively, compared to the original sequence. Furthermore, experiments have demonstrated that the BBC sequence is insensitive to random data and can achieve dynamic bit balancing to eliminate the DC component. The proposed BBC sequence design method can serve as a reference for technologies related to space gravitational wave detection.
An Improved Grey Wolf Optimizer Based on Attention Mechanism for Solving Engineering Design Problems
Authors: Zhang Yuming , Gao Yuelin , Huang Liming , Xie Xiaofeng
Published: December 2024

The grey wolf optimization (GWO) algorithm is a simple and effective meta-heuristic algorithm that mimics the leadership of grey wolves and the social behavior of wolves in nature. However, the updating of GWO population positions only relies on the guidance of α-wolf, β-wolf, and δ-wolf, and individuals are updated with equal weights. This results in the GWO search process being unable to utilize the knowledge of superior wolves better. Therefore, in this study, we propose for the first time an attention mechanism-based GWO (AtGWO). Firstly, when each position is updated, the attention strategy can adaptively assign the weight of the corresponding leader wolf to improve the global exploration ability. Second, with the introduction of omega-wolves, each position update is not only guided by the three leader wolves but also learns from their current optimal values. Finally, a hyperbolic tangent nonlinear function is used to control the convergence factor to better balance exploration and exploitation. To validate its effectiveness, AtGWO is compared with the latest GWO variant with other popular algorithms on the CEC-2014 (dim 30, 50) and CEC-2017 (dim 30, 50, 100) benchmark function sets. The experimental results indicate that AtGWO outperforms the GWO-related variants almost all the time in terms of mean, variance, and best value, which indicates its superior ability and robustness to find optimal solutions. And it is also competitive when compared to other algorithms in multimodal functions. AtGWO outperforms the comparison algorithms in terms of the mean and best value in six real-world engineering optimization problems.
Mechanical Behavior and Failure Mechanism of Rock–Concrete Composites Under the Coupling Effect of Inclined Interface Angle and Ground Temperature
Authors: Liu Shiwei , Zhao Jiaxin , Cheng Fang , Yu Hao , Chen Jiaqi
Published: December 2024

Surrounding rock and lining are composite structures with asymmetric mechanical properties. Understanding the mechanical properties and failure characteristics of rock–concrete composites is crucial for gaining insights into the mechanisms that induce disasters in deep-underground environments. Uniaxial compression and acoustic emission tests were conducted on rock–concrete composite specimens cured at temperatures of 20 °C, 40 °C, 60 °C, and 80 °C, with interface angles of 15°, 30°, 45°, 60°, 75°, and 90° respectively. The results indicated that the specimens’ strength decreased at increasing geothermal temperatures. The composites with an 80 °C curing temperature and a 60° interface angle exhibited the lowest strength. A higher geothermal temperature significantly reduced the number of cracks in the concrete component during composite failure and mitigated the influence of the inclined interface angle. The failure modes of the specimens include axial penetration splitting, interface shear, Y-shaped fracture, and interface splitting–concrete shear failure. Finally, a model relating the strength of the rock–concrete composite to the inclined interface angle and the geothermal temperature was derived and verified against the experimental results with a relative error of 9.8%. The findings have significant implications for the safety and stability of tunnels in high-temperature conditions.
Numerical Modeling of Charpy Impact Toughness Behavior and Stress Distribution of Quenching and Partitioning Steel
Authors: Kori Tamiru Hailu , Kassaye Firew Tullu , Kozłowska Aleksandra , Grajcar Adam
Published: December 2024

The toughness of steel is a critical material property that represents the ability to absorb energy at fracture, particularly in ultra-high-strength steels. The optimal balance between high strength and ductility depends on the complexity of the microstructure formed during heat treatment, which influences the toughness of the steel. In this study, a numerical modeling approach was used to investigate the Charpy impact behavior of medium manganese Q&P (quenching and partitioning) steel with a focus on toughness and stress distribution. ANSYS Explicit Dynamics was used for numerical modeling to simulate stress distribution and energy absorption in Charpy specimens. The Johnson–Cook model approach was used to describe the material behavior for such dynamic conditions. The results showed that ductility and toughness decreased with increasing partitioning time from 300 s to 900 s. The simulation results also showed that the stress distribution was more pronounced near the notch radius. The absorbed energy of the samples increased slightly as the notch radius increased from 0.1 mm to 0.25 mm, and it significantly increased as the plate thickness increased from 7 mm to 12 mm.
Partial Discharge Data Enhancement and Pattern Recognition Method Based on a CAE-ACGAN and ResNet
Authors: Li Songyuan , Wang Xiaopeng , Han Yue , Feng Junji , Yin Zhen , Yang Jiawang , Luo Weipeng , Xie Jun
Published: December 2024

In order to address the issue of the accuracy of partial discharge pattern recognition being constrained by unbalanced samples and the deep structure of the deep learning network, a method for partial discharge data enhancement and pattern recognition based on a convolutional autoencoder auxiliary classifier generative adversarial network (CAE-ACGAN) and a residual network (ResNet) is proposed. The initial step involves the preprocessing of the acquired partial discharge signals, with the phase resolved partial discharge (PRPD) spectra subsequently employed as the training samples. Secondly, a CAE-ACGAN is constructed. The model combines the advantages of a deep convolutional self-coding structure and a generative adversarial paradigm to generate high-quality phase resolved partial discharge spectrograms. Subsequently, a ResNet is employed as the classifier for partial discharge pattern recognition, utilising the CAE-ACGAN-enhanced partial discharge dataset for network training to achieve accurate recognition of partial discharge signals. The experimental findings demonstrate that the SSIM and PSNR indexes of the CAE-ACGAN model utilised in this study are 0.92 and 45.88 dB, respectively. The partial discharge pattern method employing the CAE-ACGAN and ResNet exhibits superiority in identifying partial discharges, attaining an identification accuracy of 98%, which is 7.25% higher than the pre-enhancement level.
Automation Processes for Efficient Verification of Complex Systems: An Empirical Case Study
Authors: Haugen Rune Andre , Skeie Nils-Olav , Muller Gerrit
Published: December 2024

This paper investigated the effect of automation processes in an industrial company engineering complex cyber-physical systems. The authors used an industry-as-laboratory approach as the research method, exploring an ongoing development project. The automation efforts focused on four areas: (1) test setup, (2) test execution, (3) test result analysis, and (4) documentation. All four areas showed promising results on increased effectiveness and/or efficiency. In particular, the automation of test result analysis will help the industrial company, KONGSBERG, reduce their main bottleneck in the test process, as well as reduce the risk of costly project delays. An automated system integration test process, facilitating iterative regression testing, will leverage the efficiency of the verification test process.
A Taxonomic Revision of the Weevil Genus Hypoglyptus Gerstaecker, 1855 (Coleoptera Curculionidae)
Authors: Caldara Roberto , Košťál Michael
Published: December 2024

The genus Hypoglyptus Gerstaecker, 1855 is herein revised for the first time. Based on adult morphological characters, five species are recognized as valid: Hypoglyptus conspersus (Leonhard, 1912) (Greece), H. elegans (Brullé, 1832) (Greece, Albania), H. gracilis Kiesenwetter, 1864 (Greece), H. graecus (Pic, 1902) (Greece), H. heydeni Faust, 1889 (Greece, Syria, Turkey). For this last species a lectotype is designated. Hypoglyptus pictus Gerstaecker, 1855 is proposed as n. syn. of H. elegans (Brullé, 1832). Male and female genitalia have been examined and are illustrated for the first time. The five species are very similar to and separable from each other by a few subtle differences in the shape, the sculpture, and the vestiture of the pronotum and elytra and in the more or less toothed femora. On the basis of morphological characters, the genus Hypoglyptus, previously incertae sedis in Curculionidae, is here tentatively placed in the tribe Smicronychini of the subfamily Curculioninae.
A Novel Vibration Suppression Method for Welding Robots Based on Welding Pool Instability Evaluation and Trajectory Optimization
Authors: Ma Mingtian , Lu Hong , Zhang Yongquan , Wu Zidong , Huang He , Yuan Xujie , Feng Xu , Liu Zhi , Li Zhangjie
Published: December 2024

Industrial robots are widely used in welding operations because of their high production efficiency. The structure of the robot and the complex stress conditions during welding operations lead to the vibration of the end of robot, which leads to welding defects. However, current vibration suppression techniques for welding robots usually only consider the robotic performance while overlooking their impact on the welding metal forming process. Therefore, based on the influence of robot vibration on welding pool stability during the welding process, a new welding robot vibration suppression method is proposed in this paper, along with the establishment of a welding pool stability assessment model. The proposed vibration suppression algorithm is based on the optimization of the welding trajectory. To enhance the performance of the method, the Particle Swarm Optimization (PSO) algorithm is applied to optimize the joint angular velocity and angular acceleration. Finally, robot welding experiments are designed and conducted. By comparing vibration measurement data and welding quality before and after the vibration suppression, the effectiveness and stability of the proposed method are validated.
Analysis of Multidimensional Clinical and Physiological Data with Synolitical Graph Neural Networks
Authors: Krivonosov Mikhail , Nazarenko Tatiana , Ushakov Vadim , Vlasenko Daniil , Zakharov Denis , Chen Shangbin , Blyus Oleg , Zaikin Alexey
Published: December 2024

This paper introduces a novel approach for classifying multidimensional physiological and clinical data using Synolitic Graph Neural Networks (SGNNs). SGNNs are particularly good for addressing the challenges posed by high-dimensional datasets, particularly in healthcare, where traditional machine learning and Artificial Intelligence methods often struggle to find global optima due to the “curse of dimensionality”. To apply Geometric Deep Learning we propose a synolitic or ensemble graph representation of the data, a universal method that transforms any multidimensional dataset into a network, utilising only class labels from training data. The paper demonstrates the effectiveness of this approach through two classification tasks: synthetic and fMRI data from cognitive tasks. Convolutional Graph Neural Network architecture is then applied, and the results are compared with established machine learning algorithms. The findings highlight the robustness and interpretability of SGNNs in solving complex, high-dimensional classification problems.
Pre-Occupancy Evaluation of Affective Experiences in Building Information Modeling Through SLR and an e-Delphi Survey
Authors: Renganathan Balamaheshwaran , Shanthi Priya Radhakrishnan , Senthil Ramalingam
Published: December 2024

Building information modeling (BIM) is increasingly used during the conceptual design phase, which focuses on simulations such as energy usage analysis and comfort levels, like temperature and lighting conditions, to enhance user experience and well-being, which are key factors for meeting Sustainable Development Goal 3. This study employs a systematic literature review and an e-Delphi survey to explore how a pre-occupancy evaluation integrated within BIM frameworks addresses affective responses and suggests ways to improve design decisions that align with the UN’s sustainable development goals. The study identified a research gap in how BIM evaluations are conducted during the conceptual design stage, including crucial sensory aspects for human well-being. The research suggests incorporating evidence-based design instruments like body sensor networks (BSN) and immersive virtual reality and methods like neurophenomenology to enhance the assessment of user interactions in the design process. Prioritizing the human-centered design approach right from the start can facilitate the integration of innovative workflows into architecture, engineering, and construction practices. Overcoming resistance to these workflows and methodologies is essential for advancing BIM’s role in fostering spatial environments that support health, well-being, and positive affective experiences.
Determination of Puberulic Acid in Monascus-Fermented Red Yeast Rice by LC-MS/MS Combined with Precolumn Derivatization
Authors: Pan Hui-Qin , Feng Rui , Tan Yan-Nan , Qin Xiao-Ya , Cao Yi-Min , Mao Xiu-Hong , Hu Qing , Zhou Heng
Published: December 2024

Puberulic acid (PA) is a mycotoxin produced by a species of Penicillium. It has received widespread attention as a significant contributor to the reported fatalities associated with red yeast rice dietary supplements. However, the detection of PA, especially at low concentration levels, poses a considerable challenge, with no detection methods reported thus far. Here, we present a simple and sensitive derivatization-based LC-MS/MS method, requiring no purification processes, for determination of PA in the red yeast rice. The methylating derivatization with trimethylsilyldiazomethane (TMSCHN2) was performed to enhance its analytical performance. To achieve optimal detection sensitivity, the amount of solvent and TMSCHN2 for the derivatization reaction, along with the reaction time, were individually optimized. Moreover, sample extraction solvent was carefully chosen to improve recoveries in real sample analyses. Comparatively, the proposed LC-MS/MS method achieved a superior detection sensitivity, over 100-fold higher than that of the liquid chromatography method. A good linear relationship within the concentration range of 5 ng/mL to 200 ng/mL (with a linear correlation coefficient of 0.99952) was demonstrated by the method validation. The average recovery rate was between 82.2% and 84.2%, and the repeatability (RSD of 2.1% to 10.4%, n = 6) was satisfactory. The derivatized PA remained stable within 48 h. The limit of detection and the limit of quantification could reach 2 μg/kg and 50 μg/kg, respectively. As a result, the method was successfully applied to detect PA in over 42 batches of the red yeast rice samples. It indicated a low risk of PA contaminations in the red yeast rice products made in China. Furthermore, its application to the other health food products containing red yeast rice demonstrated the applicability of the established method.
Effect of In Vitro Ruminal pH on Zearalenone Degradation and Interaction with Other Mycotoxins in a Static Gastrointestinal Model
Authors: Falkauskas Rimvydas , Jovaišienė Jurgita , Vaičiulienė Gintarė , Kerzienė Sigita , Jacevičienė Ingrida , Jacevičius Eugenijus , Jarmalaitė Inga , Ivaškienė Marija , Daunoras Gintaras , Želvytė Rasa , Baliukonienė Violeta
Published: December 2024

The degradation of zearalenone (ZEN) in the rumen of dairy cows is influenced by rumen pH, which is a key factor affecting this process. The aim of this study was to investigate the variation of ZEN in interaction with other mycotoxins at different ruminal pH environments (physiological (pH 6.5) and acidic (pH 5.5)) using an in vitro rumen model. Rumen fluid was collected from the caudoventral part of the rumen of cows using a pharyngeal–esophageal probe. To determine the changes in different mycotoxins (ZEN; AFLB1; DON; T-2) in the rumen of cows, a model rumen system was used, and mycotoxins concentrations were detected by HPLC. The study found that at pH 6.5, ZEN alone and in combination with other mycotoxins (DON; T-2; AFLB1) significantly (p < 0.05) reduced ZEN levels compared to the rumen environment at pH 5.5. It was observed that α-zearalenol (α-ZEL) and β-zearalenol (β-ZEL) concentrations were generally higher at a rumen pH of 6.5 compared to pH 5.5, averaging 47.09 µg/L and 35.23 µg/L, respectively. Additionally, the frequency of detection for both α-ZEL and β-ZEL was greater at pH 6.5 than at pH 5.5. A comparison of α-ZEL concentrations in rumen samples at pH 5.5 showed a 20% increase from the 6th to the 9th hour of the test, while β-ZEL levels remained unchanged over the same period.
Brazilian Gold Miners Working Irregularly in French Guiana: Health Status and Risk Determinants
Authors: Silva Amanda Figueira da , da Cruz Franco Vivian , Douine Maylis , Albuquerque Hermano Gomes , Hureau Louise , Sanna Alice , Atehortua Pamela Mosquera , Pereira Rafael dos Santos , da Silva Santos Simone , Marchesini Paola Barbosa , Bretas Gustavo , Gomes Margarete do Socorro Mendonça , Lambert Yann , Suárez-Mutis Martha Cecília
Published: December 2024

Brazilian garimpeiros are a highly hard-to-reach and mobile population, with little access to basic hygiene and health services, and have been crossing the border to work irregularly in gold mines in French Guiana since the 1990s. This study aimed to characterize this population and identify their main health problems. A cross-sectional study was carried out in the municipality of Oiapoque-AP, with two surveys: before (2018) and after (2019) the implementation of Malakit. Individuals were recruited from resting places and given a questionnaire regarding demographic variables, history and knowledge of malaria, and health issues in the mines. Simultaneously, a clinical evaluation was performed. The garimpeiros were mainly men from Maranhão, Pará, and Amapá, with a low educational level and who had worked on average for 10 years in the mining sites. The study population mentioned numerous health problems: malaria, followed by leishmaniasis, flu, body aches, headaches, and digestive problems. Other diseases mentioned were skin diseases, bat bites, hepatitis, and HIV infection. This vulnerable population is constantly subjected to heavy routines and exposed to different diseases and infections that can spread across borders. Knowledge of this is essential for developing public health policies that can be integrated into specific epidemiological situations.
Hospital-Based Surveillance of Respiratory Viruses Among Children Under Five Years of Age with ARI and SARI in Eastern UP, India
Authors: Deval Hirawati , Srivastava Mitali , Srivastava Neha , Kumar Niraj , Agarwal Aman , Potdar Varsha , Mehta Anita , Sharma Bhoopendra , Beniwal Rohit , Singh Rajeev , Singh Amresh Kumar , Gaur Vivek , Mittal Mahima , Dwivedi Gaurav Raj , Behera Sthita Pragnya , Kavathekar Asif , Prajapati Sanjay , Yadav Sachin , Gautam Dipti , Kumar Nalin , Iqbal Asif , Kant Rajni , Murhekar Manoj
Published: December 2024

Acute respiratory infections (ARIs) are a leading cause of death in children under five globally. The seasonal trends and profiles of respiratory viruses vary by region and season. Due to limited information and the population’s vulnerability, we conducted the hospital-based surveillance of respiratory viruses in Eastern Uttar Pradesh. Throat and nasal swabs were collected from outpatients and inpatients in the Department of Paediatrics, Baba Raghav Das (BRD) Medical College, Gorakhpur, between May 2022 and April 2023. A total of 943 samples from children aged 1 to 60 months were tested using multiplex real-time PCR for respiratory viruses in cases of ARI and SARI. Out of 943 samples tested, the highest positivity was found for parainfluenza virus [105 (11.13%) PIV-1 (79), PIV-2 (18), PIV-4 (18)], followed by adenovirus [82 (8.7%), RSV-B, [68 (7.21%)], influenza-A [46(4.9%): H1N1 = 29, H3N2 = 14), SARS CoV-2 [28 (3%)], hMPV [13(1.4%), RSV-A [4 (0.42%), and influenza-B (Victoria lineage) 1 (0.10%). The maximum positivity of respiratory viruses was seen in children between 1 to 12 months. The wide variation in prevalence of these respiratory viruses was seen in different seasons. This study enhances understanding of the seasonal and clinical trends of respiratory virus circulation and co-infections in Eastern Uttar Pradesh. The findings highlight the importance of targeted interventions to reduce the burden of respiratory infections in this region.
Development of a Luciferase Immunosorbent Assay for Detecting Crimean–Congo Hemorrhagic Fever Virus IgG Antibodies Based on Nucleoprotein
Authors: Chen Qi , Fang Yuting , Zhang Ning , Wan Chengsong
Published: December 2024

Crimean–Congo hemorrhagic fever (CCHF) is a serious tick-borne disease with a wide geographical distribution. Classified as a level 4 biosecurity risk pathogen, CCHF can be transmitted cross-species due to its aerosol infectivity and ability to cause severe hemorrhagic fever outbreaks with high morbidity and mortality. However, current methods for detecting anti-CCHFV antibodies are limited. This study aimed to develop a novel luciferase immunosorbent assay (LISA) for the detection of CCHFV-specific IgG antibodies. We designed specific antigenic fragments of the nucleoprotein and evaluated their sensitivity and specificity in detecting IgG in serum samples from mice and horses. In addition, we compared the efficacy of our LISA to a commercial enzyme-linked immunosorbent assay (ELISA). Our results demonstrated that the optimal antigen for detecting anti-CCHFV IgG was located within the stalk cut-off domain of the nucleoprotein. The LISA exhibited high specificity for serum samples from indicated species and significantly higher sensitivity (at least 128 times) compared with the commercial ELISA. The proposed CCHFV-LISA has the potential to facilitate serological diagnosis and epidemiological investigation of CCHFV in natural foci, providing valuable technical support for surveillance and early warning of this disease.
Clinical Characteristics and Outcomes in Patients with Chronic HBV Infection and Hospitalized for COVID-19 Pneumonia: A Retrospective Cohort Study
Authors: Boglione Lucio , Crobu Maria Grazia , Pirisi Mario , Smirne Carlo
Published: December 2024

The effects of a concomitant infection of hepatitis B virus (HBV) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are still debated, with a recognized major risk of HBV reactivation during immune-suppressive treatments. The aim of this study was to determine the prevalence and predictive factors of HBV reactivation in a cohort of hospitalized patients with coronavirus disease 2019 (COVID-19) and a current or past hepatitis B infection. In a monocentric retrospective observational study, we enrolled all consecutive hospital admitted patients with COVID-19 pneumonia and a positive HBV serology (N = 84) in our Infectious Diseases Unit from April 2021 to December 2023. We identified 18 (21%) HBsAg-positive/anti-HBc-positive, 41 (49%) HBsAg-negative/anti-HBc-positive/anti-HBs-positive, and 25 (30%) HBsAg-negative/anti-HBc-positive/anti-HBs-negative subjects. The overall rate of hepatitis flare was 10.7%, without any HBsAg seroreversion, severe HBV reactivation, and/or need for new HBV antiviral therapy introduction. Systemic corticosteroid treatment for COVID-19 and baseline anti-HBsAg status were associated with this risk of HBV reactivation. In conclusion, the overall risk of hepatitis flares in hospitalized COVID-19 was reasonably low, with higher doses of corticosteroids treatment being the major risk factor for HBV reactivation, and anti-HBs-positive serological status as a protective element.
Incidence of HBV Reactivation in Psoriasis Patients Undergoing Cytokine Inhibitor Therapy: A Single-Center Study and Systematic Review with a Meta-Analysis
Authors: Kuo Meng Hsuan , Ko Ping-Hung , Wang Sz-Tsan , Tseng Chih-Wei
Published: December 2024

Background: Psoriasis patients who are seropositive for hepatitis B surface antigen (HBsAg) or hepatitis B core antibody (HBcAb) face an elevated risk of hepatitis B virus reactivation (HBVr) when treated with cytokine inhibitors. This study aims to elucidate the risk in this population. Methods: A retrospective chart review was conducted to assess the risk of HBVr in 73 psoriasis patients treated with cytokine inhibitors from 2013 to 2023. Additionally, a systematic review and meta-analysis were performed, pooling data from 10 studies (including our cohort) and adhering to PRISMA guidelines. Statistical heterogeneity was assessed using the I2 statistic, and pooled proportions were calculated using a random effects model. Results: No HBVr cases were observed among the 11 HBsAg+ patients in the cohort. However, two of the sixty-two (3.2%) HBsAg−/HBcAb+ patients experienced reactivation during therapy, with outcomes ranging from spontaneous recovery in one case to death from hepatic failure despite antiviral treatment in the other. The meta-analysis, pooling data from 10 studies, revealed a reactivation rate of 21.2% (95% CI: 9.4–41.0%) in HBsAg+ patients without prophylaxis and 4.4% (95% CI: 2.2–8.7%) in HBsAg−/HBcAb+ patients. Conclusion: Antiviral prophylaxis is essential for HBsAg+ patients receiving cytokine inhibitors, given the high risk of reactivation. Despite the lower risk for HBsAg−/HBcAb+ patients, the potential severity of outcomes demands careful monitoring and timely action.
Unveiling the Molecular Architecture of HBV Spherical Subviral Particles: Structure, Symmetry, and Lipid Dynamics
Authors: Garg Sonal , Ochetto Alyssa , Hu Jianming , Wang Joseph Che-Yen
Published: December 2024

Since the discovery of the Australia antigen, now known as the hepatitis B surface antigen (HBsAg), significant research has been conducted to elucidate its physical, chemical, structural, and functional properties. Subviral particles (SVPs) containing HBsAg are highly immunogenic, non-infectious entities that have not only revolutionized vaccine development but also provided critical insights into HBV immune evasion and viral assembly. Recent advances in cryo-electron microscopy (cryo-EM) have uncovered the heterogeneity and dynamic nature of spherical HBV SVPs, emphasizing the essential role of lipid–protein interactions in maintaining particle stability. In this review, recent progress in understanding the molecular architecture of HBV SVPs is consolidated, focusing on their symmetry, lipid organization, and disassembly–reassembly dynamics. High-resolution structural models reveal unique lipid arrangements that stabilize hydrophobic residues, preserve antigenicity, and contribute to SVP functionality. These findings highlight the significance of hydrophobic interactions and lipid–protein dynamics in HBV SVP assembly and stability, offering valuable perspectives for optimizing SVP-based vaccine platforms and therapeutic strategies.
Pregnancy and COVID-19: Comparing ICU Outcomes for Pregnant and Nonpregnant Women
Authors: Lipińska-Gediga Małgorzata , Goździk Waldemar , Śmiechowicz Jakub , Adamik Barbara
Published: December 2024

Background: This study compares organ dysfunction, treatment strategies, and unfavorable outcome rates between pregnant and nonpregnant women admitted to the ICU with severe COVID-19, highlighting the increased susceptibility of pregnant women to respiratory infections due to physiological changes. Methods: A retrospective, age-matched study was conducted at a referral center specializing in critical care for pregnant women. Data from 14 pregnant/postpartum and 11 nonpregnant women were analyzed at ICU admission and on days 3, 5, and 7. Results: Acute respiratory distress syndrome was diagnosed in 100% of the pregnant/postpartum group and 64% of the nonpregnant group (p = 0.026). Inflammatory parameters were similar between groups, except for lower ferritin levels in the pregnant/postpartum group compared to the nonpregnant (120 vs. 568 µg/L at admission and 90 vs. 616 µg/L on day 3). Creatinine, lactate, and lactate dehydrogenase levels were significantly lower in the pregnant/postpartum group. A reduction in the SOFA score was observed over time in the pregnant/postpartum group (from 7.0 to 4.0 points, p = 0.009), while no change was noticed in the nonpregnant group (from 3.0 to 2.5 points, p = 0.181). Unfavorable outcome rates were similar, with two patients from each group succumbing to the disease (p = 0.604). Conclusions: The findings suggest that pregnancy does not increase the risk of unfavorable outcomes among women with severe COVID-19 receiving ICU treatment. However, additional studies with larger sample sizes are needed to validate these observations.
Exploiting the Achilles’ Heel of Viral RNA Processing to Develop Novel Antivirals
Authors: Zahedi Amiri Ali , Ahmed Choudhary , Dahal Subha , Grosso Filomena , Leng Haomin , Stoilov Peter , Mangos Maria , Toutant Johanne , Shkreta Lulzim , Attisano Liliana , Chabot Benoit , Brown Martha , Huesca Mario , Cochrane Alan
Published: December 2024

Treatment options for viral infections are limited and viruses have proven adept at evolving resistance to many existing therapies, highlighting a significant vulnerability in our defenses. In response to this challenge, we explored the modulation of cellular RNA metabolic processes as an alternative paradigm to antiviral development. Previously, the small molecule 5342191 was identified as a potent inhibitor of HIV-1 replication by altering viral RNA accumulation at doses that minimally affect host gene expression. In this report, we document 5342191 as a potent inhibitor of adenovirus, coronavirus, and influenza replication. In each case, 5342191-mediated reduction in virus replication was associated with altered viral RNA accumulation and loss of viral structural protein expression. Interestingly, while resistant viruses were rapidly isolated for compounds targeting either virus-encoded proteases or polymerases, we have not yet isolated 5342191-resistant variants of coronavirus or influenza. As with HIV-1, 5342191’s inhibition of coronaviruses and influenza is mediated through the activation of specific cell signaling networks, including GPCR and/or MAPK signaling pathways that ultimately affect SR kinase expression. Together, these studies highlight the therapeutic potential of compounds that target cellular processes essential for the replication of multiple viruses. Not only do these compounds hold promise as broad-spectrum antivirals, but they also offer the potential of greater resilience in combating viral infections.
Vaccinating in Different Settings: Best Practices from Italian Regions
Authors: Signorelli Carlo , Pennisi Flavia , D’Amelio Anna Carole , Conversano Michele , Cinquetti Sandro , Blandi Lorenzo , Rezza Giovanni
Published: December 2024

Background: The success of vaccination programs depends on a complex interplay of logistical, social, and structural factors. The objective of this study was to analyze the different approaches to vaccine administration implemented by several Italian regions since the onset of the SARS-CoV-2 pandemic. Methods: After careful qualitative review of information gathered from scientific articles, official reports (grey literature), contact with regional health authorities, and local health departments, five vaccination strategies across several Italian regions focusing on alternative vaccine providers and/or settings were identified. The innovative practices implemented by different actors covered specific topics and were then examined and described in detail. Results: In Veneto, where prevention departments were the main actor, herpes zoster vaccination coverage for the 65-year-old cohort increased from 44.4% to 54.9%; in Tuscany, family pediatricians administered 64% of all childhood vaccines; in Liguria, pharmacies delivered 70.1% of COVID-19 vaccines, while vaccinating in schools in Taranto led to higher human papilloma virus vaccination rates compared to regional and national averages. Finally, in all the regions, hospitals focused on vaccinating healthcare workers and vulnerable populations. Conclusions: The positive outcomes of these five experiences may, in a context of limited resources, encourage other national and international entities to adopt innovative practices, which offer new perspectives beyond the traditional delivery methods (i.e., local health authority vaccination centers for childhood and adolescent immunizations, and family doctors for adults and the elderly). These strategies suggest the efficacy of specific local approaches favored by regional autonomy in optimizing vaccine distribution and coverage.
A Model H5N2 Vaccine Strain for Dual Protection Against H5N1 and H9N2 Avian Influenza Viruses
Authors: Song Jin-Ha , Son Seung-Eun , Kim Ho-Won , An Se-Hee , Lee Chung-Young , Kwon Hyuk-Joon , Choi Kang-Seuk
Published: December 2024

Background/Objective: Highly pathogenic (HP) H5Nx and low-pathogenicity (LP) H9N2 avian influenza viruses (AIVs) pose global threats to the poultry industry and public health, highlighting the critical need for a dual-protective vaccine. Methods: In this study, we generated a model PR8-derived recombinant H5N2 vaccine strain with hemagglutinin (HA) and neuraminidase (NA) genes from clade 2.3.2.1c H5N1 and Y439-like H9N2 viruses, respectively. To enhance the immunogenicity of the recombinant H5N2 vaccine strain, N-glycans of the HA2 subunit, NA, and M2e were modified. Additionally, we replaced M2e with avian M2e to enhance the antigenic homogeneity of AIVs for better protection. We also replaced PR8 PB2 with 01310 PB2, which is the PB2 gene derived from an LP H9N2 avian influenza virus, to eliminate pathogenicity in mammals. The productivity of the model vaccine strain (rvH5N2-aM2e-vPB2) in embryonated chicken eggs (ECEs), its potential risk of mammalian infection, and the immunogenicity associated with different inactivation methods (formaldehyde (F/A) vs. binary ethyleneimine (BEI)) were evaluated. Results: The rvH5N2-aM2e-vPB2 strain demonstrated high productivity in ECEs and exhibited complete inhibition of replication in mammalian cells. Furthermore, compared with using F/A inactivation, inactivation using BEI significantly enhanced the immune response, particularly against NA. This enhancement resulted in increased virus neutralization titers, supporting its efficacy for dual protection against H5Nx and H9N2 avian influenza viruses. Furthermore, we demonstrated that M2e-specific immune responses, difficult to induce with inactivated vaccines, can be effectively elicited with live vaccines, suggesting a strategy to enhance M2e immunogenicity in whole influenza virus vaccines. Conclusions: Finally, the successful development of the model rH5N2 vaccine strain is described; this strain provides dual protection, has potential applicability in regions where avian influenza is endemic, and can be used to promote the development of versatile H5N2 recombinant vaccines for effective avian influenza control.
Antigen Delivery Platforms for Next-Generation Coronavirus Vaccines
Authors: Chentoufi Aziz A. , Ulmer Jeffrey B. , BenMohamed Lbachir
Published: December 2024

The COVID-19 pandemic, caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), is in its sixth year and is being maintained by the inability of current spike-alone-based COVID-19 vaccines to prevent transmission leading to the continuous emergence of variants and sub-variants of concern (VOCs). This underscores the critical need for next-generation broad-spectrum pan-Coronavirus vaccines (pan-CoV vaccine) to break this cycle and end the pandemic. The development of a pan-CoV vaccine offering protection against a wide array of VOCs requires two key elements: (1) identifying protective antigens that are highly conserved between passed, current, and future VOCs; and (2) developing a safe and efficient antigen delivery system for induction of broad-based and long-lasting B- and T-cell immunity. This review will (1) present the current state of antigen delivery platforms involving a multifaceted approach, including bioinformatics, molecular and structural biology, immunology, and advanced computational methods; (2) discuss the challenges facing the development of safe and effective antigen delivery platforms; and (3) highlight the potential of nucleoside-modified mRNA encapsulated in lipid nanoparticles (LNP) as the platform that is well suited to the needs of a next-generation pan-CoV vaccine, such as the ability to induce broad-based immunity and amenable to large-scale manufacturing to safely provide durable protective immunity against current and future Coronavirus threats.