bluuebunny/crossref_metadata_2025 huggingface dataset:
Estimating Evapotranspiration in the Qilian Mountains Using GRACE/GRACE-FO Satellite Data
Authors: Bai Bing , Yue Ping , Ren Xueyuan , Zhang Qiang , Zhang Jinyu , Yang Jinhu , Jiang Youyan
Published: May 2024

Evapotranspiration (ET) is the most significant constituent of the response to climate warming. It serves as a crucial link in the soil–vegetation–atmospheric continuum. Analyzing the driving forces and response of ET to regional-scale climate warming holds scientific significance in improving global water resource assessment methods and drought monitoring techniques. The innovation presented in this article is the calculation of ET by using GRACE/GRACE-FO satellite data through the water balance equation. The inter-annual and seasonal changes in ET in different regions of the Qilian Mountains were analyzed, along with quantifying the contribution of environmental meteorological factors to ET. The ETGRACE and ETMonitor products have good consistency, with a monthly correlation coefficient of 0.92, an NSE coefficient of 0.80, and a root mean square error of 10.38 mm. The results indicate that the increasing trend of ET in the Qilian Mountains region exhibits a “medium–high–low” distribution pattern. The rate of increase in ET is 5.2 mm/year in the central segment. In spring and summer, the overall trend of ET is an increasing one. However, the central and western segments exhibit a slight decreasing trend of ET in autumn. During winter, the southern part of the Qilian Mountains experiences a notable reduction in ET. The correlation between the changes in ET and soil moisture exhibited a strong association, with soil moisture change contributing significantly to ET: 57.8% for the eastern section, 52.8% for the middle section, and 46.9% for the western section. The thermal effect primarily controls ET variations within eastern sections, where temperature change accounts for approximately 6.7% of the total variation in ET levels. Conversely, the moisture factor dominates western sections, where precipitation change accounts for about 6.5% of the total variation in ET levels. Due to the distinct gradient characteristics of environmental meteorological factors in the central segment, the fluctuation of these factors collaboratively drives ET changes. This article provides a new approach for obtaining continuous and reliable actual evapotranspiration in high-altitude areas.
HVConv: Horizontal and Vertical Convolution for Remote Sensing Object Detection
Authors: Chen Jinhui , Lin Qifeng , Huang Haibin , Yu Yuanlong , Zhu Daoye , Fu Gang
Published: May 2024

Generally, the interesting objects in aerial images are completely different from objects in nature, and the remote sensing objects in particular tend to be more distinctive in aspect ratio. The existing convolutional networks have equal aspect ratios of the receptive fields, which leads to receptive fields either containing non-relevant information or being unable to fully cover the entire object. To this end, we propose Horizontal and Vertical Convolution, which is a plug-and-play module to address different aspect ratio problems. In our method, we introduce horizontal convolution and vertical convolution to expand the receptive fields in the horizontal and vertical directions, respectively, to reduce redundant receptive fields, so that remote sensing objects with different aspect ratios can achieve better receptive fields coverage, thereby achieving more accurate feature representation. In addition, we design an attention module to dynamically aggregate these two sub-modules to achieve more accurate feature coverage. Extensive experimental results on the DOTA and HRSC2016 datasets show that our HVConv achieves accuracy improvements in diverse detection architectures and obtains SOTA accuracy (mAP score of 77.60% with DOTA single-scale training and mAP score of 81.07% with DOTA multi-scale training). Various ablation studies were conducted as well, which is enough to verify the effectiveness of our model.
The Cost of Urban Renewal: Annual Construction Waste Estimation via Multi-Scale Target Information Extraction and Attention-Enhanced Networks in Changping District, Beijing
Authors: Huang Lei , Lin Shaofu , Liu Xiliang , Wang Shaohua , Chen Guihong , Mei Qiang , Fu Zhe
Published: May 2024

Construction waste is an inevitable byproduct of urban renewal, causing severe pressure on the environment, health, and ecology. Accurately estimating the production of construction waste is crucial for assessing the consumption of urban renewal. However, traditional manual estimation methods rely heavily on statistical data and historical experience, which lack flexibility in practical applications and are time-consuming and labor-intensive. In addition, their accuracy and timeliness need to be improved urgently. Fortunately, with the advantages of high-resolution remote sensing images (HRSIs) such as strong timeliness, large amounts of information, and macroscopic observations, they are suitable for the large-scale dynamic change detection of construction waste. However, the existing deep learning models have a relatively poor ability to extract and fuse features for small and multi-scale targets, and it is difficult to deal with irregularly shaped and fragmented detection areas. Therefore, this study proposes a Multi-scale Target Attention-Enhanced Network (MT-AENet), which is used to dynamically track and detect changes in buildings and construction waste disposal sites through HRSIs and accurately estimate the annual production of urban construction waste. The MT-AENet introduces a novel encoder–decoder architecture. In the encoder, ResNet-101 is utilized to extract high-level semantic features. A depthwise separable-atrous spatial pyramid pooling (DS-ASPP) module with different dilation rates is constructed to address insufficient receptive fields, resolving the issue of discontinuous holes when extracting large targets. A dual-attention mechanism module (DAMM) is employed to better preserve positional and channel details. In the decoder, multi-scale feature fusion (MS-FF) is utilized to capture contextual information, integrating shallow and intermediate features of the backbone network, thereby enhancing extraction capabilities in complex scenes. The MT-AENet is used to extract buildings and construction waste at different periods in the study area, and the actual production and landfill volume of construction waste are calculated based on area changes, indirectly measuring the rate of urban construction waste resource conversion. The experimental results in Changping District, Beijing demonstrate that the MT-AENet outperforms existing baseline networks in extracting buildings and construction waste. The results of this study are validated according to government statistical standards, providing a promising direction for efficiently analyzing the consumption of urban renewal.
Evaluating Tropical Cyclone-Induced Flood and Surge Risks for Vanuatu by Assessing Location Hazard Susceptibility
Authors: Do Cameron , Kuleshov Yuriy , Choy Suelynn , Sun Chayn
Published: May 2024

Tropical cyclones (TCs) can be devastating events for vulnerable countries like Vanuatu, impacting their population, livelihoods, and infrastructure, leaving the country in need of aid and recovery. Despite this, comprehensive risk information on the nuanced impacts of each region is not well understood. Every TC event is different, and understanding the potential for impact at each location empowers decision makers in the lead-up to an event or during off-season planning to make more informed decisions to direct disaster risk reduction efforts. TC hazard model data typically describe intensity and likelihood, which can be fed into risk assessment frameworks to describe probabilistic risk. This study instead uses freely available remote sensing data to create proxies for the TC hazards of storm surge and flooding and to describe only the intensity of the hazard if the event occurs at the location. This hazard susceptibility index is fed into a risk assessment framework with Vanuatu exposure and vulnerability data for domains of populations, housing, and roads. These methods allow for the risk to be estimated for each month, as well as during specific historical time periods of TC Pam, TC Harold, and the TCs Judy and Kevin, enabling future impact validation. The results show households to have the highest risk, followed by roads and population domains, while a TC-induced surge risk is overall higher than TC-induced flooding, particularly in the road domain. The results, however, show a likely underestimation of event hazards and an overestimation of Port Vila’s resistance to impacts, which is a subject of future investigation and validation.
Spatiotemporal Mechanism-Based Spacetimeformer Network for InSAR Deformation Prediction and Identification of Retrogressive Thaw Slumps in the Chumar River Basin
Authors: Wang Jing , Fan Xiwei , Zhang Zhijie , Zhang Xuefei , Nie Wenyu , Qi Yuanmeng , Zhang Nan
Published: May 2024

The increasing incidence of retrogressive thaw slumps (RTSs) in permafrost regions underscores the need for detailed spatial and temporal analysis using InSAR technology to monitor and predict dynamic changes in the process of RTSs. Nevertheless, current InSAR deformation forecasting methods employing deep learning strategies such as the traditional long short-term memory (LSTM) and recent transformer models encounter difficulties in effectively capturing temporal features. Moreover, they are limited in their ability to directly integrate spatial information. In this paper, an innovative deep learning approach named Spacetimeformer is proposed for predicting medium- and short-term InSAR deformation of RTSs in the Chumar River area. This method employs a transformer architecture with a spatiotemporal attention mechanism, which enhances the long-term prediction capabilities of time series models and dynamic spatial modeling. It is applicable to multivariate InSAR spatiotemporal deformation prediction problems. The findings include a list of 72 RTSs compiled based on derived InSAR deformation maps and Sentinel-2 optical images, of which 64 have an average deformation rate exceeding 10 mm/year, indicating signs of permafrost degradation. The density distribution of the displacement maps predicted by the Spacetimeformer model aligned well with the InSAR deformation maps obtained from the small baseline subset (SBAS) method, with the overall prediction deviation controlled within 20 mm. In addition, the point-scale prediction results were compared with LSTM and transformer models. This study indicates that the Spacetimeformer network achieved good results in predicting the deformation of RTSs, with a root mean square error of 1.249 mm. The Spacetimeformer method for deformation prediction with the spacetime mechanism presented in this study can serve as a general framework for multivariate deformation prediction based on InSAR results. It can also quantitatively assess the spatial deformation characteristics and deformation trends of RTSs.
Analysis of Lake Area Dynamics and Driving Forces in the Jianghan Plain Based on GEE and SEM for the Period 1990 to 2020
Authors: He Minghui , Liu Yi
Published: May 2024

The lakes of Jianghan Plain, as an important component of the water bodies in the middle and lower reaches of the Yangtze River plain, have made significant contributions to maintaining the ecological health and promoting the sustainable development of the Jianghan Plain. However, there is a relatively limited understanding regarding the trends of lake area change for different types of lakes and their dominant factors over the past three decades in the Jianghan Plain. Based on the Google Earth Engine (GEE) platform, combined with the water body index method, the changes in area of three different types of lakes (area > 1 km2) in the Jianghan Lake Group from 1990 to 2020 were extracted and analyzed. Additionally, the Partial least squares structural equation model (PLS-SEM) was utilized to analyze the driving factors affecting the changes in water body area of these lakes. The results show that from 1990 to 2020, the area of the lakes of the wet season and level season exhibited a decreasing trend, decreasing by 893.1 km2 and 77.9 km2, respectively. However, the area of dry season lakes increased by 59.27 km2. The areas of all three types of lakes reached their minimum values in 2006. According to the PLS-SEM results, the continuous changes in the lakes’ area are mainly controlled by environmental factors overall. Furthermore, human factors mainly influence the mutation of the lakes’ area. This study achieved precise extraction of water body areas and accurate analysis of driving factors, providing a basis for a comprehensive understanding of the dynamic changes in the lakes of Jianghan Plain, which is beneficial for the rational utilization and protection of water resources.
How Enterprises Achieve Frugal Innovation: A Configurational Study Based on the Model of Organizational Symbiosis
Authors: Zhang Zhe , Liu Hongyan , Zhao Yunhui
Published: May 2024

Frugal innovation offers cost-effective, demand-driven products for consumers in emerging markets. By leveraging this approach, enterprises can capitalize on opportunities, boost profits, and nurture beneficial consumer relationships. This study uses the transaction cost theory to explore how symbiotic relationships within environmental turbulence influence frugal innovation. The goal is to unravel the interconnected factors that drive high-performance frugal innovation, providing enterprises with a roadmap for seizing opportunities, enhancing profitability, and cultivating enduring consumer relationships. Data from 218 Chinese enterprises were collected through a survey and analyzed using fuzzy-set Qualitative Comparative Analysis (fsQCA) and Necessary Condition Analysis (NCA) methods. The research findings indicate that factors such as market dynamics, technological dynamics, collaboration with suppliers and customers, relationship governance, contract governance, and inter-organizational trust are not necessary prerequisites for high frugal innovation performance. Instead, the synergy among these factors is imperative for reaching elevated levels of frugal innovation performance. Furthermore, three distinct pathways to heightened frugal innovation performance were identified: a dual-drive mechanism involving membership relationships and governance mechanisms, a membership-driven approach in dynamic technological conditions, and a governance mechanism-driven approach in dynamic market conditions. This study offers valuable theoretical and practical insights for enterprises pursuing frugal innovation in turbulent environments, guiding them towards sustained growth and competitive advantages in new markets.
WTBD-YOLOv8: An Improved Method for Wind Turbine Generator Defect Detection
Authors: Tong Liang , Fan Changlong , Peng Zhongbo , Wei Cong , Sun Shijie , Han Jie
Published: May 2024

Wind turbine blades are the core components responsible for efficient wind energy conversion and ensuring stability. To address challenges in wind turbine blade damage detection using image processing techniques such as complex image backgrounds, decreased detection performance due to high image resolution, prolonged inference time, and insufficient recognition accuracy, this study introduces an enhanced wind turbine blade damage detection model named WTDB-YOLOv8. Firstly, by incorporating the GhostCBS and DFSB-C2f modules, the aim is to reduce the number of model parameters while enhancing feature extraction capability. Secondly, by integrating the MHSA-C2f module, which incorporates a multi-head self-attention mechanism, the focus on global information is enabled, thereby mitigating irrelevant background interference and reducing the impact of complex backgrounds on damage detection. Lastly, adopting the Mini-BiFPN structure improves the retention of features for small target objects in shallow networks and reinforces the propagation of these features in deep networks, thereby enhancing the detection accuracy of small target damage and reducing false negative rates. Through training and testing on the Wind Turbine Blade Damage Dataset (WTBDD), the WTDB-YOLOv8 model achieves an average precision of 98.3%, representing a 2.2 percentage point improvement over the original YOLOv8 model. Particularly noteworthy is the increase in precision from 93.1% to 97.9% in small target damage detection. Moreover, the total parameter count of the model decreases from 3.22 million in YOLOv8 to 1.99 million, marking a reduction of 38.2%. Therefore, the WTDB-YOLOv8 model not only enhances the detection performance and efficiency of wind turbine blade damage but also significantly reduces the model parameter count, showcasing its practical advantages in engineering applications.
Applying Blockchain, Causal Loop Diagrams, and the Analytical Hierarchy Process to Enhance Fifth-Generation Ceramic Antenna Manufacturing: A Technology–Organization–Environment Framework Approach
Authors: An Sung Yong , Ngayo Guy , Hong Seng-Phil
Published: May 2024

This study used a technology–organization–environment (TOE) framework as the primary analytical tool to explore the burgeoning capabilities of blockchain technology in the area of 5G ceramic antenna development. A causal loop diagram (CLD) analysis is used to further clarify the complex dynamics and feedback mechanisms, and the impact of blockchain on the design, production, and deployment phases of ceramic antennas, which play a pivotal role in the development of 5G communications, is studied. We found that blockchain’s unique features, including its immutable ledger and decentralized architecture, have the potential to significantly improve the transparency, security, and efficiency of the ceramic antenna manufacturing process. Technology (T), organization (O), and environment (E) were used as the top factors, and the subfactors of TOE were selected and analyzed using the Analytic Hierarchy Process (AHP) by CLD. The AHP analysis was used to evaluate the relative importance of various internal and external factors affecting the adoption of blockchain technology. The integration of the TOE framework with AHP and CLD provides a comprehensive analytical tool that enhances the understanding of the complex dynamics in the 5G ceramic antenna manufacturing process. This methodological approach not only clarifies the interactions between technological, organizational, and environmental factors but also facilitates strategic decision-making through a structured evaluation of these factors. The AHP analysis showed that technical factors are the most important in the TOE analysis of 5G ceramic antenna manufacturing, with a weight of 0.427, which indicates the important role of technical factors in the development of ceramic antenna production. In addition, environmental and organizational factors were given weights of 0.302 and 0.271, respectively, confirming the importance of technological innovation and internal process optimization. In the subfactor of Technology (T), ‘Blockchain Technology’ has the highest ranking among the subfactors, with a global weight value of 0.129, emphasizing the importance of blockchain technology. This study explored the technical and organizational complexities of introducing blockchain technology into the 5G ceramic antenna manufacturing industry and, through an in-depth investigation of the potential benefits of such integration, it aims to propose new approaches to improve quality control and manufacturing efficiency. The research findings aim to contribute to the sustainable growth of the telecommunications industry by providing strategic recommendations for the application of blockchain technology in the production of 5G ceramic antennas.
A Mechanistic Study of Enterprise Digital Intelligence Transformation, Innovation Resilience, and Firm Performance
Authors: Zhang Guangsi , Wang Xuehe , Xie Jiaping , Hu Qiang
Published: May 2024

Enterprise Digital Intelligence Transformation is based on the Digital Conversion of information and process service upgrading, further touching the enterprise’s core business, with the goal of building a new business model of Digital Intelligence Transformation at a higher level. Based on dynamic capability theory, this paper conducts an in-depth study on the mechanism of enterprise Digital Intelligence Transformation and firm performance. This paper selects manufacturing companies listed in China’s Shanghai and Shenzhen A-shares from 2013 to 2022 as the research sample, and analyzes and tests the sample data using empirical research methods in order to explore the actual impact of Digital Intelligence Transformation on firm performance, including the specific pathways of action and moderating effects. This study helps enterprises to positively face the megatrend of Digital Intelligence Transformation and upgrading and the challenges it brings, and to grasp the new opportunities in the digital era. This study finds that enterprises carry out digital empowerment transformation and development strategies, and implement information Digital Conversion, service upgrading, and Digital Intelligence Transformation to promote firm performance to different degrees. Enterprise innovation resilience has a mechanism effect between information digitalization conversion enterprise performance and process service upgrading enterprise performance. The higher the environmental uncertainty, the greater the positive contribution of information digitalization to firm performance. Digital Conversion is the base and service upgrading is the process. The current sample enterprises have limited years of data collection, and most of them have only carried out the strategic implementation of Digital Conversion or servitization, and have not reached the high-level stage of digital and intellectual transformation. Therefore, it is found that enterprise innovation resilience has not yet shown a significant role mechanism effect between digital–intelligent transformation and enterprise performance at present. And environmental uncertainty has not yet shown a significant moderating effect in the stage of Servitization Upgrading and digital–intelligent transformation. The marginal contributions of this paper are mainly reflected in the following: (1) This study introduces the dynamic capability theory to explore the role of Digital Intelligence Transformation (Digital Conversion + service upgrading) on enterprise performance. (2) This paper investigates the role of Digital Intelligence Transformation in influencing the performance of enterprises from the Digital Conversion and service upgrading phases, and enriches the relevant role and regulatory mechanisms. (3) This study provides new ideas and strategic suggestions on Digital Intelligence Transformation for enterprises with different factor intensities, at different stages of development, and in different regions.
Identification and Evolutionary Analysis of the Widely Distributed CAP Superfamily in Spider Venom
Authors: Jiang Hongcen , Wang Yiru , Zhang Guoqing , Jia Anqiang , Wei Zhaoyuan , Wang Yi
Published: May 2024

Venom plays a crucial role in the defense and predation of venomous animals. Spiders (Araneae) are among the most successful predators and have a fascinating venom composition. Their venom mainly contains disulfide-rich peptides and large proteins. Here, we analyzed spider venom protein families, utilizing transcriptomic and genomic data, and highlighted their similarities and differences. We show that spiders have specific combinations of toxins for better predation and defense, typically comprising a core toxin expressed alongside several auxiliary toxins. Among them, the CAP superfamily is widely distributed and highly expressed in web-building Araneoidea spiders. Our analysis of evolutionary relationships revealed four subfamilies (subA-subD) of the CAP superfamily that differ in structure and potential functions. CAP proteins are composed of a conserved CAP domain and diverse C-terminal domains. CAP subC shares similar domains with the snake ion channel regulator svCRISP proteins, while CAP subD possesses a sequence similar to that of insect venom allergen 5 (Ag5). Furthermore, we show that gene duplication and selective expression lead to increased expression of CAP subD, making it a core member of the CAP superfamily. This study sheds light on the functional diversity of CAP subfamilies and their evolutionary history, which has important implications for fully understanding the composition of spider venom proteins and the core toxin components of web-building spiders.
Exploration of the Molecular Mechanism by Which Caveolin-1 Regulates Changes in Blood–Brain Barrier Permeability Leading to Eosinophilic Meningoencephalitis
Authors: Chen An-Chih , Lai Shih-Chan , Lu Cheng-You , Chen Ke-Min
Published: May 2024

Angiostrongylus cantonensis, a zoonotic parasite, can invade the human central nervous system (CNS) and cause acute eosinophilic meningitis or eosinophilic meningoencephalitis. Mice infected with A. cantonensis show elevated levels of pro-inflammatory cytokines, plasminogen activators, and matrix metalloproteinase-9, resulting in disruption of the blood–brain barrier (BBB) and immune cell infiltration into the CNS. Caveolin-1 (Cav-1) regulates the permeability of the BBB, which affects immune cells and cerebrospinal fluid. This intricate interaction ultimately fuels the progression of brain damage and edema. This study aims to investigate the regulatory role of Cav-1 in the pathogenesis of meningoencephalitis induced by A. cantonensis infection. We investigated pathological alterations by triphenyl-tetrazolium chloride, brain water content, BBB permeability, Western blot analysis, and gelatin zymography in BALB/c mice after A. cantonensis. The study evaluates the critical role of Cav-1 regulation through the TLR4/MyD88 signaling pathway, modulates tight junction proteins, influences BBB permeability, and contributes to brain damage in A. cantonensis-induced meningoencephalitis.
Strange Quark Stars: The Role of Excluded Volume Effects
Authors: Lugones G. , Grunfeld Ana G.
Published: May 2024

We study cold strange quark stars employing an enhanced version of the quark-mass density-dependent model, which incorporates excluded volume effects to address non-perturbative QCD repulsive interactions. We provide a comparative analysis of our mass formula parametrization with previous models from the literature. We identify the regions within the parameter space where three-flavor quark matter is more stable than the most tightly bound atomic nucleus (stability window). Specifically, we show that excluded volume effects do not change the Gibbs free energy per baryon at zero pressure, rendering the stability window unaffected. The curves of pressure versus energy density exhibit various shapes—convex upward, concave downward, or nearly linear—depending on the mass parametrization. This behavior results in different patterns of increase, decrease, or constancy in the speed of sound as a function of baryon number density. We analyze the mass–radius relationship of strange quark stars, revealing a significant increase in maximum gravitational mass and a shift in the curves toward larger radii as the excluded volume effect intensifies. Excluded volume effects render our models compatible with all modern astrophysical constraints, including the properties of the recently observed low-mass compact object HESSJ1731.
Tackling Carbon Footprints: Sustainability Challenges of Hosting the Final Four in Kaunas, Lithuania
Authors: Perkumienė Dalia , Atalay Ahmet , Labanauskas Gintautas
Published: May 2024

The purpose of this study is to calculate the carbon footprint of the 2023 EuroLeague Men’s Final Four competition and identify the sources of the carbon footprint in sports. This study also aims to predict possible solutions to reduce this footprint. Mixed research methods were used in this study. Firstly, carbon footprint calculations related to the teams and fan travel were carried out. In the second step, interviews were conducted with the managers of the teams that won the basketball Final Four. The interviews were conducted using a semi-structured interview. The total carbon footprint of the four teams participating in the competitions was calculated as 4560.25 kg, and the average of the total carbon footprint of the teams per person was calculated as 189.74 kg. The total carbon footprint of the fans of the four teams was calculated as 4065.686 kg, and the average of the total carbon footprint per capita of the fans was calculated as 3.003 kg. According to the interview findings, the carbon footprint sources in sports were identified as traveling, energy consumption, and waste generation. Turning to renewable energy sources, waste management and sustainable transport alternatives were identified as effective solutions for reducing the carbon footprint. Analysis of the research results showed that the interest and participation in the Final Four and other international organizations are increasing. Due to increasing carbon footprint, these events and competitions should be planned and conducted in accordance with the goals of environmental sustainability. For this purpose, managers and policy makers should turn to clean energy sources, including waste management and recycling strategies, the preparation of sustainable transportation projects, and integrating all these processes into organization activities.
Acute and Long COVID Intestinal Changes in an Experimental Model of Coronavirus in Mice
Authors: Hussain Hussain , Elumalai Nila , Sampath Natarajan , Shamaladevi Nagarajarao , Hajjar Rima , Druyan Brian Zachary , Rashed Amirah B. , Ramamoorthy Rajalakshmi , Kenyon Norma S. , Jayakumar Arumugam R. , Paidas Michael J.
Published: May 2024

The COVID-19 pandemic, which emerged in early 2020, has had a profound and lasting impact on global health, resulting in over 7.0 million deaths and persistent challenges. In addition to acute concerns, there is growing attention being given to the long COVID health consequences for survivors of COVID-19 with documented cases of cardiovascular abnormalities, liver disturbances, lung complications, kidney issues, and noticeable cognitive deficits. Recent studies have investigated the physiological changes in various organs following prolonged exposure to murine hepatitis virus-1 (MHV-1), a coronavirus, in mouse models. One significant finding relates to the effects on the gastrointestinal tract, an area previously understudied regarding the long-lasting effects of COVID-19. This research sheds light on important observations in the intestines during both the acute and the prolonged phases following MHV-1 infection, which parallel specific changes seen in humans after exposure to SARS-CoV-2. Our study investigates the histopathological alterations in the small intestine following MHV-1 infection in murine models, revealing significant changes reminiscent of inflammatory bowel disease (IBD), celiac disease. Notable findings include mucosal inflammation, lymphoid hyperplasia, goblet cell hyperplasia, and immune cell infiltration, mirroring pathological features observed in IBD. Additionally, MHV-1 infection induces villous atrophy, altered epithelial integrity, and inflammatory responses akin to celiac disease and IBD. SPIKENET (SPK) treatment effectively mitigates intestinal damage caused by MHV-1 infection, restoring tissue architecture and ameliorating inflammatory responses. Furthermore, investigation into long COVID reveals intricate inflammatory profiles, highlighting the potential of SPK to modulate intestinal responses and restore tissue homeostasis. Understanding these histopathological alterations provides valuable insights into the pathogenesis of COVID-induced gastrointestinal complications and informs the development of targeted therapeutic strategies.
Detection and Genetic Characterization of Bovine Torovirus in Uruguay
Authors: Castells Matías , Benítez-Galeano María José , Marandino Ana , Caffarena Rubén Darío , Casaux María Laura , Pérez Ruben , Giannitti Federico , Colina Rodney
Published: May 2024

Bovine torovirus (BToV) is an enteric pathogen that may cause diarrhea in calves and adult cattle, which could result in economic losses due to weight loss and decreased milk production. This study aimed to report the presence, the genetic characterization and the evolution of BToV in calves in Uruguay. BToV was detected in 7.9% (22/278) of fecal samples, being identified in dairy (9.2%, 22/239) but not beef (0.0%, 0/39) calves. BToV was detected in both diarrheic (14%, 6/43) and non-diarrheic (13.2%, 5/38) dairy calves. In addition, BToV was detected in the intestinal contents of 14.9% (7/47) of naturally deceased dairy calves. A complete genome (28,446 nucleotides) was obtained, which was the second outside Asia and the first in Latin America. In addition, partial S gene sequences were obtained to perform evolutionary analyses. Nucleotide and amino acid substitutions within and between outbreaks/farms were observed, alerting the continuous evolution of the virus. Through Bayesian analysis using BEAST, a recent origin (mid-60s) of BToV, possibly in Asia, was estimated, with two introductions into Uruguay from Asia and Europe in 2004 and 2013, respectively. The estimated evolutionary rate was 1.80 × 10−3 substitutions/site/year. Our findings emphasize the importance of continued surveillance and genetic characterization for the effective management and understanding of BToV’s global epidemiology and evolution.
Mechanisms of Flavivirus Cross-Protection against Yellow Fever in a Mouse Model
Authors: Shinde Divya P. , Walker Jordyn , Reyna Rachel A. , Scharton Dionna , Mitchell Brooke , Dulaney Ennid , Bonam Srinivisa Reddy , Hu Haitao , Plante Jessica A. , Plante Kenneth S. , Weaver Scott C.
Published: May 2024

The complete lack of yellow fever virus (YFV) in Asia, and the lack of urban YFV transmission in South America, despite the abundance of the peridomestic mosquito vector Aedes (Stegomyia.) aegypti is an enigma. An immunologically naïve population of over 2 billion resides in Asia, with most regions infested with the urban YF vector. One hypothesis for the lack of Asian YF, and absence of urban YF in the Americas for over 80 years, is that prior immunity to related flaviviruses like dengue (DENV) or Zika virus (ZIKV) modulates YFV infection and transmission dynamics. Here we utilized an interferon α/β receptor knock-out mouse model to determine the role of pre-existing dengue-2 (DENV-2) and Zika virus (ZIKV) immunity in YF virus infection, and to determine mechanisms of cross-protection. We utilized African and Brazilian YF strains and found that DENV-2 and ZIKV immunity significantly suppresses YFV viremia in mice, but may or may not protect relative to disease outcomes. Cross-protection appears to be mediated mainly by humoral immune responses. These studies underscore the importance of re-assessing the risks associated with YF outbreak while accounting for prior immunity from flaviviruses that are endemic.
Mathematical Modeling Suggests That Monocyte Activity May Drive Sex Disparities during Influenza Infection
Authors: Liparulo Tatum S. , Shoemaker Jason E.
Published: May 2024

In humans, females of reproductive age often experience a more severe disease during influenza A virus infection, which may be due to differences in their innate immune response. Sex-specific outcomes to influenza infection have been recapitulated in mice, enabling researchers to study viral and immune dynamics in vivo in order to identify immune mechanisms that are differently regulated between the sexes. This study is based on the hypothesis that sex-specific outcomes emerge due to differences in the rates/speeds that select immune components respond. Using publicly available sex-specific murine data, we utilized dynamic mathematical models of the innate immune response to identify candidate mechanisms that may lead to increased disease severity in female mice. We implemented a large computational screen using the Bayesian information criterion (BIC), wherein the goodness of fit of the competing model scenarios is balanced against complexity (i.e., the number of parameters). Our results suggest that having sex-specific rates for proinflammatory monocyte induction by interferon and monocyte inhibition of virus replication provides the simplest (lowest BIC) explanation for the difference observed in the male and female immune responses. Markov-chain Monte Carlo (MCMC) analysis and global sensitivity analysis of the top performing scenario were performed to provide rigorous estimates of the sex-specific parameter distributions and to provide insight into which parameters most affect innate immune responses. Simulations using the top-performing model suggest that monocyte activity could be a key target to reduce influenza disease severity in females. Overall, our Bayesian statistical and dynamic modeling approach suggests that monocyte activity and induction parameters are sex-specific and may explain sex-differences in influenza disease immune dynamics.
SPIKENET: An Evidence-Based Therapy for Long COVID
Authors: Elumalai Nila , Hussain Hussain , Sampath Natarajan , Shamaladevi Nagarajarao , Hajjar Rima , Druyan Brian Zachary , Rashed Amirah B. , Ramamoorthy Rajalakshmi , Kenyon Norma S. , Jayakumar Arumugam R. , Paidas Michael J.
Published: May 2024

The COVID-19 pandemic has been one of the most impactful events in our lifetime, caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Multiple SARS-CoV-2 variants were reported globally, and a wide range of symptoms existed. Individuals who contract COVID-19 continue to suffer for a long time, known as long COVID or post-acute sequelae of COVID-19 (PASC). While COVID-19 vaccines were widely deployed, both unvaccinated and vaccinated individuals experienced long-term complications. To date, there are no treatments to eradicate long COVID. We recently conceived a new approach to treat COVID in which a 15-amino-acid synthetic peptide (SPIKENET, SPK) is targeted to the ACE2 receptor binding domain of SARS-CoV-2, which prevents the virus from attaching to the host. We also found that SPK precludes the binding of spike glycoproteins with the receptor carcinoembryonic antigen-related cell adhesion molecule 1 (CEACAM1) of a coronavirus, murine hepatitis virus-1 (MHV-1), and with all SARS-CoV-2 variants. Further, SPK reversed the development of severe inflammation, oxidative stress, tissue edema, and animal death post-MHV-1 infection in mice. SPK also protects against multiple organ damage in acute and long-term post-MHV-1 infection. Our findings collectively suggest a potential therapeutic benefit of SPK for treating COVID-19.
First Molecular Detection and Epidemiological Analysis of Equine Influenza Virus in Two Regions of Colombia, 2020–2023
Authors: Gonzalez-Obando Juliana , Zuluaga-Cabrera Angélica , Moreno Isabel , Úsuga Jaime , Ciuderis Karl , Forero Jorge E. , Diaz Andrés , Rojas-Arbeláez Carlos , Hernández-Ortiz Juan P. , Ruiz-Saenz Julian
Published: May 2024

Equine influenza is a viral disease caused by the equine influenza virus (EIV), and according to the WOAH, it is mandatory to report these infections. In Latin America and Colombia, EIV risk factors have not been analyzed. The objective of this research is to perform an epidemiological and molecular analysis of the EIV in horses with respiratory symptoms from 2020 to 2023 in Colombia. Molecular EIV detection was performed using RT–qPCR and nanopore sequencing. A risk analysis was also performed via the GEE method. A total of 188 equines with EIV respiratory symptoms were recruited. The positivity rate was 33.5%. The descriptive analysis showed that only 12.8% of the horses were vaccinated, and measures such as the quarantine and isolation of symptomatic animals accounted for 91.5% and 88.8%, respectively. The variables associated with the EIV were the non-isolation of positive individuals (OR = 8.16, 95% CI (1.52–43.67), p = 0.014) and sharing space with poultry (OR = 2.16, 95% CI (1.09–4.26), p = 0.027). In conclusion, this is the first EIV investigation in symptomatic horses in Colombia, highlighting the presence of the virus in the country and the need to improve preventive and control measures.
Using Surface Immunogenic Protein as a Carrier Protein to Elicit Protective Antibody to Multiple Serotypes for Candidate Group B Streptococcal Glycan Conjugate Vaccines
Authors: Duan Huiqi , Huang Wenhua , Lv Qingyu , Liu Peng , Li Qian , Kong Decong , Sun Xuyang , Zhang Xinran , Jiang Yongqiang , Chen Shaolong
Published: May 2024

Group B Streptococcus (GBS) is a life-threatening opportunistic pathogen, particularly in pregnant women, infants, and the elderly. Currently, maternal vaccination is considered the most viable long-term option for preventing GBS mother-to-infant infection, and two polysaccharide conjugate vaccines utilizing CRM197 as a carrier protein have undergone clinical phase II trials. Surface immunogenic protein (Sip), present in all identified serotypes of GBS strains so far, is a protective surface protein of GBS. In this study, the type Ia capsular polysaccharide (CPS) of GBS was utilized as a model to develop candidate antigens for a polysaccharide conjugate vaccine by coupling it with the Sip of GBS and the traditional carrier protein CRM197. Serum analysis from immunized New Zealand rabbits and CD1 mice revealed that there was no significant difference in antibody titers between the Ia-Sip group and Ia-CRM197 group; however, both were significantly higher than those observed in the Ia polysaccharide group. Opsonophagocytosis and passive immune protection results using rabbit serum indicated no significant difference between the Ia-Sip and Ia-CRM197 groups, both outperforming the Ia polysaccharide group. Furthermore, serum from the Ia-Sip group had a cross-protective effect on multiple types of GBS strains. The challenge test results in CD1 mice demonstrated that the Ia-Sip group provided complete protection against lethal doses of bacteria and also showed cross-protection against type III strain. Our study demonstrates for the first time that Ia-Sip is immunogenic and provides serotype-independent protection in glycan conjugate vaccines, which also indicates Sip may serve as an excellent carrier protein for GBS glycan conjugate vaccines and provide cross-protection against multiple GBS strains.
Cost-Effectiveness of Adjuvanted Quadrivalent Influenza Vaccine for Adults over 65 in France
Authors: Paccalin Marc , Gavazzi Gaëtan , Berkovitch Quentin , Leleu Henri , Moreau Romain , Ciglia Emanuele , Burlet Nansa , Mould-Quevedo Joaquin F.
Published: May 2024

Background: In France, influenza accounts for an average of over one million consultations with GPs, 20,000 hospitalizations, and 9000 deaths per year, particularly among the over-65s. This study evaluates the cost-effectiveness of the adjuvanted quadrivalent influenza vaccine (aQIV) compared to standard (SD-QIV) and high-dose (HD-QIV) quadrivalent influenza vaccines for individuals aged 65 and older in France. Methods: The age-structured SEIR transmission model, calibrated to simulate a mean influenza season, incorporates a contact matrix to estimate intergroup contact rates. Epidemiological, economic, and utility outcomes are evaluated. Vaccine effectiveness and costs are derived from literature and national insurance data. Quality of life adjustments for influenza attack rates and hospitalizations are applied. Deterministic and probabilistic analyses are also conducted. Results: Compared to SD-QIV, aQIV demonstrates substantial reductions in healthcare utilization and mortality, avoiding 89,485 GP consultations, 2144 hospitalizations, and preventing 1611 deaths. Despite an investment of EUR 110 million, aQIV yields a net saving of EUR 14 million in healthcare spending. Compared to HD-QIV, aQIV saves 62 million euros on vaccination costs. Cost-effectiveness analysis reveals an incremental cost-effectiveness ratio of EUR 7062 per QALY. Conclusions: This study highlights the cost-effectiveness of aQIV versus SD-QIV and HD-QIV, preventing influenza cases, hospitalizations, and deaths.
Evaluation of Algal Control Measures in Eutrophic Reservoirs Based on Aquatic Ecosystem Models
Authors: Zheng Zhen , Liao Tingting , Lin Yafeng , Zhu Xueyi , Meng Haobin
Published: May 2024

The frequency of freshwater cyanobacterial blooms is increasing globally due to climate change and eutrophication, particularly in reservoirs. Reservoir ecosystems exhibit unique characteristics, and there is a complex relationship between factors such as light, temperature, nutrient salts, hydrology, and algal growth. The impact of the other factors on algal growth varies significantly among different reservoirs. Thus, it is crucial to assess the effectiveness of various algal control measures implemented in different reservoirs. This study conducted a comprehensive assessment by establishing a eutrophication model for the Shanzi Reservoir in Fuzhou City. The model incorporated meteorology, hydrology, carbon dynamics, nutrient cycling, and biological communities. The effectiveness of diverse management measures was systematically evaluated. The findings demonstrate that increasing the water level, reducing nutrient salts in sediments, and implementing ecological fish stocking effectively suppressed algal growth to varying degrees and improved nitrogen and phosphorus levels. Lower water levels and ecological fish stocking had a significant impact on algal reproduction, while sediment reduction had a minimal effect. Conversely, lower water levels and ecological fish stocking did not significantly improve nitrogen and phosphorus concentrations in the reservoir, whereas sediment reduction had a noticeable effect. Consequently, the management strategies for the Shanzi Reservoir should prioritize external control measures and the implementation of ecological fish stocking.
CuFeS2/MXene-Modified Polyvinylidene Fluoride Membrane for Antibiotics Removal through Peroxymonosulfate Activation
Authors: Zhang Dongyang , Li Kunfu , Fang Lei , Chen Huishan
Published: May 2024

In this research, the CuFeS2/MXene-modified polyvinylidene fluoride (PVDF) membrane was prepared to activate peroxymonosulfate (PMS) to remove moxifloxacin (MOX) and its morphology; surface functional groups and hydrophilicity were also studied. The parameters of the catalytic membrane/PMS system were optimized, with an optimal loading of 4 mg/cm2 and a PMS dosage of 0.20 mM. High filtration pressure, alkaline conditions, and impurities in water could inhibit MOX removal. After continuous filtration, the removal efficiency of MOX using the catalytic membrane/PMS system and PVDF membrane was 68.2% and 9.9%, respectively. Batch filtration could remove 87.8% MOX by the extra 10 min contact time between the catalytic membrane and solution. During the filtration process, CuFeS2/MXene on the surface of the catalytic membrane activated PMS to produce SO4•−, HO•, and 1O2, and MOX was removed through adsorption and degradation. Taking humic acid (HA) as the model foulant, reversible fouling resistance in the catalytic membrane/PMS system was 22.8% of the PVDF membrane. The catalytic membrane/PMS system weakened the formation of the cake layer by oxidizing HA into smaller pollutants and followed the intermediate blocking cake filtration model. The novelty of this research was to develop a CuFeS2/MXene–PVDF membrane-activated PMS system and explore its application in antibiotics removal.