Search Results (279)

The degradation of ecosystem services (ES) poses a significant obstacle to regional sustainable development. Land-use change is widely recognized as a pivotal factor driving the spatio-temporal dynamics of ES supply and demand. However, the future impact of land-use changes on supply–demand risks remains largely unknown. To fill this knowledge gap, we conducted a study in the Gansu section of the Yellow River Basin. By integrating Cellular Automata (CA) and an enhanced Markov model within the GeoSOS-FLUS framework, we dynamically simulated land-use changes under three scenarios—the Normal Development Scenario (NDS), Ecological Protection Scenario (EPS), and Rapid Socio-economic Development Scenario (RDS)—spanning from 2020 to 2050. Furthermore, we employed the InVEST model to analyze the spatio-temporal pattern of supply, demand, supply-to-demand ratios, and supply–demand risks for water provision, carbon storage, and soil conservation under all scenarios. Firstly, all scenarios project an increase in built-up land, primarily from unused land, shrubland, grassland, and cropland. Forest land and water bodies remain stable. Secondly, water provision increases, but demand grows faster, leading to supply–demand imbalances, with high-risk areas in the north, central, and east. Soil conservation shows balanced supply and demand with high-risk areas in the north. Carbon storage remains stable, with high-risk areas in the central and east regions. Thirdly, high-risk areas for water provision increase under all scenarios, particularly under the Rapid Socio-economic Development scenario. Full article

Terrestrial ecosystems are vital carbon sinks that can effectively restrain the rise in CO₂ in the atmosphere. How ecosystem carbon storage (CS) in semi-arid watershed areas with slow urbanization is affected by comprehensive factors of the environment and land use, along with its temporal and spatial changes has still not been fully explored. Notably, there is a paucity of research on the temporal and spatial changes and development trends of CS in the rapid deformation belt of slopes from the eastern margin of the Qinghai–Tibet Plateau to the Loess Plateau. Taking Bailong River Basin (BRB) as an example, this study combined GeoSOS-FLUS, the InVEST model, and localized “social–economic–nature” scenario to simulate the long-term dynamic evolution of CS. The aim was to study how topographic factors and land use change, and their interactions impact carbon sinks and gradient effects in steep-slope areas, and then find out the relationship between carbon sinks and topographic factors to explore strategies to improve regional carbon sink capacity. The results showed that the following: (1) CS in BRB increased year by year, with a total increase of 558 tons (3.19%), and showed significant spatial heterogeneity, mainly due to the conversion of woodland and arable land; (2) except for land use type, the relationship between CS and topographic gradient is inverted U-shaped, showing a complex spatial response; and (3) it is estimated that by 2050, under the arable land protection and natural development scenarios, CS will decrease by 0.07% and 0.005%, respectively, encroachment on undeveloped mountain areas, while the ecological protection scenario gives priority to protecting the carbon sinks of woodland and grassland, and CS will increase by 0.37%. This study supports the implementation of targeted ecological protection measures through topographic gradient zoning, provides a reference for policy makers in similar topographic regions to effectively manage the spatial heterogeneity of CS, and helps further strengthen global and regional climate change mitigation efforts. Full article

In past decades, urbanization has entered a phase of rapid development, resulting in an intensified utilization of land resources. The finite nature of these resources has led to increased pressure on land availability, giving rise to a phenomenon known as land use conflict. This conflict is particularly evident in the frequent conversion of land categories, with urban impervious surfaces increasingly encroaching upon forests, grasslands, and agricultural land. Such encroachments trigger a series of land use conflict issues, which subsequently impact the function and structure of regional ecosystems. This paper analyzes the spatial and temporal changes in land use and land cover (LULC) within the urban agglomeration on the northern slope of Tianshan Mountain. It measures and evaluates the spatial and temporal evolution of land use conflicts in the study area from 1990 to 2020, utilizing conflict-related theories and the landscape risk evaluation model. Additionally, the paper explores the spatial and temporal dimensions of land use conflicts under three scenarios—natural development (ND), cultivation priority (CP), and ecological priority (EP)—for the years 2030 and 2050, informed by the Future Land Use Simulation (FLUS) model. The results indicate that unused land constitutes the predominant land use type, accounting for over 50% of the total area. The areas of cultivated land, water bodies, and urban land are experiencing an increasing trend, while the areas of forestland, grassland, and unused land are witnessing a decreasing trend. The level of land use spatial conflicts during the study period showed a decreasing and then increasing trend, with an overall upward trend and an increase in the average value of 0.03. In terms of the proportion of spatial units, mild and general conflicts exhibited a decreasing trend, with reductions of 4.21% and 2.95%, respectively. Conversely, the proportion of medium conflicts increased significantly, rising by 7.33%, while severe conflicts experienced a slight increase of 0.23%. Under the ND, CP, and EP scenarios, the spatial and temporal dynamics of future land use conflicts varied. However, the study area was predominantly characterized by general conflicts in both 2030 and 2050. In 2030, the proportions of spatial units experiencing general conflicts in the three scenarios are projected to be 61.20%, 60.39%, and 57.51%, respectively. In comparison, these proportions are projected to be 59.24%, 62.70%, and 56.29% in 2050, respectively. The anticipated future changes in land use spatial conflicts vary across different scenarios. Notably, the ND scenario indicates a rising conflict level in the study area over the next 30 years, with an overall increase of 0.03 in the mean value. In contrast, the changes in the index under the CP and EP scenarios are relatively stable. Full article

The elicitation of broadly neutralizing antibodies (bnAbs) is a major goal of vaccine design for highly mutable pathogens, such as influenza, HIV, and coronavirus. Although many rational vaccine design strategies for eliciting bnAbs have been devised, their efficacies need to be evaluated in preclinical animal models and in clinical trials. To improve outcomes for such vaccines, it would be useful to develop methods that can predict vaccine efficacies against arbitrary pathogen variants. As a step in this direction, here, we describe a simple biologically motivated model of antibody reactivity elicited by nanoparticle-based vaccines using only antigen amino acid sequences, parametrized with a small sample of experimental antibody binding data from influenza or SARS-CoV-2 nanoparticle vaccinations. Results: The model is able to recapitulate the experimental data to within experimental uncertainty, is relatively insensitive to the choice of the parametrization/training set, and provides qualitative predictions about the antigenic epitopes exploited by the vaccine, which are testable by experiment. For the mosaic nanoparticle vaccines considered here, model results suggest indirectly that the sera obtained from vaccinated mice contain bnAbs, rather than simply different strain-specific Abs. Although the present model was motivated by nanoparticle vaccines, we also apply it to a mutlivalent mRNA flu vaccination study, and demonstrate good recapitulation of experimental results. This suggests that the model formalism is, in principle, sufficiently flexible to accommodate different vaccination strategies. Finally, we show how the model could be used to rank the efficacies of vaccines with different antigen compositions. Conclusions: Overall, this study suggests that simple models of vaccine efficacy parametrized with modest amounts of experimental data could be used to compare the effectiveness of designed vaccines. Full article

Simulating and predicting carbon storage under different development scenarios is crucial for formulating effective carbon management strategies and achieving carbon neutrality goals. However, studies that focus on specific regions and incorporate local policy context require further investigation. Taking Fujian Province as a case study, this research developed four policy-driven scenarios—natural development, farmland protection, urban development, and ecological protection—based on local policy frameworks. Using the PLUS (Patch-generating Land Use Simulation) and InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) models, the study simulated and predicted the carbon storage dynamics under each scenario. The results show that carbon storage declined from 1995 to 2020, mainly due to the conversion of forests and agricultural land into construction areas. The ecological protection scenario demonstrated the highest potential for carbon storage recovery, projecting an increase to 2.02 billion tons by 2030, driven by afforestation and conservation initiatives. Conversely, the urban development scenario posed the greatest risks, leading to substantial losses. Key conservation areas, including 12 priority districts, were identified in the western and northwestern regions, while coastal urban areas, comprising 31 vulnerable districts, face significant carbon storage losses. These findings emphasize the need for balanced land use policies that prioritize both urban development and ecological protection to achieve sustainable carbon management. Full article

The intensification of climate change and the implementation of territorial spatial planning policies have jointly increased the complexity of future carbon storage changes. However, the impact of territorial spatial planning on carbon storage under future climate change remains unclear. Therefore, this study aims to reveal the potential impacts of future climate change and territorial spatial planning on carbon storage and sequestration, providing decision support for addressing climate change and optimizing territorial spatial planning. We employed the FLUS model, the InVEST model, and the variance partitioning analysis (VPA) method to simulate carbon storage under 15 different scenarios that combine climate change scenarios and territorial spatial planning for Xiamen in 2035, and to quantify the individual and combined impacts of territorial spatial planning and climate change on ecosystem carbon sequestration. The results showed that (1) by 2035, Xiamen’s carbon storage capacity is expected to range from 32.66 × 10⁶ Mg to 33.00 × 10⁶ Mg under various scenarios, reflecting a decrease from 2020 levels; (2) the implementation of territorial spatial planning is conducive to preserving Xiamen’s carbon storage, with the urban development boundary proving to be the most effective; (3) carbon storage is greatly affected by climate change, with RCP 4.5 more effective than RCP 8.5 in maintaining higher levels of carbon storage; and (4) the influence of territorial spatial planning on carbon sequestration consistently exceeds that of climate change, particularly under high-emission scenarios, where the regulatory effect of planning is especially significant. Full article

Background: Italy, particularly the northern region of Lombardy, has experienced very high rates of COVID-19 cases and deaths. Several indicators, i.e., the number of new positive cases, deaths and hospitalizations, have been used to monitor virus spread, but all suffer from biases. The aim of this study was to evaluate an alternative data source from Emergency Medical Service (EMS) activities for COVID-19 monitoring. Methods: Calls to the emergency number (112) in Lombardy (years 2015–2022) were studied and their overlap with the COVID-19 pandemic, influenza and official mortality peaks were evaluated. Modeling it as a counting process, a specific cause contribution (i.e., COVID-19 symptoms, the “signal”) was identified and enucleated from all other contributions (the “background”), and the latter was subtracted from the total observed number of calls using statistical methods for excess event estimation. Results: A total of 6,094,502 records were analyzed and filtered for respiratory and cardiological symptoms to identify potential COVID-19 patients, yielding 742,852 relevant records. Results show that EMS data mirrored the time series of cases or deaths in Lombardy, with good agreement also being found with seasonal flu outbreaks. Conclusions: This novel approach, combined with a machine learning predictive approach, could be a powerful public health tool to signal the start of disease outbreaks and monitor the spread of infectious diseases. Full article

Urbanization has led to a reduction in green space, weakening the region’s carbon sink capacity and stability and bringing a series of ecological problems, making the restoration and improvement of the ecological environment crucial. This study used Nanjing, China, as a case to construct an ecological network by applying Morphological Spatial Pattern Analysis (MSPA) and the Linkage Mapper (LM) tool based on circuit theory. The connectivity of ecological patches was evaluated by calculating the delta potential connectivity index (dPC). The CASA model (Carnegie–Ames–Stanford approach) was applied to quantify carbon sequestration in Nanjing. We propose an innovative carbon sink index (CSI) that integrates three indicators: capacity, efficiency, and variability. This index assesses the carbon sink function of ecological patches from both static and dynamic perspectives. Using the Future Land Use Simulation (FLUS) model, we simulated carbon sequestration changes in 2035, providing insights for risk assessment and future optimization strategies. The results reveal a significant positive correlation between node connectivity and both carbon sink capacity and efficiency, indicating that enhancing connectivity at key nodes can effectively improve its carbon sequestration. On this basis, by coupling dPC and CSI indices to classify ecological network nodes, we proposed four strategies for optimization: ecological conservation, structural connectivity, carbon sink improvement, and synergistic enhancement. Finally, by adding 26 ecological stepping stones, 32 ecological corridors, and optimizing landscape components, we achieved dual improvements in both the structural and functional aspects of the ecological network. After optimization, the network connectivity increased by 1.6% and the carbon sink increased by 3.82%, demonstrating a significant improvement. This study emphasizes that by protecting, enhancing, and restoring ecological spaces, the carbon sequestration function and stability of urban ecological networks can be effectively improved. These findings provide valuable insights for the scientific management of ecological spaces in urbanized areas. Full article

Flaviviruses, a group of single-stranded RNA viruses spread by mosquitoes or ticks, include several significant neurotropic viruses, such as West Nile virus (WNV), Japanese encephalitis virus (JEV), tick-borne encephalitis virus (TBEV), and Zika virus (ZIKV). These viruses can cause a range of neurological diseases during acute infection, from mild, flu-like symptoms to severe and fatal encephalitis. A total of 20–50% of patients who recovered from acute flavivirus infections experienced long-term cognitive issues. Here, we discuss these major neurotropic flaviviruses-induced clinical diseases in humans and the recent findings in animal models and provide insights into the underlying disease mechanisms. Full article

Background: Recent findings have highlighted that abnormal energy metabolism is a key feature of autosomal-dominant polycystic kidney disease (ADPKD). Emerging evidence suggests that nutritional ketosis could offer therapeutic benefits, including potentially slowing or even reversing disease progression. This systematic review aims to synthesise the literature on ketogenic interventions to evaluate the impact in ADPKD. Methods: A systematic search was conducted in Medline, Embase, and Scopus using relevant Medical Subject Headings (MeSH) and keywords. Studies assessing ketogenic interventions in the management of ADPKD in both human and animal models were selected for data extraction and analysis. Results: Three animal reports and six human studies were identified. Ketogenic diets (KD) significantly slowed polycystic kidney disease (PKD) progression in rats with improved renal function and reduced cystic areas. There was reduced renal fibrosis and cell proliferation. The supplementation of beta-hydroxybutyrate (BHB) in rats also reduced PKD progression in a dose-dependent manner. Human studies (n = 129) on KD in ADPKD reported consistent body mass index (BMI) reduction across trials, with an average weight loss of ∼4 kg. Improvements in blood pressure were also noted. Ketosis was achieved in varying degrees. Effects on kidney function (eGFR) were beneficial. Results for kidney volume were mixed but most studies were underpowered for this outcome. Lipid profiles showed increases in total cholesterol (∼1 mmol/L) and LDL cholesterol (∼0.4 mmol/L) in most studies. Safety concerns such as “keto flu” symptoms, elevated uric acid levels, and occasional kidney stones were noted. Overall feasibility and adherence to the KD were rated positively by most participants. Conclusions: Human studies are promising; however, they have been limited by small sample sizes and short durations. Larger, long-term trials are needed to assess the efficacy, adherence, and safety of ketogenic diets in people with ADPKD. Full article

Rapid urbanization in China has profoundly transformed its urban systems, bringing about considerable ecological challenges and significant imbalances between urban growth and ecological health. The Pearl River Delta (PRD) urban agglomeration, as one of China’s most economically dynamic regions, exemplifies the complex interactions between rapid urbanization and environmental sustainability. This study examined these dynamics using statistical yearbook and geographic information data from 1999 to 2018. Through a multi-scale approach integrating panel entropy, coupled coordination analysis, and FLUS models, we evaluated the relationship between urbanization and ecology at both the agglomeration and city levels. The findings revealed that while the overall coordination between urbanization and ecology in the PRD has improved, it remains at a moderate level with pronounced core-periphery disparities. Core cities face increasing ecological pressures and inefficient land use patterns. Simulation results, under three distinct policy scenarios—“unconstrained”, “growth machine”, and “compact and intensive usage/urban renewal”—and validated through field research, indicate that urban renewal presents a viable strategy for optimizing land use and mitigating ecological pressures. The study provides both a comprehensive diagnostic framework for assessing urban health and sustainability and practical intervention pathways, particularly for regions experiencing similar rapid urbanization challenges. The insights gained are especially relevant to other developing countries, offering strategies to enhance urban resilience and ecological sustainability while addressing persistent regional inequalities. Full article

Background/Objectives: Intranasal vaccination enhances protection against respiratory viruses by providing stimuli to the immune system at the primary site of infection, promoting a balanced and effective response. Influenza vectors with truncated NS1 are a promising vaccine approach that ensures a pronounced local CD8+ T-cellular immune response. Here, we describe the protective and immunomodulating properties of an influenza vector FluVec-N carrying the C-terminal fragment of the SARS-CoV-2 nucleoprotein within a truncated NS1 open reading frame. Methods: We generated several FluVec-N recombinant vectors by reverse genetics and confirmed the vector’s genetic stability, antigen expression in vitro, attenuation, and immunogenicity in a mouse model. We tested the protective potential of FluVec-N intranasal immunization in naïve mice and seropositive Th2-prone mice, primed with aluminium-adjuvanted inactivated SARS-CoV-2. Immune response in immunized and challenged mice was analyzed through serological methods and flow cytometry. Results: Double intranasal immunization of naïve mice with FluVec-N reduced weight loss and viral load in the lungs following infection with the SARS-CoV-2 beta variant. Mice primed with alum-adjuvanted inactivated coronavirus experienced substantial early weight loss and eosinophilia in the lungs during infection, demonstrating signs of enhanced disease. A single intranasal boost immunization with FluVec-N prevented the disease enhancement in primed mice by modulating the local immune response. Protection was associated with the formation of specific IgA and the early activation of virus-specific effector and resident CD8+ lymphocytes in mouse lungs. Conclusions: Our study supports the potential of immunization with influenza vector vaccines to prevent respiratory diseases and associated immunopathology. Full article

As a vital conservation area for water sources in the Yellow River Basin, understanding the spatial-temporal dynamics of vegetation coverage is crucial, along with the factors that affect it, to ensure ecological preservation and sustainable development of the Yellow River Source Region (YRSR). In this paper, we utilized Landsat surface reflectance data from 2000 to 2020 using de-clouding and masking methods implementing the Google Earth Engine (GEE) cloud platform. We investigated spatial-temporal changes in vegetation coverage by combining the maximum value composite (MVC), the dimidiate pixel model (DPM), the Theil–Sen median slope, and the Mann–Kendall test. The influencing factors on vegetation coverage were quantitatively analyzed using a geographic detector, and future tendencies in vegetation coverage were predicted utilizing the Future Land Use Simulation (FLUS) model. The outcomes suggested the following: (1) On the temporal scale, vegetation coverage exhibited a general upward trend between 2000 and 2020, with the YRSR showing a yearly growth rate of 0.23% (p < 0.001). In comparison to 2000, the area designated as having extremely high vegetation coverage increased by 19.3% in 2020. (2) Spatially, the central and southeast regions have higher values of vegetation coverage, whereas the northwest has lower values. In the study area, 75.5% of the region demonstrated a significant improvement trend, primarily in Xinghai County, Zeku County, and Dari County in the south and the northern portion of the YRSR; conversely, a notable tendency of degradation was identified in 11.8% of the area, mostly in the southeastern areas of Qumalai County, Chenduo County, Shiqu County, and scattered areas in the southeastern region. (3) With an explanatory power of exceeding 45%, the three influencing factors that had the biggest effects on vegetation coverage were mean annual temperature, elevation, and mean annual precipitation. Mean annual precipitation has been shown to have a major impact on vegetation covering; the interconnections involving these factors have increased the explanatory power of vegetation coverage’s regional distribution. (4) Predictions for 2030 show that the vegetation coverage is trending upward in the YRSR, with a notable recovery trend in the northwestern region. This study supplies a theoretical foundation to formulate strategies to promote sustainable development and ecological environmental preservation in the YRSR. Full article

The Yellow River Basin serves as a critical ecological barrier in China. However, it has increasingly faced severe ecological and environmental challenges, with soil erosion and overgrazing being particularly prominent issues. As an important region in the middle and lower reaches of the Yellow River, the Jinan section of the Yellow River Basin is similarly affected by these problems, posing significant threats to the stability and sustainability of its ecosystems. To scientifically identify areas severely impacted by soil erosion and systematically quantify the effects of climate change on vegetation coverage within the Yellow River Basin, this study focuses on the Jinan section. By analyzing the spatio-temporal evolution patterns of the Normalized Difference Vegetation Index (NDVI), this research aims to explore the driving mechanisms behind these changes and further predict the future spatial distribution of NDVI, providing theoretical support and practical guidance for regional ecological conservation and sustainable development. This study employed the slope trend analysis method to examine the spatio-temporal variation characteristics of NDVI in the Jinan section of the Yellow River Basin from 2008 to 2022 and utilized the FLUS model to predict the spatial distribution of NDVI in 2025. The Optimal Parameters-based Geographical Detector (OPGD) model was applied to systematically analyze the impacts of four key driving factors—precipitation (PRE), temperature (TEM), population density (POP), and gross domestic product (GDP) on vegetation coverage. Finally, correlation and lag effect analyses were conducted to investigate the relationships between NDVI and TEM as well as NDVI and PRE. The research results indicate the following: (1) from 2008 to 2022, the NDVI values during the growing season in the Jinan section of the Yellow River Basin exhibited a significant increasing trend. This growth suggests a continuous improvement in regional vegetation coverage, likely influenced by the combined effects of natural and anthropogenic factors. (2) The FLUS model predicts that, by 2025, the proportion of high-density NDVI areas will rise to 55.35%, reflecting the potential for further optimization of vegetation coverage under appropriate management. (3) POP had a particularly significant impact on vegetation coverage, and its interaction with TEM, PRE, and GDP generated an amplified combined effect, indicating the dominant role of the synergy between socioeconomic and climatic factors in regional vegetation dynamics. (4) NDVI exhibited a significant positive correlation with both temperature and precipitation, further demonstrating that climatic conditions were key drivers of vegetation coverage changes. (5) In urban areas, NDVI showed a certain time lag in response to changes in precipitation and temperature, whereas this lag effect was not significant in suburban and mountainous areas, highlighting the regulatory role of human activities and land use patterns on vegetation dynamics in different regions. These findings not only reveal the driving mechanisms and influencing factors behind vegetation coverage changes but also provide critical data support for ecological protection and economic development planning in the Yellow River Basin, contributing to the coordinated advancement of ecological environment construction and economic growth. Full article

China’s rural population flowing into highly urbanized areas has led to the spatial reconstruction of urban–rural land use. Exploring the laws and trends of urban–rural land use in highly urbanized areas is of great significance in promoting rural transformation. This paper takes the southern Jiangsu region as a research area and uses a system dynamics (SD) model to simulate the demand for different land types based on economic, social, policy, and environmental (ESPE) factors. Future land use simulation (FLUS) is used to simulate the spatial evolution trend of urban–rural land use based on point–axis elements. The results show that the agricultural production space is severely squeezed by the urban living space. Under the scenario of rapid expansion, the decrease in arable land quantity and the demand area for rural residential areas are the largest. Under the scenario of high-quality development, the decrease in arable land area and the demand for land in rural residential areas are lowest. Based on the spatial simulation, it is reported that the areas with more intense land use spatial reconstruction in the three scenarios are mainly concentrated in the region’s urban–rural border areas. The future evolution of urban–rural land is summarized into three models: (1) single-center-driving expansion, (2) patchy expansion near the city center, and (3) multi-center-driving expansion. This paper proposes targeted policy recommendations to provide a scientific reference for solving the conflict between urban and rural land use. Full article