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IntroductionThe influenza virus is recognized as the primary cause of human respiratory diseases, with the current influenza vaccine primarily offering strain-specific immunity and limited protection against drifting strains. Considering this, the development of a broad-spectrum influenza vaccine capable of inducing effective immunity is considered the future direction in combating influenza.MethodsThe present study proposes a novel mRNA-based multi-epitope influenza vaccine, which combines three conserved antigens derived from the influenza A virus. The antigens consist of M2 ion channel’s extracellular domain (M2e), the conserved epitope of located in HA2 of hemagglutinin (H1, H3, B), and HA1 of hemagglutinin. At the same time, trimeric sequences and ferritin were conjugated separately to investigate the immune effects of antigen multivalent presentation.ResultsImmunization studies conducted on C57BL/6 mice with these vaccines revealed that they can elicit both humoral immunity and CD4+ and CD8+ T cell responses, which collectively contribute to enhancing cross-protective effects. The virus challenge results showed that vaccinated groups had significantly reduced lung damage, lower viral loads in the lungs, nasal turbinates, and trachea, as well as decreased levels of pro-inflammatory cytokines.ConclusionThese findings clearly demonstrate the wide range of protective effects provided by these vaccines against H1N1 and B influenza viruses. The present finding highlights the potential of mRNA-based influenza vaccines encoding conserved proteins as a promising strategy for eliciting broad-spectrum protective humoral and cellular immunity against H1N1 and B influenza viruses.

Hantaan virus (HTNV) is a major public health concern due to its ability to cause hemorrhagic fever with renal syndrome (HFRS) in Eurasia. Symptoms of HFRS include fever, hemorrhage, immune dysfunction and renal impairment, and severe cases can be fatal. T cell-mediated adaptive immune responses play a pivotal role in countering HTNV infection. However, our understanding of HTNV and T cell interactions in the disease progression is limited. In this study, we found that human CD4+ T cells can be directly infected with HTNV, thereby facilitating viral replication and production. Additionally, T-cell immunoglobulin and mucin 1 (TIM-1) participated in the process of HTNV infection of Jurkat T cells, and further observed that HTNV enters Jurkat T cells via the clathrin-dependent endocytosis pathway. These findings not only affirm the susceptibility of human CD4+ T lymphocytes to HTNV but also shed light on the viral tropism. Our research elucidates a mode of the interaction between the virus infection process and the immune system. Critically, this study provides new insights into the pathogenesis of HTNV and the implications for antiviral research.

MXene is a novel two-dimensional layered nanomaterial with a very large specific surface area and abundant surface functional groups, endowing it with unique physical and chemical properties. MXene can be compounded with other functional materials to significantly improve the performance of MXene composites or broaden their application scope. Meanwhile, with the development of flexible composite preparation technology, it has promoted the continuous expansion of its application fields. The introduction and combination of different materials can improve the performance of flexible composites and make them have a broader application prospect. In recent years, researchers have started preparing MXene materials as flexible composites for applications such as supercapacitors, sensors, electromagnetic shielding and thermal management. This paper gives a brief introduction to flexible composites and MXene materials, reviews the applications of MXene based flexible composites in various fields as well as the research progress, and provides an outlook on their future development direction.

It is becoming increasingly clear that maintaining the equilibrium of gut microbiota homeostasis during viral infections, such as Hantaan virus (HTNV), is of paramount importance. In order to gain insight into the role of NOD-like receptors in the immune system, we conducted a comparative study between C57BL/6 and Nlrx1-/- mouse models to analyze changes in the gut microbiota after HTNV infection. Our findings revealed an increase in the ratio of Firmicutes to Bacteroides in Nlrx1-/- mice, suggesting a potential link to inflammation. In addition, a comprehensive analysis of serum metabolomics revealed that differential metabolites were mainly concentrated in amino acid metabolism and lipid metabolism. Amino acid metabolism mainly involves arginine, lysine, and histidine metabolism, while lipid metabolism is mainly related to glycerophospholipid metabolism and fatty acid synthesis. Analysis of the correlation between microbiota and metabolites revealed an inverse relationship between Bacteroidetes and metabolites related to glutamine metabolism, while Firmicutes were directly associated with these metabolites. Furthermore, we observed a negative correlation between the presence of Actinobacteria, Proteobacteria, and Patescibacteria and the metabolites related to polyunsaturated fatty acids (PUFAs). Our results demonstrate that HTNV infection causes changes in the composition of gut microbiota in both Nlrx1-/- and wild-type (WT) mice. Moreover, the fecal microbiota and serum metabolites of Nlrx1-/- mice display notable differences at various developmental stages. Investigating this further may help to improve our understanding of the pathogenesis of HTNV and provide potential therapeutic options.

Mariculture can provide a large amount of food without occupying land resources, which provides important assistance for humans to achieve sustainable development. In this paper, China, where the output of mariculture exceeds half of the global output, is taken as the research area. Based on the spatial distribution data of three periods of mariculture along the coast of the Chinese Mainland in 2000, 2010, and 2020 obtained from remote sensing images and from the perspective of the mariculture center, the spatial development of mariculture in three periods in China is explored. Furthermore, by spatially overlaying mariculture data with concurrent water quality data, the relationship between the development and changes in the mariculture center and the seawater quality in different geographical environments was analyzed at the national scale.. We found that (1) Mariculture in China exhibits a noticeable geographical differentiation, with the scale and development speed of mariculture in northern regions surpassing that of the southern regions. (2) Good seawater quality is the prerequisite for the formation of mariculture centers, while water quality deterioration is detrimental to the development of mariculture. (3) The formation of large-scale high-density mariculture centers does not necessarily lead to deterioration of the seawater quality. Furthermore, we found that the water depth is an important factor leading to the spatial distribution pattern of mariculture in China, i.e., dense in the north and sparse in the south. The flow velocity is an important factor determining the water quality changes in mariculture centers.

Aquaculture, a crucial component of global food production, faces sustainability challenges due to increased competition for natural resources, environmental pollution, and subpar management practices. Understanding spatial–temporal changes in aquaculture distribution can offer insights into guiding its scientific and sustainable development. While Southeast Asia constitutes a key player in global aquaculture, there exists a significant gap in long-term remote sensing monitoring of aquaculture changes at a sub-continental scale. To fill this gap, this study introduces a workflow for aquaculture extraction that combines both automated and manual methods, based on water and edge frequency detection. By using time series of Landsat images and Sentinel-2 images on the GEE platform, we extracted spatial distribution data of aquaculture in Southeast Asia for five periods from 1990 to 2020. This data, boasting an accuracy exceeding 89.53% and peaking at 95.49%, laid the foundation for investigating the spatial distribution patterns, temporal-spatial changes, and area center changes of aquaculture across the study periods. The results showed that the period of aquaculture rapid expansion was concentrated in the first two decades, followed by a gradual decline in the expansion rate, and a consistent northwestward movement of the area center. The spatial distribution pattern of aquaculture in Southeast Asia gradually changed from “Indonesia and the other producers each account for 40% and 60%” to “Vietnam, Indonesia and the other producers each account for 40%, 30%, and 30%”.

Due to the global resurgence of hemorrhagic fever with renal syndrome (HFRS), more attention is being focused on this dangerous illness. In China and Korea, the only vaccines available are the virus-inactivated vaccine against Hantaan virus (HTNV) or Seoul virus (SEOV), but their efficacy and safety are inadequate. Therefore, it is important to develop new vaccines that are safer and more efficient to neutralize and regulate areas with a high prevalence of HFRS. We employed bioinformatics methods to design a recombinant protein vaccine based on conserved regions of protein consensus sequences in HTNV and SEOV membranes. The S2 Drosophila expression system was utilized to enhance protein expression, solubility and immunogenicity. After the Gn and Gc proteins of HTNV and SEOV were successfully expressed, mice were immunized, and the humoral immunity, cellular immunity, and in vivo protection of the HFRS universal subunit vaccine were systematically evaluated in mouse models. These results indicated that the HFRS subunit vaccine generated elevated levels of binding and neutralizing antibodies, particularly IgG1, compared to that of the traditional inactivated HFRS vaccine. Additionally, the spleen cells of immunized mice secreted IFN-r and IL-4 cytokines effectively. Moreover, the HTNV-Gc protein vaccine successfully protected suckling mice from HTNV infection and stimulated GC responses. In this research, a new scientific approach is investigated to develop a universal HFRS subunit protein vaccine that is capable of producing effective humoral and cellular immunity in mice. The results suggest that this vaccine could be a promising candidate for preventing HFRS in humans.

Due to the weak information about cultural targets in the complex marine environment, an omission problem exists in large-scale mariculture extraction using single-view and single-source images. To overcome this problem, we developed a mariculture extraction method that combines dense time-series Sentinel-2 and Sentinel-1 data. A high-precision Chinese mariculture distribution map for 2020 was produced with an overall accuracy of 94.00% and a kappa coefficient of 0.91. The results show that (1) the total area of mariculture was 1173249.22 ha on the national scale, which was significantly larger than the previous studies (459595.70 and 205920.28 ha, respectively), with Shandong Province (39.09%) having the largest proportion; (2) China’s mariculture presented a spatial distribution characteristic of ‘Denser North and Sparser South’, and mariculture was centralized in the coastal zones of the northern provinces (60.76%) rather than the southern provinces; (3) the official production statistics and remote sensing-derived mariculture area revealed a highly corresponding trend at the provincial level, with an R2 reaching 0.78, which is much higher than the 0.07 and 0.41 values of the comparison data. The results directly provide data reference for mariculture production estimation and site selection or ideas for mariculture extraction in other regions and globally.

Currently, many globally accessible forest mapping products can be utilized to monitor and assess the status of and changes in forests. However, substantial disparities exist among these products due to variations in forest definitions, classification methods, and remote sensing data sources. This becomes particularly conspicuous in regions characterized by significant deforestation, like Southeast Asia, where forest mapping uncertainty is more pronounced, presenting users with challenges in selecting appropriate datasets across diverse regions. Moreover, this situation impedes the further enhancement of accuracy for forest mapping products. The aim of this research is to assess the consistency and accuracy of six recently produced forest mapping products in Southeast Asia. These products include three 10 m land cover products (Finer Resolution Observation and Monitoring Global LC (FROM-GLC10), ESA WorldCover 10 m 2020 (ESA2020), and ESRI 2020 Land Cover (ESRI2020)) and three forest thematic mapping products (Global PALSAR-2 Forest/Non-Forest map (JAXA FNF2020), global 30 m spatial distribution of forest cover in 2020 (GFC30_2020), and Generated_Hansen2020, which was synthesized based on Hansen TreeCover2010 (Hansen2010) and Hansen Global Forest Change (Hansen GFC) for the year 2020). Firstly, the research compared the area and spatial consistency. Next, accuracy was assessed using field validation points and manual densification points. Finally, the research analyzed the geographical environmental and biophysical factors influencing consistency. The results show that ESRI2020 had the highest overall accuracy for forest, followed by ESA2020, FROM-GLC10, and Generated_Hansen2020. Regions with elevations ranging from 200 to 3000 m and slopes below 15° or above 25° showed high spatial consistency, whereas other regions showed low consistency. Inconsistent regions showed complex landscapes heavily influenced by human activities; these regions are prone to being confused with shrubs and cropland and are also impacted by rubber and oil palm plantations, significantly affecting the accuracy of forest mapping. Based on the research findings, ESRI2020 is recommended for mountainous areas and abundant forest regions. However, in areas significantly affected by human activities, such as forest and non-forest edges and mixed areas of plantations and natural forests, caution should be taken with product selection. The research has identified areas of forest inconsistency that require attention in future forest mapping. To enhance our understanding of forest mapping and generate high-precision forest cover maps, it is recommended to incorporate multi-source data, subdivide forest types, and increase the number of sample points.

During the first wave of the COVID-19 outbreak, the Chinese diaspora, especially Chinese international students, were subjected to greater stress than others, because they were under pressure from both fear of infection and coping with acculturation (e.g., discrimination). Consequently, more research is needed to understand the anxiety induced by COVID-19 stresses on this specific cultural group. The main purpose of this study is to investigate the relationship between COVID-19 stress and individuals’ anxiety, and the moderating roles of Acceptance, Reframing, and Striving (ARS) coping, the family support coping strategy, and wise reasoning. To test our predictions, we collected data from 224 Chinese international students (CIS). Results indicated a strong and positive relationship between pandemic stress and anxiety. Surprisingly, both ARS and family support coping did not moderate the association between COVID-19 stress and anxiety. Instead, wise reasoning as a potential reflective coping strategy interacted with COVID-19 stress to predict anxiety. Specifically, wise reasoning predicted more anxiety when individuals perceived a low-level of COVID-19 stress, however, such a relationship disappeared when individuals perceived a high-level of COVID-19 stress. These findings about wise-reasoning extends our understanding of wisdom and how it plays a role in the context of COVID-19.

In this article, the endurance characteristic of the TiN/HZO/TiN capacitor was improved by the laminated structure of a ferroelectric Hf0.5Zr0.5O2 thin film. Altering the HZO deposition ratio, the laminated-structure interlayer was formed in the middle of the HZO film. Although small remanent polarization reduction was observed in the capacitor with a laminated structure, the endurance characteristic was improved by two orders of magnitude (from 106 to 108 cycles). Moreover, the leakage current of the TiN/HZO/TiN capacitor with the laminated-structure interlayer was reduced by one order of magnitude. The reliability enhancement was proved by the Time-Dependent Dielectric Breakdown (TDDB) test, and the optimization results were attributed to the migration inhibition and nonuniform distribution of oxygen vacancies. Without additional materials and a complicated process, the laminated-structure method provides a feasible strategy for improving HZO device reliability.

Condensed phase particles (CCPs) of plume flows in solid rocket motors (SRMs) are one of the major causes of smog and other signal characteristics, which leads to attenuation of weapons guidance system signals. In order to study the dynamic combustion characteristics of the exhaust plume in a high pressure solid rocket motor with highly-aluminized propellanta digital in-line holographic (DIH) measurement system was used for identification and analysis of CCPs of exhaust plume flows in a SRM under 10 MPa pressure. During the SRM firing, the plume particles characteristic in the field of 9–11.5 cm away from the non-expanding nozzle outlet plane was measured and analyzed. Further, in order to improve the efficiency and accuracy of particle identification, a target recognition method suitable for autonomous recognition of plume particles in a complex background from digital holographic images was established. About 12,400 individual particles from two thousand holographic images were recognized, and the 3D spatial information (number and volume probability density function) and mean diameters were obtained and analyzed. The results showed that digital in-line holography measurement technology with target recognition method established in this paper can be applied well to real-time measurement of the 3D dynamic characteristics of the plume particle field anywhere outside of the nozzle outlet of an SRM with highly aluminized propellants. By identifying each reconstructed particle, the 3D spatial distribution, CCPs size distribution and velocity in the measurement area can be obtained.

To study global and regional environment protection and sustainable development and also to optimize mapping methods, it is of great significance to compare three existing 10 m resolution global land cover products in terms of accuracy: FROM-GLC10, the ESRI 2020 land cover product (ESRI2020), and the European Space Agency world cover 2020 product (ESA2020). However, most previous validations lack field collection points in large regions, especially in Southeast Asia, which has a cloudy and rainy climate, creating many difficulties in land cover mapping. In 2018 and 2019, we conducted a 56-day field investigation in Southeast Asia and collected 3326 points from different places. By combining these points and 14,808 other manual densification points in a stratified random sampling, we assessed the accuracy of the three land cover products in Southeast Asia. We also compared the impacts of the different classification standards, the different sample methods, and the different spatial distributions of the sample points. The results show that in Southeast Asia, (1) the mean overall accuracies of the FROM-GLC10, ESRI2020, and ESA2020 products are 75.43%, 79.99%, and 81.11%, respectively; (2) all three products perform well in croplands, forests, and built-up areas; ESRI2020 and ESA2020 perform well in water, but only ESA2020 performs well in grasslands; and (3) all three products perform badly in shrublands, wetlands, or bare land, as both the PA and the UA are lower than 50%. We recommend ESA2020 as the first choice for Southeast Asia’s land cover because of its high overall accuracy. FROM-GLC10 also has an advantage over the other two in some classes, such as croplands and water in the UA aspect and the built-up area in the PA aspect. Extracting the individual classes from the three products according to the research goals would be the best practice.

The use of remote sensing to monitor coastlines with wide distributions and dynamic changes is significant for coastal environmental monitoring and resource management. However, most current remote sensing information extraction of coastlines is based on the instantaneous waterline, which is obtained by single-period imagery. The lack of a unified standard is not conducive to the dynamic change monitoring of a changeable coastline. The tidal range observation correction method can be used to correct coastline observation to a unified climax line, but it is difficult to apply on a large scale because of the distribution of observation sites. Therefore, we proposed a coastline extraction method based on the remote sensing big data platform Google Earth Engine and dense time-series remote sensing images. Through the instantaneous coastline probability calculation system, the coastline information could be extracted without the tidal range observation data to achieve a unified tide level standard. We took the Malay Islands as the experimental area and analyzed the consistency between the extraction results and the existing high-precision coastline thematic products of the same period to achieve authenticity verification. Our results showed that the coastline data deviated 10 m in proportion to a reach of 40% and deviated 50 m within a reach of 89%. The overall accuracy was kept within 100 m. In addition, we extracted 96 additional islands that have not been included in public data. The obtained multi-phase coastlines showed the spatial distribution of the changing hot regions of the Malay Islands’ coastline, which greatly supported our analysis of the reasons for the expansion and retreat of the coastline in this region. These research results showed that the big data platform and intensive time-series method have considerable potential in large-scale monitoring of coastline dynamic change and island reef change monitoring.