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Accurate measurement of socio-economic loss and the impact of disasters is crucial for effective risk assessment and management. This study introduces a Disaster Severity Index (DSI) and a Disaster Impact Index (DII), along with a composite severity matrix, to evaluate comprehensive disaster losses. By utilizing seven loss indicators across six types of natural disasters and socioeconomic indicators, we thoroughly assessed Shanghai’s historical disaster losses from 1978 to 2020. Our analysis reveals that Shanghai’s most severe annual disaster losses occurred in 1991 and 2005; however, the overall impact on the local socio-economy has been declining. According to the DSI, Chongming (0.88), Songjiang (0.64), and Qingpu (0.51) Districts exhibit the highest severity. In terms of the DII, Songjiang (0.87), Chongming (0.71), and Qingpu (0.64) Districts are most affected. The comprehensive disaster severity grading indicates that Chongming and Songjiang Districts experience the most severe impacts, while Huangpu and Xuhui Districts are less affected. The spatial distribution of disaster losses is concentrated in suburban areas, with less impact in the central city. Our methodology provides a framework for analyzing and comparing historical disaster losses in terms of time (inter-annual), space (administrative divisions), and types of disasters. It can also be used for statistical analysis and regular monitoring of disaster losses. This study not only elucidates the spatiotemporal distribution of historical disaster losses in Shanghai but also validates the efficacy of our comprehensive index models.

In seismic data interpretation, the resolution and signal-to-noise ratio of seismic profile images directly affect the subsequent interpretation of seismic data. High-frequency information represents details and boundaries, such as stratigraphic interfaces and small-scale geological features. Considering the characteristics of seismic data, this paper adopts a GAN network based on deep residual channel attention mechanism to achieve seismic profile reconstruction and random noise suppression, and improve the resolution of seismic data. The generator network in this algorithm adopts an RIR (Residual in Residual) structure, which uses both long skip connections and short skip connections to bypass abundant low-frequency information and directly learn high-frequency information in seismic data. This structure extracts deeper high-level feature information from seismic data and introduces residual blocks with channel attention (RCAB), allowing network weights to favor channels with more stratigraphic features, thereby improving the reconstruction performance of the generator. Additionally, we use a mixed loss function algorithm to train the network, incorporating a perceptual loss function to further enhance the perceptual quality of the reconstructed images and employing a relativistic adversarial loss (RaGAN) to obtain sharper seismic image edge information. To address the issue of network training relying on a large amount of training data pairs, we synthesize high-resolution seismic data and establish a high-order data degradation model to obtain low-resolution seismic data with different degradation factors. The experimental results of processing synthetic seismic data and actual data show that the proposed workflow can significantly improve the quality perception of the original data, achieve an ideal signal-to-noise ratio, further enhance the resolution effect of the reconstructed profile images, and construct more accurate structural and stratigraphic feature maps than the original seismic images.

Tropical cyclones (TCs) are among the most devastating natural hazards. Socioeconomic exposure to TCs is essential for global disaster risk assessment. This study mapped global TC hazards using TC best track data from 1990 to 2019 and the Holland wind field model. Absolute and relative exposure indices were developed, and a matrix model was used to determine the exposure hotspots of TCs. Our results show that: (1) From 1990 to 2019, the exposed GDP to TCs increased by USD 9771.5 billion, and the population increased by 570 million people, with an average annual growth rate of 3.62 % and 1.26 %, respectively. South Asia shows a significant increasing trend in both exposed GDP and the proportion of the exposed population. In terms of income levels, lower middle income countries have the fastest growth in exposed GDP and population. (2) Countries with high absolute exposure tend to be populous and economically developed, while countries with high relative exposure are mainly small island nations. The number of countries with the highest level (level V) of exposed GDP and the population is 8 and 10, respectively. Mainly located in East Asia and the Pacific. (3) From 1990 to 2019, the total area of affected cities increased by 12.94 × 104 km2. The increase in GDP and population exposure in urban areas accounted for 45.45 % and 77.53 % of the total growth in exposure, respectively. Our study contributes to understanding the dynamics of exposure characteristics in TC regions and provides an important foundation for TC risk management.

Object detection via remote sensing encounters significant challenges due to factors such as small target sizes, uneven target distribution, and complex backgrounds. This paper introduces the K-CBST YOLO algorithm, which is designed to address these challenges. It features a novel architecture that integrates the Convolutional Block Attention Module (CBAM) and Swin-Transformer to enhance global semantic understanding of feature maps and maximize the utilization of contextual information. Such integration significantly improves the accuracy with which small targets are detected against complex backgrounds. Additionally, we propose an improved detection network that combines the improved K-Means algorithm with a smooth Non-Maximum Suppression (NMS) algorithm. This network employs an adaptive dynamic K-Means clustering algorithm to pinpoint target areas of concentration in remote sensing images that feature varied distributions and uses a smooth NMS algorithm to suppress the confidence of overlapping candidate boxes, thereby minimizing their interference with subsequent detection results. The enhanced algorithm substantially bolsters the model’s robustness in handling multi-scale target distributions, preserves more potentially valid information, and diminishes the likelihood of missed detections. This study involved experiments performed on the publicly available DIOR remote sensing image dataset and the DOTA aerial image dataset. Our experimental results demonstrate that, compared with other advanced detection algorithms, K-CBST YOLO outperforms all its counterparts in handling both datasets. It achieved a 68.3% mean Average Precision (mAP) on the DIOR dataset and a 78.4% mAP on the DOTA dataset.

The accuracy and reliability of unmanned aerial vehicle (UAV) visual positioning systems are dependent on the performance of multi-source image matching algorithms. Despite many advancements, targeted performance evaluation frameworks and datasets for UAV positioning are still lacking. Moreover, existing consistency verification methods such as Random Sample Consensus (RANSAC) often fail to entirely eliminate mismatches, affecting the precision and stability of the matching process. The contributions of this research include the following: (1) the development of a benchmarking framework accompanied by a large evaluation dataset for assessing the efficacy of multi-source image matching algorithms; (2) the results of this benchmarking framework indicate that combinations of multiple algorithms significantly enhance the Match Success Rate (MSR); (3) the introduction of a novel Geographic Geometric Consistency (GGC) method that effectively identifies mismatches within RANSAC results and accommodates rotational and scale variations; and (4) the implementation of a distance threshold iteration (DTI) method that, according to experimental results, achieves an 87.29% MSR with a Root Mean Square Error (RMSE) of 1.11 m (2.22 pixels) while maintaining runtime at only 1.52 times that of a single execution, thus optimizing the trade-off between MSR, accuracy, and efficiency. Furthermore, when compared with existing studies on UAV positioning, the multi-source image matching algorithms demonstrated a sub-meter positioning error, significantly outperforming the comparative method. These advancements are poised to enhance the application of advanced multi-source image matching technologies in UAV visual positioning.

Since light propagation in a multimode fiber (MMF) exhibits visually random and complex scattering patterns due to external interference, this study numerically models temperature and curvature through the finite element method in order to understand the complex interactions between the inputs and outputs of an optical fiber under conditions of temperature and curvature interference. The systematic analysis of the fiber’s refractive index and bending loss characteristics determined its critical bending radius to be 15 mm. The temperature speckle atlas is plotted to reflect varying bending radii. An optimal end-to-end residual neural network model capable of automatically extracting highly similar scattering features is proposed and validated for the purpose of identifying temperature and curvature scattering maps of MMFs. The viability of the proposed scheme is tested through numerical simulations and experiments, the results of which demonstrate the effectiveness and robustness of the optimized network model.

IntroductionMossy biocrust represents a stable stage in the succession of biological soil crust in arid and semi-arid areas, providing a microhabitat that maintains microbial diversity. However, the impact of mossy biocrust rhizoid soil and different particle sizes within the mossy biocrust layer and sublayer on microbial diversity and soil enzyme activities remains unclear.MethodsThis study utilized Illumina MiSeq sequencing and high-throughput fluorometric technique to assess the differences in microbial diversity and soil extracellular enzymes between mossy biocrust rhizoid soil and different particle sizes within the mossy biocrust sifting and sublayer soil.ResultsThe results revealed that the total organic carbon (TOC), total nitrogen (TN), ammonium (NH4+) and nitrate (NO3−) in mossy biocrust rhizoid soil were the highest, with significantly higher TOC, TN, and total phosphorus (TP) in mossy biocrust sifting soil than those in mossy biocrust sublayer soil. Extracellular enzyme activities (EAAs) exhibited different responses to various soil particle sizes in mossy biocrust. Biocrust rhizoid soil (BRS) showed higher C-degrading enzyme activity and lower P-degrading enzyme activity, leading to a significant increase in enzyme C: P and N: P ratios. Mossy biocrust soils were all limited by microbial relative nitrogen while pronounced relative nitrogen limitation and microbial maximum relative carbon limitation in BRS. The diversity and richness of the bacterial community in the 0.2 mm mossy biocrust soil (BSS0.2) were notably lower than those in mossy biocrust sublayer, whereas the diversity and richness of the fungal community in the rhizoid soil were significantly higher than those in mossy biocrust sublayer. The predominant bacterial phyla in mossy biocrust were Actinobacteriota, Protebacteria, Chloroflexi, and Acidobacteriota, whereas in BSS0.2, the predominant bacterial phyla were Actinobacteriota, Protebacteria, and Cyanobacteria. Ascomycota and Basidiomycota were dominant phyla in mossy biocrust. The bacterial and fungal community species composition exhibited significant differences. The mean proportions of Actinobacteriota, Protebacteria, Chloroflexi, Acidobacteriota, Acidobacteria, Cyanobacteria, and Bacteroidota varied significantly between mossy biocrust rhizoid and different particle sizes of mossy biocrust sifting and sublayer soil (p

In this investigation, the mechanism of dye transfer during the mixed washing of natural cellulosic fabrics was elucidated through a comprehensive study of the hydrolysis of Reactive Red 195 (RR 195) and the subsequent adsorption of its hydrolysis products onto cellulose, approached both experimentally and theoretically. Initially, Reversed-phase high-performance liquid chromatography (RP-HPLC) was employed to identify the final products of Reactive Red 195 hydrolysis, collectively referred to as the unfixed dye substance ( UDS ). This data provided theoretical insight into the hydrolysis mechanism of the dye. Following this identification, an adsorption kinetic model was established to delineate the interaction of the hydrolysis products with cellulose. Adsorption exhibited its maximal rate at a temperature of 60°C, under conditions of a wash bath ratio of 120:1 and a pH value of 7. Furthering the investigation, a molecular dynamics model was constructed to detail the adsorption process of these hydrolysis products on the hydrophobic surface Iβ(1 0 0) of cellulose within an aqueous environment. This model offered precise insights into the adsorption volume, kinetics, and mechanistic interaction at a molecular scale. Conclusive evidence from both theoretical analyses and experimental results suggested that the hydrolysis products, devoid of reactive groups, were incapable of chemically interacting with the hydroxyl groups inherent to cellulose. Instead, it was discerned that these products underwent a physical adsorption process onto the cellulose surface. Such adsorptive behavior is postulated to be a predominant factor influencing the dye transfer phenomenon in mixed washing conditions.

In recent years, with the increasing global focus on environmental protection, the issue of microfiber release from denim during the washing process has gained attention. In this study, a programmable washing device simulating household drum washing was designed and developed, microfibers and indigo dyes released from denim washing were quantitatively detected, and we have also developed a novel method for estimating the release of microfibers during washing. The effects of washing time, washing temperature, and washing load on microfiber and indigo dye release from denim were explored. The results showed that the effect of washing load on microfiber and indigo dye release was greater than washing temperature and washing time. The research findings indicate that with an increase in washing time (35–95 min) and washing load (100–250 g), the shedding of microfibers and indigo dye significantly increases, reaching peak release levels of 343.6 μg/g fabric and 0.027 mg/L, respectively. However, there is a decreasing trend in the release of microfibers and indigo dye when the washing temperature exceeds 50 °C. Furthermore, our data suggests that an increase in washing load leads to a significant change in the number of microfibers (from 978 items/g fabric to 1997 items/g fabric) and their mass (from 156.87 μg/g fabric to 343.56 μg/g fabric). The influence of washing time, washing temperature, and washing load on microfiber length shows relatively small fluctuations within the range of 600–900 µm. This study provides new ideas and methods for estimating the release of microfiber and indigo dye in denim washing around the world.

The domain of science and engineering relies heavily on an in-depth comprehension of fluid dynamics, given the prevalence of fluids such as water, air, and interstellar gas in the universe. Euler equations form the basis for the study of fluid motion. This paper is concerned with the Cauchy problem of isentropic compressible Euler equations away from the vacuum. We use the integration method with the general test function f=f(r), proving that there exist the corresponding blowup results of C1 irrotational solutions for Euler equations and Euler equations with time-dependent damping in Rn (n≥2), provided the density-independent initial functional is sufficiently large. We also provide two simple and explicit test functions f(r)=r and f(r)=1+r, to demonstrate the blowup phenomenon in the one-dimensional case. In particular, our results are applicable to the non-radial system.

At present, organic wastewater containing dyes has become one of the main threats to the environment, and wastewater pollution caused by dyes released from fabrics during home washing also accounts for a large proportion. In this study, Ti/IrO2 electrodes for dye waste degradation were designed and prepared with Reactive Yellow 210 (RY 210), Reactive Blue 19 (RB 19) and Reactive Blue 21 (RB 21) solutions, and a laboratory electrochemical reactor was constructed. Secondly, in the reactor, the effects of current density (20–60 mA cm−2), electrolyte concentration (NaCl, 0.01–0.03 M L−1), and initial dye concentration (30–70 mg L−1) on the COD degradation rate and energy consumption of the dye solution were explored, and the parameters were optimized by the Box-Behnken design, and the equipment was realized in the washing machine. The results showed that the effect of degradation parameters on the degradation of the three groups of dyes was: current density > initial dye concentration > electrolyte concentration. Through parameter optimization, the average COD degradation rates of the three groups of dyes, Reactive Yellow 210 (RY 210), Reactive Blue 19 (RB 19) and Reactive Blue 21 (RB 21), reached 50.71%, 41.65%, and 33.12%, respectively, and the degradation energy consumption decreased by the same trend as 29.91%, 26.49%, and 65.91%, respectively.

Key points Chronic liver failure consortium-acute decompensation score (CLIF-C ADs) and extracellular liver volume (ECVIC-liver) are independent risk factors for disease progression. Patients with a lower ECVIC-liver have a better prognosis. Highest predictive efficacy using the model combining CLIF-C ADs and ECVIC-liver.

Abstract Ferroptosis, a newly discovered irondependent form of regulated cell death caused by excessive accumulation of lipid peroxides, is linked to the development and treatment response of various types of cancer, including gastric cancer (GC). Noncoding RNAs (ncRNAs), as key regulators in cancer, have both oncogenic and tumor suppressive roles. However, studies on ferroptosis-related ncRNA networks in GC are still lacking. Here, we first identified 61 differentially expressed genes associated with ferroptosis in GC by computing and analyzing gene expression profile of tumor and normal tissues for GC. Then, upstream lncRNAs and miRNAs interacting with them were found through miRNet and miRBase databases, and hub lncRNAs and miRNAs were obtained through topological analysis. Finally, the ceRNA regulatory network linked to ferroptosis in GC was established, which includes two ferroptosis marker genes (TXNIP and TSC22D3), one driver gene (GABARAPL1), and one suppressor gene (CAV1). Kaplan-Meier survival analysis showed that changes in the expression of these genes were associated with the survival of GC patients. Furthermore, our study revealed that this ceRNA network may influence the progression of GC by regulating ferroptosis process. These results will help experimental researchers to design an experiment study to further explore the roles of this regulatory network in GC ferroptosis.

Introduction: Oligopeptides exhibit great prospects for clinical application and its separation is of great importance in new drug development.Methods: To accurately predict the retention of pentapeptides with analogous structures in chromatography, the retention times of 57 pentapeptide derivatives in seven buffers at three temperatures and four mobile phase compositions were measured via reversed-phase high-performance liquid chromatography. The parameters (kHA, kA, and pKa) of the acid–base equilibrium were obtained by fitting the data corresponding to a sigmoidal function. We then studied the dependence of these parameters on the temperature (T), organic modifier composition (φ, methanol volume fraction), and polarity (PmN parameter). Finally, we proposed two six-parameter models with (1) pH and T and (2) pH and φ or PmN as the independent variables. These models were validated for their prediction capacities by linearly fitting the predicted retention factor k-value and the experimental k-value.Results: The results showed that logkHA and logkA exhibited linear relationships with 1/T, φ or PmN for all pentapeptides, especially for the acid pentapeptides. In the model of pH and T, the correlation coefficient (R2) of the acid pentapeptides was 0.8603, suggesting a certain prediction capability of chromatographic retention. Moreover, in the model of pH and φ or PmN, the R2 values of the acid and neutral pentapeptides were greater than 0.93, and the average root mean squared error was approximately 0.3, indicating that the k-values could be effectively predicted.Discussion: In summary, the two six-parameter models were appropriate to characterize the chromatographic retention of amphoteric compounds, especially the acid or neutral pentapeptides, and could predict the chromatographic retention of pentapeptide compounds.

Abstract In this paper, the effect of washing parameters on the quantity of dye discharge from fabric dyed in highly saturated color (FSC) was discussed. Firstly, the FSC was prepared with reactive red 195 to represent the dark clothes. Secondly, the effect of the washing parameters, including washing time, washing temperature, washing water volume, the weight of FSC, and the dosage of detergent, on dye discharge was analyzed through the single factor test. Thirdly, the mathematical relationship between the quantity of dye discharge (DDQ) and the four washing parameters was discussed through the center combination experiment and response surface method. And a quadratic model was built to predict the quantity of dye discharge when the FSC were washed with different washing parameters. The experimental results indicated that the quantity of dye discharge was affected by the four selected washing parameters and the optimal washing parameters to reduce the quantity of dye discharge can be deduced from the quadratic model. The optimized parameters effectively reduced 0.99 mg dye discharge per liter, and the DDQ reduction rate was up to 53.5%.

Plastic pollution has been today’s most highly visible environmental problem in the world. How to responsibly manage plastic waste to control and eliminate plastic pollution has been a global challenge. We have begun to address these issues and developed some science-based solutions and emerging technologies. However, tackling such an intractable challenge requires systematic solutions except for science-based and technology-based ones. Environmental education, fostering plastic pollution prevention within society’s educational system, will provide a powerful and feasible pathway at a low cost. Within this perspective, the value and the way forward of education in solving plastic pollution are primarily discussed. Environmental education, including school-level education for students, sustainable consumption behavior guidance, and pollution prevention education for the public, is the feasible, effective, and permanent resolution of plastic pollution in the future.

Abstract Background Post-resistance progress in paclitaxel (PTX) treatment remains a major challenge in tumor treatment. A high dose of PTX was used for cell lines to analyze the changes in molecular expression. The miR-378d was sharply reduced in surviving cells, but the role of miR-378d in Esophageal squamous cell carcinoma (ESCC) remained unclear. Methods We analyzed the relationship between miR-378d expression and the clinicopathological features of ESCC. We constructed miR-378d silent expression cell lines to study phenotypes and molecular mechanisms. Results The miR-378d expression was associated with good prognosis in patients with ESCC. miR-378d inhibition promoted chemo-resistance, monoclonal formation, EMT, migration, invasion, stemness, and metastasis of ESCC cells. miR-378d can target downregulated AKT1. Conclusions Therefore, miR-378d expression is a good prognostic factor of patients with ESCC and regulates the malignant phenotype of tumor cells through AKT.

The faded-on stains of cotton clothes are a common daily phenomenon. The desorption and adsorption of reactive dyes are theoretically responsible for the faded-on stains on cotton clothes in the washing microenvironment, especially when the light color cotton fabrics ( LCF s) are washed together with the cotton fabrics dyed in highly saturated color ( CFSC s). However, the effects of washing parameters on the desorption and adsorption kinetics of reactive dyes and the mitigation of faded-on stains in the washing microenvironment through washing parameter optimization are poorly understood. This study thoroughly discusses the desorption and adsorption behaviors of reactive red 195 in the washing microenvironment from the inhibition of color transfer. Firstly, CFSC s and LCF s were prepared by using reactive red 195 and cotton fabrics. Secondly, the effects of washing parameters, washing temperature, washing liquor ratio, and washing solution pH, on the dye desorption and adsorption rate were studied with the simulated washing device ( SWD ), followed by the response surface analysis of washing parameters. Thirdly, the modeling of desorption and adsorption kinetics and velocity were detailed. Finally, the model of dye desorption and adsorption was validated in a drum washing machine ( DWM ). The results are helpful for the design of scientific washing procedures to curb the faded-on stains of cotton clothes effectively.

The use of UAV-based remote sensing for soil moisture has developed rapidly in recent decades, with advantages such as high spatial resolution, flexible work arrangement, and ease of operation. In bare and low-vegetation-covered soils, the apparent thermal inertia (ATI) method, which adopts thermal infrared data from UAV-based remote sensing, has been widely used for soil moisture estimation at the field scale. However, the ATI method may not perform well under inconsistent weather conditions due to inconsistency of the intensity of the soil surface energy input. In this study, an improvement of the ATI method (ATI-R), considering the variation in soil surface energy input, was developed by the incorporation of solar radiation measurements. The performances of the two methods were compared using field experiment data during multiple heating processes under various weather conditions. It showed that on consistently sunny days, both ATI-R and ATI methods obtained good correlations with the volumetric water contents (VWC) (R2ATI-R = 0.775, RMSEATI-R = 0.023 cm3·cm−3 and R2ATI = 0.778, RMSEATI = 0.018 cm3·cm−3) on cloudy or a combination of sunny and cloudy days as long as there were significant soil-heating processes despite the different energy input intensities; the ATI-R method could perform better than the ATI method (cloudy: R2ATI-R = 0.565, RMSEATI-R = 0.024 cm3·cm−3 and R2ATI = 0.156, RMSEATI = 0.033 cm3·cm−3; combined: R2ATI-R = 0.673, RMSEATI-R = 0.028 cm3·cm−3 and R2ATI = 0.310, RMSEATI = 0.032 cm3·cm−3); and on overcast days, both the ATI-R and ATI methods could not perform satisfactorily (R2ATI-R = 0.027, RMSEATI-R = 0.024 cm3·cm−3 and R2ATI = 0.027, RMSEATI = 0.031 cm3·cm−3). The results indicate that supplemental solar radiation data could effectively expand applications of the ATI method, especially for inconsistent weather conditions.

The distribution of and variation in soil properties are spatially correlated and commonly obtained through interpolation techniques and point source surveys. The contradiction between sample limitation and data demand has become an obstacle to generating accurate distribution maps with conventional methods, such as geostatistical or machine learning methods. To weaken the negative impact of limited data and obtain a more accurate distribution map, we introduce a new interpolation method called CS-V into soil science. The method combines compressed sensing (CS), which is a novel signal recovery technique, with the traditional geostatistical prior and generates a distribution map by solving a sparse recovery problem. Two datasets, a complete measurement set of soil electrical conductivity (EC) and a discrete point set of soil organic matter (SOM), were used to validate the feasibility and investigate the characteristics of the method. The compressibility of the soil distribution map was first validated through the EC dataset to provide the fundamentals of CS-V. The comparison between the results of CS-V and ordinary kriging (OK) shows that CS-V can provide a higher prediction accuracy and a wider estimation range. In addition, considering the two parameters of the sparse recovery problem, the regularized parameter λ is the decisive factor that controls the interpolation results, and the influence of searching space k is diluted when λ is large enough. The CS-V method is suitable as an alternative interpolation method in soil science in the case of limited measurement data.

Primary central nervous system diffuse large B-cell lymphoma (PCNS-DLBCL) is an uncommon non-Hodgkin lymphoma subtype, and its clinical and pathological characteristics remain unclear. PCNS-DLBCL patient data were retrospectively evaluated to determine clinical and pathological characteristics and prognostic factors. Furthermore, prognoses were calculated by Kaplan–Meier and Cox regression models based on clinical observations. In total, 51 immunocompetent patients were enrolled. The median age was 55 (range, 16–82) years, and the male-to-female ratio was 3:2. Headache (n = 19; 37%) and the frontal lobe (n = 16; 31%) were the most common presenting symptom and location, respectively. The median follow-up was 33 (range, 3–86) months, and the median overall survival (OS) and progression-free survival (PFS) were 18 months [95% confidence interval (CI), 21.2–34.2] and 15 months (95% CI, 16.9–28.7), respectively. Ki-67, cluster of differentiation-3, and deep brain involvement were independent prognostic markers. Moreover, multifocal lesions and deep brain involvement were unfavorable independent prognostic markers for PFS. This study indicates that targeted drug development for adverse prognostic factors is possible and provides guidance for clinical treatment decision-making.

Fixed-wing unmanned aerial vehicles (UAVs) and multi-rotor UAVs are widely utilized in large-area (>1 km2) environmental monitoring and small-area (2) fine vegetation surveys, respectively, having different characteristics in terms of flight cost, operational efficiency, and landing and take-off methods. However, large-area fine mapping in complex forest environments is still a challenge in UAV remote sensing. Here, we developed a method that combines a multi-rotor UAV and a fixed-wing UAV to solve this challenge at a low cost. Firstly, we acquired small-scale, multi-season ultra-high-resolution red-green-blue (RGB) images and large-area RGB images by a multi-rotor UAV and a fixed-wing UAV, respectively. Secondly, we combined the reference data of visual interpretation with the multi-rotor UAV images to construct a semantic segmentation model and used the model to expand the reference data. Finally, we classified fixed-wing UAV images using the large-area reference data combined with the semantic segmentation model and discuss the effects of different sizes. Our results show that combining multi-rotor and fixed-wing UAV imagery provides an accurate prediction of tree species. The model for fixed-wing images had an average F1 of 92.93%, with 92.00% for Quercus wutaishanica and 93.86% for Juglans mandshurica. The accuracy of the semantic segmentation model that uses a larger size shows a slight improvement, and the model has a greater impact on the accuracy of Quercus liaotungensis. The new method exploits the complementary characteristics of multi-rotor and fixed-wing UAVs to achieve fine mapping of large areas in complex environments. These results also highlight the potential of exploiting this synergy between multi-rotor UAVs and fixed-wing UAVs.

Abstract Background Since severe acute respiratory syndrome coronavirus, 2 (SARS-CoV-2) was firstly reported in Wuhan City, China in December 2019, Novel Coronavirus Disease 2019 (COVID-19) that is caused by SARS-CoV-2 is predominantly spread from person-to-person on worldwide scales. Now, COVID-19 is a non-traditional and major public health issue the world is facing, and the outbreak is a global pandemic. The strict prevention and control measures have mitigated the spread of SARS-CoV-2 and shown positive changes with important progress in China. But prevention and control tasks remain arduous for the world. The objective of this study is to discuss the difference of spatial transmission characteristics of COVID-19 in China at the early outbreak stage with resolute efforts. Simultaneously, the COVID-19 trend of China at the early time was described from the statistical perspective using a mathematical model to evaluate the effectiveness of the prevention and control measures. Methods In this study, the accumulated number of confirmed cases publicly reported by the National Health Committee of the People’s Republic of China (CNHC) from January 20 to February 11, 2020, were grouped into three partly overlapping regions: Chinese mainland including Hubei province, Hubei province alone, and the other 30 provincial-level regions on Chinese mainland excluding Hubei province, respectively. A generalized-growth model (GGM) was used to estimate the basic reproduction number to evaluate the transmissibility in different spatial locations. The prevention and control of COVID-19 in the early stage were analyzed based on the number of new cases of confirmed infections daily reported. Results Results indicated that the accumulated number of confirmed cases reported from January 20 to February 11, 2020, is well described by the GGM model with a larger correlation coefficient than 0.99. When the accumulated number of confirmed cases is well fitted by an exponential function, the basic reproduction number of COVID-19 of the 31 provincial-level regions on the Chinese mainland, Hubei province, and the other 30 provincial-level regions on the Chinese mainland excluding Hubei province, is 2.68, 6.46 and 2.18, respectively. The consecutive decline of the new confirmed cases indicated that the prevention and control measures taken by the Chinese government have contained the spread of SARS-CoV-2 in a short period. Conclusions The estimated basic reproduction number thorough GGM model can reflect the spatial difference of SARS-CoV-2 transmission in China at the early stage. The strict prevention and control measures of SARS-CoV-2 taken at the early outbreak can effectively reduce the new confirmed cases outside Hubei and have mitigated the spread and yielded positive results since February 2, 2020. The research results indicated that the outbreak of COVID-19 in China was sustaining localized at the early outbreak stage and has been gradually curbed by China’s resolute efforts.

Immunoglobulin G4-related disease (IgG4-RD) is an autoimmune disease that affects several organs. An inflammatory pseudotumor is a histologically proven benign tumor-like lesion that most commonly involves the lung and orbit. It is rare in the central nervous system, but rarest in the spinal canal. In this report, we present a case of IgG4-related intramedullary spinal inflammatory pseudotumor, along with a literature review. A 29-year-old male was transferred to the Department of Neurosurgery of Lanzhou University Second Hospital with progressive quadriparesis after numbness and weakness in both lower limbs for 50 days. Enhanced magnetic resonance imaging (MRI) of the spine revealed an isointense signal on T1-weighted images and a hyperintense signal on T2-weighted images from an enhanced mass located at the thoracic vertebrae region, for which a schwannoma was highly suspected. Then, a posterior median approach was adopted. The lesion was resected. The patient received further glucocorticoid after the diagnosis of an IgG4-related inflammatory pseudotumor was established, and the patient's symptoms improved, such as quadriparesis and lower limb weakness. This case highlights the importance of considering IgG4-related inflammatory pseudotumor as a differential diagnosis in patients with lesions involving the spinal intramedullary compartment and lower limb weakness when other more threatening causes have been excluded. IgG4-related inflammatory pseudotumor is etiologically unclear and prognostically unpredictable, and imaging may not help establish the diagnosis of IgG4-related inflammatory pseudotumor due to its resemblance to malignant tumors, and total resection might not be warranted. Glucocorticoid and surgery are usually the first-line treatments used.

BackgroundDelayed post-hypoxic leukoencephalopathy (DPHL) is a demyelinating syndrome that occurs days to weeks after the brain has recovered from a coma. It is caused by the period of hypoxia and is characterized by mental disorders, extrapyramidal system symptoms, and motor changes. Common causes include cardiogenic shock, severe anemia, massive blood loss, and poisoning. Poisoning, mostly resulting from intoxication with carbon monoxide and several narcotic drugs, has been reported to be a cause of DPHL. There are only a few reports of DPHL due to nitrite poisoning in literature. We report DPHL in a patient following nitrite poisoning and a review of the literature in this context.Case PresentationA 64-year-old man presented with dizziness and nausea without vomiting. He later went into a coma after consuming a spare rib soup. After blood gas analysis, we suspected nitrite poisoning combined with metabolic acidosis, hypoxemia, and electrolyte imbalance. He gradually showed neurologic recovery to premorbid baseline after intravenous administration of methylene blue (40 mg) and symptomatic treatment. Two months later, the patient's cerebral magnetic resonance imaging (MRI) showed signs that are compatible with injury, with the patient in late stages of mental decline.ConclusionNitrite poisoning can cause DPHL. There is a period of intermittent recovery between the time of poisoning and the development of DPHL, but the specific pathogenesis and treatment are still unclear.

Hemolymphangioma is a congenital malformation of blood vessels and lymphatic vessels, commonly found in the head, neck, and subcutaneous, rarely in the viscera and extremely rarely in the liver. In this case, a 6-year-old boy was found to have abdominal distension for more than 2 months with no other obvious symptoms. Physical examination revealed a large abdominal mass that was hard and not mobile. Laboratory tests found no obvious abnormity. Preoperative ultrasound and CT showed a huge cystic and solid-cystic tumor in the abdomen with close relationship to the right lower margin of the liver and fluid accumulation in the abdominopelvic cavity. The preliminary diagnoses were a malignant tumor of embryonic origin and undifferentiated sarcoma. Liver tumor resection was performed in our hospital, and the postoperative pathology was diagnosed as hepatic hemolymphangioma. The patient recovered well after surgery. It is easy to diagnose a large abdominal mass in a child as a malignant tumor of the liver and delay the treatment—no obvious symptoms, no obvious abnormalities in laboratory tests, and imaging shows a multiocular cystic lesion with clear borders and no invasion of blood vessels, indicating that the possibility of this disease should be considered. The tumor has an abnormal rich blood supply, and preoperative imaging evaluation clearly shows the vascular pathway and blood supply status to help optimize the surgical plan.

We present a comprehensive analysis of the anomalous Goos–Hänchen (GH) displacement that occurs during the reflection of light beams at an interface between air and an anisotropic medium. This analysis also applies to the Imbert–Fedorov effect. Our study suggests that the anomalous GH displacement is primarily caused by polarization-dependent abnormal interference effects between the direct and cross-reflected light fields. Using the interface between air and a type II Weyl semimetal as an example, we provide a clear physical explanation for the relationship between spin-dependent abnormal interference effects and anomalous GH displacement. We demonstrate that spin-dependent constructive interference leads to a reduction in the GH displacement of the total reflected light field, while spin-dependent destructive interference results in an increase in the GH displacement of the total reflected light field.

Organic amendments are a proven method of reducing soil erosion. However, the effect of organic additives on the pore properties of soils waterlogged by extreme rainfall has been minimally investigated. In this study, we collected rainfall data, established a field experiment consisting of randomized groups, and imaged the pore structure of waterlogged soil treated with different organic amendments (9 t ha−1 of maize straw [MS], 2.37 t ha−1 of cattle manure [OF], a mixture of 9 t ha−1 of MS and 1.89 t ha−1 of cattle manure [SOF], 7.4 t ha−1 of biochar [BC], 8.1 t ha−1 of woody peat [WP], and 3 L ha−1 of polyacrylamide [PAM]) in three-dimensions by X-ray microtomography and digital image analysis, which further quantified the effects. The results showed that, compared with the control, BC increased the total porosity by 54.28% and the connected porosity by 119.75%, but did not affect the pore shape and size distribution. BC and SOF improved the soil connectivity indexes; e.g., their C/I ratios increased by 177.44% and 149.62%, and the coordination numbers increased by 6.75% and 15.76%, respectively. MS had fewer, but longer and larger, channels and throats. Extreme precipitation events were significantly negatively correlated with all connectivity indicators. This study shows that organic materials can optimize the pore structure of waterlogged soil, with BC being the most resistant to erosion. However, extreme precipitation events can counteract the benefits organic additives have on soil pore structure.

Plant viruses and entomopathogenic fungi (EPF) can both elicit immune responses in insects. This study was designed to clarify whether plant viruses could affect the efficacy of EPF and explore the immune responses of brown planthopper (BPH), Nilaparvata lugens, in response to different pathogen infections. In this study, a strain of Metarhizium anisopliae YTTR with high pathogenicity against BPH was selected and explored whether rice ragged stunt virus (RRSV) could affect its lethality against BPH. RNA-seq was used to detect the inner responses of BPH in response to RRSV and M. anisopliae YTTR infection. Results showed that M. anisopliae YTTR has strong lethality against BPH (RRSV-carrying and RRSV-free). RRSV invasion did not affect the susceptibility of BPH against M. anisopliae YTTR at all concentrations. At 1 × 108 spores/mL, M. anisopliae YTTR caused a cumulative mortality of 80% to BPH at 7 days post-treatment. The largest numbers of differentially expressed genes (DEGs) was obtained in BPH treated with the two pathogens than in other single pathogen treatment. In addition, KEGG enrichment analysis showed that the DEGs were mostly enriched in immune and physiological mechanisms-related pathways. Both RRSV and M. anisopliae YTTR could induce the expression changes of immune-related genes. However, most of the immune genes had varying expression patterns in different treatment. Our findings demonstrated that RRSV invasion did not have any significant effect on the pathogenicity of M. anisopliae YTTR, while the co-infection of M. anisopliae YTTR and RRSV induced more immune and physiological mechanisms -related genes’ responses. In addition, the presence of RRSV could render the interplay between BPH and M. anisopliae YTTR more intricate. These findings laid a basis for further elucidating the immune response mechanisms of RRSV-mediated BPH to M. anisopliae infection.

Xerophytes in desert improve their fitness under stress through the development of stems and branches. However, little is known about changes in the structure and function of endophytic microorganisms in response to interactions between desert plants and their environment. In this study, we analyzed the lignification indices of young and mature branches during their development in a typical desert xerophyte, Nitraria tangutorum, and combined 16S and ITS high-throughput sequencing techniques to draw the following conclusions. Nitraria tangutorum accumulated more lignin, cellulose, and hemicellulose content during lignification. In addition, the number of OTUs and diversity of endophytic bacteria and fungi were reduced. Both endophytic bacteria and fungi were governed by stochastic processes during the development of stems and branches of Nitraria tangutorum and were significantly affected by lignification indices. Meanwhile, the development of stems and branches increased the relative abundance of Cyanobacteria and Ascomycota, and the dominant bacterial genera were mostly positively correlated with the lignification indices. In addition, stem and branch lignification reduced endophytic microbial interactions in the relationship between the endophytic bacterial and fungal networks of Nitraria tangutorum. Functional prediction analysis further revealed that lignification of Nitraria tangutorum branches changed the metabolic function of endophytic bacteria. The results of this study indicate that plant endophytic microorganisms play an important role in resisting and adapting to adversity and provide support for related studies on microbial ecology in desert areas.

Glioma is a highly heterogeneous and lethal tumor with an extremely poor prognosis. Through analysis of TCGA data, we identified that OLFML2A is a key promotor of gliomagenesis. However, the molecular function of OLFML2A and its underlying mechanism of action in glioma remain unclear. In this study, we found that OLFML2A expression was significantly upregulated in glioma specimens and positively correlated with pathological grades in glioma patients. Moreover, Kaplan–Meier survival analysis of TCGA data revealed that glioma patients with higher OLFML2A expression had shorter overall survival. Importantly, OLFML2A knockdown in glioma cells inhibited cell proliferation and promoted apoptosis. Mechanistically, OLFML2A downregulation inhibits Wnt/β-catenin signaling by upregulating amyloid precursor protein (APP) expression and reducing stabilized β-catenin levels, leading to the repression of MYC, CD44, and CSKN2A2 expression. Furthermore, OLFML2A downregulation suppressed the growth of transplanted glioma subcutaneously and intracranially by inhibiting Wnt/β-catenin pathway-dependent cell proliferation. By uncovering the oncogenic effects in human and rodent gliomas, our data support OLFML2A as a potential therapeutic target for glioma.

Background: Diabetes mellitus is one of the most widespread diseases in the world, high glucose can damage islet cells, it is important to discover new natural products to inhibit high glucose damage. The protective effects and mechanisms of a novel Lentinus edodes mycelia polysaccharide (LMP) against damage induced by high glucose in MIN6 cells were explored. Methods: Cell viability, malondialdehyde (MDA) inhibition, lactate dehydrogenase (LDH) release and the activity of superoxide dismutase (SOD) were evaluated under 40 mM glucose with or without LMP for 48 h. Cell signaling pathway analysis was performed to investigate the possible mechanisms of the protective effects of LMP in MIN6 cells. Results: The results showed that LMP could increase cell viability and the activity of SOD, decrease the reactive oxygen species ( ROS) production, and reduce the MDA content and LDH release in high glucose-induced MIN6 cells. Moreover, LMP prevented high glucose-induced apoptosis by decreasing the expression of Bax and the activation of caspase-1 and caspase-3. Cell signaling pathway analysis showed that p38 mitogen-activated protein kinase (MAPK) and JNK pathways were inhibited and the Nrf2 pathway was activated after treated with LMP. Conclusion: The protective effects of LMP against MIN6 cells damage induced by high glucose might rely on the regulation of the MAPK and Nrf2 pathways. These results indicated that LMP had great potential as a therapeutic agent for the treatment of diabetes mellitus.

Impact force refers to a transient phenomenon with a very short-acting time, but a large impulse. Therefore, the detection of impact vibration is critical for the reliability, stability, and overall life of mechanical parts. Accordingly, this paper proposes a method to indirectly characterize the impact force by using an impact stress wave. The LS-DYNA software is utilized to establish the model of a ball impacting the steel plate, and the impact force of the ball and the impact response of the detection point are obtained through explicit dynamic finite element analysis. In addition, on this basis, a correspondence between the impact force and the impact response is established, and finally, an experimental platform for impact force detection is built for experimental testing. The results obtained by the finite element method are in good agreement with the experimental measurement results, and it can be inferred that the detected piezoelectric signal can be used to characterize the impact force. The method proposed herein can guide the impact resistance design and safety assessment of structures in actual engineering applications.

Background: To evaluate the diagnostic value of diffusion weighted imaging (DWI) and apparent diffusion coefficient measurement (ADC) in glioma. Methods: Thirty two low-grade glioma patients and 31 high-grade glioma patients who were confirmed by pathology in Lanzhou University Second Hospital, Lanzhou, China from February 2016 to January 2019 were selected. The other 30 patients with brain metastases were selected as a control group. DWI imaging data of the three groups were collected, and ADC, relative ADC (rADC) values in tumor parenchyma, peritumor edema area, and contralateral normal white matter area were measured, and the levels of n-acetyl aspartic acid (NAA), choline (Cho), creatine (Cr) of tumor metabolites were analyzed. Results: rADC values in the peri-tumor edema areas of the high-grade glioma group were significantly lower than those in the low-grade group and the metastatic group （P=0.011）, and the low-grade group was significantly lower than that in the metastatic group (P < 0.05). NAA/Cho and NAA/Cr in parenchymal and peritumor edema areas of patients in the advanced group were significantly lower than those in the metastatic group (P < 0.05), and Cho /Cr was significantly higher than those in the metastatic group (P < 0.05). Conclusion: the rADC value, NAA/Cho, NAA/Cr and Cho/Cr in parenchymal and peritumor edema areas of the tumor can help to distinguish high-grade glioma, low-grade glioma and brain metastases.

Recently, unmanned aerial vehicle (UAV) remote sensing has been widely used in emergency scenarios; the operating mode has transitioned from one UAV to multiple UAVs. However, the current multiple-UAV remote sensing mode is characterized by high labor costs and limited operational capabilities; meanwhile, there is no suitable UAV swarm scheduling method that can be applied to remote sensing in emergency scenarios. To solve these problems, this study proposes a UAV swarm scheduling method. Firstly, the tasks were formulated and decomposed according to the data requirements and the maximum flight range of a UAV; then, the task sets were decomposed according to the maximum flight range of the UAV swarm to form task subsets; finally, aiming at the shortest total flight range of the task subsets and to balance the flight ranges of each UAV, taking the complete execution of the tasks as the constraint, the task allocation model was constructed, and the model was solved via a particle swarm optimization algorithm to obtain the UAV swarm scheduling scheme. Compared with the direct allocation method and the manual scheduling methods, the results show that the proposed method has high usability and efficiency.

Introduction: Breast cancer is one of the most commonly diagnosed cancers in women, with a high mortality rate. Objective: In the present study, we evaluated the anticancer effect of nobiletin, a flavone glycoside, on the breast cancer cell line MCF-7. Result: Cell viability and proliferation decreased and cell morphology changed from diamond to round after being treated with nobiletin. Nobiletin induced apoptosis of breast cancer MCF-7 cells via regulating the protein expression of Bax, Bcl-2, cleaved caspase-3, and p53. The expression of Bcl-2 decreased, while the expression of Bax and p53 increased in MCF-7 cells treated with nobiletin. Meanwhile, nobiletin inhibited cell migration by downregulating the protein expression of matrix metalloproteinase-2 (MMP-2) and matrix metalloproteinase-9 (MMP-9). Moreover, phosphorylation of p38 was increased, and the translocation of p65 and nuclear factor erythroid 2-related factor 2 (Nrf2) to the nucleus was decreased, which suggested that the anticancer effects of nobiletin might at least partially rely on mediating the p38 mitogen-activated protein kinase, nuclear transcription factor-κB, and Nrf2 pathways in MCF-7 breast cancer cells. Conclusion and recommendation: Our data showed that nobiletin was a potential antitumor drug, and it provided some experimental basis for the clinical application of tumor therapy.

Abstract With the development and application of nanotechnology, large amounts of nanoparticles will be potentially released to the environment and possibly cause many severe health problems. Although the toxicity of nanoparticles has been investigated, prevention and treatment of damages caused by nanoparticles have been rarely studied. Therefore, isotope tracing and improved CT imaging techniques were used to investigate the biodistribution influence between oMWCNTs(oxidized multi-walled carbon nanotubes) and 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC)/or simvastatin (TD) in vivo. What’s more, biochemical indices in plasma and tissue histology were measured to further study therapeutic effects on the damages of oMWCNTs in mice. Isotope tracing and improved CT imaging results showed that low dosages of DOPC and TD didn’t affect the distribution of oMWCNTs in mice; conversely, the distribution and metabolism of DOPC and TD were influenced by oMWCNTs. Moreover, DOPC and/or TD improved the biocompatibility of oMWCNTs in erythrocyte suspension in vitro. Biochemical index and histopathological results indicated that DOPC and TD didn’t prevent injuries caused by oMWCNTs effectively. But TD showed a good therapeutic effect for damages. This study is the first to investigate prevention and treatment effects of drugs on damages caused by oMWCNTs and provides new insights and breakthroughs for management of nanoparticles on health hazards.

Topdressing accounts for approximately 40% of the total nitrogen (N) application of winter wheat on the Huang-Huai-Hai Plain in China. However, N use efficiency of topdressing is low due to the inadaptable topdressing method used by local farmers. To improve the N use efficiency of winter wheat, an optimization method for topdressing (THP) is proposed that uses unmanned aerial vehicle (UAV)-based remote sensing to accurately acquire the growth status and an improved model for growth potential estimation and optimization of N fertilizer amount for topdressing (NFT). The method was validated and compared with three other methods by a field experiment: the conventional local farmer’s method (TLF), a nitrogen fertilization optimization algorithm (NFOA) proposed by Raun and Lukina (TRL) and a simplification introduced by Li and Zhang (TLZ). It shows that when insufficient basal fertilizer was provided, the proposed method provided as much NFT as the TLF method, i.e., 25.05% or 11.88% more than the TRL and TLZ methods and increased the yields by 4.62% or 2.27%, respectively; and when sufficient basal fertilizer was provided, the THP method followed the TRL and TLZ methods to reduce NFT but maintained as much yield as the TLF method with a decrease of NFT by 4.20%. The results prove that THP could enhance crop production under insufficient N preceding conditions by prescribing more fertilizer and increase nitrogen use efficiency (NUE) by lowering the fertilizer amount when enough basal fertilizer is provided.

In this paper, composite films composed of soya bean protein isolate (SPI) and polyacrylamide (PAM) were prepared under variations of ultrasonic power, treatment time and heating temperature. The effects of the major processing parameters related to ultrasonic-assisted treatment were evaluated and optimized through the single-factor analysis and Box–Behnken design (BBD), respectively, when the tensile strength of composite films was considered as the response value. The single-factor analysis was carried out to study the effects of ultrasonic power, treatment time and heating temperature on the viscosity and cohesion of the slurry and the tensile strength of SPI/PAM composite films, which also provided a reasonable data range of each factor for further optimization. Experiment results indicated that these three factors play a significant role in the tensile strength of films. Then BBD was applied to optimize the treatment conditions of these three factors, using the tensile strength of films as the response value. According to the interactive second-order polynomial model of three factors and the three-dimensional response surface, the maximum tensile strength of films was obtained under the optimal condition. To verify the reliability of the model, the experiment with the optimal condition was conducted, and results demonstrated that the observed tensile strength was in agreement with the predicated one. Also, the morphology and water solubility of the films showed that the film can be coated on the yarns evenly and removed clearly.

The disruption of the delicate balance between the generation of reactive oxygen species (ROS) and antioxidant scavenging systems can lead to many health problems. Polysaccharides extracted from fungi fruit body and myceliums have several potential health benefits. In this study, the antioxidant capacity and cell protective effects of a polysaccharide isolated from Lentinus edodes mycelia (LMP) were investigated. The antioxidant properties of LMP were screened using radical scavenging (1, 1-diphenyl-2-picrylhydrazyl (DPPH), hydroxyl, and superoxide anion), reducing power and inhibition of lipid peroxidation assays. Intracellular reactive oxygen species (ROS), in response to H2O2, was determined by the dichloro-dihydro-fluorescein diacetate (DCFH-DA) assay. Rat insulinoma (INS-1) cells apoptosis was detected using flow cytometry analysis. The results showed that LMP exhibited significantly strong radical scavenging activity. At the concentration of 2.0 mg mL-1, DPPH radical, hydroxyl radical, and superoxide anion radical scavenging rates are 80.32 ± 2.58%, 92.56 ± 3.11% and 93.73 ± 2.82%, respectively. The reducing power and inhibition of lipid peroxidation activity of LMP were as strong as the positive control. LMP alleviated the intracellular reactive oxygen species level and inhibited islet cell apoptosis significantly. The results open perspectives for studies of LMP in the treatment of diabetes.

The objectives of this study are to investigate the changes of runoff and sediment load and their potential influencing factors in the Huangfuchuan catchment. The Mann-Kendall test and accumulative anomaly methods were, respectively, applied to examine the changing trends and abrupt changes. Both annual runoff and sediment load demonstrated significant reduction (p

Three new C19-norditerpenoid alkaloids (1–3), along with two known C19-norditerpenoid alkaloids (4,5), have been isolated from Aconitum szechenyianum. Based on extensive spectroscopic techniques (1D, 2D-NMR, IR, and MS) and chemical methods, their structures were established as szechenyianine D (1), szechenyianine E (2), szechenyianine F (3), 8-O-methyl-14-benzoylaconine (4), and spicatine A (5). The immunosuppressive effects of compounds 1–5 were studied using a ConA-induced or LPS-induced splenocyte proliferation model. In vitro tests showed that Compounds 2, 4, and 5 suppressed ConA-induced or LPS-induced splenocyte proliferation in a concentration-dependent manner. The CC50/IC50 values of 2, 4, and 5 suggested that these compounds were potential immunosuppressive agents for the treatment of autoimmune diseases characterized by arthritis, such as rheumatoid arthritis.