Phillygenin Attenuated Colon Inflammation and Improved Intestinal Mucosal Barrier in DSS-induced Colitis Mice via TLR4/Src Mediated MAPK and NF-κB Signaling Pathways.

Ulcerative colitis (UC) is a chronic, relapsing, and nonspecific inflammatory bowel disease (IBD). Phillygenin (PHI), a natural bioactive ingredient, isolated from Forsythiae Fructus, exhibits anti-inflammatory, anti-oxidative, and hepatoprotective activities. However, few reports provide direct evidence on the efficacy of PHI in improving colitis mice. The present study elucidated that the symptoms of DSS-induced colitis mice were alleviated after PHI administration, including body weight loss, the disease activity index, colon length shortening, colonic pathological damage, splenomegaly, and hepatomegaly. PHI treatment improved the intestinal mucosal barrier by protecting goblet cells, promoting gene expressions of Clca1, Slc26a3, and Aqp8, increasing tight junction proteins (TJs), and reducing epithelial cell apoptosis. In addition, the levels of oxidative stress (MPO, SOD, and MDA) and inflammatory cytokines (TNF-α, IL-1ß, IL-6, and IL-10) were reversed by PHI in colitis mice. According to transcriptome and network pharmacology analysis, inflammatory pathway might be an important mechanism for PHI to improve colitis. Western blotting displayed that the PHI inhibited the activation of tyrosine kinase Src mediated by TLR4, and then reduced the phosphorylation of downstream proteins p38, JNK, and NF-κB in colitis mice. In summary, our results suggested that PHI might be an appropriate and effective drug candidate to protect colitis.

Anthraquinone derivative C10 inhibits proliferation and cell cycle progression in colon cancer cells via the Jak2/Stat3 signaling pathway.

Since its discovery, anthraquinone has become very valuable as a lead compound in the development of anti-cancer drugs. Previously, we designed and synthesized a new type of amide anthraquinone derivative (1-nitro-2-acylanthraquinone glycine, C10) with good activity against colon cancer. However, its effect and the underlying mechanism are unclear. In this study, C10 significantly inhibited the proliferation of HCT116 and HT29 colon cancer cells by blocking the cell cycle at the G2/M phase. C10 also plays a role in cell cycle arrest by reducing the protein and gene expression levels of cyclin B1 and its downstream signaling molecule cyclin-dependent kinase (CDK1). In addition, molecular docking studies showed that C10 has high affinity for Jak2, the first target in the cell cycle-related Jak2/Stat3 signaling pathway. Furthermore, C10 downregulated the expression of Jak2/Stat3 signaling pathway-related signaling molecules proteins and genes, and up-regulated the expression of PIAS-3, the upstream signaling molecule of Stat3, thereby down-regulating Stat3 phosphorylation. C10 reversed the expression of Jak2/Stat3 signaling pathway-related molecules activated by IL-6. Overall, our results indicate for the first time that C10 induces cell cycle arrest and inhibits cell proliferation by inhibiting the Jak2/Stat3 signaling pathway. This study provides new insights into the potential role of Jak2/Stat3 in the regulating cell cycle-related signaling pathways that mediate the inhibitory effects of C10 on colon cancer cell proliferation.

Design, Synthesis, Molecular Docking, and Biological Evaluation of New Emodin Anthraquinone Derivatives as Potential Antitumor Substances.

The emodin anthraquinone derivatives are generally used in traditional Chinese medicine due to their various pharmacological activities. In the present study, a series of emodin anthraquinone derivatives have been designed and synthesized, among which 1,3-dihydroxy-6,8-dimethoxyanthracene-9,10-dione is a natural compound that has been synthesized for the very first time, and 1,3-dimethoxy-5,8-dimethylanthracene-9,10-dione is a compound that has never been reported earlier. Interestingly, while total seven of these compounds showed neuraminidase inhibitory activity in influenza virus with inhibition rate more than 50 %, specific four compounds exhibited significant inhibition of tumor cell proliferation. The further results demonstrate that 1,3-dimethoxy-5,8-dimethylanthracene-9,10-dione showed the best anticancer activity among all the synthesized compounds by inducing highest apoptosis rate to HCT116 cancer cells and arresting their G0/G1 cell cycle phase, through elevation of intracellular level of reactive oxygen species (ROS). Moreover, the binding of 1,3-dimethoxy-5,8-dimethylanthracene-9,10-dione with BSA protein has thoroughly been investigated. Altogether, this study suggests the neuraminidase inhibitory activity and antitumor potential of the new emodin anthraquinone derivatives.

Novel Anthraquinone Compounds Inhibit Colon Cancer Cell Proliferation via the Reactive Oxygen Species/JNK Pathway.

A series of amide anthraquinone derivatives, an important component of some traditional Chinese medicines, were structurally modified and the resulting antitumor activities were evaluated. The compounds showed potent anti-proliferative activities against eight human cancer cell lines, with no noticeable cytotoxicity towards normal cells. Among the candidate compounds, 1-nitro-2-acyl anthraquinone-leucine (8a) showed the greatest inhibition of HCT116 cell activity with an IC50 of 17.80 µg/mL. In addition, a correlation model was established in a three-dimensional quantitative structure-activity relationship (3D-QSAR) study using Comparative Molecular Field Analysis (CoMFA) and comparative molecular similarity index analysis (CoMSIA). Moreover, compound 8a effectively killed tumor cells by reactive oxygen species (ROS)-JNK activation, causing an increase in ROS levels, JNK phosphorylation, and mitochondrial stress. Cytochrome c was then released into cytoplasm, which, in turn activated the cysteine protease pathway and ultimately induced tumor cell apoptosis, suggesting a potential use of this compound for colon cancer treatment.

[Screening, identification and activity evaluation of pancreatic lipase inhibition in Prunella vulgaris].

Pancreatic lipase (PL) inhibitors were firstly screened from Prunella vulgaris with PL immobilized on carboxylic acid-terminated magnetic nanoparticles, then these possible inhibitors were identified by LC-MS/MS and mixed standards. Finally, their inhibitory effects and types on PL were tested by p-nitrophenol method. The results showed that four PL inhibitors were screened out from P. vulgaris and confirmed by LC-MS/MS and mixed standards. The IC58 and inhibition types were as follows: caffeic acid [(252.3±3.6) mg·L⁻¹, anti-competitive inhibition], rutin [(91.2±1.6)mg·L⁻¹, competitive inhibition], hesperidin [(31.5±4.4) mg·L⁻¹, competitive inhibition] and ursolic acid [(41.3±2.2) mg·L⁻¹, competitive inhibition]. Their inhibitive types and abilities on PL were related to their molecular size, hydrophobicity and the number of hydrogen bond with PL triplet.

Nine Different Chemical Species and Action Mechanisms of Pancreatic Lipase Ligands Screened Out from Forsythia suspensa Leaves All at One Time.

It is difficult to screen out as many active components as possible from natural plants all at one time. In this study, subfractions of Forsythia suspensa leaves were firstly prepared; then, their inhibitive abilities on pancreatic lipase were tested; finally, the highest inhibiting subfraction was screened by self-made immobilized pancreatic lipase. Results showed that nine ligands, including eight inhibitors and one promotor, were screened out all at one time. They were three flavonoids (rutin, IC50: 149 ± 6.0 µmol/L; hesperidin, 52.4 µmol/L; kaempferol-3-O-rutinoside, isolated from F. suspensa leaves for the first time, IC50 notably reached 2.9 ± 0.5 µmol/L), two polyphenols (chlorogenic acid, 3150 ± 120 µmol/L; caffeic acid, 1394 ± 52 µmol/L), two lignans (phillyrin, promoter; arctigenin, 2129 ± 10.5 µmol/L), and two phenethyl alcohol (forsythiaside A, 2155 ± 8.5 µmol/L; its isomer). Their action mechanisms included competitive inhibition, competitive promotion, noncompetitive inhibition, and uncompetitive inhibition. In sum, using the appropriate methods, more active ingredients can be simply and quickly screened out all at one time from a complex natural product system. In addition, F. suspensa leaves contain numerous inhibitors of pancreatic lipase.

Enhancing artificial bee colony algorithm with self-adaptive searching strategy and artificial immune network operators for global optimization.

Artificial bee colony (ABC) algorithm, inspired by the intelligent foraging behavior of honey bees, was proposed by Karaboga. It has been shown to be superior to some conventional intelligent algorithms such as genetic algorithm (GA), artificial colony optimization (ACO), and particle swarm optimization (PSO). However, the ABC still has some limitations. For example, ABC can easily get trapped in the local optimum when handing in functions that have a narrow curving valley, a high eccentric ellipse, or complex multimodal functions. As a result, we proposed an enhanced ABC algorithm called EABC by introducing self-adaptive searching strategy and artificial immune network operators to improve the exploitation and exploration. The simulation results tested on a suite of unimodal or multimodal benchmark functions illustrate that the EABC algorithm outperforms ACO, PSO, and the basic ABC in most of the experiments.

Changes in online public opinions associated with various three-child supportive policies in China: Observational study using social media data over time.

BACKGROUND: According to the Seventh National Census, China's fertility rate is less than 1.5, marking a significant national issue with potential risks. To counter this low birth rate, the Chinese government has relaxed family planning policies and introduced supportive measures. PURPOSE: Changes in birth policy have attracted considerable attention from the people of China. This article aims to study the public's response to the three-child support policy using Weibo as a window. The goal is to provide a more balanced evaluation of current perspectives, enabling policymakers to formulate better fertility information, particularly when anticipating a poor public response to controversial policies. METHODOLOGY: This research uses a crawler to gather data from Sina Weibo. Through opinion mining of Weibo posts on the three-child policy, Weibo users' online opinions on the three-child policy are analyzed from two perspectives: their attention content and sentiment tendency. Using an interrupted time series, it examines changes in online views on the policy, matching policy documents to the time nodes of Weibo posts. FINDINGS: The public has shown great interest in and provided short-term positive feedback on policies related to improving maternity insurance, birth rewards, and housing subsidies. In contrast, there has been a continuous negative response to policies such as extending maternity leave, which has particularly sparked concerns among women regarding future employment and marital rights protection. On social media, the public's attention to the three-child birth policy has focused mainly on the protection of women's rights, especially legal rights after childbirth, and issues related to physical and mental health. Child-rearing support and economic pressure are also hot topics, involving the daily expenses of multichild families, childcare services, and housing pressure. However, this study also revealed that infertile or single women express a strong desire to have children, but due to limitations in the personal medical insurance system, this desire has not been fully satisfied. CONTRIBUTIONS: Our study demonstrates the feasibility of a rapid and flexible method for evaluating the public response to various three-child supportive policies in China using near real-time social media data. This information can help policy makers anticipate public responses to future pandemic three-child policies and ensure that adequate resources are dedicated to addressing increases in negative sentiment and levels of disagreement in the face of scientifically informed but controversial, restrictions.

Evaluation of China's live streaming e-commerce industry policies based on a three-dimensional analysis framework.

As an emerging business modality and Internet format, live streaming e-commerce has developed rapidly since its emergence in 2016, especially since the outbreak of the COVID-19 epidemic in late 2019, when an increasing number of businesses from other industries attracted participation. However, with the development of the live streaming e-commerce industry, the industry's market environment is becoming increasingly chaotic. Therefore, during this period, government departments continuously formulate and implement relevant industry policies. In order to exploring the cooperation network structure, policy content distribution, and implementation effectiveness characteristics among publishers, this paper constructs a three-dimensional analysis framework of policy from the perspective of policy tools, policy effectiveness evaluation and policy publishers. The results show that in terms of policy tools, the overall structure of policy tools in the live streaming e-commerce industry is unreasonable, and different types of policy tools are significantly diverse. The proportion of environmental policy tools is greater than that of demand-based and supply-based policy tools, accounting for 62.97%, and among them, the tools related to industry regulation and management account for the largest proportion of the total, which greatly suppresses the enthusiasm of various entities in the industry for development. In terms of policy effectiveness evaluation, most of the policies do not formulate detailed long-, medium-, or short-term goals, nor are the policy priorities, incentive measures, or action modes perfect, indicating that the government's pushing and pulling forces for the live streaming e-commerce industry are insufficient. Finally, in the subject dimension of policy release, the synergy of relevant subjects is constantly improving, but there is also a phenomenon of over-concentration in the synergistic departments.

[Study on process conditions of Forsytiae Fructus].

OBJECTIVE: To study the effect of different processing methods on the content and biological activity of main chemical constituents of Forsytiae Fructus, in order to provide the basis for rational processing of Forsytiae Fructus. METHOD: The content of extracts was determined by the extract determination method of Chinese Pharmacopoeia. The effects of chemical constituents of Forsytiae Fructus under different processing conditions were compared by HPLC method. Furthermore, free radical scavenging DPPH method was used to assess the antioxidation effect, and the antibacterial effect of Forsytiae Fructus was evaluated according to the inhibition effect on staphylococcus aureus. RESULT: Considering various factors, the optimum boiling process is that adding six-fold water and boiling for 8 min. CONCLUSION: The content and activity of chemical constituents of Forsytiae Fructus are significantly different under different processing conditions.

Assessing the possibility of China reaching carbon emission peak by 2030 in the context of the COVID-19 pandemic.

At this stage, it is an important goal for China to solve environmental problems to limit the carbon emission peak by 2030 and then to lower its quality gradually thereafter. The outbreak of the COVID-19 pandemic in 2020 seriously impacted all aspects of China's social economy and brought many uncertainties to the realization of the carbon emission peak. Based on the fact, it has important theoretical and practical significance to take the problem of China's carbon emissions during the COVID-19 as the research object. Thus, this paper analyzes the current situation of China's CO2 emissions and finds out that in the context of ongoing COVID-19 response, stimulated by China's economic stimulus policies, CO2 emissions decrease firstly and then gradually rebound. On this basis, the paper constructs a dynamic model of China's CO2 emission system to simulate the change in China's CO2 emissions under different economic stimulus policies. The relevant simulation results demonstrate the following: (1) China cannot realize the CO2 emission goal by 2030 only by adopting traditional economic stimulus policies. (2) The green economic stimulus policy oriented to the development of clean energy will rebound China's CO2 emissions in the short term, but it can effectively reduce CO2 emissions in the long run. The most important factors affecting CO2 emission reduction are industrial energy consumption and industrial structure, while the energy power generation structure and the transportation structure have a relatively weak impact on the emission reduction effect. (3) The green economic stimulus policy combined with economic stimulus measures and a variety of low-carbon measures can enable China to peak CO2 emissions before 2030, with a peak value of 11.059 billion tons. In general, green economic stimulus policies can achieve a win-win situation for China's economic recovery and carbon emission peak.

Changes of people's fertility attitudes based on analysis of online public opinion on three-child policy in China.

In response to the population aging, on May 31, 2021, the Political Bureau of the Central Committee of the Communist Party of China (CPC) proposed the policy that a couple can have three children and rolled out more supportive measures to further optimize fertility policies, which is another major initiative following the universal two-child policy introduced in November 2015. Currently, a series of population policy innovations have aroused great attractions among the public and triggered a hot debating on the Internet. People's fertility attitude tendency under different related policies can reflect their current fertility intentions. Based on the fact, this paper firstly classifies the sentiment of online comment data on the three-child policy and analyzes people's sentiment tendency toward the three-child policy from the spatio-temporal perspectives. Secondly, people's points of view on the three-child policy are summarized by using Latent Dirichlet Allocation (LDA) thematic clustering. The reasons for the change in people's fertility attitude tendency under different fertility policies are analyzed by comparing the change in people's fertility attitude tendency with the change in people's attentions. Finally, a multiple regression equation is constructed to analyze the key factors influencing people's intention to have three children by using public opinion data and its extension data. The findings demonstrate: (1) people's fertility attitudes toward the three-child policy are negative and similar among different regions; (2) compared to the two-child policy, the percentage of negative and neutral attitudes toward the three-child policy increases, while the percentage of positive attitudes decreases; (3) the increase in fertility costs, the deterioration of women's employment environment, and the change in the concept of marriage and childbirth become important reasons for the negative change in people's fertility attitudes toward different policies. Therefore, the government should take measures to reduce the burden of childbirth and guide the correct concept of marriage and childbirth to improve people's fertility intentions.

The effect of customer satisfaction on floral product purchase behavior, evidence from Shanghai, China.

China's flower industry is developing rapidly, and the size of the retail market is increasing year by year. Studying the factors influencing residents' flower purchasing behavior and understanding their flower needs can help promote the sustainable development of the flower industry. Based on customer satisfaction theory, this paper uses 838 consumer research questionnaires from 15 districts in Shanghai to analyze the influence of customer satisfaction on residents' flower purchasing behavior by conducting a binary logit model and to investigate the moderating effect of flower purchasing purpose on the influence of satisfaction. The results show that price satisfaction and satisfaction with promotional methods have a significant negative effect on flower purchasing behavior, service satisfaction has a significant positive effect on purchasing behavior, and different customer purchase purposes lead to different intensities of the effect of satisfaction on purchasing behavior. According to the conclusion of the study, three countermeasures are proposed: to popularize the knowledge of flower culture, guide the concept of flower consumption, and promote the transformation of flower consumption to daily consumption; to conduct regular research on consumers by flower merchants to clarify consumers' needs and improve their satisfaction; to clarify consumers' purchase intention, increase the investment in the research and development and cultivation of flower products, and improve the supply level of flowers.

Consumers' purchase intention of wild freshwater fish during the COVID-19 pandemic.

The association between the COVID-19 pandemic and the wildlife trade in the seafood market in Wuhan has raised public concern regarding wildlife consumption and public health safety. Considering several coronavirus transmission incidents related to aquatic products and the location of wild freshwater fish in aquatic consumption in China, the effects of COVID-19 on the purchase intention of wild freshwater fish was investigated. Based on 1163 online questionnaires from eight provinces (including two province-level municipalities) in the Yangtze River Basin, ordered logistic regression was carried out to analyze the influencing factors of purchase intention of wild freshwater fish during the COVID-19 pandemic. The empirical results indicated that the COVID-19 pandemic had changed consumers' perceived risk and purchase frequency of wild freshwater fish. External stimulus caused by the COVID-19 pandemic had little influence on perceived risk and purchase intention. Consumer preference had a significant impact on perceived risk and purchase intention. Therefore, efforts should be put to strengthen the popularization of aquatic product knowledge, guide the public to develop scientific and civic eating habits, and improve the traceability system of aquatic products. [EconLit Citations: D12-Consumer Economics: Empirical Analysis, Q22-Fishery; Aquaculture].

Grounded Theory-Based User Needs Mining and Its Impact on APP Downloads: Exampled With WeChat APP.

Software development is an iterative process from designing to implementation, and to testing, in which product development staff should be closely integrated with users. Satisfying user needs effectively is often the pain point for developers. In order to alleviate this, this paper manages to establish the quantitative connection between users' online reviews and APP (Application Program) downloads. By analyzing user online comments, companies can dig out user needs and preferences. This could benefit them by making accurate market positioning of their APP products, and therefore iteratively innovating products based on user needs, which hopefully will increase the volume of APP downloads. This paper regards WeChat APP during 47 updates periods as the research object. Based on Grounded Theory, user needs are extracted after data cleaning. Next, by using semantic analysis and word frequency analysis, we are able to obtain the implicit feedbacks such as emotion tendency, satisfaction and requirements lie under online reviews. Then, we construct a quantile regression model to study the impact of users' online reviews on downloads based on the influencing factors we extracted so as to provide a decision basis for enterprises to iteratively update their products. Results show that: (1) Generally speaking, needs of WeChat users mainly focus on performance, reliability, usability, functional deficiency, functional insufficiency, and system adaptability; (2) For those APP versions with relatively fewer downloads, user needs are mostly about functional deficiency, followed by functional insufficiency, performance, usability, and system adaptability. At this stage, it is found out that users' emotion tendency and user satisfaction significantly affect the volume of downloads; (3) When the volume of APP downloads is moderate, the user needs are functional deficiency, functional insufficiency, and system adaptability. While under this circumstances, users' star ratings have a significant impact on downloads; (4) In addition, when the volume of App downloads is high, user needs are performance, usability, and system adaptability. Our methods effectively extract users' requirements from online reviews and then successfully build up the quantitative connection between the implicit feedbacks from those requirements and APP downloads.

Modeling Rumor Diffusion Process With the Consideration of Individual Heterogeneity: Take the Imported Food Safety Issue as an Example During the COVID-19 Pandemic.

At present, rumors appear frequently in social platforms. The rumor diffusion will cause a great impact on the network order and the stability of the society. So it's necessary to study the diffusion process and develop the rumor control strategies. This article integrates three heterogeneous factors into the SEIR model and designs an individual state transition mode at first. Secondly, based on the influencing factors such as the trust degree among individuals, an individual information interaction mode is constructed. Finally, an improved SEIR model named SEIR-OM model is established, and the diffusion process of rumors are simulated and analyzed. The results show that: (1) when the average value of the interest correlation is greater, the information content deviation is lower, but the rumor diffusion range will be wider. (2) The increase of the average network degree intensifies influence of rumors, but its impact on the diffusion has a peak. (3) Adopting strategies in advance can effectively reduce the influence of rumors. In addition, the government should enforce rumor-refuting strategies right after the event. Also, the number of rumor-refuting individuals must be paid attention to. Finally, the article verifies the rationality and effectiveness of the SEIR-OM model through the real case.

A Document Analysis of Peak Carbon Emissions and Carbon Neutrality Policies Based on a PMC Index Model in China.

With the commitment to peaking carbon emissions by 2030 and achieving carbon neutrality by 2060, the text analysis of policies related to peak carbon emissions and carbon neutrality has become a hot research topic in China. However, current domestic and foreign research mainly focuses on the impact and enlightenment of carbon emission measurement and other aspects and rarely optimizes the road to carbon neutrality through the analysis of policy texts. Based on both domestic and international research results, this paper takes 11 central government, ministry, province, and city policies as the research object, uses the PMC index model to calculate the PMC indices of the 11 representative documents, and draws surfaces. The results indicate that nearly half of the policies have excellent scores, but some policies still have deficiencies in terms of guarantee incentives and policy coverage. Given these shortcomings, this paper proposes that the government should provide technical assistance to industrial enterprises in addition to certain subsidies to reduce the energy consumption of enterprises in production and achieve sustainable development. While popularizing and developing low-carbon technology, enterprises should pay attention to personnel training and management, and use the digital economy to empower the transition to eco-friendly production. Based on the above research, the main contributions of this paper are as follows: to make theoretical and practical preparations for carbon neutralization and to provide suggestions for optimizing policies.

A revisit to the relationship between geothermal energy growth and underground water quality in EU economies.

This study's main goal is to evaluate how the research will look at the impact of geothermal energy production on the quality of the subterranean in the 27 European nations from 1990 to 2021. A considerable decline in the subterranean water supply can occur in EU14 emerging nations employing geothermal energy growth compared to EU13 emerging economies, according to research that uses the autoregressive distributed lag (ARDL). Fossil fuel use, population growth, and economic expansion are some factors that have a more detrimental effect on the subterranean water supply in EU14 emerging economies than in EU13 emerging nations. In contrast, the study's findings indicate that EU13 emerging nations may be better able to enhance their underground water supply than EU14 emerging economies because of more effective institutional qualities. The findings so indicate that increasing the amount of geothermal energy generation among the 27 European Union countries can accelerate subsurface water degradation at a high capacity and help achieve unionism's 2030 energy-related goals. When this is achieved, climate change will be put to check, as pollution of the environment. All calculations projected were seen to be of a good level of validity, and this is ascertained through three estimators considered in this study.

The Impacts of the COVID-19 Pandemic on Fertility Intentions of Women with Childbearing Age in China.

On 31 May 2021, the Political Bureau of the Central Committee of the Communist Party of China proposed the policy that a couple can have three children, and rolled out more supportive measures to further optimize the fertility policies. However, while the Chinese government is further optimizing its fertility policy, the sudden outbreak of COVID-19 is raging around the world, which threatens the implementation of China's fertility optimization policy. Based on this, this paper firstly explores the impact of COVID-19 on women's fertility intentions. Secondly, based on the Theory of Planned Behavior, this paper constructs a structural equation model to quantitatively reveal the specific factors that affect women's fertility intentions under the epidemic, as well as their impact paths, and then puts forward corresponding suggestions for the government to solve the problem of fertility, aiming at delaying population aging and optimizing population structure. The research results show that: (1) COVID-19 lowers the fertility intentions of women of childbearing age. (2) During the pandemic, economic pressure emerged as the biggest factor affecting women's fertility intentions. The decline in income caused by the pandemic has become an important factor in preventing women from having children. (3) The conflict between work and childbearing is still an important factor affecting the fertility intentions of women of childbearing age. The government's provision of perfect childcare services and their strengthening of the protection of women's employment rights and interests will greatly reduce women's anxiety about childbearing.

Identifying a New Social Intervention Model of Panic Buying Under Sudden Epidemic.

COVID-19 that broke out at the end of 2019 continues to spread globally, with frequent occurrence of variant disease strains, thus epidemic prevention and control become a kind of routine job. At present, due to the prevention and control measures such as maintaining social distance and community blockades, there is a boom in material purchases in many places, which not only seriously endangers social order and public environmental safety, but also easily leads to the interruption of the supply chain and the shortage of social materials. This article aims to study the intervention methods to curb the spread and spread of panic buying behavior. Firstly, through crawler technology and LDA (Latent Dirichlet Allocation) topic model, this article analyzes the intervention measures taken by various social forces in China to curb the spread of panic buying, and summarizes the multi-channel intervention measures including online and offline forms. Secondly, through the multi-Agent Monte Carlo method, the targeted intervention mechanism is supplemented in each propagation link of the panic buying propagation model, and a new social intervention model of panic buying under sudden epidemic is constructed. Then, through MATLAB modeling and simulation, the main factors affecting panic buying intervention are discussed. The simulation results show that: (1) The single plan with the best intervention effect is the supply monitoring. While the official response can play an immediate inhibitory effect, but it is affected by credibility and timeliness. The intervention effect of psychological counseling is limited, and it generally needs to be used in combination with other measures. (2) The combination strategy with the best intervention effect is "supply monitoring + official response + psychological counseling," and the worst is "information review and guidance + psychological counseling." Supply monitoring is a key measure to curb panic buying. At the same time, "information review and guidance" will have a certain counter-effect in the combined strategy. Finally, the effectiveness and universality of the proposed model are verified by examples of China and Britain.