Safety assessment of tranexamic acid: real-world adverse event analysis from the FAERS database.

Background: In recent years, with the continuous expansion of the application scope of Tranexamic acid (TXA), its usage has surged. Despite numerous studies demonstrating its powerful efficacy, concerns regarding its adverse reactions persist, necessitating comprehensive safety assessment. This study analyzed real-world data from the U.S. Food and Drug Administration to investigate TXA-related adverse events, aiming to elucidate its safety and optimize patient treatment. Methods: The adverse drug event data concerning TXA from 2004 Q1 to 2023 Q3 were collected. Following data standardization, a variety of signal quantification techniques, including the reporting odds ratios, proportional reporting ratios, Bayesian confidence propagation neural network, and empirical Bayes geometric mean were used for analysis. Results: After analyzing 16,692,026 adverse event reports, a total of 1,574 cases of adverse events related to TXA were identified, spanning 23 system organ classes and 307 preferred terms. In addition to the common thrombosis-related Vascular disorders (n = 386) and Cardiac disorders (n = 377), adverse reactions in the Nervous system disorders category were also observed (n = 785), including Myoclonus (n = 70), Status epilepticus (n = 43), and Myoclonic epilepsy (n = 17). Furthermore, this study uncovered adverse effects such as Renal cortical necrosis, Hepatic cyst rupture, and Vascular stent stenosis, which were not previously mentioned in the instructions. Although these occurred infrequently, they exhibited high signal strength. Both Retinal artery occlusion and Vascular stent thrombosis disorder were frequent and exhibited high signal strength as well. It is worth noting that 78 cases of adverse reactions were caused by confusion between incorrect product administration. Conclusion: Our research suggests that TXA has some adverse reactions that are being overlooked. As a cornerstone medication in hemorrhage treatment, it's crucial to monitor, identify, and address these adverse reactions effectively.

Astrocyte-mediated regulation of BLAWFS1 neurons alleviates risk-assessment deficits in DISC1-N mice.

Assessing and responding to threats is vital in everyday life. Unfortunately, many mental illnesses involve impaired risk assessment, affecting patients, families, and society. The brain processes behind these behaviors are not well understood. We developed a transgenic mouse model (disrupted-in-schizophrenia 1 [DISC1]-N) with a disrupted avoidance response in risky settings. Our study utilized single-nucleus RNA sequencing and path-clamp coupling with real-time RT-PCR to uncover a previously undescribed group of glutamatergic neurons in the basolateral amygdala (BLA) marked by Wolfram syndrome 1 (WFS1) expression, whose activity is modulated by adjacent astrocytes. These neurons in DISC1-N mice exhibited diminished firing ability and impaired communication with the astrocytes. Remarkably, optogenetic activation of these astrocytes reinstated neuronal excitability via D-serine acting on BLAWFS1 neurons' NMDA receptors, leading to improved risk-assessment behavior in the DISC1-N mice. Our findings point to BLA astrocytes as a promising target for treating risk-assessment dysfunctions in mental disorders.

Preliminary risk assessment of in-vessel leakage accident in ITER.

The ITER project is one of the largest international cooperative scientific projects in the world, aiming to verify the feasibility of magnetic confinement controlled nuclear fusion technology and provide a technical basis for the subsequent construction of fusion energy power stations. The success or failure of ITER will greatly affect the commercialization process of fusion energy. The probabilistic safety assessment (PSA) was a powerful means to evaluate the risk and reliability of nuclear facility and achieved great success in safety assessment of fission power plants. Based on this, the PSA progress for ITER was proposed in this paper. And the in-vessel leakage accident was investigated to verify the effectiveness of proposed method. The result shows the maximum possible radiological consequences of ITER in-vessel leakage accident of ITER is 1.6E-3 mSv, and the frequencies of this consequence is 1.63E-8/year. The reason of this consequence was also discussed in this paper. Those result could provide some valuable reference for radiation risk assessment and safety supervision of fusion commercial reactor in the nuclear future.

A Tutorial on Net Benefit Regression for Real-World Cost-Effectiveness Analysis Using Censored Data from Randomized or Observational Studies.

HIGHLIGHTS: We illustrate the steps involved in carrying out cost-effectiveness analysis using net benefit regressions with possibly censored demo data by providing step-by-step guidance and code applied to a data set.We demonstrate the importance of these new methods by illustrating how naïve methods for handling censoring can lead to biased cost-effectiveness results.

How does transition finance influence green innovation of high-polluting and high-energy-consuming enterprises? Evidence from China.

Under the impact of "double-carbon" target, transition finance has an important impact on green innovation of Chinese double-high enterprises. Using a sample of 4270 high-polluting and high-energy-consumption listed enterprises (referred to as double-high enterprises) in China from 2012 to 2021, this paper empirically examines the impact of transition finance on the green innovation of China's double-high enterprises by using a fixed-effects model. The study finds that transition finance can have a facilitating effect on green innovation in double-high enterprises. The intermediary mechanism test shows that transition finance can promote green innovation of double-high enterprises through alleviating financing constraints, increasing the level of green management, and enhancing the policy orientation effect. The heterogeneity test finds that transition finance promotes green innovation more significantly for the double-high enterprises that are state-owned, large-scale, and located in regions with high levels of intellectual property protection. Further research finds that the role of transition finance in promoting green innovation in double-high enterprises helps to promote the achievement of green development of double-high enterprises.

Preclinical assessment of IL-1ß primed human umbilical cord mesenchymal stem cells for tendon functional repair through TGF-ß/IL-10 signaling.

Background: Inadequate repair capacity and disturbed immune compartments are the main pathological causes of tendinopathy. Transplantation of mesenchymal stem cells (MSCs) become an effective clinic option to alleviate tendinopathy. Interleukin-1ß (IL-1ß) could confer on MSCs enhanced immunoregulatory capability to remodel the repair microenvironment favoring tissue repair. Therefore, IL-1ß activated UC-MSCs (1ßUC-MSCs) may exert favorable efficacy in promoting tendon repair in a preclinical tendinopathy rat model. Methods: Tendon-derived stem cells (TDSCs) were isolated and characterized. In vitro, the levels of immunoregulatory-related cytokines such as IL-1ß, IL-6, IL-10, and TGF-ß secreted by 1ßUC-MSCs and unprimed UC-MSCs was measured. And tendon-specific markers expressed by TDSCs cultured with primed cultured medium (CM) or unprimed CM were detected. In vivo, Achilles tendinopathy was induced by 30 µL collagenase I injection in Sprague Dawley rats. One week later, the rats were randomly injected with UC-MSCs primed with IL-1ß (106 cells per tendon), UC-MSCs, or PBS. After rats were sacrificed, histological evaluation, electron microscopy, biomechanical tests, gait performance were conducted to evaluate the structural and functional recovery of Achilles tendons. The inflammation and metabolic state of the extracellular matrix, and the potential mechanism were assessed by immunohistochemical staining and Western blot. Results: UC-MSCs were activated by IL-1ß to secrete higher levels of IL-10 and TGF-ß while the secretion levels of IL-6 and IL-1ß were not changed significantly, promoting a higher expression level of COL I and TNMD in TDSCs under proinflammatory environment. In vivo, the transplanted 1ßUC-MSCs could survive up to 5 weeks after injection with tenogenic differentiation and improved tendon healing histologically semi-quantified by modified Bonar scores. This structural regeneration was further confirmed by observation of ultrastructural morphology, and led to good functional recovery including improved biomechanical properties and gait performance. During this process, the inflammatory response and metabolism of the extracellular matrix was improved through TGF-ß/IL-10 pathway. Conclusion: This study demonstrated that the transplantation of UC-MSCs activated by IL-1ß exhibited satisfactory ability for promoting tendon functional repair in a tendinopathy rat model. During this process, the balance of inflammatory response and extracellular matrix metabolism was remodeled, and the TGF-ß/Smad2/3 and IL-10 signaling pathways were activated simultaneously. We cautiously conclude that the IL-1ß primed UC-MSCs could be a promising strategy for enhancing the ability of MSCs to treat tendinopathy.

Assessment of causal effects of physical activity on the risk of osteoarthritis: a two-sample Mendelian randomization study.

BACKGROUND: Growing evidence supports an association between physical activity (PA) and the risk of osteoarthritis (OA), but this may be influenced by confounding and reverse causality. Therefore, we performed a two-sample Mendelian randomization (MR) analysis to reveal the causal relationship between PA and OA. METHODS: MR was performed to explore the causation of PA and OA with genetic variants as instrumental variables. The genetic variants were derived from the summary statistics of a large genome-wide association study meta-analysis based on the European population (n = 661,399), including self-reported leisure screen time (LST) and moderate-to-vigorous physical activity (MVPA), and Arthritis Research UK Osteoarthritis Genetics Consortium cohorts (417,596, 393,873 and 403,124 for overall, hip and knee OA, respectively). The major MR analysis used in this work was the inverse variance weighted (IVW) approach, and sensitivity, pleiotropy, and heterogeneity studies were performed to evaluate the validity of the findings. RESULTS: IVW estimates indicated that LST had a risk effect on overall OA (odds ratio (OR) = 1.309, 95% confidence interval (CI): 1.198-1.430, P = 2.330 × 10-9), hip OA (OR = 1.132, 95% CI: 1.009-1.269, P = 0.034) and knee OA (OR = 1.435. 95% CI: 1.286-1.602, P = 1.225 × 10-10). In contrast, no causal relationship was found between MVPA and OA (overall OA: OR = 0.895, 95% CI: 0.664-1.205, P = 0.465; hip OA: OR = 1.189, 95% CI: 0.792-1.786, P = 0.404; knee OA: OR = 0.707, 95% CI: 0.490 -1.021, P = 0.064). In addition, we observed significant heterogeneity in instrumental variables, but no horizontal pleiotropy was detected. CONCLUSIONS: Recent findings demonstrated a protective impact of reducing LST on OA, independent of MVPA. This provides valuable insights into the role of physical activity in OA and offers lifestyle recommendations, such as reducing recreational sedentary behaviors and promoting appropriate exercise, for individuals at risk of OA.

How does green finance affect the innovation performance of enterprises? Evidence from China.

"green" + "innovation" has become a new concept of development. The integration of the two can bring win-win for the environment and economy. This paper selects the annual data of 14309 A-share companies in Shanghai and Shenzhen Stock Exchange from 2012 to 2020 as the research sample. And it uses the two-way fixed effect model to empirically test the impact of green finance on enterprise innovation performance. The study found that the development of green finance can promote the improvement of enterprise innovation performance. The analysis of influence mechanism shows that the development of green finance can reduce the financing constraints of enterprises, and then improve the innovation performance of enterprises; the development of green finance can increase the R&D investment of enterprises, and then improve the innovation performance of enterprises; green finance development can increase corporate investment in environmental protection, which in turn can improve corporate innovation performance. The results of heterogeneity test analysis show that compared with the western region, private enterprises, small and medium-sized enterprises, and high energy consumption and high pollution enterprises, the development of green finance in the central and eastern regions, state-owned enterprises, large enterprises, and non double high enterprises has more obvious role in promoting enterprise innovation performance. Therefore, the government should issue relevant policies and actively promote green finance policies that can help improve environmental and economic issues.

Comprehensively evaluate the short outcome of small bowel obstruction: A novel medical-economic score system.

BACKGROUND: Small bowel obstruction (SBO) still imposes a substantial burden on the health care system. Traditional evaluation systems for SBO outcomes only focus on a single element. The comprehensive evaluation of outcomes for patients with SBO remains poorly studied. Early intensive clinical care would effectively improve the short-term outcomes for SBO, however, the full spectrum of the potential risk status regarding the high complication-cost burden is undetermined. AIM: We aim to construct a novel system for the evaluation of SBO outcomes and the identification of potential risk status. METHODS: Patients who were diagnosed with SBO were enrolled and stratified into the simple SBO (SiBO) group and the strangulated SBO (StBO) group. A principal component (PC) analysis was applied for data simplification and the extraction of patient characteristics, followed by separation of the high PC score group and the low PC score group. We identified independent risk status on admission via a binary logistic regression and then constructed predictive models for worsened management outcomes. Receiver operating characteristic curves were drawn, and the areas under the curve (AUCs) were calculated to assess the effectiveness of the predictive models. RESULTS: Of the 281 patients, 45 patients (16.0%) were found to have StBO, whereas 236 patients (84.0%) had SiBO. Regarding standardized length of stay (LOS), total hospital cost and the presence of severe adverse events (SAEs), a novel principal component was extracted (PC score = 0.429 × LOS + 0.444 × total hospital cost + 0.291 × SAE). In the multivariate analysis, risk statuses related to poor results for SiBO patients, including a low lymphocyte to monocyte ratio (OR = 0.656), radiological features of a lack of small bowel feces signs (OR = 0.316) and mural thickening (OR = 1.338), were identified as risk factors. For the StBO group, higher BUN levels (OR = 1.478) and lower lymphocytes levels (OR = 0.071) were observed. The AUCs of the predictive models for poor outcomes were 0.715 (95%CI: 0.635-0.795) and 0.874 (95%CI: 0.762-0.986) for SiBO and StBO stratification, respectively. CONCLUSION: The novel PC indicator provided a comprehensive scoring system for evaluating SBO outcomes on the foundation of complication-cost burden. According to the relative risk factors, early tailored intervention would improve the short-term outcomes.

Exploring the global geography of cybercrime and its driving forces.

Cybercrime is wreaking havoc on the global economy, national security, social stability, and individual interests. The current efforts to mitigate cybercrime threats are primarily focused on technical measures. This study considers cybercrime as a social phenomenon and constructs a theoretical framework that integrates the social, economic, political, technological, and cybersecurity factors that influence cybercrime. The FireHOL IP blocklist, a novel cybersecurity data set, is used to map worldwide subnational cybercrimes. Generalised linear models (GLMs) are used to identify the primary factors influencing cybercrime, whereas structural equation modelling (SEM) is used to estimate the direct and indirect effects of various factors on cybercrime. The GLM results suggest that the inclusion of a broad set of socioeconomic factors can significantly improve the model's explanatory power, and cybercrime is closely associated with socioeconomic development, while their effects on cybercrime differ by income level. Additionally, results from SEM further reveals the causal relationships between cybercrime and numerous contextual factors, demonstrating that technological factors serve as a mediator between socioeconomic conditions and cybercrime.

Environmental Pollution Liability Insurance Pricing and the Solvency of Insurance Companies in China: Based on the Black-Scholes Model.

Environmental pollution liability insurance is becoming increasingly important for China to achieve its emission reduction targets. Insurance pricing is a crucial factor restricting the market share of environment pollution liability insurance, from the perspective of the Black-Scholes pricing model, which in turn has influenced the solvency of insurance companies in China. Firstly, this study analyzes the problems existing in compulsory liability insurance for environmental pollution in China. It proceeds with analyzing the price of compulsory environmental pollution liability insurance using the Black-Scholes pricing model, and derives a high premium insurance rate of 2.44%. Moreover, it performs a multivariate regression analysis using the asset and liability data, taken from the annual report, to identify three key factors affecting the solvency adequacy ratio, namely, capital debt ratio, reflecting the company asset structure; net interest rate on assets, reflecting the asset scale with actual solvency; and claim ratio, reflecting the business quality. Based on the results of regression analysis and robustness test for the China Insurance Clauses (CIC) company, People's Insurance Company of China (PICC), and Asia-Pacific Property & Casualty Insurance (API) company, it is shown that the effect of total asset, total debt, capital debt ratio, claim ratio, and net interest rate on assets on the solvency adequacy ratio is significant, with respect to the size of the coefficients. Based on the Black-Scholes pricing model found in the previous cycle of liability insurance, and keeping in view the existing problems of environmental pollution liability insurance expenditure, this paper presents suggestions that are conducive to improving the solvency of insurance companies in China.

Identifying carbon emission characteristics and carbon peak in China based on the perspective of regional clusters.

Global warming has endangered the natural ecosystem's balance, as well as human existence and development, and it is mostly caused by carbon dioxide. Identifying carbon emission characteristics and predicting carbon emission reasonably is helpful to provide indication for the effective design of emission reduction path. The most literature use a single prediction model; this paper predicts carbon emission using a number of strategies based on previous research. Considering the prediction accuracy, advantages, and disadvantages of each method, a new method combining autoregressive integrated moving average (ARIMA) model and NAR neural network (NAR-NN) is proposed; in addition, this paper attempts to explain the carbon emission characteristics and emission reduction paths of each region from the new perspective of clustering. First, the results show that China's carbon emission features can be divided into four categories: low-carbon demonstrative type, low-carbon potential type, high-carbon developed type, and high-carbon traditional type. Moreover, low-carbon demonstrative type includes merely Beijing and Shanghai, low-carbon potential type is distributed in the southeast coastal areas of China, the high-carbon developed type is mainly distributed in Northeast China, and the western region basically belongs to high-carbon traditional type. Second, ARIMA model and NAR-NN are the two best methods in terms of prediction effect, and the combined model has better prediction effect than the single model. Third, carbon emissions in most regions of China will increase in the next few years; the time of carbon peak in the east is earlier than that in the west regions of China. Beijing will probably be the first region in China to complete the carbon peak. Besides, there is a certain correlation between the carbon peak time and the type of carbon emission in each region.

Sonographic Assessment of Acute Versus Chronic Cholecystitis: An Ultrasound Probability Stratification Model.

OBJECTIVES: What sonographic variables are most predictive for acute cholecystitis? What variables differentiate acute and chronic cholecystitis? METHODS: The surgical pathology database was reviewed to identify adult patients who underwent cholecystectomy for cholecystitis and had a preceding ultrasound of the right upper quadrant within 7 days. A total of 236 patients were included in the study. A comprehensive imaging review was performed to assess for gallstones, gallbladder wall thickening, gallbladder distension, pericholecystic fluid, gallstone mobility, the sonographic Murphy's sign, mural hyperemia, and the common hepatic artery peak systolic velocity. RESULTS: Of 236 patients with a cholecystectomy, 119 had acute cholecystitis and 117 had chronic cholecystitis on surgical pathology. Statistical models were created for prediction. The simple model consists of three sonographic variables and has a sensitivity of 60% and specificity of 83% in predicting acute versus chronic cholecystitis. The most predictive variables for acute cholecystitis were elevated common hepatic artery peak systolic velocity, gallbladder distension, and gallbladder mural abnormalities. If a patient had all three of these findings on their preoperative ultrasound, the patient had a 96% chance of having acute cholecystitis. Two of these variables gave a 73-93% chance of having acute cholecystitis. One of the three variables gave a 40-76% chance of having acute cholecystitis. If the patient had 0 of 3 of the predictor variables, there was a 29% chance of having acute cholecystitis. CONCLUSIONS: Gallbladder distension, gallbladder mural abnormalities, and elevated common hepatic artery peak systolic velocity are the most important sonographic variables in predicting acute versus chronic cholecystitis.

Net-benefit regression with censored cost-effectiveness data from randomized or observational studies.

Cost-effectiveness analysis is an essential part of the evaluation of new medical interventions. While in many studies both costs and effectiveness (eg, survival time) are censored, standard survival analysis techniques are often invalid due to the induced dependent censoring problem. We propose methods for censored cost-effectiveness data using the net-benefit regression framework, which allow covariate-adjustment and subgroup identification when comparing two intervention groups. The methods provide a straightforward way to construct cost-effectiveness acceptability curves with censored data. We also propose a more efficient doubly robust estimator of average causal incremental net benefit, which increases the likelihood that the results will represent a valid inference in observational studies. Lastly, we conduct extensive numerical studies to examine the finite-sample performance of the proposed methods, and illustrate the proposed methods with a real data example using both survival time and quality-adjusted survival time as the measures of effectiveness.

Evaluation and dynamic prediction of ecological security from the perspective of sustainable development: a case study of Shaanxi Province, China.

How to measure the overall level of regional social economy, resources, and environment and how to grasp the coordinated development between them has become a hot issue. In this paper, the driving force-pressure-state-response (DPSR) model is used to build an ecological security index (ESI) system to measure the overall ecological security level of social economy, resources, and environment. In addition, dynamic nonlinear auto regressive (NAR) neural network is used to predict the ESI level to achieve the purpose of early warning. First, the results show that the weight of the employment rate, the proportion of students in colleges, and the per capita consumption level are relatively high, which play an important role for the ecological security level of Shaanxi Province. Second, Xi'an City has been the best level in ecological security level, the ecological security of Southwest Shaanxi is relatively good, which is related to its economic development and comparative advantage geographical conditions, while the ecological security level of Weinan and Shangluo are poor. Third, the ESI of most cities in Shaanxi Province is maintained at grade III. The ESI in Shaanxi has an upward trend from 2000 to 2006; however, the trend of this increase has not been maintained, and nearly half of the cities in Shaanxi have slightly decreased the ecological security level. Four, the ESI of Xi'an and Hanzhong will remain at a high level in the future, while the ecological security situation of Shangluo, Weinan, and Yulin probably become very poor in the next years.

Mental health effects of same-sex marriage legalization.

Same-sex marriage legalization (SSML) is a typical anti-discrimination policy to remove institutional discrimination against sexual minorities by providing them with marriage equality. We examine how this legalization in the Netherlands affected mental health. Conducting a difference-in-differences analysis with heterosexual individuals as a reference group, we find that SSML significantly improved mental health of sexual minorities and substantially reduced the sexual orientation gap of mental health. The beneficial effects were present for both married and non-married sexual minorities. This phenomenon suggests that part of the health gains were related to mechanisms beyond marriage itself.

Preclinical assessment on neuronal regeneration in the injury-related microenvironment of graphene-based scaffolds.

As the application of graphene nanomaterials gets increasingly attractive in the field of tissue engineering and regenerative medicine, the long-term evaluation is necessary and urgent as to their biocompatibility and regenerative capacity in different tissue injuries, such as nerve, bone, and heart. However, it still remains controversial about the potential biological effects of graphene on neuronal activity, especially after severe nerve injuries. In this study, we establish a lengthy peripheral nerve defect rat model and investigate the potential toxicity of layered graphene-loaded polycaprolactone scaffold after implantation during 18 months in vivo. In addition, we further identify possible biologically regenerative effects of this scaffold on myelination, axonal outgrowth, and locomotor function recovery. It is confirmed that graphene-based nanomaterials exert negligible toxicity and repair large nerve defects by dual regulation of Schwann cells and astroglia in the central and peripheral nervous systems. The findings enlighten the future of graphene nanomaterial as a key type of biomaterials for clinical translation in neuronal regeneration.

Comfort Level of US Radiation Oncology Graduates: Assessment of Transition to Independent Clinical Practice.

Radiation training programs are designed to prepare graduates for independent practice, with metrics in place to assess appropriateness of clinical decision-making. Here, we investigated the self-assessed preparedness of US graduates during the transition to independent practice.An anonymous, Internet-based survey was distributed to recent graduates of radiation oncology residencies (2016-2017). A Likert scale was used to assess comfort with various aspects of practice, as well as "time" to development of comfort in independent practice.Responses were obtained from 70/210 (33%), the majority reported training in programs with 5-8 residents (n = 35). Most (77%) reported designing between 500 and 900 treatment plans during training (n = 54). Only 41% of respondents reported the opportunity to review treatment plans and make decisions about safety/adequacy without attending input > 50% of the time (n = 29). Thirty percent of residents reported being responsible for seeing/managing on-treatment visits (OTVs) ≤ 75% of the time. Aspects with which practitioners reported the least comfort were understanding of billing/application to practice (2.43, IQR 2-3), orthovoltage (superficial radiation) setup and field design (2.57, IQR 1-4), and planning/delivery of prostate implants (2.82, IQR 2-4). Increased mean comfort levels were reported by those designing > 700 treatment plans in training as well as those reporting an opportunity to evaluate plans and make clinical decisions prior to attending input > 50% of the time during residency. Comfort with the delivery of stereotactic body radiation (SBRT) correlated with caseload for liver, spine, prostate, and CNS disease sites but not lung.Variations in training experiences exist across institutions. Here, a lower than expected number of residents reported seeing/managing OTVs as well as reviewing treatment plans prior to attending input during training. Overall comfort was correlated with case volume and opportunities to independently review treatment plans prior to attending input. These data highlight areas of opportunity for improving resident education with implications for ease of transition to independent clinical practice.

Simulating the Linkages Between Economy and Armed Conflict in India With a Long Short-Term Memory Algorithm.

This article analyzes the linkages between the economy and armed conflict in India using annual frequency data for the period 1989-2016, the maximum time period for which consistent data are available for the country. An adequate set of economic indicators was established to fully reflect the economic condition. Long short-term memory (LSTM), which is a machine-learning algorithm for time series, was employed to simulate the relationship between the economy and armed conflict events. In addition, LSTM was applied to predict the trend of armed conflict with two strategies: multiyear predictions and yearly predictions. The results show that both strategies can adequately simulate the relationship between the economy and armed conflict, with all simulation accuracies above 90%. The accuracy of the yearly prediction is higher than that of the multiyear prediction. Theoretically, the future state and trend of armed conflict can be predicted with LSTM and future economic data if future economic data can be predicted.