Long-term prediction modeling of shallow rockburst with small dataset based on machine learning.

Rockburst present substantial hazards in both deep underground construction and shallow depths, underscoring the critical need for accurate prediction methods. This study addressed this need by collecting and analyzing 69 real datasets of rockburst occurring within a 500 m burial depth, which posed challenges due to the dataset's multi-categorized, unbalanced, and small nature. Through a rigorous comparison and screening process involving 11 machine learning algorithms and optimization with KMeansSMOKE oversampling, the Random Forest algorithm emerged as the most optimal choice. Efficient adjustment of hyper parameter was achieved using the Optuna framework. The resulting KMSORF model, which integrates KMeansSMOKE, Optuna, and Random Forest, demonstrated superior performance compared to mainstream models such as Gradient Boosting (GB), Extreme Gradient Boosting (XBG), and Extra Trees (ET). Application of the model in a tungsten mine and tunnel project showcased its ability to accurately forecast rockburst levels, thereby providing valuable insights for risk management in underground construction. Overall, this study contributes to the advancement of safety measures in underground construction by offering an effective predictive model for rockburst occurrences.

Oxide Scale Microstructure and Scale Growth Kinetics of the Hot-Pressed SiBCN-Ti Ceramics Oxidized at 1500 °C.

In this study, the SiBCN-Ti series ceramics with different Ti contents were fabricated, and the oxidation resistance and microstructural evolution of the ceramics at 1500 °C for different times were explored. The results show that with the increase in oxidation time, pores and bubbles are gradually formed in the oxide layer. When the oxidation time is less than or more than 4 h, the Ti(C, N) in the ceramics will maintain its initial structure or mostly transform to TiN. The introduction of Ti content can promote the formation of rutile silicate glass, thus healing the cracks and improving the oxidation resistance of the ceramics effectively.

A Machine-Learning-Assisted Crystalline Structure Prediction Framework To Accelerate Materials Discovery.

Modern crystal structure prediction methods based on structure generation algorithms and first-principles calculations play important roles in the design of new materials. However, the cost of these methods is very expensive because their success mostly relies on the efficient sampling of structures and the accurate evaluation of energies for those sampled structures. Herein, we develop a Machine-learning-Assisted CRYStalline Materials sAmpling sysTem (MAXMAT) aiming to accelerate the prediction of new crystal structures. For a given chemical composition, MAXMAT can generate efficient crystal structures with the help of a Python package for crystal structure generation (PyXtal) and can quickly evaluate the energies of these generated structures using a well-developed machine learning interaction potential model (M3GNET). We have used MAXMAT to perform crystal structure searches for three different chemical systems (TiO2, MgAl2O4, and BaBOF3) to test its accuracy and efficiency. Furthermore, we apply MAXMAT to predict new nonlinear optical materials, suggesting several thermodynamically synthesizable structures with high performance in LiZnGaS3 and CaBOF3 systems.

Prediction method of pharmacokinetic parameters of small molecule drugs based on GCN network model.

CONTEXT: Accurately predicting plasma protein binding rate (PPBR) and oral bioavailability (OBA) helps to better reveal the absorption and distribution of drugs in the human body and subsequent drug design. Although machine learning models have achieved good results in prediction accuracy, they often suffer from insufficient accuracy when dealing with data with irregular topological structures. METHODS: In view of this, this study proposes a pharmacokinetic parameter prediction framework based on graph convolutional networks (GCN), which predicts the PPBR and OBA of small molecule drugs. In the framework, GCN is first used to extract spatial feature information on the topological structure of drug molecules, in order to better learn node features and association information between nodes. Then, based on the principle of drug similarity, this study calculates the similarity between small molecule drugs, selects different thresholds to construct datasets, and establishes a prediction model centered on the GCN algorithm. The experimental results show that compared with traditional machine learning prediction models, the prediction model constructed based on the GCN method performs best on PPBR and OBA datasets with an inter-molecular similarity threshold of 0.25, with MAE of 0.155 and 0.167, respectively. In addition, in order to further improve the accuracy of the prediction model, GCN is combined with other algorithms. Compared to using a single GCN method, the distribution of the predicted values obtained by the combined model is highly consistent with the true values. In summary, this work provides a new method for improving the rate of early drug screening in the future.

Equilibrium bifurcation and extreme risk in the EU carbon futures market.

Considering the long-term memory and volatility clustering of the European Union (EU) Carbon Emission Allowances (EUA) futures returns, based on the economy-energy-environment system perspective and the assumption of investors' heterogeneity, this study proposes a joint modeling approach combining the fractionally integrated generalized autoregressive conditional heteroscedasticity model (FIGARCH) and the stochastic cusp catastrophe model (SCC) to examine the equilibrium bifurcations and extreme risks in the EU carbon futures market. The relevant results are threefold. (1) The SCC model has good fitting effect and interpretability, and is an effective method for investigating catastrophe reactions under time-varying volatility conditions. (2) In the EUA futures market, chartists are mainly affected by short-term price and trading volume changes, which leads to the emergence of equilibrium bifurcations, while fundamentalists make investment decisions based on the economy, the energy market, and market supply-demand, which affects the asymmetry of equilibrium bifurcations. (3) Using the catastrophe criterion (i.e., Cardan's discriminant of the equilibrium surface equation), we identify148 equilibrium bifurcation time points in the EUA futures market from December 3, 2009 to September 16, 2020, most of which are concentrated in two upward periods with an average scale of extreme risks is about 32.51 %. Our analysis provides theoretical support for regulatory authorities to stabilize the carbon futures market and build a collaborative extreme risk management framework covering energy and macroeconomics, also proposing suggestions for traders to effectively prevent extreme risks.

Inflammation and coronary microvascular disease: relationship, mechanism and treatment.

Coronary microvascular disease (CMVD) is common in patients with cardiovascular risk factors and is linked to an elevated risk of adverse cardiovascular events. Although modern medicine has made significant strides in researching CMVD, we still lack a comprehensive understanding of its pathophysiological mechanisms due to its complex and somewhat cryptic etiology. This greatly impedes the clinical diagnosis and treatment of CMVD. The primary pathological mechanisms of CMVD are structural abnormalities and/or dysfunction of coronary microvascular endothelial cells. The development of CMVD may also involve a variety of inflammatory factors through the endothelial cell injury pathway. This paper first reviews the correlation between the inflammatory response and CMVD, then summarizes the possible mechanisms of inflammatory response in CMVD, and finally categorizes the drugs used to treat CMVD based on their effect on the inflammatory response. We hope that this paper draws attention to CMVD and provides novel ideas for potential therapeutic strategies based on the inflammatory response.

High-temperature PTT/CDT coordination nanoplatform realizing exacerbated hypoxia for enhancing hypoxia-activated chemotherapy to overcome tumor drug resistance.

BACKGROUND: Hypoxia-activated prodrugs present new opportunities for safe and effective tumor drug resistance therapy due to their high selectivity for hypoxic cells. However, the uneven distribution of oxygen in solid tumor and insufficient hypoxia in the tumor microenvironment greatly limit its therapeutic efficacy. RESULTS: In this paper, a novel AQ4N-Mn(II)@PDA coordination nanoplatform was designed and functionalized with GMBP1 to target drug-resistant tumor cells. Its excellent photothermal conversion efficiency could achieve local high-temperature photothermal therapy in tumors, which could not only effectively exacerbate tumor hypoxia and thus improve the efficacy of hypoxia-activated chemotherapy of AQ4N but also significantly accelerate Mn2+-mediated Fenton-like activity to enhance chemodynamic therapy. Moreover, real-time monitoring of blood oxygen saturation through photoacoustic imaging could reflect the hypoxic status of tumors during treatment. Furthermore, synergistic treatment effectively inhibited tumor growth and improved the survival rate of mice bearing orthotopic drug-resistant tumors. CONCLUSIONS: This study not only provided a new idea for PTT combined with hypoxia-activated chemotherapy and CDT for drug-resistant tumors but also explored a vital theory for real-time monitoring of hypoxia during treatment.

CCL22 Induces the Polarization of Immature Dendritic Cells into Tolerogenic Dendritic Cells in Radiation-Induced Lung Injury through the CCR4-Dectin2-PLC-γ2-NFATC2-Nr4a2-PD-L1 Signaling Pathway.

Recruitment of immune cells to the injury site plays a pivotal role in the pathology of radiation-associated diseases. In this study, we investigated the impact of the chemokine CCL22 released from alveolar type II epithelial (AT2) cells after irradiation on the recruitment and functional changes of dendritic cells (DCs) in the development of radiation-induced lung injury (RILI). By examining changes in CCL22 protein levels in lung tissue of C57BL/6N mice with RILI, we discovered that ionizing radiation increased CCL22 expression in irradiated alveolar AT2 cells, as did MLE-12 cells after irradiation. A transwell migration assay revealed that CCL22 promoted the migration of CCR4-positive DCs to the injury site, which explained the migration of pulmonary CCR4-positive DCs in RILI mice in vivo. Coculture experiments demonstrated that, consistent with the response of regulatory T cells in the lung tissue of RILI mice, exogenous CCL22-induced DCs promoted regulatory T cell proliferation. Mechanistically, we demonstrated that Dectin2 and Nr4a2 are key targets in the CCL22 signaling pathway, which was confirmed in pulmonary DCs of RILI mice. As a result, CCL22 upregulated the expression of PD-L1, IL-6, and IL-10 in DCs. Consequently, we identified a mechanism in which CCL22 induced DC tolerance through the CCR4-Dectin2-PLC-γ2-NFATC2-Nr4a2-PD-L1 pathway. Collectively, these findings demonstrated that ionizing radiation stimulates the expression of CCL22 in AT2 cells to recruit DCs to the injury site and further polarizes them into a tolerant subgroup of CCL22 DCs to regulate lung immunity, ultimately providing potential therapeutic targets for DC-mediated RILI.

CsAlB3O6Cl: the rational construction of a KBBF-type structure with aligned 2∞[AlB3O6Cl] layers via introducing unprecedented [AlO3Cl] tetrahedra.

The first chloroaluminoborate, CsAlB3O6Cl, with innovative AlO3Cl tetrahedra and a perfect planar arrangement of [B3O6] groups, was structurally designed and synthesized via chlorination of [AlO4] tetrahedra. Simultaneously, the smooth introduction of the [AlO3Cl] group into borates initiates the development of a chloroaluminoborate and greatly enriches the structural chemistry of aluminoborates.

Folic acid-mediated hollow Mn 3 O 4 nanocomposites for in vivo MRI/FLI monitoring the metastasis of gastric cancer.

BACKGROUND: Metastasis is one of the main factors leading to the high mortality rate of gastric cancer. The current monitoring methods are not able to accurately monitor gastric cancer metastasis. METHODS: In this paper, we constructed a new type of hollow Mn 3 O 4 nanocomposites, Mn 3 O 4 @HMSN-Cy7.5-FA, which had a size distribution of approximately 100 nm and showed good stability in different liquid environments. The in vitro magnetic resonance imaging (MRI) results show that the nanocomposite has good response effects to the acidic microenvironment of tumors. The acidic environment can significantly enhance the contrast of T 1 -weighted MRI. The cellular uptake and endocytosis results show that the nanocomposite has good targeting capabilities and exhibits good biosafety, both in vivo and in vitro. In a gastric cancer nude mouse orthotopic metastatic tumor model, with bioluminescence imaging's tumor location information, we realized in vivo MRI/fluorescence imaging (FLI) guided precise monitoring of the gastric cancer orthotopic and metastatic tumors with this nanocomposite. RESULTS: This report demonstrates that Mn 3 O 4 @HMSN-Cy7.5-FA nanocomposites is a promising nano-diagnostic platform for the precision diagnosis and therapy of gastric cancer metastasis in the future. CONCLUSIONS: In vivo MRI/FLI imaging results show that the nanocomposites can achieve accurate monitoring of gastric cancer tumors in situ and metastases. BLI's tumor location information further supports the good accuracy of MRI/FLI dual-modality imaging. The above results show that the MHCF NPs can serve as a good nano-diagnostic platform for precise in vivo monitoring of tumor metastasis. This nanocomposite provides more possibilities for the diagnosis and therapy of gastric cancer metastases.

Regulation of optimized new Shengmai powder on cardiomyocyte apoptosis and ferroptosis in ischemic heart failure rats: The mediating role of phosphatidylinositol-3-kinase/protein kinase B/tumor protein 53 signaling pathway.

ETHNOPHARMACOLOGICAL RELEVANCE: Optimized New Shengmai Powder (ONSMP) is a sophisticated traditional Chinese medicinal formula renowned for bolstering vital energy, optimizing blood circulation, and mitigating fluid retention. After years of clinical application, ONSMP has shown a significant impact in improving myocardial injury and cardiac function and has a positive effect on treating heart failure. However, many unknowns exist about the molecular biological mechanisms of how ONSMP exerts its therapeutic effects, which require further research and exploration. AIM OF THE STUDY: Exploring the potential molecular biological mechanisms by which ONSMP ameliorates cardiomyocyte apoptosis and ferroptosis in ischemic heart failure (IHF). MATERIALS AND METHODS: First, we constructed a rat model of IHF by inducing acute myocardial infarction through surgery and using echocardiography, organ coefficients, markers of heart failure, antioxidant markers, and histopathological examination to assess the effects of ONSMP on cardiomyocyte apoptosis and ferroptosis in IHF rats. Next, we used bioinformatics analysis techniques to analyze the active components, signaling pathways, and core targets of ONSMP and calculated the interactions between core targets and corresponding elements. Finally, we detected the positive expression of apoptosis and ferroptosis markers and core indicators of signaling pathways by immunohistochemistry; detected the mean fluorescence intensity of core indicators of signaling pathways by immunofluorescence; detected the protein expression of signaling pathways and downstream effector molecules by western blotting; and detected the mRNA levels of p53 and downstream effector molecules by quantitative polymerase chain reaction. RESULTS: ONSMP can activate the Ser83 site of ASK by promoting the phosphorylation of the PI3K/AKT axis, thereby inhibiting the MKK3/6-p38 axis and the MKK4/7-JNK axis signaling to reduce p53 expression, and can also directly target and inhibit the activity of p53, ultimately inhibiting p53-mediated mRNA and protein increases in PUMA, SAT1, PIG3, and TFR1, as well as mRNA and protein decreases in SLC7A11, thereby inhibiting cardiomyocyte apoptosis and ferroptosis, effectively improving cardiac function and ventricular remodeling in IHF rat models. CONCLUSION: ONSMP can inhibit cardiomyocyte apoptosis and ferroptosis through the PI3K/AKT/p53 signaling pathway, delaying the development of IHF.

Decoding ferroptosis: Revealing the hidden assassin behind cardiovascular diseases.

The discovery of regulatory cell death processes has driven innovation in cardiovascular disease (CVD) therapeutic strategies. Over the past decade, ferroptosis, an iron-dependent form of regulated cell death driven by excessive lipid peroxidation, has been shown to drive the development of multiple CVDs. This review provides insights into the evolution of the concept of ferroptosis, the similarities and differences with traditional modes of programmed cell death (e.g., apoptosis, autophagy, and necrosis), as well as the core regulatory mechanisms of ferroptosis (including cystine/glutamate transporter blockade, imbalance of iron metabolism, and lipid peroxidation). In addition, it provides not only a detailed review of the role of ferroptosis and its therapeutic potential in widely studied CVDs such as coronary atherosclerotic heart disease, myocardial infarction, myocardial ischemia/reperfusion injury, heart failure, cardiomyopathy, and aortic aneurysm but also an overview of the phenomenon and therapeutic perspectives of ferroptosis in lesser-addressed CVDs such as cardiac valvulopathy, pulmonary hypertension, and sickle cell disease. This article aims to integrate this knowledge to provide a comprehensive view of ferroptosis in a wide range of CVDs and to drive innovation and progress in therapeutic strategies in this field.

Wide band gap selenide infrared nonlinear optical materials AIIMg6Ga6Se16 with strong SHG responses and high laser-induced damage thresholds.

Infrared (IR) nonlinear optical (NLO) materials with strong NLO response, wide band gap and high laser-induced damage threshold (LIDT) are highly expected in current laser technologies. Herein, by introducing double alkaline-earth metal (AEM) atoms, three wide band gap selenide IR NLO materials AIIMg6Ga6Se16 (AII = Ca, Sr, Ba) with excellent linear and NLO optical properties have been rationally designed and fabricated. AIIMg6Ga6Se16 (AII = Ca, Sr, Ba) are composed of unique [AIISe6] triangular prisms, [MgSe6] octahedra and [GaSe4] tetrahedra. The introduction of double AEMs effectively broadens the band gaps of selenide-based IR NLO materials. Among them, CaMg6Ga6Se16, achieving the best balance between the second-harmonic generation response (∼1.5 × AgGaS2), wide band gap (2.71 eV), high LIDT (∼9 × AgGaS2), and moderate birefringence of 0.052 @ 1064 nm, is a promising NLO candidate for high power IR laser. Theoretical calculations indicate that the NLO responses and band gaps among the three compounds are mainly determined by the NLO-active [GaSe4] units. The results enrich the chemical diversity of chalcogenides, and give some insight into the design of new functional materials based on the rare [AIISe6] prismatic units.

Clinical evidence and potential mechanisms of traditional Chinese medicine for refractory heart failure: a literature review and perspectives.

Refractory heart failure (RHF), or end-stage heart failure, has a poor prognosis and high case fatality rate, making it one of the therapeutic difficulties in the cardiovascular field. Despite the continuous abundance of methods and means for treating RHF in modern medicine, it still cannot meet the clinical needs of patients with RHF. How to further reduce the mortality rate and readmission rate of patients with RHF and improve their quality of life is still a difficult point in current research. In China, traditional Chinese medicine (TCM) has been widely used and has accumulated rich experience in the treatment of RHF due to its unique efficacy and safety advantages. Based on this, we comprehensively summarized and analyzed the clinical evidence and mechanism of action of TCM in the treatment of RHF and proposed urgent scientific issues and future research strategies for the treatment of RHF with TCM, to provide reference for the treatment of RHF.

Clinical analysis of the efficacy of radiation therapy for primary high-grade gliomas guided by biological rhythms.

OBJECTIVE: High-grade glioma (HGG) patients frequently encounter treatment resistance and relapse, despite numerous interventions seeking enhanced survival outcomes yielding limited success. Consequently, this study, rooted in our prior research, aimed to ascertain whether leveraging circadian rhythm phase attributes could optimize radiotherapy results. METHODS: In this retrospective analysis, we meticulously selected 121 HGG cases with synchronized rhythms through Cosinor analysis. Post-surgery, all subjects underwent standard radiotherapy alongside Temozolomide chemotherapy. Random allocation ensued, dividing patients into morning (N = 69) and afternoon (N = 52) radiotherapy cohorts, enabling a comparison of survival and toxicity disparities. RESULTS: The afternoon radiotherapy group exhibited improved overall survival (OS) and progression-free survival (PFS) relative to the morning cohort. Notably, median OS extended to 25.6 months versus 18.5 months, with P = 0.014, with median PFS at 20.6 months versus 13.3 months, with P = 0.022, post-standardized radiotherapy. Additionally, lymphocyte expression levels in the afternoon radiation group 32.90(26.10, 39.10) significantly exceeded those in the morning group 31.30(26.50, 39.20), with P = 0.032. CONCLUSIONS: This study underscores the markedly prolonged average survival within the afternoon radiotherapy group. Moreover, lymphocyte proportion demonstrated a notable elevation in the afternoon group. Timely and strategic adjustments of therapeutic interventions show the potential to improve therapeutic efficacy, while maintaining vigilant systemic immune surveillance. A comprehensive grasp of physiological rhythms governing both the human body and tumor microenvironment can refine treatment efficacy, concurrently curtailing immune-related damage-a crucial facet of precision medicine.

Two Hydroxyfluorooxoborates Achieving Deep-Ultraviolet Cutoff Edges and Moderate Birefringence by Assembling Multi-Anionic Groups.

Assembling multi-anionic groups is conducive to utilizing respective advantage to achieve the enhancement of optical performance. Two new hydroxyfluorooxoborates, Ama2-Rb2B3O3F4(OH) and K8Cs2B15O14(OH)7F20 ⋅ H2O with [B3O3F4(OH)] six-membered rings were synthesized for the first time. The title compounds exhibit short ultraviolet cutoff edges (<200 nm) and K8Cs2B15O14(OH)7F20 ⋅ H2O possesses a moderate experimental refractive index difference of 0.051@546 nm.

Effects of Chronic Heat Stress on Growth, Apoptosis, Antioxidant Enzymes, Transcriptomic Profiles, and Immune-Related Genes of Hong Kong Catfish (Clarias fuscus).

Chronic heat stress can have detrimental effects on the survival of fish. This study aimed to investigate the impact of prolonged high temperatures on the growth, antioxidant capacity, apoptosis, and transcriptome analysis of Hong Kong catfish (Clarias fuscus). By analyzing the morphological statistics of C. fuscus subjected to chronic high-temperature stress for 30, 60, and 90 days, it was observed that the growth of C. fuscus was inhibited compared to the control group. The experimental group showed a significant decrease in body weight and body length compared to the control group after 60 and 90 days of high-temperature stress (p < 0.05, p < 0.01). A biochemical analysis revealed significant alterations in the activities of three antioxidant enzymes superoxide dismutase activity (SOD); catalase activity (CAT); glutathione peroxidase activity (GPx), the malondialdehyde content (MDA), and the concentrations of serum alkaline phosphatase (ALP); Aspartate aminotransferase (AST); and alanine transaminase (ALT) in the liver. TUNEL staining indicated stronger apoptotic signals in the high-temperature-stress group compared to the control group, suggesting that chronic high-temperature-induced oxidative stress, leading to liver tissue injury and apoptosis. Transcriptome analysis identified a total of 1330 DEGs, with 835 genes being upregulated and 495 genes being downregulated compared to the control group. These genes may be associated with oxidative stress, apoptosis, and immune response. The findings elucidate the growth changes in C. fuscus under chronic high temperature and provide insights into the underlying response mechanisms to a high-temperature environment.

Whole-tumor histogram analysis of synthetic magnetic resonance imaging predicts isocitrate dehydrogenase mutation status in gliomas.

Background: An accurate assessment of isocitrate dehydrogenase (IDH) status in patients with glioma is crucial for treatment planning and is a key factor in predicting patient outcomes. In this study, we investigated the potential value of whole-tumor histogram metrics derived from synthetic magnetic resonance imaging (MRI) in distinguishing IDH mutation status between astrocytoma and glioblastoma. Methods: In this prospective study, 80 glioma patients were enrolled from September 2019 to June 2022. All patients underwent pre- and post-contrast synthetic MRI scan protocol. Immunohistochemistry (IHC) staining or gene sequencing were used to assess IDH mutation status in tumor tissue samples. Whole-tumor histogram metrics, including T1, T2, proton density (PD), etc., were extracted from the quantitative maps, while radiological features were assessed by synthetic contrast-weighted maps. Basic clinical features of the patients were also evaluated. Differences in clinical, radiological, and histogram metrics between IDH-mutant astrocytoma and IDH-wildtype glioblastoma were analyzed using univariate analyses. Variables with statistical significance in univariate analysis were included in multivariate logistic regression analysis to develop the combined model. Receiver operating characteristic (ROC) and area under the curve (AUC) were used to assess the diagnostic performance of metrics and models. Results: The histopathologic analysis revealed that of the 80 cases, 41 were classified as IDH-mutant astrocytoma and 39 as IDH-wildtype glioblastoma. Compared to IDH-wildtype glioblastoma, IDH-mutant astrocytoma showed significantly lower T1 [10th percentile (10th), mean, and median] and post-contrast PD (10th, 90th percentile, mean, median, and maximum) values as well as higher post-contrast T1 (cT1) (10th, mean, median, and minimum) values (all P<0.05). The combined model (T1-10th + cT1-10th + age) was developed by integrating the independent influencing factors of IDH-mutant astrocytoma using the multivariate logistic regression. The diagnostic performance of this model [AUC =0.872 (0.778-0.936), sensitivity =75.61%, and specificity =89.74%] was superior to the clinicoradiological model, which was constructed using age and enhancement degree (AUC =0.822 (0.870-0.898), P=0.035). Conclusions: The combined model constructed using histogram metrics derived from synthetic MRI could be a valuable preoperative tool to distinguish IDH mutation status between astrocytoma and glioblastoma, and subsequently, could assist in the decision-making process of pretreatment.

Targeting MAPK-ERK/JNK pathway: A potential intervention mechanism of myocardial fibrosis in heart failure.

Myocardial fibrosis is a significant pathological basis of heart failure. Overactivation of the ERK1/2 and JNK1/2 signaling pathways of MAPK family members synergistically promotes the proliferation of myocardial fibroblasts and accelerates the development of myocardial fibrosis. In addition to some small molecule inhibitors and Western drugs, many Chinese medicines can also inhibit the activity of ERK1/2 and JNK1/2, thus slowing down the development of myocardial fibrosis, and are generally safe and effective. However, the specific biological mechanisms of ERK1/2 and JNK1/2 signaling pathways in myocardial fibrosis still need to be fully understood, and there is no systematic review of existing drugs and methods to inhibit them from improving myocardial fibrosis. This study aims to summarize the roles and cross-linking mechanisms of ERK1/2 and JNK1/2 signaling pathways in myocardial fibrosis and to systematically sort out the small-molecule inhibitors, Western drugs, traditional Chinese medicines, and non-pharmacological therapies that inhibit ERK1/2 and JNK1/2 to alleviate myocardial fibrosis. In the future, we hope to conduct more in-depth research from the perspective of precision-targeted therapy, using this as a basis for developing new drugs that provide new perspectives on the prevention and treatment of heart failure.