Atherosclerosis （AS） is the main pathological basis of cardiovascular diseases and seriously threatens human quality of life. Its prevention and treatment urgently need breakthroughs. The inflammatory response， which runs through the physiological and pathological evolution process of AS， is one of the important mechanisms for AS occurrence. Currently， the treatment methods for AS in Western medicine are relatively mature. However， they have adverse reactions such as abnormal liver and kidney function， drug tolerance， target vessel restenosis， and stent thrombosis， which remain the key bottleneck restricting clinical efficacy. Traditional Chinese medicine （TCM）， characterized by multiple components， multiple targets， and multi-pathway synergy， shows unique clinical application potential and efficacy advantages in the intervention of AS. This article reviewed the research progress of TCM in intervening in AS by regulating inflammatory-related signaling pathways， such as nuclear factor-κB （NF-κB）， Toll-like receptors （TLRs）， mitogen-activated protein kinase （MAPK）， and Janus kinase/signal transducer and activator of transcription （JAK/STAT）， in the past five years. It summarized the combined mechanism of action of TCM monomers， TCM pairs， and compound preparations in inhibiting the inflammatory cascade reaction through multiple targets， regulating lipid metabolism disorders， and improving vascular endothelial dysfunction and the imbalance of the microenvironment. It deepened the research on the molecular mechanism of TCM in anti-AS， so as to provide a scientific basis for the clinical transformation application and related theoretical research of TCM in anti-AS.

Atherosclerosis （AS） is the main pathological basis of cardiovascular diseases and seriously threatens human quality of life. Its prevention and treatment urgently need breakthroughs. The inflammatory response， which runs through the physiological and pathological evolution process of AS， is one of the important mechanisms for AS occurrence. Currently， the treatment methods for AS in Western medicine are relatively mature. However， they have adverse reactions such as abnormal liver and kidney function， drug tolerance， target vessel restenosis， and stent thrombosis， which remain the key bottleneck restricting clinical efficacy. Traditional Chinese medicine （TCM）， characterized by multiple components， multiple targets， and multi-pathway synergy， shows unique clinical application potential and efficacy advantages in the intervention of AS. This article reviewed the research progress of TCM in intervening in AS by regulating inflammatory-related signaling pathways， such as nuclear factor-κB （NF-κB）， Toll-like receptors （TLRs）， mitogen-activated protein kinase （MAPK）， and Janus kinase/signal transducer and activator of transcription （JAK/STAT）， in the past five years. It summarized the combined mechanism of action of TCM monomers， TCM pairs， and compound preparations in inhibiting the inflammatory cascade reaction through multiple targets， regulating lipid metabolism disorders， and improving vascular endothelial dysfunction and the imbalance of the microenvironment. It deepened the research on the molecular mechanism of TCM in anti-AS， so as to provide a scientific basis for the clinical transformation application and related theoretical research of TCM in anti-AS.

OBJECTIVE To explore the effect and mechanism of Prunus mume against hepatic fibrosis （HF）. METHODS Male SD rats were randomly divided into normal control group （n＝10） and modeling group （n＝50）. The modeling group established HF model using carbon tetrachloride. The modeled rats were randomly divided into model group （normal saline）， positive control group [colchicine， 0.09 mg/（kg·d）]， and P. mume low-dose， medium-dose and high-dose groups [1.35， 2.70， 5.40 g/（kg·d）]， with 9 rats in each group. They were given the corresponding drug/normal saline intragastrically， once a day， for 8 consecutive weeks. After the last medication， the liver index was calculated， while liver function indexes， liver fiber indexes， oxidative stress indicators and inflammatory factors of rats were measured. HE staining was used to observe the pathological changes in liver tissue of rats； Masson staining was used to observe the degree of HF in liver tissue of rats； transmission electron microscopy was used to observe the ultrastructure of liver tissue in rats； TUNEL staining was used to detect liver cell apoptosis in each group of rats. Western blot method was used to detect the protein expressions of transforming growth factor-β1 （TGF-β1） and platelet-derived growth factor （PDGF） in liver tissue of rats. RESULTS Compared with normal control group， the levels of alanine transaminase， alkaline phosphatase， aspartate transaminase， total bilirubin， malondialdehyde， procollagen type Ⅲ protein， Ⅳ-type pre collagenase， laminin， hyaluronic acid， interleukin-6， tumor necrosis factor-α， as well as the protein expressions of TGF-β1 and PDGF in model group were increased significantly， while the levels of superoxide dismutase and glutathione peroxidase were significantly reduced （P＜0.01）； the HE， Masson staining and transmission electron microscopy observation results showed obvious HF characteristics in rats of model group. Compared with model group， varying degrees of improvement in above indexes were observed in P. mume groups， and the above 2021BSZR011） indicators of rats in P. mume medium-dose and high-dose groups were reversed significantly （P＜0.05 or P＜0.01）. CONCLUSIONS P. mume has an anti-HF effect， which may be achieved through mechanisms such as antioxidation， anti-inflammation， reduction of collagen production， inhibition of PDGF protein expression， and regulation of TGF- β1 signaling pathway.

OBJECTIVE To explore the effect and mechanism of Prunus mume against hepatic fibrosis （HF）. METHODS Male SD rats were randomly divided into normal control group （n＝10） and modeling group （n＝50）. The modeling group established HF model using carbon tetrachloride. The modeled rats were randomly divided into model group （normal saline）， positive control group [colchicine， 0.09 mg/（kg·d）]， and P. mume low-dose， medium-dose and high-dose groups [1.35， 2.70， 5.40 g/（kg·d）]， with 9 rats in each group. They were given the corresponding drug/normal saline intragastrically， once a day， for 8 consecutive weeks. After the last medication， the liver index was calculated， while liver function indexes， liver fiber indexes， oxidative stress indicators and inflammatory factors of rats were measured. HE staining was used to observe the pathological changes in liver tissue of rats； Masson staining was used to observe the degree of HF in liver tissue of rats； transmission electron microscopy was used to observe the ultrastructure of liver tissue in rats； TUNEL staining was used to detect liver cell apoptosis in each group of rats. Western blot method was used to detect the protein expressions of transforming growth factor-β1 （TGF-β1） and platelet-derived growth factor （PDGF） in liver tissue of rats. RESULTS Compared with normal control group， the levels of alanine transaminase， alkaline phosphatase， aspartate transaminase， total bilirubin， malondialdehyde， procollagen type Ⅲ protein， Ⅳ-type pre collagenase， laminin， hyaluronic acid， interleukin-6， tumor necrosis factor-α， as well as the protein expressions of TGF-β1 and PDGF in model group were increased significantly， while the levels of superoxide dismutase and glutathione peroxidase were significantly reduced （P＜0.01）； the HE， Masson staining and transmission electron microscopy observation results showed obvious HF characteristics in rats of model group. Compared with model group， varying degrees of improvement in above indexes were observed in P. mume groups， and the above 2021BSZR011） indicators of rats in P. mume medium-dose and high-dose groups were reversed significantly （P＜0.05 or P＜0.01）. CONCLUSIONS P. mume has an anti-HF effect， which may be achieved through mechanisms such as antioxidation， anti-inflammation， reduction of collagen production， inhibition of PDGF protein expression， and regulation of TGF- β1 signaling pathway.

Objective To systematically evaluate the risk prediction model of anastomotic fistula after radical resection of esophageal cancer, and to provide objective basis for selecting a suitable model. Methods A comprehensive search was conducted on Chinese and English databases including CNKI, Wanfang, VIP, CBM, PubMed, EMbase, Web of Science, The Cochrane Library for relevant studies on the risk prediction model of anastomotic fistula after radical resection of esophageal cancer from inception to April 30, 2023. Two researchers independently screened literatures and extracted data information. PROBAST tool was used to assess the risk of bias and applicability of included literatures. Meta-analysis was performed on the predictive value of common predictors in the model with RevMan 5.3 software. Results A total of 18 studies were included, including 11 Chinese literatures and 7 English literatures. The area under the curve (AUC) of the prediction models ranged from 0.68 to 0.954, and the AUC of 10 models was >0.8, indicating that the prediction performance was good, but the risk of bias in the included studies was high, mainly in the field of research design and data analysis. The results of the meta-analysis on common predictors showed that age, history of hypertension, history of diabetes, C-reactive protein, history of preoperative chemotherapy, hypoproteinemia, peripheral vascular disease, pulmonary infection, and calcification of gastric omental vascular branches are effective predictors for the occurrence of anastomotic leakage after radical surgery for esophageal cancer (P<0.05). Conclusion The study on the risk prediction model of anastomotic fistula after radical resection of esophageal cancer is still in the development stage. Future studies can refer to the common predictors summarized by this study, and select appropriate methods to develop and verify the anastomotic fistula prediction model in combination with clinical practice, so as to provide targeted preventive measures for patients with high-risk anastomotic fistula as soon as possible.

Objective: To explore the feasibility of synthetic magnetic resonance imaging (syMRI) combined with clinicopathological characteristics for the pre-treatment prediction of chemoradiotherapy (CRT) response in advanced nasopharyngeal carcinoma (ANPC). Materials and Methods: Patients with ANPC treated with CRT between September 2020 and June 2022 were retrospectively enrolled and categorized into response group (RG, n = 95) and non RGs (NRG, n = 32) based on the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. The quantitative parameters from pre-treatment syMRI (longitudinal [T1] and transverse [T2] relaxation times and proton density [PD]), diffusion-weighted imaging (apparent diffusion coefficient [ADC]), and clinicopathological characteristics were compared between RG and NRG. Logistic regression analysis was applied to identify parameters independently associated with CRT response and to construct a multivariable model. The areas under the receiveroperating characteristic curve (AUC) for various diagnostic approaches were compared using the DeLong test. Results: The T1, T2, and PD values in the NRG were significantly lower than those in the RG (all P < 0.05), whereas no significant difference was observed in the ADC values between these two groups. Clinicopathological characteristics (Epstein–Barr virus [EBV]-DNA level, lymph node extranodal extension, clinical stage, and Ki-67 expression) exhibited significant differences between the two groups. Logistic regression analysis showed that T1, PD, EBV-DNA level, clinical stage, and Ki-67 expression had significant independent relationships with CRT response (all P < 0.05). The multivariable model incorporating these five variables yielded AUC, sensitivity, and specificity values of 0.974, 93.8% (30/32), and 91.6% (87/95), respectively. Conclusion SyMRI may be used for the pretreatment prediction of CRT response in ANPC. The multivariable model incorporating syMRI quantitative parameters and clinicopathological characteristics, which were independently associated with CRT response, may be a new tool for the pretreatment prediction of CRT response.

Objective: To explore the feasibility of synthetic magnetic resonance imaging (syMRI) combined with clinicopathological characteristics for the pre-treatment prediction of chemoradiotherapy (CRT) response in advanced nasopharyngeal carcinoma (ANPC). Materials and Methods: Patients with ANPC treated with CRT between September 2020 and June 2022 were retrospectively enrolled and categorized into response group (RG, n = 95) and non RGs (NRG, n = 32) based on the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. The quantitative parameters from pre-treatment syMRI (longitudinal [T1] and transverse [T2] relaxation times and proton density [PD]), diffusion-weighted imaging (apparent diffusion coefficient [ADC]), and clinicopathological characteristics were compared between RG and NRG. Logistic regression analysis was applied to identify parameters independently associated with CRT response and to construct a multivariable model. The areas under the receiveroperating characteristic curve (AUC) for various diagnostic approaches were compared using the DeLong test. Results: The T1, T2, and PD values in the NRG were significantly lower than those in the RG (all P < 0.05), whereas no significant difference was observed in the ADC values between these two groups. Clinicopathological characteristics (Epstein–Barr virus [EBV]-DNA level, lymph node extranodal extension, clinical stage, and Ki-67 expression) exhibited significant differences between the two groups. Logistic regression analysis showed that T1, PD, EBV-DNA level, clinical stage, and Ki-67 expression had significant independent relationships with CRT response (all P < 0.05). The multivariable model incorporating these five variables yielded AUC, sensitivity, and specificity values of 0.974, 93.8% (30/32), and 91.6% (87/95), respectively. Conclusion SyMRI may be used for the pretreatment prediction of CRT response in ANPC. The multivariable model incorporating syMRI quantitative parameters and clinicopathological characteristics, which were independently associated with CRT response, may be a new tool for the pretreatment prediction of CRT response.

Objective: To explore the feasibility of synthetic magnetic resonance imaging (syMRI) combined with clinicopathological characteristics for the pre-treatment prediction of chemoradiotherapy (CRT) response in advanced nasopharyngeal carcinoma (ANPC). Materials and Methods: Patients with ANPC treated with CRT between September 2020 and June 2022 were retrospectively enrolled and categorized into response group (RG, n = 95) and non RGs (NRG, n = 32) based on the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. The quantitative parameters from pre-treatment syMRI (longitudinal [T1] and transverse [T2] relaxation times and proton density [PD]), diffusion-weighted imaging (apparent diffusion coefficient [ADC]), and clinicopathological characteristics were compared between RG and NRG. Logistic regression analysis was applied to identify parameters independently associated with CRT response and to construct a multivariable model. The areas under the receiveroperating characteristic curve (AUC) for various diagnostic approaches were compared using the DeLong test. Results: The T1, T2, and PD values in the NRG were significantly lower than those in the RG (all P < 0.05), whereas no significant difference was observed in the ADC values between these two groups. Clinicopathological characteristics (Epstein–Barr virus [EBV]-DNA level, lymph node extranodal extension, clinical stage, and Ki-67 expression) exhibited significant differences between the two groups. Logistic regression analysis showed that T1, PD, EBV-DNA level, clinical stage, and Ki-67 expression had significant independent relationships with CRT response (all P < 0.05). The multivariable model incorporating these five variables yielded AUC, sensitivity, and specificity values of 0.974, 93.8% (30/32), and 91.6% (87/95), respectively. Conclusion SyMRI may be used for the pretreatment prediction of CRT response in ANPC. The multivariable model incorporating syMRI quantitative parameters and clinicopathological characteristics, which were independently associated with CRT response, may be a new tool for the pretreatment prediction of CRT response.

Objective: To explore the feasibility of synthetic magnetic resonance imaging (syMRI) combined with clinicopathological characteristics for the pre-treatment prediction of chemoradiotherapy (CRT) response in advanced nasopharyngeal carcinoma (ANPC). Materials and Methods: Patients with ANPC treated with CRT between September 2020 and June 2022 were retrospectively enrolled and categorized into response group (RG, n = 95) and non RGs (NRG, n = 32) based on the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. The quantitative parameters from pre-treatment syMRI (longitudinal [T1] and transverse [T2] relaxation times and proton density [PD]), diffusion-weighted imaging (apparent diffusion coefficient [ADC]), and clinicopathological characteristics were compared between RG and NRG. Logistic regression analysis was applied to identify parameters independently associated with CRT response and to construct a multivariable model. The areas under the receiveroperating characteristic curve (AUC) for various diagnostic approaches were compared using the DeLong test. Results: The T1, T2, and PD values in the NRG were significantly lower than those in the RG (all P < 0.05), whereas no significant difference was observed in the ADC values between these two groups. Clinicopathological characteristics (Epstein–Barr virus [EBV]-DNA level, lymph node extranodal extension, clinical stage, and Ki-67 expression) exhibited significant differences between the two groups. Logistic regression analysis showed that T1, PD, EBV-DNA level, clinical stage, and Ki-67 expression had significant independent relationships with CRT response (all P < 0.05). The multivariable model incorporating these five variables yielded AUC, sensitivity, and specificity values of 0.974, 93.8% (30/32), and 91.6% (87/95), respectively. Conclusion SyMRI may be used for the pretreatment prediction of CRT response in ANPC. The multivariable model incorporating syMRI quantitative parameters and clinicopathological characteristics, which were independently associated with CRT response, may be a new tool for the pretreatment prediction of CRT response.

Objective: To explore the feasibility of synthetic magnetic resonance imaging (syMRI) combined with clinicopathological characteristics for the pre-treatment prediction of chemoradiotherapy (CRT) response in advanced nasopharyngeal carcinoma (ANPC). Materials and Methods: Patients with ANPC treated with CRT between September 2020 and June 2022 were retrospectively enrolled and categorized into response group (RG, n = 95) and non RGs (NRG, n = 32) based on the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1. The quantitative parameters from pre-treatment syMRI (longitudinal [T1] and transverse [T2] relaxation times and proton density [PD]), diffusion-weighted imaging (apparent diffusion coefficient [ADC]), and clinicopathological characteristics were compared between RG and NRG. Logistic regression analysis was applied to identify parameters independently associated with CRT response and to construct a multivariable model. The areas under the receiveroperating characteristic curve (AUC) for various diagnostic approaches were compared using the DeLong test. Results: The T1, T2, and PD values in the NRG were significantly lower than those in the RG (all P < 0.05), whereas no significant difference was observed in the ADC values between these two groups. Clinicopathological characteristics (Epstein–Barr virus [EBV]-DNA level, lymph node extranodal extension, clinical stage, and Ki-67 expression) exhibited significant differences between the two groups. Logistic regression analysis showed that T1, PD, EBV-DNA level, clinical stage, and Ki-67 expression had significant independent relationships with CRT response (all P < 0.05). The multivariable model incorporating these five variables yielded AUC, sensitivity, and specificity values of 0.974, 93.8% (30/32), and 91.6% (87/95), respectively. Conclusion SyMRI may be used for the pretreatment prediction of CRT response in ANPC. The multivariable model incorporating syMRI quantitative parameters and clinicopathological characteristics, which were independently associated with CRT response, may be a new tool for the pretreatment prediction of CRT response.