Objective To understand the current status of traditional Chinese medicine(TCM)systematic reviews/Meta-analysis over the past 10 years.Methods Cochrane Database of Systematic Reviews,PubMed,Web of Knowledge,CNKI,SinoMed,WanFang Data,VIP databases,as well as the Cochrane Register and PROSPERO registration platform were searched to collect TCM-related systematic reviews/Meta-analysis published between January 2015 and December 2024.Literature was screened,and standardization of institutions,countries,and journals was performed.Data cleaning was conducted,and trends in publication years,high-frequency diseases,journals,institutions,and highly cited papers were analyzed.Results A total of 11,174 papers were included,involving approximately 56,656 authors from 1,422 institutions across 44 countries,covering 1,300 journals and 1,070 diseases.The top five institutions in terms of publications were Beijing University of Chinese Medicine(954 papers),Guangzhou University of Chinese Medicine(928 papers),China Academy of Chinese Medical Sciences(537 papers),Tianjin University of Chinese Medicine(460 papers),and Chengdu University of Chinese Medicine(393 papers).Foreign institutions with the highest publication volumes were concentrated in South Korea,Iran,and Australia.The most frequently published Chinese journal was Zhongyi Clinical Research with 332 papers,while the most published English journal was Evidence-Based Complementary and Alternative Medicine with 311 papers.There were 282 single-author papers involving 271 authors,and the most cited paper was referenced 323 times,The three most frequently studied diseases were diabetes(267 papers,2.39％),angina pectoris(214 papers,1.92％),and osteoarthritis(210 papers,1.88％).Non-pharmacological interventions such as acupuncture(1,265 papers,11.32％),auricular therapy(101 papers,0.90％),and Tai Chi(98 papers,0.88％)were most frequently reported.In pharmacological interventions,studies on Tripterygium wilfordii tablets(76 papers,0.68％)and Danhong injection(54 papers,0.48％)were more common.Conclusion The systematic reviews/Meta-analysis method is widely used in the field of TCM,and the field continues to grow.Active academic teams,institutions,and journals have emerged.Over the past decade,there has been a considerable body of evidence in Chinese systematic reviews on TCM for chronic diseases such as diabetes,angina pectoris,and osteoarthritis.In English-language studies,non-pharmacological therapies like acupuncture have been more widely reported,and some high-impact studies have emerged.However,challenges remain,such as issues with research transparency and methodological standardization.Future efforts should focus on establishing transparent systems and quality control mechanisms to further enhance the reliability,accuracy,and dissemination of TCM evidence-based research.

The pregnant woman was 30 years old,G2P0.This singleton pregnancy at 22 weeks of gestation was screened for second-trimester ultrasound malformations,suggesting fetal aortic valve atresia,aortic stenosis with reverse blood flow,mitral valve atresia,and markedly enlarged left ventricle,which was considered for the diagnosis of hypoplastic left heart syndrome(HLHS).The pregnancy was terminated at our hospital and subsequently underwent genetic testing with results of heterozygous variants in the NOTCH1 gene,which can cause aortic valve disease type 1.The findings of the fetal autopsy were aortic valve atresia,mitral valve widening and thickening,and left ventricular enlargement with myocardial infarction.This report focuses on the ultrasound characteristics of HLHS with left ventricular enlargement and its hemodynamic changes in order to improve clinicians'understanding of the progressive changes in the disease phenotype of HLHS.

Angiogenesis is a key link in the development of atherosclerotic plaques.Inhibiting angiogenesis con-tributes to plaque stabilization and reduces the risk of related cardiovascular events.Apolipoprotein A1 binding protein(A1 BP),an important secretory protein,has been shown in a growing body of research to play a significant role in the reg-ulation of angiogenesis.This article aims to elucidate the mechanisms of action of A1 BP on angiogenesis and cardiovascu-lar diseases,thereby providing new perspectives for the clinical treatment of cardiovascular diseases.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Based on the pharmacokinetics theory, this study investigated the pharmacokinetic characteristics of albiflorin, paeoniflorin, wogonoside, and wogonin in normal and febrile rats and summarized absorption and elimination rules of Dayuanyin in them to provide reference for further development and clinical application of Dayuanyin. Blood samples were taken from the fundus venous plexus of normal and model rats after intragastric administration of Dayuanyin at different time points. The concentration of each substance in blood was determined by ultra performance liquid chromatography-triple quadrupole mass spectrometry(UPLC-MS/MS) technique at different time points. DAS 2.0, a piece of pharmacokinetics software, was used to calculate the pharmacokinetic parameters of each component. The results show that the 4 components had good linear relationship in their respective ranges, and the results of methodological investigation met the requirements. The pharmacokinetic parameters of C_(max), T_(max), t_(1/2), AUC_(0-t), AUC_(0-∞), and MRT_(0-t) were calculated by the DAS 2.0 non-compartmental model. Compared with those in the normal group, C_(max) and AUC_(0-t) of the 4 components in the model group were significantly increased. There were significant differences in the pharmacokinetic characteristics between the normal and model groups, suggesting that the absorption and elimination of Dayuanyin may be affected by the changes of internal environment of the body in different physiological states.
Animals ; Rats ; Drugs, Chinese Herbal/administration & dosage* ; Male ; Rats, Sprague-Dawley ; Fever/metabolism* ; Tandem Mass Spectrometry ; Chromatography, High Pressure Liquid ; Glucosides/pharmacokinetics* ; Monoterpenes

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Angiogenesis is a key link in the development of atherosclerotic plaques.Inhibiting angiogenesis con-tributes to plaque stabilization and reduces the risk of related cardiovascular events.Apolipoprotein A1 binding protein(A1 BP),an important secretory protein,has been shown in a growing body of research to play a significant role in the reg-ulation of angiogenesis.This article aims to elucidate the mechanisms of action of A1 BP on angiogenesis and cardiovascu-lar diseases,thereby providing new perspectives for the clinical treatment of cardiovascular diseases.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.