Prognosis prediction and risk stratification of transarterial chemoembolization or intraarterial chemotherapy for unresectable hepatocellular carcinoma based on machine learning.

OBJECTIVE: To develop and validate a risk scoring scale model (RSSM) for stratifying prognostic risk after intra-arterial therapies (IATs) for hepatocellular carcinoma (HCC). METHODS: Between February 2014 and October 2022, 2338 patients with HCC who underwent initial IATs were consecutively enrolled. These patients were divided into training datasets (TD, n = 1700), internal validation datasets (ITD, n = 428), and external validation datasets (ETD, n = 200). Five-years death was used to predict outcome. Thirty-four clinical information were input and five supervised machine learning (ML) algorithms, including eXtreme Gradient Boosting (XGBoost), Categorical Gradient Boosting (CatBoost), Gradient Boosting Decision Tree (GBDT), Light Gradient Boosting Machine (LGBT), and Random Forest (RF), were compared using the areas under the receiver operating characteristic (AUC) with DeLong test. The variables with top important ML scores were used to build the RSSM by stepwise Cox regression. RESULTS: The CatBoost model achieved the best discrimination when 12 top variables were input, with the AUC of 0.851 (95% confidence intervals (CI), 0.833-0.868) for TD, 0.817 (95%CI, 0.759-0.857) for ITD, and 0.791 (95%CI, 0.748-0.834) for ETD. The RSSM was developed based on the immune checkpoint inhibitors (ICI) (hazard ratios (HR), 0.678; 95%CI 0.549, 0.837), tyrosine kinase inhibitors (TKI) (HR, 0.702; 95%CI 0.605, 0.814), local therapy (HR, 0.104; 95%CI 0.014, 0.747), response to the first IAT (HR, 4.221; 95%CI 2.229, 7.994), tumor size (HR, 1.054; 95%CI 1.038, 1.070), and BCLC grade (HR, 2.375; 95%CI 1.950, 2.894). Kaplan-Meier analysis confirmed the role of RSSM in risk stratification (p < 0.001). CONCLUSIONS: The RSSM can stratify accurately prognostic risk for HCC patients received IAT. On the basis, an online calculator permits easy implementation of this model. CLINICAL RELEVANCE STATEMENT: The risk scoring scale model could be easily implemented for physicians to stratify risk and predict prognosis quickly and accurately, thereby serving as a more favorable tool to strengthen individualized intra-arterial therapies and management in patients with unresectable hepatocellular carcinoma. KEY POINTS: • The Categorical Gradient Boosting (CatBoost) algorithm achieved the optimal and robust predictive ability (AUC, 0.851 (95%CI, 0.833-0.868) in training datasets, 0.817 (95%CI, 0.759-0.857) in internal validation datasets, and 0.791 (95%CI, 0.748-0.834) in external validation datasets) for prediction of 5-years death of hepatocellular carcinoma (HCC) after intra-arterial therapies (IATs) among five machine learning models. • We used the SHapley Additive exPlanations algorithms to explain the CatBoost model so as to resolve the black boxes of machine learning principles. • A simpler restricted variable, risk scoring scale model (RSSM), derived by stepwise Cox regression for risk stratification after intra-arterial therapies for hepatocellular carcinoma, provides the potential forewarning to adopt combination strategies for high-risk patients.

Tomo-seq identifies NINJ1 as a potential target for anti-inflammatory strategy in thoracic aortic dissection.

BACKGROUND: Thoracic aortic dissection (TAD) is a life-threatening disease caused by an intimal tear in the aorta. The histological characteristics differ significantly between the tear area (TA) and the distant area. Previous studies have emphasized that certain specific genes tend to cluster at the TA. Obtaining a thorough understanding of the precise molecular signatures near the TA will assist in discovering therapeutic strategies for TAD. METHODS: We performed a paired comparison of the pathological patterns in the TA with that in the remote area (RA). We used Tomo-seq, genome-wide transcriptional profiling with spatial resolution, to obtain gene expression signatures spanning from the TA to the RA. Samples from multiple sporadic TAD patients and animal models were used to validate our findings. RESULTS: Pathological examination revealed that the TA of TAD exhibited more pronounced intimal hyperplasia, media degeneration, and inflammatory infiltration compared to the RA. The TA also had more apoptotic cells and CD31+α-SMA+ cells. Tomo-seq revealed four distinct gene expression patterns from the TA to the RA, which were inflammation, collagen catabolism, extracellular matrix remodeling, and cell stress, respectively. The spatial distribution of genes allowed us to identify genes that were potentially relevant with TAD. NINJ1 encoded the protein-mediated cytoplasmic membrane rupture, regulated tissue remodeling, showed high expression levels in the tear area, and co-expressed within the inflammatory pattern. The use of short hairpin RNA to reduce NINJ1 expression in the beta-aminopropionitrile-induced TAD model led to a significant decrease in TAD formation. Additionally, it resulted in reduced infiltration of inflammatory cells and a decrease in the number of CD31+α-SMA+ cells. The NINJ1-neutralizing antibody also demonstrated comparable therapeutic effects and can effectively impede the formation of TAD. CONCLUSIONS: Our study showed that Tomo-seq had the advantage of obtaining spatial expression information of TAD across the TA and the RA. We pointed out that NINJ1 may be involved in inflammation and tissue remodeling, which played an important role in the formation of TAD. NINJ1 may serve as a potential therapeutic target for TAD.

A multitask deep learning radiomics model for predicting the macrotrabecular-massive subtype and prognosis of hepatocellular carcinoma after hepatic arterial infusion chemotherapy.

BACKGROUND: The macrotrabecular-massive (MTM) is a special subtype of hepatocellular carcinoma (HCC), which has commonly a dismal prognosis. This study aimed to develop a multitask deep learning radiomics (MDLR) model for predicting MTM and HCC patients' prognosis after hepatic arterial infusion chemotherapy (HAIC). METHODS: From June 2018 to March 2020, 158 eligible patients with HCC who underwent surgery were retrospectively enrolled in MTM related cohorts, and 752 HCC patients who underwent HAIC were included in HAIC related cohorts during the same period. DLR features were extracted from dual-phase (arterial phase and venous phase) contrast-enhanced computed tomography (CECT) of the entire liver region. Then, an MDLR model was used for the simultaneous prediction of the MTM subtype and patient prognosis after HAIC. The MDLR model for prognostic risk stratification incorporated DLR signatures, clinical variables and MTM subtype. FINDINGS: The predictive performance of the DLR model for the MTM subtype was 0.968 in the training cohort [TC], 0.912 in the internal test cohort [ITC] and 0.773 in the external test cohort [ETC], respectively. Multivariable analysis identified portal vein tumor thrombus (PVTT) (p = 0.012), HAIC response (p < 0.001), HAIC sessions (p < 0.001) and MTM subtype (p < 0.001) as indicators of poor prognosis. After incorporating DLR signatures, the MDLR model yielded the best performance among all models (AUC, 0.855 in the TC, 0.805 in the ITC and 0.792 in the ETC). With these variables, the MDLR model provided two risk strata for overall survival (OS) in the TC: low risk (5-year OS, 44.9%) and high risk (5-year OS, 4.9%). INTERPRETATION: A tool based on MDLR was developed to consider that the MTM is an important prognosis factor for HCC patients. MDLR showed outstanding performance for the prognostic risk stratification of HCC patients who underwent HAIC and may help physicians with therapeutic decision making and surveillance strategy selection in clinical practice.

The challenges and opportunities of scRNA-seq in COVID-19 research and clinical translation.

The application of single-cell RNA sequencing in COVID-19 research has greatly improved our understanding of COVID-19 pathogenesis and immunological characteristics. In this commentary, we discuss the current challenges, limitations, and perspectives in harnessing the power of single-cell RNA sequencing to accelerate both basic research and therapeutic development for COVID-19 and other emerging infectious diseases.

Single-Cell Transcriptomic Atlas of Different Human Cardiac Arteries Identifies Cell Types Associated With Vascular Physiology.

[Figure: see text].

Single-cell alternative splicing analysis reveals dominance of single transcript variant.

Alternative splicing contributes to the diversity of gene products by producing multiple transcript variants from one gene. Previous studies have revealed highly variable splicing patterns in single cells, but there is still a controversy in the understanding of the simultaneous expression of multiple transcript variants. Here we show that the dominance of a single transcript variant is a common phenomenon in single cells. We analyzed several single-cell RNA sequencing datasets and observed consistent results. Our results demonstrate that single cells tend to express one major transcript variant of a gene, and the diversity of transcript variants in cell populations mainly results from the heterogeneity of splicing pattern in single cells.

Single-Cell Transcriptomics Reveals Pre-existing COVID-19 Vulnerability Factors in Lung Cancer Patients.

Coronavirus disease 2019 (COVID-19) and cancer are major health threats, and individuals may develop both simultaneously. Recent studies have indicated that patients with cancer are particularly vulnerable to COVID-19, but the molecular mechanisms underlying the associations remain poorly understood. To address this knowledge gap, we collected single-cell RNA-sequencing data from COVID-19, lung adenocarcinoma, small cell lung carcinoma patients, and normal lungs to perform an integrated analysis. We characterized altered cell populations, gene expression, and dysregulated intercellular communication in diseases. Our analysis identified pathologic conditions shared by COVID-19 and lung cancer, including upregulated TMPRSS2 expression in epithelial cells, stronger inflammatory responses mediated by macrophages, increased T-cell response suppression, and elevated fibrosis risk by pathologic fibroblasts. These pre-existing conditions in patients with lung cancer may lead to more severe inflammation, fibrosis, and weakened adaptive immune response upon COVID-19 infection. Our findings revealed potential molecular mechanisms driving an increased COVID-19 risk in patients with lung cancer and suggested preventive and therapeutic targets for COVID-19 in this population. IMPLICATIONS: Our work reveals the potential molecular mechanisms contributing to the vulnerability to COVID-19 in patients with lung cancer.

Efficiency and safety of hepatic arterial infusion chemotherapy (HAIC) combined with anti-PD1 therapy versus HAIC monotherapy for advanced hepatocellular carcinoma: A multicenter propensity score matching analysis.

PURPOSE: To investigate the clinical efficacy and safety of combination therapy of hepatic arterial infusion chemotherapy (HAIC) and anti-programmed cell death protein-1 (PD-1) therapy in the treatment of advanced hepatocellular carcinoma (HCC). METHODS: In this retrospective clinical research, from March 2018 to December 2019, 1158 HCC patients categorized as BCLC stage C were reviewed for eligibility. We utilized propensity score matching (PSM) to mitigate initial disparities between the groups. The evaluation of the best tumor response was conducted in accordance with mRECIST 1.1 criteria. The difference in survival outcomes including overall survival (OS), progression-free survival (PFS), and objective response rate (ORR) between groups were compared. RESULTS: Following the eligibility review, 453 patients underwent a combined treatment of HAIC with PD1 inhibitors (HAIC-PD1 group), while 221 patients received HAIC monotherapy (HAIC group) met the inclusion criteria and were finally enrolled in this study. In the entire cohort, the HAIC-PD1 group exhibited significantly prolonged overall survival (median overall survival: 40.4 months vs. 9.7 months, p < 0.001) and progression-free survival (median progression-free survival: 22.1 months vs. 5.8 months, p < 0.001). By propensity score, patients were matched according to baseline differences, resulting in all 442 patients in group HAIC-PD1 (n = 221) and group HAIC (n = 221). After PSM adjustment, as well, the survival of the HAIC-PD1 group was still distinctly longer than the HAIC group (median overall survival time, 40.4 months vs 9.7 months, p < 0.001; median progression-free survival, 22.1 months vs 5.7 months, p < 0.001). Univariate and multivariable analysis demonstrated that AFP level, metastasis, and therapeutic schedule were independent predictive factors for overall survival. CONCLUSION: The combination therapy of HAIC and PD1 inhibitors successfully extended OS to advanced HCC patients and could be a better choice than HAIC monotherapy.

Hepatic artery infusion chemotherapy combined with camrelizumab plus rivoceranib for hepatocellular carcinoma with portal vein tumor thrombosis: a multicenter propensity score-matching analysis.

BACKGROUND: Portal vein tumor thrombosis (PVTT) signifies late-stage hepatocellular carcinoma (HCC) with high-risk progression and poor prognosis. As a standard treatment, sorafenib monotherapy has limited the efficacy in managing HCC with PVTT. Currently, both hepatic arterial infusion chemotherapy (HAIC) and the combination of camrelizumab and rivoceranib have shown favorable survival benefits for advanced HCC, surpassing the standard sorafenib treatment. In this study, we investigate the safety and efficacy of HAIC combined with camrelizumab and rivoceranib in treating HCC patients with PVTT. METHODS: From January 2020 to December 2021, HCC patients with PVTT, who received either a triple regime of HAIC combined with camrelizumab and rivoceranib or a dual regime of camrelizumab and rivoceranib as their first-line treatment, were reviewed for eligibility at four hospital centers in China. To balance any intergroup differences, propensity score matching (PSM) was applied. The aim of this study is to compare the efficacy of the dual and triple combination treatment regimens based on survival prognosis and tumor response and evaluate the safety based on the occurrence of adverse reactions. RESULT: In this study, a total of 411 patients who received either the triple treatment regime (HAIC combined with camrelizumab plus rivoceranib, referred to as the HAICCR group, n = 292) or the dual treatment regime (camrelizumab combined with rivoceranib, referred to as the CR group, n = 119) between January 2020 and December 2021 were included. The results showed that the HAICCR group exhibited significantly better overall survival (mOS: 19.60 months vs. 11.50 months, p < 0.0001) and progression-free survival (mPFS: 10.0 months vs. 5.6 months, p < 0.0001) compared to the CR group in the overall cohort. Moreover, the HAICCR group also had a significantly higher ORR (objective response rate, 55.5% vs. 42.0%, p = 0.013) and DCR (disease control rate, 89.0% vs. 79.0%) compared to the CR group. After PSM, a final matched cohort of 83 pairs was obtained, and the survival benefits were consistent in this cohort as well (mOS: 18.70 months vs. 11.0 months, p < 0.0001; mPFS: 10.0 months vs. 5.6 months, p < 0.0001). However, there was no significant difference in the ORR between the triple and dual combination regimes. Univariate and multivariate analysis showed that CTP (Child-Turcotte-Pugh) stage, ALBI (albumin-bilirubin index) grade, tumor number, and treatment regime were significant risk factors affecting overall survival, while AFP (α-fetoprotein) level, tumor number, metastasis, and treatment regime were significant risk factors affecting progression-free survival. As for safety, hypertension and hand-foot syndrome were the two most common adverse reactions in both groups, with no significant difference in the occurrence of adverse reactions between the two groups (p < 0.05). CONCLUSION: In the context of advanced HCC patients with PVTT, the combination regime of HAIC and camrelizumab plus rivoceranib demonstrates more excellent capacity for prolonging survival and offers a well-tolerated safety compared to the CR dual therapy approach. This triple regime represents a therapeutic modality of broad prospects and vast potential for HCC patients with PVTT.

Peripheral blood lymphocyte subsets predict the efficacy of TACE with or without PD-1 inhibitors in patients with hepatocellular carcinoma: a prospective clinical study.

Background: Although peripheral blood lymphocyte subsets, particularly PD-1+ T cells, are promising prognostic indicators for patients with cancer. However, their clinical significance remains unclear. Methods: We prospectively enrolled 157 patients with hepatocellular carcinoma (HCC) treated with transcatheter arterial chemoembolization combined with or without PD-1 inhibitors. Twenty peripheral lymphocyte subsets and cytokines were analyzed. We analyzed the differences in PD-1+ T cells between patients treated with and without PD-1 inhibitors and their associations with tumor response, survival prognosis, and clinical features. Results: We found that the baseline CD8+PD-1+ and CD4+PD-1+ T-cell frequencies in patients who had received PD-1 inhibitors were lower than those in patients who had not received PD-1 inhibitors (p < 0.001). In the former patients, there were no differences in PD-1+ T-cell frequencies between the responder and non-responder subgroups (p > 0.05), whereas in the latter patients, the levels of CD8+PD-1+ T cells, CD4+PD-1+ T cells, and CD8+PD-1+/CD4+PD-1+ ratio did not predict tumor response, progression-free survival (PFS), or overall survival (OS) (p>0.05). Furthermore, in multivariate analysis of patients treated with or without PD-1 inhibitors revealed that the levels of CD8+CD38+ T cells (OR = 2.806, p = 0.006) were associated with tumor response, whereas those of CD8+CD28+ T cells (p = 0.038, p = 0.001) and natural killer (NK) cells (p = 0.001, p = 0.027) were associated with PFS and OS. Although, these independent prognostic factors were associated with progressive tumor characteristics (p<0.05), with the exception of CD8+CD28+ T cells, changes in these factors before and after treatment were unassociated with tumor response (p > 0.05). Conclusion: Circulating CD8+CD38+ T cells, CD8+CD28+ T cells, and NK cells were identified as potential prognostic factors for tumor response and survival in patients with HCC. Contrastingly, although PD-1 inhibitors can effectively block the T cell PD-1 receptor, the baseline PD-1+ T-cell frequencies and changes in the frequency of these cells have limited prognostic value.

Analysis of MicroRNA Regulation and Gene Expression Variability in Single Cell Data.

MicroRNAs (miRNAs) regulate gene expression by binding to mRNAs, and thus reduce target gene expression levels and expression variability, also known as 'noise'. Single-cell RNA sequencing (scRNA-seq) technology has been used to study miRNA and mRNA expression in single cells. To evaluate scRNA-seq as a tool for investigating miRNA regulation, we analyzed datasets with both mRNA and miRNA expression in single-cell format. We found that miRNAs slightly reduce the expression noise of target genes; however, this effect is easily masked by strong technical noise from scRNA-seq. We suggest improvements aimed at reducing technical noise, which can be implemented in experimental design and computational analysis prior to running scRNA-seq. Our study provides useful guidelines for experiments that evaluate the effect of miRNAs on mRNA expression from scRNA-seq.

Delineating COVID-19 immunological features using single-cell RNA sequencing.

Understanding the molecular mechanisms of coronavirus disease 2019 (COVID-19) pathogenesis and immune response is vital for developing therapies. Single-cell RNA sequencing has been applied to delineate the cellular heterogeneity of the host response toward COVID-19 in multiple tissues and organs. Here, we review the applications and findings from over 80 original COVID-19 single-cell RNA sequencing studies as well as many secondary analysis studies. We describe that single-cell RNA sequencing reveals multiple features of COVID-19 patients with different severity, including cell populations with proportional alteration, COVID-19-induced genes and pathways, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection in single cells, and adaptation of immune repertoire. We also collect published single-cell RNA sequencing datasets from original studies. Finally, we discuss the limitations in current studies and perspectives for future advance.

Drug-Target Network Study Reveals the Core Target-Protein Interactions of Various COVID-19 Treatments.

The coronavirus disease 2019 (COVID-19) pandemic has caused a dramatic loss of human life and devastated the worldwide economy. Numerous efforts have been made to mitigate COVID-19 symptoms and reduce the death rate. We conducted literature mining of more than 250 thousand published works and curated the 174 most widely used COVID-19 medications. Overlaid with the human protein-protein interaction (PPI) network, we used Steiner tree analysis to extract a core subnetwork that grew from the pharmacological targets of ten credible drugs ascertained by the CTD database. The resultant core subnetwork consisted of 34 interconnected genes, which were associated with 36 drugs. Immune cell membrane receptors, the downstream cellular signaling cascade, and severe COVID-19 symptom risk were significantly enriched for the core subnetwork genes. The lung mast cell was most enriched for the target genes among 1355 human tissue-cell types. Human bronchoalveolar lavage fluid COVID-19 single-cell RNA-Seq data highlighted the fact that T cells and macrophages have the most overlapping genes from the core subnetwork. Overall, we constructed an actionable human target-protein module that mainly involved anti-inflammatory/antiviral entry functions and highly overlapped with COVID-19-severity-related genes. Our findings could serve as a knowledge base for guiding drug discovery or drug repurposing to confront the fast-evolving SARS-CoV-2 virus and other severe infectious diseases.

Analysis of microRNA Regulation in Single Cells.

MicroRNAs (miRNAs) regulate gene expression by binding to mRNAs. Consequently, they reduce target gene expression levels and expression variability, also known as "noise." Single-cell RNA sequencing (scRNA-seq) technology has been used to study miRNA and mRNA expression in single cells, and has demonstrated its strength in quantifying cell-to-cell variation. Here we describe how to investigate miRNA regulation using data with both mRNA and miRNA expression in single cell format. We show that miRNAs reduce the expression levels and also expression noise of target genes in single cells. Finally, we also discuss potential improvements in experimental design and computational analysis of scRNA-seq in order to reduce or partition the technical noise.

Prognostic significance of programmed cell death-ligand 1 expression on circulating tumor cells in various cancers: A systematic review and meta-analysis.

BACKGROUND: The prognostic significance of programmed cell death-ligand 1 (PD-L1) expression on circulating tumor cells (CTCs) has been explored but is still in controversy. We performed, for the first time, a meta-analysis to systematically evaluate its prognostic value in human cancers. METHODS: Literature databases were searched for eligible studies prior to June 30, 2021. The pooled hazard ratios (HRs) and 95% confidence intervals (95% CIs) were calculated for the associations of pre-treatment and post-treatment PD-L1+ CTCs with progression-free survival (PFS) and overall survival (OS). Subgroup analyses with regards to cancer type, treatment, CTC enrichment method, PD-L1 detection method, cut-off, and specifically the comparison model were performed. RESULTS: We included 30 eligible studies (32 cohorts, 1419 cancer patients) in our analysis. Pre-treatment PD-L1+ CTCs detected by immunofluorescence (IF) tended to predict better PFS (HR = 0.55, 95% CI 0.28-1.08, p = 0.084) and OS (HR = 0.61, 95% CI 0.36-1.04, p = 0.067) for immune checkpoint inhibitor (ICI) treatment, but were significantly associated with unfavorable survival for non-ICI therapies (PFS: HR = 1.85, 95% CI 1.21-2.85, p = 0.005; OS: HR = 2.44, 95% CI 1.69-3.51, p < 0.001). Post-treatment PD-L1+ CTCs predicted markedly worse PFS and OS. The prognostic value was obviously modulated by comparison models. Among patients with detectable CTCs, PD-L1+ individuals had comparable survival to PD-L1- individuals, except ICI treatment for which PD-L1+ may predict better PFS (HR = 0.42, 95% CI 0.17-1.06, p = 0.067). Patients with PD-L1+ CTCs had worse survival prognosis compared to those without PD-L1+ CTCs in overall analysis (PFS: HR = 2.10, 95% CI 1.59-2.77, p < 0.001; OS: HR = 2.55, 95% CI 1.70-3.81, p < 0.001) and in most subgroups. CONCLUSIONS: Our analysis demonstrated that PD-L1 positive expression on CTCs predicted better survival prognosis for ICI treatment but worse survival for other therapies, which thus can be potentially used as a prognostic marker of malignant tumor treatment. However, the prognostic value of PD-L1+ CTCs for ICI treatment needs validation by more large-scale studies in the future.

Mid-term outcomes of endovascular treatment and risk factors for recurrence in patients with Trans-Atlantic-Inter-Society II C/D femoropopliteal lesions.

BACKGROUND: The purpose of this study was to determine the efficacy of interventional endovascular treatment (EVT) and the risk factors for postoperative restenosis in patients with Trans-Atlantic Inter-Society Consensus (TASC) II C/D femoropopliteal lesions. METHODS: A total of 55 patients who received EVT for TASC II C/D femoropopliteal lesions (64 affected limbs) from October 2014 to September 2017 were examined. The mean lesion length was 19.6±5.3 (range, 15.5-26.4 cm). The femoropopliteal lesions were classified as TASC II C and TASC II D in 39 and 16 cases, respectively. The ankle-brachial index (ABI), primary patency rate, secondary patency rate, and limb salvage rate were monitored in follow-up evaluations for up to 24 months. A Cox regression model was used to evaluate the correlation between each of these factors and the restenosis rate after EVT. RESULTS: Patent TASC II C/D femoropopliteal lesions were present in 59 of the 64 limbs. The mean ABI values for the dorsal pedal artery and posterior tibial artery increased 1 month after treatment from a baseline level of 0.35±0.12 to 0.89±0.10 and from 0.43±0.15 to 0.90±0.13, respectively (P<0.01). The mean follow-up time was 19.3 (range, 6-24) months. The cumulative primary patency rates at 1, 3, 6, 12, 18, and 24 months were 98.3%, 91.5%, 84.3%, 61.1%, 53.1%, and 31.1%, respectively. The secondary patency rates at 12 and 24 months were 70.4% and 60.0%, respectively. Factors with a high hazard ratio included male sex, TASC II D, smoking, and diabetes mellitus (DM). CONCLUSIONS: EVT had a safe and satisfactory mid-term therapeutic effect on TASC II C/D femoropopliteal lesions. Male sex, TASC II D (compared to TASC II C), smoking, and DM were risk factors for restenosis. EVT has a secondary patency rate comparable to that of open surgery and can be considered a first-line treatment for TASC II C/D femoropopliteal lesions.

A review of Cremastra appendiculata (D.Don) Makino as a traditional herbal medicine and its main components.

ETHNOPHARMACOLOGICAL RELEVANCE: Cremastra appendiculata (D.Don) Makino is a herbal medicine with a medicinal history of more than a thousand years in China. It is traditionally used to treat carbuncle, swelling, abscess, fistula, scrofula and scleroma (related to modern lymph node enlargement and various tumors.). AIM OF THE REVIEW: This paper comprehensively reviewed the botany, traditional application, phytochemistry, pharmacological activities, and quality control of C. appendiculata, discussesed the application of ethnic medicine, modern scientific research and the relationship between them, and put forward some suggestions to promote the further development and utilization of C. appendiculata. We hope to provide a valuable reference for all researchers who are interested in obtaining relevant information about C. appendiculata. MATERIALS AND METHODS: The relevant information on C. appendiculata was collected through published materials and electronic databases, including ancient and modern books, Chinese Pharmacopoeia, Ph.D. and M. Sc. dissertations, PubMed, ScienceDirect, Wiley, ACS, CNKI, Springer, Taylor & Francis, Web of Science, Google Scholar, and Baidu Scholar. RESULTS: At present, 190 compounds have been isolated from C. appendiculata, including phenanthrene, dihydrophenanthrene, bibenzyl, flavonoids, terpenoids, glycosides, aromatics, and other compounds. These compounds have been reported to have a variety of pharmacological activities, such as anti-tumor, anti-bacterial, anti-angiogenesis, anti-oxidation, etc. Modern pharmacological studies have proved that C. appendiculata has significant anti-tumor activity and has a good therapeutic effect on liver cancer, gastric cancer, colon cancer, breast cancer, thyroid cancer and other malignant tumors. CONCLUSIONS: C. appendiculata is not only an excellent traditional Chinese medicine for the treatment of tumors, but also a source of bioactive molecules with good application prospects. At present, the close relationship between the chemical components and pharmacological activities of C. appendiculata has not been established, and there is a lack of systematic and in-depth research on its anti-tumor components and its mechanism. In addition, it is necessary to establish systematic and effective index components and determination standards of C. appendiculata to better explore its therapeutic potential. Therefore, it is necessary to carry out further research on C. appendiculata.