The chemical constituents from the n-butanol fraction of ethanol extract of safflower (Carthamus tinctorius L.) were isolated and purified using chromatographic process including MCI Gel CHP-20, ODS, Sephadex LH-20 column chromatography, and semi-preparative HPLC method, and one alkyne and two phenylpropanoid derivants were obtained. Their structures were identified as (5R,E)-tetradecane-12-ene-8,10-diyne-1,5,14-triol (1), (E)-8-O-β-D-glucopyranosyl n-butyl cinnamate (2), and (7S,8S)-7-(4-hydroxy-3-methoxybenzene)-7-butyl-8,9-diol (3) by modern spectroscopy methods (1D NMR, 2D NMR, UV, IR and MS). 1-3 are all new compounds. Compounds 1-3 were screened for their anti-renal fibrosis activities in vitro, and none of them showed obvious effect.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

In order to compare the differences in growth and secondary metabolite accumulation of Panax quinquefolius between understory and field planting, growth indexes, photosynthetic characteristics, soil enzyme activities, secondary metabolite contents, and antioxidant activities of P. quinquefolius under different planting modes were examined and compared, and One-way analysis of variance(ANOVA) and correlation analyses were carried out by using the software SPSS 25.0 and GraphPad Prism 9.5. The Origin 2021 software was used for plotting. The results showed that compared with those under field planting, the plant height, leaf length, leaf width, photosynthetic rate, and chlorophyll content of P. quinquefolius under understory planting were significantly reduced, and arbuscular mycorrhizal fungi(AMF) infestation rate and infestation intensity, ginsenoside content, and antioxidant activity were significantly increased. The activities of inter-root soil urease, sucrase, and catalase increased, while the activities of non-inter-root soil urease and alkaline phosphatase increased. Correlation analyses showed that the plant height and leaf length of P. quinquefolius plant were significantly positively correlated with net photosynthetic rate, transpiration rate, chlorophyll content, and electron transfer rate(P<0.05), while ginsenoside content was significantly negatively correlated with net photosynthetic rate, chlorophyll content, and electron transfer rate(P<0.05) and significantly positively correlated with AMF infestation rate and infestation intensity(P<0.05). In addition, ginsenoside content was significantly positively correlated with the activities of inter-root soil sucrase, urease, and catalase(P<0.05). This study provides basic data for revealing the mechanism of secondary metabolite accumulation in P. quinquefolius under understory planting and for exploring and practicing the ecological mode of P. quinquefolius under understory planting.
Panax/microbiology* ; China ; Secondary Metabolism ; Soil/chemistry* ; Photosynthesis ; Plant Leaves/metabolism* ; Chlorophyll/metabolism* ; Mycorrhizae

This study explores the therapeutic differences and mechanisms of salt-processed Phellodendri Chinensis Cortex in improving insulin resistance(IR) based on network pharmacology, molecular docking, and cellular experiments. The components and intersection targets of Phellodendri Chinensis Cortex in improving IR were collected from databases, and a "drug-component-target-disease" network and protein-protein interaction(PPI) network were constructed to screen core components and targets. A total of 29 active components and 240 intersection targets were identified, of which 13 were core targets. Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analyses were used to identify key signaling pathways, and molecular docking was performed to validate the binding activity between core components and targets. An IR model in HepG2 cells was induced using insulin combined with high glucose, and the effects of Phellodendri Chinensis Cortex before and after salt-processing on cell glucose consumption were evaluated. The expression of proteins related to the mitogen-activated protein kinase(MAPK) and phosphatidylinositol 3-kinase(PI3K)-protein kinase B(AKT) signaling pathways was detected by Western blot. The cellular experimental results showed that, compared with the model group, glucose consumption in the drug-treated groups was significantly increased(P<0.01), the phosphorylation level of extracellular regulated protein kinase(ERK) was decreased(P<0.05), the phosphorylation levels of PI3K and AKT were increased, and the expression of glucose transporter 4(GLUT4) was also upregulated(P<0.05). Furthermore, the effect of salt-processed Phellodendri Chinensis Cortex was better than that of raw Phellodendri Chinensis Cortex. The study demonstrates that Phellodendri Chinensis Cortex, both before and after salt-processing, improves IR by regulating the expression of related proteins in the MAPK and PI3K-AKT signaling pathways, with enhanced effects after salt-processing.
Humans ; Network Pharmacology ; Phellodendron/chemistry* ; Insulin Resistance ; Drugs, Chinese Herbal/chemistry* ; Hep G2 Cells ; Signal Transduction/drug effects* ; Molecular Docking Simulation ; Protein Interaction Maps/drug effects* ; Proto-Oncogene Proteins c-akt/genetics* ; Phosphatidylinositol 3-Kinases/genetics* ; Glucose/metabolism*

Objective： The aim of this study is to explore the predictive value of biparametric magnetic resonance imaging(bpMRI)for pelvic lymph node metastasis in prostate cancer patients with PSA≤20 μg/L and establish a nomogram. Methods： The imaging data and clinical data of 363 patients undergoing radical prostatectomy and pelvic lymph node dissection in the First Affiliated Hospital of Nanjing Medical University from July 2018 to December 2023 were retrospectively analyzed. Univariate analysis and multivariate logistic regression were used to screen independent risk factors for pelvic lymph node metastasis in prostate cancer, and a nomogram of the clinical prediction model was established. Calibration curves were drawn to evaluate the accuracy of the model. Results： Multivariate logistic regression analysis showed extrocapusular extension (OR=8.08,95%CI=2.62－24.97, P<0.01), enlargement of pelvic lymph nodes (OR=4.45,95%CI=1.16－17.11,P=0.030), and biopsy ISUP grade(OR=1.97,95%CI=1.12－3.46, P=0.018)were independent risk factors for pelvic lymph node metastasis. The C-index of the prediction model was 0.834, which indicated that the model had a good prediction ability. The actual value of the model calibration curve and the prediction probability of the model fitted well, indicating that the model had a good accuracy. Further analysis of DCA curve showed that the model had good clinical application value when the risk threshold ranged from 0.05 to 0.70.Conclusion： For prostate cancer patients with PSA≤20 μg/L, bpMRI has a good predictive value for the pelvic lymph node metastasis of prostate cancer with extrocapusular extension, enlargement of pelvic lymph nodes and ISUP grade≥4.
Humans ; Male ; Prostatic Neoplasms/diagnostic imaging* ; Lymphatic Metastasis ; Retrospective Studies ; Nomograms ; Prostate-Specific Antigen/blood* ; Lymph Nodes/pathology* ; Pelvis ; Predictive Value of Tests ; Prostatectomy ; Lymph Node Excision ; Risk Factors ; Magnetic Resonance Imaging ; Logistic Models ; Middle Aged ; Aged

OBJECTIVE: To evaluate the safety and effectiveness of robot-assisted percutaneous coronary intervention (R-PCI) compared to traditional manual percutaneous coronary intervention (M-PCI). METHODS: This prospective, multicenter, randomized controlled, non-inferior clinical trial enrolled patients with coronary heart disease who met the inclusion criteria and had indications for elective percutaneous coronary intervention. Participants were randomly assigned to either the R-PCI group or the M-PCI group. Primary endpoints were clinical and technical success rates. Clinical success was defined as visually estimated residual post-percutaneous coronary intervention stenosis < 30% with no 30-day major adverse cardiac events. Technical success in the R-PCI group was defined as successful completion of percutaneous coronary intervention using the ETcath200 robot-assisted system, without conversion to M-PCI in the event of a guidewire or balloon/stent catheter that was unable to cross the vessel or was poorly supported by the catheter. Secondary endpoints included total procedure time, percutaneous coronary intervention procedure time, fluoroscopy time, contrast volume, operator radiation exposure, air kerma, and dose-area product. RESULTS: The trial enrolled 152 patients (R-PCI: 73 patients, M-PCI: 79 patients). Lesions were predominantly B2/C type (73.6%). Both groups achieved 100% clinical success rate. No major adverse cardiac events occurred during the 30-day follow-up. The R-PCI group had a technical success rate of 100%. The R-PCI group had longer total procedure and fluoroscopy times, but lower operator radiation exposure. The percutaneous coronary intervention procedure time, contrast volume, air kerma, and dose-area product were similar between the two groups. CONCLUSIONS For certain complex lesions, performing percutaneous coronary intervention using the ETcath200 robot-assisted system is safe and effective and does not result in conversion to M-PCI.

BACKGROUND: Non-invasive computed tomography angiography (CTA)-based fractional flow reserve (CT-FFR) could become a gatekeeper to invasive coronary angiography. Deep learning (DL)-based CT-FFR has shown promise when compared to invasive FFR. To evaluate the performance of a DL-based CT-FFR technique, DeepVessel FFR (DVFFR). METHODS: This retrospective study was designed for iScheMia Assessment based on a Retrospective, single-center Trial of CT-FFR (SMART). Patients suspected of stable coronary artery disease (CAD) and undergoing both CTA and invasive FFR examinations were consecutively selected from the Beijing Anzhen Hospital between January 1, 2016 to December 30, 2018. FFR obtained during invasive coronary angiography was used as the reference standard. DVFFR was calculated blindly using a DL-based CT-FFR approach that utilized the complete tree structure of the coronary arteries. RESULTS: Three hundred and thirty nine patients (60.5 ±10.0 years and 209 men) and 414 vessels with direct invasive FFR were included in the analysis. At per-vessel level, sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) of DVFFR were 94.7%, 88.6%, 90.8%, 82.7%, and 96.7%, respectively. The area under the receiver operating characteristics curve (AUC) was 0.95 for DVFFR and 0.56 for CTA-based assessment with a significant difference (P < 0.0001). At patient level, sensitivity, specificity, accuracy, PPV and NPV of DVFFR were 93.8%, 88.0%, 90.3%, 83.0%, and 95.8%, respectively. The computation for DVFFR was fast with the average time of 22.5 ± 1.9 s. CONCLUSIONS The results demonstrate that DVFFR was able to evaluate lesion hemodynamic significance accurately and effectively with improved diagnostic performance over CTA alone. Coronary artery disease (CAD) is a critical disease in which coronary artery luminal narrowing may result in myocardial ischemia. Early and effective assessment of myocardial ischemia is essential for optimal treatment planning so as to improve the quality of life and reduce medical costs.

Radiation mainly comes from medical radiation,industrial radiation,nuclear waste and atmospheric ultraviolet radiation,etc.,radiation is divided into ionizing radiation and non-ionizing radiation.Studying the effects of ionizing and non-ionizing radiation on drug metabolism,understanding the absorption and distribution of drugs in the body after radiation and the speed of elimination under radiation conditions can provide reasonable guidance for clinical medication.This article reviews the effects of radiation on the pharmacokinetics of different drugs,elaborates the changes of different pharmacokinetics under radiation state,and discusses the reasons for the changes.