Eight compounds were isolated and purified from the ethyl acetate part of 70% acetone extract of Rehmannia glutinosa by various chromatographic techniques such as silica gel, MCI gel CHP-20, ODS, Toyopearl HW-40C, combined with TLC and semi-preparative HPLC. Their structures were elucidated by modern spectroscopy techniques (NMR, MS, UV, IR), and identified as neomartynoside A (1), osmanthuside B₆ (2), martynoside (3), isomartynoside (4), (E)-p-hydroxycinnamic acid (5), caffeic acid (6), ferulic acid (7), and methyl caffeate (8). Compound 1 is a new phenylethanol glycoside, which was identified as neomartynoside A. Compound 2 was isolated from Rehmannia glutinosa for the first time. In addition, compounds 2, 6 and 7 significantly increased relative glucose consumption, showing potential hypoglycemic activity.

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 recent years, the deep integration of artificial intelligence (AI) into medical education has created new opportunities for teaching Biochemistry and Molecular Biology, while also offering innovative solutions to the pedagogical challenges associated with protein structure and function. Focusing on the case of anaplastic lymphoma kinase (ALK) gene mutations in non-small-cell lung cancer (NSCLC), this study integrates AI into case-based learning (CBL) to develop an AI-CBL hybrid teaching model. This model features an intelligent case-generation system that dynamically constructs ALK mutation scenarios using real-world clinical data, closely linking molecular biology concepts with clinical applications. It incorporates AI-powered protein structure prediction tools to accurately visualize the three-dimensional structures of both wild-type and mutant ALK proteins, dynamically simulating functional abnormalities resulting from conformational changes. Additionally, a virtual simulation platform replicates the ALK gene detection workflow, bridging theoretical knowledge with practical skills. As a result, a multidimensional teaching system is established—driven by clinical cases and integrating molecular structural analysis with experimental validation. Teaching outcomes indicate that the three-dimensional visualization, dynamic interactivity, and intelligent analytical capabilities provided by AI significantly enhance students’ understanding of molecular mechanisms, classroom engagement, and capacity for innovative research. This model establishes a coherent training pathway linking “fundamental theory-scientific research thinking-clinical practice”, offering an effective approach to addressing teaching challenges and advancing the intelligent transformation of medical education.

Objective To evaluate the influence of the wearing position of dosimeters outside lead aprons on effective dose estimation for interventional radiology workers, analyze the differences between single and double dosimeter methods in effective dose estimation, and provide a reference for the personal dose monitoring of interventional radiology workers. Methods This study employed a combined approach of on-site monitoring and Monte Carlo simulation to evaluate the impact of the wearing position of dosimeters outside lead aprons on effective dose estimation, as well as the differences between effective doses measured using single and double dosimeters. Interventional radiology workers wore dosimeters at three positions: the neck outside the lead collar, the left chest outside the lead apron, and inside the lead apron. Effective doses were estimated using the single and double dosimeter methods specified in GBZ 128-2019 Specifications for individual monitoring of occupational external exposure, and the impact of different wearing positions on the estimation results was compared. Geant4 Monte Carlo simulations were used to model dose distributions at the neck outside the lead collar and at the left chest outside the lead apron for operators performing cardiovascular interventions under tube voltages of 70, 80, 90, and 100 kVp and exposure angles of posteroanterior (PA), anteroposterior (AP), and left anterior oblique 45° (LAO45°) positions. The study assessed the impact of dosimeter wearing position on effective dose estimation. Results Monte Carlo simulations demonstrated that neck doses consistently exceeded left chest doses across different tube voltages and exposure angles, with neck-to-chest dose ratios of 0.80-0.90. Under identical tube voltage conditions, AP showed the highest doses, followed by LAO45°, and PA demonstrated the lowest doses. The single and double dosimeter methods exhibited consistent patterns in effective dose estimation. Single dosimeter method generally yielded higher effective doses with relative deviations of 9.9% to 83%, though these deviations decreased under high tube voltages. Field monitoring data indicated that most interventional radiology workers maintained relative deviations between single and double dosimeter calculations below 6%, with neck-to-chest dose ratios of 0.95-1.1. The estimation patterns remained consistent across both methods, though single dosimeter method showed slightly higher results. Conclusion Under PA, AP, or LAO45°, the doses at the neck consistently exceeded those at the left chest. Therefore, when wearing lead protective equipment, the dosimeter should be properly positioned at the neck outside the lead collar to accurately reflect the radiation doses of surgeons. Some interventional radiology workers improperly positioned the dosimeter (intended at the neck outside the lead collar) at the left chest outside the lead apron, and this may result in an underestimation of the effective dose.

Objective To explore the protective mechanism of icariin on neuronal oxidative damage,providing a basic pharmacological basis for the treatment of cognitive impairment.Methods Glutamate was used to induce oxidative stress injury in HT22 cells.HT22 cells were divided into control group(normal cultured cells),model group(glutamate injury model)and experimental-L,-M,-H groups(5,10 and 20 μmol·L-1 icariin pretreatment for modeling,respectively).Cell proliferation was detected by cell counting kit-8(CCK-8)method;cytotoxicity was detected by lactate dehydrogenase(LDH)method;reactive oxygen species(ROS)levels were detected by flow cytometry;superoxide dismutase(SOD)levels were detected by biochemical kits;the expression levels of Kelch-like epichlorohydrin-related protein-1(Keap1),nuclear factor E2-related factor 2(Nrf2)were detected by Western blotting;the corresponding mRNA expression was detected by real-time fluorescence quantification polymerose chain reaction.Results The cell viability of control group,model group and experimental-L,-M,-H groups were(100.00±1.31)％,(66.38±2.44)％,(72.07±4.95)％,(82.41±3.57)％and(87.97±4.98)％;LDH release were(0.48±0.52)％,(18.82±2.09)％,(15.32±1.17)％,(10.37±1.39)％and(6.51±0.87)％;ROS level were(14.23±1.13)％,(41.74±1.60)％,(35.69±1.08)％,(33.28±1.69)％and(30.32±2.03)％;SOD levels were(54.84±1.17),(37.95±1.13),(48.02±1.28),(50.56±1.34)and(52.55±1.04)U·mg-1;Keap1 protein levels were 0.36±0.01,0.52±0.03,0.46±0.04,0.39±0.09 and 0.35±0.12;Nrf2 protein levels were 0.29±0.02,0.13±0.08,0.18±0.03,0.21±0.11 and 0.26±0.04;catalase(CAT)mRNA levels were 1.01±0.08,0.81±0.06,0.90±0.04,1.05±0.15 and 1.33±0.26;SOD mRNA levels were 1.09±0.12,0.83±0.03,0.86±0.08,0.94±0.08 and 1.09±0.16.Among the above indicators,the differences between the model group and the control group were statistically significant(all P＜0.01);the differences between the experimental-M,-H groups and the model group were statistically significant(P＜0.01,P＜0.05).Conclusion Icariin may activate the Keap1/Nrf2/antioxidant response element(ARE)signaling pathway,regulate the expression of related proteins,and reduce the level of ROS to effectively alleviate oxidative stress injury in neuronal cells.

Macroporous adsorption resin, MCI, Toyopearl HW-40C and silica gel column chromatography combined with the semi-preparative HPLC were used to isolate and purify the water extract of Cornus officinalis. And the structures of compounds were identified by HRESIMS, NMR, IR, UV and ECD. A total of twelve compounds were isolated from the fruits of Cornus officinalis. They were identified as neolignan B (1), 2,3-dihydro-7-methoxy-2-(4′-hydroxy-3′-methoxyphenyl)-3a-O-β-D-xylopyranosyloxymethyl-5-benzofuranpropanol (2), cornucadinoside A (3), 3,4-dihydroxyacetophenone (4), n-butyl gallate (5), 3-hydroxybenzoic acid (6), n-butyl quininate (7), 5-hydroxymaltol (8), 2-furolic acid (9), 5-hydroxymethylfurfural (10), 5-(methoxycarbonyl)-2-pyrrolidone (11), and dimethyl malate (12). Compound 1 is a new biphenyl lignan, named as neolignan B. Compounds 2, 4, 5, 7-9 and 11 were isolated from Cornus officinalis for the first time.

Eleven compounds were isolated from Eucommia ulmoides by silica gel, Sephadex LH-20, HW-40C column chromatography and semi-preparative HPLC. Their structures were identified by modern spectroscopic methods as neoeucommiate A (1), (7S,8R)-dihydrodehydrodiconiferyl alcohol (2), urolignoside (3), ficusal (4), tiruneesiin (5), glochidioboside (6), forsythialansides B (7), ecdysanol B (8), (+)-syringaresinol-4-O-β-D-glucopyranoside (9), (+)-pinoresinol 4-O-[6ʹʹ-O-vanilloyl]-β-D-glucopyranoside (10), samsesquinoside (11). Compound 1 is a new compound, compounds 3-7, 10 and 11 were isolated from Eucommia ulmoides for the first time.

Objective To investigate the predictive value of new simplified insulin resistance(IR)assessment indexes in identifying subclinical left ventricular systolic function impairment in patients with type 2 diabetes mellitus(T2DM).Methods A total of 150 T2DM patients with preserved left ventricular ejection fraction(LVEF≥50%)who were admitted to Department of Endocrinology of the First Affiliated Hospital of Air Force Medical University from June 2021 to December 2021 were retrospectively analyzed.All patients underwent two-dimensional speckle tracking echocardiography to measure left ventricular global longitudinal strain(GLS).According to GLS value,the subjects were divided into the normal group(GLS≥18%group,n=80)and the impaired group(GLS<18%group,n=70).Some new simplified IR assessment indicators were calculated and compared between the two groups,including body mass index(BMI),TG/HDL-C ratio,triglyceride-glucose(TyG)index,TyG-BMI index,TyG-WHR and metabolic score for IR(METS-IR).Correlation between the GLS and the new simplified IR assessment indexes was analyzed.The receiver operating characteristic(ROC)curve was used to analyze the diagnostic efficacy of different simplified IR assessment indexes,with the area under the curve(AUC)calculated.Furthermore,according to whether the subjects were complicated with hypertension,binary logistics regression analysis was performed to explore the independent correlation between the simplified IR assessment index and GLS<18%.Results Total 150 were included with aged(54.5±13.7)years with 96(64.0%)men and 54(36.0%)women.Compared with the GLS≥18%group,the TG/HDL-C ratio,TyG index,TyG-BMI,and METS-IR of subjects in the GLS<18%group were significantly increased(P<0.05).Pearson correlation analysis showed that TG/HDL-C ratio,TyG index,TyG-BMI,TyG-WHR,and METS-IR were negatively correlated with GLS(P<0.05).ROC analysis showed that TyG index had a certain predictive value for the evaluation of GLS<18%(AUC=0.678,95%CI 0.591-0.765,P<0.001).Stratification based on hypertension and further adjusting for confounding factors,TyG index remains significantly associated with GLS<18%(OR=3.249,95%CI 1.045-10.103,P=0.042).Conclusions The novel simplified insulin resistance evaluation indexes are closely associated with left ventricular subclinical systolic dysfunction in T2DM patients with preserved ejection fraction.TyG index is an effective index to identify left ventricular subclinical dysfunction in these populations.