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.

OBJECTIVES: To investigate the role and mechanism of Brahma-related gene 1 (Brg1) in regulating the Wnt/β-catenin signaling pathway in a bronchopulmonary dysplasia (BPD) model. METHODS: Wild-type C57BL/6 and Brg1^f1/f1 mice were randomly divided into four groups: wild-type control, wild-type BPD, Brg1^f1/f1 control, and Brg1^f1/f1 BPD (n=5 each). Immortalized mouse pulmonary alveolar type 2 cells (imPAC2) were cultured, and Brg1 gene was knocked down using lentivirus transfection technology. Cells were divided into three groups: control, empty vector, and Brg1 knockdown. Hematoxylin and eosin staining and immunofluorescence were used to detect pathological changes in mouse lung tissue. Western blot and real-time fluorescent quantitative PCR were used to measure Brg1 protein and mRNA expression levels in mouse lung tissue. Western blot and immunofluorescence were used to detect the expression of homeodomain-containing protein homeobox (HOPX), surfactant protein C (SPC), and Wnt/β-catenin signaling pathway proteins in mouse lung tissue and imPAC2 cells. The CCK8 assay was used to assess the proliferation of imPAC2 cells, and co-immunoprecipitation was performed to verify the interaction between Brg1 and β-catenin proteins in imPAC2 cells. RESULTS: Compared to the Brg1^f1/f1 control group and wild-type BPD group, the Brg1^f1/f1 BPD group showed increased alveolar diameter and SPC protein expression, and decreased relative density of pulmonary vasculature and HOPX protein expression (P<0.05). Compared to the control group, the Brg1 knockdown group showed increased cell proliferation ability, protein expression levels of SPC, Wnt5a and β-catenin, and β-catenin protein fluorescence intensity, along with decreased HOPX protein expression (P<0.05). An interaction between Brg1 and β-catenin proteins was confirmed. CONCLUSIONS The Brg1 gene may promote the proliferation of alveolar type 2 epithelial cells by regulating the Wnt/β-catenin signaling pathway, thus influencing the occurrence and development of BPD.
Animals ; DNA Helicases/genetics* ; Transcription Factors/genetics* ; Wnt Signaling Pathway/physiology* ; Nuclear Proteins/genetics* ; Mice ; Bronchopulmonary Dysplasia/etiology* ; Mice, Inbred C57BL ; beta Catenin/physiology* ; Disease Models, Animal ; Cell Proliferation ; Lung/pathology* ; Male

Stem cells play a crucial role in maintaining tissue regenerative capacity and homeostasis. However, mechanisms associated with stem cell senescence require further investigation. In this study, we conducted a proteomic analysis of human dental pulp stem cells (HDPSCs) obtained from individuals of various ages. Our findings showed that the expression of NUP62 was decreased in aged HDPSCs. We discovered that NUP62 alleviated senescence-associated phenotypes and enhanced differentiation potential both in vitro and in vivo. Conversely, the knocking down of NUP62 expression aggravated the senescence-associated phenotypes and impaired the proliferation and migration capacity of HDPSCs. Through RNA-sequence and decoding the epigenomic landscapes remodeled induced by NUP62 overexpression, we found that NUP62 helps alleviate senescence in HDPSCs by enhancing the nuclear transport of the transcription factor E2F1. This, in turn, stimulates the transcription of the epigenetic enzyme NSD2. Finally, the overexpression of NUP62 influences the H3K36me2 and H3K36me3 modifications of anti-aging genes (HMGA1, HMGA2, and SIRT6). Our results demonstrated that NUP62 regulates the fate of HDPSCs via NSD2-dependent epigenetic reprogramming.
Humans ; Dental Pulp/cytology* ; Nuclear Pore Complex Proteins/genetics* ; Cellular Senescence/genetics* ; Stem Cells/metabolism* ; Epigenesis, Genetic ; Cell Proliferation ; Cell Differentiation ; Histone-Lysine N-Methyltransferase/metabolism* ; Cells, Cultured ; Cellular Reprogramming ; Cell Movement ; Proteomics

Metabolomics covers a wide range of applications in life sciences, biomedicine, and phytology. Data acquisition (to achieve high coverage and efficiency) and analysis (to pursue good classification) are two key segments involved in metabolomics workflows. Various chemometric approaches utilizing either pattern recognition or machine learning have been employed to separate different groups. However, insufficient feature extraction, inappropriate feature selection, overfitting, or underfitting lead to an insufficient capacity to discriminate plants that are often easily confused. Using two ginseng varieties, namely Panax japonicus (PJ) and Panax japonicus var. major (PJvm), containing the similar ginsenosides, we integrated pseudo-targeted metabolomics and deep neural network (DNN) modeling to achieve accurate species differentiation. A pseudo-targeted metabolomics approach was optimized through data acquisition mode, ion pairs generation, comparison between multiple reaction monitoring (MRM) and scheduled MRM (sMRM), and chromatographic elution gradient. In total, 1980 ion pairs were monitored within 23 min, allowing for the most comprehensive ginseng metabolome analysis. The established DNN model demonstrated excellent classification performance (in terms of accuracy, precision, recall, F1 score, area under the curve, and receiver operating characteristic (ROC)) using the entire metabolome data and feature-selection dataset, exhibiting superior advantages over random forest (RF), support vector machine (SVM), extreme gradient boosting (XGBoost), and multilayer perceptron (MLP). Moreover, DNNs were advantageous for automated feature learning, nonlinear modeling, adaptability, and generalization. This study confirmed practicality of the established strategy for efficient metabolomics data analysis and reliable classification performance even when using small-volume samples. This established approach holds promise for plant metabolomics and is not limited to ginseng.

Objective To explore the efficacy and safety of evolocumab in elderly patients with high-risk cardiovascular diseases.Methods A total of 153 patients with poor lipid control after conventional statin therapy who were hospitalized in the cardiologic departments in the First,Sec-ond,Sixth and Eighth Medical Centers of Chinese PLA General Hospital from November 2019 to November 2022 were included,and divided into non-elderly group(＜60 years old,46 cases),eld-erly group(60-74 years old,66 case)and very elderly group(≥75 years old,41 cases).They were all given evolocumab treatment according to guidelines.Another 50 over-75-year-old patients with high-risk cardiovascular diseases and poor lipid control who were hospitalized in the above cardiologic departments during the same period were treated with a statin drug combined with ezetimibe,and served as conventional treatment group(control group).The baseline clinical data and the blood indicators at 4th and 12th week after drug administration,and the occurrence of ad-verse drug reactions and major adverse cardiovascular events(MACE)within 12 weeks were com-pared among the groups.Results The levels of LDL-C and TC were significantly decreased in the three evolocumab treatment groups at 4 and 12 weeks after medication when compared with the baseline values(P＜0.05,P＜0.01),but there were no obvious differences in the 2 levels among the 3 groups at 12 weeks(P＞0.05).At the time point,no statistical difference was observed in the incidence of adverse events in the three groups(2.2％vs 3.0％vs 2.4％,P＞0.05).The levels of LDL-C and TC were decreased significantly in the very elderly group and the conventional treatment group at the 12th week when compared with the baseline levels(P＜0.05,P＜0.01),and the LDL-C level at the week was notably lower in the very elderly group than the convention-al treatment group(1.36±0.44 mmol/L vs 1.87±0.56 mmol/L,P＜0.01).But no difference was seen in the incidence of MACE between the 2 groups(12.2％vs 16.0％,P＞0.05),either in sur-vival rate between them(P=0.576).Conclusion For patients of all ages,evolocumab has good short-term efficacy in lipid control,and for those over 75 years old,the drug also shows good effi-cacy and sound safety.

Concurrent chemoradiotherapy (CCRT) refers to the simultaneous treatment of chemotherapy and radiotherapy, and the effect of radiotherapy is enhanced with low-dose chemotherapy, which can reduce tumor recurrence and metastasis and improve clinical prognosis of patients. At present, the main factors for the increase of radiosensitivity of concurrent chemotherapy is that concurrent chemotherapy prevents the repair of tumor cells, and chemotherapy and radiotherapy act on different cell cycles and have synergistic effects. However, even for patients with locally advanced cervical cancer (LACC) who have undergone CCRT, the 5-year survival rate is only 60%, which is still not ideal. In order to improve the efficacy, researchers have conducted a series of exploratory studies, which consist of the combination of targeted drugs and immunodrugs, and neoadjuvant regimens before CCRT, etc. Although targeted or immunologic drugs are effective treatment of LACC, in view of the lack of large-scale evidence-based medical evidence, multi-center prospective and randomized phase III clinical trials and high-level articles are needed to improve the level of evidence-based medicine. This consensus summarizes several key evidence-based medical studies published recently, especially the clinical research progress in targeted and immunological therapies, providing reference for domestic peers.

The extent of spermatogenic impairment on intracytoplasmic sperm injection (ICSI) outcomes and the risk of major birth defects have been little assessed. In this study, we evaluated the relationship between various spermatogenic conditions, sperm origin on ICSI outcomes, and major birth defects. A total of 934 infertile men attending the Center for Reproductive Medicine of Ren Ji Hospital (Shanghai, China) were classified into six groups: nonobstructive azoospermia (NOA; n = 84), extremely severe oligozoospermia (esOZ; n = 163), severe oligozoospermia (sOZ, n = 174), mild oligozoospermia (mOZ; n = 148), obstructive azoospermia (OAZ; n = 155), and normozoospermia (NZ; n = 210). Rates of fertilization, embryo cleavage, high-quality embryos, implantation, biochemical and clinical pregnancies, abortion, delivery, newborns, as well as major birth malformations, and other newborn outcomes were analyzed and compared among groups. The NOA group showed a statistically lower fertilization rate (68.2% vs esOZ 77.3%, sOZ 78.0%, mOZ 73.8%, OAZ 76.6%, and NZ 79.3%, all P < 0.05), but a significantly higher implantation rate (37.8%) than the groups esOZ (30.1%), sOZ (30.4%), mOZ (32.6%), and OAZ (31.0%) (all P < 0.05), which was similar to that of Group NZ (38.4%). However, there were no statistically significant differences in rates of embryo cleavage, high-quality embryos, biochemical and clinical pregnancies, abortions, deliveries, major birth malformations, and other newborn outcomes in the six groups. The results showed that NOA only negatively affects some embryological outcomes such as fertilization rate. There was no evidence of differences in other embryological and clinical outcomes with respect to sperm source or spermatogenic status. Spermatogenic failure and sperm origins do not impinge on the clinical outcomes in ICSI treatment.
Azoospermia/therapy* ; China ; Female ; Humans ; Infant, Newborn ; Male ; Oligospermia/therapy* ; Pregnancy ; Pregnancy Rate ; Retrospective Studies ; Sperm Injections, Intracytoplasmic/methods* ; Sperm Retrieval ; Spermatogenesis ; Spermatozoa

Objective:To analyze the effects of two decomposition algorithms of dual-energy cone beam CT (DECBCT) (direct decomposition and iterative decomposition) on the image quality and material decomposition accuracy of different sizes of phantoms.Methods:Different sizes of imaging parts of patients were simulated using the combination of CatPhan604 phantoms and customized annuluses. CBCT with high energy of 140 kVp and low energy of 100 kVp were acquired using the Varian Edge CBCT system. Then the material decomposition of DECBCT images was performed using the two algorithms. The electron density (ED) and contrast-to-noise ratio (CNR) of each material in the CTP682 module were calculated. They were used to assess the decomposition accuracy and image quality of the two algorithms.Results:Based on the values in the Catphan604 manual, both algorithms have high ED accuracy. Only the ED accuracy of four materials of the smallest sized phantom showed statistical difference ( z = -4.21, 4.30, 2.87, 5.45, P < 0.05), but the average relative error was less than 1%. The CNR of the iterative decomposition algorithm was significantly higher than that of the direct decomposition, increasing by 51.8%-703.47%. The increase in the phantom size significantly reduced the accuracy of ED, and the increased amplitude of the relative error was up to a maximum of 2.52%. The large phantom size also reduced the image quality of iterative decomposition, and the decreased amplitude of CNR was up to a maximum of 39.71. Conclusions:Compared with the direct decomposition, the iterative decomposition algorithm can significantly reduce the image noise and improve the contrast without losing the accuracy of electron density in the DECBCT construction of different sizes of phantoms.