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.

Animal experiments are widely used in biomedical research for safety assessment, toxicological analysis, efficacy evaluation, and mechanism exploration. In recent years, the ethical review system has become more stringent, and awareness of animal welfare has continuously increased. To promote more efficient and cost-effective drug research and development, the United States passed the Food and Drug Administration (FDA) Modernization Act 2.0 in September 2022, which removed the federal mandate requiring animal testing in preclinical drug research. In April 2025, the FDA further proposed to adopt a series of "new alternative methods" in the research and development of drugs such as monoclonal antibodies, which included artificial intelligence computing models, organoid toxicity tests, and 3D micro-physiological systems, thereby gradually phasing out traditional animal experiment models. Among these cutting-edge technologies, 3D bioprinting models are a significant alternative and complement to animal models, owing to their high biomimetic properties, reproducibility, and scalability. This review provides a comprehensive overview of advancements and applications of 3D bioprinting technology in the fields of biomedical and pharmaceutical research. It starts by detailing the essential elements of 3D bioprinting, including the selection and functional design of biomaterials, along with an explanation of the principles and characteristics of various printing strategies, highlighting the advantages in constructing complex multicellular spatial structures, regulating microenvironments, and guiding cell fate. It then discusses the typical applications of 3D bioprinting in drug research and development,including high-throughput screening of drug efficacy by constructing disease models such as tumors, infectious diseases, and rare diseases, as well as conducting drug toxicology research by building organ-specific models such as those of liver and heart. Additionally,the review examines the role of 3D bioprinting in tissue engineering, discussing its contributions to the construction of functional tissues such as bone, cartilage, skin, and blood vessels, as well as the latest progress in regeneration and replacement. Furthermore, this review analyzes the complementary advantages of 3D bioprinting models and animal models in the research of disease progression, drug mechanisms, precision medicine, drug development, and tissue regeneration, and discusses the potential and challenges of their integration in improving model accuracy and physiological relevance. In conclusion, as a cutting-edge in vitro modeling and manufacturing technology, 3D bioprinting is gradually establishing a comprehensive application system covering disease modeling, drug screening, toxicity prediction, and tissue regeneration.

Animal experiments are widely used in biomedical research for safety assessment, toxicological analysis, efficacy evaluation, and mechanism exploration. In recent years, the ethical review system has become more stringent, and awareness of animal welfare has continuously increased. To promote more efficient and cost-effective drug research and development, the United States passed the Food and Drug Administration (FDA) Modernization Act 2.0 in September 2022, which removed the federal mandate requiring animal testing in preclinical drug research. In April 2025, the FDA further proposed to adopt a series of "new alternative methods" in the research and development of drugs such as monoclonal antibodies, which included artificial intelligence computing models, organoid toxicity tests, and 3D micro-physiological systems, thereby gradually phasing out traditional animal experiment models. Among these cutting-edge technologies, 3D bioprinting models are a significant alternative and complement to animal models, owing to their high biomimetic properties, reproducibility, and scalability. This review provides a comprehensive overview of advancements and applications of 3D bioprinting technology in the fields of biomedical and pharmaceutical research. It starts by detailing the essential elements of 3D bioprinting, including the selection and functional design of biomaterials, along with an explanation of the principles and characteristics of various printing strategies, highlighting the advantages in constructing complex multicellular spatial structures, regulating microenvironments, and guiding cell fate. It then discusses the typical applications of 3D bioprinting in drug research and development,including high-throughput screening of drug efficacy by constructing disease models such as tumors, infectious diseases, and rare diseases, as well as conducting drug toxicology research by building organ-specific models such as those of liver and heart. Additionally,the review examines the role of 3D bioprinting in tissue engineering, discussing its contributions to the construction of functional tissues such as bone, cartilage, skin, and blood vessels, as well as the latest progress in regeneration and replacement. Furthermore, this review analyzes the complementary advantages of 3D bioprinting models and animal models in the research of disease progression, drug mechanisms, precision medicine, drug development, and tissue regeneration, and discusses the potential and challenges of their integration in improving model accuracy and physiological relevance. In conclusion, as a cutting-edge in vitro modeling and manufacturing technology, 3D bioprinting is gradually establishing a comprehensive application system covering disease modeling, drug screening, toxicity prediction, and tissue regeneration.

Islet β cell dedifferentiation is one of the important reasons leading to insulin secretion defect or insulin resistance in patients with type 2 diabetes mellitus(T2DM).HIF-1α/PFKFB3 signaling pathway is a newly discovered biological pathway related to T2DM,which is involved in the induction of islet β cells dedifferentiation by anaerobic glycolysis under high glucose environment.This article reviews the research progress of the role of HIF-1α/PFKFB3 signaling pathway in glycolysis induced islet β cell dedifferentiation.

Objective To investigate the effect of Ophiopogonin D on lipopolysaccharide(LPS)-induced apoptosis of alveolar epithelial cells by regulating the interleukin-6(IL-6)/Janus kinase 2(JAK2)/signal transducer and activator of transcription 3(STAT3)signaling pathway.Methods A549 AT Ⅱ cells cultured in vitro were randomly divided into four groups:control group,LPS group,LPS+Ophiopogonin D group,LPS+Ophiopogonin D+colivelin(JAK2/STAT3 signal activator)group,except for the control group,and cells in all other groups were established injury models while being grouped with Ophiopogonin D and colivelin for treatment.Cell counting kit-8(CCK-8)experiment and flow cytometry were applied to detect cell proliferation and apoptosis in each group;Western blotting was applied to detect the expression of IL-6/JAK2/STAT3 signaling pathway proteins of cells in each group.Results The apoptosis rates of A549 cells in control group,LPS group,LPS+Ophiopogonin D group and LPS+Ophiopogonin D+colivelin group were(2.52±0.73)％,(52.43±4.14)％,(1.67±0.52)％and(47.94±3.43)％;IL-6 protein levels were 0.14±0.03,0.49±0.05,0.17±0.04 and 0.45±0.06,and p-JAK2/JAK2 protein levels were 0.17±0.04,0.64±0.08,0.19±0.06 and 0.61±0.07;p-STAT3/STAT3 protein levels were 0.20±0.06,0.69±0.10,0.22±0.07 and 0.65±0.09;the apoptosis rates of AT Ⅱ cells were(3.01±0.69)％,(55.16±3.94)％,(2.35±0.71)％and(50.28±3.78)％;the levels of IL-6 protein were 0.11±0.03,0.87±0.13,0.19±0.04 and 0.84±0.12;the p-JAK2/JAK2 protein levels were 0.13±0.04,0.56±0.08,0.15±0.03 and 0.53±0.07;p-STAT3/STAT3 protein levels were 0.30±0.08,0.79±0.14,0.33±0.09 and 0.75±0.13.The above indexes:control group,LPS+Ophiopogonin D group compared with LPS group,LPS+Ophiopogonin D+colivelin group compared with LPS+Ophiopogonin D group,the differences were statistically significant(all P＜0.05).Conclusion Ophiopogonin D can reduce LPS induced inflammation and oxidative stress levels by inhibiting the activation of IL-6/JAK2/STAT3 signaling pathway,ultimately reducing LPS-induced apoptosis of alveolar epithelial cells.

Objective: To understand cumulative health risk behaviors among college students and the association with adverse childhood experiences, so as to provide a theoretical basis for the prevention and control of health risk behaviors in this population. Methods: From November to December 2022, four universities in Shanghai were selected using convenience sampling, and 3 039 students were selected for a questionnaire survey using random cluster sampling. The questionnaire covered general basic information, adverse childhood experiences and health risk behaviors. A latent class analysis was carried out to explore the latent classes of health risk behaviors among the college students and multivariate Logistic regression was performed to analyze the association between adverse childhood experiences and cumulative health risk behaviors. Results: The health risk behaviors of college students were classified into three latent classes:a low risk group (84.60%), a high risk group for smoking and alcohol consumption ( 10.37 %), and an excessive sugar intake group (5.03%). The proportion of three latent classes of health risk behaviors varied significantly by childhood neglect and abuse, family functioning and other adverse childhood experiences ( χ 2=210.67, 106.55, 104.41 , P <0.01). The results of the multiple Logistic regression analysis revealed that childhood neglect and abuse, poor family functioning, and other adversities increased the risk in the high risk group for smoking and alcohol consumption among college students ( OR =6.24, 3.80, 3.68), as well as an childhood neglect and abuse increased the risk of the excessive sugar intake group among college students ( OR =2.18) ( P <0.01). Conclusions Adverse childhood experiences are associated with clustered health risk behaviors. Proactive measures should be taken to prevent the transmission of negative childhood experiences, which would contribute to reduce the occurrence of health risk behaviors among college students.

Objective:To explore the active ingredients of shengxian and jinshuiliujun decoction with the method of network pharmacology, and to verify the experimental mechanism of its treatment of silicosis.Methods:In May 2023, the active ingredients and targets of drugs in shengxian and jinshuiliujun decoction were obtained through the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) database. The target of silicosis disease was screened by databases such as Genecards, Disease Gene Network (DisGeNET), Comparative Toxicogenomics Database (CTD), etc. The screened drug targets and disease targets were intersected to obtain the target set of shengxian and jinshuiliujun decoction for the treatment of silicosis. Protein-protein interaction (PPI) network analysis was performed on the target set through STRING database, and core target genes were screened. GO enrichment analysis and KEGG pathway analysis of intersection genes were performed based on Metascape database, and molecular docking verification of key components and targets of shengxian and jinshuiliujun decoction was carried out. Twenty-four adult male SD rats with SPF grade were randomly divided into control group, model group and TCM intervention group, with 8 rats in each group. The dust-stained rat model was prepared by non-tracheal exposure of 1 ml silica suspension (50 mg/ml) in one go, and TCM intervention group was given shengxian and jinshuiliujun decoction[6 g/ (kg·d) ] on the second day. The CT of the lungs of each group was observed 28 days after the dust-stained rat model. Paraffin sections of rat lung tissues were prepared and stained with Hematoxylin-Eosin (HE) and Masson. Western blot was used to verify the expression of core target-related proteins in rat lung tissues after the intervention of shengxian and jinshuiliujun decoction for 28 days, and the differences in protein expression between groups were compared by one-way analysis of variance.Results:A total of 205 active ingredients and 3345 active compounds were selected from shengxian and jinshuiliujun decoction, corresponding to 281 targets, among which 240 targets were related to silicosis. Serine/threonine kinase 1 (AKT1), tumor protein p53 (TP53), tumor necrosis factor (TNF) and interleukin (IL) 6 may be the key targets of shengxian and jinshuiliujun decoction in the treatment of silicosis. Through enrichment analysis, 30 GO entries and 20 potential signaling pathways were screened according to P-value, including nuclear factor κB (NF-κB), mitogen-activated protein kinase (MAPK) and cancer signaling pathways. Molecular docking showed that the active compounds of shengxian and jinshuiliujun decoction had good binding with the core target proteins, and the strongest binding properties were beta-sitosterol and TNF-α (-10.45 kcal/mol). In animal experiments, the inflammatory infiltration and fibrosis of lung tissue of rats in TCM intervention group were significantly improved. Compared with control group, the levels of TNF-α, IL-1β, IL-6 and NF-κB in lung tissue of model group were significantly increased ( P<0.05). Compared with model group, the lung injury of rats in TCM intervention group was significantly improved, and the expressions of TNF-α, IL-1β, IL-6 and NF-κB were significantly decreased ( P<0.05) . Conclusion:Shengxian and jinshuiliujun decoction in the treatment of silicosis may play an anti-fibrosis role by inhibiting the NF-κB signal transduction pathway mediated by inflammatory factors such as TNF-α and IL-1β, which provides a reference for further exploring the material basis and mechanism of its action.

Objective:To investigate the early clinical characteristics of elderly patients with severe burns and the risk factors on prognosis.Methods:This study was a retrospective case series study. Clinical data of 124 elderly patients with severe burns who met the inclusion criteria and were admitted to the 12 hospitals from January 2015 to December 2020 were collected, including 4 patients from the Fourth People's Hospital of Dalian, 5 patients from Fujian Medical University Union Hospital, 22 patients from Guangzhou Red Cross Hospital of Jinan University, 5 patients from Heilongjiang Provincial Hospital, 27 patients from the First Affiliated Hospital of Naval Medical University, 9 patients from the First Affiliated Hospital of Nanchang University, 10 patients from Affiliated Hospital of Nantong University, 9 patients from Tongren Hospital of Wuhan University & Wuhan Third Hospital, 12 patients from the 924 th Hospital of PLA, 6 patients from Zhangjiagang First People's Hospital, 4 patients from Taizhou Hospital of Zhejiang Province, and 11 patients from Zhengzhou First People's Hospital. The patients' overall clinical characteristics, such as gender, age, body mass index, total burn area, full-thickness burn area, inhalation injury, causative factors, whether combined with underlying medical diseases, and admission time after injury were recorded. According to the survival outcome within 28 days after injury, the patients were divided into survival group (89 cases) and death group (35 cases). The following data of patients were compared between the two groups, including the basic data and injuries (the same as the overall clinical characteristics ahead); the coagulation indexes within the first 24 hours of injury such as prothrombin time (PT), activated partial thromboplastin time (APTT), thrombin time, D-dimer, fibrinogen degradation product (FDP), international normalized ratio (INR), and fibrinogen; the blood routine indexes within the first 24 hours of injury such as white blood cell count, platelet count, neutrophil-to-lymphocyte ratio, monocyte count, red blood cell count, hemoglobin, and hematocrit; the organ function indexes within the first 24 hours of injury such as direct bilirubin, total bilirubin, urea, serum creatinine, aspartate aminotransferase, alanine aminotransferase, total protein, albumin, globulin, blood glucose, triglyceride, total cholesterol, alkaline phosphatase, creatine kinase, electrolyte indexes (potassium, sodium, chlorine, calcium, magnesium, and phosphorus in blood), uric acid, myoglobin, and brain natriuretic peptide; the infection and blood gas indexes within the first 24 hours of injury such as procalcitonin, C-reactive protein, pH value, oxygenation index, base excess, and lactate; treatment such as whether conducted with mechanical ventilation, whether conducted with continuous renal replacement therapy, whether conducted with anticoagulation therapy, whether applied with vasoactive drugs, and fluid resuscitation. The analysis was conducted to screen the independent risk factors for the mortality within 28 days after injury in elderly patients with severe burns. Results:Among 124 patients, there were 82 males and 42 females, aged 60-97 years, with body mass index of 23.44 (21.09, 25.95) kg/m 2, total burn area of 54.00% (42.00%, 75.00%) total body surface area (TBSA), and full-thickness burn area of 25.00% (10.00%, 40.00%) TBSA. The patients were mainly combined with moderate to severe inhalation injury and caused by flame burns. There were 43 cases with underlying medical diseases. The majority of patients were admitted to the hospital within 8 hours after injury. There were statistically significant differences between patients in the 2 groups in terms of age, total burn area, full-thickness burn area, and inhalation injury, and PT, APTT, D-dimer, FDP, INR, white blood cell count, platelet count, urea, serum creatinine, blood glucose, blood sodium, uric acid, myoglobin, and urine volume within the first 24 hours of injury (with Z values of 2.37, 5.49, 5.26, 5.97, 2.18, 1.95, 2.68, 2.68, 2.51, 2.82, 2.14, 3.40, 5.31, 3.41, 2.35, 3.81, 2.16, and -3.82, respectively, P<0.05); there were statistically significant differences between two groups of patients in whether conducted with mechanical ventilation and whether applied with vasoactive drugs (with χ2 values of 9.44 and 28.50, respectively, P<0.05). Age, total burn area, full-thickness burn area, serum creatinine within the first 24 hours of injury, and APTT within the first 24 hours of injury were the independent risk factors for the mortality within 28 days after injury in elderly patients with severe burns (with odds ratios of 1.17, 1.10, 1.10, 1.09, and 1.27, 95% confidence intervals of 1.03-1.40, 1.04-1.21, 1.05-1.19, 1.05-1.17, and 1.07-1.69, respectively, P<0.05). Conclusions:The elderly patients with severe burns had the injuries mainly from flame burns, often accompanied by moderate to severe inhalation injury and enhanced inflammatory response, elevated blood glucose levels, activated fibrinolysis, and impaired organ function in the early stage, which are associated with their prognosis. Age, total burn area, full-thickness burn area, and serum creatinine and APTT within the first 24 hours of injury are the independent risk factors for death within 28 days after injury in this population.