Hepatocellular carcinoma (HCC) is a lethal cancer with high morbidity rates worldwide. It is a major threat to public health in China, due to the combination of known and new risk factors, such as endemic hepatitis B virus (HBV), dietary aflatoxin exposure, and the occurrence of metabolic dysfunction-associated steatotic liver disease (MASLD). Although many methods for surveillance and multimodal therapies, such as surgery, local ablation, transarterial therapy, and new systemic agents, have been available, the survival rates of HCC remains poor. They have very limited durable responses, long post-treatment recurrence rates, and high resistance to treatment. This reflects an imperfect picture of the biological cause of the disease and a need for new mechanistic or targeted techniques. A significant characteristic of HCC, in common with other aggressive cancers, is the presence of reprogrammed, hyperactive cell metabolism. Tumor cells hijack metabolic pathways to promote their uncontrolled growth, stress survival, invasion and metastasis. While classical mechanisms such as the Warburg effect, lipid metabolism and glutamine utilization have been understood, the lysosome, which was once viewed as a static “waste disposal unit” to remove old organelles and proteins, is instead a dynamic signaling and metabolic core. The lysosomes incorporate nutrients, energy and stress signals by master regulators such as mTORC1 (activated on its surface) that balance anabolic growth and catabolic recycling to the cellular demands. In HCC, lysosomes are not passive, but are highly active and dysregulated. HCC cells upregulate lysosomes, which scavenge intracellular components via enhanced autophagy and engulf extracellular proteins via macropinocytosis, crucial for survival in the nutrient-poor, hypoxic tumor microenvironment. In addition to metabolism, lysosomes exhibit pro-invasive functions by secreting hydrolases to remodel the extracellular matrix, promote angiogenesis, and suppress stromal immune cells to foster a pro-tumor microenvironment. In a clinical context, lysosomes play an important role in therapeutic resistance: they sequester and inactivate chemotherapeutics via lysosomal sequestration, and enhanced autophagic flux protects the cell from therapy-induced damage, contributing to relapse, as lysosomal dysfunction is a key cause of treatment failure. This makes lysosomes promising yet challenging therapeutic targets in HCC. Recent preclinical and early clinical studies investigate multiple strategies to exploit the susceptibility of lysosomes: lysosome-specific agents, alkalinizing the lysosome lumen or inducing membrane permeabilization and lysosome-dependent cell death; pharmacological inhibition of key lysosomal enzymes or autophagy to impair nutrient recycling and stress adaptation; smart nanotherapeutic agents or antibody-drug conjugates, specifically activated in the acidic lysosomal environment or utilizing lysosomal pathways for efficient intracellular drug release; and combination strategies of lysosome-targeting agents with tyrosine kinase inhibitors or immunotherapy to overcome resistance and achieve synergistic antitumor effects. In summary, our review systematically presents the role of lysosomes in HCC, from metabolic reprogramming and microenvironmental adaptation to therapeutic resistance. By synthesizing the latest mechanistic insights and preclinical advances, this review highlights the indispensable role of lysosomes in the complex HCC biological network, emphasizing that an in-depth understanding of this dynamic organelle holds great promise for developing innovative, targeted therapies, offering new hope for improving the poor prognosis of global HCC patients.

Background/Aims: Cholangiocarcinoma (CCA) is a primary malignant neoplasm with an extremely poor prognosis. While combined chemoradiotherapy has been demonstrated to delay CCA progression to a certain extent, the absence of specific molecular biomarkers or targets significantly hinders the diagnosis and treatment of CCA. Methods: Through cross-analysis of proteomics and ADMA modificationomics, we identified DDX1 overexpressed in CCA with elevated R602-ADMA modifications. HPLC-MS/MS identified PRMT1 as the methyltransferase and USP10 as the deubiquitinating enzyme for DDX1. Immunofluorescence and nuclear-cytoplasmic partitioning experiments confirmed DDX1’s nuclear localization. GO and KEGG analyses clarify the biological functions of DDX1 in response to hypoxia. RNA-seq transcriptomics analyzed key pathways influenced by DDX1. A hydrodynamic in situ CCA mouse model was established to validate the chemopreventive effects of the PRMT1-specific inhibitor GSK715 on CCA development. Results: DDX1 promotes CCA progression both in vivo and in vitro and can be inhibited by GSK715. Mechanistically, PRMT1 mediates ADMA modification at position R602 of DDX1. This modification promotes DDX1 nuclear localization by recruiting USP10 to deubiquitinate DDX1, while simultaneously inhibiting PRMT1 degradation. DDX1 promotes the transcription of PRMT1 and USP10 by binding to the mRNA 3’UTR region, establishing a positive feedback regulatory pathway. This mechanism promotes the occurrence and development of CCA and can serve as a target for the inhibitor GSK715 to suppress CCA progression. Conclusions Our study identified DDX1-R602-ADMA modification as a novel ADMA modification in CCA. It further confirmed its pivotal role in CCA progression. Targeting the USP10-PRMT1-DDX1 axis may represent a significant therapeutic approach for CCA.

Objective To explore the application effect of a standardized management method based on failure mode and effect analysis （FMEA） in optimizing the whole-process quality control system of the intravenous admixture service （PIVAS）. Methods The quality control management system of the PIVAS was optimized by establishing six quality control groups led by the head nurse, with full participation of pharmacy, nursing, and logistical staff, ensuring comprehensive coverage and traceability of all quality control links. Each group conducted risk priority number （RPN） scoring for potential failure modes in their respective quality control processes, and targeted improvement measures were formulated based on the scoring results. The RPN values of failure modes and quality control-related evaluation indicators before and after implementation were compared to achieve closed-loop management. Results After one year of management, the RPN values of the six major failure modes significantly decreased compared to those before implementation （P<0.05）. The compounding error rate dropped to 0.13%, the dispensing error rate decreased to 0.95%, the compounding efficiency increased to 98%, the delivery time was shortened by 0.45 h per batch, the intervention rate for irrational prescriptions rose to 94.87%, satisfaction improved to 96.78%, and the participation rate of quality control personnel reached 95.36% （P<0.05）. Conclusion FMEA-based identification of potential failure modes in the whole-process quality control system of the IVAS, combined with risk quantification and targeted interventions, significantly reduced high-risk failure modes, improved compounding accuracy and efficiency, and ensured the safety of clinical intravenous medication and the effectiveness of healthcare quality management.

Objective To explore the application effect of a standardized management method based on failure mode and effect analysis （FMEA） in optimizing the whole-process quality control system of the intravenous admixture service （PIVAS）. Methods The quality control management system of the PIVAS was optimized by establishing six quality control groups led by the head nurse, with full participation of pharmacy, nursing, and logistical staff, ensuring comprehensive coverage and traceability of all quality control links. Each group conducted risk priority number （RPN） scoring for potential failure modes in their respective quality control processes, and targeted improvement measures were formulated based on the scoring results. The RPN values of failure modes and quality control-related evaluation indicators before and after implementation were compared to achieve closed-loop management. Results After one year of management, the RPN values of the six major failure modes significantly decreased compared to those before implementation （P<0.05）. The compounding error rate dropped to 0.13%, the dispensing error rate decreased to 0.95%, the compounding efficiency increased to 98%, the delivery time was shortened by 0.45 h per batch, the intervention rate for irrational prescriptions rose to 94.87%, satisfaction improved to 96.78%, and the participation rate of quality control personnel reached 95.36% （P<0.05）. Conclusion FMEA-based identification of potential failure modes in the whole-process quality control system of the IVAS, combined with risk quantification and targeted interventions, significantly reduced high-risk failure modes, improved compounding accuracy and efficiency, and ensured the safety of clinical intravenous medication and the effectiveness of healthcare quality management.

Autoimmune hepatitis （AIH） is a chronic inflammatory liver disease mediated by T lymphocytes， and it can progress to liver cirrhosis or even liver failure without timely intervention. As a natural flavonoid compound， naringenin （NAR） shows a potential value in the prevention and treatment of AIH through multiple mechanisms such as remodeling immune homeostasis， targeted inhibition of inflammatory pathways， antioxidation， regulating hepatocyte metabolism and apoptosis， improving mitochondrial function， and regulating intestinal flora. However， the clinical translation and application of NAR is limited by issues such as low bioavailability and insufficient efficiency of liver-targeted delivery. This article systematically reviews the mechanism of action of NAR in the prevention and treatment of AIH， explores the potential signaling pathways involved in this process， and analyzes existing challenges in its translation and application and future research directions， so as to provide a reference for further research on NAR and its application in the prevention and treatment of AIH.

AIM To study the chemical constituents from Gymnema tingens Spreng.and their in vitro hypoglycemic activity.METHODS The 70％ethanol extract was isolated and purified by macroporous resin,silica gel,sephadex LH-20,and semi-preparative HPLC,then the structures of obtained compounds were identified by physicochemical propeties and spectral data.The in vitro hypoglycemic activity was evaluated by glucose uptake test in L6 cells.RESULTS Seventeen compounds were isolated and identified as 7-desoxyneocynapanogenin A(1),glaucogenin(2),cynatratoside A(3),atratcynoside F(4),(+)-lyoniresinol(5),(+)-lyoniresinol 3-O-α-D-rhamnopyranoside-(1→6)-β-D-glucopyranoside(6),fernandoside(7),3,4-dimethoxy-phenyl-1-O-β-D-apiofuranosyl-(1→2)-β-D-glucopyranoside(8),khaephuoside A(9),khaephuoside B(10),3,4,5-trimethoxy-phenyl-O-β-D-glucopyranoside(11),liquiritigenin(12),7,3'-dihydroxy-flavanone-4'-O-β-D-glucopyranoside(13),pinoresinol(14),syringaldehyde(15),(+)-1-hydroxy-pinoresinol-1-β-D-glucopyranoside(16),β-amyrin(17).Compounds 2-5、7、9、10、12、17 could promote the glucose uptake in L6 cells.CONCLUSION Compound 1 is a new compound,and 2-9、11-13、15-17 are isolated from this plant for the first time.Compounds 2-5、7、9、10、12、17 have good hypoglycemic activity.

Objective:To observe the relationship between preoperative controlling nutritional status(CONUT)score and cognitive impairment,as well as short-term prognosis after intravenous thrombolysis(IVT)in patients with acute ischemic stroke(AIS).Methods:187 patients with AIS who were admitted to Shandong Provincial Third Hospital from January 2023 to May 2024 were selected,they were divided into non cognitive impairment group(n=106)and cognitive impairment group(n=81)based on whether cognitive impairment occurred,they were divided into poor prognosis group(n=58 cases)and good prognosis group(n=129 cases)according to the prognosis.Preoperative CONUT scores of patients with AIS for different cognitive impairments and prognoses were compared,correlation was analyzed by Spearman rank correlation,influencing factors were analyzed by multivariate logistic regression model.Results:Preoperative CONUT score in the cognitive impairment group was higher than that in the non cognitive impairment group(P＜0.05).Preoperative CONUT score in the poor prognosis group was higher than that in the good prognosis group(P＜0.05).Spearman rank correlation test results showed that,preoperative CONUT score was positively correlated with cognitive impairment and short-term prognosis after IVT(P＜0.05).Cognitive impairment were associated with age,concomitant hypertension,baseline national institutes of health stroke scale(NIHSS)score,and 25 hydroxyvitamin D3[25-(OH)2D3](P＜0.05).Age increase,concomitant hypertension,baseline NIHSS score increase,25-(OH)2D3 decrease,preoperative CONUT score increase were risk factors for cognitive impairment in patients with AIS(P＜0.05).Conclusion:Preoperative CONUT score increase is positively correlated with cognitive impairment and short-term prognosis after IVT.Meanwhile,age increase,concomitant hypertension,baseline NIHSS score increase,25-(OH)2D3 decrease,preoperative CONUT score increase are risk factors for cognitive impairment in patient with AIS.

Objective:To analyze the effect of joint management of type 2 diabetes mellitus (T2DM) between specialty and community under the model of National Diabetes Prevention and Control Center (DPCC).Methods:A total of 2 527 T2DM patients managed by DPCC Pingshan Center of Shenzhen from January 1, 2022 to December 31, 2024 were retrospectively included. After management, the rate of downturn, reexamination rate, blood pressure compliance rate, metabolic indicators (waist circumference, body mass index, fasting blood glucose, glycosylated hemoglobin, blood lipids) and screening rate of chronic complications of diabetes (atherosclerotic cardiovascular disease, microvascular disease, diabetic peripheral neuropathy) were analyzed. Those included 2022 ( n=564), 2023 ( n=1 477), and 2024 ( n=2 527). Results:The downturn rate in 2022, 2023 and 2024 increased year by year (22.8% vs 67.2% vs 89.9%, P<0.01), and the review rate (41.1% vs 62.2% vs 52.7%, P<0.01), complication screening rate (51.6% vs 85.3% vs 62.2%, P<0.01), blood pressure compliance rate (53.1% vs 78.0% vs 67.2%, P<0.01), body mass index compliance rate (13.2% vs 17.3% vs 28.6%, P<0.01), fasting blood glucose meeting rate (46.4% vs 60.2% vs 68.5%, P<0.01), glycated hemoglobin meeting rate (58.4% vs 63.2% vs 45.6%, P<0.01) were relatively improved. Waist circumference compliance rate (30.6% vs 27.7% vs 21.6%) and blood lipid compliance rate (33.6% vs 35.5% vs 31.9%) were not significantly improved, and the review rate, blood pressure compliance rate and complication screening rate in 2024 were lower than those in 2023 and higher than those in 2022. Conclusions:The combined management of type 2 diabetes under the DPCC model has significant effects on improving the down-conversion rate, rediagnosis rate, blood pressure compliance rate, metabolic index compliance rate and the screening rate of diabetes-related chronic complications in patients with diabetes. At the same time, it was also found that with the progress of hierarchical diagnosis and treatment, the review rate, complication screening rate, blood pressure, waist circumference, blood lipid and glycosylated hemoglobin reached the standard of patients decreased compared with the previous situation, which needs to be further analyzed and improved.

Objective To establish a reversed-phase HPLC method for determining three stereoisomers in baloxavir marboxil and provide a basis for the quality specification of baloxavir marboxil.Methods The chromatographic column was CHIRALPAK IC-3(4.6 mm × 150 mm,3 μm),The mobile phase was acetonitrile-0.1％formic acid aqueous solution-isopropanol(35:50:15).The column temperature was 40 ℃.The flow rate was 0.5 mL·min-1.The injection volume was 10 μL.The detection wavelength was 259 nm.Result The isomer peaks were completely separated from the principal component peak.The detection limits for stereoisomers 1,2 and 3 were 0.024 7,0.038 7,0.038 1 μg·mL-1 respectively.The quantitation limits for stereoisomers 1,2 and 3 were 0.049 4,0.077 3,0.076 1 μg·mL-1 respectively.There were good linear relationships between the concentrations and peak area within the ranges of the study,and the linearity concentration ranges of stereoisomers 1,2 and 3 were 0.049 5-0.989 0 μg·mL-1,0.051 6-1.031 0 μg·mL-1,0.050 8-1.015 0 μg·mL-1 respectively.The linear correlation coefficients were 0.999 4.The recovery was 92.28％-103.90％.The sample solution was stable in 48 h at room temperature.Conclusion The method is accurate and reliable for determining stereoisomers in baloxavir marboxil,and provide a guideline of quality standards of baloxavir marboxil and safety evalution.

Objective To define the operation scale of the biochemical test project based on the risk model,and design the statistical quality control(SQC)strategy by rationally adjusting the risk factors.Methods The σ(σ)values for the biochemistry test items were calculated based on the imprecision(CV)of internal quality control(IQC),external quality assessment(EQA)offset bias(Bias)and allowable total error(TEa)of CLIA 2019.By evaluating and adjusting the patient risk factors,designed the SQC for multiple test biochemical items representing high σ,medium σ and low σ categories.Results Clinical biochemistry testing items with different QC levels showed different σ performance,with values for P and K quality control levels 2 higher than level 1 and the remaining items all had very similar.18 projects for risk σ≥4.96:CK,LDH,GGT,AMY,AST,MG,TG,TBIL,FE,NA,UA,CREA,P,ALP,K,ALT and CA,respectively.Controlled with a QC program 13s N=2,run size was 179～1 000 samples.ALB,GLU,CL,TP and UREA need to achieve the expected operational scale by adjusting for risk factors.Conclusion The laboratory can combine program testing performance and patient safety goals,design SQC strategies for clinical biochemistry testing programs by rationally adjusting risk factors,apply as few SQC procedures for as much testing as possible,and align the laboratory workload and reporting interval with the number of patient samples.