Liver cancer is one of the world's serious diseases today because of its high frequency and fatality rate, genetic differences, and limited effectiveness of late-stage therapy. Although chemotherapy, targeted therapy, immunotherapy, ablation and transarterial chemoembolisation (TACE) have improved the disease control of some patients, recurrence and acquired resistance are still common, especially for tumors that are hypoxic, nutrient-deprived, acidic-stressed, vascularly insufficient and exposed to repeated drug pressure. A bad environment will cause a change in the quality-control system and metabolism of cancer cells, and as a result, lysosomes have started to alter. In addition to the above catabolic functions of lysosomes, they also take part in autophagic flux, substrate recycling, iron and lipid metabolism, nutrient sensing, drug distribution, membrane repair and cell death signalling. Under the stress of therapy in liver cancer cells, increased lysosomal acidification and enhanced terminal degradation lead to prolonged autophagy; TFEB/TFE3 promotes the formation of new lysosomes and lysophagosomes to sequester weakly basic drugs, thereby reducing the concentration of active drugs and mitigating proteotoxicity and oxidative stress to promote cell survival. The above processes produce a lysosome-dependent resistant phenotype that is particularly relevant to sorafenib and doxorubicin and other drugs whose effectiveness can be reduced by protective autophagy or changes in intracellular location. Conversely, the same dependency on lysosomal homeostasis is also a vulnerability. Natural products and monomeric compounds derived from Chinese herbal medicines have various structures, multiple target regulation capabilities, and the potential to act on several lysosome-related nodes simultaneously. Based on the evidence in this review, it is believed that such compounds may sensitise liver cancer cells by inhibiting V-ATPase-mediated acid hydrolysis, obstructing late-stage autophagy-mediated degradation, disrupting lysosomal calcium or membrane homeostasis, causing lysosomal membrane permeabilisation, reducing compensatory lysosomal biogenesis, promoting ferritin degradation and ferroptosis, or enhancing acid-responsive intracellular delivery. Agents that impair lysosomal function and protective autophagy, compounds that convert enlarged or drug-sequestering lysosomes into lethal targets, and nanodelivery systems that exploit the acidic environment of endolysosomes to co-deliver natural products with chemotherapeutic drugs are examples. Lysosome-targeted intervention will have different effects under different circumstances; for example, inhibiting autophagy may result in an increase in cytotoxic stress in some areas, whereas overstimulation of autophagy or iron release from lysosomes may induce autophagic cell death or ferroptosis in other areas. Therefore, the design of therapy should take into account the status of the tumour microenvironment, autophagic flux, lysosomal pH, TFEB/TFE3 activity, drug sequestration capacity, ferroptosis sensitivity, dosing sequence and delivery route. This review systematically examines the lysosomal homeostasis in the microenvironment of liver cancer, the mechanisms through which lysosomal adaptation contributes to chemoresistance, and the rationale for combining natural products with standard agents such as sorafenib and doxorubicin. Based on basic lysosome biology, pharmacodynamic and delivery data have also been collected; as a result, some applications for future studies have been proposed, such as dynamic monitoring of autophagy flux, in vivo spatial measurements of lysosomal functions, rational optimisation of combination therapy timings, and safety assessments in immunocompetent liver cancer models prior to clinical translation. Translation difficulties are also evident, such as insufficient tumour selectivity, pharmacokinetic limitations, compensatory lysosomal regeneration, toxicity to normal liver and immune cells, and a lack of validated predictive biomarkers. A new way will be found to use biomarkers to divide the patient group, optimize nanoparticles for better delivery, design specific schedules for combined treatments based on the problem they cause within the cell, etc., thereby overcoming drug resistance and reducing the harm patients suffer from toxic treatments. This system can help select biomarkers and rational drug pairs for the next round of lysosome-centred precision trials.

Objective To observe the therapeutic effects of different doses of methylprednisolone(MP)on smoke inhalation-induced acute lung injury(SI-ALI)in rats,and to explore the changes in the expression of aquaporins(AQPs)and the underlying mechanisms for alleviating lung injury.Methods A total of 86 healthy adult male Sprague-Dawley(SD)rats were randomly divided into five groups:control group(n=6),smoke inhalation injury(SI)group(n=20),low-dose MP group(LMP,SI+0.4 mg/kg MP,n=20),medium-dose MP group(MMP,SI+4 mg/kg MP,n=20),and high-dose MP group(HMP,SI+40 mg/kg MP,n=20).A model of smoke inhalation-induced lung injury was established.The survival status of the rats in each group was monitored.Lung tissues were collected 24 hours after injury to determine the wet-to-dry(W/D)ratio of the lung tissues,arterial oxygen partial pressure(PaO2),and the expression levels of inflammatory cytokines TNF-α and IL-6.The degree of lung injury was evaluated using HE staining,and the mRNA and protein expression levels of AQP1 and AQP5 in the lung tissues were detected.Results Compared with control group,the survival rate of the rats in SI group was significantly decreased(P<0.05);compared with SI group,the survival rates of the rats in MMP and HMP groups were significantly increased(P<0.05).Compared with control group,the PaO2 of the Rats in SI group was significantly decreased(P<0.05),and the wet-to-dry(W/D)ratio and lung injury scores were significantly increased(P<0.05).Compared with SI group,the PaO2 of the rats in LMP,MMP,and HMP groups(P<0.05)was significantly increased(P<0.05),and the lung W/D ratio and injury scores in MMP and HMP groups were significantly decreased(P<0.05).ELISA results showed that compared with control group,the serum concentrations of TNF-α and IL-6 in SI group were significantly increased(P<0.05);compared with SI group,the concentrations of TNF-α and IL-6 in MMP and HMP groups were significantly decreased(P<0.05).HE staining revealed that the alveolar structure of the rats in SI group was severely damaged;compared with SI group,the damage to the alveolar structure in MMP and HMP groups was alleviated.Real-time PCR and Western blotting analysis results showed that compared with control group,the mRNA and protein expression levels of AQP1 and AQP5 in lung tissues in SI group were significantly decreased(P<0.05);however,compared with SI group,these levels in LMP,MMP,and HMP groups were significantly increased(P<0.05).Conclusions Smoke inhalation can induce acute lung injury in rats and down-regulate the expression levels of AQP1 and AQP5 in the lung tissues.Methylprednisolone can alleviate pulmonary edema and tissue damage in rats caused by smoke inhalation,and induce the up-regulation of the expression of AQP1 and AQP5.

Objective To establish and evaluate a nomogram prediction model for spontaneous peritonitis in HBV-related primary liver cancer.Methods A retrospective study was conducted on 1298 patients with HBV-related primary liver cancer hospitalized in the Kunming Third People's Hospital from January 2012 to December 2022.General data and serological indicators were collected,and patients were divided into infection group(n=262)and control group(n=1036)based on the occurrence of spontaneous peritonitis.Univariate and LASSO regression analyses were used to screen variables,followed by binary logistic regression to analyze the influencing factors of spontaneous peritonitis in HBV-related primary liver cancer patients,leading to the establishment of a nomogram prediction model.Finally,the Hosmer-lemeshow(H-L)goodness of fit test,receiver operating characteristic(ROC)curve,calibration curve,decision curve analysis(DCA)and clinical impact curve(CIC)were utilized to evaluate the fit degree,accuracy,calibration,and clinical practicability of the nomogram prediction model.Results Single factor analysis revealed significant differences between infection group and control group in portal vein cancer thrombus(PVTT),Child-Pugh grade,China Liver Cancer Staging(CNLC)stage,alcohol consumption history,smoking history,white blood cell count(WBC),neutrophil count(NE),hemoglobin(Hb),fibrinogen(FIB),abnormal prothrombin(PIVKA-Ⅱ),aspartate aminotransferase(AST),alanine aminotransferase(ALT),total protein(TP),prealbumin(PA),γ-glutamyltransferase(GGT),alkaline phosphatase(ALP),cholinesterase(CHE),total bile acid(TBA),total cholesterol(TC),low density lipoprotein(LDL),creatinine(Cr),HBV DNA,CD3+T cells count,CD4+T cells count,CD8+T cells count,CD4+T cells/CD8+T cells ratio,procalcitonin(PCT),serum amyloid A(SAA),interleukin-6(IL-6),high-sensitivity C-reactive protein(hs-CRP),alpha-fetoprotein(AFP),and IL-4(P＜0.05).LASSO regression analysis identified 5 variables:Child-Pugh grade,PVTT,WBC,CHE and hs-CRP.Binary logistic regression analysis indicated that Child-Pugh grade(Grade B:OR=5.780,95％CI 3.271-10.213,P＜0.001;Grade C:OR=14.818,95％CI 7.697-28.526,P＜0.001),PVTT(OR=2.893,95％CI 2.037-4.108,P＜0.001),WBC(OR=1.088,95％CI 1.031-1.148,P=0.002),and hs-CRP(OR=1.005,95％CI 1.001-1.010,P=0.026)were the independent risk factors of spontaneous peritonitis in HBV-related primary liver cancer patients.Using these 4 variables,a nomogram prediction model was constructed and evaluated.The P-value of the H-L goodness of fit test was 0.760.Moreover,the area under ROC curve(AUC)was 0.866,with a sensitivity of 0.870 and a specificity of 0.716.The average absolute error of the calibration curve is 0.022.DCA and CIC analyses demonstrated that the nomogram prediction model possessed some clinical utility.Conclusion The nomogram prediction model for spontaneous peritonitis in HBV-related primary liver cancer patients,constructed using Child-Pugh grade,PVTT,WBC and hs-CRP,exhibits a high fitting degree and accuracy,with the prediction probability highly consistent with the actual occurrence probability,and possesses certain clinical practicability.

ObjectiveTo study the mechanism by which Shexiang Tongxin dropping pills （STDP） ameliorate the dysfunction of coronary microvascular endothelial cells in the rat model of heart failure. MethodsThe heart failure model was established by ligation of the left anterior descending coronary artery in rats， which were then allocated into sham， model， STDP， and telmisartan （TLM） groups and treated for 21 days. The heart function was detected by echocardiography， and the levels of myocardial injury markers， nitric oxide （NO）， endothelin-1 （ET1）， and angiotensinⅡ （AngⅡ） were determined by enzyme-linked immunosorbent assay （ELISA）. The protein levels of endothelial nitric oxide synthase （eNOS） and inducible nitric oxide synthase （iNOS） were determined by Western blot. The model of cardiac microvascular endothelial cell injury was established by AngⅡ induction and then treated with the STDP-containing serum （5%， 10%， and 20%） for 24 h. The levels of NO and ET1 were measured by ELISA. Western blot was employed to determine the protein levels of eNOS， iNOS， angiotensin-converting enzyme 2 （ACE2）， and angiotensinⅡ receptor 2 （AT2）. MLN-4760， an ACE2 inhibitor， was used to explore the mechanism underpinning the regulatory effect of STDP on the ACE2-AT2/MAS pathway. ResultsCompared with the sham group， the model group showed decreases in left ventricular ejection fraction （LVEF） and left ventricular fractional shortening （LVFS） （P<0.05）， a decline in serum NO level， elevations in serum AngⅡ and ET1 levels， a reduction in p-eNOS/eNOS ratio， and up-regulation in iNOS expression （P<0.05）. Compared with the model group， STDP increased LVEF， LVFS， and cardiac output （P<0.05）， raised the level of NO and lowered the levels of AngⅡ and ET1 in the serum （P<0.05）， increased the p-eNOS/eNOS value， and inhibited iNOS expression （P<0.05）. Compared with the AngⅡ group， STDP increased the NO content and decreased the ET1 content in endothelial cells （P<0.05）， increased the p-eNOS/eNOS ratio， and inhibited the iNOS expression （P<0.05）. The ACE2 inhibitor MLN-4760 reversed the regulatory effects of STDP on p-eNOS， eNOS， and iNOS. ConclusionSTDP improves the cardiac function in the rat model of heart failure， enhances the synthesis and release of NO in cardiac microvascular endothelial cells， reduces AngⅡ and ET1 levels， and regulates the expression of p-eNOS and eNOS， thereby ameliorating the dysfunction of microvascular endothelial cells in heart failure. This mechanism is related to the upregulation of the expression of proteins in the ACE2-AT2/MAS pathway.

OBJECTIVE: The relationship between fish consumption and stroke is inconsistent, and it is uncertain whether this association varies across predicted stroke risks. METHODS: A cohort study comprising 95,800 participants from the Prediction for Atherosclerotic Cardiovascular Disease Risk in China project was conducted. A standardized questionnaire was used to collect data on fish consumption. Participants were stratified into low- and moderate-to-high-risk categories based on their 10-year stroke risk prediction scores. Hazard ratios ( HRs) and 95% confidence intervals ( CIs) were estimated using Cox proportional hazard models and additive interaction by relative excess risk due to interaction (RERI), attributable proportion (AP), and synergy index (SI). RESULTS: During 703,869 person-years of follow-up, 2,773 incident stroke events were identified. Higher fish consumption was associated with a lower risk of stroke, particularly among moderate-to-high-risk individuals ( HR = 0.53, 95% CI: 0.47-0.60) than among low-risk individuals ( HR = 0.64, 95% CI: 0.49-0.85). A significant additive interaction between fish consumption and predicted stroke risk was observed (RERI = 4.08, 95% CI: 2.80-5.36; SI = 1.64, 95% CI: 1.42-1.89; AP = 0.36, 95% CI: 0.28-0.43). CONCLUSION Higher fish consumption was associated with a lower risk of stroke, and this beneficial association was more pronounced in individuals with moderate-to-high stroke risk.
Humans ; China/epidemiology* ; Male ; Female ; Stroke/etiology* ; Middle Aged ; Prospective Studies ; Incidence ; Aged ; Animals ; Fishes ; Risk Factors ; Diet ; Seafood ; Adult ; Cohort Studies

OBJECTIVE: To identify the key features of facial and tongue images associated with anemia in female populations, establish anemia risk-screening models, and evaluate their performance. METHODS: A total of 533 female participants (anemic and healthy) were recruited from Shuguang Hospital. Facial and tongue images were collected using the TFDA-1 tongue and face diagnosis instrument. Color and texture features from various parts of facial and tongue images were extracted using Face Diagnosis Analysis System (FDAS) and Tongue Diagnosis Analysis System version 2.0 (TDAS v2.0). Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for feature selection. Ten machine learning models and one deep learning model (ResNet50V2 + Conv1D) were developed and evaluated. RESULTS: Anemic women showed lower a-values, higher L- and b-values across all age groups. Texture features analysis showed that women aged 30-39 with anemia had higher angular second moment (ASM)and lower entropy (ENT) values in facial images, while those aged 40-49 had lower contrast (CON), ENT, and MEAN values in tongue images but higher ASM. Anemic women exhibited age-related trends similar to healthy women, with decreasing L-values and increasing a-, b-, and ASM-values. LASSO identified 19 key features from 62. Among classifiers, the Artificial Neural Network (ANN) model achieved the best performance [area under the curve (AUC): 0.849, accuracy: 0.781]. The ResNet50V2 model achieved comparable results [AUC: 0.846, accuracy: 0.818]. CONCLUSION Differences in facial and tongue images suggest that color and texture features can serve as potential TCM phenotype and auxiliary diagnostic indicators for female anemia.
Humans ; Female ; Tongue/diagnostic imaging* ; Adult ; Anemia/diagnosis* ; Middle Aged ; Face/diagnostic imaging* ; Young Adult ; Machine Learning

AIM To evaluate the quality of Gegen Formula Granules.METHODS Linear calibration with two reference substances(LCTRS)was adopted in the predicting of retention time with puerarin and daidzein as internal standards.UPLC characteristic chromatograms were established.The contents of 3'-hydroxy puerarin,puerarin(internal standard),3'-methoxy puerarin,puerarin 6"-O-xyloside,puerarin apioside and daidzin were determined by quantitative determination analysis multi-components by a single marker(QAMS),after which their transfer rates were calculated.RESULTS Compared with relative retention time method,LCTRS demonstrated higher positional accuracy for characteristic peaks and wider application range for columns.There were 9 characteristic peaks in the characteristic chromatograms for 14 batches of formula granules and 15 batches of standard decoctions with the similarities of more than 0.95.The contents and transfer rates of various constituents in formula granules and standard decoctions were basically consistent.CONCLUSION The chemical constituents in formula granules and their standard decoctions of Puerariae lobatae Radix display good consistency,reliable preparation process is observable in the former.

The development of breast cancer is closely related to the information transfer in its microenvironment.As a novel information communication tool,exosomes present non-coding RNAs that are involved in breast cancer cell proliferation,migration,invasion,tumour-associated fibroblasts ogenesis,cell cycle,degradation of oncogenes,etc.This paper reviews the relationship between exosomes and the tumour microenvironment and the role of their presenting non-coding RNAs on breast cancer as well as their clinical applications in order to provide new ideas for biological research and therapeutic strategies.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.