Objective:To prepare the nanodrug paclitaxel dimer(PTX2)-loaded nanoparticles(NPs)using the block copolymer 1,2-distearoyl-sn-glycero-3-phosphoethanolamine-polyethylene glycol 2000,(DSPE-PEG2000),and to explore the killing effect of PTX2 NPs on the human lung cancer A549 cells and its influence on apop to tis.Methods:The PTX2 NPs were prepared using nanoprecipitation method.Dynamic light scattering(DLS)was employed to determine the particle size distribution,and transmission electron microscope(TEM)was used to observe the ultrastructure of the nanoparticles.After treatment of 0 and 10 mmol·L-1 dithiothreitol(DTT),dialysis method was used to evaluate the in vitro drug release profile of PTX2 NPs.The cell counting kit-8(CCK-8)method was used to assess the survival rates of the A549 cells after treated with PTX2 and PTX2 NPs with different concentrations(0.000 1,0.001 0,0.010 0,0.100 0,and 1.000 0 μmol·L-1).The A549 cells were divided into control group,PTX2 group,and PTX2 NPs group.Live/dead staining method was used to detect the survival of the A549 cells in various groups,and flow cytometry was used to detect the apoptotic rates of the A549 cells in various groups.Results:The mean hydrodynamic diameter of PTX2 NPs was determined to be 144.7nmbyDLS.TheTEM imaging confirmed uniform spherical morphology of PTX2 NPs.In a reductive environment,the PTX2 NPs exhibited continuous drug release with total paclitaxel(PTX)release of 84％within 72 h.The results of CCK-8 method showed that both PTX2 and PTX2 NPs inhibited the proliferation of A549 cells in a dose-dependent manner.When the concentrations of PTX＜0.01 μmol·L-1,compared with PTX2 group,the survival rates of A549 cells in PTX2 NPs group were significantly decreased(P＜0.01 or P＜0.001).The live/dead staining results showed that compared with PTX2 group,the number of red fluorescence-labeled dead cells in PTX2 NPs group was increased.The flow cytometry results demonstrated that compared with control group and PTX2 group,the apoptotic rates of the A549 cells in PTX2 NPs group were significantly increased(P＜0.05 orP＜0.01).Conclusion:The PTX2-loaded nanoparticles PTX2 NPs are successfully prepared which exhibits responsive drug release and demonstrates a more significant killing effect on the human lung cancer A549 cells compared to PTX2.

The integration of multi-source data and the establishment of early warning indicator systems constitute pivotal elements for advancing surveillance and early warning capacities in respiratory infectious diseases. Given the multifaceted transmission mechanisms and complex contributing factors inherent in respiratory infectious diseases, surveillance datasets and associated early warning indicators demonstrate notable heterogeneity and sophisticated interrelationships. Furthermore, as surveillance and early warning requirements significantly vary across diverse epidemiological scenarios, accurate assessment of the value and applicability of distinct data types and indicators is imperative. This paper systematically reviews and synthesizes recent advancements in surveillance data and early warning indicators for respiratory infectious diseases, drawing on both domestic and international research. Particular attention is dedicated to analyzing the applicability and efficacy of various data types and indicators within multiple practical contexts, aiming to provide robust theoretical frameworks and methodological guidance to facilitate the development of resilient and efficient surveillance and early warning systems for respiratory infectious diseases.

Hepatocellular carcinoma(HCC)is difficult to detect in its early stages and current treatment methods are associated with significant side effects and a high risk of developing drug resistance.This study aims to investigate the effect of phycocyanin(PC)on the apoptosis of human HCC HepG2 cells and its potential mechanism.HepG2 cells were treated with PC at concentrations of 0.1,0.25,0.5,1,2.5,5,and 10 μg/mL for 12 h,and with 10 μg/mL PC and 2.5 μmol/L Wip1 inhibitor(Wip1i)alone or in combination for 12 and 24 h,respectively.Cell proliferation levels were assessed using the CCK-8 cell proliferation-toxicity assay kit.Apoptosis levels were measured by Annexin V-FITC/Propidium Iodide double staining combined with flow cytometry.TMT(Tandem Mass Tag)proteomics quantitative technol-ogy was applied to analyze differential protein expression.Western blotting was used to detect the expres-sion levels of Wip1,p53,and phosphorylated-p53(Ser15)proteins.The CCK-8 assay revealed that PC effectively inhibited HepG2 cell proliferation in a concentration-dependent manner,with a half-maximal inhibitory concentration(IC50)of 19.37 μg/mL.Flow cytometry results showed that PC significantly in-duced apoptosis,with an apoptosis rate of 30.40％.Quantitative proteomics analysis indicated that PC induced activation of the p53 pathway.The CCK-8 assay showed that Wip1i enhanced the cytotoxic effect of PC on HepG2 cells.Western blotting confirmed that PC inhibited Wip1 expression,induced p53 pro-tein phosphorylation,and promoted the expression of total p53 protein.Additionally,Wip1i further en-hanced PC-mediated activation of the p53 pathway,increasing the expression of p53 and pP53(S15).In conclusion,PC may induce apoptosis by inhibiting the activity of the p53 negative regulator Wip1,thereby promoting apoptosis through the Wip1/p53 pathway.

Objective To construct a nomogram model for predicting pulmonary hemorrhage associated with the positioning of pulmonary nodules with the new four-hook positioning needle based on clinical-CT imaging features and evaluate its predictive efficacy.Methods We made a retrospective analysis of the clinical,imaging and pathological data of 449 patients with pulmonary nodules positioned by the new four-hook positioning needle.According to the random number table method(7∶3),they were divided into a training set of 314 cases and a validation set of 135 cases.Each data set was further divided into positive group and negative group for pulmonary hemorrhage according to the presence or absence of pulmonary hemorrhage.We evaluated the CT imaging features of pulmonary nodules,including nodule nature(pure ground-glass density,mixed ground-glass density,solid nodule),nodule diameter,distance from the nodule to the pleural surface(hereinafter referred to as length),nodule positioning time,and association with pulmonary hemorrhage.Independent sample t-test,Mann-Whitney U test and x2 test were used to compare the correlations of clinical and CT features of pulmonary nodules with pulmonary hemorrhage.LASSO regression and multivariate Logistic regression were employed to screen the independent risk factors related to pulmonary hemorrhage and construct a nomogram model.The receiver operating characteristic(ROC)curve was used to evaluate the predictive efficacy of the model,and the calibration curve and decision curve were respectively used for the verification of the nomogram model and evaluation of the clinical net benefit.Results The results of LASSO regression showed that the nature of pulmonary nodules,underlying diseases,smoking and length were the characteristic variables related to pulmonary hemorrhage.Based on the minimum akaike information criterion(AIC),the screened characteristic variables were included in the multivariate Logistic backward stepwise regression analysis.The results showed that the nature of pulmonary nodules,underlying diseases,smoking and length were all independent risk factors related to pulmonary hemorrhage.A nomogram was established according to the above independent risk factors and the ROC curve was drawn.The AUC of the training set was 0.86(95％CI:0.80-0.91),and the AUC of the validation set was 0.88(95％CI:0.80-0.96),with no statistically significant difference(P＞0.05).The calibration curve suggested that the predicted values of the nomogram were close to the actual values,and the decision curve analysis showed that the net benefit of the model was good.Conclusion The nomogram model established by combining clinical-CT features such as the nature of pulmonary nodules,underlying diseases,smoking and length can effectively predict pulmonary hemorrhage associated with the positioning of pulmonary nodules with the new four-hook positioning needle.

The integration of multi-source data and the establishment of early warning indicator systems constitute pivotal elements for advancing surveillance and early warning capacities in respiratory infectious diseases. Given the multifaceted transmission mechanisms and complex contributing factors inherent in respiratory infectious diseases, surveillance datasets and associated early warning indicators demonstrate notable heterogeneity and sophisticated interrelationships. Furthermore, as surveillance and early warning requirements significantly vary across diverse epidemiological scenarios, accurate assessment of the value and applicability of distinct data types and indicators is imperative. This paper systematically reviews and synthesizes recent advancements in surveillance data and early warning indicators for respiratory infectious diseases, drawing on both domestic and international research. Particular attention is dedicated to analyzing the applicability and efficacy of various data types and indicators within multiple practical contexts, aiming to provide robust theoretical frameworks and methodological guidance to facilitate the development of resilient and efficient surveillance and early warning systems for respiratory infectious diseases.

Objective To construct a nomogram model for predicting pulmonary hemorrhage associated with the positioning of pulmonary nodules with the new four-hook positioning needle based on clinical-CT imaging features and evaluate its predictive efficacy.Methods We made a retrospective analysis of the clinical,imaging and pathological data of 449 patients with pulmonary nodules positioned by the new four-hook positioning needle.According to the random number table method(7∶3),they were divided into a training set of 314 cases and a validation set of 135 cases.Each data set was further divided into positive group and negative group for pulmonary hemorrhage according to the presence or absence of pulmonary hemorrhage.We evaluated the CT imaging features of pulmonary nodules,including nodule nature(pure ground-glass density,mixed ground-glass density,solid nodule),nodule diameter,distance from the nodule to the pleural surface(hereinafter referred to as length),nodule positioning time,and association with pulmonary hemorrhage.Independent sample t-test,Mann-Whitney U test and x2 test were used to compare the correlations of clinical and CT features of pulmonary nodules with pulmonary hemorrhage.LASSO regression and multivariate Logistic regression were employed to screen the independent risk factors related to pulmonary hemorrhage and construct a nomogram model.The receiver operating characteristic(ROC)curve was used to evaluate the predictive efficacy of the model,and the calibration curve and decision curve were respectively used for the verification of the nomogram model and evaluation of the clinical net benefit.Results The results of LASSO regression showed that the nature of pulmonary nodules,underlying diseases,smoking and length were the characteristic variables related to pulmonary hemorrhage.Based on the minimum akaike information criterion(AIC),the screened characteristic variables were included in the multivariate Logistic backward stepwise regression analysis.The results showed that the nature of pulmonary nodules,underlying diseases,smoking and length were all independent risk factors related to pulmonary hemorrhage.A nomogram was established according to the above independent risk factors and the ROC curve was drawn.The AUC of the training set was 0.86(95％CI:0.80-0.91),and the AUC of the validation set was 0.88(95％CI:0.80-0.96),with no statistically significant difference(P＞0.05).The calibration curve suggested that the predicted values of the nomogram were close to the actual values,and the decision curve analysis showed that the net benefit of the model was good.Conclusion The nomogram model established by combining clinical-CT features such as the nature of pulmonary nodules,underlying diseases,smoking and length can effectively predict pulmonary hemorrhage associated with the positioning of pulmonary nodules with the new four-hook positioning needle.

Hepatocellular carcinoma(HCC)is difficult to detect in its early stages and current treatment methods are associated with significant side effects and a high risk of developing drug resistance.This study aims to investigate the effect of phycocyanin(PC)on the apoptosis of human HCC HepG2 cells and its potential mechanism.HepG2 cells were treated with PC at concentrations of 0.1,0.25,0.5,1,2.5,5,and 10 μg/mL for 12 h,and with 10 μg/mL PC and 2.5 μmol/L Wip1 inhibitor(Wip1i)alone or in combination for 12 and 24 h,respectively.Cell proliferation levels were assessed using the CCK-8 cell proliferation-toxicity assay kit.Apoptosis levels were measured by Annexin V-FITC/Propidium Iodide double staining combined with flow cytometry.TMT(Tandem Mass Tag)proteomics quantitative technol-ogy was applied to analyze differential protein expression.Western blotting was used to detect the expres-sion levels of Wip1,p53,and phosphorylated-p53(Ser15)proteins.The CCK-8 assay revealed that PC effectively inhibited HepG2 cell proliferation in a concentration-dependent manner,with a half-maximal inhibitory concentration(IC50)of 19.37 μg/mL.Flow cytometry results showed that PC significantly in-duced apoptosis,with an apoptosis rate of 30.40％.Quantitative proteomics analysis indicated that PC induced activation of the p53 pathway.The CCK-8 assay showed that Wip1i enhanced the cytotoxic effect of PC on HepG2 cells.Western blotting confirmed that PC inhibited Wip1 expression,induced p53 pro-tein phosphorylation,and promoted the expression of total p53 protein.Additionally,Wip1i further en-hanced PC-mediated activation of the p53 pathway,increasing the expression of p53 and pP53(S15).In conclusion,PC may induce apoptosis by inhibiting the activity of the p53 negative regulator Wip1,thereby promoting apoptosis through the Wip1/p53 pathway.

The plants of Rutaceae, with wide distribution in China, have a long history of medicinal use. They contain a wide variety of alkaloids, which include isoquinolines, quinolines, acridones, carbazoles, and indoles. Pharmacological studies have shown that most of these alkaloids have antitumor, anti-inflammatory, antiviral, antidiabetic and other activities. This article summarized 378 alkaloids isolated from plants of Rutaceae and their pharmacological effects, aiming to lay a basis for future drug development and sustainable utilization of plant resources.
Alkaloids/chemistry* ; Humans ; Rutaceae/chemistry* ; Animals ; Drugs, Chinese Herbal/chemistry* ; Anti-Inflammatory Agents/chemistry*

Background/Aims: The performance of machine learning (ML) in predicting the outcomes of patients with hepatocellular carcinoma (HCC) remains uncertain. We aimed to develop risk scores using conventional methods and ML to categorize early-stage HCC patients into distinct prognostic groups. Methods: The study retrospectively enrolled 1,411 consecutive treatment-naïve patients with the Barcelona Clinic Liver Cancer (BCLC) stage 0 to A HCC from 2012 to 2021. The patients were randomly divided into a training cohort (n=988) and validation cohort (n=423). Two risk scores (CATS-IF and CATS-INF) were developed to predict overall survival (OS) in the training cohort using the conventional methods (Cox proportional hazards model) and ML-based methods (LASSO Cox regression), respectively. They were then validated and compared in the validation cohort. Results: In the training cohort, factors for the CATS-IF score were selected by the conventional method, including age, curative treatment, single large HCC, serum creatinine and alpha-fetoprotein levels, fibrosis-4 score, lymphocyte-tomonocyte ratio, and albumin-bilirubin grade. The CATS-INF score, determined by ML-based methods, included the above factors and two additional ones (aspartate aminotransferase and prognostic nutritional index). In the validation cohort, both CATS-IF score and CATS-INF score outperformed other modern prognostic scores in predicting OS, with the CATSINF score having the lowest Akaike information criterion value. A calibration plot exhibited good correlation between predicted and observed outcomes for both scores. Conclusions Both the conventional Cox-based CATS-IF score and ML-based CATS-INF score effectively stratified patients with early-stage HCC into distinct prognostic groups, with the CATS-INF score showing slightly superior performance.

Objective To investigate the mechanism of Guizhi Fuling Pills in the treatment of polycystic ovary syndrome(PCOS)and endometriosis(EMT).Methods TCMSP was utilized to obtain the active ingredients and related targets of the constituent Chinese medicines of Guizhi Fuling Pills.GeneCards,PharmGKB,and TTD databases were used to screen PCOS and EMT disease targets,respectively.The Venn R diagram was drawn after obtaining the intersecting targets of drugs and diseases using the Venn R package in R software,the drug-active ingredient-potential target interactions network diagram was made in Cytoscape,the intersecting target protein-protein interactions(PPI)network diagram was drawn in the STRING platform,and Cytoscape was used to optimize the PPI network and screen the core targets.R language was applied for Gene Ontology(GO)enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis,and AutoDockTools was for molecular docking.Results A total of 85 active ingredients and 191 corresponding targets of Guizhi Fuling Pills were obtained,and 77 potential targets of Guizhi Fuling Pills for the treatment of PCOS and EMT.The core active ingredients of Guizhi Fuling Pills for PCOS and EMT were quercetin,β-sitosterol,kaempferol,hederagenin,baicalein,and the core targets were AKT1,EGFR,IL-6,TNF,and TP53.GO functional analysis yielded 2 020 biological process,34 cellular components,126 molecular functions,and KEGG enrichment analysis yielded 165 signaling pathways.Molecular docking showed that the core components in the formula docked well with the targets.Conclusion Guizhi Fuling Pills may regulate the signaling pathways of lipid and atherosclerosis,AGE-RAGE signaling pathway,fluid shear stress and atherosclerosis,and chemical carcinogenesis-receptor activation through quercetin,β-sitosterol,kaempferol,hederagenin,and baicalein,and act on AKT1,EGFR,IL-6,TNF,and TP53,thus treating PCOS and EMT with homotherapy for heteropathy.