OBJECTIVE To investigate the mechanism of Shenling baizhu san （SLBZS） in ameliorating ulcerative colitis （UC）. METHODS Mice were randomly divided into normal group， model group， and low-， medium-， high-dose SLBZS groups （3， 6， 12 g/kg）， with 10 mice in each group. Except for the normal group， mice in other groups were given free access to 3% dextran sulfate sodium solution for 7 days to establish UC models. Simultaneously， mice in each group were intragastrically administered corresponding medicinal liquid or double-distilled water once a day for consecutive 7 days. After the last administration， the histopathological morphology of colon tissues was observed； the serum levels of inflammatory factors including tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β） and IL-18 were detected； the total bile acid contents in liver， gallbladder and colon tissues were determined； the expression level of NOD-like receptor family pyrin domain-containing protein 3 （NLRP3） in colon tissues was tested. The expression levels of flora metabolism-related proteins [G protein-coupled receptor 41（GPR41），GPR43，farnesoid X receptor （FXR）， G protein-coupled bile acid receptor 1 （TGR5）， flavin-containing monooxygenase 3 （FMO3）， cytochrome P450 family 27 subfamily A member 1 （CYP27A1）， CYP7A1] in liver or colon tissues， as well as the proteins related to Toll-like receptor 4 （TLR4）/nuclear factor-κB （NF-κB）/NLRP3 inflammatory axis [TLR4， NF-κB， phosphorylated NF-κB （p-NF-κB）， myeloid differentiation factor 88 （MyD88）， NLRP3， apoptosis-associated speck-like protein containing a CARD （ASC）， caspase-1] in colon tissues were measured. RESULTS Compared with the model group， the colon tissue injury and inflammatory cell infiltration were alleviated in medium- and high-dose SLBZS groups. The serum levels of TNF-α， IL-1β and IL-18， total bile acid contents in liver and colon tissues， as well as the protein expression levels of FMO3 and CYP7A1 in liver tissues， TLR4， p-NF-κB， NF-κB， MyD88， NLRP3， ASC and caspase-1 in colon tissues were significantly decreased （P＜0.05）. Meanwhile， the total bile acid content in gallbladder， the protein expression levels of GPR41 and GPR43 in colon tissues， along with CYP27A1， FXR and TGR5 in liver tissues were significantly increased （P＜0.05）. CONCLUSIONS SLBZS may relieve colonic inflammatory injury and ameliorate UC by regulating the expression of flora metabolism-related proteins and inhibiting the abnormal activation of TLR4/NF-κB/NLRP3 inflammatory axis.

Objective:This study aimed to integrate RNA-seq data to identify key genes associated with macrophage-ferroptosis and develop a prognostic model for hepatocellular carcinoma(HCC).Methods:We retrieved a dataset from the GEO database containing transcriptome data and clinical information for 163 samples.Macrophage-related genes were identified using WGCNA and immune infiltration analyses.Ferroptosis-related genes from the FerrDbV2 database were intersected with differentially expressed genes to obtain significant macrophage-ferroptosis-related genes.Hub genes were screened via protein interaction network construction,and key genes were identified using four machine learning algorithms.These genes exhibited significant expression differences between cancer and normal tissues and were closely linked to patient prognosis.ROC curve and KM survival analyses were performed,and expression levels were validated at the transcriptome and proteome levels.Results:Four key genes RRM2,KIF20A,PCK2,and PDK4 were identified and evaluated.RRM2 and KIF20A demonstrated high importance in classification prediction models and reliable performance in ROC and KM analyses(AUC＞0.9,P＜0.05).These genes regulate cancer cell proliferation/survival and macrophage polarization/function,influencing the tumor microenvironment and HCC progression.Conclusion:RRM2 and KIF20A regulate cancer cell proliferation and survival,modulate macrophage polarization and function,and influence the immune response in the tumor microenvironment.They can serve as prognostic biomarkers and potential immunotherapy targets for hepatocellular carcinoma.

Chronic kidney disease(CKD)is a chronic disease characterized by renal structural damage and dysfunction.At present,there is still a lack of effective therapeutic drugs and prevention and treatment methods for CKD in clinical practice.More and more studies have shown that necroptosis,as a new type of programmed cell death,plays a vital role in the onset and progression of CKD.Targeting key molecules in the necroptosis pathway,such as RIPK1,RIPK3 and MLKL,the development of small molecule inhibitors has become an emerging strategy for the treatment of CKD,and has shown significant potential to pro-tect the kidneys and alleviate renal fibrosis in a variety of in vitro and in vivo models.Therefore,this article summarizes the re-search progress of the mechanism of necroptosis in recent years,and focuses on the potential role of necroptosis in the pathogene-sis of CKD and the therapeutic potential of targeting this path-way,providing a new perspective and research direction for the prevention and treatment of CKD in the future.

AIM To establish a rapid quantitative analysis model for saponins in Paris polyphylla var.yunnanensis(PPY)by near infrared spectroscopy.METHODS The contents of polyphyllins Ⅰ,Ⅱ,Ⅶ and there total content in PPY were determined by HPLC,while spectral data within the range of 10 000 to 4 000 cm-1 were collected.A quantitative analysis model was established by combining these data with partial least squares regression(PLSR).Multivariate scatter correction(MSC)and vector normalization(SNV)were applied prior to further preprocessing the spectra with original,first-order derivative(1stD),or second-order derivative(2ndD)treatments.Lastly,the model was optimized through non-smoothing(NS),Norris Derivative filtering(Nd),and Savitzky-Golay filtering(S-G)method.Model stability was evaluated based on correlation coefficients and variance.The predicted contents of each saponin component in the validation set samples were calculated.RESULTS The contents of polyphyllins Ⅰ,Ⅱ,Ⅶ were 0.42-17.98,0.46-10.44,0.23-3.86 mg/g,respectively.The total content ranged from 2.91 to 22.1 mg/g.The optimal parameters of three saponins were achieved when selecting the MSC+2ndD+S-G pretreatment method.The corresponding ratio of line segment length to segment gap was 13∶5,15∶5,11∶5,with correlation coefficients of 0.982,0.930,0.958,respectively.The root mean square errors of calibration(RMSEC)were 0.702,0.797,0.238,and the root mean square errors of prediction(RMSEP)were 1.120,0.835,0.304,respectively.The optimal parameters for the total content were obtained when selecting the MSC+2ndD+NS pretreatment method,with a correlation coefficient of 0.970,a RMSEC of 1.090,and a RMSEP of 1.740.CONCLUSION This accurate and rapid method can be used for detection of saponin contents in P.Polyphylla.

Three evaluation methods were recommended for the key properties of the intravascular catheter lubricating coating such as stability,lubricity and integrity,including insoluble particle test method,friction test procedure and appearance detection method.Fifteen batches of microcatheters produced by different manufacturers were selected for testing to clarify the three methods in test principle,step,result,characteristic.References were provided for the design,production,evaluation and regulation of intravascular catheters with lubricant coatings.[Chinese Medical Equipment Journal,2025,46(1):66-72]

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.