ObjectiveThis paper aims to clarify the material basis of Gualou Niubangtang and establish a quantitative analysis method for its main constituents， providing a reference for the overall quality control of this preparation. MethodsThe constituents in the formula were systematically characterized based on ultra-performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry （UPLC-Q-TOF-MS/MS）. Identification was performed by matching with the UNIFI 9.6 software and utilizing database platforms such as PubChem， ChemicalBook， and ChemSpider， combined with relevant literature reports. A quantitative analysis method for the seven main constituents in Gualou Niubangtang was established by using high performance liquid chromatography （HPLC）. ResultsUPLC-Q-TOF-MS/MS analysis identified 155 constituents， including 69 flavonoids， 36 terpenoids， 23 phenylpropanoids， 8 phenylethanoid glycosides， and 19 other types of constituents. In the established quantitative analysis method， the seven main constituents showed good linearity within their respective linear ranges. The precision， repeatability， stability， and spike recovery all met the required standards. The results showed that the content ranges of geniposide， liquiritin， hesperidin， arctiin， baicalin， oroxylin A-7-O-β-D-glucuronide， and wogonoside in 15 batches of Gualou Niubangtang were 13.67-21.25， 1.20-7.64， 5.45-7.45， 22.97-33.51， 29.95-39.07， 2.58-4.80， and 6.56-9.31 mg·g^-1， respectively. ConclusionThis study successfully characterizes and attributes multi-category constituents in Gualou Niubangtang， clarifying that its material basis is primarily composed of flavonoids， terpenoids， phenylethanoid glycosides， and phenylpropanoids. Furthermore， it enables the quantification of seven constituents within the formula. This work lays a foundation for research on the quality control， action mechanism， and clinical application of this formula.

ObjectiveTo investigate the effects of metformin on the immune functions of immature dendritic cells （imDCs） and the underlying mechanisms. MethodsMouse bone marrow-derived imDCs were treated with different concentrations of metformin. The working concentration and treatment time of metformin in this study were determined based on the results of cell apoptosis and cell viability assays. The effects of metformin on the phagocytic capacity of imDCs was evaluated using an antigen endocytosis assay. The expression of cluster of differentiation 205 （CD205）， the polymerization of filamentous actin （F-actin）， and the underlying regulatory mechanisms were investigated through flow cytometry， laser confocal fluorescence microscopy， and Western blot. ResultsThe working concentrations of metformin were 1， 2， 4 mmol/L for 24 h determined by the apoptosis and cell viability assays.Metformin significantly suppressed the phagocytic capacity of imDCs， down-regulated the expression of the mannose receptor CD205 on the cell surface， which was closely associated with phagocytic function； metformin inhibited the RhoA-ROCK1-LIMK1-Cofilin signaling pathway， which inhibited the polymerization of F-actin and disturbed its dynamic remodeling of imDCs. ConclusionMetformin can inhibit the expression of CD205 and disrupt the remodeling of F-actin， thereby suppressing the antigen-capturing capacity of imDCs.

ObjectiveThis study aims to observe the clinical effect of Danggui Liuhuang Tang （DGLHT） on patients with type 2 diabetes mellitus （T2DM） complicated by atherosclerotic cardiovascular disease （ASCVD） at high risk， focus on evaluating the influence of DGLHT on cardiovascular risk indicators such as flow-mediated dilation （FMD）， atherogenic index of plasma （AIP）， and triglyceride-glucose index （TyG）， and explore the regulatory effect of DGLHT on the myeloid differentiation factor 88/nuclear factor-kappa B （MyD88/NF-κB） signaling pathway. MethodsThe clinical study was a single-center， double-blind， and randomized controlled trial. A total of 68 patients with T2DM-ASCVD at high risk for cardiovascular events with Yin deficiency and fire excess syndrome were enrolled and randomly assigned to a treatment group and a control group. The treatment group was given atorvastatin calcium tablets and DGLHT， while the control group was given atorvastatin calcium tablets and placebos. The treatment course was 12 weeks， with a final study completion of 30 patients in the treatment group and 29 in the control group. Changes in cardiovascular risk indicators such as FMD， AIP， TyG， and small dense low-density lipoprotein cholesterol （sdLDL-C） index were compared. Human umbilical vein endothelial cells （HUVECs） were used to establish a vascular endothelial injury and inflammation model. The protective effect of DGLHT on endothelial injury was verified by reverse transcription polymerase chain reaction （Real-time PCR） and Western blot . ResultsAfter 12 weeks of treatment， the AIP in the treatment group significantly decreased compared with that before the treatment （P<0.05）. Compared with the control group， the treatment group showed significant improvements in FMD and TyG （P<0.05）. Additionally， the treatment group demonstrated significant reductions in two-hour postprandial glucose （2 hPG）， glycated albumin （GA）， triglycerides （TG）， apolipoprotein E （Apo E）， and sdLDL-C （P<0.05）. Analysis of traditional Chinese medicine （TCM） syndrome efficacy indicated that in the treatment group， Yin deficiency and fire excess syndromes， including dry throat and mouth （P<0.05）， excessive thirst （P<0.01）， tidal fever and night sweats （P<0.05）， and dry stools （P<0.05）， improved. Compared with the control group， the treatment group showed significant improvements in symptoms of dry throat and mouth （P<0.05） and excessive thirst （P<0.01）. TCM syndrome scores significantly decreased （P<0.01）， and the overall efficacy rate was 56.67%， significantly higher than the 10.34% observed in the control group （P<0.01）. At the cellular level， increasing concentrations of DGLHT led to decreased messenger ribonucleic acid （mRNA） levels of pro-inflammatory cytokines interleukin-6 （IL-6）， tumor necrosis factor-alpha （TNF-α）， and interleukin-1-beta （IL-1β） in lipopolysaccharide （LPS）-stimulated HUVECs （P<0.01）， with significant reductions in the high-concentration group （P<0.01）. DGLHT may inhibit the expressions of MyD88 and phosphorylated （p）-NF-κB p65 proteins in a concentration-dependent manner. ConclusionDGLHT shows significant effects in reducing cardiovascular risks and may exert an anti-inflammatory effect by inhibiting the MyD88/NF-κB signaling pathway. This finding provides a new perspective for the prevention and treatment of cardiovascular diseases in high-risk individuals with T2DM-ASCVD.

Acute Gelsemium poisoning is a systemic disease primarily affecting the central nervous system and respiratory symptoms caused by the ingestion of a substantial amount of Gelsemium within a short period. It manifests as sudden onset and rapid progression, primarily caused by accidental ingestion due to misidentification, and posing significant health risks. The compilation of the Technical Plan for Emergency Health Response to Acute Gelsemium Poisoning describes in detail the specialized practice and technical requirements in the process of handling acute Gelsemium poisoning, including accident investigation and management, laboratory testing and identification, in-hospital treatment, and health monitoring. The guidelines clarify key procedures and requirements such as personal protection, investigation elements, etiology determination, medical rescue, and health education. The key to acute Gelsemium poisoning investigation lies in promptly identifying the toxin through exposure history, clinical manifestations, and sample testing. Because there is no specific antidote for Gelsemium poisoning, immediate removal from exposure, rapid elimination of the toxin, and respiratory monitoring are critical on-site rescue measures. Visual identification of food or herbal materials, followed by laboratory testing to determine Gelsemium alkaloids in samples is a rapid effective screening method. These guidelines offer a scientific, objective, and practical framework to support effective emergency responses to acute Gelsemium poisoning incidences.

ObjectiveThe nucleolar protein PES1 (Pescadillo homolog 1) plays critical roles in ribosome biogenesis and cell cycle regulation, yet its involvement in cellular senescence remains poorly understood. This study aimed to comprehensively investigate the functional consequences of PES1 suppression in cellular senescence and elucidate the molecular mechanisms underlying its regulatory role. MethodsInitially, we assessed PES1 expression patterns in two distinct senescence models: replicative senescent mouse embryonic fibroblasts (MEFs) and doxorubicin-induced senescent human hepatocellular carcinoma HepG2 cells. Subsequently, PES1 expression was specifically downregulated using siRNA-mediated knockdown in these cell lines as well as additional relevant cell types. Cellular proliferation and senescence were assessed by EdU incorporation and SA-β-gal staining assays, respectively. The expression of senescence-associated proteins (p53, p21, and Rb) and SASP factors (IL-6, IL-1β, and IL-8) were analyzed by Western blot or qPCR. Furthermore, Northern blot and immunofluorescence were employed to evaluate pre-rRNA processing and nucleolar morphology. ResultsPES1 expression was significantly downregulated in senescent MEFs and HepG2 cells. PES1 knockdown resulted in decreased EdU-positive cells and increased SA‑β‑gal-positive cells, indicating proliferation inhibition and senescence induction. Mechanistically, PES1 suppression activated the p53-p21 pathway without affecting Rb expression, while upregulating IL-6, IL-1β, and IL-8 production. Notably, PES1 depletion impaired pre-rRNA maturation and induced nucleolar stress, as evidenced by aberrant nucleolar morphology. ConclusionOur findings demonstrate that PES1 deficiency triggers nucleolar stress and promotes p53-dependent (but Rb-independent) cellular senescence, highlighting its crucial role in maintaining nucleolar homeostasis and regulating senescence-associated pathways.

Objective Logistic regression model was used to analyze the risk factors of liver cancer in patients with hepatitis B virus-related cirrhosis. Methods A retrospective analysis was performed on 504 patients with hepatitis B cirrhosis who were treated in a hospital from April 2021 to April 2024. The occurrence of liver cancer was counted. The risk factors of liver cancer in patients with HBV-related cirrhosis were analyzed by logistic regression analysis. Results Among the 504 patients with hepatitis B cirrhosis, 101 patients developed liver cancer and 403 patients did not develop liver cancer, which were included in the liver cancer group (n=101) and the non-liver cancer group (n=403).. Among hepatitis B cirrhosis, the incidence rate of liver cancer was 20.04%. Compared with the non-liver cancer group, the proportion of patients with long-term drinking history, family history of liver cancer, history of diabetes mellitus, antiviral therapy, and HBV-DNA load>104 were higher in the liver cancer group (P<0.05). logistic regression analysis found that long-term drinking history (OR=3.077, 95%CI: 1.130-8.378, P=0.028), history of diabetes mellitus (OR=3.747, 95%CI: 1.765-7.954, P=0.001), no antiviral therapy (OR=3.466, 95%CI: 1.337-8.985, P=0.011) and HBV-DNA load>104 (OR=3.149, 95%CI: 1.353-7.328, P=0.008) could independently affect the occurrence of liver cancer in patients with hepatitis B cirrhosis. Conclusion According to logistic regression analysis, long-term drinking history, history of diabetes mellitus, no antiviral therapy, and HBV-DNA load>104 are risk factors for liver cancer in patients with HBV-related cirrhosis.

Objective To construct large medical model named by "Huaxi HongYi"and explore its application effectiveness in assisting medical record generation. Methods By the way of a full-chain medical large model construction paradigm of "data annotation - model training - scenario incubation", through strategies such as multimodal data fusion, domain adaptation training, and localization of hardware adaptation, "Huaxi HongYi" with 72 billion parameters was constructed. Combined with technologies such as speech recognition, knowledge graphs, and reinforcement learning, an application system for assisting in the generation of medical records was developed. Results Taking the assisted generation of discharge records as an example, in the pilot department, after using the application system, the average completion times of writing a medical records shortened (21 min vs. 5 min) with efficiency increased by 3.2 time, the accuracy rate of the model output reached 92.4%. Conclusion It is feasible for medical institutions to build independently controllable medical large models and incubate various applications based on these models, providing a reference pathway for artificial intelligence development in similar institutions.

The Compilation Instructions for Expert Consensus on Clinical Application of Dieda Huoxue capsules systematically expound the development methods and evidence-based basis of this consensus. In view of the weak clinical application evidence and ambiguous indications of Dieda Huoxue capsules， the Institute of Basic Research in Clinical Medicine of the China Academy of Chinese Medical Sciences and Wangjing Hospital took the lead and collaborated with 33 experts from 28 medical institutions nationwide. They strictly followed the World Health Organization （WHO） guideline-making norms and the Grading of Recommendations Assessment， Development and Evaluations （GRADE） evidence-grading system and completed the compilation through multidisciplinary cooperation. The workflow included constructing clinical questions （19 items were screened by the nominal group technique）， retrieving evidence （from Chinese and English databases and grey literature）， assessing safety （integrating drug monitoring data and clinical investigations）， and forming recommendations and consensus suggestions （3 recommendations were reached via the GRADE grid method， and 16 consensus suggestions were reached by the majority vote rule）. The results indicate that the consensus clearly states that this medicine （Dieda Huoxue capsules） is applicable to conditions like traumatic injury， blood stasis-induced pain， and sudden lumbar sprains. The recommended dose is 6 capsules each time， twice a day. Combining oral administration with external application can enhance the efficacy， and elderly patients should take the medicine at intervals. Safety monitoring suggests that it should be used with caution in people with a bleeding tendency and those with an allergic constitution. The compilation process involved three rounds of reviews by internal and external experts. Literature analysis， the Delphi method， and clinical applicability tests were employed to ensure methodological rigor. The compilation instructions comprehensively present key aspects such as project approval and registration， conflict-of-interest statements， and evidence evaluation through 12 appendices， providing methodological support for the clinical translation of the consensus. In the future， it will be continuously improved through a dynamic revision mechanism.

AIM To study the chemical constituents from Asteris Radix et Rhizoma and their anti-inflammatory activities.METHODS The extract from Asteris Radix et Rhizoma was isolated and purified by column chromatography and high performance liquid chromatography,then the structures of obtained compounds were identified by physicochemical properties and spectral data.Their anti-inflammatory activities were evaluated by RAW264.7 model.RESULTS Thirteen compounds were isolated and identified as(Z)-9,10,11-trihydroxy-12-octadecenoic acid(1),tianshic acid(2),6,6-dimethyl-2-methlenebicyclo[3.1.1]hept-3-O-(6-O-apiofuranosyl)-β-D-glucopyranoside(3),ent-16β,17-dihydroxy-kauran-19-oic acid(4),ent-17-hydroxy-19-kauranoic acid(5),7β,17-dihydroxy-16α-ent-kauran-19-oic acid 19-O-β-D-glucopyranoside ester(6),paniculoside Ⅳ(7),thomimarine A(8),cyclo-(S-Pro-R-Leu)(9),4,5-di-O-caffeoylquinic acid 1-methyl ether(10),methyl 3,5-di-O-caffeoyl quinate(11),5-acetyl-3β-hydroxy-2β-(1-hydroxyisopropyl)-2,3-dihydrobenzofurane(12),4-ally-2,6-dimethoxyphenyl glucoside(13).Compounds 1 and 3-12 had inhibition on the release of NO in RAW264.7 cells,and 4-6,8,10-12 were better than the positive control.CONCLUSION Compounds 1,6,8-9 are isolated from Compositae family for the first time,and 2-5,7,10 and 11-13 are first isolated from this plant.Compounds 1,3-12 have anti-inflammatory activities.

OBJECTIVE To explore the application of autoregressive integrated moving average model(ARIMA)in prediction of prevalence trends of carbapenem-resistant Klebsiella pneumoniae(CRKP)in intensive care unit(ICU)so as to provide scientific bases for formulating prevention strategies for CRKP infection in ICU.METHODS The number of CRKP strains that were monthly isolated from the ICU patients of Jiangnan University Affiliated Hospital between Jan.2021 and Jan.2024 was collected,the duplicate samples from the same patient were excluded,and totally 555 strains of CRKP were finally enrolled in the study.The time series differencing was performed by using R statistical software,the ARIMA model was established,the parameters of the model were determined by means of autocorrelation function(ACF)and partial autocorrelation function(PACF)images.The optimal model was screened out by Akaike information criterion(AIC)and root-mean-square error(RMSD),the robustness of the residual sequences was assessed by Box-Ljung test.The data that were detected from Sep.2023 to Jan.2024 were assigned as the validation set,the prediction accuracy of the model was assessed,and the dy-namic trend of the CRKP strains from Feb.2024 to Apr.2024 was predicted.RESULTS The isolation rate of CRKP strains in ICU showed dynamic change from 2021 to 2023(x2=66.906,P=0.001),sputum and midstream urine were the major sources.The minimal AIC of the optimal ARIMA model(8,1,10)was 222.1,with RMSE 3.67.Box-Ljung(x2=0.104,P=0.746)test indicated that there was no autocorrelation among the residual se-quences.Both the actual CRKP and the predictive value firstly rose then descended from Sep.2023 to Jan.2024,and the average relative error of the model was 9.62％for prediction.The number of isolated CRKP strains predic-ted by the model might reached to the lowest point in Feb.2024 and then showed an upward trend,and it might reach to a high peak in Apr.CONCLUSION ARIMA model is effective for short-term prediction and dynamic anal-ysis of prevalence trend of CRKP strains in the ICU so as to provide theoretical basis for early warning of hospital-associated infection and take corresponding prevention measures.