With the concurrent development of traditional Chinese medicine （TCM） and metabolomics in the diagnosis and treatment of liver failure， techniques such as nuclear magnetic resonance， mass spectrometry， chromatography， metabolic flux analysis， and bioinformatics enable the qualitative or quantitative analysis of endogenous small molecule metabolites in animal models of liver failure and patients with liver failure. These methods help identify specific biomarkers for early diagnosis and clinical intervention. This article reviews recent advancements in metabolomics for the early diagnosis of liver failure， biomarker discovery， identification of TCM syndromes， and the application of TCM in treating liver failure， aiming to provide a basis for TCM-based diagnosis and treatment of liver failure.

Objective To observe the effect of Baduanjin exercise on depression,sleep quality and life quality of patients with breast cancer in the rehabilitation period.Methods A total of 76 breast can-cer patients in postoperative rehabilitation were randomly divided into an intervention group of 38 with 2 dropping out,and a control group of 38 with 3 dropouts.Both groups received routine nursing and rehabilitation after breast cancer surgery,while the intervention group additionally practised Baduanjin for 6 weeks.The Beck Depression Inventory-Ⅱ(BDI-Ⅱ-C),Pittsburgh Sleep Quality Index(PSQI)and Quality of Life Questionnaire Core 30(EORTC QLQ-C30)were used to evaluate both groups be-fore,as well as 3 and 6 weeks after intervention.Results After 3-week intervention,the average BDI-Ⅱ-C score,the total PSQI score and the scores of all dimensions except for the hypnotic drug dimen-sion of the intervention group was significantly lower than before treatment(P<0.05),and the control group at the same time point(P<0.05),while the scores of physical,emotional,cognitive,social and role function in EORTC QLQ-C30 were significantly higher than the latter(P<0.05).Three weeks lat-er,the average BDI-Ⅱ-C score,the total PSQI score and the scores of all dimensions except for the hypnotic drug dimension of the intervention group was significantly lower than before treatment(P<0.05),and the control group at the same time point(P<0.05),while the various scores of EORTC QLQ-C30 were significantly higher than the latter(P<0.05).Compared with after 3-week intervention,after 6-week intervention,the average BDI-Ⅱ-C score,the total PSQI score and the scores of its all dimensions except for the sleep disorder dimension of the intervention group decreased significantly,while all dimension scores of EORTC QLQ-C30 except the cognitive function dimension increased sig-nificantly(P<0.05 for all).Conclusion Baduanjin is feasible in improving the sleep and life quality of patients in the rehabilitation period after breast cancer surgery,and relieving their depression.

Objective:To investigate the mechanism of polygonatum and astragalus compound(PA)in inhibiting the progression of lung adenocarcinoma. Methods:CCK-8 assay was used to assess the inhibitory rate of proliferation in A549 and H1299 cells treated with PA at different concentrations and to calculate the half maximal inhibitory concentration(IC50).C57BL/6 mice(KRASG12D/+;TP53flox/flox)were treated with adenovirus carrying Cre enzyme via nasal inhalation to establish a mouse model of primary lung adenocarcinoma.The model mice were fed with PA-containing diet to directly observe the effect of PA on the lung adenocarcinoma tissue.Immunohistochemical staining was used to examine the pathological status of the lung tissue.Bioinformatics analysis indicated that PA affects the progression of lung adenocarcinoma through the apelin-peroxisome proliferator-activated receptor gamma coactivator 1-alpha(PGC1α)-mitochondrial brown fat uncoupling protein 1(UCP1).Real-time quantitative PCR and Western blotting analysis were used to study the effect of PA on the mRNA and protein expression levels of apelin-PGC1α-UCP1 signaling pathway related genes.An ATP detection kit and flow cytometry were used to evaluate the effect of PA on the ATP and mitochondrial ROS production,respectively,in A549 and H1299 cells.siUCP1 was used to silent the expression of UCP1 while Z160 was used to induce UCP1 overexpression in A549 and H1299 cells,and the changes in ATP and mitochondrial ROS production were examined to further investigate whether PA acts on apelin-PGC1α-UCP1 signaling pathway to affect the progression of lung adenocarcinoma. Results:PA could obviously inhibit the proliferation of A549 and H1299 cells with the IC50 values of 10.66 mg/mL for A549 cells and 9.66 mg/mL for H1299 cells.In the mouse primary lung adenocarcinoma model,PA could effectively inhibit the growth of tumor,downregulate apelin-PGC1α-UCP1 signaling pathway and inhibit the expression of lung adenocarcinoma-promoting gene UCP1.In A549 and H1299 cells,PA could significantly inhibit the expression of apelin,PGC1α and UCP1(P＜0.05),promote the production of ATP(P＜0.000 1)and ROS,restore mitochondrial oxidative phosphorylation,and inhibit aerobic glycolysis(P＜0.01).UCP1 silencing could increase the production of ATP(P＜0.01)and mitochondrial ROS and decrease the expression of key glycolysis enzymes hexokinase 2(HK2)and pyruvate kinase isozyme type M2(PKM2)(P＜0.05).Increasing the expression of UCP1 could reduce the ATP production(P＜0.01)and mitochondrial ROS generation in cells while increase the expression of HK2 and PKM2(P＜0.05).Treating cells with PA and Z160 simultaneously(PA+Z160)could reverse the inhibitory effect of PA on the ATP production and glycolysis of tumor cells(P＜0.05). Conclusion:PA can downregulate the apelin-PGC1α-UCP1 signaling pathway,inhibit mitochondrial uncoupling,restore mitochondrial oxidative phosphorylation,inhibit aerobic glycolysis,reverse the Warburg effect,and thus inhibit lung adenocarcinoma progression.

Objective:To understand the current status of gastroscopy in diagnosing gastric lesions in general population, and to recommend the optimal age for the first gastroscopy and intervals for repeated gastroscopy.Methods:The gastroscopy records of residents aged 18-80 years in Yinzhou District of Ningbo, Zhejiang Province, between April 2010 and December 2021 were analyzed retrospectively. The detections of gastric lesions across different years, age and genders were described. Goodness of fit tests were applied to compare the differences in detection rates of different lesions in first-time endoscopy in different age groups and different populations. Generalized additive models were used to fit the trend of age specific gastric lesion detection rate explore the optimal age for gastroscopy. The appropriate gastroscopy intervals were determined according to the progress of the gastric lesions detected in repeated gastroscopy.Results:A total of 237 751 participants with 344 398 gastroscopy records were included in analyses. A total of 5 597 cases of chronic atrophic gastritis (CAG), 9 796 cases of intestinal metaplasia (IM), 165 cases of low-grade intraepithelial neoplasia (LGIN), 52 cases of high-grade intraepithelial neoplasia (HGIN) and 435 cases of gastric cancer were detected by the first gastroscopy. The overall detection rate of gastric lesions increased significantly in age group 45-70 years, and remained stable after 70 years old, with LGIN and HGIN showing notable increases at 50 and 55 years old, respectively. Repeated gastroscopy detected CAG, IM, LGIN, and HGIN at a higher rate compared with the first gastroscopy. Normal/superficial gastritis progressed in 3-5 years, whereas CAG or more severe lesions progressed in 1-6 years.Conclusion:Gastroscopy is recommended for general population aged 45 years and above. Furthermore, gastroscopy can be performed every 3-5 years for individuals with normal endoscopy results and once a year for patients with CAG or more severe gastric lesions.

OBJECTIVE: To investigate the effect of circulating exosomes (EXO) on T cell function in patients with sepsis. METHODS: Plasma EXO were obtained by ultracentrifugation from 10 patients with sepsis admitted to the emergency intensive care unit of Guangdong Provincial People's Hospital Affiliated to Southern Medical University. Transmission electron microscopy observation, nanoparticle tracking analysis (NTA), and Western blotting were used to detect EXO markers to identify their characteristics. Furthermore, peripheral blood mononuclear cells (PBMC) were isolated from the peripheral blood of 5 healthy volunteers, primary T cells were sorted by magnetic beads and expanded in vitro. After 24 hours of intervention with different doses (0, 1, 2.5, 5, 10 mg/L) of circulating EXO in patients with sepsis, T-cell activity was assessed using a cell counting kit-8 (CCK-8). The expression of T cell activation indicators CD69 and CD25 were observed using flow cytometry. Additional evaluations were performed on immunosuppressive indicators including the expression of programmed cell death 1 (PD-1) in CD4⁺ T cells and the proportion of regulatory T cell (Treg). RESULTS: The identification results confirmed that the successful isolation of EXO from the plasma of sepsis patients. The expression level of circulating EXO in sepsis patients was higher than that in healthy control group (mg/L: 48.78±5.14 vs. 22.18±2.25, P < 0.01). After 24 hours of intervention with 5 mg/L of plasma EXO from sepsis patients, T cells activity began to show suppression [(85.84±0.56)% vs. (100.00±0.00)%, P < 0.05]. As the dosage increased, after 24 hours of intervention with 10 mg/L of EXO, T cells activity was significantly suppressed [(72.44±2.36)% vs. (100.00±0.00)%, P < 0.01]. Compared with the healthy control group, after T cells intervention with plasma EXO from sepsis patients, the expression of early activation marker CD69 was significantly reduced [(52.87±1.29)% vs. (67.13±3.56)%, P < 0.05]. Meanwhile, there was an upregulation of PD-1 expression in T cells [(57.73±3.06)% vs. (32.07±0.22)%, P < 0.01] and an increase in the proportion of Treg [(54.67±1.19)% vs. (24.60±3.51)%, P < 0.01]. However, the expression of the late activation marker CD25 remained stable [(84.77±3.44)% vs. (85.93±2.32)%, P > 0.05]. CONCLUSIONS Circulating EXO in sepsis patients induce T cell dysfunction, which may be a novel mechanism lead to immunosuppression in sepsis.
Humans ; Leukocytes, Mononuclear ; Exosomes/metabolism* ; Programmed Cell Death 1 Receptor/metabolism* ; T-Lymphocytes, Regulatory/metabolism* ; Sepsis/metabolism*

Objective To use feature selection and Likert grading method to quantify the data of lung cancer medical records,to construct a deep extreme learning machine model optimized by the sparrow search algorithm,to classify and predict the syndrome types of traditional Chinese medicine medical record data of lung cancer,and to provide scientific and effective research on syndrome type classification of traditional Chinese medicine.means.Methods The medical records of 497 cases diagnosed with lung cancer from January 2015 to December 2021 were collected from the Affiliated Hospital of Jiangxi University of Traditional Chinese Medicine,and 412 medical records were screened as the research objects.Syndromic factors of different syndromes were summarized by feature selection and feature importance ranking,and the syndrome factors were quantified by Likert grading method.Build a deep extreme learning machine optimized based on the sparrow search algorithm,and train and test the model.Finally,the model built in this paper is compared with other machine learning models according to three evaluation criteria.Results The average classification accuracy of the SSA-DELM model established in this paper was 88.44%,while the average accuracy of the support vector machine and Bayesian network was 83.39%and 84.53%,respectively.The recall rate and F1 value of the SSA-DELM model on the five syndrome types are mostly above 80%,which is also better than other traditional machine learning models.Conclusion The results of the study show that the use of feature selection combined with Likert grading method to quantify the lung cancer medical record data,compared with the 0-1 processing data,can show the characteristics of the data,improve the accuracy of the classification model,SSA-DELM new Compared with other traditional machine learning classification models,the model has better representation learning ability and learning speed.This model not only provides a scientific and technical means for the clinical treatment of lung cancer,but also provides a useful reference for the informatization and intelligent development of TCM syndrome differentiation and treatment.

Immune Checkpoint Inhibitors ; Transcriptome ; Immunotherapy ; Biomarkers, Tumor

Steroid saponins are secondary metabolites with multiple medicinal values that are found in large quantities in natural medicines, especially Vernonia amygdalina, a famous nature medicine for the treatment of tonsillitis, diabetes, pneumonia. The current study was designed to combine molecular networking (MN) with diagnostic ions for rapid identification of Δ^7,9(11) stigmastane-type saponins which were the α-glucosidase inhibitory active substances in V. amygdalina. First, the α-glucosidase inhibitory activities of five Δ^7,9(11) stigmastane-type steroid saponins that were previously isolated were screened, which indicated that the Δ^7,9(11) stigmastane-type steroid saponin was one of the active constituents responsible for ameliorating diabetes. Furthermore, a strategy was proposed to identify stigmastane-type steroid saponins and verify the plausibility of derived fragmentation pathways by applying MN, MolNetEnhancer and unsupervised substructure annotation (MS2LDA). Based on this strategy, other seven Δ^7,9(11) stigmastane-type steroid saponins were identified from this plant. Our research provide scientific evidence for the antidiabetic potential of the steroid saponin-rich extract of V. amygdalina leaf.
alpha-Glucosidases/metabolism* ; Vernonia/chemistry* ; Plant Extracts/chemistry* ; Plant Leaves/chemistry* ; Saponins/chemistry* ; Steroids/chemistry* ; Diabetes Mellitus

OBJECTIVE：To comprehensi vely evaluate the application progress of network pharmacology methods in TCM compound prescription research ，and to provide reference for modernization of TCM compound prescription research. METHODS ： Taking“network pharmacology ”and“TCM compound prescription ”as keywords ，the literatures were retrieved from CNKI ， Wanfang database and VIP during May 2006 to May 2020. Screening literature ，the databases ，analysis platforms ，and software used of the literature were summarized ；on the basis of quantitative analysis ，the application of network pharmacology in the research of traditional Chinese medicine compound were summarized. RESULTS & CONCLUSIONS ：There were a total of 761 valid literatures ，among which the number of literatures that could be retrieved in 2019 reached 313. In the modernization research of TCM compound prescription ，network pharmacology methods were mainly usedmechanism ，material basis of pharmacodynamics ， compatibility law ，compound optimization ，and“effect-toxic”network. Commonly used databasesand platforms included traditional chinese medicine information database （TCMSP and TCMID ），therapeutic target database （TTD，OMIM），drug targets and target prediction platform （Drugbank，SwissTargetPrediction，TargetNet，PharmMapper），network pharmacology analysis and prediction software and platform （CytoScape），etc. Network pharmacology method was widely used in the field of TCM compound prescription research ，and provided new ideas and methods for the modernization of TCM compound prescription research. In the future，the related research can be combined with the pharmacokinetic parameters ，the efficacy of active compounds and related basic experiments ，use the weighted method to carry out network pharmacology analysis ，and integrate the information of multiple databases to improve the scientificity of research results.

Objective:To systematically review the influencing factors of nurses' clinical alarm response behavior.Methods:PubMed, Web of Science, Google Scholar, Spischolar, CNKI, Wanfang, VIP and other databases were searched from January 2004 to December 2019. Relevant studies on the influencing factors of nurses' clinical alarm response were searched, and the quality of articles meeting the inclusion criteria was evaluated, the contents were extracted and analyzed.Results:A total of 11 English articles were included, including 10 descriptive studies and 1 cohort study. Finally, 5 influencing factors ( P<0.01) related to nurses' response to clinical alarms were extracted, which were a large number of false alarms ( OR=0.84, 95% CI: 0.82-0.86) , nurses' risk assessment of patients' condition ( OR=0.77, 95% CI: 0.71-0.82) , clinical noise and multiple alarms ( OR=0.87, 95% CI: 0.85-0.89) , effective management of alarms ( OR=0.50, 95% CI: 0.43-0.58) and insufficient nursing staff ( OR=0.63, 95% CI: 0.57-0.68) . There is a lack of strong evidence on whether the nurses' work experience, clinical nurses' team cooperation degree, clinical alarm type identification, clinical alarm duration and working hours were the influencing factors of nurses' clinical alarm response. Conclusions:Nurses' clinical alarm response is affected by many factors. Targeted management should be carried out to improve response efficiency. More in-depth observational researches or intervention researches are suggested to be carried out to further improve the quality of nursing services.