OBJECTIVE To establish a whole-process quality management index system for traditional Chinese medicine （TCM） reserved in the department of medical institutions， providing a reference for standardized management. METHODS An initial indicator framework was determined by collecting and analyzing relevant laws， regulations， policy documents， group standards， and literature on TCM management. Two rounds of Delphi expert consultation involving 20 experts were conducted to refine and optimize the indicator system. The analytic hierarchy process was used to construct judgment matrices and convert the indicator weights into a percentage-based system； an assessment was conducted on 14 departments with reserved TCM among the affiliated units of the Quality Management and Control Center for Traditional Chinese Medicine in Hebei Province. RESULTS The response rate for both rounds of consultation was 100%， with an expert authority coefficient of 0.89. The final quality management system of TCM reserved in the department included four first-level indicators： management （composite weight： 0.366 3）， processing （composite weight： 0.119 7）， storage （composite weight： 0.291 7） and usage （composite weight： 0.222 3）， and twenty-four second-level indicators， such as establishing an organizational structure for hospital drug quality management and having dedicated regulations for backup drugs in clinical departments. Kendall’s coefficient of concordance confirmed consistency across all levels of indicators. Based on the application of the indicator system for evaluation， the average score for the standardized management of reserved TCM in the department of medical institutions increased from 67.01 points to 85.15 points over three months. CONCLUSIONS The constructed indicator system meets the standardized management requirements for reserved TCM， enabling closed-loop management across the entire process of management， processing， storage and usage. It provides a reference for medical institutions to enhance the precision and standardization of reserved TCM management.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

ObjectiveTo investigate the effects of rhizosphere organic acids secreted by the roots of Salvia miltiorrhiza on continuous cropping obstacles. MethodsThe mixed solution of organic acids in the rhizosphere of S. miltiorrhiza in continuous cropping and rotation cropping was added to the hairy roots subcultured for 21 days， and samples were collected on days 0， 2， 4， 6， 8， and 10. The changes of biomass， effective components， primary metabolites， secondary metabolites， antioxidant enzymes， and hormones in hairy roots of S. miltiorrhiza were observed and determined. ResultsCompared with the rotation cropping group and the blank control group， the simulation of organic acid secretion from the roots of S. miltiorrhiza had a significant inhibitory effect on the growth of hairy roots and decreased the content of effective components as well as total sugar and total protein in primary metabolites. Compared with the blank control group， the rotation cropping group and the continuous cropping group showed total sugar and total protein content decreases of 33.9% and 5.1%， respectively. On the other hand， the secretion of organic acids from S. miltiorrhiza roots significantly promoted the accumulation of total phenolic acids and total tanshinone， which showed increases of 14.6% and 1.6%， respectively， in continuous cropping group and rotation cropping group compared with the blank control group. ConclusionThe organic acid environment under continuous cropping significantly inhibited the growth of hairy roots and the accumulation of primary metabolites， while promoting the synthesis and accumulation of secondary metabolites of S. miltiorrhiza.

ObjectiveTo explore the molecular mechanism of the chemo-resistance in NR2F1-mediated dormant ovarian cancer（OC） cells. MethodsThe expression of the NR2F1 molecule in OC patients and its relationship with the overall survival of patients were analyzed using the GEPIA database. Nuclear receptor subfamily 2 group F member 1（NR2F1） overexpressed OC cell and control cell were constructed by lentivirus in vitro transfection. The proliferation of OC cells was analyzed by CCK-8 method. Real-time fluorescent quantitative PCR（qRT-PCR） was used to analyze the mRNA expression of dormancy-related molecular genes in OC cells. Western blot was performed to analyze the protein expression levels of related molecules. The viability of OC cells treated with different chemotherapy drugs was analyzed by trypan blue exclusion method. Annexin V-FITC/PI double-staining assay was used to detect the apoptosis of OC cells treated by different chemotherapy drugs. Transcriptome sequencing technology was used to analyze the differentially expressed genes in NR2F1 overexpressed SKOV3 cell line， and the relevant signaling pathways were screened through KEGG enrichment analysis. qRT-PCR was performed to verified the mRNA expression level of drug resistance-related molecules in OC cells. The GEPIA database was used to further verify the correlation between the expression of NR2F1 and the drug resistance-related genes. ResultsThe NR2F1 expression is low in the tumor tissues and the high expression of NR2F1 correlates with poor overall survival in the OC patients. Compared with the control group， the proliferation ability of the NR2F1 overexpressed OC cell lines was significantly reduced. The expression of dormancy-related molecules， cyclin-dependent kinase inhibitor 1B（p27）， differentiated embryonic cartilage gene-2（DEC2） and transforming growth factor-β2（TGF-β2）， increased significantly in the NR2F1 overexpressed OC cell lines， and anti-apoptotic molecule B-cell lymphoma gene-2（BCL-2） also increased. In contrast， the expression of the proliferation-related molecule KI67 was decreased. In addition， the NR2F1 overexpressed OC cell lines significantly enhanced the resistance to chemotherapy drugs. Transcriptome sequencing and KEGG enrichment analysis showed that the upregulated genes in NR2F1 overexpressed OC cells were enriched in phosphatidylinositol-3-kinase-protein kinase（PI3K-Akt） signaling pathway， focal adhesion pathway， extracellular matrix-receptor interactions and signaling pathways regulating pluripotency of stem cells， and the downregulated genes in NR2F1 overexpressed OC cells were mainly enriched in cell cycle pathway. The results of qRT-PCR verification showed that drug resistance-related molecules kinesin family member 26B（KIF26B）， secreted protein acidic and rich in cysteine（SPARC）， collagen type Ⅵ alpha 1（COL6A1）， collagen type Ⅴ alpha 2 chain（COL5A2）， frizzled homolog 1（FZD1） and inhibin subunit beta A gene（INHBA） were up-regulated in NR2F1 overexpressed OC cells. GEPIA database analysis showed that the expression of NR2F1 in OC tumor tissues was positively correlated with the expression of drug resistance-related genes KIF26B， SPARC， COL6A1， COL5A2， FZD1 and INHBA. ConclusionsThis study shows that upregulation of NR2F1 may induce dormancy in OC cells and enhance their resistance to chemo-drugs. The NR2F1-mediated drug resistance of dormant OC cells might be associated with the PI3K-Akt signaling pathway and signaling pathways regulating pluripotency of stem cells， and closely related to the upregulation of KIF26B， SPARC， COL6A1， COL5A2， FZD1 and INHBA.

In a healthy human, the airway mucus forms a thin, protective liquid layer covering the surface of the respiratory tract. It comprises a complex blend of mucin, multiple antibacterial proteins, metabolic substances, water, and electrolytes. This mucus plays a pivotal role in the lungs' innate immune system by maintaining airway hydration and capturing airborne particles and pathogens. However, heightened mucus secretion in the airway can compromise ciliary clearance, obstruct the respiratory tract, and increase the risk of pathogen colonization and recurrent infections. Consequently, a thorough exploration of the mechanisms driving excessive airway mucus secretion is crucial for establishing a theoretical foundation for the eventual development of targeted drugs designed to reduce mucus production. Across a range of lung diseases, excessive airway mucus secretion manifests with unique characteristics and regulatory mechanisms, all intricately linked to mucin. This article provides a comprehensive overview of the characteristics and regulatory mechanisms associated with excessive airway mucus secretion in several prevalent lung diseases.
Humans ; Mucus/metabolism* ; Mucins/physiology* ; Lung Diseases/metabolism* ; Respiratory Mucosa/metabolism* ; Pulmonary Disease, Chronic Obstructive/physiopathology* ; Asthma/physiopathology* ; Cystic Fibrosis/physiopathology* ; Mucociliary Clearance/physiology*

This study aims to explore the synergistic effects of the main components in salvianolic acids for Injection(SAFI) on key pathological events in cerebral ischemia, elucidating the pharmacological characteristics of SAFI in neuroprotection. Two major pathological gene modules related to endothelial injury and neuroinflammation in cerebral ischemia were mined from single-cell data. According to the topological distance calculated in network medicine, potential synergistic component combinations of SAFI were screened out. The results showed that the combination of caffeic acid and salvianolic acid B scored the highest in addressing both endothelial injury and neuroinflammation, demonstrating potential synergistic effects. The cell experiments confirmed that the combination of these two components at a ratio of 1∶1 significantly protected brain microvascular endothelial cells(bEnd.3) from oxygen-glucose deprivation/reoxygenation(OGD/R)-induced reperfusion injury and effectively suppressed lipopolysaccharide(LPS)-induced neuroinflammatory responses in microglial cells(BV-2). This study provides a new method for uncovering synergistic effects among active components in traditional Chinese medicine(TCM) and offers novel insights into the multi-component, multi-target acting mechanisms of TCM.
Brain Ischemia/metabolism* ; Neuroprotective Agents/pharmacology* ; Animals ; Drugs, Chinese Herbal/administration & dosage* ; Benzofurans/pharmacology* ; Mice ; Drug Synergism ; Caffeic Acids/pharmacology* ; Polyphenols/pharmacology* ; Humans ; Alkenes/pharmacology* ; Endothelial Cells/drug effects* ; Depsides

This study aims to reveal the effect and mechanism of Gentianella turkestanorum total extract(GTI) in ameliorating non-alcoholic steatohepatitis(NASH). UPLC-Q-TOF-MS was employed to identify the chemical components in GTI. SwissTarget-Prediction, GeneCards, OMIM, and TTD were utilized to screen the targets of GTI components and NASH. The common targets shared by GTI components and NASH were filtered through the STRING database and Cytoscape 3.9.0 to identify core targets, followed by GO and KEGG enrichment analysis. AutoDock was used for molecular docking of key components with core targets. A mouse model of NASH was established with a methionine-choline-deficient high-fat diet. A 4-week drug intervention was conducted, during which mouse weight was monitored, and the liver-to-brain ratio was measured at the end. Hematoxylin-eosin staining, Sirius red staining, and oil red O staining were employed to observe the pathological changes in the liver tissue. The levels of various biomarkers, including aspartate aminotransferase(AST), alanine aminotransferase(ALT), hydroxyproline(HYP), total cholesterol(TC), triglycerides(TG), low-density lipoprotein cholesterol(LDL-C), high-density lipoprotein cholesterol(HDL-C), malondialdehyde(MDA), superoxide dismutase(SOD), and glutathione(GSH), in the serum and liver tissue were determined. RT-qPCR was conducted to measure the mRNA levels of interleukin 1β(IL-1β), interleukin 6(IL-6), tumor necrosis factor α(TNF-α), collagen type I α1 chain(COL1A1), and α-smooth muscle actin(α-SMA). Western blotting was conducted to determine the protein levels of IL-1β, IL-6, TNF-α, and potential drug targets identified through network pharmacology. UPLC-Q-TOF/MS identified 581 chemical components of GTI, and 534 targets of GTI and 1 157 targets of NASH were screened out. The topological analysis of the common targets shared by GTI and NASH identified core targets such as IL-1β, IL-6, protein kinase B(AKT), TNF, and peroxisome proliferator activated receptor gamma(PPARG). GO and KEGG analyses indicated that the ameliorating effect of GTI on NASH was related to inflammatory responses and the phosphoinositide 3-kinase(PI3K)/AKT pathway. The staining results demonstrated that GTI ameliorated hepatocyte vacuolation, swelling, ballooning, and lipid accumulation in NASH mice. Compared with the model group, high doses of GTI reduced the AST, ALT, HYP, TC, and TG levels(P<0.01) while increasing the HDL-C, SOD, and GSH levels(P<0.01). RT-qPCR results showed that GTI down-regulated the mRNA levels of IL-1β, IL-6, TNF-α, COL1A1, and α-SMA(P<0.01). Western blot results indicated that GTI down-regulated the protein levels of IL-1β, IL-6, TNF-α, phosphorylated PI3K(p-PI3K), phosphorylated AKT(p-AKT), phosphorylated inhibitor of nuclear factor kappa B alpha(p-IκBα), and nuclear factor kappa B(NF-κB)(P<0.01). In summary, GTI ameliorates inflammation, dyslipidemia, and oxidative stress associated with NASH by regulating the PI3K/AKT/NF-κB signaling pathway.
Animals ; Non-alcoholic Fatty Liver Disease/genetics* ; Mice ; Network Pharmacology ; Male ; Drugs, Chinese Herbal/administration & dosage* ; Chromatography, High Pressure Liquid ; Liver/metabolism* ; Mice, Inbred C57BL ; Humans ; Mass Spectrometry ; Tumor Necrosis Factor-alpha/metabolism* ; Disease Models, Animal ; Molecular Docking Simulation

This study aims to explore the mechanism of Jiaotai Pills in treating depression based on metabolomics and network pharmacology. The chemical constituents of Jiaotai Pills were identified by UHPLC-Orbitrap Exploris 480, and the targets of Jiaotai Pills and depression were retrieved from online databases. STRING and Cytoscape 3.7.2 were used to construct the protein-protein interaction network of core targets of Jiaotai Pills in treating depression and the "compound-target-pathway" network. DAVID was used for Gene Ontology(GO) function and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analyses of the core targets. The mouse model of depression was established with chronic unpredictable mild stress(CUMS) and treated with different doses of Jiaotai Pills. The behavioral changes and pathological changes in the hippocampus were observed. UHPLC-Orbitrap Exploris 120 was used for metabolic profiling of the serum, from which the differential metabolites and related metabolic pathways were screened. A "metabolite-reaction-enzyme-gene" network was constructed for the integrated analysis of metabolomics and network pharmacology. A total of 34 chemical components of Jiaotai Pills were identified, and 143 core targets of Jiaotai Pills in treating depression were predicted, which were mainly involved in the arginine and proline, sphingolipid, and neurotrophin metabolism signaling pathways. The results of animal experiments showed that Jiaotai Pills alleviated the depression behaviors and pathological changes in the hippocampus of the mouse model of CUMS-induced depression. In addition, Jiaotai Pills reversed the levels of 32 metabolites involved in various pathways such as arginine and proline metabolism, sphingolipid metabolism, and porphyrin metabolism in the serum of model mice. The integrated analysis showed that arginine and proline metabolism, cysteine and methionine metabolism, and porphyrin metabolism might be the key pathways in the treatment of depression with Jiaotai Pills. In conclusion, metabolomics combined with network pharmacology clarifies the antidepressant mechanism of Jiaotai Pills, which may provide a basis for the clinical application of Jiaotai Pills in treating depression.
Animals ; Drugs, Chinese Herbal/chemistry* ; Depression/genetics* ; Mice ; Network Pharmacology ; Metabolomics ; Male ; Disease Models, Animal ; Humans ; Protein Interaction Maps/drug effects* ; Antidepressive Agents