Objective To establish a highly efficient and sensitive technical system for the identification and analysis of platycodin-type saponins, systematically compare the differences in platycodin-type saponins among Platycodon grandiflorum from different producing areas, and provide scientific references for the screening of high-quality Platycodon grandiflorum resources, authenticity evaluation, and construction of standardized quality control systems. Methods A total of 45 batches of P. grandiflorum medicinal materials from 3 producing areas （Anhui, Henan, and Jilin, with 15 batches per area） were selected as research objects. Qualitative identification and semi-quantitative analysis of saponin components were performed based on ultra-high performance liquid chromatography-quadrupole-time-of-flight tandem mass spectrometry （UHPLC-Q-TOF/MS） technology. Meanwhile, two multivariate statistical methods, principal component analysis （PCA） and partial least squares-discriminant analysis （PLS-DA）, were combined to analyze the differences in platycodin-type saponins of Platycodon grandiflorus from different producing areas. Results A total of 28 saponin components were identified from Platycodon grandiflorus of the three producing areas. PCA results showed that there were minor differences in platycodin-type saponins between Henan Platycodon grandiflorus and Jilin Platycodon grandiflorus, while Anhui P. grandiflorum exhibited significant differences from both. PLS-DA further screened 15 major differential compounds. Among them, the contents of 6 components including 3''-O-acetylpolygalacin D2 and platycodin H in Anhui Platycodon grandiflorus were higher than those in Henan and Jilin Platycodon grandiflorus; platycodigenic acid A had the highest content in Jilin Platycodon grandiflorus; the contents of platycodin D3, polygalacin J, and polygalacin D were relatively higher in Henan Platycodon grandiflorus. Conclusion This study clarified the characteristic differences in core components of Platycodon grandiflorus from the three major producing areas, which provided an important theoretical basis for the screening of high-quality Platycodon grandiflorus resources, elucidation of the mechanism underlying its authenticity, and construction of a standardized quality control system.

Objective To investigate the effective components and therapeutic mechanism of Chaihu-Guizhi-Ganjiang decoction in treating chronic non-atrophic gastritis. Methods The primary and secondary ion fragments of chemical components of Chaihu-Guizhi-Ganjiang decoction were obtained by UHPLC-Q-TOF/MS. Comparing with reference standards and literature information, a comprehensive characterization of the chemical constituents of Chaihu-Guizhi-Ganjiang decoction was conducted. Then, the network pharmacology approach was applied to explore the therapeutic mechanism of Chaihu-Guizhi-Ganjiang decoction in treatment of chronic non-atrophic gastritis based on the components in plasma and verified by immunohistochemical results. Results A total of 24 absorbed components of Chaihu-Guizhi-Ganjiang decoction were characterized, including 11 flavonoid glycosides, 3 fatty acids, 3organic acids, 2 gingerols, 2 flavonoids and, 1 each of fatty aldehydes, triterpenoids and amino acids, which mainly acted on TNF-α, IL-6, STAT3, and PTGS2. It exerted therapeutic effects by modulating signaling pathways, including the IL-17 signaling pathway and the AGE-RAGE signaling pathway, etc. Conclusion This study provided the first exploration of the effective components and therapeutic mechanism of Chaihu-Guizhi-Ganjiang decoction in treatment of chronic non-atrophic gastritis by UHPLC-Q-TOF/MS, which could offer scientific references for its further research.

ObjectiveTo elucidate the chemical composition of Danshenyin and its blood components in rats after oral administration. MethodsUltra performance liquid chromatography-quadrupole-time-of-flight tandem mass spectrometry（UPLC-Q-TOF-MS/MS） coupled with PeakView 1.2 software was used to systematically characterize and identify the components of Danshenyin aqueous extract and its migratory components in rat blood after oral administration based on the retention time， quasi-molecular ion peaks， secondary fragmentation ions， and literature reports， and a preliminary compounds identification of Salviae Miltiorrhizae Radix et Rhizoma aqueous extract， the co-decoction of Santali Albi Lignum and Amomi Fructus was carried out to attribute the chemical constituents of the aqueous extract of Danshenyin. ResultsA total of 73 compounds， including 21 phenolic acids， 23 diterpenes， 6 flavonoids， 7 organic acids， 3 volatile oils and 13 others， were identified from the aqueous extract of Danshenyin. And 36 prototypes and 15 metabolites were identified in rat plasma， the major metabolic pathways included reduction， hydration， hydroxylation， demethylation， methylation， sulfation and others， these metabolites were mainly derived from tanshinones and salvianolic acids. ConclusionThe main blood components of the aqueous extract of Danshenyin are salvianolic acids and tanshinones， which may be the material basis of the efficacy. This study can provide reference for pharmacological research， quality control， and clinical application of Danshenyin.

Objective To develop a risk prediction model for moderate-to-severe catheter-related bladder discomfort(CRBD)after non-transurethral surgery based on various machine-learning algorithms and to compare the performance of the models,so as to provide a reference for accurately identification and prevention of the postoperative moderate-to-severe CRBD.Methods A convenience sampling method was employed to recruit 719 patients as study subjects.The patients received non-transurethral surgery and intraoperative urinary catheterisation in a Tier-ⅢA hospital in Shanxi Province between January and May 2024.The clinical data were collected,with 70％of the randomly selected data was assigned to a training dataset(n=503)for the model building and the rest of 30％of data was used as the testing dataset(n=216)for internal model validation.Predictors were determined using least absolute shrinkage and selection operators(LASSO).Seven machine learning methods of logistic regression,K-nearest neighbours,random forest,artificial neural network,decision tree,light gradient boosting machine(LightGBM)and elastic net were employed to establish the risk prediction models.Performance of the models was evaluated based on the area under receiver operating characteristic curve(AUR-ROC),accuracy,precision,recall and F1 score.Results A total of 719 patients who underwent non-transurethral surgery were included in the study.It was found that 154(21.4％)patients presented with moderate to severe CRBD and 565(78.6％)patients were without or only with a mild CRBD.The predictors were deduced to six variables:gender,abdominal surgery,type of surgery,administration of dexmedetomidine before surgery,intraoperative administration of flurbiprofenate,and use of tramadol by the completion of surgery.It was found that the LightGBM model demonstrated a high stability,with 0.793 in AUC-ROC,0.763 in accuracy,0.879 in precision,0.747 in recall and 0.808 in F1.Conclusion The risk prediction model established through LightGBM for moderate-to-severe CRBD after a non-transurethral surgery exhibits a high stability.It offers a reference for medical practitioners to identify the patients with high-risk of moderate-to-severe CRBD and prepares for relevant interventions.

Objective:To gain insight into the multidimensional needs of adults with moderate-to-severe psoriasis at different stages of disease progression diagnostic and treatment dynamics based on patient journey maps, providing a basis for developing precise intervention strategies and optimizing care throughout the journey.Methods:From September to October 2024, 14 adult patients with moderate-to-severe psoriasis admitted to the Department of Dermatology of the First Hospital of Shanxi Medical University were selected by purposive sampling method for semi-structured interviews. Content analysis was used to analyze the data, drawing on theory of "timing it right" to depict a patient journey map that was reviewed and improved by the research team and patients.Results:Patient journey map was developed and condensed into four themes of experiences and challenges from pre-diagnosis to adaptation, complex emotional experiences, experiential pain points at each stage of the diagnosis and treatment, and opportunity points to improve the experience and quality of the diagnosis and treatment.Conclusions:At different stages of disease progression, the diagnosis and treatment needs of adults with moderate-to-severe psoriasis are characterized by dynamic evolution and multidimensional integration. The journey map can accurately identify patients' differentiated experiences and needs, and can provide a reference for healthcare professionals and policy makers to optimize patients' diagnostic and treatment experiences and focus on patients' health management.

Objective To develop a risk prediction model for moderate-to-severe catheter-related bladder discomfort(CRBD)after non-transurethral surgery based on various machine-learning algorithms and to compare the performance of the models,so as to provide a reference for accurately identification and prevention of the postoperative moderate-to-severe CRBD.Methods A convenience sampling method was employed to recruit 719 patients as study subjects.The patients received non-transurethral surgery and intraoperative urinary catheterisation in a Tier-ⅢA hospital in Shanxi Province between January and May 2024.The clinical data were collected,with 70％of the randomly selected data was assigned to a training dataset(n=503)for the model building and the rest of 30％of data was used as the testing dataset(n=216)for internal model validation.Predictors were determined using least absolute shrinkage and selection operators(LASSO).Seven machine learning methods of logistic regression,K-nearest neighbours,random forest,artificial neural network,decision tree,light gradient boosting machine(LightGBM)and elastic net were employed to establish the risk prediction models.Performance of the models was evaluated based on the area under receiver operating characteristic curve(AUR-ROC),accuracy,precision,recall and F1 score.Results A total of 719 patients who underwent non-transurethral surgery were included in the study.It was found that 154(21.4％)patients presented with moderate to severe CRBD and 565(78.6％)patients were without or only with a mild CRBD.The predictors were deduced to six variables:gender,abdominal surgery,type of surgery,administration of dexmedetomidine before surgery,intraoperative administration of flurbiprofenate,and use of tramadol by the completion of surgery.It was found that the LightGBM model demonstrated a high stability,with 0.793 in AUC-ROC,0.763 in accuracy,0.879 in precision,0.747 in recall and 0.808 in F1.Conclusion The risk prediction model established through LightGBM for moderate-to-severe CRBD after a non-transurethral surgery exhibits a high stability.It offers a reference for medical practitioners to identify the patients with high-risk of moderate-to-severe CRBD and prepares for relevant interventions.

Objective:To gain insight into the multidimensional needs of adults with moderate-to-severe psoriasis at different stages of disease progression diagnostic and treatment dynamics based on patient journey maps, providing a basis for developing precise intervention strategies and optimizing care throughout the journey.Methods:From September to October 2024, 14 adult patients with moderate-to-severe psoriasis admitted to the Department of Dermatology of the First Hospital of Shanxi Medical University were selected by purposive sampling method for semi-structured interviews. Content analysis was used to analyze the data, drawing on theory of "timing it right" to depict a patient journey map that was reviewed and improved by the research team and patients.Results:Patient journey map was developed and condensed into four themes of experiences and challenges from pre-diagnosis to adaptation, complex emotional experiences, experiential pain points at each stage of the diagnosis and treatment, and opportunity points to improve the experience and quality of the diagnosis and treatment.Conclusions:At different stages of disease progression, the diagnosis and treatment needs of adults with moderate-to-severe psoriasis are characterized by dynamic evolution and multidimensional integration. The journey map can accurately identify patients' differentiated experiences and needs, and can provide a reference for healthcare professionals and policy makers to optimize patients' diagnostic and treatment experiences and focus on patients' health management.

AIM: To predict the core targets and related signaling pathways of Yi-xin-yin oral liquid for the treatment of arrhythmia, heart failure and myocarditis based on UHPLC-Q-TOF/MS, network pharmacology, molecular docking methods, cell experiments, according to the“homotherapy for heteropathy”theory in traditional Chinese medicine. METHODS: UHPLC-Q-TOF / MS was used to analyze and identify the chemical composition of Yi-xin-yin oral liquid Extract and the blood-absorbing components of rats oral administrated with Yi-xin-yin oral liquid extract, which compounds were applied in the databases searching for the potential targets (TCMSP, SwissTargetPrediction) and disease targets (OMIM, Genecard). Venn diagram was used for target intersection, and the subsequent protein-protein interaction network obtained core targets by STRING11.5 database, and then construct a "disease-component-target" network by cytoscape3.9.0. Finally, DAVID database was used to analysis GO function and KEGG enrichment analysis of core targets, and molecular docking validation was performed using Autodock vina software. And, validated with H9c2 cells for potential active ingredients and targets. RESULTS: A total of 156 compounds were identified from Yi - xin-yin Oral Liquid extract; 34 compounds were identified from rat serum, including 6-gin-gerol, isoliquiritigenin, glycyrrhizic acid and other compounds, and 139 intersecting targets were obtained. The KEGG pathway enrichment analysis mainly involved the TNF signaling pathway, IL-17 signaling pathway, MAPK signaling pathway, PI3K-Akt signaling pathway and so on. The TNF and IL-6 targets were selected for molecular docking with the main compounds, and the docking results were good (less than -5 kcal/mol). In vitro cellular experiments have shown that Yi-xin-yin oral liquid can exert therapeutic effects by regulating TNF and IL-6. CONCLUSION: The main potential active ingredients of Yi-xin-yin oral liquid may be isoliquiritigenin, glycyrrhetinic acid, calycosin-7-glucoside, salvianolic acid B, and 6-gingerol, which mainly act on TNF, IL-6 and other targets to regulate specific signaling pathways and exert therapeutic effects.

Lignans are a powerful weapon for plants to resist stresses and have diverse bioactive functions to protect human health. Elucidating the mechanisms of stereoselective biosynthesis and response to stresses of lignans is important for the guidance of plant improvement. Here, we identified the complete pathway to stereoselectively synthesize antiviral (-)-lariciresinol glucosides in Isatis indigotica roots, which consists of three-step sequential stereoselective enzymes DIR1/2, PLR, and UGT71B2. DIR1 was further identified as the key gene in respoJanuary 2024nse to stresses and was able to trigger stress defenses by mediating the elevation in lignan content. Mechanistically, the phytohormone-responsive ERF transcription factor LTF1 colocalized with DIR1 in the cell periphery of the vascular regions in mature roots and helped resist biotic and abiotic stresses by directly regulating the expression of DIR1. These systematic results suggest that DIR1 as the first common step of the lignan pathway cooperates with PLR and UGT71B2 to stereoselectively synthesize (-)-lariciresinol derived antiviral lignans in I. indigotica roots and is also a part of the LTF1-mediated regulatory network to resist stresses. In conclusion, the LTF1-DIR1 module is an ideal engineering target to improve plant Defenses while increasing the content of valuable lignans in plants.

The safety of traditional Chinese Medicine (TCM) has garnered widespread attention and has become a major obstacle to its further development and internationalization. The complexity of TCM and the unpredictability of its interactions with the human body pose significant challenges to safety research. The causes of TCM safety issues are multifaceted, including intrinsic and extrinsic toxicity, confusion of herbal sources and misuse in clinical practice, inadequate patient awareness of safe medication use, and insufficient regulatory oversight of TCM quality and safety. To strengthen the risk managements, it is essential to employ scientific technologies to investigate the fundamental nature of TCM safety, leverage artificial intelligence for big data analysis and early risk warning, promote the scientific concept of safe TCM use, and establish a comprehensive lifecycle pharmacovigilance system for TCM. These will facilitate TCM safety research in China, ensure patient medication safety, and promote the healthy and sustainable development of the TCM industry and its internationalization.