Objective The HPLC fingerprint and the content determination method of the benchmark sample of Guizhi Gancao Decoction (GGD, 桂枝甘草汤) were established to study the rule of quantity-quality transmitting of GGD benchmark samples. Methods According to the method recorded in “Treatise on Febrile Diseases”, 15 batches of GGD benchmark samples were prepared and the HPLC fingerprint of 15 batches of benchmark samples was established. The peak attribution and similarity range in the fingerprint were clarified, and the quantity-quality transfer indexes such as the range of extract yield, the content range of index components and the range of transfer rate were analyzed. The quality control system for GGD benchmark samples was preliminarily established. Results A total of 40 common peaks were identified in the 15 batches of GGD benchmark samples, which with good similarity (> 0.99). The contents of protocatechuic acid, liquiritin, coumarin, cinnamyl alcohol, liquiritigenin, cinnamic acid, cinnamaldehyde, and glycyrrhizic acid in the benchmark sample were 0.080—0.087, 0.863—1.055, 0.431—0.560, 0.167—0.227, 0.087—0.127, 0.423—0.492, 0.160—0.199, and 2.437—2.904 mg/g, respectively. The transfer rates of the eight index components from decoction pieces to water decoction were 44.35%—54.84%, 40.56%—44.44%, 48.82%—56.00%, 22.84%—52.61%, 25.70%—30.02%, 33.75%—37.83%, 23.42%—28.98%, and 62.09%—65.13%, respectively. The transfer rates from the water decoction to the reference sample were 67.99%—84.39%, 62.15%—67.93%, 59.42%—74.22%, 76.20%—85.64%, 51.31%—60.73%, 78.80%—85.17%, 16.27%—22.19%, and 71.82%—76.58%, respectively. Overall, the transfer rates of components from decoction pieces to water decoction were relatively low, while the transfer rates of most components increased during the subsequent concentration and freeze-drying processes. Only cinnamaldehyde showed a significant loss during freeze-drying. The dry paste yield of the reference sample was stable, with an average transfer rate of 77.71 %. Conclusion Through the HPLC fingerprint of GGD benchmark samples and the quantity-quality transfer patterns of its active components, a preliminary quality control system based on index components was established. This provides a scientific basis for the standardization and quality consistency evaluation of GGD classical prescription preparations.

Objective To investigate the potential targets and mechanism by which curcumin regulates cholesterol metabolism in intestinal epithelial cells based on both in vivo and in vitro experiments. Methods A high-cholesterol model was established in ApoE^-/- mice fed a high-fat diet, followed by intervention with curcumin, lipid levels in serum were measured. Hematoxylin-eosin (HE) staining was used to observe pathological changes in small intestine tissue. Western blotting was used to detect the protein expressions of low-density lipoprotein receptor (LDLR), NPC1 like intracellular cholesterol transporter 1 (NPC1L1), adenosine triphosphate binding cassette transporters G8 (ABCG8), ABCG5 and liver X receptor α (LXRα) in small intestine tissue. An in vitro high-cholesterol model was constructed in rat intestinal epithelial cells-6 (IEC-6) using cholesterol micelle stimulation. After intervention with curcumin or LXRα inhibitor GSK2033, lipid levels were detected by oil red O staining and immunofluorescence. Transwell experiment was used to detect cholesterol transport. Western blotting and immunofluorescence were used to detect cholesterol metabolism-related protein expressions. Results In vivo experiments showed that 100, 200 mg/kg curcumin caused no damage to small intestine tissue structure of ApoE^-/- mice fed with high-fat diet, and could reduce the body weight and lipid levels in serum of mice (P < 0.05), regulate the expressions of proteins related to cholesterol uptake and intestinal cholesterol excretion (TICE) pathway (P < 0.05, 0.01). The regulation results of protein profile in vitro experiments were consistent with the in vivo model, and curcumin could reduce the lipid levels of intestinal epithelial cells in a high cholesterol environment and inhibit cholesterol transport (P < 0.05, 0.01). After further intervention with LXRα inhibitor GSK2033, there was a significant reversal in intracellular lipid levels and expressions of TICE pathway related proteins such as ABCG5, ABCG8 and NPC1L1 (P < 0.05). Conclusion Intestinal epithelial LXRα is an important target of curcumin for promoting cholesterol efflux and inhibiting cholesterol uptake, thereby contributing to the maintenance of systemic cholesterol homeostasis, and its effects may also involve other regulatory pathways.

Objective To investigate the chemical components and anti-inflammatory activities of the roots of Stemona tuberosa from Hainan province. Methods The chemical constituents of S. tuberosa were isolated and purified using chromatography techniques such as silica gel, gel column chromatography, and semi-preparative high-performance liquid chromatography (HPLC). Subsequently, the structures of the purified compounds were identified by modern spectroscopic methods such as nuclear magnetic resonance (NMR) and mass spectrometry (MS). Finally, the anti-inflammatory activities of the compounds were evaluated using the lipopolysaccharide (LPS)-induced murine monocyte-macrophage RAW264.7 cell model. Results A total of seven compounds were isolated from S. tuberosa, and identified as (4R)-3,5,5-trimethyl-4-(3-methylbut-2-enoyl)cyclohex-2-en-1-one (1 ), oxystemofoline (2 ), methyl 4-hydroxycinnamate (3 ), (-)-stemoamide (4 ), tuberostemospiroline (5 ), stemanthrene C (6 ), stilbostemin F (7 ). Compounds 2 and 3 exhibited inhibitory activity against NO production in LPS-induced RAW264.7 cells, with median inhibition concentration (IC₅₀) values of (42.99 ± 4.96) and (70.22 ± 0.81) μmol/L, respectively. Conclusion Compound 1 was identified as a new compound, named tuberostemoterpenone. Compound 2 was isolated from S. tuberosa for the first time. Compounds 2 and 3 exhibited no significant cytotoxicity within the tested concentration range and demonstrated certain anti-inflammatory activity.

Objective To optimize the processing technology of Jiaomaya (charred Hordei Fructus Germinatus, CHFG) and investigate its synergistic effects and mechanisms on intestinal motility in functional dyspepsia (FD) mice. Methods Thermal analysis techniques were employed to analyze the pyrolysis characteristics of maiya (Hordei Fructus Germinatus, HFG) and its active components, determining the appropriate temperature range for charring. Using 5-hydroxymethylfurfural (5-HMF) content, total flavonoids content, and appearance trait scores as evaluation indicators, the AHP-CRITIC weight analysis was applied to establish the weight of each indicator. Response surface methodology was utilized to optimize processing parameters such as temperature and duration. A multifactorial composite method was used to establish an FD mouse model. Intestinal propulsion rate, gastric emptying rate, and gastrointestinal hormone (motilin, gastrin) levels were measured to compare the pharmacological differences between optimized CHFG and raw HFG. Results Thermal analysis identified the optimal charring temperature window for HFG as 217.7—286.3 ℃. Response surface optimization yielded the best processing parameters: 270.00 ℃ for 20.00 min. Pharmacological experiments demonstrated that the high-dose CHFG group significantly improved intestinal propulsion rate (P < 0.05), gastric emptying rate (P < 0.05), and serum motilin (P < 0.05) and gastrin (P < 0.05) levels in FD mice. Conclusion The AHP-CRITIC weighting method combined with thermal analysis technology successfully optimized the processing of CHFG. The optimized CHFG significantly enhanced gastrointestinal motility in FD mice, providing methodological references for the quantification and standardization of fire control in traditional Chinese medicine processing.

Objective The study employed bioinformatics to identify prognostic genes associated with pancreatic adenocarcinoma (PAAD) and predict Chinese medicines and active ingredients that regulate these genes. Methods The integration of data from the TCGA, GTEx, and GEO databases was conducted, then screening the prognostic genes through differential gene analysis, COX regression analysis, and survival analysis. The subsequent step involves prognostic efficacy analysis and a verification of the expression trends of the identified key genes. Concurrently perform gene ontology (GO) functional and Kyoto encyclopedia of genes and genomes (KEGG) pathway analyses, as well as gene set enrichment analysis (GSEA), to identify potential pathways and biological processes. The impact of feature genes on the infiltration status of immune cells was analyzed, and their correlation with immune checkpoints was further investigated, and tumor immune escape capacity and tumor mutation burden were predicted. Validation of gene expression patterns at the single-cell level. The DSigDB, CTD, and HERB databases are used to predict the potential active ingredients of Chinese medicine and perform molecular docking. Additionally, pharmacokinetic analysis is conducted using Swiss ADME and prediction and analysis of Chinese medicine by Coremine Medical database. Cellular experiments were conducted to validate the regulatory effect of the key active ingredient on the characteristic gene. Results The investigation ultimately led to the identification of the key gene interferon alpha inducible protein 27 (IFI27), which exhibited significantly elevated expression levels in PAAD tissues. Patients exhibiting low IFI27 gene expression demonstrated superior overall survival. Enrichment analysis indicated its potential involvement in various biological processes, including apoptosis, ECM-receptor interaction, regulation of T cell activation, macrophage migration, and signaling pathways such as PI3K-Akt and NF-κB. Immune infiltration analysis indicates that IFI27 may regulate the infiltration status of various immune cells, such as B cells naive, T cells CD8⁺, T cells regulatory (Tregs), and macrophages M0, suggesting that it has an important function in regulating the tumor immune microenvironment. Meanwhile, the expression of IFI27 showed significant positive correlations with multiple immune checkpoint molecules. Further studies have revealed that low expression of IFI27 is significantly associated with the response to immunotherapy, supporting its value as a therapeutic target. Single-cell RNA sequencing verified IFI27 upregulation in PAAD, pinpointing its expression to macrophages and other immune cells. Experiments confirmed that fisetin significantly downregulated both mRNA and protein expression levels of IFI27 in pancreatic cancer cells. Furthermore, a total of 22 Chinese medicines, including Jianghuang (Curcumae Longae Rhizoma), Zaojiaoci (Gleditsiae Spina), and Yujin (Curcumae Radix), were predicted. The four qi encompass cold and warm, and the five flavors are primarily bitter, sweet, and pungent, with a focus on the liver, spleen, and stomach meridians. The main effects are activating blood and resolving stasis, moving qi to relieve pain, and clearing heat and detoxifying, combined with tonifying and inducing diuresis. Conclusion The results of this study imply that IFI27 may serve as a prognostic gene related to PAAD immunity, while fisetin and various Chinese medicines may serve as potential therapeutic drugs.

Objective To rapidly identify the chemical constituents of the ethanol extract of Dendropanax dentiger, a She ethnic medicine, using ultra performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS/MS) and feature-based molecular networking(FBMN), and preliminarily evaluate its anti-inflammatory activity. Methods Chromatographic separation was performed on an ACQUITY UPLC HSS T3 column (100 mm × 2.1 mm, 1.8 μm) using a gradient elution with 0.1% formic acid in water (A) and acetonitrile (B) as the mobile phases. MS data were acquired in both positive and negative ion modes, and FBMN was constructed on the global natural products social molecular networking (GNPS) platform (http://gnps.ucsd.edu). Based on the matching results of the SIRIUS 6.2.2 software and the GNPS database, combined with the reference standards, retention time, feature fragments, literature, and information from the PubChem and MassBank databases, and in combination with the structural clustering characteristics of FBMN, the chemical composition of the alcohol extract of D. dentiger was rapidly identified and its lysis rules were summarized. In vitro anti-inflammatory effects were evaluated using a lipopolysaccharide (LPS)-induced RAW264.7 macrophage inflammation model, with CCK-8, Western blotting, and immunofluorescence analyses. Results A total of 59 compounds were identified, including 18 phenolic acids, 11 lignans, eight flavonoids and flavonoid glycosides, six coumarins, four cyclic peptides, three phenylethanoid glycosides, four fatty acids and derivatives, two iridoids, two glycosides, and one alkaloid. Among them, 19 potentially unreported compounds were identified from D. dentiger for the first time. Three positional isomers—isochlorogenic acid A, B, and C were successfully identified via FBMN, and a methylated derivative was further proposed. The results of cell experiments demonstrated that the ethanol extract of D. dentiger significantly suppressed LPS-induced inflammatory responses in RAW264.7 cells by downregulating interleukin-1 beta (IL-1β) and tumor necrosis factor-alpha (TNF-α) expression, upregulating IL-10 secretion, and inhibiting nuclear translocation of nuclear factor-kappa-B p65(NF-κB p65) . Conclusion FBMN effectively overcomes the limitations of traditional molecular networking in isomer identification. The integration of UPLC-Q-TOF-MS/MS with FBMN enables rapid and efficient identification of the complex components in D. dentiger, leading to the first identification of 19 potentially unreported compounds. The ethanol extract of D. dentiger exhibits promising anti-inflammatory activity, providing an experimental basis for further research and development application of its active substances.

Objective To investigate the therapeutic effect and potential mechanism of Penthorum chinense (PCP) on primary sclerosing cholangitis (PSC). Methods The chemical constituents of PCP extract were analyzed using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). A total of 50 mice were randomly divided into control group, model group, obeticholic acid (6.5 mg/kg) group and PCP low-, high-dose (2, 4 g/kg) groups, with 10 mice in each group. Mice were fed with 0.1% 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC) feed to induce PSC model. After 14 d of intervention, the efficacy of PCP was evaluated by measuring serum biochemical indicators, liver histopathological changes and liver fibrosis markers. To further explore the mechanisms, transcriptomic sequencing, qRT-PCR experiment and quantitative analysis of bile acid profile were performed. Results A total of 331 chemical constituents were identified in PCP extract. Pharmacodynamic results showed that compared with model group, high-dose PCP significantly reduced liver index and levels of liver injury markers in serum (P < 0.05, 0.01, 0.001), and effectively alleviated cholestasis and fibrosis in liver tissue, with effects superior to those of positive drug obeticholic acid. Transcriptomic analysis identified 51 differentially expressed genes. Enrichment analysis suggested that the effect of PCP was associated with pathways such as bile secretion. Mechanistic validation revealed that compared with model group, high-dose PCP significantly down-regulated mRNA expressions of key enzymes for primary bile acid synthesis in liver tissue (P < 0.05), while up-regulated expression of bile acid‑conjugating enzyme (P < 0.001). Serum and liver bile acid profiling revealed that high-dose PCP intervention significantly increased the ratio of conjugated to unconjugated bile acids (P < 0.001). Conclusion PCP ameliorates DDC‑induced cholestatic liver injury and exerts a therapeutic effect on PSC by inhibiting primary bile acid synthesis, promoting bile acid conjugation and excretion.

Objective To establish the physical, chemical, and taste fingerprints of 15 batches of the classic traditional Chinese medicine formula Zhishi Xiebai Guizhi Decoction (ZXGD, 枳实薤白桂枝汤) benchmark samples, as well as a method for determining the content of three index components. Methods Fifteen batches of ZXGD benchmark samples were prepared. A physical fingerprint was constructed using six physical parameters: solid content rate, conductivity, refractive index, surface tension, density, and pH value. Similarity evaluation, principal component analysis (PCA), and cluster analysis were employed for analytical evaluation of this physical fingerprint. HPLC was used to establish the chemical fingerprint of ZXGD, followed by similarity evaluation of the chemical fingerprint. Additionally, the contents of three index components (cinnamic acid, cinnamaldehyde, and synephrine) were determined via HPLC. Electronic tongue technology was applied to analyze the taste of ZXGD, construct a taste radar chart, and generate a heatmap to analyze the correlation between taste, chemical component contents, and physical properties. Results The similarity between the physical fingerprint of each of the 15 batches of benchmark samples and the control fingerprint was greater than 0.9. Results of hierarchical cluster analysis showed that the 15 batches of samples were clustered into two groups: one group included samples S1, S6, S11, S12, and S15, while the remaining benchmark samples formed the other group. Cluster analysis based on the contents of the three index components showed results consistent with those of the physical fingerprint analysis. The heatmap revealed that cinnamaldehyde and synephrine were strongly correlated with bitterness, bitter aftertaste, saltiness, and alkaline bitter aftertaste (P < 0.05); pH value was significantly associated with sourness and richness; while synephrine exhibited correlation with electrical conductivity, refractive index, and pH value. Conclusion There is a correlation among the physical, chemical and taste attributes of ZXGD benchmark samples. The established “physical-chemical-sensory” multi-dimensional evaluation model can more comprehensively reflect the overall quality, providing a scientific basis for the quality control of ZXGD benchmark samples and the development of compound preparations.

Objective To systematically evaluate the current evidence from randomized controlled trials (RCTs) on traditional Chinese medicine (TCM) for pulmonary nodules (including early-stage lung cancer), and to provide evidence-based recommendations for future clinical practice and research. Methods Comprehensive searches were conducted across the following databases up to September 2025: Intelligent Clinical Evidence Database of Chinese Patent Medicine, China national knowledge infrastructur (CNKI), VIP Journal Database, Wanfang Data Knowledge Service Platform, Chinese biomedical literature service system (SinoMed), PubMed, Web of Science, Embase, and the Cochrane Library. Extracted data included key characteristics of participants and studies, such as disease subtype, TCM syndrome, year of publication, sample size, TCM therapeutic principles, details of treatment and control interventions, duration of treatment and follow-up, methodological details, and outcome measures. For studies involving Chinese patent medicines, extracted data were categorized using the Aireview Agent and subsequently verified manually. Data from other TCM studies were extracted and verified manually. Results A total of 70 RCTs were included, with the greatest number published in 2024. The studies showed that deficiency of both qi and yin syndrome and phlegm-stasis mutual binding syndrome were the most common TCM syndromes. The main therapeutic principles were resolving phlegm, tonifying qi, and dispersing nodules. In the treatment groups, Chinese herbal decoctions were the predominant intervention. Clinical efficacy was the most commonly reported outcome measure. In the risk-of-bias assessment, the measurement of the outcome domain was most frequently rated at high risk of bias. Conclusion RCTs of TCM interventions for pulmonary nodules (including early-stage lung cancer) exhibited several critical limitations, such as inadequate specification of disease subtypes in participant eligibility criteria, inconsistent TCM syndrome differentiation, failure to report or analyze primary endpoints, and a high risk of bias—particularly in outcome measurement. We recommend developing a core outcome set for TCM interventions in pulmonary nodules. Future clinical trials—whether decentralized or large-scale, multicenter randomized controlled trials should be stratified by disease subtype, use standardized protocols, and strictly adhere to established follow-up guidelines to generate high-quality evidence, particularly for nodules at elevated risk of malignancy.

Objective To achieve accurate, nondestructive and low-cost identification of Panax ginseng age, a P. ginseng age identification method was established in this study based on hyperspectral imaging technology combined with machine learning. Methods Hyperspectral images of 84 P. ginseng samples and hyperspectral data of 1 680 regions of interest were obtained by acquiring P. ginseng hyperspectral images in the visible-near infrared (VNIR) and short-wave infrared (SWIR) bands from one to seven years old in Tonghua, Jilin, China, respectively. The hyperspectral data of ginseng samples were preprocessed with multiple scattering correction (MSC), standard normal variation (SNV), Savitzky-Golay smoothing, first-order derivative (FD) and second-order derivative (SD) in the VNIR, SWIR and VNIR + SWIR fusion bands, and then combined with partial least squares discriminant analysis (PLS-DA), linear Then, we combined PLS-DA and LinearSVC discriminant analysis methods to establish the identification models of P. ginseng years in two classification scales distinguished by “medicinal food”, three classification scales distinguished by greater than, less than, and equal to five years, and seven classification scales distinguished by seven years, respectively. Results In the VNIR 410—720 nm band range, there was an overall trend of sequential decrease in the average spectral reflectance of P. ginseng from one year to seven years at the same wavelength. The results of confusion matrix evaluation of different classification recognition models showed that the LinearSVC model with FD preprocessing in SWIR band and fusion band had better classification and higher accuracy at three annual scales, and the prediction set accuracy of 2, 3 and 7 classification models were 99.60%, 98.41% and 95.24%, respectively. The recognition models built using the feature bands screened by the continuous projection algorithm (SPA) have higher accuracy at 2 and 3 classifications, and use fewer bands for more efficient classification and recognition. Conclusion Hyperspectral imaging technology combined with machine learning and feature band screening methods can better achieve the identification of the age of P. ginseng of specific origin, and provide a reference for realizing the practical applications of this technology in P. ginseng age identification and quality control.