Objective To address the issues of reliance on exhaustive “blind” trial-and-error and the lack of theoretical guidance in the modeling process of near-infrared spectroscopy (NIRS), this study used the solid content prediction model of Jinzhen Oral Liquid (JOL, 金振口服液) as a case study. It aimed to reveal the direction for optimizing the best model from the perspective of spectral information quality and verify its application value in model maintenance. Methods The NIRS and solid content data of 380 samples were collected. After being processed by nine preprocessing methods, prediction models for solid content were established using partial least squares (PLS) and support vector regression (SVR), respectively. An evaluation framework was innovatively constructed by introducing Shannon entropy, principal component analysis (PCA), and autoencoders to quantify spectral information quality from three dimensions: information richness, linear structure concentration, and non-linear structure capturability. Finally, by systematically analyzing the correlation between spectral information characteristics and model performance, the direction for the optimal preprocessing method was revealed. This correlation rule was then applied to model maintenance involving 294 newly added samples to screen for the optimal spectral dataset. Results It was found that for NIRS characterized by broad and overlapping peaks, both information density and information retention rate were negatively correlated with PLS model performance. Based on this correlation rule, the optimal dataset for model maintenance was successfully predicted, achieving a modeling performance (R_p² = 0.990 9) significantly superior to that of other datasets. Conclusion The correlation rules identified in this study effectively explain the impact of preprocessing on model performance. They provide a theoretical basis and guiding tools for the optimization and maintenance of spectral models, facilitating a shift from “blind trial-and-error” to “active improvement”. This offers new insights for establishing a standardized and intelligent workflow for NIRS model construction and maintenance.

Objective To develop formulation-optimized ganoderic acid A liposomes (GA-Lips) with improved stability and high encapsulation efficiency, and to evaluate their cellular uptake efficiency and in vitro antitumor activity. Methods GA-Lips were prepared using the thin-film hydration method, and formulation parameters were optimized by varying the ratios of GAA, phospholipids, and cholesterol. Particle size, ζ potential, and morphology were characterized. In vitro drug release and formulation stability were evaluated under different media, dilution, and storage conditions. Hemocompatibility was assessed by hemolysis assays. Cellular uptake efficiency was examined using confocal laser scanning microscopy and flow cytometry. Antiproliferative effects and apoptosis induction in HepG2 cells were analyzed using CCK-8 and Annexin V-FITC/PI assays, respectively. Results The optimized GA-Lips exhibited a uniform spherical morphology with a mean particle size of (74.52 ± 1.00) nm, a PDI of 0.26 ± 0.01, and a ζ potential of (-46.75 ± 1.61) mV. The formulation showed sustained drug release, excellent stability under various test conditions, and negligible hemolytic activity. GA-Lips significantly enhanced cellular uptake efficiency in HepG2 cells compared with free GAA. Moreover, GA-Lips exhibited pronounced cytotoxic effects and markedly increased apoptosis induction. Conclusion The optimized GA-Lips demonstrated favorable stability and hemocompatibility, effectively enhancing the cellular uptake efficiency and in vitro antitumor efficacy of GAA. These results support the potential of GA-Lips as a promising nanocarrier system for ganoderic acid A and provide a foundation for further in vivo and mechanistic studies.

Objective To apply multiple techniques for the combined characterization of commercially available calcined Magnetitum decoction slices and to explore the quality evaluation methods for calcined Magnetitum decoction slices. Methods Eleven batches of commercially available calcined Magnetitum decoction slices were collected. Quality inspections were carried out in accordance with the 2025 edition of the Chinese Pharmacopoeia (volume I). Thermal analysis (TA), X-ray diffraction (XRD), X-ray fluorescence (XRF), and Fourier transform infrared spectroscopy (FTIR) were utilized to characterize the thermal stability, phase composition, elemental composition, and infrared structure of the samples. Inductively coupled plasma mass spectrometry (ICP-MS) was used to determine the contents of heavy metals and harmful elements in the samples. The theoretical maximum residue limit value L and the target hazard quotient (THQ) were calculated to evaluate the health risks. Results The content determination results of 11 batches of commercially available calcined Magnetitum decoction slices were qualified, but the appearance of 4 batches of slices had a quality issue of being too red, which did not meet the requirements of the 2025 edition of the Chinese Pharmacopoeia (volume I). TA results indicated significant differences in the thermal stability of the 11 batches of commercially available calcined Magnetitum decoction slices. Five batches showed a slow weight loss trend; four batches presented weight loss steps in the temperature range of 420—580 ℃; two batches first showed weight gain and then weight loss steps in the 420—580 ℃ range. XRD results showed that the commercially available calcined Magnetitum decoction slices mainly consisted of three phases: Fe₃O₄, SiO₂, and Fe₂O₃, with significant differences in the relative diffraction intensity of Fe₂O₃. XRF results demonstrated that the commercially available calcined Magnetitum decoction slices were mainly composed of elements such as Fe, Si, Al, Mg, P, K, and Ca, and the relative contents of Fe and Si reached 90%. FTIR results showed that the commercially available calcined Magnetitum decoction slices exhibited characteristic absorption peaks of Si-O asymmetric stretching vibration, Si-O-Si symmetric stretching vibration, and Si-O bending vibration in the three wavelength bands of 1 250—1 100, 800—600, and 600—300 cm^-1, respectively, and an absorption peak of Fe-O stretching vibration appeared in the 540—570 cm^-1 band. ICP-MS results indicated that among 11 batches of commercially available calcined Magnetitum decoction slices, three batches exhibited mercury (Hg) content exceeding the limit L with a THQ greater than 1; One batch showed lead (Pb) content exceeding the limit L with THQ > 1. Conclusion The quality of calcined Magnetitum decoction slices was evaluated based on the 2025 edition of the Chinese Pharmacopoeia and multiple techniques, with the aim of providing a reference for improving the quality control of calcined Magnetitum decoction slices.

Objective To elucidate the formulation patterns and health functions of health products containing Shanyao (Dioscoreae Rhizoma) and explore the underlying mechanisms via data mining, network pharmacology, and molecular docking technologies. Methods Health products containing Dioscoreae Rhizoma were retrieved from the State Administration for Market Regulation and Yaozhi websites. Frequency analysis and Apriori algorithm-based association rule mining were implemented in R language. The TCMSP, HERB, HIT 2.0, ETCM 2.0, and TCMID databases were used to search for the active components of Dioscoreae Rhizoma, and the PubChem and SwissTargetPrediction databases were utilized to predict the targets. Then, potential targets associated with high-frequency health functions were obtained from GeneCards, TTD, DrugBank, OMIM, and PathCards databases. Functional enrichment analysis was subsequently performed using the DAVID database. Finally, molecular docking of representative Dioscoreae Rhizoma constituents with core targets was conducted using AutoDock Vina, followed by diagnostic evaluation via receiver operating characteristic (ROC) curve analysis based on GEO chip data. Results A total of 471 Dioscoreae Rhizoma-containing health products were included, dominated by capsules in formulation and targeting immune enhancement as the main health function. The formulas involved 216 types of Chinese medicinal materials, predominantly tonifying, warm in nature, sweet in taste, and attributed to the liver meridian. Gouqizi (Lycii Fructus)-Dioscoreae Rhizoma, Fuling (Poria)-Dioscoreae Rhizoma as the core medicinal ingredients. Network pharmacology analysis identified 294 active components and 892 related target genes from Dioscoreae Rhizoma, alongside 2 360 potential targets associated with the high-frequency health function of immune enhancement. Then, PPI topological analysis identified five core targets [signal transducer and activator of transcription 3 (STAT3), epidermal growth factor receptor (EGFR), protein kinase B1 (AKT1), interleukin 6 (IL6), and tumor necrosis factor (TNF)]. Enrichment analysis suggested that cancer pathway, cell apoptosis, TNF signaling pathway and chemokine signaling pathway were the key pathways for Dioscoreae Rhizoma and its compatibility to enhance immunity. Molecular docking revealed good binding affinity of core targets with characteristic components of Dioscoreae Rhizoma, notably, allantoin, dioscin, and diosgenin, with ROC analysis further confirming the diagnostic potency of EGFR. Conclusion This study identified “Dioscoreae Rhizoma-Lycii Fructus” as the core herb pair with the highest support degree in the formulation patterns of Dioscoreae Rhizoma-containing health products. The combination of Dioscoreae Rhizoma, Lycii Fructus, and Poria may take EGFR and AKT1 as core targets and exert an immune-enhancing effect by regulating the apoptosis process and inflammatory response in people with low immunity.

Objective To integrate differentially expressed genes (DEGs) in gastric cancer (GC) from the Gene Expression Omnibus (GEO) database, systematically identify core targets associated with tumor progression, and predict therapeutic Chinese medicines via network distance, providing molecular evidence for integrated traditional Chinese and Western medicine precision intervention in GC. Methods A total of 21 GC datasets (2 125 GC, 367 normal samples) were downloaded from GEO to construct an expression matrix. DEGs were screened using the limma package (|log₂(FC)| > 1, FDR < 0.05), weighted gene co-expression network analysis (WGCNA) was performed to identify modules most correlated with disease phenotype, gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analyses were conducted on key genes, seven machine learning models were built with SHapley additive exPlanations (SHAP) for feature importance interpretation; network distance between Chinese medicine target modules and GC key genes was calculated based on the human PPI network to screen topologically proximal medicines, with statistics on four properties, five flavors, meridian tropism, and efficacy. Results A total of 455 DEGs were obtained. WGCNA yielded 31 modules, with the light-yellow module (r = 0.56, q < 0.01) containing 194 hub genes; intersection with DEGs produced 177 key genes. Enrichment analysis showed GO-biological processes (BP) focused on extracellular matrix organization and adhesion, GO-cell component (CC) on collagen-containing ECM and focal adhesion, GO-molecular function (MF) on integrin/growth factor binding, and KEGG on actin cytoskeleton regulation, phosphatidylinositol-3-hydroxykinase (PI3K)-protein kinase B (Akt), and interleukin-17 (IL-17) signaling. The random forest (RF) model achieved 0.991 accuracy, with SHAP consistently ranking SULF1, THY1, DNER, and SPINK7 as top contributors. Network distance screening identified Arctii Fructus, Prunellae Spica, Atractylodis Rhizoma, Fritillariae Cirrhosae Bulbus, Ligustri Lucidi Fructus, Hypocreaceae, and Persicae Semen among the top 15 medicines, characterized by cool/cold properties, bitter flavor, liver/stomach/lung tropism, and primarily heat-clearing with deficiency-tonifying efficacy. Conclusion This study systematically elucidates GC molecular mechanisms, predicting multi-target anti-GC potential of heat-clearing, yin-nourishing, and blood-activating Chinese medicines, and provides novel strategies for GC precision diagnosis/treatment and modernization of traditional Chinese medicine.

Objective To systematically analyze the composition, structural characteristics of the UDP-glucosyltransferase (UGT) gene family in Polygonum cuspidatum, investigate its expression patterns across different root tissues, as well as its potential roles in the glycosylation of resveratrol and emodin, so as to provides a theoretical foundation for elucidating the biosynthetic mechanisms of active metabolites. Methods The UGT gene family of P. cuspidatum was identified at the genome-wide level based on transcriptome and genomic datasets. Analyses of physicochemical properties, chromosomal localization, gene structure, conserved motifs and cis-regulatory elements were then performed. The evolutionary characteristics were analyzed through phylogenetic reconstruction, gene duplication analysis and protein interaction network prediction. Correlation analysis integrating transcriptomic and metabolomic data was conducted, and six representative genes potentially involved in the glycosylation of resveratrol and emodin were selected for validation using qRT-PCR. Results A total of 178 UGT genes were identified and grouped into 14 subfamilies, exhibiting substantial structural and functional diversity. The gene family members were unevenly distributed in chromosomes, and several genes were likely generated through tandem or segmental duplication events. Promoter analysis revealed that cis-acting elements were predominantly associated with stress and hormone responses, as well as developmental regulation. Expression correlation heatmaps indicated that genes such as PcUGT065 and PcUGT130 showed strong correlation with resveratrol, emodin, and their glycosylated derivatives. The qRT-PCR results further confirmed the reliability of transcriptome-based expression patterns. Conclusion The UGT gene family in P. cuspidatum exhibits clear structural conservation along with distinct expression divergence. Several members may participate in the modification of resveratrol and emodin. This study provides a theoretical basis for future investigations into the biosynthetic mechanisms of active metabolites in P. cuspidatum and offers insights for its molecular breeding.

Objective This study aimed to comprehensively identify the key genes involved in the biosynthesis of spinosin and jujuboside A. Methods Ziziphi Spinosae Semen samples at green fruit and mature stages were selected as experimental materials to construct transcriptomic and metabolomic datasets. Key candidate genes associated with the spinosin and jujuboside A biosynthesis pathways were systematically analyzed through functional annotation and differential expression gene analysis. Results Metabolomic profiling detected 1 646 metabolites, while transcriptomic sequencing and functional annotation identified 7 316 differentially expressed genes. Results revealed that spinosin was relatively enriched during the green fruit stage of Ziziphi Spinosae Semen, whereas jujuboside A accumulated predominantly at the mature stage. Through phylogenetic and heatmap analyses, 50 key candidate genes were screened, including 33 UGTs, 12 OMTs, two OSCs, and three CYP450s, which are hypothesized to participate in the downstream biosynthesis of spinosin and jujuboside A. Conclusion This work systematically deciphers and proposes biosynthetic pathways for these components, laying a foundation for subsequent functional gene validation. It advances molecular biology research on Ziziphi Spinosae Semen bioactive compounds and provides novel insights for the development and utilization of traditional Chinese medicine resources.

Objective To identify key bacterial taxa associated with saikosaponins content. Methods Rhizosphere soil, root surface soil, and root samples of Bupleurum chinense, B. falcatum, and B. scorzonerifolium were collected. Total DNA was extracted for metagenomic analysis, and UPLC-MS was used to determine the contents of saikosaponin A (SSA), saikosaponin B₂(SSB₂), saikosaponin B₄ (SSB₄), saikosaponin C (SSC), saikosaponin D (SSD), saikosaponin E (SSE), and saikosaponin F (SSF) in the roots. Pearson correlation analysis was then employed to identify significant relationships between these medicinal components and the dominant bacterial species. Results SSD exhibited the highest content among the seven saikosaponins analyzed, with average concentrations of 217.5 μg/g in B. chinense, 116.75 μg/g in B. falcatum, and 139.7 μg/g in B. scorzonerifolium. B. falcatum had the lowest content of SSE and SSF. Metagenomic sequencing identified a total of 5 440 bacterial OTUs. The numbers of unique OTUs in the root surface, rhizosphere, and endophytic compartments were 127, 126, and 110 for B. chinense; 91, 74, and 69 for B. falcatum; and 43, 137, and 126 for B. scorzonerifolium, respectively. Azotobacter chroococcum was dominant in the rhizosphere of B. chinense and B. scorzonerifolium, whereas Streptomyces was the core taxon in the rhizosphere of B. falcatum. Klebsiella sp. and Pseudomonas were significantly enriched in the root surface and endophytic niches of B. chinense and B. falcatum, respectively. The Klebsiella sp., Cellulomonas sp., and Azotobacter chroococcum were also a highly significant positive correlated with the contents of SSA, SSB₂, SSB₄, and SSD, among the correlation network analysis. Conclusion This study revealed that Bupleurum genotype might drive saikosaponins accumulation by niche construction of specific microbial communities.

Objective Toestablish a scientific and reasonable quality evaluation and grading standard for Armeniacae Semen Amarum (ASA). Methods Taking 32 batches of dried mature seeds of Prunus armeniaca as the research objects, Their morphological parameters (longitudinal diameter, transverse diameter, thickness diameter, kernel shape index), kernel dry weight, hardness, color values (L^*、a^*、b^*、E^*_ab), odor response values, and amygdalin content were determined. Grade classification was performed using the quality constant method,and the correlations between various indicators and quality grades were investigated through correlation analysis, partial least squares-discriminant analysis (PLS-DA), and regression analysis. Results The quality constant A of the 32 batches of ASA kernels ranged from 1.04 to 3.15, Based on the A value, they could be classified into selected grade (six batches) and mixed grade (26 batches). Amygdalin content was significantly positively correlated with hardness and b^* value (P < 0.05), and the quality constant A was extremely significantly positively correlated with dry kernel weight, transverse diameter, hardness, and amygdalin content (P < 0.01). The PLS-DA model could effectively distinguish ASA of different grades, and amygdalin content and quality constant A were identified as the key variables for grading. Regression analysis showed that hardness could explain 20.0% of the variation in amygdalin content, while hardness and transverse diameter together explained 60.10% of the variation in the quality constant. Conclusion The evaluation system constructed in this study based on appearance characteristics, intrinsic components, and quality constant, which helps standardize the market order of ASA, ensure the safety and efficacy of clinical medication. It is of great significance for promoting the standardized development of ASA industry and can provide a scientific basis for the quality evaluation and market grading of ASA.

Objective To investigate the spatiotemporal distribution characteristics of kaempferol-3-O-rutinoside and ellagic acid, the medicinal marker components of Rubus chingii, and optimize the processing technology to improve their contents based on the findings. Methods Matrix-assisted laser desorption/ionization time-of-flight imaging mass spectrometry (MALDI-TOF IMS) was used for imaging analysis of R. chingii fruits, and high-performance liquid chromatography (HPLC) was employed for quantitative determination of the marker components in fresh fruits and medicinal materials processed by different technologies. Results Kaempferol-3-O-rutinoside was mainly distributed in the outer layer of the fruit, while ellagic acid and its precursors were enriched in the receptacle. Both components exhibited the highest content in green fruits and gradually decreased with fruit ripening. Compared with oven-drying, the sun-drying process significantly increased ellagic acid content by 68.71% but reduced kaempferol-3-O-rutinoside content by 41.30%. Drying after steam moistening at 120 ℃ for 30 min followed by drying effectively improved ellagic acid content without significant negative impacts on kaempferol-3-O-rutinoside content or the appearance of medicinal materials. Conclusion The tissue-specific distribution of the marker components in R. chingii is a key factor affecting their content changes during processing. Timely harvesting of green fruits and optimization of processing technology (short-time steam moistening) can synergistically improve the quality of medicinal materials.