Objective To analyze variations in HPLC fingerprint profiles, characteristic constituents, and energy-related components during the preparation of Ejiɑo (Asini Corii Colla, ACC) decoction pieces, intermediates, and formulated granules. To investigate the transfer patterns of their critical quality attributes. And to establish a multidimensional quality control methodology tailored to the characteristics of ACC formulated granules. Methods HPLC fingerprint chromatograms for ACC decoction pieces, intermediates, and formulated granules were established using an indophenol post-column derivatisation-amino acid analyser method. Common peaks were assigned using reference substances. The quality variations across ten batches of ACC samples were analyzed by combining the fingerprint data with chemometric techniques. Furthermore, a method for the simultaneous quantification of six characteristic amino acids (aspartic acid, glutamate, glycine, alanine, arginine, proline) was developed. Conventional methods were employed to determine energy components, including protein and fat content. The production processes of ACC formulated granules were evaluated multi-dimensionally to construct a dynamic quality monitoring framework. Results Fingerprint chromatograms were established for ten batches of ACC, encompassing its decoction pieces, intermediates, and formulated granules. A total of 21 common peaks were identified, and the similarity among all batches were ≥ 0.990. The average transfer rate of the primary characteristic amino acids was 75.74%—92.09% from the decoction pieces to the intermediates, and 76.63%—94.84% from the intermediates to the formulated granules. The average transfer rate of energy components was 96.75% from the decoction pieces to the intermediates, and the average transfer rate of energy components was 43.26% from the intermediates to the formulated granules. Conclusion The indophenol post-column derivatization‑amino acid analyse method was used to construct HPLC fingerprints, determine multiple characteristic components, and measure energy components simultaneously, realizing a multidimensional evaluation of Ejiao decoction pieces‑intermediates‑finished products. A dynamic quality control method for the whole production process of Ejiao formula granules was established, providing a reference for its further research and development.

Objective To study the alkaloids from the fruit of Lycium chinense and their hepatoprotective activity. Methods The compounds were isolated and purified by silica gel column chromatography, D101 macroporous resin column chromatography, ODS column chromatography, and semi-preparative HPLC. Their structures were identified by¹H-NMR, ¹³C-NMR and mass spectrometry. The acetaminophen (APAP)-induced injury of human liver cancer HepG2 cells model was used to evaluate the hepatoprotective activity of these compounds. Results Sixteen alkaloids were isolated from the ethanol extract of fruit of L. chinense. Their structures were identified as lyciumamide P (1), lyciumamide Q (2), lyciumamide R (3), N-cis-grossamide (4), cannabisin E (5), cannabisin F (6), cannabisin G (7), cannabisin H (8), heliotropamide (9), N-malonyl-tryptophan (10), N-acetyltryptophan methyl ester (11), equisetinine A (12), nicotinamide (13), methyl-5-hydroxy-2-pyridinecarboxylate (14), thymidine (15), N¹,N¹⁰-di-dihydrocaffeoylspermidine (16). Conclusion Compounds 1—16 were isolated from L. chinense for the first time. Compounds 12, 13, 15 and 16 were isolated from Lycium for the first time. Compounds 5—7 and 10—16 showed significant hepatoprotective activity against APAP-induced injury of human liver cancer HepG2 cells at 10 μmol/L.

Objective To study on the chemical constituents from Dendrobium huoshanense. Methods The chemical constituents were separated and purified by silica gel, Sephadex LH-20, semi-prepared HPLC and other chromatography techniques. Their structures were elucidated by MS, 1D and 2D NMR spectroscopic data. Results Eleven compounds (1—11) were isolated, and were identified as trans-ferulic acid nonadecyl ester (1), trans-p-hydroxycinnamic acid nonadecyl ester (2), 2,4,7-trihydroxy-9,10-dihydrophenanthrene (3), naringenin (4), 5-hydroxy-3,4′-dimethoxybibenzyl (5), 5-hydroxy-3-methoxybibenzyl (6), dendrogratiol A (7), amoenylin (8), methyl ferulate (9), protocatechuic acid (10), p-hydroxybenzaldehyde (11). At a concentration of 100 μmol/L, compounds 4 and 7 exhibited inhibitory rates of 39.0% and 38.3% against tyrosinase, respectively. Conclusion Compounds 1 and 2 are new compounds, named dendrohuoshanin A and dendrohuoshanin B. Compounds 3, 5, 7—9 were isolated for the first time from this plant. Compound 3 was the first to be separated and purified through phytochemical methods from this plant. Compounds 1, 2, and 9 belong to simple phenylpropanoids, compound 3 is a dihydrophenanthrene, compound 4 is a dihydroflavone, and compounds 5—8 are bibenzyls. Compounds 4 and 7 show potential skin-whitening effects.

Objective Chemical composition analysis of Carthamus tinctorius injection and screening of allergenic components using molecular docking technology. Methods High performance liquid chromatography-ion trap-time-of-flight high resolution mass spectrometry (HPLC-IT-TOF-MS) was used to identify the chemical constituents of Safflower Injection, and molecular docking technology was used to further screen potential allergens.Results A total of 40 compounds were identified from the Carthamus tinctorius injection, including 26 chalcone C-glycosides, eight flavonoids, three alkaloids, and three other types of compounds. All compounds were identified in negative ion mode. These compounds were linked to human serum albumin (HSA), Mas-related G protein-coupled receptor X2 (MRGPRX2) and Ras homolog gene family member A (RhoA), among which six compounds docked with HAS and nine compounds docked with MRGPRX2. It was found that 6-hydroxykaempferol compounds and safflower quinone compounds were the main allergic components in safflower injection. Conclusion A method for allergen screening combining liquid chromatography-mass spectrometry and molecular docking was established. A total of 40 compounds were identified from Safflower Injection, and 6-hydroxykaempferols and safflower quinones were identified as potential allergens. This study provides important reference and data for allergen screening and sensitization mechanism research of Safflower Injection.

As the core carrier of the theoretical system of traditional Chinese medicine (TCM), classic famous prescriptions play a vital role in the prevention and treatment of chronic diseases and major diseases. However, their secondary development still faces numerous technical bottlenecks, such as limitations caused by insufficient data standardization and inadequate evidence chains in evidence-based medicine, which restrict the transformation process from clinical practice to industrialization. Artificial intelligence (AI) has promoted the shift of traditional empirical medicine to a new research paradigm of “algorithm-model-data-scenario-application”, providing a brand-new perspective for data mining, prescription optimization, and new drug research and development of classic famous prescriptions, and empowering the modernization of TCM. This article systematically investigates how AI is reshaping the research paradigm of classic famous prescriptions, proposing an integrated framework centered on intelligent data mining, in-depth mechanism analysis, and precise efficacy evaluation. Firstly, it elaborates on the foundational basis of key technologies such as machine learning and their applicable scenarios. Secondly, from application dimensions including intelligent screening of candidate prescriptions, analysis of the material basis for efficacy, and in-depth exploration of mechanisms of action, it summarizes the research progress and application prospects of the integration of AI and classic famous prescriptions. Finally, it analyzes challenges such as data heterogeneity, lack of standards, and poor adaptability between models and TCM theories, and proposes targeted solutions, aiming to provide references for AI empowering the secondary development of classic famous prescriptions.

Objective To investigate the chemical constituents of the fruits of Phyllanthus emblica and evaluate their antioxidant and hypoglycemic activities. Methods Compounds were isolated and purified using silica gel and reversed-phase silica gel RP-18 column chromatography, followed with semi-preparative high-performance liquid chromatography (HPLC). The chemical structures were elucidated based on physicochemical properties, together with UV, NMR, HR-ESI-MS, and X-ray single-crystal diffraction methods, and comparison with literature data. Antioxidant and hypoglycemic activities were assessed by DPPH free radical scavenging and α-glucosidase inhibitory assays. Results Nine compounds were isolated from the ethyl acetate fraction of the methanol extract of P. emblica fruits and identified as 1-(2-aminobenzofuran-3-yl)-2-(2-methoxyphenyl)ethan-1-one (1), methyl dioxindole-3-acetate (2), aurantiamide (3), phyllaemblicin G3 (4), mucic acid dimethyl ester 2-O-gallate (5), chebulic acid trimethyl ester (6), 3,4,8,9,10-pentahydroxydibenzo[b,d]pyran-6-one (7), ellagic acid (8), and methyl 1-O-benzoyl-3-α- glucuronosyl glycerol (9), respectively. The bioassay showed that compounds 5-8 exhibited significant DPPH radical scavenging capacity (scavenging rates = 86.59% − 90.75%), and 1, 7, and 8 displayed inhibitory activity against α-glucosidase with IC₅₀ values ranging from 1.44 to 33.06 μmol/L. Among them, compound 7 showed the strongest inhibition, which was superior to the positive control quercetin (IC₅₀ = 4.96 μmol/L). Conclusion Compound 1 is a new alkaloid, named emblicine A, while 2, 3, and 9 are reported from the titled plant for the first time. It is the first study to identify alkaloid with hypoglycemic activity from P. emblica, providing a scientific basis for its traditional use in glycemic control and antioxidant defense.

In recent years, protoplast technology has widely applied in the fields of plant genetic transformation, breeding, and plant regeneration. Related research on model plants (such as tobacco and Arabidopsis thaliana) has been in-depth, and its application in crops like forage grass, rice, and tomatoes has also become more and more mature. With the development of the economy and the increase in health demands, the market demand for medicinal plants has been continuously growing. However, the research on their breeding and genetic transformation is still insufficient, and protoplast technology can just provide a new path for this. This paper focuses on the preparation and isolation techniques of protoplasts of medicinal plants and their application scenarios, reviews their research status and challenges, and provides a reference for in-depth research on protoplasts of medicinal plants in fields such as genetic transformation, variety improvement, and plant regeneration.

Ferns exhibit a wide variety of species in our country, with some possessing significant medicinal value. However, the overall development of medicinal fern research is insufficient, and the status of resources remains unclear. This article summarizes the current state of medicinal ferns in our country, as well as the research progress on artificial cultivation and propagation techniques, thoroughly analyzes the impacts of soil substrates, light, temperature, diseases and insects pests on the growth of medicinal ferns and the accumulation of their medicinal components, and systematically reviews the current status of processing methods and product research and development of ferns. The standardized cultivation and in-depth utilization of medicinal ferns warrant further attention, as they offer new prospects for the development and utilization of traditional Chinese medicine resources.

Objective To provide theoretical guidance for the phylogenetics, genetic diversity, and species identification of Dioscorea by integrating chloroplast genomics, codon usage bias, DNA barcoding, and machine learning technologies. Methods The chloroplast gene structures of 11 plant species were compared via IRscope and a phylogenetic tree was constructed. Codon usage bias was analyzed using tools such as CodonW and CUSP. Dioscorea materials were collected, and DNA barcode sequences were amplified and sequenced. Molecular identification was performed based on the maturase K gene (matK), photosystem b a protein gene-transfer RNA-Histidine intergenic spacer (psbA-trnH), and ribulose-bisphosphate carboxylase/oxygenase large subunit gene (rbcL) barcodes using machine learning algorithms. Results The chloroplast genomes of Dioscorea were found to be conserved and stable. Codon usage showed a significant A/T bias, with the third codon position favoring A/U endings. Natural selection was the primary factor influencing codon bias, and the common optimal codons identified were GGA and UCA. All three barcodes successfully discriminated species. Single-barcode identification using the BLOG algorithm achieved 100% success rate, while the SMO and NaïveBayes classifiers in WEKA demonstrated high identification accuracy. Conclusion The chloroplast genome of Dioscorea is conserved, and natural selection dominates its codon usage pattern. This study provides a basis and guidance for research on gene expression regulation, species identification, and resource conservation of Dioscorea.

Objective To explore “state and target” pathological mechanism of sepsis by comprehensively analyzing the single-cell transcriptomics and transcriptomic datasets related to sepsis, construct the prognostic model for “state and target” of sepsis, and explore potential target Chinese medicines and active ingredients. Methods Differential expression gene analysis and venn diagram analysis were used to identify “state and target” of sepsis related genes. Key module genes were obtained using the random walk algorithm through the connectivity of the protein-protein interaction (PPI) network. Gene ontology (GO) biological process (BP) and Kyoto encyclopedia of genes and genomes (KEGG) were used to analyze the biological functions of key module genes. To explore the role of “state and target” of sepsis related genes by single-cell transcriptome analysis. A prognostic model for “state and target” of sepsis was constructed using gene expression data and clinical survival data from sepsis patients. The expression levels of prognostic genes for “state and target” of sepsis were validated by constructing sepsis mouse model and real-time quantitative polymerase chain reaction (RT-PCR). Through reverse network pharmacology, potential targeted traditional Chinese medicines and their active components were screened, and molecular docking was used to verify the binding performance between active ingredients and prognostic targets. Results A total of 70 genes related to “toxic state” of sepsis, 67 genes related to “stasis state” of sepsis and 54 genes related to “deficiency state” of sepsis were obtained. The key module genes of “toxic state” of sepsis were closely related to inflammation, the key module genes of “stasis state” of sepsis were closely related to coagulation, and the key module genes of “deficiency state” of sepsis were closely related to cell homeostasis. AUCell score showed that monocyte had the highest score for “toxic state” and “deficiency state” of sepsis. Platelet had the highest score for “stasis state” of sepsis. The activities of metabolic and inflammatory related genes and pathways were significantly up-regulated in monocytes with high “toxic state” score. Platelet activation and coagulation/thrombosis related genes and pathways were significantly up-regulated in platelet with high “stasis state” score. Compared with control group, there were a large number of down-regulated genes in monocytes of sepsis patients, which were involved in antigen presentation, cell energy metabolism, cell cycle, protein synthesis, etc. The prognostic model for “state and target” of sepsis constructed based on eight targets [interleukin-1 receptor type 2 (IL1R2), ADP ribosylation factor like GTPase 4C (ARL4C), cytochrome C oxidase subunit 7B (COX7B), eukaryotic translation initiation factor 2 subunit gamma (EIF2S3), immediate early response 3 (IER3), LSM1 homolog (LSM1), paired basic amino acid cleaving enzyme (FURIN) and ankyrin repeat domain-containing protein 9 (ANKRD9)] had good prognostic predictive ability, and the expression levels of these genes were validated using animal experiments and RT-PCR. Based on the bioinformatics analysis tool for molecular mechanism of traditional Chinese medicine (BATMAN-TCM) database and database of constituents absorbed into the blood and metabolites of traditional Chinese medicine (DCABM-TCM), reverse network pharmacology analysis had screened multiple Chinese herbal medicines with effects of clearing heat and detoxifying, activating blood and resolving stasis, and reinforcing healthy qi and their active ingredients entering the blood. Molecular docking showed that representative active ingredients have good binding properties with prognostic targets. Conclusion Activation of inflammatory response driven by monocyte metabolic reprogramming may be the main pathological mechanism of “toxic state” of sepsis. Platelet activation-coagulation/thrombosis may be the main pathological mechanism of “stasis state” of sepsis. Monocyte dysfunction-immunosuppression may be the main pathological mechanism of “deficiency state” of sepsis. A model based on eight genes can serve as a risk prediction model for the prognosis of “state and target” of sepsis.