A new iridoid was isolated from the Tabebuia avellanedae, its anti-myocardial injury activity was determined, and its mechanisms underlying inhibition of inflammation, regulation of oxidative stress and inhibition of apoptosis were explored. The dried inner bark of the Tabebuia avellanedae was extracted with boiling water, separated by liquid-liquid extraction, and purified by silica gel/ODS/Sephadex LH-20 column chromatography coupled with high-performance liquid chromatography (HPLC) to obtain avelladoid Ⅰ (Avd Ⅰ). The structure of Avd Ⅰ was identified by nuclear magnetic resonance spectroscopy (NMR) and high-resolution mass spectrometry (HRMS). Cardiomyocyte injury model was established by 1 μg·mL^-1 doxorubicin. After treatment with 1-40 μmol·L^-1 of Avd Ⅰ, the cell viability was evaluated by methyl thiazole tetrazolium (MTT) assay, and the lactate dehydrogenase (LDH) was measured. The inflammatory factor levels of interleukin-6 (IL-6), interleukin-1β (IL-1β) and tumor necrosis factor-α (TNF-α) as well as the oxidative stress levels of lactate dehydrogenase (LDH), superoxide dismutase (SOD), malondialdehyde (MDA) and glutathione peroxidase (GSH-Px) were detected. DCFH-DA staining was employed to observe the level of reactive oxygen species (ROS), AnnexinV-FITC/PI double stainings were performed to detect the apoptosis level, JC-1 single staining was used to measure the mitochondrial membrane potential level, and the Incell-Western assay was conducted to determine the apoptosis-related protein expression levels. The results showed that the cardiomyocyte injury was improved by 1-20 μmol·L^-1 of Avd Ⅰ, and the IL-6 and IL-1β levels were decreased to near normal cell levels by 1 μmol·L^-1 Avd Ⅰ. The ROS level was strongly reduced and the SOD level was highly increased by 1 μmol·L^-1 Avd Ⅰ. In addition, 1 μmol·L^-1 Avd Ⅰ significantly decreased the apoptosis level, the B-cell lymphoma-2 associated X protein (Bax)/B-cell lymphoma-2 (Bcl-2) ratio and the cleaved cysteinyl aspartate specific proteinase 3 (cleaved caspase 3)/cysteinyl aspartate specific proteinase 3 (caspase 3) ratio. Therefore, Avd Ⅰ could stimulate the cardiomyocyte proliferation, reduce the LDH level and inhibit inflammation levels through regulating the mitochondrial apoptotic pathway.

A precursor ion selection (PIS) based ultra high performance liquid chromatography-quadrupole time of flight mass spectrometry (UHPLC-Q-TOF-MS) analytical method was used to screen the chemical components in Jiawei Dingzhi pills (JWDZP) comprehensively and rapidly. To compile the components of the compound medicine, a total of 1 921 components were found utilizing online databases and literature. After verifying the sources, unifying the component names, merging the multi-flavor attributed components, and removing the weak polar molecules, 450 components were successfully retained. The Acquity UPLC HSS T3 column (100 mm × 2.1 mm, 1.8 μm) was used, with a 0.1% formic acid water (A)-acetonitrile (B) as the mobile phase. The flow rate was 0.35 mL·min^-1, the column temperature was 35 ℃, and an electrospray ion source was used. Data was collected with the PIS strategy in both positive and negative ion modes. Compounds were screened through matching accurate molecular weight of the database, and identified according to MS/MS data (characteristic fragment ions and neutral loss), with comparison of reference. Some compounds were confirmed using standard products. A total of 176 compounds were screened out in the extract of JWDZP, among which 26 compounds were confirmed by standard products. These compounds include 96 components from the sovereign drug, and 34 coefflux components with low ion intensity. The PIS-UHPLC-Q-TOF-MS/MS method established in this study can quickly and comprehensively screen the chemical components of JWDZP, which enhanced the screening rate of components with co-elution compounds of low ion intensities and provided a basis for the study of the material foundation of JWDZP.

Exploring the action targets (groups) of traditional Chinese medicine (TCM) is an important proposition to promote the innovation and development of TCM, but it has attracted a lot of attention as to whether it is related to the efficacy or the disease. Our team found that the metabolomic signature molecules in the development of diabetes mellitus (DM) were significantly associated with the clinical efficacy of Yuquan Pill through a large clinical sample study. Taking this as a clue, our team intends to expand the information on the omics features of DM development, and discover the key targets (groups) and their lead compounds for the hypoglycemic effect of Yuquan Pill. The project includes: ① Based on the retrospective clinical trials, using omics technology integrated with generative artificial intelligence, mining the characteristic information of proteome and microbiome, forming driving factors together with metabolome characteristic molecules, and characterizing the molecular trajectories of diabetes evolution and their interference by Yuquan Pill; ② Taking the evolving molecular trajectories as a link and pointer, using anthropomorphic modeling and molecular biology techniques such as chemical proteomics to discover the key targets (groups) of Yuquan Pill's hypoglycemic effect, with the prospective clinical samples for validation; ③ Evaluate the overall response of key targets (groups) using graph neural network technology, and search for drug-derived/endogenous lead compounds with proven clinical pathologies and clear mechanisms of action, so as to provide a new paradigm and technology for the discovery of complex active ingredient targets (groups) of TCM that are related to their clinical efficacy, as well as for the discovery of innovative medicines.

In the present study, the antibacterial spectrum of turmeric extract was analyzed by measuring the minimum inhibitory concentration (MIC), and the antibacterial mechanism of turmeric extract was elaborated by determining its effects on the permeability and integrity of the cytoplasmic membrane, energy metabolism, and the morphology of the tested bacteria (Bacillus subtilis) with the highest susceptibility to the extract. The results showed that turmeric extract possessed broad-spectrum antibacterial activity against Gram-positive, Gram-negative bacteria and fungi, especially against Bacillus subtilis, with the MIC of 0.5 mg·mL^-1. Turmeric extract disrupted the liposome membrane and released calcein encapsulated within it. The permeability of the bacterial cell membrane was increased, leading to leakage of intracellular K⁺, Ca²⁺and cell wall proteins, and the integrity of the cell membrane was broken down, causing leakage of intracellular proteins and polysaccharides. Scanning electron microscope observation confirmed that the bacteria treated with turmeric extract was severely deformed. Simultaneously, cellular energy metabolism was affected, resulting in a significant reduction in the intracellular ATP content and ATPase activity in bacteria. In summary, the antibacterial mode of turmeric extract is closely related to its disruption of bacterial membrane structure.

Gegen Qinlian decoction has a wide range of clinical applications. However, there is a lack of systematic quality evaluation methods to ensure the safety and effectiveness of Gegen Qinlian decoction in clinical use. The UHPLC fingerprint and multi-component determination method of Gegen Qinlian decoction were established to provide scientific basis for the quality control and evaluation of Gegen Qinlian decoction. The chromatography was performed on a ZORBAX Eclipse Plus-C₁₈ column (150 mm × 4.6 mm, 3.5 μm) with mobile phase consisted of acetonitrile (A) - 20 mmol·L^-1 ammonium acetate (containing 0.8% acetic acid and 0.5% triethylamine) (B) and gradient elution at a flow rate of 1.0 mL·min^-1. The column temperature was 25 ℃, the detection wavelength was 260 nm, the fingerprint of 10 batches of Gegen Qinlian decoction was determined, and the similarity evaluation system of TCM chromatographic fingerprint was used for comprehensive analysis, and 9 components were quantitatively analyzed. In the fingerprint study of Gegen Qinlian decoction, a total of 18 peaks were obtained, 12 of which were identified by reference substances. Moreover, the similarity of 10 batches of Gegen Qinlian decoction was good, and all of them were greater than 0.99. In the multi-component quantitative analysis, the linear relationship between the nine components and the peak area was good (r ≥ 0.999) in the corresponding mass concentration range. The average recovery rate was 94.4%-100.3%, and the RSD was 0.1%-1.4%. The fingerprint of Gegen Qinlian decoction was studied under the same wavelength, and the content of 9 main components were determined by our established method. The method has high sensitivity and strong specificity, which provided a comprehensive scientific basis for the comprehensive evaluation of the quality of Gegen Qinlian decoction.

The anti-inflammatory effect of simplified Zhiqin Decoction was observed by using lipopolysaccharide (LPS)-induced inflammation mouse model. The main chemical constituents and the main mechanism of action of simplified Zhiqin Decoction were predicted by network pharmacology. Animal experiments verified the anti-inflammatory mechanism of simplified Zhiqin Decoction (this experiment was approved by the Animal Experiment Ethics Committee of Southwest University, approval number: IACUC-20210825-02). Simplifying Zhiqin Decoction has a significant anti-inflammatory effect on inflammatory mice, can significantly improve the overall macro shape of mice, reduce body temperature, water intake, increase the number of autonomous activities; alleviate liver, lung, spleen, thymus inflammation and pathological damage; decrease tumor necrosis factor-α (TNF-α), interleukin (IL)-1β and IL-6, nitric oxide (NO), prostaglandin E₂ (PGE₂) content in serum and urine. The contents of serum immune factors IgG, IgA and IgM were increased. Network pharmacology predicted 66 potential anti-inflammatory active components of simplified Zhiqin Decoction involving 132 inflammatory targets, and the key anti-inflammatory signaling pathway involved PI3K/AKT, TNF, JAK-STAT, etc. Animal experiments show that simplified Zhiqin Decoction can significantly reduce the expression of JAK2/STAT-PI3K/AKT-NF-κB-TNF signaling pathway related proteins in lung tissue of inflammatory mice. The results of this study showed that simplified Zhiqin Decoction had significant anti-inflammatory effects, and its main anti-inflammatory components were quercetin, β-sitosterol, kaempferol, wogonin, stigmasterol, luteolin, neobaicalein, etc. The main mechanism of its anti-inflammatory action is that it significantly inhibits the expression of JAK2/STAT-PI3K/AKT-NF-κB-TNF signaling pathway protein.

The column chromatography and semi-preparative liquid phase chromatography with several chromatographic packing materials, including macroporous adsorbent resin, silica gel, ODS, and Sephadex LH-20, were used for the separation and purification of n-butanol-soluble portion of ethanol extract of Leonurus japonicus Houtt. The structures of isolates were identified by HR-MS, IR, NMR, and acid hydrolysis reaction. Six phenylethanol glycosides were obtained from L. japonicus and identified as leonoside G (1), leonoside E (2), leonoside B (3), leonoside F (4), cistanoside G (5), and salidroside (6). Compound 1 is a new phenylethanol glycoside.

This experiment aims to study the taste-masking effects of different kinds of corrigent used individually and in combination on ibuprofen oral solution, in order to optimize the taste-masking formulation. Firstly, a wide range of corrigent and the mass fractions were extensively screened using electronic tongue technology. Subsequently, a combination of sensory evaluation, analytic hierarchy process (AHP)-fuzzy mathematics evaluation, and Box-Behnken experimental design were employed to comprehensively assess the taste-masking effects of different combinations of corrigent on ibuprofen oral solution, optimize the taste-masking formulation, and validate the results. The study received ethical approval from the Review Committee of the Beijing University of Chinese Medicine (ethical code: 2024BZYLL0102). The results showed that corrigent fractions and types were screened separately through single-factor experiments. Subsequently, a Box-Behnken response surface design combined with AHP and fuzzy mathematics evaluation was used to fit a functional model: Z = 688.310 11 - 3 023.722 22X₁ - 11.477 00X₂ + 62.721 67X₃ + 14.600 00X₁X₂ - 179.666 67X₁X₃ - 3.152 00X₂X₃ + 4 031.111 11X₁² + 0.525 28X₂² + 9.772 00X₃². This model is stable and reliable, determining the optimal taste-masking formulation to be 3.9 g·L^-1 of stevioside, 100 g L^-1 of xylitol, and 30 g L^-1 of methyl-β-cyclodextrin. The comprehensive score of the verification test is 88.14, with a relative RSD of 0.39%, indicating the feasibility of this model. This study achieved the improvement of the taste of ibuprofen oral solution through a combination of objective and subjective methods. Three types of corrigent were identified for enhancing drug taste, leading to the selection of the optimal taste-masking formulation for ibuprofen oral solution. This significantly enhanced the taste of the original formulation, improved patient compliance, and offered a new approach to mitigating the undesirable taste of formulations.

Naturally derived metabolites are valuable resources for drug research and development, and play an important role in the treatment of diseases. As the "second genome" of the body, gut microbiota is rich in metabolic enzymes, which interacts with external substances such as drugs, thus affecting the progression of diseases. This article summarizes the interaction between gut microbiota-producing enzymes and natural medicines, and focuses on the impact of this interaction on disease progression, hoping to provide new ideas for the development and pharmacological mechanism of natural medicines.

Computational biology is a branch of biology that develops and applies data analysis and theoretical methods, mathematical modeling, and computer simulation techniques for the study of biological, behavioral, and social group systems. In recent years, computational biology has received increasing attention, mainly because high-throughput technologies have greatly improved the ability to generate data. The generation of massive computational data drives the increasing computing power of devices, and the complexity and heterogeneity of data also require more systematic analysis methods, which jointly promote the development of computational biology. With the development of the era of big data, the data of biological research and experiments has increased exponentially. A single observation and experiment can no longer support high-complexity data, and computational biology has become an important and powerful tool for drug research. At present, computational biology has been applied in many fields, such as peptide synthesis and small molecule design, virtual screening, protein structure and protein interaction prediction, database construction, bioactive substance prediction and drug release monitoring, so as to provide assistance for multiple drug research processes such as drug target prediction, drug design, drug screening and drug clinical application. Computational biology has become a more time- and labor-saving "arm" than traditional drug research tools, and at the same time, the demand for drug research and development continues to promote the development of computational biology. The two complement each other and develop together, and computational biology has become an integral part of drug research.