OBJECTIVE To investigate the improvement mechanism of hyperoside （HYP） on non-alcoholic fatty liver disease （NAFLD）. METHODS Male C57BL/6 mice were randomly divided into normal （NFD） group， model （HFD） group and HYP group， with 8 mice in each group. Except for NFD group， the mice in other groups were fed with HF60 high-fat diet to establish NAFLD model； HYP group was simultaneously given HYP 100 mg/kg intragastrically every day， for 16 consecutive weeks. The body weight and liver weight of mice in each group were recorded 16 h after the last medication； the histopathological changes and lipid accumulation in the liver were observed， and the contents of triglyceride （TAG） in liver tissue and serum contents of TAG， aspartate transaminase （AST） and alanine transaminase （ALT） were measured； LC-MS/MS method was adopted to detect lipid changes in the liver tissue of mice for lipidomics analysis， and protein expressions of lipid synthesis-associated proteins peroxisome proliferator-activated receptor α （PPARα） were also tested. Human hepatocellular carcinoma cell line HepG2 was divided into normal control group， model group， HYP low-concentration group （50 μmol/L）， HYP high-concentration group （100 μmol/L）， HYP low-concentration+GW6471 （PPARαinhibitor） group， and HYP high-concentration+GW6471 group. Except for normal control group， the remaining cells were induced with oleic acid and palmitic acid to establish a high-fat cell model. The accumulation of lipid droplets in each group of cells was observed， and the TAG content was detected. RESULTS Compared with HFD group， HYP group exhibited significant reductions in liver fat vacuoles， lipid accumulation， liver weight， and TAG content in liver tissue， as well as serum contents of ALT， AST and TAG （P＜0.05）. Additionally， the expression of PPARα protein in liver tissue was significantly increased （P＜0.05）， and the pathological morphological changes associated with NAFLD were alleviated. Lipidomic analysis revealed that HYP significantly reduced the levels of TAG， diacylglycerol and other lipids in the liver. Compared with model group， cellular lipid droplet accumulation and TAG content decreased significantly in HYP low- and high-concentration groups （P＜0.05）； GW6471 could significantly reverse the improvement effect of HYP on above indicators （P＜0.05）. CONCLUSIONS HYP can effectively ameliorate NAFLD induced by a high-fat diet in mice， and the mechanism may be related to the activation of PPARα to regulate hepatic lipid synthesis.

ObjectiveTo evaluate the efficacy of Shexiang Baoxinwan in treating stable angina pectoris with Qi stagnation and blood stasis syndrome in patients with coronary artery disease （CAD） complicated with anxiety and depression and explore its underlying mechanisms. MethodsThis study employed a randomized， double-blind， and placebo-controlled clinical trial design. Patients admitted to the hospital were randomly assigned to the observation group and the control group， with 52 patients in each group. Patients in the observation and control groups received Shexiang Baoxinwan and placebo， respectively， both in combination with conventional Western medication. The dose was 45.0 mg， three times daily， for a total duration of eight weeks. The primary outcome was the Seattle Angina Questionnaire （SAQ） scores before and after treatment. Secondary outcomes included changes in traditional Chinese medicine （TCM） syndrome score， the patient health questionnaire-9 （PHQ-9）， generalized anxiety disorder-7 （GAD-7）， inflammatory markers ［interleukin-18 （IL-18）， interleukin-10 （IL-10）， tumor necrosis factor-alpha （TNF-α）， CD40， etc.］， monoamine neurotransmitters ［e.g.， dopamine （DA）］， vascular endothelial function markers ［e.g.， endothelin-1（ET-1）］， adipokines， and ischemia-modified albumin （IMA）. Adverse reactions were also recorded. ResultsA total of 92 patients completed the study， with 44 in the observation group and 48 in the control group. Compared with baseline， both groups showed significant decreases in PHQ-9， GAD-7， and TCM syndrome scores following treatment （P<0.05）， along with a significant increase in SAQ scores （P<0.05）. In the observation group， DA levels were significantly increased （P<0.05）， while levels of IL-18， TNF-α， CD40， ET-1， and IMA were decreased （P<0.05）. In contrast， the control group exhibited significantly increased CD40 levels （P<0.05）. Compared with the control group after treatment， the observation group showed significant improvements in the SAQ dimensions of physical limitation， angina stability， treatment satisfaction， and disease perception， as well as in TCM syndrome score， PHQ-9 score， IL-18， CD40， ET-1， and IMA （P<0.05）. No adverse reactions were observed in either group during treatment. ConclusionShexiang Baoxinwan can improve anxiety and depression， alleviate angina symptoms， and reduce TCM symptoms of Qi stagnation and blood stasis in CAD patients. The mechanism may involve anti-inflammation， improvement of vascular endothelial function， reduction of IMA， and increase of monoamine neurotransmitter levels.

ObjectiveTo evaluate the efficacy of Shexiang Baoxinwan in treating stable angina pectoris with Qi stagnation and blood stasis syndrome in patients with coronary artery disease （CAD） complicated with anxiety and depression and explore its underlying mechanisms. MethodsThis study employed a randomized， double-blind， and placebo-controlled clinical trial design. Patients admitted to the hospital were randomly assigned to the observation group and the control group， with 52 patients in each group. Patients in the observation and control groups received Shexiang Baoxinwan and placebo， respectively， both in combination with conventional Western medication. The dose was 45.0 mg， three times daily， for a total duration of eight weeks. The primary outcome was the Seattle Angina Questionnaire （SAQ） scores before and after treatment. Secondary outcomes included changes in traditional Chinese medicine （TCM） syndrome score， the patient health questionnaire-9 （PHQ-9）， generalized anxiety disorder-7 （GAD-7）， inflammatory markers ［interleukin-18 （IL-18）， interleukin-10 （IL-10）， tumor necrosis factor-alpha （TNF-α）， CD40， etc.］， monoamine neurotransmitters ［e.g.， dopamine （DA）］， vascular endothelial function markers ［e.g.， endothelin-1（ET-1）］， adipokines， and ischemia-modified albumin （IMA）. Adverse reactions were also recorded. ResultsA total of 92 patients completed the study， with 44 in the observation group and 48 in the control group. Compared with baseline， both groups showed significant decreases in PHQ-9， GAD-7， and TCM syndrome scores following treatment （P<0.05）， along with a significant increase in SAQ scores （P<0.05）. In the observation group， DA levels were significantly increased （P<0.05）， while levels of IL-18， TNF-α， CD40， ET-1， and IMA were decreased （P<0.05）. In contrast， the control group exhibited significantly increased CD40 levels （P<0.05）. Compared with the control group after treatment， the observation group showed significant improvements in the SAQ dimensions of physical limitation， angina stability， treatment satisfaction， and disease perception， as well as in TCM syndrome score， PHQ-9 score， IL-18， CD40， ET-1， and IMA （P<0.05）. No adverse reactions were observed in either group during treatment. ConclusionShexiang Baoxinwan can improve anxiety and depression， alleviate angina symptoms， and reduce TCM symptoms of Qi stagnation and blood stasis in CAD patients. The mechanism may involve anti-inflammation， improvement of vascular endothelial function， reduction of IMA， and increase of monoamine neurotransmitter levels.

This study investigates the effect and underlying mechanism of Guizhi Tongluo Tablets(GZTL) in treating atherosclerosis(AS) in a mouse model. Apolipoprotein E-knockout(ApoE~(-/-)) mice were randomly assigned to the following groups: model, high-, medium-, and low-dose GZTL, and atorvastatin(ATV), and age-matched C57BL/6J mice were selected as the control group. ApoE~(-/-) mice in other groups except the control group were fed with a high-fat diet for the modeling of AS and administrated with corresponding drugs via gavage for 8 weeks. General conditions, signs of blood stasis, and body mass of mice were monitored. Aortic plaques and their stability were assessed by hematoxylin-eosin, Masson, and oil red O staining. Serum levels of total cholesterol(TC), triglycerides(TG), and low-density lipoprotein cholesterol(LDL-C) were measured by biochemical assays, and those of interleukin-1β(IL-1β), tumor necrosis factor-α(TNF-α), and interleukin-6(IL-6) were determined via enzyme-linked immunosorbent assay. Apoptosis was assessed by terminal deoxynucleotidyl transferase dUTP nick end labeling(TUNEL). Single-cell RNA sequencing(scRNA-seq) was employed to analyze the differential expression of CD72hi macrophages(CD72hi-Mφ) in the aortas of AS patients and mice. The immunofluorescence assay was employed to visualize CD72hi-Mφ expression in mouse aortic plaques, and real-time fluorescence quantitative PCR was utilized to determine the mRNA levels of IL-1β, TNF-α, and IL-6 in the aorta. The results demonstrated that compared with the control group, the model group exhibited significant increases in body mass, aortic plaque area proportion, necrotic core area proportion, and lipid deposition, a notable decrease in collagen fiber content, and an increase in apoptosis. Additionally, the model group showcased elevated serum levels of TC, TG, LDL-C, IL-1β, TNF-α, and IL-6, alongside marked upregulations in the mRNA levels of IL-1β, TNF-α, and IL-6 in the aorta. In comparison with the model group, the GZTL groups and the ATV group showed a reduction in body mass, and the medium-and high-dose GZTL groups and the ATV group demonstrated reductions in aortic plaque area proportion, necrotic core area proportion, and lipid deposition, an increase in collagen fiber content, and a decrease in apoptosis. Furthermore, the treatment goups showcased lowered serum levels of TC, TG, LDL-C, IL-1β, TNF-α, and IL-6. The data of scRNA-seq revealed significantly elevated CD72hi-Mφ signaling in carotid plaques of AS patients compared with that in the normal arterial tissue. Animal experiments confirmed that CD72hi-Mφ expression, along with several pro-inflammatory cytokines, was significantly upregulated in the aortas of AS mice, which were downregulated by GZTL treatment. In conclusion, GZTL may alleviate AS by inhibiting CD72hi-Mφ activity.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Atherosclerosis/immunology* ; Mice ; Mice, Inbred C57BL ; Macrophages/immunology* ; Male ; Humans ; Apolipoproteins E/genetics* ; Tablets ; Tumor Necrosis Factor-alpha/genetics* ; Apoptosis/drug effects* ; Interleukin-1beta/genetics* ; Interleukin-6/genetics* ; Disease Models, Animal ; Mice, Knockout

Traditional Chinese medicine(TCM) solid waste is characterized by widespread availability, renewability, and substantial production volume. In the context of the "dual carbon" goals, the pyrolysis of TCM solid waste for producing fuel gas for recycling in pharmaceutical production has emerged as a crucial strategy for optimizing the energy structure in the TCM industry and developing renewable energy. This paper comprehensively reviews both internal and external factors that influence the pyrolysis of TCM solid waste. Internal factors encompass moisture content, particle size, ash content, and the morphology of the raw materials, while external factors include pyrolysis conditions, equivalence ratios, types of gasifiers, and gasifying agents. Furthermore, this paper details the challenges associated with the pyrolysis of TCM solid waste, such as the dispersion of feedstocks, the diversity of resources, the complexity of the pyrolysis process, and the variations in gasifier performance. Finally, this paper proposes measures to address these challenges. This paper aims to provide insights into the development of a circular economy for TCM resources and the advancement of low-carbon energy utilization in the TCM industry.
Pyrolysis ; Carbon/chemistry* ; Medicine, Chinese Traditional ; Solid Waste/analysis* ; Drugs, Chinese Herbal/chemistry* ; Gases/chemistry*

Colorectal cancer(CRC) is a common malignant tumor worldwide. Due to the treatment intolerance and side effects, CRC rank the top among various cancers regarding the incidence and mortality rates. Therefore, exploring new therapies is of great significance for the treatment of CRC. Aerobic glycolysis(AEG) plays an important role in the microenvironment formation, proliferation, metastasis, and recurrence of CRC and other tumor cells. It has been confirmed that intervening in the AEG pathway can effectively curb CRC. The active ingredients and compound prescriptions of traditional Chinese medicine(TCM) can effectively inhibit the proliferation, metastasis, and drug resistance and regulate the apoptosis of tumor cells by modulating AEG-associated transport proteins [eg, glucose transporters(GLUT)], key enzymes [hexokinase(HK) and phosphofructokinase(PFK)], key genes [hypoxia-inducible factor 1(HIF-1) and oncogene(c-Myc)], and signaling pathways(MET/PI3K/Akt/mTOR). Accordingly, they can treat CRC, reduce the recurrence, and improve the prognosis of CRC. Although AEG plays a key role in the development and progression of CRC, the specific mechanisms are not yet fully understood. Therefore, this article delves into the intrinsic connection of the targets and mechanisms of the AEG pathway with CRC from the perspective of tumor cell glycolysis and explores how active ingredients(oxymatrine, kaempferol, and dioscin) and compound prescriptions(Quxie Capsules, Jiedu Sangen Decoction, and Xianlian Jiedu Prescription) of TCM treat CRC by intervening in the AEG pathway. Additionally, this article explores the shortcomings in the current research, aiming to provide reliable targets and a theoretical basis for treating CRC with TCM.
Humans ; Colorectal Neoplasms/genetics* ; Drugs, Chinese Herbal/therapeutic use* ; Glycolysis/drug effects* ; Animals ; Medicine, Chinese Traditional ; Signal Transduction/drug effects*

Prostate cancer(PCa) is a common malignant tumor among elderly men, with high incidence and mortality rates worldwide, posing a serious threat to human health. Traditional treatments face limitations, highlighting the urgent need for novel therapeutic strategies. Recent studies on the regulatory mechanisms of micro ribonucleic acid(microRNA, miRNA) in tumor development has identified miRNA as new targets for PCa diagnosis and treatment. Traditional Chinese medicine(TCM), with its multi-mechanism, multi-target, and multi-pathway regulatory properties, shows promising potential in miRNA-based PCa therapy. This review summarized recent findings on miRNA' roles in PCa and research progress of TCM intervention and found that a variety of miRNA played important regulatory roles in cell differentiation, proliferation, apoptosis, invasion, metastasis, immune microenvironment, and drug resistance, and their potential as biomarkers for PCa diagnosis, prognosis, and therapy, indicating the potential to be a biomarker for the diagnosis, prognosis evaluation, and treatment of PCa. The review concluded that the active components of TCM(terpenoids, flavonoids, alkaloids, and others) and compounds(Yishen Tonglong Decoction, Shenhu Decoction, Zhoushi Qiling Decoction, Fuzheng Yiliu Decoction, and Qilan Formula) could regulate the expression of their downstream target genes by acting on specific miRNA and affect the above biological behaviors of PCa cells, thus playing a role in the treatment of PCa. This review aims to provide a theoretical basis for miRNA as potential biomarkers and therapeutic targets for PCa and suggest new avenues for further development of targeted therapy strategies against miRNA.
Humans ; MicroRNAs/metabolism* ; Prostatic Neoplasms/metabolism* ; Male ; Drugs, Chinese Herbal/therapeutic use* ; Medicine, Chinese Traditional ; Animals ; Gene Expression Regulation, Neoplastic/drug effects*

This study aimed to characterize and identify the non-volatile components in aqueous and ethanolic extracts of the stems and leaves of Rhododendron tomentosum by using sensitive and efficient ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry(UHPLC-Q-TOF-MS) combined with a self-built information database. By comparing with reference compounds, analyzing fragment ion information, searching relevant literature, and using a self-built information database, 118 compounds were identified from the aqueous and ethanolic extracts of R. tomentosum, including 35 flavonoid glycosides, 15 phenolic glycosides, 12 flavonoids, 7 phenolic acids, 7 phenylethanol glycosides, 6 tannins, 6 phospholipids, 5 coumarins, 5 monoterpene glycosides, 6 triterpenes, 3 fatty acids, and 11 other types of compounds. Among them, 102 compounds were reported in R. tomentosum for the first time, and 36 compounds were identified by comparing them with reference compounds. The chemical components in the ethanolic and aqueous extracts of R. tomentosum leaves and stems showed slight differences, with 84 common chemical components accounting for 71.2% of the total 118 compounds. This study systematically characterized and identified the non-volatile chemical components in the ethanolic and aqueous extracts of R. tomentosum for the first time. The findings provide a reference for active ingredient research, quality control, and product development of R. tomentosum.
Rhododendron/chemistry* ; Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Mass Spectrometry/methods* ; Plant Leaves/chemistry*

Non-small cell lung cancer(NSCLC) is the most common type of lung cancer worldwide, accounting for approximately 80%-85% of all lung cancer cases. Despite the clinical benefits of traditional treatments such as surgery, chemotherapy, and radiotherapy, challenges such as the high rate of postoperative recurrence and resistance of some patients to chemotherapy and targeted therapies limit their effectiveness, necessitating the exploration of more effective treatment options. In recent years, immunotherapy, especially immune checkpoint inhibitors(ICIs), has revolutionized NSCLC treatment and significantly improved the survival prognosis of some patients. However, the efficacy of immunotherapy is limited by tumor immune escape, drug resistance, and immune-related adverse events(irAEs), which have not been effectively addressed. Traditional Chinese medicine(TCM), as a traditional therapeutic approach, has shown unique advantages in NSCLC treatment, with studies indicating its ability to enhance immune responses, regulate immune checkpoints, and improve the tumor microenvironment(TME), thus boosting the efficacy of immunotherapy. Additionally, the multi-target and multi-pathway effects of TCM help mitigate the side effects of immunotherapy, further improving efficacy and safety. This review summarizes the latest research progress of TCM in NSCLC immunotherapy, focusing on the research results of TCM in enhancing the effect of immunotherapy by regulating immune cells, optimizing the immune microenvironment, and being applied with ICIs, etc. The latest research progress of TCM in alleviating irAEs is also elucidated. The aim is to provide theoretical support for the clinical application of TCM in the prevention and treatment of NSCLC and the research and development of new drugs and promote the optimization and development of combined immunotherapy and TCM treatment models.
Humans ; Carcinoma, Non-Small-Cell Lung/therapy* ; Lung Neoplasms/therapy* ; Immunotherapy/methods* ; Drugs, Chinese Herbal/therapeutic use* ; Medicine, Chinese Traditional ; Animals ; Tumor Microenvironment/drug effects*

In recent years, the application of artificial intelligence (AI) in the field of biology has witnessed remarkable advancements. Among these, the most notable achievements have emerged in the domain of protein structure prediction and design, with AlphaFold and related innovations earning the 2024 Nobel Prize in Chemistry. These breakthroughs have transformed our ability to understand protein folding and molecular interactions, marking a pivotal milestone in computational biology. Looking ahead, it is foreseeable that the accurate prediction of various physicochemical properties of proteins—beyond static structure—will become the next critical frontier in this rapidly evolving field. One of the most important protein properties is thermodynamic stability, which refers to a protein’s ability to maintain its native conformation under physiological or stress conditions. Accurate prediction of protein stability, especially upon single-point mutations, plays a vital role in numerous scientific and industrial domains. These include understanding the molecular basis of disease, rational drug design, development of therapeutic proteins, design of more robust industrial enzymes, and engineering of biosensors. Consequently, the ability to reliably forecast the stability changes caused by mutations has broad and transformative implications across biomedical and biotechnological applications. Historically, protein stability was assessed via experimental methods such as differential scanning calorimetry (DSC) and circular dichroism (CD), which, while precise, are time-consuming and resource-intensive. This prompted the development of computational approaches, including empirical energy functions and physics-based simulations. However, these traditional models often fall short in capturing the complex, high-dimensional nature of protein conformational landscapes and mutational effects. Recent advances in machine learning (ML) have significantly improved predictive performance in this area. Early ML models used handcrafted features derived from sequence and structure, whereas modern deep learning models leverage massive datasets and learn representations directly from data. Deep neural networks (DNNs), graph neural networks (GNNs), and attention-based architectures such as transformers have shown particular promise. GNNs, in particular, excel at modeling spatial and topological relationships in molecular structures, making them well-suited for protein modeling tasks. Furthermore, attention mechanisms enable models to dynamically weigh the contribution of specific residues or regions, capturing long-range interactions and allosteric effects. Nevertheless, several key challenges remain. These include the imbalance and scarcity of high-quality experimental datasets, particularly for rare or functionally significant mutations, which can lead to biased or overfitted models. Additionally, the inherently dynamic nature of proteins—their conformational flexibility and context-dependent behavior—is difficult to encode in static structural representations. Current models often rely on a single structure or average conformation, which may overlook important aspects of stability modulation. Efforts are ongoing to incorporate multi-conformational ensembles, molecular dynamics simulations, and physics-informed learning frameworks into predictive models. This paper presents a comprehensive review of the evolution of protein thermodynamic stability prediction techniques, with emphasis on the recent progress enabled by machine learning. It highlights representative datasets, modeling strategies, evaluation benchmarks, and the integration of structural and biochemical features. The aim is to provide researchers with a structured and up-to-date reference, guiding the development of more robust, generalizable, and interpretable models for predicting protein stability changes upon mutation. As the field moves forward, the synergy between data-driven AI methods and domain-specific biological knowledge will be key to unlocking deeper understanding and broader applications of protein engineering.