The interactions between microorganisms and medicinal plants are crucial to the quality improvement of medicinal plants. Medicinal plants attract microorganisms to colonize by secreting specific compounds and provide niche and nutrient support for these microorganisms, with a symbiotic network formed. These microorganisms grow in the rhizosphere, phyllosphere, and endophytic tissues of plants and significantly improve the growth performance and medicinal component accumulation of medicinal plants by promoting nutrient uptake, enhancing disease resistance, and regulating the synthesis of secondary metabolites. Microorganisms are also widely used in the ecological planting of medicinal plants, and the growth conditions of medicinal plants are optimized by simulating the microbial effects in the natural environment. The interactions between microorganisms and medicinal plants not only significantly improve the yield and quality of medicinal plants but also enhance their geoherbalism, which is in line with the concept of green agriculture and eco-friendly development. This study reviewed the research results on the interactions between medicinal plants and microorganisms in recent years and focused on the analysis of the great potential of microorganisms in optimizing the growth environment of medicinal plants, regulating the accumulation of secondary metabolites, inducing systemic resistance, and promoting the ecological planting of medicinal plants. It provides a scientific basis for the research on the interactions between medicinal plants and microorganisms, the research and development of microbial agents, and the application of microorganisms in the ecological planting of medicinal plants and is of great significance for the quality improvement of medicinal plants and the green and sustainable development of TCM resources.
Plants, Medicinal/metabolism* ; Bacteria/genetics* ; Symbiosis

Medical institutions, with their clinical practice foundation and abundant human use experience data, have become important carriers for the inheritance and innovation of traditional Chinese medicine(TCM) and the "cradles" of the preparation of new TCM. To effectively promote the transformation of new TCM originating from the TCM clinical practice in medical institutions and establish an effective evaluation index system for the transformation of new TCM conforming to the characteristics of TCM, consensus experts adopted the literature research, questionnaire survey, Delphi method, etc. By focusing on the policy and technical evaluation of new TCM originating from the TCM clinical practice in medical institutions, a comprehensive evaluation from the dimensions of drug safety, efficacy, feasibility, and characteristic advantages was conducted, thus forming a comprehensive evaluation system with four primary indicators and 37 secondary indicators. The expert consensus reached aims to encourage medical institutions at all levels to continuously improve the high-quality research and development and transformation of new TCM originating from the TCM clinical practice in medical institutions and targeted at clinical needs, so as to provide a decision-making basis for the preparation, selection, cultivation, and transformation of new TCM for medical institutions, improve the development efficiency of new TCM, and precisely respond to the public medication needs.
Medicine, Chinese Traditional/standards* ; Humans ; Consensus ; Drugs, Chinese Herbal/therapeutic use* ; Surveys and Questionnaires

Based on the ultra performance liquid chromatography-quadrupole Exactive Orbitrap mass spectrometry(UPLC-Q-Exactive Orbitrap-MS) technology, combined with related literature, databases, and reference material information, this study qualitatively analyzed the components of Dayuanyin in the tissue of rats after gavage and employed molecular docking technology to predict the rationality of the mechanism behind the antipyretic effect of the in vivo components in Dayuanyin. A total of 21, 26, 20, 21, 14, and 31 prototype components and 3, 16, 3, 7, 5, and 24 metabolites were identified from the heart, liver, spleen, lung, kidney, and hypothalamus of the rats, respectively, and the binding ability of key components and targets was further verified by molecular docking. The results showed that all components had good binding ability with targets. The established UPLC-Q-Exactive Orbitrap-MS could effectively and quickly identify the Dayuanyin components distributed in tissue and preliminarily identify their metabolites. Many components were identified in the hypothalamus, which suggested that the components delivered to the brain should be focused on in the study on Dayuanyin in the treatment of febrile diseases. The molecular docking technology was used to predict the rationality of the mechanism behind its antipyretic effect, which lays the foundation for the clarification of the material basis and action mechanism of Dayuanyin, the development of new preparations, and the prediction of quality markers.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Rats ; Molecular Docking Simulation ; Male ; Antipyretics/metabolism* ; Rats, Sprague-Dawley ; Tissue Distribution ; Mass Spectrometry ; Chromatography, High Pressure Liquid ; Hypothalamus/metabolism*

This study aims to investigate the in vitro mechanisms underlying the beneficial effects of puerarin on hepatic insulin resistance(IR) based on the carbohydrate response element-binding protein(ChREBP)/peroxisome proliferator-activated receptor(PPAR)α/PPARγ axis involved in glucose and lipid metabolism. An IR-HepG2 cell model was established by treating cells with dexamethasone for 48 h, and the cells were then treated with 10, 20, and 40 μmol·L~(-1) puerarin for 24 h. Glucose levels and output in the extracellular fluid were measured by the glucose oxidase method, while cell viability was assessed by the cell counting kit-8(CCK-8) assay. The adenosine triphosphate(ATP) content and glycogen synthesis were evaluated through chemiluminescence and periodic acid-Schiff staining, respectively. Western blot was employed to quantify the protein levels of forkhead box protein O1(FoxO1), phosphorylated forkhead box protein O1 [p-FoxO1(Ser256)], glucagon, phosphofructokinase, liver type(PFKL), pyruvate kinase L-R(PKLR), pyruvate dehydrogenase complex 1(PDHA1), insulin receptor substrate 2(IRS2), phosphatidylinositol 3-kinase p85(PI3KR1), phosphorylated protein kinase B [p-Akt(Thr308)], glycogen synthase(GYS), glycogen phosphorylase, liver type(PYGL), adiponectin(ADPN), ChREBP, PPARα, and PPARγ. Additionally, the protein levels of acetyl-CoA carboxylase 1(ACC1), phosphorylated ATP citrate lyase [p-ACLY(Ser455)], sterol regulatory element binding protein 1c(SREBP-1c), peroxisome proliferator-activated receptor gamma coactivator 1α(PGC1α), carnitine palmitoyltransferase 1α(CPT1α), and glucagon receptor(GCGR) were also determined. Immunofluorescence was employed to visualize the expression and nuclear location of ChREBP/PPARα/PPARγ. Furthermore, quantitative PCR with the antagonists GW6471 and GW9662 was employed to assess Pparα, Pparγ, and Chrebp. The findings indicated that puerarin effectively reduced both the glucose level and glucose output in the extracellular fluid of IR-HepG2 cells without obvious effect on the cell viability, and it increased intracellular glycogen and ATP levels. Puerarin down-regulated the protein levels of FoxO1 and glucagon while up-regulating the protein levels of p-FoxO1(Ser256), PFKL, PKLR, PDHA1, IRS2, PI3KR1, p-Akt(Thr308), GYS, PYGL, ADPN, ACC1, SREBP-1c, p-ACLY(Ser455), PGC1α, CPT1α, and GCGR in IR-HepG2 cells. Furthermore, puerarin up-regulated both the mRNA and protein levels of ChREBP, PPARα, and PPARγ and promoted the translocation into the nucleus. GW6471 was observed to down-regulate the expression of Pparα while up-regulating the expression of Chrebp and Pparγ. GW9662 down-regulated the expression of Pparγ while up-regulating the expression of Pparα, with no significant effect on Chrebp. In summary, puerarin activated the hepatic ChREBP/PPARα/PPARγ axis, thereby coordinating the glucose and lipid metabolism, promoting the conversion of glucose to lipids to exert the blood glucose-lowering effect.
Isoflavones/pharmacology* ; Humans ; PPAR gamma/genetics* ; Hep G2 Cells ; Glucose/metabolism* ; Lipid Metabolism/drug effects* ; PPAR alpha/genetics* ; Liver/drug effects* ; Basic Helix-Loop-Helix Leucine Zipper Transcription Factors/genetics* ; Insulin Resistance

This paper aims to investigate the hypoglycemic effect and mechanism of berberine in improving energy metabolism based on the multi-pathway regulation of brain and muscle aromatic hydrocarbon receptor nuclear translocal protein 1(BMAL1): cyclin kaput complex of day-night spontaneous output cyclin kaput(CLOCK). The dexamethasone-induced hepatic insulin resistance(IR) HepG2 cell model was used; 0.5, 1, 5, 10, 20 μmol·L~(-1) berberine were administered at 15, 18, 21, 24, 30, 36 h. The time-dose effect of glucose content in extracellular fluid was detected by glucose oxidase method. The optimal dosage and time of berberine were determined for the follow-up study. Glucose oxidase method and chemiluminescence method were respectively performed to detect hepatic glucose output and relative content of ATP in cells; Ca~(2+), reactive oxygen species(ROS), mitochondrial structure and membrane potential were detected by fluorescent probes. Moreover, ultraviolet colorimetry method was used to detect the liver type of pyruvate kinase(L-PK) and phosphoenol pyruvate carboxykinase(PEPCK). In addition, pyruvate dehydrogenase E1 subunit α1(PDHA1), phosphate fructocrine-liver type(PFKL), forkhead box protein O1(FoxO1), peroxisome proliferator-activated receptor gamma co-activator 1α(PGC1α), glucose-6-phosphatase(G6Pase), glucagon, phosphorylated nuclear factor-red blood cell 2-related factor 2(p-Nrf2)(Ser40), heme oxygenase 1(HO-1), NAD(P)H quinone oxidoreductase 1(NQO1), fibroblast growth factor 21(FGF21), uncoupled protein(UCP) 1 and UCP2 were detected by Western blot. BMAL1:CLOCK complex was detected by immunofluorescence double-staining method, combined with small molecule inhibitor CLK8. Western blot was used to detect PDHA1, PFKL, FoxO1, PGC1α, G6Pase, glucagon, Nrf2, HO-1, NQO1, FGF21, UCP1 and UCP2 in the CLK8 group. The results showed that berberine downregulated the glucose content in extracellular fluid in IR-HepG2 cells in a time-and dose-dependent manner. Moreover, berberine inhibited hepatic glucose output and reduced intracellular Ca~(2+) and ROS whereas elevated JC-1 membrane potential and improved mitochondrial structure to enhance ATP production. In addition, berberine upregulated the rate-limiting enzymes such as PFKL, L-PK and PDHA1 to promote glycolysis and aerobic oxidation but also downregulated PGC1α, FoxO1, G6Pase, PEPCK and glucagon to inhibit hepatic gluconeogenesis. Berberine not only upregulated p-Nrf2(Ser40), HO-1 and NQO1 to enhance antioxidant capacity but also upregulated FGF21, UCP1 and UCP2 to promote energy metabolism. Moreover, berberine increased BMAL1, CLOCK and nuclear BMAL1:CLOCK complex whereas CLK8 reduced the nuclear BMAL1:CLOCK complex. Finally, CLK8 decreased PDHA1, PFKL, Nrf2, HO-1, NQO1, FGF21, UCP1, UCP2 and increased FoxO1, PGC1α, G6Pase and glucagon compared with the 20 μmol·L~(-1) berberine group. BMAL1:CLOCK complex inhibited gluconeogenesis, promoted glycolysis and glucose aerobic oxidation pathways, improved the reduction status within mitochondria, protected mitochondrial structure and function, increased ATP energy storage and promoted energy consumption in IR-HepG2 cells. These results suggested that berberine mediated BMAL1:CLOCK complex to coordinate the regulation of hepatic IR cells to improve energy metabolism in vitro.
Humans ; Berberine/pharmacology* ; Gluconeogenesis/drug effects* ; Hep G2 Cells ; Glucose/metabolism* ; Liver/drug effects* ; Energy Metabolism/drug effects* ; Hypoglycemic Agents/pharmacology* ; ARNTL Transcription Factors/genetics* ; Glycolysis/drug effects* ; Oxidation-Reduction/drug effects*

Microbial detection and control of traditional Chinese medicine(TCM) decoction pieces are crucial for the quality control of TCM preparations. It is also a key area of research in the measurement technology and equipment development for TCM manufacturing. Guided by TCM manufacturing measurement methodologies, this study presented a design of a novel portable microbial detection device, using Atractylodis Macrocephalae Rhizoma decoction pieces as a demonstration. Immunomagnetic separation technology was employed for specific isolation and labeling of target microorganisms. Enzymatic signal amplification was utilized to convert weak biological signals into colorimetric signals, constructing an optical biosensor. A self-developed smartphone APP was further applied to analyze the colorimetric signals and quantify target concentrations. A portable and automated detection system based on Arduino microcontroller was developed to automatically perform target microbial separation/extraction, as well as mimetic enzyme labeling and catalytic reactions. The developed equipment specifically focuses on the rapid and quantitative microbial analysis of TCM active pharmaceutical ingredients, intermediates in TCM manufacturing, and final TCM products. Experimental results demonstrate that the equipment could detect Salmonella in samples within 2 h, with a detection limit as low as 5.1 × 10~3 CFU·mL~(-1). The equipment enables the rapid detection of microorganisms in TCM decoction pieces, providing a potential technical solution for on-site rapid screening of microbial contamination indicators in TCM. It has broad application prospects in measurement technology for TCM manufacturing and offers strong technical support for the modernization, industrialization, and intelligent development of TCM.
Drugs, Chinese Herbal/analysis* ; Atractylodes/microbiology* ; Rhizome/microbiology* ; Biosensing Techniques/methods* ; Medicine, Chinese Traditional ; Colorimetry/instrumentation* ; Quality Control

Lung cancer is the most common malignant tumor worldwide, ranking first in both incidence and mortality rates. According to the latest statistics from the International Agency for Research on Cancer (IARC), approximately 2.5 million new cases and around 1.8 million deaths from lung cancer occurred in 2022, placing a tremendous burden on global healthcare systems. The high mortality rate of lung cancer is closely linked to its subtle early symptoms, which often lead to diagnosis at advanced stages. This not only complicates treatment but also results in substantial economic losses. Current treatment options for lung cancer include surgery, radiotherapy, chemotherapy, targeted drug therapy, and immunotherapy. Among these, immunotherapy has emerged as the most groundbreaking advancement in recent years, owing to its unique antitumor mechanisms and impressive clinical benefits. Unlike traditional therapies such as radiotherapy and chemotherapy, immunotherapy activates or enhances the patient’s immune system to recognize and eliminate tumor cells. It offers advantages such as more durable therapeutic effects and relatively fewer toxic side effects. The main approaches to lung cancer immunotherapy include immune checkpoint inhibitors, tumor-specific antigen-targeted therapies, adoptive cell therapies, cancer vaccines, and oncolytic virus therapies. Among these, immune checkpoint inhibitors and tumor-specific antigen-targeted therapies have received approval from the U.S. Food and Drug Administration (FDA) for clinical use in lung cancer, significantly improving outcomes for patients with advanced non-small cell lung cancer. Although other immunotherapy strategies are still in clinical trials, they show great potential in improving treatment precision and efficacy. This article systematically reviews the latest research progress in lung cancer immunotherapy, including the development of novel immune checkpoint molecules, optimization of treatment strategies, identification of predictive biomarkers, and findings from recent clinical trials. It also discusses the current challenges in the field and outlines future directions, such as the development of next-generation immunotherapeutic agents, exploration of more effective combination regimens, and the establishment of precise efficacy prediction systems. The aim is to provide a valuable reference for the continued advancement of lung cancer immunotherapy.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.