Objective: To evaluate the implementation process of a school-family collaborative "online+offline" tobacco control intervention program in junior high school in Beijing and to explore the execution status, influencing factors and sustainability potential of the intervention, so as to provide evidence for optimizing youth tobacco control strategies. Methods: In November 2024, using the random number table method, four first year junior high school classes were selected from three schools each in Fengtai District, Tongzhou District, and Fangshan District of Beijing. One class served as the control group, while the other three classes were designated as intervention groups (one each for online intervention, offline intervention, and combined online offline intervention). The control group received only conventional education.The online intervention group was engaged in WeChat push interventions, including watching micro videos, viewing promotional materials, participating in online quizzes and mini games; the offline intervention group attended knowledge lectures, played peer games, and participated in offline knowledge competitions; the combined online offline intervention group integrated all the aforementioned online and offline intervention measures. The intervention period was from November 2024 to June 2025, spanning a total of 7 months. Based on the Practical, Robust Implementation and Sustainability Model(PRISM) framework, a qualitative research design was employed to conduct semi structured interviews with 48 participants (12 in each of the intervention groups and 12 organizational staff members) from the Centers for Disease Control and Prevention (CDC) in 3 districts and 3 sampled schools. The interview outlines were designed according to the intervention plan. Data was managed using Nvivo 12.0 software and analyzed following Colaizzi s seven step phenomenological analysis method. Theoretical saturation was assessed using a reserved subset of transcripts. Results: Four core themes were identified in the tobacco control intervention process. Overall fidelity of intervention implementation was largely consistent with the original plan, and students showed strong willingness and positive evaluations toward interactive formats such as knowledge contests and peer games, though occasional breakdowns in school-family communication and blurred boundaries between online and offline components were observed; the participants showed a polarized response in terms of satisfaction and participation, most students and parents recognized the significance of the activity, and some parents observed a reduction in smoking behavior; the implementation of internal tobacco control policies in the school was strict, and the atmosphere was favorable, but there was still room for improvement, such as the scarcity of community tobacco control activities and the difficulty in implementing smoke free units; implementation and sustainability infrastructure were preliminarily established, such as through homeroom teacher supervision and training student assistants to assisted in activities, while the sustainability support system required further refinement. Conclusion The school-family collaborative "online+offline" tobacco control intervention has demonstrated significant positive effects, but further optimization of activity design, enhancement of community reward mechanisms, and standardized training are required to improve the efficacy and sustainability of the intervention.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

ObjectiveTo investigate the mechanisms by which eupatilin （Eup） inhibits proliferation， invasion， and metastasis of non-small cell lung cancer （NSCLC） through the enhancer of zeste homolog 2/histone H3 lysine 27 trimethylation （EZH2/H3K27me3） signaling pathway. MethodsIn vivo， a subcutaneous xenograft tumor model was established in nude mice using H1299 cells to evaluate the anti-NSCLC effects of Eup. Immunohistochemistry （IHC-P） was used to detect the expression of proliferation- and invasion/metastasis-related proteins， including proliferating cell nuclear antigen （PCNA）， matrix metalloproteinase-2 （MMP-2）， matrix metalloproteinase-9 （MMP-9）， and vascular endothelial growth factor A （VEGFA）. In vitro， cell counting kit-8 （CCK-8） assays were performed to determine the viability of H1299 cells treated with different concentrations of Eup （0-200 μmol·L^-1） and to select appropriate concentrations. Colony formation and 5-ethynyl-2′-deoxyuridine （EdU） assays were used to evaluate cell proliferation. Wound healing and invasion assays were conducted to assess cell migration and invasion. Human umbilical vein endothelial cell （HUVEC） angiogenesis assays were used to evaluate the effects of Eup on angiogenesis. Transcriptomic analysis was performed to identify the targets of Eup in H1299 cells and to explore its major functions. Molecular docking and molecular dynamics simulations were conducted to predict the binding affinity and interaction stability between Eup and its target proteins. Western blot was used to detect the effects of Eup on the expression levels of EZH2/H3K27me3 pathway-related proteins and proliferation- and invasion/metastasis-related proteins， including PCNA， MMP-2， MMP-9， and VEGFA. ResultsIn the subcutaneous xenograft model， compared with the model group， Eup treatment dose-dependently inhibited the growth of H1299 xenograft tumors， and the tumor inhibition rate was significantly increased （P<0.05）. IHC-P results showed that， compared with the model group， high-dose Eup significantly reduced the expression levels of PCNA， MMP-2， MMP-9， and VEGFA in vivo （P<0.05）. In vitro， compared with the control group， Eup inhibited the proliferation， invasion， and metastasis of NSCLC cells in a concentration-dependent manner. Transcriptomic analysis further showed that， compared with the control group， Eup significantly downregulated EZH2 expression， and its functional effects were associated with inhibition of tumor metastasis. Molecular docking and molecular dynamics simulations indicated that Eup exhibited strong binding affinity with EZH2 and stable interactions. Western blot results demonstrated that， compared with the model group， Eup significantly inhibited， in a dose-dependent manner， the expression levels of EZH2， H3K27me3， and proliferation- and invasion/metastasis-related proteins （PCNA， MMP-2， MMP-9， and VEGFA） in both in vivo and in vitro experiments （P<0.05）. In vitro， compared with the control group， overexpression of EZH2 via plasmid transfection partially reversed the inhibitory effects of Eup on the expression of key proteins involved in proliferation and invasion/metastasis in H1299 cells. ConclusionEup effectively inhibits the proliferation， migration， and invasion of H1299 cells both in vivo and in vitro. The underlying mechanism may be related to inhibition of the EZH2/H3K27me3 signaling pathway and downregulation of proliferation- and invasion/metastasis-related proteins， including PCNA， MMP-2， MMP-9， and VEGFA. Eup may serve as a potential therapeutic agent for suppressing proliferation and invasion/metastasis in NSCLC.

ObjectiveTo investigate the mechanisms by which eupatilin （Eup） inhibits proliferation， invasion， and metastasis of non-small cell lung cancer （NSCLC） through the enhancer of zeste homolog 2/histone H3 lysine 27 trimethylation （EZH2/H3K27me3） signaling pathway. MethodsIn vivo， a subcutaneous xenograft tumor model was established in nude mice using H1299 cells to evaluate the anti-NSCLC effects of Eup. Immunohistochemistry （IHC-P） was used to detect the expression of proliferation- and invasion/metastasis-related proteins， including proliferating cell nuclear antigen （PCNA）， matrix metalloproteinase-2 （MMP-2）， matrix metalloproteinase-9 （MMP-9）， and vascular endothelial growth factor A （VEGFA）. In vitro， cell counting kit-8 （CCK-8） assays were performed to determine the viability of H1299 cells treated with different concentrations of Eup （0-200 μmol·L^-1） and to select appropriate concentrations. Colony formation and 5-ethynyl-2′-deoxyuridine （EdU） assays were used to evaluate cell proliferation. Wound healing and invasion assays were conducted to assess cell migration and invasion. Human umbilical vein endothelial cell （HUVEC） angiogenesis assays were used to evaluate the effects of Eup on angiogenesis. Transcriptomic analysis was performed to identify the targets of Eup in H1299 cells and to explore its major functions. Molecular docking and molecular dynamics simulations were conducted to predict the binding affinity and interaction stability between Eup and its target proteins. Western blot was used to detect the effects of Eup on the expression levels of EZH2/H3K27me3 pathway-related proteins and proliferation- and invasion/metastasis-related proteins， including PCNA， MMP-2， MMP-9， and VEGFA. ResultsIn the subcutaneous xenograft model， compared with the model group， Eup treatment dose-dependently inhibited the growth of H1299 xenograft tumors， and the tumor inhibition rate was significantly increased （P<0.05）. IHC-P results showed that， compared with the model group， high-dose Eup significantly reduced the expression levels of PCNA， MMP-2， MMP-9， and VEGFA in vivo （P<0.05）. In vitro， compared with the control group， Eup inhibited the proliferation， invasion， and metastasis of NSCLC cells in a concentration-dependent manner. Transcriptomic analysis further showed that， compared with the control group， Eup significantly downregulated EZH2 expression， and its functional effects were associated with inhibition of tumor metastasis. Molecular docking and molecular dynamics simulations indicated that Eup exhibited strong binding affinity with EZH2 and stable interactions. Western blot results demonstrated that， compared with the model group， Eup significantly inhibited， in a dose-dependent manner， the expression levels of EZH2， H3K27me3， and proliferation- and invasion/metastasis-related proteins （PCNA， MMP-2， MMP-9， and VEGFA） in both in vivo and in vitro experiments （P<0.05）. In vitro， compared with the control group， overexpression of EZH2 via plasmid transfection partially reversed the inhibitory effects of Eup on the expression of key proteins involved in proliferation and invasion/metastasis in H1299 cells. ConclusionEup effectively inhibits the proliferation， migration， and invasion of H1299 cells both in vivo and in vitro. The underlying mechanism may be related to inhibition of the EZH2/H3K27me3 signaling pathway and downregulation of proliferation- and invasion/metastasis-related proteins， including PCNA， MMP-2， MMP-9， and VEGFA. Eup may serve as a potential therapeutic agent for suppressing proliferation and invasion/metastasis in NSCLC.

Extracellular vesicles (EVs) are pivotal mediators of intercellular communication within the tumor immune microenvironment (TME). They are broadly categorized into exosomes, microvesicles, and apoptotic bodies based on their distinct biogenesis pathways. Exosomes originate from the endosomal system via multivesicular body fusion, microvesicles bud directly from the plasma membrane, and apoptotic bodies are released during programmed cell death. By shuttling diverse bioactive cargoes—including proteins, lipids, and nucleic acids such as mRNA, miRNA, and DNA—EVs exert dual modulatory effects on tumor initiation, progression, and immune evasion. Importantly, EVs exhibit remarkable compositional heterogeneity that is intrinsically linked to their cellular origin. Tumor-derived EVs (TDEVs) are typically enriched with immunosuppressive molecules like PD-L1, TGF‑β, and miR-21, which promote tumor immune escape and metastasis. In contrast, EVs derived from immune cells, such as dendritic cells or cytotoxic T lymphocytes, often carry immunostimulatory components including antigens, co-stimulatory molecules, and granzymes, thereby potentiating anti-tumor immunity. This review systematically delineates the biogenesis and molecular composition of EVs, with a particular emphasis on their dynamic regulatory functions within the TME. Specifically, we discuss how EVs mediate intricate crosstalk between immune and tumor cells, facilitating signal transfer that reshapes immune surveillance. For instance, TDEVs can induce macrophage polarization toward an M2-like pro-tumor phenotype, while also suppressing natural killer cell cytotoxicity and dendritic cell maturation. The clinical utility of EV-associated biomarkers in liquid biopsy is increasingly recognized. Circulating EVs carry tumor-specific molecular signatures that mirror the genetic and proteomic alterations of primary tumors, enabling non-invasive early diagnosis, molecular subtyping, and real-time monitoring of therapeutic responses. Their natural biocompatibility, low immunogenicity, and intrinsic ability to traverse biological barriers make them ideal candidates for drug delivery systems. This review explores cutting-edge applications, including the use of EVs in immune checkpoint blockade therapy—for instance, engineered EVs displaying anti-PD-1 antibodies or carrying siRNA to silence immunosuppressive genes. Moreover, EV-based tumor vaccines are being developed, leveraging dendritic cell-derived EVs loaded with tumor antigens to elicit potent T cell responses. The feasibility of loading EVs with therapeutic molecules such as chemotherapeutic agents, oncolytic viruses, or CRISPR-Cas9 components is also under active investigation. The advent of engineered EVs has further expanded their therapeutic potential. Through surface modification or cargo encapsulation, EVs can be tailored for targeted delivery and controlled release, enhancing precision immunotherapy. However, several hurdles impede clinical translation. Current isolation and purification methods, such as ultracentrifugation and size-exclusion chromatography, suffer from low yield and purity. Distinguishing EV subpopulations remains technically challenging due to overlapping size and marker expression. Moreover, the lack of standardized protocols for EV production, characterization, and quality control poses significant barriers to regulatory approval and clinical adoption. Looking forward, the convergence of multi-omics technologies with artificial intelligence offers a powerful approach to decipher EV heterogeneity and identify robust diagnostic signatures. Machine learning algorithms can integrate proteomic, transcriptomic, and lipidomic data from large patient cohorts to construct predictive models for cancer diagnosis and prognosis. Concurrently, advances in bioengineering are enabling the design of next-generation EVs with enhanced targeting specificity, on-demand drug release, and reduced off-target effects. Future efforts should also focus on establishing good manufacturing practice (GMP)‑compliant production processes and conducting rigorous preclinical and clinical evaluations. In summary, this review provides a comprehensive overview of EV biology, their multifaceted roles in the TME, and their transformative potential in cancer diagnostics and therapeutics. By addressing current challenges and leveraging emerging technologies, EV-based strategies are poised to revolutionize precision oncology.

Olfactory receptors (ORs) form the largest superfamily of G protein-coupled receptors (GPCRs). Traditionally recognized for their role in the nasal olfactory epithelium, where they mediate the sense of smell, accumulating evidence has firmly established their ectopic expression in non-olfactory tissues, including the intestine, lungs, and kidneys. The intestine, as the primary site for nutrient digestion and absorption, harbors a highly complex chemical environment. To adapt to this environment, the gut employs a sophisticated network of “chemosensors” to monitor luminal contents and maintain homeostasis. Among these sensors, intestinal ORs have emerged as crucial functional components, serving as a molecular bridge that connects environmental chemical signals—such as food-derived odorants—to specific physiological responses. This discovery has significantly deepened our understanding of how dietary flavors and compounds influence intestinal physiology at the molecular level. This review systematically summarizes the expression profiles, ligand classification, and biological functions of ORs within the gastrointestinal tract. Studies indicate that intestinal ORs exhibit distinct spatial distribution patterns across different gut segments and display cell-type specificity, particularly within enterocytes and enteroendocrine cells. These receptors function as versatile sensors capable of recognizing a wide variety of ligands, including exogenous dietary components, gut microbiota metabolites such as short-chain fatty acids, and endogenous small molecules like azelaic acid. Upon activation by specific ligands, intestinal ORs trigger intracellular signaling cascades, primarily involving the AC-cAMP-PKA pathway or calcium influx channels. A major focus of this review is to elucidate the molecular mechanisms by which these receptors regulate the secretion of gut hormones. Activation of specific ORs in enteroendocrine cells has been shown to stimulate the release of hormones such as glucagon-like peptide-1 (GLP-1), peptide YY (PYY), and serotonin (5-HT), thereby modulating systemic energy metabolism, glucose homeostasis, and gastrointestinal motility. Furthermore, the review addresses the critical roles of ORs in immune regulation and pathology. Evidence suggests that specific ORs contribute to the maintenance of intestinal immune homeostasis and may offer protection against inflammation. Beyond their involvement in inflammatory responses, ORs such as Olfr78 have been shown to regulate the differentiation and function of intestinal endocrine cells. Similarly, Olfr544 has been demonstrated to alleviate intestinal inflammation by remodeling the gut microbiome and metabolome. These findings collectively suggest that specific ORs hold promise as therapeutic targets for mitigating intestinal inflammation and maintaining gut homeostasis. Additionally, the review explores the emerging role of ORs in cancer. Although OR expression is often downregulated in tumor tissues compared to normal mucosa, activation of specific ORs by certain ligands can inhibit tumor cell proliferation and migration and induce apoptosis via pathways such as MEK/ERK and p38 MAPK. Conversely, other receptors, such as OR7C1, may serve as biomarkers for cancer-initiating cells. In conclusion, intestinal ORs represent a vital component of the gut’s sensory network. The review also discusses the translational potential of these findings. By elucidating the precise pairing relationships between dietary components and specific ORs, novel therapeutic strategies could be developed. Intestinal ORs may thus emerge as promising targets for nutritional and pharmacological interventions in metabolic diseases, inflammatory bowel diseases, and malignancies.

Membrane proteins are integral components of cellular membranes, accounting for approximately 30% of the mammalian proteome and serving as targets for 60% of FDA-approved drugs. They are critical to both physiological functions and disease mechanisms. Their functional protein-protein interactions form the basis for many physiological processes, such as signal transduction, material transport, and cell communication. Membrane protein interactions are characterized by membrane environment dependence, spatial asymmetry, weak interaction strength, high dynamics, and a variety of interaction sites. Therefore, in situ analysis is essential for revealing the structural basis and kinetics of these proteins. This paper introduces currently available in situ analytical techniques for studying membrane protein interactions and evaluates the characteristics of each. These techniques are divided into two categories: label-based techniques (e.g., co-immunoprecipitation, proximity ligation assay, bimolecular fluorescence complementation, resonance energy transfer, and proximity labeling) and label-free techniques (e.g., cryo-electron tomography, in situ cross-linking mass spectrometry, Raman spectroscopy, electron paramagnetic resonance, nuclear magnetic resonance, and structure prediction tools). Each technique is critically assessed in terms of its historical development, strengths, and limitations. Based on the authors’ relevant research, the paper further discusses the key issues and trends in the application of these techniques, providing valuable references for the field of membrane protein research. Label-based techniques rely on molecular tags or antibodies to detect proximity or interactions, offering high specificity and adaptability for dynamic studies. For instance, proximity ligation assay combines the specificity of antibodies with the sensitivity of PCR amplification, while proximity labeling enables spatial mapping of interactomes. Conversely, label-free techniques, such as cryo-electron tomography, provide near-native structural insights, and Raman spectroscopy directly probes molecular interactions without perturbing the membrane environment. Despite advancements, these methods face several universal challenges: (1) indirect detection, relying on proximity or tagged proxies rather than direct interaction measurement; (2) limited capacity for continuous dynamic monitoring in live cells; and (3) potential artificial influences introduced by labeling or sample preparation, which may alter native conformations. Emerging trends emphasize the multimodal integration of complementary techniques to overcome individual limitations. For example, combining in situ cross-linking mass spectrometry with proximity labeling enhances both spatial resolution and interaction coverage, enabling high-throughput subcellular interactome mapping. Similarly, coupling fluorescence resonance energy transfer with nuclear magnetic resonance and artificial intelligence (AI) simulations integrates dynamic structural data, atomic-level details, and predictive modeling for holistic insights. Advances in AI, exemplified by AlphaFold’s ability to predict interaction interfaces, further augment experimental data, accelerating structure-function analyses. Future developments in cryo-electron microscopy, super-resolution imaging, and machine learning are poised to refine spatiotemporal resolution and scalability. In conclusion, in situ analysis of membrane protein interactions remains indispensable for deciphering their roles in health and disease. While current technologies have significantly advanced our understanding, persistent gaps highlight the need for innovative, integrative approaches. By synergizing experimental and computational tools, researchers can achieve multiscale, real-time, and perturbation-free analyses, ultimately unraveling the dynamic complexity of membrane protein networks and driving therapeutic discovery.

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*

Aromatic traditional Chinese medicine(TCM) has played an important role against epidemics and viruses, and volatile components are the main components that exert the pharmacological effects of aromatic TCM. By screening the related monomer components in aromatic TCM against epidemic and viruses and analyzing and endowing TCM with medicinal properties based on its clinical application and pharmacological research according to the theoretical thinking of TCM, the key technical issues of compatibility of TCM monomer components were solved from a theoretical perspective, providing new ideas and methods for screening raw materials and formulas for the development of new TCM drugs. Based on the conditions of antiviral activity, clinical application foundation, definite therapeutic effect, and high safety, a gradient screening of aromatic TCM was carried out. Firstly, 30 aromatic TCM were screened from anti-epidemic literature and clinical trial formulas, and seven volatile monomers were further screened from them. Then, four monomer components with significant effects, namely patchouli alcohol, carvacrol, p-cymene, and eucalyptol were screened. By adopting the "four-step method for a systematic study of TCM properties", the four monomer components were endowed with medicinal properties, and compatibility and combination studies were conducted to explore the theoretical basis of monomer formulas and form monomer formulas guided by TCM theory. The screening results of volatile monomers in aromatic TCM against viral pneumonia included patchouli alcohol, carvacrol, p-cymene, and eucalyptol. The medicinal properties and compatibility theory of volatile monomer components in TCM were explored. Patchouli alcohol was the main herb, with a cool and pungent nature. It entered the lung meridian to dispel evil Qi and has the effects of aromatization, detoxification, and epidemic prevention. Carvacrol was a minister drug with a cool and pungent taste. It had the effects of aromatizing, moistening, and dissolving the exterior, as well as strengthening the spleen and stomach. p-Cymene was an adjunctive medicine with a mild and pungent nature. It entered the lungs and kidneys and had the effects of aromatic purification, cough relief, and asthma relief. Eucalyptol was also an adjunctive medicine with a pungent and warm taste. It had the functions of aromatic purification, cough relief, phlegm reduction, and pain relief. The combination of the four medicines had the effects of aromatizing, moistening, detoxifying, and epidemic prevention, as well as relieving cough and asthma and strengthening the spleen and stomach. They were used to treat viral pneumonia caused by upper respiratory tract viral infections, with symptoms such as chest tightness, cough, wheezing, fatigue, nasal congestion, runny nose, nausea, and vomiting. This study has laid a literature and theoretical foundation for further drug efficacy verification experiments, compatibility efficacy experiments, and subsequent product development and clinical applications, and it serves as an innovative practice that combines literature research, theoretical research, experimental research, and clinical practice to develop new products.
Drugs, Chinese Herbal/therapeutic use* ; Antiviral Agents/pharmacology* ; Humans ; Pneumonia, Viral/virology* ; Medicine, Chinese Traditional ; Volatile Organic Compounds/pharmacology* ; Animals