Single-cell RNA sequencing (scRNA-seq) has emerged as a transformative tool in biomedical research, overcoming the limitations of bulk RNA sequencing by resolving cellular heterogeneity, identifying rare cell subtypes, and reconstructing dynamic regulatory networks. This technology holds unprecedented potential for advancing Traditional Chinese Medicine (TCM) research, which faces challenges in deciphering the multi-component, multi-target mechanisms and heterogeneous syndromes using conventional methods. Relevant studies were retrieved from PubMed, Web of Science, Google Scholar, and CNKI up to June 2025. Search keywords included "single-cell RNA sequencing", "Traditional Chinese Medicine", "tumor", "inflammatory and autoimmune", and "cardiovascular, cerebrovascular". The inclusion criteria were as follows: (a) original research articles; (b) the application of scRNA-seq in TCM-related research, mainly for TCM in research related to tumors, inflammatory and autoimmune diseases, cardiovascular and cerebrovascular diseases, safety evaluation of TCM, and TCM Syndrome Research. The exclusion criteria comprised: (a) studies irrelevant to the review topic; (b) studies that utilized public datasets solely for data mining. scRNA-seq enables precise identification of bioactive targets of herbal compounds, dissection of synergistic modulation of cellular networks by TCM formulas, and construction of syndrome-associated molecular atlases. Its applications span diverse fields: unraveling immune regulation mechanisms of TCM in tumor therapy, elucidating immunomodulatory effects in inflammatory and autoimmune diseases, clarifying cardioprotective mechanisms in cardiovascular and cerebrovascular disorders, and facilitating safety evaluation of TCM. Additionally, scRNA-seq bridges TCM's holistic syndrome differentiation with molecular medicine by revealing dynamic correlations between TCM syndromes and cellular heterogeneity. By comparing with Western medical research paradigms, scRNA-seq highlights TCM's distinctive focus on network-driven regulation and holistic balance. This review summarizes cutting-edge studies and future directions, emphasizing scRNA-seq's role as a critical bridge in integrating TCM's systemic principles with molecular insights, thereby accelerating TCM and its integration into precision medicine.

Nasal nanodrug delivery has gained prominence as a non-invasive method for administering therapeutic agents to the brain. However, the limited nasal cavity volume and the low drug loading capacity of nanoparticles contribute to a reduced accumulation of the drug within the brain tissue. Therefore, the aim of the present study was to investigate the role of the drug delivery combination “transnasal route + nanoparticle drug delivery system + chemical osmosis technology” in promoting drug accumulation in the brain. We constructed an in vitro olfactory sheath cell model based on the direct nose–brain pathway and a vascular endothelial cell model based on the indirect pathway, and investigated the transport behaviors and mechanisms of Poly(lactic-co-glycolicacid)-Nanoparticles (PLGA-NPs) in combination with two terpene aroma constituents (menthol and curcumol). Menthol and curcumol significantly improved the intracellular accumulation of PLGA-NPs, which may be related to changes in the endocytosis pathway and intercellular tight junction proteins. Meanwhile, the results of laser scanning confocal microscopy and atomic force microscopy showed that menthol and curcumol disrupted different tight junction proteins of vascular endothelial cells, and the biomechanical properties (e.g., rigidity and roughness) of the olfactory sheath cells and vascular endothelial cell cytomembranes were also greatly changed. The delivery system of “transnasal route + nanoparticle drug delivery system + chemical osmosis technology” has great potential for intranasal delivery of drugs for the treatment of brain diseases.

Colon adenocarcinoma (COAD) is a frequently occurring and lethal cancer. Cuproptosis is an emerging type of cell death, and the underlying pathways involved in this process in COAD remain poorly understood. Transcriptomic and clinical data for COAD patients were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We investigated alterations in DNA and chromatin of cuproptosis-related genes (CRGs) in COAD. In order to identify predictive differentially expressed genes (DEGs) and various molecular subtypes, we used consensus cluster analysis. Through univariate, multivariate, and Lasso Cox regression analyses, four CRGs were identified. A risk prognostic model for cuproptosis characteristics was constructed based on four CRGs. This study also examined the association between the risk score and the tumor microenvironment (TME), the immune landscape, and drug sensitivity. We distinguished two unique molecular subtypes using consensus clustering analysis. We discovered that the clinical characteristics, prognosis, and TME cell infiltration characteristics of patients with multilayer CRG subtypes were all connected. The internal and external evaluations of the predicted accuracy of the prognostic model built using data derived from a cuproptosis risk score were completed at the same time. A nomogram and a clinical pathological analysis make it more useful in the field of medicine. A significant rise in immunosuppressive cells was observed in the high cuproptosis risk score group, with a correlation identified between the cuproptosis risk score and immune cell infiltration. Despite generally poor prognoses, the patients with a high cuproptosis risk but low tumor mutation burden (TMB), cancer stem cell (CSC) index, or microsatellite instability (MSI) may still benefit from immunotherapy. Furthermore, the cuproptosis risk score positively correlated with immune checkpoint gene expression. Analyzing the potential sensitivity to medications could aid in the development of clinical chemotherapy regimens and decision-making. CRGs are the subject of our in-depth study, which exposed an array of regulatory mechanisms impacting TME. In addition, we performed additional data mining into clinical features, prognosis effectiveness, and possible treatment medications. COAD’s molecular pathways will be better understood, leading to more precise treatment options.