The functional realization of proteins and other biological macromolecules depends on conformational dynamics and allosteric regulation, and elucidating their molecular mechanisms is an important foundation for understanding life processes. Molecular dynamics simulations are a powerful tool for investigating conformational evolution at the atomic level. However, traditional methods are limited by simulation timescales and high free-energy barriers, making it difficult to effectively capture rare conformations and their transition pathways. As a result, the development of enhanced sampling techniques has become key to overcoming this bottleneck. As a classical enhanced sampling technique, metadynamics suffers from several shortcomings, including strong dependence on collective variables and significant errors caused by bias potential accumulation. This article reviews three major improvement strategies. The first combines stochastic resetting with metadynamics, using trajectory-resetting mechanisms to improve sampling efficiency while avoiding the difficulty of optimizing collective variables. The second, SinkMeta, employs a “sinking” bias effect to enable efficient exploration of specific regions and paths. The third, OPES-based hybrid methods, improve the stability of free-energy estimation by optimizing the target distribution or the way the bias is constructed. These methods provide new ideas for characterizing free-energy landscapes and studying conformational transitions in complex biological systems, while also promoting the continued development of enhanced sampling methodologies.

OBJECTIVES: To study the molecular mechanisms of LDH-loaded si-NEAT1 for regulating paclitaxel resistance and tumor-associated macrophage (TAM) polarization in breast cancer. METHODS: qRT-PCR and Western blotting were used to detect the expression of lncRNA NEAT1, miR-133b, and PD-L1 in breast cancer SKBR3 cells and paclitaxel-resistant SKBR3 cells (SKBR3-PR). The effects of transfection with si-NEAT1 and miR-133b mimics on MRP, MCRP and PD-L1 expressions and cell proliferation, migration and apoptosis were investigated using qRT-PCR, Western blotting, scratch and Transwell assays, and flow cytometry. Rescue experiments were conducted using si-NEAT1 and miR-133b inhibitor. Human THP-1 macrophages were cultured in the presence of conditioned media (CM) derived from SKBR3 and SKBR3-PR cells with or with si-NEAT1 transfection for comparison of IL-4-induced macrophage polarization by detecting the surface markers. LDH@si-NEAT1 nanocarriers were constructed, and their effects on MRP, MCRP and PD-L1 expressions and cell behaviors of the tumor cells were examined. THP-1 cells were treated with the CM from LDH@si-NEAT1-treated tumor cells, and the changes in their polarization were assessed. RESULTS: SKBR3-PR cells showered significantly upregulated NEAT1 and PD-L1 expressions and lowered miR-133b expression as compared with their parental cells. Transfection with si-NEAT1 and miR-133b mimics inhibited viability, promoted apoptosis and enhanced MRP and BCRP expressions in SKBR3-PR cells. NEAT1 knockdown obvious upregulated miR-133b and downregulated PD-L1, MRP and BCRP expressions. The CM from SKBR3-PR cells obviously promoted M2 polarization of THP-1 macrophages, which was significantly inhibited by CM from si-NEAT1-transfected cells. Treatment with LDH@si-NEAT1 effectively inhibited migration and invasion, promoted apoptosis, and reduced MRP, BCRP and PD-L1 expressions in the tumor cells. The CM from LDH@si-NEAT1-treated SKBR3-PR cells significantly downregulated Arg-1, CD163, IL-10, and PD-L1 and upregulated miR-133b expression in THP-1 macrophages. CONCLUSIONS LDH@si-NEAT1 reduces paclitaxel resistance of breast cancer cells and inhibits TAM polarization by targeting the miR-133b/PD-L1 axis.
Humans ; MicroRNAs/genetics* ; RNA, Long Noncoding/genetics* ; Paclitaxel/pharmacology* ; Breast Neoplasms/metabolism* ; Drug Resistance, Neoplasm ; B7-H1 Antigen/metabolism* ; Cell Line, Tumor ; Female ; Tumor-Associated Macrophages ; Apoptosis ; Cell Proliferation ; Macrophages ; Cell Movement

OBJECTIVE: Varied acupoint selections represent a potential cause of the uncertainty surrounding the efficacy of acupuncture for knee osteoarthritis (OA). Skin temperature, a guiding factor for acupoint selection, may help to address this issue. This study explored thermal sensitization of acupoints used for the treatment of knee OA. METHODS: This cross-sectional case-control study enrolled cases aged 45-75 years with symptomatic knee OA and age- and gender-matched non-knee OA controls in a 1:1 ratio. All participants underwent infrared thermographic imaging. The primary outcome was the relative skin temperature of acupoint (STA), and the secondary outcome was the absolute STA of 11 acupoints. The Z test was used to compare the relative and absolute STAs between the groups. Principal component analysis was used to extract the common factors (CFs, acupoint cluster) in the STAs. A general linear model was used to identify factors affecting the STA in the knee OA cases. For the group comparisons of relative STA, P < 0.0045 (adjusted for 11 acupoints through Bonferroni correction) was considered to indicate statistical significance. For other analyses, P < 0.05 was used as the threshold for statistical significance. RESULTS: The analysis included 308 participants, consisting of 151 cases (mean age: [64.58 ± 6.67] years; male: 25.83%; mean body mass index: [25.70 ± 3.16] kg/m²) and 157 controls (mean age: [63.37 ± 5.96] years; male: 26.11%; mean body mass index: [24.47 ± 2.84] kg/m²). The relative STAs of ST34 (P = 0.0001), EX-LE2 (P < 0.0001), EX-LE5 (P = 0.0006), SP10 (P < 0.0001), BL40 (P = 0.0012) and GB39 (P = 0.0037) were higher in the knee OA group. No difference was found in the STAs of ST35, ST36, SP9, GB33 and GB34. Four CFs were identified for relative STA in both groups. The acupoints within each CF were consistent between the groups. The mean values of the relative STAs across each CF were higher in the knee OA group. In the knee OA cases, no factors were observed to affect the relative STA, while age and gender were found to affect the absolute STA. CONCLUSION Among patients with knee OA, thermal sensitization occurs in the acupoints of the lower extremity, exhibiting localized and regional thermal consistencies. The thermally sensitized acupoints that we identified in this study, ST34, SP10, EX-LE2, EX-LE5, GB39 and BL40, may be good choices for the acupuncture treatment of knee OA. Please cite this article as: Tu JF, Wang XZ, Yan SY, Wang YR, Yang JW, Shi GX, Zhang WZ, Jing LN, Yang LS, Liu DH, Wang LQ, Mi BH. Thermal sensitization of acupoints in patients with knee osteoarthritis: A cross-sectional case-control study. J Integr Med. 2025; 23(3): 289-296.
Humans ; Osteoarthritis, Knee/physiopathology* ; Male ; Cross-Sectional Studies ; Middle Aged ; Female ; Acupuncture Points ; Case-Control Studies ; Aged ; Skin Temperature ; Acupuncture Therapy

Objective:To investigate the relationship between different states of cardiac function and their changes during the course of diabetic foot ulcers(DFU), and to evaluate their impact on patient prognosis.Methods:A retrospective analysis was conducted on 194 DFU patients who were rehospitalized at approximately 3-month intervals. Basic clinical data and cardiac function-related indicators were collected at baseline and follow-up. Patients were followed until death or until November 10, 2024. Outcomes including ulcer healing, recurrence, minor amputation, and death were recorded. Logistic regression models were used to analyze the effects of cardiac function status and its changes on these four outcomes. Results:After treatment, the proportion of patients with NYHA class Ⅱ-Ⅲ decreased significantly from 33.5% at baseline to 21.6%( P=0.009). Serum N-terminal pro-B-type natriuretic peptide(NT-proBNP) level also decreased after treatment compared with baseline [635.85(59.83, 453.28) pg/mL vs 728.67(81.48, 696.15) pg/mL, P=0.055]. Serum NT-proBNP level was significantly higher in the death group compared to the survival group( P=0.002). The proportion of DFU patients with baseline NYHA class Ⅱ-Ⅲ was significantly higher than that in those with class Ⅰ( P=0.012). Regression analysis showed that an improvement in NT-proBNP levels was associated with a lower risk of DFU recurrence( OR=0.378, 95% CI 0.183-0.779, P=0.008), and improvement in NYHA class was associated with a lower mortality risk( OR=0.074, 95% CI 0.020-0.275, P<0.001). Conclusion:Cardiac function status and its changes during the treatment of DFU patients have strong prognostic implications, particularly in predicting the risk of recurrence and death outcomes.

Objective To reveal the scientific output and trends in pulmonary nodules/early-stage lung cancer prediction models. Methods Publications on predictive models of pulmonary nodules/early lung cancer between January 1, 2002 and June 3, 2023 were retrieved and extracted from CNKI, Wanfang, VIP and Web of Science database. CiteSpace 6.1.R3 and VOSviewer 1.6.18 were used to analyze the hotspots and theme trends. Results A marked increase in the number of publications related to pulmonary nodules/early-stage lung cancer prediction models was observed. A total of 12581 authors from 2711 institutions in 64 countries/regions published 2139 documents in 566 academic journals in English. A total of 282 articles from 1256 authors were published in 176 journals in Chinese. The Chinese and English journals which published the most pulmonary nodules/early-stage lung cancer prediction model-related papers were Journal of Clinical Radiology and Frontiers in Oncology, respectively. Chest was the most frequently cited journal. China and the United States were the leading countries in the field of pulmonary nodules/early-stage lung cancer prediction models. The institutions represented by Fudan University had significant academic influence in the field. Analysis of keywords revealed that multi-omics, nomogram, machine learning and artificial intelligence were the current focus of research. Conclusion Over the last two decades, research on risk-prediction models for pulmonary nodules/early-stage lung cancer has attracted increasing attention. Prognosis, machine learning, artificial intelligence, nomogram, and multi-omics technologies are both current hotspots and future trends in this field. In the future, in-depth explorations using different omics should increase the sensitivity and accuracy of pulmonary nodules/early-stage lung cancer prediction models. More high-quality future studies should be conducted to validate the efficacy and safety of pulmonary nodules/early-stage lung cancer prediction models further and reduce the global burden of lung cancer.

Objective To analyze the differences in distribution of traditional Chinese medicine (TCM) syndrome elements and salivary microbiota between the individuals with pulmonary nodules and those without, and to explore the potential correlation between the distribution of TCM syndrome elements and salivary microbiota in patients with pulmonary nodules. Methods We retrospectively recruited 173 patients with pulmonary nodules (PN) and 40 healthy controls (HC). The four diagnostic information was collected from all participants, and syndrome differentiation method was used to analyze the distribution of TCM syndrome elements in both groups. Saliva samples were obtained from the subjects for 16S rRNA high-throughput sequencing to obtain differential microbiota and to explore the correlation between TCM syndrome elements and salivary microbiota in the evolution of the pulmonary nodule disease. Results The study found that in the PN group, the primary TCM syndrome elements related to disease location were the lung and liver, and the primary TCM syndrome elements related to disease nature were yin deficiency and phlegm. In the HC group, the primary TCM syndrome elements related to disease location were the lung and spleen, and the primary TCM syndrome elements related to disease nature were dampness and qi deficiency. There were differences between the two groups in the distribution of TCM syndrome elements related to disease location (lung, liver, kidney, exterior, heart) and disease nature (yin deficiency, phlegm, qi stagnation, qi deficiency, dampness, blood deficiency, heat, blood stasis) (P<0.05). The species abundance of the salivary microbiota was higher in the PN group than that in the HC group (P<0.05), and there was significant difference in community composition between the two groups (P<0.05). Correlation analysis using multiple methods, including Mantel test network heatmap analysis and Spearman correlation analysis and so on, the results showed that in the PN group, Prevotella and Porphyromonas were positively correlated with disease location in the lung, and Porphyromonas and Granulicatella were positively correlated with disease nature in yin deficiency (P<0.05). Conclusion The study concludes that there are notable differences in the distribution of TCM syndrome elements and the species abundance and composition of salivary microbiota between the patients with pulmonary nodules and the healthy individuals. The distinct external syndrome manifestations in patients with pulmonary nodules, compared to healthy individuals, may be a cascade event triggered by changes in the salivary microbiota. The dual correlation of Porphyromonas with both disease location and nature suggests that changes in its abundance may serve as an objective indicator for the improvement of symptoms in patients with yin deficiency-type pulmonary nodules.

Objective To construct a "disease-syndrome combination" mathematical representation model for pulmonary nodules based on oral microbiome data, utilizing a multimodal data algorithm framework centered on dynamic systems theory. Furthermore, to compare predictive models under various algorithmic frameworks and validate the efficacy of the optimal model in predicting the presence of pulmonary nodules. Methods A total of 213 subjects were prospectively enrolled from July 2022 to March 2023 at the Hospital of Chengdu University of Traditional Chinese Medicine, Sichuan Cancer Hospital, and the Chengdu Integrated Traditional Chinese and Western Medicine Hospital. This cohort included 173 patients with pulmonary nodules and 40 healthy subjects. A novel multimodal data algorithm framework centered on dynamic systems theory, termed VAEGANTF (Variational Auto Encoder-Generative Adversarial Network-Transformer), was proposed. Subsequently, based on a multi-dimensional integrated dataset of “clinical features-syndrome elements-microorganisms”, all subjects were divided into training (70%) and testing (30%) sets for model construction and efficacy testing, respectively. Using pulmonary nodules as dependent variables, and combining candidate markers such as clinical features, lesion location, disease nature, and microbial genera, the independent variables were screened based on variable importance ranking after identifying and addressing multicollinearity. Missing values were then imputed, and data were standardized. Eight machine learning algorithms were then employed to construct pulmonary nodule risk prediction models: random forest, least absolute shrinkage and selection operator (LASSO) regression, support vector machine, multilayer perceptron, eXtreme Gradient Boosting (XGBoost), VAE-ViT (Vision Transformer), GAN-ViT, and VAEGANTF. K-fold cross-validation was used for model parameter tuning and optimization. The efficacy of the eight predictive models was evaluated using confusion matrices and receiver operating characteristic (ROC) curves, and the optimal model was selected. Finally, goodness-of-fit testing and decision curve analysis (DCA) were performed to evaluate the optimal model. Results There were no statistically significant differences between the two groups in demographic characteristics such as age and sex. The 213 subjects were randomly divided into training and testing sets (7 : 3), and prediction models were constructed using the eight machine learning algorithms. After excluding potential problems such as multicollinearity, a total of 301 clinical feature information, syndrome elements, and microbial genera markers were included for model construction. The area under the curve (AUC) values of the random forest, LASSO regression, support vector machine, multilayer perceptron, and VAE-ViT models did not reach 0.85, indicating poor efficacy. The AUC values of the XGBoost, GAN-ViT, and VAEGANTF models all reached above 0.85, with the VAEGANTF model exhibiting the highest AUC value (AUC=0.923). Goodness-of-fit testing indicated good calibration ability of the VAEGANTF model, and decision curve analysis showed a high degree of clinical benefit. The nomogram results showed that age, sex, heart, lung, Qixu, blood stasis, dampness, Porphyromonas genus, Granulicatella genus, Neisseria genus, Haemophilus genus, and Actinobacillus genus could be used as predictors. Conclusion The “disease-syndrome combination” risk prediction model for pulmonary nodules based on the VAEGANTF algorithm framework, which incorporates multi-dimensional data features of “clinical features-syndrome elements-microorganisms”, demonstrates better performance compared to other machine learning algorithms and has certain reference value for early non-invasive diagnosis of pulmonary nodules.

This study investigated the effects and action mechanism of tannins from Galla chinensis cream(TGCC) on the skin wound of rat tail. Male Sprague Dawley(SD) rats were randomly divided into a control group, model group, model+low-dose TGCC(50 mg per rat) group, model+high-dose TGCC group(100 mg per rat), and model+TGC+FAK inhibitor(Y15) cream(100 mg+10 mg per rat) group, with 10 rats in each group. After the rat tail skin injury model was successfully constructed, in the treatment group, corresponding drugs were applied to the wound surface, while in the control and model groups, the same amount of cream base as the TGCC group was applied by the same method. Then, sterile gauze was wrapped around the wound edge, and these operations were performed three times a day for 28 consecutive days. The wound healing status at the third, seventh, eleventh, fourteenth, twenty-first, and twenty-eighth days was recorded, and the wound healing rate and healing time were calculated. On the day after the last dose of medication, rat serum and tail skin wound tissue were collected for analyzing the activities of serum alanine aminotransferase(ALT), aspartate aminotransferase(AST), creatinine(CREA), urea, reactive oxygen species(ROS), interferon gamma(IFN-γ), interleukin(IL)-1β, IL-6, IL-4, IL-10, tumor necrosis factor(TNF)-α, as well as catalase(CAT), glutathione(GSH), lactate dehydrogenase(LDH), malondialdehyde(MDA), myeloperoxidase(MPO), superoxide dismutase(SOD), total antioxidant capacity(T-AOC), platelet endothelial cell adhesion molecule-1(CD31), and leukocyte differentiation antigen 34(CD34) in the wound tissue of rat tail skin. Hematoxylin-eosin, Masson, and sirius red staining were used to observe the morphological changes in the wound tissue of rat tail skin. The thickness of the epidermis, the number of fibroblasts and blood vessels, and the contents of collagen fibers, typeⅠ collagen(COLⅠ), and COLⅢ were calculated. The mRNA expressions of keratin 10(KRT10), KRT14, vascular endothelial growth factor(VEGF), fibroblast growth factor(FGF), epidermal growth factor(EGF), CD31, CD34, matrix metallopeptidase-2(MMP-2), MMP-9, COLⅠ, COLⅢ, desmin, fibroblast specific protein 1(FSP1), IFN-γ, IL-1β, TNF-α, IL-4, IL-6, and IL-10 in skin wound tissue were determined by quantitative real-time polymerase chain reaction(PCR). Western blot was utilized to detect the protein expressions of KRT10, KRT14, VEGF, FGF, EGF, MMP-2, MMP-9, COLⅠ, COLⅢ, desmin, FSP1, focal adhesion kinase(FAK), phosphorylated focal adhesion kinase(p-FAK), phosphatidylin-ositol-3-kinase(PI3K), phosphorylated phosphatidylin-ositol-3-kinase(p-PI3K), protein kinase B(Akt), phosphorylated protein kinase B(p-Akt), mammalian target of rapamycin(mTOR), and phosphorylated mammalian target of rapamycin(p-mTOR). The results manifest that TGCC can dramatically elevate the healing rate of rat tail wounds and shorten wound healing time. Besides, it can reduce serum ROS levels, the contents of MDA, MPO, and LDH in the rat skin wound tissue, as well as the serum IFN-γ, IL-1β, IL-6, and TNF-α levels and the mRNA expression levels of IFN-γ, IL-1β, IL-6, and TNF-α in the skin wound tissue. It can elevate the activities of CAT, GSH, SOD, and T-AOC in wound tissue, the IL-4 and IL-10 contents in serum, and the mRNA expressions of IL-4 and IL-10 in the wound tissue. In addition, TGGC can inhibit inflammatory cell infiltration and increase the epidermal thickness, counts of fibroblasts and blood vessels, and contents of collagen fibers, COLⅠ, and COLⅢ. Besides, TGCC can elevate the mRNA and protein expressions of epidermal differentiation markers(KRT10 and KRT14), endothelial cell markers(CD31 and CD34), angiogenesis and fibroblast proliferation, differentiation markers(VEGF, FGF, EGF, COLⅠ, COLⅢ, desmin, and FSP1), reduce the mRNA and protein expressions of gelatinases(MMP-2 and MMP-9), and increase protein expressions of p-FAK, p-PI3K, p-Akt, p-mTOR, as well as ratios of p-FAK/FAK, p-PI3K/PI3K, p-Akt/Akt, and p-mTOR/mTOR. These results suggest that TGCC can significantly facilitate skin wound healing, and its mechanism may be related to the activation of the FAK/PI3K/Akt/mTOR signaling pathway, inhibition of inflammatory cell infiltration in skin wound tissue, elevation of epidermal thickness, counts of fibroblasts and vessels, and contents of collagen fiber, COLⅠ, and COLⅢ, and reduction of MMP-2 and MMP-9 expressions, thus accelerating wound healing.
Animals ; Male ; Wound Healing/drug effects* ; Rats ; Rats, Sprague-Dawley ; Signal Transduction/drug effects* ; TOR Serine-Threonine Kinases/genetics* ; Phosphatidylinositol 3-Kinases/genetics* ; Skin/metabolism* ; Proto-Oncogene Proteins c-akt/genetics* ; Tannins/pharmacology* ; Humans ; Drugs, Chinese Herbal/administration & dosage* ; Focal Adhesion Kinase 1/genetics*

This study aims to explore the mechanism of lung and gut protection by Tanreqing Capsules on the mice infected with influenza virus based on "the lung-gut axis". A total of 110 C57BL/6J mice were randomized into control group, model group, oseltamivir group, and low-and high-dose Tanreqing Capsules groups. Ten mice in each group underwent body weight protection experiments, and the remaining 12 mice underwent experiments for mechanism exploration. Mice were infected with influenza virus A/Puerto Rico/08/1934(PR8) via nasal inhalation for the modeling. The lung tissue was collected on day 3 after gavage, and the lung tissue, colon tissue, and feces were collected on day 7 after gavage for subsequent testing. The results showed that Tanreqing Capsules alleviated the body weight reduction and increased the survival rate caused by PR8 infection. Compared with model group, Tanreqing Capsules can alleviate the lung injury by reducing the lung index, alleviating inflammation and edema in the lung tissue, down-regulating viral gene expression at the late stage of infection, reducing the percentage of neutrophils, and increasing the percentage of T cells. Tanreqing Capsules relieved the gut injury by restoring the colon length, increasing intestinal lumen mucin secretion, alleviating intestinal inflammation, and reducing goblet cell destruction. The gut microbiota analysis showed that Tanreqing Capsules increased species diversity compared with model group. At the phylum level, Tanreqing Capsules significantly increased the abundance of Firmicutes and Actinobacteria, while reducing the abundance of Bacteroidota and Proteobacteria to maintain gut microbiota balance. At the genus level, Tanreqing Capsules significantly increased the abundance of unclassified＿f＿Lachnospiraceae while reducing the abundance of Bacteroides, Eubacterium, and Phocaeicola to maintain gut microbiota balance. In conclusion, Tanreqing Capsules can alleviate mouse lung and gut injury caused by influenza virus infection and restore the balance of gut microbiota. Treating influenza from the lung and gut can provide new ideas for clinical practice.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Mice ; Lung/metabolism* ; Mice, Inbred C57BL ; Capsules ; Orthomyxoviridae Infections/virology* ; Gastrointestinal Microbiome/drug effects* ; Male ; Humans ; Female ; Influenza A virus/physiology* ; Influenza, Human/virology*

Objective To explore the efficacy differences between 3 Tesla magnetic resonance imaging with zero echo time(3T MRI ZTE)and high resolution computed tomography(HRCT)in the detection of pulmonary nodules and the classification diagnosis of the lung imaging reporting and data system(Lung-RADS)in sub-health populations.Methods Clinical and imaging data of 93 patients with pulmonary nodules(126 nodules in total)admitted to some hospital from July to December 2023 were retrospectively analyzed.The 126 nodules were categorized into a benign nodule group(n=51)and a malignant nodule group(n=75)using pathological findings as the gold standard.All the patients underwent examinations by 3T MRI ZTE and HRCT to compare the detection rates of the two measures for pulmonary nodules;the missed and misdiagnosis rates of 3T MRI ZTE,HRCT and Lung-RADS grading were contrasted with the postoperative pathological diagnosis results as the gold standard;comparison analyses of 3T MRI ZTE signs and HRCT signs were performed between the two groups and the patients with different Lung-RADS grades;3T MRI ZTE,HRCT and Lung-RADS grading were compared with the receiver operating characteristic(ROC)curve in terms of diagnosis efficacy for pulmonary nodules,and the consistency analysis was carried out.Results No discernible statistical variation was observed in the detection rates of pulmonary nodules between 3T MRI ZTE and HRCT(P>0.05).Lung-RADS grading had the highest rates of missed diagnosis and misdiagnosis,and 3T MRI ZTE and HRCT had similar detection rates.The malignant nodule group was different from the benign nodule group in the 3T MRI ZTE and HRCT signs in terms of lesion size,spiculation sign,lobulation sign,calcifica-tion,pleural indentation sign,cavity sign,boundary and bronchial cut-off sign,with the differences being statistically signi-ficant(all P<0.05).For the patients of Lung-RADS grade 3,the 3T MRI ZTE and HRCT signs had significant differences in terms of lesion size,spiculation sign,lobulation sign,calcification,pleural indentation sign,cavity sign and bronchial cut-off sign(all P<0.05).For the patients of Lung-RADS grade 4A,the 3T MRI ZTE and HRCT signs had significant differen-ces in terms of lesion size,calcification,boundary and bronchial cut-off sign(all P<0.05).For the patients of Lung-RADS grade 4B,the 3T MRI ZTE and HRCT signs had significant differences in terms of lesion size and calcification(all P<0.05).For the patients of Lung-RADS grade 4X,there were no significant differences found between the 3T MRI ZTE and HRCT signs(all P>0.05).HRCT had the highest sensitivity,specificity,accuracy,AUC value,predictive values and Kappa value for benign and malignant nodules,3T MRI ZTE had the values slightly lower than those of HRCT,and Lung-RADS grading had the lowest values when compared with HRCT and 3T MRI ZTE.Conclusion HRCT and 3T MRI ZTE are complementary for the evaluation of pulmonary nodules,and the differences in imaging signs between them show graded dependence.3T MRI ZTE and HRCT have no significant differences in the detection rate of pulmonary nodules,while HRCT gains advanta-ges in differentiating benign and malignant pulmonary nodules,and references are provided for the screening and clinical early diagnosis of pulmonary nodules.[Chinese Medical Equipment Journal,2025,46(9):52-59]