Objective By combining biological detection and imaging evaluation, a clinical prediction model is constructed based on a large cohort to improve the accuracy of distinguishing between benign and malignant pulmonary nodules. Methods A retrospective analysis was conducted on the clinical data of the 32 627 patients with pulmonary nodules who underwent chest CT and testing for 7 types of lung cancer-related serum autoantibodies (7-AABs) at our hospital from January 2020 to April 2024. The univariate and multivariate logistic regression models were performed to screen independent risk factors for benign and malignant pulmonary nodules, based on which a nomogram model was established. The performance of the model was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Results A total of 1 017 patients with pulmonary nodules were included in the study. The training set consisted of 712 patients, including 291 males and 421 females, with a mean age of (58±12) years. The validation set included 305 patients, comprising 129 males and 176 females, with a mean age of (58±13) years. Univariate ROC curve analysis indicated that the combination of CT and 7-AABs testing achieved the highest area under the curve (AUC) value (0.794), surpassing the diagnostic efficacy of CT alone (AUC=0.667) or 7-AABs alone (AUC=0.514). Multivariate logistic regression analysis showed that radiological nodule diameter, nodule nature, and CT combined with 7-AABs detection were independent predictors, which were used to construct a nomogram prediction model. The AUC values for this model were 0.826 and 0.862 in the training and validation sets, respectively, demonstrating excellent performance in DCA. Conclusion The combination of 7-AABs with CT significantly enhances the accuracy of distinguishing between benign and malignant pulmonary nodules. The developed predictive model provides strong support for clinical decision-making and contributes to achieving precise diagnosis and treatment of pulmonary nodules.

With the widespread adoption of low-dose CT screening and the extensive application of high-resolution CT, the detection rate of sub-centimeter lung nodules has significantly increased. How to scientifically manage these nodules while avoiding overtreatment and diagnostic delays has become an important clinical issue. Among them, lung nodules with a consolidation tumor ratio less than 0.25, dominated by ground-glass shadows, are particularly worthy of attention. The therapeutic challenge for this group is how to achieve precise and complete resection of nodules during surgery while maximizing the preservation of the patient's lung function. The "watershed topography map" is a new technology based on big data and artificial intelligence algorithms. This method uses Dicom data from conventional dose CT scans, combined with microscopic (22-24 levels) capillary network anatomical watershed features, to generate high-precision simulated natural segmentation planes of lung sub-segments through specific textures and forms. This technology forms fluorescent watershed boundaries on the lung surface, which highly fit the actual lung anatomical structure. By analyzing the adjacent relationship between the nodule and the watershed boundary, real-time, visually accurate positioning of the nodule can be achieved. This innovative technology provides a new solution for the intraoperative positioning and resection of lung nodules. This consensus was led by four major domestic societies, jointly with expert teams in related fields, oriented to clinical practical needs, referring to domestic and foreign guidelines and consensus, and finally formed after multiple rounds of consultation, discussion, and voting. The main content covers the theoretical basis of the "watershed topography map" technology, indications, operation procedures, surgical planning details, and postoperative evaluation standards, aiming to provide scientific guidance and exploration directions for clinical peers who are currently or plan to carry out lung nodule resection using the fluorescent microscope watershed analysis method.

ObjectiveTo investigate the protective effect and underlying mechanisms of Yishen Huayu prescription （YSHYP） on transdifferentiation of mouse renal tubular epithelial cells （TCMK-1） induced by transforming growth factor-β₁ （TGF-β₁）. MethodsA transdifferentiation model was established by treating TCMK-1 cells with 10 μg·L^-1 TGF-β₁. Experimental groups were established using 2 μmol·L^-1 silent information regulator 1 （SIRT1） inhibitor EX527. These included the blank group， model group， YSHYP group （treated with 10% YSHYP-medicated serum）， valsartan group （treated with 10% valsartan-medicated serum）， EX527+TGF-β₁ group， EX527+YSHYP group， and EX527 group. Immunofluorescence was used to detect the protein localization of α-smooth muscle actin （α-SMA）， E-cadherin， and microtubule-associated protein light chain 3 （LC3）. Western blot and Real-time polymerase chain reaction （Real-time PCR） were used to assess the expression of proteins and mRNA related to transdifferentiation， autophagy， and associated signaling pathways. ResultsThe results from Real-time PCR and Western blot indicate that compared with those in the blank group， expression levels of α-SMA， ubiquitin-binding protein p62 （p62）， and acetylated forkhead box protein O1（Ac-FoxO1） were significantly increased in the model group， EX527+TGF-β₁ group， and EX527 group （P<0.01）. Compared with that in the model group， the expression of α-SMA and p62 were significantly downregulated in the YSHYP and valsartan groups （P<0.05， P<0.01）. Ac-FoxO1 protein levels were significantly reduced in the YSHYP group （P<0.05）， while the valsartan group showed no significant changes in Ac-FoxO1 levels. Compared with the YSHYP group， the valsartan group showed significant differences in p62 mRNA， α-SMA， and p62 protein expression （P<0.05）. Compared with those in the blank group， LC3， Beclin1， SIRT1， and forkhead box protein O1 （FoxO1） expression levels were significantly decreased in the model group， EX527+TGF-β₁ group， and EX527 group （P<0.01）. In the model and EX527+TGF-β₁ groups， E-cadherin expression levels were significantly reduced （P<0.01）， while the EX527 group showed no statistically significant change. Compared with the model group， E-cadherin， LC3， Beclin1， SIRT1， and FoxO1 expression levels were significantly increased in both the YSHYP and valsartan groups （P<0.01， P<0.05）. Compared with the YSHYP group， the valsartan group exhibited significant differences in LC3， SIRT1， and FoxO1 mRNA expression （P<0.05， P<0.01）. Immunofluorescence results were consistent with those of Western blot and Real-time PCR. ConclusionYSHYP may protect TCMK-1 cells by activating the SIRT1/FoxO1 pathway， thereby promoting autophagy and restoring the autophagy flux to reduce the extent of transdifferentiation of TCMK-1 cells.

ObjectiveTo investigate the protective effect and underlying mechanisms of Yishen Huayu prescription （YSHYP） on transdifferentiation of mouse renal tubular epithelial cells （TCMK-1） induced by transforming growth factor-β₁ （TGF-β₁）. MethodsA transdifferentiation model was established by treating TCMK-1 cells with 10 μg·L^-1 TGF-β₁. Experimental groups were established using 2 μmol·L^-1 silent information regulator 1 （SIRT1） inhibitor EX527. These included the blank group， model group， YSHYP group （treated with 10% YSHYP-medicated serum）， valsartan group （treated with 10% valsartan-medicated serum）， EX527+TGF-β₁ group， EX527+YSHYP group， and EX527 group. Immunofluorescence was used to detect the protein localization of α-smooth muscle actin （α-SMA）， E-cadherin， and microtubule-associated protein light chain 3 （LC3）. Western blot and Real-time polymerase chain reaction （Real-time PCR） were used to assess the expression of proteins and mRNA related to transdifferentiation， autophagy， and associated signaling pathways. ResultsThe results from Real-time PCR and Western blot indicate that compared with those in the blank group， expression levels of α-SMA， ubiquitin-binding protein p62 （p62）， and acetylated forkhead box protein O1（Ac-FoxO1） were significantly increased in the model group， EX527+TGF-β₁ group， and EX527 group （P<0.01）. Compared with that in the model group， the expression of α-SMA and p62 were significantly downregulated in the YSHYP and valsartan groups （P<0.05， P<0.01）. Ac-FoxO1 protein levels were significantly reduced in the YSHYP group （P<0.05）， while the valsartan group showed no significant changes in Ac-FoxO1 levels. Compared with the YSHYP group， the valsartan group showed significant differences in p62 mRNA， α-SMA， and p62 protein expression （P<0.05）. Compared with those in the blank group， LC3， Beclin1， SIRT1， and forkhead box protein O1 （FoxO1） expression levels were significantly decreased in the model group， EX527+TGF-β₁ group， and EX527 group （P<0.01）. In the model and EX527+TGF-β₁ groups， E-cadherin expression levels were significantly reduced （P<0.01）， while the EX527 group showed no statistically significant change. Compared with the model group， E-cadherin， LC3， Beclin1， SIRT1， and FoxO1 expression levels were significantly increased in both the YSHYP and valsartan groups （P<0.01， P<0.05）. Compared with the YSHYP group， the valsartan group exhibited significant differences in LC3， SIRT1， and FoxO1 mRNA expression （P<0.05， P<0.01）. Immunofluorescence results were consistent with those of Western blot and Real-time PCR. ConclusionYSHYP may protect TCMK-1 cells by activating the SIRT1/FoxO1 pathway， thereby promoting autophagy and restoring the autophagy flux to reduce the extent of transdifferentiation of TCMK-1 cells.

Animal experiments are widely used in biomedical research for safety assessment, toxicological analysis, efficacy evaluation, and mechanism exploration. In recent years, the ethical review system has become more stringent, and awareness of animal welfare has continuously increased. To promote more efficient and cost-effective drug research and development, the United States passed the Food and Drug Administration (FDA) Modernization Act 2.0 in September 2022, which removed the federal mandate requiring animal testing in preclinical drug research. In April 2025, the FDA further proposed to adopt a series of "new alternative methods" in the research and development of drugs such as monoclonal antibodies, which included artificial intelligence computing models, organoid toxicity tests, and 3D micro-physiological systems, thereby gradually phasing out traditional animal experiment models. Among these cutting-edge technologies, 3D bioprinting models are a significant alternative and complement to animal models, owing to their high biomimetic properties, reproducibility, and scalability. This review provides a comprehensive overview of advancements and applications of 3D bioprinting technology in the fields of biomedical and pharmaceutical research. It starts by detailing the essential elements of 3D bioprinting, including the selection and functional design of biomaterials, along with an explanation of the principles and characteristics of various printing strategies, highlighting the advantages in constructing complex multicellular spatial structures, regulating microenvironments, and guiding cell fate. It then discusses the typical applications of 3D bioprinting in drug research and development,including high-throughput screening of drug efficacy by constructing disease models such as tumors, infectious diseases, and rare diseases, as well as conducting drug toxicology research by building organ-specific models such as those of liver and heart. Additionally,the review examines the role of 3D bioprinting in tissue engineering, discussing its contributions to the construction of functional tissues such as bone, cartilage, skin, and blood vessels, as well as the latest progress in regeneration and replacement. Furthermore, this review analyzes the complementary advantages of 3D bioprinting models and animal models in the research of disease progression, drug mechanisms, precision medicine, drug development, and tissue regeneration, and discusses the potential and challenges of their integration in improving model accuracy and physiological relevance. In conclusion, as a cutting-edge in vitro modeling and manufacturing technology, 3D bioprinting is gradually establishing a comprehensive application system covering disease modeling, drug screening, toxicity prediction, and tissue regeneration.

Animal experiments are widely used in biomedical research for safety assessment, toxicological analysis, efficacy evaluation, and mechanism exploration. In recent years, the ethical review system has become more stringent, and awareness of animal welfare has continuously increased. To promote more efficient and cost-effective drug research and development, the United States passed the Food and Drug Administration (FDA) Modernization Act 2.0 in September 2022, which removed the federal mandate requiring animal testing in preclinical drug research. In April 2025, the FDA further proposed to adopt a series of "new alternative methods" in the research and development of drugs such as monoclonal antibodies, which included artificial intelligence computing models, organoid toxicity tests, and 3D micro-physiological systems, thereby gradually phasing out traditional animal experiment models. Among these cutting-edge technologies, 3D bioprinting models are a significant alternative and complement to animal models, owing to their high biomimetic properties, reproducibility, and scalability. This review provides a comprehensive overview of advancements and applications of 3D bioprinting technology in the fields of biomedical and pharmaceutical research. It starts by detailing the essential elements of 3D bioprinting, including the selection and functional design of biomaterials, along with an explanation of the principles and characteristics of various printing strategies, highlighting the advantages in constructing complex multicellular spatial structures, regulating microenvironments, and guiding cell fate. It then discusses the typical applications of 3D bioprinting in drug research and development,including high-throughput screening of drug efficacy by constructing disease models such as tumors, infectious diseases, and rare diseases, as well as conducting drug toxicology research by building organ-specific models such as those of liver and heart. Additionally,the review examines the role of 3D bioprinting in tissue engineering, discussing its contributions to the construction of functional tissues such as bone, cartilage, skin, and blood vessels, as well as the latest progress in regeneration and replacement. Furthermore, this review analyzes the complementary advantages of 3D bioprinting models and animal models in the research of disease progression, drug mechanisms, precision medicine, drug development, and tissue regeneration, and discusses the potential and challenges of their integration in improving model accuracy and physiological relevance. In conclusion, as a cutting-edge in vitro modeling and manufacturing technology, 3D bioprinting is gradually establishing a comprehensive application system covering disease modeling, drug screening, toxicity prediction, and tissue regeneration.

AIM: To investigate the research status and hotspots in the field of ocular trauma over the past two decades using bibliometric software CiteSpace and VOSviewer.METHODS: A bibliometric study. Relevant literature on ocular trauma published in the past 20 a was retrieved from the CNKI database and Web of Science Core Collection in June 2025. EndNote X9 was used for literature management and verification. Microsoft Office Excel 2019 was employed for data management and statistics, with graphical representations created for frequency data. CiteSpace and VOSviewer were utilized to construct and analyze visual maps of authors, institutions, countries/regions, journals, and keywords.RESULTS: A total of 3 437 valid articles were included(911 in Chinese, 2 526 in English). English publications grew at an average annual rate of 12.7%(peak: 289 articles in 2021), while Chinese articles decreased from 31.2% in 2005(peak: 149 articles)to 6.3% in 2024. Chinese scholars showed an early surge in output but a subsequent declining trend, necessitating enhanced sustained research investment and translational outcomes. The United States(682 articles), China(272 articles), and India(206 articles)formed a core collaborative triangle, with a transnational collaboration rate of 68.2%. Six author clusters(e.g., Yan Hua/Zhang Maonian, et al.)demonstrated strong intra-group collaboration but minimal inter-group cooperation. Analysis of high-frequency keywords and burst terms revealed six global research hotspots: 1)ocular trauma score and minimally invasive vitrectomy; 2)optical coherence tomography(OCT)/ultrasound biomicroscopy(UBM)-guided diagnosis and management of intraocular foreign bodies; 3)amniotic membrane transplantation for chemical injury repair; 4)multimodal assessment of corneal perforation injuries; 5)inflammatory indicators for diagnosing endophthalmitis as a traumatic complication; 6)family-based interventions for preventing and controlling pediatric ocular trauma. Trends indicate a shift in research focus from emergency care toward artificial substitutes and full-cycle nursing rehabilitation.CONCLUSION: Differences in research outputs between China and other countries reflect imbalances in prevention policies and medical resource allocation. China should strengthen sustained investment and overcome collaboration barriers to jointly advance ocular trauma research toward full-cycle precision management.

With the widespread use of antimicrobial agents, bacterial drug resistance has become an increasingly severe issue, posing significant challenges to global healthcare. Traditional Chinese medicine (TCM) has emerged as a research focus in the field of bacterial resistance due to its broad sources, high safety profile, low toxicity, and antimicrobial mechanisms distinct from those of chemical drugs. Studies have shown that various TCM herbs, such as Scutellaria baicalensis, exert antibacterial effects through multiple pathways, including disrupting the integrity of bacterial cell walls and membranes, inhibiting nucleic acid and protein synthesis, and impairing energy production and metabolism. Additionally, certain TCM herbs, including Scutellaria baicalensis, Coptis chinensis, and Fritillaria thunbergii, can reverse antimicrobial resistance by eliminating resistant plasmids, inhibiting bacterial efflux pump function, and suppressing β-lactamase activity. TCM holds promising potential for antibacterial applications and synergistically reversing antimicrobial resistance, though systematic analyses remain limited. This review summarizes the mechanisms of antibacterial action of TCM and current research on its synergistic use with antimicrobial agents to reverse drug resistance, aiming to provide insights for developing novel TCM-based antimicrobials and addressing bacterial resistance.

OBJECTIVE To construct ensemble learning models for predicting high-use days of budesonide based on meteorological factors， thereby providing reference for hospital pharmacy management. METHODS Meteorological data for 2024 and outpatient budesonide usage data from the jurisdiction of Sanming Hospital of Integrated Traditional Chinese and Western Medicine were collected. High-use days were defined as the 75th percentile of outpatient budesonide usage， and a corresponding dataset was established. The prediction task was formulated as a classification problem， and three ensemble learning models were developed： Random Forest， Extreme Gradient Boosting （XGBoost）， and Histogram-based Gradient Boosting Classifier. Model performance was evaluated using accuracy， precision， recall， F1-score， and log-loss. Model interpretability was analyzed using Shapley Additive Explanations （SHAP）. RESULTS The Histogram-based Gradient Boosting Classifier achieved the best performance （accuracy＝0.75， F1-score＝0.48）， followed by XGBoost （accuracy＝0.74， F1-score＝0.43） and Random Forest （accuracy＝0.72， F1-score＝0.22）. SHAP results suggested that the prediction results of the last two models have the highest correction. CONCLUSIONS Ensemble learning models can effectively predict high-use days of budesonide， with the Histogram- based Gradient Boosting Classifier demonstrating the best predictive performance. Low temperature， high humidity， and low atmospheric pressure show significant positive impacts on the prediction of daily budesonide usage.

Objective To understand and grasp the status quo of resistance of Culex pipiens pallens to four commonly used insecticides in Hefei City, and to provide a scientific basis for the chemical control of mosquito larvae. Methods From June to July 2023, Cx. pipiens pallens larvae were collected from 9 counties (cities and districts) in Hefei City. The LC50 of late third-instar to early fourth-instar larvae of Cx. pipiens pallens to commonly used insecticides was determined by larval immersion method (sensitive baseline method). Results Cx.pipiens pallens larvae in Hefei City exhibited different degrees of resistance to four insecticides: permethrin, beta-cypermethrin, temephos, and propoxur. The relative resistance coefficients to permethrin and beta-cypermethrin were 26.96 and 21.17, respectively, indicating the moderate resistance level. The relative resistance coefficients to propoxur were 6.70, indicating a low resistance level. The relative resistance coefficient to temephos was 2.43, indicating a sensitivity level. Culex pipiens pallens against pyrethroids such as 0.25% permethrin, 0.025% deltamethrin and 0.025% cypermethrin in 1 h knockout rate and 24 h mortality rates were 3.25% (4/123) and 46.34% (57/123), 3.60% (5/139) and 35.97% (50/139), 3.85% (6/156) and 40.38% (63/156), respectively. For 5% malathion and 0.1% propoxur, the 1 h knockdown rate and 24 h mortality rate were 97.69% (127/130) and 99.23% (129/130), 94.48% (137/145) and 100.00% (145/145), respectively. It showed resistance to 0.25% permethrin, 0.025% deltamethrin and 0.025% cypermethrin, and sensitivity to 5% malathion and 0.1% propoxur. Conclusions Culex pipiens pallens in Hefei City have developed varying degrees of resistance to parathyroid and carbamate insecticides. In the control of mosquito vectors, it is essential to strengthen the scientific and rational use of chemical control in combination with environmental and physical control measures to form an integrated control strategy. This approach will improve the control efficiency while delaying the occurrence and development of insecticide resistance.