Objective To analyze the distribution status of the end digits of standardized blood pressure measurement recordings in the clinic and the effectiveness of standardized blood pressure measurement for community hypertension screening. Methods The first visit blood pressure measurement data from the Community Health Service Center in Jing'an District, Shanghai from June 2023 to May 2024 were collected and analyzed. According to different measurement methods, the data were divided into two groups: standardized blood pressure measurement and conventional blood pressure measurement. SPSS 19.0 software was used for data analysis. The differences in the distribution balance of the end digits of blood pressure values and the detection rate of blood pressure elevation between the two different groups were analyzed. Results The frequency range of the end digits of blood pressure recorded values in the standardized pressure measurement group was 9.42% to 10.83%, and the detection rate of elevated blood pressure was 24.89%. The conventional pressure measurement group had a preference of the end digit ^"0^", and the detection rate of elevated blood pressure was only 2.12%. The results of multiple logistic regression analysis showed that gender, age, season, and different blood pressure measurement modes were all influencing factors for the detection rate of elevated blood pressure. Conclusion The standardized blood pressure measurement mode in the clinic is suitable for community hypertension screening and pressure measurement, with higher data quality than the conventional pressure measurement mode.

To improve the targeted therapeutic effect of magnolol (Mag) on neuroblastoma, Mag-loaded mitochondria-targeting immunoliposomes modified by datuximab (aGD2) and triphenylphosphine (TPP) (Mag/aGD2-T-ILN) were prepared, and their physicochemical properties, targeting characteristics and anti-tumor activity were evaluated. Physico-chemical properties showed that the surface of Mag/aGD2-T-ILN was smooth and spherical, with good dispersibility. The particle sizes, PDI and Zeta potentials of Mag/aGD2-T-ILN were measured to be (136.5 ± 5.1) nm, 0.184 ± 0.010 and (27.5 ± 3.6) mV, respectively. Mag/aGD2-T-ILN could release the drug continuously and slowly, and maintain good stability at 4 ℃. Cytotoxicity test exhibited that the IC50 of 2-ME/aGD2-T-ILN was (4.07 ± 0.48) µmol/L, and compared with free Mag, the toxicity of Mag/aGD2-T-ILN to SH-SY5Y cells increased by 6.4 times. Cellular binding and uptake assays suggested that Rho-aGD2-T-ILN could specifically target GD2-positive tumor cells and then further reach their mitochondria. Therapeutic efficacy indicated that Mag/aGD2-T-ILN could better suppress the growth of SH-SY5Y tumor cells in the body with lower toxicity and less side-effects. The results demonstrated that the Mag/aGD2-T-ILN nanoparticles system could achieve intracellular endocytosis through specific binding of antibodies and antigens between the carrier and the surface of tumor cells and electrostatic interaction, then effectively delivered and released the drugs into mitochondria by crossing the mitochondrial phospholipid membrane through TPP, and thus achieving mitochondria-targeting therapy of Mag/aGD2-T-ILN. Through the construction of this active targeting delivery system, the clinical application value of datuximab and Mag is improved, providing a novel approach for the clinical treatment of neuroblastoma.

BACKGROUND:Nanocell vesicles possess functions such as re-epithelialization,antioxidation,anti-inflammation,and regulation of extracellular matrix remodeling.Meanwhile,apoptotic bodies have the immunomodulatory effects.Therefore,the combination of the two to form nanofusion vesicles can synergistically promote the healing of diabetic skin wounds.OBJECTIVE:To elucidate the impact of nanofusion vesicles on skin wound healing in a diabetic murine model.METHODS:(1)Material preparation and characterization:The primary bone marrow mesenchymal stem cells of C57BL/6J neonatal mice and the neutrophil apoptotic bodies of C57BL/6J mice were isolated and extracted.The nanofusion vesicles were prepared by micro-extrusion mechanism.(2)In vitro experiment:MTT assay was used to detect the proliferative effect of different concentrations of nanofusion vesicles on NIH-3T3 cells and human umbilical vein endothelial cells.Reactive oxygen species fluorescence probe was used to detect the antioxidant effect of nano-fusion vesicles on NIH-3T3 cells treated with hydrogen peroxide(H2O2).The inhibitory effect of nanofusion vesicles on RAW 264.7 macrophage inflammation induced by lipopolyside was detected by real-time quantitative RT-qPCR.(3)In vivo experiment:36 male C57BL/6J mice were employed to develop a murine model of diabetes mellitus.Following the successful induction of diabetes,two circular full-thickness wounds,each with a diameter of 6 mm,were created on either side of the diabetic mice's spine using a skin punch.The mice were divided into three groups by random number table method.The control group was injected with 0.1 mL of phosphate buffer solution.The nanovesicle group was injected with 0.1 mL nanovesicles(25 μg/mL).The nanofusion vesicle group was injected with 0.1 mL nanofusion(25 μg/mL)vesicles.After treatment for three consecutive days,the wound healing and histomorphological changes were observed.RESULTS AND CONCLUSION:(1)In vitro experiment:nanofusion vesicles,when administered at concentrations ranging from 0 to 100 μg/mL,exhibited no toxic effects and promoted the proliferation of NIH-3T3 and HUVEC cell lines.Notably,a concentration of 25 μg/mL nanofusion vesicle significantly enhanced the proliferation of NIH-3T3 cells.Furthermore,the survival rate of human umbilical vein endothelial cells was observed to increase in correlation with escalating concentrations of nanofusion vesicles.Nanofusion vesicles had a good antioxidant effect.In comparison to the H2O2 group,the fluorescence signal indicative of reactive oxygen species was progressively diminished in both the nanovesicle group and the nanofusion vesicle group.Furthermore,nanofusion vesicles possessed anti-inflammatory capabilities,effectively mitigating the inflammatory response in macrophages triggered by lipopolysaccharide stimulation.(2)In vivo experiment:Hematoxylin-eosin and Masson's trichrome staining revealed that in comparison to the control group,both the nanovesicle group and the nanofusion vesicle group exhibited a significant increase in granulation tissue formation and collagen fiber deposition within the wounds by day 6.Notably,the nanofusion vesicle group displayed the most pronounced effects.On day 12,the wound of nanofusion vesicle group was significantly reduced,and the healing rate was significantly faster than that of other groups(P＜0.01),and the effect of promoting wound healing was the most significant.Our findings demonstrated that nanofusion vesicles exhibited superior pro-cell proliferative,antioxidant,and anti-inflammatory properties,thereby exerting a beneficial effect on the promotion of skin wound healing in diabetic mouse models.

BACKGROUND:Nanocell vesicles possess functions such as re-epithelialization,antioxidation,anti-inflammation,and regulation of extracellular matrix remodeling.Meanwhile,apoptotic bodies have the immunomodulatory effects.Therefore,the combination of the two to form nanofusion vesicles can synergistically promote the healing of diabetic skin wounds.OBJECTIVE:To elucidate the impact of nanofusion vesicles on skin wound healing in a diabetic murine model.METHODS:(1)Material preparation and characterization:The primary bone marrow mesenchymal stem cells of C57BL/6J neonatal mice and the neutrophil apoptotic bodies of C57BL/6J mice were isolated and extracted.The nanofusion vesicles were prepared by micro-extrusion mechanism.(2)In vitro experiment:MTT assay was used to detect the proliferative effect of different concentrations of nanofusion vesicles on NIH-3T3 cells and human umbilical vein endothelial cells.Reactive oxygen species fluorescence probe was used to detect the antioxidant effect of nano-fusion vesicles on NIH-3T3 cells treated with hydrogen peroxide(H2O2).The inhibitory effect of nanofusion vesicles on RAW 264.7 macrophage inflammation induced by lipopolyside was detected by real-time quantitative RT-qPCR.(3)In vivo experiment:36 male C57BL/6J mice were employed to develop a murine model of diabetes mellitus.Following the successful induction of diabetes,two circular full-thickness wounds,each with a diameter of 6 mm,were created on either side of the diabetic mice's spine using a skin punch.The mice were divided into three groups by random number table method.The control group was injected with 0.1 mL of phosphate buffer solution.The nanovesicle group was injected with 0.1 mL nanovesicles(25 μg/mL).The nanofusion vesicle group was injected with 0.1 mL nanofusion(25 μg/mL)vesicles.After treatment for three consecutive days,the wound healing and histomorphological changes were observed.RESULTS AND CONCLUSION:(1)In vitro experiment:nanofusion vesicles,when administered at concentrations ranging from 0 to 100 μg/mL,exhibited no toxic effects and promoted the proliferation of NIH-3T3 and HUVEC cell lines.Notably,a concentration of 25 μg/mL nanofusion vesicle significantly enhanced the proliferation of NIH-3T3 cells.Furthermore,the survival rate of human umbilical vein endothelial cells was observed to increase in correlation with escalating concentrations of nanofusion vesicles.Nanofusion vesicles had a good antioxidant effect.In comparison to the H2O2 group,the fluorescence signal indicative of reactive oxygen species was progressively diminished in both the nanovesicle group and the nanofusion vesicle group.Furthermore,nanofusion vesicles possessed anti-inflammatory capabilities,effectively mitigating the inflammatory response in macrophages triggered by lipopolysaccharide stimulation.(2)In vivo experiment:Hematoxylin-eosin and Masson's trichrome staining revealed that in comparison to the control group,both the nanovesicle group and the nanofusion vesicle group exhibited a significant increase in granulation tissue formation and collagen fiber deposition within the wounds by day 6.Notably,the nanofusion vesicle group displayed the most pronounced effects.On day 12,the wound of nanofusion vesicle group was significantly reduced,and the healing rate was significantly faster than that of other groups(P＜0.01),and the effect of promoting wound healing was the most significant.Our findings demonstrated that nanofusion vesicles exhibited superior pro-cell proliferative,antioxidant,and anti-inflammatory properties,thereby exerting a beneficial effect on the promotion of skin wound healing in diabetic mouse models.

Background/Aims: Liver transplantation (LT) following total hepatectomy is a life-saving treatment for hepatocellular carcinoma (HCC). The HCC recurrence after LT hinders the effectiveness of the procedure. The objective of this study is to develop a pre-operative risk stratification model based on a liquid biopsy. Methods: We conducted a comprehensive multi-omics study of 260 HCC patients from three centers, including clinical data, low-coverage whole-genome sequencing of cell-free DNA (cfDNA) from plasma, as well as whole-exome, single-nucleus RNA, and spatial transcriptomics from matched tumor and non-tumor tissues. Results: We identified cfDNA-derived copy number alteration (CNA) signatures associated with post-transplant recurrence. By integrating cfDNA-derived CNA profiles with single-cell transcriptomic data, we traced recurrence-associated cfDNA to a distinct subpopulation of malignant cells within the primary tumor. These cells were embedded in a pro-metastatic microenvironment of specialized endothelial subtypes and cancer-associated fibroblasts. Notably, most recurrence-associated lesions were detectable in cfDNA prior to liver transplantation (LT). Building on these insights, we developed the ZJU Criteria based on CNA fragments and tumor markers, a pre-LT risk prediction tool that integrates conventional clinical factors with cfDNA-derived CNA signatures, and validated it using internal and independent external cohorts. Conclusion Our findings suggest that post-transplant recurrence commonly originates from advanced subclones that emerge late during tumor evolution. The ZJU Criteria provides an accurate, non-invasive strategy that significantly improves pre-LT risk stratification and clinical decision-making for patients with HCC.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

The mental health management of laboratory animals is a critical factor in ensuring the reliability of scientific research data. However, due to the subtle nature of mental state alterations and the limitations of current assessment methods, the mental health of laboratory animals is often overlooked by researchers. Therefore, there is an urgent need to explore a new, objective, simple, and practical method for evaluating mental health. Stress, as a primary factor inducing alterations in the mental state of animals, can influence experimental results across multiple research fields through the neuroendocrine-immune network. This paper first elucidates the necessity of mental health management in laboratory animals from three perspectives: factors contributing to stress, neural mechanisms of stress, and research areas affected by stress. It highlights that excluding animals with abnormal mental states before experiments can enhance the efficiency and reproducibility of biomedical studies. Second, this paper briefly summarizes existing methods for assessing the health of laboratory animals, pointing out that approaches such as behavioral tests and metabolomics have many limitations in evaluating stress responses. Existing methods struggle to meet the demand for simple, objective, and non-invasive assessment methods in animal management. Therefore, this paper focuses on hair, a biological sample with the advantages of cumulative information and non-invasive collection, and systematically describes the theoretical basis and technological advances in using hair characteristics as indicators of stress responses from three perspectives: hair traits, the levels of substances in hair, and artificial intelligence (AI). It proposes and supports an innovative technical pathway that combines hair traits with AI-based image analysis, with the aim of offering an improved solution for non-invasive and objective stress assessment, while providing theoretical support for improving the health management system of laboratory animals.

ObjectiveTo investigate the safety and efficacy of transparent cap-assisted peroral cholangiopancreatoscopy-guided electrohydraulic lithotripsy （EHL）. MethodsA retrospective analysis was performed for the clinical data of 60 patients with large common bile duct stones who were admitted to Department of Gastroenterology， Jilin People’s Hospital， from May 1， 2023 to January 31， 2026， and according to the treatment method， the patients were divided into transparent cap-assisted peroral cholangiopancreatoscopy-guided electrohydraulic lithotripsy group and peroral cholangiopancreatoscopy-guided electrohydraulic lithotripsy group， with 30 patients in each group. The two groups were compared in terms of the rate of successful single-session stone fragmentation and removal， procedural time， duration of electrohydraulic lithotripsy， clinical success rate， and complications. The independent-samples t test or the Mann-Whitney U test was used for comparison of continuous data between two groups， and the chi-square test or the Fisher’s exact test was used for comparison of categorical data between two groups. ResultsCompared with the peroral cholangiopancreatoscopy-guided electrohydraulic lithotripsy group， the transparent cap-assisted peroral cholangiopancreatoscopy-guided electrohydraulic lithotripsy group had a significantly higher technical success rate （83.33% vs 60.00%， χ²=4.022， P=0.045） and significantly shorter procedural time ［46.00 （42.25 — 49.00） min vs 54.50 （42.00 — 65.00） min， Z=2.012， P=0.044］ and duration of electrohydraulic lithotripsy ［8.00 （6.25 — 11.75） min vs 13.50 （9.25 — 17.75） min， Z=2.749， P=0.006］. Both groups achieved a clinical success rate of 100%， with no significant difference in the incidence rate of complications （P>0.05）. ConclusionTransparent cap-assisted peroral cholangiopancreatoscopy-guided electrohydraulic lithotripsy has a high rate of successful single-session stone fragmentation and removal and a short procedural time， with good safety and efficacy， and therefore， it holds promise for clinical application.

The occurrence of diabetes mellitus （DM） is closely related to insulin resistance and islet β cell dysfunction. Modern studies have found that macrophages are widely present in the liver，fat，skeletal muscle，islets， and other tissues and organs. Macrophage M1/M2 polarization plays an important role in the occurrence and development of diabetes mellitus and its related complications by intervening in inflammatory response，improving insulin resistance，and promoting tissue repair. Most of the traditional Chinese medicines that regulate the activation and polarization of macrophages are Qi-replenishing and Yin-nourishing，heat-clearing， and detoxicating medicinal，which are consistent with the etiology and pathogenesis of diabetes and its related complications. Therefore，by summarizing the mechanisms between macrophage activation，polarization， and insulin resistance in various tissues，this paper reviewed traditional Chinese medicine and its effective components and compounds in improving diabetes mellitus and its related complications through multi-channel regulation of macrophage polarization and regulation of M1/M2 ratio，providing references for the future treatment of DM and its related complications with traditional Chinese medicine.

Objective To compare the performance and efficacy of prognostic models constructed by different machine learning algorithms in predicting the survival period of lung transplantation (LTx) recipients. Methods Data from 483 recipients who underwent LTx were retrospectively collected. All recipients were divided into a training set and a validation set at a ratio of 7:3. The 24 collected variables were screened based on variable importance (VIMP). Prognostic models were constructed using random survival forest (RSF) and extreme gradient boosting tree (XGBoost). The performance of the models was evaluated using the integrated area under the curve (iAUC) and time-dependent area under the curve (tAUC). Results There were no significant statistical differences in the variables between the training set and the validation set. The top 15 variables ranked by VIMP were used for modeling and the length of stay in the intensive care unit (ICU) was determined as the most important factor. Compared with the XGBoost model, the RSF model demonstrated better performance in predicting the survival period of recipients (iAUC 0.773 vs. 0.723). The RSF model also showed better performance in predicting the 6-month survival period (tAUC _{6 months} 0.884 vs. 0.809, P = 0.009) and 1-year survival period (tAUC _{1 year} 0.896 vs. 0.825, P = 0.013) of recipients. Based on the prediction cut-off values of the two algorithms, LTx recipients were divided into high-risk and low-risk groups. The survival analysis results of both models showed that the survival rate of recipients in the high-risk group was significantly lower than that in the low-risk group (P<0.001). Conclusions Compared with XGBoost, the machine learning prognostic model developed based on the RSF algorithm may preferably predict the survival period of LTx recipients.