Objective: To investigate the safety and feasibility of transurethral blue laser vaporization of the prostate (BVP) under intravenous anesthesia without intubation. Methods: Clinical data of 30 benign prostatic hyperplasia (BPH) (prostate volume <40 mL) patients undergoing BVP under intravenous anesthesia without intubation in our hospital during Jul.and Nov.2024 were retrospectively analyzed.Preoperative and 1-month postoperative international prostate symptom score (IPSS), quality of life score (QoL), maximum urinary flow rate (Qmax), and postvoid residual volume (PVR) were compared.The operation time, cumulative blue laser activation time, recovery time, postoperative bladder irrigation time, postoperative catheter indwelling time, postoperative 2-hour visual analog scale (VAS) score and incidence of surgical and anesthetic complications were recorded. Results: All 30 patients successfully completed BVP under intravenous anesthesia without intubation.The operation time was (12.5±5.0) min, cumulative laser activation time (9.8±4.1) min, recovery time (6.8±1.2) min, postoperative bladder irrigation time (11.0±4.6) h, postoperative catheter indwelling time (2.7±1.1) days and postoperative 2-hour VAS score was (3.0±1.3).No cases required conversion to intubated general anesthesia, and no severe perioperative surgical or anesthetic complications occurred.Significant improvements in IPSS, QoL, Qmax, and PVR were observed 1 month postoperatively (P＜0.001). Conclusion: BVP under intravenous anesthesia without intubation in the treatment of prostate volume <40 mL BPH is clinically feasible, significantly improving lower urinary tract symptoms without significant surgical or anesthetic complications.

Microwave thermochemotherapy (MTC) has been applied to treat lip squamous cell carcinoma (LSCC), but a deeper understanding of its therapeutic mechanisms and molecular biology is needed. To address this, we used single-cell transcriptomics (scRNA-seq) and spatial transcriptomics (ST) to highlight the pivotal role of tumor-associated neutrophils (TANs) among tumor-infiltrating immune cells and their therapeutic response to MTC. MNDA⁺ TANs with anti-tumor activity (N1-phenotype) are found to be abundantly infiltrated by MTC with benefit of increased blood perfusion, and these TANs are characterized by enhanced cytotoxicity, ameliorated hypoxia, and upregulated IL1B, activating T&NK cells and fibroblasts via IL1B-IL1R. In this highly anti-tumor immunogenic and hypoxia-reversed microenvironment under MTC, fibroblasts accumulated in the tumor front (TF) can recruit N1-TANs via CXCL2-CXCR2 and clear N2-TANs (pro-tumor phenotype) via CXCL12-CXCR4, which results in the aggregation of N1-TANs and extracellular matrix (ECM) deposition. In addition, we construct an N1-TANs marker, MX2, which positively correlates with better prognosis in LSCC patients, and employ deep learning techniques to predict expression of MX2 from hematoxylin-eosin (H&E)-stained images so as to conveniently guide decision making in clinical practice. Collectively, our findings demonstrate that the N1-TANs/fibroblasts defense wall formed in response to MTC effectively combat LSCC.
Humans ; Neutrophils/metabolism* ; Single-Cell Analysis ; Lip Neoplasms/genetics* ; Hyperthermia, Induced/methods* ; Microwaves/therapeutic use* ; Transcriptome ; Carcinoma, Squamous Cell/immunology* ; Tumor Microenvironment

Radiopharmaceuticals operate by combining radionuclides with carriers. The radiation energy emitted by radionuclides is utilized to selectively irradiate diseased tissues while minimizing damage to healthy tissues. In comparison to external beam radiation therapy, radionuclide drugs demonstrate research potential due to their biological targeting capabilities and reduced normal tissue toxicity. This article reviews the applications and research progress of radiopharmaceuticals in cancer treatment. Several key radionuclides are examined, including ²²³Ra, ⁹⁰Y, Lutetium-177 (¹⁷⁷Lu), ²¹²Pb, and Actinium-225 (²²⁵Ac). It also explores the current development trends of radiopharmaceuticals, encompassing the introduction of novel radionuclides, advancements in imaging technologies, integrated diagnosis and treatment approaches, and equipment-medication combinations. We review the progress in the development of new treatments, such as neutron capture therapy, proton therapy, and heavy ion therapy. Furthermore, we examine the challenges and breakthroughs associated with the clinical translation of radiopharmaceuticals and provide recommendations for the research and development of novel radionuclide drugs.
Humans ; Radiopharmaceuticals/therapeutic use* ; Neoplasms/radiotherapy* ; Radioisotopes/therapeutic use* ; Animals

Digital biopsy for liver diseases is characterized by the deep integration of artificial intelligence （AI） technologies and large-scale liver disease data， through which intelligent analytics are applied to support clinical decision-making and full-cycle management. This article reviews the AI technical framework based on standardized data governance and centered on multimodal large medical models， covering the application of natural language processing， knowledge map， generative AI， and large language models in the establishment of databases for specialty diseases， diagnosis， prognosis prediction， treatment， and automated medical documentation. This article also discusses the application prospects of this framework in medical education， scientific research， and healthcare management. Although this technique shows broad application potential， it still faces challenges in areas such as multi-center data integration， model interpretability， ethics， and data security. In the future， a smart ecosystem with closed-loop optimization and human-AI collaboration should be established to promote the comprehensive implementation of digital biopsy in the whole process of medicine， education， research， and management， thereby providing help for the precise prevention and control and holistic health management of liver diseases.

Objective To explore the predictive value of serum proprotein convertase subtilisin/kexin type 9(PCSK9)and proprotein convertase subtilisin/kexin type 9(CTRP6)in pregnant women undergoing threatened abortion and fetal protection treatment for pregnancy outcomes.Methods Eighty pregnant women with threatened abortion who were treated in the Second Affiliated Hospital of Shaanxi University of Chinese Medicine from August 2021 to May 2022 were selected as the study subjects.According to the pregnancy outcome,they were grouped into the good pregnancy outcome group(n=62)and the bad pregnancy outcome group(n=18),while another 60 pregnant women with normal pregnancy tests in the hospital were selected as the control group.The serum levels of PCSK9,CTRP6,progesterone and β-human chorionic gonadotropin(β-HCG)were measured by enzyme-linked immunosorbent assay(ELISA).Pearson method was applied to analyze the correlation between serum PCSK9,CTRP6 levels and progesterone and β-HCG levels.Multivariate Logistic regression analysis was applied to analyze the factors affecting the pregnancy outcomes of pregnant women with threatened abortion.The predictive value of serum PCSK9 and CTRP6 on pregnancy outcome of pregnant women with threatened abortion and pregnancy protection treatment was analyzed by the receiver operating characteristic(ROC)curve.Results The level of progesterone(45.65±3.48,38.29±3.54 and 31.56±4.11 nmol/L),β-HCG(32 056.56±4 244.54,23 642.32±3 897.67 and 11 375.56±3 454.35 mIU/L)and CTRP6(436.53±36.23,328.44±31.06 and 277.86±25.56 ng/ml)in control group,good pregnancy outcome group and bad pregnancy outcome group decreased gradually,while the level of PCSK9(64.22±10.35,82.24±13.33 and 114.56±17.67 ng/ml)in the control group,the good pregnancy outcome group and the bad pregnancy outcome group increased gradually,with statistically significant differences(F=129.231,199.334,244.007,111.297,all P＜0.05).Pearson method showed that serum PCSK9 was negatively correlated with progesterone and β-HCG levels(r=-0.545,-0.514,all P＜0.05),and serum CTRP6 was positively correlated with progesterone and β-HCG levels(r=0.567,0.496,all P＜0.05).Multivariate Logistic regression analysis showed that the high level of PCSK9 was an independent risk factor for pregnancy outcome of threatened abortion and fetal protection treatment,and the high level of CTRP6,progesterone and β-HCG were independent protective factors for pregnancy outcome of threatened abortion and fetal protection treatment(P＜0.05).ROC results showed that the area under the curve(AUC)of serum PCSK9 and CTRP6 levels for patients with adverse pregnancy outcomes in the prediction of threatened abortion and fetal protection treatment was 0.843 and 0.849,respectively.The AUC predicted by the combination of the two was 0.941,which was better than that predicted by each individual(Z=1.725,1.882,P＜0.05),with a specificity and a sensitivity of 85.48%,94.44%,respectively.Conclusion The serum PCSK9 level of pregnant women undergoing threatened abortion and fetal protection treatment was obviously increased,and the level of CTRP6 was obviously reduced.This study indicated both have important value in predicting the pregnancy outcomes of pregnant women undergoing threatened abortion and fetal protection treatment.

Objective:To construct and validate a machine learning model for preoperative prediction of perineural invasion (PNI) status in intrahepatic cholangiocarcinoma (ICC).Methods:Clincial data of 329 patients, including 245 admitted to Zhengzhou University People's Hospital from January 2018 to June 2023 and 84 admitted to the Affiliated Cancer Hospital of Zhengzhou University from January 2013 to January 2020 were retrospectively analyzed. Patients were divided into a training set ( n=231) and a validation set ( n=98). Clinicopathological data including age, gender, hepatitis B virus (HBV) infection status were collected. Predictive variables were determined using least absolute shrinkage and selection operator (LASSO) regression analysis. Six machine learning algorithms including random forest (RF), logistic regression, and linear kernel-based support vector machine were selected to construct the preoperative prediction model for PNI in ICC. Performance metrics of the model were calculated using a confusion matrix, and the final model was selected. The model performance was evaluated in the validation set. Calibration curves were plotted to evaluate the final model, and a Pareto chart was used to visualize the importance of predictive variables. Results:LASSO regression identified nine predictive variables included in the prediction model, including carbohydrate antigen 19-9 (CA19-9), HBV infection status, alkaline phosphatase, alanine aminotransferase, prothrombin time, total bilirubin, albumin, neutrophil times gamma-glutamyl transferase to lymphocyte ratio, and tumor burden score. Among the trained six models, the area under the curve (AUC) of the RF model was 0.909, with a sensitivity of 0.842 and an accuracy of 0.870. Compared with the AUC of the RF model, the AUCs of the other 5 models were lower (all P<0.05). The AUC of the RF model for predicting PNI in ICC in validation set was 0.736. Calibration curves showed good fit of the RF model's prediction of PNI in ICC in both training and validation sets. The Pareto chart showed that CA19-9 was the most important predictive variable in the model, followed by HBV infection status. Conclusion:The machine learning model based on the RF algorithm has a high accuracy in preoperative prediction of PNI status in ICC.

Objective:To investigate the distribution characteristics of skeletal muscle mass and strength in the older adults over 65 years old in 18 longevity areas in China.Methods:The subjects were selected from the Healthy Aging and Biomarkers Cohort Study conducted in 18 longevity areas of China. A total of 4 662 older adults over 65 years old from a cross- sectional survey in 2021 were included in the study. The information about their sociodemographic characteristics, lifestyle, nutrient intake and other factors were collected through questionnaire surveys and physical examinations. Grip strength was measured by using professional electronic grip dynamometer. Total skeletal muscle mass (TSM) was measured using bioelectrical impedance analysis, and TSM was adjusted by height squared and BMI to obtain TSM Ht2 and TSM BMI. The proportion of individuals with low muscle mass and strength was determined according to the recommended method by the Asian Working Group for Sarcopenia (AWGS). Descriptive analysis was conducted on the population and regional distribution characteristics of people with different muscle mass and grip strength. A generalized additive model was used to analyze the age-related trends of muscle mass and grip strength. Results:The age of 4 662 study subjects was (82.69±10.54) years, men accounted for 46.85% (2 184 cases) and Han Chinese accounted for 96.27% (4 488 cases). The M( Q1, Q3) of TSM, TSM Ht2 and TSM BMI in men were 23.30 (20.50, 26.20) kg, 9.02 (8.13, 9.89) kg/m 2, and 1.01 (0.90, 1.13) kg·(kg/m 2) -1, respectively, which were all higher than those in women [TSM: 18.20 (15.70, 20.70) kg, TSM Ht2: 8.18 (7.42, 9.07) kg/m 2 and TSM BMI: 0.79 (0.69, 0.90) kg·(kg/m 2) -1], the differences were significant (all P<0.001). The grip strength of men [ M( Q1, Q3): 24.50 (17.80, 30.80) kg] was higher than that of women [ M( Q1, Q3): 15.60 (11.10, 19.90) kg], the difference was significant ( P<0.001). Southern elderly men had lower TSM and TSM Ht2 compared with northern elderly men (all P<0.001), while there was no significant regional difference in TSM BMI ( P>0.05). Southern elderly women had higher TSM Ht2 and TSM BMI compared with northern elderly women (all P<0.001), while there was no significant regional difference in TSM ( P>0.05). Furthermore, according to the method recommended by AWGS, the elderly with low muscle mass and grip strength were characterized by older age, illiteracy, being unmarried/divorced/widowed, poor chewing ability, impaired activity of daily living and living in southern region. Conclusion:There were population and regional differences in muscle mass and grip strength in the older adults over 65 years in 18 longevity areas of China, and these differences showed decreasing trends with age.

Objective:To develop a prediction tool for 6-year incident risk of frailty among Chinese older adults aged 65 years or above.Methods:Data from the Chinese Longitudinal Healthy Longevity Survey from 2002 to 2018 was used, including 13 676 older adults aged 65 years or above who were free of frailty at baseline. Key predictors of frailty were identified via the least absolute shrinkage and selection operator (LASSO) method, and were thereafter used to predict the incident frailty based on the Cox proportional hazards regression model. The model was internally validated by 2 000 Bootstrap resamples and evaluated for the performance of discrimination and calibration using the area under the receiver operating characteristic curve (AUC) and calibration curve, respectively. The net benefit of the developed prediction tool was evaluated by decision-curve analysis.Results:The M( Q1, Q3) age and follow-up time of the participants were 81.0 (71.0, 90.0) years and 6.0 (4.1, 9.2) years, respectively. A total of 4 126 older persons (30.2%) were recorded with frailty incidents during the follow-up, with the corresponding incidence density of 41.8/1 000 person-years. A total of 15 key predictors of frailty were selected by LASSO, namely, age, sex, race, education years, meat consumption, tea drinking, performing housework, raising domestic animals, playing cards or mahjong, and baseline status of visual function, activities of the daily living score, instrumental activities of the daily living score, hypertension, heart disease, and self-rated health. The prediction model was internally validated with an AUC of 0.802, with the max Youden's index of 0.467 at a risk threshold of 19.0%. The calibration curve showed high consistency between predicted probabilities and observed proportions of frailty events. The decision curve indicated that higher net benefits could be obtained via the prediction model than did strategies based on intervention in all or none participants for any risk threshold less than 59%, and the model-based net benefit was estimated to be 0.10 at a risk threshold of 19.0%. Conclusions:The herein developed 6-year incident risk prediction model of frailty, based on easily accessible questionnaires and physical examination variables, has good predictive performance. It has application potential in identifying populations at high risk of incident frailty.

Objective To investigate the possible mechanism of action of Jinqi Qingshu granules(JQQSG)in the treatment of community-acquired pneumonia(CAP)by network pharmacology and molecular docking technology.Methods The TCMSP database and SwissTargetPrediction database were used to obtain and screen the active ingredients and targets of JQQSG,and GeneCards,OMIM,TTD,and DisGeNET databases were used to search for the predicted targets of CAP,and the two targets were mapped and then imported into STRING database to construct a PPI network to screen the key targets,and then the GO and KEGG pathway enrichment were analyzed by the DAVID database,and molecular docking was carried out by the AutoDock Tools software.Results 209 active ingredients and 1 041 targets of JQQSG were obtained after screening;312 targets were co-activated with CAP,and 64 core targets were obtained after PPI network screening.571 biological processes,68 cellular components,and 199 molecular functions were analyzed by GO enrichment,and 165 KEGG pathways were analyzed by KEGG pathway enrichment,mainly involved in protein action,apoptosis and MAPK signaling pathway.Molecular docking suggests that the core target and the core components all have good binding ability.Conclusion The mechanism of action of JQQSG in the treatment of CAP may be related to its regulation of Akt,MAPK signaling pathway,improvement of oxidative stress,and other pathways to exert anti-inflammatory and antioxidant effects,which could lay the foundation for further in-depth study of its specific mechanism of action.

To explore the biological characteristics related to the pathogenesis and severity of respiratory syncytial virus (RSV) bronchiolitis by RNA sequencing of white blood cells in children with RSV bronchiolitis. This study is a case-control study. A total of 87 children diagnosed with bronchiolitis and RSV antigen positive and/or RSV nucleic acid positive in the pediatric respiratory department of the Second Affiliated Hospital of Wenzhou Medical University from October 2019 to April 2022 were selected as the case group. The case group was divided into three groups based on the condition: mild, moderate, and severe, and there were two groups according to the presence or absence of atopic symptoms: the atopic group and the non -atopic group, forty healthy children in the same period were selected as the control group. The whole blood leukocyte RNA of the children in the case group and the control group was extracted for RNA sequencing, and the data were analyzed to obtain differentially expressed genes (DEGs). Then, the immunobiological pathways and genes related to the pathogenesis, disease condition, and atopy were screened through Gene Ontology (GO) annotation, Kyoto Gene and Genome Encyclopedia (KEGG) annotation, and protein interaction network (PPI) construction methods. Construct the weighted gene co-expression network analysis (WGCNA) module to identify potential biological indicators related to disease severity.Compared with the control group, the case group had a total of 1 782 DEGs, including 1 586 upregulated genes and 196 downregulated genes. The GO pathway enrichment of DEGs is mainly enriched in molecular functions such as peroxidase activity and oxidoreductase activity. In the cytological components, it is mainly enriched in cytoplasmic vesicle lumen and secretory granule lumen. In biological processes, it is mainly enriched in processes such as neutrophil activation involved in immune responses, neutrophil degranulation, and neutrophil activation. KEGG analysis is mainly concentrated in the signal pathway of the viral protein interaction with cytokine and cytokine receptor. A PPI network was constructed to screen four genes at the core position, including CCL2, IL-10, MMP9 and JUN. The DEGs obtained by comparing different disease groups with the control group are mainly enriched in retrograde endocannabinoid signaling and cell apoptosis pathways. WGCNA analysis showed that the brown module related to oxygen saturation was most closely related to the disease, and its gene was mainly enriched in the RNA helicase retinoic acid inducible gene-I (RIG-I) like receptor signal pathway. There are 230 specific DEGs in the atopic group and 444 in the non -atopic group. KEGG enrichment analysis results show that both groups are enriched to NF-κB signaling pathway, the characteristic does not cause significant changes in immune response and transcriptome characteristics in children with RSV bronchiolitis. In conclusion, neutrophil activation, degranulation pathway and signal pathway of interaction between viral protein and cytokine and cytokine receptor are involved in the immune response of RSV bronchiolitis host. CCL2, IL-10, MMP9 and JUN genes may be associated with the pathogenesis. They might be potential biomarkers related to disease severity in RIG-I like receptors, cell apoptosis, and endogenous cannabinoid related signaling pathways.