Objective To explore the efficacy and safety of blue laser vaporization in the treatment of large-volume (＞80 mL) benign prostatic hyperplasia (BPH). Methods A retrospective analysis was conducted on the clinical data of 149 BPH patients with prostate volume＞80 mL who underwent blue laser vaporization at our hospital during Aug. 2023 and Aug. 2025. The 1-month postoperative maximum urinary flow rate (Qmax) and international prostate symptom score (IPSS), operation time, postoperative hemoglobin drop, bladder irrigation volume, catheter indwelling time, and incidence of postoperative complications were recorded and analyzed. Results All operations were successfully completed, without conversion to other approaches. The operation time was (41.47±11.05) minutes, postoperative hemoglobin drop (2.78±1.19) g/L, bladder irrigation volume (9.97±1.49) bags, and catheter indwelling time (3.30±1.85) days. One month after surgery, the Qmax was significantly higher than the preoperative value [(20.19±3.39) mL/s vs. (2.39±2.17) mL/s], while the IPSS was significantly lower [(4.46±0.87) vs. (27.69±2.06)], with statistically significant differences (P＜0.001). Postoperative complications included 1 case of incontinence (0.67%), 2 cases of urethral stricture/bladder neck contracture (1.34%), and 1 case of secondary bleeding (0.67%), all of which improved with symptomatic treatment. Conclusion Blue laser vaporization is effective for treating large-volume BPH, with advantages such as minimal bleeding risk, short operation time, fast recovery and safety.

Objective To construct a dynamic prediction model for JC polyomavirus (JCV) reactivation after kidney transplantation. Methods A retrospective analysis was conducted on the clinical data of 128 recipients who met the inclusion criteria and received kidney transplantation in Nanfang Hospital, Southern Medical University, from June 2021 to December 2024. Dynamic Cox regression and dynamic restricted mean survival time (RMST) regression based on the landmark method were adopted to establish the dynamic prediction models, and Monte Carlo cross-validation was used to evaluate model performance. Results The dynamic models could predict the incidence and onset time of JCV reactivation within the subsequent 3 months according to covariates at each landmark time point from the 1st to the 6th month after transplantation. Remuzzi score, body mass index and warm ischemia time were independent risk factors for JCV reactivation, while a history of urinary BK polyomavirus reactivation served as a protective factor. The median values of the area under the curve, C-index and Brier score of the dynamic Cox model were 0.873, 0.851 and 0.065 respectively, and the C-index of the dynamic RMST model was 0.829, all of which were superior to those of the static model. Conclusions The landmark-based dynamic models exhibit excellent predictive performance, which may integrate baseline data and post-transplant follow-up information to realize dynamic assessment of the risk and time window of JCV reactivation, thereby providing evidence for optimizing post-operative monitoring and individualized intervention strategies.

Objective On the basis of the theory of the tumor metastatic state, this work aims to explore the metastasis trajectories and peripheral immune response patterns in patients with non-small cell lung cancer (NSCLC) receiving vital qi-strengthening and toxin-eliminating therapy (Fuzheng Juandu) and reveal the value of peripheral immunity in assessing vital qi deficiency during metastasis. Methods A retrospective study design was adopted. Patients with NSCLC admitted from January 1, 2018, to October 31, 2025 were enrolled. Data on metastasis status and peripheral immune indices were collected at the follow-up time points of one, two, three, and five years. Group-based trajectory modeling was used to fit metastasis trajectories, and the independent predictors of trajectory grouping were analyzed through multifactor and multiclassification logistic regression. Results A total of 184 patients with NSCLC were included, and three different groups of metastasis trajectories were identified, namely, the low-risk stable (46.74%, n=86), low-risk rising (13.59%, n=25), and high-risk stable (39.67%, n=73) groups. Univariate analysis revealed substantial differences in peripheral immune indices among the three trajectory groups. Multivariate analysis showed that TNM stage, absolute neutrophil count, lymphocyte count, absolute monocyte count, platelet volume, SAA:CRP ratio, and NLR were independent predictors of the low-risk rising group, whereas TNM stage, absolute monocyte count, basophil count, SII, and NLR were independent predictors of the high-risk stable group. Conclusion Under Fuzheng Juandu therapy, patients with NSCLC exhibit three distinct metastasis trajectories, each corresponding to a specific peripheral immune response pattern. Elucidating these peripheral immune response patterns may facilitate the objective quantification of the degree of vital qi deficiency, prediction of future metastasis risk, and providing an important reference for the individualized clinical implementation of Fuzheng Juandu therapy.

Neurodegenerative diseases (NDs), particularly Alzheimer’s disease (AD) and Parkinson’s disease (PD), and cardiovascular diseases (CVDs), including heart failure (HF) and coronary artery disease (CAD), are major chronic disorders associated with population aging. Their frequent coexistence in clinical practice suggests that they may not progress independently, but may instead be linked through bidirectional pathological communication within the brain-heart axis. Epidemiological evidence underscores this clinical burden: systematic reviews and meta-analyses have reported pooled relative risks for dementia of approximately 1.27 among individuals with a history of CAD and 1.60 among those with HF, while the pooled prevalence of cognitive impairment and dementia in patients with HF has been estimated at approximately 41.42% and 19.79%, respectively. This review synthesizes current evidence on the mechanistic links, disease-state manifestations, biomarkers, and potential therapeutic strategies involved in the comorbidity between NDs and CVDs from the perspective of the brain-heart axis. The brain and heart communicate through autonomic, neuroendocrine, neuroimmune, vascular, and humoral pathways. Sympathetic activation, parasympathetic withdrawal, vagal dysfunction, cerebral hypoperfusion, endothelial injury, blood-brain barrier (BBB) alterations, peripheral immune activation, and circulating inflammatory mediators may jointly contribute to cross-organ pathological signaling. Oxidative stress and inflammatory response are not specific to the brain-heart axis; rather, they may act as candidate amplifying processes within this network. Mitochondrial dysfunction and NADPH oxidase activation can increase the generation of reactive oxygen species and reactive nitrogen species, which may activate nuclear factor-κB, the NLRP3 inflammasome, and mitogen-activated protein kinase/c-Jun N-terminal kinase signaling. These pathways can promote the release of interleukin-1β, interleukin-6, tumor necrosis factor‑α, and other inflammatory mediators, which may in turn aggravate mitochondrial injury, endothelial dysfunction, immune cell activation, and further oxidant generation. Cytokines, chemokines, oxidized lipids, mitochondrial DNA, damage-associated molecular patterns, and extracellular vesicles may transmit these signals between the cardiovascular and central nervous systems, whereas autonomic reflexes provide an additional route for bidirectional amplification. Distinct disease states illustrate different manifestations of this network. The association between AD and CVDs may involve vascular risk factors, impaired amyloid-β clearance, abnormal cholesterol homeostasis, cerebral microvascular injury, neuroinflammation, and endothelial dysfunction. HF-related cognitive impairment may be linked to reduced cardiac output, recurrent cerebral hypoperfusion, hypoxia-related signaling, BBB dysfunction, circulating inflammation, and impaired autonomic feedback. In PD, cardiovascular autonomic dysfunction and abnormalities in heart rate and blood pressure regulation may interact with vascular injury, reduced cerebral perfusion, inflammation, and oxidative stress. However, the relationship between PD and CAD remains heterogeneous and may be modified by age, ethnicity, medication use, metabolic factors, and coexisting diseases. Biomarker evaluation should therefore move beyond isolated indicators. Traditional markers, including malondialdehyde, superoxide dismutase, glutathione, C-reactive protein, and interleukin-6, reflect systemic oxidative or inflammatory burden but lack sufficient specificity to distinguish primary neurodegeneration, cardiovascular injury, or a comorbid state involving both. Greater clinical value may be obtained from cross-system panels that combine oxidative stress and inflammatory markers with cardiac stress or injury biomarkers, such as N-terminal pro-B-type natriuretic peptide; glial or neuronal biomarkers, such as glial fibrillary acidic protein and neurofilament light chain; BBB- or endothelial injury-related biomarkers; and omics-derived candidates, including microRNAs, long non-coding RNAs, DNA methylation signatures, metabolites, and proteins. Multi-omics integration and artificial intelligence-assisted analysis may support risk stratification, disease monitoring, and prediction of treatment response. However, these approaches require standardized analytical platforms, validation in independent cohorts, and careful distinction between associative findings and causal mechanisms. Potential interventions include antioxidant, anti-inflammatory, mitochondria-targeted, and multi-target combination strategies, together with emerging approaches such as nanodelivery, CRISPR/Cas9- or CRISPR/dCas9-based regulation, mesenchymal stem cell-mediated mitochondrial transfer, and ergothioneine supplementation. Nevertheless, most available evidence is indirect, preclinical, or derived from other disease indications, and no single drug or technology can currently be regarded as specific to brain-heart axis comorbidity. The clinical relevance of these strategies will depend on whether they can be matched to dominant pathological phenotypes and improve both neurological and cardiovascular outcomes. Overall, comorbidity between NDs and CVDs is more appropriately understood as a heterogeneous cross-organ regulatory network than as a disorder driven by a single pathway. Future research should prioritize multicenter longitudinal cohorts, standardized clinical phenotyping, validation of cross-system biomarker panels, and mechanism-guided interventions in clearly defined patient subgroups, with integrated assessment of cognitive function, cardiovascular events, quality of life, long-term safety, and treatment response.

ObjectiveIn order to provide a reference for the optimization of preparation process of stir-fried Glycyrrhizae Radix et Rhizoma（sf-GRR）， the quality changes during the processing was studied. MethodsGlycyrrhizae Radix et Rhizoma was processed by stir-frying for 17 min， and samples were collected every 1 min during the processing. The appearance color of the samples was determined by visual analysis technology， the moisture and extract of the process samples were detected by the drying method and the hot extraction method of alcohol-soluble extract in the general rules of the 2020 edition of Chinese Pharmacopoeia（part Ⅳ）， and the contents of liquiritin apioside， liquiritin， isoliquiritin apioside， isoliquiritin， licoricesaponin G₂ and glycyrrhizic acid in the process samples were determined by high performance liquid chromatography（HPLC）. Then principal component analysis（PCA）， partial least squares-discriminant analysis（PLS-DA） and Spearman correlation analysis were used for clustering， discrimination and correlation analysis of the appearance color， moisture， extract and the contents of six internal components. Based on artificial neural network and random forest algorithm， the prediction model of processing degree of sf-GRR was established. On this basis， based on the five principles of quality marker（Q-Maker）， explore the monitoring Q-Maker of sf-GRR. ResultsThe color of Glycyrrhizae Radix et Rhizoma deepened after stir-frying， and the appearance color of the sample changed from light yellow to dark yellow during processing. During the stir-frying process， the moisture content showed a decreasing trend with the extension of processing time， while the extract content showed an increasing trend with the extension of processing time. After stir-frying， the contents of liquiritin apioside， liquiritin and licoricesaponin G₂ showed an overall decreasing trend， while the contents of isoliquiritin apioside and isoliquiritin increased， and the content of glycyrrhizic acid increased slightly. The correlation analysis showed that moisture was positively correlated with brightness（L^*） and red/green value（a^*）， and negatively correlated with yellow/blue value（b^*） and total color difference（E^*ab）. Isoliquiritin apioside and isoliquiritin had negative correlation with L^* and a^*， and positive correlation with b^* and E^*ab. The processing process of sf-GRR could be divided into two stages of the early stage（0-14 min） and the late stage（15-17 min）， and could be divided into three stages of the early stage（0-6 min）， the middle stage（7-14 min） and the late stage（15-17 min） by combining the moisture， extract， the contents of 6 components and color values. Based on artificial neural network analysis and random forest algorithm， isoliquiritin apioside， isoliquiritin， liquiritin and glycyrrhizic acid were selected as monitoring markers for sf-GRR. ConclusionBased on the analysis of the exterior-interior indicators of process samples of sf-GRR， this paper ultimately identifies four processing monitoring markers， which can provide a basis for optimizing the processing technology of sf-GRR.

ObjectiveBased on ultra performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS）， network pharmacology， molecular docking and cell experiments， the active ingredients， possible targets and molecular mechanisms of Baoxin granules（BXG） regulating ferroptosis in the treatment of heart failure（HF） were explored. MethodsBXG intestinal absorption fluid was prepared by everted gut sac and the chemical composition contained therein were identified by UPLC-Q-TOF-MS. According to the obtained components， the potential targets of BXG were predicted， and the HF-related targets and related genes of ferroptosis were retrieved at the same time， and the intersecting targets were obtained by Venn diagram. In addition， the protein-protein interaction（PPI） network and the component-target network were constructed， and the core components and core targets were obtained by topological analysis. Then Gene Ontology（GO） function and Kyoto Encyclopedia of Genes and Genomes（KEGG） enrichment analysis were performed on the core targets， and molecular docking validation of the key targets and main components was carried out by AutoDockTools 1.5.7. H9c2 cells were used to establish a oxygen-glucose deprivation model， and the protective effect of BXG on cells was investigated by detecting cell viability， cell survival rate and reactive oxygen species（ROS） level. The protein expression levels of signal transducer and activator of transcription 3（STAT3）， phosphorylation（p）-STAT3 and glutathione peroxidase 4（GPX4） were detected by Western blot to clarify the regulatory effect of BXG on ferroptosis. ResultsA total of 61 chemical components in BXG intestinal absorption fluid were identified， and network pharmacology obtained 27 potential targets of BXG for the treatment of HF， as well as 139 signaling pathways. BXG may act on core targets such as STAT3， tumor protein p53（TP53）， epidermal growth factor receptor（EGFR）， JUN and prostaglandin-endoperoxide synthase 2（PTGS2） through core components such as glabrolide and limonin， which in turn intervene in lipid and atherosclerosis， phosphatidylinositol 3-kinase/protein kinase B（PI3K/Akt）， endocrine resistance and other signaling pathways to exert therapeutic effects on HF. Molecular docking showed that the docking results of multiple groups of targets and compounds were good. In vitro cell experiments showed that compared with the blank group， the cell viability and survival rate of the model group were significantly decreased， the level of ROS was significantly increased（P<0.01）， the expression levels of STAT3， p-STAT3， p-STAT3/STAT3 and GPX4 proteins were significantly decreased（P<0.05， P<0.01）. Compared with the model group， the cell viability and survival rate of the BXG group were significantly increased， the ROS level was significantly decreased（P<0.01）， the STAT3， p-STAT3， p-STAT3/STAT3 and GPX4 protein levels were significantly increased（P<0.05， P<0.01）. ConclusionBXG may inhibit the occurrence of ferroptosis by up-regulating the expression of STAT3 and GPX4， thus exerting a therapeutic effect on HF， and flavonoids may be the key components of this role.

Objective To conduct a bibliometric analysis of domestic and international literature on the research of Sijunzi Decoction over the past 20 years,and to explore the research status,hotspots,and development trends of Sijunzi Decoction.Methods This article retrieved journal articles related to the research of Sijunzi Decoction from 2004 to 2024 in the CNKI,Wanfang,VIP,and Web of Science databases.Microsoft Excel was used for publication volume analysis,while CiteSpace software was employed for keyword co-occurrence,clustering,and burst analysis,and then the analysis results were visualized.Results After literature retrieval and screening,3 573 Chinese articles and 113 English articles were included.Over the past two decades,the publication volume showed a trend of steadily increasing.The most frequent keywords in Chinese and English literature on the research of Sijunzi Decoction were spleen deficiency syndrome and gene expression,while the keywords with strongest burst were experimental research and data mining.Conclusion The research of Sijunzi Decoction in the last 20 years was mainly through animal experiments and clinical applications,and the research hotspots focus on the treatment of diseases of spleen deficiency syndrome and on the improvement of immune function of cancer patients.The extraction and identification of active components in Sijunzi Decoction and the study on the therapeutic mechanism in diseases of spleen deficiency syndrome are probably the future research trends.

Objective To analyze the results of health examination of soldiers stationed on an island,and to explore the health condition of the soldiers and main influencing factors,so as to provide scientific basis for further prevention and intervention.Methods The health examination reports of 507 soldiers stationed on an island were collected and analyzed.These soldiers were stratified according to age and body mass index.Priority diseases and abnormal results were analyzed.Results More than 40 kinds of abnormal results were detected,and the top 5 were sinus bradycardia,fatty liver,high uric acid,high blood pressure,and ametropia.There were significant differences in the detection rates of fatty liver,high cholesterol and kidney stone among all age groups(P<0.05).There were significant differences in the detection rates of fatty liver,high uric acid,high blood pressure and gallbladder polyps among soldiers with different BMI(P<0.05).Conclusion Metabolic diseases have become the main health problems in soldiers stationed on islands.Health care should be intensified,and health management targeting risk factors should be implemented to effectively reduce the prevalence rate and enhance combat capabilities.

Objective To establish and evaluate a nomogram prediction model for spontaneous peritonitis in HBV-related primary liver cancer.Methods A retrospective study was conducted on 1298 patients with HBV-related primary liver cancer hospitalized in the Kunming Third People's Hospital from January 2012 to December 2022.General data and serological indicators were collected,and patients were divided into infection group(n=262)and control group(n=1036)based on the occurrence of spontaneous peritonitis.Univariate and LASSO regression analyses were used to screen variables,followed by binary logistic regression to analyze the influencing factors of spontaneous peritonitis in HBV-related primary liver cancer patients,leading to the establishment of a nomogram prediction model.Finally,the Hosmer-lemeshow(H-L)goodness of fit test,receiver operating characteristic(ROC)curve,calibration curve,decision curve analysis(DCA)and clinical impact curve(CIC)were utilized to evaluate the fit degree,accuracy,calibration,and clinical practicability of the nomogram prediction model.Results Single factor analysis revealed significant differences between infection group and control group in portal vein cancer thrombus(PVTT),Child-Pugh grade,China Liver Cancer Staging(CNLC)stage,alcohol consumption history,smoking history,white blood cell count(WBC),neutrophil count(NE),hemoglobin(Hb),fibrinogen(FIB),abnormal prothrombin(PIVKA-Ⅱ),aspartate aminotransferase(AST),alanine aminotransferase(ALT),total protein(TP),prealbumin(PA),γ-glutamyltransferase(GGT),alkaline phosphatase(ALP),cholinesterase(CHE),total bile acid(TBA),total cholesterol(TC),low density lipoprotein(LDL),creatinine(Cr),HBV DNA,CD3+T cells count,CD4+T cells count,CD8+T cells count,CD4+T cells/CD8+T cells ratio,procalcitonin(PCT),serum amyloid A(SAA),interleukin-6(IL-6),high-sensitivity C-reactive protein(hs-CRP),alpha-fetoprotein(AFP),and IL-4(P＜0.05).LASSO regression analysis identified 5 variables:Child-Pugh grade,PVTT,WBC,CHE and hs-CRP.Binary logistic regression analysis indicated that Child-Pugh grade(Grade B:OR=5.780,95％CI 3.271-10.213,P＜0.001;Grade C:OR=14.818,95％CI 7.697-28.526,P＜0.001),PVTT(OR=2.893,95％CI 2.037-4.108,P＜0.001),WBC(OR=1.088,95％CI 1.031-1.148,P=0.002),and hs-CRP(OR=1.005,95％CI 1.001-1.010,P=0.026)were the independent risk factors of spontaneous peritonitis in HBV-related primary liver cancer patients.Using these 4 variables,a nomogram prediction model was constructed and evaluated.The P-value of the H-L goodness of fit test was 0.760.Moreover,the area under ROC curve(AUC)was 0.866,with a sensitivity of 0.870 and a specificity of 0.716.The average absolute error of the calibration curve is 0.022.DCA and CIC analyses demonstrated that the nomogram prediction model possessed some clinical utility.Conclusion The nomogram prediction model for spontaneous peritonitis in HBV-related primary liver cancer patients,constructed using Child-Pugh grade,PVTT,WBC and hs-CRP,exhibits a high fitting degree and accuracy,with the prediction probability highly consistent with the actual occurrence probability,and possesses certain clinical practicability.

Objective To construct a predictive model for high-grade pathological components of early invasive lung adenocarcinoma(ILAC)based on radiomics.Methods Collecting information on total 495 patients who underwent radical operation and were pathologically diagnosed as stage Ⅰ in the cardiothoracic surgery of Zhoushan Hospital from January 2015 to December 2019,including gender,age,pathological findings,tumor markers and preoperative chest CT images.The micropapillary and solid components in postoperative pathology were defined as"high-grade pathological components",while those without high-grade pathological components were classified into the low-grade group and those with high-grade pathological components were classified into the high-grade group.And patients were randomly divided into the training set(343 cases)and the validation set(152 cases)with a ratio of 7∶3 using the simple randomization grouping method.The region of interest of nodules on CT images were delineated layer by layer by scientific research platform and 1950 radiomics features were extracted.And then those features were filtrated by F-test,Pearson correlation coefficient,and L1 based feature selection.A model was built by using Logistic regression machine learning classifier,named mod 2,and radscore was also obtained.Differences between general information and CT features were analyzed.Binary Logistic regression analysis was used to construct a model for statistically significant variables,named mod 1.At the same time,Radscore was added to build the mod and named comb mod.The area under the curve(AUC),sensitivity and specificity of the three models were calculated.A nomogram was also drawn.Results A total of 495 patients were divided into the training set(n=343)and the validation set(n=152).Gender,carcinoma embryonic antigen(CEA),nodule,and maximum diameter were screened out in clinical features and involved in constructing the mod 1.Twelve features were selected from the radiomics features to build mod 2.Comb mod performed best,training set AUC:0.887,validation set AUC:0.875,and had good clinical practicability.Conclusion The model composed of general feature,CT feature and radiomics features could accurately predict high-grade pathological components in early ILAC,and provide references for clinicians to choose surgical method for patients.