[Objective] To evaluate the efficacy and safety of sacral neuromodulation (SNM) in the treatment of patients with benign prostatic hyperplasia (BPH) complicated with underactive bladder (UAB) who respond poorly to transurethral resection of the prostate (TURP). [Methods] A retrospective analysis was performed on 10 patients with BPH and UAB treated with TURP by the same surgeon in Zhongda Hospital Southeast University during Jan.2018 and Jan.2023.The residual urine volume was not significantly relieved after operation, and the maximum urine flow rate and urine volume per discharge were not significantly improved.All patients underwent phase I SNM, and urinary diaries were recorded before and after surgery to observe the average daily frequency of urination, volume per urination, maximum urine flow rate, and residual urine volume. [Results] The operation time was (97.6±11.2) min.During the postoperative test of 2-4 weeks, if the residual urine volume reduction by more than 50% was deemed as effective, SNM was effective in 6 patients (60.0%). Compared with preoperative results, the daily frequency of urination [(20.2±3.8) times vs. (13.2±3.2) times], volume per urination [(119.2±56.7) mL vs. (246.5±59.2) mL], maximum urine flow rate [(8.7±1.5) mL/s vs. (16.5±2.6) mL/s], and residual urine volume [(222.5±55.0) mL vs. (80.8±16.0) mL] were significantly improved, with statistical significance (P<0.05). There were no complications such as bleeding, infection, fever or pain.The 6 patients who had effective outcomes successfully completed phase II surgery, and the fistula was removed.During the follow-up of 1 year, the curative effect was stable, and there were no complications such as electrode displacement, incision infection, or pain in the irritation sites.The residual urine volume of the other 4 unsuccessful patients did not improve significantly, and the electrodes were removed and the vesicostomy tube was retained. [Conclusion] SNM is safe and effective in the treatment of BPH with UAB patients with poor curative effects after TURP.

ObjectiveThis study aims to observe the clinical effect of Danggui Liuhuang Tang （DGLHT） on patients with type 2 diabetes mellitus （T2DM） complicated by atherosclerotic cardiovascular disease （ASCVD） at high risk， focus on evaluating the influence of DGLHT on cardiovascular risk indicators such as flow-mediated dilation （FMD）， atherogenic index of plasma （AIP）， and triglyceride-glucose index （TyG）， and explore the regulatory effect of DGLHT on the myeloid differentiation factor 88/nuclear factor-kappa B （MyD88/NF-κB） signaling pathway. MethodsThe clinical study was a single-center， double-blind， and randomized controlled trial. A total of 68 patients with T2DM-ASCVD at high risk for cardiovascular events with Yin deficiency and fire excess syndrome were enrolled and randomly assigned to a treatment group and a control group. The treatment group was given atorvastatin calcium tablets and DGLHT， while the control group was given atorvastatin calcium tablets and placebos. The treatment course was 12 weeks， with a final study completion of 30 patients in the treatment group and 29 in the control group. Changes in cardiovascular risk indicators such as FMD， AIP， TyG， and small dense low-density lipoprotein cholesterol （sdLDL-C） index were compared. Human umbilical vein endothelial cells （HUVECs） were used to establish a vascular endothelial injury and inflammation model. The protective effect of DGLHT on endothelial injury was verified by reverse transcription polymerase chain reaction （Real-time PCR） and Western blot . ResultsAfter 12 weeks of treatment， the AIP in the treatment group significantly decreased compared with that before the treatment （P<0.05）. Compared with the control group， the treatment group showed significant improvements in FMD and TyG （P<0.05）. Additionally， the treatment group demonstrated significant reductions in two-hour postprandial glucose （2 hPG）， glycated albumin （GA）， triglycerides （TG）， apolipoprotein E （Apo E）， and sdLDL-C （P<0.05）. Analysis of traditional Chinese medicine （TCM） syndrome efficacy indicated that in the treatment group， Yin deficiency and fire excess syndromes， including dry throat and mouth （P<0.05）， excessive thirst （P<0.01）， tidal fever and night sweats （P<0.05）， and dry stools （P<0.05）， improved. Compared with the control group， the treatment group showed significant improvements in symptoms of dry throat and mouth （P<0.05） and excessive thirst （P<0.01）. TCM syndrome scores significantly decreased （P<0.01）， and the overall efficacy rate was 56.67%， significantly higher than the 10.34% observed in the control group （P<0.01）. At the cellular level， increasing concentrations of DGLHT led to decreased messenger ribonucleic acid （mRNA） levels of pro-inflammatory cytokines interleukin-6 （IL-6）， tumor necrosis factor-alpha （TNF-α）， and interleukin-1-beta （IL-1β） in lipopolysaccharide （LPS）-stimulated HUVECs （P<0.01）， with significant reductions in the high-concentration group （P<0.01）. DGLHT may inhibit the expressions of MyD88 and phosphorylated （p）-NF-κB p65 proteins in a concentration-dependent manner. ConclusionDGLHT shows significant effects in reducing cardiovascular risks and may exert an anti-inflammatory effect by inhibiting the MyD88/NF-κB signaling pathway. This finding provides a new perspective for the prevention and treatment of cardiovascular diseases in high-risk individuals with T2DM-ASCVD.

The pathogenesis of neurodegenerative diseases (NDDs) is fundamentally linked to complex and profound alterations in metabolic networks within the brain, which exhibit marked spatial heterogeneity. While conventional bulk metabolomics is powerful for detecting global metabolic shifts, it inherently lacks spatial resolution. This methodological limitation hampers the ability to interrogate critical metabolic dysregulation within discrete anatomical brain regions and specific cellular microenvironments, thereby constraining a deeper understanding of the core pathological mechanisms that initiate and drive NDDs. To address this critical gap, spatial metabolomics, with mass spectrometry imaging (MSI) at its core, has emerged as a transformative approach. It uniquely overcomes the limitations of bulk methods by enabling high-resolution, simultaneous detection and precise localization of hundreds to thousands of endogenous molecules—including primary metabolites, complex lipids, neurotransmitters, neuropeptides, and essential metal ions—directly in situ from tissue sections. This powerful capability offers an unprecedented spatial perspective for investigating the intricate and heterogeneous chemical landscape of NDD pathology, opening new avenues for discovery. Accordingly, this review provides a comprehensive overview of the field, beginning with a discussion of the technical features, optimal application scenarios, and current limitations of major MSI platforms. These include the widely adopted matrix-assisted laser desorption/ionization (MALDI)-MSI, the ultra-high-resolution technique of secondary ion mass spectrometry (SIMS)-MSI, and the ambient ionization method of desorption electrospray ionization (DESI)-MSI, along with other emerging technologies. We then highlight the pivotal applications of spatial metabolomics in NDD research, particularly its role in elucidating the profound chemical heterogeneity within distinct pathological microenvironments. These applications include mapping unique molecular signatures around amyloid β‑protein (Aβ) plaques, uncovering the metabolic consequences of neurofibrillary tangles composed of hyperphosphorylated tau protein, and characterizing the lipid and metabolite composition of Lewy bodies. Moreover, we examine how spatial metabolomics contributes to constructing detailed metabolic vulnerability maps across the brain, shedding light on the biochemical factors that render certain neuronal populations and anatomical regions selectively susceptible to degeneration while others remain resilient. Looking beyond current applications, we explore the immense potential of integrating spatial metabolomics with other advanced research methodologies. This includes its combination with three-dimensional brain organoid models to recapitulate disease-relevant metabolic processes, its linkage with multi-organ axis studies to investigate how systemic metabolic health influences neurodegeneration, and its convergence with single-cell and subcellular analyses to achieve unprecedented molecular resolution. In conclusion, this review not only summarizes the current state and critical role of spatial metabolomics in NDD research but also offers a forward-looking perspective on its transformative potential. We envision its continued impact in advancing our fundamental understanding of NDDs and accelerating translation into clinical practice—from the discovery of novel biomarkers for early diagnosis to the development of high-throughput drug screening platforms and the realization of precision medicine for individuals affected by these devastating disorders.

Abstract Modern western medicine typically focuses on treating specific symptoms or diseases, and traditional Chinese medicine (TCM) emphasizes the interconnections of the body’s various systems under external environment and takes a holistic approach to preventing and treating diseases. Phenomics was initially introduced to the field of TCM in 2008 as a new discipline that studies the laws of integrated and dynamic changes of human clinical phenomes under the scope of the theories and practices of TCM based on phenomics. While TCM Phenomics 1.0 has initially established a clinical phenomic system centered on Zhenghou (a TCM definition of clinical phenome), bottlenecks remain in data standardization, mechanistic interpretation, and precision intervention. Here, we systematically elaborates on the theoretical foundations, technical pathways, and future challenges of integrating digital medicine with TCM phenomics under the framework of “TCM phenomics 2.0”, which is supported by digital medicine technologies such as artificial intelligence, wearable devices, medical digital twins, and multi-omics integration. This framework aims to construct a closed-loop system of “Zhenghou–Phenome–Mechanism–Intervention” and to enable the digitization, standardization, and precision of disease diagnosis and treatment. The integration of digital medicine and TCM phenomics not only promotes the modernization and scientific transformation of TCM theory and practice but also offers new paradigms for precision medicine. In practice, digital tools facilitate multi-source clinical data acquisition and standardization, while AI and big data algorithms help reveal the correlations between clinical Zhenghou phenomes and molecular mechanisms, thereby improving scientific rigor in diagnosis, efficacy evaluation, and personalized intervention. Nevertheless, challenges persist, including data quality and standardization issues, shortage of interdisciplinary talents, and insufficiency of ethical and legal regulations. Future development requires establishing national data-sharing platforms, strengthening international collaboration, fostering interdisciplinary professionals, and improving ethical and legal frameworks. Ultimately, this approach seeks to build a new disease identification and classification system centered on phenomes and to achieve the inheritance, innovation, and modernization of TCM diagnostic and therapeutic patterns.

Objective To study the epidemiological characteristics of chronic obstructive pulmonary disease (COPD) in Ma'anshan area and analyze the influencing factors of acute exacerbation. Methods The clinical data of 1 676 patients with COPD who visited the Department of Respiratory Medicine of Deyu Medical Ma'anshan General Hospital from 2020 to 2022 were retrospectively analyzed. The patients were divided into acute exacerbation group and stable group according to whether they had acute exacerbation or not，and the general information, severity of COPD, previous pulmonary infection and combined hypoproteinemia were compared between the two groups. Logistic regression was used to analyze the influencing factors of acute exacerbation. Results A total of 1 676 COPD patients were mainly male (58.17%) and ≥ 46 years old (82.58%), of which the incidence of acute exacerbation of chronic obstructive pulmonary disease (AECOPD) was 78.82%. Logistic regression analysis showed that male sex , ≥46 years of age, smoking >400 cigarettes/year, occupational exposure to dust, severe and very severe COPD, recurrent new coronavirus infections, combined cardiovascular disease, or hypoproteinemia were risk factors for acute exacerbations in COPD patients. Conclusion Nearly 80% of COPD patients in Ma'anshan area have previously experienced acute exacerbations, and prevention and treatment cannot be ignored. Strengthening the education and prevention of key populations can effectively reduce the incidence of AECOPD and improve the overall prognosis of COPD patients.

Objective To investigate the value of qualitative and quantitative characteristics of gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid(Gd-EOB-DTPA)enhanced MRI in preoperative prediction of vessels encapsulating tumor clusters(VETC)pattern in hepatocellular carcinoma(HCC).Methods A total of 234 patients diagnosed with HCC by pathology were analyzed retrospectively.A total of 101 VETC-positive HCC patients and 133 VETC-negative HCC patients were included.All patients were divided into training group and validation group according to 7︰3.The training group data were used to construct a prediction model for VETC-positive HCC.Receiver operating characteristic(ROC)curve was drawn and the area under the curve(AUC)was calculated to verify the diagnostic efficiency of the model.Calibration curve was drawn to verify the calibration of the model.Results Multivariate logistic regression analysis predicted the independent risk factors for VETC-positive HCC:portal phase peripheral washout[odds ratio(OR)6.493],necrosis or severe ischemia(OR 4.756),targetoid transitional phase or hepatobiliary phase(OR 0.307),and lesion to liver signal intensity ratio(LLR)on arterial phase(OR 0.074).The AUC of the training group in predicting VETC-positive HCC was 0.790[95%confidence interval(CI)0.720-0.859].The AUC of the validation group in predicting VETC-positive HCC was 0.779(95%CI 0.668-0.889).The calibration curve diagram showed that the calibration curve(the slope was 0.91)almost coincides with the ideal curve,indicating that the prediction model had better calibration.Conclusion The qualitative and quantitative characteristics of Gd-EOB-DTPA enhanced MRI can be used to predict VETC-positive HCC preoperatively,the independent risk factors of VETC include portal phase peripheral washout,necrosis or severe ischemia,targetoid transitional phase or hepatobiliary phase,and LLR on arterial phase.

Objective To explore the the correlation between cystatin C(Cys C),beta-2 microglobulin(β2-MG)and ischemic cerebral small vessel disease(CSVD)and its subgroups.Methods Totally 234 patients with CSVD were assigned to the study group,and 92 elderly people with no abnormal findings in head MRI were selected as controls.The CSVD patients were further divided into the subgroups of lacunar infarction(LI),white matter lesion(WML)and LI+WML.Each group was compared risk factors include the blood level of Cys C and β2-MG.Results There were statistically significant differences between CSVD group and control group in cystatin C(Cys C)and β2-MG(P<0.05).Cystatin C(Cys C)and β2-MG there were statistically significant differences between WML group and control group(P<0.05),and also between WML+LI group and control group(P<0.05).Logistic regression analysis and comparison across subgroups showed Cys C and β2-MG to be the common risk factors for WML group and WML+LI group inpatients with ischemic cerebral small vessel disease.Conclusion Cys C and β2-MG are the common risk factors for WML group and WML+LI group inpatients with ischemic cerebral small vessel disease.The risk factors vary across different CSVD subgroups.

Immunoassays are widely used in medicine, food, environment and other fields due to having the advantages of simpleness, rapidness and accuracy. Combining immunoassays with nanomaterials can improve the performance of immunoassays. Compared with traditional nanomaterials, upconversion nanoparticles (UCNPs) have excellent optical properties such as good photostability, long luminescence lifetime and narrow and tunable emission bands, which can significantly reduce background noise and improve analytical sensitivity when combined with immunoassay. This paper briefly introduces the luminescence mechanism of UCNPs, summarizes the synthesis and surface modification methods of UCNPs. And then 5 UCNPs-based immunoassay techniques, namely, fluorescence resonance energy transfer, inner filter effect, magnetic separation technique, upconversion-linked immunosorbent assay and upconversion immunochromatography, are discussed in detail. These sensing protocols of UCNPs-based immunoassays have been successfully utilized to detect various targets, including small molecules, macromolecules, and pathogens, all of which closely related to food safety, human health, and environmental pollution. Finally, the challenges and prospects of this technique are summarized and prospected. Although the UCNPs immunoassays based on antibodies and antigens have made great progress, most of the research is still in the stage of laboratory, and there is a long way to go to realize its social applications. There is a series of challenges need to be overcome. (1) Designing excellent water soluble and dispersive upconversion nanomaterials is needed. Hydrophilic ligands are bound to smaller upconversion nanoparticles and removing hydrophobic surface ligands are the most widely used methods to improve solubility and dispersity. (2) Multi-detection technology platforms and multi-mode simultaneous detection platforms have great potential, which will improve the efficiency of point of care detection. (3) The researchers also need to focus on some important problems. For examples, the upconversion luminescence efficiency of UCNPs is difficult to maintain, the synthesis method is complex, and the surface modification degree and functionalization are difficult to control.

Tumor is one of the major diseases that endanger people’s health. At present, the treatments used for tumor include surgery, chemotherapy, radiotherapy and so on. Nonetheless, the traditional treatments have some disadvantages, such as insufficient treatment effect, liable to cause multidrug resistance, toxicity and side effect. Further research and exploration of tumor treatment schemes are still necessary. As the energy converter of cells, mitochondria are currently considered to be one of the most important targets for the design of new drugs for tumor, cardiovascular and neurological diseases. Nano-drug delivery carriers have the characteristics of being easily modified with active targeting groups, and it can achieve accurate targeted drug delivery to cells and organelles. This paper reviews the application of mitochondrial targeted nanoparticles in tumor diagnosis and treatment from the aspects of inhibiting tumor cell proliferation, promoting tumor cell apoptosis, inhibiting tumor recurrence and metastasis, and inducing cell autophagy.

Objective:To evaluate the objective response rate (ORR) of induction chemoimmunotherapy with camrelizumab plus TPF (docetaxel, cisplatin, and capecitabine) for locally advanced hypopharyngeal squamous cell carcinoma (LA HSCC) and potential predictive factors for ORR.Methods:A single-center, prospective, phase 2 and single-arm trial was conducted for evaluating antitumor activity of camrelizumab+TPF(docetaxel+cisplatin+capecitabine) for LA HSCC between May 21, 2021 and April 15, 2023, patients admitted to the Eye & ENT Hospital affiliated with Fudan University. The primary endpoint was ORR, and enrolled patients with LA HSCC at T3-4N0-3M0 received induction chemoimmunotherapy for three cycles: camrelizumab 200 mg day 1, docetaxel 75 mg/m 2 day 1, cisplatin 25 mg/m 2 days 1-3, and capecitabine 800 mg/m 2 days 1-14. Patients were assigned to radioimmunotherapy when they had complete response or partial response (PR)>70% (Group A), or assigned to surgery plus adjuvant radiotherapy/chemoradiotherapy when they had PR≤70% (Group B), and the responses were defined by using tumor volume evaluation system. Tumor diameter was also used to assess the treatment responses by Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1. Use SPSS 23.0 software was used to analyze the data. Results:A total of 51 patients were enrolled who underwent the induced chemoimmunotherapy for three cycles, and all were males, aged 35-69 years old. After three cycles of induction immunochemotherapy, 42 (82.4%) patients existed in Group A (complete response or PR>70%) and 9 patients (17.6%) in Group B (PR≤70%), the ORR was 82.4%. The primary endpoint achieved expected main research objectives. Compared to the patients of Group A, the patients of Group B showed the higher T stage and the larger volume of primary tumor before induced immunochemotherapy, and also had the less regression of tumor volume after induced immunochemotherapy (all P<0.05). The optimal cutoff value of pre-treatment tumor volume for predicting ORR was 39 cm 3. The T stage ( OR=12.71, 95% CI: 1.4-112.5, P=0.022) and the volume ( OR=7.1, 95% CI: 1.4-36.8, P=0.018) of primary tumor were the two main factors affecting ORR rate of induction chemoimmunotherapy. Conclusion:The induction chemoimmunotherapy with camrelizumab plus TPF shows an encouraging antitumor efficacy in LA HSCC.