[摘 要] 目的：构建负载STING激动剂DMXAA的锰卟啉金属有机框架纳米颗粒（DPM），探讨其对三阴性乳腺癌（TNBC）细胞4T1及其小鼠移植瘤的治疗效果。方法：通过物理吸附法制备 DPM 纳米颗粒，利用透射电镜、扫描电镜及纳米粒度电位仪表征其形貌与理化性质。常规培养4T1细胞，细胞实验分为对照组、超声辐照组（US组）、DPM治疗组（DPM组）和DPM治疗联合超声辐照组（DPM + US组），用CCK-8法检测细胞活性，免疫荧光法检测高迁移率族蛋白B1（HMGB1）和钙网蛋白（CRT）的表达，WB法检测STING通路相关蛋白的表达。构建4T1细胞移植瘤小鼠模型，分为四组，处理同细胞实验，测量肿瘤体积，免疫荧光法检测移植瘤组织中Ki-67、HMGB1、CRT和缺氧诱导因子-1ɑ（HIF-1ɑ）蛋白的表达，TUNEL法检测细胞凋亡，流式细胞术检测免疫细胞活化情况，对主要器官进行H-E染色，以评估纳米材料的体内安全性。结果：DPM呈梭形，平均粒径（268 ± 3.302）nm，电位（33.1 ± 0.87）mV。细胞实验中，DPM联合超声辐照可明显抑制4T1细胞的增殖（P < 0.001），提高4T1细胞中ROS水平（P < 0.001），诱导4T1细胞CRT表达上调（P < 0.001），HMGB1从细胞核中移至细胞质，激活STING信号通路[p-STING、p-TBK1、p-IRF3蛋白表达均显著增加（均P < 0.001）]。体内实验中，DPM联合超声辐照可显著抑制4T1细胞移植瘤生长（P < 0.001）并促进免疫细胞表型转化（P < 0.001），抑制移植瘤组织中Ki-67、HIF-1α蛋白表达（均P < 0.01），谷胱甘肽（GSH）产生（P < 0.01），促进CRT、HMGB1蛋白表达、ROS产生（P < 0.001），对主要器官结构无明显影响。结论： DPM联合超声辐照可通过激活STING通路显著抑制4T1细胞及其移植瘤的生长，诱导抗肿瘤免疫应答，且对主要器官无明显毒性。

Onco-critical care has emerged as an important subspecialty at the intersection of critical care medicine and oncology, attracting increasing attention in recent years. With continuous innovations in cancer therapies, patient survival has improved significantly; however, the incidence of associated critical complications has also increased. The reasons for cancer patients requiring intensive care unit admission are diverse and can be broadly categorized into three groups: progression of the underlying malignancy, treatment-related complications, and coexisting classical critical illnesses. Traditional critical care concepts and practices face limitations in addressing the multidimensional and heterogeneous challenges of onco-critical care. Based on the core mechanism of critical illness development—host/organ unregulated response (HOUR)—this article systematically elaborates on how this framework advances understanding and clinical practice into onco-critical care, with emphasis on its manifestations in neuroendocrine, immune-inflammatory, and coagulation-metabolic pathways. The review summarizes recent advances in clinical assessment and phenotyping systems for onco-critical illness and discusses a multidisciplinary, integrated management strategy centered on the "Disease Control, Host Response Modulation, Organ Support" triad. Finally, major challenges and future directions in this field are outlined. By integrating existing evidence and theoretical insights, this review aims to provide new perspectives and a theoretical foundation for the clinical management of onco-critical illness, thereby promoting its evolution toward precision and standardization.

Ulcerative colitis （UC） is a chronic and relapsing inflammatory disease of the intestine. Intestinal fibrosis represents a severe co mplication and a potential risk factor for malignant transformation. Gentianopsis paludosa is one of the traditional Tibetan medicines commonly used for treating gastrointestinal disorders such as damp-heat diarrhea and dysentery. Its chemical composition is complex， encompassing xanthones， flavonoids， terpenoids， and other bioactive components， and it exhibits properties such as clearing heat， eliminating dampness， and detoxifying. This article reviews the research progress on the pharmacodynamic material basis and mechanisms of G. paludosa against UC and associated fibrosis. Findings suggest that its extracts （e.g.， aqueous extract， ethyl acetate extract） and active constituents （e.g.， 1-hydroxy-3，7，8-trimethoxyxanthone， ursolic acid， swertiamarin， luteolin） may inhibit inflammatory cytokines， combat oxidative stress， suppress cell apoptosis， regulate intestinal microbiota and their metabolites， protect the intestinal mucosal barrier， modulate immune responses， and inhibit epithelial-mesenchymal transition， through modulating relevant signaling pathways， such as nuclear factor-kappa B， B-cell lymphoma-2 （Bcl-2）/Bcl-2-associated X protein， and transforming growth factor-β 1 /Smad， thus exerting therapeutic effects against UC and its related fibrosis via these seven aspects.

Objective:To analyze the results of Healthy Zhejiang assessment and reveal the weakness in the process of Healthy Zhejiang construction,in order to propose suggestions for promoting the high-quality of Healthy Zhejiang construction.Methods:Descriptive statistics were used to analyze the points-deduction rates of the assessment indicators of Healthy Zhejiang in 90 counties(county-level cities and districts)of Zhejiang Province and non-parametric tests were used to analyze the results of Healthy Zhejiang assessment from 2020 to 2023.Results:The overall effect of Healthy Zhejiang construction from 2020 to 2023 was remarkable,but there were inadequacies and weakness in four aspects:residents'proactive health awareness,primary healthcare service capacity,healthy living environments,and the construction and management of sports facilities.Conclusions:It is still necessary to formulate multifaceted health education program,strengthen the construction of the primary healthcare service system,improve the collection,transportation and disposal system of rural domestic waste,and continuously promote the high-quality development of public sports service.

A recombinant adenovirus(rAd)for expression of Mycobacterium tuberculosis(M.tb)c-di-AMP phosphodiesterase CnpB was constructed,and its induced humoral immune response was detected.The codon-optimized gene of M.tb CnpB was cloned into the adenoviral plasmid pcADV.The recombinant plasmid pcADV-CnpB was transfected into HEK293T cells,and expression was detected with Western blot.The recombinant plasmid pcADV-CnpB and the backbone plasmid were co-transfected into HEK293T cells to obtain the recombinant adenovirus rAd-CnpB.rAd-CnpB was amplified in HEK293T cells,and the target protein expression of rAd-CnpB was detected with Western blot and immunofluorescence.Mice were immunized with rAd-CnpB intranasally,and their sera and bronchoalveolar lavage fluid(BALF)were collected.ELISA was used to detect levels of antigen-specific antibodies.Restriction enzyme digestion and sequencing indicated that the recombinant plasmid pcADV-CnpB was successfully constructed and led to protein expression in eukaryotic cells.rAd-CnpB was packaged and produced in HEK293T cells.After amplification and purification,rAd-CnpB with a titer of 5.53×1010 PFU/mL was obtained.rAd-CnpB led to CnpB expression in HEK293T cells.Intranasal immunization with rAd-CnpB increased levels of IgG and secretory IgA in BALF and led to high levels of IgG in sera.rAd-CnpB,the recombinant adenovirus for expression of c-di-AMP phosphodiesterase CnpB was successfully constructed,and was found to induce antigen-specific humoral and mucosal immune responses through mucosal immunization.Thus,rAd-CnpB may be used in further research on new TB vaccine strategies.

Objective:To verify the efficacy of VELscope autofluorescence examination technology in the early warning of potential oral malignant diseases.Methods:80 patients with suspected dysplasia were included and underwent oral examination,visually en-hanced lesion scope(VELscope)autofluorescence examination and histopathology examination respectively,the fluorescence imaging results were compared with the histopathological results.Results:Pathological reports showed 64 cases with mild or no dysplasia,9 cases with moderate or severe dysplasia,1 case with moderate dysplasia without malignant transformation and 6 cases with cancer.The results of VELscope showed that there were 73 positive cases and negative 7 cases of fluorescence deletion.The sensitivity and specificity of VELscope were 93.75％and 9.37％respectively,and the sensitivity could reach 100％in the cancerous tissue.Con-clusion:As a non-invasive examination method,VELscope is highly sensitive but lowly specific.

BACKGROUND:A novel aggregation induced luminescence fluorescence probe based on the mechanism of intramolecular motility restriction can be used for the detection of disease markers,tumor diagnosis,and bacterial imaging recognition.OBJECTIVE:To prepare a near-infrared Ⅱ nanoprobe called FA-DSPE-PEG-AIE@NPs based on aggregation-induced luminescence,and to explore its potential of targeted fluorescence imaging and photothermal therapy for prostate cancer.METHODS:Lecithin,polyethylene glycol phospholipids,folate polyethylene glycol phospholipids,and aggregation induced luminescent molecule 2TT-oC26B were used as raw materials.The folate-targeted nanoprobe FA-DSPE-PEG-AIE@NPs were prepared by nanoprecipitation method,and basic characterization of the nanoprobe was detected.PC3 human prostate cancer cells and human umbilical vein endothelial cells were selected as experimental objects.The cytotoxicity and phototoxicity of FA-DSPE-PEG-AIE@NPs were detected.PC3 human prostate cancer cells were selected as the experimental objects.Flow cytometry and calcein/propidium iodide staining were used to assess the efficacy of photothermal therapy.PC3 human prostate cancer cells were injected subcutaneously into the abdomen of BALB/C nude mice to establish a tumor model,and nanoprobes FA-DSPE-PEG-AIE@NPs were injected into the tail vein.The mice were immediately subjected to near-infraced Ⅱ fluorescence imaging.12 hours later,the tumor was irradiated by laser for 5 minutes,and the photothermal treatment effect was observed within 14 days.RESULTS AND CONCLUSION:(1)The nanoprobes FA-DSPE-PEG-AIE@NPs with a mean diameter of(171.0±0.3)nm showed a well-defined spherical morphology.The nanoprobe had a wide absorption spectrum and tail emission extending to the near-infrared Ⅱ which emitted a bright near-infrared Ⅱ fluorescence signal under laser irradiation.(2)The nanoprobes FA-DSPE-PEG-AIE@NPs had low cytotoxicity and high phototoxicity.The results of flow cytometry and calcein/propidium iodide staining showed that nanoprobes FA-DSPE-PEG-AIE@NPs had an obvious photothermal killing effect on human prostate cancer cells.(3)The nanoprobes FA-DSPE-PEG-AIE@NPs successfully achieved near-infrared Ⅱ fluorescence imaging of mouse blood vessels and the maximum enrichment time of the tumor was 12 hours.The vessel widths of the hind leg and single blood vessels of abdomen were estimated to be 0.63 mm and 0.42 mm.The tumor volume of mice was significantly smaller after 14 days of treatment.(4)The results show that nanoprobes FA-DSPE-PEG-AIE@NPs can achieve near-infrared Ⅱ fluorescence imaging and photothermal therapy of prostate cancer effectively,which may provide a new method for early diagnosis and combined treatment of prostate cancer.

Objective To construct 5 machine-learning models and compare their performance in predicting the associations between pre-pregnancy socio-psycho-behavioral exposures of both spouses and preconception outcomes.Methods Based on Chongqing Preconception Reproductive Health and Birth Outcome Cohort of volunteers recruited from Chongqing Health Center for Women and Children during January 2019 and March 2022,5 447 couples were recruited and surveyed through interviewer-interview for the demographic and social-psychological-behavioral data of both spouses(221 variables).According to the inclusion and exclusion criteria,4 097 couples were finally included,and randomly assigned into a training set(n=2 867 spouses)and a validation set(n=1 230 spouses)at a ratio of 7∶3.Feature analysis and collinear screening were applied to select the potential exposure factors.In consideration of difficulty to carry out semen parameters analysis in primary healthcare institutions,feature Set 1 including sperm parameters and feature Set 2 excluding semen parameters were constructed by including or excluding sperm quality simultaneously in the training set and the validation set.Five algorithms,that is,Logistic Regression,Naive Bayes,Random Forest,Gradient Boosting Machine,and Support Vector Machine,were used to construct preconception outcome prediction models,and the parameters of each model were optimized using random search combined with grid search.The predictive performance of each model was compared using precision,recall,F1 score,area under the receiver operating characteristic curve(AUC),and calibration curve.The optimal model was then selected by comparing the changes in the predictive ability of the questionnaire data for fertility outcomes with or without semen parameters.Results There were 24 variables screened out in feature Set 1,and 16 variables in feature Set 2.In feature Set 1,the gradient boosting machine performed better,with a relatively higher AUC value(0.651)and better F1 score(0.61).The logistic regression model performed stably(AUC value=0.647)and was suitable as the reference model.The random forest(AUC value=0.641),Naive Bayes(AUC value=0.641),and support vector machine(AUC value=0.634)performed second-best.By utilizing the gradient boosting machine,comparable results were found between the predictions from feature sets with or without semen parameters,as in feature Set 1,the AUC value of its validation set was 0.651(95%CI:0.629～0.681),the prediction accuracy was 0.63,the recall rate was 0.65,and the average precision value F1 was 0.61;and in feature Set 2,the AUC value of its validation set was 0.649(95%CI:0.624～0.663),and both the calibration curves were close to the ideal curve.The prediction results indicated that in feature Set 1,the features highly negatively correlated with preconception outcomes were female age,male age,and no pregnancy within 1 year without contraception,while the features highly positively correlated with preconception outcomes were female pregnancy history,total sperm vitality,and use of contraceptive measures before enrollment.Conclusion Among the 5 machine-learning algorithms performed in this cohort data,the gradient boosting machine shows slightly better performance.There are 24 factors being associated with preconception outcomes in both spouses,and the performance of the simplified model excluding semen parameters is not significantly declined.It is feasible to use machine-learning methods to predict human preconception outcomes through social-psychological-behavioral questionnaires.

Objective:This study aims to establish a real world study (RWS) quality evaluation model based on Analytic Hierarchy Process -Fuzzy Comprehensive Evaluation Methods (AHP-FCE), and provide a reference basis for researchers and quality control personnel in medical and health institutions.Methods:The evaluation index framework of RWS quality was obtained by analyzing national RWS regulations. Two rounds of Delphi expert consultation were conducted, while the results were statistically analyzed and weighted using the AHP method by Yaahp software. The comprehensive evaluation model of RWS was established by combining AHP and FCE methods.Results:The RWS quality evaluation model based on AHP-FCE methods was constructed, including 6 primary indicators, 31 secondary indicators, and specific indicator evaluation methods, and validated through RWS case analysis.Conclusions:The RWS quality evaluation model constructed in this study is reasonable and practical, which can provide a reference for institutional researchers and quality managers.

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.