With the rapid development and application of cutting-edge neurotechnology， the ethical issues of brain data have become a research hotspot. Brain data， which directly accesses humans’ thoughts and the “loss of control” state under intentional control， deconstructs the subjects’ exclusive right to access their own brain， thereby comprehensively challenging human privacy. The subjects cannot fully control which brain activity signals are collected， and the decoded results of brain data violate the subjects’ autonomy while applying brain data to unknown purposes， posing challenges to informed consent. Brain data describes who you are from a “super first-person” perspective， and it can even “forge” a real first-person perspective to describe who you are. The external presentation of brain data analysis results involves ethical issues in three dimensions， namely， what should be presented， how others treat the analysis results of brain data， and the ethical risks brought about by presenting information in brain data. The governance strategies on the ethical issues of brain data require improving the relevant laws of brain data supervision， refining the ethical principles for brain data applications， leveraging the leading role of the government， and strengthening international cooperation.

Objective: To systematically characterize the developmental trajectory and interdisciplinary integration of intelligent diagnosis in traditional Chinese medicine (TCM) through quantitative topic evolution analysis, we addressed the fragmentation of existing research and clarified the long-term research structure and evolutionary patterns of the field. Methods: A topic evolution analysis was performed on Chinese-language literature pertaining to intelligent diagnosis in TCM. Publications were retrieved from the China National Knowledge Infrastructure (CNKI), Wanfang Data, and China Science and Technology Journal Database (VIP), covering the period from database inception to July 3, 2025. A hybrid segmentation approach, based on cumulative publication growth trends and inflection point detection, was applied to divide the research timeline into distinct stages. Subsequently, the latent Dirichlet allocation (LDA) model was used to extract research topics, followed by alignment and evolutionary analysis of topics across different stages. Results: A total of 3 919 publications published between 2003 and 2025 were included, and the research trajectory was divided into five stages based on data-driven breakpoint detection. The field exhibited a clear evolutionary shift from early rule-based systems and tongue-pulse image and signal analysis (2006 – 2010), to machine-learning-based syndrome and prescription modeling (2011 – 2015), followed by deep-learning-driven pattern recognition and formula association (2016 – 2020). Since 2021, research has increasingly emphasized knowledge-graph construction, multimodal integration, and intelligent clinical decision-support systems, with recent studies (2024 – 2025) showing the emergence of large language models and agent-based diagnostic frameworks. Topic evolution analysis further revealed sustained cross-stage continuity in syndrome modeling and prescription association analysis, alongside the progressive consolidation of integrated intelligent diagnostic platforms. Conclusion By identifying key technological transitions and persistent core research themes, our findings offer a structured reference framework for the design of intelligent diagnostic systems, the construction of knowledge-driven clinical decision-support tools, and the alignment of AI models with TCM diagnostic logic. Importantly, the stage-based evolutionary insights derived from this analysis can inform future methodological choices, improve model interpretability and clinical applicability, and support the translation of intelligent TCM diagnosis from experimental research to real-world clinical practice.

This paper proposes a two-stage method integrating visual foundation models （VFM） and diffusion models. The segment anything model （SAM） as VFM is combined with the SegRefiner diffusion model to construct the SAM-SegRefiner framework for automated segmentation of edema， inflammation， and thrombus regions in histopathological images of hemorrhoidal tissue， providing a reproducible technical tool for the objective quantification of pathological morphology and its application in traditional Chinese medicine （TCM） syndrome research. Trained and validated on multi-center retrospective data， the SAM-SegRefiner model achieved an average pixel accuracy of 95.32% and a mean intersection over union （mIoU） of 66.81% on an independent test set， significantly outperfor-ming comparative models such as U-Net， MixU-Net， and SAM-Med2D， and also demonstrating robust cross-center generalization capability. Furthermore， by correlating the quantitatively segmented results from the model with the patients' TCM syndrome types， the potential associations between pathomorphological features and TCM syndrome differentiation have been explored. The analysis revealed no statistically significant differences in the degree of inflammatory infiltration and thrombus formation among different syndrome types， suggesting a complex relationship between local pathological changes and systemic syndrome manifestations.

[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。

Background As climate change intensifies and extreme temperature events become more frequent, non-optimal temperature has emerged as a significant contributor to the global disease burden, representing a pressing public health challenge. Objective To analyze the disease burden, temporal trends, and health inequalities attributable to non-optimal, high, and low temperatures in China from 1990 to 2021, and to compare these findings with global levels to provide a scientific basis for targeted prevention strategies. Methods Using data from the Global Burden of Disease 2021 (GBD 2021), we extracted mortality rates and disability-adjusted life year (DALY) rates, and other indicators attributable to non-optimal, high, and low temperatures by sex, age, region, and cause. Joinpoint regression was applied to examine temporal trends. Decomposition analysis identified driving factors of change, while the slope index of inequality (SII) and concentration index (CI) quantified disparities across socio-demographic index (SDI) levels. Results From 1990 to 2021, the age-standardized mortality rates (ASMR) and age-standardized DALY rates (ASDR) attributable to non-optimal temperature in China exhibited a downward trend, decreasing from 66.48 (95%UI: 58.09, 76.56) to 32.70 (95%UI: 27.26, 39.26) per 100000 population, and from 1219.59 (95%UI: 1056.28, 1418.37) to 493.22 (95%UI: 403.88, 609.32) per 100000 population, respectively. Burdens attributable to non-optimal temperature and low temperature were higher than the global average, whereas the high temperature burden was lower. Males consistently experienced higher ASMR and ASDR attributable to non-optimal temperature than females. Cardiovascular diseases, chronic respiratory diseases, and respiratory infections and tuberculosis were the top three causes of non-optimal temperature-attributable burdens. Decomposition analysis revealed that population aging and growth were the primary drivers of increased burden, while epidemiological changes primarily drove the decline. Health inequalities were most predominant between extreme SDI regions but narrowed over time. Conclusion Despite the overall decline in burden attributable to non-optimal temperature in China, significant challenges remain, including high risks from cold exposure, gender disparities, and the compounding effects of an aging population with cardiovascular or respiratory diseases. Policy makers should prioritize climate change adaptation, focusing on elderly health and regional equity while strengthening the public health workforce.

Background Microparticles (MPs) are one of the main medium of inflammatory reaction with an important role in atherosclerotic progression. Studies on association of air pollution exposure and levels of peripheral blood MPs are limited among human. Objective To evaluate the effects of short-term exposure to air pollution on levels of peripheral blood MPs. Method A panel of 73 healthy adults was followed with 4 repeated follow-ups in Beijing, China, from November 2014 to January 2016. During each visit, we collected questionnaire information, fasting venous blood, urine, and exposures to fine particulate matter (PM_2.5), black carbon, nitric oxide, nitrogen dioxide, nitrogen oxide, sulfur dioxide, carbon monoxide, and ozone. We used linear mixed-effect models to analyze associations of air pollution exposure with levels of total MPs (TMPs) and MPs derived from various cells. Stratified analysis was conducted by levels of C-reactive protein (CRP) and malondialdehyde (MDA). Results The results showed significant associations between air pollution exposure and peripheral blood TMPs at 2 h-6 d prior to the follow-ups (P<0.05), while no statistical associations were found for MPs derived from different cell types. Significant increases in TMPs of 7.8% (95%CI: 0.7%, 15.3%) and 14.3% (95%CI: 2.8%, 27.2%) were observed with each interquartile range (IQR) increase in PM_2.5 (IQR=64.9 μg·m⁻³) at prior 18 h and NO (IQR=40.5 μg·m⁻³) at prior 48 h. Among participants with low levels of CRP and MDA, significantly positive associations were observed between air pollution exposure and levels of TMPs (P<0.05). Conclusion Short-term exposure to air pollution is significantly associated with increased levels of circulating MPs in healthy adults, and in people with lower systemic inflammation, peripheral blood MPs levels are more easily affected after exposure to air pollutants.

Background As climate change intensifies and extreme temperature events become more frequent, non-optimal temperature has emerged as a significant contributor to the global disease burden, representing a pressing public health challenge. Objective To analyze the disease burden, temporal trends, and health inequalities attributable to non-optimal, high, and low temperatures in China from 1990 to 2021, and to compare these findings with global levels to provide a scientific basis for targeted prevention strategies. Methods Using data from the Global Burden of Disease 2021 (GBD 2021), we extracted mortality rates and disability-adjusted life year (DALY) rates, and other indicators attributable to non-optimal, high, and low temperatures by sex, age, region, and cause. Joinpoint regression was applied to examine temporal trends. Decomposition analysis identified driving factors of change, while the slope index of inequality (SII) and concentration index (CI) quantified disparities across socio-demographic index (SDI) levels. Results From 1990 to 2021, the age-standardized mortality rates (ASMR) and age-standardized DALY rates (ASDR) attributable to non-optimal temperature in China exhibited a downward trend, decreasing from 66.48 (95%UI: 58.09, 76.56) to 32.70 (95%UI: 27.26, 39.26) per 100000 population, and from 1219.59 (95%UI: 1056.28, 1418.37) to 493.22 (95%UI: 403.88, 609.32) per 100000 population, respectively. Burdens attributable to non-optimal temperature and low temperature were higher than the global average, whereas the high temperature burden was lower. Males consistently experienced higher ASMR and ASDR attributable to non-optimal temperature than females. Cardiovascular diseases, chronic respiratory diseases, and respiratory infections and tuberculosis were the top three causes of non-optimal temperature-attributable burdens. Decomposition analysis revealed that population aging and growth were the primary drivers of increased burden, while epidemiological changes primarily drove the decline. Health inequalities were most predominant between extreme SDI regions but narrowed over time. Conclusion Despite the overall decline in burden attributable to non-optimal temperature in China, significant challenges remain, including high risks from cold exposure, gender disparities, and the compounding effects of an aging population with cardiovascular or respiratory diseases. Policy makers should prioritize climate change adaptation, focusing on elderly health and regional equity while strengthening the public health workforce.

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.

To summarize the clinical characteristics, antibody spectrum and neuroelectrophysiological features of autoimmune nodopathy(AN), and to explore the phenotypic differences among different antibody-positive subgroups.

Multidrug-resistant (MDR) bacterial infections have emerged as a serious challenge of global public health crisis. The overuse and misuse of conventional antibiotics have dramatically accelerated the emergence, evolution and worldwide spread of drug-resistant bacterial strains, necessitating urgent exploration of novel antibacterial strategies. Bacteriophages serve as natural bacterial predators offering distinct advantages including high host specificity, autonomous self-replication capabilities and cost-effective large-scale production. However, wild-type phages present significant clinical limitations due to their narrow host ranges, susceptibility to rapid immune clearance and poor penetration of bacterial biofilms, which severely restrict their therapeutic applications. The convergence of synthetic biology, nanotechnology and advanced gene editing technologies has accelerated the development of engineered bacteriophage platforms, providing programmable, scalable and clinically translatable pathways to overcome these inherent biological constraints. Here, we systematically delineate four fundamental strategies for engineered bacteriophage development. Chemical modification utilizes reactive functional groups such as amino, carboxyl and thiol moieties on capsid proteins through esterification, amidation or click chemistry reactions to achieve precise drug conjugation and surface functionalization. In vivo editing encompasses ultraviolet or chemical mutagenesis for random mutation induction, homologous recombination for targeted genetic alterations, recombineering methodologies including electroporation-mediated bacteriophage recombination engineering, and CRISPR-Cas systems for precise genome editing to enable exact genetic reconstruction and host range reprogramming. In vitro synthesis leverages genome engineering platforms where intact phage genomes are transferred into yeast or host bacteria to facilitate highly efficient homologous recombination, enabling large DNA fragment assembly and cross-gene host range expansion without bacterial toxicity constraints. Directed evolution combines artificial selection through mutation library screening with rational design approaches involving chimeric receptor binding protein construction or site-specific mutagenesis, effectively balancing the discovery of unknown adaptive pathways with targeted host specificity modification. Moreover, we comprehensively discuss therapeutic applications across diverse clinical scenarios. Engineered bacteriophage effectively disrupt bacterial biofilms through sophisticated functionalized delivery platforms including nanozyme-conjugated phages, phage-liposome nanoconjugates and bio-responsive hydrogels, demonstrating significantly enhanced bactericidal efficiency compared to unmodified free phages. These bioengineered vectors attenuate bacterial virulence and resensitize pathogens to antibiotics by delivering CRISPR-Cas systems or base editors to disrupt critical virulence factors such as pili, capsule synthesis machineries and quorum sensing systems, or by inactivating antibiotic resistance determinants including beta-lactamase genes. As an intelligent nanomedicine delivery platform, engineered bacteriophage enable precise pathogen elimination an through photocatalytic reactive oxygen species generation, immunomodulatory interventions, or controlled release of antibacterial drugs. Furthermore, oral administration of engineered bacteriophage facilitates microbiota modulation, which selectively eliminate intestinal pathogens while preserve beneficial commensal microbiota, thereby restoring microbial community balance and preventing complications associated with dysbiosis. Finally, we critically analyze persistent challenges including host strain matching complexity, evolution of bacterial resistance mechanisms, pharmacokinetic optimization requirements, optimal administration route selection, large-scale production quality control standards and clinical dosing determination protocols. Through multidisciplinary integration of synthetic biology, infectious disease medicine and immunology, future translational medicine studies of bacteriophage should establish comprehensive technical platforms encompassing rapid phage screening, intelligent rational design, rigorous in vivo evaluation and standardized clinical validation processes, ultimately advancing engineered bacteriophage from laboratory innovations to clinically approved therapeutics for effectively combating MDR bacterial infections.