Alzheimer's disease (AD) classification models usually segment the entire brain image into voxel blocks and assign them labels consistent with the entire image, but not every voxel block is closely related to the disease. To this end, an AD auxiliary diagnosis framework based on weakly supervised multi-instance learning (MIL) and multi-scale feature fusion is proposed, and the framework is designed from three aspects: within the voxel block, between voxel blocks, and high-confidence voxel blocks. First, a three-dimensional convolutional neural network was used to extract deep features within the voxel block; then the spatial correlation information between voxel blocks was captured through position encoding and attention mechanism; finally, high-confidence voxel blocks were selected and combined with multi-scale information fusion strategy to integrate key features for classification decision. The performance of the model was evaluated on the Alzheimer's Disease Neuroimaging Initiative (ADNI) and Open Access Series of Imaging Studies (OASIS) datasets. Experimental results showed that the proposed framework improved ACC and AUC by 3% and 4% on average compared with other mainstream frameworks in the two tasks of AD classification and mild cognitive impairment conversion classification, and could find the key voxel blocks that trigger the disease, providing an effective basis for AD auxiliary diagnosis.
Alzheimer Disease/diagnosis* ; Humans ; Neuroimaging/methods* ; Neural Networks, Computer ; Brain/diagnostic imaging* ; Magnetic Resonance Imaging ; Deep Learning ; Machine Learning

Despite that sleep disturbance and poor neurocognitive performance are common complaints among coronavirus disease 2019 (COVID-19) survivors, few studies have focused on the effect of post-COVID-19 sleep disturbance (PCSD) on cognitive function. This study aimed to identify the impact of PCSD on neurocognitive function and explore the associated risk factors for the worsening of this condition. This cross-sectional study was conducted via the web-based assessment in Chinese mainland. Neurocognitive function was evaluated by the modified online Integrated Cognitive Assessment (ICA) and the Number Ordering Test (NOT). Propensity score matching (PSM) was utilized to match the confounding factors between individuals with and without PCSD. Univariate analyses were performed to evaluate the effect of PCSD on neurocognitive function. The risk factors associated with worsened neurocognitive performance in PCSD individuals were explored using binary logistic regression. A total of 8692 individuals with COVID-19 diagnosis were selected for this study. Nearly half (48.80%) of the COVID-19 survivors reported sleep disturbance. After matching by PSM, a total of 3977 pairs (7954 individuals in total) were obtained. Univariate analyses revealed that PCSD was related to worse ICA and NOT performance (P<0.05). Underlying disease, upper respiratory infection, loss of smell or taste, severe pneumonia, and self-reported cognitive complaints were associated with worsened neurocognitive performance among PCSD individuals (P<0.05). Furthermore, aging, ethnicity (minority), and lower education level were found to be independent risk factors for worsened neurocognitive performance in PCSD individuals (P<0.05). PCSD was related to impaired neurocognitive performance. Therefore, appropriate prevention and intervention measures should be taken to minimize or prevent PCSD and eliminate its potential adverse effect on neurocognitive function.
Humans ; COVID-19/epidemiology* ; Male ; Female ; Sleep Wake Disorders/epidemiology* ; Propensity Score ; Middle Aged ; Cross-Sectional Studies ; Adult ; SARS-CoV-2 ; Aged ; Risk Factors ; China/epidemiology* ; Cognition ; Cognitive Dysfunction/etiology* ; Neuropsychological Tests

Cuproptosis, a recently identified form of regulated cell death triggered by excess intracellular copper, has emerged as a promising cytotoxic strategy for cancer therapy. However, the therapeutic efficacy of copper ionophores such as elesclomol (ES) is often hindered by cellular copper homeostasis mechanisms that limit copper influx and cuproptosis induction. To address this challenge, we developed a nanoagent utilizing outer membrane vesicle (OMV) derived from Akkermansia muciniphila (Akk) for co-delivery of antioxidant 1 copper chaperone (Atox1)-targeting siRNA and ES (siAtox1/ES@OMV) to tumors. In vitro, we demonstrated that Atox1 knockdown via siRNA significantly disrupted copper export mechanisms, resulting in elevated intracellular copper levels. Simultaneously, ES facilitated efficient copper influx and mitochondrial transport, leading to Fe-S cluster depletion, increased proteotoxic stress, and robust cuproptosis. In vivo, siAtox1/ES@OMV achieved targeted tumor delivery and induced pronounced cuproptosis. Furthermore, leveraging the immunomodulatory properties of OMVs, siAtox1/ES@OMV promoted T-cell infiltration and the activation of tumor-reactive cytotoxic T cells, enhancing tumor immune responses. The combination of siAtox1/ES-induced cuproptosis and immunogenic cell death synergistically suppressed tumor growth in both subcutaneous breast cancer and orthotopic rectal cancer mouse models. This study highlights the potential of integrating copper homeostasis disruption with a copper ionophore using an immunomodulatory OMV-based vector, offering a promising combinatorial strategy for cancer therapy.

The year 2025 marks the 110th anniversary of the Chinese Medical Association. As one of the founding institutions of modern plastic surgery in China, Department of Plastic Surgery, the First Affiliated Hospital of Air Force Medical University (Xijing Hospital), has played a pioneering role in advancing the specialty since its establishment in 1955. The department has achieved remarkable innovations in key areas such as microsurgery, skin and soft tissue expansion, facial allotransplantation, and interdisciplinary integration. Through sustained efforts in platform development, talent cultivation, and scientific research, it has evolved into a comprehensive academic center. This article provides a comprehensive overview of the department’s 70-year developmental journey, highlights its major contributions, and outlines its future directions in promoting high-quality development in plastic surgery in China.

Objective:To construct analytical dimensions for policy texts related to the pilot work of Health Impact Assessment (HIA) system in Zhejiang Province and conduct quantitative analysis, thereby providing references for improving the pilot work.Methods:Policy texts issued by Zhejiang Province between February 11, 2018, and February 29, 2024, which involved HIA content, were selected. The policy instruments theory was employed to construct an analytical framework around the dimensions of policy instruments, policy objectives, policy actors, and the interactions between policy instruments and policy objectives, and between policy instruments and policy actors. Based on this framework, a combination of literature analysis and content analysis was used to conduct a multi-dimensional quantitative analysis of the policy texts related to the pilot work of HIA system in Zhejiang Province.Results:Fifty core policy texts were included and 1 588 codes were obtained. In terms of policy instruments, environmental-type instruments were the most widely used (852 items), with internal responsibilities and methodological measures being the most frequently used; supply-type instruments were the second most used (459 items), with mechanism improvement being the most frequently used; demand-type instruments were the least used (277 items), with multi-stakeholder participation being the most frequently used. In terms of policy objectives, the objective of system construction dominated (701 articles, accounting for 56.45%), while the proportion of policy coverage, evaluation technology, and effectiveness evaluation was relatively low. In terms of policy subjects, the Party committee and government were the main policy subjects (434 articles, accounting for 39.20%), followed by health departments and public policy-making departments, while the proportion of public health institutions and social forces was extremely low. In the interaction between policy instruments and policy objectives, policy coverage, system construction, and effectiveness evaluation objectives all responded most frequently to environmental-type instruments, while the evaluation technology objectives responded more frequently to supply-type instruments. In the interaction between policy instruments and policy subjects, the Party committee and government played a dominant role in the use of policy instruments, with the health department and public policy-making department in the middle.Conclusions:The pilot work of the HIA system in Zhejiang Province presented a " environment-driven, system-construction-priority, Party-committee-and-government-led" policy characteristic. The main challenges were the imbalanced structure of policy instruments, insufficient synergy among policy objectives, and the need for greater participation of multiple stakeholders.

Health think tanks serve as a crucial intellectual support for the Healthy China strategy. The authors systematically analyzed the definitions, classifications, and operational status of health think tanks, categorizing them into five types: government-affiliated think tanks, university and research institute think tanks, social think tanks, hospital think tanks, and corporate think tanks. It was indicated that current health think tanks had significant room for improvement in both quantity and influence, particularly concerning deeper integration with policy decision-making and interdisciplinary collaboration. Although these think tanks played a unique role in supporting government decision-making, issues such as lagging institutional development, insufficient collaborative effectiveness, and difficulties in translating research findings into practice remained prominent. To enhance the ability of think tanks to serve the Healthy China strategy, this study proposed strategies including strengthening top-level design, improving participation mechanisms, optimizing management and evaluation systems, establishing data-sharing platforms, and deepening collaborative governance, with the aim of fostering the healthy development of China′s health think tanks.

Objective To explore the application value of CT-based radiomics in differentiating pneumonia-type mucinous adenocarcinoma(PTMA)from organizing pneumonia(OP).Methods A total of 52 PTMA patients and 102 OP patients were retrospectively included and randomly divided into training set(n=124)and test set(n=30)in an 8∶2 ratio.Eight PTMA patients and 22 OP patients from another hospital during the same period were included as external validation set(n=30).Clinical characteristics and CT signs of the patients were selected to construct the clinical model.Radiomics features were extracted and dimensionality reduction was performed through the least absolute shrinkage and selection operator(LASSO)algorithm.A radiomics model was constructed and the Radiomics score(Radscore)was calculated.The Radscore was combined with clinical factors to establish the combined model and a nomogram was illustrated.The models' fitting degree was analyzed by the calibration curve,while their efficacy was evaluated by the receiver operating characteristic(ROC)curve and decision curve analysis(DCA).Results The clinical model,established based on the border,cystic space and bronchial leafless tree sign,achieved area under the curve(AUC)of 0.850,0.782,and 0.759 in the training set,test set,and external validation set,respectively.Thirteen features were obtained to construct the radiomics model,with AUC of 0.925,0.865,and 0.830,respectively.The AUC of the combined model were 0.970,0.905,and 0.864,respectively,in which the calibration curve demonstrated good model fitting.DCA indicated that the combined model had the greatest clinical net benefit.Conclusion The combined model based on CT radiomics can effectively distinguish PTMA from OP.

This study aims to understand the biological characteristics of Streptococcus dysgalacti-ae of yak origin.Bacterial isolation and identification,drug susceptibility test,virulence gene test and pathogenicity test were carried out on milk samples of yaks from Naqu City to evaluate the bi-ological characteristics of the isolated strains.Meanwhile,molecular biological information such as virulence factors and drug resistance genes were analyzed by whole genome sequencing,and viru-lence genes were verified by PCR.The results showed that a strain of Streptococcus dysgalactiae was isolated from the milk of yak,and its colony morphology was pinpoint size,smooth edge and milky white.This strain is sensitive to many antibiotics(penicillin G,cephalosporin,ciprofloxacin,tetracycline,erythromycin,etc.).Virulence gene test results showed that the strain carries six key virulence genes(cyl,eno,scpB,bca,bac and napr),which may be closely related to its pathoge-nicity.In the pathogenicity test,the mice were listless and less active after infection,but no death occurred during the observation period.The pathological changes of spleen,kidney,liver and lung tissue were found,suggesting that the strain had certain pathogenic potential but not high lethali-ty.Whole genome sequencing data showed that the gene length of this strain was 4 079 280 bp,the GC content was 39.41％,3 964 coding genes were predicted,604 of which were annotated as viru-lence factors,and another 28 gene mutations may enhance its pathogenic ability.Through annota-tion of CARD database,two Pat A resistance genes and two lmrp resistance genes were found,re-vealing their potential resistance mechanism.Through whole genome sequencing technology and bioinformatics analysis method,this study revealed the genomic characteristics,drug resistance and pathogenicity mechanism of Streptococcus dysgalactiae of yak origin.The findings provide impor-tant scientific evidence for further exploration of the pathogenicity,drug resistance mechanisms,and molecular evolution of yak-derived Streptococcus agalactiae.

Objective To explore the application value of CT-based radiomics in differentiating pneumonia-type mucinous adenocarcinoma(PTMA)from organizing pneumonia(OP).Methods A total of 52 PTMA patients and 102 OP patients were retrospectively included and randomly divided into training set(n=124)and test set(n=30)in an 8∶2 ratio.Eight PTMA patients and 22 OP patients from another hospital during the same period were included as external validation set(n=30).Clinical characteristics and CT signs of the patients were selected to construct the clinical model.Radiomics features were extracted and dimensionality reduction was performed through the least absolute shrinkage and selection operator(LASSO)algorithm.A radiomics model was constructed and the Radiomics score(Radscore)was calculated.The Radscore was combined with clinical factors to establish the combined model and a nomogram was illustrated.The models' fitting degree was analyzed by the calibration curve,while their efficacy was evaluated by the receiver operating characteristic(ROC)curve and decision curve analysis(DCA).Results The clinical model,established based on the border,cystic space and bronchial leafless tree sign,achieved area under the curve(AUC)of 0.850,0.782,and 0.759 in the training set,test set,and external validation set,respectively.Thirteen features were obtained to construct the radiomics model,with AUC of 0.925,0.865,and 0.830,respectively.The AUC of the combined model were 0.970,0.905,and 0.864,respectively,in which the calibration curve demonstrated good model fitting.DCA indicated that the combined model had the greatest clinical net benefit.Conclusion The combined model based on CT radiomics can effectively distinguish PTMA from OP.

The year 2025 marks the 110th anniversary of the Chinese Medical Association. As one of the founding institutions of modern plastic surgery in China, Department of Plastic Surgery, the First Affiliated Hospital of Air Force Medical University (Xijing Hospital), has played a pioneering role in advancing the specialty since its establishment in 1955. The department has achieved remarkable innovations in key areas such as microsurgery, skin and soft tissue expansion, facial allotransplantation, and interdisciplinary integration. Through sustained efforts in platform development, talent cultivation, and scientific research, it has evolved into a comprehensive academic center. This article provides a comprehensive overview of the department’s 70-year developmental journey, highlights its major contributions, and outlines its future directions in promoting high-quality development in plastic surgery in China.