ObjectiveRepetitive transcranial magnetic stimulation (rTMS) has demonstrated efficacy in enhancing neurocognitive performance in Alzheimer’s disease (AD), but the neurobiological mechanisms linking synaptic pathology, neural oscillatory dynamics, and brain network reorganization remain unclear. This investigation seeks to systematically evaluate the therapeutic potential of rTMS as a non-invasive neuromodulatory intervention through a multimodal framework integrating clinical assessments, molecular profiling, and neurophysiological monitoring. MethodsIn this prospective double-blind trial, 12 AD patients underwent a 14-day protocol of 20 Hz rTMS, with comprehensive multimodal assessments performed pre- and post-intervention. Cognitive functioning was quantified using the mini-mental state examination (MMSE) and Montreal cognitive assessment (MOCA), while daily living capacities and neuropsychiatric profiles were respectively evaluated through the activities of daily living (ADL) scale and combined neuropsychiatric inventory (NPI)-Hamilton depression rating scale (HAMD). Peripheral blood biomarkers, specifically Aβ1-40 and phosphorylated tau (p-tau181), were analyzed to investigate the effects of rTMS on molecular metabolism. Spectral power analysis was employed to investigate rTMS-induced modulations of neural rhythms in AD patients, while brain network analyses incorporating topological properties were conducted to examine stimulus-driven network reorganization. Furthermore, systematic assessment of correlations between cognitive scale scores, blood biomarkers, and network characteristics was performed to elucidate cross-modal therapeutic associations. ResultsClinically, MMSE and MOCA scores improved significantly (P<0.05). Biomarker showed that Aβ1-40 level increased (P<0.05), contrasting with p-tau181 reduction. Moreover, the levels of Aβ1-40 were positively correlated with MMSE and MOCA scores. Post-intervention analyses revealed significant modulations in oscillatory power, characterized by pronounced reductions in delta (P<0.05) and theta bands (P<0.05), while concurrent enhancements were observed in alpha, beta, and gamma band activities (all P<0.05). Network analysis revealed frequency-specific reorganization: clustering coefficients were significantly decreased in delta, theta, and alpha bands (P<0.05), while global efficiency improvement was exclusively detected in the delta band (P<0.05). The alpha band demonstrated concurrent increases in average nodal degree (P<0.05) and characteristic path length reduction (P<0.05). Further research findings indicate that the changes in the clinical scale HAMD scores before and after rTMS stimulation are negatively correlated with the changes in the blood biomarkers Aβ1-40 and p-tau181. Additionally, the changes in the clinical scales MMSE and MoCA scores were negatively correlated with the changes in the node degree of the alpha frequency band and negatively correlated with the clustering coefficient of the delta frequency band. However, the changes in MMSE scores are positively correlated with the changes in global efficiency of both the delta and alpha frequency bands. Conclusion20 Hz rTMS targeting dorsolateral prefrontal cortex (DLPFC) significantly improves cognitive function and enhances the metabolic clearance of β-amyloid and tau proteins in AD patients. This neurotherapeutic effect is mechanistically associated with rTMS-mediated frequency-selective neuromodulation, which enhances the connectivity of oscillatory networks through improved neuronal synchronization and optimized topological organization of functional brain networks. These findings not only support the efficacy of rTMS as an adjunctive therapy for AD but also underscore the importance of employing multiple assessment methods—including clinical scales, blood biomarkers, and EEG——in understanding and monitoring the progression of AD. This research provides a significant theoretical foundation and empirical evidence for further exploration of rTMS applications in AD treatment.

Objective To study the microscopic structure and morphological characteristics of Zebrafish eyeball and retina at different developmental stages, and to lay a foundation for visual research model. Methods Select eight groups of zebrafish at different ages, with six fish in each group, 48 fish in total. Optical microscopy and transmission electron microscopy were used to observe the eyeball structure of Zebrafish at different developmental stages, and the thickness of retinal each layer was measured to analyze the temporal and spatial development pattern. The morphological characteristics of various cells in the retina and the way of nerve connection were observed from the microscopic and ultrastructural aspects, especially the structural differences between rod cells and cone cells. Results The retina of Zebrafish can be divided into ten layers including retinal pigment epithelial layer, rod cells and cone cells layer, outer limiting membrane, outer nuclear layer, outer plexiform layer, inner nuclear layer, inner plexiform layer, ganglion cell layer, nerve fiber layer, inner limiting membrane. Rod cells had a smaller nucleus and a higher electron density than cone cells. Photoreceptor terminals were neatly arranged in the outer plexiform layer, forming neural connections with horizontal cells and bipolar cells, and several synaptic ribbons are clearly visible within them. In Zebrafish retina, ganglion cell layer and inner plexiform layer are the earliest developed. With the growth and development of Zebrafish, the thickness of rod cells and cone cells layer and retinal pigment epithelial layer gradually increases, and the retinal structure was basically developed in about 10 weeks. Conclusion The retinal structure of Zebrafish is typical, with obvious stratification and highly differentiated nerve cells. There are abundant neural connections in the outer plexiform layer. The ocular development characteristics of Zebrafish are similar to those of most mammals.

Objective To analyze the combined effect of body mass index(BMI)and age with cancer occurrence among a hypertensive population in Minhang District,Shanghai.Methods Participants of this study were 212 394 hypertensive patients without cancer in Minhang District,Shanghai,registered in the electronic health information system from 2007 to 2015.Age and BMI were included as smoothing functions in the generalized additive Cox proportional risk model.The bivariate response model was constructed to visualize results using surface plots and to comprehensively analyze the association of BMI and age with the risk of cancer occurrence.Results A total of 22 141 participants developed cancer by Dec 31,2018.The association between age and the risk of cancer incidence showed an overall linear trend while the association between BMI and the risk of cancer incidence showed an overall"U"shape.BMI at about 26 kg/m2 showed the lowest risk of cancer incidence.The risk of cancer occurrence increased with increasing age in people with different BMIs.The associations between BMI and the risk of cancer incidence were different at different age groups:there was no significant association between BMI and the risk of cancer incidence in the young people(20-44 years).While in the middle-aged and older people aged over 45 years,BMI was associated with the risk of cancer incidence in a"U"shape.The lowest risk of cancer incidence was around the BMI of 26 kg/m2.Conclusion BMI among the population with hypertension should be controlled in a reasonable range,especially in the middle-aged and older population,to prevent cancer occurrence.

ObjectiveExisting artificial vision devices can be divided into two types: implanted devices and extracorporeal devices, both of which have some disadvantages. The former requires surgical implantation, which may lead to irreversible trauma, while the latter has some defects such as relatively simple instructions, limited application scenarios and relying too much on the judgment of artificial intelligence (AI) to provide enough security. Here we propose a system that has voice interaction and can convert surrounding environment information into tactile commands on head and neck. Compared with existing extracorporeal devices, our device can provide a larger capacity of information and has advantages such as lower cost, lower risk, suitable for a variety of life and work scenarios. MethodsWith the latest remote wireless communication and chip technologies, microelectronic devices, cameras and sensors worn by the user, as well as the huge database and computing power in the cloud, the backend staff can get a full insight into the scenario, environmental parameters and status of the user remotely (for example, across the city) in real time. In the meanwhile, by comparing the cloud database and in-memory database and with the help of AI-assisted recognition and manual analysis, they can quickly develop the most reasonable action plan and send instructions to the user. In addition, the backend staff can provide humanistic care and emotional sustenance through voice dialogs. ResultsThis study originally proposes the concept of “remote virtual companion” and demonstrates the related hardware and software as well as test results. The system can not only achieve basic guide functions, for example, helping a person with visual impairment to shop in supermarkets, find seats at cafes, walk on the streets, construct complex puzzles, and play cards, but also can meet the demand for fast-paced daily tasks such as cycling. ConclusionExperimental results show that this “remote virtual companion” is applicable for various scenarios and demands. It can help blind people with their travels, shopping and entertainment, or accompany the elderlies with their trips, wilderness explorations, and travels.

Tuberculosis （TB） and human immunodeficiency virus infection / acquired immune deficiency syndrome （HIV/AIDS） are both serious global public health threats. Early detection of infected persons and/or patients through TB/HIV bi-directional screening is crucial for prevention and control strategy in China and globally. In recent years， with the promotion and application of new TB and HIV detection technologies worldwide， TB/HIV bi-directional screening technologies and strategies have made remarkable changes. This expert consensus introduces the significance and challenges of TB/HIV bi-directional screening， summarizes important progress of research and applications， and makes recommendations on screening measures and procedures to further strengthen TB/HIV bi-directional screening in China.

OBJECTIVE:At present,there are many reports on the related factors associated with the incidence of cervical spine instability in patients with rheumatoid arthritis,but there are problems such as small sample size and many confounding factors,and the research results of various studies on the same related factors are also different.This article analyzed the factors related to cervical spine instability in patients with rheumatoid arthritis by means of a systematic review. METHODS:Articles related to cervical spine instability in patients with rheumatoid arthritis were collected by searching both Chinese and English databases until March 2023.The outcome of cervical spine instability in patients with rheumatoid arthritis was used as the grouping criterion to abstract basic information,baseline patient characteristics,laboratory-related tests,medication use,and other relevant risk factors.Meta-analysis was done using Stata 14.0 software. RESULTS:(1)Sixteen relevant studies,all of moderate or above quality,were included,including seven studies with case-control studies and nine with cross-sectional studies.The overall incidence of cervical spine instability in patients with rheumatoid arthritis was 43.08%.(2)Meta-analysis showed:Related risk factors included female(OR=0.60,95%CI:0.44-0.82,P=0.002);age at disease onset(SMD=-0.52,95%CI:-0.86 to-0.18,P=0.003);duration of disease(SMD=0.58,95%CI:0.14-1.02,P=0.01);body mass index(OR=0.74,95%CI:0.63-0.88,P=0.001);rheumatoid factors positive univariate analysis subgroup(OR=1.33,95%CI:1.02 to 1.72,P=0.04),C-reactive protein(SMD=0.26,95%CI:0.16-0.35,P=0.00),erythrocyte sedimentation rate(SMD=0.15,95%CI:0.002-0.29,P=0.047),anti-cyclic-citrullinated peptide antibodies(OR=1.73,95%CI:1.19-2.51,P=0.004),28-joint Disease Activity Score(SMD=0.20,95%CI:0.04-0.37,P=0.02),destruction of peripheral joints(OR=2.48,95%CI:1.60-3.85,P=0.00),and corticosteroids(OR=1.91,95%CI:1.54-2.37,P=0.00)were strongly associated with the development of rheumatoid arthritis-cervical spine instability.Female and corticosteroid use were independently associated with the occurrence of rheumatoid arthritis-cervical spine instability. CONCLUSION:Based on clinical evidence from 16 observational studies,the overall incidence of rheumatoid arthritis-cervical spine instability was 43.08%.However,the incidence of cervical spine instability in rheumatoid arthritis patients varied greatly among different studies.Gender(female)and the use of corticosteroids were confirmed as independent correlation factors for the onset of cervical spine instability in patients with rheumatoid arthritis.The results of this study still provide some guidance for early clinical recognition,diagnosis,and prevention of rheumatoid arthritis-cervical spine instability.

In the aftermath of the pandemic,the government is accelerating the development of top-tier medical resources to broaden the supply and deliver superior healthcare services.However,during this transitional phase,hospitals are experiencing operational challenges due to concurrent construction activities.Notably,a shortage of parking facilities and increased traffic con-gestion continue to impactmedial consultation experience of patients.This paper tries to explore strategies and methods for dynam-ic parking management during hospital campus expansions,offering insights for other medical institutions into grappling with pa-tient parking issues.

Objective:To develop and validate an artificial intelligence (AI) diagnostic model for coronary artery disease based on facial photos.Methods:This study was a cross-sectional study. Patients who were scheduled to undergo coronary angiography (CAG) at Beijing Anzhen Hospital and Beijing Daxing Hospital from August 2022 to November 2023 were included consecutively. Before CAG, facial photos were collected (including four angles: frontal view, left and right 60° profile, and top of the head). Photo datasets were randomly divided into a training set, a validation set (70%), and a testing set (30%). The model was constructed using Masked Autoencoder (MAE) and Vision Transformer (ViT) architectures. Firstly, the model base was pre-training using 2 million facial photos obtained from the publicly available VGGFace dataset, and fine-tuned by the training and validation sets; the model was validated in the test set. In addition, the ResNet architecture was used to process the dataset, and its outputs were compared with those of the models based on MAE and ViT. In the test set, the area under the operating characteristic curve ( AUC) of the AI model was calculated using CAG results as the gold standard. Results:A total of 5 974 participants aged 61 (54, 67) years were included, including 4 179 males (70.0%), with a total of 84 964 facial photos. There were 79 140 facial photos in the training and validation sets, with 3 822 patients with coronary artery disease; there were 5 824 facial photos in the test set, with 239 patients with coronary artery disease. The AUC value of the MAE and ViT model initialized with pre-training model weights was 0.841 and 0.824, respectively. The AUC of the ResNet model initialized with random weights was 0.810, while the AUC of the ResNet model initialized with pre-training model weights was 0.816. Conclusion:The AI model based on facial photos showes good diagnostic performance for coronary artery disease and holds promise for further application in early diagnosis.

Objective:To investigate the impact of the deep-learning-based CT fractional flow reserve (CT-FFR) on clinical decision-making and long-term prognosis in patients with obstructive coronary heart disease.Methods:In this single-center retrospective cohort study, consecutive patients with obstructive coronary heart disease (with at least one stenosis≥50%) on their first coronary computed tomography angiography (CCTA) in Beijing Anzhen Hospital from February 2017 to July 2018 were included. Baseline clinical and CT characteristics were collected. Deep-learning-based CT-FFR and Leiden CCTA risk score were calculated. All patients enrolled were followed up for at least 5 years. The study endpoint was major adverse cardiovascular events (MACE), defined as the composite of cardiac death, nonfatal myocardial infarction, unstable angina requiring hospitalization, and unplanned revascularization. Receiver operating characteristic (ROC) curves were drawn to define the optimal cut-off point of the Leiden score in predicting the 5-year MACE, and survival analysis and Cox regression were performed to explore the related factors of MACE.Results:A total of 622 patients, aged 61 (54, 66) years, with 407 (65.4%) males were included. Diagnostic coronary angiography was performed in 78 patients after their baseline CCTA, with 34 (43.6%) patients had CT-FFR>0.80. During a follow-up time of 2 181 (2 093, 2 355) days, 155 patients (24.9%) suffered from MACE. ROC derived optimal cut-off point of Leiden score for predicting MACE was 15.48. Survival analysis found that male patients, Leiden risk score>15 and CT-FFR≤0.80 had worse prognosis. Multivariate Cox regression analysis identified CT-FFR≤0.80 as an robust and independent predictor of MACE ( HR=4.98, 95% CI 3.15-7.86, P<0.001). Conclusion:Deep-learning-based CT-FFR aids in clinical decision-making and the evaluation of long-term prognosis in patients with obstructive coronary heart disease.

Objective This study aimed to investigate the potential relationship between urinary metals copper (Cu), arsenic (As), strontium (Sr), barium (Ba), iron (Fe), lead (Pb) and manganese (Mn) and grip strength. Methods We used linear regression models, quantile g-computation and Bayesian kernel machine regression (BKMR) to assess the relationship between metals and grip strength.Results In the multimetal linear regression, Cu (β=-2.119), As (β=-1.318), Sr (β=-2.480), Ba (β=0.781), Fe (β= 1.130) and Mn (β=-0.404) were significantly correlated with grip strength (P < 0.05). The results of the quantile g-computation showed that the risk of occurrence of grip strength reduction was -1.007 (95％ confidence interval:-1.362, -0.652; P < 0.001) when each quartile of the mixture of the seven metals was increased. Bayesian kernel function regression model analysis showed that mixtures of the seven metals had a negative overall effect on grip strength, with Cu, As and Sr being negatively associated with grip strength levels. In the total population, potential interactions were observed between As and Mn and between Cu and Mn (Pinteractions of 0.003 and 0.018, respectively).Conclusion In summary, this study suggests that combined exposure to metal mixtures is negatively associated with grip strength. Cu, Sr and As were negatively correlated with grip strength levels, and there were potential interactions between As and Mn and between Cu and Mn.