ObjectiveTo observe the activation patterns and functional connectivity in the prefrontal cortex of patients with post-stroke anxiety (PSA) using functional near-infrared spectroscopy, in order to explore the underlying neural mechanism. MethodsFrom December, 2024 to September, 2025, 120 stroke patients were selected in Changzhou De'an Hospital. They were divided into PSA group (n = 60) and non-PSA group (n = 60) according to the score of Hamilton Anxiety Scale (HAMA). All patients wore an 18-channel fNIRS acquisition cap for detection. The differences in resting-state functional connectivity between the frontopolar cortex (FPC) and dorsolateral prefrontal cortex (DLPFC) were examined in both groups, as well as task-related activation in these brain regions. ResultsResting-state functional connectivity analysis revealed no statistically significant difference in network connectivity between two groups in the FPC and DLPFC regions (|t| < 1.301, P > 0.05). Task-related activation results revealed significantly reduced activation in the contralateral FPC of PSA group compared to the non-PSA group (Z = -2.063, P < 0.05). Activation levels in this region showed a negative correlation with the scores of HAMA (ρ = -0.201, P = 0.028). ConclusionActivation decreased in the contralateral frontal pole during the task state for patients with PSA, and the activation levels negatively correlates with anxiety severities.

ObjectiveTo observe the activation patterns and functional connectivity in the prefrontal cortex of patients with post-stroke anxiety (PSA) using functional near-infrared spectroscopy, in order to explore the underlying neural mechanism. MethodsFrom December, 2024 to September, 2025, 120 stroke patients were selected in Changzhou De'an Hospital. They were divided into PSA group (n = 60) and non-PSA group (n = 60) according to the score of Hamilton Anxiety Scale (HAMA). All patients wore an 18-channel fNIRS acquisition cap for detection. The differences in resting-state functional connectivity between the frontopolar cortex (FPC) and dorsolateral prefrontal cortex (DLPFC) were examined in both groups, as well as task-related activation in these brain regions. ResultsResting-state functional connectivity analysis revealed no statistically significant difference in network connectivity between two groups in the FPC and DLPFC regions (|t| < 1.301, P > 0.05). Task-related activation results revealed significantly reduced activation in the contralateral FPC of PSA group compared to the non-PSA group (Z = -2.063, P < 0.05). Activation levels in this region showed a negative correlation with the scores of HAMA (ρ = -0.201, P = 0.028). ConclusionActivation decreased in the contralateral frontal pole during the task state for patients with PSA, and the activation levels negatively correlates with anxiety severities.

ObjectiveTo observe the activation patterns and functional connectivity in the prefrontal cortex of patients with post-stroke anxiety (PSA) using functional near-infrared spectroscopy, in order to explore the underlying neural mechanism. MethodsFrom December, 2024 to September, 2025, 120 stroke patients were selected in Changzhou De'an Hospital. They were divided into PSA group (n = 60) and non-PSA group (n = 60) according to the score of Hamilton Anxiety Scale (HAMA). All patients wore an 18-channel fNIRS acquisition cap for detection. The differences in resting-state functional connectivity between the frontopolar cortex (FPC) and dorsolateral prefrontal cortex (DLPFC) were examined in both groups, as well as task-related activation in these brain regions. ResultsResting-state functional connectivity analysis revealed no statistically significant difference in network connectivity between two groups in the FPC and DLPFC regions (|t| < 1.301, P > 0.05). Task-related activation results revealed significantly reduced activation in the contralateral FPC of PSA group compared to the non-PSA group (Z = -2.063, P < 0.05). Activation levels in this region showed a negative correlation with the scores of HAMA (ρ = -0.201, P = 0.028). ConclusionActivation decreased in the contralateral frontal pole during the task state for patients with PSA, and the activation levels negatively correlates with anxiety severities.

The molecular mechanism of verbascoside(OC1) in promoting acetylcholine(ACh) release in the pathogenesis of Alzheimer's disease(AD) was studied. Adrenal pheochromocytoma cells(PC12) of rats induced by β-amyloid protein(1-42)(Aβ_(1-42)) were used as AD models in vitro and were divided into control group, model group(Aβ_(1-42) 10 μmol·L~(-1)), OC1 treatment group(2 and 10 μg·mL~(-1)). The effect of OC1 on phosphorylated proteins in AD models was analyzed by whole protein phosphorylation quantitative omics, and the selectivity of OC1 for calcium channel subtypes was virtually screened in combination with computer-aided drug design. The fluorescence probe Fluo-3/AM was used to detect Ca~(2+) concentration in cells. Western blot analysis was performed to detect the effects of OC1 on the expression of phosphorylated calmodulin-dependent protein kinase Ⅱ(p-CaMKⅡ, Thr286) and synaptic vesicle-related proteins, and UPLC/Q Exactive MS was used to detect the effects of OC1 on ACh release in AD models. The effects of OC1 on acetylcholine esterase(AChE) activity in AD models were detected. The results showed that the differentially modified proteins in the model group and the OC1 treatment group were related to calcium channel activation at three levels: GO classification, KEGG pathway, and protein domain. The results of molecular docking revealed the dominant role of L-type calcium channels. Fluo-3/AM fluorescence intensity decreased under the presence of Ca~(2+) chelating agent ethylene glycol tetraacetic acid(EGTA), L-type calcium channel blocker verapamil, and N-type calcium channel blocker conotoxin, and the effect of verapamil was stronger than that of conotoxin. This confirmed that OC1 promoted extracellular Ca~(2+) influx mainly through its interaction with L-type calcium channel protein. In addition, proteomic analysis and Western blot results showed that the expression of p-CaMKⅡ and downstream vesicle-related proteins was up-regulated after OC1 treatment, indicating that OC1 acted on vesicle-related proteins by activating CaMKⅡ and participated in synaptic remodeling and transmitter release, thus affecting learning and memory. OC1 also decreased the activity of AChE and prolonged the action time of ACh in synaptic gaps.
Animals ; Rats ; Glucosides/administration & dosage* ; Acetylcholine/metabolism* ; Alzheimer Disease/genetics* ; PC12 Cells ; Phenols/chemistry* ; Neurotransmitter Agents/metabolism* ; Drugs, Chinese Herbal ; Calcium-Calmodulin-Dependent Protein Kinase Type 2/genetics* ; Humans ; Phosphorylation/drug effects* ; Calcium/metabolism* ; Polyphenols

Objective To construct a "disease-syndrome combination" mathematical representation model for pulmonary nodules based on oral microbiome data, utilizing a multimodal data algorithm framework centered on dynamic systems theory. Furthermore, to compare predictive models under various algorithmic frameworks and validate the efficacy of the optimal model in predicting the presence of pulmonary nodules. Methods A total of 213 subjects were prospectively enrolled from July 2022 to March 2023 at the Hospital of Chengdu University of Traditional Chinese Medicine, Sichuan Cancer Hospital, and the Chengdu Integrated Traditional Chinese and Western Medicine Hospital. This cohort included 173 patients with pulmonary nodules and 40 healthy subjects. A novel multimodal data algorithm framework centered on dynamic systems theory, termed VAEGANTF (Variational Auto Encoder-Generative Adversarial Network-Transformer), was proposed. Subsequently, based on a multi-dimensional integrated dataset of “clinical features-syndrome elements-microorganisms”, all subjects were divided into training (70%) and testing (30%) sets for model construction and efficacy testing, respectively. Using pulmonary nodules as dependent variables, and combining candidate markers such as clinical features, lesion location, disease nature, and microbial genera, the independent variables were screened based on variable importance ranking after identifying and addressing multicollinearity. Missing values were then imputed, and data were standardized. Eight machine learning algorithms were then employed to construct pulmonary nodule risk prediction models: random forest, least absolute shrinkage and selection operator (LASSO) regression, support vector machine, multilayer perceptron, eXtreme Gradient Boosting (XGBoost), VAE-ViT (Vision Transformer), GAN-ViT, and VAEGANTF. K-fold cross-validation was used for model parameter tuning and optimization. The efficacy of the eight predictive models was evaluated using confusion matrices and receiver operating characteristic (ROC) curves, and the optimal model was selected. Finally, goodness-of-fit testing and decision curve analysis (DCA) were performed to evaluate the optimal model. Results There were no statistically significant differences between the two groups in demographic characteristics such as age and sex. The 213 subjects were randomly divided into training and testing sets (7 : 3), and prediction models were constructed using the eight machine learning algorithms. After excluding potential problems such as multicollinearity, a total of 301 clinical feature information, syndrome elements, and microbial genera markers were included for model construction. The area under the curve (AUC) values of the random forest, LASSO regression, support vector machine, multilayer perceptron, and VAE-ViT models did not reach 0.85, indicating poor efficacy. The AUC values of the XGBoost, GAN-ViT, and VAEGANTF models all reached above 0.85, with the VAEGANTF model exhibiting the highest AUC value (AUC=0.923). Goodness-of-fit testing indicated good calibration ability of the VAEGANTF model, and decision curve analysis showed a high degree of clinical benefit. The nomogram results showed that age, sex, heart, lung, Qixu, blood stasis, dampness, Porphyromonas genus, Granulicatella genus, Neisseria genus, Haemophilus genus, and Actinobacillus genus could be used as predictors. Conclusion The “disease-syndrome combination” risk prediction model for pulmonary nodules based on the VAEGANTF algorithm framework, which incorporates multi-dimensional data features of “clinical features-syndrome elements-microorganisms”, demonstrates better performance compared to other machine learning algorithms and has certain reference value for early non-invasive diagnosis of pulmonary nodules.

Objective To analyze the publication condition and development trends of global post-stroke fatigue(PSF)research from 2004 to 2024.Methods Relevant literature on PSF pub-lished between January 1,2004,and August 1,2024,were systematically searched and screened from WoSCC database.Visual analysis of publication volume,contributing countries,institutions,authors,and keywords in PSF research was conducted using CiteSpace software.Results A total of 373 articles were included in this study.The overall publication volume related to PSF exhibited an upward trend.The country,institution,and author with the highest number of publications were the United Kingdom,the University of Oslo,and LERDAL A,respectively.High-frequency keywords in-cluded quality of life,depression,fatigue severity scale,follow up,epidemiology,symptoms,associ-ations,and rehabilitation,while the emerging keywords were health care professionals,risk factors,and participation.Conclusion PSF-related research has demonstrated an overall upward trend.As-sessment and measurement protocols,rehabilitation treatment approaches,impacts on quality of life,and the intrinsic relationship with depression have emerged as research hotspots.Further exploration of precise and systematic assessment methods,along with the construction of scientific rehabilitation management programs and risk prediction models,will become the focal points of future research.

OBJECTIVE To explore the effect of failure mode and effect analysis(FMEA)on management of hospi-tal-associated infections(HAIs)in hemodialysis center.METHODS In Nov.2023,the risk priority number(RPN)integrated with action priority(AP)was adopted to identify,analyze and evaluate the risk factors in man-agement of HAIs in hemodialysis center of Tongji Hospital Affiliated to Tongji Medical College,Huazhong Uni-versity of Science and Technology by FMEA method.The high risk points that needed to be taken interventions were screened out,and the targeted measures were formulated to control the risks.At the end of the intervention period,a second round of risk assessment was carried out for improvement status of the high-risk points in Nov.2024,and the effect on the management of HAIs was evaluated.RESULTS The risk assessment was carried out for 48 risk points covering eight aspects,including organizational structure,self-inspection and supervision,staff management,environmental layout,cleaning and disinfection,surveillance,operation procedures and i-tem management.There were 9 risk points with the RPN values greater than 125,3 of which were with the AP value of"H".There were 8 risk points with the RPN value less than 125 and 6 risk points with the AP value drop-ping down to L after the targeted intervention measures were taken,indicating that the risk management has a-chieved favorable effect.CONCLUSIONS The RPN and AP integrated with FMEA can accurately identify the high-risk points in the quality management of the hemodialysis center.It is necessary to take targeted interven-tion measures so as to boost the effect on prevention and control of HAIs in the hemodialysis center and reduce the risk of HAIs in the hemodialysis patients.

Objective To explore the diagnostic value of dual-low-dose CT energy spectral imaging combined with adaptive statis-tical iterative reconstruction-Veo(ASIR-V)in distinguishing benign and malignant thyroid nodules.Methods A total of 242 patients with thyroid nodules were included.In part Ⅰ,the initial 90 patients were randomly and equally assigned to the conventional scan group,the low radiation dose group,and the dual-low-dose group.Both subjective and objective image qualities,the radiation dose,and contrast agent dosage in these three groups were evaluated,respectively.In part Ⅱ,the remaining 152 patients underwent dual-low-dose CT energy spectral scanning.Radiographic features of thyroid nodules in benign and malinant groups were observed,fol-lowed by spectral imaging analysis.The iodine concentration(IC)value,normalized iodine concentration(NIC)value,effective atomic number(Eff-Z),and λHU value of benign and malignant nodules were measured and compared,respectively.Results There were significant differences in nodule morphology,sign of edge truncation,enhancement characteristics and nodule boundary enhancement between benign and malignant thyroid nodules(P<0.05).There were statistically significant differences in IC value,NIC value,and λHU value in the venous phase among the three groups(P<0.05).The sensitivity and specificity of IC,NIC,λHU were 81.6%and 60.0%,86.4%and 67.5%,88.8%and 65.0%,respectively.The area under the curve(AUC)of combining the three energy spectral parameters with radiographic fea-tures via binary logistic regression model was 0.905,and the sensitivity and specificity were 82.4%and 87.5%,respectively.The effective dose(ED)in the dual-low-dose group was reduced by 60.13%com-pared to the conventional scan group,and the contrast agent dos-age was reduced by 38.56%.Conclusion The dual-low-dose CT energy spectral imaging combined with ASIR-V significantly reduced the radiation dose and the contrast agent dosage,and might help in distinguishing between benign and malignant thyroid nodules,demonstrating considerable clinical application value.

Objective:To observe any effect of combining visual deprivation training (VDT) with repeated low-frequency transcranial magnetic stimulation (rTMS) in the treatment of lower limb motor dysfunction among stroke survivors.Methods:Fifty stroke survivors were randomly assigned to either a control group or an experimental group ( n=25 each). In addition to routine rehabilitation treatment, the control group received rTMS targeting the primary motor cortex (M1, lower limb representation area) of the unaffected hemisphere, while the experimental group also received VDT. Before and after 4 weeks of the treatments, everyone′s lower limb motor function, balance, gait and ability in the activities of daily living were evaluated using the Fugl-Meyer lower extremity assessment (FMA-LE), the root mean square (RMS) values generated through surface electromyography of the affected tibialis anterior muscle, the Berg Balance Scale (BBS), the Timed Up and Go Test (TUGT), the Tinetti Gait Assessment (TGA), and the modified Barthel Index (MBI). Results:After the treatment, both groups showed significant improvements in their average FMA-LE, BBS, TUGT, TGA and MBI results, as well as in the RMS values of the affected tibialis anterior muscle. The experimental group showed significantly greater improvement compared to the control group.Conclusions:The combination of VDT and low-frequency rTMS can effectively improve the lower limb motor function, balance and gait of stroke survivors. It is more effective than rTMS alone. The combined therapy is worthy of clinical application and promotion.

The aging trend is intensifying currently,but there is still a lack of standardized diagnosis and treat-ment schemes for severe infections in elderly people.This paper focuses on the recommendations for immune-related clinical diagnosis and treatment routes as well as the idea of risk stratified diagnosis and treatment for elderly peo-ple,aiming to effectively prevent infectious diseases in elderly people and perform stratified management through systematic and scientific means of immune function monitoring and regulation,so as to enhance the standardized level of diagnosis and treatment as well as clinical treatment effect of infection in elderly people.