Objective To study the correlation of cognitive dysfunction with autonomic nerve function damage in patients with cerebral small vessel disease (CSVD). Methods A total of 310 patients with CSVD admitted from June 2022 to June 2025 were included. Montreal Cognitive Assessment Scale (MoCA) was applied for cognitive function assessment, and Scale for Outcomes in PD for Autonomic Symptoms (SCOPA-AUT) was used to evaluate autonomic nerve function damage. The incidence rate of autonomic nerve function damage, total score and dimensions scores of SCOPA-AUT were counted. According to the presence or absence of autonomic nerve function damage, the enrolled patients were categorized into damage group and non-damage group. The total score of MoCA and scores of dimensions were compared between both groups. Pearson correlation analysis model was utilized to analyze the correlation between total score of MoCA and scores of dimensions of SCOPA-AUT in patients with CSVD. Results Among the 310 patients, 63.87% cases (198 / 310) had autonomic nerve function damage. The SCOPA-AUT total score and scores of dimensions of gastrointestinal function, urinary system function, cardiovascular function, body temperature regulation, pupil movement and sexual function were (34.16 ± 10.41) points, (10.25 ± 3.31) points, (9.44 ± 2.89) points, (4.02 ± 1.66) points, (6.41 ± 2.35) points, (1.35 ± 0.49) points and (2.69 ± 0.81) points. The total score of MoCA and scores of language function, naming, delayed recall and attention in the damage group were lower than those in the non-damage group (P < 0.05). Pearson correlation analysis results revealed that the total score, urinary system score, cardiovascular function score and body temperature regulation score of SCOPA-AUT were negatively correlated with the total score of MoCA (r = -0.545, -0.598, -0.607, -0.615, P < 0.05), and the gastrointestinal function score, pupil movement score and sexual function score were not significantly associated with total score of MoCA (P > 0.05). Conclusion The risk of autonomic nerve function damage is high in patients with CSVD, and it involves multiple systems and is closely related to the cognitive function of patients.

Objective To develop and validate a risk prediction model for social dysfunction in middle-aged and elderly patients with ischemic stroke.Methods A non-matched case-control study was conducted among ischemic stroke patients admitted to the neurology department of a tertiary hospital in Tangshan between August 2022 and March 2023.Patients who developed social dysfunction within 3 months after discharge were assigned to a case group,while those without it were assigned to a control group.Multivariate logistic regression was used to identify significant predictors and construct a nomogram-based prediction model.The model's discrimination and calibration were assessed using the area under the receiver operating characteristic curve(AUC)and the Hosmer-Lemeshow test.Internal validation was performed via bootstrap resampling,and clinical utility was evaluated using decision curve analysis.Results Logistic regression identified the following as significant risk factors for social dysfunction(P＜0.05):male gender,age≥60 years,primary education or below,rural residence,income＜3 000,cognitive impairment,low disability acceptance,poor self-management ability,suboptimal utilization of chronic disease resources,low future-oriented coping,and high cumulative ecological risk.The nomogram achieved an AUC of 0.874,with a sensitivity of 79.4％and specificity of 80.7％.The Hosmer-Lemeshow test indicated good calibration(x2=3.631,P=0.88).Conclusion The developed nomogram provides an effective tool for predicting the risk of social dysfunction in middle-aged and elderly ischemic stroke patients,facilitating early identification of high-risk individuals.

Objective To investigate the value of multimodal model integrating digital mammography(MG)and MRI radiomics features for preoperative prediction of lymphovascular invasion(LVI)status in breast cancer.Methods The clinical and imaging data from 336 patients with pathologically confirmed invasive breast cancer were retrospectively analyzed and randomly divided into a training group(235 cases)and a test group(101 cases)according to the ratio of 7∶3.Feature dimensionality reduction was carried out by Pearson correlation analysis followed by least absolute shrinkage and selection operator(LASSO)regression.Radiomics models were constructed based on MG craniocaudal(CC),dynamic contrast enhancement(DCE),T2 WI,and integrated MRI sequences;a multimodal model was further developed by incorporating clinical high-risk factors.The predictive efficiency of each model was evaluated by plotting receiver operating characteristic(ROC)curve.Results The ROC curve analysis showed that the multimodal model performed the best predictive efficiency,with area under the curve(AUC)of 0.989 and 0.861,accuracy of 0.949 and 0.782,sensitivity of 0.923 and 0.828,and specificity of 0.962 and 0.764 in the training group and test group respectively.Conclusion The multimodal model,integrating MG and MRI radiomics features,show optimal performance and can be served as a preoperative prediction of LVI status in breast cancer.

Objective To develop and validate a risk prediction model for social dysfunction in middle-aged and elderly patients with ischemic stroke.Methods A non-matched case-control study was conducted among ischemic stroke patients admitted to the neurology department of a tertiary hospital in Tangshan between August 2022 and March 2023.Patients who developed social dysfunction within 3 months after discharge were assigned to a case group,while those without it were assigned to a control group.Multivariate logistic regression was used to identify significant predictors and construct a nomogram-based prediction model.The model's discrimination and calibration were assessed using the area under the receiver operating characteristic curve(AUC)and the Hosmer-Lemeshow test.Internal validation was performed via bootstrap resampling,and clinical utility was evaluated using decision curve analysis.Results Logistic regression identified the following as significant risk factors for social dysfunction(P＜0.05):male gender,age≥60 years,primary education or below,rural residence,income＜3 000,cognitive impairment,low disability acceptance,poor self-management ability,suboptimal utilization of chronic disease resources,low future-oriented coping,and high cumulative ecological risk.The nomogram achieved an AUC of 0.874,with a sensitivity of 79.4％and specificity of 80.7％.The Hosmer-Lemeshow test indicated good calibration(x2=3.631,P=0.88).Conclusion The developed nomogram provides an effective tool for predicting the risk of social dysfunction in middle-aged and elderly ischemic stroke patients,facilitating early identification of high-risk individuals.

Objective To investigate the value of multimodal model integrating digital mammography(MG)and MRI radiomics features for preoperative prediction of lymphovascular invasion(LVI)status in breast cancer.Methods The clinical and imaging data from 336 patients with pathologically confirmed invasive breast cancer were retrospectively analyzed and randomly divided into a training group(235 cases)and a test group(101 cases)according to the ratio of 7∶3.Feature dimensionality reduction was carried out by Pearson correlation analysis followed by least absolute shrinkage and selection operator(LASSO)regression.Radiomics models were constructed based on MG craniocaudal(CC),dynamic contrast enhancement(DCE),T2 WI,and integrated MRI sequences;a multimodal model was further developed by incorporating clinical high-risk factors.The predictive efficiency of each model was evaluated by plotting receiver operating characteristic(ROC)curve.Results The ROC curve analysis showed that the multimodal model performed the best predictive efficiency,with area under the curve(AUC)of 0.989 and 0.861,accuracy of 0.949 and 0.782,sensitivity of 0.923 and 0.828,and specificity of 0.962 and 0.764 in the training group and test group respectively.Conclusion The multimodal model,integrating MG and MRI radiomics features,show optimal performance and can be served as a preoperative prediction of LVI status in breast cancer.

Objective:To investigate the myocardial protective effect of extracorporeal cardiac shock wave therapy (CSWT) combined with sulfur hexafluoride microbubble post-conditioning on myocardial ischemia-reperfusion injury (MI/RI) in rats, and to provide theoretical support for clinical treatment of MI/RI.Methods:A total of 32 male SD rats were randomly divided into 4 groups: sham operation group (Sham group), MI/RI group (IR group), CSWT group (IR+ SW group), and CSWT combined with sulfur hexafluoride microbubble treatment group (IR+ SW+ MB group), with 8 rats in each group. Therapeutic intervention was performed in IR+ SW group and IR+ SW+ MB group on the 1st, 3rd and 5th day after modeling. The left ventricular end-diastolic diameter (LVEDD), left ventricular end-systolic diameter (LVESD), left ventricular ejection fraction (LVEF) and left ventricular fractional shortening (LVFS) of the rats were measured by echocardiography before and after treatment. On the 7th day, myocardial fibrosis was assessed by Masson staining, and cardiomyocyte apoptosis was observed by TUNEL staining. The myocardial apoptotic proteins Bcl-2, BAX, Cleaved-Caspase-3 and Cleaved-Caspase-9 in the infarct boundary area were detected by Western blot. The differences of the above indexes among different groups were compared.Results:①There was no significant change in heart rhythm and heart rate among the groups before and after treatment, and there was no significant difference in heart rate ( P>0.05). ②The echocardiographic results after treatment showed that, compared with IR group, LVEDD and LVESD in IR+ SW group and IR+ SW+ MB group decreased in turn, while LVEF and LVFS increased in turn with significant differences between each two groups (all P<0.05). ③Compared with IR group, the degrees of myocardial fibrosis and apoptosis in IR+ SW group and IR+ SW+ MB group were alleviated in turn, and the relief in IR+ SW+ MB group was the most obvious. Quantitative analysis showed that compared with IR group, the proportions of cardiomyocyte apoptosis in IR+ SW group and IR+ SW+ MB group decreased in turn, and there were significant differences between each two groups (all P<0.05). ④The results of Western blot detection showed that compared with IR group, the levels of Bcl-2 in IR+ SW group and IR+ SW+ MB group increased in turn, while the levels of BAX and the activation level of Caspase-3 and Caspase-9 protein decreased in turn. These differences were all statistically significant between each two groups (all P<0.05) except for the activation level of Caspase-3 protein between IR+ SW group and IR+ SW+ MB group ( P>0.05). Conclusions:CSWT combined with sulfur hexafluoride microbubble therapy can improve left ventricular remodeling and left ventricular systolic function by inhibiting cardiomyocyte apoptosis.

Objective To investigate the related factors of early neurological deterioration in elderly patients with thrombolysis for acute occlusive stroke of large intracranial vessels. Methods Clinical materials of 480 elderly patients with thrombolysis for acute occlusive stroke of large intracranial vessels were retrospectively analyzed. The National Institutes of Health Stroke Scale (NIHSS) was used to evaluate the neurological function of patients within 72 hours after thrombectomy, and the patients were divided into deterioration group and non-deterioration group. The baseline materials were compared between the two groups, the factors of early neurological deterioration were analyzed, and the receiver operating characteristic (ROC) curve was drawn to analyze the predictive value of risk. Results Among 480 elderly patients with thrombolysis for acute occlusive stroke of large intracranial vessels, 92 cases (19.17%) had early neurological deterioration; the blood glucose level, white blood cell count, incidence of dysphagia, and incidence of coma in the deterioration group were significantly higher than those in the non-deterioration group (P < 0.05); the Logistic regression analysis showed that high level of blood glucose (95%CI, 1.203 to 1.478), high level of white blood cell count (95%CI, 1.159 to 1.408), dysphagia (95%CI, 7.049 to 31.475), and coma (95%CI, 8.375 to 43.195) were risk factors for early neurological deterioration in elderly patients with thrombolysis for acute occlusive stroke of large intracranial vessels (OR>1, P < 0.05). ROC curve results showed that blood glucose, white blood cell count, dysphagia, and coma had certain predictive value for early neurological deterioration in elderly patients with thrombolysis for acute occlusive stroke of large intracranial vessels[the area under the curve (AUC) was 0.733, 0.708, 0.707 and 0.701]; the ROC curve showed AUC was 0.934, indicating that the model was reliable and stable. Conclusion Early neurological deterioration in elderly patients with thrombolysis for acute occlusive stroke of large intracranial vessels may be related to factors such as blood glucose, white blood cell count, dysphagia, and coma. Early risk assessment and relevant intervention measures can be taken clinically to improve prognosis.

Understanding the connection between brain and behavior in animals requires precise monitoring of their behaviors in three-dimensional (3-D) space. However, there is no available three-dimensional behavior capture system that focuses on rodents. Here, we present MouseVenue3D, an automated and low-cost system for the efficient capture of 3-D skeleton trajectories in markerless rodents. We improved the most time-consuming step in 3-D behavior capturing by developing an automatic calibration module. Then, we validated this process in behavior recognition tasks, and showed that 3-D behavioral data achieved higher accuracy than 2-D data. Subsequently, MouseVenue3D was combined with fast high-resolution miniature two-photon microscopy for synchronous neural recording and behavioral tracking in the freely-moving mouse. Finally, we successfully decoded spontaneous neuronal activity from the 3-D behavior of mice. Our findings reveal that subtle, spontaneous behavior modules are strongly correlated with spontaneous neuronal activity patterns.
Animals ; Behavior, Animal ; Brain/diagnostic imaging* ; Imaging, Three-Dimensional/methods* ; Mice ; Neuroimaging ; Rodentia

Measuring eye movement is a fundamental approach in cognitive science as it provides a variety of insightful parameters that reflect brain states such as visual attention and emotions. Combining eye-tracking with multimodal neural recordings or manipulation techniques is beneficial for understanding the neural substrates of cognitive function. Many commercially-available and custom-built systems have been widely applied to awake, head-fixed small animals. However, the existing eye-tracking systems used in freely-moving animals are still limited in terms of their compatibility with other devices and of the algorithm used to detect eye movements. Here, we report a novel system that integrates a general-purpose, easily compatible eye-tracking hardware with a robust eye feature-detection algorithm. With ultra-light hardware and a detachable design, the system allows for more implants to be added to the animal's exposed head and has a precise synchronization module to coordinate with other neural implants. Moreover, we systematically compared the performance of existing commonly-used pupil-detection approaches, and demonstrated that the proposed adaptive pupil feature-detection algorithm allows the analysis of more complex and dynamic eye-tracking data in free-moving animals. Synchronized eye-tracking and electroencephalogram recordings, as well as algorithm validation under five noise conditions, suggested that our system is flexibly adaptable and can be combined with a wide range of neural manipulation and recording technologies.

Objective:To understand the sleep quality and mental health status of nurses in public health emergencies, and analyze the correlation between them.Methods:A total of 128 first-line nursing staff participating in public health emergencies on February 22-23, 2020 in Tianjin Beichen Hospital, Tianjin First Central Hospital, Tianjin Fourth Central Hospital were investigated by the general data questionnaire, Pittsburgh Sleep Quality Index (PSQI), and Symptom Checklist 90 (SCL-90).Results:70.3%(90/128) of nursing staff had poor sleep quality, and the total score of PSQI was (9.71±4.01) points, which was statistically significant compared with the domestic norm ( t value was 16.479, P<0.01). The total score of SCL-90 was 1.59±0.52, which was statistically significant compared with the domestic norm ratio ( t value was 4.505, P<0.01). One-way ANOVA showed that the nursing staff's age had a significant impact on sleep quality, and the difference was statistically significant ( F value was 4.092, P<0.05). Pearson correlation analysis showed that the Pittsburgh sleep quality scale index scores and symptom self-assessment scale and somatization, force, sensitive interpersonal relationship, depression, anxiety, hostile, terrorist, paranoia, and psychosis were positively correlated( r values were 0.292-0.444, P< 0.01). Conclusions:The sleep quality and mental health status of nurses in public health emergencies are poor, and the sleep quality is correlated with mental health status.