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Background: Poststroke cognitive impairment (PSCI) is highly prevalent in stroke survivors and correlated with unfavorable clinical outcomes. This study aimed to identify the neural substrate of PSCI using atlas-based disconnectome analysis and assess the value of disconnection score, a baseline measure for stroke-induced structural disconnection, in PSCI prediction. Methods: A multicenter prospective cohort of 676 first-ever patients with acute ischemic stroke was enrolled from 3 independent hospitals in China. Sociodemographic, clinical, and neuroimaging data were collected at acute stage of stroke. Cognitive assessment was performed at 3 months after stroke. Voxel-wise and tract-wise disconnectome analysis were performed to uncover the strategic structural disconnection pattern for global PSCI. Disconnection score was calculated for each participant in leave-one-dataset-out cross-validation. Multivariable logistic regression was performed for the association between disconnection score and PSCI. Prediction models with and without disconnection score were developed, cross-validated, and compared in terms of discrimination and goodness-of-fit. Results: Compared with lesions of non-PSCI, those of PSCI were more likely to have fiber connections with left prefrontal cortex and left deep structures (thalamus and basal ganglia). Disconnection score could predict the risk and severity of PSCI during cross-validation, and was independently associated with PSCI after controlling for all baseline covariates (odds ratio, 1.38 [95% CI, 1.17–1.64]; P Conclusions: A strategic structural disconnection pattern centered on left prefrontal cortex, thalamus, and basal ganglia is identified for global PSCI using indirect disconnectome analysis. The baseline disconnection score is independently predictive of PSCI and has significant incremental value to preexisting sociodemographic, clinical, and neuroimaging predictors. Registration: URL: http://www.chictr.org.cn/enIndex.aspx ; Unique identifier: ChiCTR-ROC-17013993.

BACKGROUND Healthcare is considered one of the most stressful occupations because multiple stressors exist in the workplace. Mobile stress management intervention is currently widely used in mental health intervention as an affordable and accessible approach. However, one of the major challenges in applying mobile intervention is the low interaction and engagement of participants, which hinders the optimal effects of mobile intervention, especially in self-guided mobile interventions where employees receive no human support during the intervention. OBJECTIVE The present study aims to compare the effects of CIMI, a complex interactive multimodal intervention, on physiological and psychological stress measures in comparison to the self-guided mobile intervention. METHODS We conducted a non-randomized, controlled study in two Chinese general hospitals. This study enrolled 245 healthcare workers who met the inclusion criteria for at least one of the three dimensions of the Depression, Anxiety, and Stress scale. All eligible participants were required to complete a questionnaire and wear a 24-hour Holter device to assess the physiological indicators of stress as indexed by heart rate variability at both baseline and post-intervention. During the program, participants in the CIMI group received a 12-week online intervention with the following four components: mobile stress management education, a web-based WeChat social network, tailored feedback, and a nurse coach, while the control group only received a self-guided intervention. RESULTS After a 12-week intervention, the perceived stress, depression, anxiety, fatigue, sleepiness symptoms, and subjective happiness in the CIMI group improved more significantly than those in the self-guided group. Additionally, we found a reduction in HRV parameters in the control group rather than the CIMI group. CONCLUSIONS CIMI was an effective intervention for improving both psychological and physiological indicators of stress among distressed HCWs. The findings provide objective evidence for developing an effective and economically viable mobile stress management intervention with a minimum of human support, but further research is needed. CLINICALTRIAL ClinicalTrial.gov., NCT05239065; https://clinicaltrials.gov/ct2/show/NCT05239065.

Guo Li,1 Ping Jing,2 Guohua Chen,3 Junhua Mei,3 Jinfeng Miao,1 Wenzhe Sun,1 Yan Lan,1 Xin Zhao,1 Xiuli Qiu,1 Zhou Zhu,1,* Suiqiang Zhu1,* 1Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, People’s Republic of China; 2Department of Neurology, Wuhan Central Hospital, Wuhan, Hubei, 430014, People’s Republic of China; 3Department of Neurology, Wuhan First Hospital, Wuhan, Hubei, 430022, People’s Republic of China*These authors contributed equally to this workCorrespondence: Zhou Zhu Tel +86-18171081029Email zhouzhu@hust.edu.cnSuiqiang Zhu Tel +86-13035101141Email zhusuiqiang@163.comPurpose: The early detection of major post-stroke depression (PSD) is essential to optimize patient care. A major PSD prediction tool needs to be developed and validated for early screening of major PSD patients.Patients and Methods: A total of 639 acute ischemic stroke (AIS) patients from three hospitals were consecutively recruited and completed a 3-month follow-up. Sociodemographic, clinical and laboratory test data were collected on admission. With major depression criteria being met in the DSM-V, 17-item Hamilton Rating Scale For Depression (HRSD) score ≥ 17 at 3 months after stroke onset was regarded as the primary endpoint. Multiple imputation was used to substitute the missing values and multivariable logistic regression model was fitted to determine associated factors with a bootstrap backward selection process. The nomogram was constructed based on the regression coefficients of the associated factors. Performance of the nomogram was assessed by discrimination (C-statistics) and calibration curve.Results: A total of 7.04% (45/639) of patients were diagnosed with major PSD at 3 months. The final logistic regression model included age, baseline NIHSS and mRS scores, educational level, calcium–phosphorus product, history of hypertension and atrial fibrillation. The model had acceptable discrimination, based on a C-statistic of 0.81 (95% CI, 0.791– 0.829), with 71.1% sensitivity and 78.6% specificity. We also transformed the model to a nomogram, an easy-to-use clinical tool which could be used to facilitate the early screening of major PSD patients at 3 months.Conclusion: We identified several associated factors of major PSD at 3 months and constructed a convenient nomogram to guide follow-up and aid accurate prognostic assessment.Keywords: major post-stroke depression, nomogram, calcium–phosphorus product, C-statistic

Saiyue Deng,1 Quan Wang,2 Jingjing Fan,3 Xiaoyun Yang,3 Junhua Mei,4 Jiajia Lu,5 Guohua Chen,4 Yuan Yang,1 Wenhua Liu,6 Runsen Wang,7 Yujia Han,7 Rong Sheng,7 Wei Wang,1 Li Ba,1 Fengfei Ding1,8 1Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, People’s Republic of China; 2School of Nursing, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430000, People’s Republic of China; 3Cardiac Unit, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, People’s Republic of China; 4Department of Neurology, Wuhan No.1 Hospital, Wuhan, 430022, People’s Republic of China; 5Cardiac Unit, Wuhan No.1 Hospital, Wuhan, 430022, People’s Republic of China; 6Department of Clinical Research Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430000, People’s Republic of China; 7Huawei Technologies Co, Shenzhen, People’s Republic of China; 8Department of Pharmacology, Shanghai Medical College, Fudan University, Shanghai, 200032, People’s Republic of ChinaCorrespondence: Fengfei Ding, Department of Pharmacology, Shanghai Medical College, Fudan University, Shanghai, 200032, People’s Republic of China, Tel +86 134 7625 5813, Email fengfei_ding@fudan.edu.cn Li Ba, Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, People’s Republic of China, Tel +86 136 0764 1809, Email bali2015@126.comPurpose: Heart rate variability (HRV) indices have been used as stress indicators. Rare studies investigated the associations of circadian rhythms of the HRV indices with the stress, mood, and sleep conditions in populations under stress.Methods: In total 257 female participants (203 shift workers and 54 non-shift workers) were included. All the participants completed a structured questionnaire to assess the stress, mood, and sleep conditions and performed 24-hour Holter electrocardiogram monitoring on the day away from shifts. Using epochs of 1-min or 5-min beat-to-beat intervals, the HRV indices (SDNN, RMSSD, LF, HF, LF/HF, and LFnu, SD1, SD2, SD1/SD2) were plotted as a function of time and fitted into cosine periodic curves, respectively. Three mathematical parameters based on the cosine periodic curves were extracted, MESOR (M, overall averages of the cosine curve), amplitude (A, amplitude of the peak of the cosine curve), and acrophase (θ, latency to the peak) to quantify the circadian rhythms of the HRV indices. Multivariable linear regression models were used to reveal the associations of these parameters with the clinical assessments of stress, mood, or sleep conditions, as well as with the 24-h averages of the HRV indices.Results: The parameters M and A of SDNN, RMSSD, LF, and HF, and θ of LF/HF and LFnu significantly differ between shift and non-shift workers. The parameter θ of LF/HF positively correlates with the severity of stress and anxiety. The parameter A of LF/HF and LFnu also positively correlates with daytime sleepiness and sleep fragmentation. In addition, the parameters M and A instead of θ of SDNN, RMSSD, LF, LF/HF, and LFnu significantly correlate with the 24-h averages of HRV indices.Conclusion: The circadian rhythms of the HRV indices over 24 hours can, to some extent, predict the severity of stress, emotion and sleep conditions in female populations under stress.Keywords: circadian rhythms, HRV indices, mental health, stress, sleepiness, fatigue, sleep fragmentation

BACKGROUND Post-stroke depression (PSD) is the most common and serious psychological disorder following stroke. Developing a screening model for PSD at discharge by combination of multiple factors may provide more information in clinical practice than verifying the independent effects of risk factors. OBJECTIVE We aimed to construct two screening tools for PSD in general and young adult stroke patients based on Decision tree (DT) model. METHODS A prospective multicenter cohort study was conducted, including stroke patients within 7 days of the onset of symptoms from May 2018 to October 2019. The associated factors were obtained by multivariate-adjusted binary logistic regression with backward elimination. Chi-squared automatic interaction detection (CHAID) method was used as the separation (growing) method in DT. RESULTS Significant associated factors with PSD at discharge in general stroke patients included hemorrhagic stroke (OR=2.097; 95% CI, 1.36–3.22; P=0.001), higher educational level (OR=0.633; 95% CI, 0.51–0.79; P< 0.001), without medical insurance (OR=1.277; 95% CI, 1.04–1.56; P=0.019) and history of stroke (OR=0.639; 95% CI, 0.48–0.85; P=0.002). History of hypertension and higher educational level were associated with PSD at discharge in young adults in DT model. CONCLUSIONS Several associated factors were found and two decision tree models for PSD at discharge in general and young adult stroke patients were constructed. They could be used as convenient PSD screening tool in clinical practice.

Background Exploring etiological clues to adolescent depression, especially in female adolescents, might be helpful to improve the social environment of female adolescents. The aim at this study is to explore psycho-social factors of female adolescents with high depressive symptomatology and gender differences in depressive symptoms among Chinese adolescents. Method We examined 4100 adolescents from Wuhan city and Jianli county via a cross-sectional study. Depressive symptomatology was screened through the Chinese version of Center for Epidemiology Studies Depression Scale. Multivariate logistic regression was performed to explore the factors related to high depressive symptomatology in female and male adolescents, respectively. Results The prevalence of high depressive symptomatology in female and male were 38.9 and 30.2% respectively. The psycho-social factors of high depressive symptomatology in female adolescents were age (Adjusted odds ratio [aOR] = 1.201, 95% confidence interval [CI], 1.076 ~ 1.341), single parent family (aOR = 2.004, 95%CI, 1.448 ~ 2.772) and fathers’ education level (compared to primary school and below, [Junior middle school, aOR = 0.641, 95%CI, 0.439 ~ 0.934; Senior middle school, aOR = 0.603, 95%CI, 0.410 ~ 0.888; College degree and above, aOR = 0.639, 95%CI, 0.437 ~ 0.936]). Conclusion Fathers’ education level was associated with high depressive symptomatology in female adolescents. Female adolescents whose father with primary school education or below deserves more attention. Further epidemiologic researches need to be conducted to explore the different risk factors between female and male adolescents in China.

BACKGROUND: Providing high-quality training to residency students during the coronavirus 2019 (COVID-19) pandemic has been a goal of our institution. Since 2108, we began to take microlectures to students teaching. Microlectures are online presentations, and the microlecture teaching method has many advantages, such as a short teaching time, situational resource composition, diverse communication, strong pertinence and can attend microlectures from home. The aim of the present study was to evaluate the advantages of the microlecture teaching method on students in standardized residency training. METHODS: Students from our department were randomly divided into the traditional teaching group (control group) and the microlecture teaching group (observation group). The teaching duration for both groups was 3 months. All students were assessed on basic knowledge of the neurology before enrollment. After the teaching session, the students were assessed on teaching effect, theoretical operation, and clinical practice satisfaction. The students also evaluated the teachers, and the teachers evaluated the students. RESULTS: A total of 84 students participated in the study and were divided equally into the observation group (42 students) and the control group (42 students). The results showed that the rate of reaching the standard of teaching effect, achievement of theory and operation, satisfaction with clinical practice, the student's grades by teachers, and student satisfaction with teachers were significantly higher in the observation group than in the control group (all P

In this paper, the mathematical model of the dynamic characteristics of the pilot water hydraulic overflow valve is analyzed and established, and the linear treatment and Laplace transformation of the differential equation are carried out at a stable working point. Simulink software in MATLAB is used to simulate the block diagram of the mathematical model, and the effect of main structure parameters of the valve is obtained, such as inlet volume \(V_{0}\) and core upper chamber volume \(V_{2}\) of the main valve, damping hole diameter \(d_{1}\) and the inlet volume \(V_{1}\) of the pilot valve. The analysis results provide certain guiding significance for the optimization design of pilot overflow valve.

The speed regulating valve is used to control the motion speed of the executive components of the hydraulic system by regulating flow rate for accomplishing the uniform and stable motion. The valve is a combined flow valve by two valves in series, one is a constant differential pressure reducing valve, and the other is a throttle valve. The pressure reducing valve automatically compensates the influence of load, and the pressure is always kept constant. However, it does not change and eliminates the influence of load change on flow, but this flow stability range of the flow control valve is limited, that is, there is a limit to pressure change on the inlet and outlet. This paper introduces the structure principle and flow stability analysis of the flow control valve.

Additional file 2: Table S2. Characteristics of LBC and non-LBC subjects

This paper studies a novel structured light measurement instrument for complex manufactured parts. In this research, a quick and accurate light plane calibration method and a novel light strip center extraction method were used to establish the measurement instrument. First, the intrinsic and external parameters of the camera are calibrated by Zhang's method. Second, a novel light plane calibration technique is proposed by using the original parameters and images in the process of camera calibration, which can be used to improve the accuracy of the measurement system because both the camera calibration and light plane calibration are based on the same target. Third, a subpixel extraction method is presented to extract the light strip center on the basis of the geometric center method. Finally, the constructed instrument is used to detect the geometric information of the complex manufactured parts. The experimental results show that the maximum measurement error is 0.1 mm under a measurement range of 50 mm and the accuracy is 0.2%, which indicates that the measurement instrument is fast, robust, and accurate enough to be applied to many kinds of measurements, such as railroad track deformation, the inner wall of a pipe, and so on.