Objective To study the effect of electrical stimulation breath training on lung function of patients following pulmonary lobectomy. Methods 62 patients following pulmonary lobectomy were randomly allocated into experimental group (n=30 )and control group (n=32). The experimental group received a 4-week supervised electrical stimulation breath training program using an electric stimulus feedback trainer (20mins per time, 3 times per week);The control group received postoperative routine nursing. Cadiopulmonary function evaluation of 2 groups were tested before and after the experiment. The evaluation included the 6-min walking test (6MWD), FVC, FEV1,W,AT and VO2max/kg. Results After 4 week training, the value of 6MWD,W,FVC,FEV1 all improved, compared to the baseline value (P < 0.05) and the value of 6MWD,W,FVC,FEV1 were more obvious in experimental group, compared to control group(P<0.05). The AT value and the VO2max/kg value increased than the baseline value (P<0.05)and the improvement degree was more remarkable in experimental group than that in control group (P<0.05). Conclusion Electrical stimulation breath training can improve cardiopulmonary function of the patients following pulmonary lobectomy.

The characterization methods in the field of protein adsorption on biological materials in recent years were reviewed from the aspects of protein adsorption amount, adsorption layer thickness, molecular conformational change after protein adsorption, molecular morphology after protein adsorption, and protein molecule adsorption process simulation. These methods include biochemical analysis, surface plasmon resonance (SPR), dissipative quartz crystal microbalance ( QCM-D ) , ellipsometry ( ELM ) , optical interference reflection ( RIFS ) , attenuated total reflection Fourier transformed infrared spectroscopy (ATR-FTIR), circular dichroism (CD), atomic force microscopy ( AFM ) and computer molecular simulation techniques . In this paper , the basic principles , the advantages and disadvantages of the above characterization methods and related researches were reviewed. This paper provides a comprehensive and reliable basis for the selection of protein experimental characterization methods in protein adsorption, biomaterial design and other research, and provides new ideas for research in the field of protein.

Objective: To investigate the abnormalities of the blood system in landfill workers. Methods: A cohort study was conducted for 224 landfill workers who were followed up for 6 consecutive years with abnormal routine blood test results and a low platelet count as the outcome events. The life-table method was used to analyze the incidence rates of these two outcome events, and the incidence rates were compared between first-and second-line workers. Results: A total of 71 workers had abnormal routine blood test results, among whom 29 had abnormal leukocyte count, 14 had abnormal erythrocyte count, 40 had abnormal platelet count, 17 had abnormal hemoglobin, and 29 had a reduction in platelet count. For these landfill workers, the 6-year abnormal rate of routine blood test results was 43.2%, and the incidence rate of low platelet count within 6 years was 13.5%. The first-line workers had a significantly lower abnormal rate of routine blood test results than the second-line workers (P=0.020) , and the relative risk of abnormal routine blood test results in the first-and second-line workers was 0.592. There was no significant difference in the incidence rate of low platelet count between the two groups of workers (P≥0.05) . Conclusion The landfill has an adverse effect on the blood system of landfill workers, and the second-line workers have greater impairment than the first-line workers.

With the progress of information technology and intelligent technology,the intelligent development of urine testing instruments is facing new opportunities.Using the disease cybernetics theory model to analyze the business process and current urine testing instruments of clinical urine analyzer,a generational theoretical model of urine testing instruments has been constructed,which is conducive to guiding the intelligent development direction of urine testing instruments.The study divides urine testing instruments into one to four generations of products,with the first-generation of products being operated by doctors.The second-generation products are currently available for laboratory technicians to use various urine analyzers.The third-generation products further optimize the testing process and intelligence,without the need for inspectors to operate.The fourth-generation products are unmanned and do not require sampling.It can be seen that with the development of technology,urine analysis has indeed become more convenient,but after all,various instruments have their limitations.Therefore,the establishment of a theoretical model for the generation of urine testing instruments should be applied in clinical urine testing,which can not only improve the efficiency of urine analysis but also improve its quality.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

Objective:To explore the relationship between childhood trauma and anxiety in vocational school students, and to analyze the mediating role of emotion dysregulation.Methods:A cross-sectional survey was conducted in one vocational school in Ganzhou, all students completed a series of questionnaires, including the childhood trauma questionnaire (CTQ), difficulties in emotion regulation scale (DERS), and generalized anxiety disorder scale (GAD-7).The cut-off score for anxiety symptom was set GAD-7≥5.The data were analyzed using SPSS 23.0 and SPSS macro program PROCESS V4.0.Results:(1) The rate of anxiety in vocational school students was 42.96%, and girls were 27.1% higher than boys ( OR=1.271, 95% CI=1.095-1.474).(2) The CTQ (44(38, 51)) and DERS (98(89, 111)) in students with anxiety were both significantly higher than those in students without anxiety (39(34, 45), 81(73, 90), Z=-17.910, -33.859, both P<0.001).(3) Regression analysis showed that girls ( β=0.240, OR=1.271, 95% CI=1.095~1.474), childhood trauma ( β=0.028, OR=1.028, 95% CI=1.019~1.037), and emotion dysregulation ( β=0.076, OR=1.080, 95% CI=1.073-1.086) were significant predictors for anxiety.(4) Path analysis and mediating effect showed that childhood trauma positively predicted anxiety ( β=0.059, 95% CI=0.048-0.071) and emotion dysregulation ( β=0.802, 95% CI=0.749-0.854), and emotion dysregulation positively predicted anxiety ( β=0.139, 95% CI=0.132-0.145).Emotion dysregulation had a significant mediating effect (effect value=0.112, 95% CI=0.101-0.121) in the relationship between childhood trauma and anxiety, with the indirect effect accounting for 65.50% of the total effect. Conclusion:The incidence of anxiety symptoms is high among vocational school students, and childhood trauma not only directly affects anxiety symptoms, but also indirectly affects anxiety symptoms through emotion dysregulation.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.

Objective: To explore glymphatic impairment in pediatric refractory epilepsy (RE) using multi-parameter magnetic resonance imaging (MRI), assess its relationship with white-matter (WM) abnormalities and clinical indicators, and preliminarily evaluate the performance of multi-parameter MRI in discriminating RE from drug-sensitive epilepsy (DSE). Materials and Methods: We retrospectively included 70 patients with DSE (mean age, 9.7 ± 3.5 years; male:female, 37:33) and 26 patients with RE (9.0 ± 2.9 years; male:female, 12:14). The diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index as well as fractional anisotropy (FA), mean diffusivity (MD), and nodal efficiency values were measured and compared between patients with RE and DSE. With sex and age as covariables, differences in the FA and MD values were analyzed using tract-based spatial statistics, and nodal efficiency was analyzed using a linear model. Pearson’s partial correlation was analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the discrimination performance of the MRI-based machine-learning models through five-fold cross-validation. Results: In the RE group, FA decreased and MD increased in comparison with the corresponding values in the DSE group, and these differences mainly involved the callosum, right and left corona radiata, inferior and superior longitudinal fasciculus, and posterior thalamic radiation (threshold-free cluster enhancement, P < 0.05). The RE group also showed reduced nodal efficiency, which mainly involved the limbic system, default mode network, and visual network (false discovery rate, P < 0.05), and significantly lower DTI-ALPS index (F = 2.0, P = 0.049). The DTI-ALPS index was positively correlated with FA (0.25 ≤ r ≤ 0.32) and nodal efficiency (0.22 ≤ r ≤ 0.37), and was negatively correlated with the MD (-0.24 ≤ r≤ -0.34) and seizure frequency (r = -0.47). A machine-learning model combining DTI-ALPS, FA, MD, and nodal efficiency achieved a cross-validated ROC curve area of 0.83 (sensitivity, 78.2%; specificity, 84.8%). Conclusion Pediatric patients with RE showed impaired glymphatic function in comparison with patients with DSE, which was correlated with WM abnormalities and seizure frequency. Multi-parameter MRI may be feasible for distinguishing RE from DSE.