Objective:To investigate the structural changes in the spinal cord in multiple sclerosis (MS) and neuromyelitis optica spectrum disorders (NMOSD) and their relationship with clinical disability.Methods:This study was cross-sectional. A retrospective analysis of clinical and imaging data from 124 patients with MS (MS group), 101 patients with aquaporin-4 antibody-positive NMOSD (NMOSD group), and 110 healthy controls (HC group) from seven medical centers were conducted from January 2018 to October 2021. All subjects underwent 3D T 1WI, and the upper cervical spinal cord cross-sectional area (MUCCA) was segmented and measured. All patients completed the expanded disability status scale (EDSS) assessments at baseline and during follow-up, as well as the baseline 25-foot walk test (T25FW) and the nine-hole peg test (NHPT). Patients were classified into EDSS progression and non-progression groups based on follow-up EDSS scores. Comparisons of MUCCA among the three groups were conducted using analysis of covariance, controlling for age and sex as covariates. Pairwise comparisons between groups were performed using the HSD test. Univariate linear regression and logistic models were employed to identify candidate predictors of baseline clinical disability status or EDSS progression in the MS and NMOSD groups. L1 regularized multivariable linear regression analysis was used to determine independent predictors of baseline clinical disability status or EDSS progression. Independent predictors were then combined to establish a logistic regression model, and the model′s performance in predicting EDSS progression was evaluated using receiver operating characteristic analysis and the area under the curve (AUC). Results:A total of 144 patients completed follow-up EDSS assessments, with a follow-up duration of 3.30 (1.10, 6.42) years, including 82 patients in the MS group and 62 patients in the NMOSD group. Controlling for sex and age as covariates, the overall difference in MUCCA among the MS, NMOSD, and HC groups was statistically significant ( P=0.001). The MUCCA in the MS group was lower than that in the HC group, with a significant difference ( t=-2.54, P=0.007); the MUCCA in the NMOSD group was also lower than that in the HC group, with a significant difference ( t=-2.80, P=0.002). However, the difference in MUCCA between the MS and NMOSD groups was not statistically significant ( t=-0.40, P=0.882). In the MS group, MUCCA was an independent predictor of baseline EDSS score (β=-0.03), baseline T25FW score (β=-0.09), and baseline NHPT score (β=-0.30). In the NMOSD group, MUCCA (β=-0.08), age (β=0.06), and baseline EDSS score (β=-0.43) were independent predictors of EDSS progression, and the logistic regression model incorporating these three factors predicted EDSS progression with an AUC of 0.82. Conclusions:Significant spinal cord atrophy occurs in patients with both MS and NMOSD. Atrophy of the upper cervical spinal cord can predict the degree of disability in MS patients and the progression of clinical disability in NMOSD patients.

Objective:To investigate the structural changes in the spinal cord in multiple sclerosis (MS) and neuromyelitis optica spectrum disorders (NMOSD) and their relationship with clinical disability.Methods:This study was cross-sectional. A retrospective analysis of clinical and imaging data from 124 patients with MS (MS group), 101 patients with aquaporin-4 antibody-positive NMOSD (NMOSD group), and 110 healthy controls (HC group) from seven medical centers were conducted from January 2018 to October 2021. All subjects underwent 3D T 1WI, and the upper cervical spinal cord cross-sectional area (MUCCA) was segmented and measured. All patients completed the expanded disability status scale (EDSS) assessments at baseline and during follow-up, as well as the baseline 25-foot walk test (T25FW) and the nine-hole peg test (NHPT). Patients were classified into EDSS progression and non-progression groups based on follow-up EDSS scores. Comparisons of MUCCA among the three groups were conducted using analysis of covariance, controlling for age and sex as covariates. Pairwise comparisons between groups were performed using the HSD test. Univariate linear regression and logistic models were employed to identify candidate predictors of baseline clinical disability status or EDSS progression in the MS and NMOSD groups. L1 regularized multivariable linear regression analysis was used to determine independent predictors of baseline clinical disability status or EDSS progression. Independent predictors were then combined to establish a logistic regression model, and the model′s performance in predicting EDSS progression was evaluated using receiver operating characteristic analysis and the area under the curve (AUC). Results:A total of 144 patients completed follow-up EDSS assessments, with a follow-up duration of 3.30 (1.10, 6.42) years, including 82 patients in the MS group and 62 patients in the NMOSD group. Controlling for sex and age as covariates, the overall difference in MUCCA among the MS, NMOSD, and HC groups was statistically significant ( P=0.001). The MUCCA in the MS group was lower than that in the HC group, with a significant difference ( t=-2.54, P=0.007); the MUCCA in the NMOSD group was also lower than that in the HC group, with a significant difference ( t=-2.80, P=0.002). However, the difference in MUCCA between the MS and NMOSD groups was not statistically significant ( t=-0.40, P=0.882). In the MS group, MUCCA was an independent predictor of baseline EDSS score (β=-0.03), baseline T25FW score (β=-0.09), and baseline NHPT score (β=-0.30). In the NMOSD group, MUCCA (β=-0.08), age (β=0.06), and baseline EDSS score (β=-0.43) were independent predictors of EDSS progression, and the logistic regression model incorporating these three factors predicted EDSS progression with an AUC of 0.82. Conclusions:Significant spinal cord atrophy occurs in patients with both MS and NMOSD. Atrophy of the upper cervical spinal cord can predict the degree of disability in MS patients and the progression of clinical disability in NMOSD patients.

Objective:To explore the non-bacterial pathogen distribution, epidemiological characteristics, and clinical features of acute respiratory infections in children in Sichuan Province.Methods:Using a retrospective cohort study method, this study selected hospitalized children diagnosed with acute respiratory infections at West China Second Hospital of Sichuan University from February 2019 to January 2021, and tested 13 pathogens using polymerase chain reaction (PCR)-fragment analysis. The children were divided into infant group (<1 year old), toddler group (1 year old ≤ age <3 years old), preschool group (3 years old ≤ age <6 years old) and school-age group (6 years old ≤ age <18 years old). The distribution of pathogen positive rates, seasonal epidemic characteristics, clinical characteristics, and some laboratory test indicators were analyzed in children. Statistical analysis was performed on the results using SPSS 22.0 software, with count data expressed as percentages and inter group comparisons using SPSS 22.0 software χ2 Inspection. Results:A total of 2 922 pediatric patients were included in this study, with 1 748 (59.8%) positive for pathogens detected. Among them, 1 391 (79.6%) were detected as a single pathogen, and 357 (20.4%) were detected as a mixture of two or more pathogens. The most commonly detected pathogens were rhinovirus (HRV) (39.7%), syncytial virus (RSV) (22.8%), and parainfluenza virus (PIV) (12.5%). Pathogen positivity is more common in children under 6 years old ( χ2=146.59, P<0.001), with a slightly higher positivity rate in male children (61.3%, 1 047/1 707) than in female children (57.7%, 701/1 215) ( χ2=3.91, P=0.048), and compared with pathogen negative children, positive children are more prone to symptoms such as cough, wheezing, and shortness of breath ( χ2=259.15, 366.06, 12.48, P<0.001). The distribution of different pathogens varies among children of different age groups, and HRV is more common in children aged 1-3 and 3-6 years old ( χ2=9.74, P<0.001), while RSV is more common in children under 1 year old ( χ2=178.63, P<0.001), while mycoplasma pneumoniae (MP) and influenza virus (InfA/B) are less common in children under 1 year old ( χ2=92.54, 12.90,22.21, P<0.01). The prevalence of multiple pathogens showed seasonal changes. HRV showed a high prevalence trend in spring and autumn, while the prevalence of RSV infection was mainly seen in autumn and winter festivals. The positive rate of different pathogens after the outbreak of novel coronavirus pneumonia was significantly lower than that before the outbreak ( χ2=252.68, P<0.001). Conclusion:The detection rate of non-bacterial respiratory pathogens in children in Sichuan Province from 2019 to 2021 is high, which is prone to symptoms such as cough, wheezing, and shortness of breath, with HRV and RSV being the main types. The positive rate of respiratory pathogens varies among different age groups, genders, and seasons.

Objective:To explore the non-bacterial pathogen distribution, epidemiological characteristics, and clinical features of acute respiratory infections in children in Sichuan Province.Methods:Using a retrospective cohort study method, this study selected hospitalized children diagnosed with acute respiratory infections at West China Second Hospital of Sichuan University from February 2019 to January 2021, and tested 13 pathogens using polymerase chain reaction (PCR)-fragment analysis. The children were divided into infant group (<1 year old), toddler group (1 year old ≤ age <3 years old), preschool group (3 years old ≤ age <6 years old) and school-age group (6 years old ≤ age <18 years old). The distribution of pathogen positive rates, seasonal epidemic characteristics, clinical characteristics, and some laboratory test indicators were analyzed in children. Statistical analysis was performed on the results using SPSS 22.0 software, with count data expressed as percentages and inter group comparisons using SPSS 22.0 software χ2 Inspection. Results:A total of 2 922 pediatric patients were included in this study, with 1 748 (59.8%) positive for pathogens detected. Among them, 1 391 (79.6%) were detected as a single pathogen, and 357 (20.4%) were detected as a mixture of two or more pathogens. The most commonly detected pathogens were rhinovirus (HRV) (39.7%), syncytial virus (RSV) (22.8%), and parainfluenza virus (PIV) (12.5%). Pathogen positivity is more common in children under 6 years old ( χ2=146.59, P<0.001), with a slightly higher positivity rate in male children (61.3%, 1 047/1 707) than in female children (57.7%, 701/1 215) ( χ2=3.91, P=0.048), and compared with pathogen negative children, positive children are more prone to symptoms such as cough, wheezing, and shortness of breath ( χ2=259.15, 366.06, 12.48, P<0.001). The distribution of different pathogens varies among children of different age groups, and HRV is more common in children aged 1-3 and 3-6 years old ( χ2=9.74, P<0.001), while RSV is more common in children under 1 year old ( χ2=178.63, P<0.001), while mycoplasma pneumoniae (MP) and influenza virus (InfA/B) are less common in children under 1 year old ( χ2=92.54, 12.90,22.21, P<0.01). The prevalence of multiple pathogens showed seasonal changes. HRV showed a high prevalence trend in spring and autumn, while the prevalence of RSV infection was mainly seen in autumn and winter festivals. The positive rate of different pathogens after the outbreak of novel coronavirus pneumonia was significantly lower than that before the outbreak ( χ2=252.68, P<0.001). Conclusion:The detection rate of non-bacterial respiratory pathogens in children in Sichuan Province from 2019 to 2021 is high, which is prone to symptoms such as cough, wheezing, and shortness of breath, with HRV and RSV being the main types. The positive rate of respiratory pathogens varies among different age groups, genders, and seasons.

Objective:To investigate the efficacy of a machine learning model based on radiomics of brain lesions on T 2WI in differentiating multiple sclerosis (MS) from neuromyelitis optica spectrum disorders (NMOSD). Methods:Totally 223 MS and NMOSD patients who were treated from January 2009 to September 2018 in Beijing Tiantan Hospital Affiliated to Capital Medical University, Donghu Branch of the First Affiliated Hospital of Nanchang University, Tianjin Medical University General Hospital, and Xuanwu Hospital of Capital Medical University were analyzed retrospectively, and according to the proportion of 7∶3, 223 patients were completely randomly divided into training set (156 cases) and test set (67 cases). A total of 74 patients with MS and NMOSD who were treated in Huashan Hospital Affiliated to Fudan University and China-Japan Friendship Hospital of Jilin University from January 2009 to September 2018 and in Xianghu Branch of the First Affiliated Hospital of Nanchang University from March 2020 to September 2021 were collected as an independent external validation set. All patients underwent brain cross-sectional MR T 2WI, radiomics features were extracted from T 2WI, and features were selected by max-relevance and min-redundancy and least absolute shrinkage and selection operator algorithms. Then various machine learning classifier models (logistic regression, decision tree, AdaBoost, random forest or support vector machine) were constructed to differentiate MS from NMOSD. The area under curve (AUC) of receiver operating characteristics was used to evaluate the performance of each classifier model in the training set, test set and external validation set. Results:Based on multi-center T 2WI, a total of 11 radiomics features related to the discrimination between MS and NMOSD were extracted and classifier models were constructed. Among them, the random forest model had the best efficiency in distinguishing MS from NMOSD, and its AUC values for distinguishing MS from NMOSD in the training set, test set and external validation set were 1.000, 0.944 and 0.902, with specificity of 100%, 76.9% and 86.0%, and sensitivity of 100%, 92.1% and 79.7%, respectively. Conclusion:The random forest model based on the radiomic features of T 2WI of brain lesions can effectively distinguish MS from NMOSD.

Objective:To investigate the influencing factors for unfavorable outcome of low-grade aneurysmal subarachnoid hemorrhage (aSAH).Methods:A retrospective study was performed. The clinical data of 273 patients with aSAH of World Federation of Neurosurgery (WNFS) grading I and II, admitted to our hospital from April 2017 to March 2021, were collected. According to modified Rankin scale (mRS) scores 3 months after treatment, these patients were divided into favorable outcome group (mRS scores of 0-2) and unfavorable outcome group (mRS scores of 3-6). Statistical methods were used to analyze the clinical and imaging data differences between the two groups and identify the independent influencing factors for unfavorable outcome. Receiver operating characteristic (ROC) curves were drawn to evaluate the predictive values of different independent factors in unfavorable outcome.Results:Among the 273 patients with low-grade aSAH, 45 patients had unfavorable outcome and 228 patients had favorable outcome. Univariate analysis showed that there was significant difference between the 2 groups in age, Fisher grading distribution, proportions of patients complicated with shunt dependent hydrocephalus, with delayed cerebral ischemia, or with intracranial hemorrhage, and WNFS grading ( P<0.05). Multivariate Logistic regression analysis showed that concurrent shunt dependent hydrocephalus ( OR=5.075, 95%CI: 1.705-15.102, P=0.004), age ( OR=1.090, 95%CI: 1.036-1.147, P=0.004), delayed cerebral ischemia ( OR=8.282, 95%CI: 3.447-19.896, P=0.000), and postoperative intracranial hemorrhage ( OR=8.603, 95%CI: 2.332-31.745, P=0.001) were independent influencing factors for unfavorable outcome. ROC curve analysis showed that the optimal diagnostic threshold of age was 65 years, and the areas under ROC curve for delayed cerebral ischemia and age in predicting unfavorable outcome were 0.733 ( 95%CI: 0.653-0.813, P=0.000) and 0.709 ( 95%CI: 0.622-0.796, P=0.000). Conclusion:Low-grade aSAH patients with age≥65, postoperative shunt dependent hydrocephalus, delayed cerebral ischemia, and intracranial hemorrhage are more likely to have unfavorable outcome; age and complicated delayed cerebral ischemia have certain diagnostic value in low-grade aSAH patients.

Objective:To evaluate the effect of remote ischemic preconditioning on comfort level of patients after radial artery intervention.Methods:A total of 160 patients with coronary heart disease were selected from the Second Ward of Cardiology Department of the First Affiliated Hospital of Xinjiang Medical University from June to December 2018 by convenience sampling method. All the patients underwent transradial angiography and intervention (TAI) and were randomly divided into the control group (80 cases) and the intervention group (80 cases) . The control group received routine nursing care, while the intervention group received routine nursing care and remote ischemic preconditioning intervention for 3 times within 24 hours before surgery. The difference of vascular complications and comfort degree between the two groups within 24 hours after operation were compared.Results:There was significant difference in the degree of swelling and pain between the two groups 12 hours after TAI ( P<0.05) . There was no osteofascial compartment syndrome in the two groups within 24 hours after Tai. There was no significant difference in the occurrence of radial artery occlusion and local bleeding between the two groups ( P>0.05) . There was significant difference in the occurrence of radial artery stenosis and vagal reflex between the two groups ( P<0.05) . Conclusions:Remote ischemic preconditioning can effectively reduce the incidence of postoperative complications such as radial artery stenosis in patients undergoing coronary intervention via radial artery, and improve the postoperative comfort level of patients.

Objective To investigate the significance of procalcitonin(PCT),C-reactive protein(CRP),white blood cell(WBC) and other inflammatory markers in the diagnosis of pediatric patients with HFMD.Methods 138 cases of pediatric patients with foot and mouth disease(study group)and 50 cases of healthy children(control group)were recruited in the study.Procalcitonin (PCT),white blood cell(WBC),neutrophil count(NC),lymphocyte count(Ly),immunoglobulins,C-reactive protein and other indi-cators were determined and compared.Results PCT,CRP,WBC,NC,Ly% and IgM levels were higher in study group than those in control group,the differences were all statistically significant(P <0.05 );IgG,IgA levels in control group were lower than that in control group,the differences were statistically significant(P <0.05).Conclusion PCT,WBC,NC,Ly,CRP and IgA,IgG,IgM can provide experimental evidence for diagnosis of children with hand foot and mouth disease.

Neonatal inherited metabolic diseases are a group of metabolic disorders caused by singe gene defect to cause a series of clinical symptoms.Neonatal dried blood spots have the advantages of simple preparation,safety,good stability,and show strong practicability in different screening methods for inherited metabolic diseases.With the development of screening methods,more and more diseases could be diagnosed by screening.The emergence of tandem mass spectrometry and molecular biological techniques promote the newborn screening and automation for inherited metabolic disease effectively.Inherited metabolic diseases induce great harm to the newborn,which could cause not only system organs damage,but also lead to death.Therefore,early screening is important for patients' prognosis.

Objective To observe the expression and influence of SH2-B in hepatocarcinoma,and to investigate the molecular mechanisms of canceration in hepatocarcinoma.Methods By using SABC imunohis-tochemistry,the expressions of SH2-B were detected in 27 cases of hepatitis,29 cases of hepatocirrhosis and 47 cases of hepatocarcinoma.Hepatocarcinoma cell (HepG)2 with a low-expressed SH2-B was selected using immunofluorescence assay.There were 3 groups:the transfected group (transfected with pcDNA3.1 -SH2-B), the vector group (transfected with pcDNA3.1 )and the blank group (without transfection).After gene transfec-tion,SH2-B expression was detected by Western blotting;cell proliferation was measured by MTT assay;cell colony was counted by colony formation test;and cell cycle was analyzed by flowcy tometer.Results The posi-tive rate of SH2-B in hepatocarcinoma (95.7%)was significantly higher than 55.2% in hepatocirrhosis (χ2 =1 8.64,P <0.01 )and 25.9% in hepatitis (χ2 =40.01 ,P <0.01 ).After being transfected with pcDNA 3.1 -SH2-B,SH2-B expression dramatically increased in HepG2 cells.After cultured for 48 h,the average optical density value of the transfected group was 1 .1 2 ±0.1 9,obviously higher than 0.45 ±0.1 1 in the vector group (t =-31 .55,P <0.01 ),which indicated that cells proliferation was significantly enhanced after being trans-fected with SH2-B.The cell colony numbers of the transfected group was 1 66 ±1 4,significantly higher than
82 ±8 in the vector group (t =-20.33,P <0.01 )and 78 ±9 in the blank group (t =-1 9.64,P <0.01 ), which indicated that the cell colony numbers increased after being transfected with SH2-B.The S stage cells of the transfected group was (45.7 ±5.8)%,significantly higher than (1 9.4 ±4.7)% in the vector group (t =-20.33,P <0.01 )and (20.5 ±5.1 )% in the blank group (t =-34.69,P <0.01 ),which indicated that SH2-B could enhance promote cell cycle of HepG2 cells.Conclusion The expression of SH2-B in hepatocar-cinoma is high,and it may be involved in the canceration of hepatocarcinoma though promoting cell cycle,cell proliferation and cell transformation.