AIM To investigate the effects of volatile oil from Acorus tatarinowii Schott(A.tatarinowii)on neuroinflammation in a rat model of tic disorders.METHODS The SD rats were randomly divided into the blank group(8 rats)and the model group(40 rats).The rat models of tic disorders established successfully by intraperitoneal injection of iminodiapropionitrile(IDPN)were further divided into the model group,the tiapride group and the high-dose,moderate-dose and low-dose A.tatarinowii volatile oil groups,with 8 rats in each group.The 4-week intragastric treatment of respective drug was initiated the next day after the completion of modeling,and normal saline was dosed upon the blank group and the model group,during which the rats' behavioral changes were assessed by stereotyped behavior and motor behavior score every week.After the administration,the rats had their morphological changes of striatal neurons observed by Nissl staining;their levels of TGF-β,IL-10,TNF-αand IL-1β in serum and striatum detected by ELISA;their striatal protein expressions of CX3CL1 and CX3CR1 detected by Western blot and immunohistochemistry;and their striatal expressions of M1,M2 microglia marker proteins CD86,CD206,SYN and PSD-95 detected by immunofluorescence co-staining.RESULTS Compared with the model group,the A.tatarinowii volatile oil groups demonstrated improved twitch-like behavior;decreased scores of motor behavior and rigid behavior(P＜0.01);alleviated damage of Nissl bodies in neurons;increased serum and striatum levels of TGF-β and IL-10(P＜0.05,P＜0.01);decreased levels of TNF-α and IL-1β(P＜0.01);decreased striatal protein expressions of CX3CL1 and CX3CR1(P＜0.01);increased protein expressions of PSD95 and SYN(P＜0.05,P＜0.01);and decreased CD86/Iba1(P＜0.01)and increased CD206/Iba1(P＜0.01)in terms of the fluorescence intensity.CONCLUSION A.tatarinowii volatile oil contributes an anti-tic effect and improves the neuroinflammation in the brain of the rat model of tic disorders by promoting the transformation of microglia into M2 type via CX3CL1/CX3CR1 signal axis.

Objective:To describe the prevalence of anxiety disorders and its distribution in Inner Mongolia Autonomous Region,and to explore the relevant factors of anxiety disorders.Methods:From June 2019 to Decem-ber 2019,representative multi-stage disproportionate stratified sampling procedure was used to sample in residents aged 18 and over in the Inner Mongolia Autonomous Region.All respondents were face-to-face interviewed by trained interviewers.Composite International Diagnostic Interview-3.0(CIDI-3.0)was used to diagnose anxiety disorders according to the criteria and definition of the Diagnostic and Statistical Manual of Mental Disorders,Fourth Edition(DSM-Ⅳ).Chi-square test and multivariate logistic regression analysis were used for statistical anal-ysis.Results:Totally 12 315 people were interviewed in the survey.The weighted 12-mouth prevalence rate of any anxiety disorder was 4.64％,and the lifetime prevalence rate was 6.25％.The weighted 12-month prevalence rate of anxiety disorders was higher in female than that in male(5.38％vs.3.92％).The rate was higher in rural resi-dents than that in urban residents(5.67％vs.3.95％).The rate was higher in people with chronic diseases than that in people without chronic diseases(6.81％vs.2.29％).Logistic regression analysis showed that unmarried(OR=2.32,95％CI:1.31-4.10),separated/divorced(OR=2.49,95％CI:1.33-4.67),in debt(OR=1.55,95％CI:1.04-2.32),chronic disease(OR=2.22,95％CI:1.39-3.53),family history of anxiety disorders(OR=12.05,95％CI:8.78-16.53),poor sleep(OR=2.64,95％CI:1.97-3.54)were risk factors of occurrence of anxiety disorders,while junior high school(OR=0.65,95％CI:0.44-0.96)was protective factor of anxiety disor-ders.Conclusion:Adults with chronic diseases,poor sleep,unmarried or separated/divorced,family history of anxi-ety disorders,and financial debt are at higher risk groups of anxiety disorder in Inner Mongolia Autonomous Re-gion.

AIM To investigate the effects of volatile oil from Acorus tatarinowii Schott(A.tatarinowii)on neuroinflammation in a rat model of tic disorders.METHODS The SD rats were randomly divided into the blank group(8 rats)and the model group(40 rats).The rat models of tic disorders established successfully by intraperitoneal injection of iminodiapropionitrile(IDPN)were further divided into the model group,the tiapride group and the high-dose,moderate-dose and low-dose A.tatarinowii volatile oil groups,with 8 rats in each group.The 4-week intragastric treatment of respective drug was initiated the next day after the completion of modeling,and normal saline was dosed upon the blank group and the model group,during which the rats' behavioral changes were assessed by stereotyped behavior and motor behavior score every week.After the administration,the rats had their morphological changes of striatal neurons observed by Nissl staining;their levels of TGF-β,IL-10,TNF-αand IL-1β in serum and striatum detected by ELISA;their striatal protein expressions of CX3CL1 and CX3CR1 detected by Western blot and immunohistochemistry;and their striatal expressions of M1,M2 microglia marker proteins CD86,CD206,SYN and PSD-95 detected by immunofluorescence co-staining.RESULTS Compared with the model group,the A.tatarinowii volatile oil groups demonstrated improved twitch-like behavior;decreased scores of motor behavior and rigid behavior(P＜0.01);alleviated damage of Nissl bodies in neurons;increased serum and striatum levels of TGF-β and IL-10(P＜0.05,P＜0.01);decreased levels of TNF-α and IL-1β(P＜0.01);decreased striatal protein expressions of CX3CL1 and CX3CR1(P＜0.01);increased protein expressions of PSD95 and SYN(P＜0.05,P＜0.01);and decreased CD86/Iba1(P＜0.01)and increased CD206/Iba1(P＜0.01)in terms of the fluorescence intensity.CONCLUSION A.tatarinowii volatile oil contributes an anti-tic effect and improves the neuroinflammation in the brain of the rat model of tic disorders by promoting the transformation of microglia into M2 type via CX3CL1/CX3CR1 signal axis.

Objective:To describe the prevalence of anxiety disorders and its distribution in Inner Mongolia Autonomous Region,and to explore the relevant factors of anxiety disorders.Methods:From June 2019 to Decem-ber 2019,representative multi-stage disproportionate stratified sampling procedure was used to sample in residents aged 18 and over in the Inner Mongolia Autonomous Region.All respondents were face-to-face interviewed by trained interviewers.Composite International Diagnostic Interview-3.0(CIDI-3.0)was used to diagnose anxiety disorders according to the criteria and definition of the Diagnostic and Statistical Manual of Mental Disorders,Fourth Edition(DSM-Ⅳ).Chi-square test and multivariate logistic regression analysis were used for statistical anal-ysis.Results:Totally 12 315 people were interviewed in the survey.The weighted 12-mouth prevalence rate of any anxiety disorder was 4.64％,and the lifetime prevalence rate was 6.25％.The weighted 12-month prevalence rate of anxiety disorders was higher in female than that in male(5.38％vs.3.92％).The rate was higher in rural resi-dents than that in urban residents(5.67％vs.3.95％).The rate was higher in people with chronic diseases than that in people without chronic diseases(6.81％vs.2.29％).Logistic regression analysis showed that unmarried(OR=2.32,95％CI:1.31-4.10),separated/divorced(OR=2.49,95％CI:1.33-4.67),in debt(OR=1.55,95％CI:1.04-2.32),chronic disease(OR=2.22,95％CI:1.39-3.53),family history of anxiety disorders(OR=12.05,95％CI:8.78-16.53),poor sleep(OR=2.64,95％CI:1.97-3.54)were risk factors of occurrence of anxiety disorders,while junior high school(OR=0.65,95％CI:0.44-0.96)was protective factor of anxiety disor-ders.Conclusion:Adults with chronic diseases,poor sleep,unmarried or separated/divorced,family history of anxi-ety disorders,and financial debt are at higher risk groups of anxiety disorder in Inner Mongolia Autonomous Re-gion.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective To analyze the influencing factors of death in the elderly with coronavirus disease 2019(COVID-19).Methods The case data of death caused by COVID-19 in West China Fourth Hospital from January 1 to July 8,2023 were collected,and surviving cases from the West China Elderly Health Cohort infected with COVID-19 during the same period were selected as the control.LASSO-Logistic regression was adopted to analyze the data after propensity score matching and the validity of the model was verified by drawing the receiver operating characteristic curve.Results A total of 3 239 COVID-19 survivors and 142 deaths with COVID-19 were included.The results of LASSO-Logistic regression showed that smoking(OR=3.33,95%CI=1.46-7.59,P=0.004),stroke(OR=3.55,95%CI=1.15-10.30,P=0.022),malignant tumors(OR=19.93, 95%CI=8.52-49.23, P<0.001),coronary heart disease(OR=7.68, 95%CI=3.52-17.07, P<0.001),fever(OR=0.51, 95%CI=0.26-0.96, P=0.042),difficulty breathing or asthma symptoms(OR=21.48, 95%CI=9.44-51.95, P<0.001),and vomiting(OR=8.19,95%CI=2.87-23.58, P<0.001)increased the risk of death with COVID-19.The prediction model constructed based on the influencing factors achieved an area under the curve of 0.889 in the test set.Conclusions Smoking,stroke,malignant tumors,coronary heart disease,fever,breathing difficulty or asthma symptoms,and vomiting were identified as key factors influencing the death risk in COVID-19.
Humans ; COVID-19/mortality* ; Aged ; Propensity Score ; China/epidemiology* ; Risk Factors ; Logistic Models ; Smoking ; SARS-CoV-2 ; Male ; Female ; Stroke ; Neoplasms