OBJECTIVETo study the chemical constituents of the whole plants of Pedicularis densispica.

METHODThe chemical constituents were isolated by various chromatographic methods and their structures were determined by chemical evidences and spectral data.

RESULTTen compounds were isolated and identified as acacetin (1), apigenin-7-0-beta-glucopyranoside (2), kaempferol-3,7-O-alpha-dirhamnopyranoside (3), scutellarein-7-0-beta-glucopyranoside (4), chrysoeriol-7-O-beta-glucopyranoside (5), pedicutricone A (6), dearabinosyl pneumonanthoside (7), salidroside (8), darendoside B (9), and maltol-beta-D-glucopyranoside (10).

CONCLUSIONThese compounds were isolated from the titled plant for the first time. Except compounds 6 and 8, the others were obtained for the first time from the genus Pedicularis.

Drugs, Chinese Herbal ; analysis ; isolation & purification ; Flavonoids ; analysis ; isolation & purification ; Pedicularis ; chemistry ; Sesquiterpenes ; analysis ; isolation & purification

The petroleum ether fraction of ethanol extract of Acorus tatarinowii were separated by column chromatography and recrystallization to afford seven compounds. On the spectroscopic analysis, they were identified as 1-hydroxy-7(11),9-guaiadien-8-one (1), calamenone(2), cis-asarone(3), chrysophanol (4), physcion (5), emodin (6), (+)-galbacin (7). Compound 1 is a new compound. Compounds 4-7 were isolated from this plant for the first time.
Acorus ; chemistry ; Ethanol ; Ether ; Plant Extracts ; analysis

Objective To explore application of automatic tube current modulation combined with iterative reconstruction in CT scanning ( non-enhanced and enhanced) of neck. Methods A total of 80 patients with CT scanning of neck were randomly divided into test group(n=40, automatic tube current modulation, iterative reconstruction ) and control group ( n = 40, 200 mAs, filtered-back-projection reconstruction ) . Subjective scores and objective evaluation of two groups were evaluated. Evaluation included image noise ( SD ) of thyroid gland, trapezius muscle, sternocleidomastoid muscle, submandibular gland, lateral pterygoid muscle and brain tissue. Effective dose ( E ) was compared. Results The E of non-enhanced and enhanced scanning in test group was lower than that of control group with the statistically significant difference(t = -2. 451, -2. 451, P <0. 05). The subjective scores of non-enhanced and enhanced scanning in test group were higher than those of control group with the statistically significant difference (Z = - 1.969, - 2.056, P < 0.05), while SD of thyroid gland, trapezius muscle, sternocleidomastoid muscle, submandibular gland in test group were lower than that of control group with the statistically significant difference ( t =2. 400,2. 516,2. 120,2. 411,4. 134,4. 674, 2. 711,2. 892, P<0. 05). There were no significant differences in SD of lateral pterygoid muscle, brain tissue of non-enhanced and enhanced scanning between two groups (P>0. 05). Conclusions Automatic tube current modulation combined with iterative reconstruction in CT scanning of neck could improve image quality, and reduce effectively radiation dose.

Objective To investigate the effect of CareDose 4D combined with Care kV on CT pulmonary ground glass nodule ( GGN) with respect to quality and radiation dose. Methods The thoracic model containing 6 GGN was performed by using 7 low-dose schemes. The CareDose 4D + Care kV was adopted in scheme 1. In schemes 2, 3 and 4, the tube voltage was 120 kV, and the tube current 30, 20 and 10 mAs respectively. In schemes 5, 6 and 7, the tube voltage was 100 kV, and the tube current was 30, 20 and 10 mAs, respectively. The image quality [ CT value, contrast noise ratio ( CNR) , noise value (SD) and subjective score] and effective dose (E) were compared. Results There was no statistically significant difference in CT value of GGN among different schemes (P>0. 05). The SD of scheme 1 was higher than those of schemes 2, 3 and 5, but lower than those f scheme 7, while the CNR of scheme 1 was lower than those of schemes 2, 3 and 5, but higher than that of scheme 7 ( t=13. 020, 9. 560, 8. 120,-5. 720, -7. 849, -5. 192, -4. 130, 1. 361,P<0. 05). SD and CNR of scheme 1 were not significantly different from those of scheme 4 and 6 ( P>0. 05) . The subjective scores of each GGN of schemes 1, 2, 3, 5 and 6 was over 3 points, but and the subjective scores of one GGN of each of schemes 4 and 7 were below 3 points. The value E of the scheme 1 was reduced by 63. 0％, 44. 4％, 38. 8％, and 9. 1％, compared with the schemes 2, 3, 5 and 6, respectively. Conclusions CareDose 4D combined with Care kV in low-dose lung CT scan can ensure the image quality of GGN and reduce the radiation dose effectively.

Objective To explore the influence of iterative algorithm on image quality in ultralow-dose CT scan of lung.Methods The thoracic model was scanned using different parameter combinations.The tube voltage was chose with 80,100 kV in ultra-low dose group and the mAs was selected by 10,15,20,25 and 30 mAs.The control group selected the parameters of 120 kV,30 mAs.All the images were reconstructed with filtered back projection (FBP group) and iterative algorithm (IR group).The image noise and effective dose (E) were compared.Results When tube current and voltage were constant,the image noise of IR group was lower than that of FBP group,and the difference was statistically significant (t =1.102-8.070,P＜0.05).When the tube current was constant,the image noise of the 80 kV with FBP group was higher than that of 100 kV with FBP group,and the image noise of the 80 kV with IR group was lower than the 100 kV with FBP group(t =-8.639-7.841,P＜0.05).Compared with the conventional low-dose with FBP group,the image noise of each ultra-low-dose with FBP group was significantly increased,and the image noise of (80 kV,10 mAs),(80 kV,15 mAs),(80 kV,20 mAs) with IR group was significantly increased,and the image noise of (100 kV,15 mAs),(100 kV,20 mAs),(100 kV,25 mAs),(100 kV,30 mAs) with IR group was significantly reduced (t=-8.140-23.028,P＜0.05).There was no significant difference in image noise between the groups of (80 kV,25 mAs),(80 kV,30 mAs),(100 kV,10 mAs) with IR and the group of conventional low dose with FBP (P＞0.05).Compared with the conventional low dose group,the E of the groups of (80 kV,25 mAs),(80kV,30mAs),(100kV,10 mAs),(100kV,15mAs),(100kV,20mAs),(100kV,25 mAs),(100 kV,30 mAs) was decreased by 75.9％,71.0％,79.8％,70.4％,60.3％,50.2％,40.0％,respectively.Conclusions The image quality of the ultra-low dose protocol (100 kV,10mAs) with iterative algorithm is similar to that of the conventional low dose with FBP group,and the radiation dose could be significantly reduced.

Objective:To assess the agreement of manual measurement, semi-automatic measurement based on computer-aided diagnosis (CAD), and automatic measurement based on artificial intelligence (AI) in measuring diameters and volumes of solid pulmonary nodules.Methods:The clinical and low dose CT (LDCT) data of 165 participants in lung cancer screening of Sichuan Cancer Hospital from July 2018 to April 2020 were retrospectively analyzed. The largest nodule of each participant was selected to analyze, and its diameter and volume were measured by one junior and one senior radiologist using manual measurement, semi-automatic measurement based on CAD, and automatic measurement based on AI. Referring to Lung CT imaging reporting and data system (Lung-RADS, version 1.1), all nodules were classified into Lung-RADS 2, 3, 4A, 4B, 4X categories and low and high risk groups according to the diameter and volume measured by different measurement methods. Repeated-measures analysis of variance and paired t-test were used to compare the differences in the diameter and volume of lung nodules measured by different methods. The consistency of the three methods in measuring nodule diameter and volume was assessed by the correlation coefficient (ICC). Linear weighted Kappa coefficient was applied to assess the consistency of different measurement methods in Lung-RADS classification results; simple Kappa coefficient was applied to assess the consistency of different methods in high and low risk grouping results. Results:Difference in the diameters of pulmonary nodules measured by manual measurement, semi-automatic measurement based on CAD, and automatic measurement based on AI was statistically significant [(14.9±6.3) mm, (17.0±6.7) mm, (15.0±5.7) mm, F=88.39, P<0.001], and the pairwise comparisons showed that there was significant difference between semi-automatic measurement based on CAD and manual measurement method ( t=10.97, P<0.001), semi-automatic measurement based on CAD and automatic measurement based on AI ( t=10.07, P<0.001), but no significant difference between manual measurement method and automatic measurement based on AI method ( t=1.04, P=0.301). There was no significant difference in the measurement of pulmonary nodule volumes between the semi-automatic measurement and the automatic measurement method based on AI ( Z=0.70, P=0.482). The consistency of pulmonary nodules diameter measured by different measurement methods was high (ICC>0.75), and the consistency of semi-automatic and automatic measurement of lung nodule volume was high (ICC=0.927). The consistency of three methods for lung-RADS classification and high-and low-risk grouping according to nodule diameter was good (Kappa>0.80). The agreements between the semi-automatic measurement and the automatic measurement method for Lung-RADS classification and high-and low-risk grouping according to nodule volume were good (Kappa>0.80). Conclusion:In terms of diameter measurement of solid pulmonary nodules, automatic measurement based on AI is more consistent with manual measurement than semi-automatic measurement based on CAD. The agreement between automatic measurement and semi-automatic measurement is high in terms of volume measurement.

ObjectiveTo analyze the management and treatment for patients with severe mental disorders in Chengdu from 2016 to 2020， in order to provide references for the relevant authorities to formulate policies and improving the mental health service system. MethodsData relating to 22 districts （cities） and counties in Chengdu from January 1， 2016 to December 31， 2020 were extracted from the National Information System for Severe Mental Disorders. Indicators such as reported prevalence rate， management rate， standardized management rate， medication rate， regular medication rate and stable condition rate of patients with severe mental disorders were analyzed on a yearly basis. ResultsBy the end of 2020， there were 71 899 registered cases of severe mental disorders in Chengdu， with a reported prevalence rate of 0.34%， a standardized management rate of 95.53%， and a regular medication rate of 72.50%. From 2016 to 2020， except the reported prevalence rate （χ²=269.566， P<0.01）， management rate （χ²=384.030， P<0.01）， standardized management rate （χ²=309.742， P<0.01）， medication rate （χ²=414.252， P<0.01）， regular medication rate （χ²=316.172， P<0.01） and stable condition rate （χ²=288.335， P<0.01） had linear trends of increasing with the annual increase. ConclusionFrom 2016 to 2020， the management rate， treatment rate and regular medication rate of patients with severe mental disorders have been increased year by year in Chengdu. Nevertheless， the increase in reported prevalence rate should be accompanied by strengthened management and follow-up to increase the regular medication rate to maintain the stability of patients' conditions.

ObjectiveTo understand the status of stigma and subjective well-being of patients with mental disorders and co-resident family members， to analyze the correlation between them， and to compare the impact of stigma upon the subjective well-being of patients and family members of the same household. MethodsPatients with mental disorders （n=154） and their families （n=154） who visited the outpatient department of a tertiary psychiatric hospital in Chengdu from October to November 2019 were selected， and four instruments were used for collecting the data， including self-designed demographic information questionnaire， self-designed disease-related information questionnaire， brief version of Internalized Stigma of Mental Illness Scale （ISMI-10） and Index of Well-Being Scale （IWB）. ResultsA total of 118 （76.62%） patients with mental disorders and 151 （98.05%） family members experienced stigma. The total score and each factors score in ISMI-10 of family members were higher than those of patients （P<0.01）， and the total score and each dimension score in IWB were lower than those of patients （P<0.01）. Pearson correlation analysis showed that ISMI-10 total score of patients and family members was negatively correlated with IWB total score （r=-0.600，-0.202， P<0.05 or 0.01）. After controlling demographic and disease-related variables， multiple linear regression analysis showed that the regression model of mental disorder patients achieved good fit effect （adjusted R²=0.457）， with statistical significance （F=26.746， P<0.01）， while the regression model of co-living family members was lack of fit （adjusted R²=0.035）. After controlling for family demographic variables， the model was at the statistical level （F=3.769， P<0.01）. ConclusionMental disorder patients have low illness stigma and high subjective well-being， whereas the opposite is true for family members. Moreover， there is a negative relationship between stigma and subjective well-being for both patients and family members， stigma is a significant factor affecting subjective well-being for people with mental disorders.

This article gives a review on domestic and foreign researches on the non-drug intervention for patients with perimenopausal depression published from 2012 to 2022， so as to provide a reference for clinical treatment and nursing. Currently， pharmacotherapy is the mainstay of treatment for perimenopausal depression， while many existing problems remain to be solved such as the variation in treatment effect and the difficulty in maintaining emotional stability. however，high safety and relatively low cost are the characteristics of non-drug intervention， so this article expounds on the non-drug intervention measures for perimenopausal depression， such as music therapy， dietary therapy， exercise therapy， acupuncture therapy and repetitive transcranial magnetic stimulation （rTMS）.

BackgroundThe occurrence rate of dangerous behaviors in patients with severe mental disorders is higher than that of the general population. In China， there is limited research on the prediction of dangerous behaviors in community-dwelling patients with severe mental disorders， particularly in terms of predicting models using data mining techniques other than traditional methods. ObjectiveTo explore the influencing factors of dangerous behaviors in community-dwelling patients with severe mental disorders and testing whether the classification decision tree model is superior to the Logistic regression model. MethodsA total of 11 484 community-dwelling patients with severe mental disorders who had complete follow-up records from 2013 to 2022 were selected on December 2023. The data were divided into a training set （n=9 186） and a testing set （n=2 298） in an 8∶2 ratio. Logistic regression and classification decision trees were separately used to establish predictive models in the training set. Model discrimination and calibration were evaluated in the testing set. ResultsDuring the follow-up period， 1 115 cases （9.71%） exhibited dangerous behaviors. Logistic regression results showed that urban residence， poverty， guardianship， intellectual disability， history of dangerous behaviors， impaired insight and positive symptoms were risk factors for dangerous behaviors （OR=1.778， 1.459， 2.719， 1.483， 3.890， 1.423， 2.528， 2.124， P<0.01）. Being aged ≥60 years， educated， not requiring prescribed medication and having normal social functioning were protective factors for dangerous behaviors （OR=0.594， 0.824， 0.422， 0.719， P<0.05 or 0.01）. The predictive effect in the testing set showed an area under curve （AUC） of 0.729 （95% CI： 0.692~0.766）， accuracy of 70.97%， sensitivity of 59.71%， and specificity of 72.05%. The classification decision tree results showed that past dangerous situations， positive symptoms， overall social functioning score， economic status， insight， household registration， disability status and age were the influencing factors for dangerous behaviors. The predictive effect in the testing set showed an AUC of 0.721 （95% CI： 0.705~0.737）， accuracy of 68.28%， sensitivity of 64.46%， and specificity of 68.60%. ConclusionThe classification decision tree does not have a greater advantage over the logistic regression model in predicting the risk of dangerous behaviors in patients with severe mental disorders in the community. ［Funded by Chengdu Medical Research Project （number， 2020052）］