Aim To study the molecular basis of protection on myocardial ischemic injuries of total flavones of choerospondias axiaris fructus(TFC). Methods The microarray analysis for the protein expression in myocardium provide a strong tool to explore the key protein candidates involved in the pathogenesis of ischemic injury.Surface enhanced laser desorption/ionization(SELDI) mass spectrometry with protein chip IMAC3,SAX2 and NP20 was used to compare the differentially expressed protein in TFC-treated and untreated ischemic myocardium in rats and the results were analysized with Proteinchip Software 3.0.2.Results Seven differentially expressed proteins were indentified in TFC treated myocardium.These differential effects correlated with the expression of five downregulated proteins and two upregulated proteins,and four of them were discovered on the IMAC3 chip and one of them was discovered on the SAX2 chip.Conclusions The myocardial protection of TFC may be mediated by the differential expression of these proteins which could be the key protein candidates for further investigation.

Objective To investigate the changing characteristics of myocardial movement in patients with dilated cardiomyopathy by three?di?mensional speckle tracking echocardiography(3D?STE). Methods The peak systolic global longitudinal train(GLS),global radial strain(GRS), global circumferential stain(GCS)and global area strain(GAS)of left ventricle were measured by 3D?STE technology in 69 patients with dilated cardiomyopathy. According to the left ventricular ejection fraction(LVEF),all patients were divided into group A(35%≤LVEF<50%)and group B (LVEF<35%). The differences of measurements were compared between two groups. The correlation between global myocardial strain in all direc?tions and left ventricular ejection fraction was analyzed. Results The GLS,GRS,GCS and GAS were significantly higher in group A than those in group B(P<0.01). The GLS,GRS,GCS and GAS were correlated with LVEF in group A(r=-0.871,0.610,-0.423,-0.797;P<0.05).The GCS,GRS and GAS were correlated with LVEF in group B(r=-0.517,0.368,-0.438;P<0.05). There was no significant correlation between GLS and LVEF in group B. Conclusion 3D?STE technology can be applied to evaluate the change of the myocardial movement. GLS is a promis?ing marker of the prognosis in patients with DCM.

Objective To observe the clinical effect of percutaneous vertebroplasty(PVP) in the treatment of elderly patients with thoracolumbar vertebral compression fractures.Methods From September 2014 to September 2015,70 elderly patients with vertebral compression fractures in Cilin Hospital were selected and randomly divided into two groups according to the digital table,with 35 cases in each group.The control group received conservative treatment,the study group was given PVP treatment.Before and after treatment,the visual analogue scale (VAS),functional independence measure(FIM) score were compared between the two groups.The loss of vertebral height,vertebral height restoration of anterior and posterior margin,Cobb angle correction and quality of life(SF-36) score changes were compared between the two groups.Results After treatment,the VAS score,FIM score of the study group were (3.46 ± 0.25) points,(67.94 ± 5.48) points,which of the control group were (5.02 ± 0.13) points,(51.49 ± 3.84) points,there were statistically significant differences between the two groups (t =32.75,14.54,all P ＜ 0.05).The vertebral height lost,vertebral height restoration and margin,Cobb angle correction in the study group were (4.90 ± 0.23) mm,(93.84 ± 1.12) ％,(11.21 ± 0.24) °,respectively,which were better than those in the control group (t =34.67,101.31,190.57,all P ＜ 0.05).The SF-36 scores between the two groups had statistically significant differences(all P ＜ 0.05).Conclusion PVP in the treatment of elderly patients with thoracolumbar compression fractures has good effect,it can help to relieve the pain,improve the quality of life of patients.

OBJECTIVE: To analyze the indications of the therapies for rheumatoid arthritis (RA) with neural network model analysis. METHODS: Three hundred and ninety-seven patients were included in the clinical trial from 9 clinical centers. They were randomly divided into Western medicine (WM) treated group, 194 cases; and traditional Chinese herbal medicine (CM) treated group, 203 cases. A complete physical examination and 18 common clinical manifestations were prepared before the randomization and after the treatment. The WM therapy included voltaren extended action tablet, methotrexate and sulfasalazine. The CM therapy included Glucosidorum Tripterygii Totorum Tablet and syndrome differentiation treatment. The American College of Rheumatology 20 (ACR20) was taken as efficacy evaluation. All data were analyzed on SAS 8.2 statistical package. The relationships between each variable and efficacy were analyzed, and the variables with P<0.2 were included for the data mining analysis with neural network model. All data were classified into training set (75%) and verification set (25%) for further verification on the data-mining model. RESULTS: Eighteen variables in CM and 24 variables in WM were included in the data-mining model. In CM, morning stiffness, swollen joint number, peripheral immunoglobulin M (IgM) level, tenderness joint number, tenderness, rheumatoid factor (RF), C-reactive protein (CRP) and joint pain were positively related to the efficacy, and disease duration and more urination at night negatively related to the efficacy. In WM, erythrocyte sedimentation rate (ESR), weak waist, white fur in tongue, joint pain, joint stiffness and swollen joint were positively related to the efficacy, and yellow fur in tongue, red tongue, white blood negatively related to the efficacy. In the analysis with the neural network model in the patients of verification set, the predictive response rates of 20% patients would be 100% and 90% in the treatment with CM and WM, respectively. CONCLUSION: Neural network model analysis, based on the full clinical trial data with collection of both traditional Chinese medicine and modern medicine diagnostic information, shows a good predictive role for the information in the efficacy in rheumatoid arthritis.

OBJECTIVE: To evaluate the correlations between clinical symptoms and treatment efficacy in patients with rheumatoid arthritis (RA). METHODS: Four hundred and thirteen patients were included in the clinical trial from 9 clinical centers. They were randomly divided into Western medicine-treated group with 204 cases and Chinese herbal drug-treated group with 209 cases. Eighteen clinical symptoms were evaluated before and after treatment. The Western medicine therapy included voltaren extended release tablets, methotrexate and sulfasalazine. The Chinese herbal drug therapy included glucosidorum Tripterygii totorum tablets and Yishen Juanbi Tablets combined with treatment based on syndrome differentiation. The American College of Rheumatology 20 (ACR20) was used as efficacy evaluation criteria. RESULTS: In the Chinese herbal drug-treated group, clinical symptoms such as arthralgia and tenderness of joints were positively correlated with the efficacy after 12-week treatment, while frequent urination at night was negatively correlated. In the same group, tenderness of joints and fever were positively correlated with the efficacy after 24-week treatment, while deep-colored and turbid urine was negatively correlated. In the Western medicine-treated group, tenderness of joints and thirst were positively correlated with the efficacy after 12-week treatment, while vertigo was negatively correlated. And in the same group, tenderness of joints was positively correlated with the efficacy after 24-week treatment, while heaviness of limbs was negatively correlated to the efficacy. The statistical results showed that the treatment efficacy was improved when the correlated symptoms were included in the indications. CONCLUSION: The treatment efficacy of RA is correlated with some symptoms, so further studies should proceed on these correlations in order to achieve better treatment outcome.

Objective: To study risk factors for non-alcoholic fatty liver disease (NAFLD) and vascular erectile dysfunction (ED) in patients with metabolic syndrome (MS). Methods: A total of 18 096 subjects were selected from people undergoing physical examination from 2008 to 2009 in northern cities of China by random cluster sampling method, and analyzed the risk factors for NAFLD and ED. Results: The 18 096 cases with age 18~76 (46.8±10.1) years old，containing 10 096 (55.79%) males and 8 000 (44.21%) females. Awareness rate of MS was 8.33% and prevalence rate of MS in healthy adults was 21.18%. Most common components of MS were hyperuricemia (27%, 4838/18096), obesity and overweight (21%), hypertension (20%,) and dyslipidemia (17%) in turn. Body mass index (BMI, kg/m2) and waist/hip ratio (WHR) of all MS subgroups from high to low were ED group [(28.9±1.1), (1.26±0.03)], overweight or obesity group [(27.5±2.3), (1.31±0.03)], prediabetes group [(26.8±2.6), (1.03±0.03)] and hypertension group [(26.1±1.3), (0.90±0.04)] in turn. A total of 3 721 MS patients （20.56%）complicated with NAFLD; By means of NAFLD complicated by MS as dependent variable, Logistic regression analysis indicated that increased ALT, waist circumference（WC）, age, DM family history, LDL-C and BMI (β=1.004~0.479, P=0.000~0.016 in turn) were risk factors for NAFLD, and physical exercise and occupational physical work were protective factors for NAFLD. There were 106 ED males and its prevalence rate was 1.04%; Logistic regression analysis indicated that age, WC, LDL-C, DM family history and BMI (β=0.681~0.238, P=0.000~0.018 in turn) were risk factors for ED, and educational degree, physical exercise and occupational physical work were protective factors for ED. Conclusion: Risk factors for NAFLD and ED in MS were closely correlated with MS. It’s a new path to prevent and treat NAFLD and ED through correcting risk factors of MS.

Objective:To investigate the impact of China's Mental Health Law on the work of psychological counseling in colleges and universities, and to explore ways to improve the law. Methods: Totally 12 heads of college and university counseling centers in Beijing were conducted with semi-structured interviews. The average age of the interviewees was (40 ±7) years old, with master or doctor degrees in psychology or related disciplines. The method of content analysis was used to analyze the interviewees' understanding of the " Mental Health Law". Results: All of the 12 interviewees had gained some understanding of the "Mental Health Law", and accordingly amended the regulation of their counseling centers. Also, interviewees suggested the positive and negative impacts brought by the law, such as enhancing practitioners' legislative sense, clarifying their responsibilities and boundaries as college and university counseling, as well as difficulties to distinguish psychotherapy and psychological counseling, ambiguity in the legality of working with students who were diagnosed with mental disorders. Moreover, interviewees threw out suggestions on improving the law from the aspect of industry standard, supervision department and vocational qualification. Conclusion: The execution of "Mental Health Law" improves practitioners' legislative sense, clarifies their responsibility. Nevertheless, it does not clearly distinguish psychotherapy from psychological counseling, and be lack of regulation on the psychological counseling industry.

The purpose of this study was to investigate the formation thermodynamics of baicalein(BE)-nicotinamide(NCT)cocrystals in three solvents including ethyl acetate, acetone and trichloromethane. The solubilities of BE, NCT and BE-NCT in the above solvents at 25 °C were measured. Ternary phase diagrams(TPDs)of the BE-NCT-solvent systems were established. The non-linear fitting equation according to 1 ∶1 complexation mechanism of BE-NCT cocrystals demonstrated a good correlation between calculated and experiment data. ΔG0< 0 suggested that BE-NCT cocrystal formation was a spontaneous process. Among the organic solvents studied, the absolute value of ΔG0 in trichloromethane was significantly lower than that in the other two solvents. In addition, the cocrystallization zone in trichloromethane was far away from stoichiometric line. This study provides a theoretical foundation for solvent selection and preparation-condition optimization of BE-NCT cocrystals.

Objective:To investigate the attributes and influencing factors of care needs for maternal after perinatal loss, and to provide a reference for promoting maternal physical and mental health and improving the quality of care.Methods:From February to June of 2023, a cross-sectional study was used, 222 maternal after perinatal loss were selected by the convenience sampling method and completed a battery of questionnaires, including a general information questionnaire, the Distress Thermometer (DT), the Perceived Social Support Scale (PSSS), the Attitudes Toward Seeking Professional Psychological Help Scale-Short Form (ATSPPH-SF) and Kano Model-based Questionnaire on Care Needs for Maternal after Perinatal Loss.Results:A total of 207 maternal after perinatal loss were included in the complete data, (31.12±4.55) years old, (68.64 ± 10.70) of PSSS, (16.10 ± 3.43) of ATSPPH-SF. The care needs for maternal after perinatal loss included 4 must-be quality, 8 one-dimensional quality and 13 attractive quality. Multiple linear regression analysis showed that education level ( t=2.28), the PSSS score ( t=2.15) and the ATSPPH-SF score ( t=3.94) were the main influencing factors of care needs for maternal after perinatal loss (all P<0.05). Conclusions:Health care professionals should gradually improve the nursing service system according to the priority division of care needs attributes of maternal after perinatal loss, and develop personalized care according to different influencing factors.

As a promising method in artificial intelligence, deep learning has been proven successful in several domains ranging from acoustics and images to natural language processing. With medical imaging becoming an important part of disease screening and diagnosis, deep learning-based approaches have emerged as powerful techniques in medical image areas. In this process, feature representations are learned directly and automatically from data, leading to remarkable breakthroughs in the medical field. Deep learning has been widely applied in medical imaging for improved image analysis. This paper reviews the major deep learning techniques in this time of rapid evolution and summarizes some of its key contributions and state-of-the-art outcomes. The topics include classification, detection, and segmentation tasks on medical image analysis with respect to pulmonary medical images, datasets, and benchmarks. A comprehensive overview of these methods implemented on various lung diseases consisting of pulmonary nodule diseases, pulmonary embolism, pneumonia, and interstitial lung disease is also provided. Lastly, the application of deep learning techniques to the medical image and an analysis of their future challenges and potential directions are discussed.