Objective: To compare the effectiveness of qualitative and quantitative fecal immunochemical tests (FIT) in identifying colorectal cancer, so as to provide insights into perfecting screening strategies for colorectal cancer. Methods: Participants in the Colorectal Cancer Screening Program for Key Populations in Zhejiang Province from May 2020 to December 2021 were recruited, and their demographic information, lifestyle and disease history were collected through a questionnaire survey. Qualitative or quantitative FIT along with a questionnaire-based risk assessment were employed as the initial screening tests. Individuals who were positive in any FIT or had high-risk assessment results were required to attend a subsequent colonoscopy examination. The positive rate, detection rate of colorectal cancer, positive predictive value and number of colonoscopies required were compared between qualitative and quantitative FITs, and stratified analyses by gender and age were conducted. Results: Totally 4 099 769 participants were included. The qualitative FIT group included 3 574 917 individuals, yielding a positive rate of 11.35%, a detection rate of 1.19%, a positive predictive value of 0.48% and 83.84 colonoscopies required to detect one cancer case. The quantitative FIT group involved 524 852 individuals, yielding a positive rate of 6.70%, a detection rate of 2.31%, a positive predictive value of 1.01% and 43.23 colonoscopies required to detect one cancer case. The quantitative FIT group showed significantly higher detection rate of colorectal cancer, higher positive predictive value and less number of colonoscopies required compared to the qualitative FIT group (all P<0.05). The same results were obtained after stratification by gender and age. Conclusion Compared to qualitative FIT, quantitative FIT improves the detection of colorectal cancer and reduces the workload of colonoscopy examinations, making it more suitable for colorectal cancer screening in large-scale populations.

Objective To observe the correlations of chest CT quantitative parameters in patients with acute exacerbation of chronic obstructive pulmonary disease(AECOPD)with blood eosinophil(EOS)level.Methods Chest CT data of 162 AECOPD patients with elevated eosinophils were retrospectively analyzed.The patients were divided into low EOS group(n=105)and high EOS group(n=57)according to the absolute counting of blood EOS.The quantitative CT parameters,including the number of whole lung bronchi and the volume of blood vessels,low-attenuation area percentage(LAA％)of whole lung,of left/right lung and each lobe of lung,as well as the luminal diameter(LD),wall thickness(WT),wall area(WA)and WA percentage of total bronchial cross-section(WA％)of grade 3 to 8 bronchi were compared between groups.Spearman correlations were performed to analyze the correlations of quantitative CT parameters with blood EOS level.Results LAA％of the whole lung,of the left/right lung and each lobe of lung,as well as of the upper lobe of right lung LDgrade4,middle lobe of right lung WTgrade5,upper lobe of right lung WAgrade4,middle lobe of right lung WAgrade5 and lower lobe of left lung WAgrade3 in low EOS group were all higher than those in high EOS group(all P＜0.05).Except for the upper lobe of right lung LDgrade4,the above quantitative CT indexes being significant different between groups were all weakly and negatively correlated with blood EOS level(r=-0.335 to-0.164,all P＜0.05).Conclusion Chest CT quantitative parameters of AECOPD patients were correlated with blood EOS level,among which LAA％,a part of WT and WA were all weakly negatively correlated with blood EOS level.

Triple-negative breast cancer (TNBC) is a nasty disease with extremely high malignancy and poor prognosis. Annexin A3 (ANXA3) is a potential prognosis biomarker, displaying an excellent correlation of ANXA3 overexpression with patients' poor prognosis. Silencing the expression of ANXA3 effectively inhibits the proliferation and metastasis of TNBC, suggesting that ANXA3 can be a promising therapeutic target to treat TNBC. Herein, we report a first-in-class ANXA3-targeted small molecule (R)-SL18, which demonstrated excellent anti-proliferative and anti-invasive activities to TNBC cells. (R)-SL18 directly bound to ANXA3 and increased its ubiquitination, thereby inducing ANXA3 degradation with moderate family selectivity. Importantly, (R)-SL18 showed a safe and effective therapeutic potency in a high ANXA3-expressing TNBC patient-derived xenograft model. Furthermore, (R)-SL18 could reduce the β-catenin level, and accordingly inhibit the Wnt/β-catenin signaling pathway in TNBC cells. Collectively, our data suggested that targeting degradation of ANXA3 by (R)-SL18 possesses the potential to treat TNBC.

Objective:To investigate the feasibility of classifying imaging patterns of dermatomyositis/polymyositis-related interstitial lung disease (DM/PM-ILD) into subtypes based on chest CT radiomics features and a model was constructed by machine learning algorithms.Methods:From November 2011 to November 2020, 107 patients diagnosed with PM/DM-ILD at the First Affiliated Hospital of Xi′an Jiaotong University were retrospectively analyzed. A total of 315 cases with chest CT were collected. Doctors pre-classified image patterns, including 105 cases with non-specific interstitial pneumonia (NSIP), 90 cases with organizing pneumonia (OP), and 66 cases with non-specific interstitial pneumonia combined with organizing pneumonia (NSIP+OP), 35 cases with common interstitial pneumonia (UIP), and 19 cases with diffuse alveolar damage (DAD), ANOVA was used to test the difference of baseline clinical information among the imaging classification groups. All images were divided into the training set and the est set by stratified random sampling at a ratio of 4∶1. In each CT scan, 3D slicer was used to segment each lung lobe, and then reconstructed into 3 mm 3 of voxels, and Pyradiomics library was used to extract the radiomic features of the whole lung and each lobe. The multi-classification goal was achieved by constructing random forest base classifiers for each of the five groups and then voting as the final model. In the process of constructing the base classifier, firstly, the balance between sample groups was achieved by SMOTETomek comprehensive sampling, and the optimal feature set was selected by independent sample t test and L1 regularized least absolute shrinkage and selection operator (LASSO) regression. In this study, the Radiomics model was constructed based on chest CT radiomics features, and the Radiomics + model was constructed by introducing gender and age information. The base classifier and the integration model use the mean accuracy and the area under the receiver operator characteristics analysis curve (AUC) to evaluate the performance, respectively. Results:There was a statistically significant difference ( P<0.05) between the ages of the NSIP, OP, NSIP+OP, UIP, and DAD groups [(57±13),(53±8),(54±10),(44±11), and (46±8)years old, respectively], F=11.82, P<0.001. In the Radiomics model, for each group of NSIP, OP, NSIP+OP, UIP, and DAD, the AUCs of the training set were 0.87, 0.91, 0.91, 0.96, and 0.99, respectively, and the AUC of the test set were 0.81, 0.82, 0.79, 0.93, 0.89. In the final Radiomics + model, for each group of NSIP, OP, NSIP+OP, UIP, and DAD, the AUCs of the training set were 0.89, 0.91, 0.92, 0.97, and 0.99, respectively, and the AUCs of the test set were 0.84, 0.82, 0.78, 0.94, 0.90. Conclusion:Based on chest CT radiomics features and key clinical features (sex, age), the Radiomics + model constructed by machine learning has good classification performance for the imaging patterns of PM/DM-LD.

Objective:To systematically evaluate and analyze the original research of prescription sequence symmetry analysis (PSSA), summarize its research progress and methodological details, and provide a reference for the future use of this method.Methods:The keywords related to PSSA were used for literature retrieval from Chinese databases (CNKI, Wanfang, and VIP) and English databases (PubMed, Embase, and Cochrane). Original articles that were related to PSSA and published before June 30, 2020 were selected. Information form was developed by Excel. Stata was used for the statistics analysis.Results:There were 45 eligible articles included in the research. Since 2013, the number of studies using PSSA has increased rapidly. These studies were mainly conducted in Japan ( n=11, 24.44%), China ( n=10, 22.22%), Denmark ( n=9, 20.00%), and Australia ( n=8, 17.78%). Medical claim database was used most commonly when PSSA was implemented. The included studies involved 16 types of drugs, of which the number of studies of psychotropic drugs and statins was highest ( n=8, 17.78%), and adverse reactions of almost all human systems were involved. In terms of methodology, 35 (77.78%) and 43 (95.56%) studies clearly reported the run-in period and interval period, of which 14 (31.11%) and 9 (20.00%) respectively gave the method or reason for determining the duration. In addition, 16 articles (35.56%) and 18 articles (40.00%) reported sensitivity analysis and subgroup analysis results, respectively. Conclusions:PSSA, one of the effective methods for safety signal detection in healthcare databases, has developed rapidly, but the methodological details and result reporting need to be improved. In China, PSSA research is still in its infancy, and it is necessary to pay attention to the quality of research and promote methodological exploration.

Objective:To systematically summarize and assess risk prediction models for occurrence of cervical cancer and to provide evidence for selecting the most reliable model for practice, and guide cervical cancer screening.Methods:Two groups of keywords related to cervical cancer and risk prediction model were searched on Chinese databases (CNKI, and Wanfang) and English databases (PubMed, Embase, and Cochrane Library). Original articles that developed or validated risk prediction models and published before November 21, 2019, were selected. Information form was created based on the CHARMS checklist. The PROBAST was used to assess the risk of bias.Results:12 eligible articles were identified, describing 15 prediction models, of which five were established in China. The predicted outcomes included multiple stages from cervical precancerous lesions to cancer occurrence, i.e., abnormal Pap smear (1), occurrence or recurrence of CIN (9), and occurrence of cervical cancer (5), etc. The most frequently used predictors were HPV infection (12), age (7), smoking (5), and education (5). There were two models using machine learning to develop models. In terms of model performance, the discrimination ranged from 0.53 to 0.87, while only two models assessed the calibration correctly. Only two models were externally validated in Taiwan of China, using people in different periods. All of the models were at high risk of bias, especially in the analysis domain. The problems were concentrated in the improper handling of missing data (13), preliminary evaluation of model performance (13), improper use of internal validation (12), and insufficient sample size (11). In addition, the problems of inconsistency measurements of predictors and outcomes (8) and the flawed report of the use of blindness for outcome measures (8) were also severe. Compared with the other models, the Rothberg (2018) model had relatively high quality. Conclusions:There are a certain number of cervical cancer risk prediction models, but the quality is poor. It is urgent to improve the measurement of predictors and outcomes, the statistical analysis details such as handling missing data and evaluation of model performance and externally validate existing models to better guide screening.

Objective:To understand the current status of rare disease related health information release in WeChat official accounts in China.Methods:We used a series of key words containing "rare diseases" and the names of the top 30 rare diseases in hospitalizations in China to search WeChat official accounts. Eligible articles were selected by systematic sampling. All including WeChat official accounts and articles were evaluated to extract the basic information.Results:No relevant WeChat official accounts were found for 14 rare diseases (46.67 %). Most of the WeChat official accounts (52.17 %) were initiated by patients and patient groups. No significant difference was detected in the total number of articles between the official accounts related with Traditional Chinese Medicine (TCM) and non-TCM related ones, however, the frequency of the monthly information release was significantly higher in TCM related official accounts ( P<0.001), while the average reading number of articles was significantly higher in non-TCM related official accounts ( P<0.001). Nearly 80 % of the WeChat official accounts had navigation menu, and the average reading number of official accounts with menus was larger than those without menus. The top three topics were rare disease diagnosis and treatment knowledge (46.00 %), public welfare activity for rare diseases (12.81 %) and uncorrelated things (8.65 %), while the first three leading topics were cutting-edge information, public welfare activity and patient story, respectively. Conclusions:The scale for rare disease related health information release based on WeChat official accounts in China has been basically formed, but it is still in development stage. Many improvements should be made in their coverage of rare diseases, release frequency, topic and form. It is urgent to establish or recreate some high-quality WeChat official accounts in order to provide precise information and effectively facilitate the prevention and treatment of rare diseases.

Objective: To explore the effects of Yiqi Yangyin Liangxue method on platelets, interleukin-10(IL-10) and transforming growth factor beta (TGF-β) of immune thrombocytopenic purpura(ITP) model mice, and to analyze its curative effect and possible mechanism. Methods: A total of 100 ITP model mice were randomly divided into blank group, model group, single Chinese medicine group, single hormone group and Chinese medicine combined with hormone group.Drug intervention was started on the 8th day after the establishment of the model, and the drug was given for a total of 14 days.The blood of mice was collected and the levels of platelets, TGF-β and IL-10 in serum of mice in each group were detected. Results: There was no statistically significant difference in platelet count among all groups before modeling(F=0.556, P>0.05). Before administration, there was statistically significant difference between the model group and the blank group (t=28.207, P<0.01), there were no statistically significant differences between the model group and the traditional Chinese medicine group, hormone group, hormone+ traditional Chinese medicine group (t=-1.96, -0.464, -0.979, all P>0.05). After gastric administration, the platelet counts in the traditional Chinese medicine group[(710.45±124.52)×10⁹/L], hormone group[(768.10±127.42)×10⁹/L], hormone+ traditional Chinese medicine group[(908.05±89.66)×10⁹/L] were significantly higher than that in the model group[(413.55±38.84)×10⁹/L](t=-10.18, -11.90, -22.63, all P<0.01). After gastric administration, there was no statistically significant difference between the traditional Chinese medicine group and the hormone group(t=-1.447, P>0.05). After gastric administration, the platelet count of the hormone+ traditional Chinese medicine group was significantly higher than that of the hormone group and the traditional Chinese medicine group(t=-4.017, -5.759, all P<0.01). There was statistically significant difference in IL-10 level among groups after administration(F=32.20, P<0.01). IL-10 levels between the model group[(20.28±0.75)ng/L] and traditional Chinese medicine group[(21.41±1.40)ng/L], hormone group[(21.79±1.14)ng/L] and traditional Chinese medicine+ hormone group[(23.14±1.34)ng/L] had statistically significant differences (t=-3.18, -4.93, -8.33, all P<0.01). There was no statistically significant difference between the traditional Chinese medicine group and hormone group(t=-0.927, P>0.05). There were statistically significant differences between the traditional Chinese medicine+ hormone group and traditional Chinese medicine group, hormone group (t=-3.97, -3.43, all P<0.01). There was statistically significant difference in TGF-beta level among all groups after administration(F=31.16, P<0.01). The TGF-β levels between the model group[(82.32±3.42)ng/L] and Chinese medicine group[(88.10±8.51)ng/L], hormone group[(90.03±4.50)ng/L] and Chinese medicine combined with hormone group[(94.41±2.53)ng/L] had statistically significant differences (t=-2.82, -6.10, -12.70, all P<0.01). There was no significant difference in TGF-β level between the Chinese medicine group and hormone group(t=-0.90, P>0.05). There were statistically significant differences in in TGF-beta level between the traditional Chinese medicine+ hormone group and Chinese medicine group, hormone group (t=-3.18, -3.79, all P<0.01). Conclusion Yiqi Yangyin Liangxue method can reduce platelet destruction by regulating the levels of IL-10 and TGF-β and inhibiting immunity, and it has good therapeutic effect on ITP.

Objective: To observe the effect of Yiqi Yangyin Liangxue method on peripheral blood platelet count and CD₄⁺ CD₂₅⁺ regulatory T cells(Treg) in mice model of immune thrombocytopenic purpura(ITP). Methods: A total of 100 mice were randomly divided into blank control group, model group, Chinese medicine group, hormone group, Chinese medicine+ hormone group, with 20 mice in each group.In addition to the blank control group, the other four groups were intraperitoneally injected with guinea pig anti-mouse platelet serum(APS) to establish the ITP model.The peripheral blood platelet counts of mice in each group were determined by animal blood analyzer before modeling, before and after gavage, and CD₄⁺ CD₂₅⁺ Treg cells in each group were detected by flow cytometry after gavage. Results: After intragastric administration, compared with the model group, the peripheral blood platelet count of mice in the other groups increased significantly[(413.55±38.84)×10⁹/L, (710.45±124.52)×10⁹/L, (768.10±127.42)×10⁹/L, (908.05±89.66)×10⁹/L, t=-10.18, -11.90, -22.63, all P<0.01], and the proportion of CD₄⁺ CD₂₅⁺ Treg cells in peripheral blood increased significantly[(1.649±0.286)%, (2.000±0.193)%, (2.286±0.271)%, (2.648±1.883)%, t=-4.54, -7.221, -13.031, all P<0.01]. All indicators of the Chinese medicine+ hormone group had statistically significant differences compared with those of the Chinese medicine group and the hormone group(t=-5.759, -4.107, -10.762, -4.902, all P<0.01). Conclusion Yiqi Yangyin Liangxue method may up-regulate the expression of CD₄⁺ CD₂₅⁺ Treg cells in peripheral blood of ITP mice, thereby reducing excessive platelet damage.

Objective To analyze the clinical effects of thrombolytic therapy in patients with ischemic in-hos-pital stroke (IHS). Methods The clinical data were collected from patients with ischemic IHS in the last five years. The patients were divided into thrombolysis group and non-thrombolysis group, according to the use of recombinant tissue plasminogen activator (r-tPA) treatment. The clinical outcomes were measured by the modified Rankin scale (mRS) at discharge. Results There were a total of 121 patients in this study. There were 6 patients in thrombolysis group and 115 patients in the non-thrombolysis group, respectively. Six patients (100%) in the thrombolysis group achieved favor-able outcomes (mRS 0~2) at discharge whereas only 42 patients (36.5%) in the non-thrombolysis group achieved fa-vourable outcomes. The rate of favorable outcomes was significantly higher in the thrombolysis group than in the non-thrombolysis group (P<0.05). Conclusions R-tPA thrombolytic therapy can improve the prognosis of patients with ischemic IHS.