1.Pulmonary anaplastic lymphoma kinase positive histiocytosis: report of a case.
W M XU ; Z R GAO ; X LI ; Y JIANG ; Q FENG ; L W RUAN ; Y Y WANG
Chinese Journal of Pathology 2023;52(11):1168-1170
2.Comparative untargeted proteomic analysis of ADME proteins and tumor antigens for tumor cell lines.
Xiaomei GU ; Qing XIAO ; Qian RUAN ; Yuezhong SHU ; Ashok DONGRE ; Ramaswamy IYER ; W Griffith HUMPHREYS ; Yurong LAI
Acta Pharmaceutica Sinica B 2018;8(2):252-260
In the present study, total membrane proteins from tumor cell lines including HepG2, Hep3B2, H226, Ovcar3 and N87 were extracted and digested with LysC and trypsin. The resulting peptide lysate were pre-fractionated and subjected to untargeted quantitative proteomics analysis using a high resolution mass spectrometer. The mass spectra were processed by the MaxQuant and the protein abundances were estimated using total peak area (TPA) method. A total of 6037 proteins were identified, and the analysis resulted in the identification of 2647 membrane proteins. Of those, tumor antigens and absorption, metabolism, disposition and elimination (ADME) proteins including UDP-glucuronosyltransferase, cytochrome P450, solute carriers and ATP-binding cassette transporters were detected and disclosed significant variations among the cell lines. The principal component analysis was performed for the cluster of cell lines. The results demonstrated that H226 is closely related with N87, while Hep3B2 aligned with HepG2. The protein cluster of Ovcar3 was apart from that of other cell lines investigated. By providing for the first time quantitative untargeted proteomics analysis, the results delineated the expression profiles of membrane proteins. These findings provided a useful resource for selecting targets of choice for anticancer therapy through advancing data obtained from preclinical tumor cell line models to clinical outcomes.
3.Effect of baseline CD(4)(+) T cell count on drop-out of antiretroviral therapy in HIV infected persons in Guangxi Zhuang Autonomous Region, 2008-2015.
X H LIU ; Q Y ZHU ; J M SU ; Q MENG ; X J ZHOU ; Z Y SHEN ; Z Z TANG ; W M YANG ; Y H RUAN ; Y M SHAO
Chinese Journal of Epidemiology 2018;39(9):1216-1221
Objective: To investigate the effect of baseline CD(4)(+) T cell count (CD(4)) on drop-out of antiretroviral therapy (ART) in HIV infected persons. Methods: Retrospective cohort was conducted in this study. HIV infected persons aged≥18 years and receiving free ART for the first time in Guangxi Zhuang Autonomous Region (Guangxi) from 2008 to 2015 were selected from the antiretroviral treatment database of National Comprehensive HIV/AIDS Information System, with follow-up conducted till May 30, 2016. Cause-specific Cox proportional hazard models were used to evaluate effect of different CD(4) on the drop-out of ART in the HIV infected persons. Results: A total of 58 502 eligible study participants were included in this retrospective cohort study. The average drop-out ratio was 4.8/100 person-years. After controlling the following baseline covariates: age, sex, marital status, route of HIV infection, WHO clinical stage before ART, initial/current ART regiment, ART regiment adjustment, and year of initiating ART for potential confounding, the adjusted HR of drop-out for HIV infected persons with 200- cells/μl, 351-cells/μl and ≥500 cells/μl were 1.110 (95%CI: 1.053-1.171, P<0.001), 1.391 (95%CI: 1.278-1.514, P<0.001) and 1.695 (95%CI: 1.497-1.918, P<0.001), respectively, in risk for drop-out compared with those with baseline CD(4)<200 cells/μl. Among the HIV infected persons, 56.0% (1 601/2 861) of drug withdrawal was due to poor compliance with medication. Conclusions: With the increase of baseline CD(4) when initiating ART, the risk for the drop-out in HIV infected persons increased significantly. To further reduce the drop-out of ART, it is important to take CD(4) into account in initiating ART and to strengthen the health education on treatment compliancy and training for healthcare providers.
Adolescent
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Anti-Retroviral Agents/administration & dosage*
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CD4 Lymphocyte Count
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China/epidemiology*
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HIV
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HIV Infections/virology*
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Humans
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Incidence
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Medication Adherence
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Retrospective Studies
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T-Lymphocytes
4.Impact of COVID-19 pandemic on the management of imported malaria in China.
Y LIU ; D WANG ; Z HE ; T ZHANG ; H YAN ; W LIN ; X ZHANG ; S LU ; Y LIU ; D WANG ; J LI ; W RUAN ; S LI ; H ZHANG
Chinese Journal of Schistosomiasis Control 2023;35(4):383-388
OBJECTIVE:
To examine the impact of COVID-19 pandemic on the epidemic status of imported malaria and national malaria control program in China, so as to provide insights into post-elimination malaria surveillance.
METHODS:
All data pertaining to imported malaria cases were collected from Anhui Province, Hubei Province, Henan Province, Zhejiang Province and Guangxi Zhuang Autonomous Region during the period from January 1, 2018 through December 31, 2021. The number of malaria cases, species of malaria parasites, country where malaria parasite were infected, diagnosis and treatment after returning to China, and response were compared before (from January 1, 2018 to January 22, 2020) and after the COVID-19 pandemic (from January 23, 2020 to December 31, 2021).
RESULTS:
A total of 2 054 imported malaria cases were reported in Anhui Province, Hubei Province, Henan Province, Zhejiang Province and Guangxi Zhuang Autonomous Region during the period from January 1, 2018 to December 31, 2021, and there were 1 722 cases and 332 cases reported before and after the COVID-19 pandemic, respectively. All cases were reported within one day after definitive diagnosis. The annual mean number of reported malaria cases reduced by 79.30% in Anhui Province, Hubei Province, Henan Province, Zhejiang Province and Guangxi Zhuang Autonomous Region after the COVID-19 pandemic (171 cases) than before the pandemic (826 cases), and the number of monthly reported malaria cases significantly reduced in Anhui Province, Hubei Province, Henan Province, Zhejiang Province and Guangxi Zhuang Autonomous Region since February 2020. There was a significant difference in the constituent ratio of species of malaria parasites among the imported malaria cases in Anhui Province, Hubei Province, Henan Province, Zhejiang Province and Guangxi Zhuang Autonomous Region before and after the COVID-19 pandemic (χ2 = 146.70, P < 0.05), and P. falciparum malaria was predominant before the COVID-19 pandemic (72.30%), while P. ovale malaria (44.28%) was predominant after the COVID-19 pandemic, followed by P. falciparum malaria (37.65%). There was a significant difference in the constituent ratio of country where malaria parasites were infected among imported malaria cases in Anhui Province, Hubei Province, Henan Province, Zhejiang Province and Guangxi Zhuang Autonomous Region before and after the COVID-19 pandemic (χ2 = 13.83, P < 0.05), and the proportion of malaria cases that acquired Plasmodium infections in western Africa reduced after the COVID-19 pandemic that before the pandemic (44.13% vs. 37.95%; χ2 = 4.34, P < 0.05), while the proportion of malaria cases that acquired Plasmodium infections in eastern Africa increased after the COVID-19 pandemic that before the pandemic (9.58% vs. 15.36%; χ2 = 9.88, P = 0.02). The proportion of completing case investigation within 3 days was significantly lower after the COVID-19 pandemic than before the pandemic (96.69% vs. 98.32%; χ2= 3.87, P < 0.05), while the proportion of finishing foci investigation and response within 7 days was significantly higher after the COVID-19 pandemic than before the pandemic (100.00% vs. 98.43%; χ2 = 3.95, P < 0.05).
CONCLUSIONS
The number of imported malaria cases remarkably reduced in Anhui Province, Hubei Province, Henan Province, Zhejiang Province and Guangxi Zhuang Autonomous Region of China during the COVID-19 pandemic, with a decreased proportion of completing case investigations within 3 days. The sensitivity of the malaria surveillance-response system requires to be improved to prevent the risk of secondary transmission of malaria due to the sharp increase in the number of imported malaria cases following the change of the COVID-19 containment policy.
Humans
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Pandemics
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China/epidemiology*
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Incidence
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COVID-19/epidemiology*
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Malaria/prevention & control*
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Malaria, Falciparum/epidemiology*
5.Incidence of fall related injury in people aged 50 and above and risk factors in 8 provinces in China: a cross-sectional study.
Y F GUO ; W J MA ; Q J ZHANG ; M YU ; Y Z XIAO ; X L GUO ; Y L ZHU ; F LIU ; Y RUAN ; S Y SUN ; Z Z HUANG ; Y ZHENG ; F WU
Chinese Journal of Epidemiology 2018;39(3):258-263
Objective: To estimate the incidence and distribution characteristics of fall related injury in people aged ≥50 years in 8 provinces in China and related physiological, psychological and social risk factors. Methods: Cross-sectional data were collected from adults aged ≥50 years participating in the World Health Organization (WHO) study on global ageing and adult health (SAGE) round 1 in China. Two-level hierarchical logistic model was used to identify the related factors for fall-related injury. All the models were stratified by living area (urban/rural). Results: Estimated incidence of fall related injury (road traffic injury was not included) was 3.2%. Ageing and multiple chronic conditions (OR=2.55, 95%CI: 1.41-4.64) was significantly associated with the incidence of fall related injury in urban area. In rural area, depression (OR=4.33, 95% CI: 2.52-7.42) and multiple chronic conditions (OR=2.46, 95%CI: 1.37-4.41) were associated with the incidence of fall related injury. Conclusions: This study estimated the incidence of fall related injury in adults aged ≥50 years in 8 provinces in China. A significant association between multiple chronic conditions and fall related injury were found in both urban and rural residents. Targeted measures should be taken for the prevention and control of chronic diseases in elderly population.
Accidental Falls/statistics & numerical data*
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Aged
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China
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Chronic Disease/epidemiology*
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Cross-Sectional Studies
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Depression/epidemiology*
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Humans
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Incidence
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Logistic Models
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Middle Aged
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Risk Factors
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Rural Population
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Wounds and Injuries/etiology*