- Seroprevalence of Brucellosis in Human Immunodeficiency Virus Infected Patients in Hamadan, Iran
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Fariba Keramat, Mohammad Mehdi Majzobi, Jalal Poorolajal, Zohreh Zarei Ghane, Maryam Adabi
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Osong Public Health Res Perspect. 2017;8(4):282-288. Published online August 31, 2017
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DOI: https://doi.org/10.24171/j.phrp.2017.8.4.09
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3,574
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 Abstract
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- Objectives
Brucellosis is a systemic disease with a wide spectrum of clinical manifestations. This study aimed to determine the seroprevalence of brucellosis in human immunodeficiency virus (HIV) infected patients in Hamadan Province in the west of Iran. MethodsA total of 157 HIV-infected patients were screened through standard serological tests, including Wright’s test, Coombs’ Wright test, and 2-mercaptoethanol Brucella agglutination test (2ME test), blood cultures in Castaneda media, and CD4 counting. Data were analyzed using Stata version 11. ResultsWright and Coombs’ Wright tests were carried out, and only 5 (3.2%) patients had positive serological results. However, all patients had negative 2ME results, and blood cultures were negative for Brucella spp. Moreover, patients with positive serology and a mean CD4 count of 355.8 ± 203.11 cells/μL had no clinical manifestations of brucellosis, and, and the other patients had a mean CD4 count of 335.55 ± 261.71 cells/μL. ConclusionResults of this study showed that HIV infection is not a predisposing factor of acquiring brucellosis.
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Citations
Citations to this article as recorded by  - A case of brucellosis concomitant with HIV infection in China
Shuai-Bing Dong, Li-Ping Wang, Chao-Xue Wu, Fan Li, Yong Yue, Dong-Ri Piao, Hong-Yan Zhao, Hai Jiang
Infectious Diseases of Poverty.2020;[Epub] CrossRef - Investigation of Linc-MAF-4 expression as an effective marker in brucellosis
Reza Gheitasi, Fariba Keramat, Ghasem Solgi, Mehrdad Hajilooi
Molecular Immunology.2020; 123: 60. CrossRef - Human Brucellosis: Risks and Prevalence among Iranian Blood Donors Residing in Endemic Areas
Maryam Zadsar, Mohammad Reza Shirzadi, Mohammad Zeynali, Mahboubeh Rasouli, Gharib Karimi
Transfusion Medicine and Hemotherapy.2020; 47(2): 103. CrossRef - Prevalence and risk factors of brucellosis among febrile patients attending a community hospital in south western Uganda
Richard Migisha, Dan Nyehangane, Yap Boum, Anne-Laure Page, Amaia Zúñiga-Ripa, Raquel Conde-Álvarez, Fred Bagenda, Maryline Bonnet
Scientific Reports.2018;[Epub] CrossRef
- Joint Disease Mapping of Two Digestive Cancers in Golestan Province, Iran Using a Shared Component Model
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Parisa Chamanpara, Abbas Moghimbeigi, Javad Faradmal, Jalal Poorolajal
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Osong Public Health Res Perspect. 2015;6(3):205-210. Published online June 30, 2015
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DOI: https://doi.org/10.1016/j.phrp.2015.02.002
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2,766
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Abstract
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- Objectives
Recent studies have suggested the occurrence patterns and related diet factor of esophagus cancer (EC) and gastric cancer (GC). Incidence of these cancers was mapped either in general and stratified by sex. The aim of this study was to model the geographical variation in incidence of these two related cancers jointly to explore the relative importance of an intended risk factor, diet low in fruit and vegetable intake, in Golestan, Iran.
Methods
Data on the incidence of EC and GC between 2004 and 2008 were extracted from Golestan Research Center of Gastroenterology and Hepatology, Hamadan, Iran. These data were registered as new observations in 11 counties of the province yearly. The Bayesian shared component model was used to analyze the spatial variation of incidence rates jointly and in this study we analyzed the data using this model. Joint modeling improved the precision of estimations of underlying diseases pattern, and thus strengthened the relevant results.
Results
From 2004 to 2008, the joint incidence rates of the two cancers studied were relatively high (0.8–1.2) in the Golestan area. The general map showed that the northern part of the province was at higher risk than the other parts. Thus the component representing diet low in fruit and vegetable intake had larger effect of EC and GC incidence rates in this part. This incidence risk pattern was retained for female but for male was a little different.
Conclusion
Using a shared component model for joint modeling of incidence rates leads to more precise estimates, so the common risk factor, a diet low in fruit and vegetables, is important in this area and needs more attention in the allocation and delivery of public health policies.
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Citations
Citations to this article as recorded by
- Predicting 5-Year Survival Status of Patients with Breast Cancer based on Supervised Wavelet Method
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Maryam Farhadian, Hossein Mahjub, Jalal Poorolajal, Abbas Moghimbeigi, Muharram Mansoorizadeh
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Osong Public Health Res Perspect. 2014;5(6):324-332. Published online December 31, 2014
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DOI: https://doi.org/10.1016/j.phrp.2014.09.002
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2,664
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Classification of breast cancer patients into different risk classes is very important in clinical applications. It is estimated that the advent of high-dimensional gene expression data could improve patient classification. In this study, a new method for transforming the high-dimensional gene expression data in a low-dimensional space based on wavelet transform (WT) is presented.
Methods
The proposed method was applied to three publicly available microarray data sets. After dimensionality reduction using supervised wavelet, a predictive support vector machine (SVM) model was built upon the reduced dimensional space. In addition, the proposed method was compared with the supervised principal component analysis (PCA).
Results
The performance of supervised wavelet and supervised PCA based on selected genes were better than the signature genes identified in the other studies. Furthermore, the supervised wavelet method generally performed better than the supervised PCA for predicting the 5-year survival status of patients with breast cancer based on microarray data. In addition, the proposed method had a relatively acceptable performance compared with the other studies.
Conclusion
The results suggest the possibility of developing a new tool using wavelets for the dimension reduction of microarray data sets in the classification framework.
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Citations
Citations to this article as recorded by - Diagnosing thyroid disorders: Comparison of logistic regression and neural network models
Shiva Borzouei, Hossein Mahjub, NegarAsaad Sajadi, Maryam Farhadian
Journal of Family Medicine and Primary Care.2020; 9(3): 1470. CrossRef - Thyroid disorder diagnosis based on Mamdani fuzzy inference system classifier
Negar Asaad Sajadi, Hossein Mahjub, Shiva Borzouei, Maryam Farhadian
Koomesh Journal.2020; 22(1): 107. CrossRef - Diagnosis of hypothyroidism using a fuzzy rule-based expert system
Negar Asaad Sajadi, Shiva Borzouei, Hossein Mahjub, Maryam Farhadian
Clinical Epidemiology and Global Health.2019; 7(4): 519. CrossRef - WaveICA: A novel algorithm to remove batch effects for large-scale untargeted metabolomics data based on wavelet analysis
Kui Deng, Fan Zhang, Qilong Tan, Yue Huang, Wei Song, Zhiwei Rong, Zheng-Jiang Zhu, Kang Li, Zhenzi Li
Analytica Chimica Acta.2019; 1061: 60. CrossRef
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