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Omidifar N, Bagheri Lankarani K, Aghazadeh Ghadim MB, Khoshdel N, Joulaei H, Keshani P, Saghi SA, Nikmanesh Y. The Seroprevalence of Hepatitis A in Patients with Positive Human Immunodeficiency Virus. Middle East J Dig Dis 2023; 15:196-202. [PMID: 38023458 PMCID: PMC10660319 DOI: 10.34172/mejdd.2023.344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/04/2023] [Accepted: 06/20/2023] [Indexed: 12/01/2023] Open
Abstract
Background: Hepatitis A virus (HAV) can have severe manifestations in adult patients with other liver diseases, particularly in those infected with human immunodeficiency virus (HIV). This study aimed to measure immunity against HAV in HIV-positive individuals to determine the necessity of vaccination against HAV in this population. Methods: This cross-sectional study investigated 171 HIV-positive patients aged 18 years or older who were tested for serum IgG anti-viral hepatitis A antibody. The prevalence and its determinants were analyzed based on patient data. Results: The average age of the patients was 44.2 years old. The prevalence of HAV antibody positivity was 97.7%. The prevalence was higher in patients older than 30 years. There was a close association between hepatitis C virus (HCV) infection (P=0.002). There were no significant correlations between antibody levels and sex, marital status, employment status, education level, economic status, smoking status, drug use status, and physical activity level. The mean and median CD4+ counts in patients with positive (reactive) antibody (Ab) levels were 458 and 404±294, respectively, while the mean and median CD4+ counts in patients with non-reactive antibody levels were 806 and 737±137, respectively, in those who tested negative for anti-HAV Ab (P=0.05). Conclusion: The prevalence of anti-hepatitis A IgG antibodies in people with HIV was very high in Shiraz. There is an increasing trend in the number of older patients and those with HCV infections. The negative association with CD4 was borderline in this study, which needs to be confirmed in larger groups.
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Affiliation(s)
- Navid Omidifar
- Biotechnology Research Center and Department of Pathology, Medical School, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Kamran Bagheri Lankarani
- Department of Internal Medicine, School of Medicine, Health Policy Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Mir Behrad Aghazadeh Ghadim
- Department of Clinical Biochemistry, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Nika Khoshdel
- Department of Medicine, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Hassan Joulaei
- HIV/AIDS Research Center, Institute of Health, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Parisa Keshani
- HIV/AIDS Research Center, Institute of Health, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Seyyed Amirreza Saghi
- Cellular and Molecular Biology Research Center, Larestan University of Medical Sciences, Larestan, Iran
- Student Research Committee, Larestan University of Medical Sciences, Larestan, Iran
| | - Yousef Nikmanesh
- Gastroenterohepatology Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
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Khatami SH, Karami S, Siahkouhi HR, Taheri-Anganeh M, Fathi J, Aghazadeh Ghadim MB, Taghvimi S, Shabaninejad Z, Tondro G, Karami N, Dolatshah L, Soltani Fard E, Movahedpour A, Darvishi MH. Aptamer-based biosensors for Pseudomonas aeruginosa detection. Mol Cell Probes 2022; 66:101865. [PMID: 36162597 DOI: 10.1016/j.mcp.2022.101865] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 09/20/2022] [Accepted: 09/20/2022] [Indexed: 12/30/2022]
Abstract
Pseudomonas aeruginosa possesses innate antibiotic resistance mechanisms, and carbapenem-resistant Pseudomonas aeruginosa has been considered the number one priority in the 2017 WHO list of antimicrobial-resistant crucial hazards. Early detection of Pseudomonas aeruginosa can circumvent treatment challenges. Various techniques have been developed for the detection of P. aeruginosa detection. Biosensors have recently attracted unprecedented attention in the field of point-of-care diagnostics due to their easy operation, rapid, low cost, high sensitivity, and selectivity. Biosensors can convert the specific interaction between bioreceptors (antibodies, aptamers) and pathogens into optical, electrical, and other signal outputs. Aptamers are novel and promising alternatives to antibodies as biorecognition elements mainly synthesized by systematic evolution of ligands by exponential enrichment and have predictable secondary structures. They have comparable affinity and specificity for binding to their target to antibody recognition. Since 2015, there have been about 2000 journal articles published in the field of aptamer biosensors, of which 30 articles were on the detection of P. aeruginosa. Here, we have focused on outlining the recent progress in the field of aptamer-based biosensors for P. aeruginosa detection based on optical, electrochemical, and piezoelectric signal transduction methods.
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Affiliation(s)
- Seyyed Hossein Khatami
- Department of Clinical Biochemistry, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Sajedeh Karami
- Department of Chemistry, Shiraz University, Shiraz, Iran
| | - Hamid Reza Siahkouhi
- Department of Clinical Sciences, Faculty of Veterinary Medicine, Shahid Bahonar University of Kerman, Kerman, Iran
| | - Mortaza Taheri-Anganeh
- Cellular and Molecular Research Center, Cellular and Molecular Medicine Institute, Urmia University of Medical Sciences, Urmia, Iran
| | - Javad Fathi
- Department of Bacteriology and Virology, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
| | | | - Sina Taghvimi
- Department of Biology, Faculty of Science, Shahid Chamran University of Ahvaz, Ahvaz, Iran
| | - Zahra Shabaninejad
- Department of Nanobiotechnology, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, Iran
| | - Gholamhossein Tondro
- Department of Biotechnology, School of Veterinary Medicine, Shiraz University, Shiraz, Iran
| | - Neda Karami
- TU Wien, Institute of Solid-State Electronics, Vienna A, 1040, Austria
| | - Leila Dolatshah
- Department of Pathology, School of Veterinary Medicine, Shiraz University, Shiraz, Iran
| | - Elahe Soltani Fard
- Department of Molecular Medicine, School of Advanced Technologies, Shahrekord University of Medical Sciences, Shahrekord, Iran
| | | | - Mohammad Hasan Darvishi
- Nanobiotechnology Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran.
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Sisakht M, Bemani P, Ghadim MBA, Rahimi A, Sakhteman A. PyProtModel: An easy to use GUI for comparative protein modeling. J Mol Graph Model 2022; 112:108134. [DOI: 10.1016/j.jmgm.2022.108134] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2021] [Revised: 01/05/2022] [Accepted: 01/11/2022] [Indexed: 11/29/2022]
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