Fakher Rahim
@cihan university-Sulaimaniya/ sulicihan.edu.krd
Health sciences
Fakher Rahim
RESEARCH INTERESTS
Bioinformatics
Global Burden of Disease
Molecular epidemiology
Health economics
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Jaimie D Steinmetz, Katrin Maria Seeher, Nicoline Schiess, Emma Nichols, Bochen Cao, Chiara Servili, Vanessa Cavallera, Ewerton Cousin, Hailey Hagins, Madeline E Moberg,et al.
Elsevier BV
Amir Monfaredan, Fakher Rahim, Gholamreza Tavoosidana, Mohammad Hossein Modarressi, Alaviyehsadat Hosseininasab, Ali-Akbar Aghajani-Afrouzi, Mahdi Shafiee Sabet, and Elahe Motevaseli
LLC Science and Innovations
Background and Aims — Exosomes, which are tiny double-layered membranes originating from eukaryotic cells, have been recognized as a valuable natural vehicle for delivering substances because of their optimal size, compatibility with living organisms, strong structure, ability to carry a large amount of cargo, and capacity to be modified on their surface. Methods — Various strategies have been employed to isolate exosomes due to the challenges associated with maintaining their high purity. The current investigation utilized a soft lithography technique to fabricate channels for exosome separation, incorporating immunoaffinity capabilities. Both biochemical and biophysical assays were conducted to assess the quality of isolated exosomes from various sources (serum, cell supernatant, and urine) and compared with a commercially available kit. Results — The current investigation employed a microfluidic method to capture CD63-conjugated magnetic beads, resulting in a very effective separation of exosomes. Based on the data, there were no notable variations in miRNAs that were statistically significant. This demonstrates that the engineered chip successfully achieved the separation of the exosome while preserving the integrity of its nucleic acid components. Conclusion — The results shown that the current methodology effectively isolated exosomes with a high yield rate, purity, and minimal time requirement. The imatinib laden exosomes demonstrated anticancer efficacy against the KYO-1 cell line in all of their forms.
Nameer Hashim Qasim, Abzal Zhumagaliuly, Rabiga Khozhamkul, and Fakher Rahim
Elsevier BV
Fakher Rahim
Walter de Gruyter GmbH
Mohsen Naghavi, Kanyin Liane Ong, Amirali Aali, Hazim S Ababneh, Yohannes Habtegiorgis Abate, Cristiana Abbafati, Rouzbeh Abbasgholizadeh, Mohammadreza Abbasian, Mohsen Abbasi-Kangevari, Hedayat Abbastabar,et al.
Elsevier BV
Austin E Schumacher, Hmwe Hmwe Kyu, Amirali Aali, Cristiana Abbafati, Jaffar Abbas, Rouzbeh Abbasgholizadeh, Madineh Akram Abbasi, Mohammadreza Abbasian, Samar Abd ElHafeez, Michael Abdelmasseh,et al.
Elsevier BV
N. V. Bhattacharjee, Austin E. Schumacher, Amirali Aali, Yohannes Habtegiorgis Abate, Rouzbeh Abbasgholizadeh, Mohammadreza Abbasian, M. Abbasi-Kangevari, Hedayat Abbastabar, S. ElHafeez, S. Abd-Elsalam,et al.
Jorge R Ledesma, Jianing Ma, Meixin Zhang, Ann V L Basting, Huong Thi Chu, Avina Vongpradith, Amanda Novotney, Kate E LeGrand, Yvonne Yiru Xu, Xiaochen Dai,et al.
Elsevier BV
Fakher Rahim, Toguzbaeva Karlygash, Nameer Hashim Qasim, Fariza Khozhamkul, Kenesh Dzhusupov, Ainur Tekmanova, and Kussaiynova Elmira
Springer Science and Business Media LLC
Mehran Yari, Fakher Rahim, Elham Maraghi, Mahmood Banari, Aliasghar Valipour, Azimeh Karimyan, and Morteza Abdullatif Khafaie
Briefland
Background: Background: Chronic kidney disease (CKD) is defined by a glomerular filtration rate (GFR) or markers of kidney damage persisting for more than 3 months. In Iran, the age-adjusted prevalence of CKD is 14.9%, based on the published literature. It has emerged as a significant health concern associated with morbidity, mortality, and a diminished quality of life. Objectives: The present study aimed to assess the survival rate and its predictors in hemodialysis patients. Methods: The data were collected from teaching hospitals affiliated with Abadan University of Medical Sciences between January 2002 and December 2017. The patient survival period was plotted using Kaplan-Meier survival curves. The Cox regression model was employed to analyze the influence of various variables on the desired time. Results: A total of 389 patients were included in the study. Among them, 79% were married, and 229 (60.1%) were illiterate. The probabilities of 1-, 5-, and 10-year survival of the patients were 0.92, 0.46, and 0.02, respectively. The Cox regression model revealed that the risk of death in hemodialysis patients with hypertension was 1.45 times higher than in those without hypertension. Additionally, factors such as rural residence, older age, using permanent catheters, high serum creatinine, and blood urea nitrogen (BUN) levels increased the adjusted hazard ratio in hemodialysis patients. Conclusions: After adjusting for confounding factors, this study demonstrated a significant association between advancing age, hypertension, using permanent catheters, and reduced survival rates in patients with end-stage renal disease (ESRD).
Sepideh Alavi-Moghadam, Shayesteh Kokabi-Hamidpour, Mostafa Rezaei-Tavirani, Bagher Larijani, Rasta Arjmand, Fakher Rahim, Ahmad Rezazadeh-Mafi, Hossein Adibi, and Babak Arjmand
Springer US
Babak Arjmand, Sepideh Alavi-Moghadam, Mostafa Rezaei-Tavirani, Shayesteh Kokabi-Hamidpour, Rasta Arjmand, Kambiz Gilany, Mohsen Rajaeinejad, Fakher Rahim, Nazli Namazi, and Bagher Larijani
Springer US
Fakher Rahim, Amin Zaki Zadeh, Pouya Javanmardi, Temitope Emmanuel Komolafe, Mohammad Khalafi, Ali Arjomandi, Haniye Alsadat Ghofrani, and Kiarash Shirbandi
Springer Science and Business Media LLC
Abstract Background Osteoporosis is a significant health problem in the skeletal system, associated with bone tissue changes and its strength. Machine Learning (ML), on the other hand, has been accompanied by improvements in recent years and has been in the spotlight. This study is designed to investigate the Diagnostic Test Accuracy (DTA) of ML to detect osteoporosis through the hip dual-energy X-ray absorptiometry (DXA) images. Methods The ISI Web of Science, PubMed, Scopus, Cochrane Library, IEEE Xplore Digital Library, CINAHL, Science Direct, PROSPERO, and EMBASE were systematically searched until June 2023 for studies that tested the diagnostic precision of ML model-assisted for predicting an osteoporosis diagnosis. Results The pooled sensitivity of univariate analysis of seven studies was 0.844 (95% CI 0.791 to 0.885, I2 = 94% for 7 studies). The pooled specificity of univariate analysis was 0.781 (95% CI 0.732 to 0.824, I2 = 98% for 7 studies). The pooled diagnostic odds ratio (DOR) was 18.91 (95% CI 14.22 to 25.14, I2 = 93% for 7 studies). The pooled mean positive likelihood ratio (LR+) and the negative likelihood ratio (LR−) were 3.7 and 0.22, respectively. Also, the summary receiver operating characteristics (sROC) of the bivariate model has an AUC of 0.878. Conclusion Osteoporosis can be diagnosed by ML with acceptable accuracy, and hip fracture prediction was improved via training in an Architecture Learning Network (ALN).
Armin Aryannejad, Sahar Saeedi Moghaddam, Baharnaz Mashinchi, Mohammadreza Tabary, Negar Rezaei, Sarvenaz Shahin, Nazila Rezaei, Mohsen Naghavi, Bagher Larijani, Farshad Farzadfar,et al.
Springer Science and Business Media LLC
Fakher Rahim, Mohammad Khalafi, Mohammad Davoodi, and Kiarash Shirbandi
Springer Science and Business Media LLC
Abstract Background Posterior cingulate cortex (PCC) is a paralimbic cortical structure with a fundamental role in integrative functions of the default mode network (DMN). PCC activation and deactivation of interconnected structures within the medial temporal lobe is essential in memory recall. Aim Assessing the metabolomics content changes in PCC of the patients with Alzheimer’s disease (AD) compared to healthy controls (HC) to find a new method for early AD detection was the primary goal of this study. Methods We performed a comprehensive search through eight international indexing databases. Searches were done using the medical subject headings (Mesh) keywords. Outcome measures included Population (HC/AD), Age (y), Gender (Male/Female), MRI equipment, Tesla (T), MMSE (mean ± SD), absolute and ratio absolutes metabolites in the PCC. All meta-analyses were performed using STATA V.14 tools to provide pooled figures. Results Studies published from 1980 to 2019 using the 1H-NMR technique of 3,067 screened studies, 18 studies comprising 1647 people (658 males and 941 females, 921 HC and 678 AD cases) were included. The results revealed a significant increase in mI content and a substantial decrease in NAA, Glu, and Glx levels of the PCC in AD patients compared to HC. Conclusions Our meta-analysis showed that microstructural disruptions in the PCC could be used as a marker for early AD detection. Although NAA, mI, Glu, and (NAA, Cho, and mI)/Cr biomarkers are substantial metabolites for diagnosis and are most sensitive for diagnosis. Trial registration PROSPERO Registration: CRD42018099325.
Maryam Maleki, Zahra Noorimotlagh, Seyyed Abbas Mirzaee, Neemat Jaafarzadeh, Susana Silva Martinez, Fakher Rahim, and Mohammadreza Kaffashian
Walter de Gruyter GmbH
Abstract Autism spectrum disorder (ASD) increased dramatically over the past 25 years because of genetic and environmental factors. This systematic review (SR) aimed to determine the association between maternal exposure during pregnancy to environmental pesticides and other associations with the risk of ASD progression in children. PubMed (MEDLINE), Scopus (Elsevier) and the Institute for Scientific Information (ISI) Web of Science were searched using appropriate keywords up to March 2021. Twenty-four studies met the inclusion/exclusion criteria and were selected. Most studies reported that ASD increases the risk of offspring after prenatal exposure to environmental pesticides in pregnant mother’s residences, against offspring of women from the same region without this exposure. The main potential mechanisms inducing ASD progressions are ROS and prostaglandin E2 synthesis, AChE inhibition, voltage-gated sodium channel disruption, and GABA inhibition. According to the included studies, the highest rates of ASD diagnosis increased relative to organophosphates, and the application of the most common pesticides near residences might enhance the prevalence of ASD.
Dongze Wu, Yingzhao Jin, Yuhan Xing, Melsew Dagne Abate, Mohammadreza Abbasian, Mohsen Abbasi-Kangevari, Zeinab Abbasi-Kangevari, Foad Abd-Allah, Michael Abdelmasseh, Mohammad-Amin Abdollahifar,et al.
Elsevier BV
William M Gardner, Christian Razo, Theresa A McHugh, Hailey Hagins, Victor M Vilchis-Tella, Conor Hennessy, Heather Jean Taylor, Nandita Perumal, Kia Fuller, Kelly M Cercy,et al.
Elsevier BV
Oleg Zolotarev, Aida Khakimova, Fakher Rahim, Engin Senel, Igor Zatsman, and Dongxiao Gu
Ovid Technologies (Wolters Kluwer Health)
Background: Acne or acne vulgaris is the most common chronic inflammatory disease of the sebaceous follicles. Objectives: The present study aims to identify the main lines of research in the field of acne treatment using reproducible scientometric methods. In this article, we reviewed the following research trends: facial acne, different antibiotics, retinoids, anti-inflammatory drugs, epidermal growth factor receptor inhibitors therapy, and associated diseases. Methods: The analysis of publications from the PubMed collection was carried out from 1871 to 2022. All data were analyzed using Microsoft Excel. The evolution of the terminological portrait of the disease is shown. Results: Trends in the use of various groups of antibiotics, retinoids, anti-inflammatory drugs, and photodynamic therapy for acne treatment have been found. There is a growing interest in clindamycin and doxycycline (polynomial and exponential growth, respectively). The effects of isotretinoin are also being studied more frequently (active linear growth). The publication of studies on spironolactone is increasing (linear growth). There is also a steady interest in the use of epidermal growth factor receptor inhibitors in the recent years. There is active research on acne and polycystic ovary syndrome (exponential growth). Limitations: Only articles in English were selected. The most frequent terms were considered. Conclusions: The dynamics of publication activity in the field of acne was considered. The aim of the current scientometric study was to analyze the global trends in acne treatments. The trend analysis made it possible to identify the most explored areas of research, as well as indicate those areas in dermatology in which interest is declining.
Nematollah Jaafarzadeh, Ali poormohammadi, Halime Almasi, Zeinab Ghaedrahmat, Fakher Rahim, and Amir Zahedi
Walter de Gruyter GmbH
Abstract Object Arsenic as a chemical is found in rock, soil, air and used in various industries and their products, such as colors, hairs, and fertilizers. Humans may be exposed to arsenic mainly through food and drinking water. Due to its adverse health effects, its presence in drinking water has become a public health concern. Methods In this systematic review, we investigated the relationship between arsenic concentration in drinking water and the risk of kidney cancer in humans. For this reason, various electronic databases were searched from 1992 February to November 2021. In this review, three ecological studies, two case-control studies, and four cohort studies were investigated. Results High levels of arsenic (100 μg/L) have been reported in many countries such as southwest Taiwan, Niigata, Argentine, and northern Chile. A significant relationship was observed between kidney cancer incidence and its mortality rate with high arsenic levels in drinking water. Conclusions Despite the limitations in some previous studies, reviewing and comparing the data of different regions indicates a scientific relationship between kidney cancer incidence and high concentrations of arsenic in drinking water.
Sara Momtazmanesh, Sahar Saeedi Moghaddam, Seyyed-Hadi Ghamari, Elaheh Malakan Rad, Negar Rezaei, Parnian Shobeiri, Amirali Aali, Mohsen Abbasi-Kangevari, Zeinab Abbasi-Kangevari, Michael Abdelmasseh,et al.
Elsevier BV
Mohsen Abbasi-Kangevari, Mohammad-Reza Malekpour, Masoud Masinaei, Sahar Saeedi Moghaddam, Seyyed-Hadi Ghamari, Zeinab Abbasi-Kangevari, Negar Rezaei, Nazila Rezaei, Ali H Mokdad, Mohsen Naghavi,et al.
Elsevier BV