Publications by authors named "Mohammad Zangooei"

11 Publications

  • Page 1 of 1

Handling of uncertainty in medical data using machine learning and probability theory techniques: a review of 30 years (1991-2020).

Ann Oper Res 2021 Mar 21:1-42. Epub 2021 Mar 21.

Department of Electronics and Computer Engineering, Ngee Ann Polytechnic, Singapore, Singapore.

Understanding the data and reaching accurate conclusions are of paramount importance in the present era of big data. Machine learning and probability theory methods have been widely used for this purpose in various fields. One critically important yet less explored aspect is capturing and analyzing uncertainties in the data and model. Proper quantification of uncertainty helps to provide valuable information to obtain accurate diagnosis. This paper reviewed related studies conducted in the last 30 years (from 1991 to 2020) in handling uncertainties in medical data using probability theory and machine learning techniques. Medical data is more prone to uncertainty due to the presence of noise in the data. So, it is very important to have clean medical data without any noise to get accurate diagnosis. The sources of noise in the medical data need to be known to address this issue. Based on the medical data obtained by the physician, diagnosis of disease, and treatment plan are prescribed. Hence, the uncertainty is growing in healthcare and there is limited knowledge to address these problems. Our findings indicate that there are few challenges to be addressed in handling the uncertainty in medical raw data and new models. In this work, we have summarized various methods employed to overcome this problem. Nowadays, various novel deep learning techniques have been proposed to deal with such uncertainties and improve the performance in decision making.
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http://dx.doi.org/10.1007/s10479-021-04006-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7982279PMC
March 2021

MicroRNA-494 induces breast cancer cell apoptosis and reduces cell viability by inhibition of nicotinamide phosphoribosyltransferase expression and activity.

EXCLI J 2019 12;18:838-851. Epub 2019 Sep 12.

Department of Biochemistry, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran.

Breast cancer (BC) is the most prevalent cause of cancer-related death in women worldwide. BC is frequently associated with elevated levels of nicotinamide phosphoribosyltransferase (NAMPT) in blood and tumor tissue. MicroRNA-494 (miR-494) has been described to play key anti-tumor roles in human cancers. The aim of the present study was to investigate the inhibitory effect of miR-494 on NAMPT-mediated viability of BC cells. In this experimental study, MCF-7 and MDA-MB-231 cells were cultured and then transfected with miR-494 mimic, miR-494 inhibitor and their negative controls. The mRNA and protein expression of NAMPT were assessed using real-time PCR and Western blotting, respectively. Subsequently, intracellular NAD levels were determined by a colorimetric method. Finally, cell apoptosis was examined by flow cytometry. Bioinformatics evaluations predicted NAMPT as a miR-494 target gene which was confirmed by luciferase reporter assay. Our results showed an inverse relationship between the expression of miR-494 and NAMPT in both MCF-7 and MDA-MB-231 cell lines. miR-494 significantly down-regulated NAMPT mRNA and protein expression and was also able to reduce the cellular NAD content. Cell viability was decreased following miR-494 up-regulation. In addition, apoptosis was induced in MCF-7 and MDA-MB-231 cells by miR-494 mimic. Our findings indicate that miR-494 acts as a tumor suppressor and has an important effect in suppressing the growth of BC cells through NAMPT. Therefore, miR-494 might be considered as a novel therapeutic target for the management of human breast cancer.
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http://dx.doi.org/10.17179/excli2018-1748DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6806255PMC
September 2019

Hesperetin is a potent bioactivator that activates SIRT1-AMPK signaling pathway in HepG2 cells.

J Physiol Biochem 2019 Jun 15;75(2):125-133. Epub 2019 May 15.

Department of Clinical Biochemistry, School of Medicine, Iran University of Medical Sciences, Tehran, Iran.

Sirtuin 1 (SIRT1) is a deacetylase enzyme that plays crucial roles in controlling many cellular processes and its downregulation has been implicated in different metabolic disorders. Recently, several polyphenols have been considered as the effective therapeutic approaches that appear to influence SIRT1. The main goal of this study was to evaluate the effect of hesperetin, a citrus polyphenolic flavonoid, on SIRT1 and AMP-activated kinase (AMPK). HepG2 cells were treated with hesperetin in the presence or absence of EX-527, a SIRT1 specific inhibitor, for 24 h. Resveratrol was used as a positive control. SIRT1 gene expression, protein level, and activity were measured by RT-PCR, Western blotting, and fluorometric assay, respectively. AMPK phosphorylation was also determined by Western blotting. Our results indicated a significant increase in SIRT1 protein level and activity as well as an induction of AMPK phosphorylation by hesperetin. These effects of hesperetin were abolished by EX-527. Furthermore, hesperetin reversed the EX-527 inhibitory effects on SIRT1 protein expression and AMPK phosphorylation. These findings suggest that hesperetin can be a novel SIRT1 activator, even stronger than resveratrol. Therefore, the current study may introduce hesperetin as a new strategy aimed at upregulation SIRT1-AMPK pathway resulting in various cellular processes regulation.
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http://dx.doi.org/10.1007/s13105-019-00678-4DOI Listing
June 2019

Signaling Crosstalk of FHIT, p53, and p38 in etoposide-induced apoptosis in MCF-7 cells.

J Cell Biochem 2019 06 4;120(6):9125-9137. Epub 2019 Jan 4.

Department of Toxicology Pharmacology, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran.

Fragile histidine trail (FHIT) is a tumor suppressor in response to DNA damage which has been deleted in various tumors. However, the signaling mechanisms and interactions of FHIT with regard to apoptotic proteins including p53 and p38 in the DNA damage-induced apoptosis are not well described. In the present study, we used etoposide-induced DNA damage in MCF-7 as a model to address these crosstalks. The time course study showed that the expression of FHIT, p53, and p38MAPK started after 1 hour following etoposide treatment. FHIT overexpression led to increase p53 expression, p38 activation, and augmented apoptosis following etoposide-induced DNA damage compared to wild-type cells. However, FHIT knockdown blocked p53 expression, delayed p38 activation, and completely inhibited etoposide-induced apoptosis. Inhibition of p38 activity prevented induction of p53, FHIT, and apoptosis in this model. Thus, activation of p38 upon etoposide treatment leads to increase in FHIT and p53 expression. In p53 knockdown MCF-7, the FHIT induction was hampered but p38 activation was induced in lower doses of etoposide. In p53 knockdown cells, inhibition of p38 induced FHIT expression and apoptosis. Our data demonstrated that the exposure of MCF-7 cells to etoposide increases apoptosis through a mechanism involving the activation of the p38-FHIT-p53 pathway. Moreover, our findings suggest signaling interaction for these pathways may represent a promising therapy for breast cancer.
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http://dx.doi.org/10.1002/jcb.28188DOI Listing
June 2019

Invasion and migration of MDA-MB-231 cells are inhibited by block of AhR and NFAT: role of AhR/NFAT1/β4 integrin signaling.

J Appl Toxicol 2019 02 7;39(2):375-384. Epub 2018 Oct 7.

Department of Toxicology and Pharmacology, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran.

Benzo[α]pyrene (BaP) can have significant role in the development of breast cancer via aryl hydrocarbon receptor (AhR) activation. AhR activation has been studied in several functions such as survival, migration and invasion of cancer cells. In cancer, integrins contribute to the migration/invasion process and are regulated by nuclear factor of activated T cells (NFAT) and transforming growth factor (TGF) beta pathways. The aim of the present study was to examine the effect of BaP, an activator of AhR and cyclosporine A (CsA), as inhibitor of NFAT on migration and invasion of MDA-MB-231 cells. Furthermore, the effects of BaP and CsA were evaluated regarding the crosstalk of AhR, NFAT1 and TGF-β receptor 1 signaling. Treatment of MDA-MB-231 with BaP resulted in significantly more live cells in low doses; however, blocking NFAT with CsA decreased the viability of the cells. Activation of AhR by BaP induced invasion as well as migration in MDA-MB-231 cells, which was blocked by AhR antagonist. Unlike BaP, block of NFAT with CsA inhibited cell migration and cell invasion. In these cells, BaP significantly reduced AhR expression while this reduction was reversed by CH-223191; however, CsA treatment lowered the AhR expression only at low dose. The level of β4 integrin was significantly reduced by CsA at 1 and 2.5 μm. Protein levels of Snail and TGF-β receptor 1 were not significantly altered by BaP and CsA treatments. Considering these findings, the low AhR expression and high β4 integrin level following BaP and/or CsA treatments may contribute to the higher invasion/migration in MDA-MB-231 cells.
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http://dx.doi.org/10.1002/jat.3728DOI Listing
February 2019

Investigating the effect of visfatin on ERalpha phosphorylation (Ser118 and Ser167) and ERE-dependent transcriptional activity.

EXCLI J 2018 4;17:516-525. Epub 2018 Jun 4.

Department of Biochemistry, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran.

Obesity is associated with higher postmenopausal breast cancer incidence. Visfatin level alteration is one of the mechanisms by which obesity promotes cancer. Ligand-independent activation of estrogen receptor alpha (ERα) is also associated with carcinogenesis. The activity of ERα is modulated through phosphorylation on multiple sites by a number of protein kinases. Here we investigated the effect of visfatin as a novel adipocytokine on the phosphorylation and activity of ERα in MCF-7 breast cancer cells. We showed that exogenous administration of visfatin significantly increased the phosphorylation of ERα at serine 118 (Ser118) and 167 (Ser167) residues. Visfatin-induced Ser118 phosphorylation was diminished after treatment of cells with U0126 (MEK1/2 inhibitor). Furthermore, our results showed that visfatin-induced Ser167 phosphorylation is mediated through both MAPK and PI3K/Akt signaling pathways. Inhibition of the enzymatic activity of visfatin by FK866 had no effect on phosphorylation of ERα. We also showed that visfatin enhanced the estrogen response element (ERE)-dependent activity of ER in the presence of 17-β estradiol (E2). Additional study on T47D cells showed that visfatin also increased Ser118 and Ser167 phosphorylation of ERα and enhanced ERE-dependent activity in the presence of E2 in these cells.
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http://dx.doi.org/10.17179/excli2018-1299DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6046625PMC
June 2018

Hybrid multiscale modeling and prediction of cancer cell behavior.

PLoS One 2017 28;12(8):e0183810. Epub 2017 Aug 28.

Department of Computer Engineering, Sharif University of Technology, Tehran, Iran.

Background: Understanding cancer development crossing several spatial-temporal scales is of great practical significance to better understand and treat cancers. It is difficult to tackle this challenge with pure biological means. Moreover, hybrid modeling techniques have been proposed that combine the advantages of the continuum and the discrete methods to model multiscale problems.

Methods: In light of these problems, we have proposed a new hybrid vascular model to facilitate the multiscale modeling and simulation of cancer development with respect to the agent-based, cellular automata and machine learning methods. The purpose of this simulation is to create a dataset that can be used for prediction of cell phenotypes. By using a proposed Q-learning based on SVR-NSGA-II method, the cells have the capability to predict their phenotypes autonomously that is, to act on its own without external direction in response to situations it encounters.

Results: Computational simulations of the model were performed in order to analyze its performance. The most striking feature of our results is that each cell can select its phenotype at each time step according to its condition. We provide evidence that the prediction of cell phenotypes is reliable.

Conclusion: Our proposed model, which we term a hybrid multiscale modeling of cancer cell behavior, has the potential to combine the best features of both continuum and discrete models. The in silico results indicate that the 3D model can represent key features of cancer growth, angiogenesis, and its related micro-environment and show that the findings are in good agreement with biological tumor behavior. To the best of our knowledge, this paper is the first hybrid vascular multiscale modeling of cancer cell behavior that has the capability to predict cell phenotypes individually by a self-generated dataset.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0183810PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5573302PMC
October 2017

Integrating evolutionary game theory into an agent-based model of ductal carcinoma in situ: Role of gap junctions in cancer progression.

Comput Methods Programs Biomed 2016 Nov 24;136:107-17. Epub 2016 Aug 24.

Software Engineering, Department of Computer Engineering, Sharif University of Technology, Azadi Avenue, Tehran, Iran.

Background And Objective: There are many cells with various phenotypic behaviors in cancer interacting with each other. For example, an apoptotic cell may induce apoptosis in adjacent cells. A living cell can also protect cells from undergoing apoptosis and necrosis. These survival and death signals are propagated through interaction pathways between adjacent cells called gap junctions. The function of these signals depends on the cellular context of the cell receiving them. For instance, a receiver cell experiencing a low level of oxygen may interpret a received survival signal as an apoptosis signal. In this study, we examine the effect of these signals on tumor growth.

Methods: We make an evolutionary game theory component in order to model the signal propagation through gap junctions. The game payoffs are defined as a function of cellular context. Then, the game theory component is integrated into an agent-based model of tumor growth. After that, the integrated model is applied to ductal carcinoma in situ, a type of early stage breast cancer. Different scenarios are explored to observe the impact of the gap junction communication and parameters of the game theory component on cancer progression. We compare these scenarios by using the Wilcoxon signed-rank test.

Results: The Wilcoxon signed-rank test succeeds in proving a significant difference between the tumor growth of the model before and after considering the gap junction communication. The Wilcoxon signed-rank test also proves that the tumor growth significantly depends on the oxygen threshold of turning survival signals into apoptosis.

Conclusions: In this study, the gap junction communication is modeled by using evolutionary game theory to illustrate its role at early stage cancers such as ductal carcinoma in situ. This work indicates that the gap junction communication and the oxygen threshold of turning survival signals into apoptosis can notably affect cancer progression.
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http://dx.doi.org/10.1016/j.cmpb.2016.08.011DOI Listing
November 2016

The Preventive Effect of L-Lysine on Lysozyme Glycation in Type 2 Diabetes.

Acta Med Iran 2016 Jan;54(1):24-31

Department of Clinical Biochemistry, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.

Lysozyme is a bactericidal enzyme whose structure and functions change in diabetes. Chemical chaperones are small molecules including polyamines (e.g. spermine), amino acids (e.g. L-lysine) and polyols (e.g. glycerol). They can improve protein conformation in several stressful conditions such as glycation. In this study, the authors aimed to observe the effect of L-lysine as a chemical chaperone on structure and function of glycated lysozyme. In this study, in vitro and in vivo effects of L-lysine on lysozyme glycation were investigated. Lysozyme was incubated with glucose and/or L-lysine, followed by an investigation of its structure by electrophoresis, fluorescence spectroscopy, and circular dichroism spectroscopy and also assessment of its bactericidal activity against M. lysodeikticus. In the clinical trial, patients with type 2 diabetes mellitus (T2DM) were randomly divided into two groups of 25 (test and control). All patients received metformin and glibenclamide for a three months period. The test group was supplemented with 3 g/day of L-lysine. The quantity and activity of lysozyme and other parameters were then measured. Among the test group, L-lysine was found to reduce the advanced glycation end products (AGEs) in the sera of patients with T2DM and in vitro condition. This chemical chaperone reversed the alteration in lysozyme structure and function due to glycation and resulted in increased lysozyme activity. Structure and function of glycated lysozyme are significantly improved by l-lysine; therefore it can be considered an effective therapeutic supplementation in T2DM, decreasing the risk of infection in these patients.
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January 2016

Protein fold recognition with a two-layer method based on SVM-SA, WP-NN and C4.5 (TLM-SNC).

Int J Data Min Bioinform 2013 ;8(2):203-23

SCS Lab, Computer Engineering Department, Electrical and Computer Engineering Faculty, Tarbiat Modares University, Tehran, Iran.

The structural knowledge of protein is crucial in understanding its biological role. An effort is made to assign a fold to a given protein in a protein fold recognition problem. A computational Two-Layer Method (TLM) based on the Support Vector Machine (SVM), the Neural Network (NN) and the Decision Tree (C4.5) has been developed in this study for the assignment of a protein sequence to a folding class in SCOP. Prediction accuracy is measured on a dataset and the accuracy of the proposed method is very promising in comparison with other classification methods.
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http://dx.doi.org/10.1504/ijdmb.2013.055507DOI Listing
March 2014

Hepatitis disease diagnosis using a novel hybrid method based on support vector machine and simulated annealing (SVM-SA).

Comput Methods Programs Biomed 2012 Nov 2;108(2):570-9. Epub 2011 Oct 2.

SCS Lab, Electrical and Computer Engineering Department, Tarbiat Modares University, Terhran, Iran.

In this study, diagnosis of hepatitis disease, which is a very common and important disease, is conducted with a machine learning method. We have proposed a novel machine learning method that hybridizes support vector machine (SVM) and simulated annealing (SA). Simulated annealing is a stochastic method currently in wide use for difficult optimization problems. Intensively explored support vector machine due to its several unique advantages is successfully verified as a predicting method in recent years. We take the dataset used in our study from the UCI machine learning database. The classification accuracy is obtained via 10-fold cross validation. The obtained classification accuracy of our method is 96.25% and it is very promising with regard to the other classification methods in the literature for this problem.
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http://dx.doi.org/10.1016/j.cmpb.2011.08.003DOI Listing
November 2012
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