فهرست مطالب nasrin amiri dash atan

Ferroptosis, an oxidative and iron-dependent cell death, is a new type of regulated cell death. There are few studies on the mechanisms of ferroptosis in the skin and related diseases. Arsenic is shown to induce ferroptosis cell death. This study aimed to decipher the relationship between arsenic exposure and ferroptosis cell death in the skin.

Arsenic-gene interactions were obtained. Then, skin-specific arsenic-gene interactions were screened. Ferroptosis-related genes were identified. Analysis of functional and biological interactions was performed to identify possible mechanisms.

The arsenic-gene interactions and the ferroptosis-related genes showed an overlap of 59 genes. Functional enrichment, protein-protein interaction, and transcription factor (TF)/miRNA target gene interaction analyses were used to look into the mechanism of arsenic-induced ferroptosis in the skin. ACTB, CTNNB1, HSPA8, SRC, RACK1, CD44, and SQSTM1were identified as key proteins. Gene ontology analysis of these proteins indicated the mitochondrial morphology and functionality changes following arsenic-induced ferroptosis in the skin. HIF1A and SP1 TFs regulate a large number of genes compared to other TFs. Ten miRNAs with high interaction with ferroptosis-associated genes were identified.

This work investigated the mechanism of arsenic-induced ferroptosis in the skin and identified key genes and regulators, and functional analysis highlighted the role of mitochondria in this skin exposure

Bisphenol A (BPA), an endocrine disruptor, is associated with metabolic disorders. However, several studies have suggested that exposure to BPA can cause obesity. It has recently got more attention from scientists as a risk factor for obesity due to its ability to mimic natural estrogens and bind to their receptors. Nonetheless, the molecular mechanism underpinning the environmental etiology of metabolic disorders has not been not fully clarified. In this regard, BPA exposure directly disrupts endocrine regulation, neuroimmune and signaling pathways, and gut microbes, resulting in obesity. In addition, epidemiological studies have revealed a significant relationship between BPA exposure and the development of obesity, although conflicting results have been reported. Therefore, this review summarized the possible role and molecular mechanisms associated with BPA exposure that may lead to obesity based on in vivo and in vivo studies.

 Leishmaniasis is among the seven more significant tropical diseases, and it is a major global health issue with a wide range of clinical symptoms and potentially lethal consequences. Resveratrol and its derivatives have been shown to have anti-Leishmanial properties. This study aimed to use a meta-analysis of relevant papers to determine the leishmanicidal impact of resveratrol and its derivatives.

 A comprehensive search method was used to query the electronic databases of PubMed, ScienceDirect, Embase, ISI Web of Science, and Scopus up until June 2021. The articles that met the inclusion criteria were chosen. Random-effects models were used to calculate mean differences in IC50 (concentration corresponding to a 50% reduction in Leishmania) for each outcome. The Newcastle-Ottawa Scale was used to assess the quality of the evidence. To assess heterogeneity and the stability of the pooled data, sensitivity and subgroup analyses were performed. The Egger's and Begg's tests were used to assess publication bias.

 In the meta-analysis, nine studies were considered. Resveratrol (RSV) and its derivatives significantly reduced survivability in Leishmania promastigote [24.02 mg/ml; (95% CI 17.1, 30.8); P<0.05; I2 = 99.8%; P Heterogeneity = 0.00] and amastigote [18.3 mg/ml; (95% CI 13.5, 23.2); P<0.05; I2 = 99.6%; P Heterogeneity= 0.00]. The meta-analysis revealed a considerable publication bias. Sensitivity analyses revealed that the effect magnitude was similar, but the heterogeneity was reduced. According to subgroup analysis, the pooled effect sizes of leishmanicidal resveratrol and its derivatives were altered by the kind of stilbenes and Leishmania species.

 According to the findings of this meta-analysis, RSV and its derivatives could be a possible therapeutic option for leishmaniasis. However, more research is needed to confirm and employ this chemical against Leishmania.

This meta-analysis was designed to reassess the prognostic and clinicopathologic values of the microRNA-125 family in GC patients.

The miR-125 family (including miR-125a, miR-125b) has been reported as being pivotal prognostic biomarkers of gastric cancer (GC). However, there is controversy about the role of the miR-125 family in predicting the progression of GC.

The miR-125 family (including miR-125a, miR-125b) has been reported as being pivotal prognostic biomarkers of gastric cancer (GC). However, there is controversy about the role of the miR-125 family in predicting the progression of GC.

The electronic databases of PubMed, ISI Web of Science, Scopus, and Cochrane Library were systematically searched for relevant studies. Overall survival (OS) rate as the primary outcome from each study was extracted. The overall hazard ratio (HR or survival rate in patients with GC) and odds ratio (OR) with 95% confidence interval (CI) was calculated to evaluate the association between miR-125 family expression and prognosis and susceptibility to gastric cancer. The quality of evidence was evaluated using the Newcastle-Ottava Scale (NOS). The extracted data was combined based on the random-effects model.

The low expression of miR-125 family predicts poor OS in GC patients. Thus, the miR-125 family may be helpful as a potential biomarker for the prognosis of gastric cancer.

Leishmaniasis is one of the most important infectious diseases caused by different species of the Leishmania, which is a public health problem worldwide. So far, no effective vaccine is introduced for this disease and drug therapy is associated with many side effects. Therefore, this study was designed to identify novel FDA-approved compounds with anti-leishmanial activity.

In this experimental study, proteomics, protein network analysis, and molecular docking were used. Protein profile was identified by LC-MS/MS and protein network analysis was performed using Cytoscape. Processing of the compound structure and molecular docking was performed by HyperChem and AutoDock Vina, respectively. Finally, docking results were interpreted by LigPlot+.

Based on proteomics and protein network analysis, glycosomal malate dehydrogenase was suggested as a potential drug target. Among the compounds, the best docking results were associated with Conivaptan and Avodart with a binding energy level of -10.5 and -10.2, respectively. Also, molecular docking studies showed that the most important bonds involved in drug-receptor binding were hydrogen and hydrophobic bonds.

The current study demonstrated the importance of integrated proteomics, protein network and docking to identify novel compounds with anti-Leishmania properties. According to this study, Conivaptan and Avodart, also approved by the Food and Drug Administration, are effective inhibitors of glycosomal malate dehydrogenase in Leishmania major and Leishmania tropica which meanwhile require further in-vitro and in-vivo experiments.

Leishmania (L) major and L. tropica are the etiological agents of cutaneous leishmaniosis. Leishmania species cause a board spectrum of phenotypes. A small number of genes are differentially expressed between them that have likely an important role in the disease phenotype. Procyclic and metacyclic are two morphological promastigote forms of Leishmania that express different genes. The glutathione peroxidase is an important antioxidant enzyme that essential in parasite protection against oxidative stress and parasite survival. This study aimed to compare glutathione peroxidase (TDPX) gene expression in procyclic and metacyclic and also interspecies in Iranian isolates of L. major and L. tropica.

The samples were cultured in Novy-Nicolle-Mc Neal medium to obtain the promastigotes and identified using PCR-RFLP technique. They were then grown in RPMI1640 media for mass cultivation. The expression level of TDPX gene was compared by Real-time PCR.

By comparison of expression level, up-regulation of TDPX gene was observed (5.37 and 2.29 folds) in L. major and L. tropica metacyclic compared to their procyclic, respectively. Moreover, there was no significant difference between procyclic forms of isolates, while 3.05 folds up-regulation in metacyclic was detected in L. major compared L. tropica.

Our data provide a foundation for identifying infectivity and high survival related factors in the Leishmania spp. In addition, the results improve our understanding of the molecular basis of metacyclogenesis and development of new potential targets to control or treatment and also, to the identification of species-specific factors contributing to virulence and pathogenicity in the host cells.

The current study aimed to report a pooled analysis of the association of the circulating levels of liver enzymes and total bilirubin with severe and non-severe COVID-19.

The ongoing coronavirus outbreak is an important threat to health worldwide. Epidemiological data representing greater risk of liver failure in patients infected with Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2).

Electronic databases were comprehensively searched using Medline, ISI Web of Science, EMBASE, and the Cochrane Library up to July 2020. Outcomes from each relevant study were pooled using a random-effects model. Heterogeneity was analyzed by Q test and I2 statistics. Sensitivity analysis was also evaluated.

A total of 24 studies were included (4,246 patients) in this study. We found a significant association of COVID-19 severity with increased levels of ALT [SMD: 1.40 U/L; 95% CI (0.93, 1.88); P < 0.05, I2 = 96.5%, PHeterogenity = 0.000 ], AST [SMD: 2.11 U/L; 95% CI (1.40, 2.83); P < 0.05, I2 = 97.9%, PHeterogenity = 0.000], LDH [SMD: 3.88 U/L; 95% CI (2.70, 5); P < 0.05, I2 = 98.7%, PHeterogenity = 0.000] and TBil [SMD: 1.08 mol/L; 95% CI (0.44, 1.72); P = 0.001, I2 = 97.7, PHeterogenity = 0.000], whereas, ALP values [SMD: 0.31; 95% CI (-1.57, 2.20); P = 0.74] was not significant between severe and non-severe COVID-19 patients. Moreover, elevated liver enzymes were found more in males [OR: 1.52, (95% CI 1.26, 1.83), P < 0.05] with severe COVID-19 infection than in females.

The alterations of liver function indexes caused by SARS-CoV-2 infection suggested a potential prognosis biomarker for screening of severe patients at early stages of the disease.

This study aimed to determine whether patients with elevated CRP, TNFα, and IL-6 levels may be at increased risk for severe infection and liver damage of COVID-19.

The COVID-19 outbreak is a serious health problem to human beings. The evidence suggests that inflammatory markers related to liver damage increase in severe forms of COVID-19 compared to mild cases.

The electronic databases ISI Web of Science, EMBASE, and Cochrane Library were comprehensively searched for articles published up to May, 2020. Data from each identified study was combined using the random effects model to estimate standardized mean difference (SMD) and 95% confidence intervals (95% CIs). Sensitivity and publication bias were also calculated.

Totally, 23 studies were included in this meta-analysis comprising 4313 patients with COVID-19. The random effects results demonstrated that patients with severe COVID-19 had significantly higher levels of CRP [SMD = 3.26 mg/L; (95% CI 2.5, 3.9); p<0.05; I2 = 98.02%; PHeterogeneity = 0.00], TNFα [SMD = 1.78 ng/mL; (95% CI 0.39, 3.1); p=0.012; I2 = 98.2%; PHeterogeneity = 0.00], and IL-6 [ SMD = 3.67 ng/mL; (95% CI 2.4, 4.8); p<0.05; I2 = 97.8%; PHeterogeneity = 0.00] compared with those with the mild form of the disease. Significant heterogeneity was present. No significant publication bias was observed in the meta-analysis. Sensitivity analyses showed a similar effect size while reducing the heterogeneity.

The data suggests that enhanced inflammation may be associated with COVID-19-related liver damage, possibly involving inflammatory marker-related mechanisms

Gastric Ulcer (GU) is the most prevalent gastrointestinal disorder induced by various factors and Non-Steroid Anti-Inflammatory Drugs (NSAIDs) as one of the most common reasons. Due to the absence of appropriate molecular markers for GU, the aim of this study was to utilize a metabolomics approach in order to find potential metabolite markers for the disease.

Stomach tissue samples from indomethacin-treated rats and normal controls were used to perform a 1H-NMR metabolomics study. The altered metabolites were identified using random forest multivariate analysis.

ROC curves showed that the random forest model had a good predictive performance with AUC of 1 for the test and 0.708 for the training sets. Seventeen differentially expressed metabolites were found between GU and normal tissue sample. These metabolites included trimethylamine, betaine, carnitine, methionine, acetylcho line, choline, N,N-Dimethylglycine, cis-aconitate, tryptophan, spermidine, acetylcarnitine, creatinine, pantothenate, taurine, isoleucine, glucose and kynurenine.

The results of the study demonstrated that metabolomics approach could serve as a viable method to find potential markers for GU. Surely, further studies are needed for the validation of the results.

Advancing in genome sequencing has greatly propelled the understanding of the living world, however, it is insufficient for full description of a biological system. Focusing on, proteomics has emerged as another large-scale platform for improving the understanding of biology. Proteomic experiments can be used for different aspects of clinical and health sciences such as food technology, biomarker discovery and drug target identification. Since proteins are main constituents of foods, proteomic technology can monitor and characterize protein content of foods and their change during production process. The proteomic biomarker discovery is advanced in various diseases such as cancer, cardiovascular diseases, AIDS and renal diseases which provide non-invasive methods by the use of body fluids such as urine and serum. Proteomics is also used in drug target identification using different approaches such as chemical proteomics and protein interaction networks. The development and application of proteomics has increased tremendously over the last decade. Advances in proteomics methods offer many promising new directions of studying in clinical fields. In this regard, we want to discuss proteomics technology application in food investigations, drug and biomarker discovery will be discussed.

Leishmania is a protozoan parasite responsible for significant morbidity and mortality worldwide. Protozoan parasites of the genus leishmania are found as promastigotes in the sandfly vector and as amastigotes in mammalian macrophages. Mechanisms controlling stage-regulated gene expression in these organisms are poorly understood. Gene regulation in leishmania, like other trypanosomatides, performs in posttranscriptional and posttranslational levels. However, the correlation between mRNA content and protein contents is poor in these parasites. The completion of the genome sequence of several species of Leishmania has had a significant effect on the pathogenesis researches of Leishmaniasis. The prevalence of parasites becoming resistant to anti- leishmania drugs is increasing in several parts of the world including Iran. As protein is the most important target for drugs in response to a variety of signals including drugs, so, it seems protein profiles in both of the sensitive and resistant leishmania parasites could greatly promise about the mechanisms of responses to antileishmanial drugs. Also, many studies have been carried out to determine the factors associated with leishmania infection as well as their molecular mechanisms. In such studies, the new proteomics technology has been of great value. In fact one of the main objectives of proteomics is to identify and discover the disease-related pathologies and novel drug targets. In the current review article, proteomics- based studies investigating leishmania spp. are introduced.

Pre-eclampsia (PE) is a pregnancy disorder characterized by hypertension and proteinuria. The evidence has suggested that microRNAs (miRs) are associated with pre-eclampsia pathogenesis; however, these results are inconsistent. The aim of this study was to assess the association between miR-210 expression and PE risk.
Previous studies were selected using PubMed, Scopus, MEDLINE, EMBASE, Science Direct, Google Scholar, Directory of Open Access Journals (DOAJ), and Scientific Information Database (SID). This meta-analysis includes 12 studies associated with miR-210 and pre-eclampsia and necessary information was extracted.

The standardized mean differences [(SMD (0.32) 95% CI (014–0.49), p=0.97] and heterogeneity were determined with the chi-square test (Q=3.63 df =11 p= 0.97), which found no heterogeneity between these studies. Additionally, publication bias was evaluated by Egger’s and Begg´s tests. Visual inspection of the funnel plot graphically, and statistically with Egger’s weighted regression [(p= 0.35) (95% CI -0.90 – 2.29)] and Begg’s rank correlation (p= 0.21), found no important publication bias between studies within the meta-analysis.
Our findings suggest that miR-210 contributes to the pathogenesis of PE; therefore, miR-210 could serve as a novel biomarker to predict PE pathophysiology. Further studies are required in this field to characterize the mechanism involved in this process.

Although leishmaniasis is regarded as a public health problem, no effective vaccine or decisive treatment has been introduced for this disease. Therefore, representing novel therapeutic proteins is essential. Protein-protein Interaction network analysis is a suitable tool to discover novel drug targets for leishmania major. To this aim, gene and protein expression data is used for instructing protein network and the key proteins are highlighted. In this computational and bioinformatics study, the protein/gene expression data related to leishmania major were studied, and 252 candidate proteins were extracted. Then, the protein networks of these proteins were explored and visualized by using String database and Cytoscape software. Finally, clustering and gene ontology were performed by MCODE and PANTHER databases, respectively. Based on gene ontology analysis, most of the leishmania major proteins were located in cell compartments and membrane. Catalytic activity and binding were regarded as the relevant molecular functions and metabolic and cellular processes were the significant biological process. In this network analysis, UB-EP52, EF-2, chaperonin, Hsp70.4, Hsp60, tubulin alpha and beta chain, and ENOL and LACK were introduced as hub-bottleneck proteins. Based on clustering analysis, Lmjf.32.3270, ENOL and Lmjf.13.0290 were determined as seed proteins in each cluster. The results indicated that hub proteins play a significant role in pathogenesis and life cycle of leishmania major. Further studies of hubs will provide a better understanding of leishmaniasis mechanisms. Finally, these key hub proteins could be a suitable and helpful potential for drug targets and treating leishmaniasis by considering their validation.

Aim: The aim of this study was the evaluation of the prevalence of NAFLD in patients with type 2 diabetes mellitus.
Non-alcoholic fatty liver disease (NAFLD) is an emerging disease with high prevalence in patients with type 2 diabetes mellitus (T2DM). Many studies have reported the prevalence of NAFLD in type 2 diabetes mellitus patients. However, these results are inconsistent.
A Literature search was conducted in PubMed, Scopus, web of science and Science Direct from 2005 to August 2017. The necessary information was extracted. Heterogeneity was evaluated using I2 statistic. Meta-regression analyses were performed to the estimation of the relationship between the year of study and sample size with the prevalence of NAFLD. Publication bias was assessed by both Begg rank correlation and Egger tests. Subgroup analysis was performed for identification of sources heterogeneity.
Seventeen studies involving 10897 type 2 diabetes mellitus patients with NAFLD were included in this meta-analysis. The overall prevalence of NAFLD in type 2 diabetes mellitus patients by random effects models was 54% (95% CI, 45%- 64%). There is a significant heterogeneity across studies with (I2= 99%, p> 0.01). The funnel plot as graphically and Begg and Egger as statistically showed no publication bias among studies. Subgroup analysis indicated that the prevalence of NAFLD in type 2 diabetes mellitus patients differed in predictive factors such as lipid profile, BMI, HbA1c, AST, and ALT. This finding in spite of heterogeneity of documents is corresponding to the positive correlation between NAFLD and type 2 diabetes mellitus.
The findings indicated that the overall prevalence of NAFLD among type 2 diabetes mellitus patients is significantly higher. It can be concluded that type 2 diabetes mellitus patients should be managed to prevent NAFLD.

Proteins are fundamental components of cells which mediate many essential biological processes. Proteomics is a rapidly growing field for the study of proteome, the protein complement expressed by the genome of an organism or cell type. The large-scale analysis of proteins leads to a more comprehensive view of molecular and cellular pathways that improves the overall understanding of the complex processes supporting the living systems. The analysis of proteome is significantly challenging due to high dynamic range and difficulties in assessment of low abundance proteins and the absence of efficient purification and identification techniques. A variety of methods have been utilized for protein studies including gel-based techniques, protein microarrays, mass spectrometry-based approaches such as MALDI and SELDI, high and ultra-performance liquid chromatography and fourier transform ion cyclotron resonance mass spectrometry. NMR spectroscopy and X-Ray crystallography methods are also used for structural study of proteins. This review aims to give a brief overview of some of the above techniques and their most recent advances. We also introduce Proteominer, a recent protein enrichment technology for the exploration of the entire proteome content

Backgroud: Protein-protein interaction, plays a key role in signal transduction in signaling pathways. Different approaches are used for prediction of these interactions including experimental and computational approaches. In conventional node-edge protein-protein interaction networks, we can only see which proteins interact but ‘structural networks’ show us how these proteins interact which can give us so much information about the network. Structural networks help us understand the molecular basis of cellular functions and regulatory mechanisms in signaling pathways. In this study, we aimed to construct a structural network for a part of cAMP signaling pathway which has PKA (cAMP-dependent protein kinase catalytic subunit alpha) as the hub. A part of cAMP signaling pathway was selected from kegg database and interactions of PKA as hub protein with some of its partners were achieved using Hex8.00 software. The interfaces of the resulted complexes were predicted by KFC2 server. Hex8.00, as a docking software, gave us the complexes from the interaction of PKA with 15 proteins of its partners. For each complex, the KFC2 server gave us the amino acid composition of the interfaces. Using this amino acid composition, we draw a structural network which shows the binding sites on PKA surface. We have constructed a structural network for cAMP signaling pathway which shows how PKA interacts with its partners. This network can be used for understanding the mechanisms of signal transduction and also for drug design purposes.

Glaucoma, a group of multifactor ocular diseases, is the second leading cause of blindness worldwide. Primary open angle (POA) is the most common type of glaucoma, characterized by progressive optic nerve degeneration. Numerous genes and proteins have been revealed to be associated with POAG, but the pathologic mechanisms of the disease are still poorly understood. Proteomics, the collective study of proteins in an organism at a given condition, has extensively been used for the high-throughput identification of proteins related to POAG. A significant obstacle in proteomics studies is the data variability which makes it hard to interpret the results. Pathway analysis and network topological information can help address the challenge and provide a greater appreciation of the disease mechanism and progression. The purpose of this paper is to determine POAG biological and network information to further understand the mechanisms associated with POAG. PANTHER classification system was used, including classification with gene ontology, protein class and pathway. 474 gene/protein IDs were extracted from previous proteomic studies. Among pathways found by PANTHER classification, apoptosis signaling pathway was the most significant pathway (with the p-value of 5.54E-12). Other PANTHER categories results demonstrated that developmental processes, receptor binding, extracellular region and extracellular matrix proteins were the most significant biological process, molecular function, cellular component and protein class respectively. Pathway analysis aids to find probable mechanisms involved in POAG. A network analysis on proteins was also performed using STRING database and cytoscape software. From network analysis, candidate biomarkers for the disease were introduced.