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Background and Aim: Heterogeneous insertion of Organizational affiliations can cause loss of ranking points in the national and international levels. So, we decided to investigate the different affiliations of Shahid Beheshti University of Medical Sciences in scientific publications that indexed in Web of Science and their effect on the result of research activities evaluation in the year 2012. Materials and Methods: Methodology of this study is bibliometric approach with descriptive survey. The study included 1139 scientific production of Shahid Beheshti University of Medical Sciences that indexed in Web of Science in the first one in April 2011 to April 2012. Results: 1139 articles indexed in the Web of Science, 94/38% in the evaluation of the research activities of the ministry of health have been scored and 5/61% failed. Among the unsuccessful papers 1/01%, had been inserted affiliation incorrectly. One-sample t-test showed that the mean score of 1/01% has no significant statistical impact on the total average rating of products indexed in Web of Science. Conclusion: Investigation showed that standard insertion of affiliation has impact on enterprise University Ranked and University status at the international level.

Introduction: Type 1 diabetes (T1D) results from autoimmune destruction of insulin-producing beta cells in pancreatic islets of Langerhans. To develop efficient treatments for T1D, it is required to identify suitable therapeutic markers. Systems biology offers approaches to better understanding of functional elements in the disease. Our aim was to investigate larger number of candidate markers in T1D by topological analysis of constructed PPI based on gene expression. Materials and Methods: In this study, gene expression profile of peripheral blood mononuclear cells from newly diagnosed type 1 diabetic children was prepared from Gene Expression Omnibus and analyzed to get differentially expressed genes. Then, these genes were mapped to PPIs data to construct related subnetwork. Five topological features were calculated by Cytoscape software. Finally, degree, betweenness and closeness centrality features were utilized to identify candidate markers. Results: 2467 differentially expression genes were obtained by statistical analyzing of gene expression profile in which 1024 were upregulated and 1443 were downregulated. After mapping these genes on PPI network, there was constructed subnetwork with 949 nodes and 1776 edges. By topological analysis of the subnetwork, we determined high degree nodes (hub) and high betweenness nodes (bottleneck). Then, 9 hub-bottleneck proteins that were more central (high closeness centrality) in the subnetwork were identified and introduced as candidate markers. Conclusion: The obtained markers from network via systemic view can be considered as new diagnostic markers and potential therapeutic targets for T1D

Introduction: Studies show that ethanol can induce changes in proteomic profile of human fibroblast cells. Some of these proteins are important in promoting cancer. Thus, analyzing function and interaction networks of these proteins are essential for better understanding the carcinogenesis mechanism of ethanol. Materials and Methods: In this study the protein-protein interaction network (PPI) of six significant down-regulated proteins in human fibroblast cells (HFFF2) treated with ethanol were analyzed by using Cytoscape software and its algorithms. Results: PPI network analysis showed that the constructed network consisted of 756 nodes and 1166 edges. Results indicated that Heterogeneous nuclear ribonucleoprotein A1 with degree = 528 and Betweenness Centrality = 0.74 is a hub protein that ethanol can alter its expression. In addition, module evaluation showed that the hub protein has a key role in different overlapped complexes. On the other hand, annotation studies by using DAVID program indicated that this protein is involved in different important biological processes in the cell. Conclusion: The six down-regulated proteins treated with ethanol may become carcinogenic and can impose vast alterations in other vital biological processes of the cell. Among them, Heterogeneous nuclear ribonucleoprotein A1 is the most important one

Objective(s):Neurodegenerative Alzheimer’s disease (AD) is associated with profound deficits in synaptic transmission and synaptic plasticity. Long-term potentiation (LTP), an experimental form of synaptic plasticity, is intensively examined in hippocampus. In this study we evaluated the effect of aqueous extract of lavender (Lavandula angustifolia) on induction of LTP in the CA1 area of hippocampus. In response to stimulation of the Schaffer collaterals the baseline or tetanized field extracellular postsynaptic potentials (fEPSPs) were recorded in the CA1 area. Materials and Methods: The electrophysiological recordings were carried out in four groups of rats; two control groups including the vehicle (CON) and lavender (CE) treated rats and two Alzheimeric groups including the vehicle (ALZ) and lavender (AE) treated animals. Results: The extract inefficiently affected the baseline responses in the four testing groups. While the fEPSPs displayed a considerable LTP in the CON animals, no potentiation was evident in the tetanized responses in the ALZ rats. The herbal medicine effectively restored LTP in the AE group and further potentiated fEPSPs in the CE group. Conclusion:The positive effect of the lavender extract on the plasticity of synaptic transmission supports its previously reported behavioral effects on improvement of impaired spatial memory in the Alzheimeric animals.

Background: Aerobic exercises induce adaptations that improve physiological function. However, aerobic exercises, oxidative reproduction may lead to injury and other health issues such as adverse cardiac effects. The aim of this study is to evaluate the effect of aerobic exercises on protein expression change in the heart left ventricle to determine the advantages and disadvantages related to this mode of exercise.Methods: Male Wistar rats were randomized into two groups; trained (T) and control (C). Animals from T group were trained for 8 weeks, and then 2D LC-MS/MS iTRAQ method was used for extracting and analyzing the left ventricular proteins. Certain proteins that were highlighted in the special process were selected for further analysis via protein-protein interaction network (PPI) method. The identified proteins were enriched via gene ontology (GO) to find biological terms.Results: We identify five overexpressed antioxidant proteins in T group compared with C group including extracellular superoxide dismutase [Cu-Zn], Frataxin, protein kinase C delta type, STE20/SPS1-related proline-alanine-rich protein kinase, and amyloid-beta A4 protein. Conclusions: Findings indicate that catalase and insulin are two exercise-related proteins. However, they were not included in the significant differentially expressed proteins. Finally it was found that enhancement of antioxidative activity is a direct effect of aerobic exercises.

Introduction: Cardiopulmonary resuscitation (CPR) is a method to improve survival of patients with cardiac arrest. This study aimed to identify the key genes affected five minutes after cardiac arrest, hoping to elevate the efficacy of CPR. Methods: In this bioinformatics study differentially expressed genes of six pigs were downloaded from GEO and screened. The significant and characterized genes were analyzed via calculating fold change and protein-protein interaction (PPI) networks. The crucial nodes were determined based on centrality parameters and their related biological processes were investigated via ClueGO. Results: 17 significant up-regulated (LogFC ≥ 2) and 22 down-regulated (LogFC < -0.5) genes were detected. Transthyretin (TTR logFC = 4.59) and Gonadotropin-releasing hormone receptor (GNRHR logFC = 3.84) had higher logFC among up-regulated and down-regulated genes, respectively. The critical genes including four up-regulated and five down-regulated genes were detected from network analysis. GNRHR and Prolactin precursor (PRL) were among the most important down res 5 minutes after cardiac arrest and Beta-2 adrenergic receptor and Cadherin-1 were among the most important up regulated gens. Conclusion: The introduced potential biomarkers could reveal a new molecular aspect for CPR performance and pituitary gland protection was highlighted in this respect.

Background & Objective: Ginkgo biloba is an herbal medicine that has a positive effect on improving memory. It prevents oxidative damage in mitochondria and cell death in a variety of Neuropathies. Besides, baclofen is prescribed for its analgesic and anti-inflammatory effects but has negative impact on memory. The objective of this study is to investigate the interaction of ginkgo with GABA b receptor agonist (baclofen) by passive avoidance behavior in mice. Materials & Methods: Passive avoidance learning and memory method was used to evaluate memory by I maze shuttle box. The rats were divided into six groups. The first group were fed with only oral Ginkgo. The second and the third groups received different dosages of intraperitoneal baclofen. Groups four and five received both ginkgo and baclofen. The sixth group, as the control group, received only saline. All the injections were performed at a certain time in a day. Result: The injection of ginkgo alone, compared with control group, didn’t create any significant change in memory. The injection of different dosages of baclofen decreased the memory significantly . The injection of both ginkgo and baclofen improved memory . Conclusion: Administration of baclofen reduces and impairs memory. Ginkgo improved baclofen induced amnesia. It seems that this operation is done by interference with GABA neurotransmitters. Ginkgo biloba can possibly be used as an adjuvant drug to decrease the side effects of baclofen.

The association of genes polymorphism of DGAT1 and SCD1 has proved with milk nutritive value. The aim of the present study was the comparison of genetic structure of DGAT1 and SCD1 loci between Holstein and Simmental population. 102 Mazandaran Simmental and Holstein cows were randomly selected and done blooding of neck vein. In digestion of SCD1 PCR products (725bp) with AluI enzyme, two alleles V and A were revealed with the frequency of 79 and 21 percent and 92 and 8 percent in Holstein and Simmental breeds, respectively. In digestion of the 325bp fragment of this gene with NcoI enzyme, two alleles of C and T were detected with the frequency of 40 and 60 percent and 45 and 55 percent in Holstein and Simmental breed, respectively. Two alleles of A and K were detected from amplification of DGAT1 locus with the frequency of 60 and 40 percent and 57 and 43 percent in Holstein and Simmental population, respectively. The result of statistical comparison of genotype and allele frequency in studied loci between two breeds indicates that DGAT1locus and second locus of SCD1 gene are same as gene frequency between two breeds and are different as genotype frequency in DGAT1 locus and are same as genotype frequency in SCD1 locus. According to observed polymorphisms, we can result that studied loci are fit for selection of animals with favorite genotype for increasing of production of milk useful fatty acids

Background The involvement of multiple genes and missing heritability, which are dominant in complex diseases such as multiple sclerosis (MS), entail using network biology to better elucidate their molecular basis and genetic factors. We therefore aimed to integrate interactome (protein–protein interaction (PPI)) and transcriptomes data to construct and analyze PPI networks for MS disease. Methods Gene expression profiles in paired cerebrospinal fluid (CSF) and peripheral blood mononuclear cells (PBMCs) samples from MS patients, sampled in relapse or remission and controls, were analyzed. Differentially expressed genes which determined only in CSF (MS vs. control) and PBMCs (relapse vs. remission) separately integrated with PPI data to construct the Query-Query PPI (QQPPI) networks. The networks were further analyzed to investigate more central genes, functional modules and complexes involved in MS progression. Results The networks were analyzed and high centrality genes were identified. Exploration of functional modules and complexes showed that the majority of high centrality genes incorporated in biological pathways driving MS pathogenesis. Proteasome and spliceosome were also noticeable in enriched pathways in PBMCs (relapse vs. remission) which were identified by both modularity and clique analyses. Finally, STK4, RB1, CDKN1A, CDK1, RAC1, EZH2, SDCBP genes in CSF (MS vs. control) and CDC37, MAP3K3, MYC genes in PBMCs (relapse vs. remission) were identified as potential candidate genes for MS, which were the more central genes involved in biological pathways. Discussion This study showed that network-based analysis could explicate the complex interplay between biological processes underlying MS. Furthermore, an experimental validation of candidate genes can lead to identification of potential therapeutic targets.

Introduction: Gene-set analysis of microarray data determines biological pathways or gene setswith differential expression in a phenotype of interest. In contrast to the analysis of individual genes, gene-set analysis utilizes existing biological knowledge of genes in assessing differential expression. This paper compared the biological performance of two gene-set analysis methods.Materials and Methods: To determinegene sets, which are differentially expressed between acute lymphoblastic leukemia (ALL) with BCR/ABL and those with no observed cytogenetic abnormalities, the real microarray data come from a clinical trial in acute lymphoblastic leukaemia were used in this study. For this reason, we used two GSA methods; GSEA-category and Global test and then the data were analyzedusing by R software.Results: Globaltest identified 114 out of 200 gene sets introduced in KEGG with differentially expressed on comparing the group with BCR/ABL to those with no observed cytogenetic abnormalities. While Category could identify just 30 gene sets of this set.Conclusion: Both of used methods include number of gene sets affecting ALL. So the more thorough study is needed to identify the more metric method. Evaluation of common gene sets among the two methods could identify the latest findings of biologists only by the used statistical methods.

Forecasting the product demand is one of the most important activities of every organization for planning the sale and finally making a comprehensive plan. It in fact determines the amount of the activities an organization carries out in the future and also provides the managers with a clear understanding of the amount and quality of the respected activities. In this article, a model based on Artificial Intelligence and Data Mining algorithms is proposed for predicting the amount of sale in tile and ceramic industry. The proposed model is a hybrid model consisting of dimensionality reduction, clustering and forecasting. In order to construct the model, this research uses independent component analysis, Manifold learning, K-means clustering and support vector regression. The present research studies 50 cases of Irana Tile Company's past 3 years of monthly sales. Because of the decrease in generic and sampling errors, the results obtained from this model show a superior precision compared to other traditional forecasting methods.

Background. Biclustering algorithms for the analysis of high-dimensional gene expression data were proposed. Among them, the plaid model is arguably one of the most flexible biclustering models up to now. Objective. The main goal of this study is to provide an evaluation of plaid models. To that end, we will investigate this model on both simulation data and real gene expression datasets. Methods. Two simulated matrices with different degrees of overlap and noise are generated and then the intrinsic structure of these data is compared with biclusters result. Also, we have searched biologically significant discovered biclusters by GO analysis. Results. When there is no noise the algorithm almost discovered all of the biclusters but when there is moderate noise in the dataset, this algorithm cannot perform very well in finding overlapping biclusters and if noise is big, the result of biclustering is not reliable. Conclusion. The plaid model needs to be modified because when there is a moderate or big noise in the data, it cannot find good biclusters. This is a statistical model and is a quite flexible one. In summary, in order to reduce the errors, model can be manipulated and distribution of error can be changed.

Background: According to the literature, there are a number of chronic and acute myeloid leukemias with unique, complex chromosome translocations. This study aims to conduct a brief review of the incidence of complex chromosome translocations in myeloid leukemia and reports a case of myeloid leukemia with complex chromosome translocations.Methods: We conducted a web-based search for all peer review articles published on the subject of complex chromosome tranlsocations in chronic and acute myeloid leukemia in MEDLINE, PubMed and Mitelman (http://cgapanci.nih.gov/chromosomes/Mitelman) databases in addition to other pertinent web references. In addition, we performed conventional cytogenetic studies of 24- to 72-h cultures on bonemarrow/peripheral blood cells obtained from the current case. Cells were finally treated by the giemsa-trypsin-giemsa banding technique.Results: The result of this case revealed an abnormal karyotype that had a novel complex translocation which involved chromosomes 2, 5, 9, and 22. We performed karyotyping after the initiation of chemotherapy. Karyotyping results showed a complex karyotype 46,XX,t(9;22;2;5).Conclusion: This study discusses a case of chronic myeloid leukemia with complex chromosome translocations and may provide novel information regarding these translocations in leukemias.

Introduction: Adenosine deaminase (ADA) is a purine catabolic enzyme that removes amino group of adenosine or 2' deoxyadenosine irreversibly. ADA enhances immune system and also intervenes the inflammation process. In this study, the effect of ibuprofen as an anti- inflammatory drug has been studied on the ADA activity in the physiologic and pathologic temperatures. Materials and Methods: ADA was assessed in the presence of 3 different doses of ibuprofen at 37oC and 42oC via spectrometry in 265 nm. Results: Ibuprofen at high and low doses had an activation effect on the ADA activity at 37oC and moderated the sensitivity of enzyme activity to its substrate. It also decreased the anti-inflammatory effect of adenosine via decrease of its concentration and had a positive effect on immune system as well. The activation of the enzyme by Ibuprofen was decreased at 42oC and also Ibuprofen moderated the effect of temperature on dependency of enzyme activity to its substrate. Ibuprofen effects on immune system and anti-inflammatory effects of adenosine decreased at 42oC. Conclusion: Ibuprofen is a putative activator for adenosine deaminase and administration of this drug could be useful for immune deficiency. Since there is no activator for ADA so far, this drug is important. Ibuprofen decreases anti-inflammatory effect of adenosine. In-vivo studies would be needed .

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Introduction: Because of producing large amount of proteomics data and requiring new proceduresfor analyzing them, collective analysis of proteins can help us in identifying new annotation patterns indataset. Furthermore, this type of analysis is a time- consuming process too. Cluster analysis, as a suitablestatistic procedure, can be used for analyzing these datasets. This paper's objective was evaluating theefficiency of fuzzy clustering method in recognizing new patterns within proteins which are related togastric cancers.Materials and Methods: Fuzzy clustering procedure has been used to analyze the identified includedproteins in esophagus, stomach and colon cancers. Proteins were clustered based on three aspects of GeneOntology (GO) and results were compared.Results: Fuzzy clustering was implemented and non-fuzziness indexes based on biological process,cellular component and molecular function were obtained equal to 0.41, 0.55 and 0.35, respectively.Obtained index based on molecular function showed the efficiency of fuzzy clustering method. Despite ofnon-substantial silhouette widths for the entire dataset, most of the proteins in each cluster hadremarkable biological communions. Using Term Enrichment software to determine statistically enrichedGO terms in the entire dataset and clusters, it was cleared that the fuzzy clustering has revealed novelannotation patterns within dataset that would not have been identified otherwise.Conclusion: Considering fuzzy clustering outputs, the efficiency of this method for better and flexibleproteins analysis was cleared. As fuzzy clustering method has placed proteins, that have more similarities,with high probabilities together. Therefore, it can be used for the situations that some of proteins haveunknown characteristics. Furthermore it seems that the proteins clustered via their cellular componentsimilarities, have also biological and functional similarities which this requires more investigations.

Coronary artery calcium scoring (CACS) is a reasonable test for patients with the possibility of atherosclerosis. It can also be used for reclassifying the coronary artery disease (CAD) to the high-risk status by higher CACS and subsequently modifying the management of the patients.The purpose of this study was to investigate the association of CACS to the severity of coronary artery disease in the patients who were scheduled to perform coronary artery angiography (CAG) by tradition. CACS could be a simple, relatively cost-benefit, and noninvasive method for early screening of patients with obstructive coronary artery disease.In the present study, CAC scoring was evaluated by non-enhanced Multi-Detector Computed Tomography (MDCT) in a total 239 patient suffering from coronary artery disease. Of them, 223 patients were planned to undergo CAG based on clinical examination or other noninvasive diagnostic methods (such as MPI, ETT, EKG or Echo).Our results showed that 11 of 67 patients with a negative CACS (zero) had obstructive coronary artery disease derived from the results of CAG. We also found a significant correlation between high CACS (more than 400) and extensive obstructive CAD, except for the two patients who had only mild CAD. There was a linear correlation between CACS and the severity of CAD on the basis of Gensini score and the number of involved arteries (CC=0.507, PV400) might be a significant indicative of CAD in referring patients.

Background. Focal segmental glomerulosclerosis (FSGS) is a glomerular injury with various pathogenic mechanisms. Urine proteome panel might help in noninvasive diagnosis and better understanding of pathogenesis of FSGS. Method. We have analyzed the urine sample of 11 biopsy-proven FSGS subjects, 8 healthy controls, and 6 patients with biopsy-proven IgA nephropathy (disease controls) by means of liquid chromatography tandem mass spectrometry (nLC-MS/MS). Multivariate analysis of quantified proteins was performed by principal component analysis (PCA) and partial least squares (PLS). Results. Of the total number of 389 proteins, after multivariate analysis and additional filter criterion and comparing FSGS versus IgA nephropathy and healthy subjects, 77 proteins were considered as putative biomarkers of FSGS. CD59, CD44, IBP7, Robo4, and DPEP1 were the most significant differentially expressed proteins. These proteins are involved in pathogenic pathways: complement pathway, sclerosis, cell proliferation, actin cytoskeleton remodeling, and activity of TRPC6.There was complete absence of DPEP1 in urine proteome of FSGS subjects compared with healthy and disease controls. DPEP1 acts via leukotrienes on TRPC6 and results in increased podocyte motility and proteinuria. Conclusion. The results suggest a panel of candidate biomarkers for noninvasive diagnosis of FSGS, while complete absence of DPEP1 might represent a novel marker of FSGS.

About two centuries have passed since the first deaths due to traffic accidents. Recent research shows that 38% of unnatural deaths in Iran are because of road accidents. According to statistics published by Iran forensics, from 2000 to 2010, 235587 people have been killed in traffic accidents and 2281810 people have been injured. [1] Given that planners and policy makers are concerned with decreasing accidents and also because information forms the fundamental part of preventive programs, lack of sufficient information regarding the causes of accidents will be an obstacle to fulfill such programs. Collection of appropriate data and access to sufficient information regarding the causes of traffic accidents such as the type of accident (traffic or non-traffic), compliance with safety regulations and standards (such as fastening seatbelt, no cell-phone use, no drinking or eating, use of helmet by motor cyclists, and etc.), vehicles involved, rate and type of injury, time and location of accident can help organizations in implementation of preventive programs. In this regard, Minimum Data Set (MDS) plays a fundamental role in meeting policy makers' needs. MDS make data comparison possible and allows medical institutions to identify patients and meet governmental requirements, institutional needs and medical society's ideals. [2, 3] Tee (2012) in his study entitled "Inception of an Australian Spine Trauma Registry: The Minimum Data Set" showed that there is a need to comprehensive registry of collected data associated with spinal cord trauma both regarding spinal column and spinal cord injuries in order to inform policy makers properly and create preventive strategies for future patients. [4] Shaban (2009) in his study "The Long Term Effects of early Analysis of a Trauma Registry in United Arab Emirates" concluded that creating a registry system is a challenging issue in developing countries; however, it is feasible and leads to development of nationwide data bases. [5] Coats (2009) in his study "Beyond the Trauma Registry" stated that the first step toward a high quality trauma registry system is a proper information center or MDS. [6] Executive regulations associated with mandatory use of seat belt and helmet which was a joint proposal by interior, justice, industries and mines, and road and transport ministries was passed in cabinet meeting dated on March 17, 2001and was delivered on April 10, 2001; however, it wasn’t forced until 2005. According to the study, the rate of deaths due to accidents has been 13% a year before the law enforcement and 9.7% a year after it. [7] Conclusion: Obviously, without reflection and dissemination of information and statistics on the causes of traffic accidents, organizations, responsible authorities, and policy makers wouldn’t pass the above regulations. Since information is the basis of decision making, it would be better to establish a Minimum Data Set for local and national accidents so that stemming and designing preventive programs is possible.

IgA nephropathy is the most common cause of primary glomerulonephritis. There are different pathologic biopsy-based scoring systems in use, but there is no consensus among nephrologists yet regarding the best classification method. Our aim was to test urine proteomics as a non-invasive method for classification of IgA nephropathy. This aim was pursued by discovering novel prognostic protein biomarkers in urine, and linking them to pathogenesis of the disease through known signaling and metabolic pathways. 13 urine samples of the patients with biopsy-proven IgA nephropathy were analyzed via two proteomics approaches: nanoflow LC-MS/MS and GeLC-MS/MS. The results of label-free quantification were subjected to multivariate statistical analysis, which could classify patients into two groups, broadly corresponding to the primary and advance stages. The proteome classification correlated well with biopsy-based scoring systems, especially endocapillary hypercellularity score of the Oxford's classification. Differentially excreted candidate proteins were found as potential prognostic biomarkers: afamin, leucine-rich alpha-2-glycoprotein, ceruloplasmin, alpha-1-microgolbulin, hemopexin, apolipoprotein A-I, complement C3, vitamin D-binding protein, beta-2-microglobulin, and retinol-binding protein 4. Pathway analysis suggested impairment of Extra Cellular Matrix (ECM)-Receptor Interaction pathways as well as activation of complement and coagulation pathway in progression of IgA nephropathy.

Background The induction of cancers incidence by exogenous agents, such as chemical, radiation and especially research on viruses is an interested area of active basic subjects and clinical investigation. Prominent researches sounds a high prevalence of HBV marker has been found in patients with leukemia as compared to the general population. Methods: Present  study was conducted from 1996 to 2010   among patients with chronic acute myeloid leukemia and corresponding with non malignant patients. In this investigation,  Cytochemical staining, immunophenotyping, cytogenetic /molecular cytogenetics, Elisa, enzyme immunoassay and Western blot, were the main subject of laboratory manipulation. Results: Hepatitis B virus was diagnosed in one non malignant control patient (%0.004) and four infected with leukemia patients (%3). The differences of leukemic patients revealed statistical significant when compared with non malignant patients (P=0.0047). Conclusion: In this pilot study, the prevalence of HBV infection was higher in patients with leukemia than in patients as non malignant patients. Our findings are also important as they are among the first to suggest here a potentially significant influence of  HBV infection may plays a probably major role in the process of myeloid malignant development. However, the number of cases are not large enough to draw firm conclusion. Moreover, we suggest that this pilot study, issue warrants further investigation by large consortium project.

Background and objectives: Positive role of coffee consumption on regulation of human blood sugar has been highlighted by researchers. On the other hand, metformin is the common drug against type 2 diabetes. This study aimed to explore possible ways to use coffee as a complementary agent beside metformin or independently versus type 2 diabetes. Methods: Proteomic data about effect of two major compounds of coffee (caffeine and trigonelline) on improvement of diabetic condition was searched and analyzed via protein-protein interaction (PPI) network analysis and gene ontology enrichment. Gene expression profiles of human whole blood of diabetic patients (responsive to metformin) versus control were extracted from GSE83983 which is recorded in Gene Expression Omnibus (GEO) database. After pre-evaluation of data by GEO2R program, the significant differentially expressed genes (DEGs) were assessed via PPI network analysis and regulatory network evaluation. Results: Caffeine and trigonelline effectively regulate the glycolytic processes to fight against diabetic condition. HSP90AA1, TLR4, RELA, ARRB, LRRK2, STAT5B, LYN, and TLR2 genes that are involved in diabetes were affected significantly by metformin. Conclusion: It can be concluded that coffee consumption can improve sugar regulation in diabetes similar to metformin. IT seems that the optimized consumption quantity of coffee can be considered as controller of blood sugar in diabetic patients. [ABSTRACT FROM AUTHOR]

The current research has been carried out with the aim of presenting the pattern of combined shopping behavior of customers in large chain stores. This research is applied in terms of purpose, and in terms of survey-exploratory approach. The statistical population of this research was a group of marketing experts in the retail industry and were interviewed in depth. This selection and conducting of interviews continued until theoretical saturation was reached and then it was stopped. In this research, the snowball sampling method was used and in this process, 9 experts were interviewed in depth. In this research, since the foundational data theory method was used, the main tool for data collection was in-depth and unstructured interviews with human resources experts. Finally, after three open, central and selective codings, the conceptual model of the research was designed based on the paradigm model. [ABSTRACT FROM AUTHOR]

Aim: The current study aimed to introduce the key proteins involved in liver ischemia/reperfusion (I/R) injury through protein-protein interaction (PPI) analysis. Background: Liver transplantation (LT) is a well-known treatment for liver diseases that threaten patients with mortality. LT is a complex operation, and several risks, including liver I/R injury, affect its success. Improving LT requires detection of its molecular mechanism. Experiments have revealed that high throughput methods such as proteomics in combination with bioinformatics are useful tools for analyzing the molecular mechanism of disease. Methods: The differentially expressed proteins (DEPs) involved in liver I/R injury were extracted from the literature. The queried DEPs plus the first 100 neighbors were included in a network through STRING database using Cytoscape software. Degree, betweenness centrality, closeness centrality, and stress were considered to determine the central nodes. The queried DEPs were assessed by action map analysis using the CluePedia application of Cytoscape software. The key proteins were identified by comparing network analysis and action map evaluation results. Results: Six proteins, namely ALB, INS, GAPDH, CAT, IL6, and TNF, among the added first neighbors were determined as the central first neighbors. MPO, CRP, MMP9, and HMOX1 were selected as central DEPs among the queried proteins. Action map analysis confirmed the PPI findings. The final evaluation revealed that MMP9 in combination with CRP and HMOX1 plays a critical role in liver I/R injury. Conclusion: The significant role of MMP9 in liver I/R injury was detected in this study. Two central proteins (CRP and HMOX1) were shown to have a regulatory effect on MMP9; CRP activated MMP9, while HMXO1 downregulated it. [ABSTRACT FROM AUTHOR]

Aim: This study aims to investigate the anticancer molecular mechanism of RT2 through protein-protein interaction (PPI) network analysis. For this aim, a bioinformatics evaluation of the proteome profile of colon cancer is carried out. Background: Antimicrobial peptides such as RT2 showed anticancer properties against various tumors. The molecular mechanism of the anticancer effect of RT2 is a challenging subject. Methods: By applying Cytoscape V.3.9.1 and integrated apps, the profile of the interaction network and related centrality is analyzed. An enrichment analysis of hub bottlenecks was also performed, and highlighted biological processes were visualized and determined. Results: Several 207 differentially expressed proteins were retrieved by PPI network analysis, and 10 hub bottlenecks were introduced. Among these differentially expressed proteins (DEPs), only AKT1 is from the queried DEPs. Key biological processes contributing to RT2 targeting mechanism include "Regulation of fibroblast proliferation", "Positive regulation of cyclin-dependent protein serine/threonine kinase activity", "positive regulation of miRNA transcription", and "fungiform papilla formation". Conclusion: In conclusion, central proteins Tp53, MYC, EGFR, AKT1, HDAC1, and SRC can be introduced as a targeted biomarker panel of bioactive peptide treatments. However, extensive research is required to establish this claim before clinical application. [ABSTRACT FROM AUTHOR]

Maintaining a healthy balance between commensal, and pathogenic bacteria within the gut microbiota is crucial for ensuring the overall health, and well-being of the host. In fact, by affecting innate, and adaptive immune responses, the gut microbiome plays a key role in maintaining intestinal homeostasis and barrier integrity. Dysbiosis is the loss of beneficial microorganisms and the growth of potentially hazardous microorganisms in a microbial community, which has been linked to numerous diseases. As the primary inducer of circadian rhythm, light can influence the human intestinal microbiome. Photobiomodulation therapy (PBMT), which is the use of red (630-700 nm), and near-infrared light (700 and 1200 nm), can stimulate healing, relieve pain, and reduce inflammation, and affect the circadian rhythm and gut microbiome beneficially. Our focus in this paper is on the effects of PBMT on gut microbiota, to provide an overview of how it can help control gut microbiota dysbiosis-related disorders. [ABSTRACT FROM AUTHOR]