The variability of phenolic constituents and antioxidant properties among wild populations of Ziziphora clinopodioides Lam.

In this study, phenolic derivatives and antioxidant activities of fourteen Ziziphora clinopodioides populations, as well as LC-MS/MS analysis of three specific flavonoids were evaluated. Generally, high contents of phenolic derivatives were found in shoot extracts compared to roots. LC-MS/MS, a powerful analytical technique, was employed for the identification and quantify the individual flavonoids in Z. clinopodioides populations' extracts, in a quantity order of quercetin > rutin > apigenin. Scavenging activity by DPPH and FRAP was performed, and accordingly, in the shoot, the highest values for the DDPH were 4.61 ± 0.4 and 7.59 ± 0.26 µg ml- 1 in populations 1 and 13, respectively, and for the FRAP were 328.61 ± 5.54 and 292.84 ± 2.85 mg g DW- 1, in populations 6 and 1 respectively. Multivariate analysis results of the principal component analysis indicated the amount of polyphenols to be useful indicators in differentiating the geographical localities which explain 92.7% of the total variance. According to the results of hierarchical cluster analysis, the studied populations could be separated into two groups in that the contents of phenolic derivatives and antioxidant activities of different plant parts. Both shoot and root samples were well discriminated with the orthogonal partial least squares discriminant analysis (R2X: 0.861; Q2: 0.47) model. The validity of the model was confirmed by using receiver operating characteristic curve analysis and permutation tests. Such data make an important addition to our current knowledge of Ziziphora chemistry and are decisive in the identification of germplasms with a homogeneous phytochemical profile, high chemical content and bioactivity. The present results could also be helpful for the potential application of Z. clinopodioides in different kinds of industries as natural antioxidants. Supplementary Information: The online version contains supplementary material available at 10.1007/s12298-023-01283-y.

ICP-OES assessment of trace and toxic elements in Ziziphora clinopodioides Lam. from Iran by chemometric approaches.

The aim of the study was to evaluate the concentrations of some essential and toxic elements (including Ca, K, Mg, Na, Fe, Cu, Mn, Zn, Co, Mo, Pb, Ni, Cr, and Cd) in Ziziphora clinopodioides Lam. (endemic Iranian herb) from 14 different regions by ICP-OES (inductively coupled plasma-optical emission spectrometry) method followed by multivariate statistical analyses. The analytical performances were assessed as the limit of detection (LOD), limit of quantification (LOQ), precision, and accuracy. Multivariate analysis (CA, PCA and HCA) showed the elemental distribution in the roots were higher than the shoots and significant element was Ca between regions. Three principal components (PCs) explained 77.94% of the total variance. They were as follows: PC1 with Cu, Zn, K, Cr, Ni, and Mn; PC2 with Na, Ca, Pb, and Fe; and PC3 with Mg. Hierarchical cluster analysis indicated four groups of Z. clinopodioides samples from the 14 regions based on their trace and toxic element levels. These chemometric approaches with multivariate analysis enable researchers to understand and quantify the relationship between the variables in a data set, and the analysis considers more than one factor. The concentrations of Cu, Na, Mn, Zn, and Pb in most Z. clinopodioides samples were below the WHO (world health organization) limit for herbal medicines (10, 51,340, 200, 50, and 10 µg g-1 respectively), while Fe and Ca levels were higher than allowed (15 and 614 µg g-1 respectively). However, the WHO limit for Mg, K, Co, and Mo in medicinal plants has not yet been determined. The results of this study confirmed that different parts of Z. clinopodioides can be used as an important source for human nutrition due to its essential mineral elements.

Metabolomic study of serum in patients with invasive ductal breast carcinoma with LC-MS/MS approach.

BACKGROUND: Invasive ductal carcinoma (IDC) is the most common type of breast cancer so its early detection can lead to a significant decrease in mortality rate. However, prognostic factors for IDC are not adequate and we need novel markers for the treatment of different individuals. Although positron emission tomography and magnetic resonance imaging techniques are available, they are based on morphological features that do not provide any clue for molecular events accompanying cancer progression. In recent years, "omics" approaches have been extensively developed to propose novel molecular signatures of cancers as putative biomarkers, especially in biofluids. Therefore, a mass spectrometry-based metabolomics investigation was performed to find some putative metabolite markers of IDC and potential metabolites with prognostic value related to the estrogen receptor, progesterone receptor, lymphovascular invasion, and human epidermal growth factor receptor 2. METHODS: An untargeted metabolomics study of IDC patients was performed by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). The multivariate principal component analysis by XCMS online built a model that could separate the study groups and define the significantly altered m/z parameters. The most important biological pathways were also identified by pathway enrichment analysis. RESULTS: The results showed that the significantly altered metabolites in IDC serum samples mostly belonged to amino acids and lipids. The most important involved pathways included arginine and proline metabolism, glycerophospholipid metabolism, and phenylalanine, tyrosine, and tryptophan biosynthesis. CONCLUSIONS: Significantly altered metabolites in IDC serum samples compared to healthy controls could lead to the development of metabolite-based potential biomarkers after confirmation with other methods and in large cohorts.

A Nuclear Magnetic Resonance-Based Metabolomic Study to Identify Metabolite Differences between Iranian Isolates of Leishmania major and Leishmania tropica.

Background: Cutaneous leishmaniasis caused by Leishmania species (L. spp) is one of the most important parasitic diseases in humans. To gain information on the metabolite variations and biochemical pathways between L. spp, we used the comparative metabolome of metacyclic promastigotes in the Iranian isolates of L. major and L. tropica by proton nuclear magnetic resonance (1H-NMR). Methods: L. tropica and L. major were collected from three areas of Iran, namely Gonbad, Mashhad, and Bam, between 2017 and 2018, and were cultured. The metacyclic promastigote of each species was separated, and cell metabolites were extracted. 1H-NMR spectroscopy was applied, and the data were processed using ProMatab in MATLAB (version 7.8.0.347). Multivariate statistical analyses, including the principal component analysis and the orthogonal projections to latent structures discriminant analysis, were performed to identify the discriminative metabolites between the two L. spp. Metabolites with variable influences in projection values of more than one and a P value of less than 0.05 were marked as significant differences. Results: A set of metabolites were detected, and 24 significantly differentially expressed metabolites were found between the metacyclic forms of L. major and L. tropica isolates. The top differential metabolites were methionine, aspartate, betaine, and acetylcarnitine, which were increased more in L. tropica than L. major (P<0.005), whereas asparagine, 3-hydroxybutyrate, L-proline, and kynurenine were increased significantly in L. major (P<0.01). The significantly altered metabolites were involved in eight metabolic pathways. Conclusion: Metabolomics, as an invaluable technique, yielded significant metabolites, and their biochemical pathways related to the metacyclic promastigotes of L. major and L. tropica. The findings offer greater insights into parasite biology and how pathogens adapt to their hosts.

Identification of key candidate genes and pathways associated with colorectal aberrant crypt foci-to-adenoma-to-carcinoma progression.

AIM: The present study aimed to detect key candidate genes and pathways involved in colorectal aberrant crypt foci-to-adenoma-to-carcinoma progression. BACKGROUND: Although colorectal cancer (CRC) is the third most common type of cancer, the involved signaling pathways and driver-genes remain largely unclear. CRC begins with the malignant transformation of precancerous lesions including aberrant crypt foci (ACF) and benign adenomatous polyp or adenoma. METHODS: A list of formerly reported ACF, adenoma, and CRC-associated proteins was obtained from GeneCards, and then the data in online David Bioinformatics Resources was analyzed. The protein-protein interactions were surveyed utilizing String database and Cytoscape software. After hubs and bottlenecks were recognized, the key genes and pathways were identified through different bioinformatics analysis. RESULTS: The most important pathways associated with colorectal aberrant crypt foci-to-adenoma progression were attributed to "pathways in cancer" and "chemokine signaling pathway" and those in adenoma-to-carcinoma progression were related to "pathways in cancer," "chemokine signaling pathway," and "Ras signaling pathway." The genes participating in these pathways are key ones. Furthermore, PRKACB, CUL2, and GSK3B were significant as the seed in the clusters related to adenoma and GNB1, RALBP1, ROCK1, and IKBKG in the clusters related to cancer. CONCLUSION: The key candidate genes and pathways in progress CRC formed precursor lesions were identified by integrated bioinformatics analysis. The results could lead to a better understanding of the cause and underlying molecular events as well as detection of therapeutic targets for CRC.

Proteomic study of advanced cirrhosis based on HCV to reveal potential biomarkers.

AIM: We aimed to carry out proteomic assessment of long-term effects of hepatitis C on liver. BACKGROUND: Cirrhosis is a condition where liver is damaged and loses its efficiency, and has the high rate of mortality in the world. Proteome profiling may help to identify important proteins and find the pathogenesis Cirrhosis is a condition where liver is damaged and loses its efficiency, and has the high rate of mortality in the world. Proteome profiling may help to identify important proteins and find the pathogenesis. METHODS: Here, by the application of two-dimensional polyacrylamide gel electrophoresis (2-D PAGE), combined with (MALDI-TOF-TOF MS), proteome profile of decompensated HCV cirrhosis is determined compared to healthy matched controls. Furthermore, Cytoscape has used network analysis. The proteome comparison between two groups identified proteins with significant expression changes (p<0.05 and fold change ≥ 1.5). RESULTS: We found upregulation of IGHA1, C3, A1BG, IGKC and one isoform of HP. Also, lower expression of APOA4 and the other spot of HP in advanced cirrhosis patients were revealed based on HCV compared to matched controls. According to network analysis, ALB has been introduced as a key protein, which may play an important role in pathogenesis. CONCLUSION: Integration of the proteomics with protein interaction data led to the identification of several novel key proteins related to the immune system that may reflect the long-term effects of hepatitis C virus on the liver, and can introduce as therapeutic targets for advanced HCV- cirrhosis.

Early diagnosis of colorectal cancer via plasma proteomic analysis of CRC and advanced adenomatous polyp.

AIM: This paper aimed to identify new candidate biomarkers in blood for early diagnosis of CRC. BACKGROUND: Colorectal cancer (CRC) is the third most widespread malignancies increasing globally. The high mortality rate associated with colorectal cancer is due to the delayed diagnosis in an advanced stage while the metastasis has occurred. For better clinical management and subsequently to reduce mortality of CRC, early detection biomarkers are in high demand. METHODS: A 2D-PAGE separation of proteins was performed followed by tandem mass Spectrometry (MALDI-TOF-TOF) to discover potential plasma protein markers for CRC and AA (advanced adenomas). Furthermore, western blot method was used to confirm a part of the results in colorectal tissue samples. RESULTS: The significantly altered proteins including HPR, HP, ALB, KRT1, APOA1, FGB, IGJ and C4A were down-regulated in polyp relative to normal, and CRC compare to polyp surprisingly, and inversely, ORM2 was up-regulated with the fold change ≥ 2 and p-value ≤ 0.05. We also surveyed APOA1, FGB, and C4A for further confirmation of their expression changes by western blotting. All three of them showed a decreasing trend from normal toward CRC tissue samples as it mentioned before, but just changes of FGB and C4A were significant. CONCLUSION: The results demonstrated that plasma proteins can be less invasive markers for the detection of CRC. FGB and C4A can be considered as plasma potential biomarkers to early diagnosis of CRC patients and understanding the underlying procedures in tumorigenesis. Undoubtedly, the additional study must be conducted on large scale cohorts to verify the results.

Metabolomic Analysis of Membranous Glomerulonephritis: Identification of a Diagnostic Panel and Pathogenic Pathways.

BACKGROUND: Primary membranous glomerulonephritis (MGN) is a major cause of nephrotic syndrome in adults. Its diagnosis is based on invasive biopsy, and the current traditional serum or urinary biomarkers, such as the anti-phospholipase A2 receptor, are not adequately sensitive or specific. AIM OF THE STUDY: Our purpose is to identify a sensitive and specific noninvasive panel of biomarkers for the diagnosis of MGN by using metabolomic techniques and to explore the pathogenic pathways that are involved in disease development. METHODS: The urine metabolome of 66 MGN patients, 31 healthy controls, and 72 disease controls, were analyzed using nuclear magnetic resonance (NMR) and gas chromatography-tandem mass spectrometry (GC-MS/MS). Advanced multivariate statistical analyses were performed for the construction of diagnostic models and biomarker discovery. Receiver operating characteristic (ROC) curve analysis was used to suggest the most sensitive and specific diagnostic panel. RESULTS: The NMR-based diagnostic model showed allantoic acid and deoxyuridine as the most overrepresented and underrepresented biomarkers, respectively differentiating MGN from both control groups. The GC-MS/MS-based diagnostic model showed oxalic acid as the most overrepresented biomarker and 2-hydroxyglutaric acid lactone as the only underrepresented specific biomarker. A panel of a combination of the most accurate predictors of NMR and GC-MS/MS was composed of α-hydroxybutyric acid, 3,4-Dihydroxymandelic acid, 5α-cholestanone, 2-hydroxyglutaric acid lactone, nicotinamide, epicoprostanol, and palmitic acid. Nine impaired pathways were identified in MGN, such as pyrimidine metabolism and NAD salvage. CONCLUSIONS: This comprehensive metabolomic study of MGN indicates a panel of promising biomarkers, which is complementary to current traditional biomarkers, and needs to be validated in a larger cohort.

Chronic kidney disease: a review of proteomic and metabolomic approaches to membranous glomerulonephritis, focal segmental glomerulosclerosis, and IgA nephropathy biomarkers.

Chronic Kidney Disease (CKD) is a global health problem annually affecting millions of people around the world. It is a comprehensive syndrome, and various factors may contribute to its occurrence. In this study, it was attempted to provide an accurate definition of chronic kidney disease; followed by focusing and discussing on molecular pathogenesis, novel diagnosis approaches based on biomarkers, recent effective antigens and new therapeutic procedures related to high-risk chronic kidney disease such as membranous glomerulonephritis, focal segmental glomerulosclerosis, and IgA nephropathy, which may lead to end-stage renal diseases. Additionally, a considerable number of metabolites and proteins that have previously been discovered and recommended as potential biomarkers of various CKDs using '-omics-' technologies, proteomics, and metabolomics were reviewed.

Serum-based metabolic alterations in patients with papillary thyroid carcinoma unveiled by non-targeted 1H-NMR metabolomics approach.

OBJECTIVES: As the most prevalent endocrine system malignancy, papillary thyroid carcinoma had a very fast rising incidence in recent years for unknown reasons besides the fact that the current methods in thyroid cancer diagnosis still hold some limitations. Therefore, the aim of this study was to improve the potential molecular markers for diagnosis of benign and malignant thyroid nodules to prevent unnecessary surgeries for benign tumors. MATERIALS AND METHODS: In this study, 1H-NMR metabolomics platform was used to seek the discriminating serum metabolites in malignant papillary thyroid carcinoma (PTC) compared to benign multinodular goiter (MNG) and healthy subjects and also to better understand the disease mechanisms using bioinformatics analysis. Multivariate statistical analysis showed that PTC and MNG samples could be successfully discriminated in PCA and OPLS-DA score plots. RESULTS: Significant metabolites that differentiated malignant and benign thyroid lesions included citrate, acetylcarnitine, glutamine, homoserine, glutathione, kynurenine, nicotinic acid, hippurate, tyrosine, tryptophan, ß-alanine, and xanthine. The significant metabolites in the PTC group compared to healthy subjects also included scyllo- and myo-inositol, tryptophan, propionate, lactate, homocysteine, 3-methyl glutaric acid, asparagine, aspartate, choline, and acetamide. The metabolite sets enrichment analysis demonstrated that aspartate metabolism and urea cycle were the most important pathways in papillary thyroid cancer progression. CONCLUSION: The study results demonstrated that serum metabolic fingerprinting could serve as a viable method for differentiating various thyroid lesions and for proposing novel potential markers for thyroid cancers. Obviously, further studies are needed for the validation of the results.

Deciphering the transcription factor-microRNA-target gene regulatory network associated with graphene oxide cytotoxicity.

Graphene oxide (GO) has recently emanated as a promising material in cancer treatment. To unveil the underlying mechanisms of microRNAs (miRNAs) and potential target genes involved in GO cytotoxicity, we firstly compiled GO-related miRNAs and genes in human cancer cell lines treated with GO from public databases and published works. Besides miRNAs as post-transcriptional regulators of gene expression, transcription factors (TFs) are also the main regulators at the transcriptional level. In the following, we explored the regulatory relationships between miRNAs, target genes, and TFs. Thereafter, a gene regulatory network consisting of GO-responsive miRNAs, GO-responsive genes, and known human TFs was constructed. Then, 3-node regulatory motif types were detected in the resulting network. Among them, miRNA-FFL (feed-forward loop) was identified as a significant motif type. A total of 184 miRNA-FFLs were found and merged to generate a regulatory sub-network. Pathway analysis of the resulting sub-network highlighted adherens junction, focal adhesion, and TGFß signaling pathways as the major pathways that previous studies demonstrate them to be the affected pathways in GO-treated cells. Functional investigations displayed that miRNAs might be involved in the control of apoptosis through disruption of cell adhesion in response to cytotoxicity. Moreover, GO-cell interactions can lead to miRNA targeting of genes (i.e. Rac1 and RhoA) involved in the cytoskeleton assembly process. These specific toxic properties support biomedical applications of GO, especially for cancer therapy.

Network analysis of membranous glomerulonephritis based on metabolomics data.

Membranous glomerulonephritis (MGN) is one of the most frequent causes of nephrotic syndrome in adults. It is characterized by the thickening of the glomerular basement membrane in the renal tissue. The current diagnosis of MGN is based on renal biopsy and the detection of antibodies to the few podocyte antigens. Due to the limitations of the current diagnostic methods, including invasiveness and the lack of sensitivity of the current biomarkers, there is a requirement to identify more applicable biomarkers. The present study aimed to identify diagnostic metabolites that are involved in the development of the disease using topological features in the component­reaction­enzyme­gene (CREG) network for MGN. Significant differential metabolites in MGN compared with healthy controls were identified using proton nuclear magnetic resonance and gas chromatography­mass spectrometry techniques, and multivariate analysis. The CREG network for MGN was constructed, and metabolites with a high centrality and a striking fold­change in patients, compared with healthy controls, were introduced as putative diagnostic biomarkers. In addition, a protein­protein interaction (PPI) network, which was based on proteins associated with MGN, was built and analyzed using PPI analysis methods, including molecular complex detection and ClueGene Ontology. A total of 26 metabolites were identified as hub nodes in the CREG network, 13 of which had salient centrality and fold­changes: Dopamine, carnosine, fumarate, nicotinamide D­ribonucleotide, adenosine monophosphate, pyridoxal, deoxyguanosine triphosphate, L­citrulline, nicotinamide, phenylalanine, deoxyuridine, tryptamine and succinate. A total of 13 subnetworks were identified using PPI analysis. In total, two of the clusters contained seed proteins (phenylalanine­4­hydroxlylase and cystathionine γ­lyase) that were associated with MGN based on the CREG network. The following biological processes associated with MGN were identified using gene ontology analysis: 'Pyrimidine­containing compound biosynthetic process', 'purine ribonucleoside metabolic process', 'nucleoside catabolic process', 'ribonucleoside metabolic process' and 'aromatic amino acid family metabolic process'. The results of the present study may be helpful in the diagnostic and therapeutic procedures of MGN. However, validation is required in the future.

Decreased apolipoprotein A4 and increased complement component 3 as potential markers for papillary thyroid carcinoma: A proteomic study.

BACKGROUND:: Thyroid carcinomas have comprised the fastest rising incidence of cancer in the past decade. Currently, the diagnosis of thyroid tumors is performed by the fine-needle aspiration biopsy (FNAB) method, which still holds some challenges and limitations, mostly in discriminating malignant and benign lesions. Therefore, the development of molecular markers to distinguish between these lesion types are in progress. METHODS:: A 2D-PAGE separation of proteins was performed followed by tandem mass spectrometry with the aim of discovering potential serum protein markers for papillary thyroid carcinoma and multinodular goiter. Protein-protein interaction network analysis revealed the most important pathways involved in the progression of papillary thyroid cancer. The enzyme-linked immunosorbent assay method was used to confirm a part of the results. RESULTS:: The significantly altered proteins included C3, C4A, GC, HP, TTR, APOA4, APOH, ORM2, KRT10, AHSG, IGKV3-20, and IGKC. We also confirmed that increased complement component 3 and decreased apolipoprotein A4 occurred in papillary thyroid cancer. Network investigations demonstrated that complement activation cascades and PPAR signaling might play a role in the pathogenesis of thyroid cancer. CONCLUSION:: The results demonstrated that serum proteomics could serve as a viable method for proposing novel potential markers for thyroid tumors. Surely, further research must be performed in larger cohorts to validate the results.

Effect of ghrelin on serum metabolites in Alzheimer's disease model rats; a metabolomics studies based on 1H-NMR technique.

OBJECTIVES: Alzheimer's disease (AD) is dysfunction of the central nervous system and as a neurodegenerative disease. The objective of this work is to investigate metabolic profiling in the serum of animal models of AD compared to healthy controls and then to peruse the role of ghrelin as a therapeutic approach for the AD. MATERIALS AND METHODS: Nuclear magnetic resonance (NMR) technique was used for identification of metabolites that are differentially expressed in the serum of a rat model of the AD with or without ghrelin treatment. Using multivariate statistical analysis, models were built and indicated. RESULTS: There were significant differences and high predictive power between AD and ghrelin-treated groups. The area under curve (AUC) of receiver operating characteristic (ROC) curve and Q2 were 0.870 and 0.759, respectively. A biomarker panel consisting of 14 metabolites was identified to discriminate the AD from the control group. Another panel of 12 serum metabolites was used to differentiate AD models from treated models. CONCLUSION: Both panels had good agreements with clinical diagnosis. Analysis of the results displayed that ghrelin improved memory and cognitive abilities. Affected pathways by ghrelin included oxidative stress, and osteoporosis pathways and vascular risk factors.

Fluoxetine Regulates Ig Kappa Chain C Region Expression Levels in the Serum of Obsessive-Compulsive Disorder Patients: A proteomic Approach.

Obsessive-Compulsive Disorder (OCD) is one of the most common mental conditions. Proteome profiling may help identifying important proteins and finally shed lights to complexity of OCD underlying mechanisms. Here, by the application gel-based proteomic approach the proteome profile of patients with washing subtype of OCD before and after treatment with Fluoxetine (positive responders) are compared to healthy matched controls. However, only one of the differentially expressed proteins is examined and introduced in this paper. Proteomic analysis was done by the application of two-dimensional polyacrylamide gel electrophoresis (2-D PAGE), combined with (MALDI-TOF-TOF MS)-based. Furthermore, network analysis and biological annotation were handled by Cytoscape Plug-in and CluePedia. The proteome comparison between groups identified protein with the significant expression changes (p<0.05 and fold change ≥ 1.5). While the expression level of Ig Kappa Chain C Region is significantly decreased in OCD patients before any treatments, the trend is almost normalized after treatment with Fluoxetine in positive responders. In addition, interaction profile of IGKC shows that the interacting proteins may be affected as the expression pattern of IGKC changes in OCD patients. In conclusion, IGKC may be introduced as potential biomarker in our study; yet, investigation in bigger sample size and application of validation methods is a requirement.

Serum Proteomic Profiling of Obsessive-Compulsive Disorder, Washing Subtype: A Preliminary Study.

INTRODUCTION: Obsessive-Compulsive Disorder (OCD) is a disabling mental condition that its proteomic profiling is not yet investigated. Proteomics is a valuable tool to discover biomarker approaches. It can be helpful to detect protein expression changes in complex disorders such as OCD. METHODS: Here, by the application of 2D gel electrophoresis (2DE), a pilot study of serum proteome profile of females with washing subtype of OCD was performed. Serum samples were obtained from females with washing subtype of OCD. Following the protein extraction from the serum with acetone perception, the samples were subjected to 2DE for separation based on pI and molecular weight (MW) with triple replications. Finally, the protein spots were visualized using Coomassie blue staining method and analyzed by Progenesis SameSpots software. Furthermore, protein-protein interaction (PPI) network analysis was handled by the application of Cytoscape software. RESULTS: The results suggested that 41 matched spots demonstrated significant expression alterations among which 5 proteins including immunoglobulin heavy constant alpha-1 (IGHA1), apolipoprotein A-4 (APOA4), haptoglobin (HP), protein α-1-antitrypsin (SERPINA1), and component 3 (C3) were identified by database query. Additionally, PPI network analysis indicated the central role of SERPINA1 and C3 in the network integrity. However, albumin (ALB), amyloid precursor protein (APP), and protein α-1-antitrypsin (APOA1) proteins were important in OCD PPI network as well. The identified proteins were related to 3 processes: acute-phase response, hydrogen peroxide catabolic process, and regulation of triglyceride metabolic process. CONCLUSION: It was concluded that these proteins may have a fundamental role in OCD pathogenesis. Moreover, the dysregulation of inflammatory and antioxidant systems in OCD risk was suggested by the current study. However, evaluation of bigger sample sizes and application of mass spectrometry are essential requirements to confirm this preliminary evaluation.

NMR spectroscopy-based metabolomic study of serum in sulfur mustard exposed patients with lung disease.

Sulfur mustard (SM) is a vesication chemical warfare agent for which there is currently no antidote. Despite years of research, there is no common consensus about the pathophysiological basis of chronic pulmonary disease caused by this chemical warfare agent. In this study, we combined chemometric techniques with nuclear magnetic resonance (NMR) spectroscopy to explore the metabolic profile of sera from SM-exposed patients. A total of 29 serum samples obtained from 17 SM-injured patients, and 12 healthy controls were analyzed by Random Forest. Increased concentrations of seven amino acids, glycerol, dimethylamine, ketone bodies, lactate, acetate, citrulline and creatine together with the decreased very low-density lipoproteins (VLDL) levels were observed in patients compared with control subjects. Our study reveals the metabolic profile of sera from SM-injured patients and indicates that NMR-based methods can distinguish these patients from healthy controls.

Metabolomic analysis of human cirrhosis, hepatocellular carcinoma, non-alcoholic fatty liver disease and non-alcoholic steatohepatitis diseases.

Metabolome analysis is used to evaluate the characteristics and interactions of low molecular weight metabolites under a specific set of conditions. In cirrhosis, hepatocellular carcinoma, non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatotic hepatitis (NASH) the liver does not function thoroughly due to long-term damage. Unfortunately the early detection of cirrhosis, HCC, NAFLD and NASH is a clinical problem and determining a sensitive, specific and predictive novel method based on biomarker discovery is an important task. On the other hand, metabolomics has been reported as a new and powerful technology in biomarker discovery and dynamic field that cause global comprehension of system biology. In this review, it has been collected a heterogeneous set of metabolomics published studies to discovery of biomarkers in researches to introduce diagnostic biomarkers for early detection and the choice of patient-specific therapies.

NMR- and GC/MS-based metabolomics of sulfur mustard exposed individuals: a pilot study.

Sulfur mustard (SM) is a potent alkylating agent and its effects on cells and tissues are varied and complex. Due to limitations in the diagnostics of sulfur mustard exposed individuals (SMEIs) by noninvasive approaches, there is a great necessity to develop novel techniques and biomarkers for this condition. We present here the first nuclear magnetic resonance (NMR) and gas chromatography-mass spectrometry (GC/MS) metabolic profiling of serum from and healthy controls to identify novel biomarkers in blood serum for better diagnostics. Of note, SMEIs were exposed to SM 30 years ago and that differences between two groups could still be found. Pathways in which differences between SMEIs and healthy controls are observed are related to lipid metabolism, ketogenesis, tricarboxylic acid (TCA) cycle and amino acid metabolism.

Evaluation of liver cirrhosis and hepatocellular carcinoma using Protein-Protein Interaction Networks.

AIM: In the current study, we analysised only the articles that investigate serum proteome profile of cirrhosis patients or HCC patients versus healthy controls. BACKGROUND: Increased understanding of cancer biology has enabled identification of molecular events that lead to the discovery of numerous potential biomarkers in diseases. Protein-protein interaction networks is one of aspect that could elevate the understanding level of molecular events and protein connections that lead to the identification of genes and proteins associated with diseases. METHODS: Gene expression data, including 63 gene or protein names for hepatocellular carcinoma and 29 gene or protein names for cirrhosis, were extracted from a number of previous investigations. The networks of related differentially expressed genes were explored using Cytoscape and the PPI analysis methods such as MCODE and ClueGO. Centrality and cluster screening identified hub genes, including APOE, TTR, CLU, and APOA1 in cirrhosis. RESULTS: CLU and APOE belong to the regulation of positive regulation of neurofibrillary tangle assembly. HP and APOE involved in cellular oxidant detoxification. C4B and C4BP belong to the complement activation, classical pathway and acute inflammation response pathway. Also, it was reported TTR, TFRC, VWF, CLU, A2M, APOA1, CKAP5, ZNF648, CASP8, and HSP27 as hubs in HCC. In HCC, these include A2M that are corresponding to platelet degranulation, humoral immune response, and negative regulation of immune effector process. CLU belong to the reverse cholesterol transport, platelet degranulation and human immune response. APOA1 corresponds to the reverse cholesterol transport, platelet degranulation and humoral immune response, as well as negative regulation of immune effector process pathway. CONCLUSION: In conclusion, this study suggests that there is a common molecular relationship between cirrhosis and hepatocellular cancer that may help with identification of target molecules for early treatment that is essential in cancer therapy.