Non-obstructive azoospermia (NOA) occurs in approximately 10% of infertile men. Retrieval of the spermatozoa from the testicle of NOA patients is an invasive approach. Seminal plasma is an excellent source for exploring to find the biomarkers for presence of spermatozoa in testicular tissue. The present discovery phase study aimed to use metabolic fingerprinting to detect spermatogenesis from seminal plasma in NOA patients as a non-invasive method.In this study, 20 men with NOA were identified based on histological analysis who had their first testicular biopsy in 2015 at Avicenna Fertility Center, Tehran, Iran. They were divided into two groups, a positive testicular sperm extraction (TESE(+)) and a negative testicular sperm extraction (TESE(-)). Seminal plasma of NOA patients was collected before they underwent testicular sperm extraction (TESE) operation. The metabolomic fingerprinting was evaluated by Raman spectrometer. Principal component analysis (PCA) and an unsupervised statistical method, was used to detect outliers and find the structure of the data. The PCA was analyzed by MATLAB software.Metabolic fingerprinting of seminal plasma from NOA showed that TESE (+) versus TESE(-) patients were classified by PCA. Furthermore, a possible subdivision of TESE(-) group was observed. Additionally, TESE(-) patients were in extreme oxidative imbalance compared to TESE(+) patients.Metabolic fingerprinting of seminal plasma can be considered as a breakthrough, an easy and cheap method for prediction presence of spermatogenesis in NOA.
Insulin resistance (IR) evolved from excessive energy intake and poor energy expenditure, affecting the patient's quality of life. Amino acid and acylcarnitine metabolomic profiles have identified consistent patterns associated with metabolic disease and insulin sensitivity. Here, we have measured a wide array of metabolites (30 acylcarnitines and 20 amino acids) with the MS/MS and investigated the association of metabolic profile with insulin resistance.The study population (n = 403) was randomly chosen from non-diabetic participants of the Surveillance of Risk Factors of NCDs in Iran Study (STEPS 2016). STEPS 2016 is a population-based cross-sectional study conducted periodically on adults aged 18-75 years in 30 provinces of Iran. Participants were divided into two groups according to the optimal cut-off point determined by the Youden index of HOMA-IR for the diagnosis of metabolic syndrome. Associations were investigated using regression models adjusted for age, sex, and body mass index (BMI).People with high IR were significantly younger, and had higher education level, BMI, waist circumference, FPG, HbA1c, ALT, triglyceride, cholesterol, non-HDL cholesterol, uric acid, and a lower HDL-C level. We observed a strong positive association of serum BCAA (valine and leucine), AAA (tyrosine, tryptophan, and phenylalanine), alanine, and C0 (free carnitine) with IR (HOMA-IR); while C18:1 (oleoyl L-carnitine) was inversely correlated with IR.In the present study, we identified specific metabolites linked to HOMA-IR that improved IR prediction. In summary, our study adds more evidence that a particular metabolomic profile perturbation is associated with metabolic disease and reemphasizes the significance of understanding the biochemistry and physiology which lead to these associations.
Molecular pathophysiology of COVID-19 is not completely known. Expression changes in patients' plasma proteins have revealed new information about the disease. Introducing the key targeted plasma protein in fatal conditions of COVID-19 infection is the aim of this study.Significant differentially expressed proteins (DEPs) in the plasma of cases with a fatal condition of COVID-19 were extracted from an original article. These proteins were included in a network via STRING database along with 100 first neighbor proteins to determine central nodes of the network for analyzing.Queried and added proteins were included in a scale free network. Three hub nodes were identified as critical target proteins. The top queried hub proteins were chains of fibrinogen; Fibrinogen Alpha chain (FGA), Fibrinogen gamma chain (FGG), and Fibrinogen beta chain (FGB), which are related to the coagulation process.It seems that fibrinogen dysregulation has a deep impact on the fatality of COVID-19 infection.
Background: Although the application of ultraviolet B (UVB) in phototherapy of human skin is a common therapeutic method, it is known as a risk factor for skin cancer. This study aims to assess the role of differentially expressed genes (DEGs) to find the critical one that is mainly responsible for skin protection against UVB radiation.Methods: The gene expression profiles of irradiated mice by UVB that issued skin protection against exposure are extracted from Gene Expression Omnibus (GEO) and analyzed by GEO2R. The significant DEGs are assessed via gene ontology (GO) analysis and the critical individuals are investigated via action mapping.Results: Thirty-eight significant DEGs that provide skin resistance against UVB irradiation were determined. Among the query DEGs, 26 individuals were related to 43 biological terms. Flt4, F3, Tspan6, Cblb, and Itgb6 were highlighted as the critical DEGs to promote skin protection against UVB irradiation.Conclusion: The finding indicates that Flt4 is the key DEG that is mainly responsible for protecting skin from UVB exposure.
Introducing possible diagnostic and therapeutic biomarker candidates via the identification of chief dysregulated proteins in COVID-19 patients is the aim of this study.Molecular studies, especially proteomics, can be considered as suitable approaches for discovering the hidden aspect of the disease.Differentially expressed proteins (DEPs) of three patients with demonstrated severe condition (S-COVID-19) were compared to healthy cases by a proteomics study. Cytoscape software and STRING database were used to construct the protein-protein interaction (PPI) network. The central DEPs were identified through topological analysis of the network. ClueGO+CluePedia were applied to find the biological processes related to the central nodes. MCODE molecular complex detection (MCODE) was used to discover protein complexes.A total of 242 DEPs from among 256 query ones were included in the network. Centrality analysis of the network assigned 16 hub-bottlenecks, nine of which were presented in the highest-scored protein complex. Ten protein complexes were determined. APOA1 was identified as the protein complex seed, and APP, EGF, and C3 were the top hub-bottlenecks of the network. The results specify that up-regulation of C3 and down-regulation of APOA1 in urine play a role in the stiffness in respiration and, accordingly, the severity of COVID-19. Moreover, dysregulation of APP and APOA1 could both contribute to the possible adverse effects of COVID-19 on the nervous system.The introduced central proteins of the S-COVID-19 interaction network, particularly APOA1, can be considered as diagnostic and therapeutic targets related to the coronavirus disease after being approved with complementary studies.
'%3e%3cg id='e'%3e%3cg id='c' fill='none' stroke='%23fff' stroke-width='2'%3e%3cpath id='b' d='M0 1h26M1 10V5h8v4h8V5h-5M4 9h2m20 0h-5V5h8m0-5v9h8V0m-4 0v9' transform='scale(1.4)'/%3e%3cpath id='a' d='M0 7h9m1 0h9' transform='scale(2.8)'/%3e%3cuse xlink:href='%23a' y='120'/%3e%3cuse xlink:href='%23b' y='145.2'/%3e%3c/g%3e%3cg id='d'%3e%3cuse xlink:href='%23c' x='56'/%3e%3cuse xlink:href='%23c' x='112'/%3e%3cuse xlink:href='%23c' x='168'/%3e%3c/g%3e%3c/g%3e%3cuse xlink:href='%23d' x='168'/%3e%3cuse xlink:href='%23e' x='392'/%3e%3c/g%3e%3cg fill='%23da0000' transform='matrix(45 0 0 45 315 180)'%3e%3cg id='f'%3e%3cpath d='M-.548.836A.912.912 0 0 0 .329-.722 1 1 0 0 1-.548.836'/%3e%3cpath d='M.618.661A.764.764 0 0 0 .422-.74 1 1 0 0 1 .618.661M0 1l-.05-1L0-.787a.31.31 0 0 0 .118.099V-.1l-.04.993zM-.02-.85 0-.831a.144.144 0 0 0 .252-.137A.136.136 0 0 1 0-.925'/%3e%3c/g%3e%3cuse xlink:href='%23f' transform='scale(-1 1)'/%3e%3c/g%3e%3c/svg%3e)
