Association of xenobiotic-metabolizing enzymes (GSTM1 and GSTT 1), and pro-inflammatory cytokines (TNF-α and IL-6) genetic polymorphisms with non-alcoholic fatty liver disease

Molecular Biology Reports - Previous studies have revealed that genetic polymorphisms of the Glutathione S-transferase M1 and T1 (GSTM1 and GSTT1), tumor necrosis factor-α (TNF-α), and...     

RETRACTED ARTICLE: Serum Zinc and Adiponectin Levels in Patients with Polycystic Ovary Syndrome,Adjusted for Anthropometric,Biochemical, Dietary Intake,and Physical Activity Measures

Biological Trace Element Research -     

The ENPP1 K121Q polymorphism is not associated with type 2 diabetes and related metabolic traits in an Iranian population

The K121Q polymorphism of the ectoenzyme nucleotide pyrophosphate phosphodiesterase 1 (ENPP1) gene has been variably associated with insulin resistance and type 2 diabetes (T2D) in several populations. However, this association has not been studied in Iranian subjects and we hypothesized that the K121Q variant might be associated with T2D and related metabolic traits in this population. The K121Q genotypes were determined by PCR-restriction fragment length polymorphism in 377 normoglycemic controls and 155 T2D patients. T2D patients had significantly higher values for systolic and diastolic blood pressure, BMI, glucose, cholesterol, triglyceride, LDL, apoB, insulin, and HOMA-IR, and lower levels of HDL than the normoglycemic subjects. The frequency of the Q allele did not differ between T2D and normoglycemic subjects (OR 0.96, 95% CI 0.90-2.00, P?=?0.70). The Q allele frequency was 16.5% in T2D and 15.2% in normoglycemic subjects. The ENPP1 genotype (KQ?+?QQ) was not associated with the systolic and diastolic blood pressure, glucose, triglyceride, cholesterol, LDL-C and HDL-C, apo B, BMI, HOMA-IR, and insulin levels in both normoglycemic and T2D groups. Our results suggest that the ENPP1 121Q allele might not be associated with T2D and related metabolic traits among Iranian subjects.     

In Vitro Evaluation of a Soluble Leishmania Promastigote Surface Antigen as a Potential Vaccine Candidate against Human Leishmaniasis

PSA (Promastigote Surface Antigen) belongs to a family of membrane-bound and secreted proteins present in several Leishmania (L.) species. PSA is recognized by human Th1 cells and provides a high degree of protection in vaccinated mice. We evaluated humoral and cellular immune responses induced by a L. amazonensis PSA protein (LaPSA-38S) produced in a L. tarentolae expression system. This was done in individuals cured of cutaneous leishmaniasis due to L. major (CCLm) or L. braziliensis (CCLb) or visceral leishmaniasis due to L. donovani (CVLd) and in healthy individuals. Healthy individuals were subdivided into immune (HHR-Lm and HHR-Li: Healthy High Responders living in an endemic area for L. major or L. infantum infection) or non immune/naive individuals (HLR: Healthy Low Responders), depending on whether they produce high or low levels of IFN-γ in response to Leishmania soluble antigen. Low levels of total IgG antibodies to LaPSA-38S were detected in sera from the studied groups. Interestingly, LaPSA-38S induced specific and significant levels of IFN-γ, granzyme B and IL-10 in CCLm, HHR-Lm and HHR-Li groups, with HHR-Li group producing TNF-α in more. No significant cytokine response was observed in individuals immune to L. braziliensis or L. donovani infection. Phenotypic analysis showed a significant increase in CD4+ T cells producing IFN-γ after LaPSA-38S stimulation, in CCLm. A high positive correlation was observed between the percentage of IFN-γ-producing CD4+ T cells and the released IFN-γ. We showed that the LaPSA-38S protein was able to induce a mixed Th1 and Th2/Treg cytokine response in individuals with immunity to L. major or L. infantum infection indicating that it may be exploited as a vaccine candidate. We also showed, to our knowledge for the first time, the capacity of Leishmania PSA protein to induce granzyme B production in humans with immunity to L. major and L. infantum infection.     

Understanding the Underlying Mechanism of HA-Subtyping in the Level of Physic-Chemical Characteristics of Protein

The evolution of the influenza A virus to increase its host range is a major concern worldwide. Molecular mechanisms of increasing host range are largely unknown. Influenza surface proteins play determining roles in reorganization of host-sialic acid receptors and host range. In an attempt to uncover the physic-chemical attributes which govern HA subtyping, we performed a large scale functional analysis of over 7000 sequences of 16 different HA subtypes. Large number (896) of physic-chemical protein characteristics were calculated for each HA sequence. Then, 10 different attribute weighting algorithms were used to find the key characteristics distinguishing HA subtypes. Furthermore, to discover machine leaning models which can predict HA subtypes, various Decision Tree, Support Vector Machine, Naïve Bayes, and Neural Network models were trained on calculated protein characteristics dataset as well as 10 trimmed datasets generated by attribute weighting algorithms. The prediction accuracies of the machine learning methods were evaluated by 10-fold cross validation. The results highlighted the frequency of Gln (selected by 80% of attribute weighting algorithms), percentage/frequency of Tyr, percentage of Cys, and frequencies of Try and Glu (selected by 70% of attribute weighting algorithms) as the key features that are associated with HA subtyping. Random Forest tree induction algorithm and RBF kernel function of SVM (scaled by grid search) showed high accuracy of 98% in clustering and predicting HA subtypes based on protein attributes. Decision tree models were successful in monitoring the short mutation/reassortment paths by which influenza virus can gain the key protein structure of another HA subtype and increase its host range in a short period of time with less energy consumption. Extracting and mining a large number of amino acid attributes of HA subtypes of influenza A virus through supervised algorithms represent a new avenue for understanding and predicting possible future structure of influenza pandemics.     

MaxHiC: A robust background correction model to identify biologically relevant chromatin interactions in Hi-C and capture Hi-C experiments

Hi-C is a genome-wide chromosome conformation capture technology that detects interactions between pairs of genomic regions and exploits higher order chromatin structures. Conceptually Hi-C data counts interaction frequencies between every position in the genome and every other position. Biologically functional interactions are expected to occur more frequently than transient background and artefactual interactions. To identify biologically relevant interactions, several background models that take biases such as distance, GC content and mappability into account have been proposed. Here we introduce MaxHiC, a background correction tool that deals with these complex biases and robustly identifies statistically significant interactions in both Hi-C and capture Hi-C experiments. MaxHiC uses a negative binomial distribution model and a maximum likelihood technique to correct biases in both Hi-C and capture Hi-C libraries. We systematically benchmark MaxHiC against major Hi-C background correction tools including Hi-C significant interaction callers (SIC) and Hi-C loop callers using published Hi-C, capture Hi-C, and Micro-C datasets. Our results demonstrate that 1) Interacting regions identified by MaxHiC have significantly greater levels of overlap with known regulatory features (e.g. active chromatin histone marks, CTCF binding sites, DNase sensitivity) and also disease-associated genome-wide association SNPs than those identified by currently existing models, 2) the pairs of interacting regions are more likely to be linked by eQTL pairs and 3) more likely to link known regulatory features including known functional enhancer-promoter pairs validated by CRISPRi than any of the existing methods. We also demonstrate that interactions between different genomic region types have distinct distance distributions only revealed by MaxHiC. MaxHiC is publicly available as a python package for the analysis of Hi-C, capture Hi-C and Micro-C data.     

Molecular testing of <Emphasis Type="Italic">Klebsiella pneumoniae</Emphasis> contaminating tissue allografts recovered from deceased donors

Microbiological screening of tissue allografts is crucial to prevent the transmission of bacterial and fungal infections to transplant recipients. Klebsiella was the most prevalent and resistant contaminating microorganism observed in our setting in the Iranian Tissue Bank. This study was conducted to determine the presence of extended-spectrum β-lactamase (ESBL) genes, antimicrobial resistance patterns of Klebsiella pneumoniae isolates, and their clonal relationships in allograft materials. K. pneumoniae contaminating bone and other tissue allografts recovered from deceased donors were identified and ESBL isolates were detected using a phenotypic confirmatory method. Antimicrobial susceptibility testing was carried out using the disk diffusion method. Distribution of ESBL genes and molecular typing were performed using polymerase chain reaction (PCR) and Repetitive-element (rep-PCR) methods. Of 3828 donated tissues, 51 (1.3%) were found contaminated by K. pneumoniae isolates. Compared to tissue allografts from brain-dead, heart-beating tissue donors, allografts from donors with circulatory cessation were associated with a higher risk of K. pneumoniae contamination [odds ratio (OR), 1.2 (CI 95% 0.9–2.3) (P value < 0.001)]. Half of the isolates produced ESBL, and the rate of susceptibility to cephalosporins was 51%. Among isolates, 22 (43.1%) harbored CTX-M, 31 (60.8%) SHV, and 9 (17.6%) harbored TEM types. The rep-dendrogram indicated that clones having identical or related strains with a similar antibiotype were isolated in the same period. This study provides evidence that a single clone of K. pneumoniae contaminated tissue allografts recovered from many different donors. A single clone found on tissues from several donors suggests contamination of tissues from a single source such as the tissue recovery process and environment. Genomic DNA testing and clonality of contaminating bacteria using molecular methods can focus the epidemiologic investigation on the tissue allograft recovery process including a search for contamination of the tissue recovery room environment, recovery staff, recovery equipment, reagents, solutions and supplies.     

Comparison of different solvents for extraction of polyhydroxybutyrate from Cupriavidus necator

Polyhydroxybutyrate (PHBs) have attracted much attention due to their biodegradability and biocompatibility properties. The main drawback to the commercial production of them is their high cost. The recovery of PHB from bacterial cytoplasm significantly increases total processing costs. Efficient, economical, and environment‐friendly extraction of PHB from cells is required for its industrial production. In the present study, several nonhalogenated organic solvents (ethylene carbonate, dimethyl sulfoxide, dimethyl formamide, hexane, propanol, methanol, and acetic acid) were examined for their efficacy regarding recovery at different temperatures from culture broth containing Cupriavidus necator cells. The highest recovery percentage (98.6%) and product purity (up to 98%) were seen to be those of ethylene carbonate‐assisted extraction at 150°C within 60 min of incubation time. Average molecular weight of the recovered PHB (1.3 × 10⁶) was not significantly affected by the extraction solvent and conditions. The melting point of PHB extracted using ethylene carbonate was measured to be 176.2°C with an enthalpy of fusion of 16.8% and the corresponding degree of crystallinity of 59.2%. NMR and GC analyses confirmed that the extracted biopolymer was PHB. The presented strategy can help researchers to reduce the cost to obtain the final product.     

Cold plasma relieved toxicity signs of nano zinc oxide in <Emphasis Type="Italic">Capsicum annuum</Emphasis> cayenne via modifying growth,differentiation, and physiology

Taking functional scientific devices and metal-based nanoparticles into account, the present research was carried out to evaluate the plant (Capsicum annuum) responses to cold plasma and zinc oxide nanoparticle (nZnO) in in vitro and pot conditions. Seeds were exposed to plasma (0.84 W/cm² surface power densities) with three exposure times (0, 60, and 120 s) and/or two concentrations of nZnO (0 and 100 mgl^??1). The treated seeds were cultured in hormone-free MS medium (MS) or supplemented with 2 mgl^??1 BA and 0.5 mgl^??1 IAA (MSH). The seed pre-treatment with plasma enhanced a germination process and plant early growth, in contrast with the nZnO treatment. The treatment of nZnO significantly decreased the total fresh mass and leaf area in the seedlings grown in both culture media, while its growth-delaying impact was mitigated by the plasma treatment. The chlorophyll a and carotenoid were increased to 39.35 and 32% for the plasma-treated seedlings, respectively, than the control. The plasma and/or nZnO treatments acted as effective elicitors to induce the peroxidase activities in both culture media. Similarly, the activities of phenylalanine ammonia-lyase and soluble phenols were found to be significantly higher in the plasma and/or nZnO groups in both roots and leaves. Interestingly, inhibiting effects of nZnO on xylem differentiation was alleviated by the plasma treatments. In the pot condition, soaking seeds before the plasma treatment was the most effective method to affect plant growth. This is a first report reflecting the potential benefits of the cold plasma treatment to improve plant growth and resistance to the nanoparticle.