Ability of the matrix protein of vesicular stomatitis virus to suppress beta interferon gene expression is genetically correlated with the inhibition of host RNA and protein synthesis

The vesicular stomatitis virus (VSV) matrix (M) protein plays a major role in the virus-induced inhibition of host gene expression. It has been proposed that the inhibition of host gene expression by M protein is responsible for suppressing activation of host interferon gene expression. Most wild-type (wt) strains of VSV induce little if any interferon gene expression. Interferon-inducing mutants of VSV have been isolated previously, many of which contain mutations in their M proteins. However, it was not known whether these M protein mutations were responsible for the interferon-inducing phenotype of these viruses. Alternatively, mutations in other genes besides the M gene may enhance the ability of VSV to induce interferons. These hypotheses were tested by transfecting cells with mRNA expressing wt and mutant M proteins in the absence of other viral components and determining their ability to inhibit interferon gene expression. The M protein mutations were the M51R mutation originally found in the tsO82 and T1026R1 mutant viruses, the double substitution V221F and S226R found in the TP3 mutant virus, and the triple substitution E213A, V221F, and S226R found in the TP2 mutant virus. wt M proteins suppressed expression of luciferase from the simian virus 40 promoter and from the beta interferon (IFN-beta) promoter, while M proteins of interferon-inducing viruses were unable to inhibit luciferase expression from either promoter. The M genes of the interferon-inducing mutants of VSV were incorporated into the wt background of a recombinant VSV infectious cDNA clone. The resulting recombinant viruses were tested for their ability to activate interferon gene expression and for their ability to inhibit host RNA and protein synthesis. Each of the recombinant viruses containing M protein mutations induced expression of a luciferase reporter gene driven by the IFN-beta promoter and induced production of interferon bioactivity more effectively than viruses containing wt M proteins. Furthermore, the M protein mutant viruses were defective in their ability to inhibit both host RNA synthesis and host protein synthesis. These data support the idea that wt M protein suppresses interferon gene expression through the general inhibition of host RNA and protein synthesis.     

Study of quercetin and fisetin synergistic effect on breast cancer and potentially involved signaling pathways

Naturally-derived drugs have drawn much attention in recent decades. Efficiency, lower toxicity, and economic reasons are some of their advantages that justify this broad range of administration for different diseases, including cancer. If we can find a specific combination that boosts the effects of their single therapy, leading to synergism effect, increased efficiency, and decreased toxicity, they can act even better. Quercetin and fisetin, two well-known flavonoids, have been used to fight against various cancers. In this study, we investigated their possible synergism quercetin and fisetin on MCF7, MDA-MB-231, BT549, T47D, and 4T1 breast cancer cell lines. Then the optimum combined dose was used to study their impacts on wound healing abilities and clonogenic properties. The real-time qPCR was used to study the expression of their validated downstream effectors in predicted pathways. A significant synergism effect (p < .01, combination index: <1) was observed for all cell lines. Combination therapy was significantly more effective in colony formation (p < .0001) and wound healing assays (p < .001) compared to single therapies. The expression level of potential effectors was also showed a greater change. In vivo study confirmed the in vitro results and showed how significantly (p < .001) their synergism promotes their singular function in inhibiting cancer progression. The breast cancer mouse models receiving combined therapy lived longer with higher average body weight and smaller tumor sizes. These results exhibit that quercetin and fisetin inhibit cancer cell proliferation, migration and colony formation synergistically, and matrix metalloproteinase signaling and apoptotic pathways are relatively responsible for inhibitory activities.     

Diagnostic and prognostic value of circular RNA CDR1as/ciRS‐7 for solid tumours: A systematic review and meta‐analysis

The circular RNA, CDR1as/ciRS‐7, functions as a vital regulator in various cancers; however, the predictive value of CDR1as remains controversial. Therefore, a comprehensive analysis for clarifying the precise diagnostic and prognostic value of CDR1as in solid tumours is needed. A literature review of several databases was conducted for identifying potential studies. Pooled odds ratios (ORs) and hazard ratios (HRs) were used for evaluating the diagnostic accuracy variables and survival. Overall, 15 studies (1787 patients) and 11 studies (1578 patients) were included for diagnostic and prognostic outcome syntheses, respectively. Up‐regulated CDR1as expression was found to be correlated with worse clinicopathological characteristics, including the T status, N status, histological grade, TNM stage and distant metastasis. The synthesized sensitivity was 0.72 (95% confidence interval [CI], 0.65‐0.79), and the specificity was 0.80 (95% CI, 0.74‐0.86). The positive likelihood ratio (LR), negative LR and diagnostic odds ratio (DOR) were 3.70, 0.34 and 10.80, respectively. The area under the receiver operator characteristic curve was 0.84 (95% CI, 0.80‐0.87). In the pooled prognostic analysis, patients with high CDR1as expression had worse overall survival (HR = 2.40, P < 0.001) and disease‐free survival (HR = 1.74, P < 0.001). These results suggest that CDR1as is a reliable diagnostic and prognostic biomarker with high accuracy and efficiency, which may potentially facilitate clinical decisions on solid tumours in the future.     

Using paracrine effects of Ad-MSCs on keratinocyte cultivation and fabrication of epidermal sheets for improving clinical applications

Recent advances in wound healing have made cell therapy a potential approach for the treatment of various types of skin defects such as trauma, burns, scars and diabetic leg ulcers. Cultured keratinocytes have been applied to burn patients since 1981. Patients with acute and chronic wounds can be treated with autologous/allograft cultured keratinocytes. There are various methods for cultivation of epidermal keratinocytes used in cell therapy. One of the important properties of an efficient cell therapy is the preservation of epidermal stem cells. Mesenchymal Stem Cells (MSCs) are major regulatory cells involved in the acceleration of wound healing via induction of cell proliferation, angiogenesis and stimulating the release of paracrine signaling molecules. Considering the beneficial effects of MSCs on wound healing, the main aim of the present study is investigating paracrine effects of Adipose-derived Mesenchymal Stem Cell (Ad-MSCs) on cultivation of keratinocytes with focusing on preservation of stem cells and their differentiation process. We further introduced a new approach for culturing isolated keratinocytes in vitro in order to generate epidermal keratinocyte sheets without using a feeder layer. To do so, Ad-MSC conditioned medium was applied as an alternative to commercial media for keratinocyte cultivation. In this study, the expression of several stem/progenitor cell (P63, K19 and K14) and differentition (K10, IVL and FLG) markers was examined using real time PCR on days 7, 14 and 21 of culture in keratinocytes in Ad-MSC conditioned medium. P63 and α6 integrin expression was also evaluated via flow cytometry. The results were compared with control group including keratinocytes cultured in EpiLife medium and our data indicated that this Ad-MSC conditioned medium is a good alternative for keratinocyte cultivation and producing epidermal sheets for therapeutic and clinical purposes. The reasons are the expression of stem cell and differentiation markers and overcoming the requirement for feeder layer which leads to a xenograft-free transplantation. Besides, this approach has low cost and is easier to perform. However, more in vitro and in vivo experiments as well as safety evaluation required before clinical applications.     

An explorative study on potent Gram-negative specific LpxC inhibitors: CoMFA,CoMSIA, HQSAR and molecular docking

Pathogenic Gram-negative bacteria are responsible for nearly half of the serious human infections. Hologram quantitative structure–activity relationships (HQSAR), comparative molecular field analysis (CoMFA), and comparative molecular similarity index analysis (CoMSIA) were implemented on a group of 32 of potent Gram-negative LpxC inhibitors. The most effective HQSAR model was obtained using atoms, bonds, donor, and acceptor as fragment distinction. The cross-validated correlation coefficient (q²), non-cross-validated correlation coefficient (r²), and predictive correlation coefficient (r²_Pred) for test set of HQSAR model were 0.937, 0.993, and 0.892, respectively. The generated models were found to be statistically significant as the CoMFA model had (r²?=?0.967, q²?=?0.804, r²_Pred?=?0.827); the CoMSIA model had (r²?=?0.963, q²?=?0.752, r²_Pred?=?0.857). Molecular docking was employed to validate the results of the HQSAR, CoMFA, and CoMSIA models. Based on the obtained information, six new LpxC inhibitors have been designed.     

Contamination of breast milk with lead,mercury, arsenic,and cadmium in Iran: a systematic review and meta-analysis

BioMetals - Breast milk is a complete food for the development of the newborn, but it can also be an important route for environmental pollutants transmission to the infants. This study was aimed...     

A comparison study of the interaction between β-lactoglobulin and retinol at two different conditions: spectroscopic and molecular modeling approaches

The interaction between bovin β-Lactoglobulin (β-LG) and retinol at two different pH values was investigated by multispectroscopic, zeta potential, molecular modeling, and conductometry measurements. The steady state and polarization fluorescence spectroscopy revealed that complex formation at two different pH values could occur through a remarkable static quenching. According to fluorescence quenching, one set of binding site at pH 2 and two sets of binding sites at pH 7 were introduced for binding of retinol to β-LG that show the enhancement of saturation score of β-LG to retinol in dimmer condition. The polarization fluorescence analysis represented that there is more affinity between β-LG and retinol at pH 7 rather than at pH 2. The effect of retinol on β-LG was studied by UV-visible, circular dichroism (CD), and synchronous fluorescence, which indicated that retinol induced more structural changes on β-LG at pH 7. β-LG–retinol complex formation at two different pH values was recorded via applying resonance light scattering (RLS) and zeta potential. Conductometry and RLS showed two different behaviors of interaction between β-LG and retinol at two different pH values; therefore, dimmer formation played important roles in different behaviors of interaction between β-LG and retinol. The zeta potential was the implied combination of electrostatic and hydrophobic forces which are involved in β-LG–retinol complex at two different pH values, and the hydrophobic interactions play a dominant role in complex formation. Molecular modeling was approved by all experimental results. The acquired results suggested that monomer and dimmer states of β-LG can be induced by retinol with different behaviors.     

Cytokine gene polymorphism and graft-versus-host disease: a survey in Iranian bone marrow transplanted patients

Graft versus host disease (GVHD) is a major complication of bone marrow transplantation (BMT). Numerous studies have shown the potential role of cytokine genotypes in the occurrence of GVHD. In this retrospective, case–control study we aimed to investigate the association between 13 cytokine genes and acute GVHD (aGVHD) after HLA-identical sibling BMT in 91 Iranian subjects. Negative association was found between aGVHD and donor IL-10/GCC haplotype or donor IL-4Ra-A allele in the population study. When compared within the leukemia subgroup, we observed positive association between recipient IL-1α ?889/C allele and aGVHD. Also there were negative association between recipient IL-10/CAA haplotype and donor IL-4Ra/A allele and development of aGVHD. Among the different genotypes only donor IL-4Ra and donor IL-12 showed significant association. We conclude that several cytokine polymorphisms are positively and negatively associated with aGVHD in Iranian HLA matched siblings, of which IL-4Ra and IL-12 may play important roles.     

Major depressive disorder diagnosis based on effective connectivity in EEG signals: a convolutional neural network and long short-term memory approach

Deep learning techniques have recently made considerable advances in the field of artificial intelligence. These methodologies can assist psychologists in early diagnosis of mental disorders and preventing severe trauma. Major Depression Disorder (MDD) is a common and serious medical condition whose exact manifestations are not fully understood. So, early discovery of MDD patients helps to cure or limit the adverse effects. Electroencephalogram (EEG) is prominently used to study brain diseases such as MDD due to having high temporal resolution information, and being a noninvasive, inexpensive and portable method. This paper has proposed an EEG-based deep learning framework that automatically discriminates MDD patients from healthy controls. First, the relationships among EEG channels in the form of effective brain connectivity analysis are extracted by Generalized Partial Directed Coherence (GPDC) and Direct directed transfer function (dDTF) methods. A novel combination of sixteen connectivity methods (GPDC and dDTF in eight frequency bands) was used to construct an image for each individual. Finally, the constructed images of EEG signals are applied to the five different deep learning architectures. The first and second algorithms were based on one and two-dimensional convolutional neural network (1DCNN–2DCNN). The third method is based on long short-term memory (LSTM) model, while the fourth and fifth algorithms utilized a combination of CNN with LSTM model namely, 1DCNN-LSTM and 2DCNN-LSTM. The proposed deep learning architectures automatically learn patterns in the constructed image of the EEG signals. The efficiency of the proposed algorithms is evaluated on resting state EEG data obtained from 30 healthy subjects and 34 MDD patients. The experiments show that the 1DCNN-LSTM applied on constructed image of effective connectivity achieves best results with accuracy of 99.24% due to specific architecture which captures the presence of spatial and temporal relations in the brain connectivity. The proposed method as a diagnostic tool is able to help clinicians for diagnosing the MDD patients for early diagnosis and treatment.