Comparison of different artificial neural network architectures in modeling of Chlorella sp. flocculation

Biodiesel production from microalgae feedstock should be performed after growth and harvesting of the cells, and the most feasible method for harvesting and dewatering of microalgae is flocculation. Flocculation modeling can be used for evaluation and prediction of its performance under different affective parameters. However, the modeling of flocculation in microalgae is not simple and has not performed yet, under all experimental conditions, mostly due to different behaviors of microalgae cells during the process under different flocculation conditions. In the current study, the modeling of microalgae flocculation is studied with different neural network architectures. Microalgae species, Chlorella sp., was flocculated with ferric chloride under different conditions and then the experimental data modeled using artificial neural network. Neural network architectures of multilayer perceptron (MLP) and radial basis function architectures, failed to predict the targets successfully, though, modeling was effective with ensemble architecture of MLP networks. Comparison between the performances of the ensemble and each individual network explains the ability of the ensemble architecture in microalgae flocculation modeling.     

Anti-hyperglycemic effects of Eryngium billardierei F. Delaroche extract on insulin-resistance HepG2 cells in vitro

Background

Insulin resistance as a major problem is associated with type 2 diabetes mellitus. This study investigated the effect of Eryngium billardierei on insulin-resistance induced HepG2 cells.

Methods and results

MTT method was used to evaluate the viability of HepG2 cells treated with various doses of E. billardierei extract. An insulin-resistance model was established in HepG2 cells. Next, MTT assay and Acridine orange staining were performed to investigate the viability of cells in the vicinity of different concentrations of insulin, pioglitazone, and E. billardierei extract in an insulin-resistance media. The glucose uptake test was performed to select the optimal insulin concentration. Expression levels of IR, G6Pase, and PEPCK genes were assessed by real-time RT-PCR. According to obtained data, E. billardierei at concentrations of 0.5 and 1 mg/mL show no toxicity on cells. Furthermore, based on MTT assay and glucose uptake test 10^?5 mol/L insulin was chosen as the model group to induce insulin-resistance in HepG2 cells for gene expression analysis. Finally, 1 mg/mL E. billardierei not only induced no cytotoxicity but also showed an increase in the expression of IR as well as a reduction in G6Pase and PEPCK level compared to the control and model groups.

Conclusions

The obtained data indicated that 1 mg/mL E. billardierei might have an anti-insulin resistance effect on insulin-resistance HepG2 cells in vitro and could be a promising candidate with anti-hyperglycemic properties for diabetes treatments.

Graphical abstract

     

ROTS: reproducible RNA-seq biomarker detector—prognostic markers for clear cell renal cell cancer

Recent comprehensive assessments of RNA-seq technology support its utility in quantifying gene expression in various samples. The next step of rigorously quantifying differences between sample groups, however, still lacks well-defined best practices. Although a number of advanced statistical methods have been developed, several studies demonstrate that their performance depends strongly on the data under analysis, which compromises practical utility in real biomedical studies. As a solution, we propose to use a data-adaptive procedure that selects an optimal statistic capable of maximizing reproducibility of detections. After demonstrating its improved sensitivity and specificity in a controlled spike-in study, the utility of the procedure is confirmed in a real biomedical study by identifying prognostic markers for clear cell renal cell carcinoma (ccRCC). In addition to identifying several genes previously associated with ccRCC prognosis, several potential new biomarkers among genes regulating cell growth, metabolism and solute transport were detected.     

Predicting efficiency of different chemical extraction methods in risk assessment of trace metals in sediment of the Persian Gulf

Different chemical methods have been developed to evaluate the bioavailable fraction of the trace metals. Due to the lack of a universal method for analysis of the bioavailable metal fractions, due to the differences in sediment characteristics, it is necessary to validate an appropriate chemical method for assessing the available fraction of trace metals. For this propose, in this study, different chemical extraction methods including extraction with HCl and desorption test as a single reagent leaching test as well as geochemical fractions method have been evaluated. Bushehr coastal sediments in the Persian Gulf coasts have been selected for this purpose. To validate the efficacy of these methods, a gastropod species (Trochus erithreus), as a bioindicator, has been selected and monitored for trace metals of Fe²⁺, Pb²⁺, Cu²⁺, Zn²⁺, Mn²⁺, and Ni²⁺. According to the one-way ANOVA results, all partial extraction methods for all the trace metals (except for Mn²⁺) showed no significant variation, but linear correlation coefficients were between the results of the selective chemical extraction methods and concentrations of trace metals in organism tissues. It offered that selective extraction with HCl can be used as a simple method for measuring the bioavailable fraction of the metals in the sediments.     

Modulation of Glucose Transporter Protein by Dietary Flavonoids in Type 2 Diabetes Mellitus

Diabetes mellitus (DM) is a metabolic diseases characterized by hyperglycemia due to insufficient or inefficient insulin secretory response. This chronic disease is a global problem and there is a need for greater emphasis on therapeutic strategies in the health system. Phytochemicals such as flavonoids have recently attracted attention as source materials for the development of new antidiabetic drugs or alternative therapy for the management of diabetes and its related complications. The antidiabetic potential of flavonoids are mainly through their modulatory effects on glucose transporter by enhancing GLUT-2 expression in pancreatic β cells and increasing expression and promoting translocation of GLUT-4 via PI3K/AKT, CAP/Cb1/TC10 and AMPK pathways. This review highlights the recent findings on beneficial effects of flavonoids in the management of diabetes with particular emphasis on the investigations that explore the role of these compounds in modulating glucose transporter proteins at cellular and molecular level.     

A Novel Molecular Design for a Hybrid Phage-DNA Construct Against DKK1

Nucleic acid immunization has recently exhibited a great promise for immunotherapy of various diseases. However, it is now clear that powerful strategies are imminently needed to improve their efficiency. In this regard, whole bacteriophage particles have been described as efficient DNA vaccine delivery vehicles, capable of circumventing the limitations of naked DNA immunization. Moreover, phage particles could be engineered to display specific peptides on their surfaces. Given these inherent characteristics of phages, we have designed a novel hybrid phage-DNA immunization vector using both M13 and pAAV plasmid elements. Following the construction and in vitro confirmation of the designed vectors, they were used for comparative mice immunization, carrying the same DNA sequence. The results indicated the efficacy of the designed hybrid phage particles, to elicit higher humoral immunity, in comparison to conventional DNA-immunization vectors (pCI). In light of these findings, it could be concluded that using adeno-associated virus (AAV) expression cassette along with displaying TAT peptide on the surface of the phage particle could be deemed as an appealing strategy to enhance the DNA-immunization and vaccination efficacy.