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.     

Machine learning models effectively distinguish attention-deficit/hyperactivity disorder using event-related potentials

Accurate diagnosis of Attention-Deficit/Hyperactivity Disorder (ADHD) is a significant challenge. Misdiagnosis has significant negative medical side effects. Due to the complex nature of this disorder, there is no computational expert system for diagnosis. Recently, automatic diagnosis of ADHD by machine learning analysis of brain signals has received an increased attention. This paper aimed to achieve an accurate model to discriminate between ADHD patients and healthy controls by pattern discovery. Event-Related Potentials (ERP) data were collected from ADHD patients and healthy controls. After pre-processing, ERP signals were decomposed and features were calculated for different frequency bands. The classification was carried out based on each feature using seven machine learning algorithms. Important features were then selected and combined. To find specific patterns for each model, the classification was repeated using the proposed patterns. Results indicated that the combination of complementary features can significantly improve the performance of the predictive models. The newly developed features, defined based on band power, were able to provide the best classification using the Generalized Linear Model, Logistic Regression, and Deep Learning with the average accuracy and Receiver operating characteristic curve > %99.85 and > 0.999, respectively. High and low frequencies (Beta, Delta) performed better than the mid, frequencies in the discrimination of ADHD from control. Altogether, this study developed a machine learning expert system that minimises misdiagnosis of ADHD and is beneficial for the evaluation of treatment efficacy.Graphical abstract      

Removal of heavy metals from industrial wastewater using microbial fuel cell

Removal efficiency of gold from a solution of pure tetrachloroaurate ions was investigated using microbial fuel cell (MFC) technology. The effects of type of catholyte solution and initial gold concentration on the removal efficiency were considered. Due to its presence at high levels in the gold wastewater, the effect of copper ions on the removal efficiency of the gold ions was also studied. The effects of pH and initial biomass concentration on the gold removal efficiency was also determined. The results showed that after 5 h contact time, 95% of gold removal efficiency from a wastewater containing 250 ppm of initial gold ions at ambient temperature using 80 g/L yeast concentration was achieved. After 48 h of the cell''s operation under the same condition, 98.86% of AuCl₄ ^– ions were successfully removed from the solution. At initial gold concentration in the waste solution of 250 ppm, pH 2, and initial yeast concentration of 80 g/L, 100% removal efficiency of the gold was achieved. On the other hand, the most suitable condition for copper removal was found at a pH of 5.2, where 53% removal efficiency from the waste solution was accomplished.     

Construction of miRNA‐lncRNA‐mRNA co‐expression network affecting EMT‐mediated cisplatin resistance in ovarian cancer

Platinum resistance is one of the major concerns in ovarian cancer treatment. Recent evidence shows the critical role of epithelial–mesenchymal transition (EMT) in this resistance. Epithelial‐like ovarian cancer cells show decreased sensitivity to cisplatin after cisplatin treatment. Our study prospected the association between epithelial phenotype and response to cisplatin in ovarian cancer. Microarray dataset {"type":"entrez-geo","attrs":{"text":"GSE47856","term_id":"47856"}}GSE47856 was acquired from the GEO database. After identifying differentially expressed genes (DEGs) between epithelial‐like and mesenchymal‐like cells, the module identification analysis was performed using weighted gene co‐expression network analysis (WGCNA). The gene ontology (GO) and pathway analyses of the most considerable modules were performed. The protein–protein interaction network was also constructed. The hub genes were specified using Cytoscape plugins MCODE and cytoHubba, followed by the survival analysis and data validation. Finally, the co‐expression of miRNA‐lncRNA‐TF with the hub genes was reconstructed. The co‐expression network analysis suggests 20 modules relating to the Epithelial phenotype. The antiquewhite4, brown and darkmagenta modules are the most significant non‐preserved modules in the Epithelial phenotype and contain the most differentially expressed genes. GO, and KEGG pathway enrichment analyses on these modules divulge that these genes were primarily enriched in the focal adhesion, DNA replication pathways and stress response processes. ROC curve and overall survival rate analysis show that the co‐expression pattern of the brown module''s hub genes could be a potential prognostic biomarker for ovarian cancer cisplatin resistance.     

Contribution of Lithologic and Anthropogenic Factors to Surface Soil Heavy Metals in Western Iran Using Multivariate Geostatistical Analyses

Heavy metals’ origin, accumulation, and distribution in soil have been the focus of much attention by many researchers. The objective of this study was to recognize the sources of heavy metals in surface soils in Hamadan Province in western Iran using multivariate geostatistical techniques. A total of 263 surface (0–10 cm) soil samples and 18 rock samples from major parent materials were collected. Cobalt (Co), chromium (Cr), copper (Cu), nickel (Ni), lead (Pb), and zinc (Zn) contents of the samples were determined. Selected soil physical and chemical characteristics were also measured. A multivariate geostatistical analysis was performed to identify the common source of heavy metals. The quantities of Co, Cr, and Ni were found to be associated with parent rocks, corresponding to the first factor termed the “lithologic component.” The second factor was mainly attributed to Cu, which also comprised the first and third factors, indicating a mixed source both from lithologic and anthropogenic inputs. Zn and Pb contents were related to the anthropogenic activities and comprised the third factor. A significant correlation was found between metals from the lithogenic sources and selected soil properties such as soil organic matter, clay, CEC, and carbonate, indicating an interaction among them. Generally, Zn and Pb showed a less significant correlation with soil properties.     

Increasing the quality of services and resource utilization in vehicular cloud computing using best host selection methods

One of the technology for increasing the safety and welfare of humans in roads is Vehicular Cloud Computing (VCC). This technology can utilize cloud computing advantages in the Vehicular Ad Hoc Network (VANET). VCC by utilizing modern equipment along with current vehicles, can play a significant role in the area of smart transportation systems. Given the potential of this technology, effective methods for managing existing resources and providing the expected service quality that is essential for such an environment are not yet available as it should. One of the most important barriers to providing such solutions seems to be resource constraints and very high dynamics in vehicles in VCC. In this article, based on virtualization and taking into account the environment with these features, we propose simple ways to manage resources better and improve the quality of service. We were able to achieve better results in simulation than previous methods by providing a flexible data structure to control the important data in the environment effectively. To illustrate the impact of the proposed methods, we compared them with some of the most important methods in this context, and we used SUMO 1.2.0 and MATLAB R2019a software to simulate them. Simulation results indicate that the proposed methods provide better results than previous methods in terms of resource efficiency, Quality of Service (QoS), and load balancing.

     

Cytosolic phospholipase A2α sustains pAKT,pERK and AR levels in PTEN-null/mutated prostate cancer cells

Constitutive phosphorylation of protein kinase B (AKT) is a common feature of cancer caused by genetic alteration in the phosphatase and tensin homolog (PTEN) gene and is associated with poor prognosis. This study determined the role of cytosolic phospholipase A₂α (cPLA₂α) in AKT, extracellular signal-regulated kinase (ERK) and androgen receptor (AR) signaling in PTEN-null/mutated prostate cancer cells. Doxycycline (Dox)-induced expression of cPLA₂α led to an increase in pAKT, pGSK3β and cyclin D1 levels in LNCaP cells that possess a PTEN frame-shift mutation. In contrast, silencing cPLA₂α expression with siRNA decreased pAKT, pGSK3β and cyclin D1 levels in both PC-3 (PTEN deletion) and LNCaP cells. Silencing of cPLA₂α decreased pERK and AR protein levels. The inhibitory effect of cPLA₂α siRNA on pAKT and AR protein levels was reduced by the addition of arachidonic acid (AA), whereas the stimulatory effect of AA on pAKT, pERK and AR levels was decreased by an inhibitor of 5-hydroxyeicosatetraenoic acid production. Pharmacological blockade of cPLA₂α with Efipladib reduced pAKT and AR levels with a concomitant inhibition of PC-3 and LNCaP cell proliferation. These results demonstrate an important role for cPLA₂α in sustaining AKT, ERK and AR signaling in PTEN-null/mutated prostate cancer cells and provide a potential molecular target for treating prostate cancer.     

Control of apple blue mould disease with Torulaspora delbrueckii in combination with Silicon

In this study, Torulaspora delbrueckii alone and in combination with silicon were evaluated for the control of apple blue mould disease caused by Penicillium expansum. In vitro, the antagonistic effects of T. delbrueckii in controlling mycelial growth of P. expansum on potato-dextrose-agar (PDA) in dual cultures, and the growth of P. expansum alone with cell-free metabolites and volatile components of T. delbrueckii were assayed. In vitro, to evaluate the direct effect of silicon on mycelial growth of pathogen, silicon at different concentrations (0.2, 0.4, 0.6, 1 and 2% (wt./vol.)) was added to PDA medium. Silicon at 0.6% (wt./vol.) and above concentrations completely inhibited the mycelial growth of P. expansum. However, it had no significant effect on population dynamics of yeast in vitro and in apple wounds. In vivo, silicon at 0.2 and 1% (wt./vol.) in combination with antagonistic yeast (1 × 10⁸ cell/ml) was a more effective approach to reduce the lesion diameter of blue mould decay of apples than the application of silicon or T. delbrueckii alone at 20 and 4°C, respectively.