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.     

Sublocalization of an Ataxia-Telangiectasia Gene Distal to D11S384 by Ancestral Haplotyping In Costa Rican Families

In an effort to localize a gene for ataxia-telangiectasia (A-T), we have genotyped 27 affected Costa Rican families, with 13 markers, in the chromosome 11q22-23 region. Significant linkage disequilibrium was detected for 9/13 markers between D11S1816 and D11S1391. Recombination events observed in these pedigrees places A-T between D11S1819 and D11S1960. One ancestral haplotype is common to 24/54 affected chromosomes and roughly two-thirds of the families. Inferred (ancestral) recombination events involving this common haplotype in earlier generations suggest that A-T is distal to D11S384 and proximal to D11S1960. Several other common haplotypes were identified, consistent with multiple mutations in a single gene. When considered together with all other evidence, this study further sublocalizes the major A-T locus to ≈200 kb, between markers S384 and S535.     

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      

Intermittent motion in desert locusts: behavioural complexity in simple environments

Animals can exhibit complex movement patterns that may be the result of interactions with their environment or may be directly the mechanism by which their behaviour is governed. In order to understand the drivers of these patterns we examine the movement behaviour of individual desert locusts in a homogenous experimental arena with minimal external cues. Locust motion is intermittent and we reveal that as pauses become longer, the probability that a locust changes direction from its previous direction of travel increases. Long pauses (of greater than 100 s) can be considered reorientation bouts, while shorter pauses (of less than 6 s) appear to act as periods of resting between displacements. We observe power-law behaviour in the distribution of move and pause lengths of over 1.5 orders of magnitude. While Lévy features do exist, locusts' movement patterns are more fully described by considering moves, pauses and turns in combination. Further analysis reveals that these combinations give rise to two behavioural modes that are organized in time: local search behaviour (long exploratory pauses with short moves) and relocation behaviour (long displacement moves with shorter resting pauses). These findings offer a new perspective on how complex animal movement patterns emerge in nature.     

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.     

Heat stress aggravates oxidative stress,apoptosis, and endoplasmic reticulum stress in the cerebellum of male C57 mice

Molecular Biology Reports - The current study was set to assess the effect of heat stress exposure on oxidative stress, apoptosis, and endoplasmic reticulum stress markers in the cerebellum of male...     

Structure-activity study of phosphoramido acid esters as acetylcholinesterasf inhibitors

Phosphoramido acid esters (CH₃)₂NP(O)X(p-OC₆H₄-CH₃) (containing P-Cl (1), P-O (2), P-F (3), P-CN (5), and P-N (4,6) bonds, X for 2, 4 and 6 is OCH₃, (C₂H₅)₂N and morpholin) have been synthesized to investigate the structure-activity study of AChE enzyme inhibition, through the parameters logP, δ³¹P and IC₅₀. After their characterization by ³¹P, ³¹P{¹H}, ¹³C, ¹H NMR, IR and mass spectroscopy, the parameters logP and δ³¹P (³¹P chemical shift in NMR) were used to evaluated the lipophilicity and electronical properties. The ability of compounds to inhibit human AChE was predicted by PASS software (version 1.193), and experimentally evaluated by a modified Ellman's assay.     

Expression profile of lncRNAs and miRNAs in esophageal cancer: Implications in diagnosis,prognosis, and therapeutic response

Esophageal cancer is the seventh most common cancer worldwide. Although a number of environmental and lifestyle-related risk factors have been identified for this kind of cancer, the exact molecular mechanisms of tumor evolution have not been clarified yet. Long noncoding RNAs (lncRNAs) and microRNAs (miRNAs) as important regulators of gene expression and chromatin configuration have essential roles in the pathogenesis of esophageal cancer. They have been shown to alter the function of cancer-related signaling pathways such as phosphoinositide 3-kinase/protein kinase B and Wnt pathway, thus they might modulate the response of patients to pathway-targeted therapies. Moreover, a number of lncRNAs, such as AFAP1-AS1, UCA1, HOTAIR, LOC285194, and TUSC7, are involved in conferring chemoresistant/radioresistant in esophageal cancer cells. A complex network of interaction exists between lncRNAs and miRNAs in the context of esophageal cancer. Finally, various panels of lncRNAs and miRNAs have been introduced that can predict the survival of esophageal cancer patients. In this review article, we summarize the recent findings regarding the role of miRNAs and lncRNAs in the pathogenesis of esophageal cancer with the special focus on their regulatory roles on signaling pathways, their potential as diagnostic/prognostic markers, and their relevance with therapeutic response.