Cinobufacini induced MDA-MB-231 cell apoptosis-associated cell cycle arrest and cytoskeleton function

Cinobufacini is a traditional Chinese anti-tumor drug and widely used in clinic experiences. But little is known about its effect on the cells. In this study, the effects of cinobufacini on breast cancer MDA-MB-231 cell were evaluated by CCK-8 assay, and the data showed cinobufacini could inhibit the MDA-MB-231 cells growth effectively in dose-dependent and time-dependent manners. Cell apoptosis and cell cycle were detected by flow cytometry analysis. After the cells being treated with 50 μg/mL cinobufacini for 48 h, the early apoptosis percentage (20.45 ± 1.46%) is much higher than the normal group (7.73 ± 1.21%). The cell cycle data indicated that cinobufacini caused a cell cycle arrest at S phase. What's more, cinobufacini can affect the disruption of cytoskeleton, and these alterations changed the cell-surface ultrastructure and the cell morphology which were detected by atomic force microscopy (AFM) at nanoscale level. It indicated that the cell membrane structure and cytoskeleton networks were destroyed and the cell tails were narrowed after the cell being treated with cinobufacini. The present study is to provide valuable new insights to understand the mechanism of the drug in anti-tumor process. Furthermore, the knowledge concerning the signaling of cell cycle is potentially important to clinical utility.     

Revealing a Brain Network Endophenotype in Families with Idiopathic Generalised Epilepsy

Idiopathic generalised epilepsy (IGE) has a genetic basis. The mechanism of seizure expression is not fully known, but is assumed to involve large-scale brain networks. We hypothesised that abnormal brain network properties would be detected using EEG in patients with IGE, and would be manifest as a familial endophenotype in their unaffected first-degree relatives. We studied 117 participants: 35 patients with IGE, 42 unaffected first-degree relatives, and 40 normal controls, using scalp EEG. Graph theory was used to describe brain network topology in five frequency bands for each subject. Frequency bands were chosen based on a published Spectral Factor Analysis study which demonstrated these bands to be optimally robust and independent. Groups were compared, using Bonferroni correction to account for nonindependent measures and multiple groups. Degree distribution variance was greater in patients and relatives than controls in the 6–9 Hz band (p = 0.0005, p = 0.0009 respectively). Mean degree was greater in patients than healthy controls in the 6–9 Hz band (p = 0.0064). Clustering coefficient was higher in patients and relatives than controls in the 6–9 Hz band (p = 0.0025, p = 0.0013). Characteristic path length did not differ between groups. No differences were found between patients and unaffected relatives. These findings suggest brain network topology differs between patients with IGE and normal controls, and that some of these network measures show similar deviations in patients and in unaffected relatives who do not have epilepsy. This suggests brain network topology may be an inherited endophenotype of IGE, present in unaffected relatives who do not have epilepsy, as well as in affected patients. We propose that abnormal brain network topology may be an endophenotype of IGE, though not in itself sufficient to cause epilepsy.     

An Ensemble Method with Hybrid Features to Identify Extracellular Matrix Proteins

The extracellular matrix (ECM) is a dynamic composite of secreted proteins that play important roles in numerous biological processes such as tissue morphogenesis, differentiation and homeostasis. Furthermore, various diseases are caused by the dysfunction of ECM proteins. Therefore, identifying these important ECM proteins may assist in understanding related biological processes and drug development. In view of the serious imbalance in the training dataset, a Random Forest-based ensemble method with hybrid features is developed in this paper to identify ECM proteins. Hybrid features are employed by incorporating sequence composition, physicochemical properties, evolutionary and structural information. The Information Gain Ratio and Incremental Feature Selection (IGR-IFS) methods are adopted to select the optimal features. Finally, the resulting predictor termed IECMP (Identify ECM Proteins) achieves an balanced accuracy of 86.4% using the 10-fold cross-validation on the training dataset, which is much higher than results obtained by other methods (ECMPRED: 71.0%, ECMPP: 77.8%). Moreover, when tested on a common independent dataset, our method also achieves significantly improved performance over ECMPP and ECMPRED. These results indicate that IECMP is an effective method for ECM protein prediction, which has a more balanced prediction capability for positive and negative samples. It is anticipated that the proposed method will provide significant information to fully decipher the molecular mechanisms of ECM-related biological processes and discover candidate drug targets. For public access, we develop a user-friendly web server for ECM protein identification that is freely accessible at http://iecmp.weka.cc.     

Association between Polymorphisms in the Renin-Angiotensin-Aldosterone System Genes and Essential Hypertension in the Han Chinese Population

Background

Renin-angiotensin-aldosterone system (RAAS) is the most important endocrine blood pressure control mechanism in our body, genes encoding components of this system have been strong candidates for the investigation of the genetic basis of hypertension. However, previous studies mainly focused on limited polymorphisms, thus we carried out a case-control study in the Han Chinese population to systemically investigate the association between polymorphisms in the RAAS genes and essential hypertension.

Methods

905 essential hypertensive cases and 905 normotensive controls were recruited based on stringent inclusion and exclusion criteria. All 41 tagSNPs within RAAS genes were retrieved from HapMap, and the genotyping was performed using the GenomeLab SNPstream Genotyping System. Logistic regression analysis, Multifactor dimensionality reduction (MDR), stratified analysis and crossover analysis were used to identify and characterize interactions among the SNPs and the non-genetic factors.

Results

Serum levels of total cholesterol (TC) and triglyceride (TG), and body mass index (BMI) were significantly higher in the hypertensive group than in the control group. Of 41 SNPs genotyped, rs3789678 and rs2493132 within AGT, rs4305 within ACE, rs275645 within AGTR1, rs3802230 and rs10086846 within CYP11B2 were shown to associate with hypertension. The MDR analysis demonstrated that the interaction between BMI and rs4305 increased the susceptibility to hypertension. Crossover analysis and stratified analysis further indicated that BMI has a major effect, and rs4305 has a minor effect.

Conclusion

These novel findings indicated that together with non-genetic factors, these genetic variants in the RAAS may play an important role in determining an individual’s susceptibility to hypertension in the Han Chinese.     

Isolation and characterization of mesenchymal stem cells from chicken bone marrow

The bone marrow mesenchymal stem cells (BMSCs) are multipotent stem cells, which can differentiate in vitro into many cell types. However, the vast majority of experimental materials were obtained from human, mouse, rabbit and other mammals, but rarely in poultry. So, in this study, Thirty- to sixty-day old chicken was chosen as experimental animal, to isolate and characterize BMSCs from them. To investigate the biological characteristics of chicken BMSCs, immunofluorescence and RT-PCR were used to detect the characteristic surface markers of BMSCs. Growth curves were drawn in accordance with cell numbers. To assess the differentiation capacity of the BMSCs, cells were induced to differentiate into osteoblasts, adipocytes, and endothelial cells. The surface markers of BMSCs, CD29, CD44, CD31, CD34, CD71 and CD73, were detected by immunofluorescence and RT-PCR assays. The growth curves of different passages were all typically sigmoidal. Karyotype analysis showed that these in vitro cultured cells were genetically stable. In addition, BMSCs were successfully induced to differentiate into osteoblasts, adipocytes, and endothelial cells. The results suggest that the BMSCs isolated from chicken possess similar biological characteristics with those separated from other species, and their multi-lineage differentiation potentiality herald a probable application for cellular transplant therapy in tissue engineering.