Mutation of mitochondria genome: trigger of somatic cell transforming to cancer cell

Nearly 80 years ago, scientist Otto Warburg originated a hypothesis that the cause of cancer is primarily a defect in energy metabolism. Following studies showed that mitochondria impact carcinogenesis to remodel somatic cells to cancer cells through modifying the genome, through maintenance the tumorigenic phenotype, and through apoptosis. And the Endosymbiotic Theory explains the origin of mitochondria and eukaryotes, on the other hands, the mitochondria also can fall back. Compared to chromosome genomes, the mitochondria genomes were not restricted by introns so they were mutated(fall back) easy. The result is that mitochondria lose function and internal environment of somatic cell become acid and evoked chromosome genomes to mutate, in the end somatic cells become cancer cells. It is the trigger of somatic cell transforming to cancer cell that mitochondria genome happen mutation and lose function

Stability Analysis of a Car-Following Model on Two Lanes

Considering lateral influence from adjacent lane, an improved car-following model is developed in this paper. Then linear and nonlinear stability analyses are carried out. The modified Korteweg-de Vries (MKdV) equation is derived with the kink-antikink soliton solution. Numerical simulations are implemented and the result shows good consistency with theoretical study

Map Matching Based on Conditional Random Fields and Route Preference Mining for Uncertain Trajectories

In order to improve offline map matching accuracy of uncertain GPS trajectories, a map matching algorithm based on conditional random fields (CRF) and route preference mining is proposed. In this algorithm, road offset distance and the temporal-spatial relationship between the sampling points are used as features of GPS trajectory in a CRF model, which integrates the temporal-spatial context information flexibly. The driver route preference is also used to bolster the temporal-spatial context when a low GPS sampling rate impairs the resolving power of temporal-spatial context in CRF, allowing the map matching accuracy of uncertain GPS trajectories to get improved significantly. The experimental results show that our proposed algorithm is more accurate than existing methods, especially in the case of a low-sampling-rate

Aboveground Biomass and Soil Moisture as Affected by Short-Term Grazing Exclusion in Eastern Alpine Meadows of the Qinghai-Tibet Plateau, China

Heavy grazing substantially influences grassland vegetation and animal nutrition on the Qinghai-Tibet plateau (Guo et al. 2003). Degradation is characterized by a reduction in vegetation height, reduced ground cover decrease in species diversity (Wang et al. 2007). The objective of this study was to determine the effects of short-term exclusion from grazing on aboveground herbage, forage nutritive value, and soil moisture in an alpine meadow in the eastern zone of the plateau. Three farms, applying different intensity of grazing over the summer months, were compared

Engineering students' approaches to learning and views on collaboration: How do both evolve in a PBL environment and what are their contributing and constraining factors?

Background: This study investigated the development of engineering students' approaches to learning and views on collaboration in a PBL environment. Material and methods: An explanatory mixed research approach was employed with participants from four PBL-implementing engineering courses in Qatar and China. 197students responded to two surveys, and 168 students participated in group interviews. Results: While the study reveals increased adoption of deep approaches to learning on team projects, little influence on surface approaches to learning was found. The study also provides evidence supporting the positive relationship between students' adoption of deep learning approaches and their acknowledgement of values of collaboration in teamwork. Conclusions: This study suggests that while PBL characteristics may support deep learning, certain factors may underpin surface learning, including a feeling of insecurity during first experiences with it, lack of skills, and assessment methods that favor surface learning. Further efforts on engaging students with PBL may benefit both deep learning and team effectiveness.Scopu

Golden carbon nanotube membrane for continuous flow catalysis

In this work, a high-performance catalytic membrane, composed of ultrasmall gold nanoclusters (AuNCs) and high aspect-ratio carbon nanotubes (CNTs), was designed for the continuous-flow catalytic reactions. In this hybrid catalytic membrane, the Au core of the NCs serves as high-performance catalyst, and the ligand of the NCs plays two key roles: (1) as a well-defined surfactant assembly to effectively dissolve CNTs in aqueous solution and (2) as an efficient protecting ligand for Au core to avoid agglomeration. Due to the above-mentioned features, a homogeneous 3D self-support catalytic membrane can be readily fabricated by vacuum filtration of the hybrid AuNCs/CNTs. The catalytic activity of the as-designed catalytic membrane was evaluated using 4-nitrophenol hydrogenation as a model catalytic reaction. The data suggest that the continuous flow catalytic reactor could achieve complete conversion of the substrate (i.e., 4-nitrophenol) within a single flow through the membrane with a hydraulic residence time (τ) of 3.0 s. The catalytic membrane also showed enhanced catalytic kinetics as compared to the conventional batch reactor due to the convectively enhanced mass transfer. In addition, three important parameters, including the Au loading amount, substrate concentration, and flow rate, were identified as key factors that could affect the performance of the catalytic membrane