Scholarly

The Role and Importance of Genome Sequencing in Prediction of Cancer Risk

Year: 2017 Volume: 11 Issue: 8 460 - 465 Pages

Abstract: The role and relative importance of intrinsic and extrinsic factors in the development of complex diseases such as cancer still remains a controversial issue. Determining the amount of variation explained by these factors needs experimental data and statistical models. These models are nevertheless based on the occurrence and accumulation of random mutational events during stem cell division, thus rendering cancer development a stochastic outcome. We demonstrate that not only individual genome sequencing is uninformative in determining cancer risk, but also assigning a unique genome sequence to any given individual (healthy or affected) is not meaningful. Current whole-genome sequencing approaches are therefore unlikely to realize the promise of personalized medicine. In conclusion, since genome sequence differs from cell to cell and changes over time, it seems that determining the risk factor of complex diseases based on genome sequence is somewhat unrealistic, and therefore, the resulting data are likely to be inherently uninformative.

Synchrony between Genetic Repressilators in Sister Cells in Different Temperatures

Year: 2015 Volume: 9 Issue: 7 761 - 764 Pages

Abstract: We used live E. coli containing synthetic genetic oscillators to study how the degree of synchrony between the genetic circuits of sister cells changes with temperature. We found that both the mean and the variability of the degree of synchrony between the fluorescence signals from sister cells are affected by temperature. Also, while most pairs of sister cells were found to be highly synchronous in each condition, the number of asynchronous pairs increased with increasing temperature, which was found to be due to disruptions in the oscillations. Finally we provide evidence that these disruptions tend to affect multiple generations as opposed to individual cells. These findings provide insight in how to design more robust synthetic circuits and in how cell division can affect their dynamics.

Parameters Identification of Mathematical Model of the Fission Yeast Cell Cycle Control Using Evolutionary Strategy

Year: 2008 Volume: 2 Issue: 8 1001 - 1007 Pages

Abstract: Complex assemblies of interacting proteins carry out most of the interesting jobs in a cell, such as metabolism, DNA synthesis, mitosis and cell division. These physiological properties play out as a subtle molecular dance, choreographed by underlying regulatory networks that control the activities of cyclin-dependent kinases (CDK). The network can be modeled by a set of nonlinear differential equations and its behavior predicted by numerical simulation. In this paper, an innovative approach has been proposed that uses genetic algorithms to mine a set of behavior data output by a biological system in order to determine the kinetic parameters of the system. In our approach, the machine learning method is integrated with the framework of existent biological information in a wiring diagram so that its findings are expressed in a form of system dynamic behavior. By numerical simulations it has been illustrated that the model is consistent with experiments and successfully shown that such application of genetic algorithms will highly improve the performance of mathematical model of the cell division cycle to simulate such a complicated bio-system.

Virtual Laboratory for Learning Biology – A Preliminary Investigation

Year: 2010 Volume: 4 Issue: 11 2147 - 2150 Pages

Abstract: This study aims to conduct a preliminary investigation to determine the topic to be focused in developing Virtual Laboratory For Biology (VLab-Bio). Samples involved in answering the questionnaire are form five students (equivalent to A-Level) and biology teachers. Time and economical resources for the setting up and construction of scientific laboratories can be solved with the adaptation of virtual laboratories as an educational tool. Thus, it is hoped that the proposed virtual laboratory will help students to learn the abstract concepts in biology. Findings show that the difficult topic chosen is Cell Division and the learning objective to be focused in developing the virtual lab is “Describe the application of knowledge on mitosis in cloning".

Determination of an Efficient Differentiation Pathway of Stem Cells Employing Predictory Neural Network Model

Year: 2010 Volume: 4 Issue: 10 1545 - 1548 Pages

Abstract: The stem cells have ability to differentiated themselves through mitotic cell division and various range of specialized cell types. Cellular differentiation is a way by which few specialized cell develops into more specialized.This paper studies the fundamental problem of computational schema for an artificial neural network based on chemical, physical and biological variables of state. By doing this type of study system could be model for a viable propagation of various economically important stem cells differentiation. This paper proposes various differentiation outcomes of artificial neural network into variety of potential specialized cells on implementing MATLAB version 2009. A feed-forward back propagation kind of network was created to input vector (five input elements) with single hidden layer and one output unit in output layer. The efficiency of neural network was done by the assessment of results achieved from this study with that of experimental data input and chosen target data. The propose solution for the efficiency of artificial neural network assessed by the comparatative analysis of “Mean Square Error" at zero epochs. There are different variables of data in order to test the targeted results.

X-ray Crystallographic Analysis of MinC N-Terminal Domain from Escherichia coli

Year: 2010 Volume: 4 Issue: 8 560 - 563 Pages

Abstract: MinC plays an important role in bacterial cell division system by inhibiting FtsZ assembly. However, the molecular mechanism of the action is poorly understood. E. coli MinC Nterminus domain was purified and crystallized using 1.4 M sodium citrate pH 6.5 as a precipitant. X-ray diffraction data was collected and processed to 2.3 Å from a native crystal. The crystal belonged to space group P212121, with the unit cell parameters a = 52.7, b = 54.0, c = 64.7 Å. Assuming the presence of two molecules in the asymmetric unit, the Matthews coefficient value is 1.94 Å3 Da-1, which corresponds to a solvent content of 36.5%. The overall structure of MinCN is observed as a dimer form through anti-parallel ß-strand interaction.

More Realistic Model for Simulating Min Protein Dynamics: Lattice Boltzmann Method Incorporating the Role of Nucleoids

Year: 2010 Volume: 4 Issue: 7 451 - 456 Pages

Abstract: The dynamics of Min proteins plays a center role in accurate cell division. Although the nucleoids may presumably play an important role in prokaryotic cell division, there is a lack of models to account for its participation. In this work, we apply the lattice Boltzmann method to investigate protein oscillation based on a mesoscopic model that takes into account the nucleoid-s role. We found that our numerical results are in reasonably good agreement with the previous experimental results On comparing with the other computational models without the presence of nucleoids, the highlight of our finding is that the local densities of MinD and MinE on the cytoplasmic membrane increases, especially along the cell width, when the size of the obstacle increases, leading to a more distinct cap-like structure at the poles. This feature indicated the realistic pattern and reflected the combination of Min protein dynamics and nucleoid-s role.

Oleate Induces Apoptosis in 3T3-L1 Adipocytes

Year: 2011 Volume: 5 Issue: 9 513 - 516 Pages

Abstract: Oleic acid (C18:1) play an important role in proliferation of fat cells. In this study, the effect of oleate on cells viability in 3T3-L1 cells (fat cells) was investigated. The 3T3-L1 cells were treated with various concentrations of oleate in the presence of 23 mM glucose. Oleate was added to adipogenic media (day 0) to investigate the influence of oleate on proliferation of postconfluent preadipocytes after 24 h induction. 0.1 mM oleate promoted cell division by increasing 33.9% number of cells from basal control in postconfluent preadipocytes. However, there were no significantly different in cells viability with control cells when oleate concentrations were increased up to 0.5 mM. When added to differentiated adipocytes (day 12) for 48 h, the number of cells decreased as oleate concentrations increased. 92.7% of cells lost demonstrated apoptosis and necrosis after 48 h with 0.5 mM oleate. The fluorochrome staining was examined under fluorescence microscopy using acridine orange and ethidium bromide double staining. Furthermore, the presence of high lactate (60.6% increased from basal control) released into plasma has shown the direct cytotoxicity of 0.5 mM oleate on adipocytes.

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