Spatiotemporal modeling and model restructuration approaches in studies of intracellular signalling pathways

The main focus of the research is to understand the complex phenomena of cell transduction pathways and cell biology in a single cell. Mathematical modeling and experimental evaluation are widely used approaches for this kind of research. Firstly, A multiscale framework for protein-protein interaction has been established using Brownian dynamics algorithm. Sit specific feature, steric collision, diffusion, co-localization and complex formation with time and space has been included in this spatial modeling framework. By implementation of the time adaptive feature in this framework, the computation time reduces in an order of magnitude compared with traditional modeling framework. This multiscale Brownian framework has been used for the investigation FcεRI aggregation which is an important signaling pathway for immune cells. Using the spatial modeling framework, FcεRI aggregation in the presence of trivalent antigen showed consistent results with current experimental studies. Secondly, the rule-based modeling approach is an excellent way of performing large biochemical network modeling for a single cell as it considers the site-specific features. However, the major difficulty of rule-based modeling approach is combinatorial complexity. In this study, model restructuring approaches have been applied to overcome this problem for cell signaling pathway modeling. These mechanistic modeling approaches are very effective to model large network of signaling pathways together without compromising the accuracy. Finally, Cell size dependent cellular uptake study carried out using confocal microscopy and flow cytometer. To understand the particle uptake behavior with time and steady state condition, reaction-diffusion and kinetics model has been developed in these work. After a detailed analysis of experimental data and models, it showed that total particle uptake is increasing with cell size, however, particle flux is reducing in larger cells --Abstract, page iv

Jatropha Biofuel Industry: The Challenges

Considering environmental issues and to reduce dependency on fossil fuel many countries have politicized to replenish fossil fuel demand from renewable sources. Citing the potential of Jatropha mostly without any scientific and technological backup, it is believed to be one of the most suitable biofuel candidates. Huge grants were released by many projects for huge plantation of Jatropha (millions of hectares). Unfortunately, there has been no significant progress, and Jatropha did not contribute much in the energy scenario. Unavailability of high-yielding cultivar, large-scale plantation without the evaluation of the planting materials, knowledge gap and basic research gap seem to be the main reasons for failure. Thus, the production of Jatropha as a biofuel has been confronted with various challenges such as production, oil extraction, conversion and also its use as a sustainable biofuel. In this chapter, we disclose the challenges and possible remedy for the contribution in the biofuel industry

A Multiscale Algorithm for Spatiotemporal Modeling of Multivalent Protein-Protein Interaction

This article introduces a multiscale framework for spatiotemporal modeling of protein-protein interaction. Cellular protein molecules represent multivalent species that contain modular features, such as binding domains and phosphorylation motifs. The binding and transformations of these features occur at a small time and spatial scale. On the other hand, space and time involved in protein diffusion, colocalization, and formation of complexes could be relatively large. Here, we present an agent-based framework integrated with a multiscale Brownian Dynamics (BD) simulation algorithm. The framework employs spatial graphs to describe multivalent molecules and complexes with their site-specific details. By implementing a time-adaptive feature, the BD algorithm enables efficient computation while capturing the site-specific interactions of the diffusing species at the sub-nanometer scale. We demonstrate these capabilities by modeling two multivalent molecules, one representing a ligand and the other a receptor, in a two-dimensional plane (cell membrane). Using the model, we show that the algorithm can accelerate computation by orders of magnitudes in both concentrated and dilute regimes. We also show that the algorithm enables robust model predictions against a wide range of selection of time step sizes

Dissecting Particle Uptake Heterogeneity in a Cell Population using Bayesian Analysis

Individual cells in a solution display variable uptake of nanomaterials, peptides, and nutrients. Such variability reflects their heterogeneity in endocytic capacity. In a recent work, we have shown that the endocytic capacity of a cell depends on its size and surface density of endocytic components (transporters). We also demonstrated that in MDA-MB-231 breast cancer cells, the cell-surface transporter density (n) may decay with cell radius (r) following the power rule n ~ rα, where α ≈ −1. In this work, we investigate how n and r may independently contribute to the endocytic heterogeneity of a cell population. Our analysis indicates that the smaller cells display more heterogeneity because of the higher stochastic variations in n. By contrast, the larger cells display a more uniform uptake, reflecting less-stochastic variations in n. We provide analyses of these dependencies by establishing a stochastic model. Our analysis reveals that the exponent α in the above relationship is not a constant; rather, it is a random variable whose distribution depends on cell size r. Using Bayesian analysis, we characterize the cell-size-dependent distributions of α that accurately capture the particle uptake heterogeneity of MDA-MB-231 cells

Delineation of groundwater potential zones using a parsimonious concept based on catastrophe theory and analytical hierarchy process

A cost-effective “parsimonious” approach to delineating groundwater potential zones is proposed, based on catastrophe theory (CT) and analytical hierarchy process (AHP) in a geographic information system (GIS). Eleven indicators that influence groundwater storage (slope, drainage density, surface-water body (proximity), soil permeability, aquitard thickness, aquifer thickness, hydraulic conductivity, specific yield, recharge, aquitard resistivity and aquifer resistivity) were prepared. The suitable weights of the factors and the index values of the features of the factors were normalized using AHP and CT multicriteria decision analysis (MCDA) techniques for the development of a groundwater potential index (GWPI) map. Finally, the relative sensitivity of the factors was evaluated to develop a parsimonious groundwater potential index (P-GWPI) map using the most sensitive themes. GWPI and P-GWPI maps were validated using 14-year average annual post-monsoon depth to groundwater level data of 36 monitoring wells in a study area in Bangladesh. The generated GWPI map classified the study area as moderately good, good and very good groundwater potential covering an area of 19.5, 40.3 and 40.2% respectively. Subsequently, a modified GWPI map was developed using effective weights derived from single-parameter sensitivity analysis. The P-GWPI map developed using the most sensitive factors categorized the groundwater potential zones as moderately good (13.0%), good (38.2%) and very good (48.8%). The results of this study can serve as guidelines for future groundwater exploration, planning and management of the area, and the methodology used can also be easily adopted in other similar and data-scarce areas

Non-sulphide zeolite catalyst for bio-jet-fuel conversion

In recent years, the production of bio-aviation fuels has received increased attention because of its renewability and environmental benefits. Catalytic hydrocracking is a convenient way to produce bio-jet fuel from vegetable oil. Among the different types of catalysts, sulphided zeolites showed more catalytic activity for bio-fuel conversion. However, the uses of different sulphiding agents in this process causes the emission of HS gas and exposes the environment to sulphur residues, which are responsible for pollution and the greenhouse effect. Conversely, various non-sulphide zeolite catalysts, such as noble metal supported on ZSM-5, HZSM-5, SAPO-11, beta- zeolite, SBA-15 and mesoporous-Y zeolite, also showed considerable activity for bio-fuel conversion. Therefore, it is time to improve the non-sulphide zeolite catalysts for the production of bio-jet fuel to combat fuel recession and mitigate environmental problems. Several good reviews are available on the catalytic conversion of bio-jet fuel. This review is distinct from the previous ones, as it combines most of the previous reviews, illustrates the different supported non-sulphide zeolite-type catalysts and their preparation methods, characteristics and performance in bio-jet fuel production

Gas chromatography mass spectrometry analysis and in vitro antibacterial activity of essential oil from Trigonella foenum-graecum

Objective: To evaluate the antibacterial activity of essential oil from Trigonella foenum-graecum seeds powder, and identify the compounds from the extracted oil. Methods: The seeds powder of Trigonella foenum-graecum was subjected to Clevenger extractor. Seven strains of bacteria were used to test antibacterial activity of the extract. The activity against bacteria was tested by disk diffusion method using Whatman No. 1 filter paper. Gas chromatography mass spectrometry analysis was performed with an Agilent7890/5975B-gas chromatography/mass selective detector. Results: The hydrodistillation of seeds powder yielded 0.285% (v/w) of oil. Disk diffusion of the oil showed bactericidal activity against both Gram negative and Gram positive bacteria of tasted strains. The inhibition zone ranged from (8 ± 0) mm to (15.0 ± 0.7) mm depending on microbial strains. Gas chromatography mass spectrometry analysis showed 14 different compounds. The total compounds represented 80.96% of the oil. Conclusions: The antibacterial activity is due to the effects of different biological active compounds present in the extract. Identification of the compounds may help to develop new effective antimicrobial agent(s). Further researches on purification, characterization and toxicology of the active compounds are needed

Quantitative Analysis of the Correlation between Cell Size and Cellular Uptake of Particles

The size of a cell is central to many functions, including cellular communication and exchange of materials with the environment. This modeling and experimental study focused on understanding how the size of a cell determines its ability to uptake nanometer-scale extracellular materials from the environment. Several mechanisms in the cell plasma membrane mediate cellular uptake of nutrients, biomolecules, and particles. These mechanisms involve recognition and internalization of the extracellular molecules via endocytic components, such as clathrin-coated pits, vacuoles, and micropinocytic vesicles. Because the demand for an external resource could be different for cells of different sizes, the collective actions of these various endocytic routes should also vary based on the cell size. Here, using a reaction-diffusion model, we analyze single-cell data to interrogate the one/one mapping between the size of the MDA-MB 231 breast cancer cells and their ability to uptake nanoparticles. Our analysis indicates that under both reaction- and diffusion-controlled regimes, cellular uptake follows a linear relationship with the cell radius. Furthermore, this linear dependency is insensitive to particle size variation within 20-200 nm range. This result is counterintuitive because the general perception is that cellular uptake is proportional to the cell volume (mass) or surface area and hence follow a cubic or square relationship with the cell radius. A further analysis using our model reveals a potential mechanism underlying this linear relationship

Microcontroller Based Automotive Vehicle Anti- Theft Braking System

An estimated 300 million vehicles was stolen every year around the world. This has become a national problem today which also has some solutions. To solve this problem we have many options using microcontroller is the best option. In this project we demonstrated microcontroller based automotive braking system. Beside that it can also able to send the location of vehicles. The first one is introduced as the security system and second one is reporting system. For the first system we used microcontroller PIC16F887. Again the reporting system is based on the Global Positioning system (GPS) and Global System of Mobile (GSM) network. A vehicle can be tracked through GPS. This overall system not only brings a solution of prevent stealing vehicles but also show a practical use of GPS and GSM network. The proposed issues on this project are, making it useable for the vehicle, less expensive, and more accurate. In this era of modern technologies, when machines have become indispensable and each second translates into advancement, such microcontroller based anti-theft system can make life secure with a rise in human productivity