Bioautomation

Volume 20, Issue 2
Bioinformatics
Open Tools of Drug Designing for Open Research	159-182
Kanika Gupta, Ashok Kumar [ +/- abstract ][ full text ]
Drug detection and growth is intense, lengthy and interdisciplinary process. Traditionally, drug discovery was done by amalgamating compounds in a time-utilizing multi-step processes and then they were further investigated for their respective promising candidates. Nowadays in silico methods for drug designing have come into play, which helps in the identification of drug targets using various bioinformatics drug designing tools. They can also be used to analyze the target structures for probable binding site, generate potential molecules, examine their drug likeness, dock particular molecules with the target, rank them in accordance to their binding affinities and further amend the molecules to upgrade their binding characteristics and finally obtain potential candidates for drug discovery. As the structural information of many protein targets become available through X-Ray crystallography, NMR and bioinformatics approaches, there comes an increasing demand for the computer based tools which can recognize and inspect the active sites and suggest potential druggable unit which could specifically bind to these active sites. The major advantages of these bioinformatics drug designing tools is that they are available everywhere on internet, they have decreased support costs, decreased license costs, software integration, easy monitoring and grid calculations. For the above mentioned reasons, we compile in this review 49 online tools which could be beneficial to biotechnologist for in silico drug design.
Fluoride Stimulates the Proliferation of Osteoclasts in vitro by Upregulating MCM3	183-192
Shengbin Bai, Hongxiang Chen, Tian Li, Wen Qin, Libin Liao, Shumei Feng, Jinjie Zhong [ +/- abstract ][ full text ]
We have previously shown that the expression of the minichromosome maintenance protein 3 (MCM3) gene was upregulated in lymphocytes of patients with skeletal fluorosis. We speculated that increased MCM3 expression may be contribute to osteopathy in patients with skeletal fluorosis. Here, we investigated the effect of fluoride on the proliferation of osteoclasts derived from RAW264.7 cells and the involvement of MCM3. Our MTT assays showed that 0.25 mM NaF markedly stimulated the proliferation of RAW264.7 cells. The RT-PCR and immunoblotting assays revealed that 0.25 mM NaF upregulated MCM3 expression in RAW264.7 cells. The MTT assays additionally demonstrated that stimulation with MCM3 potentiated the effect of fluorine on the proliferation of RAW264.7 cells. These results demonstrated that fluoride at clinical relevant concentration upregulates MCM3 expression in osteoclasts in vitro. We are currently conducting a series of experiments to examine whether increased MCM3 in osteoclasts indeed contributes to osteopathy in skeletal fluorosis.
Numerical Solution of a Fractional Order Model of HIV Infection of CD4⁺T Cells Using Müntz-Legendre Polynomials	193-204
Mojtaba Rasouli Gandomani, M. Tavassoli Kajani [ +/- abstract ][ full text ]
In this paper, the model of HIV infection of CD4⁺T cells is considered as a system of fractional differential equations. Then, a numerical method by using collocation method based on the Müntz-Legendre polynomials to approximate solution of the model is presented. The application of the proposed numerical method causes fractional differential equations system to convert into the algebraic equations system. The new system can be solved by one of the existing methods. Finally, we compare the result of this numerical method with the result of the methods have already been presented in the literature.
Quantitative Analysis of Geometric Structures and Experimental Evaluation of Rooster Beak	205-214
Xinping Li, Kang Wu, Yidong Ma [ +/- abstract ][ full text ]
Quantitative analysis of rooster beak maxillary bone is highly significant to reveal the mechanism of the easy discretization and low damage in kernel dispersal. A 3D scanner is used to collect point-cloud data of rooster beak as well as extract maxillary bone horizontal and longitudinal feature curves into Matlab for curve fitting and curvature analysis. Results show that curvature values of crosscutting curves increase from side to center. These values sharply increase when curves move from side close to the center. Curvature values of the longitudinal cutting feature curves of the rooster beak maxillary bone are evidently less than those of the crosscutting curves. Geometry characteristics of rooster beak facilitate the dispersal of corn ear. High-speed photography showed that, the beak can efficiently destroy the arrangement law between kernels, and the corn ear is dispersed. The discrete roller is based on the model of the rooster beak. The experiment of discrete roller showed that the discrete and damage rates of the dent corn are 77.34% and 0.19%, respectively. The discrete and damage rates of the flint corn are 31.19% and 0.29%, respectively, under discrete roller speed of 250 rev·min^-1 and moisture content of corn ear of 14.5%.
Evaluation of the Relationship between Urine Purine Derivatives with Metabolizable Energy and Metabolizable Protein in Lactating Holstein Cows	215-226
Chunbo Wei, Zhibo Wang, Yongli Qu [ +/- abstract ][ full text ]
The objective of this experiment was to evaluate the relationship between purine derivatives (PD) excretion in total collection or spot sampling of urine and metabolizable energy (ME) and metabolizable protein (MP) of dairy cattle. Twenty-seven dairy cows were selected to investigate the changes of PD, creatinine (C), and purine derivative/creatinine ratio (PD/C) in the urine of cows fed different diets using the total pooled urine samples collected throughout 7 days of trial period (total collection) or spot urine collection at 800-900 and 1800-1900 on the days 20 and 21. The rations were formulated with three levels of ME (127% ME/ME required, 100% ME/ME required, 75% ME/ME required) and three levels of MP (123% MP/MP required, 100% MP/MP required, 80% MP/MP required) using the CPM-Dairy 3 model. Our data demonstrated a strongly linear relationship between the concentration of PD (and PD/C) and ME and MP level of the diets using total collection or spot sampling. It was concluded that the concentration of PD and PD/C may have potential to predict the ME and MP supply in the dairy rations, and that the PD/C could be determined by spot urine sampling instead of total urine collection.
Biomedical systems
Detection Algorithm of a Heat-transfer System Based on Pennes Bio-heat Transfer Formula Processing	227-236
Wenju Ji, Jianwen Wang [ +/- abstract ][ full text ]
Biological experiments and clinical trials indicate that low temperature treatment technology is of great significance to the treatment of craniocerebral injury by protecting the brain nerves and reducing its sequela. However, the major challenge at present is how to appropriately control the degree and timing sequence of hypothermia in treating craniocerebral injury in order to meet the requirement of protecting the brain and reducing the side effects. By establishing a mathematical model of craniocerebral heat transfer, this paper theoretically studies the forecast of temperature distribution of the brain and the selective refrigeration control. Furthermore, this study provides guidance for practical clinical treatment by researching the rules of hypothermia and warming in different parts of the brain.
Privacy Preserving Fall Detection Based on Simple Human Silhouette Extraction and a Linear Support Vector Machine	237-252
Velislava Spasova, Ivo Iliev, Galidiya Petrova [ +/- abstract ][ full text ]
The paper presents a novel fast, real-time and privacy protecting algorithm for fall detection based on geometric properties of the human silhouette and a linear support vector machine. The algorithm uses infrared and visible light imagery in order to detect the human. A simple real-time human silhouette extraction algorithm has been developed and used to extract features for training of the support vector machine. The achieved sensitivity and specificity of the proposed approach are over 97% which match state of the art research in the area of fall detection. The developed solution uses low-cost hardware components and open source software library and is suitable for usage in assistive systems for the home or nursing homes.
Osteoporosis Recognition Based on Similarity Metric with SVM	253-264
Ke Zhou, Jie Cai, Yong-hui Xu, Tian-xiu Wu [ +/- abstract ][ full text ]
The purpose: Applying different techniques of classification to osteoporotic bone tissue texture analysis, exploring the recognition rate of the different classification methods. Methods: Using gray-level co-occurrence matrix (GLCM) and running a length matrix texture analysis to extract bone tissue slice image characteristic parameters, and to classify respectively 4x and 10x microscope images of the two groups: the sham (SHAM) and the ovariectomized (OVX) group image. Results: The metric support vector machine (SVM) classification algorithm, based on SVM learning or recognition rate, was higher than the stand-alone measure, and the classification results were stable. Conclusion: Measurement of the SVM classification algorithm for osteoporotic bone slices texture analysis revealed a high recognition rate.
MR Image Contrast Enhancement by Wavelet-based Contourlet Transform	265-278
Zhongliang Luo, Yingbiao Jia [ +/- abstract ][ full text ]
The contrast of magnetic resonance (MR) image local regions is low, edges blurred and image contains noise. To improve image contrast of local regions and solve the problem of noise enlarging, an MR image contrast enhancement algorithm by wavelet-based contourlet transform (WBCT) was put forward in this paper. Firstly, MR images were decomposed into low-pass and a series of high-pass sub-band images by WBCT, then algorithm adjustment coefficients of sub-band images were used through an enhancement operator. Finally, the contrast enhanced image was obtained by inverse WBCT. Compared with several image enhancement algorithms, the experimental results demonstrated that the ability of the proposed method in highlighting MR image's subtle features and preserving edges while suppressing noise. The contrast enhanced image had better visual effect, which is beneficial to doctor for diagnosing diseases.
Bioprocess systems
Application of NO Reduction Dynamical Model in SNCR Denitration System Based on Biomass	279-288
Feng Ran, Bingshuai Wang, Licui Qin [ +/- abstract ][ full text ]
In recent years, studies on denitration by applying biomass reburning method has drawn the attention of many researchers due to the characteristics of low sulfur and nitrogen content, high volatile, high ash focal activity, zero CO₂ net emissions, etc. Based on Chemkin software and selective non-catalytic reduction (SNCR) denitration chemical kinetic model, this paper conducted SNCR denitration chemical kinetic modeling. And the results showed that: with the increase of residence time, under the different initial concentration of NO, SNCR denitration efficiency tends to stabilize after the first increase. Moreover, the higher the initial concentration of NO, the longer the residence time which is required to achieve the greatest denitration efficiency. With the increase of ammonia nitrogen ratio, SNCR denitration efficiency increases step by step. When the normalized stoichiometric ratio (NSR) is greater than 1.5, the denitration efficiency is at a basic stable state. Under the same conditions, simulation results of the SNCR results agree well with the test results. Therefore, it can be concluded that carrying out the SNCR denitration chemical dynamics simulation using Chemkin software can provide a reference for tests and mechanism researches on SNCR, biomass reburning and advanced reburning denitration.
Prediction of Temperature Conditions of Autothermal Thermophilic Aerobic Digestion Bioreactors at Wastewater Treatment Plants	289-300
Elisaveta Kirilova, Natasha Vaklieva-Bancheva, Rayka Vladova [ +/- abstract ][ full text ]
Energy integration plays a significant role in increasing energy efficiency and sustainability of production systems. In order to model real energy integrated systems, sometimes we don't need rigorous models for involved units, but easily implemented and fast ones instead. This study presents an approach based on Artificial Neural Networks (ANNs) for predicting the main parameters of industrial Autothermal Thermophilic Aerobic Digestion (ATAD) bioreactors that are crucial for their energy integration. To create such predictive ANN model, four architectures with different number of hidden layers and artificial neurons in each one of them have been investigated. The developed ANN architectures have been trained and validated with data samplings obtained through long-term measurements of the operational conditions of real ATAD bioreactors. To train the models, BASIC genetic algorithm has been implemented. Using three independent measures for validation of the models, the best ANN architectures were selected. It is shown that selected ANN models predict with sufficient accuracy these ATAD parameters and are suitable for the implementation in an energy integration framework.
Rapid and Sensitive Detection of the Main Contaminating Fungus Penicillium restrictum in Jet Fuel using Loop-Mediated Isothermal Amplification Combined with a Lateral Flow Dipstick	301-312
Xiong Yun, Hao Yang, Peng Zhu, Hailong Huang [ +/- abstract ][ full text ]
We report a new contaminating fungus of jet fuel, Penicillium restrictum, which accounted for nearly 17% of the total sequence identified from five jet fuel samples as determined by the application of Illumina MiSeq sequencing-by-synthesis. We also report the development and validation of a new loop-mediated isothermal amplification (LAMP) assay combined with a lateral flow dipstick (LFD) for the repaid detection of P. restrictum. The optimal reaction conditions and primer set for LAMP were determined using a real-time turbidimeter. The LAMP-LFD assay was 1000-fold more sensitive than traditional PCR. P. restrictum could be detected specifically using the LAMP-LFD assay, and no amplification was observed when genomic DNA from another seven fungi found in jet fuel was tested. Eleven jet fuel samples from the field were tested using the LAMP-LFD assay we developed. Seven of them were positive for the presence of P. restrictum. These results were verified by traditional microbiological detection methods. Our results indicate that the LAMP-LFD assay is a rapid, accurate and sensitive tool for the detection of P. restrictum and could represent a new template for the detection of contaminating fungi in jet fuel.