Volume 24, Issue 1
InterCriteria Analysis of Data Obtained from Patients with Behterev’s Disease5-14
Bistra Zaharieva, Lyubka Doukovska, Simeon Ribagin, Irina Radeva
Bistra Zaharieva, Lyubka Doukovska, Simeon Ribagin, Irina Radeva (2020) InterCriteria Analysis of Data Obtained from Patients with Behterev’s Disease, Int J Bioautomation, 24 (1), 5-14, doi: 10.7546/ijba.2020.24.1.000507
Abstract: This paper continues series of research on application of the novel approach of InterCriteria Analysis (ICrA) to medical data. It describes a new method of analyzing the treatment results of patients with Behterev’s disease in order to aid the decision making process for treatment course - InterCriteria Analysis. The ICrA analysis is applied on the results of medicine, physiotherapeutic treatment and kinesitherapeutical program characteristics. The main goal is an improvement of general quality of patients’ life through practices of specific methodology of kinesitherapy and ergotherapy. The object of empirical study is health status of patients suffering Rheumatoid spondylitis in relation to their current life conditions. Here are analyzed the data from observation about 25 patients (14 women and 11 men, aged 25 to 67). The results confirm previously performed research, showing that the muscles in the human body are closely connected and the improving of one movement will lead to improving another. The obtained results also prove applicability of ICrA to the researched problem, give grounds for extending its application and potential of further in-depth study.

Keywords: InterCriteria аnalysis, Decision making, Bechterev's disease, Ankylosing spondylitis
Understanding miRNA Based Gene Regulation in Parkinson’s Disease:
An in silico Approach
15-28
Surya Narayan Rath, Manorama Patri
Surya Narayan Rath, Manorama Patri (2020) Understanding miRNA Based Gene Regulation in Parkinson’s Disease: An in silico Approach, Int J Bioautomation, 24 (1), 15-28, doi: 10.7546/ijba.2020.24.1.000555
Abstract: Parkinson’s disease (PD) is the second most common neurodegenerative disorder, mainly characterized by depletion or insufficient release of dopaminergic neurons in substantia nigra of the midbrain. Literature studies revealed the role of some protein coding genes such as LRRK2, SNCA, DJ-1, and Parkin in the disease pathway of PD and are regulated by few micro RNAs (miRNAs). miRNAs are highly conserved non-coding single stranded RNAs (~18-22bp) that target mRNA at 3’UTR (un-translated region) of protein coding genes and act as natural inhibitors. In spite of many researches, miRNAs based gene regulation in PD is still less understood. Therefore, the networks of miRNAs involved in normal development and survival of distinct neuronal populations, which are vulnerable in PD need to be addressed. Argonaute (AGO) protein is a family of protein, which assists miRNAs to bind with mRNAs of the target genes. The current study was undergone to elucidate the binding mechanism between AGO protein and miRNAs, and also with miRNAs-mRNAs duplex at atomic level by implicating computational approach. Therefore, thirty one miRNAs and twenty three different target genes involved in PD pathology were selected from public database and literatures. In silico analysis predicted strong binding affinity between three miRNAs such as miR-27b, miR-124-3p, and miR-29a with mRNAs of CYP1B1 and CDC42 genes respectively which may be considered as potent factors in gene regulation. The current investigation throws light towards understanding miRNAs based gene silencing mechanism in PD.

Keywords: miRNAs, Neurodegenerative disorders, Parkinson’s disease, Argonaute, Dopaminergic neurons
Case Studies on Neural Networks for Prediction in Health/Diseases Problems29-40
Edy Mulyanto, Arry Maulana Syarif, Fikri Budiman, Khafiizh Hastuti
Edy Mulyanto, Arry Maulana Syarif, Fikri Budiman, Khafiizh Hastuti (2020) Case Studies on Neural Networks for Prediction in Health/Diseases Problems, Int J Bioautomation, 24 (1), 29-40, doi: 10.7546/ijba.2020.24.1.000579
Abstract: Human health is one of topics which require minimum error or even zero tolerance error in all research including in computer science research. Classification in health problems is an interesting and ongoing topic research to solve a problem with minimum error result where neural network has become a popular approach in this area. Types and characteristics of data sources selected to make a prediction for seven health disease problems were described in this paper. The summary of the report is expected to be stimulation for next researches interest in selecting a method or a technique which is appropriate with the health problem to solve.

Keywords: Neural network, Classification, Prediction, Health
TNF-α: Common Culprit of Inflammatory Diseases41-50
Muhammad Nadeem, Uffaq Naz, Syeda Marriam Bakhtiar
Muhammad Nadeem, Uffaq Naz, Syeda Marriam Bakhtiar (2020) TNF-α: Common Culprit of Inflammatory Diseases, Int J Bioautomation, 24 (1), 41-50, doi: 10.7546/ijba.2020.24.1.000601
Abstract: Inflammation is a necessary evil required for restorative activities and healing but is also involved in the onset of diseases. Inflammatory markers such as Interleukin 6 (IL-6), ACE, and Tumor Necrosis Factor-α (TNF-α) are reported to be vital in the onset of various diseases including coronary artery disease (CAD), obesity, and diabetes. These inflammatory markers are reported from the various populations and are also involved in the pathophysiology of many other diseases. Yet there is no explanation that how these genes controlling specific inflammatory pathways are responsible for all of these diseases. Therefore, pathways enrichment method is exploited to identify the role of inflammatory genes in the onset of CAD, obesity, and diabetes. The results are verified and analyzed using protein-protein interaction network and disease-gene network analysis. It is concluded that CAD, obesity, and diabetes are linked with each other through AGE/RAGE and HIF-1 Signaling Pathway. It is also found that TNF-α is the common inflammatory gene which is involved for CAD, obesity, and diabetes.

Keywords: Inflammatory pathways, Pathway analysis, Protein-protein interaction, Network analysis, Disease-gene networks
Rationale for the Structural Organization of a Computerized Monitoring and Control System for Greenhouse Microclimate Using the Scale Transformation Method51-64
Ivan S. Laktionov, Oleksandr V. Vovna, Volodymyr I. Bondarenko, Anatolii A. Zori, Vladyslav A. Lebediev
Ivan S. Laktionov, Oleksandr V. Vovna, Volodymyr I. Bondarenko, Anatolii A. Zori, Vladyslav A. Lebediev (2020) Rationale for the Structural Organization of a Computerized Monitoring and Control System for Greenhouse Microclimate Using the Scale Transformation Method, Int J Bioautomation, 24 (1), 51-64, doi: 10.7546/ijba.2020.24.1.000612
Abstract: Industrial greenhouses are complex engineering structures that should provide control and operational management over microclimate parameters that affect the efficiency of evapotranspiration and photosynthesis processes, there by determining the rates of growth, volume and quality of vegetable production. The proposed method of physical modelling of the dynamics of microclimate parameters, in contrast to existing ones, takes into account the complex effect of the regulated list of controlled quantities on photosynthetic efficiency of greenhouse crops. An improved structural and algorithmic organization of a computerized information and measurement system for monitoring and control over industrial greenhouse microclimate has been synthesized, which takes into account the current trends in the development of infocommunication, sensory and microprocessor technologies. A laboratory prototype of an industrial automated greenhouse has been created, which takes into account the conditions for geometric, kinematic and dynamic similarity to real greenhouses. Promising areas of further study of the proposed model of the large-scale transition from the laboratory to the full-scale prototype are identified.

Keywords: Physical model, Laboratory prototype, Greenhouse, Dimension, Computerized technologies
Antimycotic Activity of Sumac Extract in Composites Based on Epoxidized Natural Rubber for Application in Footwear Soles Production65-78
Nikolay Dishovsky, Dessislava Marinkova, Raya Raykova, Latinka Vladimirova
Nikolay Dishovsky, Dessislava Marinkova, Raya Raykova, Latinka Vladimirova (2020) Antimycotic Activity of Sumac Extract in Composites Based on Epoxidized Natural Rubber for Application in Footwear Soles Production, Int J Bioautomation, 24 (1), 65-78, doi: 10.7546/ijba.2020.24.1.000613
Abstract: Biofilms are attached to different kinds of surfaces or associated with interfaces. The microbial communities are often composed of multiple species, which interact between each other. Attachment is complex process, regulated by diverse characteristics of the growing media, substrates and cell surface. Biofilms have different effects, which can affect changes in surface properties of polymer carriers. Accumulated biomass may provoke negative effects by direct attack, which leads to destruction of polymer matrixes. An option to solve the problem is introduction of bioactive ingredient into the composite. The aim of our study was to find and propose bioactive ingredients, derived from renewable sources, particularly such exhibiting of antimycotic influence, which can be included to elastomeric composite materials. These materials can be used for obtaining of winter footwear soles with adhesion, increasing to various types of icy surfaces. The influence of introduced antimycotic additive, extracted from Cotinus coggygria plant, was investigated. Antimycotic activity of obtained plant extracts against two eukaryotic strains was investigated by diffusion method in agar broth. The formation of biofilms from Candida lypolitica and Candida albicans strains onto natural rubber vulcanizates, kinetics and growth of biofilms strains were also observed.

Keywords: Biofilms, Extract, Antimycotic effect, Elastomeric composite materials
Trehalose Lipid Biosurfactant Reduced Cancer Cell Viability but Did not Affect the Isometric Contraction of Rat Mesenteric Arteries in vitro79-86
Boris Kadinov, Biliana Nikolova, Iana Tsoneva, Severina Semkova, Lyudmila Kabaivanova, Daniela Dimitrova
Boris Kadinov, Biliana Nikolova, Iana Tsoneva, Severina Semkova, Lyudmila Kabaivanova, Daniela Dimitrova (2020) Trehalose Lipid Biosurfactant Reduced Cancer Cell Viability but Did not Affect the Isometric Contraction of Rat Mesenteric Arteries in vitro, Int J Bioautomation, 24 (1), 79-86, doi: 10.7546/ijba.2020.24.1.000708
Abstract: Trehalose lipid biosurfactant from Nocardia farcinica strain is a naturally derived substance with potent anticancer activity. The increasing interest in naturally derived substances-based modality of cancer treatment requires investigations of the possible adverse effects of these substances, including the effects on vasculature. Therefore the present study was designed to investigate the effect of Trehalose lipid on isometric contraction of isolated rat mesenteric arteries. The contractile responses of arteries under Trehalose lipid was studied using wire myography for small blood vessels. The isometric contractions of rat mesenteric artery rings with intact endothelium were examined. The effect of this biosurfactant was assessed in arteries precontracted with 42 mM KCl as a vascular smooth muscle depolarizing stimulus. The results showed that Trehalose lipid (75 µM) failed to change high K+-induced contractions. The observed lack of effect of Trehalose lipid biosurfactant on the contractility of rat mesenteric arteries in vitro together with finding of reduced cancer cells viability makes it to be a suitable for potential medical application.

Keywords: Trehalose lipid, Breast cancer cells, Mesenteric artery, Isometric contraction, Vascular smooth muscle, Rat
Spark-based Parallelization of Basic Local Alignment Search Tool87-98
Hui Wang, Leixiao Li, Chengdong Zhou, Hao Lin, Dan Deng
Hui Wang, Leixiao Li, Chengdong Zhou, Hao Lin, Dan Deng (2020) Spark-based Parallelization of Basic Local Alignment Search Tool, Int J Bioautomation, 24 (1), 87-98, doi: 10.7546/ijba.2020.24.1.000767
Abstract: Sequence alignment is a key link of bioinformatics analysis. The basic local alignment search tool (BLAST) is a popular sequence alignment algorithm with high accuracy. However, the BLAST is inefficient in comparing and analyzing a massive amount of gene sequencing data. To solve the problem, this paper designs a distributed parallel BLAST method called SparkBLAST, based on the big data technique Spark. Under the in-memory computing framework Spark, SparkBLAST identifies the task of sequence alignment, divides the sequence dataset, and compares the sequence data. The Apache Hadoop YARN was adopted to task scheduling and resource allocation. Finally, the SparkBLAST was compared with standalone BLAST through experiments. The results show that SparkBLAST realized the speedup ratio of 3.95, without sacrificing the accuracy. In other words, SparkBLAST greatly outshines the standalone BLAST in calculation efficiency. The research findings provide bioinformatics researchers a highly efficient tool for sequence alignment.

Keywords: Sequence alignment, Basic local alignment search tool, Spark, Parallelization, Speedup

Sponsored by National Science Fund of Bulgaria, Grant No KP-06-NP/1/13, 2019

© 2020, BAS, Institute of Biophysics and Biomedical Engineering