A hybrid of ant colony optimization and flux variability analysis to improve the production of l-phenylalanine and biohydrogen

In silico metabolic engineering has shown many successful results in genome - scale model reconstruction and modification of metabolic network by implementing reaction deletion strategies to improve microbial strain such as production yield and growth rate. While improving the metabolites production, optimization algorithm has been implemented gradually in previous studies to identify the near - optimal sets of reaction knockout to obtain the best results. However, previous works implemented other algorithms that differ than this study which faced with several issues such as premature convergence and able to only produce low production yield because of ineffective algorithm and existence of complex metabolic data. The lack of effective genome models is because of the presence thousands of reactions in the metabolic network caused complex and high dimensional data size that contains competing pathway of non - desirable product. Indeed, the suitable population size and knockout number for this new algorithm have been tested previously. This study proposes an algorithm that is a hybrid of the ant colony optimization algorithm and flux variability analysis (ACOFVA) to predict near - optimal sets of reactions knockout in an effort to improve the growth rates and the production rate of L - phenylalanine and biohydrogen in Saccharomyces cerevisiae and cyanobacteria Synechocystis sp PCC6803 respectively

Prevalence of Metabolic Syndrome in Iranian Professional Drivers: Results from a Population Based Study of 12,138 Men

It is evident that professional driving is associated with substantial changes in lifestyle habits. Professional drivers are prone to metabolic syndrome (MetS) and its complications because their working environment is characterized by numerous stress factors such as lack of physical activity due to working in a fixed position, disruption in diet, and irregular sleep habits. The aim of the present study was to estimate the prevalence of MetS among long distance drivers residing in West Azerbaijan province in Iran.To assess the prevalence of metabolic syndrome among professional long distance drivers, 12138 participants were enrolled in this cross sectional study. The MetS was defined using International Diabetes Federation criteria.Among12138 participants, 3697 subjects found to be MetS. The crude and age-adjusted rates of MetS were 30.5% and 32.4% respectively. Based on Body mass index (BMI), 5027 subjects (41.4%) were overweight (BMI ≥25.01–30 kg/m2), and 2592 (21.3%) were obese (BMI ≥30.01 kg/m2). The presence of central obesity was more common than other components. The associations of MetS with BMI, pack-year smoking, age, weekly driving duration and driving experiences were significant in the logistic regression. By increasing BMI, pack-year smoking, age, weekly driving duration and driving experiences, odds ratio of MetS was increased.The study suggests that MetS has become a noteworthy health problem among Iranian long distance drivers. This might be due to the following facts: sitting in a fixed position for long hours while working, cigarette smoking, job stress, unhealthy diet and lack of physical activity. Educational programs should be established for promoting healthy lifestyle and also for early detection and appropriate intervention

A Novel Conserved Isoform of the Ubiquitin Ligase UFD2a/UBE4B Is Expressed Exclusively in Mature Striated Muscle Cells

Yeast Ufd2p was the first identified E4 multiubiquitin chain assembly factor. Its vertebrate homologues later referred to as UFD2a, UBE4B or E4B were also shown to have E3 ubiquitin ligase activity. UFD2a function in the brain has been well established in vivo, and in vitro studies have shown that its activity is essential for proper condensation and segregation of chromosomes during mitosis. Here we show that 2 alternative splice forms of UFD2a, UFD2a-7 and -7/7a, are expressed sequentially during myoblast differentiation of C2C12 cell cultures and during cardiotoxin-induced regeneration of skeletal muscle in mice. UFD2a-7 contains an alternate exon 7, and UFD2a-7/7a, the larger of the 2 isoforms, contains an additional novel exon 7a. Analysis of protein or mRNA expression in mice and zebrafish revealed that a similar pattern of isoform switching occurs during developmental myogenesis of cardiac and skeletal muscle. In vertebrates (humans, rodents, zebrafish), UFD2a-7/7a is expressed only in mature striated muscle. This unique tissue specificity is further validated by the conserved presence of 2 muscle-specific splicing regulatory motifs located in the 3′ introns of exons 7 and 7a. UFD2a interacts with VCP/p97, an AAA-type ATPase implicated in processes whose functions appear to be regulated, in part, through their interaction with one or more of 15 previously identified cofactors. UFD2a-7/7a did not interact with VCP/p97 in yeast 2-hybrid experiments, which may allow the ATPase to bind cofactors that facilitate its muscle-specific functions. We conclude that the regulated expression of these UFD2a isoforms most likely imparts divergent functions that are important for myogenisis

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field

Doctor can I buy a new kidney? I've heard it isn't forbidden: what is the role of the nephrologist when dealing with a patient who wants to buy a kidney?

Organ trafficking is officially banned in several countries and by the main Nephrology Societies. However, this practice is widespread and is allowed or tolerated in many countries, hence, in the absence of a universal law, the caregiver may be asked for advice, placing him/her in a difficult balance between legal aspects, moral principles and ethical judgments. In spite of the Istanbul declaration, which is a widely shared position statement against organ trafficking, the controversy on mercenary organ donation is still open and some experts argue against taking a negative stance. In the absence of clear evidence showing the clinical disadvantages of mercenary transplantation compared to chronic dialysis, self-determination of the patient (and, with several caveats, of the donor) may conflict with other ethical principles, first of all non-maleficence. The present paper was drawn up with the participation of the students, as part of the ethics course at our medical school. It discusses the situation in which the physician acts as a counselor for the patient in the way of a sort of “reverse” informed consent, in which the patient asks advice regarding a complex personal decision, and includes a peculiar application of the four principles (beneficence, non-maleficence, justice and autonomy) to the donor and recipient parties

A hybrid genetic algorithm and support vector machine classifier for feature selection and classification of gene expression

Advancement in gene expression technology offers the ability to measure the expression levels of thousand of genes in parallel. Gene expression microarray data is expected to significantly aid in the development of efficient cancer diagnosis and classification platforms. Key issues that need to be addressed under such circumstances are the efficient selection of a small subset of genes that might profoundly contribute to disease identification from the thousand of genes measured on microarrays that are inherently noisy. This research deals with finding a small subset of informative genes from gene expression data which maximizes the classification accuracy. This research proposed a hybrid between Genetic Algorithm and Support Vector Machine classifier for selecting an optimal small subset of informative genes and classifying the optimal subset. Two benchmark data sets were used to evaluate the usefulness of the approach for small and high dimension data. Although, the experimental results showed that the hybrid method performed better than some of the best previous methods on small dimensional data, its performance deteriorated significantly on the higher dimensional data. An improved version of the hybrid method was designed by introducing a new algorithm for features selection based on improved chromosome representation to replace the original algorithm on the hybrid method which appeared to perform poorly on high dimensional data. The results of the gene expression microarray classification demonstrated that the proposed method performed better than the original and the previous methods. The informative genes from the experiment results proved to be biologically plausible when compared with the biological results produced from biologist and computer scientist researches

Aspartate biosynthesis pathway simulation using an improved differential evolution algorithm through parameter estimation

Aspartate Biosynthesis Pathway Simulation Using an Improved Differential Evolution Algorithm through Parameter Estimation Chuii Khim Chong1, Mohd Saberi Mohamad1, Safaai Deris1, Shahir Shamsir2, Yee Wen Choon1 and Lian En Chai1 1 Artificial Intelligence and Bioinformatics Research Group, Faculty of Computer Science and Information Systems, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia. 2 Department of Biological Sciences, Faculty of Biosciences and Bioengineering, Universiti Teknologi Malaysia, 81310 UTM Skudai, Johor, Malaysia Corresponding author’s e-mail: [email protected] Keywords: Parameter Estimation, Differential Evolution Algorithm, Kalman Filter, Simulation. Introduction. Metabolic Engineering is a method which allows modifications of the pathways in suitable host cells. It aims at producing a novel or achieving an expected amount of desire compound for medical and industrial use. Recent studies mainly have concentrated on the aim of analysis by altering the computer readable data from the biological process. Thus, with the study of metabolic pathway, scientists can simulate the process inside the cell by mathematical modeling. The main goal of system biology is to develop an accurate pathway model that functions as a biological function simulator. Aspartate biosynthesis pathway is a sequence of events that occur in a cell causing production of amino acid called aspartate. Aspartate is very crucial in the urea cycle for the proper elimination of waste products from dietary protein. Parameter estimation is one of the crucial steps in constructing mathematical model. Regrettably, it faces a number of difficulties, for example high complexity of the model which is caused by the increasing number of unidentified parameters and equations in the model [1], and the existence of noisy data which causes low accuracy [2]. Thus, we proposed IDE which is a hybrid of DE and KF, to solve the existence of noisy data that leads to low accuracy for estimated result and the increasing unidentified parameters which lead to the complexity of the model. Noisy data can occur when the retrieved results differ from each other and this is due to apparatus limitation or human error. The advantages of DE are speed, straightforwardness, efficiency, and ease of use as it contains only few control parameters [3]. Moreover, KF can improve DE’s performance as it uses Kalman gain value which handles noisy data to update the population [2]. Moonchai Sompop et al. [4] and Christophe Chassagnole et al. [5], implemented DE as a parameter estimation approach to enhance the production of aspartate, bacteriocin, beer, and the simulation of the actual process in cell by estimating the control parameters and kinetic parameters