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Kohat, Pakistan

Kohat University of Science and Technology is a public sector university established in 2001 at Kohat District, Khyber Pakhtunkhwa province of Pakistan by the governor, Lt. Gen. Syed Iftikhar Hussan Shah. Wikipedia.


Hossain Z.,West Bengal State University | Khatoon A.,Kohat University of Science and Technology | Komatsu S.,Japan National Agriculture and Food Research Organization
Journal of Proteome Research | Year: 2013

Plant response to abiotic stresses depends upon the fast activation of molecular cascades involving stress perception, signal transduction, changes in gene and protein expression and post-translational modification of stress-induced proteins. Legumes are extremely sensitive to flooding, drought, salinity and heavy metal stresses, and soybean is not an exception of that. Invention of immobilized pH gradient strips followed by advancement in mass spectrometry has made proteomics a fast, sensitive and reliable technique for separation, identification and characterization of stress-induced proteins. As the functional translated portion of the genome plays an essential role in plant stress response, proteomic studies provide us a finer picture of protein networks and metabolic pathways primarily involved in stress tolerance mechanism. Identifying master regulator proteins that play key roles in the abiotic stress response pathway is fundamental in providing opportunities for developing genetically engineered stress-tolerant crop plants. This review highlights recent contributions in the field of soybean biology to comprehend the complex mechanism of abiotic stress acclimation. Furthermore, strengths and weaknesses of different proteomic methodologies of extracting complete proteome and challenges and future prospects of soybean proteome study both at organ and whole plant levels are discussed in detail to get new insights into the plant abiotic stress response mechanism. © 2013 American Chemical Society. Source


Farooqi A.A.,Rashid Latif Medical College | ur Rehman Z.,Kohat University of Science and Technology | Muntane J.,University of Seville | Muntane J.,CIBER ISCIII
OncoTargets and Therapy | Year: 2014

There is increasing progress in translational oncology and tremendous breakthroughs have been made as evidenced by preclinical and clinical trials. Data obtained from high-throughput technologies are deepening our understanding about the molecular and gene network in cancer cells and rapidly emerging in vitro and in vivo evidence is highlighting the role of antisense agents as specific inhibitors of the expression of target genes, thus modulating the response of cancer cells to different therapeutic strategies. Much information is continuously being added into various facets of molecular oncology and it is now understood that over expression of antiapoptotic proteins, oncogenes, oncogenic microRNAs (miRNA), and fusion proteins make cancer cells difficult to target. Delivery of antisense oligonucleotides has remained a challenge and technological developments have helped in overcoming hurdles by improving the ability to penetrate cells, effective and targeted binding to gene sequences, and down regulation of target gene function. Different delivery systems, including stable nucleic acid lipid particles, have shown potential in enhancing the delivery of cargo to the target site. In this review, we attempt to summarize the current progress in the development of antisense therapeutics and their potential in medical research. We partition this multi component review into introductory aspects about recent breakthroughs in antisense therapeutics. We also discuss how antisense therapeutics have shown potential in resensitizing resistant cancer cells to apoptosis by targeted inhibition of antiapoptotic proteins, oncogenic miRNAs, and BCR-ABL. © 2014 Farooqi et al. Source


Mashwani W.K.,Kohat University of Science and Technology | Salhi A.,University of Essex
Applied Soft Computing Journal | Year: 2014

In recent years, hybridization of multi-objective evolutionary algorithms (MOEAs) with traditional mathematical programming techniques have received significant attention in the field of evolutionary computing (EC). The use of multiple strategies with self-adaptation manners can further improve the algorithmic performances of decomposition-based evolutionary algorithms. In this paper, we propose a new multiobjective memetic algorithm based on the decomposition approach and the particle swarm optimization (PSO) algorithm. For brevity, we refer to our developed approach as MOEA/D-DE+PSO. In our proposed methodology, PSO acts as a local search engine and differential evolution works as the main search operator in the whole process of optimization. PSO updates the position of its solution with the help of the best information on itself and its neighboring solution. The experimental results produced by our developed memtic algorithm are more promising than those of the simple MOEA/D algorithm, on most test problems. Results on the sensitivity of the suggested algorithm to key parameters such as population size, neighborhood size and maximum number of solutions to be altered for a given subproblem in the decomposition process are also included. Source


Ashiq S.,University of Peshawar | Hussain M.,Kohat University of Science and Technology | Ahmad B.,University of Peshawar
Fungal Genetics and Biology | Year: 2014

Medicinal plants are widely used as home remedies and raw materials for the pharmaceutical industries. Herbal remedies are used in the prevention, treatment and cure of disorders and diseases since ancient times. However, use of medicinal herbs may not meet the requirements of quality, safety and efficacy. During harvesting, handling, storage and distribution, medicinal plants are subjected to contamination by various fungi, which may be responsible for spoilage and production of mycotoxins. The increasing consumption of medicinal plants has made their use a public health problem due to the lack of effective surveillance of the use, efficacy, toxicity and quality of these natural products. The increase in use of medicinal plants may lead to an increase in the intake of mycotoxins therefore contamination of medicinal plants with mycotoxins can contribute to adverse human health problems and therefore represents a special hazard. Numerous natural occurrences of mycotoxins in medicinal plants and traditional herbal medicines have been reported from various countries including Spain, China, Germany, India, Turkey and from Middle East as well. This review discusses the important mycotoxins and their natural occurrences in medicinal plants and their products. © 2014 Elsevier Inc. Source


Jan M.A.,Kohat University of Science and Technology | Khanum R.A.,University of Essex
Applied Soft Computing Journal | Year: 2013

Penalty functions are frequently employed for handling constraints in constrained optimization problems (COPs). In penalty function methods, penalty coefficients balance objective and penalty functions. However, finding appropriate penalty coefficients to strike the right balance is often very hard. They are problems dependent. Stochastic ranking (SR) and constraint-domination principle (CDP) are two promising penalty functions based constraint handling techniques that avoid penalty coefficients. In this paper, the extended/modified versions of SR and CDP are implemented for the first time in the multiobjective evolutionary algorithm based on decomposition (MOEA/D) framework. This led to two new algorithms, CMOEA/D-DE-SR and CMOEA/D-DE-CDP. The performance of these new algorithms is tested on CTP-series and CF-series test instances in terms of the HV-metric, IGD-metric, and SC-metric. The experimental results are compared with NSGA-II, IDEA, and the three best performers of CEC 2009 MOEA competition, which showed better and competitive performance of the proposed algorithms on most test instances of the two test suits. The sensitivity of the performance of proposed algorithms to parameters is also investigated. The experimental results reveal that CDP works better than SR in the MOEA/D framework. © 2012 Elsevier B.V. All rights reserved. Source

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