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Construction of Covalently Linked Caspase-9 Dimer and Its Biochemical Characterization
Karki, Pratap,Dahal, Giri Raj,Park, Il-Seon 朝鮮大學校 附設 醫學硏究所 2007 The Medical Journal of Chosun University Vol.32 No.1
The activation of caspase-9 is best described by induced proximity model that postulates the dimer-driven assembly of monomeric caspase-9 in apoptosome as an activation mechanism. Further, the crystallographic structure of active caspase-9 has shown that termini of monomers lie quite close to each other. With an aim to analyze the role of dimehzation and proteolytic processing in activation, constitutively dimeric forms of caspase-9 were engineered by connecting termini of two caspase-9 molecules. These dimers could be overexpressed and purified in Escherichia coli. The recombinant dimers showed 2-fold increment in specific activity over their respective monomer that was lower than expected if dimerization is the only mechanisJi to activate caspase-9. Citrate, a well-known kosmotrope to enhance dimenzation, increased the activity of wild type monomer and dimer by -75 and -10 times respectively which was -5 times better than that of corresponding uncleavable mutant ones. The possible reason behind this failure of engineered dimers to mimic Apaf-l activated caspase-9 may lie in the distinctly different scenario of dimehzation in two cases or it may be the outcome of the defective design that restricted the complete dimehzation. However, this simple design could enable to produce constitutively dimeric caspase-9 with catalytic advancements over their monomers that may be helpful for future studies to elucidate the molecular mechanism of caspase-9 activation.
Methods in the spatial deep learning: current status and future direction
Bhogendra Mishra,Ashok Dahal,Nirajan Luintel,Tej Bahadur Shahi,Saroj Panthi,Shiva Pariyar,Bhoj Raj Ghimire 대한공간정보학회 2022 Spatial Information Research Vol.30 No.2
A deep neural network (DNN), evolved from a traditional artificial neural network, has been seamlessly adapted for the spatial data domain over the years. Deep learning (DL) has been widely applied for a number of applications and a variety of thematic domains. This article reports on a systematic review of methods adapted in major DNN applications with remote sensing data published between 2010 and 2020 aiming to understand the major application area, a framework for model development and the prospect of DL application in spatial data analysis. It has been found that image fusion, change detection, scene classification, image segmentation, and feature detection are the most commonly used application areas. Based on the publication in these thematic areas, a generic framework has been devised to guide a model development using DL based on the methods followed in the past. Finally, recent trends and prospects in terms of data, method, and application of deep learning with remote sensing data are discussed. The review finds that while DL-based approaches have the potential to unfold hidden information, they face challenges in selecting the most appropriate data, methods, and model parameterizations which may hinder the performance. The increasing trend of application of DL in the spatial domain is expected to leverage its strength at its optimum to the research frontiers.
Effects of spark dielectric barrier discharge plasma on water sterilization and seed germination
Dhakal Oat Bahadur,Dahal Roshani,Acharya Tirtha Raj,Lamichhane Prajwal,Gautam Sandhya,Lama Bhupendra,khanal Raju,Kaushik Nagendra Kumar,최은하,Chalise Roshan 한국물리학회 2023 Current Applied Physics Vol.54 No.-
This study investigated the effects of spark dielectric barrier discharge (SDBD) plasma on water sterilization and seed germination using an in-situ treatment method. The plasma diagnostics used I–V characteristics and optical emission spectroscopy. The electron, rotational, and vibrational temperature, as well as electron density were measured. The findings revealed that SDBD plasma treatment caused significant changes in the physicochemical properties of the liquids. In addition, the concentrations of H2O2, NO2− and NO3− were increased after 8 min of plasma treatment to 30, 40, and 100 mgL−1, respectively. The effectiveness of the SDBD plasma treatment was evaluated based on bacterial inactivation and seed germination. After 8 min of plasma treatment, an almost complete removal of E. coli and S. aureus was achieved. Furthermore, the germination of coriander seeds was enhanced when they were treated with SDBD plasma for 5 min. SDBD plasma shows promise for water sterilization, seed germination, and sustainability.
Thapa, Arjun,Shahnawaz, Md,Karki, Pratap,Raj Dahal, Giri,Sharoar, Md Golam,Yub Shin, Song,Sup Lee, Jung,Cho, Byungyun,Park, Il-Seon Eaton Pub. Co 2008 Biotechniques Vol.44 No.6
<P>Proteins and peptides expressed in the prokaryotic system often form inclusion bodies. Solubilization and refolding procedures can be used for their recovery, but this process remains difficult. One strategy for improving the solubility of a protein of interest is to fuse it to a highly soluble protein. To select a suitable fusion partner capable of solubilizing the aggregation-prone (inclusion body-forming) proteins and peptides, Escherichia coli thermostable proteins were identified and tested. Among them, trigger factor (TF) protein was selected because of its high expression and stability. Using an expression system based on fusion to TF, selected proteins and peptides that otherwise form inclusion bodies were expressed in soluble state and were purified like other soluble proteins. This system provides a convenient method for production of aggregation-prone proteins and peptides.</P>