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  • Open Access

    ARTICLE

    In Silico Disulfide Bond Engineering to Improve Human LEPTIN Stability

    Bahram Barati1, Fatemeh Fazeli Zafar1, Shuanhu Hu1, Najmeh Fani2, Sajjad Eshtiaghi3, Shuang Wang1,*

    Journal of Renewable Materials, Vol.9, No.11, pp. 1843-1857, 2021, DOI:10.32604/jrm.2021.016301 - 04 June 2021

    Abstract Enhancing the stability of biomolecules is one of the hot topics in industry. In this study, we enhanced the stability of an important protein called LEPTIN. LEPTIN is a hormone secreted by fat cells playing an essential role in body weight and composition, and its deficiency can result in several disorders. The treatment of related LEPTIN dysfunctions is often available in the form of injection. To decrease the cost and the frequency of its applications can be achieved by increasing its lifetime through engineering LEPTIN. In this study, to engineer LEPTIN, we have introduced disulfide… More > Graphic Abstract

    <i>In Silico</i> Disulfide Bond Engineering to Improve Human LEPTIN Stability

  • Open Access

    ARTICLE

    Biochemical and Thermal Analysis of Spirulina Biomass through FTIR, TGA, CHN

    Ruma Arora Soni1,*, K. Sudhakar1,3,4,*, R. S. Rana2

    Energy Engineering, Vol.118, No.4, pp. 1045-1056, 2021, DOI:10.32604/EE.2021.016082 - 31 May 2021

    Abstract Spirulina is a sort of algae that grows in both fresh and seawater. It is considered the Earth’s most nutritionally dense food. Certain claims about Spirulina’s beneficial health properties are attributed to the relatively high protein content of the cells. Spirulina’s lipid, fatty acid profile, and biochemical composition have received little attention. The purpose of this study is to investigate the nature and decomposition of spirulina biomass at various temperatures. In the present investigation, Fourier transforms infrared spectroscopy, thermogravimetric analysis, and elemental analysis were used to study spirulina biomass biochemical characteristics. The optimal content of… More >

  • Open Access

    ARTICLE

    Proteomic Analysis of High Temperature Stress-Responsive Proteins in Chrysanthemum Leaves

    Xin Li, Feiya Liao, Qiqi Ma, Beibei Jiang*, Yuanzhi Pan, Cheng Luo, Xinjie Wang, Aining Ran

    Phyton-International Journal of Experimental Botany, Vol.90, No.5, pp. 1415-1423, 2021, DOI:10.32604/phyton.2021.016143 - 27 May 2021

    Abstract Chrysanthemum is one of the most important ornamental flowers in the world, and temperature has a significant influence on its field production. In the present study, differentially expressed proteins were investigated in the leaves of Dendranthema grandiflorum ‘Jinba’ under high temperature stress using label-free quantitative proteomics techniques. The expressed proteins were comparatively identified and analyzed. A total of 1,463 heat-related, differentially expressed proteins were successfully identified by Liquid Chromatography-tandem Mass Spectrometry (LC-MS/MS), and 1,463 heat-related, differentially expressed proteins were successfully identified by mass spectrometry after a high temperature treatment. Among these, 701 proteins were upregulated and… More >

  • Open Access

    ARTICLE

    DTLM-DBP: Deep Transfer Learning Models for DNA Binding Proteins Identification

    Sara Saber1, Uswah Khairuddin2,*, Rubiyah Yusof2, Ahmed Madani1

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3563-3576, 2021, DOI:10.32604/cmc.2021.017769 - 06 May 2021

    Abstract The identification of DNA binding proteins (DNABPs) is considered a major challenge in genome annotation because they are linked to several important applied and research applications of cellular functions e.g., in the study of the biological, biophysical, and biochemical effects of antibiotics, drugs, and steroids on DNA. This paper presents an efficient approach for DNABPs identification based on deep transfer learning, named “DTLM-DBP.” Two transfer learning methods are used in the identification process. The first is based on the pre-trained deep learning model as a feature’s extractor and classifier. Two different pre-trained Convolutional Neural Networks… More >

  • Open Access

    ARTICLE

    Accumulation Characteristics of Protein and Non-Protein Components and Their Correlations with Protein Concentration in Rice Grains

    Xiaoli Zhang1,2,#, Xiaohong Yin2,3,#, Jiana Chen3,#, Fangbo Cao3, Yu Liu3, Zhengwu Xiao3, Liqin Hu3, Guanghui Chen3, Tianfeng Liang1,2,*, Min Huang3,*

    Phyton-International Journal of Experimental Botany, Vol.90, No.4, pp. 1285-1292, 2021, DOI:10.32604/phyton.2021.014778 - 27 April 2021

    Abstract Protein in rice grains is an important source of nutrition for rice consumers. This study mainly aimed to identify the critical factors that determine grain protein concentration in rice. Accumulation parameters, including mean accumulation rate (Rmean) and active accumulation duration (Dactive), for protein and non-protein components and their correlations with protein concentration in rice grains were investigated in field experiments conducted over two years with six rice cultivars. Results showed that grain protein concentration ranged from 9.6% to 11.9% across cultivars and years. Accumulation processes of protein and non-protein components were well fitted by the logistic More >

  • Open Access

    ARTICLE

    Ultrastructural analysis shows persistence of adhesion and tight junction proteins in mature human hair

    LORENZO ALIBARDI1, BERND NOECKER2

    BIOCELL, Vol.45, No.4, pp. 1013-1022, 2021, DOI:10.32604/biocell.2021.013913 - 22 April 2021

    Abstract The differentiation of cells composing mature human hairs produces layers with different corneous characteristics that would tend to flake away one from another, as in the corneous layer of the epidermis, without anchoring junctions. It is likely that cell junctions established in the forming cells of the hair bulb are not completely degraded like in the corneous layer of the epidermis but instead remain in the hair shaft to bind mature cuticle, cortex, and medulla cells into a compact hair shaft. During cell differentiation in hairs, cell junctions seem to disappear, and little is known… More >

  • Open Access

    ARTICLE

    Overexpression of rice F-box phloem protein gene OsPP12-A13 confers salinity tolerance in Arabidopsis

    CHUNKUN FAN, YONGPENG ZHANG, CHUNBAO YANG, YAWEI TANG, JI QU, BU JIE, DEJI QUZHEN, LIYUN GAO*

    BIOCELL, Vol.45, No.4, pp. 1121-1135, 2021, DOI:10.32604/biocell.2021.014336 - 22 April 2021

    Abstract Salinity is a serious challenge for agriculture production by limiting the arable land. Rice is a major staple food crop but very sensitive to salt stress. In this study, we used Arabidopsis for the functional characterization of a rice F-box gene LOC_Os04g48270 (OsPP12-A13) under salinity stress. OsPP12-A13 is a nuclear-localized protein that is strongly upregulated under salinity stress in rice and showed the highest expression in the stem, followed by roots and leaves. Two types of transgenic lines for OsPP12-A13 were generated, including constitutive tissue over-expression using the CaMV35S promoter and phloem specific over-expression using the pSUC2 promoter.… More >

  • Open Access

    ARTICLE

    Covalent and Ionic Bonding between Tannin and Collagen in Leather Making and Shrinking: A MALDI-ToF Study

    Antonio Pizzi*

    Journal of Renewable Materials, Vol.9, No.8, pp. 1345-1364, 2021, DOI:10.32604/jrm.2021.015663 - 08 April 2021

    Abstract Collagen powder hydrolysates were reacted with a solution of commercial mimosa bark tannin extract. The mixture was prepared at ambient temperature and prepared at 80°C to determine what reactions, if any, did occur between the collagen protein through its amino acids and the polyphenolic condensed tannin. The reaction products obtained were analyzed by matrix assisted laser desorption ionization time-of-flight (MALDI ToF) mass spectrometry. Reactions between the two materials did appear to occur, with the formation of a relatively small proportion of covalent and ionic linkages at ambient temperature but a considerable proportion of covalent linkages… More >

  • Open Access

    ARTICLE

    Genome-wide Analysis of a Plant AT-rich Sequence and Zinc-binding Protein (PLATZ) in Triticum Aestivum

    Xiaohang He1, Minjie Liu2, Zhengwu Fang1, Dongfang Ma1,2,3,*, Yilin Zhou1,3,*, Junliang Yin1

    Phyton-International Journal of Experimental Botany, Vol.90, No.3, pp. 971-986, 2021, DOI:10.32604/phyton.2021.012726 - 30 March 2021

    Abstract Plant AT-rich sequence and zinc-binding protein (PLATZ) is a plant transcription factor that has been studied in corn. PLATZ can non-specifically bind to sequences rich in A/T bases to induce transcriptional repression. It is involved in the regulation of dehydration tolerance in seeds. In this study, we performed bioinformatics analysis to identify and characterize wheat PLATZ(TaPLATZ)genes. We identified 49 wheat PLATZ genes by searching the wheat genome by using known PLATZ gene sequences from rice, Arabidopsis, and maize. Phylogenetic analysis on PLATZ gene sequences from different species was performed. We found that PLATZs could be divided into three groups.… More >

  • Open Access

    ARTICLE

    Multifactorial Disease Detection Using Regressive Multi-Array Deep Neural Classifier

    D. Venugopal1, T. Jayasankar2,*, N. Krishnaraj3, S. Venkatraman4, N. B. Prakash5, G. R. Hemalakshmi5

    Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 27-38, 2021, DOI:10.32604/iasc.2021.015205 - 17 March 2021

    Abstract Comprehensive evaluation of common complex diseases associated with common gene mutations is currently a hot area of human genome research into causative new developments. A multi-fractal analysis of the genome is performed by placing the entire DNA sequence into smaller fragments and using the chaotic game representation and systematic methods to calculate the general dimensional spectrum of each fragment. This is a time consuming process as it uses floating point to represent large data sets and requires processing time. The proposed Regressive Multi-Array Deep Neural Classifier (RMDNC) system is implemented to reduce the computation time,… More >

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