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1,166 results on '"Naik, K."'

19. Harnessing the Power of Saussurea obvallata Zinc Oxide Nanoparticles for Accelerated Wound Healing and Antimicrobial Action

Author

Moalwi A, Naik K, Muddapur UM, Aldoah B, AlWadai HH, Alamri AM, Alsareii SA, Mahnashi MH, Shaikh IA, Khan AA, and More SS

Subjects
green synthesis, wound healing, zinc oxide nps, saussurea obvallata, antimicrobial, Medicine (General), R5-920
Abstract

Adel Moalwi,1 Keerti Naik,2 Uday M Muddapur,2 Bader Aldoah,1 Hajar Hassan AlWadai,1 Abdulrahman Manaa Alamri,1 Saeed A Alsareii,1 Mater H Mahnashi,3 Ibrahim Ahmed Shaikh,4 Aejaz Abdullatif Khan,5 Sunil S More6 1Department of Surgery, College of Medicine, Najran University, Najran, Saudi Arabia; 2Department of Biotechnology, KLE Technological University, BVB Campus, Hubballi, Karnataka, India; 3Department of Pharmaceutical Chemistry, College of Pharmacy, King Khalid University, Abha, Saudi Arabia; 4Department of Pharmacology, College of Pharmacy, Najran University, Najran, Saudi Arabia; 5Department of General Science, Ibn Sina National College for Medical Studies, Jeddah, Saudi Arabia; 6School of Basic and Applied Sciences, Dayananda Sagar University, Bangalore, Karnataka, IndiaCorrespondence: Uday M Muddapur; Mater H Mahnashi, Email muddapur@kletech.ac.in; matermaha@gmail.comIntroduction: Zinc oxide nanoparticles (ZnONPs) have been the subject of substantial research by virtue of their utility across extensive downstream applications. Moreover, the ZnONPs are inexpensive, reliable, and easy to produce. Green synthesis employing biological systems, particularly plant extracts, has arisen as a subject of study in nanotechnology and is gaining importance due to its multiple applications in biology, chemistry, physics, and medicine.Methods: Aqueous extract of S. obvallata was prepared and ZnONPs were synthesised using zinc acetate as a substrate. UV-Vis spectrophotometric measurement confirmed the production of ZnONPs. The ZnONPs were characterized by employing SEM, EDS, XRD, and FTIR. The ZnONPs were screened for its antimicrobial and wound healing potential.Results: The peak of absorbance for UV-Vis was observed at 370 nm. The average dimension of the particles was found to be 22.58 nm. The antibacterial activity of ZnONPs was efficient in countering a broad spectrum of bacteria and the fungi C. albicans. The results of in vitro and in vivo wound healing assays indicate that the ZnONPs possess potent wound healing potential. In the cell migration assay, the percentage of wound closure was observed to be 84.70% (p < 0.001) for ZnONPs compared to the untreated group (8.12%). In the excision wound healing rat model, the animals treated with ZnONPs and Povidone-Iodine showed a significant (p < 0.01) wound contraction in comparison to the untreated animals.Discussion: The ZnONPs promoted wound healing processes and showed promise as a therapeutic agent. However, further research is needed to understand the mechanisms of action and evaluate the long-term safety and effectiveness of ZnONPs in wound healing applications. By using renewable biological materials, the green synthesis of ZnONPs minimizes the need for synthetic reagents and lowers the total carbon footprint related to the production of nanoparticles.Keywords: green synthesis, wound healing, zinc oxide NPs, Saussurea obvallata, antimicrobial

Published
2024

33. Exploring selection signatures in the divergence and evolution of lipid droplet (LD) associated genes in major oilseed crops

Author

Ramya Parakkunnel, Bhojaraja Naik K, Girimalla Vanishree, Anjitha George, Sripathy KV, Aruna YR, Udaya Bhaskar K, A Anandan, and Sanjay Kumar

Subjects
Germination, Lipid droplet, Lipoxygenase, Phospholipase D, Natural selection, Oleosin, Biotechnology, TP248.13-248.65, Genetics, QH426-470
Abstract

Abstract Background Oil bodies or lipid droplets (LDs) in the cytosol are the subcellular storage compartments of seeds and the sites of lipid metabolism providing energy to the germinating seeds. Major LD-associated proteins are lipoxygenases, phospholipaseD, oleosins, TAG-lipases, steroleosins, caleosins and SEIPINs; involved in facilitating germination and enhancing peroxidation resulting in off-flavours. However, how natural selection is balancing contradictory processes in lipid-rich seeds remains evasive. The present study was aimed at the prediction of selection signatures among orthologous clades in major oilseeds and the correlation of selection effect with gene expression. Results The LD-associated genes from the major oil-bearing crops were analyzed to predict natural selection signatures in phylogenetically close-knit ortholog clusters to understand adaptive evolution. Positive selection was the major force driving the evolution and diversification of orthologs in a lineage-specific manner. Significant positive selection effects were found in 94 genes particularly in oleosin and TAG-lipases, purifying with excess of non-synonymous substitution in 44 genes while 35 genes were neutral to selection effects. No significant selection impact was noticed in Brassicaceae as against LOX genes of oil palm. A heavy load of deleterious mutations affecting selection signatures was detected in T-lineage oleosins and LOX genes of Arachis hypogaea. The T-lineage oleosin genes were involved in mainly anther, tapetum and anther wall morphogenesis. In Ricinus communis and Sesamum indicum > 85% of PLD genes were under selection whereas selection pressures were low in Brassica juncea and Helianthus annuus. Steroleosin, caleosin and SEIPINs with large roles in lipid droplet organization expressed mostly in seeds and were under considerable positive selection pressures. Expression divergence was evident among paralogs and homeologs with one gene attaining functional superiority compared to the other. The LOX gene Glyma.13g347500 associated with off-flavor was not expressed during germination, rather its paralog Glyma.13g347600 showed expression in Glycine max. PLD-α genes were expressed on all the tissues except the seed,δ genes in seed and meristem while β and γ genes expressed in the leaf. Conclusions The genes involved in seed germination and lipid metabolism were under strong positive selection, although species differences were discernable. The present study identifies suitable candidate genes enhancing seed oil content and germination wherein directional selection can become more fruitful.

Published
2024
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35. Structure and reaction study of Z=120 isotopes using non-relativistic and relativistic mean-field formalism

Author

Pattnaik, Jeet Amrit, Naik, K. C., Panda, R. N., Bhuyan, M., and Patra, S. K.

Subjects
Nuclear Theory
Abstract

An extensive study is carried out for the island of stability in the superheavy nuclei of Z=120 and N=164-220 within the effective field theory motivated relativistic mean-field (E-RMF) and the non-relativistic Skyrme-Hartree-Fock (SHF) approaches. The relativistic G3 and IOPB-I and non-relativistic SLy4 and SkMP parameter sets are used for the investigations. Surface properties such as symmetry energy, neutron pressure and the curvature coefficient of symmetry energy are discussed within the coherent density fluctuation model (CDFM) using the Skyrme and the Br\"uckner energy density functionals. The volume and surface contributions of symmetry energy are evaluated using Danielewicz's liquid drop approximation within the CDFM. The total nuclear reaction and elastic differential cross-sections are also obtained for both SHF and E-RMF within the Glauber model. The peaks in the symmetry energy at N = 182 for SHF and N=184 for E-RMF are seen, which are absent in the Br\"uckner functional. The shifting of peak in the symmetry energy with Br\"uckner functional can be correlated to the Coester-band problem. The enhanced total reaction cross-section for relativistic density of $^{304}120$ suggests the extra stability of this nucleus. This further confirms the shell/sub-shell closure of N = 184 in E-RMF force. The differential cross-section shows its force independent nature and significant increase with the scattering angle., Comment: 13 pages, 9 figures, 1 table

Published
2022

40. Stainless Steel-Reinforced Concrete (SSRC): a Review

Author

Sai PhaniSwethaswari, S., Kasagani, Hanuma, Anjaneyulu Naik, K., Srinivas, Chava, di Prisco, Marco, Series Editor, Chen, Sheng-Hong, Series Editor, Vayas, Ioannis, Series Editor, Kumar Shukla, Sanjay, Series Editor, Sharma, Anuj, Series Editor, Kumar, Nagesh, Series Editor, Wang, Chien Ming, Series Editor, Cui, Zhen-Dong, Series Editor, Sreekeshava, K. S., editor, Kolathayar, Sreevalsa, editor, and Vinod Chandra Menon, N., editor

Published
2024
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44. Predicting Credit Risk for Unsecured Lending: A Machine Learning Approach

Author

Naik, K. S.

Subjects
Quantitative Finance - Risk Management, Computer Science - Machine Learning, Quantitative Finance - Statistical Finance
Abstract

Since the 1990s, there have been significant advances in the technology space and the e-Commerce area, leading to an exponential increase in demand for cashless payment solutions. This has led to increased demand for credit cards, bringing along with it the possibility of higher credit defaults and hence higher delinquency rates, over a period of time. The purpose of this research paper is to build a contemporary credit scoring model to forecast credit defaults for unsecured lending (credit cards), by employing machine learning techniques. As much of the customer payments data available to lenders, for forecasting Credit defaults, is imbalanced (skewed), on account of a limited subset of default instances, this poses a challenge for predictive modelling. In this research, this challenge is addressed by deploying Synthetic Minority Oversampling Technique (SMOTE), a proven technique to iron out such imbalances, from a given dataset. On running the research dataset through seven different machine learning models, the results indicate that the Light Gradient Boosting Machine (LGBM) Classifier model outperforms the other six classification techniques. Thus, our research indicates that the LGBM classifier model is better equipped to deliver higher learning speeds, better efficiencies and manage larger data volumes. We expect that deployment of this model will enable better and timely prediction of credit defaults for decision-makers in commercial lending institutions and banks., Comment: 9 pages, 4 figures, 3 tables

Published
2021

47. Direct-acting antiviral therapies for hepatitis C infection: global registration, reimbursement, and restrictions

Author

Sargsyants, N., Suleymanova, L., Salkic, N., Simonova, M., Nemeth-Blazic, T., Mravcik, V., Kivimets, K., Salupere, R., Butsashvili, M., Soselia, G., Makara, M., Tolmane, I., Jancorienė, L., Stratulat, S., Flisiak, R., Gheorghe, L., Cernat, R., Lakhov, A., Stanevich, O., Jarcuska, P., Peck-Radosavljevic, M., Robaeys, G., Øvrehus, A., Foster, G., Sutinen, J., Farkkila, M., Rautiainen, H., Vuoti, S., Nikolova, D., Pawlotsky, J.M., Rockstroh, J., Sypsa, V., Papatheodoridis, G., Olafsson, S., Feeney, E., Teti, E., Seguin-Devaux, C., Pocock, J., Reiff, S., McDougall, N., Van der Valk, M., Dalgard, O., Tato Marinho, R., Dillon, J., Peters, E., Bojovic, K., Matičič, M., Kåberg, M., Bruggmann, P., Healy, B., Chong, V.H., Yi, S., Tucker, J., Pasaribu, L.R., Tanaka, J., Ashley, E.A., Abu Hassan, M.R., Mohammed, N.S., Chan, H.K., Gidaagaya, S., Kyi, K.P., Hyung Joon, K., Chin, B., Baladjay, P.C., Kao, J.H., Wansom, T., da Cruz, B., Flower, B., Ehsan, E., Al Mahtab, M., Khandu, L., Bhadoria, A.S., Alavi, M., KC, P., Hamid, S., Biryukov, S., Alymbaeva, D., Alaei, A., Bakieva, S., Flichman, D., Carmo, R.F., Valdez, E., Cortes, C.P., Contreras, F., Teran, E., Velez-Moller, P., Jagnarine, T., Mills, M., Goodman-Meza, D., Sánchez, J., Montenegro-Idrogo, J.J., Lugo Canales, A.M., Davy, J., Alexander, A., Gerona, S., Perazzo, R., Balak, D., Kelly-Hanku, A., Fineanganofo, A., Gane, E., Raymond, N., Debzi, N., Sridharan, K., Waked, I., Turner, D., Shibolet, O., Al Muzaini, A., El Nakib, M., Sheriff, D.S., Brahni, T., Essayagh, T., Essayagh, S., Hjaija, D., Al-Naamani, K., Sanai, F.M., Pasquale, H., Bedri, S., Chakroun, M., Ghrabi, A., Akarca, U.S., Falcao, V., Edmond Gbedo, S., Ouoba, S., Nyabenda, F., Rocher Mbella, M., Mahamat Moussa, A., Youssouf, T., Boniface, Y., Akilimali Shindano, T., Hamida, M.E., Mongo, A., Mapapa, C., Desalegn, H., Embinga, E.L.A., Ndow, G., Nartey, Y., Cisse, M., Djalo, M.A., Mugambi, M., Nyakowa, M., Jeuronlon, M.K., Ngoma, J., Manitrala Ramanampamonjy, R., Naik, K., Soyjaudah, M.D., Filipe, E., Nnakelu, E., Serumondo, J., Mbodj, M., Patino, M., Aalto, M.K., Waweru, P., Dagnra, A., Ocama, P., Maghimbi, A., Hamooya, B.M., Katsidzira, L., Rios, C., Thormann, M., Al Marzooqi, N., Al Rand, H.M., Francois, K., Hamoudi, W., Alkharty, M., Skripo, O., Uka, T., Marshall, Alison D, Willing, Alex R, Kairouz, Abe, Cunningham, Evan B, Wheeler, Alice, O’Brien, Nicholas, Perera, Vidura, Ward, John W, Hiebert, Lindsey, Degenhardt, Louisa, Hajarizadeh, Behzad, Colledge, Samantha, Hickman, Matthew, Jawad, Danielle, Lazarus, Jeffrey V, Matthews, Gail V, Scheibe, Andrew, Vickerman, Peter, Dore, Gregory J, and Grebely, Jason

Published
2024
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