Bharathiar University

About: Bharathiar University is a education organization based out in Coimbatore, Tamil Nadu, India. It is known for research contribution in the topics: Thin film & Adsorption. The organization has 5812 authors who have published 8628 publications receiving 143934 citations. The organization is also known as: BU.

Enzymatic electrochemical glucose biosensors by mesoporous 1D hydroxyapatite-on-2D reduced graphene oxide

Abstract: A novel hydrothermal process was used for the preparation of hydroxyapatite (HAp) nanorods on two-dimensional reduced graphene oxides (RGO). The hydrothermal reaction temperature improves the crystallinity of HAp and partially reduces graphene oxide (GO) to RGO. The crystalline structure, chemical composition and morphology of the prepared nanocomposites were characterized by using various analytical techniques. Nanorods of HAp with a diameter and length of ∼32 and 60–85 nm were grown on basal planes and edges of the layered RGO sheets. The estimated specific surface area and pore-size distribution are 120 m2 g−1 and 5.6 nm, respectively. We also report the direct electrochemistry of glucose oxidase (GOx) on 1D HAp-on-2D RGO nanocomposite-modified glassy carbon electrode (GCE) for glucose sensing. The electrocatalytic and electroanalytical applications of the proposed RGO/HAp/GOx-modified GCE were studied by cyclic voltammetry (CV) and amperometry. The increased electron rate constant of 3.50 s−1 was obtained for the modified GCE. The reported biosensor exhibits a superior detection limit and higher sensitivity ca. 0.03 mM and 16.9 μA mM−1 cm−2, respectively, with a wide linear range of 0.1–11.5 mM. The tremendous analytical parameters of the reported sensor surpass those of related modified electrodes and are promising for practical industrial applications.

Malaria Parasite Detection From Peripheral Blood Smear Images Using Deep Belief Networks

Abstract: In this paper, we propose a novel method to identify the presence of malaria parasites in human peripheral blood smear images using a deep belief network (DBN). This paper introduces a trained model based on a DBN to classify 4100 peripheral blood smear images into the parasite or non-parasite class. The proposed DBN is pre-trained by stacking restricted Boltzmann machines using the contrastive divergence method for pre-training. To train the DBN, we extract features from the images and initialize the visible variables of the DBN. A concatenated feature of color and texture is used as a feature vector in this paper. Finally, the DBN is discriminatively fine-tuned using a backpropagation algorithm that computes the probability of class labels. The optimum size of the DBN architecture used in this paper is 484-600-600-600-600-2, in which the visible layer has 484 nodes and the output layer has two nodes with four hidden layers containing 600 hidden nodes in every layer. The proposed method has performed significantly better than the other state-of-the-art methods with an F-score of 89.66%, a sensitivity of 97.60%, and specificity of 95.92%. This paper is the first application of a DBN for malaria parasite detection in human peripheral blood smear images.

Antifungal Activity of Chitosan Nanoparticles Encapsulated With Cymbopogon martinii Essential Oil on Plant Pathogenic Fungi Fusarium graminearum

Abstract: Application of synthetic fungicides in agricultural commodities has been restricted due to development of fungicide resistance fungi and deleterious impact on environment and health of farm animals and humans. Hence, there is an urge for development of mycobiocides, and the present study was undertaken to determine the antifungal activity of Cymbopogon martinii essential oil (CMEO) on post-harvest pathogen Fusarium graminearum. The CMEO was extracted by hydrodistillation and GC-MS chemical profile revealed the presence of 46 compounds and abundant was geraniol (19.06%). The minimum inhibitory concentration and minimum fungicidal concentration of CMEO were determined as 421.7 ± 27.14 and 618.3 ± 79.35 ppm, respectively. The scanning electron microscopic observation of CMEO exposed macroconidia was exhibited a detrimental morphology with vesicles, craters, protuberance, and rough surfaces related to control fungi. The CMEO induced the death of fungi through elevating intracellular reactive oxygen species and lipid peroxidation, and depleting ergosterol content. Regrettably, essential oils are highly volatile and become unstable and lose their biological features on exposure to light, heat, pH, moisture, and oxygen. To overcome these issues, chitosan encapsulated CMEO nanoparticles (Ce-CMEO-NPs) were prepared. The synthesized Ce-CMEO-NPs have spherical morphology with Zeta potential of 39.3-37.2 mV and their corresponding size was found in range of 455-480 nm. The Fourier transform infrared analysis confirmed that bio-active constituents of CMEO were well stabilized due to chitosan conjugation and successfully formed Ce-CMEO-NPs. The in vitro release assay observed that the release of CMEO is stabilized due to the complex formation with chitosan and thereby, increases the lifetime antifungal activity of CMEO by gradual release of antifungal constituents of Ce-CMEO-NPs. In conclusion, antifungal and antimycotoxin activities of CMEO and Ce-CMEO-NPs against F. graminearum were assessed in maize grains under laboratory conditions over a storage period of 28 days. Interestingly, Ce-CMEO-NPs were presented efficient and enhanced antifungal and antimycotoxin activities related to CMEO, and it could be due to perseverance of antifungal activity by controlled release of antifungal constituents from Ce-CMEO-NPs. The study concluded that Ce-CMEO-NPs could be highly appropriate as mycobiocides in safeguarding the agricultural commodities during storage period in agricultural and food industries.