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| 1 | In vitro cytotoxicity and antimicrobial activity of Talaromyces flavus SP5 inhabited in the marine sediment of Southern Coast of India显示文摘Marine sediment samples were collected from the coastal areas of Southern India, particularly in Kanyakumari District. Twenty-eight different fungal strains were isolated. The screening of fungi from marine sediment was done to isolate a potent fungus that can produce bioactive compounds for biomedical applications. Only three strains viz Trichoderma gamsii SP4, Talaromyces flavus SP5 and Aspergillus oryzae SP6 were screened for further studies. The intracellular bioactive compounds were extracted using solvent extraction method. The crude extracts were tested for its anti-microbial and anti-cancer properties and analytically characterized using Gas Chromatography Mass Spectrometry(GC-MS). All the three extracts were active, but the extract from T. flavus SP5 was found to be more active against various human pathogens, viz., Pseudomonas aeruginosa ATCC 27853(17.8 ± 0.1), Escherichia coli ATCC 52922(18.3 ± 0.3), and Candida tropicalis ATCC 750(17.7 ± 0.4). It also exhibited cytotoxic activity against HEp2 carcinoma cell line with the LC_(50) value of 25.7 μg·mL^(-1). The GC-MS data revealed the presence of effective bioactive compounds. These results revealed that the extract from isolated fungus T. flavus SP5 acted as a potent antimicrobial, antifungal, and anticancer agent, providing basic information on the potency of marine fungi towards biomedical applications; further investigation may lead to the development of novel anticancer drugs. | Bibin G.Anand C.K.Navin Thomas S.Prakash | 2016 | Chinese Journal of Natural Medicines2016，14，12： | 4 |
| 2 | Equivariant analytical mapping of first principles Hamiltonians to accurate and transferable materials models显示文摘We propose a scheme to construct predictive models for Hamiltonian matrices in atomic orbital representation from ab initio data as a function of atomic and bond environments.The scheme goes beyond conventional tight binding descriptions as it represents the ab initio model to full order,rather than in two-centre or three-centre approximations.We achieve this by introducing an extension to the atomic cluster expansion(ACE)descriptor that represents Hamiltonian matrix blocks that transform equivariantly with respect to the full rotation group.The approach produces analytical linear models for the Hamiltonian and overlap matrices.Through an application to aluminium,we demonstrate that it is possible to train models from a handful of structures computed with density functional theory,and apply them to produce accurate predictions for the electronic structure.The model generalises well and is able to predict defects accurately from only bulk training data. | Liwei Zhang Berk Onat Geneviève Dusson Adam McSloy G.Anand Reinhard J.Maurer Christoph Ortner James R.Kermode | 2022 | npj Computational Materials2022，，1： | 2 |
| 3 | Deep learning network with Euclidean similarity factor for Brain MR Tumor segmentation and volume estimation显示文摘The major goal of this paper is to isolate tumor region from nontumor regions and the estimation of tumor volume.Accurate segmentation is not an easy task due to the varying size,shape and location of the tumor.After segmentation,volume estimation is necessary in order to accurately estimate the tumor volume.By exactly estimating the volume of abnormal tissue,physicians can do excellent prognosis,clinical planning and dosage estimation.This paper describes a new Euclidean Similarity factor(ESF)based active contour model with deep learning for segmenting the tumor region into complete,core and enhanced tumor portions.Initially,the ESF considers the spatial distances and intensity differences of the region automatically to detect the tumor region.It preserves the image details but removes the noisy details.Then,the 3D Convolutional Neural Network(3D CNN)segments the tumor by automatically extracting spatiotemporal features.Finally,the extended shoelace method estimates the volume of the tumor accurately for n-sided polygons.The simulation result achieves a high accuracy of 92%and Jaccard index of 0.912 and computes the tumor volume with effective performance than existing approaches. | G.Anand Kumar P.V.Sridevi | 2019 | International Journal of Modeling, Simulation, and Scientific Computing2019，10，6： | 0 |
| 4 | Mimosine functionalized gold nanoparticles (Mimo-AuNPs) suppress β-amyloid aggregation and neuronal toxicity显示文摘Evidence suggests that increased level/aggregation of beta-amyloid(Aβ)peptides initiate neurodegeneration and subsequent development of Alzheimer’s disease(AD).At present,there is no effective treatment for AD.In this study,we reported the effects of gold nanoparticles surface-functionalized with a plant-based amino acid mimosine(Mimo-AuNPs),which is found to cross the blood-brain barrier,on the Aβfibrillization process and toxicity.Thioflavin T kinetic assays,fluorescence imaging and electron microscopy data showed that Mimo-AuNPs were able to suppress the spontaneous and seed-induced A_(1-42) aggregation.Spectroscopic studies,molecular docking and biochemical analyses further revealed that Mimo-AuNPs stabilize A_(1-42) to remain in its monomeric state by interacting with the hydrophobic domain of A_(1-42)(i.e.,Lys16 to Ala21)there by preventing a conformational shift towards theβ-sheet structure.Additionally,Mimo-AuNPs were found to trigger the disassembly of matured A_(1-42) fibers and increased neuronal viability by reducing phosphorylation of tau protein and the production of oxyradicals.Collectively,these results reveal that the surface-functionalization of gold nanoparticles with mimosine can attenuate Aβfibrillization and neuronal toxicity.Thus,we propose Mimo-AuNPs may be used as a potential treatment strategy towards AD-related pathologies. | Bibin G.Anand Qi Wu Govindarajan Karthivashan Kiran P.Shejale Sara Amidian Holger Wille Satyabrata Kar | 2021 | Bioactive Materials2021，6，12： | 0 |
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