A Novel Isoform of the Hepatic Antimicrobial Peptide, Hepcidin (Hepc-CB1), from a Deep-Sea Fish, the Spinyjaw Greeneye Chlorophthalmus bicornis (Norman, 1939): Molecular Characterisation and Phylogeny

Hepcidin is cysteine-rich short peptide of innate immune system of fishes, equipped to perform prevention and proliferation of invading pathogens like bacteria and viruses by limiting iron availability and activating intracellular cascades. Hepcidins are diverse in teleost fishes, due to the varied aquatic environments including exposure to pathogens, oxygenation and iron concentration. In the present study, we report a 87-amino acid (aa) preprohepcidin (Hepc-CB1) with a signal peptide of 24 aa, a prodomain of 39 aa and a bioactive mature peptide of 24 aa from the gill mRNA transcripts of the deep-sea fish spinyjaw greeneye, Chlorophthalmus bicornis. Molecular characterisation and phylogenetic analysis categorised the peptide to HAMP2-like group with a mature peptide of 2.53 kDa; a net positive charge (?3) and capacity to form b-hairpin-like structure configured by 8 conserved cysteines. The present work provides new insight into the mass gene duplication events and adaptive evolution of hepcidin isoforms with respect to environmental influences and positive Darwinian selection. This work reports a novel hepcidin isoform under the group HAMP2 from a nonacanthopterygian deep-sea fish, C. bicornis

Learning disability prediction tool using ANN and ANFIS

Learning Disability (LD) is a neurological condition that affects a child’s brain and impairs his ability to carry out one or many specific tasks. LD affects about 15 % of children enrolled in schools. The prediction of LD is a vital and intricate job. The aim of this paper is to design an effective and powerful tool, using the two intelligent methods viz., Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System, for measuring the percentage of LD that affected in school-age children. In this study, we are proposing some soft computing methods in data preprocessing for improving the accuracy of the tool as well as the classifier. The data preprocessing is performed through Principal Component Analysis for attribute reduction and closest fit algorithm is used for imputing missing values. The main idea in developing the LD prediction tool is not only to predict the LD present in children but also to measure its percentage along with its class like low or minor or major. The system is implemented in Mathworks Software MatLab 7.10. The results obtained from this study have illustrated that the designed prediction system or tool is capable of measuring the LD effectively

Array pattern nulling by element position perturbations using a genetic algorithm

A genetic algorithm has been used for null steering in phased and adaptive arrays . It has been shown that it is possible to steer the array null s precisely to the required interference directions and to achieve any prescribed null depths . A comparison with the results obtained from the analytic solution shows the advantages of using the genetic algorithm for null steering in linear array patterns