A New Synthetic Peptide with In vitro Antibacterial Potential Against Escherichia coli O157:H7 and Methicillin-Resistant Staphylococcus aureus (MRSA).

In this work, we performed the rational design of a cationic antimicrobial peptide, GIBIMPY4, using the software DEPRAMPs developed at the GIBIM research group. GIBIMPY4 has a length of 17 amino acids, it is amphipathic, its structure is α-helix and it has a net charge of (+5). Solid-phase peptide synthesis was performed using the Fmoc strategy in acid medium. The primary structure was confirmed by MALDI-TOF mass spectrometry. The antimicrobial activity of the peptide was evaluated by broth microdilution method by measuring optical density in 96-well microplates. The minimal inhibitory concentration of GIBIMPY4 to kill 50 % of the bacterial cells (MIC50) was 6.20 ± 0.02 µM for MRSA and 4.55 ± 0.02 µM for E. coli O157:H7, while also reporting a bacteriostatic effect for the later. GIBIMPY4 activity was sensitive to salt concentration in E. coli but insignificant effect in its activity against MRSA. The peptide seems to be a broad-spectrum antimicrobial agent based on the results against Gram-positive and Gram-negative bacteria and was specific for bacterial cells E. coli O157:H7 with index of specificity equal to 9.01 in vitro assays.

Construction of a predictive model for concentration of nickel and vanadium in vacuum residues of crude oils using artificial neural networks and LIBS.

A predictive model to determine the concentration of nickel and vanadium in vacuum residues of Colombian crude oils using laser-induced breakdown spectroscopy (LIBS) and artificial neural networks (ANNs) with nodes distributed in multiple layers (multilayer perceptron) is presented. ANN inputs are intensity values in the vicinity of the emission lines 300.248, 301.200 and 305.081 nm of the Ni(I), and 309.310, 310.229, and 311.070 nm of the V(II). The effects of varying number of nodes and the initial weights and biases in the ANNs were systematically explored. Average relative error of calibration/prediction (REC/REP) and average relative standard deviation (RSD) metrics were used to evaluate the performance of the ANN in the prediction of concentrations of two elements studied here.