Psidium guajava L. is widely used like food and in folk medicine all around the world. Many studies have demonstrated that guava leaves have anti-hyperglycaemic and anti-hyperlipidemic activities, among others. The biological activity of guava leaves belongs mainly to phenolic compounds. Andalusia is one of the regions in Europe where guava is grown, thus, the aim of this work was to study the phenolic compounds present in Andalusian guava leaves at different oxidation state (low, medium and high). The phenolic compounds in guava leaves were determined by HPLC-DAD-ESI-qTOF-MS. We identified seventy-to phenolic compounds and, to our knowledge, twelve of them were determined for the first time in guava leaves in negative ionization mode. Moreover, positive ionization mode allowed the identification of the cyanidin-glucoside. To our knowledge this compound has been identified for the first time in guava leaves.

The results obtained by chromatographic analysis reported that guava leaves with low degree of oxidation have a higher content gallic and ellagic derivatives and flavonols compared to the other two guava leaf samples. Contrary, high oxidation state guava leaves reported the highest content of cyanidin-glucoside that was 2.6 and 15 times higher than guava leaves with medium and low oxidation state, respectively.

The qTOF platform permitted the determination of several phenolic compounds and provided new information about guava leaf phenolic composition that could be useful for nutraceutical production.

Lithium ion batteries (LIBs) have attracted extensive attention in various fields such us portable electronic devices or electric/hybrid electric vehicles owing to its high energy density, long cycle life, rapid charge capability, and no memory effect. For commercial LIBs, the positive electrode material is typically a metal oxide or phosphate while graphite is the most widely used anode material. However, to develop higher energy density systems new materials are required. In this sense, nanoparticulate and hybrid composites based on carbon coated metal oxides attract promising interest as high-performance electrode materials for next generation lithium-ion batteries (LIBs). In this study, nanoparticulate g-Fe₂O₃/C composites with different carbon proportion have been prepared by a freeze-drying synthesis procedure. The characterization has been performed by elemental analysis, X-ray powder diffraction (XRD), transmission electron microscopy (TEM), electron paramagnetic resonance (EPR), magnetic susceptibility measurements and Mossbauer spectroscopy. Morphological studies revealed that nanoparticles of g-Fe₂O₃ in the composites are well-dispersed in the matrix of amorphous carbon. The magnetic and spectroscopic measurements corroborated that described composition and morphology. The electrochemical study showed that composites with carbon have promising electrochemical performances. These samples yielded specific discharge capacities of 1200 mAh/g after operating for 100 cycles at 1C. These excellent results could be explained by the homogeneity of particle size and structure as well as the uniform distribution of g-Fe₂O₃ nanoparticles in the in situ generated amorphous carbon matrix.

In connection with synthetic applications, we have foreseen to study the reactivity of the poorly reactive tert-butyl acrylate electrophile with chiral imines of unsymmetrical ketones, using conventional or microwave flash heating under carefully controlled reaction conditions in order to develop a very quick and efficient access to the corresponding Michael adducts in which a created stereogenic quaternary carbon center was fully stereocontrolled. Depending on the conditions, either a keto ester or a lactam were obtained. A good correlation was obtained between experiment and theoretical calculations. . The stereoselectivity of the process (e>95%)  was determined using natural abundance ¹³C-{¹H} NMR in a chiral polypeptide liquid crystal.

Neuroimaging data from magnetic resonance techniques are widely used as non-invasive biomarkers for the evaluation and early diagnosis of Alzheimer’s Disease (AD). Alzheimer Prediction by Spectroscopy Voxel Volume is a free Web tool to predict the AD diagnosis (AlzPred-SVV: http://bio-aims.udc.es/AlzPredSVV.php). The inputs are two variables related to a voxel acquired in the left hippocampus: The total volume and the volume of CSF contained in the voxel. The classification method is based on Machine Learning techniques. The tool is based on an HTML/PHP user interface with a Python/Java implementation of the model.

Synthesis and characterization of Carbon nanotube/Hydroxyapatite/Clay based Hybrid antimicrobial biomaterial for potential tissue engineering application

Subrata Kar^a,b, Papiya Nandy^b, Ruma Basu^b,c and Sukhen Das^*a,b,d

^aPhysics Department, Jadavpur University, Kolkata-700 032, India.

^bCentre for Interdisciplinary Research and Education, Kolkata 700 068, India

^cPhysics Department, Jogamaya Devi College, Kolkata 700 026

^dIndian Institute of Engineering, Science and Technology, Howrah, India

*Corresponding author

Inorganic ceramic materials have recently been enjoying a great deal of attention for uses as biomaterial over the traditionally used polymeric material. The ability of silica based ceramics to release Si-containing ionic products makes them osteoconductive and their special surface composition has drawn considerable attention for its use as osteogenic proliferation, differentiation and gene expression of tissue cells. Here Pristine Multiwalled carbon nanotube (MWCNT) was functionalized by acid oxidation and used as template for nucleation of hydroxyapatite crystal. The CNT-HAP thus formed was further reinforced with exfoliated Montmoriollite(MMT) clay to increase the mechanical property of the nanocomposite. The synthesized composite viz CNT-HAP (HC) and CNT(HAP)-MMT(CHC) were characterized by fourier transform infrared spectroscopy(FTIR), X-ray diffraction(XRD), Scanning electron microscopy and transmission electron microscopy(TEM) and thermogravimetric analysis(TGA) . The biomedical application of CHC, blood compatibility was studied in terms of hemolysis assay and platelet adhesion assay. Finally, in vitro dissolution assay and the antibacterial activity of the material were further explored for establishing its use as an antibacterial biomaterial. The nanocomposite thus designed exhibited a promising candidate as an antimicrobial biomaterial for tissue Engineering application.

Cheminformatics and bioinformatics are extensively using predictive modelling and exhibit a need for standardization of methodologies such as data splitting, cross-validation methods, best model criteria and Y-randomization. RRegrs is a new R package, available at https://www.github.com/enanomapper/RRegrs (0.05 release), which suggests an integrated framework to assist model selection and speed up the process of predictive model development. The tool proposes a fully validated scheme by employing repeated 10-fold and leave-one-out cross-validation for ten linear and non-linear regression methods. Standardized reports are produced to compare the output of modelling algorithms and assess cross-validation results for selected models. Here, we demonstrate RRegrs capabilities in terms of performance using five well-established data sets.

Experimental analysis starts with very similar premises: given a specific problem, we need to either collect or generate a dataset and to choose the best model according to the performance. A set of techniques can be evaluated (i.e. statistical or metaheuristic approaches) as well as results from previous works that should be taken into account. Thus, it is necessary to analyse the behaviour of a method with respect to the others in equality of conditions. Therefore it is necessary to formalize an experimental design to solve as effectively as possible the problem with different approaches and to estimate the error rate; so different results from different methods can be compared. In this work we propose four phases for any experimental design: extraction of data, pre-processing of data, learning and selection of the best model. These generic phases encapsulate the main operations and steps that should be performed during an experimental analysis (some of them mandatory and other optional), independently of the kind of data or method used and are not mandatory and can be adapted to a new specific domain. The proposed experimental design has proven to be a vital contribution to compare different techniques under the same conditions in different scopes.

It is known that individual amino acids can have a decisive role in the stabilization of a protein structure. Moreover, it is likely that specific amino acid combinations also fulfil structural and stabilizing roles in protein structure. We present Prot-SSP, an analytical Python tool designed to gather and parse sequence and structural data from sets of PDB files and determine amino acid residue pairing propensities and correlations in alpha helices and beta strands, in various secondary structure contexts. This versatile and user-friendly bioinformatic tool has proven useful for the analysis of a selected set of protein structures as shown in an illustrative example.

TI2BioP (Topological Indices to BioPolymers) is a software to estimate topological indices (TIs) from two-dimensional (2D) graphical approaches for the natural biopolymers DNA, RNA and proteins The methodology mainly turns long biopolymeric sequences into 2D artificial graphs such as Cartesian and four-color maps but also reads other 2D graphs from the thermodynamic folding of DNA/RNA strings inferred from other programs. The topology of such 2D graphs is either encoded by node or adjacency matrixes for the calculation of the spectral moments as TIs. These numerical indices were used to build up alignment-free models to the functional classification of biosequences and to calculate alignment-free distances for phylogenetic purposes. We released the version 2.0 of the software that can be freely downloaded from http://ti2biop.sourceforge.net/.

The antibacterial activity of bisacodyl, a drug used in therapeutic as laxative, and its ferrocenyl analogues was investigated against Gram-positive and Gram-negative foodborne pathogens including Listeria monocytogenes, Escherichia coli, Enterococcus faecalis, Salmonella enterica, Micrococcus luteus and Staphylococcus aureus. The results showed that most of these compounds exhibit an excellent antimicrobial activity, and the bisacodyl analogues seemed to be more bactericides than bacteriostatic.