Objective: to analyze the predictive value of affective symptomatology in a first psychotic episode sample followed up during three and five years, regarding to hospitalization, relapses, suicidal behaviour, working level, social activity and global functioning.

Method: 112 inpatients with a first psychotic episode were included in a longitudinal-prospective study followed up during three (N=91) and five-year (N=82). Assessments included the YMRS and HRDS-21, the GAF, the Strauss-Carpenter prognostic scale, the PANSS and the Phillips pre-morbid adjustment scale. We used descriptive and logistic analysis to determine the predictive factors associated to the number of relapses, hospitalizations and suicide attempts; depressive, manic, activation and dysphoric dimensions as covariables.

Results: 91.46% of relapses and 21% of suicide attempts at fifth year. The GAF discriminated among prognostic groups from the third year (p 0.020), with the poorest prognosis in the schizophrenia group, while bipolar disorders and the rest of the diagnoses achieved an intermediate prognosis. The Strauss-Carpenter scale, specifically working, social activity and global functioning items, discriminated among three diagnostic groups and between affective and non-affective psychosis (p<0.05); while schizophrenia scored the poorest outcome, bipolar disorder scored the highest. Depressive dimension was significantly associated with a lower number of relapses and hospitalizations (p= 0.045 and p= 0.012) and manic dimension with more relapses (p= 0.023).

Conclusion: The depressive dimension presents the best prognosis. On the contrary, the activation dimension, in general, gives a more favourable prognosis with regards to functionality (social) and unfavourable with respect to relapses. Finally, the manic dimension is associated with a worse evolution regarding relapses. Only the dysphoric dimension is not associated with syndromic and/or functional prognosis.

In the crisis of fast diminishing fossil fuels, looking for alternative energy sources by utilizing solar energy has the highest research priority and engineered nanoparticles play a very important role here.

Using a specially designed photoelectrochemical cell and  a mixture of  two dyes, Phenosaffranine (PSF) and Azure C (AZC) conjugated with oxidized multi-walled carbon nanotubes (OMWCNTs) we have been able to generate photovoltage  of  reasonably high magnitude (763 mV). The storage time is also quite high ~ 66 hrs. The photovoltage cycle was reproducible upon further illumination. Energy conversion efficiency (η%) of the cell has been calculated for the system (η% = 4.33).

Spectral studies show that with addition of OMWCNTs to a fixed concentration of PSF and  AZC solution, the absorbance increases throughout the spectral range. FTIR spectrum reveals that there is no chemical change in the mixed system indicating that only the dyes got adsorbed on the side walls on the OMWCNTs. From fluorescence spectral study, it has been seen that while fluorescence intensity of PSF quenches with addition of  AZC, which does not have any fluorescence of its own, the  intensity regains with addition of  OMWCNTs. This emphasizes the role of oxidized multi-walled carbon nanotubes in the performance of photoelectrochemical cell of mixed dye system.

Use of Azo dyes, having one or more azo bond (-N=N-), are more than 70% among all textile dyes used. The stability and the xenobiotic nature of reactive of these azo dyes make them recalcitrant and hence they are not totally degraded by conventional wastewater treatment processes that involve physical, chemicals or activated sludge methods.  The dyes are therefore released into the environment, in the form of colored waste water.  Color of the waste effluent is an important parameter for a long time. So the main criteria of removing the waste and degrade is to first remove the color of the effluent.  Some common techniques which are used for degrading the chemically complex dye have several harmful side effects and they   are not very cost effective and some require long retention time.  So extensive research is going on to find a simple method which should obviously be a low cost process, will need less time to complete the process and will have minimum harmful side effects.

Cobalt Alumino Silicate Ceramic (CASC) composites, with different molar weight concentration (i.e. G₀=0, G₁=0.4, G₂=0.6, G₃=0.8, G₄=1.0, and G₅=1.2 (M.W.)) of cobaltus acetate are prepared via sol-gel route. XRD shows mullite and cobalt aluminate phase which is found to depend on the concentrations of Co⁺² ions. Field emission scanning electron microscope (FESEM) images show for all samples of CASC nanocomposites after sintering at 1400^oC, nano sized cobalt aluminate grains are embedded in evenly spread mullite grains; but in case of G₀, there are only evenly spread mullite grains. The study of dielectric property of the composite samples at room temperature shows that at all concentration (G_1, G₂, G₃, G₄ and G₅) the dielectric constant is higher than pure mullite (G₀) and there is a critical concentration of cobaltus acetate (G₃) where there is maximum enhancement of dielectric constant in the higher frequency range from 40 KHz to 2 MHz. The dielectric constant varies from 44.77 to 37.75 for G₃ and from 29.8 to 24.12 for G₀ respectively. The tangent loss of composite with G₃ has the lowest value than that of other concentrations including pure mullite in the frequency range 40 KHz to 2MHz. Due to high dielectric constant and low tangent loss, the composite with specific concentration and in the high frequency range has great importance as an electronic material.

In Bioinformatics, review of the state of the art about computational tools, including the interpretation of generated outputs and the restrictions of each software, contributes for choosing the best application to a specific problem. This way, an important research topic is the study of the impact of mutations in the treatment of complex diseases. The mutations play a major role in the cells for presenting advantages and disadvantages by the fact that its can affect protein stability. Actually, researchers need accurate computational tools for prediction of how single point amino acid mutations affect the stability of a protein structure. For the analysis of single mutation points effects the tools generally use machine learning techniques. Recent works show significant advances in predicting stability upon point mutation. This paper presents an evaluation of computational tools for thermodynamics and structural analysis of protein stability upon point mutation prediction. We choose to evaluate for thermodynamic analysis the software CUPSAT (Cologne University Protein Stability Analysis Tool) and mCSM (mutation Cutoff Scanning Matrix), and for structural analysis the software FoldX and Modeller. It was chosen these software since, according to literature, they are commonly used in these kind of analyzes. In our proposed evaluation we verify the software outputs and verify the proximity to experimental results. As a case study we selected a set of 50 proteins extracted from: (i) MutaProt, which analyses pairs of PDB files whose members differ in one, or two, amino acids; (ii) ProTherm, database that contain experimentally determined thermodynamic parameters of protein stability. Each mutation in the datasets has attributes, as: PDB code, mutation, solvent accessibility, pH value, temperature and energy change (ddG). A stability prediction model was successfully created, and the majority of the point mutations were predicted successfully having a high correlation and low standard error.

Influenza virus is well recognized for high level of mutations that lead to development of new strains and subtypes, primarily through genetic shifts and drifts. Another mechanism of genetic change is through recombination, often observed in mammalian genes but controversial in viral genomes, which involves exchanges of short nucleotide sequences between two strains that coinfect the same cell. While evidence of such recombinations is rare to disputed in influenza genomes, we have observed that well-defined segments of influenza genes such as the hemagglutinin and neuraminidase have shown identical sequences between various strains that is best explained by segment exchange. Thus we had in our earlier study of the spread and proliferation of H5N1 bird flu observed that the neuraminidase with three segments – the transmembrane, stalk and body – shows evidence of exchange of one or other segments between different strains. Extending our work to the hemagglutinin of various subtypes, we noticed the same phenomena: Hemagglutinin has two segments, HA1 and HA2, where we found several instances where the segments seem to have been exchanged. Our analyses was based on RNA descriptors calculated in a 2D graphical representation scheme which have been proved to easily identify identical sequences. In this paper we discuss some of the details of this phenomenon in influenza genes which could be important in monitoring development of new highly pathogenic strains

Biosynthesis of estrogens from androgens is catalyzed by cytochrome P450 aromatase. Target enzymes of triazoles in steroidogenesis are the sterol 14-alfa-demethylase (encoded by the CYP51 gene) and the aromatase (encoded by the CYP19 gene). Aromatase inhibition by the triazole compounds Letrozole (LTZ) and Anastrozole is a prevalent therapy for estrogen-dependent postmenopausal breast cancer. Triazole containing compounds as systemic fungicides are widely used in agriculture due to its high efficiency, broad spectrum, low toxicity and long effectiveness. They target 14α-demethylase, but some were previously shown to inhibit aromatase, thereby raising the possibility of endocrine disruptive effects. However, mechanistic analysis of their inhibition has never been undertaken. In this study inhibitory effect of triazole fungicides were evaluated on the human aromatase enzyme and compared with the Letrozole (LTZ), the most potent inhibitor of aromatase, which is used as anti-estrogen for breast cancer treatment. For this study was used software AUTODOCK to calculate inhibition energy (IE) of triazoles on aromatase enzyme CYP19A1. As triazole moieties are widely used in fungicides, some studies reported that agricultural triazole pesticides are culprits for the development of resistance to other triazole containing drugs. To avoid the risk of possible development of resistance to other triazole drugs and to reduce toxicity of aromatase inhibitors in the treatment of breast cancer, there are used different methods in order to find out new preventive strategies. Hypothesis of this study is that common agricultural triazole fungicides may express inhibitory effect on human aromatase enzyme Cyp19A1, in this way contributing to drug resistance and increased risk of cumulative toxicity of anti-estrogen medications. In our study we performed virtual screening of 15 fungicides and AI reference drug Letrozole to measure inhibitory effect on human aromatase. In this way we aim to range which pesticides are most potent inhibitors of Cyp19A1 enzyme to predict and prevent possible summative cumulating effect of fungicide undesirably overlapping with the activity of anticancer drugs. In our docking study we used together the X-ray structure of human cytochrome P450 aromatase Cyp19A1 (PDB code 3S79, resolution 2.75 Å) associated with the metabolism of estrogens and carcinogens with breast cancer, with a collection of commercially available compounds, particularly, 15 triazole fungicides and anticancer drug Letrozole as reference standard. The binding affinity was evaluated by the binding energies, docking energy, inhibition constant, intermolecular energy, and RMSD values. It was demonstrated that the docking protocol could reliably reproduce the interaction of aromatase with its substrate with an RMSD of 0 Å. We found that four triazole fungicides compounds: Triticonazole, Tebuconazole, Metconazole and Fluquinconazole, exhibited minimal inhibition constant (IC). These compounds with minimal binding energy are safer in terms of toxicity and resistance of other prescription drugs like non-steroid AIs like Letrosole.

Abstract: Post-genomic molecular biology embodies high-throughput experimental techniques and hence it is a data-rich field. The goal of development of this tool is to utilize free available biological data of green algae in order to produce new metabolic pathway knowledge and to aid mining of newly generated data. The variety of biological sequence and functional information are stored in different online database, so getting annotation information of genome from different database is challenging task for reconstruction of pathway.Here we apply data integration approach to provide rich representation that enables pathway names based text mining of biological data in terms of integrated networks and conceptual spaces. The publicly available green algae genome annotated data can be used to aid mining of important biological enzymes in metabolic networks. We developed an integrative bioinformatics approach that utilizes publicly available knowledge of enzyme-metabolites interactions, network topological analysis like betweenness, closeness and degree for assigning node importance with quantitative values. The application of our software is revealed importance of role of potential enzymes in biological functions in view of network centrality values, which were calculated by various algorithms. The results provided in this work indicate that integration of heterogeneous biological data facilitates advanced mining of data to create metabolic pathway networks. The methods can be applied for gaining insight into functions of enzymes, metabolites and other molecules, as well as for offering interpretation of functional evolution of metabolites with help of topological analysis and reconstruction of phylogenetic tree from sequence data.

Pharmaceutical and biomedical industries demand simple, safe and reproducible processing methods thus urging the development of novel straightforward manufacturing approaches. The product manufacturing by the green processing of admixtures and end-product would avoid long and costly purification (downstream) steps. In this work, the green supercritical fluid technology is used for the processing of nanoporous carriers (aerogels) for bioactive agents [1,2]. Aerogels in the form of one micron-sized particles were processed and loaded with a model bioactive compound (ketoprofen). Results show that the carrier has excellent textural properties (specific surface area of 200 m²/g) and a high loading capacity (7 wt.%) of the bioactive compound in the amorphous form. Release profile tests show the capacity of the carrier to modulate the drug release to the medium (PBS pH 7.4). The resulting material can be incorporated in the formulation of several pharmaceutical and biomedical products.

[1] Carbohydrate Polymers 117 (2015) 797-806

[2] Carbohydrate Polymers 86 (2011) 1425-2438

Abstract: TiO₂ nanotubes have been synthesized using a 2-step strategy that involves the hydrothermal preparation of intermediate titanates followed by a subsequent thermal/hydrothermal treatment of these species to produce the desired oxide. In the first step the influence of parameters such as temperature, pH or reaction time on the composition, structure and morphology of the intermediate species has been studied. We have then examined how temperature and the presence of surfactants affect the composition, structure, morphology and particle size of the titanium dioxide obtained in the second thermal/hydrothermal treatment. In particular, we have studied the effects that the presence of CTAB has upon the morphology of the final product. Both intermediate and final species have been studied by means of X-ray diffraction, transmission electron microscopy, IR spectroscopy and thermogravimetric analysis. This way we have been able to identify NaTi₃O₆(OH).2H₂O and (TiO₂)_x(H₂O)_y as the intermediate titanate species and rutile and anatase as the final TiO₂ polymorphs. Finally, it is worth mentioning the preparation of spindle- or oval-shaped anatase, obtained via hydrothermal synthesis in the presence of CTAB.