Alright: a distinctive pathway of change from the 18th century to the present day

The origins of the vast majority of the words we use in contemporary English go back as far as Old or Middle English. In contrast, alright and all right in their present-day application appear to be the result of a more recent evolution, as there is no evidence of their use, not even in the two-word form, in the published fiction before the 18th century. Furthermore, there are not in the research literature, at least to my knowledge, any previous linguistic studies on this specific subject matter. The present article is simply an attempt to describe the various processes of diachronic change that brought about the emergence of alright.

Cholesterol 24S-Hydroxylase overexpression inhibits the liver X receptor (LXR) pathway by activating small guanosine triphosphate-binding proteins (sGTPases) in neuronal cells

The neuronal-specific cholesterol 24S-hydroxylase (CYP46A1) is important for brain cholesterol elimination. Cyp46a1 null mice exhibit severe deficiencies in learning and hippocampal long-term potentiation, suggested to be caused by a decrease in isoprenoid intermediates of the mevalonate pathway. Conversely, transgenic mice overexpressing CYP46A1 show an improved cognitive function. These results raised the question of whether CYP46A1 expression can modulate the activity of proteins that are crucial for neuronal function, namely of isoprenylated small guanosine triphosphate-binding proteins (sGTPases). Our results show that CYP46A1 overexpression in SH-SY5Y neuroblastoma cells and in primary cultures of rat cortical neurons leads to an increase in 3-hydroxy-3-methyl-glutaryl-CoA reductase activity and to an overall increase in membrane levels of RhoA, Rac1, Cdc42 and Rab8. This increase is accompanied by a specific increase in RhoA activation. Interestingly, treatment with lovastatin or a geranylgeranyltransferase-I inhibitor abolished the CYP46A1 effect. The CYP46A1-mediated increase in sGTPases membrane abundance was confirmed in vivo, in membrane fractions obtained from transgenic mice overexpressing this enzyme. Moreover, CYP46A1 overexpression leads to a decrease in the liver X receptor (LXR) transcriptional activity and in the mRNA levels of ATP-binding cassette transporter 1, sub-family A, member 1 and apolipoprotein E. This effect was abolished by inhibition of prenylation or by co-transfection of a RhoA dominant-negative mutant. Our results suggest a novel regulatory axis in neurons; under conditions of membrane cholesterol reduction by increased CYP46A1 expression, neurons increase isoprenoid synthesis and sGTPase prenylation. This leads to a reduction in LXR activity, and consequently to a decrease in the expression of LXR target genes.

Thermodynamic pathway for the formation of SnSe and SnSe2 polycrystalline thin films by selenization of metal precursors

In this work, tin selenide thin films (SnSex) were grown on soda lime glass substrates by selenization of dc magnetron sputtered Sn metallic precursors. Selenization was performed at maximum temperatures in the range 300 °C to 570 °C. The thickness and the composition of the films were analysed using step profilometry and energy dispersive spectroscopy, respectively. The films were structurally and optically investigated by X-ray diffraction, Raman spectroscopy and optical transmittance and reflectance measurements. X-Ray diffraction patterns suggest that for temperatures between 300 °C and 470 °C, the films are composed of the hexagonal-SnSe2 phase. By increasing the temperature, the films selenized at maximum temperatures of 530 °C and 570 °C show orthorhombic-SnSe as the dominant phase with a preferential crystal orientation along the (400) crystallographic plane. Raman scattering analysis allowed the assignment of peaks at 119 cm−1 and 185 cm−1 to the hexagonal-SnSe2 phase and those at 108 cm−1, 130 cm−1 and 150 cm−1 to the orthorhombic-SnSe phase. All samples presented traces of condensed amorphous Se with a characteristic Raman peak located at 255 cm−1. From optical measurements, the estimated band gap energies for hexagonal-SnSe2 were close to 0.9 eV and 1.7 eV for indirect forbidden and direct transitions, respectively. The samples with the dominant orthorhombic-SnSe phase presented estimated band gap energies of 0.95 eV and 1.15 eV for indirect allowed and direct allowed transitions, respectively.

A checklist for patient safety rounds at the care pathway level

Objective - To define a checklist that can be used to assess the performance of a department and evaluate the implementation of quality management (QM) activities across departments or pathways in acute care hospitals. Design - We developed and tested a checklist for the assessment of QM activities at department level in a cross-sectional study using on-site visits by trained external auditors. Setting and Participants - A sample of 292 hospital departments of 74 acute care hospitals across seven European countries. In every hospital, four departments for the conditions: acute myocardial infarction (AMI), stroke, hip fracture and deliveries participated. Main outcome measures - Four measures of QM activities were evaluated at care pathway level focusing on specialized expertise and responsibility (SER), evidence-based organization of pathways (EBOP), patient safety strategies and clinical review (CR). Results - Participating departments attained mean values on the various scales between 1.2 and 3.7. The theoretical range was 0-4. Three of the four QM measures are identical for the four conditions, whereas one scale (EBOP) has condition-specific items. Correlations showed that every factor was related, but also distinct, and added to the overall picture of QM at pathway level. Conclusion - The newly developed checklist can be used across various types of departments and pathways in acute care hospitals like AMI, deliveries, stroke and hip fracture. The anticipated users of the checklist are internal (e.g. peers within the hospital and hospital executive board) and external auditors (e.g. healthcare inspectorate, professional or patient organizations).

Automatic learning for the classification of chemical reactions and in statistical thermodynamics

This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.

Molybdenum-containing proteins from Sulphate Reducing Bacteria: studying proteins with novel cofactors and revealing new features of old enzymes

Dissertação apresentada para a obtenção do Grau de Doutor em Bioquímica, especialidade de Bioquímica-Física pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia

Bacterial enzymes and multi-enzymatic systems for cleaning-up dyes from the environment

Synthetic dyes are xenobiotic compounds that are being increasingly used in several industries, with special emphasis in the paper, textile and leather industries. Over 100,000 commercial dyes exist today and more than 7 × 105 tons of dyestuff is produced annually, of which 1–1.5 × 105 tons is released into the wastewaters (Rai et al in Crit Rev Environ Sci Tecnhol 35:219–238, 2005). Among these, azo dyes, characterized by the presence of one or more azo groups (–N=N–), and anthraquinonic dyes represent the largest and most versatile groups.

Functional and structural characterization of the RNase II-family of enzymes

Dissertation presented to obtain a Doctoral Degree in Biology by Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa

Characterization of Nitric Oxide Reductase (NOR) from pseudomonas nautica, a study on biologic nitric oxide reduction

Dissertation submitted to obtain the phD degree in Biochemistry, specialty in Physical- Biochemistry, by the Faculdade de Ciências e Tecnologia from the Universidade Nova de Lisboa

Crystallographic studies on molybdopterin-dependent enzymes

Dissertação para obtenção do Grau de Doutor em Bioquímica, Especialidade Bioquímica Estrutural

Crystallographic studies on two hyperthermophilic enzymes

Dissertation presented to obtain the Ph.D degree in Biochemistry

Secretion of five extracellular enzymes by strains of chromoblastomycosis agents

The gelatinase, urease, lipase, phospholipase and DNase activities of 11 chromoblastomycosis agents constituted by strains of Fonsecaea pedrosoi, F. compacta, Phialophora verrucosa, Cladosporium carrionii, Cladophialophora bantiana and Exophiala jeanselmei were analyzed and compared. All strains presented urease, gelatinase and lipase activity. Phospholipase activity was detected only on five of six strains of F. pedrosoi. DNase activity was not detected on the strains studied. Our results indicate that only phospholipase production, induced by egg yolk substrate, was useful for the differentiation of the taxonomically related species studied, based on their enzymatic profile.

Effects of UV radiation exposure on DNA and DNA repair enzymes

Dissertação para obtenção do Grau de Mestre em Biotecnologia

Analysis of the pathway of developing a national mental health plan for Suriname

ABSTRACT: The aim of this analysis was to analyze and describe the steps that have been taken in the development of the mental health policy in Suriname after the WHO AIMS. The objectives are: 1.To review the steps to be taken in developing a mental health policy and plan for a country 2.To gather information and data concerning mental health policy and plan development in Suriname 3.To draw conclusion from the experience gained that can be applied to other countries. In general, the information that was gathered from the four countries Guyana, Barbados, Trinidad & Tobago and Suriname, was compared with the WHO steps for developing a mental health policy and plan. Were these steps taken into consideration, when developing their mental health policy and plan? If not, what were the reasons why it did not happen? The checklist for evaluating a mental health plan was used in Suriname. This checklist assisted to see if the results of the recommendations given by the WHO AIMS to develop a effective and balanced mental health plan were taken into consideration. The mayor findings of the analysis are that Suriname as well as Guyana used the steps in developing their mental health policy and plan. Barbados and Trinidad & Tobago did not develop a mental health policy and plan. Suriname and Guyana have a mental health coordinating body at the Ministry of Health. Trinidad & Tobago as well as Barbados have a mental health focal person at the Ministry of Health of the respective countries. It can be concluded that successfully improving of health systems and services for mental health is combining theoretical concepts, expert knowledge and cooperation of many stakeholders. The appointment of a mental health coordinating unit at the Ministry of Health is crucial for the development of mental health in a country. Furthermore, mental health is everyone’s business and responsibility. Implementing the steps to be taken when developing a mental health policy and plan as recommended by WHO may be a slow process requiring the mobilization of political will. That’s why it is crucial that persons responsible for this process work close with all stakeholders in relevant sectors, taking their needs into consideration and try to translate that in clear objectives. It is common knowledge that improving the quality of mental health must be accompanied by the availability of financial and human resources. Finally, a mental health policy and plan should be one document tackling all aspects of mental health of a community.

New spectroscopic and electrochemical insights on a class I superoxide reductase: evidence for an intramolecular electron-transfer pathway

Biochem. J. (2011) 438,485–494 doi:10.1042/BJ20110836