Transverse relaxation-optimized NMR spectroscopy with the outer membrane protein OmpX in dihexanoyl phosphatidylcholine micelles

The 2H,13C,15N-labeled, 148-residue integral membrane protein OmpX from Escherichia coli was reconstituted with dihexanoyl phosphatidylcholine (DHPC) in mixed micelles of molecular mass of about 60 kDa. Transverse relaxation-optimized spectroscopy (TROSY)-type triple resonance NMR experiments and TROSY-type nuclear Overhauser enhancement spectra were recorded in 2 mM aqueous solutions of these mixed micelles at pH 6.8 and 30°C. Complete sequence-specific NMR assignments for the polypeptide backbone thus have been obtained. The 13C chemical shifts and the nuclear Overhauser effect data then resulted in the identification of the regular secondary structure elements of OmpX/DHPC in solution and in the collection of an input of conformational constraints for the computation of the global fold of the protein. The same type of polypeptide backbone fold is observed in the presently determined solution structure and the previously reported crystal structure of OmpX determined in the presence of the detergent n-octyltetraoxyethylene. Further structure refinement will have to rely on the additional resonance assignment of partially or fully protonated amino acid side chains, but the present data already demonstrate that relaxation-optimized NMR techniques open novel avenues for studies of structure and function of integral membrane proteins.

Toward optimized carbohydrate-based anticancer vaccines: Epitope clustering, carrier structure, and adjuvant all influence antibody responses to Lewisy conjugates in mice

The feasibility of using carbohydrate-based vaccines for the immunotherapy of cancer is being actively explored at the present time. Although a number of clinical trials have already been conducted with glycoconjugate vaccines, the optimal design and composition of the vaccines has yet to be determined. Among the candidate antigens being examined is Lewisy (Ley), a blood group-related antigen that is overexpressed on the majority of human carcinomas. Using Ley as a model for specificity, we have examined the role of epitope clustering, carrier structure, and adjuvant on the immunogenicity of Ley conjugates in mice. A glycolipopeptide containing a cluster of three contiguous Ley-serine epitopes and the Pam3Cys immunostimulating moiety was found to be superior to a similar construct containing only one Ley-serine epitope in eliciting antitumor cell antibodies. Because only IgM antibodies were produced by this vaccine, the effect on immunogenicity of coupling the glycopeptide to keyhole limpet hemocyanin was examined; although both IgM and IgG antibodies were formed, the antibodies reacted only with the immunizing structure. Reexamination of the clustered Ley-serine Pam3Cys conjugate with the adjuvant QS-21 resulted in the identification of both IgG and IgM antibodies reacting with tumor cells, thus demonstrating the feasibility of an entirely synthetic carbohydrate-based anticancer vaccine in an animal model.

Decrease in Phosphoribulokinase Activity by Antisense RNA in Transgenic Tobacco. Relationship between Photosynthesis, Growth, and Allocation at Different Nitrogen Levels1

To study the direct effects of photosynthesis on allocation of biomass by altering photosynthesis without altering leaf N or nitrate content, phosphoribulokinase (PRK) activity was decreased in transgenic tobacco (Nicotiana tabacum L.) with an inverted tobacco PRK cDNA and plants were grown at different N levels (0.4 and 5 mm NH4NO3). The activation state of PRK increased as the amount of enzyme was decreased genetically at both levels of N. At high N a 94% decrease in PRK activity had only a small effect (20%) on photosynthesis and growth. At low N a 94% decrease in PRK activity had a greater effect on leaf photosynthesis (decreased by up to 50%) and whole-plant photosynthesis (decreased by up to 35%) than at high N. These plants were up to 35% smaller than plants with higher PRK activities because they had less structural dry matter and less starch, which was decreased by 3- to 4-fold, but still accumulated to 24% to 31% of dry weight; young leaves contained more starch than older leaves in older plants. Leaves had a higher ion and water content, and specific leaf area was higher, but allocation between shoot and root was unaltered. In conclusion, low N in addition to a 94% decrease in PRK by antisense reduces the activity of PRK sufficient to diminish photosynthesis, which limits biomass production under conditions normally considered sink limited.

Computer simulations of enzyme catalysis: Finding out what has been optimized by evolution

The origin of the catalytic power of enzymes is discussed, paying attention to evolutionary constraints. It is pointed out that enzyme catalysis reflects energy contributions that cannot be determined uniquely by current experimental approaches without augmenting the analysis by computer simulation studies. The use of energy considerations and computer simulations allows one to exclude many of the popular proposals for the way enzymes work. It appears that the standard approaches used by organic chemists to catalyze reactions in solutions are not used by enzymes. This point is illustrated by considering the desolvation hypothesis and showing that it cannot account for a large increase in kcat relative to the corresponding kcage for the reference reaction in a solvent cage. The problems associated with other frequently invoked mechanisms also are outlined. Furthermore, it is pointed out that mutation studies are inconsistent with ground state destabilization mechanisms. After considering factors that were not optimized by evolution, we review computer simulation studies that reproduced the overall catalytic effect of different enzymes. These studies pointed toward electrostatic effects as the most important catalytic contributions. The nature of this electrostatic stabilization mechanism is far from being obvious because the electrostatic interaction between the reacting system and the surrounding area is similar in enzymes and in solution. However, the difference is that enzymes have a preorganized dipolar environment that does not have to pay the reorganization energy for stabilizing the relevant transition states. Apparently, the catalytic power of enzymes is stored in their folding energy in the form of the preorganized polar environment.

Extended theory about the allocation of time: Description and application to the increase in the retirement age policies

This paper revises mainstream economic models which include time use in an explicit and endogenous manner, suggesting a extended theory which escape from the main problem existing in the literature. In order to do it, we start by presenting in section 2 the mainstream time use models in economics, showing their main features. Once this is done, we introduce the reader in the main problems this kind of well established models imply, within section 3, being the most highlighted the problem of joint production. Subsequently, we propose an extended theory which solves the problem of joint production; this is extensively described in section 4. Last, but not least, we apply this model to offer a time use analysis of the effect of a policy which increases the retirement age in a life-cycle perspective for a representative individual.

Optimized Monte Carlo method for glasses

A new Monte Carlo algorithm is introduced for the simulation of supercooled liquids and glass formers, and tested in two model glasses. The algorithm thermalizes well below the Mode Coupling temperature and outperforms other optimized Monte Carlo methods.

Logística operacional: alocação de bases operacionais em distribuição de energia elétrica.

Ser eficiente é um requisito para a sustentabilidade das empresas concessionárias de distribuição de energia elétrica no Brasil. A busca pela eficiência deve estar em harmonia com a melhoria contínua da qualidade, da segurança e da satisfação dos consumidores e das partes envolvidas. O desafio de atender múltiplos objetivos requer que as empresas do setor desenvolvam soluções inovadoras, com a mudança de processos, tecnologia, estrutura e a capacitação das pessoas. Desenvolver um modelo operacional eficiente e uma gestão rigorosa dos custos são fatores-chave para o sucesso das empresas, considerando o contexto regulatório de revisão tarifária que incentiva a melhoria do desempenho. O modelo operacional é definido a partir da organização logística dos recursos para atendimento da demanda de serviços, que define também os custos fixos e variáveis de pessoal (salário, horas extras, refeições), infraestrutura (manutenção de prédios, ferramentas e equipamentos) e deslocamentos (manutenção de veículos, combustível), por exemplo. A melhor alocação e o melhor dimensionamento de bases operacionais possibilitam a redução dos custos com deslocamento e infraestrutura, favorecendo o aproveitamento da força de trabalho em campo, a melhoria do atendimento dos clientes e da segurança dos colaboradores. Este trabalho apresenta uma metodologia de otimização de custos através da alocação de bases e equipes operacionais, com o modelamento matemático dos objetivos e restrições do negócio e a aplicação de algoritmo evolutivo para busca das melhores soluções, sendo uma aplicação de Pesquisa Operacional, no campo da Localização de Instalações, em distribuição de energia elétrica. O modelo de otimização desenvolvido possibilita a busca pelo ponto de equilíbrio ótimo que minimiza o custo total formado pelos custos de infraestrutura, frota (veículos e deslocamentos) e pessoal. O algoritmo evolutivo aplicado no modelo oferece soluções otimizadas pelo melhoramento de conjuntos de variáveis binárias com base em conceitos da evolução genética. O modelo de otimização fornece o detalhamento de toda a estrutura operacional e de custos para uma determinada solução do problema, utilizando premissas de produtividade e deslocamentos (velocidades e distâncias) para definir as abrangências de atuação das bases operacionais, recursos (equipes, pessoas, veículos) necessários para atendimento da demanda de serviços, e projetar todos os custos fixos e variáveis associados. A metodologia desenvolvida neste trabalho considera também a projeção de demanda futura para a aplicação no estudo de caso, que evidenciou a efetividade da metodologia como ferramenta para a melhoria da eficiência operacional em empresas de distribuição de energia elétrica.

Contextual visual localization: cascaded submap classification, optimized saliency detection, and fast view matching

In this paper, we present a novel coarse-to-fine visual localization approach: contextual visual localization. This approach relies on three elements: (i) a minimal-complexity classifier for performing fast coarse localization (submap classification); (ii) an optimized saliency detector which exploits the visual statistics of the submap; and (iii) a fast view-matching algorithm which filters initial matchings with a structural criterion. The latter algorithm yields fine localization. Our experiments show that these elements have been successfully integrated for solving the global localization problem. Context, that is, the awareness of being in a particular submap, is defined by a supervised classifier tuned for a minimal set of features. Visual context is exploited both for tuning (optimizing) the saliency detection process, and to select potential matching views in the visual database, close enough to the query view.

An optimized pseudorandom generator using packed matrices

Most cryptographic services and information security protocols require a dependable source of random data; pseudorandom generators are convenient and efficient for this application working as one of the basic foundation blocks on which to build the required security infrastructure. We propose a modification of a previously published matricial pseudorandom generator that significantly improves performance and security by using word packed matrices and modifying key scheduling and bit extraction schemes. The resulting generator is then successfully compared to world class standards.

Photocatalytic oxidation of propene in gas phase at low concentration by optimized TiO2 nanoparticles

In the present study, nanocrystalline titanium dioxide (TiO2) was prepared by sol–gel method at low temperature from titanium tetraisopropoxide (TTIP) and characterized by different techniques (gas adsorption, XRD, TEM and FTIR). Variables of the synthesis, such as the hydrolyzing agent (acetic acid or isopropanol) and calcination temperatures (300–800 °C), were analyzed to get uniform size TiO2 nanoparticles. The effect that these two variables have on the structure of the resultant TiO2 nanoparticles and on their photocatalytic activity is investigated. The photocatalytic activities of TiO2 nanoparticles were evaluated for propene oxidation at low concentration (100 ppmv) under two different kinds of UV light (UV-A ∼ 365 nm and UV-C ∼ 257.7 nm) and compared with Degussa TiO2 P-25, used as reference sample. The results show that both hydrolyzing agents allow to prepare TiO2 nanoparticles and that the hydrolyzing agent influences the crystalline structure and its change with the thermal treatments. Interestingly, the prepared TiO2 nanoparticles possess anatase phase with small crystalline size, high surface area and higher photocatalytic activity for propene oxidation than commercial TiO2 (Degussa P-25) under UV-light. Curiously, these prepared TiO2 nanoparticles are more active with the 365 nm source than with the 257.7 nm UV-light, which is a remarkable advantage from an application point of view. Additionally, the obtained results are particularly good when acetic acid is the hydrolyzing agent at both wavelengths used, possibly due to the high crystallinity, low anatase phase size and high surface oxygen groups’ content in the nanoparticles prepared with it, in comparison to those prepared using isopropanol.