Relation of pretreatment sequence diversity in NS5A region of HCV genotype 1 with immune response between pegylated-INF/ribavirin therapy outcomes

Hepatitis C virus (HCV) infection frequently persists despite substantial virus-specific immune responses and the combination of pegylated interferon (INF)-alpha and ribavirin therapy. Major histocompatibility complex class I restricted CD8+ T cells are responsible for the control of viraemia in HCV infection, and several studies suggest protection against viral infection associated with specific HLAs. The reason for low rates of sustained viral response (SVR) in HCV patients remains unknown. Escape mutations in response to cytotoxic T lymphocyte are widely described; however, its influence in the treatment outcome is ill understood. Here, we investigate the differences in CD8 epitopes frequencies from the Los Alamos database between groups of patients that showed distinct response to pegylated alpha-INF with ribavirin therapy and test evidence of natural selection on the virus in those who failed treatment, using five maximum likelihood evolutionary models from PAML package. The group of sustained virological responders showed three epitopes with frequencies higher than Non-responders group, all had statistical support, and we observed evidence of selection pressure in the last group. No escape mutation was observed. Interestingly, the epitope VLSDFKTWL was 100% conserved in SVR group. These results suggest that the response to treatment can be explained by the increase in immune pressure, induced by interferon therapy, and the presence of those epitopes may represent an important factor in determining the outcome of therapy.

Synthesis of LiFePO4@carbon nanotube core-shell nanowires with a high-energy efficient method for superior lithium ion battery cathodes

A high-energy efficient method is developed for the synthesis of LiFePO4@CNT core-shell nanowire structures. The method consists of two steps: liquid deposition approach to prepare FePO4@CNT core-shell nanowires and solvothermal lithiation to obtain the LiFePO4@CNT core-shell nanowires at a low temperature. The solution phase method can be easily scaled up for commercial application. The performance of the materials produced by this method is evaluated in Li ion batteries. The one-dimensional LiFePO4@CNT nanowires offer a stable and efficient backbone for electron transport. The LiFePO4@CNT core-shell nanowires exhibit a high capacity of 132.8 mAh g^-1 at a rate of 0.2C, as well as high rate capability (64.4 mAh g^-1 at 20C) for Li ion storage.

The competition between metastable and equilibrium S (Al2CuMg) phase during the decomposition of AlCuMg alloys

Abstract The decomposition sequence of the supersaturated solid solution leading to the formation of the equilibrium S (Al2CuMg) phase in AlCuMg alloys has long been the subject of ambiguity and debate. Recent high-resolution synchrotron powder diffraction experiments have shown that the decomposition sequence does involve a metastable variant of the S phase (denoted S1), which has lattice parameters that are distinctly different to those of the equilibrium S phase (denoted S2). In this paper, the difference between these two phases is resolved using high-resolution synchrotron and neutron powder diffraction and atom probe tomography, and the transformation from S1 to S2 is characterised in detail by in situ synchrotron powder diffraction. The results of these experiments confirm that there are no significant differences between the crystal structures of S1 and S2, however, the powder diffraction and atom probe measurements both indicate that the S1 phase forms with a slight deficiency in Cu. The in situ isothermal aging experiments show that S1 forms rapidly, reaching its maximum concentration in only a few minutes at high temperatures, while complete conversion to the S2 phase can take thousands of hours at low temperature. The kinetics of S phase precipitation have been quantitatively analysed for the first time and it is shown that S1 phase forms with an average activation energy of 75 kJ/mol, which is much lower than the activation energy for Cu and Mg diffusion in an Al matrix (136 kJ/mol and 131 kJ/mol, respectively). The mechanism of the replacement of S1 with the equilibrium S2 phase is discussed.

Degradation observations of encapsulated planar CH3NH3PbI3 perovskite solar cells at high temperatures and humidity

The stability of encapsulated planar-structured CH3NH3PbI3 (MAPbI3) perovskite solar cells (PSCs) was investigated under various simulated environmental conditions. The tests were performed under approximately one sun (100 mW cm^-2) illumination, varying temperature (up to 85 °C cell temperature) and humidity (up to 80%). The application of advanced sealing techniques improved the device stability, but all devices showed significant degradation after prolonged aging at high temperature and humidity. The degradation mechanism was studied by post-mortem analysis of the disassembled cells using SEM and XRD. This revealed that the degradation was mainly due to the decomposition of MAPbI3, as a result of reaction with H2O, and the subsequent reaction of hydroiodic acid, formed during MAPbI3 decomposition, with the silver back contact electrode layer.

Study on LiFe1 − xSm xPO4/C used as cathode materials for lithium-ion batteries with low Sm component

LiFe1 − xSmxPO4/C cathode materials were synthesized though a facile hydrothermal method. Compared with high-temperature solid-phase sintering, the method can allow for the fabrication of low Sm content (2 %), a scarce and expensive rare earth element, while the presence of an optimized carbon coating with large amount of sp²-type carbon sharply increases the material’s electrochemical performance. The high-rate dischargeability at 5 C, as well as the exchange current density, can be increased by 21 and 86 %, respectively, which were attributed to the fine size and the large cell parameter a/c as much. It should be pointed out that the a/c value will be increased for the LiFePO4 Sm-doped papered by both of the two methods, while the mechanism is different: The value c is increased for the front and the value a is decreased for the latter, respectively.

Synthesis of Al-doped Mg2Si1-xSnx compound using magnesium alloy for thermoelectric application

Abstract Mg2Si1-xSnx thermoelectric compounds were synthesized through a solid-state reaction at 700 °C between chips of Mg2Sn-Mg eutectic alloy and silicon fine powders. The Al dopants were introduced by employing AZ31 magnesium alloy that contains aluminum. The as-synthesized Mg2Si1-xSnx powders were consolidated by spark plasma sintering at 650-700 °C. X-ray diffraction and scanning electron microscopy revealed that the Mg2Si1-xSnx bulk materials were comprised of Si-rich and Sn-rich phases. Due to the complex microstructures, the electrical conductivities of Mg2Si1-xSnx are lower than Mg2Si. As a result, the average power factor of Al0.05Mg2Si0.73Sn0.27 is about 1.5 × 10^-3 W/mK² from room temperature to 850 K, being less than 2.5 × 10^-3 W/mK² for Al0.05Mg2Si. However, the thermal conductivity of Mg2Si1-xSnx was reduced significantly as compared to Al0.05Mg2Si, which enabled the ZT of Al0.05Mg2Si0.73Sn0.27 to be superior to Al0.05Mg2Si. Lastly, the electric power generation from one leg of Al0.05Mg2Si and Al0.05Mg2Si0.73Sn0.27 were evaluated on a newly developed instrument, with the peak output power of 15-20 mW at 300 °C hot-side temperature.

Preparation of size-selective Mn3O4 hexagonal nanoplates with superior electrochemical properties for pseudocapacitors

Porous Mn3O4 hexagonal nanoplates were synthesized through annealing the hydrohausmannite precursor obtained by a one-pot hydrothermal process and by precisely controlling the concentrations of potassium hydroxide and glucose. The effect of potassium hydroxide and glucose on the growth of hexagonal nanoplates was investigated, and a growth mechanism was also proposed. Due to its abundant pores, the pure Mn3O4-based electrode exhibits excellent cycling stability with 100% capacity retention after 5000 cycles. The asymmetric supercapacitor exhibited high performance with an energy density of 17.276 W h kg^-1 at a power density of 207.3 W kg^-1 in a wide potential window of 1.5 V.

Relation of pretreatment sequence diversity in NS5A region of HCV genotype 1 with immune response between pegylated-INF/ribavirin therapy outcomes

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Correlação dos níveis séricos e dos polimorfismos nos genes de citocinas (TNF-α, INF-γ, TGF-β1 e IL-10) com a apresentação clínica da hepatite B crônica

A hepatite B crônica apresenta amplo espectro de manifestações clínicas, resultante de diversos fatores, tais como o padrão de secreção e polimorfismo nos genes de citocinas. Este trabalho objetiva correlacionar os polimorfismos TNF-α -308G/A, INF-γ +874A/T, TGF-β1 -509C/T e IL-10 -1081A/G e os níveis séricos destas citocinas com a apresentação clínica da hepatite B. Foram selecionados 53 casos consecutivos de hepatite B, sendo divididos em grupo A (portador inativo= 30) e B (hepatite crônica/cirrose= 23). Como grupo controle, selecionaram-se 100 indivíduos com anti-HBc e anti-HBs positivos. Os níveis séricos das citocinas foram determinados por ensaios imunoenzimáticos, tipo ELISA (eBiosceince, Inc. Califórnia, San Diego, USA). A amplificação gênica das citocinas se realizou pela PCR e a análise histopatológica obedeceu à classificação METAVIR. Identificou-se maior prevalência do genótipo TNF-α -308AG (43,3% vs. 14,4%) no grupo B do que nos controles e a presença do alelo A se correlacionou com risco de infecção crônica pelo VHB (OR= 2,6). Os níveis séricos de INF-γ e de IL-10 foram maiores (p< 0,001) nos controles do que os demais grupos e, inversamente, as concentrações plasmáticas de TGF-β1 foram menores no grupo controle (p< 0,01). Observou-se, na histopatologia hepática, que atividade inflamatória > 2 se correlacionou com maiores níveis de TNF-α e de INF-γ (p< 0,05), assim como a fibrose > 2 com maiores níveis de INF-γ (p< 0,01). Na população pesquisada, menores níveis séricos de INF-γ e de IL-10 e maiores de TGF-β1 estiveram associados com a hepatite B crônica, bem como a presença do alelo A no gene TNF-α - 308 aumentou em 2,6 o risco de cronificação.

Participação das citocinas Interleucina-12, Interferon-γ, Interleucina-4 e Interleucina-10 e investigação de polimorfismos nos genes do INF-γ (IFNG+874) e da IL-10 (IL10-1082) na malária causada por Plasmodium vivax

A resposta imune na malária é complexa, e os mecanismos de ativação e regulação de linfócitos T efetores e de memória ainda são pouco compreendidos. No presente estudo, determinamos a concentração das citocinas Interferon-γ (IFN-γ), Interleucina-10 (IL-10), Interleucina-4 (IL-4) e Interleucina-12 (IL-12) no soro de indivíduos infectados por Plasmodium vivax, investigamos os polimorfismos no gene do IFN-γ (IFNG+874) e da IL-10 (IL10-1082) e analisamos a associação destes polimorfismos com a concentração das citocinas e com a densidade parasitária. A concentração das citocinas foi determinada por ELISA, e a genotipagem dos polimorfismos IFNG+874 e IL10-1082 foi realizada pelas técnicas de ASO-PCR e PCR-RFLP, respectivamente. Os indivíduos infectados apresentaram níveis séricos de IFN-γ e IL-10 aumentados. A produção de IFN-γ foi maior nos indivíduos primoinfectados, porém não foi associada com a redução da parasitemia. A produção de IL-10 foi alta e associada com altas parasitemias. As citocinas IL-4 e IL-12 não foram detectadas. As freqüências dos genótipos homozigoto mutante AA, heterozigoto AT e selvagem TT do gene do IFN-γ foram 0,51, 0,39 e 0,10, respectivamente. As freqüências dos genótipos homozigoto mutante AA, heterozigoto AG e selvagem GG para IL10 foram 0,49, 0,43 e 0,08, respectivamente. Apenas o polimorfismo do IFN-γ foi associado com níveis reduzidos desta citocina. Na malária causada por P. vivax, houve produção de citocina que caracteriza o perfil Th1 (IFN-γ), com possível participação da IL-10 na imunorregulação.

Influence of INF-gamma gene polymorphism in HTLV-1 proviral load

Financial Support FAPESP, CNPq, CTC/FUNDHERP and INCTC.

Kernel Methods for Tree Structured Data

Machine learning comprises a series of techniques for automatic extraction of meaningful information from large collections of noisy data. In many real world applications, data is naturally represented in structured form. Since traditional methods in machine learning deal with vectorial information, they require an a priori form of preprocessing. Among all the learning techniques for dealing with structured data, kernel methods are recognized to have a strong theoretical background and to be effective approaches. They do not require an explicit vectorial representation of the data in terms of features, but rely on a measure of similarity between any pair of objects of a domain, the kernel function. Designing fast and good kernel functions is a challenging problem. In the case of tree structured data two issues become relevant: kernel for trees should not be sparse and should be fast to compute. The sparsity problem arises when, given a dataset and a kernel function, most structures of the dataset are completely dissimilar to one another. In those cases the classifier has too few information for making correct predictions on unseen data. In fact, it tends to produce a discriminating function behaving as the nearest neighbour rule. Sparsity is likely to arise for some standard tree kernel functions, such as the subtree and subset tree kernel, when they are applied to datasets with node labels belonging to a large domain. A second drawback of using tree kernels is the time complexity required both in learning and classification phases. Such a complexity can sometimes prevents the kernel application in scenarios involving large amount of data. This thesis proposes three contributions for resolving the above issues of kernel for trees. A first contribution aims at creating kernel functions which adapt to the statistical properties of the dataset, thus reducing its sparsity with respect to traditional tree kernel functions. Specifically, we propose to encode the input trees by an algorithm able to project the data onto a lower dimensional space with the property that similar structures are mapped similarly. By building kernel functions on the lower dimensional representation, we are able to perform inexact matchings between different inputs in the original space. A second contribution is the proposal of a novel kernel function based on the convolution kernel framework. Convolution kernel measures the similarity of two objects in terms of the similarities of their subparts. Most convolution kernels are based on counting the number of shared substructures, partially discarding information about their position in the original structure. The kernel function we propose is, instead, especially focused on this aspect. A third contribution is devoted at reducing the computational burden related to the calculation of a kernel function between a tree and a forest of trees, which is a typical operation in the classification phase and, for some algorithms, also in the learning phase. We propose a general methodology applicable to convolution kernels. Moreover, we show an instantiation of our technique when kernels such as the subtree and subset tree kernels are employed. In those cases, Direct Acyclic Graphs can be used to compactly represent shared substructures in different trees, thus reducing the computational burden and storage requirements.