Modulation of parasitemia and antibody responce to Trypanosoma cruzy by cyclophosphamide in Calomys callosus (Rodentia, Cricetidae)

Calomys callosus a wild rodent, previously described as harboring Trypanosoma cruzi, has a low susceptibility to infection by this protozoan. Experiments were designed to evaluate the contribution of the immune response to the resistance to T. cruzi infection exhibited by C. calossus. Animals were submitted to injections of high (200 mg/kg body weight) and low (20 mg/kg body weight) doses of cyclophosphamide on days -1 or -1 and +5, and inoculated with 4 x 10³ T. cruzi on day O. Parasitemia, mortality and antibody response as measured by direct agglutination of trypomastigotes were observed. Two hundred mg doses of cyclophosphamide resulted in higher parasitemia and mortality as well as in suppression of the antibody response. A single dose of 20 mg enhanced antibody levels on the 20th day after infection, while an additional dose did not further increase antibody production. Parasitemia levels were not depressed, but rather increased in both these groups as compared to untreated controls. Passive transfer of hyperimmune C. callosus anti-T. cruzi serum to cyclophosphamide immunosuppressed animals resulted in lower parasitemia and mortality rates. These results indicate that the immune response plays an important role in the resistance of C. callossus to T. cruzi.

Day-ahead Resource Scheduling Including Demand Response for Electric Vehicles

The energy resource scheduling is becoming increasingly important, as the use of distributed resources is intensified and massive gridable vehicle (V2G) use is envisaged. This paper presents a methodology for day-ahead energy resource scheduling for smart grids considering the intensive use of distributed generation and V2G. The main focus is the comparison of different EV management approaches in the day-ahead energy resources management, namely uncontrolled charging, smart charging, V2G and Demand Response (DR) programs i n the V2G approach. Three different DR programs are designed and tested (trip reduce, shifting reduce and reduce+shifting). Othe r important contribution of the paper is the comparison between deterministic and computational intelligence techniques to reduce the execution time. The proposed scheduling is solved with a modified particle swarm optimization. Mixed integer non-linear programming is also used for comparison purposes. Full ac power flow calculation is included to allow taking into account the network constraints. A case study with a 33-bus distribution network and 2000 V2G resources is used to illustrate the performance of the proposed method.

Modified Particle Swarm Optimization Applied to Integrated Demand Response and DG Resources Scheduling

The elastic behavior of the demand consumption jointly used with other available resources such as distributed generation (DG) can play a crucial role for the success of smart grids. The intensive use of Distributed Energy Resources (DER) and the technical and contractual constraints result in large-scale non linear optimization problems that require computational intelligence methods to be solved. This paper proposes a Particle Swarm Optimization (PSO) based methodology to support the minimization of the operation costs of a virtual power player that manages the resources in a distribution network and the network itself. Resources include the DER available in the considered time period and the energy that can be bought from external energy suppliers. Network constraints are considered. The proposed approach uses Gaussian mutation of the strategic parameters and contextual self-parameterization of the maximum and minimum particle velocities. The case study considers a real 937 bus distribution network, with 20310 consumers and 548 distributed generators. The obtained solutions are compared with a deterministic approach and with PSO without mutation and Evolutionary PSO, both using self-parameterization.

Distributed, Agent-Based Intelligent System for Demand Response Program Simulation in Smart Grids

A distributed, agent-based intelligent system models and simulates a smart grid using physical players and computationally simulated agents. The proposed system can assess the impact of demand response programs.

Decision Support Concerning Demand Response Programs Design and Use – A Conceptual Framework and Simulation Tool

Demand response can play a very relevant role in the context of power systems with an intensive use of distributed energy resources, from which renewable intermittent sources are a significant part. More active consumers participation can help improving the system reliability and decrease or defer the required investments. Demand response adequate use and management is even more important in competitive electricity markets. However, experience shows difficulties to make demand response be adequately used in this context, showing the need of research work in this area. The most important difficulties seem to be caused by inadequate business models and by inadequate demand response programs management. This paper contributes to developing methodologies and a computational infrastructure able to provide the involved players with adequate decision support on demand response programs and contracts design and use. The presented work uses DemSi, a demand response simulator that has been developed by the authors to simulate demand response actions and programs, which includes realistic power system simulation. It includes an optimization module for the application of demand response programs and contracts using deterministic and metaheuristic approaches. The proposed methodology is an important improvement in the simulator while providing adequate tools for demand response programs adoption by the involved players. A machine learning method based on clustering and classification techniques, resulting in a rule base concerning DR programs and contracts use, is also used. A case study concerning the use of demand response in an incident situation is presented.

Distributed Generation and Demand Response Dispatch for a Virtual Power Player Energy and Reserve Provision

Recent changes in the operation and planning of power systems have been motivated by the introduction of Distributed Generation (DG) and Demand Response (DR) in the competitive electricity markets' environment, with deep concerns at the efficiency level. In this context, grid operators, market operators, utilities and consumers must adopt strategies and methods to take full advantage of demand response and distributed generation. This requires that all the involved players consider all the market opportunities, as the case of energy and reserve components of electricity markets. The present paper proposes a methodology which considers the joint dispatch of demand response and distributed generation in the context of a distribution network operated by a virtual power player. The resources' participation can be performed in both energy and reserve contexts. This methodology contemplates the probability of actually using the reserve and the distribution network constraints. Its application is illustrated in this paper using a 32-bus distribution network with 66 DG units and 218 consumers classified into 6 types of consumers.

Dynamic load management in a smart home to participate in demand response events

In future power systems, in the smart grid and microgrids operation paradigms, consumers can be seen as an energy resource with decentralized and autonomous decisions in the energy management. It is expected that each consumer will manage not only the loads, but also small generation units, heating systems, storage systems, and electric vehicles. Each consumer can participate in different demand response events promoted by system operators or aggregation entities. This paper proposes an innovative method to manage the appliances on a house during a demand response event. The main contribution of this work is to include time constraints in resources management, and the context evaluation in order to ensure the required comfort levels. The dynamic resources management methodology allows a better resources’ management in a demand response event, mainly the ones of long duration, by changing the priorities of loads during the event. A case study with two scenarios is presented considering a demand response with 30 min duration, and another with 240 min (4 h). In both simulations, the demand response event proposes the power consumption reduction during the event. A total of 18 loads are used, including real and virtual ones, controlled by the presented house management system.

Electrochemical response of 70Co-30Ni highly branched 3D-dendritic structures for charge storage electrodes

A 70Co-30Ni dendritic alloy was produced on stainless steel by pulse electrodeposition in the cathodic domain, and oxidized by potential cycling. X-ray diffraction (XRD) identified the presence of two phases and scanning electron microscopy (SEM) evidenced an open 3D highly branched dendritic morphology. After potential cycling in 1 M KOH, SEM and X-ray photoelectron spectroscopy (XPS) revealed, respectively, the presence of thin nanoplates, composed of Co and Ni oxi-hydroxides and hydroxides over the original dendritic film. Cyclic voltammetry tests showd the presence of redox peaks assigned to the oxidation and reduction of Ni and Co centres in the surface film. Charge/discharge measurements revealed capacity values of 121 mAh g(1) at 1 mA cm(2). The capacity retention under 8000 cycles was above 70%, stating the good reversibility of these redox materials and its suitability to be used as charge storage electrodes. Electrochemical impedance spectroscopy (EIS) spectra, taken under different applied bias, showed that the capacitance increased when the electrode was fully oxidized and decreased when the electrode was reduced, reflecting different states-of-charge of the electrode. (C) 2015 Elsevier Ltd. All rights reserved.

Hepatitis B vaccine - proposal for a standardized assessment of immune response

The authors developed a comparative study of the various methods of assessment of immune response to Hepatitis B vaccine. Eighty-six health care professionals underwent a vaccination programme with three doses of plasma-derived vaccine against Hepatitis B (H-B-Vax, Merck, Sharp & Dohme) given intra-muscularly. Assessment of immune response was carried out three months after the end of the programme, by radioimmunoassay (RIA) and enzymeimmunoassay (EIA). The results showed that the semi-quantitative assessment of Anti-HBs antibodies by RIA or EIA was perfectly comparable to the reference method (quantitative determination of antibodies by RIA). In view of these findings, the authors suggest a standardization of assessment of immune response to the vaccine, thus permitting correct planning of booster doses and easier comparison between different studies

Multiple linear and principal component regressions for modelling ecotoxicity bioassay response

The ecotoxicological response of the living organisms in an aquatic system depends on the physical, chemical and bacteriological variables, as well as the interactions between them. An important challenge to scientists is to understand the interaction and behaviour of factors involved in a multidimensional process such as the ecotoxicological response.With this aim, multiple linear regression (MLR) and principal component regression were applied to the ecotoxicity bioassay response of Chlorella vulgaris and Vibrio fischeri in water collected at seven sites of Leça river during five monitoring campaigns (February, May, June, August and September of 2006). The river water characterization included the analysis of 22 physicochemical and 3 microbiological parameters. The model that best fitted the data was MLR, which shows: (i) a negative correlation with dissolved organic carbon, zinc and manganese, and a positive one with turbidity and arsenic, regarding C. vulgaris toxic response; (ii) a negative correlation with conductivity and turbidity and a positive one with phosphorus, hardness, iron, mercury, arsenic and faecal coliforms, concerning V. fischeri toxic response. This integrated assessment may allow the evaluation of the effect of future pollution abatement measures over the water quality of Leça River.

An uncertainty and sensitivity analysis applied to the prioritisation of pharmaceuticals as surface water contaminants from wastewater treatment plant direct emissions

In this study, the concentration probability distributions of 82 pharmaceutical compounds detected in the effluents of 179 European wastewater treatment plants were computed and inserted into a multimedia fate model. The comparative ecotoxicological impact of the direct emission of these compounds from wastewater treatment plants on freshwater ecosystems, based on a potentially affected fraction (PAF) of species approach, was assessed to rank compounds based on priority. As many pharmaceuticals are acids or bases, the multimedia fate model accounts for regressions to estimate pH-dependent fate parameters. An uncertainty analysis was performed by means of Monte Carlo analysis, which included the uncertainty of fate and ecotoxicity model input variables, as well as the spatial variability of landscape characteristics on the European continental scale. Several pharmaceutical compounds were identified as being of greatest concern, including 7 analgesics/anti-inflammatories, 3 β-blockers, 3 psychiatric drugs, and 1 each of 6 other therapeutic classes. The fate and impact modelling relied extensively on estimated data, given that most of these compounds have little or no experimental fate or ecotoxicity data available, as well as a limited reported occurrence in effluents. The contribution of estimated model input variables to the variance of freshwater ecotoxicity impact, as well as the lack of experimental abiotic degradation data for most compounds, helped in establishing priorities for further testing. Generally, the effluent concentration and the ecotoxicity effect factor were the model input variables with the most significant effect on the uncertainty of output results.

Immune response in mice immunized with acidic antigenic fractions from Trypanosoma cruzi cytosol

The humoral and cellular immune responses as well as the resistance to infection with bloodstream forms of T. cruzi were studied in mice immunized with acidic antigenic fractions from parasite cytosol, F III and F IV, plus Bordetella pertussis as adjuvant. The immunization with F III induced positive ITH and DTH responses to homologous antigens. In mice immunized with F IV, the ITH was negative and four out of six animals presented positive DTH reactions. In both groups of mice the analysis of IgG aginst T. cruzi showed that the major isotype elicited was IgG1. Specific IgE was also detected in sera from F III immunized mice, thus confirming the presence of homocytothropic antibodies. The parasitemias reached by F III and F IV immunized mice after challenge were lower than those of the controls showing in this way a partial protection against the acute infection. The histological studies of heart and skeletal muscle performed two months after the infection revealed variable mononuclear infiltration in all infected mice despite immunization.

Gastric acid secretion response in the Cebus apella: a monkey model of chronic Chagas disease

The objective was to study the secretory pattern, both basal and stimulated either by histamine (0.1 mg/kg) or pentagastrin (64 ug/kg) in eighteen Cebus apella monkeys chronically infected with different T. cruzi strains (CA1, n=10; Colombian, n=4 and Tulahuen, n=4) and to describe the morphological findings in the gastrointestinal tract in twelve infected (6 sacrificed and 6 spontaneously dead) and four healthy monkeys. All infected monkeys and 35 healthy ones were evaluated by contrast X-ray examination. No differences were observed in basal acid output between control and infected groups. Animals infected with the Tulahuen and Colombian strains showed significant lower values of peak acid output in response to histamine or pentagastrin (p<0.01 and p<0.05 respectively; "t" test) in comparison to the controls. Barium contrast studies showed enlargement and dilatation of the colon in three infected animals. Histopathological lesions were seen in 75% of the autopsied animals either in colon alone (33%) or both, in colon and esophagus (42%). The normal secretion observed in the CA1 infected group could be due to a lower virulence of the strain, a lower esophagic tropism or the necessity of a longer post-infection time to cause lesions.

Immunization aganist hepatitis B in children from endemic zone: evaluation of the antibody response against the DNA recombinant vaccine (Engerix B-20 mcg)

A previous seroepidemiological study in the rural zone of Vargem Alta (ES) SouthEast of Brazil, showed a prevalence of up to 9% of hepatitis B surface antigen (HBsAg) in some areas. One hundred susceptible children aging 1 to 5 years old were selected and immunized with a recombinant DNA hepatitis B vaccine (Smith-Kline 20 mcg) using the 0-1-6 months vaccination schedule. Blood samples were collected at the time of the first vaccine dose (month 0) in order to confirm susceptible individuals and 1,3,6 and 8 months after the first dose , to evaluate the antibody response. Our results showed that two and five months after the second dose, 79% and 88% of children seroconverted respectively, reaching 97% after the third dose. The levels of anti-HBs were calculated in milli International Units/ml (mIU/ml) and demonstrated the markedly increase of protective levels of antibodies after the third dose. These data showed a good immunogenicity of the DNA recombinant hepatitis B vaccine when administered in children of endemic areas.

The role of functional polymorphisms in immune response genes as biomarkers of BCG Immunotherapy outcome in bladder cancer: Establishment of a predictive profile in a Southern Europe population

OBJECTIVE: To evaluate the predictive value of genetic polymorphisms in the context of BCG immunotherapy outcome and create a predictive profile that may allow discriminating the risk of recurrence. MATERIAL AND METHODS: In a dataset of 204 patients treated with BCG, we evaluate 42 genetic polymorphisms in 38 genes involved in the BCG mechanism of action, using Sequenom MassARRAY technology. Stepwise multivariate Cox Regression was used for data mining. RESULTS: In agreement with previous studies we observed that gender, age, tumor multiplicity and treatment scheme were associated with BCG failure. Using stepwise multivariate Cox Regression analysis we propose the first predictive profile of BCG immunotherapy outcome and a risk score based on polymorphisms in immune system molecules (SNPs in TNFA-1031T/C (rs1799964), IL2RA rs2104286 T/C, IL17A-197G/A (rs2275913), IL17RA-809A/G (rs4819554), IL18R1 rs3771171 T/C, ICAM1 K469E (rs5498), FASL-844T/C (rs763110) and TRAILR1-397T/G (rs79037040) in association with clinicopathological variables. This risk score allows the categorization of patients into risk groups: patients within the Low Risk group have a 90% chance of successful treatment, whereas patients in the High Risk group present 75% chance of recurrence after BCG treatment. CONCLUSION: We have established the first predictive score of BCG immunotherapy outcome combining clinicopathological characteristics and a panel of genetic polymorphisms. Further studies using an independent cohort are warranted. Moreover, the inclusion of other biomarkers may help to improve the proposed model.