A regulated response to mitochondrial dysfunction modulates longevity and rates of living

Aging is a long-standing biological question of tremendous social and cultural importance. Despite this, only in the last 15 years has biology started to make significant progress in understanding the underlying mechanisms that regulate aging. This progress stemmed mainly from the use of model organisms, which allowed the discovery of several genes directly modulating longevity. Interestingly, several of these longevity genes are necessary for normal mitochondrial function, and disruption of their activity delays the aging process. This is somewhat paradoxical, considering the importance of cellular respiration for energy production and viability of eukaryotic organisms. One possible rationalization for this is that by decreasing cellular respiration, reactive oxygen species (ROS) generation is also reduced, and in that way, cellular decay and aging are delayed.(...)

Performance assessment of a wind energy conversion system using a hierarchical controller structure

This paper deals with a hierarchical structure composed by an event-based supervisor in a higher level and two distinct proportional integral (PI) controllers in a lower level. The controllers are applied to a variable speed wind energy conversion system with doubly-fed induction generator, namely, the fuzzy PI control and the fractional-order PI control. The event-based supervisor analyses the operation state of the wind energy conversion system among four possible operational states: park, start-up, generating or brake and sends the operation state to the controllers in the lower level. In start-up state, the controllers only act on electric torque while pitch angle is equal to zero. In generating state, the controllers must act on the pitch angle of the blades in order to maintain the electric power around the nominal value, thus ensuring that the safety conditions required for integration in the electric grid are met. Comparisons between fuzzy PI and fractional-order PI pitch controllers applied to a wind turbine benchmark model are given and simulation results by Matlab/Simulink are shown. From the results regarding the closed loop point of view, fuzzy PI controller allows a smoother response at the expense of larger number of variations of the pitch angle, implying frequent switches between operational states. On the other hand fractional-order PI controller allows an oscillatory response with less control effort, reducing switches between operational states. (C) 2015 Elsevier Ltd. All rights reserved.

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.

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.

Nonlinear dynamics of the patient’s response to drug effect during general anesthesia

In today’s healthcare paradigm, optimal sedation during anesthesia plays an important role both in patient welfare and in the socio-economic context. For the closed-loop control of general anesthesia, two drugs have proven to have stable, rapid onset times: propofol and remifentanil. These drugs are related to their effect in the bispectral index, a measure of EEG signal. In this paper wavelet time–frequency analysis is used to extract useful information from the clinical signals, since they are time-varying and mark important changes in patient’s response to drug dose. Model based predictive control algorithms are employed to regulate the depth of sedation by manipulating these two drugs. The results of identification from real data and the simulation of the closed loop control performance suggest that the proposed approach can bring an improvement of 9% in overall robustness and may be suitable for clinical practice.

Estimation of rotational frequency response functions

As it is widely known, in structural dynamic applications, ranging from structural coupling to model updating, the incompatibility between measured and simulated data is inevitable, due to the problem of coordinate incompleteness. Usually, the experimental data from conventional vibration testing is collected at a few translational degrees of freedom (DOF) due to applied forces, using hammer or shaker exciters, over a limited frequency range. Hence, one can only measure a portion of the receptance matrix, few columns, related to the forced DOFs, and rows, related to the measured DOFs. In contrast, by finite element modeling, one can obtain a full data set, both in terms of DOFs and identified modes. Over the years, several model reduction techniques have been proposed, as well as data expansion ones. However, the latter are significantly fewer and the demand for efficient techniques is still an issue. In this work, one proposes a technique for expanding measured frequency response functions (FRF) over the entire set of DOFs. This technique is based upon a modified Kidder's method and the principle of reciprocity, and it avoids the need for modal identification, as it uses the measured FRFs directly. In order to illustrate the performance of the proposed technique, a set of simulated experimental translational FRFs is taken as reference to estimate rotational FRFs, including those that are due to applied moments.

Virtual Power Player Using Demand Response to Deal with Unexpected Low Wind Power Generation

Demand response is assumed as an essential resource to fully achieve the smart grids operating benefits, namely in the context of competitive markets and of the increasing use of renewable-based energy sources. Some advantages of Demand Response (DR) programs and of smart grids can only be achieved through the implementation of Real Time Pricing (RTP). The integration of the expected increasing amounts of distributed energy resources, as well as new players, requires new approaches for the changing operation of power systems. The methodology proposed in this paper aims the minimization of the operation costs in a distribution network operated by a virtual power player that manages the available energy resources focusing on hour ahead re-scheduling. When facing lower wind power generation than expected from day ahead forecast, demand response is used in order to minimize the impacts of such wind availability change. In this way, consumers actively participate in regulation up and spinning reserve ancillary services through demand response programs. Real time pricing is also applied. The proposed model is especially useful when actual and day ahead wind forecast differ significantly. Its application is illustrated in this paper implementing the characteristics of a real resources conditions scenario in a 33 bus distribution network with 32 consumers and 66 distributed generators.

Stochastic Short-term Incentive-based Demand Response Scheduling of Load-serving Entities

In competitive electricity markets it is necessary for a profit-seeking load-serving entity (LSE) to optimally adjust the financial incentives offering the end users that buy electricity at regulated rates to reduce the consumption during high market prices. The LSE in this model manages the demand response (DR) by offering financial incentives to retail customers, in order to maximize its expected profit and reduce the risk of market power experience. The stochastic formulation is implemented into a test system where a number of loads are supplied through LSEs.

Incentive-based demand response programs designed by asset-light retailers for day-ahead market

Following the deregulation experience of retail electricity markets in most countries, the majority of the new entrants of the liberalized retail market were pure REP (retail electricity providers). These entities were subject to financial risks because of the unexpected price variations, price spikes, volatile loads and the potential for market power exertion by GENCO (generation companies). A REP can manage the market risks by employing the DR (demand response) programs and using its' generation and storage assets at the distribution network to serve the customers. The proposed model suggests how a REP with light physical assets, such as DG (distributed generation) units and ESS (energy storage systems), can survive in a competitive retail market. The paper discusses the effective risk management strategies for the REPs to deal with the uncertainties of the DAM (day-ahead market) and how to hedge the financial losses in the market. A two-stage stochastic programming problem is formulated. It aims to establish the financial incentive-based DR programs and the optimal dispatch of the DG units and ESSs. The uncertainty of the forecasted day-ahead load demand and electricity price is also taken into account with a scenario-based approach. The principal advantage of this model for REPs is reducing the risk of financial losses in DAMs, and the main benefit for the whole system is market power mitigation by virtually increasing the price elasticity of demand and reducing the peak demand.

Cost Allocation Model for Distribution Networks Considering High Penetration of Distributed Energy Resources

The high penetration of distributed energy resources (DER) in distribution networks and the competitiveenvironment of electricity markets impose the use of new approaches in several domains. The networkcost allocation, traditionally used in transmission networks, should be adapted and used in the distribu-tion networks considering the specifications of the connected resources. The main goal is to develop afairer methodology trying to distribute the distribution network use costs to all players which are usingthe network in each period. In this paper, a model considering different type of costs (fixed, losses, andcongestion costs) is proposed comprising the use of a large set of DER, namely distributed generation(DG), demand response (DR) of direct load control type, energy storage systems (ESS), and electric vehi-cles with capability of discharging energy to the network, which is known as vehicle-to-grid (V2G). Theproposed model includes three distinct phases of operation. The first phase of the model consists in aneconomic dispatch based on an AC optimal power flow (AC-OPF); in the second phase Kirschen’s andBialek’s tracing algorithms are used and compared to evaluate the impact of each resource in the net-work. Finally, the MW-mile method is used in the third phase of the proposed model. A distributionnetwork of 33 buses with large penetration of DER is used to illustrate the application of the proposedmodel.

Indicadores de qualidade para a contratualização de cuidados paliativos

RESUMO - Âmbito e objectivos: O presente trabalho incide sobre a área dos cuidados paliativos, nomeadamente, visa contribuir para uma maior efectividade do processo de aquisição e acompanhamento deste tipo de cuidados. Neste contexto, e como objectivo principal do estudo, foram identificados os indicadores chave, na vertente da qualidade, indispensáveis para a conceptualização de um modelo de contratualização e, consequentemente, para assegurar a monitorização, acompanhamento e avaliação da actividade realizada. Método e metodologias: Numa primeira fase, foi conduzida uma pesquisa documental tendente ao levantamento dos indicadores, na dimensão da qualidade, em utilização nos cuidados paliativos em vários países, tendo sido escolhidos aqueles que apresentavam indicadores já validados, designadamente, o Canadá, Reino Unido, Austrália, Espanha e EUA. Desta forma, foram seleccionados os indicadores comuns aos vários países estudados, para efeitos de discussão e consensualização, no âmbito de uma Técnica de Grupo Nominal, passíveis de integrarem um modelo de contratualização nesta área em Portugal. Apresentação e discussão de resultados: Da pesquisa documental resultaram 188 indicadores na dimensão qualidade, em utilização nos países estudados, tendo sido identificados 19 indicadores comuns. Estes indicadores foram submetidos a discussão e consensualização em reunião de peritos, tendo sido hierarquizados os sete indicadores mais adequados para a contratualização em cuidados paliativos: composição de uma equipa interdisciplinar; capacidade de resposta doentes tratados/pedido de acesso; avaliação inicial e periódica das necessidades (oito domínios); acessibilidade farmacológica; congruência entre os cuidados prestados e os desejados; prática regular de reuniões multidisciplinares; conferência familiar, pelo menos 2 vezes. Conclusões: No panorama nacional, não se conhecem indicadores unanimemente ratificados como adequados à avaliação da efectividade, qualidade e eficiência dos cuidados paliativos. Por outro lado, atento o objectivo do presente trabalho, a informação recolhida a nível internacional devolveu indicadores aplicáveis maioritariamente num contexto da avaliação da prestação dos cuidados paliativos, e Indicadores de Qualidade para a Contratualização de Cuidados Paliativos em Portugal x/ 93 não tanto num contexto de um processo de contratualização efectivo. Assim, partindo destes indicadores, em utilização nos vários países estudados, o estudo permitiu identificar sete indicadores considerados como adequados para a contratualização destes cuidados, em Portugal. -------------- ABSTRACT - Scope and objectives: This work focuses on the palliative care area, in particular, aims to contribute to greater effectiveness of the monitoring and procurement process of this type of care. In this context, as the main objective of the study, key indicators were identified regarding the quality issue, crucial to the conceptualization of a contracting model, and consequently to ensure the monitoring, supervising and evaluating of the undertaken activities. Method and methodology: Initially, a documentary research was held. That research aimed to surveying the indicators in their dimension of quality, regarding their use in palliative care throughout several countries. The chosen countries already had validated indicators, namely, Canada, United Kingdom , Australia, Spain and the USA. Thus, the indicators selected were common to all the above mentioned countries, for discussion purposes and agreement, as part of a Nominal Group Technique, that could integrate a model of contracting in this area in Portugal. Presentation and result discussion: The documentary research resulted in 188 quality indicators in use in the referred countries, 19 of those indicators were common to all countries. These indicators were submitted for discussion and agreement at a meeting of experts, having been ranked the seven most appropriate indicators for palliative care contracting: composition of an interdisciplinary team; response ability to the patients / access requests, initial and periodic assessment of the needs (eight areas), pharmacology accessibility; congruence between the desired care and its effective provision and regular practice of multidisciplinary meetings, family conferences, at least two times. Conclusions: In the national scene, unanimously ratified as suitable indicators to assess the effectiveness, efficiency and quality of palliative care are unknown. On other hand, given the objective of this work, the international collection of information has given applicable indicators mostly in the context of assessing the provision of palliative care, rather than an effective contracting process context. Thus, based on these indicators in use in the studied countries, the study itself identified seven indicators considered appropriate for the contracting of such care in Portugal.

Natural antioxidants extraction and their incorporation into model pharmaceutical systems

Dissertation to obtain a Master Degree in Biotechnology

McCoy cell line as a possible model containing CD4+ receptors for the study of HIV-1 replication

Several studies have recently shown the use of recombinant rabies virus as potential vector-viral vaccine for HIV-1. The sequence homology between gp 120 and rabies virus glycoprotein has been reported. The McCoy cell line has therefore been used to show CD4+ or CD4+ like receptors. Samples of HIV-1 were isolated, when plasma of HIV-1 positive patients was inoculated in the McCoy cell line. The virus infection was then studied during successive virus passages. The proteins released in the extra cellular medium were checked for protein activity, by exposure to SDS Electrophoresis and blotting to nitro-cellulose filter, then reacting with sera of HIV positive and negative patients. Successive passages were performed, and showed viral replication, membrane permeabilization, the syncytium formation, and the cellular lysis (cytopathic effect). Flow cytometry analysis shows clear evidence that CD4+ receptors are present in this cell line, which enhances the likelihood of easy isolation and replication of HIV. The results observed allow the use of this cell line as a possible model for isolating HIV, as well as for carrying out studies of the dynamics of viral infection in several situations, including exposure to drugs in pharmacological studies, and possibly studies and analyses of the immune response in vaccine therapies.

Nonlinear dynamics of the patient’s response to drug effect during general anesthesia

In today’s healthcare paradigm, optimal sedation during anesthesia plays an important role both in patient welfare and in the socio-economic context. For the closed-loop control of general anesthesia, two drugs have proven to have stable, rapid onset times: propofol and remifentanil. These drugs are related to their effect in the bispectral index, a measure of EEG signal. In this paper wavelet time–frequency analysis is used to extract useful information from the clinical signals, since they are time-varying and mark important changes in patient’s response to drug dose. Model based predictive control algorithms are employed to regulate the depth of sedation by manipulating these two drugs. The results of identification from real data and the simulation of the closed loop control performance suggest that the proposed approach can bring an improvement of 9% in overall robustness and may be suitable for clinical practice.

A system model and stack for the parallelization of time-critical applications on many-core architectures

3rd Workshop on High-performance and Real-time Embedded Systems (HIRES 2015). 21, Jan, 2015. Amsterdam, Netherlands.