Akkermansia muciniphila and improved metabolic health during a dietary intervention in obesity: relationship with gut microbiome richness and ecology

Objective: Individuals with obesity and type 2 diabetes differ from lean and healthy individuals in their abundance of certain gut microbial species and microbial gene richness. Abundance of Akkermansia muciniphila, a mucin-degrading bacterium, has been inversely associated with bodyfat mass and glucose intolerance in mice, but more evidence is needed in humans. The impact of diet and weight loss on this bacterial species is unknown. Our objective was to evaluate the association between fecal A. muciniphila abundance, fecal microbiome gene richness, diet, host characteristics, and their changes after calorie restriction (CR). Design: The intervention consisted of a 6-week CR period followed by a 6-week weight stabilization (WS) diet in overweight and obese adults (N=49, including 41 women). Fecal A. muciniphila abundance, fecal microbial gene richness, diet and bioclinical parameters were measured at baseline and after CR and WS. Results: At baseline A. muciniphila was inversely related to fasting glucose, waist-to-hip ratio, and subcutaneous adipocyte diameter. Subjects with higher gene richness and A. muciniphila abundance exhibited the healthiest metabolic status, particularly in fasting plasma glucose, plasma triglycerides and body fat distribution. Individuals with higher baseline A. muciniphila displayed greater improvement in insulin sensitivity markers and other clinical parameters after CR. A. muciniphila was associated with microbial species known to be related to health. Conclusion: A. muciniphila is associated with a healthier metabolic status and better clinicaloutcomes after CR in overweight/obese adults, however the interaction between gut microbiota ecology and A. muciniphila has to be taken into account.

Repeat-measures longitudinal study evaluating behavioural and gastrointestinal symptoms in children with autism before, during and after visceral osteopathic technique (VOT)

Summary: This study investigated the influence of visceral osteopathic technique (VOT) on the behaviour and gastrointestinal (GI) symptoms of children with autism using a validated questionnaire to measure outcome. Methods: The 49 recruited autistic children suffered GI symptoms and impaired social interaction and communication, but were otherwise healthy. Thirty minute VOT sessions were applied to the abdomens of the children over a 6 week period whilst their GI and behavioural parameters were recorded. Outcomes were measured using a modified Autism Research Institute Secretin Outcomes Survey Form, the ‘S.O.S Form’. Four questionnaires were completed by parents before treatment (control period), four completed during treatment (treatment period) and one completed six weeks after the last treatment (post treatment period). Subjects acted as their own controls. Results: Results from repeat ANOVA demonstrated a positive, overall significant, symptomatic improvement (p < 0.05) in ‘social behaviour and communication’ and ‘digestive signs’ subscales of the questionnaire comparing before and after VOT. Significant improvement in vomiting (p = 0.00029), poor appetite (p = 0.039) and eye contact (p = 0.035) was also demonstrated after VOT application. Discussion and conclusion: The experimental hypothesis has been supported indicating a positive effect of VOT on some of the measured GI symptoms and behavioural patterns in this group of children with autism. This data indicates that the application of VOT may be of benefit to children with autism and GI disturbance.

Smart City-Regional Governance: A 'Dual Transition'

This paper introduces the concept of ‘dual transition’ in relation to the notion of ‘smartness’ in city-regional governance. This consists of two intersecting dimensions, a broader change in political-economic and societal circumstances which surround city-regions, and a more detailed, local change towards ‘smartness’ in policy practices. Although ‘smart’ seems to have become a somewhat ubiquitous adjective in urban policy, it seeks to project policies that seek to go beyond a one-dimensional ‘growth agenda’ by addressing also the multifaceted quest for social, economic and environmental sustainability. The underlying shift in discourse, rationality and suggested policy responses in both dimensions may be captured by the concept of ‘transition’ in relation to policies and governance. Originally developed in conjunction with broad political-economic regime change, such as post-authoritarian democratisation, the idea of ‘transition’ has also been applied to the more specific concept of sustainability as ‘sustainability transition’.

Fase pré-analítica – o laboratório no papel principal_SPML 2016

O Programa Nacional de Avaliação Externa da Qualidade (PNAEQ) foi criado em 1978 como sendo uma das atribuições do Instituto Nacional de Saúde Doutor Ricardo Jorge (INSA). A sua missão é promover, organizar e coordenar programas de avaliação externa da qualidade (AEQ) para laboratórios que exerçam atividade no setor da saúde. O primeiro programa de AEQ do PNAEQ para avaliação da Fase Pré-Analítica foi distribuído em 2007. Os ensaios são pluridisciplinares, podendo incluir o envio de amostras para avaliação das condições para processamento (aceitação ou rejeição, preparação, acondicionamento), a simulação de requisições médicas, a resposta a questionários, a interpretação de casos-estudo, o levantamento de dados (auditorias ou monitorização de indicadores) ou a realização de chamadas anónimas (“cliente mistério”). O PNAEQ disponibiliza ainda 4 programas em colaboração com a Labquality (Flebotomia e POCT, Química Clínica, Microbiologia e Gases no Sangue) e 1 programa com a ECAT (Hemostase). Em 2015 e 2016, o objetivo dos programas da Fase Pré-Analítica do PNAEQ foi proporcionar o envolvimento do laboratório no processo de avaliação e monitorização da fase pré-analítica, conferindo-lhe ferramentas que lhe permitam realizar a sua autoavaliação. A fase pré-analítica é a que absorve o maior número de erros na análise de amostras biológicas, representando 40% a 70% de todas as falhas ocorridas no processamento analítico (Codagnone et al, 2014). A principal razão está na dificuldade em controlar as variáveis pré-analíticas , uma vez que esta fase envolve inúmeras atividades não automatizadas como a colheita, o manuseamento, o transporte e a preparação das amostras.

Avaliação da Qualidade Laboratorial no Processo Pré-Analítico_SPML 2016

Devido à necessidade de selecionar e monitorizar indicadores de desempenho do processo pré analítico, a nível nacional, a Sociedade Portuguesa de Química Clínica e Medicina Laboratorial implementou o grupo de trabalho neste âmbito. Na reunião pretende-se, numa discussão interativa com os participantes, apresentar os trabalhos já desenvolvidos e planear projetos futuros que sejam consensuais e com impacto direto na melhoria da qualidade nesta fase extra-analítica. Um breve questionário será distribuído no início da apresentação de modo a recolher informação para organização dos trabalhos. Os dados recolhidos serão analisados pelos responsáveis/coordenadores do grupo de trabalho que divulgarão posteriormente a metodologia a implementar. Pretende-se ainda que sejam elaboradas diretrizes, para posterior divulgação, que poderão servir de guia com o objetivo de diminuição das falhas observadas na fase pré analítica.

Boletim Epidemiológico Observações: Vol. 5 (2016), Número Especial 7, Doenças Raras

Número Especial do Boletim Epidemiológico Observações dedicado às Doenças Raras. Observações é uma publicação científica trimestral do INSA, IP, que visa contribuir para o conhecimento da saúde da população, os fatores que a influenciam, a decisão e a intervenção em Saúde Pública, assim como a avaliação do seu impacte na população portuguesa. Através do acesso público e gratuito a resultados científicos gerados por atividades de observação em saúde, monitorização e vigilância epidemiológica, é dada especial atenção à disseminação rápida de informação relevante para a resposta a temas de relevo para a saúde da população portuguesa, tendo como principal alvo todos os profissionais, investigadores e decisores intervenientes na área da Saúde Pública em Portugal.

MASGriP – a Multi-Agent Smart Grid Simulation Platform

The increasing number of players that operate in power systems leads to a more complex management. In this paper a new multi-agent platform is proposed, which simulates the real operation of power system players. MASGriP – A Multi-Agent Smart Grid Simulation Platform is presented. Several consumer and producer agents are implemented and simulated, considering real characteristics and different goals and actuation strategies. Aggregator entities, such as Virtual Power Players and Curtailment Service Providers are also included. The integration of MASGriP agents in MASCEM (Multi-Agent System for Competitive Electricity Markets) simulator allows the simulation of technical and economical activities of several players. An energy resources management architecture used in microgrids is also explained.

Typical load profiles in the smart grid context – a clustering methods comparison

The present research paper presents five different clustering methods to identify typical load profiles of medium voltage (MV) electricity consumers. These methods are intended to be used in a smart grid environment to extract useful knowledge about customer’s behaviour. The obtained knowledge can be used to support a decision tool, not only for utilities but also for consumers. Load profiles can be used by the utilities to identify the aspects that cause system load peaks and enable the development of specific contracts with their customers. The framework presented throughout the paper consists in several steps, namely the pre-processing data phase, clustering algorithms application and the evaluation of the quality of the partition, which is supported by cluster validity indices. The process ends with the analysis of the discovered knowledge. To validate the proposed framework, a case study with a real database of 208 MV consumers is used.

A multi-agent based approach for intelligent smart grid management

The spread and globalization of distributed generation (DG) in recent years has should highly influence the changes that occur in Electricity Markets (EMs). DG has brought a large number of new players to take action in the EMs, therefore increasing the complexity of these markets. Simulation based on multi-agent systems appears as a good way of analyzing players’ behavior and interactions, especially in a coalition perspective, and the effects these players have on the markets. MASCEM – Multi-Agent System for Competitive Electricity Markets was created to permit the study of the market operation with several different players and market mechanisms. MASGriP – Multi-Agent Smart Grid Platform is being developed to facilitate the simulation of micro grid (MG) and smart grid (SG) concepts with multiple different scenarios. This paper presents an intelligent management method for MG and SG. The simulation of different methods of control provides an advantage in comparing different possible approaches to respond to market events. Players utilize electric vehicles’ batteries and participate in Demand Response (DR) contracts, taking advantage on the best opportunities brought by the use of all resources, to improve their actions in response to MG and/or SG requests.

Energy efficiency analysis considering the use of an intelligent systems management in a smart home

In this abstract is presented an energy management system included in a SCADA system existent in a intelligent home. The system control the home energy resources according to the players definitions (electricity consumption and comfort levels), the electricity prices variation in real time mode and the DR events proposed by the aggregators.

Using demand response to deal with unexpected low wind power generation in the context of smart grid

Demand response is assumed an essential resource to fully achieve the smart grids operating benefits, namely in the context of competitive markets. 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 aims the minimization of the operation costs in a smart grid operated by a virtual power player. It is especially useful when actual and day ahead wind forecast differ significantly. When facing lower wind power generation than expected, RTP is used in order to minimize the impacts of such wind availability change. The proposed model application is here illustrated using the scenario of a special wind availability reduction day in the Portuguese power system (8th February 2012).

A regulatory framework for short-term stochastic maintenance outage scheduling in smart grids

The current regulatory framework for maintenance outage scheduling in distribution systems needs revision to face the challenges of future smart grids. In the smart grid context, generation units and the system operator perform new roles with different objectives, and an efficient coordination between them becomes necessary. In this paper, the distribution system operator (DSO) of a microgrid receives the proposals for shortterm (ST) planned outages from the generation and transmission side, and has to decide the final outage plans, which is mandatory for the members to follow. The framework is based on a coordination procedure between the DSO and other market players. This paper undertakes the challenge of optimization problem in a smart grid where the operator faces with uncertainty. The results show the effectiveness and applicability of the proposed regulatory framework in the modified IEEE 34- bus test system.

Day-ahead resource scheduling in smart grids considering Vehicle-to-Grid and network constraints

Energy resource scheduling becomes increasingly important, as the use of distributed resources is intensified and massive gridable vehicle use is envisaged. The present paper proposes a methodology for dayahead energy resource scheduling for smart grids considering the intensive use of distributed generation and of gridable vehicles, usually referred as Vehicle- o-Grid (V2G). This method considers that the energy resources are managed by a Virtual Power Player (VPP) which established contracts with V2G owners. It takes into account these contracts, the user´s requirements subjected to the VPP, and several discharge price steps. Full AC power flow calculation included in the model allows taking into account network constraints. The influence of the successive day requirements on the day-ahead optimal solution is discussed and considered in the proposed model. A case study with a 33 bus distribution network and V2G is used to illustrate the good performance of the proposed method.

Coordination between mid-term maintenance outage decisions and short-term security-constrained scheduling in smart distribution systems

Distribution systems are the first volunteers experiencing the benefits of smart grids. The smart grid concept impacts the internal legislation and standards in grid-connected and isolated distribution systems. Demand side management, the main feature of smart grids, acquires clear meaning in low voltage distribution systems. In these networks, various coordination procedures are required between domestic, commercial and industrial consumers, producers and the system operator. Obviously, the technical basis for bidirectional communication is the prerequisite of developing such a coordination procedure. The main coordination is required when the operator tries to dispatch the producers according to their own preferences without neglecting its inherent responsibility. Maintenance decisions are first determined by generating companies, and then the operator has to check and probably modify them for final approval. In this paper the generation scheduling from the viewpoint of a distribution system operator (DSO) is formulated. The traditional task of the DSO is securing network reliability and quality. The effectiveness of the proposed method is assessed by applying it to a 6-bus and 9-bus distribution system.

An integrated approach for distributed energy resource short term scheduling in smart grids considering realistic power system simulation

The large increase of distributed energy resources, including distributed generation, storage systems and demand response, especially in distribution networks, makes the management of the available resources a more complex and crucial process. With wind based generation gaining relevance, in terms of the generation mix, the fact that wind forecasting accuracy rapidly drops with the increase of the forecast anticipation time requires to undertake short-term and very short-term re-scheduling so the final implemented solution enables the lowest possible operation costs. This paper proposes a methodology for energy resource scheduling in smart grids, considering day ahead, hour ahead and five minutes ahead scheduling. The short-term scheduling, undertaken five minutes ahead, takes advantage of the high accuracy of the very-short term wind forecasting providing the user with more efficient scheduling solutions. The proposed method uses a Genetic Algorithm based approach for optimization that is able to cope with the hard execution time constraint of short-term scheduling. Realistic power system simulation, based on PSCAD , is used to validate the obtained solutions. The paper includes a case study with a 33 bus distribution network with high penetration of distributed energy resources implemented in PSCAD .