2,085 research outputs found
Barreiras e facilitadores da adesão em intervenções psicológicas baseadas na internet com adolescentes: uma revisão sistemática
Orientação: Diogo LamelaA investigação tem vindo a demonstrar alguma evidência empÃrica acerca do potencial
das intervenções psicológicas mediadas pela internet/tecnologia na promoção da saúde mental
em adolescentes. Contudo, pouco se sabe em relação a potenciais barreiras e facilitadores
identificados pelos adolescentes na adesão a este tipo de intervenções. Desta forma, esta revisão
sistemática pretendeu rever sistematicamente a investigação produzida até ao momento sobre
estas variáveis clÃnicas, bem como potenciais moderadores associados. Foram triados artigos de
uma base de dados (Web of Science), publicados entre janeiro de 2008 a janeiro de 2019, de
modo a selecionar estudos que analisavam, quantitativamente, barreiras ou facilitadores
percebidos à adesão em adolescentes (dos 12 aos 18 anos). Dos 2220 artigos triados
inicialmente, cinco cumpriram os critérios de inclusão. Foram identificadas barreiras
relacionadas com fatores pessoais e internos (e.g., esquecimento, desinteresse), design e
conteúdo dos programas (e.g., dúvidas quanto à relevância e utilidade do próprio programa,
problemas de utilização ou compreensão do conteúdo), e a privacidade e estigma. Foram
identificados como facilitadores da adesão, a natureza interativa das intervenções digitais. Não
foram identificados moderadores nos estudos incluÃdos. Implicações para a prática clÃnica e
estudos futuros foram discutidos. Será importante que estudos futuros explorem, de forma mais
rigorosa, algumas das variáveis anteriormente mencionadas, bem como moderadores e/ou
caraterÃsticas mais especificas, com o objetivo de adaptar os programas de intervenção
online/digitais disponÃveis ou futuros, tornando-os mais adequados para os adolescentes como
população-alvo.Research has been demonstrating some empirical evidence about the potential of
internet/technology mediated psychological interventions in promoting mental health in
adolescents. However, little is known about potential barriers and facilitators identified by
adolescents in adhering to this type of intervention. Thus, this systematic review aimed to
systematically review the research produced so far on these clinical variables, as well as
potential associated moderators. Articles from a database (Web of Science), published from
January 2008 to January 2019, were screened to select studies that quantitatively analyzed
perceived barriers or facilitators of adherence in adolescents (12 to 18 years). Of the 2220
articles initially screened, five met the inclusion criteria. Barriers related to personal and internal
factors (e.g., forgetfulness, disinterest), program design and content (e.g., doubts about the
relevance and usefulness of the program itself, problems of use or understanding of the content),
and privacy and stigma have been identified. Adherence facilitators have identified the
interactive nature of digital interventions. No moderators were identified in the included studies.
Implications for clinical practice and future studies were discussed. It will be important for
future studies to more accurately explore some of the variables mentioned above, as well as
more specific moderators and/or characteristics, in order to adapt available or future
online/digital intervention programs, making them more suitable for adolescents as the target
population
Evaluation of methods for the reconstruction of specific models from omics data
Recent efforts have allowed the development of genome-scale metabolic models for several organisms, including humans. These models have been used to predict cellular metabolism under the framework of constraint-based modeling. The application in health related research has spanned the issues of drug discovery, biomarker identification and targeting diseases such as cancer or Alzheimer. However, the human organism includes several cell types, each one with a different metabolic profile and functions. So, it is imperative to develop tissue-specific metabolic models. This challenge was addressed by several approaches, namely the Model-Building Algorithm, Metabolic Context specificity Assessed by Deterministic Reaction Evaluation and Task-driven Integrative Network Inference for Tissues methods. All these approaches use a generic model as a template and integrate evidences from omics data, literature and/or network analysis to infer the tissue specific metabolic model. Nevertheless, their results have not yet been adequately and critically evaluated and compared. We analysed the consistency between several omics data sources and reconstructed metabolic models of hepatocytes using different methods and distinct data sources as inputs. The results show that omics data sources have a poor overlapping and, in some cases, are contradictory. Additionally, the hepatocyte metabolic models generated are dependent on the combination of method and omics data source. Finally, we conclude that reliable methods for a priori omics data integration are required to support human cells models reconstruction
Computational tools for strain optimization by adding reactions
This paper introduces a new plug-in for the OptFlux Metabolic Engineering
platform, aimed at finding suitable sets of reactions to add to the genomes of microbes
(wild type strain), as well as finding complementary sets of deletions, so that
the mutant becomes able to overproduce compounds with industrial interest, while
preserving their viability. The optimization methods used are Evolutionary Algorithms
and Simulated Annealing. The usefulness of this plug-in is demonstrated by
a case study, regarding the production of vanillin by the bacterium E. coli
Estados TrombofÃlicos no doente com cancro. Incidência, profilaxia, tratamento e perpetivas futuras
In silico strain optimization by adding reactions to metabolic models
Nowadays, the concerns about the environment and the needs to increase the productivity at low costs, demand for the search of new ways to produce compounds with industrial interest. Based on the increasing knowledge of biological processes, through genome sequencing projects, and high-throughput experimental techniques as well as the available computational tools, the use of microorganisms has been considered as an approach to produce desirable compounds. However, this usually requires to manipulate these organisms by genetic engineering and/ or changing the enviromental conditions to make the production of these compounds possible. In many cases, it is necessary to enrich the genetic material of those microbes with hereologous pathways from other species and consequently adding the potential to produce novel compounds. This paper introduces a new plug-in for the OptFlux Metabolic Engineering platform, aimed at finding suitable sets of reactions to add to the genomes of selected microbes (wild type strain), as well as finding complementary sets of deletions, so that the mutant becomes able to overproduce compounds with industrial interest, while preserving their viability. The necessity of adding reactions to the metabolic model arises from existing gaps in the original model or motivated by the productions of new compounds by the organism. The optimization methods used are metaheuristics such as Evolutionary Algorithms and Simulated Annealing. The usefulness of this plug-in is demonstrated by a case study, regarding the production of vanillin by the bacterium E. coli.This work is supported by project PTDC/EIA-EIA/115176/2009, funded by Portuguese FCT and Programa COMPETE
Customer relationship management at Sport Lisboa e Benfica: football customer segmentation
The purpose of this study is to consolidate the knowledge and learning from the field lab at
SL Benfica and propose a conceptual framework for customer-based lifecycle segmentation that
suits the club’s needs and its customer base. Relevant customer relationship management and
segmentation literature was reviewed and served as the basis for the proposed segmentation method
supported by 78 qualitative semi-structured interviews with Benfica supporters. Benfica needs to
improve its targeting and marketing efforts and realize the true potential behind certain segments of
customers within its database by applying a customer-based lifecycle segmentation technique as
proposed in this study
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