21 resultados para Frailty phenotype


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O crescimento da população idosa impõe o desenvolvimento de serviços de qualidade orientados para as necessidades comuns desta faixa etária. A área dos cuidados continuados corresponde a um segmento em crescimento com um forte potencial de desenvolvimento no que concerne ao domínio dos sistemas de informação (SI). O presente trabalho pressupõe o acompanhamento do processo de integração de um SI de uma Unidade Hospitalar (UH) numa Unidade de Cuidados Continuados (UCC) para idosos. A análise envolveu o recurso à Teoria Actor-network (ANT), enquanto posicionamento teórico de relevo para o desenvolvimento de SI. Esta teoria coloca, equitativamente, em destaque os factores humano e não humano como concorrentes para o sucesso no desenvolvimento de um SI. O processo em destaque neste trabalho envolveu a análise compreensiva dos SI das unidades de saúde envolvidas; monitorização e descrição do processo de integração do SI de inspiração hospitalar na UCC; avaliação do resultado final; estabelecimento de requisitos fundamentais para o desenho de um SI adaptado a uma organização prestadora de cuidados continuados a idosos. Estas etapas foram desenvolvidas tendo por base a concretização de 3 ciclos, integradores dos conceitos da ANT com o processo de Engenharia de Requisitos: Ciclo 1 - análise do sistema sócio-técnico; Ciclo 2 – desenho do novo sistema sócio-técnico; Ciclo 3 – transformação da rede sócio-técnica. A metodologia inerente ao processo envolveu a análise documental, realização de notas de campo, entrevista e questionário. Os requisitos são apresentados através da conceptualização de um SI denominado Gestão de Cuidados Residenciais (GCR). Conclui-se, que para que um SI resulte com eficácia, eficiência e efetividade para uma organização, deverá revelar-se adaptado ao propósito e missão da organização em causa, sob pena de induzir fragilidade ao ciclo operacional e ao modelo de gestão de informação.

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Prostate cancer (PCa) is a major cause of cancer-related morbidity and mortality worldwide. Although early disease is often efficiently managed therapeutically, available options for advanced disease are mostly ineffective. Aberrant DNA methylation associated with gene-silencing of cancer-related genes is a common feature of PCa. Therefore, DNA methylation inhibitors might constitute an attractive alternative therapy. Herein, we evaluated the anti-cancer properties of hydralazine, a non-nucleoside DNA methyltransferases (DNMT) inhibitor, in PCa cell lines. In vitro assays showed that hydralazine exposure led to a significant dose and time dependent growth inhibition, increased apoptotic rate and decreased invasiveness. Furthermore, it also induced cell cycle arrest and DNA damage. These phenotypic effects were particularly prominent in DU145 cells. Following hydralazine exposure, decreased levels of DNMT1, DNMT3a and DNMT3b mRNA and DNMT1 protein were depicted. Moreover, a significant decrease in GSTP1, BCL2 and CCND2 promoter methylation levels, with concomitant transcript re-expression, was also observed. Interestingly, hydralazine restored androgen receptor expression, with upregulation of its target p21 in DU145 cell line. Protein array analysis suggested that blockage of EGF receptor signaling pathway is likely to be the main mechanism of hydralazine action in DU145 cells. Our data demonstrate that hydralazine attenuated the malignant phenotype of PCa cells, and might constitute a useful therapeutic tool.

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Since the discovery of the first penicillin bacterial resistance to β-lactam antibiotics has spread and evolved promoting new resistances to pathogens. The most common mechanism of resistance is the production of β-lactamases that have spread thorough nature and evolve to complex phenotypes like CMT type enzymes. New antibiotics have been introduced in clinical practice, and therefore it becomes necessary a concise summary about their molecular targets, specific use and other properties. β-lactamases are still a major medical concern and they have been extensively studied and described in the scientific literature. Several authors agree that Glu166 should be the general base and Ser70 should perform the nucleophilic attack to the carbon of the carbonyl group of the β-lactam ring. Nevertheless there still is controversy on their catalytic mechanism. TEMs evolve at incredible pace presenting more complex phenotypes due to their tolerance to mutations. These mutations lead to an increasing need of novel, stronger and more specific and stable antibiotics. The present review summarizes key structural, molecular and functional aspects of ESBL, IRT and CMT TEM β-lactamases properties and up to date diagrams of the TEM variants with defined phenotype. The activity and structural characteristics of several available TEMs in the NCBI-PDB are presented, as well as the relation of the various mutated residues and their specific properties and some previously proposed catalytic mechanisms.

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Background: Prostate cancer (PCa), a highly incident and heterogeneous malignancy, mostly affects men from developed countries. Increased knowledge of the biological mechanisms underlying PCa onset and progression are critical for improved clinical management. MicroRNAs (miRNAs) deregulation is common in human cancers, and understanding how it impacts in PCa is of major importance. MiRNAs are mostly downregulated in cancer, although some are overexpressed, playing a critical role in tumor initiation and progression. We aimed to identify miRNAs overexpressed in PCa and subsequently determine its impact in tumorigenesis. Results: MicroRNA expression profiling in primary PCa and morphological normal prostate (MNPT) tissues identified 17 miRNAs significantly overexpressed in PCa. Expression of three miRNAs, not previously associated with PCa, was subsequently assessed in large independent sets of primary tumors, in which miR-182 and miR-375 were validated, but not miR-32. Significantly higher expression levels of miR-375 were depicted in patients with higher Gleason score and more advanced pathological stage, as well as with regional lymph nodes metastases. Forced expression of miR-375 in PC-3 cells, which display the lowest miR-375 levels among PCa cell lines, increased apoptosis and reduced invasion ability and cell viability. Intriguingly, in 22Rv1 cells, which displayed the highest miR-375 expression, knockdown experiments also attenuated the malignant phenotype. Gene ontology analysis implicated miR-375 in several key pathways deregulated in PCa, including cell cycle and cell differentiation. Moreover, CCND2 was identified as putative miR-375 target in PCa, confirmed by luciferase assay. Conclusions: A dual role for miR-375 in prostate cancer progression is suggested, highlighting the importance of cellular context on microRNA targeting.

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Previous experiments revealed that DHH1, a RNA helicase involved in the regulation of mRNA stability and translation, complemented the phenotype of a Saccharomyces cerevisiae mutant affected in the expression of genes coding for monocarboxylic-acids transporters, JEN1 and ADY2 (Paiva S, Althoff S, Casal M, Leao C. FEMS Microbiol Lett, 1999, 170∶301–306). In wild type cells, JEN1 expression had been shown to be undetectable in the presence of glucose or formic acid, and induced in the presence of lactate. In this work, we show that JEN1 mRNA accumulates in a dhh1 mutant, when formic acid was used as sole carbon source. Dhh1 interacts with the decapping activator Dcp1 and with the deadenylase complex. This led to the hypothesis that JEN1 expression is post-transcriptionally regulated by Dhh1 in formic acid. Analyses of JEN1 mRNAs decay in wild-type and dhh1 mutant strains confirmed this hypothesis. In these conditions, the stabilized JEN1 mRNA was associated to polysomes but no Jen1 protein could be detected, either by measurable lactate carrier activity, Jen1-GFP fluorescence detection or western blots. These results revealed the complexity of the expression regulation of JEN1 in S. cerevisiae and evidenced the importance of DHH1 in this process. Additionally, microarray analyses of dhh1 mutant indicated that Dhh1 plays a large role in metabolic adaptation, suggesting that carbon source changes triggers a complex interplay between transcriptional and post-transcriptional effects.

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High-content analysis has revolutionized cancer drug discovery by identifying substances that alter the phenotype of a cell, which prevents tumor growth and metastasis. The high-resolution biofluorescence images from assays allow precise quantitative measures enabling the distinction of small molecules of a host cell from a tumor. In this work, we are particularly interested in the application of deep neural networks (DNNs), a cutting-edge machine learning method, to the classification of compounds in chemical mechanisms of action (MOAs). Compound classification has been performed using image-based profiling methods sometimes combined with feature reduction methods such as principal component analysis or factor analysis. In this article, we map the input features of each cell to a particular MOA class without using any treatment-level profiles or feature reduction methods. To the best of our knowledge, this is the first application of DNN in this domain, leveraging single-cell information. Furthermore, we use deep transfer learning (DTL) to alleviate the intensive and computational demanding effort of searching the huge parameter's space of a DNN. Results show that using this approach, we obtain a 30% speedup and a 2% accuracy improvement.