21 resultados para multivariate


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O estudo teve como objectivo comparar o impacto do estigma e do bem-estar subjectivo em pessoas com diferentes doenças crónicas. Foram avaliados 729 doentes, recrutados em hospitais de Portugal, que após o diagnóstico retomaram a sua vida normal. Controlando para um conjunto de variáveis sócio-demográficas e clínicas, a aplicação de Modelos de Análise de Covariância Multivariada, permitiu verificar diferenças significativas apenas para a percepção do estigma entre os grupos de doenças crónicas. Pessoas com obesidade, epilepsia e esclerose múltipla referem mais estigma e pessoas com diabetes tipo1 e miastenia gravis referem menos estigma.

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Doutoramento em Economia Financeira e Contabilidade

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Human mesenchymal stem/stromal cells (MSCs) have received considerable attention in the field of cell-based therapies due to their high differentiation potential and ability to modulate immune responses. However, since these cells can only be isolated in very low quantities, successful realization of these therapies requires MSCs ex-vivo expansion to achieve relevant cell doses. The metabolic activity is one of the parameters often monitored during MSCs cultivation by using expensive multi-analytical methods, some of them time-consuming. The present work evaluates the use of mid-infrared (MIR) spectroscopy, through rapid and economic high-throughput analyses associated to multivariate data analysis, to monitor three different MSCs cultivation runs conducted in spinner flasks, under xeno-free culture conditions, which differ in the type of microcarriers used and the culture feeding strategy applied. After evaluating diverse spectral preprocessing techniques, the optimized partial least square (PLS) regression models based on the MIR spectra to estimate the glucose, lactate and ammonia concentrations yielded high coefficients of determination (R2 ≥ 0.98, ≥0.98, and ≥0.94, respectively) and low prediction errors (RMSECV ≤ 4.7%, ≤4.4% and ≤5.7%, respectively). Besides PLS models valid for specific expansion protocols, a robust model simultaneously valid for the three processes was also built for predicting glucose, lactate and ammonia, yielding a R2 of 0.95, 0.97 and 0.86, and a RMSECV of 0.33, 0.57, and 0.09 mM, respectively. Therefore, MIR spectroscopy combined with multivariate data analysis represents a promising tool for both optimization and control of MSCs expansion processes.