Woolly hair nevus: case report and review of literature

Woolly hair nevus consists of a patch of curly and hypopigmented hair that is restricted to an area of the scalp. It is usually benign but it can be associated with other systemic findings. Trichoscopy and dermoscopy may be useful when analyzing this entity. The authors describe a case of woolly hair nevus in a 5-year-old boy and present a review of the literature of woolly hair nevus, including classification, histopathology, associated systemic findings, and the recent described genetic mutations

Biomarkers discovery for prognosis of COVID-19 based on metabolomics

Thesis to obtain the Master degree in Biomedical EngineeringBackground and Goals: A novel coronavirus strain, SARS-CoV-2, emerged in late 2019, generating a viral epidemic. This new, highly transmissible strain outnumbered both SARS and MERS in terms of affected people. Symptoms of the novel virus included fever, cough, and chest pain, as well as dyspnea and bilateral lung infiltration in severe instances. Due to the relevance of the COVID pandemic, this thesis aims to develop a predictive model for the outcome of COVID-19 critically ill patients, at Intensive Care Unit (ICU) based on a metabolomic serum analysis, acquired by Fourier-transform infrared spectroscopy (FTIR) and liquid chromatography coupled to mass spectrometry (LC-MS). Methods: Two assay groups were analysed based on Fourier-transform infrared (FTIR) spectroscopy and liquid-chromatography associated to mass spectrometry (LC-MS). The first experiment aimed to evaluate the influence of two distinct metabolite extraction techniques on the samples metabolome, namely methanol and acetonitrile:methanol:water solvent mixture on 6 patients. It was conducted prediction for the outcome of these patients as well the evaluation of the sera’s metabolic profile with FTIR spectroscopic and LC-MS data. The second experiment used a larger patient sample size (n=24) and evaluated the serum metabolome extracted with acetonitrile:methanol:water protocol based on the patients’ condition, non-ventilated discharged from ICU (n=8), ventilated and deceased in ICU (n=8), and ventilated discharged from ICU (n=8), along with the development of an outcome prediction model, using metabolite analysis. Results: Methanol as a solvent for metabolite extraction resulted in extracting higher content of lipids in comparison with acetonitrile:methanol:water solvent mixture, which resulted in a higher peptide output. On the first assay, based on FTIR spectroscopy, with was possible to predict the patients’ survivability with an Area Under the Curve (AUC) of 0.98 and a CA of 0.97 regardless from the extraction method for the first assay. In the second assay, metabolites were extracted based on the acetonitrile:methanol:water protocol. For FTIR spectral data, prediction algorithms achieved a CA of 0.85 for prediction between non-ventilated and ventilated discharged patients, and 0.85 for distinction between non-ventilated discharged and ventilated deceased patients and 0.77 for distinction between ventilated discharged and ventilated deceased patients. Based on LC-MS data, it was possible to achieve CA’s of 1.00 when predicting the ventilation status between discharged patients and for non-ventilated discharged patients and outcome between non-ventilated and ventilated patients, and 0.96 for distinction between ventilated discharged patients and ventilated deceased patients. Conclusions: The metabolome extraction from serum based on acetonitrile:methanol:water protocol enabled to predict the outcome and condition regarding ventilation of COVID-19 patients in ICU. These results were obtained by two different techniques, FTIR spectroscopy and LC-MS. Therefore, serum metabolomics presented as a useful technique that could significantly contribute to a better management of critical patients, as the ones in severe status of COVID-19. Irrespective from the positive results obtained with the algorithms for predicting patient outcomes, it is crucial to note that the study samples were quite small. As a conclusion, further research is necessary to confirm the results of this study.Introdução e Objetivos: Uma nova estirpe de coronavírus, SARS-CoV-2, surgiu no final de 2019, o que gerou um surto pandémico. Esta nova variante altamente transmissível superou tanto a SARS quanto a MERS em termos de pessoas infetadas. Os sintomas deste novo vírus incluem febre, tosse e dor torácica, assim como dispneia e infiltração pulmonar bilateral em casos graves. Devido à relevância da pandemia COVID, esta tese tem como objetivo desenvolver um modelo preditivo para o prognóstico de doentes críticos COVID-19 com base em análise metabolómica por espectroscopia de infravermelho por transformada de Fourier (FTIR) e espectrometria de massa acoplada a cromatografia líquida (LC-MS) Métodos: Dois grupos de ensaio foram analisados com base em espectrometria de infravermelho por transformada de Fourier (FTIR) e espetrometria de massa acoplada a cromatografia líquida (LC-MS). A primeira experiência visou avaliar a influência de duas técnicas de extração de metabolitos no metaboloma das amostras, nomeadamente metanol e a mistura de solvente de acetronitrilo:metanol:água em 6 doentes. Foi realizada a previsão para o desfecho da doença para estes doentes assim como a avaliação do perfil metabólico do soro com recurso à espectroscopia FTIR e LC-MS. A segunda experiência utilizou uma dimensão de doentes superior (n=24) e avaliou o metaboloma das amostras de soro extraídas com acetonitrilo:metanol:água com base no estado dos doentes, sem necessidade de ventilação e com alta da UCI (n=8), ventilados e com óbito na UCI (n=8) e ventilados com alta da UCI (n=8), juntamente com o desenvolvimento de um modelo de previsão para o desfecho da doença com os resultados da análise do metaboloma. Resultados: O metanol como solvente para a extração de metabolitos resultou na extração de um perfil mais lipídico quando comparado com a mistura de solventes de acetonitrilo:metanol:água que teve um perfil mais peptídico. No primeiro ensaio, com base na espectroscopia FTIR, foi possível prever a sobrevivência dos pacientes com uma área sob a curva (AUC) de 0,98 e uma Precisão de Classificação (CA) de 0,97, independentemente do método de extração. No segundo ensaio, foram extraídos metabolitos com base no protocolo acetonitrilo:metanol:água. No que diz respeito aos dados espectrais FTIR, os algoritmos de previsão atingiram um CA de 0,85 para previsão entre doentes não ventilados e ventilados ambos com alta da UCI, 0.85 entre doentes não-ventilados com alta e doentes ventilados com óbito na UCI, e 0.77 entre doentes ventilados com alta UCI e doentes ventilados com óbito na UCI. Com base em dados de LC-MS, foi possível obter CA's de 1,00 para a previsão entre doentes não ventilados e ventilados com alta UCI e também para doentes não ventilados e ventilados com óbito na UCI, e CA de 0.96 para a distinção entre pacientes ventilados com alta e ventilados com óbito na UCI. Conclusões: A extração do metaboloma do soro com base no protocolo acetonitrilo:metanol:água permitiu prever o desfecho da doença e a condição em relação à ventilação de pacientes com COVID-19 em contexto de UCI. Esses resultados foram obtidos por duas técnicas diferentes, espectroscopia FTIR e LC-MS. A metabolómica do soro apresentou-se como uma técnica útil que pode contribuir significativamente para uma melhor gestão de pacientes críticos, como os em estado grave de COVID-19. Independentemente dos resultados positivos obtidos com os algoritmos de previsão, é crucial notar que as amostras do estudo foram pequenas. Conclui-se a necessidade de continuar a pesquisa de modo a corroborar os resultados deste estudo.info:eu-repo/semantics/publishedVersio

Biomarkers discovery for prognosis of COVID-19 based on metabolomics

Mestrado em Engenharia BiomédicaThis work was supported by Instituto Politécnico de Lisboa grant IDI&CA/IPL/2020/NephoMD/ISEL and the FCT grant DSAIPA/DS/0117/2020 - PREMO - Predictive Models of COVID-19 Outcomes for Higher Risk Patients Towards a Precision Medicine.ABSTRACT - Background and Goals: A novel coronavirus strain, SARS-CoV-2, emerged in late 2019, generating a viral epidemic. This new, highly transmissible strain outnumbered both SARS and MERS in terms of affected people. Symptoms of the novel virus included fever, cough, and chest pain, as well as dyspnea and bilateral lung infiltration in severe instances. Due to the relevance of the COVID pandemic, this thesis aims to develop a predictive model for the outcome of COVID-19 critically ill patients, in Intensive Care Unit (ICU) based on a metabolomic serum analysis, acquired by Fourier-transform infrared spectroscopy (FTIR) and liquid chromatography coupled to mass spectrometry (LC-MS). Methods: Two assay groups were analyzed based on Fourier-transform infrared (FTIR) spectroscopy and liquid chromatography associated with mass spectrometry (LC-MS). The first experiment aimed to evaluate the influence of two distinct metabolite extraction techniques on the samples' metabolome, namely methanol and acetonitrile: methanol:water solvent mixture on 6 patients. It was conducted prediction for the outcome of these patients as well as the evaluation of the sera’s metabolic profile with FTIR spectroscopic and LC-MS data. The second experiment used a larger patient sample size (n=24) and evaluated the serum metabolome extracted with acetonitrile:methanol:water protocol based on the patient’s condition, non-ventilated discharged from ICU (n=8), ventilated and deceased in ICU (n=8), and ventilated discharged from ICU (n=8), along with the development of an outcome prediction model, using metabolite analysis. Results: Methanol as a solvent for metabolite extraction resulted in extracting a higher content of lipids in comparison with acetonitrile:methanol:water solvent mixture, which resulted in a higher peptide output. On the first assay, based on FTIR spectroscopy, with was possible to predict the patients’ survivability with an Area Under the Curve (AUC) of 0.98 and a CA of 0.97 regardless of the extraction method for the first assay. In the second assay, metabolites were extracted based on the acetonitrile:methanol:water protocol. For FTIR spectral data, prediction algorithms achieved a CA of 0.85 for the prediction between non-ventilated and ventilated discharged patients, 0.85 for the distinction between non-ventilated discharged and ventilated deceased patients, and 0.77 for the distinction between ventilated discharged and ventilated deceased patients. Based on LC-MS data, it was possible to achieve CA’s of 1.00 when predicting the ventilation status between discharged patients and for non-ventilated discharged patients and outcome between non-ventilated and ventilated patients, and 0.96 for distinction between ventilated discharged patients and ventilated deceased patients. Conclusions: The metabolome extraction from serum based on acetonitrile:methanol:water protocol enabled to prediction of the outcome and condition regarding ventilation of COVID-19 patients in the ICU. These results were obtained by two different techniques, FTIR spectroscopy and LC-MS. Therefore, serum metabolomics presented as a useful technique that could significantly contribute to better management of critical patients, such as the ones with severe status of COVID-19. Irrespective of the positive results obtained with the algorithms for predicting patient outcomes, it is crucial to note that the study samples were quite small. As a conclusion, further research is necessary to confirm the results of this study.RESUMO - Introdução e Objetivos: Uma nova estirpe de coronavírus, SARS-CoV-2, surgiu no final de 2019, o que gerou um surto pandémico. Esta nova variante altamente transmissível superou tanto a SARS quanto a MERS em termos de pessoas infetadas. Os sintomas deste novo vírus incluem febre, tosse e dor torácica, assim como dispneia e infiltração pulmonar bilateral em casos graves. Devido à relevância da pandemia COVID, esta tese tem como objetivo desenvolver um modelo preditivo para o prognóstico de doentes críticos COVID-19 com base em análise metabolómica por espectroscopia de infravermelho por transformada de Fourier (FTIR) e espectrometria de massa acoplada a cromatografia líquida (LC-MS) Métodos: Dois grupos de ensaio foram analisados com base em espectrometria de infravermelho por transformada de Fourier (FTIR) e espetrometria de massa acoplada a cromatografia líquida (LC-MS). A primeira experiência visou avaliar a influência de duas técnicas de extração de metabolitos no metaboloma das amostras, nomeadamente metanol e a mistura de solvente de acetronitrilo:metanol:água em 6 doentes. Foi realizada a previsão para o desfecho da doença para estes doentes assim como a avaliação do perfil metabólico do soro com recurso à espectroscopia FTIR e LC-MS. A segunda experiência utilizou uma dimensão de doentes superior (n=24) e avaliou o metaboloma das amostras de soro extraídas com acetonitrilo:metanol:água com base no estado dos doentes, sem necessidade de ventilação e com alta da UCI (n=8), ventilados e com óbito na UCI (n=8) e ventilados com alta da UCI (n=8), juntamente com o desenvolvimento de um modelo de previsão para o desfecho da doença com os resultados da análise do metaboloma. Resultados: O metanol como solvente para a extração de metabolitos resultou na extração de um perfil mais lipídico quando comparado com a mistura de solventes de acetonitrilo:metanol:água que teve um perfil mais peptídico. No primeiro ensaio, com base na espectroscopia FTIR, foi possível prever a sobrevivência dos pacientes com uma área sob a curva (AUC) de 0,98 e uma Precisão de Classificação (CA) de 0,97, independentemente do método de extração. No segundo ensaio, foram extraídos metabolitos com base no protocolo acetonitrilo:metanol:água. No que diz respeito aos dados espectrais FTIR, os algoritmos de previsão atingiram um CA de 0,85 para previsão entre doentes não ventilados e ventilados ambos com alta da UCI, 0.85 entre doentes não-ventilados com alta e doentes ventilados com óbito na UCI, e 0.77 entre doentes ventilados com alta UCI e doentes ventilados com óbito na UCI. Com base em dados de LC-MS, foi possível obter CA's de 1,00 para a previsão entre doentes não ventilados e ventilados com alta UCI e também para doentes não ventilados e ventilados com óbito na UCI, e CA de 0.96 para a distinção entre pacientes ventilados com alta e ventilados com óbito na UCI. Conclusões: A extração do metaboloma do soro com base no protocolo acetonitrilo:metanol:água permitiu prever o desfecho da doença e a condição em relação à ventilação de pacientes com COVID-19 em contexto de UCI. Esses resultados foram obtidos por duas técnicas diferentes, espectroscopia FTIR e LC-MS. A metabolómica do soro apresentou-se como uma técnica útil que pode contribuir significativamente para uma melhor gestão de pacientes críticos, como os em estado grave de COVID-19. Independentemente dos resultados positivos obtidos com os algoritmos de previsão, é crucial notar que as amostras do estudo foram pequenas. Conclui-se a necessidade de continuar a pesquisa de modo a corroborar os resultados deste estudo.N/

Application to mobile cloud computing

Carreiro, H., & Oliveira, T. (2019). Impact of transformational leadership on the diffusion of innovation in firms: Application to mobile cloud computing. Computers in Industry, 107(May), 104-113. https://doi.org/10.1016/j.compind.2019.02.006Leadership is a key determinant for organizations to adopt innovation successfully. However, research has not explored the leadership components that impact adoption stages (initiation, adoption, and routinization). In this work, we develop and empirically test a model based on both the transformational leadership components and the stages of the diffusion of innovation theory, using PLS methods and drawing on data from 154 firms, to study the adoption of a new technology, mobile cloud computing (MCC). Components such as vision, intellectual stimulation, supportive leadership, and personal recognition are significant for the intention to adopt, while supportive leadership is a driver for both adoption and routinization. The results of our study show that leaders’ vision, combined with the capacity to consider others’ feelings and recognize others’ personal needs (both indicators of providing individual support), are strongly related with the adoption of an important IS innovation such as MCC. The present study shows that it is relevant to understand the influence of the leadership component separately on the diffusion of an innovation, rather than to keep them as just one all-encompassing construct. To the best of our knowledge, this is the first study to address the adoption of MCC in firms.authorsversionpublishe

Access to long-term credit and productivity of small and medium firms: A causal evidence

This letter assesses the impact of a variation in access to a targeted loan program from Brazil’s development bank on investment and productivity. Results suggest that eligible firms increased their relative investment rate and productivity, but results are robust only for permanent rather than temporary improvements in access to credit

Experimental validation of a bearing wear model using the directional response of the rotor-bearing system

The present work gives continuity in the analysis of the wear influence on cylindrical hydrodynamic bearings by presenting an experimental validation of the wear model previously proposed by the authors. This validation is carried on using the frequency response of the rotor-bearings system in directional coordinates. For this purpose, a test rig was assembled in order to evaluate the behavior of the rotating system when supported by hydrodynamic bearings with different wear patterns. The experimental measurements are used to validate the wear model, comparing the anisotropy influence on the experimental and numerical responses. The simulated directional frequency responses showed a good agreement with the experimental ones, demonstrating the potential of the proposed wear model in satisfactorily represent its influence on the rotor-bearings system response in the frequency range where the numerical model was validated884CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQCOORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPESFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESPNão temNão temNão te