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ObjectivesAnxiety and depression are relevant comorbidities in asthma, but, in Portugal and Spain, data on this topic are scarce. We assessed, in patients with asthma, the frequency of anxiety and depression using the Hospital Anxiety and Depression Scale (HADS) and the European Quality of Life Five Dimension Questionnaire (EQ-5D); the level of agreement between these questionnaires, and the factors associated with these symptoms.MethodsThis is a secondary analysis of the INSPIRERS studies. A total of 614 adolescents and adults with persistent asthma (32.6±16.9 years, 64.7% female) were recruited from 30 primary care centres and 32 allergy, pulmonology and paediatric clinics. Demographic and clinical characteristics, HADS and EQ-5D were collected. A score ≥8 on Hospital Anxiety and Depression Scale-Anxiety/Hospital Anxiety and Depression Scale-Depression or a positive answer to EQ-5D item 5 indicated the presence of these symptoms. Agreement was determined by Cohen’s kappa. Two multivariable logistic regressions were built.ResultsAccording to HADS, 36% of the participants had symptoms of anxiety and 12% of depression. According to EQ-5D, 36% of the participants had anxiety/depression. The agreement between questionnaires in identifying anxiety/depression was moderate (k=0.55, 95% CI 0.48 to 0.62). Late asthma diagnosis, comorbidities and female gender were predictors of anxiety/depression, while better asthma control, health-related quality of life and perception of health were associated with lower odds for anxiety/depression.ConclusionAt least 1/3 of the patients with persistent asthma experience symptoms of anxiety/depression, showing the relevance of screening these disorders in patients with asthma. EQ-5D and HADS questionnaires showed a moderate agreement in the identification of anxiety/depression symptoms. The identified associated factors need to be further investigated in long-term studies.

SARS-CoV-2 triggered a worldwide pandemic disease, COVID-19, for which an effective treatment has not yet been settled. Among the most promising targets to fight this disease is SARS-CoV-2 main protease (Mpro), which has been extensively studied in the last few months. There is an urgency for developing effective computational protocols that can help us tackle these key viral proteins. Hence, we have put together a robust and thorough pipeline of in silico protein–ligand characterization methods to address one of the biggest biological problems currently plaguing our world. These methodologies were used to characterize the interaction of SARS-CoV-2 Mpro with an α-ketoamide inhibitor and include details on how to upload, visualize, and manage the three-dimensional structure of the complex and acquire high-quality figures for scientific publications using PyMOL (Protocol 1); perform homology modeling with MODELLER (Protocol 2); perform protein–ligand docking calculations using HADDOCK (Protocol 3); run a virtual screening protocol of a small compound database of SARS-CoV-2 candidate inhibitors with AutoDock 4 and AutoDock Vina (Protocol 4); and, finally, sample the conformational space at the atomic level between SARS-CoV-2 Mpro and the α-ketoamide inhibitor with Molecular Dynamics simulations using GROMACS (Protocol 5). Guidelines for careful data analysis and interpretation are also provided for each Protocol.

Freedom is an important fundamental right, foreseen in the Federal Constitution of 1988, which can only be affected in the exhaustive hypotheses described by the Constitution itself. However, in relation to the military police, freedom suffers serious violations, without observing the constitutionally stipulated parameters. These are disciplinary punishments, which restrict the freedom of military police officers through administrative means, without any provision in the law. In addition, there are several aspects of these measures that indicate their inadequacy in relation to the current constitutional order, both formal and material. In any case, the law no 13.967/2019 introduces important changes in this context, with the objective of extinguishing the private measures of freedom, making sure that in fact the fundamental right to freedom of military police is respected.

Understanding protein–protein interactions (PPIs) is fundamental to describe and to characterize the formation of biomolecular assemblies, and to establish the energetic principles underlying biological networks. One key aspect of these interfaces is the existence and prevalence of hot-spots (HS) residues that, upon mutation to alanine, negatively impact the formation of such protein–protein complexes. HS have been widely considered in research, both in case studies and in a few large-scale predictive approaches. This review aims to present the current knowledge on PPIs, providing a detailed understanding of the microspecifications of the residues involved in those interactions and the characteristics of those defined as HS through a thorough assessment of related field-specific methodologies. We explore recent accurate artificial intelligence-based techniques, which are progressively replacing well-established classical energy-based methodologies. This article is categorized under: Data Science > Databases and Expert Systems Structure and Mechanism > Computational Biochemistry and Biophysics Molecular and Statistical Mechanics > Molecular Interactions.

Text mining (TM) is a semi-automatized, multi-step process, able to turn unstructured into structured data. TM relevance has increased upon machine learning (ML) and deep learning (DL) algorithms’ application in its various steps. When applied to biomedical literature, text mining is named biomedical text mining and its specificity lies in both the type of analyzed documents and the language and concepts retrieved. The array of documents that can be used ranges from scientific literature to patents or clinical data, and the biomedical concepts often include, despite not being limited to genes, proteins, drugs, and diseases. This review aims to gather the leading tools for biomedical TM, summarily describing and systematizing them. We also surveyed several resources to compile the most valuable ones for each category.

Cells suffer from perturbations by different stimuli, which, consequently, rise to individual alterations in their profile and function that may end up affecting the tissue as a whole. This is no different if we consider the effect of a therapeutic agent on a biological system. As cells are exposed to external ligands their profile can change at different single-omics levels. Detecting how these changes take place through different sequencing technologies is key to a better understanding of the effects of therapeutic agents. Single-cell RNA-sequencing stands out as one of the most common approaches for cell profiling and perturbation analysis. As a result, single-cell transcriptomics data can be integrated with other omics data sources, such as proteomics and epigenomics data, to clarify the perturbation effects and mechanism at the cell level. Appropriate computational tools are key to process and integrate the available information. This chapter focuses on the recent advances on ligand-induced perturbation and single-cell omics computational tools and algorithms, their current limitations, and how the deluge of data can be used to improve the current process of drug research and development.

Este trabalho tem como princípio informar os riscos biológicos, ergonômicos, químicos, físicos e acidentes, que ocorrem dentro das indústrias que, muitas vezes, não são demostrados ou explanado aos trabalhadores no início de cada turno, deixando-os expostos e sujeitos a danos quase irreversíveis, como: som de ruídos, vibrações, inalações de gazes, exposição a vapores, iluminação inadequada entre outros fatores. Este trabalho teve como objetivo analisar e identificar os procedimentos que devem ser utilizados para garantir a segurança aos colaboradores, buscando minimizar ou evitar possíveis acidentes que podem vir ocorrer no ambiente de trabalho, acarretando problemas futuros que interferem na vida pessoal e podem levar às doenças ocupacionais. No ambiente de trabalho, os riscos podem ser distinguidos por cores, sendo elas verde, vermelha, marrom, amarelo e azul, facilitando para identificar os perigos aos trabalhadores, informações contribuem para o entendimento do colaborador. As indústrias estão sujeitas à legislação e está protege a saúde e segurança dos colaboradores, levando um ambiente de trabalho agradável e seguro.

Globally with over 10 million deaths per year, cancer is the most transversal disease across countries, cultures, and ethnicities, affecting both developed and developing regions. Tumorigenesis is dynamically altered by distinct events and can be lethal when untreated. Despite the innovative therapeutics available, multidrug resistance (MDR) to chemotherapy remains the major hindrance to the success of cancer therapy. The multiple mechanisms by which cancer cells evade cell death are diverse, indicating that MDR involves complex interconnected biological networks. Molecular profiling is currently able to stratify cancer into its distinct subtypes and help identify the best therapeutics, leading to "translational systems medicine". Highly specialized methodologies are generating a large amount of "omics" data - including epigenetics, genomics, transcriptomics, proteomics, metabolomics, as well as pharmacogenomics. Many of the resulting databases store data in non-standard formats, which need to be converted, interpreted, and merged into readable formats. The latest development of artificial intelligence (AI) methodologies and tools, coupled with advancements in large-scale data management and powerful graphic processing computing units, potentiate the integration of these large data sources into relevant biological networks, which will enhance our understanding of cancer MDR. In this review, we revisit common MDR mechanisms and compile a list of the most relevant "omics" public databases. We highlight examples of AI methods that are now decisively contributing to clear advances in cancer research, such as identification of new drugs from large databases and prediction of relevant drug, target, and system properties. An overview of several freely available "ready-to-use" algorithms is also provided. The described molecular scale AI algorithms and tools will undoubtedly guide important improvements in efficiency and efficacy of traditional methods of cancer diagnostics and treatment.

In the Prologue to his Livro de Linhagens, Count Pedro de Barcelos both emulates and subverts his great grandfather’s legal codes (mainly Partida IV), in order to create an ethosfor the Iberian aristocracy. This ethosis based on the convergence between natura(the divinely established order of the world), lineage and blood kinship, which, in the Count’s Aristotelian grounded view, leads to a widely spread friendship/solidarity that has a pacifying effect on social tensions. It is a kind of friendship ontologically linked with God and the Creation, pre-existing to the instituted relations of domination, and capable of substituting them advantageously as a mechanism of social regulation. According to Pedro de Barcelos’ argument, the ancient aristocratic practices emerging from this friendship perform as a kind of embryonic habituswhose preservation is linked to the survival of the Iberian aristocracy as a social group endowed with a specific legitimising symbolic capital.

Membrane proteins (MPs) encompass a large family of proteins with distinct cellular functions, and although representing over 50% of existing pharmaceutical drug targets, their structural and functional information is still very scarce. Over the last years, in silico analysis and algorithm development were essential to characterize MPs and overcome some limitations of experimental approaches. The optimization and improvement of these methods remain an ongoing process, with key advances in MPs' structure, folding, and interface prediction being continuously tackled. Herein, we discuss the latest trends in computational methods toward a deeper understanding of the atomistic and mechanistic details of MPs.

Desenvolvido no âmbito do Mestrado em Ciências da Educação, no domínio da Infância, Família e Sociedade, o presente relatório centra-se nas experiências de formação alcançadas ao longo do estágio realizado na Divisão de Educação (DE) da Câmara Municipal de Esposende (CME), durante os meses de outubro de 2020 a maio de 2021. Com base nos contributos teórico-concetuais das Ciências da Educação, da Sociologia da Infância e do quadro legislativo referente às competências das autarquias locais, ao longo do percurso de estágio foi estabelecido e assumido um posicionamento firmado nos direitos das crianças, na inclusão socioeducativa das crianças e jovens, na sua participação e na contribuição para um desenvolvimento local situado e com significado para cada um/a deles/as. Desta forma, o estágio decorreu em dois momentos distintos: um primeiro em que estive presencialmente na DE, durante o mês de outubro, permitindo colaborar com determinados procedimentos e refletir sobre os modos de funcionamento e organização dos/as colegas, assim como; num segundo momento realizado em teletrabalho, de novembro de 2020 a maio de 2021, a participação em várias reuniões online possibilitaram-me dar continuidade à compreensão dos modos de funcionamento da equipa e, para além disso, e de outras ações e tarefas que desenvolvi em contexto de estágio, foi fundamental e significativo para a minha experiência profissional e pessoal a possibilidade de efetuar uma avaliação ao Projeto AMAReMAR, realizar uma Cartografia Socioeducativa das Crianças e Jovens: para uma Educação Inclusiva e criar um vídeo para o evento VIVER ABRIL, privilegiando sempre uma abordagem participativa e de envolvimento das crianças e jovens e, no caso do projeto, também dos/as adultos/as implicados/as no mesmo. Posto isto, perante as arritmias marcadas pelo estágio, com fases de recuos e avanços, o presente relatório culmina num objeto de reflexão e análise das várias aprendizagens e competências pessoal e socialmente desenvolvidas e conseguidas ao longo do estágio.

Portuguese Journal of Pediatrics, Vol. 52 No. 3 (2021)

Severe Acute Respiratory Syndrome CoronaVirus-2 (SARS-CoV-2) is composed by four structural proteins and several accessory non-structural proteins. SARS-CoV-2's most abundant structural protein, Membrane (M) protein, has a pivotal role both during viral infection cycle and host interferon antagonism. This is a highly conserved viral protein, thus an interesting and suitable target for drug discovery. In this paper, we explain the structural and dynamic nature of M protein homodimer. To do so, we developed and applied a detailed and robust in silico workflow to predict M protein dimeric structure, membrane orientation, and interface characterization. Single Nucleotide Polymorphisms (SNPs) in M protein were retrieved from over 1.2 M SARS-CoV-2 genomes and proteins from the Global Initiative on Sharing All Influenza Data (GISAID) database, 91 of which were located at the predicted dimer interface. Among those, we identified SNPs in Variants of Concern (VOC) and Variants of Interest (VOI). Binding free energy differences were evaluated for dimer interfacial SNPs to infer mutant protein stabilities. A few high-prevalent mutated residues were found to be especially relevant in VOC and VOI. This realization may be a game changer to structure driven formulation of new therapeutics for SARS-CoV-2.

Objetivo: Necessidade de conhecimento a respeito das estratégias de mobilização utilizadas para minimização do surgimento de lesões por pressão em pacientes restritos ao leito hospitalar. Método: este estudo trata-se de uma revisão sistemática, em que utilizou-se critérios de elegibilidade baseados na estratégia PICO, no qual incluiu ensaios clínicos aleatórios, que continham títulos que abordassem sobre "lesões por pressão” e/ou sobre "mobilização". Resultados: O processo de seleção identificou 1076 estudos. Após a leitura completa e exclusão de duplicatas e resumos de triagem, 229 estudos foram selecionados. Dentre esses, 15 artigos científicos atenderam aos critérios de inclusão. Todos os estudos apontaram as lesões por pressão como complicação ou efeito adverso relacionado ao imobilismo e internação prolongada. Conclusão: As evidências demonstram que a mobilização precoce consiste numa técnica segura com resultados positivos a curto e longo prazo. Assim como, ganho de força muscular, mobilidade e redução do tempo de internação dos pacientes nas UTI.

Objetivo: Trata-se de uma revisão sistemática de artigos que estudam as estratégias de pronação dos últimos 5 anos em unidades de terapia intensiva. Métodos: Foram observados poucos artigos que tratem desse tema, totalizando 4 estudos de um total de 143 extraídos das bases de dados da PUBMED; SCOPUS; WEB OF SCIENCE; EMBASE. Resultados: Os estudos demonstram estratégias semelhantes usadas no planejamento da técnica por profissionais que realizam a pronação, é possível perceber também a concordância de que a pronação em pacientes com síndromes respiratórias internados em unidades de terapia intensiva pode ser um procedimento que atue na redução do tempo de internação e/ou as taxas de mortalidade, além de poder evitar complicações graves. Conclusão: Por tanto é necessário salientar a importância de estudos sobre o tema.