Ligation Tunes Protein Reactivity in an Ancient Haemoglobin: Kinetic Evidence for an Allosteric Mechanism in Methanosarcina acetivorans Protoglobin

Protoglobin from Methanosarcina acetivorans (MaPgb) is a dimeric globin with peculiar structural properties such as a completely buried haem and two orthogonal tunnels connecting the distal cavity to the solvent. CO binding to and dissociation from MaPgb occur through a biphasic kinetics. We show that the heterogenous kinetics arises from binding to (and dissociation from) two tertiary conformations in ligation-dependent equilibrium. Ligation favours the species with high binding rate (and low dissociation rate). The equilibrium is shifted towards the species with low binding (and high dissociation) rates for the unliganded molecules. A quantitative model is proposed to describe the observed carbonylation kinetics

Relatório de estágio em farmácia comunitária

Relatório de estágio realizado no âmbito do Mestrado Integrado em Ciências Farmacêuticas, apresentado à Faculdade de Farmácia da Universidade de Coimbr

COVID-19 symptoms at hospital admission vary with age and sex: results from the ISARIC prospective multinational observational study

Background: The ISARIC prospective multinational observational study is the largest cohort of hospitalized patients with COVID-19. We present relationships of age, sex, and nationality to presenting symptoms. Methods: International, prospective observational study of 60 109 hospitalized symptomatic patients with laboratory-confirmed COVID-19 recruited from 43 countries between 30 January and 3 August 2020. Logistic regression was performed to evaluate relationships of age and sex to published COVID-19 case definitions and the most commonly reported symptoms. Results: ‘Typical’ symptoms of fever (69%), cough (68%) and shortness of breath (66%) were the most commonly reported. 92% of patients experienced at least one of these. Prevalence of typical symptoms was greatest in 30- to 60-year-olds (respectively 80, 79, 69%; at least one 95%). They were reported less frequently in children (≤ 18 years: 69, 48, 23; 85%), older adults (≥ 70 years: 61, 62, 65; 90%), and women (66, 66, 64; 90%; vs. men 71, 70, 67; 93%, each P < 0.001). The most common atypical presentations under 60 years of age were nausea and vomiting and abdominal pain, and over 60 years was confusion. Regression models showed significant differences in symptoms with sex, age and country. Interpretation: This international collaboration has allowed us to report reliable symptom data from the largest cohort of patients admitted to hospital with COVID-19. Adults over 60 and children admitted to hospital with COVID-19 are less likely to present with typical symptoms. Nausea and vomiting are common atypical presentations under 30 years. Confusion is a frequent atypical presentation of COVID-19 in adults over 60 years. Women are less likely to experience typical symptoms than men

Theoretical and practical analyses in metagenomic sequence classification

Metagenomics is the study of genomic sequences in a heterogeneous microbial sample taken, e.g. from soil, water, human microbiome and skin. One of the primary objectives of metagenomic studies is to assign a taxonomic identity to each read sequenced from a sample and then to estimate the abundance of the known clades. With ever-increasing metagenomic datasets obtained from high-throughput sequencing technologies readily available nowadays, several fast and accurate methods have been developed that can work with reasonable computing requirements. Here we provide an overview of the state-of-the-art methods for the classification of metagenomic sequences, especially highlighting theoretical factors that seem to correlate well with practical factors, and could therefore be useful in the choice or development of a new method in experimental contexts. In particular, we emphasize that the information derived from the known genomes and eventually used in the learning and classification processes may create several experimental issues—mostly based on the amount of information used in the processes and its uniqueness, significance, and redundancy,—and some of these issues are intrinsic both in current alignment-based approaches and in compositional ones. This entails the need to develop efficient alignment-free methods that overcome such problems by combining the learning and classification processes in a single framework