Objectives: Angiotensin-converting enzyme inhibitors (ACEi), angiotensin II receptor blockers (ARBs), and HMG-CoA reductase inhibitors ("statins") have been hypothesized to affect COVID-19 severity. However, up to now, no studies investigating this association have been conducted in the most vulnerable and affected population groups (ie, older adults residing in nursing homes). The objective of this study was to explore the association of ACEi/ARB and/or statins with clinical manifestations in COVID-19einfected older adults residing in nursing homes. Design: We undertook a retrospective multicenter cohort study to analyze the association between ACEi/ ARB and/or statin use with clinical outcome of COVID-19. The outcomes were (1) serious COVID-19 defined as long-stay hospital admission or death within 14 days of disease onset, and (2) asymptomatic (ie, no disease symptoms in the whole study period while still being diagnosed by polymerase chain reaction). Setting and participants: A total of 154 COVID-19epositive subjects were identified, residing in 1 of 2 Belgian nursing homes that experienced similar COVID-19 outbreaks. Measures: Logistic regression models were applied with age, sex, functional status, diabetes, and hypertension as covariates. Results: We found a statistically significant association between statin intake and the absence of symptoms during COVID-19 (odds ratio [OR] 2.91; confidence interval [CI] 1.27e6.71), which remained statistically significant after adjusting for covariates (OR 2.65; CI 1.13e6.68). Although the effects of statin intake on serious clinical outcome were in the same beneficial direction, these were not statistically significant (OR 0.75; CI 0.24e1.87). There was also no statistically significant association between ACEi/ ARB and asymptomatic status (OR 2.72; CI 0.59e25.1) or serious clinical outcome (OR 0.48; CI 0.10e1.97).

BackgroundRecent research has provided fascinating indications and evidence that the host health is linked to its microbial inhabitants. Due to the development of high-throughput sequencing technologies, more and more data covering microbial composition changes in different disease types are emerging. However, this information is dispersed over a wide variety of medical and biomedical disciplines.DescriptionDisbiome is a database which collects and presents published microbiota-disease information in a standardized way. The diseases are classified using the MedDRA classification system and the micro-organisms are linked to their NCBI and SILVA taxonomy. Finally, each study included in the Disbiome database is assessed for its reporting quality using a standardized questionnaire.ConclusionsDisbiome is the first database giving a clear, concise and up-to-date overview of microbial composition differences in diseases, together with the relevant information of the studies published. The strength of this database lies within the combination of the presence of references to other databases, which enables both specific and diverse search strategies within the Disbiome database, and the human annotation which ensures a simple and structured presentation of the available data.

a b s t r a c tEthnopharmacological relevance: N-Alkylamides (NAAs) are a promising group of bioactive compounds, which are anticipated to act as important lead compounds for plant protection and biocidal products, functional food, cosmeceuticals and drugs in the next decennia. These molecules, currently found in more than 25 plant families and with a wide structural diversity, exert a variety of biologicalpharmacological effects and are of high ethnopharmacological importance. However, information is scattered in literature, with different, often unstandardized, pharmacological methodologies being used. Therefore, a comprehensive NAA database (acronym: Alkamid) was constructed to collect the available structural and functional NAA data, linked to their occurrence in plants (family, tribe, species, genus). Materials and methods: For loading information in the database, literature data was gathered over the period 1950-2010, by using several search engines. In order to represent the collected information about NAAs, the plants in which they occur and the functionalities for which they have been examined, a relational database is constructed and implemented on a MySQL back-end. Results: The database is supported by describing the NAA plant-, functional-and chemical-space. The chemical space includes a NAA classification, according to their fatty acid and amine structures. Conclusions: The Alkamid database (publicly available on the website http://alkamid.ugent.be/) is not only a central information point, but can also function as a useful tool to prioritize the NAA Q8 choice in the evaluation of their functionality, to perform data mining leading to quantitative structure-property relationships (QSPRs), functionality comparisons, clustering, plant biochemistry and taxonomic evaluations.

Quorum-sensing (QS) peptides are biologically attractive molecules, with a wide diversity of structures and prone to modifications altering or presenting new functionalities. Therefore, the Quorumpeps database (http://quorumpeps.ugent.be) is developed to give a structured overview of the QS oligopeptides, describing their microbial origin (species), functionality (method, result and receptor), peptide links and chemical characteristics (3D-structure-derived physicochemical properties). The chemical diversity observed within this group of QS signalling molecules can be used to develop new synthetic bio-active compounds.

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