Summary: Sambamba is a high-performance robust tool and library for working with SAM, BAM and CRAM sequence alignment files; the most common file formats for aligned next generation sequencing data. Sambamba is a faster alternative to samtools that exploits multi-core processing and dramatically reduces processing time. Sambamba is being adopted at sequencing centers, not only because of its speed, but also because of additional functionality, including coverage analysis and powerful filtering capability.Availability and implementation: Sambamba is free and open source software, available under a GPLv2 license. Sambamba can be downloaded and installed from http://www.open-bio.org/wiki/Sambamba.Sambamba v0.5.0 was released with doi:10.5281/zenodo.13200.Contact: j.c.p.prins@umcutrecht.nl

High-mass-resolution imaging mass spectrometry promises to localize hundreds of metabolites in tissues, cell cultures, and agar plates with cellular resolution, but it is hampered by the lack of bioinformatics tools for automated metabolite identification. We report pySM, a framework for false discovery rate (FDR)-controlled metabolite annotation at the level of the molecular sum formula, for high-mass-resolution imaging mass spectrometry (https://github.com/alexandrovteam/pySM). We introduce a metabolite-signal match score and a target-decoy FDR estimate for spatial metabolomics.

Metabolites, lipids, and other small molecules are key constituents of tissues supporting cellular programs in health and disease. Here, we present METASPACE, a community-populated knowledge base of spatial metabolomes from imaging mass spectrometry data. METASPACE is enabled by a high-performance engine for metabolite annotation in a confidence-controlled way that makes results comparable between experiments and laboratories. By sharing their results publicly, engine users continuously populate a knowledge base of annotated spatial metabolomes in tissues currently including over 3000 datasets from human cancer cohorts, whole-body sections of animal models, and various organs. The spatial metabolomes can be visualized, explored and shared using a web app as well as accessed programmatically for large-scale analysis. By using novel computational methods inspired by natural language processing, we illustrate that METASPACE provides molecular coverage beyond the capacity of any individual laboratory and opens avenues towards comprehensive metabolite atlases on the levels of tissues and organs.

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The pandemic of the novel coronavirus infection (COVID-19), caused by SARS‑CoV‑2, has become a challenge to healthcare systems in all countries of the world. Patients with comorbidity are the most vulnerable group with the high risk of adverse outcomes. The problem of managing these patients in context of a pandemic requires a comprehensive approach aimed both at the optimal management in self-isolated patients not visiting medical facilities, and management of comorbidities in patients with COVID-19. The presented consensus covers these two aspects of managing patients with cardiovascular disease, diabetes, chronic obstructive pulmonary disease, gastrointestinal disease, and also pay attention to the multiple organ complications of COVID-19.

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Using photoelectron diffraction and spectroscopy, we explore the structural and electronic properties of the hexagonal boron nitride (h-BN) monolayer epitaxially grown on the Co(0001) surface. Perfect matching of the lattice parameters allows formation of a well-defined interface where the B atoms occupy the hollow sites while the N atoms are located above the Co atoms. The corrugation of the h-BN monolayer and its distance from the substrate were determined by means of R-factor analysis. The obtained results are in perfect agreement with the density functional theory (DFT) predictions. The electronic structure of the interface is characterized by a significant mixing of the h-BN and Co states. Such hybridized states appear in the h-BN band gap. This allows to obtain atomically resolved scanning tunneling microscopy (STM) images from the formally insulating 2D material being in contact with ferromagnetic metal. The STM images reveal mainly the nitrogen sublattice due to a dominating contribution of nitrogen orbitals to the electronic states at the Fermi level. We believe that the high quality, well-defined structure and interesting electronic properties make the h-BN/Co(0001) interface suitable for spintronic applications.

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