Genomic investigations of unexplained acute hepatitis in children

Since its first identification in Scotland, over 1,000 cases of unexplained paediatric hepatitis in children have been reported worldwide, including 278 cases in the UK1. Here we report an investigation of 38 cases, 66 age-matched immunocompetent controls and 21 immunocompromised comparator participants, using a combination of genomic, transcriptomic, proteomic and immunohistochemical methods. We detected high levels of adeno-associated virus 2 (AAV2) DNA in the liver, blood, plasma or stool from 27 of 28 cases. We found low levels of adenovirus (HAdV) and human herpesvirus 6B (HHV-6B) in 23 of 31 and 16 of 23, respectively, of the cases tested. By contrast, AAV2 was infrequently detected and at low titre in the blood or the liver from control children with HAdV, even when profoundly immunosuppressed. AAV2, HAdV and HHV-6 phylogeny excluded the emergence of novel strains in cases. Histological analyses of explanted livers showed enrichment for T cells and B lineage cells. Proteomic comparison of liver tissue from cases and healthy controls identified increased expression of HLA class 2, immunoglobulin variable regions and complement proteins. HAdV and AAV2 proteins were not detected in the livers. Instead, we identified AAV2 DNA complexes reflecting both HAdV-mediated and HHV-6B-mediated replication. We hypothesize that high levels of abnormal AAV2 replication products aided by HAdV and, in severe cases, HHV-6B may have triggered immune-mediated hepatic disease in genetically and immunologically predisposed children

Machine Learning for Health: Algorithm Auditing & Quality Control.

Developers proposing new machine learning for health (ML4H) tools often pledge to match or even surpass the performance of existing tools, yet the reality is usually more complicated. Reliable deployment of ML4H to the real world is challenging as examples from diabetic retinopathy or Covid-19 screening show. We envision an integrated framework of algorithm auditing and quality control that provides a path towards the effective and reliable application of ML systems in healthcare. In this editorial, we give a summary of ongoing work towards that vision and announce a call for participation to the special issue  Machine Learning for Health: Algorithm Auditing & Quality Control in this journal to advance the practice of ML4H auditing

Amphipols outperform dodecylmaltoside micelles in stabilizing membrane protein structure in the gas phase

Noncovalent mass spectrometry (MS) is emerging as an invaluable technique to probe the structure, interactions, and dynamics of membrane proteins (MPs). However, maintaining native-like MP conformations in the gas phase using detergent solubilized proteins is often challenging and may limit structural analysis. Amphipols, such as the well characterized A8-35, are alternative reagents able to maintain the solubility of MPs in detergent-free solution. In this work, the ability of A8-35 to retain the structural integrity of MPs for interrogation by electrospray ionization-ion mobility spectrometry-mass spectrometry (ESI-IMS-MS) is compared systematically with the commonly used detergent dodecylmaltoside. MPs from the two major structural classes were selected for analysis, including two β-barrel outer MPs, PagP and OmpT (20.2 and 33.5 kDa, respectively), and two α-helical proteins, Mhp1 and GalP (54.6 and 51.7 kDa, respectively). Evaluation of the rotationally averaged collision cross sections of the observed ions revealed that the native structures of detergent solubilized MPs were not always retained in the gas phase, with both collapsed and unfolded species being detected. In contrast, ESI-IMS-MS analysis of the amphipol solubilized MPs studied resulted in charge state distributions consistent with less gas phase induced unfolding, and the presence of lowly charged ions which exhibit collision cross sections comparable with those calculated from high resolution structural data. The data demonstrate that A8-35 can be more effective than dodecylmaltoside at maintaining native MP structure and interactions in the gas phase, permitting noncovalent ESI-IMS-MS analysis of MPs from the two major structural classes, while gas phase dissociation from dodecylmaltoside micelles leads to significant gas phase unfolding, especially for the α-helical MPs studied