PET-BIDS, an extension to the brain imaging data structure for positron emission tomography

The Brain Imaging Data Structure (BIDS) is a standard for organizing and describing neuroimaging datasets, serving not only to facilitate the process of data sharing and aggregation, but also to simplify the application and development of new methods and software for working with neuroimaging data. Here, we present an extension of BIDS to include positron emission tomography (PET) data, also known as PET-BIDS, and share several open-access datasets curated following PET-BIDS along with tools for conversion, validation and analysis of PET-BIDS datasets

Industry-Scale Orchestrated Federated Learning for Drug Discovery

To apply federated learning to drug discovery we developed a novel platform in the context of European Innovative Medicines Initiative (IMI) project MELLODDY (grant n{\deg}831472), which was comprised of 10 pharmaceutical companies, academic research labs, large industrial companies and startups. The MELLODDY platform was the first industry-scale platform to enable the creation of a global federated model for drug discovery without sharing the confidential data sets of the individual partners. The federated model was trained on the platform by aggregating the gradients of all contributing partners in a cryptographic, secure way following each training iteration. The platform was deployed on an Amazon Web Services (AWS) multi-account architecture running Kubernetes clusters in private subnets. Organisationally, the roles of the different partners were codified as different rights and permissions on the platform and administrated in a decentralized way. The MELLODDY platform generated new scientific discoveries which are described in a companion paper.Comment: 9 pages, 4 figures, to appear in AAAI-23 ([IAAI-23 track] Deployed Highly Innovative Applications of AI

PET-BIDS, an extension to the brain imaging data structure for positron emission tomography

The Brain Imaging Data Structure (BIDS) is a standard for organizing and describing neuroimaging datasets. It serves not only to facilitate the process of data sharing and aggregation, but also to simplify the application and development of new methods and software for working with neuroimaging data. Here, we present an extension of BIDS to include positron emission tomography (PET) data (PET-BIDS). We describe the PET-BIDS standard in detail and share several open-access datasets curated following PET-BIDS. Additionally, we highlight several tools which are already available for converting, validating and analyzing PET-BIDS datasets.Competing Interest StatementThe authors have declared no competing interest

Parallel K-H turbulence as a test case for plasma edge fluid modelling

International audienc

Brain Metabolic Profile in Presymptomatic GRN Carriers Throughout a 5-Year Follow-up

International audienceBackground and Objectives. GRN variants are a frequent cause of familial frontotemporal dementia (FTD). Monitoring disease progression in asymptomatic carriers of genetic variants is a major challenge in delivering preventative therapies before clinical onset. This study aimed to assess the usefulness of fluorodeoxyglucose (FDG)-PET in identifying metabolic changes in presymptomatic GRN carriers (PS- GRN +), and to trace their longitudinal progression. Methods. Participants were longitudinally evaluated over 5 years in a prospective cohort study focused on GRN disease (Predict-PGRN). They underwent cognitive/behavioral assessment, plasma neurofilament measurement, brain MRI and FDG-PET. Voxel-wise comparisons of structural and metabolic imaging data between the two groups were performed for each time-point. Longitudinal PET changes were evaluated with voxel-wise comparisons and the metabolic percent annual changes method. The association of regional brain metabolism with plasma neurofilament and cognitive changes was analyzed. Results. Among the 80 individuals enrolled in the study, 58 (27 PS- GRN + and 31 non-carriers) were included in the analyses. Cross-sectional comparisons between PS- GRN + and controls found a significant hypometabolism in the left superior temporal sulcus (STS) region (encompassing the middle and superior temporal gyri), approximately 15 years before the expected disease onset, without significant cortical atrophy. The longitudinal metabolic decline over the following 5 years peaked around the right STS in carriers ( p <0.001), without significantly greater volume loss compared to controls. Their estimated annualized metabolic decrease (-1.37%) was higher than in controls (-0.21%, p =0.004). Lower glucose uptake was associated with higher neurofilament increase ( p =0.003) and lower frontal cognitive scores ( p =0.014) in PS- GRN +. Discussion. This study detected brain metabolic changes in the STS region, preceding structural and cognitive alterations, thus contributing to the characterization of the pathochronology of preclinical GRN disease. Due to the STS involvement in the perception of facially communicated cues, it is likely that its dysfunction contributes to social cognition deficits characterizing FTD. Overall, our study highlights brain metabolic changes as an early disease-tracking biomarker, and proposes annualized percent decrease as a metric to monitor therapeutic response in forthcoming trials

Opinion forming in the digital age

The Internet provides fast and ubiquitous communication that enables all kinds of communities and provides citizens with easy access to vast amounts of information, although the information is not necessarily verified and may present a distorted view of real events or facts. The Internet’s power as an instant source of mass information can be used to influence opinions, which can have far-reaching consequences.This report’s purpose is to provide input into the advisory processes that determine European support for research into the effects and management of Fake News (e.g. deliberate misinformation), Echo Chambers (e.g. closed communities where biases can be reinforced through lack of diversity in opinions), and the Internet’s influence on social and political movements such as Populism; to provide insight into how innovation that takes these aspects into account can be supported. To address this aim, this report concerns socio-technical implications of the Internet related to the impact of closed communities and misinformation and makes recommendations derived from a consultation with domain experts concerning the research needed to address specific challenges.This study has used the Delphi Method, an iterative consultation mechanism aimed at consensus building within a targeted panel of experts. Three rounds of iteration were undertaken and a total of fourteen experts participated in all three rounds. The result of the consultation is 67 assertion statements that reached consensus amongst the experts in five broad themes, and these are presented in this report and summarised into key recommendations.The key overarching recommendation is that we need to understand how opinions are formed and are influenced in the current digital age. Investigations are needed to understand the underlying cognitive and emotional processes that enable peoples’ opinions to be influenced in the context of a hybrid media system that mixes online and offline channels and broadcast and interactive social media.<br/