Genomic newborn screening: Are we entering a new era of screening?

Population newborn screening (NBS) for phenylketonuria began in the United States in 1963. In the 1990s electrospray ionization mass spectrometry permitted an array of pathognomonic metabolites to be identified simultaneously, enabling up to 60 disorders to be recognized with a single test. In response, differing approaches to the assessment of the harms and benefits of screening have resulted in variable screening panels worldwide. Thirty years on and another screening revolution has emerged with the potential for first line genomic testing extending the range of screening conditions recognized after birth to many hundreds. At the annual SSIEM conference in 2022 in Freiburg, Germany, an interactive plenary discussion on genomic screening strategies and their challenges and opportunities was conducted. The Genomics England Research project proposes the use of Whole Genome Sequencing to offer extended NBS to 100 000 babies for defined conditions with a clear benefit for the child. The European Organization for Rare Diseases seeks to include "actionable" conditions considering also other types of benefits. Hopkins Van Mil, a private UK research institute, determined the views of citizens and revealed as a precondition that families are provided with adequate information, qualified support, and that autonomy and data are protected. From an ethical standpoint, the benefits ascribed to screening and early treatment need to be considered in relation to asymptomatic, phenotypically mild or late-onset presentations, where presymptomatic treatment may not be required. The different perspectives and arguments demonstrate the unique burden of responsibility on those proposing new and far-reaching developments in NBS programs and the need to carefully consider both harms and benefits

European Health Data Space – an opportunity now to grasp the future of data-driven healthcare

Peer reviewedPostprin

Experts and 'knowledge that counts': A study into the world of brain cancer diagnosis

This paper provides a close, in situ look into the life of a neuro-oncology (brain cancer) clinic of a large hospital in Israel, based on a six-month participant observation. It points to the many challenges involved in the solidification of brain tumour diagnoses by different experts, and presents these epistemological and practical complexities as they uncover in daily routine. The paper's task is two-fold: first, to underline the technological and epistemological grounds of 'expertise' in the medicoscientific practice of diagnosis, and their roles in the assertion of expert authoritativeness; and second, to provide analytical tools to approach the complexity of diagnostic processes, the potential frictions it may create, and the related mechanisms of resolution. These mechanisms include Hierarchisation: ranking the relative validity and reliability of the different sources of information, eventually prioritising reports from more authoritative expertises (e.g. imaging reports would be considered more reliable than patients' accounts); Sequencing: relying upon the temporal dimension, and defining the discrepancy itself as a diagnostic sign (e.g. the degradation or amelioration of the disease); Negotiation: adjusting diagnoses via a preliminary exchange between experts and a consequent "fine tuning" of the reports (e.g. radiologists being aware of clinical evaluations before finalising their reports); Peripheralising: turning to other expertises to "explain away" symptoms that do not fit with a well established initial diagnosis (e.g. asserting that a symptom's source was orthopaedic rather than neurological); and pragmatism: using information only as far as it provided sufficient grounds for treatment decisions, leaving ambiguities unresolved. These five mechanisms are presented here in the context of the daily work of the clinic.Israel Expertise Epistemology Diagnosis Hospital Fieldwork Authoritativeness Brain cancer clinic

Fabrication and hydrogen sorption behaviour of nanoparticulate MgH_2 incorporated in a porous carbon host

Nanoparticles of MgH_2 incorporated in a mesoporous carbon aerogel demonstrated accelerated hydrogen exchange kinetics but no thermodynamic change in the equilibrium hydrogen pressure. Aerogels contained pores from <2 to ~30 nm in diameter with a peak at 13 nm in the pore size distribution. Nanoscale MgH_2 was fabricated by depositing wetting layers of nickel or copper on the aerogel surface, melting Mg into the aerogel, and hydrogenating the Mg to MgH_2. Aerogels with metal wetting layers incorporated 9–16 wt% MgH_2, while a metal free aerogel incorporated only 3.6 wt% MgH_2. The improved hydrogen sorption kinetics are due to both the aerogel limiting the maximum MgH_2 particle diameter and a catalytic effect from the Ni and Cu wetting layers. At 250 °C, MgH_2 filled Ni decorated and Cu decorated carbon aerogels released H_2 at 25 wt% h^−1 and 5.5 wt% h^−1, respectively, while a MgH_2 filled aerogel without catalyst desorbed only 2.2 wt% h^−1 (all wt% h^−1 values are with respect to MgH_2 mass). At the same temperature, MgH_2 ball milled with synthetic graphite desorbed only 0.12 wt% h^−1, which demonstrated the advantage of incorporating nanoparticles in a porous host

Reversible Ligand Exchange in a Metal–Organic Framework (MOF): Toward MOF-Based Dynamic Combinatorial Chemical Systems

Reversible benzene dicarboxylate/2-bromobenzene dicarboxylate ligand exchange has been studied in the cubic metal–organic framework MOF-5. Significant exchange (up to ∼50%), with continuous compositional variation, was observed using ex-situ ¹H NMR following treatment over ∼6 h at ∼85 °C in 10–40 mM ligand solutions. Exchange occurred without significant structural degradation as characterized by X-ray diffraction, nitrogen adsorption, and scanning electron microscopy. Solid-state ¹³C NMR was used to show that exchanged ligands were incorporated into the framework lattice and not simply adsorbed within the pores. Exchange was found to be sensitive to the small free energy changes caused by the ligand concentration in the exchanging solution indicating that exchange is energetically nearly degenerate. This demonstration of reversible, nearly isoenergetic exchange indicates that mixed ligand MOFs could be developed as dynamic combinatorial chemical systems

The synthesis and hydrogen storage properties of a MgH_2 incorporated carbon aerogel scaffold

A new approach to the incorporation of MgH_2 in the nanometer-sized pores of a carbon aerogel scaffold was developed, by infiltrating the aerogel with a solution of dibutylmagnesium (MgBu_2) precursor, and then hydrogenating the incorporated MgBu_2 to MgH_2. The resulting impregnated material showed broad x-ray diffraction peaks of MgH_2. The incorporated MgH_2 was not visible using a transmission electron microscope, which indicated that the incorporated hydride was nanosized and confined in the nanoporous structure of the aerogel. The loading of MgH_2 was determined as 15–17 wt%, of which 75% is reversible over ten cycles. Incorporated MgH_2 had >5 times faster dehydrogenation kinetics than ball-milled activated MgH2, which may be attributed to the particle size of the former being smaller than that of the latter. Cycling tests of the incorporated MgH_2 showed that the dehydrogenation kinetics are unchanged over four cycles. Our results demonstrate that confinement of metal hydride materials in a nanoporous scaffold is an efficient way to avoid aggregation and improve cycling kinetics for hydrogen storage materials

Are the European reference networks for rare diseases ready to embrace machine learning? A mixed-methods study

Abstract Background The delay in diagnosis for rare disease (RD) patients is often longer than for patients with common diseases. Machine learning (ML) technologies have the potential to speed up and increase the precision of diagnosis in this population group. We aim to explore the expectations and experiences of the members of the European Reference Networks (ERNs) for RDs with those technologies and their potential for application. Methods We used a mixed-methods approach with an online survey followed by a focus group discussion. Our study targeted primarily medical professionals but also other individuals affiliated with any of the 24 ERNs. Results The online survey yielded 423 responses from ERN members. Participants reported a limited degree of knowledge of and experience with ML technologies. They considered improved diagnostic accuracy the most important potential benefit, closely followed by the synthesis of clinical information, and indicated the lack of training in these new technologies, which hinders adoption and implementation in routine care. Most respondents supported the option that ML should be an optional but recommended part of the diagnostic process for RDs. Most ERN members saw the use of ML limited to specialised units only in the next 5 years, where those technologies should be funded by public sources. Focus group discussions concluded that the potential of ML technologies is substantial and confirmed that the technologies will have an important impact on healthcare and RDs in particular. As ML technologies are not the core competency of health care professionals, participants deemed a close collaboration with developers necessary to ensure that results are valid and reliable. However, based on our results, we call for more research to understand other stakeholders’ opinions and expectations, including the views of patient organisations. Conclusions We found enthusiasm to implement and apply ML technologies, especially diagnostic tools in the field of RDs, despite the perceived lack of experience. Early dialogue and collaboration between health care professionals, developers, industry, policymakers, and patient associations seem to be crucial to building trust, improving performance, and ultimately increasing the willingness to accept diagnostics based on ML technologies