Web-based Dashboard on ECMO Utilization in Germany: An Interactive Visualization, Analyses, and Prediction Based on Real-life Data

In Germany, a comprehensive reimbursement policy for extracorporeal membrane oxygenation (ECMO) results in the highest per capita use worldwide, although benefits remain controversial. Public ECMO data is unstructured and poorly accessible to healthcare professionals, researchers, and policymakers. In addition, there are no uniform policies for ECMO allocation which confronts medical personnel with ethical considerations during health crises such as respiratory virus outbreaks.Retrospective information on adult and pediatric ECMO support performed in German hospitals was extracted from publicly available reimbursement data and hospital quality reports and processed to create the web-based ECMO Dashboard built on Open-Source software. Patient-level and hospital-level data were merged resulting in a solid base for ECMO use analysis and ECMO demand forecasting with high spatial granularity at the level of 413 county and city districts in Germany.The ECMO Dashboard ( https://www.ecmo-dash.de/ ), an innovative visual platform, presents the retrospective utilization patterns of ECMO support in Germany. It features interactive maps, comprehensive charts, and tables, providing insights at the hospital, district, and national levels. This tool also highlights the high prevalence of ECMO support in Germany and emphasizes districts with ECMO surplus - where patients from other regions are treated, or deficit - origins from which ECMO patients are transferred to other regions. The dashboard will evolve iteratively to provide stakeholders with vital information for informed and transparent resource allocation and decision-making.Accessible public routine data could support evidence-informed, forward-looking resource management policies, which are urgently needed to increase the quality and prepare the critical care infrastructure for future pandemics.

Short-term predictor for COVID-19 severity from a longitudinal multi-omics study for practical application in intensive care units

BACKGROUND

The COVID-19 pandemic challenged the management of technical and human resources in intensive care units (ICU) across the world. Several long-term predictors for COVID-19 disease progression have been discovered. However, predictors to support short-term planning of resources and medication that can be translated to future pandemics are still missing. A workflow was established to identify a predictor for short-term COVID-19 disease progression in the acute phase of intensive care patients to support clinical decision-making.

METHODS

Thirty-two patients with SARS-CoV-2 infection were recruited on admission to the ICU and clinical data collected. During their hospitalization, plasma samples were acquired from each patient on multiple occasions, excepting one patient for which only one time point was possible, and the proteome (Inflammation, Immune Response and Organ Damage panels from Olink® Target 96), metabolome and lipidome (flow injection analysis and liquid chromatography-mass spectrometry) analyzed for each sample. Patient visits were grouped according to changes in disease severity based on their respiratory and organ function, and evaluated using a combination of statistical analysis and machine learning. The resulting short-term predictor from this multi-omics approach was compared to the human assessment of disease progression. Furthermore, the potential markers were compared to the baseline levels of 50 healthy subjects with no known SARS-CoV-2 or other viral infections.

RESULTS

A total of 124 clinical parameters, 271 proteins and 782 unique metabolites and lipids were assessed. The dimensionality of the dataset was reduced, selecting 47 from the 1177 parameters available following down-selection, to build the machine learning model. Subsequently, two proteins (C-C motif chemokine 7 (CCL7) and carbonic anhydrase 14 (CA14)) and one lipid (hexosylceramide 18:2; O2/20:0) were linked to disease progression in the studied SARS-CoV-2 infections. Thus, a predictor delivering the prognosis of an upcoming worsening of the patient's condition up to five days in advance with a reasonable accuracy (79 % three days prior to event, 84 % four to five days prior to event) was found. Interestingly, the predictor's performance was complementary to the clinicians' capabilities to foresee a worsening of a patient.

CONCLUSION

This study presents a workflow to identify omics-based biomarkers to support clinical decision-making and resource management in the ICU. This was successfully applied to develop a short-term predictor for aggravation of COVID-19 symptoms. The applied methods can be adapted for future small cohort studies.

Expectations of Anesthesiology and Intensive Care Professionals Toward Artificial Intelligence: Observational Study

BACKGROUND

Artificial intelligence (AI) applications offer numerous opportunities to improve health care. To be used in the intensive care unit, AI must meet the needs of staff, and potential barriers must be addressed through joint action by all stakeholders. It is thus critical to assess the needs and concerns of anesthesiologists and intensive care physicians related to AI in health care throughout Europe.

OBJECTIVE

This Europe-wide, cross-sectional observational study investigates how potential users of AI systems in anesthesiology and intensive care assess the opportunities and risks of the new technology. The web-based questionnaire was based on the established analytic model of acceptance of innovations by Rogers to record 5 stages of innovation acceptance.

METHODS

The questionnaire was sent twice in 2 months (March 11, 2021, and November 5, 2021) through the European Society of Anaesthesiology and Intensive Care (ESAIC) member email distribution list. A total of 9294 ESAIC members were reached, of whom 728 filled out the questionnaire (response rate 728/9294, 8%). Due to missing data, 27 questionnaires were excluded. The analyses were conducted with 701 participants.

RESULTS

A total of 701 questionnaires (female: n=299, 42%) were analyzed. Overall, 265 (37.8%) of the participants have been in contact with AI and evaluated the benefits of this technology higher (mean 3.22, SD 0.39) than participants who stated no previous contact (mean 3.01, SD 0.48). Physicians see the most benefits of AI application in early warning systems (335/701, 48% strongly agreed, and 358/701, 51% agreed). Major potential disadvantages were technical problems (236/701, 34% strongly agreed, and 410/701, 58% agreed) and handling difficulties (126/701, 18% strongly agreed, and 462/701, 66% agreed), both of which could be addressed by Europe-wide digitalization and education. In addition, the lack of a secure legal basis for the research and use of medical AI in the European Union leads doctors to expect problems with legal liability (186/701, 27% strongly agreed, and 374/701, 53% agreed) and data protection (148/701, 21% strongly agreed, and 343/701, 49% agreed).

CONCLUSIONS

Anesthesiologists and intensive care personnel are open to AI applications in their professional field and expect numerous benefits for staff and patients. Regional differences in the digitalization of the private sector are not reflected in the acceptance of AI among health care professionals. Physicians anticipate technical difficulties and lack a stable legal basis for the use of AI. Training for medical staff could increase the benefits of AI in professional medicine. Therefore, we suggest that the development and implementation of AI in health care require a solid technical, legal, and ethical basis, as well as adequate education and training of users.

ABCE1 Controls Ribosome Recycling by an Asymmetric Dynamic Conformational Equilibrium

The twin-ATPase ABCE1 has a vital function in mRNA translation by recycling terminated or stalled ribosomes. As for other functionally distinct ATP-binding cassette (ABC) proteins, the mechanochemical coupling of ATP hydrolysis to conformational changes remains elusive. Here, we use an integrated biophysical approach allowing direct observation of conformational dynamics and ribosome association of ABCE1 at the single-molecule level. Our results from FRET experiments show that the current static two-state model of ABC proteins has to be expanded because the two ATP sites of ABCE1 are in dynamic equilibrium across three distinct conformational states: open, intermediate, and closed. The interaction of ABCE1 with ribosomes influences the conformational dynamics of both ATP sites asymmetrically and creates a complex network of conformational states. Our findings suggest a paradigm shift to redefine the understanding of the mechanochemical coupling in ABC proteins: from structure-based deterministic models to dynamic-based systems.

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Both ATP sites of ABCE1 are in an asymmetric conformational equilibrium

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Each ATP site can adopt three functionally distinct conformational states

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These equilibria shift during ribosome recycling depending on interaction partners

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ATP binding, but not hydrolysis, is required for ribosome splitting

Molecular analysis of the ribosome recycling factor ABCE1 bound to the 30S post-splitting complex

Ribosome recycling by the twin‐ATPase ABCE1 is a key regulatory process in mRNA translation and surveillance and in ribosome‐associated protein quality control in Eukarya and Archaea. Here, we captured the archaeal 30S ribosome post‐splitting complex at 2.8 Å resolution by cryo‐electron microscopy. The structure reveals the dynamic behavior of structural motifs unique to ABCE1, which ultimately leads to ribosome splitting. More specifically, we provide molecular details on how conformational rearrangements of the iron–sulfur cluster domain and hinge regions of ABCE1 are linked to closure of its nucleotide‐binding sites. The combination of mutational and functional analyses uncovers an intricate allosteric network between the ribosome, regulatory domains of ABCE1, and its two structurally and functionally asymmetric ATP‐binding sites. Based on these data, we propose a refined model of how signals from the ribosome are integrated into the ATPase cycle of ABCE1 to orchestrate ribosome recycling.

Ribosome recycling in mRNA translation, quality control, and homeostasis

Protein biosynthesis is a conserved process, essential for life. Ongoing research for four decades has revealed the structural basis and mechanistic details of most protein biosynthesis steps. Numerous pathways and their regulation have recently been added to the translation system describing protein quality control and messenger ribonucleic acid (mRNA) surveillance, ribosome-associated protein folding and post-translational modification as well as human disorders associated with mRNA and ribosome homeostasis. Thus, translation constitutes a key regulatory process placing the ribosome as a central hub at the crossover of numerous cellular pathways. Here, we describe the role of ribosome recycling by ATP-binding cassette sub-family E member 1 (ABCE1) as a crucial regulatory step controlling the biogenesis of functional proteins and the degradation of aberrant nascent chains in quality control processes.

Ribosome recycling is coordinated by processive events in two asymmetric ATP sites of ABCE1

The stepwise ribosome disassembly in the translation cycle of eukaryotes and archaea is scheduled by discrete molecular events within the asymmetric ribosome recycling factor ABCE1.

Ribosome recycling orchestrated by ABCE1 is a fundamental process in protein translation and mRNA surveillance, connecting termination with initiation. Beyond the plenitude of well-studied translational GTPases, ABCE1 is the only essential factor energized by ATP, delivering the energy for ribosome splitting via two nucleotide-binding sites by a yet unknown mechanism. Here, we define how allosterically coupled ATP binding and hydrolysis events in ABCE1 empower ribosome recycling. ATP occlusion in the low-turnover control site II promotes formation of the pre-splitting complex and facilitates ATP engagement in the high-turnover site I, which in turn drives the structural reorganization required for ribosome splitting. ATP hydrolysis and ensuing release of ABCE1 from the small subunit terminate the post-splitting complex. Thus, ABCE1 runs through an allosterically coupled cycle of closure and opening at both sites, consistent with a processive clamp model. This study delineates the inner mechanics of ABCE1 and reveals why various ABCE1 mutants lead to defects in cell homeostasis, growth, and differentiation.

Structure of the ribosome post-recycling complex probed by chemical cross-linking and mass spectrometry

Ribosome recycling orchestrated by the ATP binding cassette (ABC) protein ABCE1 can be considered as the final—or the first—step within the cyclic process of protein synthesis, connecting translation termination and mRNA surveillance with re-initiation. An ATP-dependent tweezer-like motion of the nucleotide-binding domains in ABCE1 transfers mechanical energy to the ribosome and tears the ribosome subunits apart. The post-recycling complex (PRC) then re-initiates mRNA translation. Here, we probed the so far unknown architecture of the 1-MDa PRC (40S/30S·ABCE1) by chemical cross-linking and mass spectrometry (XL-MS). Our study reveals ABCE1 bound to the translational factor-binding (GTPase) site with multiple cross-link contacts of the helix–loop–helix motif to the S24e ribosomal protein. Cross-linking of the FeS cluster domain to the ribosomal protein S12 substantiates an extreme lever-arm movement of the FeS cluster domain during ribosome recycling. We were thus able to reconstitute and structurally analyse a key complex in the translational cycle, resembling the link between translation initiation and ribosome recycling.

Ribosome recycling orchestrated by ABCE1 connects translation termination and mRNA surveillance mechanisms with re-initiation. Using a cross-linking and mass spectrometry approach, Kiosze-Becker et al. provide new information on the large conformational rearrangements that occur during ribosome recycling.