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Scaffolds are needed that can act as temporary templates for bone regeneration and actively stimulate vascularized bone growth so that bone grafting is no longer necessary. To achieve this, the scaffold must have a suitable interconnected pore network and be made of an osteogenic material. Bioactive glass is an ideal material because it rapidly bonds to bone and degrades over time, releasing soluble silica and calcium ions that are thought to stimulate osteoprogenitor cells. Melt-derived bioactive glasses, such as the original Bioglass composition, are available commercially, but porous scaffolds have been difficult to produce because Bioglass and similar compositions crystallize on sintering. Sol-gel foam scaffolds have been developed that avoid this problem. They have a hierarchical pore structure comprising interconnected macropores, with interconnect diameters in excess of the 100 microm that is thought to be needed for vascularized bone ingrowth, and an inherent nanoporosity of interconnected mesopores (2-50 nm) which is beneficial for the attachment of osteoprogenitor cells. They also have a compressive strength in the range of cancellous bone. This paper describes the optimized sol-gel foaming process and illustrates the importance of optimizing the hierarchical structure from the atomic through nano, to the macro scale with respect to biological response. [ABSTRACT FROM AUTHOR]

Inorganic/organic hybrid biomaterials have been developed to obtain synergy of the inorganic and organic co-networks for implant and 3D printed scaffold applications, providing combinations of bioactivity, toughness and controlled biodegradation. SiO 2 -CaO CME /PTHF/PCL-diCOOH sol-gel hybrids previously showed potential for osteogenesis due to the addition of calcium to the silicate network of the hybrid, using calcium methoxyethoxide (CME) as the calcium source. Here, we investigate other calcium sources to improve mechanical properties and printability of the hybrid inks. The aim was to produce porous scaffolds with mechanical properties similar to trabecular bone. The original Ca-free hybrid composition SiO 2 /PTHF/PCL-diCOOH was highly elastic and the addition of Ca increased strength while introducing bioactivity, with hydroxyapatite formation in simulated body fluid (SBF), and no negative effects on the metabolic activity of human bone marrow stromal cells (hBMSCs). However, when the hybrid was 3D printed by Direct Ink Writing, the mechanical properties were insufficient for a load sharing bone scaffold. Alternative calcium sources were investigated here, using concentrated CME (cCME), calcium hydroxide (CH), calcium ethoxide (CE), and calcium ethoxyethoxide (CEE). CEE improved the overall printability and final structure of the hybrid scaffold obtained and apatite formed on its surface in SBF. This hybrid reached the highest stress at failure (0.55 ± 0.08 MPa) and toughness modulus (0.13 ± 0.03 MPa), with a corresponding strain of >50%. With this calcium source and the optimal 70 : 30 TEOS : CEE molar ratio, scaffold properties were optimised by increasing the strut size whilst maintaining the interconnected channel size >400 μm and increasing the inorganic : organic ratio. Using a TEOS : PCL-diCOOH ratio of 85 : 15 wt%, giving a final inorganic content of 35.7 wt%, showed the optimal mechanical properties with a stress at failure of 3.1 ± 0.54 MPa for strain of 26%, and a toughness modulus of 0.58 ± 0.06 MPa, whilst keeping an open porosity >38%. Compressive strength was within the lower range of trabecular bone (2-12 MPa), and there was no observed cytotoxic effect on hBMSCs, indicating potential for use of this hybrid for bone regeneration., Competing Interests: There are no conflicts to declare., (This journal is © The Royal Society of Chemistry.)

Automated blood vessel segmentation is critical for biomedical image analysis, as vessel morphology changes are associated with numerous pathologies. Still, precise segmentation is difficult due to the complexity of vascular structures, anatomical variations across patients, the scarcity of annotated public datasets, and the quality of images. Our goal is to provide a foundation on the topic and identify a robust baseline model for application to vascular segmentation using a new imaging modality, Hierarchical Phase-Contrast Tomography (HiP-CT). We begin with an extensive review of current machine-learning approaches for vascular segmentation across various organs. Our work introduces a meticulously curated training dataset, verified by double annotators, consisting of vascular data from three kidneys imaged using HiP-CT as part of the Human Organ Atlas Project. HiP-CT pioneered at the European Synchrotron Radiation Facility in 2020, revolutionizes 3D organ imaging by offering a resolution of around 20 μm/voxel and enabling highly detailed localised zooms up to 1-2 μm/voxel without physical sectioning. We leverage the nnU-Net framework to evaluate model performance on this high-resolution dataset, using both known and novel samples, and implementing metrics tailored for vascular structures. Our comprehensive review and empirical analysis on HiP-CT data sets a new standard for evaluating machine learning models in high-resolution organ imaging. Our three experiments yielded Dice similarity coefficient (DSC) scores of 0.9523, 0.9410, and 0.8585, respectively. Nevertheless, DSC primarily assesses voxel-to-voxel concordance, overlooking several crucial characteristics of the vessels and should not be the sole metric for deciding the performance of vascular segmentation. Our results show that while segmentations yielded reasonably high scores-such as centerline DSC ranging from 0.82 to 0.88, certain errors persisted. Specifically, large vessels that collapsed due to the lack of hydrostatic pressure (HiP-CT is an ex vivo technique) were segmented poorly. Moreover, decreased connectivity in finer vessels and higher segmentation errors at vessel boundaries were observed. Such errors, particularly in significant vessels, obstruct the understanding of the structures by interrupting vascular tree connectivity. Our study establishes the benchmark across various evaluation metrics, for vascular segmentation of HiP-CT imaging data, an imaging technology that has the potential to substantively shift our understanding of human vascular networks., (© 2024. The Author(s).)

Purpose: To date, no non-invasive imaging modality has been employed to profile the structural intricacies of the hippocampal arterial microvasculature in humans. We hypothesised that synchrotron-based imaging of the human hippocampus would enable precise characterisation of the arterial microvasculature., Methods: Two preserved human brains from, a 69-year-old female and a 63-year-old male body donors were imaged using hierarchical phase-contrast tomography (HiP-CT) with synchrotron radiation at multiple voxel resolutions from 25.08 μm down to 2.45 μm. Subsequent manual and semi-automatic artery segmentation were performed followed by morphometric analyses. These data were compared to published data from alternative methodologies., Results: HiP-CT made it possible to segment in context the arterial architecture of the human hippocampus. Our analysis identified anterior, medial and posterior hippocampal arteries arising from the P2 segment of the posterior cerebral artery on the image slices. We mapped arterial branches with external diameters greater than 50 μm in the hippocampal region. We visualised vascular asymmetry and quantified arterial structures with diameters as small as 7 μm., Conclusions: Through the application of HiP-CT, we have provided the first imaging visualisation and quantification of the arterial system of the human hippocampus at high resolution in the context of whole brain imaging. Our results bridge the gap between anatomical and histological scales., (© 2024. The Author(s).)

Efficient algorithms are needed to segment vasculature in new three-dimensional (3D) medical imaging datasets at scale for a wide range of research and clinical applications. Manual segmentation of vessels in images is time-consuming and expensive. Computational approaches are more scalable but have limitations in accuracy. We organized a global machine learning competition, engaging 1,401 participants, to help develop new deep learning methods for 3D blood vessel segmentation. This paper presents a detailed analysis of the top-performing solutions using manually curated 3D Hierarchical Phase-Contrast Tomography datasets of the human kidney, focusing on the segmentation accuracy and morphological analysis, thereby establishing a benchmark for future studies in blood vessel segmentation within phase-contrast tomography imaging., Competing Interests: Competing Interests GMW is a paid consultant for the NIH-funded Human BioMolecular Atlas Program (HuBMAP). Other authors declare no competing interests.

Transitions in eruptive style during volcanic eruptions strongly depend on how easily gas and magma decouple during ascent. Stronger gas-melt coupling favors highly explosive eruptions, whereas weaker coupling promotes lava fountaining and lava flows. The mechanisms producing these transitions are still poorly understood because of a lack of direct observations of bubble dynamics under natural magmatic conditions. Here, we combine x-ray radiography with a novel high-pressure/high-temperature apparatus to observe and quantify in real-time bubble growth and coalescence in basaltic magmas from 100 megapascals to surface. For low-viscosity magmas, bubbles coalesce and recover a spherical shape within 3 seconds, implying that, for lava fountaining activity, gas and melt remain coupled during the ascent up to the last hundred meters of the conduit. For higher-viscosity magmas, recovery times become longer, promoting connected bubble pathways. This apparatus opens frontiers in unraveling magmatic/volcanic processes, leading to improved hazard assessment and risk mitigation.

Automated blood vessel segmentation is critical for biomedical image analysis, as vessel morphology changes are associated with numerous pathologies. Still, precise segmentation is difficult due to the complexity of vascular structures, anatomical variations across patients, the scarcity of annotated public datasets, and the quality of images. Our goal is to provide a foundation on the topic and identify a robust baseline model for application to vascular segmentation using a new imaging modality, Hierarchical Phase-Contrast Tomography (HiP-CT). We begin with an extensive review of current machine learning approaches for vascular segmentation across various organs. Our work introduces a meticulously curated training dataset, verified by double annotators, consisting of vascular data from three kidneys imaged using Hierarchical Phase-Contrast Tomography (HiP-CT) as part of the Human Organ Atlas Project. HiP-CT, pioneered at the European Synchrotron Radiation Facility in 2020, revolutionizes 3D organ imaging by offering resolution around 20 μm /voxel, and enabling highly detailed localized zooms up to 1 μm /voxel without physical sectioning. We leverage the nnU-Net framework to evaluate model performance on this high-resolution dataset, using both known and novel samples, and implementing metrics tailored for vascular structures. Our comprehensive review and empirical analysis on HiP-CT data sets a new standard for evaluating machine learning models in high-resolution organ imaging. Our three experiments yielded Dice scores of 0.9523 and 0.9410, and 0.8585, respectively. Nevertheless, DSC primarily assesses voxel-to-voxel concordance, overlooking several crucial characteristics of the vessels and should not be the sole metric for deciding the performance of vascular segmentation. Our results show that while segmentations yielded reasonably high scores-such as centerline Dice values ranging from 0.82 to 0.88, certain errors persisted. Specifically, large vessels that collapsed due to the lack of hydro-static pressure (HiP-CT is an ex vivo technique) were segmented poorly. Moreover, decreased connectivity in finer vessels and higher segmentation errors at vessel boundaries were observed. Such errors, particularly in significant vessels, obstruct the understanding of the structures by interrupting vascular tree connectivity. Through our review and outputs, we aim to set a benchmark for subsequent model evaluations using various modalities, especially with the HiP-CT imaging database., Competing Interests: Competing interests The authors declare no competing interests.

The architecture of the kidney vasculature is essential for its function. Although structural profiling of the intact rodent kidney vasculature has been performed, it is challenging to map vascular architecture of larger human organs. We hypothesised that hierarchical phase-contrast tomography (HiP-CT) would enable quantitative analysis of the entire human kidney vasculature. Combining label-free HiP-CT imaging of an intact kidney from a 63-year-old male with topology network analysis, we quantitated vasculature architecture in the human kidney down to the scale of arterioles. Although human and rat kidney vascular topologies are comparable, vascular radius decreases at a significantly faster rate in humans as vessels branch from artery towards the cortex. At branching points of large vessels, radii are theoretically optimised to minimise flow resistance, an observation not found for smaller arterioles. Structural differences in the vasculature were found in different spatial zones of the kidney reflecting their unique functional roles. Overall, this represents the first time the entire arterial vasculature of a human kidney has been mapped providing essential inputs for computational models of kidney vascular flow and synthetic vascular architectures, with implications for understanding how the structure of individual blood vessels collectively scales to facilitate organ function.

Background Current clinical imaging modalities such as CT and MRI provide resolution adequate to diagnose cardiovascular diseases but cannot depict detailed structural features in the heart across length scales. Hierarchical phase-contrast tomography (HiP-CT) uses fourth-generation synchrotron sources with improved x-ray brilliance and high energies to provide micron-resolution imaging of intact adult organs with unprecedented detail. Purpose To evaluate the capability of HiP-CT to depict the macro- to microanatomy of structurally normal and abnormal adult human hearts ex vivo. Materials and Methods Between February 2021 and September 2023, two adult human donor hearts were obtained, fixed in formalin, and prepared using a mixture of crushed agar in a 70% ethanol solution. One heart was from a 63-year-old White male without known cardiac disease, and the other was from an 87-year-old White female with a history of multiple known cardiovascular pathologies including ischemic heart disease, hypertension, and atrial fibrillation. Nondestructive ex vivo imaging of these hearts without exogenous contrast agent was performed using HiP-CT at the European Synchrotron Radiation Facility. Results HiP-CT demonstrated the capacity for high-spatial-resolution, multiscale cardiac imaging ex vivo, revealing histologic-level detail of the myocardium, valves, coronary arteries, and cardiac conduction system across length scales. Virtual sectioning of the cardiac conduction system provided information on fatty infiltration, vascular supply, and pathways between the cardiac nodes and adjacent structures. HiP-CT achieved resolutions ranging from gross (isotropic voxels of approximately 20 µm) to microscopic (approximately 6.4-µm voxel size) to cellular (approximately 2.3-µm voxel size) in scale. The potential for quantitative assessment of features in health and disease was demonstrated. Conclusion HiP-CT provided high-spatial-resolution, three-dimensional images of structurally normal and diseased ex vivo adult human hearts. Whole-heart image volumes were obtained with isotropic voxels of approximately 20 µm, and local regions of interest were obtained with resolution down to 2.3-6.4 µm without the need for sectioning, destructive techniques, or exogenous contrast agents. Published under a CC BY 4.0 license Supplemental material is available for this article. See also the editorial by Bluemke and Pourmorteza in this issue.

Improving the scalability of tissue imaging throughput with bright, coherent X-rays requires identifying and mitigating artifacts resulting from the interactions between X-rays and matter. At synchrotron sources, long-term imaging of soft tissues in solution can result in gas bubble formation or cavitation, which dramatically compromises image quality and integrity of the samples. By combining in-line phase-contrast imaging with gas chromatography in real time, we were able to track the onset and evolution of high-energy X-ray-induced gas bubbles in ethanol-embedded soft tissue samples for tens of minutes (two to three times the typical scan times). We demonstrate quantitatively that vacuum degassing of the sample during preparation can significantly delay bubble formation, offering up to a twofold improvement in dose tolerance, depending on the tissue type. However, once nucleated, bubble growth is faster in degassed than undegassed samples, indicating their distinct metastable states at bubble onset. Gas chromatography analysis shows increased solvent vaporization concurrent with bubble formation, yet the quantities of dissolved gasses remain unchanged. By coupling features extracted from the radiographs with computational analysis of bubble characteristics, we uncover dose-controlled kinetics and nucleation site-specific growth. These hallmark signatures provide quantitative constraints on the driving mechanisms of bubble formation and growth. Overall, the observations highlight bubble formation as a critical yet often overlooked hurdle in upscaling X-ray imaging for biological tissues and soft materials and we offer an empirical foundation for their understanding and imaging protocol optimization. More importantly, our approaches establish a top-down scheme to decipher the complex, multiscale radiation-matter interactions in these applications., (open access.)

Porosity in directed energy deposition (DED) deteriorates mechanical performances of components, limiting safety-critical applications. However, how pores arise and evolve in DED remains unclear. Here, we reveal pore evolution mechanisms during DED using in situ X-ray imaging and multi-physics modelling. We quantify five mechanisms contributing to pore formation, migration, pushing, growth, removal and entrapment: (i) bubbles from gas atomised powder enter the melt pool, and then migrate circularly or laterally; (ii) small bubbles can escape from the pool surface, or coalesce into larger bubbles, or be entrapped by solidification fronts; (iii) larger coalesced bubbles can remain in the pool for long periods, pushed by the solid/liquid interface; (iv) Marangoni surface shear flow overcomes buoyancy, keeping larger bubbles from popping out; and (v) once large bubbles reach critical sizes they escape from the pool surface or are trapped in DED tracks. These mechanisms can guide the development of pore minimisation strategies., (© 2024. The Author(s).)

Introduction: Hybrids consist of inorganic and organic co-networks that are indistinguishable above the nanoscale, which can lead to unprecedented combinations of properties, such as high toughness and controlled degradation. Methods: We present 3D printed bioactive hybrid scaffolds for bone regeneration, produced by incorporating calcium into our "Bouncy Bioglass", using calcium methoxyethoxide (CME) as the calcium precursor. SiO 2 -CaO CME /PTHF/PCL-diCOOH hybrid "inks" for additive manufacturing (Direct Ink Writing) were optimised for synergy of mechanical properties and open interconnected pore channels. Results and Discussion: Adding calcium improved printability. Changing calcium content (5, 10, 20, 30, and 40 mol.%) of the SiO 2 -CaO CME /PTHF/PCL-diCOOH hybrids affected printability and mechanical properties of the lattice-like scaffolds. Hybrids containing 30 mol.% calcium in the inorganic network (70S30C CME -CL) printed with 500 µm channels and 100 µm strut size achieved the highest strength (0.90 ± 0.23 MPa) and modulus of toughness (0.22 ± 0.04 MPa). These values were higher than Ca-free SiO 2 /PTHF/PCL-diCOOH hybrids (0.36 ± 0.14 MPa strength and 0.06 ± 0.01 MPa toughness modulus). Over a period of 90 days of immersion in simulated body fluid (SBF), the 70S30C CME -CL hybrids also kept a stable strain to failure (~30 %) and formed hydroxycarbonate apatite within three days. The extracts released by the 70S30C CME -CL hybrids in growth medium did not cause cytotoxic effects on human bone marrow stromal cells over 24 h of culture., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Heyraud, Tallia, Sory, Ting, Tchorzewska, Liu, Pilsworth, Lee, Hanna, Rankin and Jones.)

Imaging across different scales is essential for understanding healthy organ morphology and pathophysiological changes. The macro- and microscale three-dimensional morphology of large samples, including intact human organs, is possible with X-ray microtomography (using laboratory or synchrotron sources). Preparation of large samples for high-resolution imaging, however, is challenging due to limitations such as sample shrinkage, insufficient contrast, movement of the sample and bubble formation during mounting or scanning. Here, we describe the preparation, stabilization, dehydration and mounting of large soft-tissue samples for X-ray microtomography. We detail the protocol applied to whole human organs and hierarchical phase-contrast tomography at the European Synchrotron Radiation Facility, yet it is applicable to a range of biological samples, including complete organisms. The protocol enhances the contrast when using X-ray imaging, while preventing sample motion during the scan, even with different sample orientations. Bubbles trapped during mounting and those formed during scanning (in the case of synchrotron X-ray imaging) are mitigated by multiple degassing steps. The sample preparation is also compatible with magnetic resonance imaging, computed tomography and histological observation. The sample preparation and mounting require 24-36 d for a large organ such as a whole human brain or heart. The preparation time varies depending on the composition, size and fragility of the tissue. Use of the protocol enables scanning of intact organs with a diameter of 150 mm with a local voxel size of 1 μm. The protocol requires users with expertise in handling human or animal organs, laboratory operation and X-ray imaging., (© 2023. Springer Nature Limited.)

In-line phase contrast synchrotron tomography combined with in situ mechanical loading enables the characterisation of soft tissue micromechanics via digital volume correlation (DVC) within whole organs. Optimising scan time is important for reducing radiation dose from multiple scans and to limit sample movement during acquisition. Also, although contrasted edges provided by in-line phase contrast tomography of soft tissues are useful for DVC, the effect of phase contrast imaging on its accuracy has yet to be investigated. Due to limited time at synchrotron facilities, scan parameters are often decided during imaging and their effect on DVC accuracy is not fully understood. Here, we used previously published data of intervertebral disc phase contrast tomography to evaluate the influence of i) fibrous image texture, ii) number of projections, iii) tomographic reconstruction method, and iv) phase contrast propagation distance on DVC results. A greater understanding of how image texture influences optimal DVC tracking was obtained by visualising objective function mapping, enabling tracking inaccuracies to be identified. When reducing the number of projections, DVC was minimally affected by image high frequency noise but with a compromise in accuracy. Iterative reconstruction methods improved image signal-to-noise and consequently significantly lowered DVC displacement uncertainty. Propagation distance was shown to affect DVC accuracy. Consistent DVC results were achieved within a propagation distance range which provided contrast to the smallest scale features, where; too short a distance provided insufficient features to track, whereas too long led to edge effect inconsistencies, particularly at greater deformations. Although limited to a single sample type and image setup, this study provides general guidelines for future investigations when optimising image quality and scan times for in situ phase contrast x-ray tomography of fibrous connective tissues., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Laser powder bed fusion (LPBF) can produce high-value metallic components for many industries; however, its adoption for safety-critical applications is hampered by the presence of imperfections. The interdependency between imperfections and processing parameters remains unclear. Here, the evolution of porosity and humps during LPBF using X-ray and electron imaging, and a high-fidelity multiphase process simulation, is quantified. The pore and keyhole formation mechanisms are driven by the mixing of high temperatures and high metal vapor concentrations in the keyhole is revealed. The irregular pores are formed via keyhole collapse, pore coalescence, and then pore entrapment by the solidification front. The mixing of the fast-moving vapor plume and molten pool induces a Kelvin-Helmholtz instability at the melt track surface, forming humps. X-ray imaging and a high-fidelity model are used to quantify the pore evolution kinetics, pore size distribution, waviness, surface roughness, and melt volume under single layer conditions. This work provides insights on key criteria that govern the formation of imperfections in LPBF and suggest ways to improve process reliability., (© 2022 The Authors. Advanced Science published by Wiley-VCH GmbH.)

Multifocal microscopy (MUM), a technique to capture multiple fields of view (FOVs) from distinct axial planes simultaneously and on one camera, was used to perform micro-particle image velocimetry (µPIV) to reconstruct velocity and shear stress fields imposed by a liquid flowing around a cell. A diffraction based multifocal relay was used to capture images from three different planes with 630 nm axial spacing from which the axial positions of the flow-tracing particles were calculated using the image sharpness metric. It was shown that MUM can achieve an accuracy on the calculated velocity of around (0.52 ± 0.19) µm/s. Using fixed cells, MUM imaged the flow perturbations at sub-cellular level, which showed characteristics similar to those observed in the literature. Using live cells as an exemplar, MUM observed the effect of changing cell morphology on the local flow during perfusion. Compared to standard confocal laser scanning microscope, MUM offers a clear advantage in acquisition speed for µPIV (over 300 times faster). This is an important characteristic for rapidly evolving biological systems where there is the necessity to monitor in real time entire volumes to correlate the sample responses to the external forces., (© 2022. The Author(s).)

Background: COVID-19 is characterized by a heterogeneous clinical presentation, ranging from mild symptoms to severe courses of disease. 9-20% of hospitalized patients with severe lung disease die from COVID-19 and a substantial number of survivors develop long-COVID. Our objective was to provide comprehensive insights into the pathophysiology of severe COVID-19 and to identify liquid biomarkers for disease severity and therapy response., Methods: We studied a total of 85 lungs (n = 31 COVID autopsy samples; n = 7 influenza A autopsy samples; n = 18 interstitial lung disease explants; n = 24 healthy controls) using the highest resolution Synchrotron radiation-based hierarchical phase-contrast tomography, scanning electron microscopy of microvascular corrosion casts, immunohistochemistry, matrix-assisted laser desorption ionization mass spectrometry imaging, and analysis of mRNA expression and biological pathways. Plasma samples from all disease groups were used for liquid biomarker determination using ELISA. The anatomic/molecular data were analyzed as a function of patients' hospitalization time., Findings: The observed patchy/mosaic appearance of COVID-19 in conventional lung imaging resulted from microvascular occlusion and secondary lobular ischemia. The length of hospitalization was associated with increased intussusceptive angiogenesis. This was associated with enhanced angiogenic, and fibrotic gene expression demonstrated by molecular profiling and metabolomic analysis. Increased plasma fibrosis markers correlated with their pulmonary tissue transcript levels and predicted disease severity. Plasma analysis confirmed distinct fibrosis biomarkers (TSP2, GDF15, IGFBP7, Pro-C3) that predicted the fatal trajectory in COVID-19., Interpretation: Pulmonary severe COVID-19 is a consequence of secondary lobular microischemia and fibrotic remodelling, resulting in a distinctive form of fibrotic interstitial lung disease that contributes to long-COVID., Funding: This project was made possible by a number of funders. The full list can be found within the Declaration of interests / Acknowledgements section at the end of the manuscript., Competing Interests: Declaration of interests HHK received fees for lectures and consultations from Roche Pharma AG, Novartis, AstraZeneca, Genomic Health, Pfizer, and Amgen, all outside the present study. MMH received fees for lectures and consultations from Acceleron, Actelion, Bayer, GSK, Janssen, MSD, and Pfizer, all outside the present study. TW declares funding by the German Ministry of Research and Education. MAK and DJL declare the possession of “Nordic Bioscience” stock options. BS received fees for lectures from Boehringer Ingelheim. The other authors have no potential conflicts of interest to report., (Copyright © 2022 The Author(s). Published by Elsevier B.V. All rights reserved.)