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High-resolution volume reconstruction from multiple motion-corrupted stacks of 2D slices plays an increasing role for fetal brain Magnetic Resonance Imaging (MRI) studies. Currently existing reconstruction methods are time-consuming and often require user interactions to localize and extract the brain from several stacks of 2D slices. We propose a fully automatic framework for fetal brain reconstruction that consists of four stages: 1) fetal brain localization based on a coarse segmentation by a Convolutional Neural Network (CNN), 2) fine segmentation by another CNN trained with a multi-scale loss function, 3) novel, single-parameter outlier-robust super-resolution reconstruction, and 4) fast and automatic high-resolution visualization in standard anatomical space suitable for pathological brains. We validated our framework with images from fetuses with normal brains and with variable degrees of ventriculomegaly associated with open spina bifida, a congenital malformation affecting also the brain. Experiments show that each step of our proposed pipeline outperforms state-of-the-art methods in both segmentation and reconstruction comparisons including expert-reader quality assessments. The reconstruction results of our proposed method compare favorably with those obtained by manual, labor-intensive brain segmentation, which unlocks the potential use of automatic fetal brain reconstruction studies in clinical practice.

Greenhouse gas emissions need to be drastically reduced to mitigate the environmental impacts caused by climate change, and to lead to a transformation of the European energy system. A model landscape consisting of four final energy consumption sector models with high spatial (NUTS-3) and temporal (hourly) resolution and the multi-energy system model ISAaR is extended and applied to investigate the transformation pathway of the European energy sector in the deep emission mitigation scenario solidEU. The solidEU scenario describes not only the techno-economic but also the socio-political contexts, and it includes the EU27 + UK, Norway, and Switzerland. The scenario analysis shows that volatile renewable energy sources (vRES) dominate the energy system in 2050. In addition, the share of flexible sector coupling technologies increases to balance electricity generation from vRES. Seasonal differences are balanced by hydrogen storage with a seasonal storage profile. The deployment rates of vRES in solidEU show that a fast, profound energy transition is necessary to achieve European climate protection goals.

•Outlier-robust slice-based motion correction for functional fetal brain imaging.•Huber L2 identified as suitable regularization for volumetric reconstruction.•Signal quality assessment benchmark for functional fetal brain analysis.•Efficient use of scanning time facilitated by reduction of motion corrupted data. Motion correction is an essential preprocessing step in functional Magnetic Resonance Imaging (fMRI) of the fetal brain with the aim to remove artifacts caused by fetal movement and maternal breathing and consequently to suppress erroneous signal correlations. Current motion correction approaches for fetal fMRI choose a single 3D volume from a specific acquisition timepoint with least motion artefacts as reference volume, and perform interpolation for the reconstruction of the motion corrected time series. The results can suffer, if no low-motion frame is available, and if reconstruction does not exploit any assumptions about the continuity of the fMRI signal. Here, we propose a novel framework, which estimates a high-resolution reference volume by using outlier-robust motion correction, and by utilizing Huber L2 regularization for intra-stack volumetric reconstruction of the motion-corrected fetal brain fMRI. We performed an extensive parameter study to investigate the effectiveness of motion estimation and present in this work benchmark metrics to quantify the effect of motion correction and regularised volumetric reconstruction approaches on functional connectivity computations. We demonstrate the proposed framework’s ability to improve functional connectivity estimates, reproducibility and signal interpretability, which is clinically highly desirable for the establishment of prognostic noninvasive imaging biomarkers. The motion correction and volumetric reconstruction framework is made available as an open-source package of NiftyMIC.

Background Eukaryotic cells are highly compartmentalized by a variety of organelles that carry out specific cellular processes. The position of these organelles within the cell is elaborately regulated and vital for their function. For instance, the position of lysosomes relative to the nucleus controls their degradative capacity and is altered in pathophysiological conditions. The molecular components orchestrating the precise localization of organelles remain incompletely understood. A confounding factor in these studies is the fact that organelle positioning is surprisingly non-trivial to address e.g., perturbations that affect the localization of organelles often lead to secondary phenotypes such as changes in cell or organelle size. These phenotypes could potentially mask effects or lead to the identification of false positive hits. To uncover and test potential molecular components at scale, accurate and easy-to-use analysis tools are required that allow robust measurements of organelle positioning. Results Here, we present an analysis workflow for the faithful, robust, and quantitative analysis of organelle positioning phenotypes. Our workflow consists of an easy-to-use Fiji plugin and an R Shiny App. These tools enable users without background in image or data analysis to (1) segment single cells and nuclei and to detect organelles, (2) to measure cell size and the distance between detected organelles and the nucleus, (3) to measure intensities in the organelle channel plus one additional channel, (4) to measure radial intensity profiles of organellar markers, and (5) to plot the results in informative graphs. Using simulated data and immunofluorescent images of cells in which the function of known factors for lysosome positioning has been perturbed, we show that the workflow is robust against common problems for the accurate assessment of organelle positioning such as changes of cell shape and size, organelle size and background. Conclusions OrgaMapper is a versatile, robust, and easy-to-use automated image analysis workflow that can be utilized in microscopy-based hypothesis testing and screens. It effectively allows for the mapping of the intracellular space and enables the discovery of novel regulators of organelle positioning.

Hyperspectral imaging (HSI) has shown promise in the field of intra-operative imaging and tissue differentiation as it carries the capability to provide real-time information invisible to the naked eye whilst remaining label free. Previous iterations of intra-operative HSI systems have shown limitations, either due to carrying a large footprint limiting ease of use within the confines of a neurosurgical theater environment, having a slow image acquisition time, or by compromising spatial/spectral resolution in favor of improvements to the surgical workflow. Lightfield hyperspectral imaging is a novel technique that has the potential to facilitate video rate image acquisition whilst maintaining a high spectral resolution. Our pre-clinical and first-in-human studies (IDEAL 0 and 1, respectively) demonstrate the necessary steps leading to the first use of a real-time lightfield hyperspectral system in neuro-oncology surgery. A lightfield hyperspectral camera (Cubert Ultris ×50) was integrated in a bespoke imaging system setup so that it could be safely adopted into the open neurosurgical workflow whilst maintaining sterility. Our system allowed the surgeon to capture hyperspectral data (155 bands, 350-1,000 nm) at 1.5 Hz. Following successful implementation in a pre-clinical setup (IDEAL 0), our system was evaluated during brain tumor surgery in a single patient to remove a posterior fossa meningioma (IDEAL 1). Feedback from the theater team was analyzed and incorporated in a follow-up design aimed at implementing an IDEAL 2a study. Focusing on our IDEAL 1 study results, hyperspectral information was acquired from the cerebellum and associated meningioma with minimal disruption to the neurosurgical workflow. To the best of our knowledge, this is the first demonstration of HSI acquisition with 100+ spectral bands at a frame rate over 1Hz in surgery. This work demonstrated that a lightfield hyperspectral imaging system not only meets the design criteria and specifications outlined in an IDEAL-0 (pre-clinical) study, but also that it can translate into clinical practice as illustrated by a successful first in human study (IDEAL 1). This opens doors for further development and optimisation, given the increasing evidence that hyperspectral imaging can provide live, wide-field, and label-free intra-operative imaging and tissue differentiation.

Background Physical inactivity is a globally growing public health problem, contributing to significant disease burden (cardiovascular disease, diabetes, cancers, depression) and associated healthcare and societal costs. In Austria, several underserved groups (UGs) display lower than average physical activity (PA) levels, including people aged 30–45 and 60 + years, and those without employment, with minimal education level, or with migration background. PA promotion requires an approach that answers to local circumstances and the specific needs of UGs, to develop tailored and contextualized concepts. The public involvement project “Ganz Salzburg Bewegen” [“All of Salzburg Moving”] aimed to develop such concepts for UGs in the city of Salzburg, Austria. Methods In 2023, we conducted a large-scale participatory design process in the Lehen district of the city of Salzburg, involving citizens from UGs in needs assessment and ideation of concepts for PA promotion. Over 400 citizens engaged in a four-day community conversation event, eight citizen interviewers spoke with 53 peers, and 80 citizens participated in a two-day ideas workshop, co-designing PA promotion concepts together with design and PA promotion experts. Results The process resulted in 98 ideas addressing issues of inclusivity, accessibility and affordability of PA, and including aspects of community building and social participation to support engagement and motivation for PA. Ten ideas were selected, developed further in collaboration with design experts, and presented in a public exhibition at which citizens voted for their favourites with over 960 “likes”. Our evaluation showed that there was good representation from UGs, and that 90–97% of citizens were satisfied with their engagement in the project, felt they could adequately express their personal opinions, and thought they could comprehend the tasks and explanations for different activities well. The Public and Patient Engagement Evaluation Tool (PPEET) indicated overall good quality of involvement activities. Conclusions This public involvement project has successfully employed participatory design methods at large scale to catalyze change for PA in an urban setting. This practice example and our learnings throughout the process may offer transferable insights to others who plan participatory projects and co-design for PA promotion in the public domain and with UGs. Plain English summary Many people in Austria are not physically active enough. This can lead to serious health problems like heart disease, diabetes, cancer, and depression. This issue is especially common among certain groups, including adults aged 30–45 and 60+, people without jobs, those with limited education, and people from migrant backgrounds. To help, we need solutions that fit the needs of these groups and their local communities. The project “All of Salzburg Moving” focused on creating ways to encourage physical activity in the Lehen neighborhood of Salzburg, Austria. In 2023, we involved over 500 local residents through street events, interviews, and workshops. This included citizens working together with experts to identify barriers to being active and brainstorm creative solutions. Participants came up with 98 ideas, many of which focused on making physical activity easier to access, more inclusive, and more affordable. These ideas also emphasized the importance of building a sense of community to motivate people to stay active. Ten of the best ideas were refined with professional designers and displayed in a public exhibition, where residents voted on their favourites. The feedback from participants was very positive, with most feeling that their voices were heard, and the activities were easy to understand. We are now looking for funding to put the top ideas into action and test how well they work in real life. This project showed that involving the community can inspire meaningful and practical solutions to improve physical activity.

Maintaining plasma membrane tension is important for eukaryotic cells. How altered membrane tension is sensed and relayed to downstream factors, such as the target of rapamyin complex 2 (TORC2), is poorly understood. Reorganization of a signalling lipid into discrete membrane domains is now shown to inactivate TORC2 in yeast.

Objective Reliable airway patency diagnosis in fetal tracheolaryngeal obstruction is crucial to select and plan ex utero intrapartum treatment (EXIT) surgery. We compared the clinical utility of magnetic resonance imaging (MRI) super-resolution reconstruction (SRR) of the trachea, which can mitigate unpredictable fetal motion effects, with standard 2-dimensional (2D) MRI for airway patency diagnosis and assessment of fetal neck mass anatomy. Study Design A single-center case series of 7 consecutive singleton pregnancies with complex upper airway obstruction (2013-2019). Setting A tertiary fetal medicine unit performing EXIT surgery. Methods MRI SRR of the trachea was performed involving rigid motion correction of acquired 2D MRI slices combined with robust outlier detection to reconstruct an isotropic high-resolution volume. SRR, 2D MRI, and paired data were blindly assessed by 3 radiologists in 3 experimental rounds. Results Airway patency was correctly diagnosed in 4 of 7 cases (57%) with 2D MRI as compared with 2 of 7 cases (29%) with SRR alone or paired 2D MRI and SRR. Radiologists were more confident (P = .026) in airway patency diagnosis when using 2D MRI than SRR. Anatomic clarity was higher with SRR (P = .027) or paired data (P = .041) in comparison with 2D MRI alone. Radiologists detected further anatomic details by using paired images versus 2D MRI alone (P < .001). Cognitive load, as assessed by the NASA Task Load Index, was increased with paired or SRR data in comparison with 2D MRI. Conclusion The addition of SRR to 2D MRI does not increase fetal airway patency diagnostic accuracy but does provide improved anatomic information, which may benefit surgical planning of EXIT procedures.