Breakthrough Infections in SARS-CoV-2-Vaccinated Multiple Myeloma Patients Improve Cross-Protection against Omicron Variants.

Patients with multiple myeloma (MM) are a heterogenous, immunocompromised group with increased risk for COVID-19 morbidity and mortality but impaired responses to primary mRNA SARS-CoV-2 vaccination. The effects of booster vaccinations and breakthrough infections (BTIs) on antibody (Ab) levels and cross-protection to variants of concern (VOCs) are, however, not sufficiently evaluated. Therefore, we analysed humoral and cellular vaccine responses in MM patients stratified according to disease stage/treatment into group (1) monoclonal gammopathy of undetermined significance, (2) after stem cell transplant (SCT) without immunotherapy (IT), (3) after SCT with IT, and (4) progressed MM, and in healthy subjects (prospective cohort study). In contrast to SARS-CoV-2 hu-1-specific Ab levels, Omicron-specific Abs and their cross-neutralisation capacity remained low even after three booster doses in a majority of MM patients. In particular, progressed MM patients receiving anti-CD38 mAb and those after SCT with IT were Ab low responders and showed delayed formation of spike-specific B memory cells. However, MM patients with hybrid immunity (i.e., vaccination and breakthrough infection) had improved cross-neutralisation capacity against VOCs, yet in the absence of severe COVID-19 disease. Our results indicate that MM patients require frequent variant-adapted booster vaccinations and/or changes to other vaccine formulations/platforms, which might have similar immunological effects as BTIs.

Extensive thoracoabdominal aortic electro septotomy: A case report of a novel approach in the treatment of chronic aortic dissections.

Treatment of post-dissection arch and thoracoabdominal aortic aneurysms presents significant therapeutic challenges. True lumen collapse or take off of aortic branches from the false lumen makes endograft alignment difficult, if not impossible. We present herein the first successful case of an extensive thoracoabdominal electro aortic septotomy of the entire dissection membrane from the aortic arch down to the aortic bifurcation during an open redo aortic arch replacement employing the frozen elephant trunk technique. The procedure was performed on a 59 years old female patient presenting with a progressive post-dissection aortic aneurysm during follow-up with a maximum diameter of 6 cm 11 years after operating on an acute type A aortic dissection. Due to the extensive longitudinal aortic electric septotomy, we created a new "common lumen" for subsequent endovascular completion of the repair.

EUBUCCO v0.1: European building stock characteristics in a common and open database for 200+ million individual buildings.

Building stock management is becoming a global societal and political issue, inter alia because of growing sustainability concerns. Comprehensive and openly accessible building stock data can enable impactful research exploring the most effective policy options. In Europe, efforts from citizen and governments generated numerous relevant datasets but these are fragmented and heterogeneous, thus hindering their usability. Here, we present EUBUCCO v0.1, a database of individual building footprints for ~202 million buildings across the 27 European Union countries and Switzerland. Three main attributes - building height, construction year and type - are included for respectively 73%, 24% and 46% of the buildings. We identify, collect and harmonize 50 open government datasets and OpenStreetMap, and perform extensive validation analyses to assess the quality, consistency and completeness of the data in every country. EUBUCCO v0.1 provides the basis for high-resolution urban sustainability studies across scales - continental, comparative or local studies - using a centralized source and is relevant for a variety of use cases, e.g., for energy system analysis or natural hazard risk assessments.

Robust and Easy-to-Use One-Pot Workflow for Label-Free Single-Cell Proteomics.

The analysis of ultralow input samples or even individual cells is essential to answering a multitude of biomedical questions, but current proteomic workflows are limited in their sensitivity and reproducibility. Here, we report a comprehensive workflow that includes improved strategies for all steps, from cell lysis to data analysis. Thanks to convenient-to-handle 1 µL sample volume and standardized 384-well plates, the workflow is easy for even novice users to implement. At the same time, it can be performed semi-automatized using CellenONE, which allows for the highest reproducibility. To achieve high throughput, ultrashort gradient lengths down to 5 min were tested using advanced µ-pillar columns. Data-dependent acquisition (DDA), wide-window acquisition (WWA), data-independent acquisition (DIA), and commonly used advanced data analysis algorithms were benchmarked. Using DDA, 1790 proteins covering a dynamic range of four orders of magnitude were identified in a single cell. Using DIA, proteome coverage increased to more than 2200 proteins identified from single-cell level input in a 20 min active gradient. The workflow enabled differentiation of two cell lines, demonstrating its suitability to cellular heterogeneity determination.

LivWell: a sub-national Dataset on the Living Conditions of Women and their Well-being for 52 Countries.

Data on women's living conditions and socio-economic development are important for understanding and addressing the pronounced challenges and inequalities faced by women worldwide. While such information is increasingly available at the national level, comparable data at the sub-national level are missing. We here present the LivWell global longitudinal dataset, which includes a set of key indicators on women's socio-economic status, health and well-being, access to basic services and demographic outcomes. It covers 447 regions in 52 countries and includes a total of 265 different indicators. The majority of these are based on 199 Demographic and Health Surveys (DHS) for the period 1990-2019 and are complemented by extensive information on socio-economic and climatic conditions in the respective regions. The resulting dataset offers various opportunities for policy-relevant research on gender inequality, inclusive development and demographic trends at the sub-national level.

Structural failure in bridging stentgrafts for branched endovascular aneurysm repair: a case-control study.

OBJECTIVE: To present a case series of spontaneous structural failure of bridging stentgrafts (BSGs) after branched endovascular aortic repair (bEVAR), as well as their failure types and their detection. While bEVAR is a safe and effective procedure, one main limitation is the reintervention rate associated with the BSGs. Structural failure of BSGs, defined as fabric disruption, stent fracture with leak or complete separation is a major cause for reinterventions and difficult to detect in computed tomography angiography (CTA). METHODS: From a multicenter bEVAR complication database, structural BSG failures were identified. Patient and BSG characteristics, detection mode, failure type, treatment and outcome were recorded and compared with bEVAR patients with intact BSGs. RESULTS: Twenty-three BSG failures were detected in 12 patients with only 43% directly identified in CTA, after a mean of 21.4 months after implantation. The BSGs were Advanta (n = 4), E-Ventus (n = 16) and BeGraft (n = 3) in 10 renal, 9 superior mesenteric, and 4 celiac branches. Religning with another BSG was successful in 20/22 cases, one BSG failure necessitated renal branch embolization (organ loss), and one mesenteric bypass surgery. Two reintervention-related mortalities occurred. CONCLUSION: Structural failure of BSGs is a serious limitation for bEVAR, which can result in high reintervention rates and serious complications. BSG failure typically occurs in single-layer types and events are clustered in patients. The necessary reinterventions carry serious morbidity and mortality. Since the use as BSG in bEVAR is off-label with all current BSG manufacturers, caution is advised regarding patient-informed consent.

Learning from urban form to predict building heights.

Understanding cities as complex systems, sustainable urban planning depends on reliable high-resolution data, for example of the building stock to upscale region-wide retrofit policies. For some cities and regions, these data exist in detailed 3D models based on real-world measurements. However, they are still expensive to build and maintain, a significant challenge, especially for small and medium-sized cities that are home to the majority of the European population. New methods are needed to estimate relevant building stock characteristics reliably and cost-effectively. Here, we present a machine learning based method for predicting building heights, which is based only on open-access geospatial data on urban form, such as building footprints and street networks. The method allows to predict building heights for regions where no dedicated 3D models exist currently. We train our model using building data from four European countries (France, Italy, the Netherlands, and Germany) and find that the morphology of the urban fabric surrounding a given building is highly predictive of the height of the building. A test on the German state of Brandenburg shows that our model predicts building heights with an average error well below the typical floor height (about 2.5 m), without having access to training data from Germany. Furthermore, we show that even a small amount of local height data obtained by citizens substantially improves the prediction accuracy. Our results illustrate the possibility of predicting missing data on urban infrastructure; they also underline the value of open government data and volunteered geographic information for scientific applications, such as contextual but scalable strategies to mitigate climate change.

The environmental footprint of health care: a global assessment.

BACKGROUND: Health-care services are necessary for sustaining and improving human wellbeing, yet they have an environmental footprint that contributes to environment-related threats to human health. Previous studies have quantified the carbon emissions resulting from health care at a global level. We aimed to provide a global assessment of the wide-ranging environmental impacts of this sector. METHODS: In this multiregional input-output analysis, we evaluated the contribution of health-care sectors in driving environmental damage that in turn puts human health at risk. Using a global supply-chain database containing detailed information on health-care sectors, we quantified the direct and indirect supply-chain environmental damage driven by the demand for health care. We focused on seven environmental stressors with known adverse feedback cycles: greenhouse gas emissions, particulate matter, air pollutants (nitrogen oxides and sulphur dioxide), malaria risk, reactive nitrogen in water, and scarce water use. FINDINGS: Health care causes global environmental impacts that, depending on which indicator is considered, range between 1% and 5% of total global impacts, and are more than 5% for some national impacts. INTERPRETATION: Enhancing health-care expenditure to mitigate negative health effects of environmental damage is often promoted by health-care practitioners. However, global supply chains that feed into the enhanced activity of health-care sectors in turn initiate adverse feedback cycles by increasing the environmental impact of health care, thus counteracting the mission of health care. FUNDING: Australian Research Council, National eResearch Collaboration Tools and Resources project.

Correction to: The urinary microbiome shows different bacterial genera in renal transplant recipients and non-transplant patients at time of acute kidney injury - a pilot study.

An amendment to this paper has been published and can be accessed via the original article.

The urinary microbiome shows different bacterial genera in renal transplant recipients and non-transplant patients at time of acute kidney injury - a pilot study.

BACKGROUND: In the past urine was considered sterile. Through the introduction of next generation sequencing, it has become clear that a urinary microbiome exists. Acute kidney injury (AKI) represents a major threat to kidney transplant recipients. Remarkable changes in the urinary metabolome occur during AKI, which may influence the urinary microbiome. To our knowledge, this is the first study that examines the urinary microbiome in renal transplant recipients (RTX) and non-transplant recipients (nRTX) at time of AKI. METHODS: In this cross-sectional pilot-study the urinary microbiome of 21 RTX and 9 nRTX with AKI was examined. Clean catch morning urine samples were obtained from all patients on the first day of AKI diagnosis. AKI was defined according to KDIGO guidelines. Urinary microbiota and the urinary metabolome during AKI were assessed in one patient. 16S rRNA sequencing was performed. Sequences were processed using UPARSE-pipeline for operational taxonomic units (OTU) and taxon finding. RESULTS: We successfully extracted and sequenced bacterial DNA from 100% of the urine samples. All 30 patients revealed at least 106,138 reads. 319 OTU and 211 different genera were identified. The microbiotic diversity richness in the RTX group was no different from the nRTX group. Eighteen genera were solely present in nRTX and 7 in RTX. CONCLUSIONS: The urinary microbiome at time of AKI showed different bacterial genera in RTX compared to nRTX. The nRTX group exhibited no different diversity to the RTX group. Irrespective of the status of a previous renal transplantation, the urinary microbiome comprised > 210 different genera. An intraindividual change in microbiota diversity and richness was observed in one study patient during recovery from AKI.

Measurements of thermophysical properties of solid and liquid NIST SRM 316L stainless steel.

In this work, we perform high accuracy measurements of thermophysical properties for the National Institute of Standards and Technology standard reference material for 316L stainless steel. As these properties can be sensitive to small changes in elemental composition even within the allowed tolerances for an alloy class, by selecting a publicly available standard reference material for study our results are particularly useful for the validation of multiphysics models of industrial metal processes. An ohmic pulse-heating system was used to directly measure the electrical resistivity, enthalpy, density, and thermal expansion as functions of temperature. This apparatus applies high current pulses to heat wire-shaped samples from room temperature to metal vaporization. The great advantage of this particular pulse-heating apparatus is the very short experimental duration of 50 µs, which is faster than the collapse of the liquid wire due to gravitational forces, as well as that it prevents any chemical reactions of the hot liquid metal with its surroundings. Additionally, a differential scanning calorimeter was used to measure specific heat capacity from room temperature to around 1400 K. All data are accompanied by uncertainties according to the guide to the expression of uncertainty in measurement.

A novel approach to immunoapheresis of C3a/C3 and proteomic identification of associates.

BACKGROUND: Complement factor C3 represents the central component of the complement cascade and its activation split product C3a plays an important role in inflammation and disease. Many human disorders are linked to dysregulation of the complement system and alteration in interaction molecules. Therefore, various therapeutic approaches to act on the complement system have been initiated. METHODS AND RESULTS: Aiming to develop a tool to eliminate C3a/C3 from the circulation, in a first step a high affine murine monoclonal antibody (mAb) (3F7E2-mAb) was generated against complement factor C3 and selected for binding to the C3a region to serve as immunoaffinity reagent. Functional testing of the 3F7E2-mAb revealed an inhibition of Zymosan-induced cleavage of C3a from C3. Subsequently, a C3a/C3 specific 3F7E2-immunoaffinity column was developed and apheresis of C3a/C3 and associates was performed. Finally, a proteomic analysis was carried out for identification of apheresis products. C3a/C3 was liberated from the 3F7E2-column together with 278 proteins. C3a/C3 interaction specificity was validated by using a haptoglobin immunoaffinity column as control and biostatistic analysis revealed 39 true C3a/C3 interactants. CONCLUSION: A novel and functionally active mAb was developed against complement factor C3a/C3 and used in a specific immunoaffinity column that allows apheresis of C3a/C3 and associates and their identification by proteomic analysis. This methodological approach of developing specific antibodies that can be used as immunoaffinity reagents to design immunoaffinity columns for elimination and further identification of associated proteins could open new avenues for the development of tailored immunotherapy in various complement-mediated or autoimmune diseases.

A Multi-center Prospective Study for Implementation of an MRI-Only Prostate Treatment Planning Workflow.

Purpose: This project investigates the feasibility of implementation of MRI-only prostate planning in a prospective multi-center study. Method and Materials: A two-phase implementation model was utilized where centers performed retrospective analysis of MRI-only plans for five patients followed by prospective MRI-only planning for subsequent patients. Feasibility was assessed if at least 23/25 patients recruited to phase 2 received MRI-only treatment workflow. Whole-pelvic MRI scans (T2 weighted, isotropic 1.6 mm voxel 3D sequence) were converted to pseudo-CT using an established atlas-based method. Dose plans were generated using MRI contoured anatomy with pseudo-CT for dose calculation. A conventional CT scan was acquired subsequent to MRI-only plan approval for quality assurance purposes (QA-CT). 3D Gamma evaluation was performed between pseudo-CT calculated plan dose and recalculation on QA-CT. Criteria was 2%, 2 mm criteria with 20% low dose threshold. Gold fiducial marker positions for image guidance were compared between pseudo-CT and QA-CT scan prior to treatment. Results: All 25 patients recruited to phase 2 were treated using the MRI-only workflow. Isocenter dose differences between pseudo-CT and QA-CT were -0.04 ± 0.93% (mean ± SD). 3D Gamma dose comparison pass-rates were 99.7% ± 0.5% with mean gamma 0.22 ± 0.07. Results were similar for the two centers using two different scanners. All gamma comparisons exceeded the 90% pass-rate tolerance with a minimum gamma pass-rate of 98.0%. In all cases the gold fiducial markers were correctly identified on MRI and the distances of all seeds to centroid were within the tolerance of 1.0 mm of the distances on QA-CT (0.07 ± 0.41 mm), with a root-mean-square difference of 0.42 mm. Conclusion: The results support the hypothesis that an MRI-only prostate workflow can be implemented safely and accurately with appropriate quality assurance methods.

Reducing Urban Greenhouse Gas Footprints.

Cities are economically open systems that depend on goods and services imported from national and global markets to satisfy their material and energy requirements. Greenhouse Gas (GHG) footprints are thus a highly relevant metric for urban climate change mitigation since they not only include direct emissions from urban consumption activities, but also upstream emissions, i.e. emissions that occur along the global production chain of the goods and services purchased by local consumers. This complementary approach to territorially-focused emission accounting has added critical nuance to the debate on climate change mitigation by highlighting the responsibility of consumers in a globalized economy. Yet, city officials are largely either unaware of their upstream emissions or doubtful about their ability to count and control them. This study provides the first internationally comparable GHG footprints for four cities (Berlin, Delhi NCT, Mexico City, and New York metropolitan area) applying a consistent method that can be extended to other global cities using available data. We show that upstream emissions from urban household consumption are in the same order of magnitude as cities' overall territorial emissions and that local policy leverage to reduce upstream emissions is larger than typically assumed.

Regression and statistical shape model based substitute CT generation for MRI alone external beam radiation therapy from standard clinical MRI sequences.

In MR only radiation therapy planning, generation of the tissue specific HU map directly from the MRI would eliminate the need of CT image acquisition and may improve radiation therapy planning. The aim of this work is to generate and validate substitute CT (sCT) scans generated from standard T2 weighted MR pelvic scans in prostate radiation therapy dose planning. A Siemens Skyra 3T MRI scanner with laser bridge, flat couch and pelvic coil mounts was used to scan 39 patients scheduled for external beam radiation therapy for localized prostate cancer. For sCT generation a whole pelvis MRI (1.6 mm 3D isotropic T2w SPACE sequence) was acquired. Patients received a routine planning CT scan. Co-registered whole pelvis CT and T2w MRI pairs were used as training images. Advanced tissue specific non-linear regression models to predict HU for the fat, muscle, bladder and air were created from co-registered CT-MRI image pairs. On a test case T2w MRI, the bones and bladder were automatically segmented using a novel statistical shape and appearance model, while other soft tissues were separated using an Expectation-Maximization based clustering model. The CT bone in the training database that was most 'similar' to the segmented bone was then transformed with deformable registration to create the sCT component of the test case T2w MRI bone tissue. Predictions for the bone, air and soft tissue from the separate regression models were successively combined to generate a whole pelvis sCT. The change in monitor units between the sCT-based plans relative to the gold standard CT plan for the same IMRT dose plan was found to be [Formula: see text] (mean ± standard deviation) for 39 patients. The 3D Gamma pass rate was [Formula: see text] (2 mm/2%). The novel hybrid model is computationally efficient, generating an sCT in 20 min from standard T2w images for prostate cancer radiation therapy dose planning and DRR generation.

TORC1 signaling exerts spatial control over microtubule dynamics by promoting nuclear export of Stu2.

The target of rapamycin complex 1 (TORC1) is a highly conserved multiprotein complex that functions in many cellular processes, including cell growth and cell cycle progression. In this study, we define a novel role for TORC1 as a critical regulator of nuclear microtubule (MT) dynamics in the budding yeast Saccharomyces cerevisiae This activity requires interactions between EB1 and CLIP-170 plus end-tracking protein (+TIP) family members with the TORC1 subunit Kog1/Raptor, which in turn allow the TORC1 proximal kinase Sch9/S6K1 to regulate the MT polymerase Stu2/XMAP215. Sch9-dependent phosphorylation of Stu2 adjacent to a nuclear export signal prevents nuclear accumulation of Stu2 before cells enter mitosis. Mutants impaired in +TIP-TORC1 interactions or Stu2 nuclear export show increased nuclear but not cytoplasmic MT length and display nuclear fusion, spindle positioning, and elongation kinetics defects. Our results reveal key mechanisms by which TORC1 signaling controls Stu2 localization and thereby contributes to proper MT cytoskeletal organization in interphase and mitosis.

Fast automated segmentation of multiple objects via spatially weighted shape learning.

Active shape models (ASMs) have proved successful in automatic segmentation by using shape and appearance priors in a number of areas such as prostate segmentation, where accurate contouring is important in treatment planning for prostate cancer. The ASM approach however, is heavily reliant on a good initialisation for achieving high segmentation quality. This initialisation often requires algorithms with high computational complexity, such as three dimensional (3D) image registration. In this work, we present a fast, self-initialised ASM approach that simultaneously fits multiple objects hierarchically controlled by spatially weighted shape learning. Prominent objects are targeted initially and spatial weights are progressively adjusted so that the next (more difficult, less visible) object is simultaneously initialised using a series of weighted shape models. The scheme was validated and compared to a multi-atlas approach on 3D magnetic resonance (MR) images of 38 cancer patients and had the same (mean, median, inter-rater) Dice's similarity coefficients of (0.79, 0.81, 0.85), while having no registration error and a computational time of 12-15 min, nearly an order of magnitude faster than the multi-atlas approach.

MRI-alone radiation therapy planning for prostate cancer: Automatic fiducial marker detection.

PURPOSE: The feasibility of radiation therapy treatment planning using substitute computed tomography (sCT) generated from magnetic resonance images (MRIs) has been demonstrated by a number of research groups. One challenge with an MRI-alone workflow is the accurate identification of intraprostatic gold fiducial markers, which are frequently used for prostate localization prior to each dose delivery fraction. This paper investigates a template-matching approach for the detection of these seeds in MRI. METHODS: Two different gradient echo T1 and T2* weighted MRI sequences were acquired from fifteen prostate cancer patients and evaluated for seed detection. For training, seed templates from manual contours were selected in a spectral clustering manifold learning framework. This aids in clustering "similar" gold fiducial markers together. The marker with the minimum distance to a cluster centroid was selected as the representative template of that cluster during training. During testing, Gaussian mixture modeling followed by a Markovian model was used in automatic detection of the probable candidates. The probable candidates were rigidly registered to the templates identified from spectral clustering, and a similarity metric is computed for ranking and detection. RESULTS: A fiducial detection accuracy of 95% was obtained compared to manual observations. Expert radiation therapist observers were able to correctly identify all three implanted seeds on 11 of the 15 scans (the proposed method correctly identified all seeds on 10 of the 15). CONCLUSIONS: An novel automatic framework for gold fiducial marker detection in MRI is proposed and evaluated with detection accuracies comparable to manual detection. When radiation therapists are unable to determine the seed location in MRI, they refer back to the planning CT (only available in the existing clinical framework); similarly, an automatic quality control is built into the automatic software to ensure that all gold seeds are either correctly detected or a warning is raised for further manual intervention.