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Along with Arctic warming, climate models project a strong increase in Arctic precipitation in the 21st century as well as an increase in the ratio of liquid to total precipitation. In the precipitation-rich region of south-east Greenland, precipitation changes could locally have significant impacts on runoff. However, climate data are sparse in this remote region. This study focuses on improving our understanding of the past precipitation changes on Ammassalik island in south-east Greenland between 1958 and 2021. To assess past changes in air temperature at 2-meter and precipitation, output from a regional polar climate model (RACMO2.3p2) is evaluated with measurements from automatic weather stations in Tasiilaq and on Mittivakkat glacier. In addition, RACMO2.3p2 is used to assess past seasonal changes in air temperature at 2-meter, precipitation amount, precipitation phase and the altitude of the rain/snow boundary. We find that the climate model accurately represents the monthly average observed air temperature at 2-meter. While total precipitation is overestimated, interannual variability of precipitation is properly captured. We report a significant increase of summer temperature at 2-meter of +0.3°C/decade (p

Ecological values of water have gained increasing attention over the past decades in both (eco)hydrological research and water resources management. Water quality is an important ecological steering variable, and graphical water quality diagrams may aid in rapid interpretation of the hydrochemical status of a site. Traditionally used water quality diagrams for showing multiple variables (e.g. Stiff, Maucha) were developed primarily for hydrogeological purposes, with limited information on ecologically relevant nutrient parameters.This paper presents adapted classical water quality diagrams that retain the traditional information on ions for hydrogeological characterization, and additionally provide information on nutrients for ecological water quality characterization.A scaling factor is used for the minor ions to visually get them across more equally compared to the macro-ion ions in the water quality diagram. Scaling of minor ions is presented based on average concentrations, as well as on water quality policy norms. Four different water quality diagrams are presented, all with the same ions included, but with different appearances to suit different preferences of individual users. Regional, national and continental scale data are used to illustrate how the different diagrams show spatial and temporal water quality characteristics.The adapted diagrams are innovative with respect to adding comprehensive visual information on the four ecohydrologically relevant nutrient species levels (NO3, NH4, PO4, K), advanced insight in redox status from the combination of four redox sensitive parameters (Fe, NO3, SO4, NH4) and the option to scale minor ions relative to average measured concentrations or to water quality policy norms. Using policy norms for scaling has the advantage of providing an ‘alarm function’ of exceedance of norms when concentrations surpass the ring used in the diagram. We discuss possible standardisation of scaling factors to enable comparability between sites.

Computer-assisted technologies have made significant progress in fetoscopic laser surgery, including placental vessel segmentation. However, the intra- and inter-procedure variabilities in the state-of-the-art segmentation methods remain a significant hurdle. To address this, we investigated the use of conditional generative adversarial networks (cGANs) for fetoscopic image segmentation and compared their performance with the benchmark U-Net technique for placental vessel segmentation. Two deep-learning models, U-Net and pix2pix (a popular cGAN model), were trained and evaluated using a publicly available dataset and an internal validation set. The overall results showed that the pix2pix model outperformed the U-Net model, with a Dice score of 0.80 [0.70; 0.86] versus 0.75 [0.0.60; 0.84] (p-value < 0.01) and an Intersection over Union (IoU) score of 0.70 [0.61; 0.77] compared to 0.66 [0.53; 0.75] (p-value < 0.01), respectively. The internal validation dataset further validated the superiority of the pix2pix model, achieving Dice and IoU scores of 0.68 [0.53; 0.79] and 0.59 [0.49; 0.69] (p-value < 0.01), respectively, while the U-Net model obtained scores of 0.53 [0.49; 0.64] and 0.49 [0.17; 0.56], respectively. This study successfully compared U-Net and pix2pix models for placental vessel segmentation in fetoscopic images, demonstrating improved results with the cGAN-based approach. However, the challenge of achieving generalizability still needs to be addressed.

We use extremely bright and ultrashort pulses from an x-ray free-electron laser (XFEL) to measure correlations in x rays scattered from individual bioparticles. This allows us to go beyond the traditional crystallography and single-particle imaging approaches for structure investigations. We employ angular correlations to recover the three-dimensional (3D) structure of nanoscale viruses from x-ray diffraction data measured at the Linac Coherent Light Source. Correlations provide us with a comprehensive structural fingerprint of a 3D virus, which we use both for model-based and ab initio structure recovery. The analyses reveal a clear indication that the structure of the viruses deviates from the expected perfect icosahedral symmetry. Our results anticipate exciting opportunities for XFEL studies of the structure and dynamics of nanoscale objects by means of angular correlations.

This study explores the capabilities of the Coherent X-ray Imaging Instrument at the Linac Coherent Light Source to image small biological samples. The weak signal from small samples puts a significant demand on the experiment. Aerosolized Omono River virus particles of ∼40 nm in diameter were injected into the submicrometre X-ray focus at a reduced pressure. Diffraction patterns were recorded on two area detectors. The statistical nature of the measurements from many individual particles provided information about the intensity profile of the X-ray beam, phase variations in the wavefront and the size distribution of the injected particles. The results point to a wider than expected size distribution (from ∼35 to ∼300 nm in diameter). This is likely to be owing to nonvolatile contaminants from larger droplets during aerosolization and droplet evaporation. The results suggest that the concentration of nonvolatile contaminants and the ratio between the volumes of the initial droplet and the sample particles is critical in such studies. The maximum beam intensity in the focus was found to be 1.9 × 1012 photons per µm2 per pulse. The full-width of the focus at half-maximum was estimated to be 500 nm (assuming 20% beamline transmission), and this width is larger than expected. Under these conditions, the diffraction signal from a sample-sized particle remained above the average background to a resolution of 4.25 nm. The results suggest that reducing the size of the initial droplets during aerosolization is necessary to bring small particles into the scope of detailed structural studies with X-ray lasers.

Despite increasing knowledge of disease‐causing genes in human genetics, approximately half of the individuals affected by neurodevelopmental disorders remain genetically undiagnosed. Part of this missing heritability might be caused by genetic variants outside of protein‐coding genes, which are not routinely diagnostically investigated. A recent preprint identified de novo variants in the non‐coding spliceosomal snRNA gene RNU4‐2 as a cause of a frequent novel syndromic neurodevelopmental disorder. Here we mined 164 whole genome sequencing (WGS) trios from individuals with neurodevelopmental or multiple congenital anomaly disorders that received diagnostic genomic investigations at our clinic. We identify a recurrent de novo RNU4‐2 variant (NR_003137.2(RNU4‐2):n.64_65insT) in a 5‐year‐old girl with severe global developmental delay, hypotonia, microcephaly, and seizures that likely explains her phenotype, given that extensive previous genetic investigations failed to identify an alternative cause. We present detailed phenotyping of the individual obtained during a 5‐year follow‐up. This includes photographs showing recognizable facial features for this novel disorder, which might allow prioritizing other currently unexplained affected individuals sharing similar facial features for targeted investigations of RNU4‐2. This case illustrates the power of re‐analysis to solve previously unexplained cases even when a diagnostic genome remains negative. [ABSTRACT FROM AUTHOR]

Introduction: Statistical shape modelling (SSM) is used to analyse morphology, discover qualitatively and quantitatively unique shape features within a population, and generate mean shapes and shape modes that show morphological variability. Hierarchical agglomerative clustering is a machine learning analysis used to identify subgroups within a given population in relation to shape features. We tested the application of both methods in the clinically relevant scenario of patients undergoing aortic valve repair (AVR). Every year, around 5000 patients undergo surgical AVR in the UK. Aims: Evaluate aortic morphology and identify subgroups amongst patients who had undergone AVR, including Ozaki, Ross, and valve-sparing procedures using SSM and unsupervised hierarchical clustering analysis. This methodological framework can evaluate both pre- and post-surgical variability across subgroups undergoing different surgeries. Methods: Pre- (n = 47) and post- (n = 35) operative three-dimensional (3D) aortic models were reconstructed from computed tomography (CT) and cardiac magnetic resonance (CMR) images. Computational analyses for SSM and hierarchical clustering were run separately for the two subgroups, assessing (a) ascending aorta only and (b) the whole aorta. This allows for exploring possible variations in morphological classification related to the input shape. Results: Most patients in the Ross procedure subgroup exhibited differences in aortic morphology from other subgroups, including an elongated ascending and wide aortic arch pre-operatively, and an elongated ascending aorta with a slightly enlarged sinus post-operatively. In hierarchical clustering, the Ross aortas also appeared to cluster together compared to the other surgical procedures, both pre-operatively and post-operatively. There were significant differences between clusters in terms of clustering distance in the pre-operative analyses (p = 0.003 for ascending aortas, p = 0.016 for whole aortas). There were no significant differences between the clusters in post-operative analyses (p = 0.47 for ascending, p = 0.19 for whole aorta). Conclusions: We demonstrated the feasibility of evaluating aortic morphology before and after different aortic valve surgeries using SSM and hierarchical clustering. This framework could be used to further explore shape features associated with surgical decision-making pre-operatively and, importantly, to identify subgroups whose morphology is associated with poorer clinical outcomes post-operatively. Statistical shape modelling (SSM) and unsupervised hierarchical clustering are two statistical methods that can be used to assess morphology, show morphological variations, with the latter being able to identify subgroups within a population. These methods have been applied to the population of aortic valve replacement (AVR) patients since there are different surgical procedures (traditional AVR, Ozaki, Ross, and valve-sparing). The aim is to evaluate aortic morphology and identify subgroups within this population before and after surgery. Computed tomography and cardiac magnetic resonance images were reconstructed into 3D models of the ascending aorta and whole aorta, which were then input into SSM and hierarchical clustering. The results show that the Ross aortic morphology is quite different from the other aortas. The clustering did not classify the aortas based on the surgical procedures; however, most of the Ross group did cluster together, indicating low variability within this surgical group. [ABSTRACT FROM AUTHOR]

Respiratory infections caused by Bordetella pertussis are reemerging despite high pertussis vaccination coverage. Since the introduction of the acellular pertussis vaccine in the late twentieth century, circulating B. pertussis strains increasingly lack expression of the vaccine component pertactin (Prn). In some countries, up to 90% of the circulating B. pertussis strains are deficient in Prn. To better understand the resurgence of pertussis, we investigated the response of human monocyte-derived dendritic cells (moDCs) to naturally circulating Prn-expressing (Prn-Pos) and Prn-deficient (Prn-Neg) B. pertussis strains from 2016 in the Netherlands. Transcriptome analysis of moDC showed enriched IFNα response-associated gene expression after exposure to Prn-Pos B. pertussis strains, whereas the Prn-Neg strains induced enriched expression of interleukin- and TNF-signaling genes, as well as other genes involved in immune activation. Multiplex immune assays confirmed enhanced proinflammatory cytokine secretion by Prn-Neg stimulated moDC. Comparison of the proteomes from the Prn-Pos and Prn-Neg strains revealed, next to the difference in Prn, differential expression of a number of other proteins including several proteins involved in metabolic processes. Our findings indicate that Prn-deficient B. pertussis strains induce a distinct and stronger immune activation of moDCs than the Prn-Pos strains. These findings highlight the role of pathogen adaptation in the resurgence of pertussis as well as the effects that vaccine pressure can have on a bacterial population.

To achieve a more sustainable management of the subsiding Dutch peatlands, adaptations such as progressively higher surface water levels, pressurized field drains and a transition from dairy farming to paludiculture are considered. However, a clear understanding of implementation pathways for adaptive management strategies is lacking. Therefore, we used the RE:PEAT tool to elucidate the short-term and long-term impacts during 2025–2100 of two adaptive management strategies in Polder Zegveld and how to fairly distribute the costs and benefits of these strategies among the stakeholder groups. The strategies resulted in marked differences in soil subsidence and temporal trends in societal costs and benefits that affected stakeholders unequally. The adaptations were shown to reduce soil subsidence and enhance the sustainability of peatland management. We explored several options for a collective implementation of the adaptative management strategies. In addition, we discuss several ideas to further capitalize on the potential of the RE:PEAT tool to support peatland management. Currently, we are developing additional features that enable high spatio-temporal resolution simulations of the integrated dynamics of the surface water system, the shallow groundwater system, rainfall-runoff processes and solute transport. In combination with the PCDitch model, this will also enable detailed ecological assessments. This will pave the way for implementation pathways for adaptive management strategies that will contribute to a more sustainable peatland management.

Slitere National Park in Latvia is home to rich fens with many endangered and threatened plant species. This study aims to address how the hydrological systems affect vegetation biodiversity (cf. Wolejko et al. 2019) in the mire systems of the National Park: the base-rich inter-dune mires and extremely base-rich calcareous fens. Groundwater samples from these areas were collected for measurements of ion composition and natural isotopes of C, H and O. Also, we simulated groundwater flow paths from the highest local topographical point (a nearby sandy plateau) to the sea, and calculated the residence times of these groundwater flows. The results show that the inter-dune mires are supplied by a mixture of local and regional groundwater systems. The groundwater supply at one of the inter-dune mires was dominated by local groundwater flow from adjacent dunes, but we also detected a small input of calcareous water. This dominance of local groundwater may have resulted from the presence of drainage ditches and a small stream that drains into the Baltic Sea. In contrast, the extremely base-rich fens were found to be solely dependent on regional groundwater which is likely to discharge at the plateau foothills due to the presence of fault structures. Thus, the mires in Slitere National Park are not as undisturbed as was previously believed. Drainage may have affected the original hydrological flow paths. Further research on the extent of these changes is recommended to preserve the endangered species and high biodiversity of these fens. Also, in order to trace the origin of groundwater flows, further investigation into the larger landscape beyond the plateau might be required.