| 1. |
- Morabito, L., et al.
(author)
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Sub-arcsecond imaging with the International LOFAR Telescope: I. Foundational calibration strategy and pipeline
- 2022
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In: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 658
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Journal article (peer-reviewed)abstract
- The International LOFAR Telescope is an interferometer with stations spread across Europe. With baselines of up to ∼2000 km, LOFAR has the unique capability of achieving sub-arcsecond resolution at frequencies below 200 MHz. However, it is technically and logistically challenging to process LOFAR data at this resolution. To date only a handful of publications have exploited this capability. Here we present a calibration strategy that builds on previous high-resolution work with LOFAR. It is implemented in a pipeline using mostly dedicated LOFAR software tools and the same processing framework as the LOFAR Two-metre Sky Survey (LoTSS). We give an overview of the calibration strategy and discuss the special challenges inherent to enacting high-resolution imaging with LOFAR, and describe the pipeline, which is publicly available, in detail. We demonstrate the calibration strategy by using the pipeline on P205+55, a typical LoTSS pointing with an 8 h observation and 13 international stations. We perform in-field delay calibration, solution referencing to other calibrators in the field, self-calibration of these calibrators, and imaging of example directions of interest in the field. We find that for this specific field and these ionospheric conditions, dispersive delay solutions can be transferred between calibrators up to ∼1.5° away, while phase solution transferral works well over ∼1°. We also demonstrate a check of the astrometry and flux density scale with the in-field delay calibrator source. Imaging in 17 directions, we find the restoring beam is typically ∼0.3″ ×0.2″ although this varies slightly over the entire 5 deg2 field of view. We find we can achieve ∼80-300 μJy bm-1 image rms noise, which is dependent on the distance from the phase centre; typical values are ∼90 μJy bm-1 for the 8 h observation with 48 MHz of bandwidth. Seventy percent of processed sources are detected, and from this we estimate that we should be able to image roughly 900 sources per LoTSS pointing. This equates to ∼ 3 million sources in the northern sky, which LoTSS will entirely cover in the next several years. Future optimisation of the calibration strategy for efficient post-processing of LoTSS at high resolution makes this estimate a lower limit.
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| 2. |
- Wilman, H. R., et al.
(author)
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Genetic studies of abdominal MRI data identify genes regulating hepcidin as major determinants of liver iron concentration
- 2019
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In: Journal of Hepatology. - : Elsevier. - 0168-8278 .- 1600-0641. ; 71:3, s. 594-602
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Journal article (peer-reviewed)abstract
- Background & Aims: Excess liver iron content is common and is linked to the risk of hepatic and extrahepatic diseases. We aimed to identify genetic variants influencing liver iron content and use genetics to understand its link to other traits and diseases. Methods: First, we performed a genome-wide association study (GWAS) in 8,289 individuals from UK Biobank, whose liver iron level had been quantified by magnetic resonance imaging, before validating our findings in an independent cohort (n = 1,513 from IMI DIRECT). Second, we used Mendelian randomisation to test the causal effects of 25 predominantly metabolic traits on liver iron content. Third, we tested phenome-wide associations between liver iron variants and 770 traits and disease outcomes. Results: We identified 3 independent genetic variants (rs1800562 [C282Y] and rs1799945 [H63D] in HFE and rs855791 [V736A] in TMPRSS6) associated with liver iron content that reached the GWAS significance threshold (p <5 × 10−8). The 2 HFE variants account for ∼85% of all cases of hereditary haemochromatosis. Mendelian randomisation analysis provided evidence that higher central obesity plays a causal role in increased liver iron content. Phenome-wide association analysis demonstrated shared aetiopathogenic mechanisms for elevated liver iron, high blood pressure, cirrhosis, malignancies, neuropsychiatric and rheumatological conditions, while also highlighting inverse associations with anaemias, lipidaemias and ischaemic heart disease. Conclusion: Our study provides genetic evidence that mechanisms underlying higher liver iron content are likely systemic rather than organ specific, that higher central obesity is causally associated with higher liver iron, and that liver iron shares common aetiology with multiple metabolic and non-metabolic diseases. Lay summary: Excess liver iron content is common and is associated with liver diseases and metabolic diseases including diabetes, high blood pressure, and heart disease. We identified 3 genetic variants that are linked to an increased risk of developing higher liver iron content. We show that the same genetic variants are linked to higher risk of many diseases, but they may also be associated with some health advantages. Finally, we use genetic variants associated with waist-to-hip ratio as a tool to show that central obesity is causally associated with increased liver iron content.
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| 3. |
- Bar, N., et al.
(author)
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A reference map of potential determinants for the human serum metabolome
- 2020
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In: Nature. - : Nature Research. - 0028-0836 .- 1476-4687. ; 588:7836, s. 135-140
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Journal article (peer-reviewed)abstract
- The serum metabolome contains a plethora of biomarkers and causative agents of various diseases, some of which are endogenously produced and some that have been taken up from the environment1. The origins of specific compounds are known, including metabolites that are highly heritable2,3, or those that are influenced by the gut microbiome4, by lifestyle choices such as smoking5, or by diet6. However, the key determinants of most metabolites are still poorly understood. Here we measured the levels of 1,251 metabolites in serum samples from a unique and deeply phenotyped healthy human cohort of 491 individuals. We applied machine-learning algorithms to predict metabolite levels in held-out individuals on the basis of host genetics, gut microbiome, clinical parameters, diet, lifestyle and anthropometric measurements, and obtained statistically significant predictions for more than 76% of the profiled metabolites. Diet and microbiome had the strongest predictive power, and each explained hundreds of metabolites—in some cases, explaining more than 50% of the observed variance. We further validated microbiome-related predictions by showing a high replication rate in two geographically independent cohorts7,8 that were not available to us when we trained the algorithms. We used feature attribution analysis9 to reveal specific dietary and bacterial interactions. We further demonstrate that some of these interactions might be causal, as some metabolites that we predicted to be positively associated with bread were found to increase after a randomized clinical trial of bread intervention. Overall, our results reveal potential determinants of more than 800 metabolites, paving the way towards a mechanistic understanding of alterations in metabolites under different conditions and to designing interventions for manipulating the levels of circulating metabolites.
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| 6. |
- Clay, P. M., et al.
(author)
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Implementation of integrated ecosystem assessments in the International Council for the Exploration of the Sea-conceptualizations, practice, and progress
- 2023
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In: Ices Journal of Marine Science. - 1054-3139. ; 80:5, s. 1516-1528
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Journal article (peer-reviewed)abstract
- With increasing activities of multiple sectors in marine spaces, management of marine social-ecological systems requires more holistic approaches. Adopting such an approach, however, presents difficult institutional and disciplinary challenges. Here, we use the International Council for the Exploration of the Sea (ICES) as a case study on the implementation of ecosystem-based management (EBM) and integrated ecosystem assessments (IEAs). ICES includes EBM and IEAs in its Science Priorities and established IEA Working Groups (WGs) to carry out regional IEAs. But to what degree does this IEA WG work follow best practices? We examine policy documents, academic literature, and interview data from chairs of all IEA WGs. Results indicate mixed success. All groups acknowledge the holistic goals of IEA, and many use the IEA model as laid out by Levin et al. However, we found a significant variation in the degree to which the full model is applied. We identified two primary areas for improvement: (1) integration of social and economic issues and (2) involvement of stakeholders. We offer examples of how WGs have been making progress towards full IEAs, discuss how ICES can further support this transition, and suggest lessons with respect to the adoption of EBM and IEAs more broadly.
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| 7. |
- Flores, H., et al.
(author)
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Impact of climate change on Antarctic krill
- 2012
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In: Marine Ecology-Progress Series. - : Inter-Research Science Center. - 0171-8630 .- 1616-1599. ; 458, s. 1-19
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Journal article (peer-reviewed)abstract
- Antarctic krill Euphausia superba (hereafter 'krill') occur in regions undergoing rapid environmental change, particularly loss of winter sea ice. During recent years, harvesting of krill has in creased, possibly enhancing stress on krill and Antarctic ecosystems. Here we review the overall impact of climate change on krill and Antarctic ecosystems, discuss implications for an ecosystem-based fisheries management approach and identify critical knowledge gaps. Sea ice decline, ocean warming and other environmental stressors act in concert to modify the abundance, distribution and life cycle of krill. Although some of these changes can have positive effects on krill, their cumulative impact is most likely negative. Recruitment, driven largely by the winter survival of larval krill, is probably the population parameter most susceptible to climate change. Predicting changes to krill populations is urgent, because they will seriously impact Antarctic ecosystems. Such predictions, however, are complicated by an intense inter-annual variability in recruitment success and krill abundance. To improve the responsiveness of the ecosystem-based management approach adopted by the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR), critical knowledge gaps need to be filled. In addition to a better understanding of the factors influencing recruitment, management will require a better understanding of the resilience and the genetic plasticity of krill life stages, and a quantitative understanding of under-ice and benthic habitat use. Current precautionary management measures of CCAMLR should be maintained until a better understanding of these processes has been achieved. [GRAPHICS] .
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| 9. |
- Coenen, Mirthe, et al.
(author)
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Spatial distributions of white matter hyperintensities on brain MRI: A pooled analysis of individual participant data from 11 memory clinic cohorts
- 2023
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In: NeuroImage. Clinical. - 2213-1582. ; 40
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Journal article (peer-reviewed)abstract
- INTRODUCTION: The spatial distribution of white matter hyperintensities (WMH) on MRI is often considered in the diagnostic evaluation of patients with cognitive problems. In some patients, clinicians may classify WMH patterns as "unusual", but this is largely based on expert opinion, because detailed quantitative information about WMH distribution frequencies in a memory clinic setting is lacking. Here we report voxel wise 3D WMH distribution frequencies in a large multicenter dataset and also aimed to identify individuals with unusual WMH patterns. METHODS: Individual participant data (N=3525, including 777 participants with subjective cognitive decline, 1389 participants with mild cognitive impairment and 1359 patients with dementia) from eleven memory clinic cohorts, recruited through the Meta VCI Map Consortium, were used. WMH segmentations were provided by participating centers or performed in Utrecht and registered to the Montreal Neurological Institute (MNI)-152 brain template for spatial normalization. To determine WMH distribution frequencies, we calculated WMH probability maps at voxel level. To identify individuals with unusual WMH patterns, region-of-interest (ROI) based WMH probability maps, rule-based scores, and a machine learning method (Local Outlier Factor (LOF)), were implemented. RESULTS: WMH occurred in 82% of voxels from the white matter template with large variation between subjects. Only a small proportion of the white matter (1.7%), mainly in the periventricular areas, was affected by WMH in at least 20% of participants. A large portion of the total white matter was affected infrequently. Nevertheless, 93.8% of individual participants had lesions in voxels that were affected in less than 2% of the population, mainly located in subcortical areas. Only the machine learning method effectively identified individuals with unusual patterns, in particular subjects with asymmetric WMH distribution or with WMH at relatively rarely affected locations despite common locations not being affected. DISCUSSION: Aggregating data from several memory clinic cohorts, we provide a detailed 3D map of WMH lesion distribution frequencies, that informs on common as well as rare localizations. The use of data-driven analysis with LOF can be used to identify unusual patterns, which might serve as an alert that rare causes of WMH should be considered.
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| 10. |
- Viborg Lindskrog, Sia, et al.
(author)
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An integrated multi-omics analysis identifies prognostic molecular subtypes of non-muscle-invasive bladder cancer
- 2021
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In: Nature Communications. - : Springer Nature. - 2041-1723. ; 12:1
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Journal article (peer-reviewed)abstract
- The molecular landscape in non-muscle-invasive bladder cancer (NMIBC) is characterized by large biological heterogeneity with variable clinical outcomes. Here, we perform an integrative multi-omics analysis of patients diagnosed with NMIBC (n=834). Transcriptomic analysis identifies four classes (1, 2a, 2b and 3) reflecting tumor biology and disease aggressiveness. Both transcriptome-based subtyping and the level of chromosomal instability provide independent prognostic value beyond established prognostic clinicopathological parameters. High chromosomal instability, p53-pathway disruption and APOBEC-related mutations are significantly associated with transcriptomic class 2a and poor outcome. RNA-derived immune cell infiltration is associated with chromosomally unstable tumors and enriched in class 2b. Spatial proteomics analysis confirms the higher infiltration of class 2b tumors and demonstrates an association between higher immune cell infiltration and lower recurrence rates. Finally, the independent prognostic value of the transcriptomic classes is documented in 1228 validation samples using a single sample classification tool. The classifier provides a framework for biomarker discovery and for optimizing treatment and surveillance in next-generation clinical trials.
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