Korstzwammen (Corticiaceae s.l.) langs de Belgische kust

Since 1982 Corticiaceae s.l. have been studied in the dune area along the Belgian coast. 66 species are listed and located in 4 woods. Exsiccata are kept at Gent, Herbarium of the State Universit

Adult-onset autoinflammation caused by somatic mutations in UBA1:A Dutch case series of patients with VEXAS

Background: A novel autoinflammatory syndrome was recently described in male patients who harbored somatic mutations in the X-chromosomal UBA1 gene. These patients were characterized by adult-onset, treatment-refractory inflammation with fever, cytopenia, dysplastic bone marrow, vacuoles in myeloid and erythroid progenitor cells, cutaneous and pulmonary inflammation, chondritis, and vasculitis, which is abbreviated as VEXAS. Objective: This study aimed to (retrospectively) diagnose VEXAS in patients who had previously been registered as having unclassified autoinflammation. We furthermore aimed to describe clinical experiences with this multifaceted, complex disease. Methods: A systematic reanalysis of whole-exome sequencing data from a cohort of undiagnosed patients with autoinflammation from academic hospitals in The Netherlands was performed. When no sequencing data were available, targeted Sanger sequencing was applied in cases with high clinical suspicion of VEXAS. Results: A total of 12 male patients who carried mutations in UBA1 were identified. These patients presented with adult-onset (mean age 67 years, range 47-79 years) autoinflammation with systemic symptoms, elevated inflammatory parameters, and multiorgan involvement, most typically involving the skin and bone marrow. Novel features of VEXAS included interstitial nephritis, cardiac involvement, stroke, and intestinal perforation related to treatment with tocilizumab. Although many types of treatment were initiated, most patients became treatment-refractory, with a high mortality rate of 50%. Conclusion: VEXAS should be considered in the differential diagnosis of males with adult-onset autoinflammation characterized by systemic symptoms and multiorgan involvement. Early diagnosis can prevent unnecessary diagnostic procedures and provide better prognostic information and more suitable treatment options, including stem cell transplantation

Role of nitrogen lewis basicity in boronate affinity chromatography of nucleosides. Anal

Urinary modified nucleosides have a potential role as cancer biomarkers, and most of the methods used in their study have utilized low-pressure phenylboronate affinity chromatography materials for the purification of the cisdiol-containing nucleosides. In this study, a boronate HPLC column was surprisingly shown not to trap the nucleosides as would be expected from experience with the classic Affigel 601 resin but showed only partial selectivity toward cis-diol groups while other groups exhibited better retention. In aprotic conditions, trapping of nucleosides was possible; however, the selectivity toward cis-diol-containing compounds was lost with the Lewis basicity of available nitrogens being the main determinant of retention. The experimental findings are compared to and confirmed by DFT calculations. Modified nucleosides are naturally occurring modifications of the "normal" nucleosides. They have various roles within many nucleic acids but are mainly found in transfer RNA. They are excreted from the body via the urine as they cannot be salvaged; moreover, some are toxic when allowed to accumulate. Many past reports have investigated the modified nucleosides as potential cancer biomarkers and indicate considerable promise. [1][2][3][4][5] The methodologies used in these studies are wide ranging; however, since the introduction of boronate affinity chromatography as a ribonucleoside-selective cleanup step, on Affi-Gel 601 (Bio-Rad), utilized by Gehrke et al., 1,2 most research employed this off-line cleanup step process in the analysis. The subsequent identification/quantification of the ribonucleosides was almost exclusively carried out via RPLC-UV methods. More recently, some CE-UV methods have also been developed. [6][7][8][9] The further potential/ demand to obtain unambiguous identification via mass spectrometric detection led to the development of some off-line boronate chromatography GC/MS procedures. 3,5,10 However, the most natural choice for the analysis of the prepurified urinary nucleosides analysis is found in LC-MS. 11 Yet, the development of LC-MS procedures for urinary nucleosides only advanced 12 when electrospray mass spectrometry (ESI-MS) became available. Past studies by our group have considered the cleanup samples prior to ESI-MS analysis, 13 the optimization of the detection conditions, 14 comparison of various mass spectrometric methods, 15 and identification of the excreted nucleosides. 16,17 Other groups have taken advantage of mass spectrometry in the study of these compounds

Implementation of Early Next-Generation Sequencing for Inborn Errors of Immunity:A Prospective Observational Cohort Study of Diagnostic Yield and Clinical Implications in Dutch Genome Diagnostic Centers

OBJECTIVE: Inborn errors of immunity (IEI) are a heterogeneous group of disorders, affecting different components of the immune system. Over 450 IEI related genes have been identified, with new genes continually being recognized. This makes the early application of next-generation sequencing (NGS) as a diagnostic method in the evaluation of IEI a promising development. We aimed to provide an overview of the diagnostic yield and time to diagnosis in a cohort of patients suspected of IEI and evaluated by an NGS based IEI panel early in the diagnostic trajectory in a multicenter setting in the Netherlands. STUDY DESIGN: We performed a prospective observational cohort study. We collected data of 165 patients with a clinical suspicion of IEI without prior NGS based panel evaluation that were referred for early NGS using a uniform IEI gene panel. The diagnostic yield was assessed in terms of definitive genetic diagnoses, inconclusive diagnoses and patients without abnormalities in the IEI gene panel. We also assessed time to diagnosis and clinical implications. RESULTS: For children, the median time from first consultation to diagnosis was 119 days versus 124 days for adult patients (U=2323; p=0.644). The median turn-around time (TAT) of genetic testing was 56 days in pediatric patients and 60 days in adult patients (U=1892; p=0.191). A definitive molecular diagnosis was made in 25/65 (24.6%) of pediatric patients and 9/100 (9%) of adults. Most diagnosed disorders were identified in the categories of immune dysregulation (n=10/25; 40%), antibody deficiencies (n=5/25; 20%), and phagocyte diseases (n=5/25; 20%). Inconclusive outcomes were found in 76/165 (46.1%) patients. Within the patient group with a genetic diagnosis, a change in disease management occurred in 76% of patients. CONCLUSION: In this cohort, the highest yields of NGS based evaluation for IEI early in the diagnostic trajectory were found in pediatric patients, and in the disease categories immune dysregulation and phagocyte diseases. In cases where a definitive diagnosis was made, this led to important disease management implications in a large majority of patients. More research is needed to establish a uniform diagnostic pathway for cases with inconclusive diagnoses, including variants of unknown significance

Transverse Momentum Dependent (TMD) Parton Distribution Functions: Status and Prospects

We review transverse momentum dependent (TMD) parton distribution functions, their application to topical issues in high-energy physics phenomenology, and their theoretical connections with QCD resummation, evolution and factorization theorems. We illustrate the use of TMDs via examples of multi-scale problems in hadronic collisions. These include transverse momentum qT spectra of Higgs and vector bosons for low qT, and azimuthal correlations in the production of multiple jets associated with heavy bosons at large jet masses. We discuss computational tools for TMDs, and present the application of a new tool, TMDLIB, to parton density fits and parameterizations

Tree migration-rates : narrowing the gap between inferred post-glacial rates and projected rates

Faster-than-expected post-glacial migration rates of trees have puzzled ecologists for a long time. In Europe, post-glacial migration is assumed to have started from the three southern European peninsulas (southern refugia), where large areas remained free of permafrost and ice at the peak of the last glaciation. However, increasing palaeobotanical evidence for the presence of isolated tree populations in more northerly microrefugia has started to change this perception. Here we use the Northern Eurasian Plant Macrofossil Database and palaeoecological literature to show that post-glacial migration rates for trees may have been substantially lower (60–260 m yr–1) than those estimated by assuming migration from southern refugia only (115–550 m yr–1), and that early-successional trees migrated faster than mid- and late-successional trees. Post-glacial migration rates are in good agreement with those recently projected for the future with a population dynamical forest succession and dispersal model, mainly for early-successional trees and under optimal conditions. Although migration estimates presented here may be conservative because of our assumption of uniform dispersal, tree migration-rates clearly need reconsideration. We suggest that small outlier populations may be a key factor in understanding past migration rates and in predicting potential future range-shifts. The importance of outlier populations in the past may have an analogy in the future, as many tree species have been planted beyond their natural ranges, with a more beneficial microclimate than their regional surroundings. Therefore, climate-change-induced range-shifts in the future might well be influenced by such microrefugia

Machine learning for beam dynamics studies at the CERN Large Hadron Collider

Machine learning entails a broad range of techniques that have been widely used in Science and Engineering since decades. High-energy physics has also profited from the power of these tools for advanced analysis of colliders data. It is only up until recently that Machine Learning has started to be applied successfully in the domain of Accelerator Physics, which is testified by intense efforts deployed in this domain by several laboratories worldwide. This is also the case of CERN, where recently focused efforts have been devoted to the application of Machine Learning techniques to beam dynamics studies at the Large Hadron Collider (LHC). This implies a wide spectrum of applications from beam measurements and machine performance optimisation to analysis of numerical data from tracking simulations of non-linear beam dynamics. In this paper, the LHC-related applications that are currently pursued are presented and discussed in detail, paying also attention to future developments