Unexplained hypothermia and bradycardia in two pediatric patients with Wegener’s granulomatosis

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Comprehensive routine diagnostic screening to identify predictive mutations, gene amplifications, and microsatellite instability in FFPE tumor material

Background: Sensitive and reliable molecular diagnostics is needed to guide therapeutic decisions for cancer patients. Although less material becomes available for testing, genetic markers are rapidly expanding. Simultaneous detection of predictive markers, including mutations, gene amplifications and MSI, will save valuable material, time and costs. Methods: Using a single-molecule molecular inversion probe (smMIP)-based targeted next-generation sequencing (NGS) approach, we developed an NGS panel allowing detection of predictive mutations in 33 genes, gene amplifications of 13 genes and microsatellite instability (MSI) by the evaluation of 55 microsatellite markers. The panel was designed to target all clinically relevant single and multiple nucleotide mutations in routinely available lung cancer, colorectal cancer, melanoma, and gastro-intestinal stromal tumor samples, but is useful for a broader set of tumor types. Results: The smMIP-based NGS panel was successfully validated and cut-off values were established for reliable gene amplification analysis (i.e. relative coverage ≥3) and MSI detection (≥30% unstable loci). After validation, 728 routine diagnostic tumor samples including a broad range of tumor types were sequenced with sufficient sensitivity (2.4% drop-out), including samples with low DNA input (< 10 ng; 88% successful), low tumor purity (5-10%; 77% successful), and cytological material (90% successful). 75% of these tumor samples showed ≥1 (likely) pathogenic mutation, including targetable mutations (e.g. EGFR, BRAF, MET, ERBB2, KIT, PDGFRA). Amplifications were observed in 5.5% of the samples, comprising clinically relevant amplifications (e.g. MET, ERBB2, FGFR1). 1.5% of the tumor samples were classified as MSI-high, including both MSI-prone and non-MSI-prone tumors. Conclusions: We developed a comprehensive workflow for predictive analysis of diagnostic tumor samples. The smMIP-based NGS analysis was shown suitable for limited amounts of histological and cytological material. As smMIP technology allows easy adaptation of panels, this approach can comply with the rapidly expanding molecular markers

A pre-transplantation risk assessment tool for graft survival in Dutch pediatric kidney recipients

Background. A prediction model for graft survival including donor and recipient characteristics could help clinical decision-making and optimize outcomes. The aim of this study was to develop a risk assessment tool for graft survival based on essential pre-transplantation parameters. Methods. The data originated from the national Dutch registry (NOTR; Nederlandse OrgaanTransplantatie Registratie). A multivariable binary logistic model was used to predict graft survival, corrected for the transplantation era and time after transplantation. Subsequently, a prediction score was calculated from the β-coefficients. For internal validation, derivation (80%) and validation (20%) cohorts were defined. Model performance was assessed with the area under the curve (AUC) of the receiver operating characteristics curve, Hosmer–Lemeshow test and calibration plots. Results. In total, 1428 transplantations were performed. Ten-year graft survival was 42% for transplantations before 1990, which has improved to the current value of 92%. Over time, significantly more living and pre-emptive transplantations have been performed and overall donor age has increased (P < .05).The prediction model included 71 829 observations of 554 transplantations between 1990 and 2021. Other variables incorporated in the model were recipient age, re-transplantation, number of human leucocyte antigen (HLA) mismatches and cause of kidney failure. The predictive capacity of this model had AUCs of 0.89, 0.79, 0.76 and 0.74 after 1, 5, 10 and 20 years, respectively (P < .01). Calibration plots showed an excellent fit. Conclusions. This pediatric pre-transplantation risk assessment tool exhibits good performance for predicting graft survival within the Dutch pediatric population. This model might support decision-making regarding donor selection to optimize graft outcomes

Can bryophyte groups increase functional resolution in tundra ecosystems?

Funding Information: This study was supported by a grant to SL from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie, Grant No. 797446 and by the Independent Research Fund Denmark, Grant no. 0135-00140B. Funding from the Academy of Finland (grant 322266), National Science Foundation (1504224, 1836839, PLR-1504381 and PLR-1836898), Independent Research Fund Denmark (9040-00314B), Moscow State University, (project No 121032500089-1), Natural Sciences and Engineering Research Council of Canada, ArcticNet, Polar Continental Shelf Program, Northern Science Training Program, Polar Knowledge Canada, Royal Canadian Mounted Police, Tomsk State University competitiveness improvement program and the Russian Science Foundation (grant No 20-67-46018) are gratefully acknowledged. Matthias Ahrens provided valuable insights on the cushion growth form, and we are most thankful. We thank Gaius Shaver and two anonymous reviewers for providing valuable critique and input to earlier versions of this manuscript. Publisher Copyright: © the author(s) or their institution(s).The relative contribution of bryophytes to plant diversity, primary productivity, and ecosystem functioning increases towards colder climates. Bryophytes respond to environmental changes at the species level, but because bryophyte species are relatively difficult to identify, they are often lumped into one functional group. Consequently, bryophyte function remains poorly resolved. Here, we explore how higher resolution of bryophyte functional diversity can be encouraged and implemented in tundra ecological studies. We briefly review previous bryophyte functional classifications and the roles of bryophytes in tundra ecosystems and their susceptibility to environmental change. Based on shoot morphology and colony organization, we then propose twelve easily distinguishable bryophyte functional groups. To illustrate how bryophyte functional groups can help elucidate variation in bryophyte effects and responses, we compiled existing data on water holding capacity, a key bryophyte trait. Although plant functional groups can mask potentially high interspecific and intraspecific variability, we found better separation of bryophyte functional group means compared with previous grouping systems regarding water holding capacity. This suggests that our bryophyte functional groups truly represent variation in the functional roles of bryophytes in tundra ecosystems. Lastly, we provide recommendations to improve the monitoring of bryophyte community changes in tundra study sites.Peer reviewe

Can bryophyte groups increase functional resolution in tundra ecosystems?

The relative contribution of bryophytes to plant diversity, primary productivity, and ecosystem functioning increases towards colder climates. Bryophytes respond to environmental changes at the species level, but because bryophyte species are relatively difficult to identify, they are often lumped into one functional group. Consequently, bryophyte function remains poorly resolved. Here, we explore how higher resolution of bryophyte functional diversity can be encouraged and implemented in tundra ecological studies. We briefly review previous bryophyte functional classifications and the roles of bryophytes in tundra ecosystems and their susceptibility to environmental change. Based on shoot morphology and colony organization, we then propose twelve easily distinguishable bryophyte functional groups. To illustrate how bryophyte functional groups can help elucidate variation in bryophyte effects and responses, we compiled existing data on water holding capacity, a key bryophyte trait. Although plant functional groups can mask potentially high interspecific and intraspecific variability, we found better separation of bryophyte functional group means compared with previous grouping systems regarding water holding capacity. This suggests that our bryophyte functional groups truly represent variation in the functional roles of bryophytes in tundra ecosystems. Lastly, we provide recommendations to improve the monitoring of bryophyte community changes in tundra study sites

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives