46 research outputs found

    TRY plant trait database – enhanced coverage and open access

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    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

    Possibilities for preventive treatment in rheumatoid arthritis? Lessons from experimental animal models of arthritis: a systematic literature review and meta-analysis

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    Objective Current research in rheumatoid arthritis focuses on preclinical disease phases as it is hypothesised that early preclinical treatment might prevent progression to full-blown disease. Since performance of studies in prearthritis phases in humans is challenging, animal models offer an opportunity to evaluate preventive treatments. We performed a systematic literature review and summarised treatment effects during different stages of arthritis development in animal models.Methods Eight medical literature databases were systematically searched. Studies were selected if they reported effects of synthetic or biological disease-modifying antirheumatic drugs in animal models of arthritis (collagen-induced arthritis and adjuvant-induced arthritis) on arthritis severity, as measured with arthritis severity scores, paw swelling or paw volume. Quality was assessed using an 11-item checklist. Study characteristics were extracted and effect sizes obtained in high-quality studies were summarised in meta-analyses. Studies were categorised into three groups: prophylactic (prior to generation of autoantibody response), prearthritis (after induction of autoantibody response) and therapeutic intervention (after arthritis development).Results Out of 1415 screened articles, 22 studies (including n=712 animals) were eligible of good quality and included in meta-analyses. Prophylactic (16 experiments, n=312 animals) and prearthritis treatment (9 experiments, n=156 animals) both were associated with a reduction of arthritis severity (pConclusions Data of experimental studies in animal models of arthritis suggest that prophylactic and prearthritis treatment strategies are effective and hint at differences in efficacy between antirheumatic drugs.Pathophysiology and treatment of rheumatic disease

    Journal of European integration : = Revue d'intégration européenne

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    Background: Fc gamma receptors (Fc gamma Rs) play a crucial role in immunity by linking IgG antibody-mediated responses with cellular effector and regulatory functions. Genetic variants in these receptors have been previously identified as risk factors for several chronic inflammatory conditions. The present study aimed to investigate the presence of copy number variations (CNVs) in the FCGR3B gene and its potential association with the autoimmune disease rheumatoid arthritis (RA). Methodology/Principal Findings: CNV of the FCGR3B gene was studied using Multiplex Ligation Dependent Probe Amplification (MLPA) in 518 Dutch RA patients and 304 healthy controls. Surprisingly, three independent MLPA probes targeting the FCGR3B promoter measured different CNV frequencies, with probe#1 and #2 measuring 0 to 5 gene copies and probe#3 showing little evidence of CNV. Quantitative-PCR correlated with the copy number results from MLPA probe#2, which detected low copy number (1 copy) in 6.7% and high copy number (>= 3 copies) in 9.4% of the control population. No significant difference was observed between RA patients and the healthy controls, neither in the low copy nor the high copy number groups (p-values = 0.36 and 0.71, respectively). Sequencing of the FCGR3B promoter region revealed an insertion/deletion (indel) that explained the disparate CNV results of MLPA probe#1. Finally, a non-significant trend was found between the novel -256A>TG indel and RA (40.7% in healthy controls versus 35.9% in RA patients; P = 0.08). Conclusions/Significance: The current study highlights the complexity and poor characterization of the FCGR3B gene sequence, indicating that the design and interpretation of genotyping assays based on specific probe sequences must be performed with caution. Nonetheless, we confirmed the presence of CNV and identified novel polymorphisms in the FCGR3B gene in the Dutch population. Although no association was found between RA and FCGR3B CNV, the possible protective effect of the -256A>TG indel polymorphism must be addressed in larger studies.Development and application of statistical models for medical scientific researc

    Identification of CXCL13 as a Marker for Rheumatoid Arthritis Outcome Using an In Silico Model of the Rheumatic Joint

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    Objective. Rheumatoid arthritis (RA) is characterized by inflammation and joint destruction, with the degree of damage varying greatly among patients. Prediction of disease severity using known clinical and serologic risk factors is inaccurate. This study was undertaken to identify new serologic markers for RA severity using an in silico model of the rheumatic joint. Methods. An in silico model of a prototypical rheumatic joint was used to predict candidate markers associated with erosiveness. The following 4 markers were chosen for validation: tartrate-resistant acid phosphatase 5b (TRAP-5b), N-telopeptide of type I collagen (NTX), angiopoietin 2 (Ang-2), and CXCL13. Serum from 74 RA patients was used to study whether radiologic joint destruction (total erosion score and total Sharp/van der Heijde score [SHS]) after 4 years of disease was associated with serum levels at the time of diagnosis. Serum marker levels were determined using enzyme-linked immunosorbent assays. For confirmation, baseline serum levels were analyzed for an association with progression of joint damage over 7 years of followup in a cohort of 155 patients with early RA. Results. Comparison of high and low quartiles of erosion score and SHS at 4 years showed a difference in baseline serum CXCL13 level (P = 0.011 and P = 0.018, respectively). In the confirmation cohort, elevated baseline CXCL13 levels were associated with increased rates of joint destruction during 7 years of followup (P < 0.001 unadjusted and P <= 0.004 with adjustment for C-reactive protein level). Analyzing anti-CCP-2-positive and anti-CCP-2-negative RA separately yielded a significant result only in the anti-CCP2- negative group (P <= 0.001). Conclusion. Our findings indicate that CXCL13 is a novel serologic marker predictive of RA severity. This marker was identified with the help of an in silico model of the RA joint.Pathophysiology and treatment of rheumatic disease
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