ENIGMA-anxiety working group : Rationale for and organization of large-scale neuroimaging studies of anxiety disorders

Altres ajuts: Anxiety Disorders Research Network European College of Neuropsychopharmacology; Claude Leon Postdoctoral Fellowship; Deutsche Forschungsgemeinschaft (DFG, German Research Foundation, 44541416-TRR58); EU7th Frame Work Marie Curie Actions International Staff Exchange Scheme grant 'European and South African Research Network in Anxiety Disorders' (EUSARNAD); Geestkracht programme of the Netherlands Organization for Health Research and Development (ZonMw, 10-000-1002); Intramural Research Training Award (IRTA) program within the National Institute of Mental Health under the Intramural Research Program (NIMH-IRP, MH002781); National Institute of Mental Health under the Intramural Research Program (NIMH-IRP, ZIA-MH-002782); SA Medical Research Council; U.S. National Institutes of Health grants (P01 AG026572, P01 AG055367, P41 EB015922, R01 AG060610, R56 AG058854, RF1 AG051710, U54 EB020403).Anxiety disorders are highly prevalent and disabling but seem particularly tractable to investigation with translational neuroscience methodologies. Neuroimaging has informed our understanding of the neurobiology of anxiety disorders, but research has been limited by small sample sizes and low statistical power, as well as heterogenous imaging methodology. The ENIGMA-Anxiety Working Group has brought together researchers from around the world, in a harmonized and coordinated effort to address these challenges and generate more robust and reproducible findings. This paper elaborates on the concepts and methods informing the work of the working group to date, and describes the initial approach of the four subgroups studying generalized anxiety disorder, panic disorder, social anxiety disorder, and specific phobia. At present, the ENIGMA-Anxiety database contains information about more than 100 unique samples, from 16 countries and 59 institutes. Future directions include examining additional imaging modalities, integrating imaging and genetic data, and collaborating with other ENIGMA working groups. The ENIGMA consortium creates synergy at the intersection of global mental health and clinical neuroscience, and the ENIGMA-Anxiety Working Group extends the promise of this approach to neuroimaging research on anxiety disorders

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

Spionage im Friedensvölkerrecht

Arbeit an der Bibliothek noch nicht eingelangt - Daten nicht geprüftInnsbruck, Univ., Diplomarb., 2020(VLID)486884

Nintedanib and a bi-specific anti-VEGF/Ang2 nanobody selectively prevent brain metastases of lung adenocarcinoma cells

Brain metastases (BM) are an ever-increasing challenge in oncology, threatening quality of life and survival of many cancer patients. The majority of BM originate from lung adenocarcinoma, and stage III patients have a risk of 40-50% to develop BM in the first years of disease onset. As therapeutic options are limited, prevention of their occurrence is an attractive concept. Here we investigated whether Nintedanib (BIBF 1120), a tyrosine kinase inhibitor (TKI) targeting the VEGF pathway approved for lung adenocarcinoma, and the dual anti-VEGF-A/Ang2 nanobody BI836880 have the potential to prevent BM formation. A mouse model of brain metastasis from lung adenocarcinoma was used in which tumor cells were injected intracardially. Metastases formation occurred inside and outside of the brain and was followed by MRI, IVIS, and immunohistochemistry. BM were reduced in volume and number by both Nintedanib and the dual anti-VEGF-A/Ang2 nanobody, which translated into improved survival. Both compounds were able to normalize cerebral blood vessels at the site of brain metastatic lesions. Extracranial metastases, however, were not reduced, and meningeal metastases only partially. Interestingly, unspecific control IgG also lead to brain vessel normalization and reduction of brain and meningeal metastases. This data indicates a brain-specific group effect of antiangiogenic compounds with respect to metastasis prevention, most likely by preventing an early angiogenic switch. Thus, Nintedanib and BI836880 are promising candidates for future BM preventive study concepts in lung adenocarcinoma patients

Shared and anxiety-specific pediatric psychopathology dimensions manifest distributed neural correlates

Background: Imaging research has not yet delivered reliable psychiatric biomarkers. One challenge, particularly among youth, is high comorbidity. This challenge might be met through canonical correlation analysis (CCA) designed to model mutual dependencies between symptom dimensions and neural measures. We map the multivariate associations that intrinsic functional connectivity manifests with pediatric symptoms of anxiety, irritability, and attention-deficit/hyperactivity disorder (ADHD) as common, impactful, co-occurring problems. We evaluate the replicability of such latent dimensions in an independent sample. Methods: We obtained ratings of anxiety, irritability, and ADHD, and 10 minutes of resting-state functional magnetic resonance imaging data, from two independent cohorts. Both cohorts (discovery: N=182; replication: N=326) included treatment-seeking youth with anxiety disorders, disruptive mood dysregulation disorder, ADHD, or without psychopathology. Functional connectivity was modeled as partial correlations among 216 brain areas. CCA, and independent-component analysis (ICA) jointly sought maximally-correlated, maximally-interpretable rsfMRI/clinical dimensions. Results: We identified seven canonical variates in the discovery and five in the replication cohort. Of these canonical variates, three exhibited similarities across datasets: two variates consistently captured shared aspects of irritability, ADHD, and anxiety, while the third was specific to anxiety. Across cohorts, canonical variates did not relate to specific resting-state networks but comprised edges interconnecting established networks within and across both hemispheres. Conclusions: Findings revealed two replicable types of clinical variates, one related to multiple symptom dimensions and a second relatively specific to anxiety. Both types involved a multitude of broadly-distributed, weak brain connections as opposed to strong connections encompassing known resting-state networks

Inflammatory Biomarkers and Clinical Judgment in the Emergency Diagnosis of Urgent Abdominal Pain

BACKGROUND: The early diagnosis of urgent abdominal pain (UAP) is challenging. Most causes of UAP are associated with extensive inflammation. Therefore, we hypothesized that quantifying inflammation using interleukin-6 and/or procalcitonin would provide incremental value in the emergency diagnosis of UAP. METHODS: This was an investigator-initiated prospective, multicenter diagnostic study enrolling patients presenting to the emergency department (ED) with acute abdominal pain. Clinical judgment of the treating physician regarding the presence of UAP was quantified using a visual analog scale after initial clinical and physician-directed laboratory assessment, and again after imaging. Two independent specialists adjudicated the final diagnosis and the classification as UAP (life-threatening, needing urgent surgery and/or hospitalization for acute medical reasons) using all information including histology and follow-up. Interleukin-6 and procalcitonin were measured blinded in a central laboratory. RESULTS: UAP was adjudicated in 376 of 1038 (36%) patients. Diagnostic accuracy for UAP was higher for interleukin-6 [area under the ROC curve (AUC), 0.80; 95% CI, 0.77-0.82] vs procalcitonin (AUC, 0.65; 95% CI, 0.62-0.68) and clinical judgment (AUC, 0.69; 95% CI, 0.65-0.72; both P < 0.001). Combined assessment of interleukin-6 and clinical judgment increased the AUC at presentation to 0.83 (95% CI, 0.80-0.85) and after imaging to 0.87 (95% CI, 0.84-0.89) and improved the correct identification of patients with and without UAP (net improvement in mean predicted probability: presentation, +19%; after imaging, +15%; P < 0.001). Decision curve analysis documented incremental value across the full range of pretest probabilities. A clinical judgment/interleukin-6 algorithm ruled out UAP with a sensitivity of 97% and ruled in UAP with a specificity of 93%. CONCLUSIONS: Interleukin-6 significantly improves the early diagnosis of UAP in the ED