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  • 1
    Online Resource
    Online Resource
    Central and non‐central networks, cognition, clinical symptoms, and polygenic risk scores in schizophrenia
    Wiley ; 2017
    In:  Human Brain Mapping Vol. 38, No. 12 ( 2017-12), p. 5919-5930
    Details
    In: Human Brain Mapping, Wiley, Vol. 38, No. 12 ( 2017-12), p. 5919-5930
    Abstract: Schizophrenia is a complex disorder that may be the result of aberrant connections between specific brain regions rather than focal brain abnormalities. Here, we investigate the relationships between brain structural connectivity as described by network analysis, intelligence, symptoms, and polygenic risk scores (PGRS) for schizophrenia in a group of patients with schizophrenia and a group of healthy controls. Recently, researchers have shown an interest in the role of high centrality networks in the disorder. However, the importance of non‐central networks still remains unclear. Thus, we specifically examined network‐averaged fractional anisotropy (mean edge weight) in central and non‐central subnetworks. Connections with the highest betweenness centrality within the average network ( 〉 75% of centrality values) were selected to represent the central subnetwork. The remaining connections were assigned to the non‐central subnetwork. Additionally, we calculated graph theory measures from the average network (connections that occur in at least 2/3 of participants). Density, strength, global efficiency, and clustering coefficient were significantly lower in patients compared with healthy controls for the average network ( p FDR   〈  0.05). All metrics across networks were significantly associated with intelligence ( p FDR   〈  0.05). There was a tendency towards significance for a correlation between intelligence and PGRS for schizophrenia ( r  = −0.508, p  = 0.052) that was significantly mediated by central and non‐central mean edge weight and every graph metric from the average network. These results are consistent with the hypothesis that intelligence deficits are associated with a genetic risk for schizophrenia, which is mediated via the disruption of distributed brain networks. Hum Brain Mapp 38:5919–5930, 2017 . © 2017 Wiley Periodicals, Inc.
    Type of Medium: Online Resource
    ISSN: 1065-9471 , 1097-0193
    URL: Issue
    URL: Article
    DOI: 10.1002/hbm.v38.12
    DOI: 10.1002/hbm.23798
    Language: English
    Publisher: Wiley
    Publication Date: 2017
    detail.hit.zdb_id: 1492703-2
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  • 2
    Online Resource
    Online Resource
    A Case for Synthetic Data in Regulatory Decision‐Making in Europe
    Wiley ; 2023
    In:  Clinical Pharmacology & Therapeutics Vol. 114, No. 4 ( 2023-10), p. 795-801
    Details
    In: Clinical Pharmacology & Therapeutics, Wiley, Vol. 114, No. 4 ( 2023-10), p. 795-801
    Abstract: Regulators are faced with many challenges surrounding health data usage, including privacy, fragmentation, validity, and generalizability, especially in the European Union, for which synthetic data may provide innovative solutions. Synthetic data, defined as data artificially generated rather than captured in the real world, are increasingly being used for healthcare research purposes as a proxy to real‐world data (RWD). Currently, there are barriers particularly challenging in Europe, where sharing patient's data is strictly regulated, costly, and time‐consuming, causing delays in evidence generation and regulatory approvals. Recent initiatives are encouraging the use of synthetic data in regulatory decision making and health technology assessment to overcome these challenges, but synthetic data have still to overcome realistic obstacles before their adoption by researchers and regulators in Europe. Thus, the emerging use of RWD and synthetic data by pharmaceutical and medical device industries calls regulatory bodies to provide a framework for proper evidence generation and informed regulatory decision making. As the provision of data becomes more ubiquitous in scientific research, so will innovations in artificial intelligence, machine learning, and generation of synthetic data, making the exploration and intricacies of this topic all the more important and timely. In this review, we discuss the potential merits and challenges of synthetic data in the context of decision making in the European regulatory environment. We explore the current uses of synthetic data and ongoing initiatives, the value of synthetic data for regulatory purposes, and realistic barriers to the adoption of synthetic data in healthcare.
    Type of Medium: Online Resource
    ISSN: 0009-9236 , 1532-6535
    URL: Issue
    URL: Article
    DOI: 10.1002/cpt.v114.4
    DOI: 10.1002/cpt.3001
    RVK:
    XA 36900
    Language: English
    Publisher: Wiley
    Publication Date: 2023
    detail.hit.zdb_id: 2040184-X
    SSG: 15,3
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  • 3
    Online Resource
    Online Resource
    Intracranial and subcortical volumes in adolescents with early‐onset psychosis: A multisite mega‐analysis from the ENIGMA consortium
    Wiley ; 2022
    In:  Human Brain Mapping Vol. 43, No. 1 ( 2022-01), p. 373-384
    Details
    In: Human Brain Mapping, Wiley, Vol. 43, No. 1 ( 2022-01), p. 373-384
    Abstract: Early‐onset psychosis disorders are serious mental disorders arising before the age of 18 years. Here, we investigate the largest neuroimaging dataset, to date, of patients with early‐onset psychosis and healthy controls for differences in intracranial and subcortical brain volumes. The sample included 263 patients with early‐onset psychosis (mean age: 16.4 ± 1.4 years, mean illness duration: 1.5 ± 1.4 years, 39.2% female) and 359 healthy controls (mean age: 15.9 ± 1.7 years, 45.4% female) with magnetic resonance imaging data, pooled from 11 clinical cohorts. Patients were diagnosed with early‐onset schizophrenia ( n  = 183), affective psychosis ( n  = 39), or other psychotic disorders ( n  = 41). We used linear mixed‐effects models to investigate differences in intracranial and subcortical volumes across the patient sample, diagnostic subgroup and antipsychotic medication, relative to controls. We observed significantly lower intracranial (Cohen's d  = −0.39) and hippocampal ( d  = −0.25) volumes, and higher caudate ( d  = 0.25) and pallidum ( d  = 0.24) volumes in patients relative to controls. Intracranial volume was lower in both early‐onset schizophrenia ( d  = −0.34) and affective psychosis ( d  = −0.42), and early‐onset schizophrenia showed lower hippocampal ( d  = −0.24) and higher pallidum ( d  = 0.29) volumes. Patients who were currently treated with antipsychotic medication ( n  = 193) had significantly lower intracranial volume ( d  = −0.42). The findings demonstrate a similar pattern of brain alterations in early‐onset psychosis as previously reported in adult psychosis, but with notably low intracranial volume. The low intracranial volume suggests disrupted neurodevelopment in adolescent early‐onset psychosis.
    Type of Medium: Online Resource
    ISSN: 1065-9471 , 1097-0193
    URL: Issue
    URL: Article
    DOI: 10.1002/hbm.v43.1
    DOI: 10.1002/hbm.25212
    Language: English
    Publisher: Wiley
    Publication Date: 2022
    detail.hit.zdb_id: 1492703-2
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