This study, as a part of a participatory action research project, reports the development process of an innovative collaboration between child and adolescent psychiatry and child welfare, for adolescent girls with multiple and complex needs. The findings emerge from a qualitative descriptive analysis of four focus groups with 30 professionals closely involved in this project, and describe the evolution of the collaborative efforts and outcomes through time. Participants describe large investments and negative consequences of rapid organizational change in the beginning of the collaboration project, while benefits of the intensive collaboration only appeared later. A shared person-centred vision and enhanced professionals' confidence were pointed out as important contributors in the evolution of the collaboration. Findings were compared to the literature and showed significant analogy with the life cycle model for shared service centres that describe the maturation of collaborations from a management perspective. These findings enrich the knowledge about the development process of collaboration in health and social care. In increasingly collaborative services, child and adolescent psychiatrists and policy makers should be aware that gains from a collaboration will possibly only be achieved in the longer term, and benefit from knowing which factors have an influence on the evolution of a collaboration project.
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http://dx.doi.org/10.1007/s00787-018-1147-7 | DOI Listing |
Drugs Aging
January 2025
Division of Rheumatology, Department of Internal Medicine, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan.
IgG4-related disease (IgG4-RD) is an immune-mediated disorder characterized by organ enlargement and dysfunction. The formation of tertiary lymphoid tissues (TLTs) in affected organs is crucial for understanding IgG4-RD, as T follicular helper (Tfh) 2 cells within TLTs drive IgG4+B cell differentiation, contributing to mass formation. Key cytokines IL-4 and IL-10, produced by Tfh2 cells, are essential for this process.
View Article and Find Full Text PDFCytotherapy
November 2024
Institute of Immunology and Immunotherapy, College of Medicine and Health, University of Birmingham, Birmingham, UK. Electronic address:
Background Aims: Extracellular vesicles (EVs) have gained traction as potential cell-free therapeutic candidates. Development of purification methods that are scalable and robust is a major focus of EV research. Yet there is still little in the literature that evaluates purification methods against potency of the EV product.
View Article and Find Full Text PDFJ Am Soc Mass Spectrom
January 2025
Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, Florida 32611, United States.
Reproducibility in untargeted metabolomics data processing remains a significant challenge due to software limitations and the complex series of steps required. To address these issues, we developed Nextflow4MS-DIAL, a reproducible workflow for liquid chromatography-mass spectrometry (LC-MS) metabolomics data processing, validated with publicly available data from MetaboLights (MTBLS733). Nextflow4MS-DIAL automates LC-MS data processing to minimize human errors from manual data handling.
View Article and Find Full Text PDFNano Lett
January 2025
Co-Innovation Center of Efficient Processing and Utilization of Forest Resources, Nanjing Forestry University, Nanjing 210037, China.
Developing sustainable structural materials to replace traditional carbon-intensive structural materials fundamentally reshapes the concept of circular development. Herein, we propose an interface engineering strategy that utilizes water as a liquid medium to replace the residual air within natural wood. This approach minimizes the absorption of water-based softening agents by microcapillary channels of wood, enabling the controlled softening of the cell walls.
View Article and Find Full Text PDFAdv Sci (Weinh)
January 2025
College of Physics Science & Technology, School of Life Sciences, Institute of Life Science and Green Development, Key Laboratory of Brain-Like Neuromorphic Devices and Systems of Hebei Province, Hebei University, Baoding, 071002, China.
Hardware system customized toward the demands of graph neural network learning would promote efficiency and strong temporal processing for graph-structured data. However, most amorphous/polycrystalline oxides-based memristors commonly have unstable conductance regulation due to random growth of conductive filaments. And graph neural networks based on robust and epitaxial film memristors can especially improve energy efficiency due to their high endurance and ultra-low power consumption.
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