The eukaryotic chaperonin, CCT (Chaperonin Containing TCP1 or TriC-TCP-1 Ring Complex) has been subjected to physical and genetic analyses in S. cerevisiae which can be extrapolated to human CCT (hCCT), owing to its structural and functional similarities with yeast CCT (yCCT). Studies on hCCT and its interactome acquire an additional dimension, as it has been implicated in several disease conditions like neurodegeneration and cancer. We attempt to study its stress response role in general, which will be reflected in the aspects of human diseases and yeast physiology, through computational analysis of the interactome. Towards consolidating and analysing the interactome data, we prepared and compared the unique CCT-interacting protein lists for S. cerevisiae and H. sapiens, performed GO term classification and enrichment studies which provide information on the diversity in CCT interactome, in terms of protein classes in the data set. Enrichment with disease-associated proteins and pathways highlight the medical importance of CCT. Different analyses converge, suggesting the significance of WD-repeat proteins, protein kinases and cytoskeletal proteins in the interactome. The prevalence of proteasomal subunits and ribosomal proteins suggest a possible cross-talk between protein-synthesis, folding and degradation machinery. A network of chaperones and chaperonins that function in combination can also be envisaged from the CCT interactome-Hsp70 interactome analysis.
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http://dx.doi.org/10.1016/j.compbiolchem.2016.09.002 | DOI Listing |
Introduction: Solitary plasmacytomas are tumors characterized by a local increase of malignant plasma cells in soft tissue or bone and may occur anywhere without evidence of systemic disease. The aim was to focus on the main surgical techniques and outcomes for this rare chest wall tumor.
Methods: Patients with solitary plasmacytoma involving a rib, who were operated for diagnostic or treatment purposes between 2018 and 2023 were retrospectively reviewed.
Int J Med Inform
January 2025
Department of Computer Science and Artificial Intelligence, University of Udine, 33100, Italy.
Background: Segmentation models for clinical data experience severe performance degradation when trained on a single client from one domain and distributed to other clients from different domain. Federated Learning (FL) provides a solution by enabling multi-party collaborative learning without compromising the confidentiality of clients' private data.
Methods: In this paper, we propose a cross-domain FL method for Weakly Supervised Semantic Segmentation (FL-W3S) of white blood cells in microscopic images.
Medicine (Baltimore)
January 2025
Department of Medical Imaging, Jincheng People's Hospital, Shanxi, China.
Rationale: Thrombus is the most common occupying lesion in the cardiac chambers, it is often distinguished from cardiac neoplastic occupations. Among them, the most common is cardiac myxoma, whose imaging manifestations are often confused with thrombus. However, the 2 types of lesions have different therapeutic strategies and are both potentially high-risk sources of embolism, so early differentiation between intracardiac thrombus and cardiac tumor is essential.
View Article and Find Full Text PDFJMIR Ment Health
January 2025
Inspire, Belfast, United Kingdom.
Background: There is potential for digital mental health interventions to provide affordable, efficient, and scalable support to individuals. Digital interventions, including cognitive behavioral therapy, stress management, and mindfulness programs, have shown promise when applied in workplace settings.
Objective: The aim of this study is to conduct an umbrella review of systematic reviews in order to critically evaluate, synthesize, and summarize evidence of various digital mental health interventions available within a workplace setting.
J Med Internet Res
January 2025
School of Business, Innovation and Sustainability, Halmstad University, Halmstad, Sweden.
Background: Recent advancements in artificial intelligence (AI) have changed the care processes in mental health, particularly in decision-making support for health care professionals and individuals with mental health problems. AI systems provide support in several domains of mental health, including early detection, diagnostics, treatment, and self-care. The use of AI systems in care flows faces several challenges in relation to decision-making support, stemming from technology, end-user, and organizational perspectives with the AI disruption of care processes.
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