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Neph et al. (2012) (Circuitry and dynamics of human transcription factor regulatory networks. Cell, 150: 1274-1286) reported the transcription factor (TF) regulatory networks of 41 human cell types using the DNaseI footprinting technique. This provides a valuable resource for uncovering regulation principles in different human cells. In this paper, the architectures of the 41 regulatory networks and the distributions of housekeeping and specific regulatory interactions are investigated. The TF regulatory networks of different human cell types demonstrate similar global three-layer (top, core and bottom) hierarchical architectures, which are greatly different from the yeast TF regulatory network. However, they have distinguishable local organizations, as suggested by the fact that wiring patterns of only a few TFs are enough to distinguish cell identities. The TF regulatory network of human embryonic stem cells (hESCs) is dense and enriched with interactions that are unseen in the networks of other cell types. The examination of specific regulatory interactions suggests that specific interactions play important roles in hESCs.
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http://dx.doi.org/10.1093/nar/gku923 | DOI Listing |
J Environ Pathol Toxicol Oncol
January 2025
Department of Oncology, Jiangsu Cancer Hospital & Jiangsu Institute of Cancer Research & The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing 210009, China.
Noncoding RNA regulatory networks play crucial roles in human breast cancer. The aim of this study was to establish a network containing multi-type RNAs and RBPs in triple-negative breast cancer (TNBC). Differential expression analyses of lncRNAs, miRNAs, and genes were performed using the GEO2R tool.
View Article and Find Full Text PDFJ Chem Inf Model
September 2025
College of Agriculture and Biological Science, Dali University, Dali 671000, China.
The E76K mutation in protein tyrosine phosphatase (PTP) SHP2 is a recurrent driver of developmental disorders and cancers, yet the mechanism by which this single-site substitution promotes persistent activation remains elusive. Here, we combine path-based conformational sampling, unbiased molecular dynamics (MD) simulations, Markov state models (MSMs), and neural relational inference (NRI) to elucidate how E76K reshapes the activation landscape and regulatory architecture of SHP2. Using a minimum-action trajectory derived from experimentally determined closed and open structures, we generated representative transition intermediates to guide the unbiased MD simulations.
View Article and Find Full Text PDFPLoS One
September 2025
Orthopaedics, Hebei Medical University Third Hospital, Shijiazhuang, China.
Enoxaparin sodium (ES), a low molecular weight heparin derivative, has recently been recognized for its diverse biological activities. In particular, the ability of heparin to modulate inflammation has been utilized to enhance the biocompatibility of bone implant materials. In this study, we utilized poly (methyl methacrylate) (PMMA), a drug loading bone implant material, as a matrix and combined this with enoxaparin sodium (ES) to create enoxaparin sodium PMMA cement (ES-PMMA) to investigate the regulatory effects of ES on inflammatory responses in bone tissue from an animal model.
View Article and Find Full Text PDFPLoS One
September 2025
Department of Emergency Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China.
Background: Heat illness is a dangerous condition marked by a widespread inflammatory response. Although Pogostemon cablin (Blanco) Benth and its derivatives are clinically used, their mechanisms remain unclear.
Methods: 11 heat illness patients and 14 healthy volunteers from Southwest Medical University Affiliated Hospital were enrolled.
J Hepatol
July 2025
Else Kroener Fresenius Center for Digital Health, Technical University Dresden, Dresden, Germany; Department of Medicine I, Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, 01307 Dresden, Germany; Medical Oncology, National Center for Tumor Disease
Artificial intelligence (AI) methods in hepatology have proliferated since the mid-2010s, with numerous publications and some regulatory approvals. Yet, adoption of AI methods in real-world clinical practice and clinical research remains limited. Despite clear benefits of using AI to analyze complex data types in hepatology, such as histopathology, radiology images, multi-omics and more recently, natural language patient data, there are still substantial barriers and challenges to its integration into routine clinical workflows.
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