One of the main tasks in network theory is to infer relations among interacting elements. We propose global modeling as a tool to detect links between nodes and their nature. Various situations using small network motifs are investigated under the assumption that the variable to be measured at each node provides full observability when isolated. Such a choice ensures no intrinsic difficulties for getting a global model in the coupled situation. As a first step toward unveiling the coupling function in larger network motifs, we consider three different scenarios involving Rössler systems diffusively coupled, in a couple or embedded in a network, or parametrically forced. We show that the global modeling is able to determine not only the existence of an interaction but also its functional form, to retrieve the dynamics of the whole system, and to extract the equations governing the single node dynamics as if it was isolated.
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http://dx.doi.org/10.1063/1.5037335 | DOI Listing |
Best Pract Res Clin Anaesthesiol
September 2024
Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, CWN L1, Boston, MA, 02115, USA. Electronic address:
Since 2015, reductions in maternal mortality have stalled globally. In some parts of the world, severe maternal morbidity and mortality have increased, and most cases are thought to be from preventable causes. This is further exacerbated by significant racial, ethnic, and geographic disparities in maternal health outcomes, particularly among countries with diverse populations.
View Article and Find Full Text PDFGenet Epidemiol
January 2025
Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Boston, Massachusetts, USA.
Large-scale gene-environment interaction (GxE) discovery efforts often involve analytical compromises for the sake of data harmonization and statistical power. Refinement of exposures, covariates, outcomes, and population subsets may be helpful to establish often-elusive replication and evaluate potential clinical utility. Here, we used additional datasets, an expanded set of statistical models, and interrogation of lipoprotein metabolism via nuclear magnetic resonance (NMR)-based lipoprotein subfractions to refine a previously discovered GxE modifying the relationship between physical activity (PA) and HDL-cholesterol (HDL-C).
View Article and Find Full Text PDFJ Med Econ
January 2025
UNESCO-TWAS, The World Academy of Sciences, Trieste, Italy.
Aim: Dynamic cancer control is a current health system priority, yet methods for achieving it are lacking. This study aims to review the application of system dynamics modeling (SDM) on cancer control and evaluate the research quality.
Methods: Articles were searched in PubMed, Web of Science, and Scopus from the inception of the study to November 15th, 2023.
Brief Bioinform
November 2024
Center for Genomics and Biotechnology, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Haixia Institute of Science and Technology, Fujian Agriculture and Forestry University, No. 15 Shangxiadian Road, Cangshan District, Fuzhou 350002, China.
Spatial transcriptomics (ST) technologies enable dissecting the tissue architecture in spatial context. To perceive the global contextual information of gene expression patterns in tissue, the spatial dependence of cells must be fully considered by integrating both local and non-local features by means of spatial-context-aware. However, the current ST integration algorithm ignores for ST dropouts, which impedes the spatial-aware of ST features, resulting in challenges in the accuracy and robustness of microenvironmental heterogeneity detecting, spatial domain clustering, and batch-effects correction.
View Article and Find Full Text PDFFront Microbiol
December 2024
Guangdong Laboratory for Lingnan Modern Agriculture, National Risk Assessment Laboratory for Antimicrobial Resistance of Animal Original Bacteria, College of Veterinary Medicine, South China Agricultural University, Guangzhou, China.
Introduction: The emergence of the wide variety of novel tigecycline resistance (X) variants, including (X3), (X4), (X5), and (X6), has raised a serious threat to global public health and posed a significant challenge to the clinical treatment of multidrug-resistant bacterial infections.
Methods: In this study, we evaluated the synergism of tigecycline combining with other antibiotics as a means of overcoming the (X)-mediated resistance in spp. Antibiotic synergistic efficacy was evaluated through chequerboard experiments, time-kill assays and dose-response curves.
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