We analyse mathematical models of blood flow in two simple vascular networks in order to identify structural features that lead to the formation of multiple equilibria. Our models are based on existing rules for blood rheology and haematocrit splitting. By performing bifurcation analysis on these simple network flow models, we identify a link between the changing flow direction in key vessels and the existence of multiple equilibria. We refer to these key vessels as redundant vessels, and relate the maximum number of equilibria with the number of redundant vessels. We vary geometric parameters of the two networks, such as vessel length ratios and vessel diameters, to demonstrate that equilibria are uniquely defined by the flow in the redundant vessels. Equilibria typically emerge in sets of three, each having a different flow characteristic in one of the network's redundant vessels. For one of the three equilibria, the flow within the relevant redundant vessel will be smaller in magnitude than the other two and the redundant vessel will contain few Red Blood Cells (RBCs), if any. For the other two equilibria, the redundant vessel contains RBCs and significant flow in the two available directions. These structural features of networks provide a useful geometric property when studying the equilibria of blood flow in microvascular networks.
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http://dx.doi.org/10.1007/s11538-024-01404-y | DOI Listing |
Bull Math Biol
January 2025
Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Woodstock Rd, Oxford, Oxfordshire, OX2 6GG, UK.
We analyse mathematical models of blood flow in two simple vascular networks in order to identify structural features that lead to the formation of multiple equilibria. Our models are based on existing rules for blood rheology and haematocrit splitting. By performing bifurcation analysis on these simple network flow models, we identify a link between the changing flow direction in key vessels and the existence of multiple equilibria.
View Article and Find Full Text PDFBioengineering (Basel)
November 2024
Department of Radiology, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul 03080, Republic of Korea.
We assessed the feasibility of using deep learning-based image harmonization to improve the reproducibility of radiomics features in abdominal CT scans. In CT imaging, harmonization adjusts images from different institutions to ensure consistency despite variations in scanners and acquisition protocols. This process is essential because such differences can lead to variability in radiomics features, affecting reproducibility and accuracy.
View Article and Find Full Text PDFBMC Cancer
December 2024
Department of Radiation Oncology, Nanfang Hospital, Southern Medical University, 1838 North Guangzhou Avenue, Guangzhou, 510515, Guangdong, P.R. China.
Purpose: Antiangiogenesis therapy has become a hot field in cancer research. Given that tumor blood vessels often express specific markers related to angiogenesis, the study of these heterogeneous molecules in different tumor vessels holds promise for advancing anti-angiogenic therapy. Previously using phage display technology, we identified a targeting peptide named GX1 homing to gastric cancer vessels for the first time.
View Article and Find Full Text PDFMicrobiol Spectr
December 2024
Department of Microbiology, Immunology, and Molecular Genetics, University of Kentucky, Lexington, Kentucky, USA.
Unlabelled: are facultative intracellular bacterial pathogens that cause foodborne disease in humans. The bacteria can use the surface protein InlA to invade intestinal epithelial cells or transcytose across M cells in the gut, but it is not well understood how the bacteria traffic from the underlying lamina propria to the draining mesenteric lymph nodes (MLN). Previous studies indicated that associated with both monocytes and dendritic cells in the intestinal lamina propria.
View Article and Find Full Text PDFFront Aging Neurosci
November 2024
Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Objectives: To investigate the potential trade-offs among brain structural network characteristics across different stages of cognitive impairment in cerebral small vessel disease (CSVD) based on diffusion tensor imaging (DTI).
Methods: A total of 264 CSVD patients, including 95 patients with non-cognitive impairment (NCI), 142 with mild cognitive impairment (MCI), 27 with vascular dementia (VaD), and 30 healthy controls (HC) underwent cognitive test and brain diffusion magnetic resonance imaging (MRI). The brain structural network was constructed using connections between 90 cortical and subcortical regions.
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