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The corneal micropocket angiogenesis assay is an experimental protocol for studying vessel network formation, or neovascularization, in vivo. The assay is attractive due to the ease with which the developing vessel network can be observed in the same animal over time. Measurements from the assay have been used in combination with mathematical modeling to gain insights into the mechanisms of angiogenesis. While previous modeling studies have adopted planar domains to represent the assay, the hemispherical shape of the cornea and asymmetric positioning of the angiogenic source can be seen to affect vascular patterning in experimental images. As such, we aim to better understand: i) how the geometry of the assay influences vessel network formation and ii) how to relate observations from planar domains to those in the hemispherical cornea. To do so, we develop a three-dimensional, off-lattice mathematical model of neovascularization in the cornea, using a spatially resolved representation of the assay for the first time. Relative to the detailed model, we predict that the adoption of planar geometries has a noticeable impact on vascular patterning, leading to increased vessel 'merging', or anastomosis, in particular when circular geometries are adopted. Significant differences in the dynamics of diffusible aniogenesis simulators are also predicted between different domains. In terms of comparing predictions across domains, the 'distance of the vascular front to the limbus' metric is found to have low sensitivity to domain choice, while metrics such as densities of tip cells and vessels and 'vascularized fraction' are sensitive to domain choice. Given the widespread adoption and attractive simplicity of planar tissue domains, both in silico and in vitro, the differences identified in the present study should prove useful in relating the results of previous and future theoretical studies of neovascularization to in vivo observations in the cornea.
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http://dx.doi.org/10.1371/journal.pcbi.1006049 | DOI Listing |
Int J Numer Method Biomed Eng
September 2025
School of Mathematics and Statistics, University of Glasgow, Glasgow, UK.
Blood perfusion in cardiac tissues involves intricate interactions among vascular networks and tissue mechanics. Perfusion deficit is one of the leading causes of cardiac diseases, and modeling certain cardiac conditions that are clinically infeasible, invasive, or costly can provide valuable supplementary insights to aid clinicians. However, existing homogeneous perfusion models lack the complexity required for patient-specific simulations.
View Article and Find Full Text PDFBiotechnol J
September 2025
Department of Biochemical Engineering, University College London, London, UK.
Chimeric antigen receptor T-cell (CAR-T) therapies have demonstrated clinical efficacy in treating haematological malignancies, resulting in multiple regulatory approvals. However, there is a need for robust manufacturing platforms and the use of GMP-aligned reagents to meet the clinical and commercial demands. This study investigates the impact of serum/xeno-free medium (SXFM) and cytokine supplementation on CAR-T cell production in static and agitated culture systems, using 24-well plate G-Rex vessels and 500 mL stirred tank bioreactors (STRs), respectively.
View Article and Find Full Text PDFWorld Neurosurg
September 2025
Departments of Neurology; Department of Biological Science; Doctoral Program of Clinical and Experimental Medicine, College of Medicine, National Sun Yat-Sen University, Kaohsiung, Taiwan; Department of Neurology, Xiamen Chang Gung Memorial Hospital, Xiamen, Fujian, China. Electronic address: chlu99
Objective: Endovascular thrombectomy (EVT) is a time-critical therapy for acute ischemic stroke (AIS) caused by large vessel occlusion. To improve transfer efficiency, a web-based EVT transfer system was implemented in the Taiwan Stroke Network. This study evaluated its impact on workflow metrics and patient outcomes.
View Article and Find Full Text PDFBiomed Phys Eng Express
September 2025
College of Computer Science and Technology, China University of Petroleum East China - Qingdao Campus, College of Computer Science and Technology, China University of Petroleum (East China), Qingdao 266580, China, Qingdao, Shandong, 266580, CHINA.
Purpose: Cerebrovascular segmentation is crucial for the diagnosis and treatment of cerebrovascular diseases. However, accurately extracting cerebral vessels from Time-of-Flight Magnetic Resonance Angiography (TOF-MRA) remains challenging due to the topological complexity and anatomical variability.
Methods: This paper presents a novel Y-shaped segmentation network with fast Fourier convolution and Mamba, termed F-Mamba-YNet.
Neural Netw
September 2025
Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen, China. Electronic address:
Automatic segmentation of retinal vessels from retinography images is crucial for timely clinical diagnosis. However, the high cost and specialized expertise required for annotating medical images often result in limited labeled datasets, which constrains the full potential of deep learning methods. Recent advances in self-supervised pretraining using unlabeled data have shown significant benefits for downstream tasks.
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