Wedgwood, K. C. A. | Search bioRxiv

bioRxiv2025

Plasmonic imaging of living pancreatic beta-cell networks

We present a novel plasmonic imaging technique for real-time, label-free tracking of bioelectrical interactions in live pancreatic beta-cell networks. Surface plasmon resonance microscopy (SPRM) is utilized to reveal synchronized glucose-induced intensity oscillations that are suppressed by calcium channel blockers. These oscillations are observed at the subcellular scale with a resolution of 1 m. The technique can also uncover the extracellular spread of these oscillations beyond the cells. We further combine SPRM with network analysis to quantify coordinated electrical activity within the living cell network using both amplitude and phase-based metrics. Our results demonstrate a new method for studying electrical communication in pancreatic beta-cells, which could be crucial for understanding dysregulation in diabetes and advancing treatment development. This technique holds promise for investigating electrical connectivity in biological cell networks with applications in neuroscience, cardiac science, and bioelectricity in cancer, microbiology, development and regeneration. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=114 SRC="FIGDIR/small/649945v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@1dc0ce1org.highwire.dtl.DTLVardef@1d1c333org.highwire.dtl.DTLVardef@6684acorg.highwire.dtl.DTLVardef@906170_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2017

Modelling of the cardiopulmonary responses to maximal aerobic exercise in patients with cystic fibrosis

Cystic fibrosis (CF) is a debilitating chronic condition, which requires complex and expensive disease management. Exercise has now been recognised as a critical factor in improving health and quality of life in patients with CF. Hence, cardiopulmonary exercise testing (CPET) is used to determine aerobic fitness of young patients as part of the clinical management of CF. However, at present there is a lack of conclusive evidence for one limiting system of aerobic fitness for CF patients at an individual patient level.\n\nHere, we perform detailed data analysis that allows us to identify important systems-level factors that affect aerobic fitness. We use patients data and principal component analysis to confirm the dependence of CPET performance on variables associated with ventilation and metabolic rates of oxygen consumption. We find that the time at which participants cross the anaerobic threshold (AT) is well correlated with their overall performance. Furthermore, we propose a predictive modelling framework that captures the relationship between ventilatory dynamics, lung capacity and function and performance in CPET within a group of children and adolescents with CF. Specifically, we show that using Gaussian processes (GP) we can predict AT at the individual patient level with reasonable accuracy given the small sample size of the available group of patients. We conclude by presenting future perspectives for improving and extending the proposed framework.\n\nOur modelling and analysis have the potential to pave the way to designing personalised exercise programmes that are tailored to specific individual needs relative to patients treatment therapies.

physiology↗