Biology subjects

Briggs, J. K.

Publications and source records attributed to Briggs, J. K..

5 recordsLinked to original sources

bioRxiv2025

Physics-Informed Digital Twin Can Predict Cerebral Blood Flow and Cerebral Vascular Regulation Mechanisms in Neurocritical Care Patients

1Cerebral blood flow is vital for brain function and is acutely controlled through a set of physiological mechanisms known as cerebral vascular regulation (CVR)[1-3]. It remains challenging to directly measure the dynamics and function of individual CVR mechanisms[4], limiting our ability to understand and optimize brain perfusion, particularly for neurologically injured patients. Digital twins offer an ideal tool for overcoming this gap because they enable estimation, tracking, and forecasting of unmeasured physiological states[5, 6]. Here, we introduce CereBRLSIM (Cerebral Blood Regulation Latent State Inference and Modeling), a digital twin that integrates physiological knowledge and patient data to infer CVR function and predict cerebral dynamics. Using both in vivo experiments and simulated data, CereBRLSIM predicted cerebral hemodynamics with high accuracy and estimated the dynamics of myogenic, endothelial, and metabolic mechanisms underlying CVR. When personalized to neurocritical care patient data, CereBRLSIM differentiated cerebral hemodynamic phenotypes, predicted patient outcomes, and forecasted blood flow with significantly higher accuracy than machine learning models. This work provides a novel, interpretable, and clinically compatible approach for quantifying CVR function and forecasting cerebral blood flow, enabling new opportunities in precision diagnostics and foundational understanding of cerebral hemodynamics.

bioengineering↗

bioRxiv2024

Diminished gap junction coupling under diabetogenic conditions does not drive loss of functional β-cell sub-populations

Within the islets of Langerhans, gap junction coupling is important for synchronizing oscillatory free-calcium activity ([Ca2+]) and regulating pulsatile insulin release. In islets from multiple models of diabetes, gap junction coupling is disrupted, and [Ca2+] synchronization and pulsatile insulin is lost. Functional sub-populations have been identified within the islet that are linked to driving synchronized [Ca2+] and insulin release. These sub-populations can be disrupted under conditions associated with diabetes such as glucolipotoxicity and inflammatory environments, and their loss may drive islet dysfunction. Here we investigated how loss of gap junction coupling influences functional subpopulations under diabetogenic environments. We treated islets with a cocktail of pro-inflammatory cytokines, and protected gap junction coupling via co-treatment with a Cx36 peptide S293 that was previously shown to specifically prevent a decline in gap junction permeability and synchronized [Ca2+] dynamics. We performed calcium imaging and ChR2 stimulation, analyzed islet [Ca2+] dynamics and the presence of functional sub-populations including hubs and first-responders. 1h or 24h cytokine-treatment disrupted gap junction coupling, which was fully prevented by S293 peptide co-treatment. Treatment with pro-inflammatory cytokines decreased the recruitment of [Ca2+] upon ChR2 stimulation, increased the time between first and last responding cells upon glucose stimulation, and reduced the number and consistency of hub cells. When preserving gap junction coupling by S293 during cytokine treatment, the presence and consistency of these sub-populations was only marginally improved. We therefore concluded that while gap junction coupling is important for functional sub-populations to exert their influence on islet function, restoration of gap junctions alone is not sufficient to recover functional sub-populations upon diabetogenic conditions. Thus, preventing a disruption to intrinsic {beta}-cell properties that define functional subpopulations is likely important for preserving these sub-populations during diabetes.

biophysics↗

bioRxiv2024

Glucokinase activity controls subpopulations of lower case Greek beta-cells that alternately lead islet Ca2+ oscillations

Oscillations in insulin secretion, driven by islet Ca2+ waves, are crucial for glycemic control. Prior studies, performed with single-plane imaging, suggest that subpopulations of electrically coupled {beta}-cells have privileged roles in leading and coordinating the propagation of Ca2+ waves. Here, we used 3D light- sheet imaging to analyze the location and Ca2+ activity of single {beta}-cells within the entire islet at >2 Hz. In contrast with single-plane studies, 3D network analysis indicates that the most highly synchronized {beta}-cells are located at the islet center, and remain regionally but not cellularly stable between oscillations. This subpopulation, which includes hub cells, is insensitive to changes in fuel metabolism induced by glucokinase and pyruvate kinase activation. {beta}-cells that initiate the Ca2+ wave ( leaders) are located at the islet periphery, and strikingly, change their identity over time via rotations in the wave axis. Glucokinase activation, which increased oscillation period, reinforced leader cells and stabilized the wave axis. Pyruvate kinase activation, despite increasing oscillation frequency, had no effect on leader cells, indicating the wave origin is patterned by fuel input. These findings emphasize the stochastic nature of the {beta}-cell subpopulations that control Ca2+ oscillations and identify a role for glucokinase in spatially patterning leader {beta}-cells. Highlights* Studies of islet Ca2+ oscillations by 3D light-sheet imaging provide a more complete picture of {beta}- cell subpopulations than prior 2D studies. * Highly synchronized {beta}-cells (including hub cells) are a regionally-stable subpopulation located at the islet center that is insensitive to metabolic perturbation. * Glucokinase activation patterns the Ca2+ wave axis, which originates from stochastic {beta}-cell subpopulations on the islet periphery that change between oscillations. * The stochasticity of leader {beta}-cells, and the stability of hubs, is geographically consistent with the peripheral location of /{delta}-cells in mouse islets.

biophysics↗

bioRxiv2022

What do Functional Synchronization Networks Indicate About Underlying Structure and System Dynamics? A network theory study in the islet

Diabetes is caused by dysfunction of electrically coupled heterogeneous {beta}-cells within the pancreatic islet. Functional networks have been used to represent cellular synchronization and study {beta}-cells subpopulations, which play an important role in driving dynamics. The mechanism by which highly synchronized {beta}-cell subpopulations drive islet function is not clear. We used experimental and computational techniques to investigate the relationship between functional networks, structural (gap-junction) networks, and underlying {beta}-cell dynamics. Highly synchronized subpopulations in the functional network were differentiated by metabolic dynamics rather than structural coupling. Consistent with this, metabolic similarities were more predictive of edges in the islet functional network. Finally, removal of gap junctions, as occurs in diabetes, caused decreases in the efficiency and clustering of the functional network. These results indicate that metabolism rather than structure drives connections in the function network, deepening our interpretation of functional networks and the formation of functional sub-populations in dynamic tissues such as the islet.

biophysics↗

bioRxiv2020

Small subpopulations of β-cells do not drive islet oscillatory dynamics via gap junction communication

The islets of Langerhans exist as a multicellular network that is important for the regulation of blood glucose levels. The majority of cells in the islet are insulin-producing {beta}-cells, which are excitable cells that are electrically coupled via gap junction channels. {beta}-cells have long been known to display heterogeneous functionality. However, due to gap junction electrical coupling, {beta}-cells show coordinated [Ca2+] oscillations when stimulated with glucose, and global quiescence when unstimulated. Small subpopulations of highly functional {beta}-cells have been suggested to control the dynamics of [Ca2+] and insulin release across the islet. In this study, we investigated the theoretical basis of whether small subpopulations of {beta}-cells can disproportionality control islet [Ca2+] dynamics. Using a multicellular model of the islet, we generated continuous or bimodal distributions of {beta}-cell heterogeneity and examined how islet [Ca2+] dynamics depended on the presence of cells with increased excitability or increased oscillation frequency. We found that the islet was susceptible to marked suppression of [Ca2+] when a [~]10% population of cells with high metabolic activity was hyperpolarized; where hyperpolarizing cells with normal metabolic activity had little effect. However, when these highly metabolic cells were removed from the islet model, near normal [Ca2+] remained. Similarly, when [~]10% of cells with either the highest frequency or earliest elevations in [Ca2+] were removed from the islet, the [Ca2+] oscillation frequency remained largely unchanged. Overall these results indicate that small populations of {beta}-cells with either increased excitability or increased frequency, or signatures of [Ca2+] dynamics that suggest such properties, are unable to disproportionately control islet-wide [Ca2+] via gap junction coupling. As such, we need to reconsider the physiological basis for such small {beta}-cell populations or the mechanism by which they may be acting to control normal islet function. Author summaryMany biological systems can be studied using network theory. How heterogeneous cell subpopulations come together to create complex multicellular behavior is of great value in understanding function and dysfunction in tissues. The pancreatic islet of Langerhans is a highly coupled structure that is important for maintaining blood glucose homeostasis. {beta}-cell electrical activity is coordinated via gap junction communication. The function of the insulin-producing {beta}-cell within the islet is disrupted in diabetes. As such, to understand the causes of islet dysfunction we need to understand how different cells within the islet contribute to its overall function via gap junction coupling. Using a computational model of {beta}-cell electrophysiology, we investigated how small highly functional {beta}-cell populations within the islet contribute to its function. We found that when small populations with greater functionality were introduced into the islet, they displayed signatures of this enhanced functionality. However, when these cells were removed, the islet, retained near-normal function. Thus, in a highly coupled system, such as an islet, the heterogeneity of cells allows small subpopulations to be dispensable, and thus their absence is unable to disrupt the larger cellular network. These findings can be applied to other electrical systems that have heterogeneous cell populations.

biophysics↗