AI algorithm for personalized resource allocation and treatment of hemorrhage casualties.

A deep neural network-based artificial intelligence (AI) model was assessed for its utility in predicting vital signs of hemorrhage patients and optimizing the management of fluid resuscitation in mass casualties. With the use of a cardio-respiratory computational model to generate synthetic data of hemorrhage casualties, an application was created where a limited data stream (the initial 10 min of vital-sign monitoring) could be used to predict the outcomes of different fluid resuscitation allocations 60 min into the future. The predicted outcomes were then used to select the optimal resuscitation allocation for various simulated mass-casualty scenarios. This allowed the assessment of the potential benefits of using an allocation method based on personalized predictions of future vital signs versus a static population-based method that only uses currently available vital-sign information. The theoretical benefits of this approach included up to 46% additional casualties restored to healthy vital signs and a 119% increase in fluid-utilization efficiency. Although the study is not immune from limitations associated with synthetic data under specific assumptions, the work demonstrated the potential for incorporating neural network-based AI technologies in hemorrhage detection and treatment. The simulated injury and treatment scenarios used delineated possible benefits and opportunities available for using AI in pre-hospital trauma care. The greatest benefit of this technology lies in its ability to provide personalized interventions that optimize clinical outcomes under resource-limited conditions, such as in civilian or military mass-casualty events, involving moderate and severe hemorrhage.

Predictive analytics identifies key factors driving hyperalgesic priming of muscle sensory neurons.

Hyperalgesic priming, a form of neuroplasticity induced by inflammatory mediators, in peripheral nociceptors enhances the magnitude and duration of action potential (AP) firing to future inflammatory events and can potentially lead to pain chronification. The mechanisms underlying the development of hyperalgesic priming are not well understood, limiting the identification of novel therapeutic strategies to combat chronic pain. In this study, we used a computational model to identify key proteins whose modifications caused priming of muscle nociceptors and made them hyperexcitable to a subsequent inflammatory event. First, we extended a previously validated model of mouse muscle nociceptor sensitization to incorporate Epac-mediated interaction between two G protein-coupled receptor signaling pathways commonly activated by inflammatory mediators. Next, we calibrated and validated the model simulations of the nociceptor's AP response to both innocuous and noxious levels of mechanical force after two subsequent inflammatory events using literature data. Then, by performing global sensitivity analyses that simulated thousands of nociceptor-priming scenarios, we identified five ion channels and two molecular processes (from the 18 modeled transmembrane proteins and 29 intracellular signaling components) as potential regulators of the increase in AP firing in response to mechanical forces. Finally, when we simulated specific neuroplastic modifications in Kv1.1 and Nav1.7 alone as well as with simultaneous modifications in Nav1.7, Nav1.8, TRPA1, and Kv7.2, we observed a considerable increase in the fold change in the number of triggered APs in primed nociceptors. These results suggest that altering the expression of Kv1.1 and Nav1.7 might regulate the neuronal hyperexcitability in primed mechanosensitive muscle nociceptors.

Identification of key factors driving inflammation-induced sensitization of muscle sensory neurons.

Sensory neurons embedded in muscle tissue that initiate pain sensations, i.e., nociceptors, are temporarily sensitized by inflammatory mediators during musculoskeletal trauma. These neurons transduce peripheral noxious stimuli into an electrical signal [i.e., an action potential (AP)] and, when sensitized, demonstrate lower activation thresholds and a heightened AP response. We still do not understand the relative contributions of the various transmembrane proteins and intracellular signaling processes that drive the inflammation-induced hyperexcitability of nociceptors. In this study, we used computational analysis to identify key proteins that could regulate the inflammation-induced increase in the magnitude of AP firing in mechanosensitive muscle nociceptors. First, we extended a previously validated model of a mechanosensitive mouse muscle nociceptor to incorporate two inflammation-activated G protein-coupled receptor (GPCR) signaling pathways and validated the model simulations of inflammation-induced nociceptor sensitization using literature data. Then, by performing global sensitivity analyses that simulated thousands of inflammation-induced nociceptor sensitization scenarios, we identified three ion channels and four molecular processes (from the 17 modeled transmembrane proteins and 28 intracellular signaling components) as potential regulators of the inflammation-induced increase in AP firing in response to mechanical forces. Moreover, we found that simulating single knockouts of transient receptor potential ankyrin 1 (TRPA1) and reducing the rates of Gαq-coupled receptor phosphorylation and Gαq subunit activation considerably altered the excitability of nociceptors (i.e., each modification increased or decreased the inflammation-induced fold change in the number of triggered APs compared to when all channels were present). These results suggest that altering the expression of TRPA1 or the concentration of intracellular Gαq might regulate the inflammation-induced increase in AP response of mechanosensitive muscle nociceptors.

Development and validation of a mathematical model to simulate human cardiovascular and respiratory responses to battlefield trauma.

Mathematical models of human cardiovascular and respiratory systems provide a viable alternative to generate synthetic data to train artificial intelligence (AI) clinical decision-support systems and assess closed-loop control technologies, for military medical applications. However, existing models are either complex, standalone systems that lack the interface to other applications or fail to capture the essential features of the physiological responses to the major causes of battlefield trauma (i.e., hemorrhage and airway compromise). To address these limitations, we developed the cardio-respiratory (CR) model by expanding and integrating two previously published models of the cardiovascular and respiratory systems. We compared the vital signs predicted by the CR model with those from three models, using experimental data from 27 subjects in five studies, involving hemorrhage, fluid resuscitation, and respiratory perturbations. Overall, the CR model yielded relatively small root mean square errors (RMSEs) for mean arterial pressure (MAP; 20.88 mm Hg), end-tidal CO2 (ETCO2 ; 3.50 mm Hg), O2 saturation (SpO2 ; 3.40%), and arterial O2 pressure (PaO2 ; 10.06 mm Hg), but a relatively large RMSE for heart rate (HR; 70.23 beats/min). In addition, the RMSEs for the CR model were 3% to 10% smaller than the three other models for HR, 11% to 15% for ETCO2 , 0% to 33% for SpO2 , and 10% to 64% for PaO2 , while they were similar for MAP. In conclusion, the CR model balances simplicity and accuracy, while qualitatively and quantitatively capturing human physiological responses to battlefield trauma, supporting its use to train and assess emerging AI and control systems.

In silico Identification of Key Factors Driving the Response of Muscle Sensory Neurons to Noxious Stimuli.

Nociceptive nerve endings embedded in muscle tissue transduce peripheral noxious stimuli into an electrical signal [i.e., an action potential (AP)] to initiate pain sensations. A major contributor to nociception from the muscles is mechanosensation. However, due to the heterogeneity in the expression of proteins, such as ion channels, pumps, and exchangers, on muscle nociceptors, we currently do not know the relative contributions of different proteins and signaling molecules to the neuronal response due to mechanical stimuli. In this study, we employed an integrated approach combining a customized experimental study in mice with a computational model to identify key proteins that regulate mechanical nociception in muscles. First, using newly collected data from somatosensory recordings in mouse hindpaw muscles, we developed and then validated a computational model of a mechanosensitive mouse muscle nociceptor. Next, by performing global sensitivity analyses that simulated thousands of nociceptors, we identified three ion channels (among the 17 modeled transmembrane proteins and four endoplasmic reticulum proteins) as potential regulators of the nociceptor response to mechanical forces in both the innocuous and noxious range. Moreover, we found that simulating single knockouts of any of the three ion channels, delayed rectifier voltage-gated K+ channel (Kv1.1) or mechanosensitive channels Piezo2 or TRPA1, considerably altered the excitability of the nociceptor (i.e., each knockout increased or decreased the number of triggered APs compared to when all channels were present). These results suggest that altering expression of the gene encoding Kv1.1, Piezo2, or TRPA1 might regulate the response of mechanosensitive muscle nociceptors.

Predictive Approach Identifies Molecular Targets and Interventions to Restore Angiogenesis in Wounds With Delayed Healing.

Impaired angiogenesis is a hallmark of wounds with delayed healing, and currently used therapies to restore angiogenesis have limited efficacy. Here, we employ a computational simulation-based approach to identify influential molecular and cellular processes, as well as protein targets, whose modulation may stimulate angiogenesis in wounds. We developed a mathematical model that captures the time courses for platelets, 9 cell types, 29 proteins, and oxygen, which are involved in inflammation, proliferation, and angiogenesis during wound healing. We validated our model using previously published experimental data. By performing global sensitivity analysis on thousands of simulated wound-healing scenarios, we identified six processes (among the 133 modeled in total) whose modulation may improve angiogenesis in wounds. By simulating knockouts of 25 modeled proteins and by simulating different wound-oxygenation levels, we identified four proteins [namely, transforming growth factor (TGF)-ß, vascular endothelial growth factor (VEGF), fibroblast growth factor-2 (FGF-2), and angiopoietin-2 (ANG-2)], as well as oxygen, as therapeutic targets for stimulating angiogenesis in wounds. Our modeling results indicated that simultaneous inhibition of TGF-ß and supplementation of either FGF-2 or ANG-2 could be more effective in stimulating wound angiogenesis than the modulation of either protein alone. Our findings suggest experimentally testable intervention strategies to restore angiogenesis in wounds with delayed healing.

Computational analysis identifies putative prognostic biomarkers of pathological scarring in skin wounds.

BACKGROUND: Pathological scarring in wounds is a prevalent clinical outcome with limited prognostic options. The objective of this study was to investigate whether cellular signaling proteins could be used as prognostic biomarkers of pathological scarring in traumatic skin wounds. METHODS: We used our previously developed and validated computational model of injury-initiated wound healing to simulate the time courses for platelets, 6 cell types, and 21 proteins involved in the inflammatory and proliferative phases of wound healing. Next, we analysed thousands of simulated wound-healing scenarios to identify those that resulted in pathological (i.e., excessive) scarring. Then, we identified candidate proteins that were elevated (or decreased) at the early stages of wound healing in those simulations and could therefore serve as predictive biomarkers of pathological scarring outcomes. Finally, we performed logistic regression analysis and calculated the area under the receiver operating characteristic curve to quantitatively assess the predictive accuracy of the model-identified putative biomarkers. RESULTS: We identified three proteins (interleukin-10, tissue inhibitor of matrix metalloproteinase-1, and fibronectin) whose levels were elevated in pathological scars as early as 2 weeks post-wounding and could predict a pathological scarring outcome occurring 40 days after wounding with 80% accuracy. CONCLUSION: Our method for predicting putative prognostic wound-outcome biomarkers may serve as an effective means to guide the identification of proteins predictive of pathological scarring.

Wound healing in Mac-1 deficient mice.

Mac-1 (CD11b/CD18) is a macrophage receptor that plays several critical roles in macrophage recruitment and activation. Because macrophages are essential for proper wound healing, the impact of Mac-1 deficiency on wound healing is of significant interest. Prior studies have shown that Mac-1-/- mice exhibit deficits in healing, including delayed wound closure in scalp and ear wounds. This study examined whether Mac-1 deficiency influences wound healing in small excisional and incisional skin wounds. Three millimeter diameter full thickness excisional wounds and incisional wounds were prepared on the dorsal skin of Mac-1 deficient (Mac-1-/- ) and wild type (WT) mice, and wound healing outcomes were examined. Mac-1 deficient mice exhibited a normal rate of wound closure, generally normal levels of total collagen, and nearly normal synthesis and distribution of collagens I and III. In incisional wounds, wound breaking strength was similar for Mac-1-/- and WT mice. Wounds of Mac-1 deficient mice displayed normal total macrophage content, although macrophage phenotype markers were skewed as compared to WT. Interestingly, amounts of TGF-ß1 and its downstream signaling molecules, SMAD2 and SMAD3, were significantly decreased in the wounds of Mac-1 deficient mice compared to WT. The results suggest that Mac-1 deficiency has little impact on the healing of small excisional and incisional wounds. Moreover, the findings demonstrate that the effect of single genetic deficiencies on wound healing may markedly differ among wound models. These conclusions have implications for the interpretation of the many prior studies that utilize a single model system to examine wound healing outcomes in genetically deficient mice.

Predictive Analysis of Mechanistic Triggers and Mitigation Strategies for Pathological Scarring in Skin Wounds.

Wound fibrosis (i.e., excessive scar formation) is a medical problem of increasing prevalence, with poorly understood mechanistic triggers and limited therapeutic options. In this study, we employed an integrated approach that combines computational predictions with new experimental studies in mice to identify plausible mechanistic triggers of pathological scarring in skin wounds. We developed a computational model that predicts the time courses for six essential cell types, 18 essential molecular mediators, and collagen, which are involved in inflammation and proliferation during wound healing. By performing global sensitivity analyses using thousands of model-simulated wound-healing scenarios, we identified five key processes (among the 90 modeled processes) whose dysregulation may lead to pathological scarring in wounds. By modulating a subset of these key processes, we simulated fibrosis in wounds. Moreover, among the 18 modeled molecular mediators, we identified TGF-ß and the matrix metalloproteinases as therapeutic targets whose modulation may reduce fibrosis. The model predicted that simultaneous modulation of TGF-ß and matrix metalloproteinases would be more effective in treating excessive scarring than modulation of either therapeutic target alone. Our model was validated with previously published and newly generated experimental data, and suggested new in vivo experiments.

Computational Identification of Mechanistic Factors That Determine the Timing and Intensity of the Inflammatory Response.

Timely resolution of inflammation is critical for the restoration of homeostasis in injured or infected tissue. Chronic inflammation is often characterized by a persistent increase in the concentrations of inflammatory cells and molecular mediators, whose distinct amount and timing characteristics offer an opportunity to identify effective therapeutic regulatory targets. Here, we used our recently developed computational model of local inflammation to identify potential targets for molecular interventions and to investigate the effects of individual and combined inhibition of such targets. This was accomplished via the development and application of computational strategies involving the simulation and analysis of thousands of inflammatory scenarios. We found that modulation of macrophage influx and efflux is an effective potential strategy to regulate the amount of inflammatory cells and molecular mediators in both normal and chronic inflammatory scenarios. We identified three molecular mediators - tumor necrosis factor-α (TNF-α), transforming growth factor-ß (TGF-ß), and the chemokine CXCL8 - as potential molecular targets whose individual or combined inhibition may robustly regulate both the amount and timing properties of the kinetic trajectories for neutrophils and macrophages in chronic inflammation. Modulation of macrophage flux, as well as of the abundance of TNF-α, TGF-ß, and CXCL8, may improve the resolution of chronic inflammation.

Computational approach to characterize causative factors and molecular indicators of chronic wound inflammation.

Chronic inflammation is rapidly becoming recognized as a key contributor to numerous pathologies. Despite detailed investigations, understanding of the molecular mechanisms regulating inflammation is incomplete. Knowledge of such critical regulatory processes and informative indicators of chronic inflammation is necessary for efficacious therapeutic interventions and diagnostic support to clinicians. We used a computational modeling approach to elucidate the critical factors responsible for chronic inflammation and to identify robust molecular indicators of chronic inflammatory conditions. Our kinetic model successfully captured experimentally observed cell and cytokine dynamics for both acute and chronic inflammatory responses. Using sensitivity analysis, we identified macrophage influx and efflux rate modulation as the strongest inducing factor of chronic inflammation for a wide range of scenarios. Moreover, our model predicted that, among all major inflammatory mediators, IL-6, TGF-ß, and PDGF may generally be considered the most sensitive and robust indicators of chronic inflammation, which is supported by existing, but limited, experimental evidence.

Role of microprojections in myoendothelial feedback--a theoretical study.

We investigated the role of myoendothelial projections (MPs) in endothelial cell (EC) feedback response to smooth muscle cell (SMC) stimulation using mathematical modelling. A previously developed compartmental EC-SMC model is modified to include MPs as subcellular compartments in the EC. The model is further extended into a 2D continuum model using a finite element method (FEM) approach and electron microscopy images to account for MP geometry. The EC and SMC are coupled via non-selective myoendothelial gap junctions (MEGJs) which are located on MPs and allow exchange of Ca(2+), K(+), Na(+) and Cl(-) ions and inositol 1,4,5-triphosphate (IP3). Models take into consideration recent evidence for co-localization of intermediate-conductance calcium-activated potassium channels (IKCa) and IP3 receptors (IP3Rs) in the MPs. SMC stimulation causes an IP3-mediated Ca(2+) transient in the MPs with limited global spread in the bulk EC. A hyperpolarizing feedback generated by the localized IKCa channels is transmitted to the SMC via MEGJs. MEGJ resistance (Rgj) and the density of IKCa and IP3R in the projection influence the extent of EC response to SMC stimulation. The predicted Ca(2+) transients depend also on the volume and geometry of the MP. We conclude that in the myoendothelial feedback response to SMC stimulation, MPs are required to amplify the SMC initiated signal. Simulations suggest that the signal is mediated by IP3 rather than Ca(2+) diffusion and that a localized rather than a global EC Ca(2+) mobilization is more likely following SMC stimulation.

Intercellular communication in the vascular wall: a modeling perspective.

Movement of ions (Ca(2+) , K(+) , Na(+) , and Cl(-) ) and second messenger molecules like inositol 1, 4, 5-trisphosphate inside and in between different cells is the basis of many signaling mechanisms in the microcirculation. In spite of the vast experimental efforts directed toward evaluation of these fluxes, it has been a challenge to establish their roles in many essential microcirculatory phenomena. Recently, detailed theoretical models of calcium dynamics and plasma membrane electrophysiology have emerged to assist in the quantification of these intra and intercellular fluxes and enhance understanding of their physiological importance. This perspective reviews selected models relevant to estimation of such intra and intercellular ionic and second messenger fluxes and prediction of their relative significance to a variety of vascular phenomena, such as myoendothelial feedback, conducted responses, and vasomotion.

Endothelial Ca2+ wavelets and the induction of myoendothelial feedback.

When arteries constrict to agonists, the endothelium inversely responds, attenuating the initial vasomotor response. The basis of this feedback mechanism remains uncertain, although past studies suggest a key role for myoendothelial communication in the signaling process. The present study examined whether second messenger flux through myoendothelial gap junctions initiates a negative-feedback response in hamster retractor muscle feed arteries. We specifically hypothesized that when agonists elicit depolarization and a rise in second messenger concentration, inositol trisphosphate (IP(3)) flux activates a discrete pool of IP(3) receptors (IP(3)Rs), elicits localized endothelial Ca(2+) transients, and activates downstream effectors to moderate constriction. With use of integrated experimental techniques, this study provided three sets of supporting observations. Beginning at the functional level, we showed that blocking intermediate-conductance Ca(2+)-activated K(+) channels (IK) and Ca(2+) mobilization from the endoplasmic reticulum (ER) enhanced the contractile/electrical responsiveness of feed arteries to phenylephrine. Next, structural analysis confirmed that endothelial projections make contact with the overlying smooth muscle. These projections retained membranous ER networks, and IP(3)Rs and IK channels localized in or near this structure. Finally, Ca(2+) imaging revealed that phenylephrine induced discrete endothelial Ca(2+) events through IP(3)R activation. These events were termed recruitable Ca(2+) wavelets on the basis of their spatiotemporal characteristics. From these findings, we conclude that IP(3) flux across myoendothelial gap junctions is sufficient to induce focal Ca(2+) release from IP(3)Rs and activate a discrete pool of IK channels within or near endothelial projections. The resulting hyperpolarization feeds back on smooth muscle to moderate agonist-induced depolarization and constriction.

Modeling Ca2+ signaling in the microcirculation: intercellular communication and vasoreactivity.

A network of intracellular signaling pathways and complex intercellular interactions regulate calcium mobilization in vascular cells, arteriolar tone, and blood flow. Different endothelium-derived vasoreactive factors have been identified and the importance of myoendothelial communication in vasoreactivity is now well appreciated. The ability of many vascular networks to conduct signals upstream also is established. This phenomenon is critical for both short-term changes in blood perfusion as well as long-term adaptations of a vascular network. In addition, in a phenomenon termed vasomotion, arterioles often exhibit spontaneous oscillations in diameter. This is thought to improve tissue oxygenation and enhance blood flow. Experimentation has begun to reveal important aspects of the regulatory machinery and the significance of these phenomena for the regulation of local perfusion and oxygenation. Mathematical modeling can assist in elucidating the complex signaling mechanisms that participate in these phenomena. This review highlights some of the important experimental studies and relevant mathematical models that provide the current understanding of these mechanisms in vasoreactivity.

A mathematical model of vasoreactivity in rat mesenteric arterioles. II. Conducted vasoreactivity.

This study presents a multicellular computational model of a rat mesenteric arteriole to investigate the signal transduction mechanisms involved in the generation of conducted vasoreactivity. The model comprises detailed descriptions of endothelial (ECs) and smooth muscle (SM) cells (SMCs), coupled by nonselective gap junctions. With strong myoendothelial coupling, local agonist stimulation of the EC or SM layer causes local changes in membrane potential (V(m)) that are conducted electrotonically, primarily through the endothelium. When myoendothelial coupling is weak, signals initiated in the SM conduct poorly, but the sensitivity of the SMCs to current injection and agonist stimulation increases. Thus physiological transmembrane currents can induce different levels of local V(m) change, depending on cell's gap junction connectivity. The physiological relevance of current and voltage clamp stimulations in intact vessels is discussed. Focal agonist stimulation of the endothelium reduces cytosolic calcium (intracellular Ca(2+) concentration) in the prestimulated SM layer. This SMC Ca(2+) reduction is attributed to a spread of EC hyperpolarization via gap junctions. Inositol (1,4,5)-trisphosphate, but not Ca(2+), diffusion through homocellular gap junctions can increase intracellular Ca(2+) concentration in neighboring ECs. The small endothelial Ca(2+) spread can amplify the total current generated at the local site by the ECs and through the nitric oxide pathway, by the SMCs, and thus reduces the number of stimulated cells required to induce distant responses. The distance of the electrotonic and Ca(2+) spread depends on the magnitude of SM prestimulation and the number of SM layers. Model results are consistent with experimental data for vasoreactivity in rat mesenteric resistance arteries.