An in silico modeling approach to understanding the dynamics of the post-burn immune response

Introduction

Burns are characterized by a massive and prolonged acute inflammation, which persists for up to months after the initial trauma. Due to the complexity of the inflammatory process, Predicting the dynamics of wound healing process can be challenging for burn injuries. The aim of this study was to develop simulation models for the post-burn immune response based on (pre)clinical data.

Methods

The simulation domain was separated into blood and tissue compartments. Each of these compartments contained solutes and cell agents. Solutes comprise pro-inflammatory cytokines, anti-inflammatory cytokines and inflammation triggering factors. The solutes diffuse around the domain based on their concentration profiles. The cells include mast cells, neutrophils, and macrophages, and were modeled as independent agents. The cells are motile and exhibit chemotaxis based on concentrations gradients of the solutes. In addition, the cells secrete various solutes that in turn alter the dynamics and responses of the burn wound system.

Results

We developed an Glazier-Graner-Hogeweg method-based model (GGH) to capture the complexities associated with the dynamics of inflammation after burn injuries, including changes in cell counts and cytokine levels. Through simulations from day 0 - 4 post-burn, we successfully identified key factors influencing the acute inflammatory response, i.e., the initial number of endothelial cells, the chemotaxis threshold, and the level of chemoattractants.

Conclusion

Our findings highlight the pivotal role of the initial endothelial cell count as a key parameter for intensity of inflammation and progression of acute inflammation, 0 - 4 days post-burn.

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 G_αq-coupled receptor phosphorylation and G_αq 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 G_αq might regulate the inflammation-induced increase in AP response of mechanosensitive muscle nociceptors.

Silicone gel sheeting for treating keloid scars

BACKGROUND

Keloid scarring is one of the most common types of pathological scarring. Keloid scars that fail to heal can affect a person's physical and psychological function by causing pain, pruritus, contractures, and cosmetic disfigurement. Silicone gel sheeting (SGS) is made from medical-grade silicone reinforced with a silicone membrane backing and is one of the most commonly used treatments for keloid scars. However, there is no up-to-date systematic review assessing the effectiveness of SGS for keloid scars. A clear and rigorous review of current evidence is required to guide clinicians, healthcare managers and people with keloid scarring.

OBJECTIVES

To assess the effectiveness of silicone gel sheeting for the treatment of keloid scars compared with standard care or other therapies.

SEARCH METHODS

We used standard, extensive Cochrane search methods. The latest search date was December 2021.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) that recruited people with any keloid scars and assessed the effectiveness of SGS.

DATA COLLECTION AND ANALYSIS

Two review authors independently performed study selection, risk of bias assessment, data extraction and GRADE assessment of the certainty of evidence. We resolved initial disagreements by discussion, or by consulting a third review author when necessary.

MAIN RESULTS

Two studies met the inclusion criteria. Study sample sizes were 16 and 20 participants. The trials were clinically heterogeneous with differences in causes for scarring (e.g. surgery, infected wounds, and trauma), site (e.g. chest and back), and ages of scars. The duration of follow-up was three and four and a half months. The included studies reported three comparisons; SGS compared with no treatment, SGS compared with non-silicone gel sheeting (a dressing similar to SGS but which does not contain silicone), and SGS compared with intralesional injections of triamcinolone acetonide. One trial had a split-body design and one trial had an unclear design (resulting in a mix of paired and clustered data). The included studies reported limited outcome data for the primary review outcome of scar severity measured by health professionals and no data were reported for severity of scar measured by patients or adverse events. For secondary outcomes some data on pain were reported, but health-related quality of life and cost-effectiveness were not reported. Both trials had suboptimal outcome reporting, thus many domains in the risk of bias were assessed as unclear. All evidence was rated as being very low-certainty, mainly due to risk of bias, indirectness, and imprecision.  SGS compared with no treatment Two studies with 33 participants (76 scars) reported the severity of scar assessed by health professionals, and we are uncertain about the effect of SGS on scar severity compared with no treatment (very low-certainty evidence, downgraded once for risk of bias, once for inconsistency, once for indirectness, and once for imprecision). We are uncertain about the effect of SGS on pain compared with no treatment (21 participants with 40 scars; very low-certainty evidence, downgraded once for risk of bias, once for inconsistency, once for indirectness, and once for imprecision). No data were reported for other outcomes including scar severity assessed by patients, adverse events, adherence to treatment, health-related quality of life and cost-effectiveness. SGS compared with non-SGS One study with 16 participants (25 scars) was included in this comparison. We are uncertain about the effect of SGS on scar severity assessed by health professionals compared with non-SGS (very low-certainty evidence, downgraded once for risk of bias, once for indirectness, and once for imprecision). We are also uncertain about the effect of SGS on pain compared with non-SGS (very low-certainty evidence, downgraded once for risk of bias, once for indirectness, and once for imprecision). No data were reported for other outcomes including scar severity assessed by patients, adverse events, adherence to treatment, health-related quality of life and cost-effectiveness. SGS compared with intralesional injections of triamcinolone acetonide One study with 17 participants (51 scars) reported scar severity assessed by health professionals, and we are uncertain about the effect of SGS on scar severity compared with intralesional injections of triamcinolone acetonide (very low-certainty evidence, downgraded once for risk of bias, once for indirectness, and once for imprecision). This study also reported pain assessed by health professionals among 5 participants (15 scars) and we are uncertain about the effect of SGS on pain compared with intralesional injections of triamcinolone acetonide (very low-certainty evidence, downgraded once for risk of bias, once for indirectness, and twice for imprecision). No data were reported for other outcomes including scar severity assessed by patients, adverse events, adherence to treatment, health-related quality of life and cost-effectiveness.

AUTHORS' CONCLUSIONS

There is currently a lack of RCT evidence about the clinical effectiveness of SGS in the treatment of keloid scars. From the two studies identified, there is insufficient evidence to demonstrate whether the use of SGS compared with no treatment, non-SGS, or intralesional injections of triamcinolone acetonide makes any difference in the treatment of keloid scars. Evidence from the included studies is of very low certainty, mainly driven by the risk of bias, indirectness, and imprecision due to small sample size. Further well-designed studies that have good reporting methodologies and address important clinical, quality of life and economic outcomes are required to reduce uncertainty around decision-making in the use of SGS to treat keloid scars.

Mechanobiological wound model for improved design and evaluation of collagen dermal replacement scaffolds

Skin wounds are among the most common and costly medical problems experienced. Despite the myriad of treatment options, such wounds continue to lead to displeasing cosmetic outcomes and also carry a high burden of loss-of-function, scarring, contraction, or nonhealing. As a result, the need exists for new therapeutic options that rapidly and reliably restore skin cosmesis and function. Here we present a new mechanobiological computational model to further the design and evaluation of next-generation regenerative dermal scaffolds fabricated from polymerizable collagen. A Bayesian framework, along with microstructure and mechanical property data from engineered dermal scaffolds and autograft skin, were used to calibrate constitutive models for collagen density, fiber alignment and dispersion, and stiffness. A chemo-bio-mechanical finite element model including collagen, cells, and representative cytokine signaling was adapted to simulate no-fill, dermal scaffold, and autograft skin outcomes observed in a preclinical animal model of full-thickness skin wounds, with a focus on permanent contraction, collagen realignment, and cellularization. Finite element model simulations demonstrated wound cellularization and contraction behavior that was similar to that observed experimentally. A sensitivity analysis suggested collagen fiber stiffness and density are important scaffold design features for predictably controlling wound contraction. Finally, prospective simulations indicated that scaffolds with increased fiber dispersion (isotropy) exhibited reduced and more uniform wound contraction while supporting cell infiltration. By capturing the link between multi-scale scaffold biomechanics and cell-scaffold mechanochemical interactions, simulated healing outcomes aligned well with preclinical animal model data. STATEMENT OF SIGNIFICANCE: Skin wounds continue to be a significant burden to patients, physicians, and the healthcare system. Advancing the mechanistic understanding of the wound healing process, including multi-scale mechanobiological interactions amongst cells, the collagen scaffolding, and signaling molecules, will aide in the design of new skin restoration therapies. This work represents the first step towards integrating mechanobiology-based computational tools with in vitro and in vivo preclinical testing data for improving the design and evaluation of custom-fabricated collagen scaffolds for dermal replacement. Such an approach has potential to expedite development of new and more effective skin restoration therapies as well as improve patient-centered wound treatment.

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.

A computational bio-chemo-mechanical model of in vivo tissue-engineered vascular graft development

Stenosis is the primary complication of current tissue-engineered vascular grafts used in pediatric congenital cardiac surgery. Murine models provide considerable insight into the possible mechanisms underlying this situation, but they are not efficient for identifying optimal changes in scaffold design or therapeutic strategies to prevent narrowing. In contrast, computational modeling promises to enable time- and cost-efficient examinations of factors leading to narrowing. Whereas past models have been limited by their phenomenological basis, we present a new mechanistic model that integrates molecular- and cellular-driven immuno- and mechano-mediated contributions to in vivo neotissue development within implanted polymeric scaffolds. Model parameters are inferred directly from in vivo measurements for an inferior vena cava interposition graft model in the mouse that are augmented by data from the literature. By complementing Bayesian estimation with identifiability analysis and simplex optimization, we found optimal parameter values that match model outputs with experimental targets and quantify variability due to measurement uncertainty. Utility is illustrated by parametrically exploring possible graft narrowing as a function of scaffold pore size, macrophage activity, and the immunomodulatory cytokine transforming growth factor beta 1 (TGF-β1). The model captures salient temporal profiles of infiltrating immune and synthetic cells and associated secretion of cytokines, proteases, and matrix constituents throughout neovessel evolution, and parametric studies suggest that modulating scaffold immunogenicity with early immunomodulatory therapies may reduce graft narrowing without compromising compliance.

Interactions at engineered graft-tissue interfaces: A review

The interactions at the graft-tissue interfaces are critical for the results of engraftments post-implantation. To improve the success rate of the implantations, as well as the quality of the patients' life, understanding the possible reactions between artificial materials and the host tissues is helpful in designing new generations of material-based grafts aiming at inducing specific responses from surrounding tissues for their own reparation and regeneration. To help researchers understand the complicated interactions that occur after implantations and to promote the development of better-designed grafts with improved biocompatibility and patient responses, in this review, the topics will be discussed from the basic reactions that occur chronologically at the graft-tissue interfaces after implantations to the existing and potential applications of the mechanisms of such reactions in designing of grafts. It offers a chance to bring up-to-date advances in the field and new strategies of controlling the graft-tissue interfaces.

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)-β, 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-β 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.

Electronic supplementary material

The online version of this article (10.1186/s12967-018-1406-x) contains supplementary material, which is available to authorized users.