THE ACUTE INFLAMMATORY RESPONSE IN DIVERSE SHOCK STATES

Increase in activated protein C mediates acute traumatic coagulopathy in mice

In severely injured and hypoperfused trauma patients, endogenous acute coagulopathy (EAC) is associated with an increased morbidity and mortality. Recent human data correlate this coagulopathy with activation of the protein C pathway. To examine the mechanistic role of protein C in the development of EAC, we used a mouse model of trauma and hemorrhagic shock, characterized by the combination of tissue injury and severe metabolic acidosis. Mice were subjected to one of four treatment groups: 1) C, control; 2) T, trauma (laparotomy); 3) H, hemorrhage (MAP, 35 mmHg x 60 min); 4) TH, trauma + hemorrhage. After 60 min, blood was drawn for analysis. Compared with C mice, the TH mice had a significantly elevated activated partial thromboplastin time (23.3 vs. 34.5 s) and significantly increased levels of activated protein C (aPC; 2.30 vs. 13.58 ng/mL). In contrast, T and H mice did not develop an elevated activated partial thromboplastin time or increased aPC. Selective inhibition of the anticoagulant property of aPC prevented the coagulopathy seen in response to trauma/hemorrhage (23.5 vs. 38.6 s [inhibitory vs. control monoclonal antibody]) with no impact on survival during the shock period. However, complete blockade of both the anticoagulant and cytoprotective functions of aPC caused 100% mortality within 45 min of shock, with histopathology evidence of pulmonary thrombosis and perivascular hemorrhage. These results indicate that our unique mouse model of T/H shock mimics our previous observations in trauma patients and demonstrates that EAC is mediated by the activation of the protein C pathway. In addition, the cytoprotective effect of protein C activation seems to be necessary for survival of the initial shock injury.

Mathematical modeling of posthemorrhage inflammation in mice: studies using a novel, computer-controlled, closed-loop hemorrhage apparatus

Hemorrhagic shock (HS) elicits a global acute inflammatory response, organ dysfunction, and death. We have used mathematical modeling of inflammation and tissue damage/dysfunction to gain insight into this complex response in mice. We sought to increase the fidelity of our mathematical model and to establish a platform for testing predictions of this model. Accordingly, we constructed a computerized, closed-loop system for mouse HS. The intensity, duration, and time to achieve target MAP could all be controlled using a software. Fifty-four male C57/black mice either were untreated or underwent surgical cannulation. The cannulated mice were divided into 8 groups: (a) 1, 2, 3, or 4 h of surgical cannulation alone and b) 1, 2, 3, or 4 h of cannulation + HS (25 mmHg). MAP was sustained by the computer-controlled reinfusion and withdrawal of shed blood within +/-2 mmHg. Plasma was assayed for the cytokines TNF, IL-6, and IL-10 as well as the NO reaction products NO2-/NO3-. The cytokine and NO2-/NO3- data were compared with predictions from a mathematical model of post-hemorrhage inflammation, which was calibrated on different data. To varying degrees, the levels of TNF, IL-6, IL-10, and NO2/NO3 predicted by the mathematical model matched these data closely. In conclusion, we have established a hardware/software platform that allows for highly accurate, reproducible, and mathematically predictable HS in mice.

The acute inflammatory response in trauma / hemorrhage and traumatic brain injury: current state and emerging prospects

Traumatic injury/hemorrhagic shock (T/HS) elicits an acute inflammatory response that may result in death. Inflammation describes a coordinated series of molecular, cellular, tissue, organ, and systemic responses that drive the pathology of various diseases including T/HS and traumatic brain injury (TBI). Inflammation is a finely tuned, dynamic, highly-regulated process that is not inherently detrimental, but rather required for immune surveillance, optimal post-injury tissue repair, and regeneration. The inflammatory response is driven by cytokines and chemokines and is partially propagated by damaged tissue-derived products (Damage-associated Molecular Patterns; DAMP's). DAMPs perpetuate inflammation through the release of pro-inflammatory cytokines, but may also inhibit anti-inflammatory cytokines. Various animal models of T/HS in mice, rats, pigs, dogs, and non-human primates have been utilized in an attempt to move from bench to bedside. Novel approaches, including those from the field of systems biology, may yield therapeutic breakthroughs in T/HS and TBI in the near future.

Early cytokine production risk stratifies trauma patients for multiple organ failure

BACKGROUND

Shock is a prime inciting event for postinjury multiple organ failure (MOF), believed to induce a state of injurious systemic inflammation. In animal models of hemorrhagic shock, early (< 24 hours) changes in cytokine production are an index of the systemic inflammatory response syndrome. However, their predictive value in trauma patients remains to be fully elucidated.

STUDY DESIGN

In a prospective observational pilot study of > 1 year at an urban Level I trauma center, serial (every 4 hours) serum cytokine levels were determined during a 24-hour period using multiplex suspension immunoassay in patients with major torso trauma (excluding severe brain injury) who met criteria for standardized shock resuscitation. Temporal cytokine expression was assessed during shock resuscitation in severe trauma patients to predict risk for MOF. MOF was assessed with the Denver score.

RESULTS

Of 48 study patients (mean age 39 +/- 3 years, 67% men, 88% blunt mechanism, mean Injury Severity Score 25 +/- 2), MOF developed in 11 (23%). MOF patients had a considerably higher mortality (64% versus 3%) and fewer ICU-free days (3.5 +/- 2 versus 17.8 +/- 1.3 days) compared with non-MOF patients. Traditional predictors of MOF, including age (45 +/- 7 versus 38 +/- 3 years; p=0.21), Injury Severity Score (26 +/- 3 versus 25 +/- 2; p=0.67), admission hemoglobin (11.4 +/- 0.9 versus 12.1 +/- 0.5 g/dL; p=0.22), international normalized ratio (1.6 +/- 0.2 versus 1.4 +/- 0.06; p=0.17), and base deficit (9.0 +/- 2 versus 7.1 +/- 0.8; p=0.19), were not significantly different between MOF and non-MOF patients. Statistical analysis identified six candidate predictors of MOF: inducible protein 10, macrophage inflammatory protein-1beta, interleukin-10, interleukin-6, interleukin-1Ra, and eotaxin.

CONCLUSIONS

These data provide insight into cytokine expression during traumatic shock that can enable earlier identification of patients at risk for development of MOF.

In silico simulation of corticosteroids effect on an NFkB- dependent physicochemical model of systemic inflammation

BACKGROUND

During the onset of an inflammatory response signaling pathways are activated for "translating" extracellular signals into intracellular responses converging to the activation of nuclear factor (NF)-kB, a central transcription factor in driving the inflammatory response. An inadequate control of its transcriptional activity is associated with the culmination of a hyper-inflammatory response making it a desired therapeutic target. Predicated upon the nature of the response, a systems level analysis might provide rational leads for the development of strategies that promote the resolution of the response.

METHODOLOGY AND FINDINGS

A physicochemical host response model is proposed to integrate biological information in the form of kinetic rules and signaling cascades with pharmacokinetic models of drug action for the modulation of the response. The unifying hypothesis is that the response is triggered by the activation of the NFkB signaling module and corticosteroids serve as a template for assessing anti-inflammatory strategies. The proposed in silico model is evaluated through its ability to predict and modulate uncontrolled responses. The pre-exposure of the system to hypercortisolemia, i.e. 6 hr before or simultaneously with the infectious challenge "reprograms" the dynamics of the host towards a balanced inflammatory response. However, if such an intervention occurs long before the inflammatory insult a symptomatic effect is observed instead of a protective relief while a steroid infusion after inducing inflammation requires much higher drug doses.

CONCLUSIONS AND SIGNIFICANCE

We propose a reversed engineered inflammation model that seeks to describe how the system responds to a multitude of external signals. Timing of intervention and dosage regimes appears to be key determinants for the protective or symptomatic effect of exogenous corticosteroids. Such results lie in qualitative agreement with in vivo human studies exposed both to LPS and corticosteroids under various time intervals thus improving our understanding of how interacting modules generate a behavior.

Interacting neuroendocrine and innate and acquired immune pathways regulate neutrophil mobilization from bone marrow following hemorrhagic shock

Polymorphonuclear neutrophils (PMN) are critical innate immune effector cells that either protect the host or exacerbate organ dysfunction by migrating to injured or inflamed tissues. Resuscitated hemorrhagic shock following major trauma promotes the development of organ inflammation by priming PMN migration and activation in response to a second, often trivial, stimulus (a so-called "two hit" phenomenon). PMN mobilization from bone marrow supports a sustained, hemorrhagic shock/resuscitation (HS/R)-primed migration of PMN. We addressed the role and mechanism of HS/R in regulating PMN egress from bone marrow. We demonstrate that HS/R through the alarmin HMGB1 induces IL-23 secretion from macrophages in an autocrine and TLR4 signaling-dependent manner. In turn IL-23, through an IL-17 G-CSF-mediated mechanism, induces PMN egress from bone marrow. We also show that beta-adrenergic receptor activation by catecholamine of macrophages mediates the HS/R-induced release of HMGB1. These data indicate that HS/R, a global ischemia/reperfusion stimulus, regulates PMN mobilization through a series of interacting pathways that include neuroendocrine and innate and acquired immune systems. Blocking this novel signaling axis may present a novel therapeutic target for posttrauma inflammation.

Translational potential of systems-based models of inflammation

A critical goal of translational research is to convert basic science to clinically relevant actions related to disease prevention, diagnosis, and eventually enable physicians to identify and evaluate treatment strategies. Integrated initiatives are identified as valuable in uncovering the mechanism underpinning the progression of human diseases. Tremendous opportunities have emerged in the context of systems biology that aims at the deconvolution of complex phenomena to their constituent elements and the quantification of the dynamic interactions between these components through the development of appropriate computational and mathematical models. In this review, we discuss the potential role systems-based translation research can have in the quest to better understand and modulate the inflammatory response.

Evidence for the participation of soluble triggering receptor expressed on myeloid cells-1 in the systemic inflammatory response syndrome after multiple trauma

BACKGROUND

Based on the implication of soluble triggering receptor expressed on myeloid cells (sTREM-1) in the septic cascade, it was investigated whether it participates or not in posttraumatic systemic inflammatory response syndrome (SIRS).

METHODS

Blood was sampled on days 1, 4, 7, and 15 from 69 patients with SIRS after multiple injuries and upon presentation of a septic complication. Concentrations of sTREM-1, tumor necrosis factor-alpha (TNFalpha), interleukin (IL)-6, IL-8, and interferon-gamma were determined by an enzyme immunoassay. Samples drawn on day 1 from 10 trauma patients without SIRS served as controls.

RESULTS

In 26 patients with SIRS without septic complication, sTREM-1, TNFalpha, and IL-8 remained stable over follow-up; IL-6 decreased and interferon-gamma increased on days 4 and 7 compared with day 1. TNFalpha was the only variable being higher upon advent of septic shock compared with patients without SIRS and upon presentation of SIRS, sepsis, and severe sepsis (p of comparisons with all subgroups <0.0001). Mortality of patients with sTREM-1 greater than 180 pg/mL was 5.3% compared with 28.0% of those with sTREM-1 lower than 180 pg/mL (p 0.035). sTREM-1 higher than 40 pg/mL had sensitivity 56.5% and specificity 91.7% for the differential diagnosis between SIRS and sepsis after multiple injuries.

CONCLUSIONS

This is the first study providing evidence about the participation of sTREM-1 in posttraumatic SIRS. Its levels are increased and remain constant over time in patients who did not develop any complications whereas it seems to behave as an anti-inflammatory mediator.

Modeling endotoxin-induced systemic inflammation using an indirect response approach

A receptor mediated model of endotoxin-induced human inflammation is proposed. The activation of the innate immune system in response to the endotoxin stimulus involves the interaction between the extracellular signal and critical receptors driving downstream signal transduction cascades leading to transcriptional changes. We explore the development of an in silico model that aims at coupling extracellular signals with essential transcriptional responses through a receptor mediated indirect response model. The model consists of eight (8) variables and is evaluated in a series of biologically relevant scenarios indicative of the non-linear behavior of inflammation. Such scenarios involve a self-limited response where the inflammatory stimulus is cleared successfully; a persistent infectious response where the inflammatory instigator is not eliminated, leading to an aberrant inflammatory response, and finally, a persistent non-infectious inflammatory response that can be elicited under an overload of the pathogen-derived product; as such high dose of the inflammatory insult can disturb the dynamics of the host response leading to an unconstrained inflammatory response. Finally, the potential of the model is demonstrated by analyzing scenarios associated with endotoxin tolerance and potentiation effects.

Patterns of cytokine release and evolution of remote organ dysfunction after bilateral femur fracture

The interaction between the complex pattern of cytokine release and remote organ dysfunction after trauma is incompletely understood. The aim of this study was to investigate the pattern of cytokine release and its association with the evolution of remote organ dysfunction after bilateral femur fracture. Male C57/BL6 mice were euthanized at six different time points (1-6 h) after bilateral femur fracture. Serum cytokine concentrations were measured with the Luminex multiplexing platform, and serum alanine aminotransferase levels were measured with the Vitros 950 Chemistry System. Hepatic and pulmonary myeloperoxidase activity was determined with an enzyme-linked immunosorbent assay kit. Permeability changes of the lung were assessed via bronchoalveolar lavage, and those of the liver via assessment of edema formation. Serum TNF-alpha was unchanged in the fracture group throughout the experiment. Serum IL-6 and keratinocyte levels peaked at 5 h postinjury, whereas IL-10 levels peaked at 2 and 6 h. A brief IL-1beta peak was observed at 3 h after fracture. Hepatic and pulmonary myeloperoxidase activity was significantly elevated within 1 h after trauma. Hepatic permeability was significantly increased within 2 h, and pulmonary permeability was significantly increased within 6 h after injury. Serum alanine aminotransferase levels peaked at 3 and 5 h postinjury. The pattern of serum IL-6, keratinocyte, IL-10, and IL-1beta release was dynamic, whereas no significant elevations in TNF-alpha were observed. The early hepatic and pulmonary infiltration of polymorphonuclear cells occurred in the absence of significantly elevated serum cytokine levels, suggesting that either early minor changes with an unbalance in inflammatory mediators or locally produced cytokines may initiate this process.

Mechanistic simulations of inflammation: current state and future prospects

Inflammation is a normal, robust physiological process. It can also be viewed as a complex system that senses and attempts to resolve homeostatic perturbations initiated from within the body (for example, in autoimmune disease) or from the outside (for example, in infections). Virtually all acute and chronic diseases are either driven or modulated by inflammation. The complex interplay between beneficial and harmful arms of the inflammatory response may underlie the lack of fully effective therapies for many diseases. Mathematical modeling is emerging as a frontline tool for understanding the complexity of the inflammatory response. A series of articles in this issue highlights various modeling approaches to inflammation in the larger context of health and disease, from intracellular signaling to whole-animal physiology. Here we discuss the state of this emerging field. We note several common features of inflammation models, as well as challenges and prospects for future studies.

A patient-specific in silico model of inflammation and healing tested in acute vocal fold injury

The development of personalized medicine is a primary objective of the medical community and increasingly also of funding and registration agencies. Modeling is generally perceived as a key enabling tool to target this goal. Agent-Based Models (ABMs) have previously been used to simulate inflammation at various scales up to the whole-organism level. We extended this approach to the case of a novel, patient-specific ABM that we generated for vocal fold inflammation, with the ultimate goal of identifying individually optimized treatments. ABM simulations reproduced trajectories of inflammatory mediators in laryngeal secretions of individuals subjected to experimental phonotrauma up to 4 hrs post-injury, and predicted the levels of inflammatory mediators 24 hrs post-injury. Subject-specific simulations also predicted different outcomes from behavioral treatment regimens to which subjects had not been exposed. We propose that this translational application of computational modeling could be used to design patient-specific therapies for the larynx, and will serve as a paradigm for future extension to other clinical domains.

The role of fracture-associated soft tissue injury in the induction of systemic inflammation and remote organ dysfunction after bilateral femur fracture

OBJECTIVES

The storage of preformed cytokines in soft tissue as well as the immunocompetence of adipocytes has been reported. We hypothesized that fracture-associated soft tissue injury plays a pivotal role in the induction of systemic inflammation and remote organ dysfunction after fracture.

MATERIALS AND METHODS

Male C57/BL6 mice sustained either severe soft tissue injury to both thighs (STI), bilateral femur fracture with minimal soft tissue injury (Fx), or the combination of both (Fx+STI) and were euthanized 6 hours after injury. Serum cytokine concentrations were measured using the Luminex multiplexing platform, and serum ALT levels were measured with the Vitros 950 Chemistry System. Hepatic myeloperoxidase activity, a marker for polymorphonuclear cell infiltration, and hepatic IL-6 levels were determined using ELISA kits. Hepatic permeability changes were assessed via measurement of edema formation.

RESULTS

STI as well as Fx both induced significantly elevated serum IL-6 and L-10 levels as compared with Sham animals (P < 0.05). Further, serum IL-6 and IL-10 levels were significantly higher after STI as compared with Fx (P < 0.05). Serum KC and MCP-1 levels were significantly elevated after STI but not after Fx (P < 0.05). STI as well as Fx resulted in significantly increased serum ALT levels and hepatic polymorphonuclear cell infiltration. The combination of both injuries resulted in further increased systemic inflammatory mediators as well as marked liver inflammation and dysfunction represented by significantly elevated serum ALT levels, hepatic polymorphonuclear cell infiltration, hepatic IL-6 concentrations, and hepatic edema formation as compared with Sham animals (P < 0.05).

CONCLUSIONS

Although STI and Fx both induced a systemic inflammatory response, this was more pronounced after STI. However, the combination of both injuries (Fx+STI) was required to induce marked liver dysfunction. Our data indicate that fracture-associated soft tissue injury is a major contributor to the systemic inflammatory response after bilateral femur fracture. This should be recognized especially in multiply injured patients, who are susceptible to systemic inflammation with remote organ dysfunction.

In vivo-to-in silico iterations to investigate aeroallergen-host interactions

BACKGROUND

Allergic asthma is a complex process arising out of the interaction between the immune system and aeroallergens. Yet, the relationship between aeroallergen exposure, allergic sensitization and disease remains unclear. This knowledge is essential to gain further insight into the origin and evolution of allergic diseases. The objective of this research is to develop a computational view of the interaction between aeroallergens and the host by investigating the impact of dose and length of aeroallergen exposure on allergic sensitization and allergic disease outcomes, mainly airway inflammation and to a lesser extent lung dysfunction and airway remodeling.

METHODS AND PRINCIPAL FINDINGS

BALB/C mice were exposed intranasally to a range of concentrations of the most pervasive aeroallergen worldwide, house dust mite (HDM), for up to a quarter of their lifespan (20 weeks). Actual biological data delineating the kinetics, nature and extent of responses for local (airway inflammation) and systemic (HDM-specific immunoglobulins) events were obtained. Mathematical equations for each outcome were developed, evaluated, refined through several iterations involving in vivo experimentation, and validated. The models accurately predicted the original biological data and simulated an extensive array of previously unknown responses, eliciting two- and three-dimensional models. Our data demonstrate the non-linearity of the relationship between aeroallergen exposure and either allergic sensitization or airway inflammation, identify thresholds, behaviours and maximal responsiveness for each outcome, and examine inter-variable relationships.

CONCLUSIONS

This research provides a novel way to visualize allergic responses in vivo and establishes a basic experimental platform upon which additional variables and perturbations can be incorporated into the system.

Equation-based models of dynamic biological systems

The purpose of this review is to introduce differential equations as a simulation tool in the biological and clinical sciences. This modeling technique is very mature and has been a preferred tool of physiologists and bioengineers and of quantitative scientists in general to describe and predict the behavior of complex interacting systems. However, this methodology has not been widely used within clinical medicine due to a lack of familiarity with highly quantitative methods and a greater acquaintance with statistical modeling approaches based on inference and empirical data analysis. We will describe various aspects of equation-based modeling, including underlying assumptions, strengths, and weaknesses and provide specific examples of simple models. We conclude that the usefulness of quantitative modeling, including equation-based models, is ultimately linked to the quality and abundance of observation obtained on the system being modeled. Equation-based modeling, although potentially an integrative approach, is complementary to and extends the potential of traditional statistically based approaches to inference.

An ensemble of models of the acute inflammatory response to bacterial lipopolysaccharide in rats: results from parameter space reduction

In previous work, we developed an 8-state nonlinear dynamic model of the acute inflammatory response, including activated phagocytic cells, pro- and anti-inflammatory cytokines, and tissue damage, and calibrated it to data on cytokines from endotoxemic rats. In the interest of parsimony, the present work employed parametric sensitivity and local identifiability analysis to establish a core set of parameters predominantly responsible for variability in model solutions. Parameter optimization, facilitated by varying only those parameters belonging to this core set, was used to identify an ensemble of parameter vectors, each representing an acceptable local optimum in terms of fit to experimental data. Individual models within this ensemble, characterized by their different parameter values, showed similar cytokine but diverse tissue damage behavior. A cluster analysis of the ensemble of models showed the existence of a continuum of acceptable models, characterized by compensatory mechanisms and parameter changes. We calculated the direct correlations between the core set of model parameters and identified three mechanisms responsible for the conversion of the diverse damage time courses to similar cytokine behavior in these models. Given that tissue damage level could be an indicator of the likelihood of mortality, our findings suggest that similar cytokine dynamics could be associated with very different mortality outcomes, depending on the balance of certain inflammatory elements.

Translational systems biology of inflammation

Inflammation is a complex, multi-scale biologic response to stress that is also required for repair and regeneration after injury. Despite the repository of detailed data about the cellular and molecular processes involved in inflammation, including some understanding of its pathophysiology, little progress has been made in treating the severe inflammatory syndrome of sepsis. To address the gap between basic science knowledge and therapy for sepsis, a community of biologists and physicians is using systems biology approaches in hopes of yielding basic insights into the biology of inflammation. “Systems biology” is a discipline that combines experimental discovery with mathematical modeling to aid in the understanding of the dynamic global organization and function of a biologic system (cell to organ to organism). We propose the term translational systems biology for the application of similar tools and engineering principles to biologic systems with the primary goal of optimizing clinical practice. We describe the efforts to use translational systems biology to develop an integrated framework to gain insight into the problem of acute inflammation. Progress in understanding inflammation using translational systems biology tools highlights the promise of this multidisciplinary field. Future advances in understanding complex medical problems are highly dependent on methodological advances and integration of the computational systems biology community with biologists and clinicians.

Mathematical model of the acute inflammatory response to Escherichia coli in intramammary challenge

We constructed a mathematical model of the early response to Escherichia coli infection of the mammary gland and explored the roles and interactions between inflammatory cells and bacteria. The model incorporates 3 equations that describe the interactions among bacteria, milk somatic cells, and blood leukocyte densities. These 3 equations were fitted to cell densities observed during acute inflammatory responses in unvaccinated and vaccinated heifers inoculated with 10(4) or 10(6) cfu of E. coli. The rates computed for the cellular transit from the storage sites to the blood and from the blood to the milk were lower in cows receiving 10(4) cfu but increased at approximately 6 x 10(-6) and 30 x 10(-6) microL/cfu per h in nonvaccinated or vaccinated cows inoculated with 10(6) cfu, respectively. The cellular rates of bacterial killing were highest in unvaccinated cows ( approximately 400 x 10(-6) microL/cell per h) when compared with vaccinated cows (200 to 300 x 10(-6) microL/cell per h). A critical density of milk somatic cells at which bacteria density is constant was computed from the model at 2 x 10(6) cells/mL, and a one-way sensitivity analysis revealed that the changes in milk cellular densities were mostly sensitive to variations in the rate of bacterial killing and in the rate of production of inflammatory cells.

Anesthetics impact the resolution of inflammation

BACKGROUND

Local and volatile anesthetics are widely used for surgery. It is not known whether anesthetics impinge on the orchestrated events in spontaneous resolution of acute inflammation. Here we investigated whether a commonly used local anesthetic (lidocaine) and a widely used inhaled anesthetic (isoflurane) impact the active process of resolution of inflammation.

METHODS AND FINDINGS

Using murine peritonitis induced by zymosan and a systems approach, we report that lidocaine delayed and blocked key events in resolution of inflammation. Lidocaine inhibited both PMN apoptosis and macrophage uptake of apoptotic PMN, events that contributed to impaired PMN removal from exudates and thereby delayed the onset of resolution of acute inflammation and return to homeostasis. Lidocaine did not alter the levels of specific lipid mediators, including pro-inflammatory leukotriene B(4), prostaglandin E(2) and anti-inflammatory lipoxin A(4), in the cell-free peritoneal lavages. Addition of a lipoxin A(4) stable analog, partially rescued lidocaine-delayed resolution of inflammation. To identify protein components underlying lidocaine's actions in resolution, systematic proteomics was carried out using nanospray-liquid chromatography-tandem mass spectrometry. Lidocaine selectively up-regulated pro-inflammatory proteins including S100A8/9 and CRAMP/LL-37, and down-regulated anti-inflammatory and some pro-resolution peptides and proteins including IL-4, IL-13, TGF-â and Galectin-1. In contrast, the volatile anesthetic isoflurane promoted resolution in this system, diminishing the amplitude of PMN infiltration and shortening the resolution interval (Ri) approximately 50%. In addition, isoflurane down-regulated a panel of pro-inflammatory chemokines and cytokines, as well as proteins known to be active in cell migration and chemotaxis (i.e., CRAMP and cofilin-1). The distinct impact of lidocaine and isoflurane on selective molecules may underlie their opposite actions in resolution of inflammation, namely lidocaine delayed the onset of resolution (T(max)), while isoflurane shortened resolution interval (Ri).

CONCLUSIONS

Taken together, both local and volatile anesthetics impact endogenous resolution program(s), altering specific resolution indices and selective cellular/molecular components in inflammation-resolution. Isoflurane enhances whereas lidocaine impairs timely resolution of acute inflammation.

Modeling longitudinal data in acute illness

Biomarkers of sepsis could allow early identification of high-risk patients, in whom aggressive interventions can be life-saving. Among those interventions are the immunomodulatory therapies, which will hopefully become increasingly available to clinicians. However, optimal use of such interventions will probably be patient specific and based on longitudinal profiles of such biomarkers. Modeling techniques that allow proper interpretation and classification of these longitudinal profiles, as they relate to patient characteristics, disease progression, and therapeutic interventions, will prove essential to the development of such individualized interventions. Once validated, these models may also prove useful in the rational design of future clinical trials and in the interpretation of their results. However, only a minority of mathematicians and statisticians are familiar with these newer techniques, which have undergone remarkable development during the past two decades. Interestingly, critical illness has the potential to become a key testing ground and field of application for these emerging modeling techniques, given the increasing availability of point-of-care testing and the need for titrated interventions in this patient population.

Translational systems biology: introduction of an engineering approach to the pathophysiology of the burn patient

The pathophysiology of the burn patient manifests the full spectrum of the complexity of the inflammatory response. In the acute phase, inflammation may have negative effects via capillary leak, the propagation of inhalation injury, and development of multiple organ failure. Attempts to mediate these processes remain a central subject of burn care research. Conversely, inflammation is a necessary prologue and component in the later stage processes of wound healing. Despite the volume of information concerning the cellular and molecular processes involved in inflammation, there exists a significant gap between the knowledge of mechanistic pathophysiology and the development of effective clinical therapeutic regimens. Translational systems biology (TSB) is the application of dynamic mathematical modeling and certain engineering principles to biological systems to integrate mechanism with phenomenon and, importantly, to revise clinical practice. This study will review the existing applications of TSB in the areas of inflammation and wound healing, relate them to specific areas of interest to the burn community, and present an integrated framework that links TSB with traditional burn research.

Agent-based model of inflammation and wound healing: insights into diabetic foot ulcer pathology and the role of transforming growth factor-beta1

Inflammation and wound healing are inextricably linked and complex processes, and are deranged in the setting of chronic, nonhealing diabetic foot ulcers (DFU). An ideal therapy for DFU should both suppress excessive inflammation while enhancing healing. We reasoned that biological simulation would clarify mechanisms and help refine therapeutic approaches to DFU. We developed an agent-based model (ABM) capable of reproducing qualitatively much of the literature data on skin wound healing, including changes in relevant cell populations (macrophages, neutrophils, fibroblasts) and their key effector cytokines (tumor necrosis factor-alpha [TNF], interleukin [IL]-1beta, IL-10, and transforming growth factor [TGF]-beta1). In this simulation, a normal healing response results in tissue damage that first increases (due to wound-induced inflammation) and then decreases as the collagen levels increase. Studies by others suggest that diabetes and DFU are characterized by elevated TNF and reduced TGF-beta1, although which of these changes is a cause and which one is an effect is unclear. Accordingly, we simulated the genesis of DFU in two ways, either by (1) increasing the rate of TNF production fourfold or (2) by decreasing the rate of TGF-beta1 production 67% based on prior literature. Both manipulations resulted in increased inflammation (elevated neutrophils, TNF, and tissue damage) and delayed healing (reduced TGF-beta1 and collagen). Our ABM reproduced the therapeutic effect of platelet-derived growth factor/platelet releasate treatment as well as DFU debridement. We next simulated the expected effect of administering (1) a neutralizing anti-TNF antibody, (2) an agent that would increase the activation of endogenous latent TGF-beta1, or (3) latent TGF-beta1 (which has a longer half-life than active TGF-beta1), and found that these therapies would have similar effects regardless of the initial assumption of the derangement that underlies DFU (elevated TNF vs. reduced TGF-beta1). In silico methods may elucidate mechanisms of and suggest therapies for aberrant skin healing.

Challenges for modeling and interpreting the complex biology of severe injury and inflammation

Human injury is associated with inflammatory responses that are modulated by the acute and chronic activity of endogenous factors and exogenous interventions. A characteristic feature of chronic, severe inflammatory states is the diminished signal output variability of many organ systems, including innate immune responsiveness and endogenous neural and endocrine-mediated functions. The attenuation of signal/response variability and integration of feedback capacity may contribute to systemic and tissue-specific deterioration of function. Some well-intentioned therapies directed toward support of systemic and tissue functions may actually promote the loss of system(s) adaptability and contribute to adverse outcomes in severely stressed patients. In vivo and in silico models of stress, injury, and infection have yet to fully define the influences of ongoing stressful stimulae as well as genetic variation and epigenetic factors in the context of an evolving inflammatory state. Experimental and human models incorporating variable, antecedent stress(es) and altered neuroendocrine rhythms might approximate the altered adaptability in immune and organ function responses. Such models may also provide insights into the salient mechanisms of risk and outcome more precisely than do the constrained study conditions of current animal or human models of systemic inflammation.

In Silico Modeling in Infectious Disease

Infectious disease has witnessed the emergence of mathematical modeling a tool of synthesizing data of growing complexity now available to clinicians and basic scientists alike. The purpose of this review is to introduce mathematical tools commonly used to model infectious disease. We will illustrate the use of equation-based, agent-based or statistical modeling approaches to a variety of examples pertaining to acute inflammation, bacterial dynamics, viral dynamics, and signaling pathways, focusing of host-pathogen interactions rather than population models. We will discuss the strengths and weaknesses of these approaches and offer future perspectives for this rapidly evolving field.

Trevor Trust – AstraZeneca R&D Boston, 35 Gatehouse Drive, Waltham, MA 02451, USA

Challenges and rewards on the road to translational systems biology in acute illness: four case reports from interdisciplinary teams

INTRODUCTION

Translational systems biology approaches can be distinguished from mainstream systems biology in that their goal is to drive novel therapies and streamline clinical trials in critical illness. One systems biology approach, dynamic mathematical modeling (DMM), is increasingly used in dealing with the complexity of the inflammatory response and organ dysfunction. The use of DMM often requires a broadening of research methods and a multidisciplinary team approach that includes bioscientists, mathematicians, engineers, and computer scientists. However, the development of these groups must overcome domain-specific barriers to communication and understanding.

METHODS

We present 4 case studies of successful translational, interdisciplinary systems biology efforts, which differ by organizational level from an individual to an entire research community.

RESULTS

Case 1 is a single investigator involved in DMM of the acute inflammatory response at Cook County Hospital, in which extensive translational progress was made using agent-based models of inflammation and organ damage. Case 2 is a community-level effort from the University of Witten-Herdecke in Cologne, whose efforts have led to the formation of the Society for Complexity in Acute Illness. Case 3 is an institution-based group, the Biosystems Group at the University of California, San Francisco, whose work has included a focus on a common lexicon for DMM. Case 4 is an institution-based, transdisciplinary research group (the Center for Inflammation and Regenerative Modeling at the University of Pittsburgh), whose modeling work has led to internal education efforts, grant support, and commercialization.

CONCLUSION

A transdisciplinary approach, which involves team interaction in an iterative fashion to address ambiguity and is supported by educational initiatives, is likely to be necessary for DMM in acute illness. Communitywide organizations such as the Society of Complexity in Acute Illness must strive to facilitate the implementation of DMM in sepsis/trauma research into the research community as a whole.

The tumor necrosis factor alpha -308 G/A polymorphism does not influence inflammation and coagulation response in human endotoxemia

Tumor necrosis factor (TNF)-alpha plays a major role in the immune system. Release of proinflammatory cytokines, such as TNF-alpha and interleukin 6, by macrophages and other cells occurs in response to bacterial products. It has been reported that the TNF-alpha -308 G/A polymorphism in the TNF-alpha gene determines basal TNF-alpha levels. We hypothesized that it may also be associated with the degree of inflammatory response in a well-standardized model of systemic inflammation. Eighty-seven young men (age range, 19-35 years) received 2 ng/kg i.v. endotoxin (lipopolysaccharide [LPS]). The TNF-alpha promoter genotype was analyzed on a TaqMan genomic analyzer. Inflammation markers (interleukin 6, TNF-alpha), temperature, and coagulation markers (prothrombin fragment F1+2, D-dimer) were measured at 0, 2, 6, and 24 h after LPS infusion. Tumor necrosis factor-alpha plasma concentrations increased from a baseline 1.3 ng/L (range, 0.8-3.1 ng/L) before LPS infusion to a peak of 57.5 ng/L (range, 10.8-131.4 ng/L) at 2 h after LPS and then decreased continually to 10.8 ng/L (range, 4.7-16.5 ng/L) after 6 h and returned to baseline values after 24 h (1.9 ng/L [range, 1.1-3.9 ng/L]). We observed no significant differences in TNF-alpha baseline levels or in response to LPS after stratification of the data according to TNF-alpha genotype. Basal and peak values of selected inflammatory and coagulation markers were not different between wild-type TNF-alpha -308 individuals (GG) and carriers of the TNF-alpha -308 mutant allele (GA and AA). The TNF-alpha -308 G/A polymorphism does not contribute significantly to the individual variability of systemic TNF-alpha plasma concentrations after endotoxin challenge. Thus, if any, the impact of the TNF-alpha -308 G/A polymorphism on systemic endotoxin-triggered inflammation seems to be limited.

Mathematical modeling in necrotizing enterocolitis--a new look at an ongoing problem

Necrotizing enterocolitis (NEC) is the most common and lethal disease that affects the gastrointestinal (GI) tract of the premature infant. The etiology of NEC remains undefined. The only consistent epidemiological precursors for NEC are prematurity and enteral alimentation. Various inflammatory mediators, including tumor necrosis factor (TNF)-a, interleukin (IL)-1, IL-6, IL-8, IL-10, IL-18, platelet-activating factor (PAF), and nitric oxide (NO) have been implicated in the pathogenesis of NEC, but the kinetics and role of these agents are ill-defined. Currently, there are no biomarker predictors of NEC risk and severity. Sera or tissue from early time points in the development of the disease may help delineate early inflammatory events that predispose an individual to NEC, thus providing an interventional opportunity. We suggest that the lack of diagnostic and therapeutic modalities for NEC are due to the absence of a systems view of the disease, which in turn is hindered by a lack of sensitive physiological measurements that predict perturbations in the intestinal tissue compartment and an inability to reliably test serial samples for the presence of inflammatory mediators in small volumes and in a high-throughput manner. Computational modeling is a useful tool in the study of complex systems such as the inflammatory process. Computation models provide an "existence proof" for a given mechanism, uncover subtle inconsistencies between the underlying hypotheses and quantitative data, and force one to ask how much is known. We suggest that a properly validated and calibrated mathematical model of inflammation and its pathologic consequences in NEC will be useful for predicting the physiologic and biologic response in infants suffering from the disease.

Evidence-based modeling of critical illness: an initial consensus from the Society for Complexity in Acute Illness

INTRODUCTION

Given the complexity of biological systems, understanding their dynamic behaviors, such as the Acute Inflammatory Response (AIR), requires a formal synthetic process. Dynamic Mathematical Modeling (DMM) represents a suite of methods intended for inclusion within the required synthetic framework. The DMM, however, is a relatively novel approach in the practice of biomedical research. The Society for Complexity in Acute Illness (SCAI) was formed in 2004 from the leading research groups using DMM in the study of acute inflammation. This society believes that it is important to offer guidelines for the design, development, and use of DMM in the setting of AIR research to avoid the "garbage in, garbage out" problem. Accordingly, SCAI identified a need for and carried out a critical appraisal of DMM as currently used in the setting of acute illness.

METHODS

The SCAI annual meeting in 2005, the Fourth International Conference on Complexity in Acute Illness (Cologne, Germany), was structured with the intent of developing a consensus statement on the methods and execution of DMM in AIR research. The conference was organized to include a series of interactive breakout sessions that included thought leaders from both the DMM and acute illness fields, the results of which were then presented in summary form to the entire group for discussion and consensus. The information in this article represents the concatenation of those presentations.

RESULTS

The output from the Fourth International Conference on Complexity in Acute Illness involved consensus statements for the following topics: (1) the need for DMM; (2) a suggested approach for the process of establishing a modeling project; (3) the type of "wet" laboratory experiments and data needed to establish a modeling project; (4) general quality measures for data to be input to a modeling project; and (5) a descriptive list of several types of DMM to provide guidance in selection of a method for a project.

CONCLUSION

We believe that the complexity of biological systems requires that DMM needs to be among the methods used to improve understanding and make progress with attempts to characterize and manipulate the AIR. We believe that this consensus statement will help guide the integration, rational implementation, and standardization of DMM into general biomedical research.

The role of initial trauma in the host's response to injury and hemorrhage: insights from a correlation of mathematical simulations and hepatic transcriptomic analysis

Trauma and hemorrhagic shock (HS) elicit severe physiological disturbances that predispose the victims to subsequent organ dysfunction and death. The general lack of effective therapeutic options for these patients is mainly due to the complex interplay of interacting inflammatory and physiological elements working at multiple levels. Systems biology has emerged as a new paradigm that allows the study of large portions of physiological networks simultaneously. Seeking a better understanding of the interplay among known inflammatory pathways, we constructed a mathematical model encompassing the dynamics of the acute inflammatory response that incorporates the intertwined effects of inflammation and global tissue damage. The model was calibrated using data from C57Bl/6 mice subjected to endotoxemia, sham operation (i.e., surgical trauma induced by cannulation [ST]) or ST + HS+ resuscitation (ST-HS-R). An in silico simulation, made at whole-organism level, suggested that similar pathways of different magnitudes were operant as the degree of total body damage increased. We sought to validate this hypothesis by subjecting mice to HS and comparing the models predictions to circulating markers of inflammation and tissue injury as well as the global transcriptomic response of the liver. C57Bl/6 mice were subjected to ST or ST-HS (without resuscitation). Liver gene expression was assessed using an Affymetrix DNA microarray (GeneChip Mouse Expression Set 430A, Affymetrix, Santa Clara, CA), which contains 22,621 probe sets and effectively interrogates 12,341 mouse genes. The microarray data sets were subjected to hierarchical clustering and pathway analysis. In agreement with model predictions, circulating levels of inflammation/tissue injury markers and the microarray analysis both demonstrated that ST alone accounts for a substantial proportion of the observed phenotypic and genetic/molecular changes versus untreated animals. The addition of HS further increased the magnitude of gene expression, but relatively few additional genes were recruited. Mathematical simulations and DNA microarrays, both systems biology tools, may provide valuable insight into the complex global physiological interactions that occur in response to trauma and hemorrhagic shock.

Estrogen-mediated activation of non-genomic pathway improves macrophages cytokine production following trauma-hemorrhage

Although 17beta-estradiol (E2) attenuates the alterations in Kupffer cells and splenic macrophages (MPhi) cytokine production following trauma-hemorrhage, the mechanism by which this occurs remains unknown. Utilizing a cell-impermeable E2 conjugated with BSA (E2-BSA), we examined the non-genomic effects of E2 on the above two cell population cytokine production, MAPK and transcription factors activation following trauma-hemorrhage. Male Sprague-Dawley rats underwent trauma-hemorrhage (mean BP 40 mmHg for 90 min, then resuscitation). E2, E2-BSA (1 mg/kg E2) with or without an estrogen receptor antagonist (ICI 182,780), or vehicle was administrated during resuscitation. Two hrs thereafter, Kupffer cells and SMPhi production of IL-6, TNF-alpha, and IL-10, activation of MAPK (p38, ERK-1/2, and JNK), and transcription factors (NF-kappaB and AP-1) were determined. IL-6, TNF-alpha, and IL-10 productive capacity, MAPK, and transcription factors activation increased in Kupffer cells while they decreased in SMPhi following trauma-hemorrhage. However, E2 administration normalized all of these alterations. Although E2-BSA also attenuated the alterations in cytokine production/transcription factors, the values were higher in Kupffer cells and lower in SMPhi compared to shams. In contrast, E2-BSA prevented trauma-hemorrhage-mediated changes in MAPK activation to the same extent as E2. Co-administration of ICI 182,780 abolished E2-BSA effects. Although some MAPK inhibitors suppressed cytokine production, the inhibitor effectiveness was dependent on cytokine, cell type and animal condition (trauma-hemorrhage or sham). Thus, E2 effects on Kupffer cells and SMPhi cytokine production and transcription factors activation following trauma-hemorrhage are mediated at least in part via non-genomic pathway and these non-genomic effects are likely mediated via MAPK pathways.

A dynamical model of human immune response to influenza A virus infection

We present a simplified dynamical model of immune response to uncomplicated influenza A virus (IAV) infection, which focuses on the control of the infection by the innate and adaptive immunity. Innate immunity is represented by interferon-induced resistance to infection of respiratory epithelial cells and by removal of infected cells by effector cells (cytotoxic T-cells and natural killer cells). Adaptive immunity is represented by virus-specific antibodies. Similar in spirit to the recent model of Bocharov and Romanyukha [1994. Mathematical model of antiviral immune response. III. Influenza A virus infection. J. Theor. Biol. 167, 323-360], the model is constructed as a system of 10 ordinary differential equations with 27 parameters characterizing the rates of various processes contributing to the course of disease. The parameters are derived from published experimental data or estimated so as to reproduce available data about the time course of IAV infection in a naïve host. We explore the effect of initial viral load on the severity and duration of the disease, construct a phase diagram that sheds insight into the dynamics of the disease, and perform sensitivity analysis on the model parameters to explore which ones influence the most the onset, duration and severity of infection. To account for the variability and speed of adaptation of the adaptive response to a particular virus strain, we introduce a variable that quantifies the antigenic compatibility between the virus and the antibodies currently produced by the organism. We find that for small initial viral load the disease progresses through an asymptomatic course, for intermediate value it takes a typical course with constant duration and severity of infection but variable onset, and for large initial viral load the disease becomes severe. This behavior is robust to a wide range of parameter values. The absence of antibody response leads to recurrence of disease and appearance of a chronic state with nontrivial constant viral load.

IN SILICO MODELS OF ACUTE INFLAMMATION IN ANIMALS

Trauma and hemorrhagic shock elicit an acute inflammatory response, predisposing patients to sepsis, organ dysfunction, and death. Few approved therapies exist for these acute inflammatory states, mainly due to the complex interplay of interacting inflammatory and physiological elements working at multiple levels. Various animal models have been used to simulate these phenomena, but these models often do not replicate the clinical setting of multiple overlapping insults. Mathematical modeling of complex systems is an approach for understanding the interplay among biological interactions. We constructed a mathematical model using ordinary differential equations that encompass the dynamics of cells and cytokines of the acute inflammatory response, as well as global tissue dysfunction. The model was calibrated in C57Bl/6 mice subjected to (1) various doses of lipopolysaccharide (LPS) alone, (2) surgical trauma, and (3) surgery + hemorrhagic shock. We tested the model's predictive ability in scenarios on which it had not been trained, namely, (1) surgery +/- hemorrhagic shock + LPS given at times after the beginning of surgical instrumentation, and (2) surgery + hemorrhagic shock + bilateral femoral fracture. Software was created that facilitated fitting of the mathematical model to experimental data, as well as for simulation of experiments with various inflammatory challenges and associated variations (gene knockouts, inhibition of specific cytokines, etc.). Using this software, the C57Bl/6-specific model was recalibrated for inflammatory analyte data in CD14-/- mice and was used to elucidate altered features of inflammation in these animals. In other experiments, rats were subjected to surgical trauma +/- LPS or to bacterial infection via fibrin clots impregnated with various inocula of Escherichia coli. Mathematical modeling may provide insights into the complex dynamics of acute inflammation in a manner that can be tested in vivo using many fewer animals than has been possible previously.

A reduced mathematical model of the acute inflammatory response II. Capturing scenarios of repeated endotoxin administration

Bacterial lipopolysaccharide (LPS; endotoxin) is a potent immunostimulant that can induce an acute inflammatory response comparable to a bacterial infection. Experimental observations demonstrate that this biological response can be either blunted (tolerance) or augmented (potentiation) with repeated administration of endotoxin. Both phenomena are of clinical relevance. We show that a four-dimensional differential equation model of this response reproduces many scenarios involving repeated endotoxin administration. In particular, the model can display both tolerance and potentiation from a single parameter set, under different administration scenarios. The key determinants of the outcome of our simulations are the relative time-scales of model components. These findings support the hypothesis that endotoxin tolerance and other related phenomena can be considered as dynamic manifestations of a unified acute inflammatory response, and offer specific predictions related to the dynamics of this response to endotoxin.

A reduced mathematical model of the acute inflammatory response: I. Derivation of model and analysis of anti-inflammation

The acute inflammatory response, triggered by a variety of biological or physical stresses on an organism, is a delicate system of checks and balances that, although aimed at promoting healing and restoring homeostasis, can result in undesired and occasionally lethal physiological responses. In this work, we derive a reduced conceptual model for the acute inflammatory response to infection, built up from consideration of direct interactions of fundamental effectors. We harness this model to explore the importance of dynamic anti-inflammation in promoting resolution of infection and homeostasis. Further, we offer a clinical correlation between model predictions and potential therapeutic interventions based on modulation of immunity by anti-inflammatory agents.

In silico and in vivo approach to elucidate the inflammatory complexity of CD14-deficient mice

The inflammatory phenotype of genetically modified mice is complex, and the role of Gram-negative lipopolysaccharide (LPS) in acute inflammation induced by surgical cannulation trauma, alone or in combination with hemorrhage and resuscitation ("hemorrhagic shock"), is both complex and controversial. We sought to determine if a mathematical model of acute inflammation could elucidate both the phenotype of CD14-deficient (CD14(-/-)) mice--following LPS, cannulation, or hemorrhagic shock--and the role of LPS in trauma/hemorrhage-induced inflammation. A mathematical model of inflammation initially calibrated in wild-type (C57Bl/6) mice subjected to LPS, cannulation, and hemorrhagic shock was recalibrated in CD14(-/-) mice subjected to the same insults, yielding an ensemble of models that suggested specific differences at the cellular and molecular levels (for example, 43-fold lower activation of leukocytes by LPS). The CD14(-/-)-specific model ensemble could account for complex changes in inflammatory analytes in these mice following LPS treatment. Model prediction of similar organ damage in CD14(-/-) and wild-type mice subjected to cannulation alone or with hemorrhagic shock was verified in vivo (similar ALT levels). These studies suggest that LPS-CD14 responses do not cause inflammation in surgical trauma/hemorrhagic shock and demonstrate a novel use of combined in silico and in vivo methods to elucidate the complex inflammatory phenotype of genetically modified animals.

Sepsis progression and outcome: a dynamical model

Background

Sepsis (bloodstream infection) is the leading cause of death in non-surgical intensive care units. It is diagnosed in 750,000 US patients per annum, and has high mortality. Current understanding of sepsis is predominately observational and correlational, with only a partial and incomplete understanding of the physiological dynamics underlying the syndrome. There exists a need for dynamical models of sepsis progression, based upon basic physiologic principles, which could eventually guide hourly treatment decisions.

Results

We present an initial mathematical model of sepsis, based on metabolic rate theory that links basic vascular and immunological dynamics. The model includes the rate of vascular circulation, a surrogate for the metabolic rate that is mechanistically associated with disease progression. We use the mass-specific rate of blood circulation (SRBC), a correlate of the body mass index, to build a differential equation model of circulation, infection, organ damage, and recovery. This introduces a vascular component into an infectious disease model that describes the interaction between a pathogen and the adaptive immune system.

Conclusion

The model predicts that deviations from normal SRBC correlate with disease progression and adverse outcome. We compare the predictions with population mortality data from cardiovascular disease and cancer and show that deviations from normal SRBC correlate with higher mortality rates.

Toll-like receptor-4 signaling mediates hepatic injury and systemic inflammation in hemorrhagic shock

BACKGROUND

Hemorrhagic shock and resuscitation (HS/R) activates inflammatory pathways leading to organ injury after trauma. Toll-like receptors (TLRs), such as TLR4, are required for activation of proinflammatory cellular signaling pathways in response to microbial products, but can also recognize endogenous molecules released from damaged tissues. Using mouse strains deficient in TLR4 protein or signaling, we hypothesized that TLR4 would be important for development of systemic inflammation and hepatic injury after HS/R. We sought to determine the role of lipolysaccharide through use of CD14-/- mice.

STUDY DESIGN

TLR4-mutant (C[3H]/HeJ), TLR4-deficient (TLR4-/-), CD14-/-, TLR2-/- mice and wild-type (WT) controls were subjected to HS/R or sham procedure (Sham). At 6.5 hours, mice were euthanized for determination of serum interleukin (IL)-6, IL-10, and alanine aminotransferase concentrations. Hepatic nuclear factor-kappaB DNA-binding (electrophoretic mobility shift assay) and tumor necrosis factor, IL-10, and inducible nitric oxide synthase mRNA expression (semiquantitative reverse transcriptase-polymerase chain reaction) were determined.

RESULTS

Relative to sham, TLR4-competent (C[3H]/HeOuJ) mice exhibited a significant increase in serum alanine aminotransferase, IL-6, and IL-10 after HS/R (p < 0.05). TLR4-mutant (C[3H]/HeJ) mice were protected from HS/R-induced hepatocellular injury and had lower circulating IL-6 and IL-10 levels than WT (p < 0.05). Similarly, TLR4-/- mice had lower circulating IL-6 and IL-10 levels than WT after HS/R (p < 0.05). Hepatic nuclear factor-kappaB activation and tumor necrosis factor, IL-10, and inducible nitric oxide synthase mRNA expression were lower in TLR4-mutant compared with TLR4-competent mice after HS/R. In contrast, serum ALT concentrations were comparable between CD14-/- and TLR2-/- mice and their WT counterparts after HS/R.

CONCLUSIONS

These results suggest that TLR4, but not TLR2, signaling is required for initiation of the systemic inflammatory response and development of hepatocellular injury after HS/R. Lack of involvement of CD14 argues for a lipolysaccharide-independent role for TLR4 in this process.