Ensemble Models of Neutrophil Trafficking in Severe Sepsis

A hallmark of severe sepsis is systemic inflammation which activates leukocytes and can result in their misdirection. This leads to both impaired migration to the locus of infection and increased infiltration into healthy tissues. In order to better understand the pathophysiologic mechanisms involved, we developed a coarse-grained phenomenological model of the acute inflammatory response in CLP (cecal ligation and puncture)-induced sepsis in rats. This model incorporates distinct neutrophil kinetic responses to the inflammatory stimulus and the dynamic interactions between components of a compartmentalized inflammatory response. Ensembles of model parameter sets consistent with experimental observations were statistically generated using a Markov-Chain Monte Carlo sampling. Prediction uncertainty in the model states was quantified over the resulting ensemble parameter sets. Forward simulation of the parameter ensembles successfully captured experimental features and predicted that systemically activated circulating neutrophils display impaired migration to the tissue and neutrophil sequestration in the lung, consequently contributing to tissue damage and mortality. Principal component and multiple regression analyses of the parameter ensembles estimated from survivor and non-survivor cohorts provide insight into pathologic mechanisms dictating outcome in sepsis. Furthermore, the model was extended to incorporate hypothetical mechanisms by which immune modulation using extracorporeal blood purification results in improved outcome in septic rats. Simulations identified a sub-population (about of the treated population) that benefited from blood purification. Survivors displayed enhanced neutrophil migration to tissue and reduced sequestration of lung neutrophils, contributing to improved outcome. The model ensemble presented herein provides a platform for generating and testing hypotheses in silico, as well as motivating further experimental studies to advance understanding of the complex biological response to severe infection, a problem of growing magnitude in humans

Model-free immune therapy: A control approach to acute inflammation

International audienceControl of an inflammatory immune response is still an ongoing research. Here, a strategy consisting of manipulating a pro and anti-inflammatory mediator is considered. Already existing and promising model-based techniques suffer unfortunately from a most difficult calibration. This is due to the different types of inflammations and to the strong parameter variation between patients. This communication explores another route via the new model-free control and its corresponding "intelligent" controllers. A "virtual" patient, i.e., a mathematical model, is only employed for digital simulations. A most interesting feature of our control strategy is the fact that the two outputs which must be driven are sensorless. This difficulty is overcome by assigning suitable reference trajectories to two other outputs with sensors. Several most encouraging computer simulations, corresponding to different drug treatment strategies, are displayed and discussed.

Predicting Experimental Sepsis Survival with a Mathematical Model of Acute Inflammation

Sepsis is characterized by an overactive, dysregulated inflammatory response that drives organ dysfunction and often results in death. Mathematical modeling has emerged as an essential tool for understanding the underlying complex biological processes. A system of four ordinary differential equations (ODEs) was developed to simulate the dynamics of bacteria, the pro- and anti-inflammatory responses, and tissue damage (whose molecular correlate is damage-associated molecular pattern [DAMP] molecules and which integrates inputs from the other variables, feeds back to drive further inflammation, and serves as a proxy for whole-organism health status). The ODE model was calibrated to experimental data from E. coli infection in genetically identical rats and was validated with mortality data for these animals. The model demonstrated recovery, aseptic death, or septic death outcomes for a simulated infection while varying the initial inoculum, pathogen growth rate, strength of the local immune response, and activation of the pro-inflammatory response in the system. In general, more septic outcomes were encountered when the initial inoculum of bacteria was increased, the pathogen growth rate was increased, or the host immune response was decreased. The model demonstrated that small changes in parameter values, such as those governing the pathogen or the immune response, could explain the experimentally observed variability in mortality rates among septic rats. A local sensitivity analysis was conducted to understand the magnitude of such parameter effects on system dynamics. Despite successful predictions of mortality, simulated trajectories of bacteria, inflammatory responses, and damage were closely clustered during the initial stages of infection, suggesting that uncertainty in initial conditions could lead to difficulty in predicting outcomes of sepsis by using inflammation biomarker levels

Closing the loop: A combined computational modeling and experimental approach provides novel insights into immune cell signaling systems and their global effects.

Systems biology is an approach that marries complimentary disciplines, encouraging the use of quantitative methods to help define, explain, and predict biological processes. By building computational models of biological systems, we can pose new biologically motivated questions and make falsifiable, quantitative predictions. In this thesis I will discuss the cycle of model building and experimental validation, and how it has provided insight into poorly and understood systems and allowed us to predict the effects of perturbations on these systems, which could have real and significant effects in human health and medicine. First, we model the activation of neutrophils in sepsis. By fitting a single model to two sets of data, coming from animals that survive and succumb to the same bacterial challenge, we create a realistic representation of biological variation, showing how a single network architecture can lead to different outcomes. Additionally, this method allows us to identify markers for sepsis susceptibility and identify and optimize a potential treatment option to lead to improved outcomes. Next, we model signaling downstream of the T cell receptor, and how this leads to differentiation decision making in CD4 T cells. By modeling the dynamics of this signaling network under varying antigen doses, we are able to identify network elements critical to dose discrimination, leading to the production of Treg cells following low dose stimulation and Th cells following high dose stimulation. We can then perturb these elements of the network, to potentially fine tune mature T cell populations to alter the trajectories of autoimmune disorders or cancer. Finally, we model the dynamics of IL-17 signaling. This allows us to understand how ubiquitin scaffolds form following cytokine stimulation, leading to the activation of NF-B, and how the ubiquitin editing enzyme A20 acts as a negative feedback regulator by breaking these chains. This allows us to better understand ubiquitin oligomerization as a fulcrum in the system, and how changes in A20 and ubiquitin binding proteins lead to different profiles of NF-B activation and could play a role in inflammatory disorders

Sepse como fator de risco para o desenvolvimento de transtornos psiquiátricos em modelos animais

Tese de Doutorado apresentada ao Programa de Pós-Graduação em Ciências da Saúde da Universidade do Extremo Sul Catarinense – UNESC, para obtenção do título de Doutor em Ciências da Saúde.Sepse é definida como a síndrome da resposta inflamatória sistêmica em resposta a uma infecção, podendo estar envolvida como fator de risco para o desenvolvimento de transtornos psiquiátricos. No entanto, ainda não está bem esclarecido seu mecanismo fisiopatológico e comportamental. Portanto, o objetivo deste estudo foi avaliar animais sépticos submetidos a modelos de transtornos psiquiátricos, como esquizofrenia, depressão e mania, também foram avaliados os níveis de neurotrofinas, dano oxidativo em lipídeos e carbonilação de proteínas em estruturas cerebrais. Também foram avaliados os parâmetros comportamentais tais como a atividade locomotora a interação social, os movimentos estereotipados, a memória aversiva e a anedonia. Neste estudo foram utilizados ratos Wistar machos adultos. Os animais foram submetidos ao modelo de sepse, através da ligação e perfuração cecal (CLP), em modelo animal de esquizofrenia, através da administração de cetamina intraperitoneal (i.p) em diferentes doses ( 5; 15; 25mg/kg). No modelo animal de mania, através do protocolo de estresse crônico variado (ECV), já no modelo animal de mania o mesmo foi realizado através da administração de m-AMPH (i.p.) em diferentes doses (0,25; 0,5; 1mg/kg). Nesse estudo verificou-se que os animais submetidos ao modelo animal de sepse, com a administração de cetamina na dose 25mg/kg, apresentaram aumento na atividade locomotora e aumento no tempo de latência ao primeiro contato no teste de interação social. Na dose de 15mg/kg de cetamina os animais apresentaram aumento nos movimentos estereotipados. Quanto à memória aversiva, os animais administrados com cetamina aprenderam, porém menos, em relação ao grupo controle. Os animais sépticos submetidos ao ECV não mostraram comportamento anedônico. Os animais do grupo CLP quando submetidos ao protocolo de ECV não apresentaram diminuição dos níveis de BDNF, NGF e GDNF em hipocampo. Somente em hipocampo, o ECV diminuiu o dano a proteínas no grupo CLP. Enquanto que os animais submetidos à sepse, não responderam na dose efetiva de 1mg/kg que induz hiperlocomoção nos animais controles. Observou-se que a dose de 0,25 mg/kg de m-AMPH elevou os níveis de NFG no hipocampo no grupo sham e no grupo CLP. Além disso, a dose de 0,5 mg/kg de m-AMPH no grupo CLP apresentou aumento dos níveis de NGF em hipocampo. A dose de 0,25 e 0,5 mg/kg de m-AMPH apresentou um aumento dos níveis proteicos de GDNF quando comparados ao grupo CLP que recebeu salina. A dose de 1mg/kg de m-AMPH não aumentou o dano a lipídeos e proteínas nas estruturas avaliadas. As doses de 0,25 e 1 mg/kg de m-AMPH diminuíram o dano a proteínas em estriado. Concluiu-se então, que nesses modelos animais de transtornos psiquiátricos, a sepse, pré dispõe no modelo animal de esquizofrenia somente a alterações comportamentais, enquanto que no transtorno depressivo e na mania isso não ocorreu. Porém em algumas análises bioquímicas, como nos níveis de neurotrofinas sugere-se que a sepse predispõe a estes transtornos.Sepsis is defined as a systemic inflammatory response syndrome in response to an infection and may be involved as a risk factor for the development of psychiatric disorders. However, it is not yet well understood its pathophysiological and behavioral mechanism. Therefore, this study aimed to evaluate septic animals in the models of psychiatric disorders such as schizophrenia, depression and mania, assessing the neurotrophin levels, oxidative damage in lipids and protein carbonylation in brain structures and behavior as locomotor activity, social interaction , stereotyped movements, and anhedonia aversive memory. In this study adult male Wistar rats were used. The animals were submitted to the model of sepsis by cecal ligation and puncture (CLP), the animal model of schizophrenia by administration of ketamine intraperitoneally (ip) at different doses (5, 15, 25mg / kg) to the animal model mania, varied by chronic stress protocol (ECV) and the animal model of mania by administration of m-AMPH (ip) at several dose levels (0.25, 0.5, 1 mg / kg). In this study it was found that animals in the animal model of sepsis and administered ketamine at a dose 25 mg / kg showed an increase in locomotor activity and increased latency to first contact in the social interaction test. With the dose of 15 mg / kg ketamine animals showed an increase in stereotyped movements. As for the aversive memory, the animals administered ketamine learned, but less than in the control group. Septic animals submitted to ECV showed no anedônico behavior. The CLP animals when subjected to ECV protocol does not show decreased levels of BDNF, NGF and GDNF in hippocampus. Only in the hippocampus, the ECV decreased the damage to proteins in the CLP group. While the animals subjected to sepsis are not responding to effective dose of 1 mg / kg which induces hyperlocomotion in control animals. It was observed that the dose of 0.25 mg / kg of AMPH-m elevated NGF levels in the hippocampus in sham and CLP. Furthermore, the dose of 0.5 mg / kg of AMPH-m CLP group showed an increase in NGF levels in hippocampus. The dose of 0.25 and 0.5 mg / kg of AMPH-m showed an increase in GDNF protein levels when compared to the group receiving saline PLC. The dose of 1 mg / kg of AMPH-m did not increase the damage to lipids and proteins in the evaluated structure. Doses of 0.25 and 1 mg / kg of AMPH-m damage decreased in the striatum proteins. It was therefore concluded that these animal models of psychiatric disorders, sepsis predisposes the animal model of schizophrenia behaviorally, while depressive disorders and mania did not occur, though in some chemistries, such as neurotrophin levels, we suggest that sepsis predisposes to these disorders

Effect of Ascorbate on Coagulation and Fibrinolytic Factors in the Septic Microvasculature

Sepsis, a systemic inflammatory response to an infection, is a significant cause of morbidity and mortality worldwide. The microcirculation during sepsis fails, in part, due to microthrombosis and the resulting plugging of capillaries, precipitating organ failure. Intravenous injection of ascorbate has been shown to reduce capillary plugging, however the mechanism of this protective effect is unclear. We hypothesized that ascorbate-mediated destabilization of the microthrombi through promoting fibrinolysis could contribute to this protection. We showed that streptokinase, a pro-fibrinolytic agent, reduced the capillary plugging to a similar degree as ascorbate. This similarity provided the impetus for studying the effect of ascorbate on fibrinolysis. Sepsis increased the urokinase plasminogen activator (u-PA) and tissue plasminogen activator (t-PA) mRNA expression in the skeletal muscle and liver in mice. No effect of ascorbate was observed on u-PA or t-PA expression levels. Sepsis also increased the plasminogen activator inhibitor 1 (PAI-1) mRNA and protein expression and activity in these tissues, but ascorbate did not affect these increases. The local PAI-1 release by both platelets and endothelial cells may play a critical role in microthrombus formation in capillaries. We observed that PAI-1 released by isolated endothelial cells was not affected by ascorbate. However, thrombin-induced PAI-1 release from platelets was inhibited by ascorbate pH-dependently. We have also discovered that the PAI-1 release from platelets was nitric oxide independent. It has been shown that PAI-1 has a protective role in sepsis, namely that PAI-1 knockout leads to increased bacterial content, increased neutrophil apoptosis and increased mortality. Therefore, the lack of effect of ascorbate on PAI-1 in the tissue may maintain PAI-1’s beneficial role in sepsis. Consistently, we observed that sepsis-induced increases in bacterial count, PAI-1 expression and myeloperoxidase content in various organs were not affected by ascorbate. Overall, the lack of effect of ascorbate indicates that the protection by ascorbate through reduced capillary plugging is not through a fibrinolytic mechanism. Other mechanisms such as platelet-endothelial cell adhesion and changes in red blood cell deformability in the capillaries should be explored as possible mechanisms of protection by ascorbate

Mathematical Modeling in Systems Medicine: New Paradigms for Glucose Control in Critical Care

Stress hyperglycemia occurs frequently in critical care patients and many of the harmful repercussions may be mitigated by maintaining glucose within a ``healthy'' zone. While the exact range of the zone varies, glucose below 80 $mg/dl$ or above 130 $mg/dl$ increases risk of mortality. Zone glucose control (ZGC) is accomplished primarily using insulin administration to reduce hyperglycemia. Alternatively, we propose also allowing glucose administration to be used to raise blood glucose and avoid hypoglycemia. While there have been attempts to create improved paradigms for treatment of stress hyperglycemia, inconsistencies in glycemic control protocols as well as variation in outcomes for different ICU subpopulations has contributed to the mixed success of glucose control in critical care and subsequent disagreement regarding treatment protocols. Therefore, a more accurate, personalized treatment that is tailored to an individual may significantly improve patient outcome. The most promising method to achieve better control using a personalized strategy is through the use of a model-based decision support system (DSS), wherein a mathematical patient model is coupled with a controller and user interface that provides for semi-automatic control under the supervision of a clinician. Much of the error and subsequent failure to control blood glucose comes from the failure to resolve inter- and intrapatient variations in glucose dynamics following insulin administration. The observed variation arises from the many biologically pathways that affect insulin signaling for patients in the ICU. Mathematical modeling of the biological pathways of stress hyperglycemia can improve understanding and treatment. Trauma and infection lead to the development of systemic insulin resistance and elevated blood glucose levels associated with stress hyperglycemia. We develop mathematical models of the biological signaling pathways driving fluctuations in insulin sensitivity and resistance. Key metabolic mediators from the inflammatory response and counterregulatory response are mathematically represented acting on insulin-mediated effects causing increases or decreases in blood glucose concentration. Data from published human studies are used to calibrate a composite model of glucose and insulin dynamics augmented with biomarkers relevant to critical care. The resulting mathematical description of the underlying mechanisms of insulin resistance could be used in a model-based decision support system to estimate patient-specific metabolic status and provide more accurate insulin treatment and glucose control for critical care patients

Surface Coatings for Modifying Circulating Blood Cell Behavior

Advances to biomaterial polymers and surface coatings have markedly improved the safety and efficacy of extracorporeal devices, but there is untapped potential to use these surfaces to modulate blood cell behavior. Sepsis, a severe inflammatory response to infection that affects nearly 1 million Americans per year, results in high levels of interleukin (IL-8) spilling into the circulatory system and diffusing into healthy tissue. Subsequently, circulating neutrophils become redirected into these healthy tissues, where they impair organ function. The focus of this work is the development of an extracorporeal device which can “reprogram” neutrophils using IL-8 immobilized within the device. Additionally, a zwitterionic thromboresistant coating was developed to reduce platelet deposition in extracorporeal devices. A mechanistic computational model was developed to study the role of IL-8 induced CXCR-1/2 neutrophil surface receptor downregulation and its role in the progression of sepsis. The findings suggest that a device which modulates receptor expression could reduce morbidity and mortality in sepsis, but there is also potential for harm if implemented incorrectly. Scaled prototypes of an extracorporeal device, which used immobilized IL-8 to reduce neutrophil migratory response, were constructed and evaluated. While significant downregulation of CXCR-1 and CXCR-2 was achieved, this effect was insufficient to cause consistent migratory shutoff to IL-8 as measured by a Boyden chamber chemotaxis assay. Learnings from this testing were used to develop alternate device concepts which modulate leukocyte activity within an extracorporeal circuit. A zwitterionic macromolecule surface coating was developed to reduce platelet deposition on polymethylpentene (PMP) hollow fiber membranes (HFMs). Two techniques of PMP HFM functionalization and subsequent conjugation of sulfobetaine block copolymers were evaluated within scaled PMP fiber minimodules. Both fiber configurations resulted in an 80-95% reduction in adherent platelets from whole ovine blood, stability under shear stress, and uninhibited gas exchange performance relative to unmodified HFMs. Initial testing indicates this coating is effective on polycarbonate and poly(vinyl chloride), two other materials commonly found in extracorporeal circuits, which may allow for tip to tip coating of extracorporeal circuits

On Signal Transduction in Human Embryonic Stem Cells: Towards a Systems View

Human embryonic stem cells (hESC) have been a major cell source for research in regenerative medicine due to the demonstration of properties of self-renewal and efficient lineage specific differentiation, both on additions of external cues. Self-renewal provides the potential to extract large quantities of naïve cells that can then be differentiated to clinically relevant mature lineages. While there exists significant proof-of-concept to transform stem cells to the desired lineage, generating fully functional cell types is still an unmet challenge. A major reason for this is our limited understanding of the complexity of the transformation process. The overarching goal of this PhD research was to provide strategies to bring mathematical modeling into the realm of stem cell research, particularly to analyze the complex regulatory network of signaling events controlling cell fate. This work focused on the signaling pathways that in concert control the balance of self-renewal and endoderm differentiation of hESCs. We proposed a framework for developing mechanistic understanding from disparate signaling pathways using combinations of data-driven and equation based models. As a first step, we analyzed growth factor mediated PI3K/AKT pathway that must remain highly active to inhibit differentiation in self-renewal state. Using an integrated approach of mechanistic modeling, systems analysis and experimental validation we identified the role of a regulatory process (negative feedback) in maintaining signal amplitudes and controlling the propagation of parameter uncertainty down the pathway in the self-renewal state. To analyze endoderm differentiation, biclustering with bootstrapping formulation was used to identify co-regulated transcription factor patterns under a combinatorial modulation of endoderm inducing signaling pathways. In the final step, a detailed mechanistic analysis was done to characterize the dynamic features of TGF-β/SMAD pathway for inducing endoderm. Utilizing a dynamic Bayesian network formulism, AKT mediated crosstalk connections were inferred from the detailed time series data. Modeling of competing AKT-SMAD interactions followed by parametric ensemble analysis enabled identification of plausible hypotheses that could explain experimental observations. Using our integrated approach, we can now begin to rationally optimize for desirable fate of hESCs with reduced variability and accelerate the path towards therapeutic applications of hESCs