An Agent-Based Model of a Hepatic Inflammatory Response to Salmonella: A Computational Study under a Large Set of Experimental Data

Citation: Shi, Z. Z., Chapes, S. K., Ben-Arieh, D., & Wu, C. H. (2016). An Agent-Based Model of a Hepatic Inflammatory Response to Salmonella: A Computational Study under a Large Set of Experimental Data. Plos One, 11(8), 39. doi:10.1371/journal.pone.0161131We present an agent-based model (ABM) to simulate a hepatic inflammatory response (HIR) in a mouse infected by Salmonella that sometimes progressed to problematic proportions, known as "sepsis". Based on over 200 published studies, this ABM describes interactions among 21 cells or cytokines and incorporates 226 experimental data sets and/or data estimates from those reports to simulate a mouse HIR in silico. Our simulated results reproduced dynamic patterns of HIR reported in the literature. As shown in vivo, our model also demonstrated that sepsis was highly related to the initial Salmonella dose and the presence of components of the adaptive immune system. We determined that high mobility group box-1, C-reactive protein, and the interleukin-10: tumor necrosis factor-a ratio, and CD4+ T cell: CD8+ T cell ratio, all recognized as biomarkers during HIR, significantly correlated with outcomes of HIR. During therapy-directed silico simulations, our results demonstrated that anti-agent intervention impacted the survival rates of septic individuals in a time-dependent manner. By specifying the infected species, source of infection, and site of infection, this ABM enabled us to reproduce the kinetics of several essential indicators during a HIR, observe distinct dynamic patterns that are manifested during HIR, and allowed us to test proposed therapy-directed treatments. Although limitation still exists, this ABM is a step forward because it links underlying biological processes to computational simulation and was validated through a series of comparisons between the simulated results and experimental studies

Erratum to: 36th International Symposium on Intensive Care and Emergency Medicine

[This corrects the article DOI: 10.1186/s13054-016-1208-6.]

Metabolic profiling for detection of staphylococcus aureus infection and antibiotic resistance

Due to slow diagnostics, physicians must optimize antibiotic therapies based on clinical evaluation of patients without specific information on causative bacteria. We have investigated metabolomic analysis of blood for the detection of acute bacterial infection and early differentiation between ineffective and effective antibiotic treatment. A vital and timely therapeutic difficulty was thereby addressed: the ability to rapidly detect treatment failures because of antibiotic-resistant bacteria. Methicillin-resistant (MRSA) and methicillin-sensitive (MSSA) were used and for infecting mice, while natural MSSA infection was studied in humans. Samples of bacterial growth media, the blood of infected mice and of humans were analyzed with combined Gas Chromatography/Mass Spectrometry. Multivariate data analysis was used to reveal the metabolic profiles of infection and the responses to different antibiotic treatments. experiments resulted in the detection of 256 putative metabolites and mice infection experiments resulted in the detection of 474 putative metabolites. Importantly, ineffective and effective antibiotic treatments were differentiated already two hours after treatment start in both experimental systems. That is, the ineffective treatment of MRSA using cloxacillin and untreated controls produced one metabolic profile while all effective treatment combinations using cloxacillin or vancomycin for MSSA or MRSA produced another profile. For further evaluation of the concept, blood samples of humans admitted to intensive care with severe sepsis were analyzed. One hundred thirty-three putative metabolites differentiated severe MSSA sepsis (n = 6) from severe sepsis (n = 10) and identified treatment responses over time. Combined analysis of human, , and mice samples identified 25 metabolites indicative of effective treatment of sepsis. Taken together, this study provides a proof of concept of the utility of analyzing metabolite patterns in blood for early differentiation between ineffective and effective antibiotic treatment in acute infections

Macrophage activation-like syndrome: an immunological entity associated with rapid progression to death in sepsis

Abstract Background A subanalysis of a randomized clinical trial indicated sepsis survival benefit from interleukin (IL)-1 blockade in patients with features of the macrophage activation-like syndrome (MALS). This study aimed to investigate the frequency of MALS and to develop a biomarker of diagnosis and prognosis. Methods Patients with infections and systemic inflammatory response syndrome were assigned to one test cohort (n = 3417) and a validation cohort (n = 1704). MALS was diagnosed for patients scoring positive either for the hemophagocytic syndrome score and/or having both hepatobiliary dysfunction and disseminated intravascular coagulation. Logistic regression analysis was used to estimate the predictive value of MALS for 10-day mortality in both cohorts. Ferritin, sCD163, IL-6, IL-10, IL-18, interferon gamma (IFN-γ), and tumor necrosis factor alpha (TNF-α) were measured in the blood the first 24 h; ferritin measurements were repeated in 747 patients on day 3. Results The frequency of MALS was 3.7% and 4.3% in the test and the validation cohort, respectively. In both cohorts, MALS was an independent risk factor for 10-day mortality. A ferritin level above 4420 ng/ml was accompanied by 66.7% and 66% mortality after 28 days, respectively. Ferritin levels above 4420 ng/ml were associated with an increase of IL-6, IL-18, INF-γ, and sCD163 and a decreased IL-10/TNF-α ratio, indicating predominance of pro-inflammatory phenomena. Any less than 15% decrease of ferritin on day 3 was associated with more than 90% sensitivity for unfavorable outcome after 10 days. This high mortality risk was also validated in an independent Swedish cohort (n = 109). Conclusions MALS is an independent life-threatening entity in sepsis. Ferritin measurements can provide early diagnosis of MALS and may allow for specific treatment

Risk assessment in sepsis: a new prognostication rule by APACHE II score and serum soluble urokinase plasminogen activator receptor

Introduction: Early risk assessment is the mainstay of management of patients with sepsis. APACHE II is the gold standard prognostic stratification system. A prediction rule that aimed to improve prognostication by APACHE II with the application of serum suPAR (soluble urokinase plasminogen activator receptor) is developed.Methods: A prospective study cohort enrolled 1914 patients with sepsis including 62.2% with sepsis and 37.8% with severe sepsis/septic shock. Serum suPAR was measured in samples drawn after diagnosis by an enzyme-immunoabsorbent assay; in 367 patients sequential measurements were performed. After ROC analysis and multivariate logistic regression analysis a prediction rule for risk was developed. The rule was validated in a double-blind fashion by an independent confirmation cohort of 196 sepsis patients, predominantly severe sepsis/septic shock patients, from Sweden.Results: Serum suPAR remained stable within survivors and non-survivors for 10 days. Regression analysis showed that APACHE II ≥17 and suPAR ≥12 ng/ml were independently associated with unfavorable outcome. Four strata of risk were identified: i) APACHE II <17 and suPAR <12 ng/ml with mortality 5.5%; ii) APACHE II < 17 and suPAR ≥12 ng/ml with mortality 17.4%; iii) APACHE II ≥ 17 and suPAR <12 ng/ml with mortality 37.4%; and iv) APACHE II ≥17 and suPAR ≥12 ng/ml with mortality 51.7%. This prediction rule was confirmed by the Swedish cohort.Conclusions: A novel prediction rule with four levels of risk in sepsis based on APACHE II score and serum suPAR is proposed. Prognostication by this rule is confirmed by an independent cohort. © 2012 Giamarellos-Bourboulis et al.; licensee BioMed Central Ltd

Resistin and NGAL are associated with inflammatory response, endothelial activation and clinical outcomes in sepsis

© 2017, Springer International Publishing. Objective and design: Resistin and neutrophil gelatinase-associated lipocalin (NGAL) are upregulated in circulating leucocytes in sepsis, but the significance of this is uncertain. We evaluated associations between Resistin and NGAL with endothelial cell activation and clinical outcomes in a prospective observational study in the Emergency Department (ED). Methods: Serum levels of Resistin, NGAL, inflammatory cytokines (IL-6, IL-10) and soluble endothelial adhesion molecules (VCAM-1, ICAM-1) were measured at defined time points up to 24 h. Patterns and relationships between markers were investigated using linear mixed regression models. Predictive values for clinical outcomes for markers at enrollment were assessed by logistic regression and receiver operator characteristic (ROC) curves. Results: 186 participants (89 septic-shock, 69 sepsis, 28 uncomplicated infection) were compared with 29 healthy controls. Median Resistin and NGAL were higher in uncomplicated infection compared to controls, and in septic shock compared to non-shock sepsis. Resistin and NGAL correlated with IL-6 and IL-10, with VCAM-1 and ICAM-1, and with organ failure. Resistin and NGAL were associated with septic shock but had limited predictive utility for mortality. Conclusion: Resistin and NGAL correlate with expression of endothelial cell adhesion molecules in sepsis. Further evaluation of the role of Resistin and NGAL in sepsis pathogenesis is warranted