Nanoparticles (NPs) are easily contaminated by bacterial endotoxin (lipopolysaccharide [LPS]). The presence of LPS can be responsible for many immune/inflammatory effects attributed to NPs. In this study, we examined the effects of LPS adsorption on the NP surface on the formation of a biocorona in biological fluids and on the subsequent inflammation-inducing activity of NPs. Different gold (Au) NPs with sizes ranging from 10 to 80 nm and with different surface functionalization (sodium citrate, lipoic acid, and branched polyethyleneimine (BPEI), or polyethylene glycol (PEG)) were exposed to E. coli LPS under different conditions. The binding capacity of LPS to the surface of AuNPs was dose- and time-dependent. LPS attached to sodium citrate and lipoic acid coatings, but did not adhere to BPEI- or PEG-coated NPs. By computational simulation, the binding of LPS to AuNPs seems to follow the Langmuir absorption isotherm. The presence of LPS on AuNP surface interfered and caused a decrease in the formation of the expected biomolecular corona upon incubation in human plasma. LPS-coated AuNPs, but not the LPS-free NPs, induced significant inflammatory responses in vitro. Notably, while free LPS did also induce an anti-inflammatory response, LPS bound to NPs appeared unable to do so. In conclusion, the unintentional adsorption of LPS onto the NP surface can affect the biocorona formation and the inflammatory properties of NPs. Thus, for an accurate interpretation of NP interactions with cells, it is extremely important to be able to distinguish the intrinsic NP biological effects from those caused by biologically active contaminants such as endotoxin.

Sepsis is a systemic inflammatory response (SIR) to infection. In this work, a system dynamics mathematical model (SDMM) is examined to describe the basic components of SIR and sepsis progression. Both innate and adaptive immunities are included, and simulated resultsin silicohave shown that adaptive immunity has significant impacts on the outcomes of sepsis progression. Further investigation has found that the intervention timing, intensity of anti-inflammatory cytokines, and initial pathogen load are highly predictive of outcomes of a sepsis episode. Sensitivity and stability analysis were carried out using bifurcation analysis to explore system stability with various initial and boundary conditions. The stability analysis suggested that the system could diverge at an unstable equilibrium after perturbations ifrt2max(maximum release rate of Tumor Necrosis Factor- (TNF-)αby neutrophil) falls below a certain level. This finding conforms to clinical findings and existing literature regarding the lack of efficacy of anti-TNF antibody therapy.

Hepatitis B virus (HBV) and hepatitis delta virus (HDV) are highly prevalent viruses estimated to infect approximately 300 million people and 12–72 million people worldwide, respectively. HDV requires the HBV envelope to establish a successful infection. Concurrent infection with HBV and HDV can result in more severe disease outcomes than infection with HBV alone. These viruses can cause significant hepatic disease, including cirrhosis, fulminant hepatitis, and hepatocellular carcinoma, and represent a significant cause of global mortality. Therefore, a thorough understanding of these viruses and the immune response they generate is essential to enhance disease management. This review includes an overview of the HBV and HDV viruses, including life cycle, structure, natural course of infection, and histopathology. A discussion of the interplay between HDV RNA and HBV DNA during chronic infection is also included. It then discusses characteristics of the immune response with a focus on reactions to the antigenic hepatitis B surface antigen, including small, middle, and large surface antigens. This paper also reviews characteristics of the immune response to the hepatitis D antigen (including small and large antigens), the only protein expressed by hepatitis D. Lastly, we conclude with a discussion of recent therapeutic advances pertaining to these viruses.

We 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-α 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.