Administration route governs the therapeutic efficacy, biodistribution and macrophage targeting of anti-inflammatory nanoparticles in the lung.

BACKGROUND: Uncontrolled inflammation is a central problem for many respiratory diseases. The development of potent, targeted anti-inflammatory therapies to reduce lung inflammation and re-establish the homeostasis in the respiratory tract is still a challenge. Previously, we developed a unique anti-inflammatory nanodrug, P12 (made of hexapeptides and gold nanoparticles), which can attenuate Toll-like receptor-mediated inflammatory responses in macrophages. However, the effect of the administration route on its therapeutic efficacy and tissue distribution remained to be defined. RESULTS: In this study, we systematically compared the effects of three different administration routes [the intratracheal (i.t.), intravenous (i.v.) and intraperitoneal (i.p.)] on the therapeutic activity, biodistribution and pulmonary cell targeting features of P12. Using the LPS-induced ALI mouse model, we found that the local administration route via i.t. instillation was superior in reducing lung inflammation than the other two routes even treated with a lower concentration of P12. Further studies on nanoparticle biodistribution showed that the i.t. administration led to more accumulation of P12 in the lungs but less in the liver and other organs; however, the i.v. and i.p. administration resulted in more nanoparticle accumulation in the liver and lymph nodes, respectively, but less in the lungs. Such a lung favorable distribution was also determined by the unique surface chemistry of P12. Furthermore, the inflammatory condition in the lung could decrease the accumulation of nanoparticles in the lung and liver, while increasing their distribution in the spleen and heart. Interestingly, the i.t. administration route helped the nanoparticles specifically target the lung macrophages, whereas the other two administration routes did not. CONCLUSION: The i.t. administration is better for treating ALI using nanodevices as it enhances the bioavailability and efficacy of the nanodrugs in the target cells of the lung and reduces the potential systematic side effects.

Mechanisms of a Sustained Anti-inflammatory Drug Response in Alveolar Macrophages Unraveled with Mathematical Modeling.

Both initiation and suppression of inflammation are hallmarks of the immune response. If not balanced, the inflammation may cause extensive tissue damage, which is associated with common diseases, e.g., asthma and atherosclerosis. Anti-inflammatory drugs come with side effects that may be aggravated by high and fluctuating drug concentrations. To remedy this, an anti-inflammatory drug should have an appropriate pharmacokinetic half-life or better still, a sustained anti-inflammatory drug response. However, we still lack a quantitative mechanistic understanding of such sustained effects. Here, we study the anti-inflammatory response to a common glucocorticoid drug, dexamethasone. We find a sustained response 22 hours after drug removal. With hypothesis testing using mathematical modeling, we unravel the underlying mechanism-a slow release of dexamethasone from the receptor-drug complex. The developed model is in agreement with time-resolved training and testing data and is used to simulate hypothetical treatment schemes. This work opens up for a more knowledge-driven drug development to find sustained anti-inflammatory responses and fewer side effects.

The α7 nicotinic acetylcholine receptor agonist GTS-21 improves bacterial clearance in mice by restoring hyperoxia-compromised macrophage function.

BACKGROUND: Mechanical ventilation, in combination with supraphysiological concentrations of oxygen (i.e., hyperoxia), is routinely used to treat patients with respiratory distress, such as COVID-19. However, prolonged exposure to hyperoxia compromises the clearance of invading pathogens by impairing macrophage phagocytosis. Previously, we have shown that the exposure of mice to hyperoxia induces the release of the nuclear protein high mobility group box-1 (HMGB1) into the pulmonary airways. Furthermore, extracellular HMGB1 impairs macrophage phagocytosis and increases the mortality of mice infected with Pseudomonas aeruginosa (PA). The aim of this study was to determine whether GTS-21 (3-(2,4-dimethoxybenzylidene) anabaseine), an α7 nicotinic acetylcholine receptor (α7nAChR) agonist, could (1) inhibit hyperoxia-induced HMGB1 release into the airways; (2) enhance macrophage phagocytosis and (3) increase bacterial clearance from the lungs in a mouse model of ventilator-associated pneumonia. METHOD: GTS-21 (0.04, 0.4, and 4 mg/kg) or saline were administered by intraperitoneal injection to mice that were exposed to hyperoxia (≥ 99% O2) and subsequently challenged with PA. RESULTS: The systemic administration of 4 mg/kg i.p. of GTS-21 significantly increased bacterial clearance, decreased acute lung injury and decreased accumulation of airway HMGB1 compared to the saline control. To determine the mechanism of action of GTS-21, RAW 264.7 cells, a macrophage-like cell line, were incubated with different concentrations of GTS-21 in the presence of 95% O2. The phagocytic activity of macrophages was significantly increased by GTS-21 in a dose-dependent manner. In addition, GTS-21 significantly inhibited the cytoplasmic translocation and release of HMGB1 from RAW 264.7 cells and attenuated hyperoxia-induced NF-κB activation in macrophages and mouse lungs exposed to hyperoxia and infected with PA. CONCLUSIONS: Our results indicate that GTS-21 is efficacious in improving bacterial clearance and reducing acute lung injury via enhancing macrophage function by inhibiting the release of nuclear HMGB1. Therefore, the α7nAChR represents a possible pharmacological target to improve the clinical outcome of patients on ventilators by augmenting host defense against bacterial infections.

Novel coronavirus SARS-CoV-2 (Covid-19) dynamics inside the human body.

A knowledge-based cybernetic framework model representing the dynamics of SARS-CoV-2 inside the human body has been studied analytically and in silico to explore the pathophysiologic regulations. The following modeling methodology was developed as a platform to introduce a predictive tool supporting a therapeutic approach to Covid-19 disease. A time-dependent nonlinear system of ordinary differential equations model was constructed involving type-I cells, type-II cells, SARS-CoV-2 virus, inflammatory mediators, interleukins along with host pulmonary gas exchange rate, thermostat control, and mean pressure difference. This formalism introduced about 17 unknown parameters. Estimating these unknown parameters requires a mathematical association with the in vivo sparse data and the dynamic sensitivities of the model. The cybernetic model can simulate a dynamic response to the reduced pulmonary alveolar gas exchange rate, thermostat control, and mean pressure difference under a very critical condition based on equilibrium (steady state) values of the inflammatory mediators and system parameters. In silico analysis of the current cybernetical approach with system dynamical modeling can provide an intellectual framework to help experimentalists identify more active therapeutic approaches.