Advanced optical imaging for the rational design of nanomedicines

Despite the enormous potential of nanomedicines to shape the future of medicine, their clinical translation remains suboptimal. Translational challenges are present in every step of the development pipeline, from a lack of understanding of patient heterogeneity to insufficient insights on nanoparticle properties and their impact on material-cell interactions. Here, we discuss how the adoption of advanced optical microscopy techniques, such as super-resolution optical microscopies, correlative techniques, and high-content modalities, could aid the rational design of nanocarriers, by characterizing the cell, the nanomaterial, and their interaction with unprecedented spatial and/or temporal detail. In this nanomedicine arena, we will discuss how the implementation of these techniques, with their versatility and specificity, can yield high volumes of multi-parametric data; and how machine learning can aid the rapid advances in microscopy: from image acquisition to data interpretation.

Identification of fluorescently-barcoded nanoparticles using machine learning

Barcoding of nano- and micro-particles allows distinguishing multiple targets at the same time within a complex mixture and is emerging as a powerful tool to increase the throughput of many assays. Fluorescent barcoding is one of the most used strategies, where microparticles are labeled with dyes and classified based on fluorescence color, intensity, or other features. Microparticles are ideal targets due to their relative ease of detection, manufacturing, and higher homogeneity. Barcoding is considerably more challenging in the case of nanoparticles (NPs), where their small size results in a lower signal and greater heterogeneity. This is a significant limitation since many bioassays require the use of nano-sized carriers. In this study, we introduce a machine-learning-assisted workflow to write, read, and classify barcoded PLGA-PEG NPs at a single-particle level. This procedure is based on the encapsulation of fluorescent markers without modifying their physicochemical properties (writing), the optimization of their confocal imaging (reading), and the implementation of a machine learning-based barcode reader (classification). We found nanoparticle heterogeneity as one of the main factors that challenges barcode separation, and that information extracted from the dyes' nanoscale confinement effects (such as Förster Resonance Energy Transfer, FRET) can aid barcode identification. Moreover, we provide a guide to reaching the optimal trade-off between the number of simultaneous barcodes and classification accuracy supporting the use of this workflow for a variety of bioassays.

High Mobility Group Box 1 Release by Cholangiocytes Governs Biliary Atresia Pathogenesis and Correlates With Increases in Afflicted Infants

BACKGROUND AND AIMS

Biliary atresia (BA) is a devastating cholangiopathy of infancy. Upon diagnosis, surgical reconstruction by Kasai hepatoportoenterostomy (HPE) restores biliary drainage in a subset of patients, but most patients develop fibrosis and progress to end-stage liver disease requiring liver transplantation for survival. In the murine model of BA, rhesus rotavirus (RRV) infection of newborn pups results in a cholangiopathy paralleling that of human BA. High-mobility group box 1 (HMGB1) is an important member of the danger-associated molecular patterns capable of mediating inflammation during infection-associated responses. In this study, we investigated the role of HMGB1 in BA pathogenesis.

APPROACH AND RESULTS

In cholangiocytes, RRV induced the expression and release of HMGB1 through the p38 mitogen-activated protein kinase signaling pathway, and inhibition of p38 blocked HMGB1 release. Treatment of cholangiocytes with ethyl pyruvate suppressed the release of HMGB1. Administration of glycyrrhizin in vivo decreased symptoms and increased survival in the murine model of BA. HMGB1 levels were measured in serum obtained from infants with BA enrolled in the PROBE and START studies conducted by the Childhood Liver Disease Research Network. High HMGB1 levels were found in a subset of patients at the time of HPE. These patients had higher bilirubin levels 3 months post-HPE and a lower survival of their native liver at 2 years.

CONCLUSIONS

These results suggest that HMGB1 plays a role in virus induced BA pathogenesis and could be a target for therapeutic interventions in a subset of patients with BA and high HMGB1.

Innate Immunity and Pathogenesis of Biliary Atresia

Biliary atresia (BA) is a devastating fibro-inflammatory disease characterized by the obstruction of extrahepatic and intrahepatic bile ducts in infants that can have fatal consequences, when not treated in a timely manner. It is the most common indication of pediatric liver transplantation worldwide and the development of new therapies, to alleviate the need of surgical intervention, has been hindered due to its complexity and lack of understanding of the disease pathogenesis. For that reason, significant efforts have been made toward the development of experimental models and strategies to understand the etiology and disease mechanisms and to identify novel therapeutic targets. The only characterized model of BA, using a Rhesus Rotavirus Type A infection of newborn BALB/c mice, has enabled the identification of key cellular and molecular targets involved in epithelial injury and duct obstruction. However, the establishment of an unleashed chronic inflammation followed by a progressive pathological wound healing process remains poorly understood. Like T cells, macrophages can adopt different functional programs [pro-inflammatory (M1) and resolutive (M2) macrophages] and influence the surrounding cytokine environment and the cell response to injury. In this review, we provide an overview of the immunopathogenesis of BA, discuss the implication of innate immunity in the disease pathogenesis and highlight their suitability as therapeutic targets.

Pharmacological inhibition of STAT3 pathway ameliorates acute liver injury in vivo via inactivation of inflammatory macrophages and hepatic stellate cells

Liver diseases represent a major health problem worldwide, in particular, acute liver injury is associated with high mortality and morbidity. Inflammatory macrophages and hepatic stellate cells (HSCs) are known to be involved in the pathogenesis of acute liver injury. In this study, we have investigated the implication of STAT3 inhibition in acute liver injury/early fibrogenesis. In fibrotic human livers, we found STAT3 mRNA expression was significantly upregulated and correlated with collagen I expression. In vitro, STAT3 signaling pathway was found to be activated in TGFβ-activated HSCs and inflammatory macrophages. STAT3 inhibitor, WP1066 significantly inhibited TGFβ-induced collagen I, vimentin and α-SMA expression, and contractility in human HSCs. In LPS- and IFNγ-induced pro-inflammatory macrophages, WP1066 strongly attenuated nitric-oxide release and expression of major inflammatory markers such as TNF-α, iNOS, CCL2, IL-1β, IL-6, and CCR2. In vivo in CCl4-induced acute liver injury mouse model, WP1066 significantly reduced collagen expression, HSCs activation, and intrahepatic inflammation. Finally, in LPS-induced human hepatic 3D spheroid model, WP1066 inhibited LPS-induced fibrotic and inflammatory parameters. In conclusion, our results demonstrate that the therapeutic inhibition of STAT3 pathway using WP1066 targeting HSCs and inflammatory macrophages suggests a potential pharmacological approach for the treatment of acute liver injury.