Tolerance induction with quantum dots displaying tunable densities of self-antigen

During autoimmune diseases like type 1 diabetes or multiple sclerosis (MS), the immune system mistakenly recognizes and attacks healthy tissues in the body. In MS, myelin, which surrounds and protects the axons of neurons, is attacked by inflammatory cells leading to neurodegeneration. The current standard of care for MS patients is regular injection of immunosuppressive drugs that non-specifically suppress immune function, leaving patients immunocompromised and open to opportunistic infection. New investigations aim to address this problem with immunotherapy-based strategies that promote myelin-specific tolerance. Recent reports reveal that the development of inflammation or tolerance against certain molecules is influenced by the concentration and form of self-antigen presented to immune cells (i.e. free, particle).Strategies that allow tunable delivery of self-antigen are therefore of great interest to further probe these connections. Quantum dots (QDs) were chosen as the nanomaterial to investigate these questions because they can be conjugated with a large and controllable number of biomolecules.Additionally, their size facilitates rapid drainage through lymphatics to lymph nodes (LNs), where they accumulate and can be visualized by deep-tissue imaging due to their intrinsic fluorescence. Please click Additional Files below to see the full abstract

Dissecting regulatory T cell expansion using polymer microparticles presenting defined ratios of self-antigen and regulatory cues

Biomaterials allow for the precision control over the combination and release of cargo needed to engineer cell outcomes. These capabilities are particularly attractive as new candidate therapies to treat autoimmune diseases, conditions where dysfunctional immune cells create pathogenic tissue environments during attack of self-molecules termed self-antigens. Here we extend past studies showing combinations of a small molecule immunomodulator co-delivered with self-antigen induces antigen-specific regulatory T cells. In particular, we sought to elucidate how different ratios of these components loaded in degradable polymer particles shape the antigen presenting cell (APC) -T cell interactions that drive differentiation of T cells toward either inflammatory or regulatory phenotypes. Using rapamycin (rapa) as a modulatory cue and myelin self-peptide (myelin oligodendrocyte glycoprotein- MOG) – self-antigen attacked during multiple sclerosis (MS), we integrate these components into polymer particles over a range of ratios and concentrations without altering the physicochemical properties of the particles. Using primary cell co-cultures, we show that while all ratios of rapa:MOG significantly decreased expression of co-stimulation molecules on dendritic cells (DCs), these levels were insensitive to the specific ratio. During co-culture with primary T cell receptor transgenic T cells, we demonstrate that the ratio of rapa:MOG controls the expansion and differentiation of these cells. In particular, at shorter time points, higher ratios induce regulatory T cells most efficiently, while at longer time points the processes are not sensitive to the specific ratio. We also found corresponding changes in gene expression and inflammatory cytokine secretion during these times. The in vitro results in this study contribute to in vitro regulatory T cell expansion techniques, as well as provide insight into future studies to explore other modulatory effects of rapa such as induction of maintenance or survival cues

Modelling the impact of social mixing and behaviour on infectious disease transmission: application to SARS-CoV-2

In regard to infectious diseases socioeconomic determinants are strongly associated with differential exposure and susceptibility however they are seldom accounted for by standard compartmental infectious disease models. These associations are explored here with a novel compartmental infectious disease model which, stratified by deprivation and age, accounts for population-level behaviour including social mixing patterns. As an exemplar using a fully Bayesian approach our model is fitted, in real-time if required, to the UKHSA COVID-19 community testing case data from England. Metrics including reproduction number and forecasts of daily case incidence are estimated from the posterior samples. From this UKHSA dataset it is observed that during the initial period of the pandemic the most deprived groups reported the most cases however this trend reversed after the summer of 2021. Forward simulation experiments based on the fitted model demonstrate that this reversal can be accounted for by differential changes in population level behaviours including social mixing and testing behaviour, but it is not explained by the depletion of susceptible individuals. In future epidemics, with a focus on socioeconomic factors the approach outlined here provides the possibility of identifying those groups most at risk with a view to helping policy-makers better target their support.Comment: Main article: 25 pages, 6 figures. Appendix 2 pages, 1 figure. Supplementary Material: 15 pages, 14 figures. Version 2 - minor updates: fixed typos, updated mathematical notation and small quantity of descriptive text added. Version 3 - minor update: made colour coding consistent across all time series figure

Enhancing anti-tumor immunity through local gene delivery to lymph nodes

Biodegradable polymer carriers offer attractive features for therapeutic cancer vaccines including delivery of multiple vaccine components, efficient internalization, and sustained release of adjuvants and tumor-associated antigens (TAAs). We previously demonstrated that local delivery of depots containing nucleic acid-based toll-liked receptor agonists (TLRas) to lymph nodes (LNs) potently enhances antigen-specific T cell immunity. Building on this work, we hypothesized that local LN delivery of microparticles loaded with TAA-encoding plasmid DNA (pDNA) and TLRas might drive strong local expression and presentation of antigen by LN-resident antigen presenting cells. These effects could help drive more potent and effective CD8+ T cell functions that slow or stop tumor growth.https://doi.org/10.1186/2051-1426-3-S2-P43

Nano-Imprinted Thin Films of Reactive, Azlactone-Containing Polymers: Combining Methods for the Topographic Patterning of Cell Substrates with Opportunities for Facile Post-Fabrication Chemical Functionalization

Laser scanning confocal microscopy (LSCM) and atomic force microscopy (AFM) were used to characterize changes in nanoscale structure that occur when ultrathin polyelectrolyte multilayers (PEMs) are incubated in aqueous media. The PEMs investigated here were fabricated by the deposition of alternating layers of plasmid DNA and a hydrolytically degradable polyamine onto a precursor film composed of alternating layers of linear poly(ethylene imine) (LPEI) and sodium poly(styrene sulfonate) (SPS). Past studies of these materials in the context of gene delivery revealed transformations from a morphology that is smooth and uniform to one characterized by the formation of nanometer-scale particulate structures. We demonstrate that in-plane registration of LSCM and AFM images acquired from the same locations of films fabricated using fluorescently labeled polyelectrolytes allows the spatial distribution of individual polyelectrolyte species to be determined relative to the locations of topographic features that form during this transformation. Our results suggest that this physical transformation leads to a morphology consisting of a relatively less disturbed portion of film composed of polyamine and DNA juxtaposed over an array of particulate structures composed predominantly of LPEI and SPS. Characterization by scanning electron microscopy and energy-dispersive X-ray microanalysis provides additional support for this interpretation. The combination of these different microscopy techniques provides insight into the structures and dynamics of these multicomponent thin films that cannot be achieved using any one method alone, and could prove useful for the further development of these assemblies as platforms for the surface-mediated delivery of DNA

Bayesian inference for high-dimensional discrete-time epidemic models: spatial dynamics of the UK COVID-19 outbreak

In the event of a disease outbreak emergency, such as COVID-19, the ability to construct detailed stochastic models of infection spread is key to determining crucial policy-relevant metrics such as the reproduction number, true prevalence of infection, and the contribution of population characteristics to transmission. In particular, the interaction between space and human mobility is key to prioritising outbreak control resources to appropriate areas of the country. Model-based epidemiological intelligence must therefore be provided in a timely fashion so that resources can be adapted to a changing disease landscape quickly. The utility of these models is reliant on fast and accurate parameter inference, with the ability to account for large amount of censored data to ensure estimation is unbiased. Yet methods to fit detailed spatial epidemic models to national-level population sizes currently do not exist due to the difficulty of marginalising over the censored data. In this paper we develop a Bayesian data-augmentation method which operates on a stochastic spatial metapopulation SEIR state-transition model, using model-constrained Metropolis-Hastings samplers to improve the efficiency of an MCMC algorithm. Coupling this method with state-of-the-art GPU acceleration enabled us to provide nightly analyses of the UK COVID-19 outbreak, with timely information made available for disease nowcasting and forecasting purposes

Overcoming Ovarian Cancer Drug Resistance with a Cold Responsive Nanomaterial

Drug resistance due to overexpression of membrane transporters in cancer cells and the existence of cancer stem cells (CSCs) is a major hurdle to effective and safe cancer chemotherapy. Nanoparticles have been explored to overcome cancer drug resistance. However, drug slowly released from nanoparticles can still be efficiently pumped out of drug-resistant cells. Here, a hybrid nanoparticle of phospholipid and polymers is developed to achieve cold-triggered burst release of encapsulated drug. With ice cooling to below ∼12 °C for both burst drug release and reduced membrane transporter activity, binding of the drug with its target in drug-resistant cells is evident, while it is minimal in the cells kept at 37 °C. Moreover, targeted drug delivery with the cold-responsive nanoparticles in combination with ice cooling not only can effectively kill drug-resistant ovarian cancer cells and their CSCs in vitro but also destroy both subcutaneous and orthotopic ovarian tumors in vivo with no evident systemic toxicity

Visualising spatio-temporal health data: the importance of capturing the 4th dimension

Confronted by a rapidly evolving health threat, such as an infectious disease outbreak, it is essential that decision-makers are able to comprehend the complex dynamics not just in space but also in the 4th dimension, time. In this paper this is addressed by a novel visualisation tool, referred to as the Dynamic Health Atlas web app, which is designed specifically for displaying the spatial evolution of data over time while simultaneously acknowledging its uncertainty. It is an interactive and open-source web app, coded predominantly in JavaScript, in which the geospatial and temporal data are displayed side-by-side. The first of two case studies of this visualisation tool relates to an outbreak of canine gastroenteric disease in the United Kingdom, where many veterinary practices experienced an unusually high case incidence. The second study concerns the predicted COVID-19 reproduction number along with incidence and prevalence forecasts in each local authority district in the United Kingdom. These studies demonstrate the effectiveness of the Dynamic Health Atlas web app at conveying geospatial and temporal dynamics along with their corresponding uncertainties.Comment: 4 Figures, 27 page