162 research outputs found
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.
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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
Targeted Programming of the Lymph Node Environment Causes Evolution of Local and Systemic Immunity
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
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