Antiretroviral treatment (ART) has improved survival for people with HIV. But it cannot cure HIV as ART cannot remove HIV from cells containing virus in a resting state, known as the HIV reservoir. Current ART options usually requires daily oral medications, challenges include long-term side effects, treatment fatigue, drug resistance and expense. Broadly neutralising antibodies (bNAbs) are a new type of HIV treatment that may provide a safe, effective, and long-acting alternative to ART. Early studies suggest bNAbs may 'train' the immune system leading to long lasting HIV-specific responses. Monkeys given bNAbs early in SHIV infection, demonstrated virus control for up to 4 years. Two individuals treated with bNAbs in a small human study have unexpectedly continued to maintain undetectable virus levels in blood even beyond 30 weeks. However these studies were not randomised. The largest reservoir of HIV in the body is in the gut. It can be up to 5 times larger than in blood. It is uncertain if bNAbs enter gut tissue as well as in blood. Immune responses in the gut also differ from blood in many ways, such as slower recovery even after starting ART. Finally, we do not know how bNAbs affect the gut HIV reservoir. The RIO trial is an ongoing funded study. It compares a single dose of two types of bNAbs against inactive drug (placebo). Participants then stop ART and will return for frequent viral load tests. When the virus is detectable in blood, they will restart ART. Participants receiving placebo will be given the bNAbs after restarting ART. The RIO trial provides a unique chance to study the impact of bNAbs on the gut immune system and HIV reservoir through rectal biopsies. I will study rectal biopsies samples collected from RIO participants before and after they receive the study drugs (see Annex 1). These small 3mm biopsies are collected by an experienced clinician through a safe and painless procedure in clinic, using a short plastic tube in their rectum. This is less invasive than other common gut procedures such as colonoscopies and have minimal risks. The project aims to answer 3 research questions: 1: Are the bNAbs levels in the gut comparable to blood? Paired rectal tissue and blood bNAb levels will be measured using a highly sensitive test that can measure even single molecules of bNAbs present. If peak gut tissue bNAb concentrations are comparable to blood, these data will support further research of bNAbs for the eradication of HIV gut reservoir. This work will be done on an expected n = 10 participants who are randomised to receive the bNAbs in the main study. 2: Do bNAbs 'train' immune cells in the gut? I will use fluorescent antibody 'dyes' to look for the presence of both bNAbs and immune cells in biopsy sections through an automatic microscope. If bNAbs can 'train' HIV-specific immune responses, we will expect to see bNAbs in areas of immune cells called germinal centres. Learning how bNAbs 'train' gut immune responses may help researchers design better treatment or vaccines. 3: Do bNAbs affect the HIV reservoir in the gut? Studying resting HIV reservoir containing cells is challenging, as most contain defective HIV DNA and only about 1% contain intact HIV DNA. Cells containing intact HIV DNA are likely the source of rebound virus when ART is stopped. I will improve an existing intact HIV DNA test to sort intact from defective HIV DNA in the rectal tissue for analysis. This test will provide a more accurate, in-depth analysis of the HIV reservoir. Using the improved test, I will be able to map how the resting HIV reservoir has changed after being exposed to bNAbs. By comparing samples from the same individual, I can test if the viral reservoir has grown during ART interruption, and if bNAbs has an impact on the HIV reservoir. Findings from this project will provide insight into how the bNAbs work in the gut, and aid development of bNAbs and other strategies to eradicate the gut HIV reservoir.

Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.

Research context: Populations of the same species in locations hundreds of kilometers apart often fluctuate in unison or partly in unison, a phenomenon called synchrony. For instance, British aphid species, of economic importance because they are a major agricultural pest, outbreak 80% in synchrony over short distances and 50% in synchrony over distances of 200km, a huge distance for most aphid species. In fact, synchrony is widespread, and has been detected in birds, lemmings, fish such as cod, human pathogens such as measles, amphibians, and numerous other species. Many species exhibiting synchrony are of major conservation, economic, or health importance. Population synchrony has practical importance for several reasons. For instance, synchronized pest or disease populations require a coordinated response. An endangered species whose populations are synchronized is in accentuated danger of final extinction because populations are simultaneously low and might all go extinct by chance at once. An exploited synchronized species is periodically unavailable or less available across a wide area in many markets. Synchrony has been measured with methods that characterize the degree of synchrony between two populations only by a single number from 1 (perfect synchrony) down to -1 (perfect asynchrony). This approach is useful but limited: our results show synchrony is too complex to be captured with one number. Synchrony between two populations can occur mainly on short time scales, with little to no synchrony on long time scales; or on long time scales, with little or no synchrony on short time scales; or on any range of time scales. Synchrony between environmental variables in different locations has the same complexity. For instance, temperatures in London and Glasgow rise and fall largely together on annual time scales (seasonal variation) and multi-annual time scales (the North Atlantic Oscillation), but short-time-scale (day-to-day) temperature variation in London may resemble that in Glasgow much less. Different time scales of synchrony have different ecological and extinction-risk implications, and may have different implications for optimal control strategies for pests. In addition, new and important preliminary results show that the time-scale-specific structure of environmental synchrony is changing as part of climate change, and likely affects population synchrony, and thereby extinction risk. Research aims: We will use large spatio-temporal databases, new theory, and new lab experiments to obtain a broad time-scale-specific description of environmental and population synchrony, and to assess the implications of observed patterns for climate change, extinction risks, and inference of what mechanisms cause synchrony in the field. Applications: We will provide information about a newly observed and previously unrecognized aspect of climate change and a global assessment of its overarching importance for conservation and pest management applications and for ecological understanding.

Complex system often exhibit a dynamics that can be regarded as superpositionof several dynamics on different time scales.A simple example is a Brownian partice that moves in an inhomogeneousenvironment which exhibits temperature fluctuations in space and time on a relatively large scale. There is a superposition of two relevant stochastic processes,a fast one given by the velocity of the particle and a much slower onedescribing changes in the environment. It has become common to call thesetypes of systems 'superstatistical' since they consist of a superposition of twostatistics, a fast one as described by ordinary statistical mechanicsand a much slower one describing changes of the environment. The superstatistics is very general and has been recently applied to a variety of complex systems, including hydrodynamicturbulence, pattern forming nonequilibrium systems, solar flares, cosmic rays,wind velocity fluctuations, hydro-climatic fluctuations, share price evolution,random networks and random matrix theory.The aim of the research proposal is twofold.On the theoretical side, the aim is to develop a generalisedstatistical mechanics formalism that describes a large variety of complexsystems of the above type in an effective way. Rather thantaking into account every detail of the complex system, one seeksfor an effective description with few relevant variables. For thisthe methods of thermodynamics are generalised:One starts with more general entropy functionsthat take into account changes of the environment(or, in general, large-scale fluctuations of a relevant system parameter) as well. An extended theory also takes into account how fast the local system relaxes to equilibrium,thus describing finite time scale separation effects.On the applied side, the aim is to apply the above theory to a large variety of time series generated by different complexsystems (pattern forming granular gases, brain activityduring epileptic seizures, earthquake activity in Japan and California, evolutionof share price indices, velocity differences in turbulent flows).It will be investigated which superstatistical phenomena are universal(i.e. independent of details of the complex system studied) and whichare specific to a particular system. Possible universality classeswill be extracted directly from the data. Application-specific modelswill be developed to explain the observed probability distributionsof the slowly varying system parameters.

A landscape model consists of a parameterised family of potential functions together with a Riemannian metric. The dynamical system associated with this is given by the corresponding gradient vectorfield. Any Morse-Smale dynamical system with only rest point attractors and any system that admits a filtration admits such a representation except in a small neighbourhood of attractors and repellers. Such landscape models are of great interest in Developmental Biology because they correspond to Waddington's famous epigenetic landscapes but can also be rigorously associated with network models of the relevant genetic systems. When used to model the dynamics of a cell the parameters of the landscape correspond to signals being received by the cell. These can be due to morphogens in the cell's environment or signals coming from other cells. When these signal are altered, the landscape changes and this can cause bifurcations which destroy the attractor governing a cell's state and this can lead to a change in the cell's state. This is cellular differentiation, the way by which cell can change their cell type and specification. For example, stem cells differentiate in this way eventually to provide cells for all the tissue types in the body. The formation of the vertebrate trunk provides an important example of how cell fate decisions in developing tissues are made by signal controlled gene regulatory networks. Our biological collaborators have been studying part of this, namely the time course of differentiation of mouse embryonic stem cells to anterior neural or neural-mesodermal progenitors using such multidimensional single cell data. These experiments and the associated mathematical analysis has suggested that underlying this system is a highly non-trivial landscape of a complexity significantly greater than any published. This will be a key exploratory system that we will use to develop our ideas and we will work closely with the Briscoe and Warmflash labs to do this. However, it is important to stress that the purpose of this proposal is to focus strongly on developing mathematical ideas and tools and not just to be embedded in a particular biological project. On the other hand, access to state-of-the art data is very important. It ensures biological relevance and work with real data, rather than simulated data, raises real mathematical challenges. More and more powerful biological tools are becoming available to study such processes but the increasing amount and complexity of the data produced and the fact that the processes are carried out by complex systems means that new mathematical tools are need to help understand what is going on. In particular, biologists can now measure the numbers of multiple molecules in each of tens of thousands of cells in a single experiment. The key aim of this project is to increase our understanding of landscape models and combine this with state-of-the-art statistical techniques to provide new tools to analyse such data and to use it to probe the mechanisms of cellular differentiation and cellular decision-making in some important biological systems. The project involves deep collaboration with biological labs both in terms of data and biological ideas. It will be an excellent example of data science since it involves informatics (bioinformatics), statistics, mathematics (analysis, geometry & probability), hp computing and science (biology). It provides a new method of date dimension reduction a key theme in data science.