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Women who are born with an inherited mutation in the BRCA1 gene have a very high lifetime risk of developing breast and ovarian cancer. These women tend to have a strong family history of breast cancer and can develop breast cancer at a young age. Additionally, a large proportion of breast cancer that develop sporadically (non-inherited breast cancers) have lost the function of the BRCA1 gene. BRCA1s primary role in cells is to repair and maintain DNA and by doing this BRCA1 protects cells from being able to turn into cancers. However, the exact mechanisms through which BRCA1 protects and repairs damaged DNA remain unknown. Nevertheless, recently there have been significant advances in how BRCA1 related cancers are treated with the advent of "targeted" cancer therapies called PARP inhibitors that specifically kill cancers like BRCA1 linked cancers that have defects in their ability to repair damaged DNA. We have recently identified a new function for BRCA1 where it, with the help of other proteins called mRNA splicing proteins, helps cells to repair damaged DNA by regulating the levels of DNA repair proteins within a cell and ensuring there is enough of these proteins to repair DNA that has been damaged. Recently, a number of mutations have also been found in a significant proportion of breast, ovarian and haematological cancers in the mRNA splicing proteins that help BRCA1 carry out this new function. The proposed research in this project aims to: 1) Identify if and how hereditary mutations in BRCA1 affect this new function of BRCA1 helping us to understand whether this new function of BRCA1 really plays a role in the development of hereditary cancers. 2) Identify which DNA repair proteins that BRCA1 and the other mRNA splicing proteins, regulate are important for BRCA1 to carry out it's DNA repair functions. 3) Understand how cancer associated mutations in the mRNA splicing proteins that help BRCA1 repair damaged DNA affect the way these proteins are able to help BRCA1 repair damaged DNA and how they affect the way that cancers respond to different treatments. The proposed research will add significantly to our understanding of how BRCA1 works to prevent the development of cancer. Additionally, this research may lead to the development of new tests to help decide which treatments specific cancer patients will benefit from and may also identify new proteins associated with cancer that could be targeted for future therapies.

Grass pea is a pulse crop with remarkable tolerance to drought as well as flooding, making its seeds an important local food source in several tropical countries, especially Ethiopia, Sudan and Eritrea as well as India and Bangladesh. In times of weather extremes causing crop losses, grass pea often remains one of the most available foods and the cheapest source of protein, helping people survive during food shortages. The mounting challenge of climate change increases the need for crops that can be grown sustainably and withstand weather extremes. Through its 8000-year history of cultivation grass pea has been a part of human diets - from Neolithic sites in the Balkans, through the bronze-age middle east, the Roman Empire and medieval Europe until the modern day. But despite its value for food and nutritional security, grass pea carries the stigma of a potentially dangerous food. Its seeds and leaves contain a neurotoxic compound that can cause a debilitating disease known as neurolathyrism. This disease only appears in people who are malnourished and consume large amounts of grass pea over several months. Yet the fear of neurolathyrism, which has been known since antiquity, has led to grass pea being undervalued by farmers, breeders and scientists, making it an 'orphan crop'. There is no significant international trade in grass pea and too little research to develop the potential of this resilient, sustainable source of protein. Grass pea is able to fix nitrogen from the air (through symbiosis with nodulating bacteria), can efficiently use soil phosphate through its mycorrhizal associations, can penetrate into hard, heavy soil and is relatively tolerant to pests and diseases. All these characteristics make it an ideal crop for agriculture where farming inputs (fertiliser, pesticides, irrigation, etc.) are limited, as is the case in most smallholder farms in Sub-Saharan Africa. We therefore believe that improved grass pea varieties can have a significant impact beyond the millions of people who already cultivate it in Africa today and could become a crucial sustainable food source for many more. Our project aims to remove the limitations of this crop by using the tools and resources we have already developed in our previous research to breed new varieties that are safe to consume, high-yielding, nutritious and resilient to environmental stress. We have identified new low-toxin variants with lower beta-ODAP contents than any existing varieties. In addition we have sequenced and assembled the grass pea genome and transcriptomes under stress and non-stress conditions and we are working to enable modern crop improvement methods on the back of these. Through this research partnership we have access to grass pea lines representing the global diversity of the crop and those that are locally adapted to East Africa and to expertise on smallholder agriculture and seed systems. The UPGRADE project will build on this foundation and create a partnership to translate bioscience research advances on grass pea into new varieties with tangible benefits for smallholder farmers. Besides this, our research will generate valuable data on the performance of grass pea and the physiological role and regulation of the production of the toxin in the plant. Through a better foundational understanding, we and other researchers will be better able to direct future breeding efforts and deliver the promise of grass pea.

The vast majority of problems that lie at the forefront of science are governed by mathematical equations that cannot be solved exactly. In the modern era, large-scale numerical computation and data analysis are powerful tools, but many questions still elude brute-force computation. For complex multi-scale and multi-parameter systems, it is often necessary to apply key reductions dependent on the smallness or largeness of certain parameters. The application of these reductions is called asymptotic analysis; these methods have the power to dramatically simplify complex systems to their salient features, extract key mechanisms, and provide details in regions where numerics and experiments fail. As noted by Crighton [1] "[the] design of computational or experimental schemes without the guidance of asymptotic information is wasteful at best, and dangerous at worst, because of the possible failure to identify crucial (stiff) features..." Some of the most challenging problems relate to the prediction of exponentially small effects that are invisible to traditional asymptotic analysis and often mistakenly considered as negligible. In some cases, these effects may correspond to some observable feature, such as an oscillation or wave in the system; in other cases, they may be largely non-observable, but instead serve to determine whether certain solutions are permissible. Over the last few decades, there has been an appreciation for the ubiquity of problems where exponentially-small effects are paradoxically important -- these problems can be found in studies related to dendritic crystal growth, viscous fluid flow, water waves, quantum tunneling, geophysics, and more. There are significant mathematical and computational challenges for the study of exponentially small terms. For example, the traditional mathematical techniques that exist, developed in the early 20th century, are usually insufficient. Exponential asymptotics is the name given to the set of specialised techniques that have been developed over the last two decades for these problems. In the last few years, some of the most significant applications of exponential asymptotics have related to the development of theory for free-surface flows. This includes the study of (i) water waves produced by gravity-driven flows past slow-moving full-bodied ships; (ii) solitary waves in a fluid of finite depth including both gravity and capillary effects; and (iii) viscous flows where bubbles or fingers are produced at an interface. These problems all involve crucial exponentially small effects. Despite the above successes, a significant bottleneck has emerged in numerous studies in the area: the majority of existing exponential asymptotic techniques are limited to ordinary differential equations where, for instance, only a one-dimensional fluid interface is considered. Many of the spectacular successes of exponential asymptotics that have emerged in the last two decades have analogues in higher-dimensional space or in time-dependent formulations, where the system is governed by partial differential equations. However, the standard techniques in exponential asymptotics are not easily adapted to study such situations. The most recent preliminary work on seeking extensions of the theory has shown that the likely avenue for progress lies with combining analytical methods with computational and data-driven approaches---hence a hybrid numerical-asymptotic approach to exponential asymptotics. The development of these methodologies, and the subsequent applications to multi-dimensional problems in fluid mechanics forms the main thrust of this project. [1] Crighton, D. G. (1994). Asymptotics--an indispensable complement to thought, computation and experiment in applied mathematical modelling. In Proc. 7th Eur. Conf. on Math. Industry (ECMI), Montecatini (pp. 3-19).

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