Worldwide, oral cancer (OSCC) is the eighth most common cancer and a major global health concern, with an annual incidence of around 398,000 and more than 222,000 deaths worldwide. OSCC is often difficult to treat; surgery and radiotherapy remain the standard treatments but, despite improvements, are associated with significant morbidity and a relatively static 5-year survival rate of around 50-60%. Around 15-80% of OSCC develop from a precursor lesion (OPL), most commonly a white patch (leukoplakia). The current gold standard for determining leukoplakia management is pathological diagnosis of dysplasia, with transformation rates of 24.1% being reported in severe dysplasia. At present, the only effective treatment is surgical excision. However, studies indicate that this is not likely to reduce the risk of recurrence or malignant change. It is clear that more effective treatments are required for both premalignant lesions and established OSCC. Immunotherapy represents the most promising new cancer therapy for several decades. These treatments harness the power of the patient's immune system to fight the cancer, in the same way that the immune system might fight a virus. Cancers are recognised by the immune system as "foreign' because they express proteins (antigens) not usually found in normal tissues. Some patients have a strong immune response against their cancer; this can be seen in the tumour tissue as immune cells (lymphocytes) attacking the cancer cells. However, most cancers are not well recognised by the immune system, and the immune system needs to be stimulated to respond. If we identify the abnormal proteins on the cancer cells, then we can design vaccines against these antigens to generate an immune response against the cancer cell (just like vaccinating against a virus); recent studies have shown that premalignant lesions in the cervix can be successfully cleared through vaccination. This type of cancer is caused by a virus (human papillomavirus) and vaccines are designed to target viral proteins. By contrast, in most cancers and premalignant lesions targetable antigens are unknown. This proposal aims to identify common tumour associated antigens (TAA; cancer testis antigens and others) expressed in OPL and OSCC as part of a therapeutic strategy to develop vaccines to treat and prevent this disease. Expression of cancer testis antigens have been described in OPL, and preliminary work by the Cancer Research Malaysia (CRM) team have identified two antigens, MADGED4B and FJX1 that are commonly expressed in both OPL and OSCC. We will extend this analysis, examining global gene expression in cases of dysplasia and with OSCC to identify common tumour antigens, focusing on those found early in the disease process, before cancer develops. We will use these antigens to make vaccines using a novel vaccine design developed by the University of Southampton team (UoS), and test these in a humanised mouse cancer models. The vaccine is based on a plant virus that produces a powerful immune response in a similar way to human viruses; but is safe, cheap and readily mass-produced in plants. This is attractive for low-to-middle income economies such as Malaysia, where OSCC is especially prevalent, but conventional treatment is unattainable for many patients. A cost-effective vaccine strategy that can target OPL before cancer develops and also treat OSCC would transform the management of this disease worldwide.

For the majority of cancers, early detection results in better survival. Oral cancer is one of the few cancers that is visible and many of these cancers are preceded by a potentially malignant lesion where medical intervention can prevent the development of cancer. Taken together, oral cancer presents an opportunity for early detection. However, identifying which oral lesion has a propensity to become oral cancer is not straightforward without specialised training and this problem is confounded by the lack of specialists who are trained in this expertise particularly in low- and middle-income countries, where the majority of oral cancers are diagnosed. One innovative approach to overcome this is to develop an artificial intelligence algorithm to classify oral lesions into those that are benign and those that are potentially malignant or are occult cancer so that patients can be triaged accordingly to receive appropriate clinical management. In this project, we propose to work within a multi-disciplinary, international team to collate a library of images from existing and prospective collections that will facilitate the development of an artificial intelligence algorithm that will be tested and validated. The outcome of this project will pave the way for further rigorous testing, development of an App incorporating this automated tool and clinical validation for the early detection of oral cancer. The development of an automated tool for the classification of oral lesions will facilitate the identification of patients most at risk to develop oral cancer so that these individuals can be managed appropriately. This project is particularly impactful in the low- and middle-income countries as the majority of the global burden of oral cancer is found in these countries.

Globally, water-related diseases are a major obstacle to sustainable development (WHO, 2018). Many of these diseases, such as Cholera and Hepatitis A, have been successfully phased out in Malaysia. However, leptospirosis and malaria still affect Malaysians every year. The annual incidence rate of Leptospirosis is actually increasing, from 0.97 cases per 100,000 population in 2004 to 12.47 per 100,000 in 2012. It is well known that leptospirosis and malaria are strongly linked to environmental conditions, and humidity and temperature in particular. Although scientific understanding of this link is advancing at a rapid pace, it is still very difficult to build computational models that make quantitative forecasts of outbreaks. Yet such systems are indispensable for proactive disease management, and to optimise the allocation of resources for medical prevention and interventions. A major difficulty with predicting outbreaks of water-related diseases is the large number of driving factors, which span the environmental and socio-economic realms. Additionally, many of the processes that link the driving factors with disease outbreaks, are highly non-linear and difficult to represent in computational algorithms. This proposal therefore sets out to explore the use of artificial intelligence approaches to identify and model the physical and microbiological interactions that lead to conditions favouring disease occurrences, with the goal of developing an early warning system for disease outbreaks. The complexity and non-linearity in the processes makes AI methods such as the neural network approach highly promising as it is inherently suited to problems that are mathematically difficult to describe and highly non-linear. The scientific field of artificial intelligence is developing at a very rapid pace. This evolution is driven by the exponentially increasing amount of information available online (often referred to as the "big data" era), much of which is highly unstructured and diverse (e.g., data from social media such as twitter feeds and news posts). This has resulted in the development of many novel and powerful algorithms and routines. However, its exploration in the context of water-related diseases is still very limited. Therefore, we propose to leverage these breakthroughs, by testing and adapting these new methodologies to advance predictive modelling of the link between hydrometeorological extremes and water-related diseases. The proposed research combines extensive compilation, synthesis and integration of socio-demographic and infrastructural data alongside data of environmental extremes, with novel computational algorithms to "learn" from the datasets and leverage the outcomes to improve operational forecasting systems. We have assembled a world-leading consortium of scientists that combines expertise on hydrometeorological extremes, artificial intelligence and community health issues. We will use the Malaysian state of Negeri Sembilan as a case study, and will work in close collaboration with the State Department of Health. This will allow us to access historical records that include patients' demographic information. More recently, risk assessment have been conducted using questionnaires that includes assessment of water supply and drainage infrastructure. The epidemiological data will be complemented by environmental data from the Department of Meteorology and the Department of Irrigation and Drainage (which are either available for academic use for free or a small fee), and monthly water quality monitoring data from local District Offices. References WHO, 2018. http://www.who.int/water_sanitation_health/diseases-risks/diseases/diarrhoea

This proposal is to develop and deploy for the first time lightweight low cost (disposable) multi-species chemical sondes to address limitations in composition measurement capability in the troposphere and low stratosphere. The sondes would incorporate state of the art CO, O3 and CO2 sensors developed by the applicants, and would be launched on standard meteorological balloons flown by National Weather Services (thus providing T, P, RH). The intention is that the sonde be suitable for use in global sonde networks such as SHADOZ and GRUAN as well as for stand-alone use, with applicability to both short term case studies (e.g. transport, chemical processes) and long term monitoring (for example linked to trend detection and climate change). The project will be in four phases: - Development and construction: involving integration of chemical sensors into a sensor module and its interface with the existing Vaisala RS92 and the new RS41 radiosonde systems. - Testing and validation: to be carried out in the JOSIE atmospheric simulation chamber, on simultaneous flights with conventional ozone sondes and in parallel with flights by the NERC FAAM research aircraft. - Field deployment: to be conducted as a) an intensive field activity as part of a larger measurement campaign, and b) regular measurement for 12-18 months. These deployments will be in Malaysia and will be used in studies of the tropical atmosphere. - Data analysis: statistical analysis of composition profiles and comparisons with the NAME and UKCA models to study chemical and transport processes in the tropical tropopause layer (TTL) and the transport of constituents in the free troposphere over Southeast Asia. We have, together with our project partners, the expertise and knowledge to develop and prove these new composition sondes which have the potential to revolutionise atmospheric measurement programmes through their ability to be launched routinely by operational meteorological agencies with minimum infrastructure.

Long-term measurements of the atmospheric composition are required for a full understanding of the effects of human emissions of greenhouse gases and pollutants. For historic reasons, the network of observing stations run under the auspices of the World Meteorological Organisation's Global Atmospheric Watch program has some regions which are well studied (e.g. Europe and North America) and some which are not. One region where the observing capability is limited is that part of Southeast Asia and the West Pacific known as the 'Maritime Continent'. In this project, we will work with the University of Malaya and the Malaysian Meteorological Department to develop a high-quality, long-term atmospheric monitoring program at the new field station at Bachok on the Malaysian peninsula. This site is extremely well located for studies of the outflow of the rapidly developing Southeast Asian countries, as well as for the interaction of that air with the much cleaner atmosphere in the southern hemisphere. The Universities of Cambridge and East Anglia both have experience in making long-term measurements. In particular UEA have operated a well-instrumented observing site at Weybourne on the north Norfolk coast for well over a decade. This expertise will be used to develop the existing capability in Malaysia and to design and implement a programme of long-term measurements at Bachok. The focus of the measurements in the first instance will be greenhouse gases, ozone depleting substances, and chemical pollutants. In addition we will be encouraging the involvement of other interested scientists in NCAS Composition, the UK more generally and beyond to strengthen the planned measurement program. A demonstration activity will be arranged in the winter monsoon season when the flow is strongly from Southeast Asia. This activity will have two aims: (i) ensuring high quality measurements are made at the site; and (ii) determine the characteristics of the site and its suitability for the assessment of both global and regional atmospheric composition. Many of the measurements made in this activity will then be continued in to the monitoring programme. It is important to ensure that such measurements are fully exploited, and to this end we will both collaborate with partners in Taiwan and Australia and develop a modelling strategy for the interpretation of the data in conjunction with UK modelling groups including those at Cambridge, UEA and within NCAS. Exchange visits will be used for training purposes and for the development of collaborative interpretive studies (and peer-reviewed publications). Finally, a major scientific conference will be held towards the end of the project, linking in to international programs such as WMO-GAW, IGAC or SOLAS.