In the past two decades numerous viruses have emerged from animals to cause outbreaks in the human population. These include Swine Flu, Ebola viruses, Zika virus, and three coronaviruses, including SARS-CoV-2, the cause of the ongoing COVID-19 pandemic. The frequency of virus emergence is accelerating likely due to our increased travel as well as global environmental and climate changes that bring humans and animals in ever closer contact. To identify which viruses pose the most risk for future pandemics, it's important to understand what it is about pandemic viruses that enables them to spread so efficiently between humans. One of our most important front-line defences against infection is our innate immune system. This system is present in all cells, and is made up of a network of sensors that can detect invading viruses, activate antiviral defences and initiate a warning system that places neighbouring cells in a state of readiness to stop infection. To infect us and transmit, all viruses must overcome this front-line defence, by escaping detection or by disabling the response or usually a complex combination of both. Viruses that jump between species, such as coronaviruses, must overcome this defence system in each new host. I previously found that, despite having only recently emerged in humans, isolates of SARS-CoV-2 collected at the start of the pandemic could effectively suppress activation of the human innate immune system to allow viral spread. This suggests the virus was pre-armed with countermeasures to overcome human defences. The emergence of more transmissible variants throughout the pandemic, called variants of concern (VOCs), suggests that SARS-CoV-2 is adapting to spread better in its new human host. I discovered that the VOCs were able to suppress activation of the innate immune system even more potently than the early isolates, which may increase their chance of establishing infection to transmit. Virus manipulation can change the course of the innate immune response and drive disease, resulting from inappropriate immune activation that damages tissues, as occurs in severe COVID-19. All together our new understanding helps explain how the innate immune system is a key determinant in pandemic virus emergence, transmission, and disease. The goal of my research programme is to understand how emerging viruses overcome the innate immune system to become pandemic. Studying SARS-CoV-2, and its adaptation to humans in real time, provides an unparalleled opportunity to understand the molecular mechanisms underlying human infection. I will firstly identify the countermeasures the original SARS-CoV-2 virus used to overcome human innate immune defences. This will lead me to discover key innate immune barriers to emerging viruses and understand how they work. Secondly, I will investigate how SARS-CoV-2 variants have adapted to get better at overcoming the human innate immune system to transmit more effectively. This will reveal what aspects of the innate immune system are unique to humans. Thirdly, I will discover how SARS-CoV-2 manipulation of the innate immune system drives inappropriate responses that cause disease. The virus is a master manipulator of the cell environment to make it conducive for viral replication. Because of this, we can use it as an excellent tool to learn how the innate immune response works, which is relevant to understanding other diseases where the innate immune system is defective. Through this fellowship, I will maximise what we can learn from SARS-CoV-2 to lay the groundwork for understanding future emerging viruses, which all encounter the same defences, and discover exciting new biology about how the innate immune system works in health and disease.

UCLA are developing a new surgical technique for people who are suffering from the total loss of voice. The cause of this disease is often due to the total or partial paralysis of what is popularly called the 'vocal cord'. Our interest is in the nerve that stimulates the muscles that stretch the 'vocal cord', which then allows us to vibrate our 'voice box' and speak.Another surgical technique is currently in use to treat people suffering from spasmodic dysphonia. This is another little understood disease that cause the 'voice box' to vibrate when we do not want it to do so. Thus sufferers have a disturbed speech pattern. The team at UCLA has been successfully applying a surgical technique to cure this disease that relies on moving the nerve that stimulates the muscle, from one position to another. Known as 'Selective Laryngeal Adductor Denervation-Reinervation' this technique has been shown to be successful in about 70% of patients treated. The UCLA team now wish to apply their surgical skills to treating paralysis of the vocal fold by reinervation of the Recurrent Laryngeal Nerve (RLN); but before we attempt this treatment we need to understand more about how the RLN works.This is a small study, using dogs, which will measure the change in the stiffness (i.e. effectiveness) of the vocal fold when different levels of electrical stimulation are applied to the nerve. From this data we will be able to quantify the relationship, and thus develop the new surgical procedure.If successful then we will be able to make people suffering from paralysis of the 'voice box' to speak again.

The proposal is to explore the potential of using a fully ionised gas or plasma as an efficient short pulse amplifier. By exciting a plasma wave by two colliding (seed and pump respectively) pulses in plasma, it is possible to amplify the short seed pulse efficiently. The bandwidth of the plasma amplifier medium is enhanced when a chirped pump pulse is utilised. In the linear regime, before saturation of the amplifying process takes over, the long chirped pump laser pulse provides distributed amplification where different spectral components of the seed are amplified at different longitudinal positions in the plasma through the creation of a chirped plasma density echelon, much like a diffraction grating. This behaves as a long chirped mirror which simultaneously backscatters and compresses the chirped pump pulse and effectively broadens the gain bandwidth to that of the pump. The gain and the bandwidth of the amplifier depend on the natural oscillation frequency of the plasma (the plasma frequency) and the chirp rate (the rate at which the frequency changes along the pump pulse) and spectral bandwidth of the pump. This contrasts with conventional chirped pulse amplifiers (CPAs) and optical parametric chirped pulse amplifiers (OPCPAs) where the probe is chirped while the pump is usually monochromatic (un-chirped). The chirped pulse Raman amplifier has potential use either as a high fidelity ultra-short pulse high power linear amplifier or as a compressor of high energy chirped pulses from a conventional CPA amplifier. It also avoids the requirement for extremely large and expensive optical elements and compressors in vast vacuum chambers. Furthermore, because chirped pulse Raman amplification is a three wave parametric interaction it provides a means of eliminating pre-pulses and pedestals which usually limit the usefulness of conventional solid state CPA amplifiers. This research proposal will investigate the linear and non-linear stages of Raman amplification with a view to develop extremely high power lasers which have the potential of opening up new frontiers of physics such as using lasers to create particles from vacuum or create astrophysical conditions in the laboratory.

Many of the clouds in the atmosphere contain ice particles. These ice particles play an important role in the climate system, because high-altitude cirrus clouds cover around 30% of the globe at any one time, and act to warm the planet. Ice particles are also important for the development of precipitation, and not only in cold polar climates: even in mid-latitudes (like the UK), over three quarters of the precipitation that falls originates as snowflakes aloft - it is just that most of it melts before arriving at the surface. Ice particles, both in clouds and in snowfall at the surface, precipitate. In other words, they are able to grow large enough to fall through the air. This has several implications. The most obvious of these is that the rate at which the particles fall out controls the transport of water vertically through the atmosphere and to the surface. More subtly, the movement of each ice particle through the air directly influences the rate at which the particle grows, evaporates and melts. For example, if the air is humid enough, water molecules will diffuse to the ice crystal's surface and deposit there, leading to growth. If the particle is stationary, this growth occurs steadily but slowly, because the growing ice crystal depletes the vapour around it, leading to a shallow gradient in the concentration of molecules. If the particle is falling, this growth can occur much faster, because the ice crystal is constantly falling into fresh, humid air, leading to steep concentration gradients. The quantitative details of exactly how fast an ice particle of a given size and shape falls, and how much the growth rates are enhanced by, is determined by the airflow around the ice particle, or its aerodynamics. Unfortunately, this is an area of cloud physics where our understanding is extremely limited. The aerodynamics of simple shapes like spheres, spheroids and discs is well studied. However it is clear from observation of natural ice particles that they are not simple in their geometry. Instead the particles are often complex and irregular in their shape. We have almost no high-quality data on the aerodynamics of such particles. As a result, even state-of-the-art microphysical models are forced to approximate the aerodynamical effects on ice processes as though these complex irregular particles were spheres or spheroids, hoping that this is an adequate approximation. To solve this problem, experimental data is needed for the aerodynamics of particles with the complex shapes that we observe in the atmosphere. The stumbling block is that making suitable observations of natural ice particles in free-fall is extremely challenging. In snowfall at the surface the particles are small, fragile, easily blown by the wind, and likely to melt or evaporate if not handled with great care. Direct sampling of falling particles in cirrus clouds is impossible. In neither case is it possible to directly determine the airflow around the particle or the influence of that flow on the microphysical process rates. In this project we overcome these problems with the use of analogues. Using 3D printing techniques we will create plastic particles with the same complex geometry as natural ice particles. By dropping the particles in tanks of liquids, and through air in the laboratory and a vertical wind tunnel, we can determine how the fall speed of the particles is controlled by their size and geometry. Exploiting recent developments in tomographic particle imaging velocimetry we can measure the airflow around the falling analogues. From this we can directly determine how the airflow enhances the particle growth, evaporation and melting rates.

SUMMARY The Amazon is the most important biome of South America, harbouring extraordinarily high levels of biodiversity and providing important ecosystems services. This biome is particularly notable for evolving independently from fire and in a moist, warm climate. In recent decades, altered fire regimes and an increasingly hotter and drier climate has pushed this key biome towards ecological thresholds that will likely lead to major losses in biodiversity and ecosystem services. Similarly, the ecotonal forests at the Amazon-Cerrado transition are unique ecosystems in terms of form and function, but they may be the first to suffer large-scale tree mortality and species loss due to the combined effects of increased anthropogenic disturbance, altered fire regimes and a drier climate. Vulnerability of fire and droughts are closely intertwined in Amazonian and transitional forests because fires in this region only occur when there is water stress and a human ignition source. Thus, drought increases vulnerability to fire, but we do not yet understand the magnitude and spatial variation of these vulnerabilities. Once a forest burns there is immediate tree mortality, but recent evidence also shows a significant time-lagged mortality that can last for decades, becoming an important carbon source. However, the mechanistic processes that lead to time-lagged tree mortality in this myriad of forest ecosystems encompassing the Amazon biome and the Amazon-Cerrado transition are still poorly understood. We also lack knowledge on how these processes might vary spatially across the biome and its transition. A better understanding of the mechanisms that lead to tree mortality after fires and droughts is needed to design future policies that emphasise nature-based solutions including restoration and natural regeneration. This proposal presents a multi-level approach that aims at deciphering the mechanisms that underly vulnerability to fire and time-lagged post-fire mortality across the tropical forests in Amazon and Amazon-Cerrado transition. To achieve this aim, we will quantify fire vulnerability at three different scales and link them through an upscaling approach. First, we will identify the ecological mechanisms, reflected through functional traits, that explain why individuals and species die after fires occur. For this, we will focus on poorly understood traits that can be related to fire and/or hydraulic functioning. Second, at the community scale, we will examine how vegetation structure, community traits and microclimate affect the probability to burn, through an intensive characterisation of different vegetation types with multispectral and light detection and ranging (LIDAR) imagery. Third, we will use our our unique ground-dataset on functional traits, vegetation structure and moisture dynamics, and the latest state-of-art remotely sensed information on structure and water stress to predict the vulnerability of the Amazon forests and Amazon-Cerrado transitional forests. This information will be directly applicable for the detection of sensitive hotspots (areas particularly vulnerable to fire) through satellite products. We will deliver quantifiable early-warning metrics of ecosystem vulnerability to fire that can be mapped and incorporated into fire management policies. This is a revised version of a NERC proposal that was rejected with a score of 7 by the NERC Panel in July 2020, and we have carefully addressed the Panel's comments. Specifically, we have clarified the methodology and we have reformulated the hypotheses, so they address vulnerability to fire and not drought fire-interactions.