Healthcare relies on medical devices, yet often these have significant risk of infection and failure. The medical device market is estimated to be just under US$500 billion, while US$25 billion is spent annually on treatment of chronic wounds. As our populations becomes older, our healthcare systems are also becoming stressed by multi-antibiotic resistance and viral outbreaks. For example, 50% of initial COVID-19 fatalities were due to secondary bacterial infections [Zhou et al. The Lancet, 2020]. Medical device failure rates of up to 20% burden our health service disproportionately through device centred infection, immune rejection, or both. The biomaterials that devices and external wound care products are made from significantly influence immune and healing responses and affect the outcome of infection. In the EPSRC Programme Grant "Next Generation Biomaterials Discovery", physical surface patterns (topographies) combined with novel polymers were found which both reduce bacterial biofilm formation and increase the immune acceptance of materials in vitro and in vivo in preclinical infection models. This provides a new paradigm for biomaterials used as implants and wound care products, where novel polymers can be topographically patterned to improved healing and acceptance using bio-instruction. To exploit these findings requires targeting to specific medical device environments and elucidation of the mechanism of action for translation by industry. This project will utilise 3D printing to manufacture ChemoTopoChips containing over a thousand polymer chemistry-topography combinations that allow the possible design space to be efficiently explored and mapped using semi-automated in-vitro measurements of host immune cell and infecting pathogen interactions individually and in co-culture. These ChemoTopoChips will allow a very high content of molecular information to be extracted from biomolecules secreted into the culture media (the secretome), those adsorbed to the surface (the biointerface) and their impact on both host cells and bacteria. The same fabrication approaches will be used to make devices for preclinical testing; in vivo information will be maximised using minimally invasive monitoring of infection and healing over time and detailed analysis of explants. These information streams will be merged using artificial intelligence (specifically machine learning) to build effective models of performance and provide mechanistic insight, allowing design of materials ready for translation as medical devices outside this project. After consultation with a wide range of clinicians we have chosen to target the following two devices: -Wound care products for chronic/non-healing wounds: dressings to reduce infection, induce immune-homeostasis and promote healing in chronic wounds that result in 7000 diabetes related amputations in the UK per year and cost the NHS £1bn a year to manage. -Implants requiring tissue integration but prone to fibrosis/adhesion and biofilm-associated infection: surgical meshes used for repair of hernias or pelvic organ prolapse commonly afflicting women after childbirth. The NHS undertakes 100k such operation each year with infection rates of up to 10%, plus foreign body response complications. The team assembled to exploit this opportunity has unique experience in the areas of biomaterials, artificial intelligence, additive manufacturing and in vitro and in vivo measurements of immune and bacterial responses to biomaterials. Facilities including the recently opened £100m Nottingham Biodiscovery Institute, the recently funded EPSRC £1m suite of high resolution/high throughput 3D printers and the unique £2.5m 3DOrbiSIMS Cat2 cryo-facility. These investments in Nottingham make this the only location in the world that is capable of undertaking this project. An Advisory Board of clinicians, industrial partners and leading academics will meet annually to provide input to the project.

We propose to undertake the first detailed scientific studies into the flight biology, migratory physiology and energetics of bar-headed geese in the wild using the latest electronic dataloggering technology. Ultimately, we will address the question of where are the limits to sustainable avian flight performance at high altitudes and what is the effect of body mass? In particular, how do larger species cope during flight with the combined effects of reduced air density, low oxygen availability and decreased temperature? Only a few species of larger birds are thought to be able to sustain long periods of flapping flight at high altitudes and these have received little study. The best known species is the bar-headed goose (Anser indicus) which performs one of the most physically challenging and impressive avian migrations by flying twice a year through the high plateau areas of the Himalayas, with some populations travelling between high altitude breeding grounds in China and lowland wintering areas in northern India. Despite their extraordinary flight performance and immensely interesting physiology and behaviour, neither the aerodynamic or physiological adaptations required to perform such feats are well understood. We will use miniature GPS tracking devices to provide detailed position and altitude during the flights so that we can identify their route in relation to the geographical topography and environmental conditions. This will also allow us to measure their rates of climb when migrating through the mountains. The bar-headed goose migration is exceptional for such a large bird as aerodynamic and biomechanical considerations suggest that as birds increase in body mass flight performance should deteriorate. Thus, bar-headed geese with a body mass of around 2.5 to 3.5 kg should only have a marginal physical capacity to sustain climbing flight even at sea level, and this ability should get worse as altitude increases due to the decrease in air density. By using 3-axis accelerometry we will be able to calculate the net aerodynamic forces acting on the body of the birds and monitor any changes in wingbeat frequency and relative wingbeat amplitude in response to changes in altitude and during the climbing flight. Their flights are also remarkable due to the physiological difficulties of sustaining any kind of exercise while coping with the harsh environmental conditions of the Tibetan plateau, especially the low ambient temperatures and the reduced availability of oxygen. Nevertheless, bar-headed geese have been recorded to fly between 4,000 m and 8,000 m, where partial pressures of oxygen are around 50% that of sea-level and temperatures can be as low as -20 C. We will measure the heart beat frequency of the birds during flights at different altitudes and estimate the maximum efforts expended during climbing flights in relation to their maximum expected capabilities. To place the remarkable migratory flights of the bar-headed goose in context, some 90% of avian migrations over land occur below 2000 m and the majority below 1000 m, which is well below the level of some of the main breeding lakes of the bar-headed goose (4,200 m to 4,718 m). We anticipate that the geographical barrier of the Himalayas should force these relatively large birds to fly close to the limits of their cardiac, muscular, respiratory and aerodynamic abilities. Indeed, this proposal will address the hypothesis that these migratory climbing flights may only by possible with the assistance of favourable up currents of air due to weather fronts or topographical reflections. Recent developments in electronic dataloggers now make it possible to measure both physical and physiological aspects of flight behaviour in free-flying birds rather than in animals constrained by captive conditions. Access to free-flying bar-headed geese would provide a unique opportunity to study the flight biology of a relatively large bird pushed to the extremes of its performance.

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.

The SABYDOMA programme addresses developments in the safety by design (SbD) paradigm by examining four industrial case studies in detail where the TRLs will advance from 4 to 6. Each TRL activity will progress from being lab based at TRL4 to being industry based at TRL6. The TRL4 activity will involve only innovation with regular industrial communication whereas the TRL6 activity will involve industrially located activities with innovation communication. One of the novel themes of this study is to use system control and optimisation theory including the Model Predictive Control (MPC) philosophy to bind the whole subject of SbD from laboratory innovation to the industrial production line and from decision making processes to project governance. An equally important innovative step is the building of high throughput online platforms where nanomaterial (NM) is manufactured and screened at the point of production. The screening signal controls the NM redesign and production in a feedback loop. Screens will involve (a) physiochemical sensing elements (b) in-vitro targets of increasing complexity from the 2D biomembrane to cell-line and more complex cell-line elements; and, (c) multiple in-vitro targets with multiple end-points; developed in current H2020 projects. Two of the industrial studies include composite coating manufacture where the coating’s stability and toxicity will be tested using a flow through microfluidic flow cell system coupled to online screens. This is part of the release and ageing investigations on the NM and NM coatings and the results of these will feed back to the production line design. At every step on the TRL ladder the in-silico modelling will be applied to optimise and redefine the relevant activities. By the same token regulatory and governance principles of SbD will be used to refine the technological development. The final deliverable will be four distinct technologies applying SbD to the four industrial processes respectively.

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.