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Metastatic bone cancer is an incurable disease and one of the most complex cancers to treat. Due to the high dose, tumour imaging is currently performed at the beginning and end of standard particle radio-therapy (PRT), making personalised treatment difficult. The main goal of BoneOscopy is to develop a radically new technology to enable informed medical decisions by monitoring bone cancer on a daily basis during PRT. At the heart of BoneOscopy is the ability to detect prompt gamma (PGs) emitted by cancer during PRT and separate them from healthy tissue, unlocking the full potential of spectroscopic analysis without the need for additional dose. The development of a highly specialised detection and collimation system will enable accurate spectroscopic analysis of a very small volume or region within the cancer. As the number of PRT centres grows, we anticipate that within 10 years BoneOscopy will benefit all patients treated with proton and carbon ions. The objectives of BoneOscopy will be achieved by its interdisciplinary consortium, which brings together six partners from five European countries with key expertise in bioengineering and PRT (DKFZ), medical physics and engineering (CSIC), fast electronics for PRT (LIP), Monte Carlo simulations and clinical PRT experience (THM), turnkey software for high performance medical devices (Cosylab) and EU project management, communication and dissemination (accelCH). If achieved, the proposed science-totechnology breakthrough will have a transformative impact on current cancer treatment by providing a safe, personalised and quantitative measure of daily treatment efficacy, thereby contributing to the global fight against cancer. In summary, BoneOscopy will lead to a significant reduction in the health burden in Europe and worldwide, improved quality of life for patients, reduced costs for healthcare systems and improved sustainability of healthcare.

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Photoplethysmogram (PPG) signals are easy to collect non-invasively using cheap devices and are used in
the clinic and in wearable devices for home monitoring. It is recognised that PPG signals contain a wealth of
valuable physiological information for monitoring or diagnosing a range of health conditions. Machine learning (ML) is applied to PPG signals but there is a lack of work on trustworthiness, which is crucial in a medical context. By developing methods to quantify both the data and model uncertainty for ML applied to PPG signals, this project aims to generate reference datasets to benchmark such models and to identify models with high
accuracy and low uncertainty thus providing trustworthy models that are ripe for implementation.

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OSTEONET aims to (i) build a multidisciplinary research network involving experts of technical and medical disciplines to merge their expertise and exploit possible synergies for the development of reliable and sustainable 3D in vitro cell models of healthy and aged bone tissue and (ii) train a cohort of scientists and technologists in exploiting the model features to increase knowledge on the effects of ageing on bone biology and mechanobiology, and on bone response to drugs, to leverage the use of 3D cell models in clinics and basic/industrial research labs.
Bone ageing reduces the quality of life of the elderly and puts social and economic burden on society. Ageing bones fail more easily when challenged mechanically or with toxicants or pollutants, and respond differently to drugs than healthy bone. To personalize therapies and enable better preventive care for the elderly it is essential to develop reliable and sustainable in vitro models of aged bone tissue alternative to animal tests which often fail to capture human-specific features. Several scientific studies support the idea
that in vitro models of bone tissue are an outstanding resource for (i) the comprehension of bone physiology, (ii) a better understanding of pathological pathways in most bone dysfunctions, (iii) testing new or repurposed drugs for bone treatment before preclinical trials with animal models.
The networking activities planned in OSTEONET will unravel and share knowledge on the mechanisms driving the information transfer from the biochemical and biomechanical levels, which drive osteosynthesis and osseointegration, to the cascade of molecular and cellular events emerging as an elaborated and physiological bone, and on the mechanisms of the different response of healthy and aged bone tissue to mechano-biological stimuli and drugs.

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TP1: Erweiterung der Forschungsinfrastruktur HyFuel-Campus-Mittelhessen: Beitrag zur Entwicklung der strombasierten grünen Wasserstofftechnologie. Mittels der Beschaffung von apparativer Ausstattung für den Laborbetrieb der H2-Wertschöpfungskette wird die Forschung unter Realbedingung ermöglicht.

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Das Forschungsvorhaben soll einen Beitrag zur Entwicklung der strombasierten grünen Wasserstofftechnologie leisten. Mittels der Beschaffung von apparativer Ausstattung für den Laborbetrieb der gesamten H2-Wertschöpfungskette wird die Forschung unter Realbedingung auf dem Campus Gießen ermöglicht.

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Über die Entwicklung von standardisierten Verfahren, wie methodisch-systematische Plattformtechnologien, soll die Integration von innovativen Techniken im Translationsprozess bei der Impfstoffproduktion maßgeblich unterstützt werden. Die darüber verkürzte Zeitspanne zur Bereitstellung von neuen Vakzinen kann signifikant dazu beitragen, die sozialen und ökonomischen Auswirkungen bei zukünftigen Epidemien und Pandemien wirkungsvoller zu kontrollieren.

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Im Rahmen des Vorhabens werden hybride Optiken entwickelt. Diese bestehen aus additiv gefertigten Tragstrukturen, die optische Elemente wie Glaslinsen fassen. Die Tragstrukturen werden monolithisch und in Leichtbauweise ausgeführt. Das führt zu leichten und besonders robusten optischen Systemen, die sich in optische Sensorik integrieren lassen, welche unter harschen Umweltbedingungen zuverlässig und wartungsarm arbeitet und trotzdem ihre Umwelt detailliert wahrnimmt. Solche Sensorik wird für das Weiterverfolgen der Roadmap des Internet der Dinge benötigt. Das Potential hybrider Optik wird darüber hinaus für optische System wie Mikroskope, Messköpfe oder Objektive untersucht. Des Weiteren findet intensiver Transfer des generierten Wissens mit der regionalen Wirtschaft statt.