Zoekresultaten

CureQ Predict, Delay & Cure polyglutamine(Q) caused neurodegeneration

Huntington’s disease (HD) and various spinocerebellar ataxias (SCA) are autosomal dominantly inherited neurodegenerative disorders caused by a CAG repeat expansion in the disease-related gene1. The impact of HD and SCA on families and individuals is enormous and far reaching, as patients typically display first symptoms during midlife. HD is characterized by unwanted choreatic movements, behavioral and psychiatric disturbances and dementia. SCAs are mainly characterized by ataxia but also other symptoms including cognitive deficits, similarly affecting quality of life and leading to disability. These problems worsen as the disease progresses and affected individuals are no longer able to work, drive, or care for themselves. It places an enormous burden on their family and caregivers, and patients will require intensive nursing home care when disease progresses, and lifespan is reduced. Although the clinical and pathological phenotypes are distinct for each CAG repeat expansion disorder, it is thought that similar molecular mechanisms underlie the effect of expanded CAG repeats in different genes. The predicted Age of Onset (AO) for both HD, SCA1 and SCA3 (and 5 other CAG-repeat diseases) is based on the polyQ expansion, but the CAG/polyQ determines the AO only for 50% (see figure below). A large variety on AO is observed, especially for the most common range between 40 and 50 repeats11,12. Large differences in onset, especially in the range 40-50 CAGs not only imply that current individual predictions for AO are imprecise (affecting important life decisions that patients need to make and also hampering assessment of potential onset-delaying intervention) but also do offer optimism that (patient-related) factors exist that can delay the onset of disease.To address both items, we need to generate a better model, based on patient-derived cells that generates parameters that not only mirror the CAG-repeat length dependency of these diseases, but that also better predicts inter-patient variations in disease susceptibility and effectiveness of interventions. Hereto, we will use a staggered project design as explained in 5.1, in which we first will determine which cellular and molecular determinants (referred to as landscapes) in isogenic iPSC models are associated with increased CAG repeat lengths using deep-learning algorithms (DLA) (WP1). Hereto, we will use a well characterized control cell line in which we modify the CAG repeat length in the endogenous ataxin-1, Ataxin-3 and Huntingtin gene from wildtype Q repeats to intermediate to adult onset and juvenile polyQ repeats. We will next expand the model with cells from the 3 (SCA1, SCA3, and HD) existing and new cohorts of early-onset, adult-onset and late-onset/intermediate repeat patients for which, besides accurate AO information, also clinical parameters (MRI scans, liquor markers etc) will be (made) available. This will be used for validation and to fine-tune the molecular landscapes (again using DLA) towards the best prediction of individual patient related clinical markers and AO (WP3). The same models and (most relevant) landscapes will also be used for evaluations of novel mutant protein lowering strategies as will emerge from WP4.This overall development process of landscape prediction is an iterative process that involves (a) data processing (WP5) (b) unsupervised data exploration and dimensionality reduction to find patterns in data and create “labels” for similarity and (c) development of data supervised Deep Learning (DL) models for landscape prediction based on the labels from previous step. Each iteration starts with data that is generated and deployed according to FAIR principles, and the developed deep learning system will be instrumental to connect these WPs. Insights in algorithm sensitivity from the predictive models will form the basis for discussion with field experts on the distinction and phenotypic consequences. While full development of accurate diagnostics might go beyond the timespan of the 5 year project, ideally our final landscapes can be used for new genetic counselling: when somebody is positive for the gene, can we use his/her cells, feed it into the generated cell-based model and better predict the AO and severity? While this will answer questions from clinicians and patient communities, it will also generate new ones, which is why we will study the ethical implications of such improved diagnostics in advance (WP6).

drivEr trainIng anD assEssmenT: a dIgital approaCh (EIDETIC)

Receiving the first “Rijbewijs” is always an exciting moment for any teenager, but, this also comes with considerable risks. In the Netherlands, the fatality rate of young novice drivers is five times higher than that of drivers between the ages of 30 and 59 years. These risks are mainly because of age-related factors and lack of experience which manifests in inadequate higher-order skills required for hazard perception and successful interventions to react to risks on the road. Although risk assessment and driving attitude is included in the drivers’ training and examination process, the accident statistics show that it only has limited influence on the development factors such as attitudes, motivations, lifestyles, self-assessment and risk acceptance that play a significant role in post-licensing driving. This negatively impacts traffic safety. “How could novice drivers receive critical feedback on their driving behaviour and traffic safety? ” is, therefore, an important question. Due to major advancements in domains such as ICT, sensors, big data, and Artificial Intelligence (AI), in-vehicle data is being extensively used for monitoring driver behaviour, driving style identification and driver modelling. However, use of such techniques in pre-license driver training and assessment has not been extensively explored. EIDETIC aims at developing a novel approach by fusing multiple data sources such as in-vehicle sensors/data (to trace the vehicle trajectory), eye-tracking glasses (to monitor viewing behaviour) and cameras (to monitor the surroundings) for providing quantifiable and understandable feedback to novice drivers. Furthermore, this new knowledge could also support driving instructors and examiners in ensuring safe drivers. This project will also generate necessary knowledge that would serve as a foundation for facilitating the transition to the training and assessment for drivers of automated vehicles.

Generic bovine kinetic modelling platform

The composition of diets and supplements given to bovine cattle are constantly evolving. These changes are driven by the social call for a more sustainable beef and dairy production, interests to influence the nutritional value of bovine products for human consumption, and to increase animal health. These adaptations can introduce (new) compounds in the beef and milk supply chain. Currently, the golden standard to study transfer of compounds from feed or veterinary medicine to cows and consequences for human health is performing animal studies, which are time consuming, costly and thus limited. Although animal studies are increasingly debated for ethical reasons, cows are still in the top 10 list of most used animals for animal experiments in Europe. There is, however, no widely applicable alternative modelling tool available to rapidly predict transfer of compounds, apart from individual components like cattle kinetic models and simple in vitro kinetic assays. Therefore, this project aims to develop a first-of-a-kind generic bovine kinetic modelling platform that predicts the transfer of compounds from medicine/supplements and feed to bovine tissues. This will provide new tools for the efficacy and safety evaluation of veterinary medicine and feed and facilitates a rapid evaluation of human health effects of bovine origin food products, thereby contributing to an increased safety in the cattle production chain and supporting product innovations, all without animal testing. This will be accomplished by integrating existing in silico and in vitro techniques into a generic bovine modelling platform and further developing state-of-the-art in vitro bovine organoid cell culturing systems. The platform can be used world-wide by stakeholders involved in the cattle industry (feed-/veterinary medicine industry, regulators, risk assessors). The project partners involve a strong combination of academia, knowledge institutes, small and medium enterprises, industry, branche-organisations and Proefdiervrij, all driven by their pursuit for animal free innovations.

Markiezenhof Qualitative (in part also funded by Digireal).

We had been involved in the redesign of the 4 Period Rooms of the Marquise Palace, also called the Palace of Secrets, in Bergen op Zoom. This design was based on the biography of a historical figure: Marie Anne van Arenberg, whose dramatic life was marked by secrets. Each of the 4 rooms represents a turning moment in Marie Anne’s story: the official marriage, the secret marriage and the betrayal, the dilemma and choice, with, in a final room, the epilogue. These different episodes are reflected in the way the rooms are furnished: the ballroom, the bedroom, the dining room. The Secret Marquise as design and exhibition has brought more visitors to the museum. As designers and researchers, however, we were interested in understanding more about this success, and, in particular, in understanding the visitors experience, both emotionally and sensorially at different moments/situations during the story-driven experience.In the fall of 2021, the visitors’ lived experience was evaluated using different approaches: a quantitative approach using biometric measurements to register people’s emotions during their visit, and a qualitative one consisting of a combination of observations, visual imagery, and interpretative phenomenological analysis (IPA).Qualitatively, our aim was to understand how respondents made sense of Marie Anne’s story in the way in which this was presented throughout the exhibition. We specifically looked at the personal context and frame of reference (e.g., previous experiences, connection to the visitor’s own life story, associations with other stories from other sources). In the design of the rooms, we used a combination of digital/interactive elements (such as a talking portrait, an interactive dinner table, an interactive family painting), and traditional physical objects (some 17th century original objects, some reproductions from that time). The second focal point of the study is to understand how these different elements lead the visitors experience.

Measuring communicative participation by PROMs in speech and language therapy

communicative participation, language disordersOBJECTIVE(S)/RESEARCH QUESTION(S) Speech and language therapists (SLTs) are the primary care professionals to treat language and communication disorders. Their treatment is informed by a variety of outcome measures. At present, diagnosis, monitoring of progress and evaluation are often based on performance-based and clinician-reported outcomes such as results of standardized speech, language, voice, or communication tests. These tests typically aim to capture how well the person can produce or understand language in a controlled situation, and therefore only provide limited insight in the person’s challenges in life. Performance measures do not incorporate the unobservable feelings such as a patient's effort, social embarrassment, difficulty, or confidence in communication. Nor do they address language and communication difficulties experienced by the person themselves, the impact on daily life or allow patients to set goals related to their own needs and wishes. The aim of our study is give our patients a voice and empower SLTs to incorporate their patient's perspective in planning therapy. We will Aangemaakt door ProjectNet / Generated by ProjectNet: 08-12-2020 12:072Subsidieaanvraag_digitaal / Grant Application_digitaalDossier nummer / Dossier number: 80-86900-98-041DEFINITIEFdevelop a valid and reliable patient-reported outcome measure that provides information on communicative participation of people with communication disorders and integrate this item bank in patient specific goal setting in speech and language therapy. Both the item bank and the goal setting method will be adapted in cocreation with patients to enable access for people with communication difficulties.STUDY DESIGN Mixed methods research design following the MRC guidance for process evaluation of complex interventions, using PROMIS methodology including psychometric evaluation and an iterative user-centered design with qualitative co-creation methods to develop accessible items and the goal setting method.RESEARCH POPULATION Children, adolescents and adults with speech, language, hearing, and voice disorders.OUTCOME MEASURES An online patient-reported outcome measure on communicative participation, the Communicative Participation Item Bank (CPIB), CPIB items that are accessible for people with language understanding difficulties, a communicative-participation person-specific goal setting method developed with speech and language therapists and patients and tested on usability and feasibility in clinical practice, and a course for SLTs explaining the use of the goal-setting method in their clinical reasoning process.RELEVANCE This study answers one of the prioritized questions in the call for SLTs to systematically and reliably incorporate the clients’ perspective in their daily practice to improve the quality of SLT services. At present patient reported outcomes play only a small role in speech and language therapy because 1) measures (PROMS) are often invalid, not implemented and unsuitable for clinical practice and 2) there is a knowledge gap in how to capture and interpret outcomes from persons with language disorders.

PhD study: Evaluation study of the community-based intervention JOGG in Drenthe