As part of an 8-week intervention study in Dutch nursing homes, we used video-analysis to observe the interaction of psychogeriatric participants with either the handler, the stimulus (dog or robot) or other clients during weekly dog, robot (RAI, robot assisted interventions) and control (human facilitator only) group sessions. Additionally, we measured the initiative of the handler to engage participants. Several baseline characteristics, including dementia severity, neuropsychiatric symptoms and medication usage, were recorded as possible confounders.Participant-handler interaction is increased in all three groups compared to a baseline of no interaction, while inter-client interaction is not. In the dog group participant-handler interaction scores are similar to participant-dog interaction scores, while in the robot group participant-handler interaction scores are significantly lower than participant-robot interaction scores. Handler initiative does not differ between the three groups.Our results suggest that a handler effect of AAI on social interaction in dementia care does exist and we hypothesize this effect is linked to the required fully embodied, mutual attunement between dog and handler and between dog-handler team and participants. This embodied interaction distinguishes AAI from RAI and when the required attunement is met, AAI can significantly increase the social interaction of people with dementia.
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Dogs are considered humans’ best friend, but this relationship is not all puppies and sunshine. Zoonoses, biting incidents, hereditary problems, and other welfare issues can threaten the relationship, especially when humans are not aware of them. Public opinion on dogs in the densely populated Netherlands was therefore examined. Dutch newspapers and Facebook were analyzed with frame analysis. A positive view of dogs seems predominant, followed by one that sees dogs as normal, while problems with dogs are less common. That dogs are considered close to humans is exemplified by the found norms that the needs of dogs must be met, that severe penalties must be applied when humans do not respect the welfare of dogs, and that dog keepers and conditions are responsible for problems with dogs. The image of the dog as ordinary may hinder public awareness, despite the norms that emphasize the importance of dog welfare.
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Zoonoses, biting incidents, hereditary problems, and other issues can threaten the welfare of both humans and dogs. The Dutch government and animal welfare organizations seem to have little effect in their campaigns to influence the behavior of (potential) dog keepers, who can experience dissonance when faced with these campaigns and use coping strategies to relieve the dissonance instead of changing their behavior. In this study, in focus group discussions, dog keepers with pedigree dogs, high-risk dogs, foreign shelter dogs, and dogs purchased at puppy farms shared their experiences with opinions on dogs and were confronted with negative opinions on their dogs. The data were analyzed using a coping strategies framework. Most coping strategies were found in all groups, but were used in response to different dilemmas, with different manifestations. These differences should be kept in mind when behavior change in dog keepers is opportune. Special attention should be given to differentiating target groups, as use of the detachment coping strategy suggests that boundaries might be set differently than expected. Broad attention on problems with and for dogs can address perceived dissonance and prompt behavior change. In dialogue with dog keepers, in influential campaigns and in policy formulation, the chances of success are greater if initiators are aware of the strategies that they may encounter.
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Every year the police are confronted with an ever increasing number of complex cases involving missing persons. About 100 people are reported missing every year in the Netherlands, of which, an unknown number become victims of crime, and presumed buried in clandestine graves. Similarly, according to NWVA, several dead animals are also often buried illegally in clandestine graves in farm lands, which may result in the spread of diseases that have significant consequences to other animals and humans in general. Forensic investigators from both the national police (NP) and NWVA are often confronted with a dilemma: speed versus carefulness and precision. However, the current forensic investigation process of identifying and localizing clandestine graves are often labor intensive, time consuming and employ classical techniques, such as walking sticks and dogs (Police), which are not effective. Therefore, there is an urgent request from the forensic investigators to develop a new method to detect and localize clandestine graves quickly, efficiently and effectively. In this project, together with practitioners, knowledge institutes, SMEs and Field labs, practical research will be carried out to devise a new forensic investigation process to identify clandestine graves using an autonomous Crime Scene Investigative (CSI) drone. The new work process will exploit the newly adopted EU-wide drone regulation that relaxes a number of previously imposed flight restrictions. Moreover, it will effectively optimize the available drone and perception technologies in order to achieve the desired functionality, performance and operational safety in detecting/localizing clandestine graves autonomously. The proposed method will be demonstrated and validated in practical operational environments. This project will also make a demonstrable contribution to the renewal of higher professional education. The police and NVWA will be equipped with operating procedures, legislative knowledge, skills and technological expertise needed to effectively and efficiently performed their forensic investigations.
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).
The missing link in diagnostic testing for rheumatoid arthritis (RA) is an agglutination assay, easy to perform and dedicated to decentralized testing. Approximately 75% of RA patients produce autoantibodies to citrullinated proteins (ACPA), which can be detected using an agglutination-based diagnostic test. Such a diagnostic test will be cheaper, less laborious and faster than current tests and does not require sophisticated equipment. Novio Catalpa is developing this alternative test for ACPA in collaboration with Radboud University. To develop this test, specifically tagged and citrullinated nanobodies are needed, but the production is still challenging. Current methods for the production of ACPA diagnostics involve chemical synthesis, in which a variety of toxic chemicals are used in each step. The alternative assay involves nanobodies fused with RA-biomarker target entities, which can be completely produced by ‘green synthesis’ in the yeast Pichia pastoris using the expertise of HAN BioCentre. The yeast P. pastoris has proven to be able to produce nanobodies and is a fast and cost-effective platform that often results in high protein yields. Goal of the project is therefore to determine the feasibility and best green route to produce purified nanobodies tagged with citrullinated ACPA targets that can be used for developing an agglutination assay for RA. P. pastoris does not produce endogenous PAD enzymes which are needed for citrullination of the nanobodies in order to be able to use it in a RA agglutination test. Therefore, PAD enzymes from other sources need to be tested and applied. The project results will be directly used by Novio Catalpa to further develop the innovative test for RA. This project will contribute to and finally result in a single-step agglutination assay suitable for both point-of-care testing and automation in clinical laboratories.