BackgroundGait analysis has been used for decades to quantify knee function in patients with knee osteoarthritis; however, it is unknown whether and to what extent inter-laboratory differences affect the comparison of gait data between studies. Therefore, the aim of this study was to perform an inter-laboratory comparison of knee biomechanics and muscle activation patterns during gait of patients with knee osteoarthritis.MethodsKnee biomechanics and muscle activation patterns from patients with knee osteoarthritis were analyzed, previously collected at Dalhousie University (DAL: n = 55) and Amsterdam UMC, VU medical center (VUmc: n = 39), using their in-house protocols. Additionally, one healthy male was measured at both locations. Both direct comparisons and after harmonization of components of the protocols were made. Inter-laboratory comparisons were quantified using statistical parametric mapping analysis and discrete gait parameters.ResultsThe inter-laboratory comparison showed offsets in the sagittal plane angles, moments and frontal plane angles, and phase shifts in the muscle activation patterns. Filter characteristics, initial contact identification and thigh anatomical frame definitions were harmonized between the laboratories. After this first step in protocol harmonization, the offsets in knee angles and sagittal plane moments remained, but the inter-laboratory comparison of the muscle activation patterns improved.ConclusionsInter-laboratory differences obstruct valid comparisons of gait datasets from patients with knee osteoarthritis between gait laboratories. A first step in harmonization of gait analysis protocols improved the inter-laboratory comparison. Further protocol harmonization is recommended to enable valid comparisons between labs, data-sharing and multicenter trials to investigate knee function in patients with knee osteoarthritis.
MULTIFILE
Numerous laboratory-based studies recorded eye movements in participants with varying expertise when watching video projections in the lab. Although research in the lab offers the advantage of internal validity, reliability and ethical considerations, ecological validity is often questionable. Therefore the current study compared visual search in 13 adult cyclists, when cycling a real bicycle path and while watching a film clip of the same road. Dwell time towards five Areas of Interest (AOIs) is analysed. Dwell time (%) in the lab and real-life was comparable only for the low quality bicycle path. Both in real-life and the lab, gaze is predominantly driven towards the road. Since gaze behaviour in the lab and real-life tends to be comparable with increasing task-complexity (road quality), it is concluded that under certain task constraints laboratory experiments making use of video clips might provide valuable information regarding gaze behaviour in real-life.
DOCUMENT
A large, recently published, inter-laboratory study by the ReAct group has shown that there is considerable variability in DNA recovery that exists between forensic laboratories. The presence of this inter-laboratory variability presents issues when one laboratory wishes to carry out an evaluation and needs to use the data produced by another laboratory. One option proposed by the ReAct group is for laboratories to carry out a calibration exercise so that appropriate adjustments between laboratories can be made. This will address some issues, but leave others unanswered, such as how to make use of the decades of transfer and persistence data that has already been published. In this work we present a method to utilise data produced in other laboratories (whether it provides DNA amounts or a probability of transfer) that takes into account inter-laboratory variability within an evaluation. This will allow evaluations to continue, without calibration data, and ensures that the strength of findings is appropriately represented. In this paper we discuss complicating factors with the various ways in which previous data has been reported, and their limitations in supporting probability assignments when carrying out an evaluation. We show that a combination of producing calibration information for new data (as suggested by the ReAct group) and development of strategies where calibration data is not available will provide the best way forward in the field of evaluations given activities.
DOCUMENT
The BECEE initiative represents a transformative collaboration between four leading European HEIs—Hanze University of Applied Sciences (HUAS), Zurich University of Applied Sciences (ZHAW), South East Technological University (SETU), and Universiteti "Aleksandër Moisiu" Durrës (UAMD). Our consortium embodies the essence of BECEE and the EIT Knowledge Triangle Model because it also comprises of 4 industry partners (KPN, Eindhoven, The Netherlands, Innofuse, Zurich, Switzerland, Dungarvan Enterprise Centre, South East, Ireland, and Linda Laboratory, Durrës, Albania) bringing together partners from education, research, and business who are equally committed to collaborate on innovation action plans to fostering balanced collaborative entrepreneurship ecosystems in our respective regions. This consortium, therefore, is strategically designed to pool diverse strengths, creating a synergetic force for innovation and entrepreneurship that transcends the capabilities of any single organisation.
An important line of research within the Center of Expertise HAN BioCentre is the development of the nematode Caenorhabditis elegans as an animal testing replacement organism. In the context of this, us and our partners in the research line Elegant! (project number. 2014-01-07PRO) developed reliable test protocols, data analysis strategies and new technology, to determine the expected effects of exposure to specific substances using C. elegans. Two types of effects to be investigated were envisaged, namely: i) testing of possible toxicity of substances to humans; and ii) testing for potential health promotion of substances for humans. An important deliverable was to show that the observed effects in the nematode can indeed be translated into effects in humans. With regard to this aspect, partner Preventimed has conducted research in obesity patients during the past year into the effect of a specific cherry extract that was selected as promising on the basis of the study with C. elegans. This research is currently being completed and a scientific publication will have to be written. The Top Up grant is intended to support the publication of the findings from Elegant! and also to help design experimental protocols that enable students to become acquainted with alternative medical testing systems to reduce the use of laboratory animals during laboratory training.
Cell-based production processes in bioreactors and fermenters need to be carefully monitored due to the complexity of the biological systems and the growth processes of the cells. Critical parameters are identified and monitored over time to guarantee product quality and consistency and to minimize over-processing and batch rejections. Sensors are already available for monitoring parameters such as temperature, glucose, pH, and CO2, but not yet for low-concentration substances like proteins and nucleic acids (DNA). An interesting critical parameter to monitor is host cell DNA (HCD), as it is considered an impurity in the final product (downstream process) and its concentration indicates the cell status (upstream process). The Molecular Biosensing group at the Eindhoven University of Technology and Helia Biomonitoring are developing a sensor for continuous biomarker monitoring, based on Biosensing by Particle Motion. With this consortium, we want to explore whether the sensor is suitable for the continuous measurement of HCD. Therefore, we need to set-up a joint laboratory infrastructure to develop HCD assays. Knowledge of how cells respond to environmental changes and how this is reflected in the DNA concentration profile in the cell medium needs to be explored. This KIEM study will enable us to set the first steps towards continuous HCD sensing from cell culture conditions controlling cell production processes. It eventually generates input for machine learning to be able to automate processes in bioreactors and fermenters e.g. for the production of biopharmaceuticals. The project entails collaboration with new partners and will set a strong basis for subsequent research projects leading to scientific and economic growth, and will also contribute to the human capital agenda.