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
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.
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Detecting practical problems of persons with dementia (PwD) experience at home, and advising them on solutions to facilitate aging in place are complex and challenging tasks for nurses and case managers. In this two group randomized, controlled laboratory experiment, the efficacy of a decision support application aiming to increase nurses' and case managers' confidence in clinical judgment and decision-making was tested. The participants (N = 67) assessed a case of a PwD within the problem domains: self-reliance, safety and informal care, and provided suggestions for possible solutions. Participants used either their regular procedure with (intervention group) or without the App (control group) to conduct these tasks. No statistically significant difference was found on the primary outcome measure, the overall level of confidence. However, nurses and case managers highly recommended use of the App in practice. To explain these results, more research on the potential added value of the App is needed.
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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.
