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Purpose: To evaluate the efficacy of the virtual reality training simulator Eyesi to prepare surgeons for performing pars plana vitrectomies and its potential to predict the surgeons’ performance.
Methods: In a preparation phase, four participating vitreoretinal surgeons performed repeated simulator training with predefined tasks. If a surgeon was assigned to perform a vitrectomy for the management of complex retinal detachment after a surgical break of at least 60 hours it was randomly decided whether a warmup training on the simulator was required (n = 9) or not (n = 12). Performance at the simulator was measured using the built-in scoring metrics. The surgical performance was determined by two blinded observers who analyzed the video-recorded interventions. One of them repeated the analysis to check for intra-observer consistency. The surgical performance of the interventions with and without simulator training was compared. In addition, for the surgeries with simulator training, the simulator performance was compared to the performance in the operating room.
Results: Comparing each surgeon’s performance with and without warmup trainingshowed a significant effect of warmup training onto the final outcome in the operating room. For the surgeries that were preceeded by the warmup procedure, the performance at the simulator was compared with the operating room performance. We found that there is a significant relation. The governing factor of low scores in the simulator were iatrogenic retinal holes, bleedings and lens damage. Surgeons who caused minor damage in the simulation also performed well in the operating room.
Conclusions: Despite the large variation of conditions, the effect of a warmup training as well as a relation between the performance at the simulator and in the operating room was found with statistical significance. Simulator training is able to serve as a warmup to increase the average performance.
Abstract: The hallmarks of Alzheimer’s disease (AD) are characterized by cognitive decline and behavioral changes. The most prominent brain region affected by the progression of AD is the hippocampal formation. The pathogenesis involves a successive loss of hippocampal neurons accompanied by a decline in learning and memory consolidation mainly attributed to an accumulation of senile plaques. The amyloid precursor protein (APP) has been identified as precursor of Aβ-peptides, the main constituents of senile plaques. Until now, little is known about the physiological function of APP within the central nervous system. The allocation of APP to the proteome of the highly dynamic presynaptic active zone (PAZ) highlights APP as a yet unknown player in neuronal communication and signaling. In this study, we analyze the impact of APP deletion on the hippocampal PAZ proteome. The native hippocampal PAZ derived from APP mouse mutants (APP-KOs and NexCreAPP/APLP2-cDKOs) was isolated by subcellular fractionation and immunopurification. Subsequently, an isobaric labeling was performed using TMT6 for protein identification and quantification by high-resolution mass spectrometry. We combine bioinformatics tools and biochemical approaches to address the proteomics dataset and to understand the role of individual proteins. The impact of APP deletion on the hippocampal PAZ proteome was visualized by creating protein-protein interaction (PPI) networks that incorporated APP into the synaptic vesicle cycle, cytoskeletal organization, and calcium-homeostasis. The combination of subcellular fractionation, immunopurification, proteomic analysis, and bioinformatics allowed us to identify APP as structural and functional regulator in a context-sensitive manner within the hippocampal active zone network.
Author Summary: More than 20 years ago, the amyloid precursor protein (APP) was identified as the precursor protein of the Aβ peptide, the main component of senile plaques in brains affected by Alzheimer’s disease. However, little is known about the physiological function of amyloid precursor protein. Allocating APP to the proteome of the structurally and functionally dynamic presynaptic active zone highlights APP as a hitherto unknown player within the presynaptic network. The hippocampus is the most prominent brain region for learning and memory consolidation, and a vulnerable target for neurodegenerative disease, e. g. Alzheimer’s disease. Therefore, our experimental design is focused on the hippocampal neurotransmitter release site. Currently, the underlying mechanism of how APP acts within presynaptic networks is still elusive. Within the scope of this research article, we constructed a network of APP within the presynaptic active zone and how deletion of APP affects these individual networks. We combine bioinformatics tools and biochemical approaches to address the dataset provided by proteomics. Furthermore, we could unravel that APP executes regulatory functions within the synaptic vesicle cycle, cytoskeletal rearrangements and Ca2+-homeostasis. Taken together, our findings offer a new perspective on the physiological function of APP in the central nervous system and may provide a molecular link to the pathogenesis of Alzheimer’s disease.