Matrix deposition is a critical step in obtaining reproducible and spatially representative matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging data. To date, few limited studies have examined the optimization of matrix spraying parameters for maximizing analyte extraction while minimizing analyte delocalization. Herein, we present a study using automated pneumatic spraying with a heated sample-holder tray to determine an optimized model for mouse whole kidney lipid imaging using a 2,5-dihydroxybenzoic acid matrix in which the solvent flow rate, nozzle velocity, and sample heating were optimized using a two-level factorial experimental design. Parameters examined to determine the optimum model include the number of analytes, the matrix crystal size, off tissue delocalization, the signal intensity, and spray time. Our results show that sample heating using a heated tray while spraying improves the MALDI imaging performance. This improvement is possible because higher solvent flow rates can be used in the pneumatic sprayer, allowing for better sample extraction, while sample delocalization is minimized due to sample heating.
BACKGROUND AND AIM:The transition of care at discharge from Pediatric Intensive Care Unit (PICU) is a critical process that can imply patients' and families' safety and experience with nursing care. The tool for the transition of care Transped Care was submitted to content validation with nine specialists and then incorporated to information technology as an application (App). The aim of this study was to evaluate the usability of the Transped care App.
METHOD:To evaluate the prototype Transped Care App the Delphi technique was implemented. The System Usability Scale (SUS) was used and the ten proposed statements measured by a Likert scale with five points. The sample consisted of five nurses, with experience on pediatric critical care; they simulated the use of the Transped Care App in clinical practice from December/2021 to January/2022. The answers were analyzed according to Nielsen's heuristics.
RESULTS:The results of the SUS application showed maximum usability analysis in the majority of the constructs measured, with exception of functions integration (40%), unnecessary complexity (20%), problems during use (20%) and confidence to use (20%). According to Nielsen's heuristics the analysis demonstrated that Transped Care App was perceived as easy to learn, efficient, easy to memorize, having the ability to minimize errors and being satisfactory to be used in the PICU transition process.
CONCLUSIONS:The usability analysis of Transped Care App was satisfactory providing support to improvements and to clinical application and impact analysis of Transped Care App during the transition of care from PICUs.
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