Stain-free nucleus identification in holographic learning flow cyto-tomography

Quantitative Phase Imaging (QPI) has gained popularity because it can avoid the staining step, which in some cases is difficult or impossible. However, QPI does not provide the well-known specificity to various parts of the cell (e.g., organelles, membrane). Here we show a novel computational segmentation method based on statistical inference that bridges the gap between the specificity of Fluorescence Microscopy (FM) and the label-free property of QPI techniques to identify the cell nucleus. We demonstrate application to stain-free cells reconstructed through the holographic learning and in flow cyto-tomography modality. In particular, by means of numerical simulations and two cancer cell lines, we demonstrate that the nucleus-like regions can be accurately distinguished within the stain-free tomograms. We show that our experimental results are consistent with confocal FM data and microfluidic cytofluorimeter outputs. This is a significant step towards extracting the three-dimensional (3D) intracellular specificity directly from the phase-contrast data in a typical flow cytometry configuration.

The Effects of Classes using Virtual Reality Simulations of the Hospital Environment on Knowledge of the Hospital Environment, Academic Self-efficacy, Learning Flow, Educational Satisfaction and Academic Achievement in Nursing Students

Purpose: This study examined the effects of virtual reality (VR)-based fundamental nursing education on nursing students’ knowledge of the hospital environment, academic self-efficacy, learning flow, educational satisfaction, and academic achievement.Methods: In total, 137 nursing students participated in this non-equivalent control group pretest-posttest study, with 69 and 68 in the experimental and control groups, respectively. Differences in the dependent variables between the two groups before and after the intervention were compared using the independent-sample t-test and Mann-Whitney U test.Results: The VR intervention group showed significantly higher knowledge of the hospital environment (t=3.88, p<.001), educational satisfaction (z=-3.82, p<.001), and academic achievement (z=-2.54, p=.011) than the control group.Conclusion: These findings indicate that VR-based education is an effective intervention for improving knowledge of the hospital environment, educational satisfaction, and academic achievement in nursing education.