Unpacking self-care: The connection between mindfulness, self-compassion, and self-care for counselors

With an escalating need for provision of mental health services to clients with serious and complex mental health concerns, it is vital that professional counselors find ways to prevent and address the adverse effects of working in stressful, emotionally demanding environments (Craig & Sprang, 2010). While self-care has been shown to mitigate compassion fatigue, self-care activities can be vague and difficult to prioritize. In this article, the authors present a review of the literature on mindfulness in mitigating compassion fatigue in counselors and propose a conceptualization of mindfulness as a gateway to self-care through self-compassion. Implications for research, counselor training, and professional development are discussed

Content-aware image restoration: Pushing the limits of fluorescence microscopy.

Fluorescence microscopy is a key driver of discoveries in the life sciences, with observable phenomena being limited by the optics of the microscope, the chemistry of the fluorophores, and the maximum photon exposure tolerated by the sample. These limits necessitate trade-offs between imaging speed, spatial resolution, light exposure, and imaging depth. In this work we show how content-aware image restoration based on deep learning extends the range of biological phenomena observable by microscopy. We demonstrate on eight concrete examples how microscopy images can be restored even if 60-fold fewer photons are used during acquisition, how near isotropic resolution can be achieved with up to tenfold under-sampling along the axial direction, and how tubular and granular structures smaller than the diffraction limit can be resolved at 20-times-higher frame rates compared to state-of-the-art methods. All developed image restoration methods are freely available as open source software in Python, FIJI, and KNIME