Browsing by Author "Wu, Jimin"

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    Associations of meaning of illness with psychosocial, clinical, and immunological characteristics in patients with Leptomeningeal metastasis
    (Elsevier, 2021) Walker, Julie G.; Armstrong, Terri S.; O'Brien, Barbara J.; Gilbert, Mark R.; Casarez, Rebecca L.; Fagundes, Christopher; Heijnen, Cobi J.; Andersen, Clark R.; Yuan, Ying; Wu, Jimin; LoBiondo-Wood, Geri
    Background Leptomeningeal metastasis (LM) creates symptoms related to both the disease within the nervous system and treatment toxicities. Biologic processes, such as inflammation and behavioral processes, such as the meaning ascribed to illness (Meaning of Illness: MoI), can impact physical and psychosocial symptoms. The aim of this study was to understand the relationships among MoI, physical and psychosocial symptoms, and inflammation in patients with LM. Methods Thirty enrolled participants completed the MD Anderson Symptom Inventory-Brain Tumor with spine experimental symptoms added. Meaning of illness, quality of life (QoL), and depression were captured by validated instruments. Interleukin (IL)-6 and tumor necrosis factor (TNF)-α in serum and cerebrospinal fluid (CSF) were measured by ELISA. Correlations were performed to assess relationships among the variables. Results Participants were primarily white (73%), female (63%). Median age was 54 years (34–83). Breast (50%) and lung (20%) were most common diagnosis. Higher MoI scores were associated with better QoL (p < .01) and fewer depressive symptoms (p < .01). All CSF samples contained IL-6 and all but one sample had elevated IL-6. Higher levels of IL-6 in the CSF were associated with greater symptom burden (p < .01) and interference of symptoms in daily life (p = .02) but not MoI. Conclusions MoI was associated with QoL and depression. High levels of IL-6 in the CSF were associated with more severe symptoms. This study provides the groundwork for future research, including interventional studies to improve QoL in patients with LM.
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    Real-time, deep-learning aided lensless microscope
    (Optica Publishing Group, 2023) Wu, Jimin; Boominathan, Vivek; Veeraraghavan, Ashok; Robinson, Jacob T.; Bioengineering; Electrical and Computer Engineering; Computer Science
    Traditional miniaturized fluorescence microscopes are critical tools for modern biology. Invariably, they struggle to simultaneously image with a high spatial resolution and a large field of view (FOV). Lensless microscopes offer a solution to this limitation. However, real-time visualization of samples is not possible with lensless imaging, as image reconstruction can take minutes to complete. This poses a challenge for usability, as real-time visualization is a crucial feature that assists users in identifying and locating the imaging target. The issue is particularly pronounced in lensless microscopes that operate at close imaging distances. Imaging at close distances requires shift-varying deconvolution to account for the variation of the point spread function (PSF) across the FOV. Here, we present a lensless microscope that achieves real-time image reconstruction by eliminating the use of an iterative reconstruction algorithm. The neural network-based reconstruction method we show here, achieves more than 10000 times increase in reconstruction speed compared to iterative reconstruction. The increased reconstruction speed allows us to visualize the results of our lensless microscope at more than 25 frames per second (fps), while achieving better than 7 µm resolution over a FOV of 10 mm2. This ability to reconstruct and visualize samples in real-time empowers a more user-friendly interaction with lensless microscopes. The users are able to use these microscopes much like they currently do with conventional microscopes.