The non-selective beta-blocker timolol has shown promising evidence for healing chronic, recalcitrant wounds, improving scar cosmesis, and expediting the completion of secondary intention. The purpose of our pilot study is to use clinical imaging, two-photon excitement fluorescence (TPF) and second harmonic generation (SHG) microscopy to evaluate the temporal and molecular effects of timolol vs. normal saline in Sprague-Dawley rats traumatized by 5-millimeter dermal punch biopsy. Initial findings suggest timolol delays wound contraction, but advanced imaging techniques may reveal novel collagenous or vascular mechanisms by which timolol is affecting acute wound healing.
In the recent studies of cartilage imaging with nonlinear optical microscopy, we discovered that autofluorescence of chondrocytes provided useful information for the viability assessment of articular cartilage. However, one of the hurdles to apply this technology in research or clinical applications is the lack of image processing tools that can perform automated and cell-based analysis. In this report, we present our recent effort in the cell segmentation using deep learning algorithms with the second harmonic generation images. Two traditional segmentation methods, adaptive threshold, and watershed, were used to compare the outcomes of different methods. We found that deep learning algorithms did not show a significant advantage over the traditional methods. Once the cellular area is determined, the viability index is calculated as the intensity ratio between two autofluorescence channels in the cellular area. We found the viability index correlated well with the chondrocyte viability. Again, deep learning segmentation did not show a significant difference from the traditional segmentation methods in terms of the correlation.
Covering the ends of long bones, articular cartilage provides a smooth, lubricated surface to absorb impact and distribute loads during movement so that underlying bone is protected. This function is facilitated by a complex and well-organized extracellular matrix (ECM). Being the only cell type in articular cartilage, chondrocytes are responsible for maintaining the homeostasis of the cartilage ECM; as such, the viability of chondrocytes is a critical parameter to reflect the quality of the cartilage. Most prevalent cell viability assays rely on dye staining and thereby cannot be performed for longitudinal monitoring or in-vivo assessment. Here we demonstrate that two-photon autofluorescence (TPAF) microscopy distinguishes live cells from dead cells in intact ex-vivo cartilage tissues, which provides a non-invasive method to assess cell viability. In our study, the endogenous fluorophores such as nicotinamide adenine dinucleotide (phosphate) (NAD(P)H) and flavin adenine dinucleotide (FAD) were used to image chondrocytes in cartilages on rat tibia condyles immediately after harvesting. Second harmonic generation (SHG) imaging was also performed to examine the integrity of the extracellular and pericellular matrix. On the same tissue, the cell viability assay with Calcein-AM and Ethidium homodimer-1 (EthD-1) labeling was used as a gold standard to identify live or dead cells. We found that live cells presented stronger NAD(P)H fluorescence than dead cells in general and were readily identified if pseudo colors were used for showing two-channel images. Owing to its non-destructive nature, this method holds the potential value in assessing cell viability of engineered or living tissues without dye labeling.
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