Gregory McNally (gendercrack0)

Given this, Raman spectroscopy can reliably distinguish the early characterization of DR in addition to providing intrinsic key molecules that is sensitive to identify the early disease progression.An accurate and automated tissue segmentation algorithm for retinal optical coherence tomography (OCT) images is crucial for the diagnosis of glaucoma. However, due to the presence of the optic disc, the anatomical structure of the peripapillary region of the retina is complicated and is challenging for segmentation. To address this issue, we develop a novel graph convolutional network (GCN)-assisted two-stage framework to simultaneously label the nine retinal layers and the optic disc. Specifically, a multi-scale global reasoning module is inserted between the encoder and decoder of a U-shape neural network to exploit anatomical prior knowledge and perform spatial reasoning. We conduct experiments on human peripapillary retinal OCT images. We also provide public access to the collected dataset, which might contribute to the research in the field of biomedical image processing. The Dice score of the proposed segmentation network is 0.820 ± 0.001 and the pixel accuracy is 0.830 ± 0.002, both of which outperform those from other state-of-the-art techniques.Light-sheet microscopy has become indispensable for imaging developing organisms, and imaging from multiple directions (views) is essential to improve its spatial resolution. We combine multi-view light-sheet microscopy with microfluidics using adaptive optics (deformable mirror) which corrects aberrations introduced by the 45o-tilted glass coverslip. The optimal shape of the deformable mirror is computed by an iterative algorithm that optimizes the point-spread function in two orthogonal views. Simultaneous correction in two optical arms is achieved via a knife-edge mirror that splits the excitation path and combines the detection paths. Our design allows multi-view light-sheet microscopy with microfluidic devices for precisely controlled experiments and high-content screening.Phase-transition nanoparticles have been identified as effective theragnostic, anti-cancer agents. However, non-selective delivery of these agents results in inaccurate diagnosis and insufficient treatment. check details In this study, we report on the development of targeted phase-transition polymeric nanoparticles (NPs) for the imaging and treatment of breast cancer cell lines over-expressing human epidermal growth factor receptor 2 (HER2). These NPs contain a perfluorohexane liquid interior and gold nanorods (GNRs) stabilized by biodegradable and biocompatible copolymer PLGA-PEG. Water-insoluble therapeutic drug Paclitaxel (PAC) and fluorescent dye were encapsulated into the PLGA shell. The NP surfaces were conjugated to HER2-binding agent, Herceptin, to actively target HER2-positive cancer cells. We evaluated the potential of using these NPs as a photoacoustic contrast agent. The efficacy of cancer cell treatment by laser-induced vaporization and stimulated drug release were also investigated. The results showed that our synthesized PLGA-PEG-GNRs (mean diameter 285 ± 29 nm) actively targeted HER2 positive cells with high efficacy. The laser-induced vaporization caused more damage to the targeted cells versus PAC-only and negative controls. This agent may provide better diagnostic imaging and therapeutic potential than current methods for treating HER2-positive breast cancer.We present a significant step toward ultrahigh-resolution, motion-insensitive characterization of vascular dynamics. Optical coherence tomography angiography (OCTA) is an invaluable diagnostic technology for non-invasive, label-free vascular imaging in vivo. However, since it relies on detecting moving cells from consecutive scans, high-resolution OCTA is susceptible to tissue motion, which imposes challenges in resolving and quantifying small vessels. We developed a novel OCTA technique named ultrahigh-resolution factor angiograph