Deep Segmentation of OCTA for Evaluation and Association of Changes of Retinal Microvasculature with Alzheimer’s Disease and Mild Cognitive Impairment

BackgroundOptical coherence tomography angiography (OCTA) enables fast and non-invasive high-resolution imaging of retinal microvasculature and is suggested as a potential tool in the early detection of retinal microvascular changes in Alzheimer's Disease (AD). We developed a standardised OCTA analysis framework and compared their extracted parameters among controls and AD/mild cognitive impairment (MCI) in a cross-section study.MethodsWe defined and extracted geometrical parameters of retinal microvasculature at different retinal layers and in the foveal avascular zone (FAZ) from segmented OCTA images obtained using well-validated state-of-the-art deep learning models. We studied these parameters in 158 subjects (62 healthy control, 55 AD and 41 MCI) using logistic regression to determine their potential in predicting the status of our subjects.ResultsIn the AD group, there was a significant decrease in vessel area and length densities in the inner vascular complexes (IVC) compared with controls. The number of vascular bifurcations in AD is also significantly lower than that of healthy people. The MCI group demonstrated a decrease in vascular area, length densities, vascular fractal dimension and the number of bifurcations in both the superficial vascular complexes (SVC) and the IVC compared with controls. A larger vascular tortuosity in the IVC, and a larger roundness of FAZ in the SVC, can also be observed in MCI compared with controls.ConclusionOur study demonstrates the applicability of OCTA for the diagnosis of AD and MCI, and provides a standard tool for future clinical service and research. Biomarkers from retinal OCTA images can provide useful information for clinical decision-making and diagnosis of AD and MCI

ROSE: A Retinal OCT-Angiography Vessel Segmentation Dataset and New Model

Optical Coherence Tomography Angiography (OCTA) is a non-invasive imaging technique that has been increasingly used to image the retinal vasculature at capillary level resolution. However, automated segmentation of retinal vessels in OCTA has been under-studied due to various challenges such as low capillary visibility and high vessel complexity, despite its significance in understanding many vision-related diseases. In addition, there is no publicly available OCTA dataset with manually graded vessels for training and validation of segmentation algorithms. To address these issues, for the first time in the field of retinal image analysis we construct a dedicated Retinal OCTA SEgmentation dataset (ROSE), which consists of 229 OCTA images with vessel annotations at either centerline-level or pixel level. This dataset with the source code has been released for public access to assist researchers in the community in undertaking research in related topics. Secondly, we introduce a novel split-based coarse-to-fine vessel segmentation network for OCTA images (OCTA-Net), with the ability to detect thick and thin vessels separately. In the OCTA-Net, a split-based coarse segmentation module is first utilized to produce a preliminary confidence map of vessels, and a split-based refined segmentation module is then used to optimize the shape/contour of the retinal microvasculature. We perform a thorough evaluation of the state-of-the-art vessel segmentation models and our OCTA-Net on the constructed ROSE dataset. The experimental results demonstrate that our OCTA-Net yields better vessel segmentation performance in OCTA than both traditional and other deep learning methods. In addition, we provide a fractal dimension analysis on the segmented microvasculature, and the statistical analysis demonstrates significant differences between the healthy control and Alzheimer's Disease group. This consolidates that the analysis of retinal microvasculature may offer a new scheme to study various neurodegenerative diseases

Single-cell RNA sequencing reveals cancer stem-like cells and dynamics in tumor microenvironment during cholangiocarcinoma progression

Cholangiocarcinoma is a malignancy of the bile ducts that is driven by activities of cancer stem-like cells and characterized by a heterogeneous tumor microenvironment. To better understand the transcriptional profiles of cancer stem-like cells and dynamics in the tumor microenvironment during the progression of cholangiocarcinoma, we performed single-cell RNA analysis on cells collected from three different timepoints of tumorigenesis in a YAP/AKT mouse model. Bulk RNA sequencing data from TCGA (The Cancer Genome Atlas program) and ICGC cohorts were used to verify and support the finding. In vitro and in vivo experiments were performed to assess the stemness of cancer stem-like cells. We identified Tm4sf1high malignant cells as cancer stem-like cells. Across timepoints of cholangiocarcinoma formation in YAP/AKT mice, we found dynamic change in cancer stem-like cell/stromal/immune cell composition. Nevertheless, the dynamic interaction among cancer stem-like cells, immune cells, and stromal cells at different timepoints was elaborated. Collectively, these data serve as a useful resource for better understanding cancer stem-like cell and malignant cell heterogeneity, stromal cell remodeling, and immune cell reprogramming. It also sheds new light on transcriptomic dynamics during cholangiocarcinoma progression at single-cell resolution

Performance and characterization of the SPT-3G digital frequency-domain multiplexed readout system using an improved noise and crosstalk model

The third-generation South Pole Telescope camera (SPT-3G) improves upon its predecessor (SPTpol) by an order of magnitude increase in detectors on the focal plane. The technology used to read out and control these detectors, digital frequency-domain multiplexing (DfMUX), is conceptually the same as used for SPTpol, but extended to accommodate more detectors. A nearly 5× expansion in the readout operating bandwidth has enabled the use of this large focal plane, and SPT-3G performance meets the forecasting targets relevant to its science objectives. However, the electrical dynamics of the higher-bandwidth readout differ from predictions based on models of the SPTpol system due to the higher frequencies used and parasitic impedances associated with new cryogenic electronic architecture. To address this, we present an updated derivation for electrical crosstalk in higher-bandwidth DfMUX systems and identify two previously uncharacterized contributions to readout noise, which become dominant at high bias frequency. The updated crosstalk and noise models successfully describe the measured crosstalk and readout noise performance of SPT-3G. These results also suggest specific changes to warm electronics component values, wire-harness properties, and SQUID parameters, to improve the readout system for future experiments using DfMUX, such as the LiteBIRD space telescope

Effect of a pressure-equalizing film on the trajectory and attitude robustness of an underwater vehicle considering the uncertainty of the platform velocity

A vertically moving underwater vehicle with an air film attached to its exterior can significantly weaken the hydrodynamic disturbances caused by launch conditions. To quantify the ability of a pressure-equalizing film to improve the trajectory and attitude robustness of vehicles under an uncertain platform velocity input, the response surface model of nonintrusive polynomial chaos was built based on sample spacing constructed with a nested sparse grid-based stochastic collocation method. The results indicate the uncertainty bars of the horizontal displacement exhibit an expanding-contracting-expanding pattern with a ‘spindle’ shape as the vehicle moves. In contrast, the horizontal velocity presents an ‘hourglass’ shape. Additionally, the horizontal velocity and the pitching angular velocity of the vehicle are quite sensitive to the uncertainty of the platform velocity, and the large mean value and uncertainty of these factors will statistically worsen the trajectory and attitude of the vehicle. Implementation of an exhaust during the water-emerging process can weaken the horizontal motion and pitching rotation of a vehicle, as well as the relevant uncertainty. This is attributed to a generated pressure-equalizing region with a low uncertainty. Thus, an exhaust is urgently needed in the water-emerging process of these vehicles

Immunotherapy of hepatocellular carcinoma with infection of hepatitis B or C virus

Hepatocellular carcinoma (HCC) has one of highest mortalities globally amongst cancers, but has limited therapeutic options once in the advanced stage. Hepatitis B or C virus infection are the most common drivers for HCC carcinogenesis, triggering chronic liver inflammation and adding to the complexity of the immune microecosystem of HCC. The emergence of immunotherapy has afforded a new avenue of therapeutic options for patients with advanced HCC with a history of hepatitis B or C virus infection. This article reviews the change of immunity elicited by hepatitis B or C virus infection, the immune feature of HCC, and the clinical evidence for immunotherapy in advanced HCC and discusses future directions in this field

Effects of Morphology and Temperature on the Tensile Characteristics of Carbon Nitride Nanothreads

Very recently synthesized carbon nitride nanothreads (CNNTs) by compressing crystalline pyridine show outperformance in chemical and physical properties over diamond nanothreads. Here, using first-principle based ReaxFF molecular dynamics (MD) simulations, a comprehensive investigation on mechanical characteristics of seven experimentally synthesized CNNTs is performed. All the CNNTs exhibit unique tensile properties that change with molecular morphology, atomic arrangement and the distribution of nitrogen in the skeleton. CNNTs with more effective loading covalent bonds at cross-sections are more mechanically robust. Surprisingly, tiny CNNT with periodic unit structures of 5462-cage shows extreme ductility because of formation of linear polymer via 4-step dissociation-and-reformation of bonds at extremely low temperature of 1 to 15 K, however, it yields by brittle failure at one cross-section with low ductility at higher temperature, similar to other CNNTs at different temperatures, which offers a feasible way to design a kind of lightweight material that can be used in ultra-low temperature conditions, for example, harsh deep space environment. Results also show that temperature significantly affects the fracture stress and rupture strain but not the effective stiffness. Analysis of atomic bond orders and bond lengthening reveals that the unique nonlinear elasticity of CNNTs is attributed to the occurrence of local bond transformations. This study provides physical insights into the tensile characteristics of CNNTs for design and application of the CNNT-based nanostructures as multifunctional materials