Immune signatures underlying post-acute COVID-19 lung sequelae.

Severe coronavirus disease 2019 (COVID-19) pneumonia survivors often exhibit long-term pulmonary sequelae, but the underlying mechanisms or associated local and systemic immune correlates are not known. Here, we have performed high-dimensional characterization of the pathophysiological and immune traits of aged COVID-19 convalescents, and correlated the local and systemic immune profiles with pulmonary function and lung imaging. We found that chronic lung impairment was accompanied by persistent respiratory immune alterations. We showed that functional severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)­specific memory T and B cells were enriched at the site of infection compared with those of blood. Detailed evaluation of the lung immune compartment revealed that dysregulated respiratory CD8+ T cell responses were associated with the impaired lung function after acute COVID-19. Single-cell transcriptomic analysis identified the potential pathogenic subsets of respiratory CD8+ T cells contributing to persistent tissue conditions after COVID-19. Our results have revealed pathophysiological and immune traits that may support the development of lung sequelae after SARS-CoV-2 pneumonia in older individuals, with implications for the treatment of chronic COVID-19 symptoms.

[Behavioral and structural prevention of skin cancer : Implementation and effectiveness]. / Verhaltens- und Verhältnisprävention Hautkrebs : Umsetzung und Effektivität.

BACKGROUND: Ultraviolet radiation (UV)-induced malignancies, especially skin cancer, have continued to increase for decades. The main cause is natural and artificial UV radiation. The affected persons and the health care system are heavily burdened. The situation threatens to worsen, as climate change could lead to an increase in UV radiation exposure of the population and, thus, the risk of UV-related cancer in Germany as well. The prevention of UV-related diseases is, therefore, a health and radiation protection objective that needs to be considered. OBJECTIVE: Necessary and appropriate prevention measures for the precaution of UV-related cancer are presented. MATERIALS AND METHODS: The currently recommended and applied primary behavioral and structural preventive measures and potential, prevention-related relief for the health care system are examined and summarized. RESULTS: Numerous behavioral and structural preventive measures are already being applied. Sustainably designed, multicomponent and personalized behavioral preventive measures in combination with structural prevention modules are effective and have a high economic and health-related benefit. The use of modern media and multimedia measures is recommended. CONCLUSION: Structural prevention measures in addition to behavioral measures enable a reduction of the cancer risk caused by UV radiation. The aim must be to establish these measures nationwide for the entire population.

Evaluation of Fast-Forward Video Visualization.

We evaluate and compare video visualization techniques based on fast-forward. A controlled laboratory user study (n = 24) was conducted to determine the trade-off between support of object identification and motion perception, two properties that have to be considered when choosing a particular fast-forward visualization. We compare four different visualizations: two representing the state-of-the-art and two new variants of visualization introduced in this paper. The two state-of-the-art methods we consider are frame-skipping and temporal blending of successive frames. Our object trail visualization leverages a combination of frame-skipping and temporal blending, whereas predictive trajectory visualization supports motion perception by augmenting the video frames with an arrow that indicates the future object trajectory. Our hypothesis was that each of the state-of-the-art methods satisfies just one of the goals: support of object identification or motion perception. Thus, they represent both ends of the visualization design. The key findings of the evaluation are that object trail visualization supports object identification, whereas predictive trajectory visualization is most useful for motion perception. However, frame-skipping surprisingly exhibits reasonable performance for both tasks. Furthermore, we evaluate the subjective performance of three different playback speed visualizations for adaptive fast-forward, a subdomain of video fast-forward.

Visualization of Astronomical Nebulae via Distributed Multi-GPU Compressed Sensing Tomography.

The 3D visualization of astronomical nebulae is a challenging problem since only a single 2D projection is observable from our fixed vantage point on Earth. We attempt to generate plausible and realistic looking volumetric visualizations via a tomographic approach that exploits the spherical or axial symmetry prevalent in some relevant types of nebulae. Different types of symmetry can be implemented by using different randomized distributions of virtual cameras. Our approach is based on an iterative compressed sensing reconstruction algorithm that we extend with support for position-dependent volumetric regularization and linear equality constraints. We present a distributed multi-GPU implementation that is capable of reconstructing high-resolution datasets from arbitrary projections. Its robustness and scalability are demonstrated for astronomical imagery from the Hubble Space Telescope. The resulting volumetric data is visualized using direct volume rendering. Compared to previous approaches, our method preserves a much higher amount of detail and visual variety in the 3D visualization, especially for objects with only approximate symmetry.

Visual Analytics Methodology for Eye Movement Studies.

Eye movement analysis is gaining popularity as a tool for evaluation of visual displays and interfaces. However, the existing methods and tools for analyzing eye movements and scanpaths are limited in terms of the tasks they can support and effectiveness for large data and data with high variation. We have performed an extensive empirical evaluation of a broad range of visual analytics methods used in analysis of geographic movement data. The methods have been tested for the applicability to eye tracking data and the capability to extract useful knowledge about users' viewing behaviors. This allowed us to select the suitable methods and match them to possible analysis tasks they can support. The paper describes how the methods work in application to eye tracking data and provides guidelines for method selection depending on the analysis tasks.

Visualizing the Evolution and Interaction of Vortices and Shear Layers in Time-Dependent 3D Flow.

In this paper, we present a visualization and tracking system for coherent structures. For this purpose, we propose to consider shear stress-the stretching and shear of particles inside a flow-in vortex dynamics. Based on a discussion and comparison of recent methods for computing shear stress, we introduce visualization techniques in order to provide a representation of shear layers according to their physical interpretation. This paper contributes a combination of theory in fluid mechanics and the corresponding visualization: 1) shear layer criteria are assessed according to how well they can be combined with common vortex identification criteria; 2) sheets of maximal shear are introduced as an appropriate visual representation of shear layers; 3) a visualization method is described for simultaneous tracking of vortices and shear layers as well as their interaction; and 4) the relevance of shear layers in vortex dynamics is demonstrated by means of several examples. We have implemented these new techniques in an interactive visualization system for time-dependent 3D flow. The system is used by fluid mechanics experts in their research of shear-vortex interaction.

The role of color in high-level vision.

Traditional theories of object recognition have emphasized the role of shape information in high-level vision. However, the accumulating behavioral, neuroimaging and neuropsychological evidence indicates that the surface color of an object affects its recognition. In this article, we discuss the research that examines the conditions under which color influences the operations of high-level vision and the neural substrates that might mediate these operations. The relationship between object color and object recognition is summarized in the 'Shape+Surface' model of high-level vision.