Genetic replacement of surfactant protein-C reduces respiratory syncytial virus induced lung injury

BACKGROUND: Individuals with deficiencies of pulmonary surfactant protein C (SP-C) develop interstitial lung disease (ILD) that is exacerbated by viral infections including respiratory syncytial virus (RSV). SP-C gene targeted mice (Sftpc -/-) lack SP-C, develop an ILD-like disease and are susceptible to infection with RSV. METHODS: In order to determine requirements for correction of RSV induced injury we have generated compound transgenic mice where SP-C expression can be induced on the Sftpc -/- background (SP-C/Sftpc -/-) by the administration of doxycycline (dox). The pattern of induced SP-C expression was determined by immunohistochemistry and processing by Western blot analysis. Tissue and cellular inflammation was measured following RSV infection and the RSV-induced cytokine response of isolated Sftpc +/+ and -/- type II cells determined. RESULTS: After 5 days of dox administration transgene SP-C mRNA expression was detected by RT-PCR in the lungs of two independent lines of bitransgenic SP-C/Sftpc -/- mice (lines 55.3 and 54.2). ProSP-C was expressed in the lung, and mature SP-C was detected by Western blot analysis of the lavage fluid from both lines of SP-C/Sftpc -/- mice. Induced SP-C expression was localized to alveolar type II cells by immunostaining with an antibody to proSP-C. Line 55.3 SP-C/Sftpc -/- mice were maintained on or off dox for 7 days and infected with 2.6x10(7) RSV pfu. On day 3 post RSV infection total inflammatory cell counts were reduced in the lavage of dox treated 55.3 SP-C/Sftpc -/- mice (p = 0.004). The percentage of neutrophils was reduced (p = 0.05). The viral titers of lung homogenates from dox treated 55.3 SP-C/Sftpc -/- mice were decreased relative to 55.3 SP-C/Sftpc -/- mice without dox (p = 0.01). The cytokine response of Sftpc -/- type II cells to RSV was increased over that of Sftpc +/+ cells. CONCLUSIONS: Transgenic restoration of SP-C reduced inflammation and improved viral clearance in the lungs of SP-C deficient mice. The loss of SP-C in alveolar type II cells compromises their response to infection. These findings show that the restoration of SP-C in Sftpc -/- mice in response to RSV infection is a useful model to determine parameters for therapeutic intervention

Single-Image Depth Prediction Makes Feature Matching Easier

Good local features improve the robustness of many 3D re-localization and multi-view reconstruction pipelines. The problem is that viewing angle and distance severely impact the recognizability of a local feature. Attempts to improve appearance invariance by choosing better local feature points or by leveraging outside information, have come with pre-requisites that made some of them impractical. In this paper, we propose a surprisingly effective enhancement to local feature extraction, which improves matching. We show that CNN-based depths inferred from single RGB images are quite helpful, despite their flaws. They allow us to pre-warp images and rectify perspective distortions, to significantly enhance SIFT and BRISK features, enabling more good matches, even when cameras are looking at the same scene but in opposite directions.Comment: 14 pages, 7 figures, accepted for publication at the European conference on computer vision (ECCV) 202

Albumin Microspheres as “Trans-ferry-beads” for Easy Cell Passaging in Cell Culture Technology

Protein hydrogels represent ideal materials for advanced cell culture applications, including 3D-cultivation of even fastidious cells. Key properties of fully functional and, at the same time, economically successful cell culture materials are excellent biocompatibility and advanced fabrication processes allowing their easy production even on a large scale based on affordable compounds. Chemical crosslinking of bovine serum albumin (BSA) with N-(3-dimethylaminopropyl)-N’-ethylcarbodiimide hydrochloride (EDC) in a water-in-oil emulsion with isoparaffinic oil as the continuous phase and sorbitan monooleate as surfactant generates micro-meter-scale spherical particles. They allow a significant simplification of an indispensable and laborious step in traditional cell culture workflows. This cell passaging (or splitting) to fresh culture vessels/flasks conventionally requires harsh trypsinization, which can be omitted by using the “trans-ferry-beads” presented here. When added to different pre-cultivated adherent cell lines, the beads are efficiently boarded by cells as passengers and can be easily transferred afterward for the embarkment of novel flasks. After this procedure, cells are perfectly viable and show normal growth behavior. Thus, the trans-ferry-beads not only may become extremely affordable as a final product but also may generally replace trypsinization in conventional cell culture, thereby opening new routes for the establishment of optimized and resource-efficient workflows in biological and medical cell culture laboratories

A supervised hierarchical segmentation of remote-sensing images using a committee of multi-scale convolutional neural networks

This paper presents a supervised, hierarchical remote-sensing image segmentation technique using a committee of multi-scale convolutional neural networks. With existing techniques, segmentation is achieved through fine-tuning a set of predefined feature detectors. However, such a solution is not robust since the introduction of new sensors or applications would require novel features and techniques to be developed. Conversely, the proposed method achieves segmentation through a set of learnt feature detectors. In order to learn feature detectors, the proposed method exploits a committee of convolutional neural networks that perform multi-scale analysis on each band in order to derive individual confidence maps on region boundaries. Confidence maps are then inter-fused in order to produce a fused confidence map. Furthermore, the fused map is intra-fused using a morphological scheme into a hierarchical segmentation map. The proposed method is quantitatively compared to baseline techniques on a publicly available data set. The results presented in this paper highlight the improved accuracy of the proposed method

Reanalysis in Earth System Science: Towards Terrestrial Ecosystem Reanalysis

A reanalysis is a physically consistent set of optimally merged simulated model states and historical observational data, using data assimilation. High computational costs for modelled processes and assimilation algorithms has led to Earth system specific reanalysis products for the atmosphere, the ocean and the land separately. Recent developments include the advanced uncertainty quantification and the generation of biogeochemical reanalysis for land and ocean. Here, we review atmospheric and oceanic reanalyses, and more in detail biogeochemical ocean and terrestrial reanalyses. In particular, we identify land surface, hydrologic and carbon cycle reanalyses which are nowadays produced in targeted projects for very specific purposes. Although a future joint reanalysis of land surface, hydrologic and carbon processes represents an analysis of important ecosystem variables, biotic ecosystem variables are assimilated only to a very limited extent. Continuous data sets of ecosystem variables are needed to explore biotic-abiotic interactions and the response of ecosystems to global change. Based on the review of existing achievements, we identify five major steps required to develop terrestrial ecosystem reanalysis to deliver continuous data streams on ecosystem dynamics

Novel standards in the measurement of rat insulin granules combining electron microscopy, high-content image analysis and in silico modelling

Knowledge of number, size and content of insulin secretory granules is pivotal for understanding the physiology of pancreatic beta cells. Here we re-evaluated key structural features of rat beta cells, including insulin granule size, number and distribution as well as cell size