Safe and Effective Cynomolgus Monkey GLP—Tox Study with Repetitive Intrathecal Application of a TGFBR2 Targeting LNA-Gapmer Antisense Oligonucleotide as Treatment Candidate for Neurodegenerative Disorders

The capability of the adult central nervous system to self-repair/regenerate was demonstrated repeatedly throughout the last decades but remains in debate. Reduced neurogenic niche activity paralleled by a profound neuronal loss represents fundamental hallmarks in the disease course of neurodegenerative disorders. We and others have demonstrated the endogenous TGFβ system to represent a potential pathogenic participant in disease progression, of amyotrophic lateral sclerosis (ALS) in particular, by generating and promoting a disequilibrium of neurodegenerative and neuroregenerative processes. The novel human/primate specific LNA Gapmer Antisense Oligonucleotide “NVP-13”, targeting TGFBR2, effectively reduced its expression and lowered TGFβ signal transduction in vitro and in vivo, paralleled by boosting neurogenic niche activity in human neuronal progenitor cells and nonhuman primate central nervous system. Here, we investigated NVP-13 in vivo pharmacology, safety, and tolerability following repeated intrathecal injections in nonhuman primate cynomolgus monkeys for 13 weeks in a GLP-toxicology study approach. NVP-13 was administered intrathecally with 1, 2, or 4 mg NVP-13/animal within 3 months on days 1, 15, 29, 43, 57, 71, and 85 in the initial 13 weeks. We were able to demonstrate an excellent local and systemic tolerability, and no adverse events in physiological, hematological, clinical chemistry, and microscopic findings in female and male Cynomolgus Monkeys. Under the conditions of this study, the no observed adverse effect level (NOAEL) is at least 4 mg/animal NVP-13

Satellite and in situ observations for advancing global Earth surface modelling: a review

In this paper, we review the use of satellite-based remote sensing in combination with in situ data to inform Earth surface modelling. This involves verification and optimization methods that can handle both random and systematic errors and result in effective model improvement for both surface monitoring and prediction applications. The reasons for diverse remote sensing data and products include (i) their complementary areal and temporal coverage, (ii) their diverse and covariant information content, and (iii) their ability to complement in situ observations, which are often sparse and only locally representative. To improve our understanding of the complex behavior of the Earth system at the surface and sub-surface, we need large volumes of data from high-resolution modelling and remote sensing, since the Earth surface exhibits a high degree of heterogeneity and discontinuities in space and time. The spatial and temporal variability of the biosphere, hydrosphere, cryosphere and anthroposphere calls for an increased use of Earth observation (EO) data attaining volumes previously considered prohibitive. We review data availability and discuss recent examples where satellite remote sensing is used to infer observable surface quantities directly or indirectly, with particular emphasis on key parameters necessary for weather and climate prediction. Coordinated high-resolution remote-sensing and modelling/assimilation capabilities for the Earth surface are required to support an international application-focused effort

Synthesis and biochemical evaluation of intelligent, catalytic active agents

Die vorliegende Arbeit befasst sich mit der Erforschung neuartiger Wirkstoffe, gegen Krankheiten bei denen oxidativer Stress (OS) auftritt. Dazu gehören Krankheiten wie Parkinson, Alzheimer oder Rheumatoide Arthritis. Auch Krebs wird mit dem Überwiegen von Pro- gegenüber Antioxidantien in Zusammenhang gebracht. Im Kampf gegen Oxidantien spielen Katalysatoren, die natürliche Enzyme nachahmen können, eine wichtige Rolle. Da nicht nur Superoxidanionen und Wasserstoffperoxid, sondern auch labile Metallionen OS verursachen, sollen multifunktional gebaute Moleküle, die katalytische mit metallbindenden Eigenschaften vereinen, OS als Multi-Stressoren-Ereignis optimal bekämpfen. Ein weiterer Schwerpunkt liegt auf Krebswirkstoffen. Von besonderem Interesse sind effektive und vor allem selektive katalytische Wirkstoffe, mit Glutathion-Peroxidase-ähnlicher Aktivität. Die "intelligenten" Katalysatoren sollen auf oxidativ gestresste Krebszellen angepasst sein, aber nicht zytotoxisch auf Zellen mit normalen Redoxverhältnissen wirken. Eine Reihe von multifuktional gebauten Wirkstoffen, auf Basis von Chalkogen- und Chinon-Redoxzentren sowie Makrozyklen, wurde synthetisiert und in Zellkulturstudien untersucht. Zu den vielversprechendsten Stukturen gehören zwei Verbindungen, welche einen Schutz vor dem mit OS assoziierten Zelltod vermitteln. Mehrere Verbindungen konnten gefunden werden, die Krebszellen mit erhöhten intrazellulären Konzentrationen an oxidativen Stressoren selektiv töten.The thesis covers the development of new active agents against illnesses which are associated with oxidative stress (OS). Parkinson\u27s disease, Alzheimer\u27s disease or Rheumatoid Arthritis do belong to it. Cancer is as well associated with the overbalance of pro- against antioxidants. Catalysts which mimic natural enzyms play an important role in modern drug development. Not only superoxide anions and hydrogen peroxide but also labile metal ions can cause OS. Multifunctional molecules, which combine catalytic and metal binding properties should treat OS as multi-stressor event in an optimal way. Another focal point are drugs for cancer therapy. Of special interest are effective and above all selective catalytic agents with gluthatione peroxidase-like activity. The "intelligent" catalysts should distinguish between cancer cells under OS and cells under normal redox conditions. A range of multifunctional built drugs has been synthesized containing chalkogen and quinone redox centers as well as macrocycles, and explored in cell culture studies. To the most promising stuctures belong two compounds, which protect cells from cell death caused by OS. Several compounds are able to kill cancer cells selectively, that are more oxidatively stressed

New tool for spatio-temporal image fusion in remote sensing: a case study approach using Sentinel-2 and Sentinel-3 data

Remote sensing image fusion allows the spectral, spatial and temporal enhancement of images. New techniques for image fusion are constantly emerging shifting the focus from pan-sharpening to spatiotemporal fusion of data originating from different sensors and platforms. However, the application of image fusion in the field of Earth observation still remains limited. The number and complexity of the different techniques available today can be overwhelming thus preventing users from fully exploiting the potential of fusion. The aim of this study is to make fusion products more accessible to users by providing them with a simple tool for spatiotemporal fusion in Python. This tool will contribute to the better exploitation of data from available sensors making possible to bring the images to the spectral, spatial and temporal resolution required by the user. The fusion algorithm implemented in the tool is based on the spatial and temporal adaptive reflectance fusion model (STARFM) - a well established fusion technique in the field of remote sensing often used as benchmark by other algorithms. The capabilities of the tool are demonstrated by three case studies using Sentinel-2 and simulated Sentinel-3 data. The first case study is about deforestation in the Amazon forest. The other two case studies concentrate on detecting change in an agricultural site in Southern Germany and urban flooding caused by the hurricane Harvey

Advancing Earth Surface Representation via Enhanced Use of Earth Observations in Monitoring and Forecasting Applications

The representation of the Earth's surface in global monitoring and forecasting applications is moving towards capturing more of the relevant processes, while maintaining elevated computational efficiency and therefore a moderate complexity. These schemes are developed and continuously improved thanks to well instrumented field-sites that can observe coupled processes occurring at the surface–atmosphere interface (e.g., forest, grassland, cropland areas and diverse climate zones). Approaching global kilometer-scale resolutions, in situ observations alone cannot fulfil the modelling needs, and the use of satellite observation becomes essential to guide modelling innovation and to calibrate and validate new parameterization schemes that can support data assimilation applications. In this book, we review some of the recent contributions, highlighting how satellite data are used to inform Earth surface model development (vegetation state and seasonality, soil moisture conditions, surface temperature and turbulent fluxes, land-use change detection, agricultural indicators and irrigation) when moving towards global km-scale resolutions

ESA's soil moisture and ocean salinity mission – achievements and applications after more than 6 years in orbit

ESA's soil moisture and ocean salinity mission – achievements and applications after more than 6 years in orbi

Synergies betwwen Smos and sentinel-3

International audienceAfter almost 9 years in orbit L-band satellite radiometry has demonstrated its impacts and values for a wide range of science and applications. However, so as to cover specific applications use of other sensors can prove very valuable. In particular use of altimetry, optical and thermal infrared measurements can offer new avenues. Many of them were tested with existing satellites at the time of SMOS launch, but with the Copernicus' Sentinel-3 mission's data now available, new applications and operational products can be envisioned

The SMOS level2 soil moisture algorithm. Principles and future trends

International audienceThe Soil Moisture and Ocean Salinity (SMOS) mission is ESA’s (European Space Agency) second Earth Explorer Opportunity mission, launched in November 2009. It is a joint programme between ESA CNES (Centre National d’Etudes Spatiales) and CDTI (Centro para el Desarrollo Tecnologico Industrial). SMOS carries a single payload, an L-Band 2D interferometric radiometer in the 1400-1427 MHz protected band. The goal of the level 2 algorithm is to deliver global soil moisture maps with a desired accuracy of 0.04 m3/m3. To reach this goal a retrieval algorithm was developed and implemented in the Ground segment which processes level 1 to level 2 data. In this context, a group of institutes prepared the soil moisture Algorithm Theoretical Basis document (ATBD) to be used to produce the operational algorithm. The principle of the soil moisture retrieval algorithm is based on an iterative approach which aims at minimizing a cost function. The main component of the cost function is given by the sum of the squared weighted differences between measured and modelled brightness temperature (TB) data, for a variety of incidence angles. The algorithm finds the best set of the parameters, e.g. soil moisture (SM) and vegetation characteristics, which drive the direct TB model and minimizes the cost function. The end user Level 2 SM product contains soil moisture, vegetation opacity, and estimated dielectric constant of any surface, brightness temperatures computed at 42.5°, flags and quality indices, and other parameters of interest. Based on recent study and analysis (see paper by JP Wigneron on LMEB, P Ferrazzoli on forest etc.. and results acquired since launch we have revisited the algorithm(flags, retrievals outputs, aux data). The goal of this presentation is to give an update on the algorithm changes and trends. Validation will be presented in other papers