Efficient chemotherapy of rat glioblastoma using Doxorubicin-loaded PLGA nanoparticles with different stabilizers

Background: Chemotherapy of glioblastoma is largely ineffective as the blood-brain barrier (BBB) prevents entry of most anticancer agents into the brain. For an efficient treatment of glioblastomas it is necessary to deliver anti-cancer drugs across the intact BBB. Poly(lactic-co-glycolic acid) (PLGA) nanoparticles coated with poloxamer 188 hold great promise as drug carriers for brain delivery after their intravenous injection. In the present study the anti-tumour efficacy of the surfactant-coated doxorubicin-loaded PLGA nanoparticles against rat glioblastoma 101/8 was investigated using histological and immunohistochemical methods. Methodology: The particles were prepared by a high-pressure solvent evaporation technique using 1% polyvinylalcohol (PLGA/PVA) or human serum albumin (PLGA/HSA) as stabilizers. Additionally, lecithin-containing PLGA/HSA particles (Dox-Lecithin-PLGA/HSA) were prepared. For evaluation of the antitumour efficacy the glioblastoma-bearing rats were treated intravenously with the doxorubicin-loaded nanoparticles coated with poloxamer 188 using the following treatment regimen: 3×2.5 mg/kg on day 2, 5 and 8 after tumour implantation; doxorubicin and poloxamer 188 solutions were used as controls. On day 18, the rats were sacrificed and the antitumour effect was determined by measurement of tumour size, necrotic areas, proliferation index, and expression of GFAP and VEGF as well as Isolectin B4, a marker for the vessel density. Conclusion: The results reveal a considerable anti-tumour effect of the doxorubicin-loaded nanoparticles. The overall best results were observed for Dox-Lecithin-PLGA/HSA. These data demonstrate that the poloxamer 188-coated PLGA nanoparticles enable delivery of doxorubicin across the blood-brain barrier in the therapeutically effective concentrations

A Multi-perspective Analysis of Carrier-Grade NAT Deployment

As ISPs face IPv4 address scarcity they increasingly turn to network address translation (NAT) to accommodate the address needs of their customers. Recently, ISPs have moved beyond employing NATs only directly at individual customers and instead begun deploying Carrier-Grade NATs (CGNs) to apply address translation to many independent and disparate endpoints spanning physical locations, a phenomenon that so far has received little in the way of empirical assessment. In this work we present a broad and systematic study of the deployment and behavior of these middleboxes. We develop a methodology to detect the existence of hosts behind CGNs by extracting non-routable IP addresses from peer lists we obtain by crawling the BitTorrent DHT. We complement this approach with improvements to our Netalyzr troubleshooting service, enabling us to determine a range of indicators of CGN presence as well as detailed insights into key properties of CGNs. Combining the two data sources we illustrate the scope of CGN deployment on today's Internet, and report on characteristics of commonly deployed CGNs and their effect on end users

More than counting pixels - perspectives on the importance of remote sensing training in ecology and conservation

This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1002/rse2.27As remote sensing (RS) applications and resources continue to expand, their importance for ecology and conservation increases – and so does the need for effective and successful training of professionals working in those fields. Methodological and applied courses often form part of university curricula, but their practical and long-term benefits only become clear afterwards. Having recently received such training in an interdisciplinary master’s programme, we provide our perspectives on our shared education. Through an online survey we include experiences of students and professionals in different fields. Most participants perceive their RS education as useful for their career, but express a need for more training at university level. Hands-on projects are considered the most effective learning method. Besides methodological knowledge, soft skills are clear gains, including problem solving, self-learning and finding individual solutions, and the ability to work in interdisciplinary teams. The largest identified gaps in current RS training concern the application regarding policy making, methodology and conservation. To successfully prepare students for a career, study programmes need to provide RS courses based on state-of-the-art methods, including programming, and interdisciplinary projects linking research and practice supported by a sound technical background.German Research Foundation (DFG), University of Bayreut

More than counting pixels – perspectives on the importance of remote sensing training in ecology and conservation

This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1002/rse2.27As remote sensing (RS) applications and resources continue to expand, their importance for ecology and conservation increases – and so does the need for effective and successful training of professionals working in those fields. Methodological and applied courses often form part of university curricula, but their practical and long-term benefits only become clear afterwards. Having recently received such training in an interdisciplinary master’s programme, we provide our perspectives on our shared education. Through an online survey we include experiences of students and professionals in different fields. Most participants perceive their RS education as useful for their career, but express a need for more training at university level. Hands-on projects are considered the most effective learning method. Besides methodological knowledge, soft skills are clear gains, including problem solving, self-learning and finding individual solutions, and the ability to work in interdisciplinary teams. The largest identified gaps in current RS training concern the application regarding policy making, methodology and conservation. To successfully prepare students for a career, study programmes need to provide RS courses based on state-of-the-art methods, including programming, and interdisciplinary projects linking research and practice supported by a sound technical background.German Research Foundation (DFG), University of Bayreut

TerraSAR-X and Wetlands: A Review

Since its launch in 2007, TerraSAR-X observations have been widely used in a broad range of scientific applications. Particularly in wetland research, TerraSAR-X\u27s shortwave X-band synthetic aperture radar (SAR) possesses unique capabilities, such as high spatial and temporal resolution, for delineating and characterizing the inherent spatially and temporally complex and heterogeneous structure of wetland ecosystems and their dynamics. As transitional areas, wetlands comprise characteristics of both terrestrial and aquatic features, forming a large diversity of wetland types. This study reviews all published articles incorporating TerraSAR-X information into wetland research to provide a comprehensive study of how this sensor has been used with regard to polarization, and the function of the data, time-series analyses, or the assessment of specific wetland ecosystem types. What is evident throughout this literature review is the synergistic fusion of multi-frequency and multi-polarization SAR sensors, sometimes optical sensors, in almost all investigated studies to attain improved wetland classification results. Due to the short revisiting time of the TerraSAR-X sensor, it is possible to compute dense SAR time-series, allowing for a more precise observation of the seasonality in dynamic wetland areas as demonstrated in many of the reviewed studies

Assessing Forest Cover Dynamics and Forest Perception in the Atlantic Forest of Paraguay, Combining Remote Sensing and Household Level Data

The Upper Parana Atlantic Forest (BAAPA) in Paraguay is one of the most threatened tropical forests in the world. The rapid growth of deforestation has resulted in the loss of 91% of its original cover. Numerous efforts have been made to halt deforestation activities, however farmers’ perception towards the forest and its benefits has not been considered either in studies conducted so far or by policy makers. This research provides the first multi-temporal analysis of the dynamics of the forest within the BAAPA region on the one hand, and assesses the way farmers perceive the forest and how this influences forest conservation at the farm level on the other. Remote sensing data acquired from Landsat images from 1999 to 2016 were used to measure the extent of the forest cover and deforestation rates over 17 years. Farmers’ influence on the dynamics of the forest was evaluated by combining earth observation data and household survey results conducted in the BAAPA region in 2016. Outcomes obtained in this study demonstrate a total loss in forest cover of 7500 km 2 . Deforestation rates in protected areas were determined by management regimes. The combination of household level and remote sensing data demonstrated that forest dynamics at the farm level is influenced by farm type, the level of dependency/use of forest benefits and the level of education of forest owners. An understanding of the social value awarded to the forest is a relevant contribution towards preserving natural resources

Mapping threatened dry deciduous dipterocarp forest in South-east Asia for conservation management

Habitat loss is the primary reason for species extinction, making habitat conservation a critical strategy for maintaining global biodiversity. Major habitat types, such as lowland tropical evergreen forests or mangrove forests, are already well represented in many conservation priorities, while others are underrepresented. This is particularly true for dry deciduous dipterocarp forests (DDF), a key forest type in Asia that extends from the tropical to the subtropical regions in South-east Asia (SE Asia), where high temperatures and pronounced seasonal precipitation patterns are predominant. DDF are a unique forest ecosystem type harboring a wide range of important and endemic species and need to be adequately represented in global biodiversity conservation strategies. One of the greatest challenges in DDF conservation is the lack of detailed and accurate maps of their distribution due to inaccurate open-canopy seasonal forest mapping methods. Conventional land cover maps therefore tend to perform inadequately with DDF. Our study accurately delineates DDF on a continental scale based on remote sensing approaches by integrating the strong, characteristic seasonality of DDF. We also determine the current conservation status of DDF throughout SE Asia. We chose SE Asia for our research because its remaining DDF are extensive in some areas but are currently degrading and under increasing pressure from significant socio-economic changes throughout the region. Phenological indices, derived from MODIS vegetation index time series, served as input variables for a Random Forest classifier and were used to predict the spatial distribution of DDF. The resulting continuous fields maps of DDF had accuracies ranging from R-2 = 0.56 to 0.78. We identified three hotspots in SE Asia with a total area of 156,000 km(2), and found Myanmar to have more remaining DDF than the countries in SE Asia. Our approach proved to be a reliable method for mapping DDF and other seasonally influenced ecosystems on continental and regional scales, and is very valuable for conservation management in this region

TerraSAR-X and Wetlands: A Review

Since its launch in 2007, TerraSAR-X observations have been widely used in a broad range of scientific applications. Particularly in wetland research, TerraSAR-X’s shortwave X-band synthetic aperture radar (SAR) possesses unique capabilities, such as high spatial and temporal resolution, for delineating and characterizing the inherent spatially and temporally complex and heterogeneous structure of wetland ecosystems and their dynamics. As transitional areas, wetlands comprise characteristics of both terrestrial and aquatic features, forming a large diversity of wetland types. This study reviews all published articles incorporating TerraSAR-X information into wetland research to provide a comprehensive study of how this sensor has been used with regard to polarization, and the function of the data, time-series analyses, or the assessment of specific wetland ecosystem types. What is evident throughout this literature review is the synergistic fusion of multi-frequency and multi-polarization SAR sensors, sometimes optical sensors, in almost all investigated studies to attain improved wetland classification results. Due to the short revisiting time of the TerraSAR-X sensor, it is possible to compute dense SAR time-series, allowing for a more precise observation of the seasonality in dynamic wetland areas as demonstrated in many of the reviewed studies

Der Gelbe Fluss im Wandel - Multisensorale und multitemporale Analyse des Einzugsgebietes des Gelben Flusses in China mittels Fernerkundungsdaten vor dem Hintergrund des Globalen Wandels

As a cradle of ancient Chinese civilization, the Yellow River Basin has a very long human-environment interrelationship, where early anthropogenic activities re- sulted in large scale landscape modifications. Today, the impact of this relationship has intensified further as the basin plays a vital role for China’s continued economic development. It is one of the most densely-populated, fastest growing, and most dynamic regions of China with abundant natural and environmental resources providing a livelihood for almost 190 million people. Triggered by fundamental economic reforms, the basin has witnessed a spectacular economic boom during the last decades and can be considered as an exemplary blueprint region for contemporary dynamic Global Change processes occurring throughout the country, which is currently transitioning from an agrarian-dominated economy into a modern urbanized society. However, this resourcesdemanding growth has led to profound land use changes with adverse effects on the Yellow River social-ecological systems, where complex challenges arise threatening a long-term sustainable development. Consistent and continuous remote sensing-based monitoring of recent and past land cover and land use change is a fundamental requirement to mitigate the adverse impacts of Global Change processes. Nowadays, technical advancement and the multitude of available satellite sensors, in combination with the opening of data archives, allow the creation of new research perspectives in regional land cover applications over heterogeneous landscapes at large spatial scales. Despite the urgent need to better understand the prevailing dynamics and underlying factors influencing the current processes, detailed regional specific land cover data and change information are surprisingly absent for this region. In view of the noted research gaps and contemporary developments, three major objectives are defined in this thesis. First (i), the current and most pressing social-ecological challenges are elaborated and policy and management instruments towards more sustainability are discussed. Second (ii), this thesis provides new and improved insights on the current land cover state and dynamics of the entire Yellow River Basin. Finally (iii), the most dominant processes related to mining, agriculture, forest, and urban dynamics are determined on finer spatial and temporal scales. The complex and manifold problems and challenges that result from long-term abuse of the water and land resources in the basin have been underpinned by policy choices, cultural attitude, and institutions that have evolved over centuries in China. The tremendous economic growth that has been mainly achieved by extracting water and exploiting land resources in a rigorous, but unsustainable manner, might not only offset the economic benefits, but could also foster social unrest. Since the early emergence of the first Chinese dynasties, flooding was considered historically as a primary issue in river management and major achievements have been made to tame the wild nature of the Yellow River. Whereas flooding is therefore largely now under control, new environmental and social problems have evolved, including soil and water pollution, ecological degradation, biodiversity decline, and food security, all being further aggravated by anthropogenic climate change. To resolve the contemporary and complex challenges, many individual environmental laws and regulations have been enacted by various Chinese ministries. However, these policies often pursue different, often contradictory goals, are too general to tackle specific problems and are usually implemented by a strong top-down approach. Recently, more flexible economic and market-based incentives (pricing, tradable permits, investments) have been successfully adopted, which are specifically tailored to the respective needs, shifting now away from the pure command and regulating instruments. One way towards a more holistic and integrated river basin management could be the establishment of a common platform (e.g. a Geographical Information System) for data handling and sharing, possibly operated by the Yellow River Basin Conservancy Commission (YRCC), where available spatial data, statistical information and in-situ measures are coalesced, on which sustainable decision-making could be based. So far, the collected data is hardly accessible, fragmented, inconsistent, or outdated. The first step to address the absence and lack of consistent and spatially up-to-date information for the entire basin capturing the heterogeneous landscape conditions was taken up in this thesis. Land cover characteristics and dynamics were derived from the last decade for the years 2003 and 2013, based on optical medium-resolution hightemporal MODIS Normalized Differenced Vegetation Index (NDVI) time series at 250 m. To minimize the inherent influence of atmospheric and geometric interferences found in raw high temporal data, the applied adaptive Savitzky-Golay filter successfully smoothed the time series and substantially reduced noise. Based on the smoothed time series data, a large variety of intra-annual phenology metrics as well as spectral and multispectral annual statistics were derived, which served as input variables for random forest (RF) classifiers. High quality reference data sets were derived from very high resolution imagery for each year independently of which 70 % trained the RF models. The accuracy assessments for all regionally specific defined thematic classes were based on the remaining 30 % reference data split and yielded overall accuracies of 87 % and 84 % for 2003 and 2013, respectively. The first regional adapted Yellow River Land Cover Products (YRB LC) depict the detail spatial extent and distribution of the current land cover status and dynamics. The novel products overall differentiate overall 18 land cover and use classes, including classes of natural vegetation (terrestrial and aquatic), cultivated classes, mosaic classes, non-vegetated, and artificial classes, which are not presented in previous land cover studies so far. Building on this, an extended multi-faceted land cover analysis on the most prominent land cover change types at finer spatial and temporal scales provides a better and more detailed picture of the Yellow River Basin dynamics. Precise spatio-temporal products about mining, agriculture, forest, and urban areas were examined from long-trem Landsat satellite time series monitored at annual scales to capture the rapid rate of change in four selected focus regions. All archived Landsat images between 2000 and 2015 were used to derive spatially continuous spectral-temporal, multi-spectral, and textural metrics. For each thematic region and year RF models were built, trained and tested based on a stablepixels reference data set. The automated adaptive signature (AASG) algorithm identifies those pixels that did not change between the investigated time periods to generate a mono-temporal reference stable-pixels data set to keep manual sampling requirements to a minimum level. Derived results gained high accuracies ranging from 88 % to 98 %. Throughout the basin, afforestation on the Central Loess Plateau and urban sprawl are identified as most prominent drivers of land cover change, whereas agricultural land remained stable, only showing local small-scale dynamics. Mining operations started in 2004 on the Qinghai-Tibet Plateau, which resulted in a substantial loss of pristine alpine meadows and wetlands. In this thesis, a novel and unique regional specific view of current and past land cover characteristics in a complex and heterogeneous landscape was presented by using a multi-source remote sensing approach. The delineated products hold great potential for various model and management applications. They could serve as valuable components for effective and sustainable land and water management to adapt and mitigate the predicted consequences of Global Change processes.Der Gelbe Fluss - in der Landessprache Huange He genannt - ist für die Ausprägung und Entwicklung der chinesischen Kultur von großer Bedeutung. Aufgrund der frühen Einflussnahme auf die natürlichen Ökosysteme in dieser Region durch den Menschen, entwickelte sich dort eine ausgeprägte Interaktion zwischen Mensch und Umwelt. Diese Wechselbeziehung hat sich infolge der gegenwärtigen rapiden sozioökonomischen Veränderungen in den letzten Jahrzehnten weiter intensiviert. Das Einzugsgebiet des Gelben Flusses bildet die Lebensgrundlage für fast 190 Millionen Menschen, die zum Großteil von natürlichen Ressourcen abhängig sind. Zudem gehört es zu den wirtschaftlich bedeutendsten und am schnellsten wachsenden Regionen in ganz China. Durch weitreichende Reformen wurde ein wirtschaftlicher Aufstieg forciert, um den Agrarstaat China zu einem modernen Industrie- und Dienstleistungsstaat weiterzuentwickeln. Ein derartiges rasantes wie auch ressourcenintensives Wirtschaftswachstum führte schließlich zu einem enormen Wandel in den Bereichen der Landbedeckung und Landnutzung. Hinzu kamen neue und komplexere wirtschafts-, sozial- und umweltpolitische Herausforderungen, die bis heute eine langfristige und nachhaltige Entwicklung der Region gefährden. Aus diesem Blickwinkel kann das Becken des Gelben Flusses als regionales Spiegelbild der durch den Globalen Wandel bedingten, gegenwärtigen Veränderungsprozesse in ganz China gelten. Eine wichtige Voraussetzung für den adäquaten Umgang mit den Herausforderungen des Globalen Wandels sind kontinuierliche Informationen über aktuelle sowie historische Veränderungen von Landbedeckung und Landnutzung. Infolge der technologischen Entwicklung steht heute eine Vielfalt an Satellitenbildsystemen mit immer höherer zeitlicher und räumlicher Auflösung zur Verfügung. In Verbindung mit kostenfreien und offenen Datenzugriffen ist es möglich, daraus neue Forschungsperspektiven im Bereich der Landoberflächenkartierung - insbesondere für heterogene Landschaften - zu entwickeln. Zur Generierung thematischer Karten werden häufig Klassifikationen entlang verschiedener räumlicher und zeitlicher Skalen vollzogen. Daraus können zusätzlich die nötigen Informationen für lokale wie auch regionale Entscheidungsträger abgeleitet werden. Trotz dieser neuen Möglichkeiten sind regionalspezifische Informationen, die einem besseren Verständnis der Dynamiken von Landoberflächen im Bereich des Gelben-Fluss-Beckens dienen, noch rar. Dieses Forschungsdesiderat wurde im Rahmen dieser Arbeit aufgegriffen, wobei folgende Schwerpunkte gesetzt werden: (i) Zunächst werden die vorherrschenden sozioökologischen Herausforderungen für das gesamte Einzugsgebiet des Gelben Flusses dargestellt sowie verschiedene Management- sowie Politikmodelle für eine nachhaltigere Ressourcennutzung diskutiert. (ii) Darauf aufbauend wird die fernerkundliche Ableitung von Landbedeckungs- und Landnutzungsveränderungen der letzten Dekade im Gebiet des gesamten Gelben Flusses flächendeckend durchgeführt und anschließend interpretiert. (iii) Im letzten Schritt werden basierend auf den zuvor abgeleiteten Informationsprodukten die dominierenden Landoberflächendynamiken in höherer zeitlicher und räumlicher Auflösung detailliert untersucht. Insbesondere die dynamischen Prozesse der Minenausbreitung, Landwirtschaft, Waldgebiete und der urbanen Räume rücken in den Fokus. Aufgrund jahrzehntelanger Übernutzung der natürlichen Ressourcen im Gebiet des Gelben Flusses in Verbindung mit politischen Entscheidungen, der vorherrschenden kulturellen Prägung wie auch der Entwicklung der dort ansässigen Institutionen ist eine vielschichtige Problematik entstanden, die für die gesamte Region eine große Herausforderung darstellt. Durch frühzeitige Maßnahmen der Flutbekämpfung und Flussregulierung konnte den zahlreichen Überflutungen der Vergangenheit entgegengewirkt und das Risiko großflächiger Überschwemmungen minimiert werden. Trotz dieser Erfolge ergeben sich laufend neue, komplexere Herausforderungen mit verheerenden Auswirkungen auf Ökologie und Gesellschaft, wie zum Beispiel Boden- und Wasserdegradation, Entwaldung, Rückgang der Artenvielfalt, Ernährungsunsicherheiten und ein steigendes soziales Ungleichgewicht. Durch den anthropogenen Klimawandel werden diese negativen Probleme noch weiter verstärkt. Zwar wurden sie von der chinesischen Regierung als solche erkannt, dennoch scheiterten die Versuche, mit zahlreichen Gesetzen und Verordnungen die genannten Folgen einzudämmen, an unkonkreten Formulierungen, so dass diese der Komplexität der Herausforderungen nicht gerecht wurden. Die in jüngster Zeit verfolgten modernen und deutlich flexibleren, marktorientierten Ansätze (z.B. Subventionen, Wasserzertifikate), die speziell an die lokalen Gegebenheiten angepasst wurden, zeigen bereits Erfolge. Mit Hilfe einer gemeinsamen Daten- und Informationsplattform, beispielsweise in Form eines Geographischen Informationssystems (GIS), wäre eine integrierte und holistische Flussmanagementstrategie für den Gelben Fluss leichter realisierbar. Auf diese Weise könnten alle verfügbaren statistischen-, räumlichen- und Feldaufnahmen gespeichert, harmonisiert und geteilt und so die bisher noch unvollständigen und veralteten Daten laufend aktualisiert werden. Die Flussbehörde des Gelben Flusses (Yellow River Conservancy Commission) böte sich an, ein solches System zu verwalten. In dieser Arbeit wird die heterogene Landbedeckungsstruktur für das gesamte Einzugsgebiet des Gelben Flusses für die Jahre 2003 und 2013 erfasst und interpretiert. Die fernerkundlichen Eingangsdaten für die einzelnen Klassifikationen bestehen aus optischen MODIS NDVI-Zeitserien, aus denen jährlich phänologische Parameter berechnet werden. Da die Qualität optischer Satellitenbilder häufig durch Wolken und Schatten beeinträchtigt ist, müssen die betroffenen Flächen maskiert und entfernt werden. Die so entstandenen Lücken in der Zeitserie werden durch einen Filteralgorithmus (SavitskyGolay) aufgefüllt und geglättet. Die verwendeten RandomForest-Klassifikationsverfahren ermöglichen die Ableitung von Landbedeckungen und -dynamiken. Diese neuen und räumlich detaillierten Produkte unterscheiden insgesamt 18 verschiedene Landbedeckungsund Landnutzungsklassen. Erstmals liefern diese eine regional spezifische Charakterisierung der vorherrschenden Landbedeckung im Gebiet des Gelben Flusses. Darauf aufbauend erfolgt eine sowohl zeitlich als auch räumlich detailliertere Untersuchung der wichtigsten Veränderungen im Bereich der Landbedeckung, die auf dichten Landsat-Zeitserien basiert. Jährliche Informationen über Dynamiken von Minenabbaugebieten, Landwirtschaft, Waldgebieten und urbanen Räumen zeigen präzise lokale Veränderungen im Einzugsgebiet des Gelben Flusses. Die daraus abgeleiteten Ergebnisse lassen insbesondere auf dem Lössplateau die Auswirkungen ökologischer Restorationsmaßnahmen erkennen, bei denen degradierte Flächen in Waldsysteme umgewandelt wurden. Auf dem Qinghai-Tibet-Plateau zeigt sich eine dramatische Ausbreitung von Kohletagebau zu Lasten der besonders anfälligen alpinen Matten und Feuchtgebiete. Auch der anhaltende Trend zur Urbanisierung spiegelt sich in den hier gewonnenen Ergebnissen deutlich wider. Durch die Kombination von Fernerkundungsdaten unterschiedlicher räumlicher und zeitlicher Auflösungen liefert diese Arbeit neue und bisher einzigartige Einblicke in historische und aktuelle Landbedeckungsdynamiken einer heterogenen Landschaft. Die regionalen Analysen wie auch die thematischen Informationsprodukte besitzen somit großes Potential zur Verbesserung der Informationsgrundlage. Die Ergebnisse dienen außerdem als aussagekräftige Entscheidungsgrundlage mit dem Ziel eines angemessenen und nachhaltigen Land- und Wassermanagements für die natürlichen Ökosysteme im Becken des Gelben Flusses