Anticancer effects of selenium compounds on human colonic carcinoma cells

Studies performed so far on different human carcinoma cell lines, as well as numerous case-control and epidemiological studies have given proof to the protective effects of selenium against cancer. However, the anticancer properties of selenium are site-specific. The aim of this work was to evaluate the cytotoxic effect of selenium against CaCo2 human colon carcinoma cells, and SW620 lymph node metastasis of colon carcinoma cell line. Three selenium compounds, seleno-DL-cystine (SeC), seleno-L-methionine (SeM) and sodium selenite were used. Initial number of cells was 210 4 and the cells were incubated for 72 h with the aforementioned Se compounds at 10, 100 and 1000 µmol Se concentrations. Cytotoxicity was measured by the MTT cell survival assay. In the present study, decreased viabilities of both CaCo2 and SW620 cells were established following the treatment with selenite, SeC, and SeM. At 10 µmol Se levels all three chemical forms exerted a more or less anticipated cytotoxic effect with viability decreases ranging from 22 to 37%. However, the other two levels of 100 and 1000 µmol Se did not exhibit an expected proportional rise in cytotoxic effect compared to 10 µmol, which warrants further research on the reasons for increased resistance of these cells. Cell morphology also indicates that investigated Se forms induced apoptotic cell death in both cell lines. The results confirm the applicability of Se in the prevention and treatment of the investigated cancer sites

40Ar/39Ar and 14C geochronology of the Albano maar deposits: Implications for 2 defining the age and eruptive style of the most recent explosive activity at Colli 3 Albani Volcanic District, Central Italy

New 40Ar/39Ar and 14C ages have been found for the Albano multiple maar pyroclastic units and underlying 25 paleosols to document the most recent explosive activity in the Colli Albani Volcanic District (CAVD) near 26 Rome, Italy, consisting of seven eruptions (Albano 1 27 ^ = ^ oldest). Both dating methodologies have been applied on several proximal units and on four mid-distal fall/surge deposits, the latter correlated, according to two 28 current different views, to either the Albano or the Campi di Annibale hydromagmatic center. The 40Ar/39Ar 29 ages on leucite phenocrysts from the mid-distal units yielded ages of ca. 72 ka, 73 ka, 41 ka and 36 ka BP, 30 which are indistinguishable from the previously determined 40Ar/39Ar ages of the proximal Albano units 1, 2, 31 5 and 7, thus confirming their stratigraphic correspondence. 32 Twenty-one 14C ages of the paleosols beneath Albano units 3, 5, 6 and 7 were found for samples collected 33 from 13 proximal and distal sections, some of which were the same sections sampled for 40Ar/39Ar 34 measurements. The 14C ages were found to be stratigraphically inconsistent and highly scattered, and were 35 systematically younger than the 40Ar/39Ar ages, ranging 36 ^ from 35 ka ^ to 3 ka. Considering the significant consistence of the 40Ar/39Ar chronological framework, we interpret the scattered and contradictory 14C ages 37 to be the result of a variable contamination of the paleosols by younger organic carbon deriving from the 38 superficial soil horizons. 39 These results suggest that multiple isotopic systems anchored to a robust stratigraphic framework may need 40 to be employed to determine accurately the geochronology of the CAVD as well as other volcanic districts. 4

FotoQuest Go: A citizen science tool for in-situ land use and land cover monitoring

Every three years, dating back to 2006, Eurostat conducts an exhaustive Land Use/Cover Area frame Survey (LUCAS), where professional surveyors visit approximately 270,000 locations across EU countries to acquire photos and record detailed in-situ information on land use/cover. This conventional approach to ground-based calibration/ validation data acquisition is rather costly and is limited to detecting changes on a fixed 3-year cycle. As such, within the EU’s Earth Observation (EO) monitoring framework, there is a need for low-cost solutions for acquiring high quality ground-based data to support the delivery of timely, accurate and well-validated environmental monitoring products. By leveraging the proliferation of mobile devices the FotoQuest Go mobile application offers a citizen-centric tool to mapping land use and land cover dynamics. FotoQuest Go engages citizens and crowdsources the needed information in a more participatory approach while directly complementing the LUCAS survey findings. This paper describes the recent results of a 2017 FotoQuest Go crowdsourcing campaign conducted in Austria, where 100+ participants recorded land use and land cover observations from over 895 LUCAS locations. When visiting a location, the application guides the participants through a series of tasks (i.e. photo acquisition, questionnaire) that follows a subset of the standard LUCAS surveyor data collection protocol. Once the protocol is completed, participants upload their observations for quality check. Experts would then review each submission and provide feedback directly to the participants within 24hrs. Combined with the feedback was a monetary incentive of 1 EUR for each successfully completed location or quest. It was discovered that the quality control and assurance process was very effective in not only ensuring useful and high-quality citizen science data, but also providing a means to facilitate learning among the participants. In other words, within the 2017 FotoQuest Go campaign, we learned that timely and detailed feedback helped to improve the data collected by participants when they visited subsequent locations. This paper will elaborate the added value of quality-assured citizen science data to the domain of traditionally-collected data for land use and land cover monitoring. FotoQuest Go has considerable potential to lower expenditure costs on in-situ data collection and greatly extend the current sources of such data for earth system science research, thereby realizing citizen-powered innovations in the processing chain of land use/cover monitoring activities both within and beyond Europe

FotoQuest Go: A Citizen Science Approach to the Collection of In-Situ Land Cover and Land Use Data for Calibration and Validation

The Land Use/Cover Area frame Survey (LUCAS) is a harmonized data collection exercise on land cover and land use, which employs a systematic sample across EU member countries. The survey is undertaken every three years by trained surveyors and is a rich data set of land use and land cover, including geotagged photographs. LUCAS has been used to validate the CORINE land cover map, which is generated for EU member countries every 6 years, and it represents one of the only publicly available in situ data sets for the calibration and validation of products derived from Earth Observation for Europe. However, the LUCAS exercise is undertaken at a considerable cost to the taxpayer. Given that citizen science is becoming more popular, i.e., the involvement of citizens in scientific research including data collection, we set out to determine whether citizens could help in gathering in situ data on land use and land cover. Advantages of this approach include data collection that is at a denser sample in some areas, the potential for more up-to-date information, since LUCAS is only carried out every 3 years, and as a cost effective way to complement and enrich LUCAS data collection. To test out this idea of land use and land cover data collection by citizens, the FotoQuest Go app was developed. FotoQuest Go is one of many tools that are part of the H2020-funded LandSense Citizen Observatory for land cover and land use. FotoQuest Go (shown in Figure 1) leads any citizen taking part in our crowdsourcing campaigns to pre-specified locations shown on the map. In some cases, these locations overlap with LUCAS points so that quality assurance can be undertaken, comparing the land cover and land use data from the citizens with that of the professional surveyors. As a location on the map is reached, users are asked to take 4 photographs in 4 cardinal directions away from the location and one at the actual point. The map guides the users, e.g., only allowing them to take a photograph if the compass direction is S, N, E or W, and providing advice regarding how the photos should be taken, e.g. two-thirds land and one-third sky. The citizens are then asked to classify the land cover using a simple, visual decision tree, followed by the land use. The app has been designed to be easy-to-use. For example, it is visually attractive and intuitive as the map interface provides guidance on reaching locations, and the app helps users in taking optimal photographs. The decision tree for determining land use and land cover has also been designed in a simple user-friendly fashion. A number of different campaigns have been run with FotoQuest Go, where incentives for participation have ranged from prizes at the end of the campaign to small, monetary rewards for each point captured that was deemed to be of sufficient quality. These gamification elements have helped to motivate the crowd and make the crowdsourcing experience more fun. An analysis of the data showed good agreement between the citizens and the surveyors at the LUCAS locations when considering high level land cover classes, e.g. forest, urban, water, etc., i.e., accuracies greater than 80%. Thus, using an app such as FotoQuest Go, citizens can collect land cover and land use data that could be used for calibration and validation of land cover and land use maps. Moreover, many geotagged photographs have been collected, which could additionally be interpreted and used for calibration and validation purposes. More recently, the main functionality contained within FotoQuest Go has been moved into the PAYSAGES mobile app for crowdsourcing data on land cover and land use. The idea is to involve citizens in the validation and improvement of the French land cover map developed by the French Mapping Agency (IGN). The PAYSAGES app has been developed within the H2020 LandSense Citizen Observatory as part of a demonstration case in urban areas. The app will be used in data collection campaigns during the summer of 2019

A global dataset of crowdsourced land cover and land use reference data

Global land cover is an essential climate variable and a key biophysical driver for earth system models. While remote sensing technology, particularly satellites, have played a key role in providing land cover datasets, large discrepancies have been noted among the available products. Global land use is typically more difficult to map and in many cases cannot be remotely sensed. In-situ or ground-based data and high resolution imagery are thus an important requirement for producing accurate land cover and land use datasets and this is precisely what is lacking. Here we describe the global land cover and land use reference data derived from the Geo-Wiki crowdsourcing platform via four campaigns. These global datasets provide information on human impact, land cover disagreement, wilderness and land cover and land use. Hence, they are relevant for the scientific community that requires reference data for global satellite-derived products, as well as those interested in monitoring global terrestrial ecosystems in general

Characterizing the Spatial and Temporal Availability of Very High Resolution Satellite Imagery in Google Earth and Microsoft Bing Maps as a Source of Reference Data

Very high resolution (VHR) satellite imagery from Google Earth and Microsoft Bing Maps is increasingly being used in a variety of applications from computer sciences to arts and humanities. In the field of remote sensing, one use of this imagery is to create reference data sets through visual interpretation, e.g., to complement existing training data or to aid in the validation of land-cover products. Through new applications such as Collect Earth, this imagery is also being used for monitoring purposes in the form of statistical surveys obtained through visual interpretation. However, little is known about where VHR satellite imagery exists globally or the dates of the imagery. Here we present a global overview of the spatial and temporal distribution of VHR satellite imagery in Google Earth and Microsoft Bing Maps. The results show an uneven availability globally, with biases in certain areas such as the USA, Europe and India, and with clear discontinuities at political borders. We also show that the availability of VHR imagery is currently not adequate for monitoring protected areas and deforestation, but is better suited for monitoring changes in cropland or urban areas using visual interpretation