Simple concentration method enables the use of gargle and mouthwash instead of nasopharyngeal swab sampling for the diagnosis of COVID-19 by PCR.

Since its emergence in December 2019, SARS-CoV-2 is causing one of the most devastating pandemics in human history. Currently, the most important method for definitive diagnosis of COVID-19 is identification of SARS-CoV-2 RNA in nasopharyngeal swab samples by RT-PCR. Nasopharyngeal swab sampling is a discomforting procedure sometimes with adverse effects, which also poses a risk for infection for the personnel performing the sampling. We have developed a new method for concentrating biological samples, which enabled us to use gargle and mouthwash samples to be used in RT-PCR, for the diagnosis of COVID-19, as an alternative to nasopharyngeal swab samples. We have analyzed nasopharyngeal and gargle and mouthwash samples, before and after concentration, of 363 patients by RT-PCR for the presence of SARS-CoV-2. Among 114 patients in which SARS-CoV-2 was identified in at least one of their samples, the virus was identified in 76 (66.7%), 67 (58.8%), and 101 (88.6%) of nasopharyngeal swab, gargle, and mouthwash samples before and after concentration, respectively. When concentrated by our new method, gargle and mouthwash samples can be used instead of nasopharyngeal samples in identification of SARS-CoV-2 by RT-PCR, with the same or better sensitivity. Eliminating the need for nasopharyngeal sampling will save the patients from an invasive and painful procedure and will lower the risk of infection for the healthcare personnel taking the sample. This easy sampling procedure may decrease the workload of hospitals, shorten the turnaround time of obtaining test results, and thus enable rapid isolation of infected patients.

Assessing soil biodiversity potentials in Europe.

Soil is important as a critical component for the functioning of terrestrial ecosystems. The largest part of the terrestrial biodiversity relies, directly or indirectly, on soil. Furthermore, soil itself is habitat to a great diversity of organisms. The suitability of soil to host such a diversity is strongly related to its physico-chemical features and environmental properties. However, due to the complexity of both soil and biodiversity, it is difficult to identify a clear and unambiguous relationship between environmental parameters and soil biota. Nevertheless, the increasing diffusion of a more integrated view of ecosystems, and in particular the development of the concept of ecosystem services, highlights the need for a better comprehension of the role played by soils in offering these services, including the habitat provision. An assessment of the capability of soils to host biodiversity would contribute to evaluate the quality of soils in order to help policy makers with the development of appropriate and sustainable management actions. However, so far, the heterogeneity of soils has been a barrier to the production of a large-scale framework that directly links soil features to organisms living within it. The current knowledge on the effects of soil physico-chemical properties on biota and the available data at continental scale open the way towards such an evaluation. In this study, the soil habitat potential for biodiversity was assessed and mapped for the first time throughout Europe by combining several soil features (pH, soil texture and soil organic matter) with environmental parameters (potential evapotranspiration, average temperature, soil biomass productivity and land use type). Considering the increasingly recognized importance of soils and their biodiversity in providing ecosystem services, the proposed approach appears to be a promising tool that may contribute to open a forum on the need to include soils in future environmental policy making decisions.

Combining Soil Databases for Topsoil Organic Carbon Mapping in Europe.

Accuracy in assessing the distribution of soil organic carbon (SOC) is an important issue because of playing key roles in the functions of both natural ecosystems and agricultural systems. There are several studies in the literature with the aim of finding the best method to assess and map the distribution of SOC content for Europe. Therefore this study aims searching for another aspect of this issue by looking to the performances of using aggregated soil samples coming from different studies and land-uses. The total number of the soil samples in this study was 23,835 and they're collected from the "Land Use/Cover Area frame Statistical Survey" (LUCAS) Project (samples from agricultural soil), BioSoil Project (samples from forest soil), and "Soil Transformations in European Catchments" (SoilTrEC) Project (samples from local soil data coming from six different critical zone observatories (CZOs) in Europe). Moreover, 15 spatial indicators (slope, aspect, elevation, compound topographic index (CTI), CORINE land-cover classification, parent material, texture, world reference base (WRB) soil classification, geological formations, annual average temperature, min-max temperature, total precipitation and average precipitation (for years 1960-1990 and 2000-2010)) were used as auxiliary variables in this prediction. One of the most popular geostatistical techniques, Regression-Kriging (RK), was applied to build the model and assess the distribution of SOC. This study showed that, even though RK method was appropriate for successful SOC mapping, using combined databases was not helpful to increase the statistical significance of the method results for assessing the SOC distribution. According to our results; SOC variation was mainly affected by elevation, slope, CTI, average temperature, average and total precipitation, texture, WRB and CORINE variables for Europe scale in our model. Moreover, the highest average SOC contents were found in the wetland areas; agricultural areas have much lower soil organic carbon content than forest and semi natural areas; Ireland, Sweden and Finland has the highest SOC, on the contrary, Portugal, Poland, Hungary, Spain, Italy have the lowest values with the average 3%.