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Dual centrifugation (DC) is an innovative in-vial homogenization and in-vial nanomilling technique that has been in use for the preparation of liposomes for more than one decade. Since then, DC has continuously been developed for preparing various liposomes and other lipid nanoparticles including emulsions and solid lipid nanoparticles (SLNs) as well as polymersomes and nanocrystals. Improvements in equipment technology have been achieved over the past decade, so that DC is now on its way to becoming the quasi-standard for the simple, fast, and aseptic production of lipid nanoparticles and nanocrystals in small and medium batch sizes, including the possibility of simple and fast formulation screening or bedside preparations of therapeutic nanoparticles. More than 68 publications in which DC was used to produce nanoparticles have appeared since then, justifying an initial review of the use of DC for pharmaceutical nanotechnology. [ABSTRACT FROM AUTHOR]

Dual centrifugation (DC) is a new and versatile technique for the preparation of liposomes by in-vial homogenization of lipid-water mixtures. Size, size distribution, and entrapping efficiencies are strongly dependent on the lipid concentration during DC-homogenization. In this study, we investigated the detailed structure of DC-made liposomes. To do so, an assay to determine the ratio of inner to total membrane surfaces of liposomes (inaccessible surface) was developed based on either time-resolved or steady-state fluorescence spectroscopy. In addition, cryogenic electron microscopy (cryo-EM) was used to confirm the lamellarity results and learn more about liposome morphology. One striking result leads to the possibility of producing a novel type of liposome—small multilamellar vesicles (SMVs) with low PDI, sizes of the order of 100 nm, and almost completely filled with bilayers. A second particularly important finding is that VPGs can be prepared to contain open bilayer structures that will close spontaneously when, after storage, more aqueous phase is added and liposomes are formed. Through this process, a drug can effectively be entrapped immediately before application. In addition, dual centrifugation at lower lipid concentrations is found to produce predominantly unilamellar vesicles. [ABSTRACT FROM AUTHOR]

The hydrological drought in Northern Italy in 2022 was, in large part, the consequence of a snow drought in the Italian Alps in the winter of 2021/22 and the resulting deficit of melt water runoff. In this communication, we assessed the snow-cover dynamics in nine Alpine Italian catchments using long time series of satellite-derived snow line elevation (SLE) measurements. We compared the SLE of the hydrological year 2021/22 to the long-term dynamics of 1985–2021. In early 2022, the SLE was located several hundred meters above the expected median values in all of the nine catchments. This resulted in deficits of snow-covered area of up to 83% in the Western Alps (catchment of Sesia, March 2022) and up to 61% in the Eastern Alps (Brenta, March 2022) compared to the long-term median. Although snow-cover data from optical satellite imagery do not contain information about snow depth and water content, in a preliminary qualitative analysis, the derived SLE dynamics show good agreement with the Standardized Snowpack Index (SSPI) which is based on the snow water equivalent (SWE). While the exact relationships between SLE, SWE, and runoff have to be explored further on the catchment basis, long-time series of SLE may have potential for use in drought early warning systems. [ABSTRACT FROM AUTHOR]

Snow is a vital environmental parameter and dynamically responsive to climate change, particularly in mountainous regions. Snow cover can be monitored at variable spatial scales using Earth Observation (EO) data. Long-lasting remote sensing missions enable the generation of multi-decadal time series and thus the detection of long-term trends. However, there have been few attempts to use these to model future snow cover dynamics. In this study, we, therefore, explore the potential of such time series to forecast the Snow Line Elevation (SLE) in the European Alps. We generate monthly SLE time series from the entire Landsat archive (1985–2021) in 43 Alpine catchments. Positive long-term SLE change rates are detected, with the highest rates (5–8 m/y) in the Western and Central Alps. We utilize this SLE dataset to implement and evaluate seven uni-variate time series modeling and forecasting approaches. The best results were achieved by Random Forests, with a Nash–Sutcliffe efficiency (NSE) of 0.79 and a Mean Absolute Error (MAE) of 258 m, Telescope (0.76, 268 m), and seasonal ARIMA (0.75, 270 m). Since the model performance varies strongly with the input data, we developed a combined forecast based on the best-performing methods in each catchment. This approach was then used to forecast the SLE for the years 2022–2029. In the majority of the catchments, the shift of the forecast median SLE level retained the sign of the long-term trend. In cases where a deviating SLE dynamic is forecast, a discussion based on the unique properties of the catchment and past SLE dynamics is required. In the future, we expect major improvements in our SLE forecasting efforts by including external predictor variables in a multi-variate modeling approach. [ABSTRACT FROM AUTHOR]

In the past decades, various Earth observation-based time series products have emerged, which have enabled studies and analysis of global change processes. Besides their contribution to understanding past processes, time series datasets hold enormous potential for predictive modeling and thereby meet the demands of decision makers on future scenarios. In order to further exploit these data, a novel pixel-based approach has been introduced, which is the spatio-temporal matrix (STM). The approach integrates the historical characteristics of a specific land cover at a high temporal frequency in order to interpret the spatial and temporal information for the neighborhood of a given target pixel. The provided information can be exploited with common predictive models and algorithms. In this study, this approach was utilized and evaluated for the prediction of future urban/built-settlement growth. Random forest and multi-layer perceptron were employed for the prediction. The tests have been carried out with training strategies based on a one-year and a ten-year time span for the urban agglomerations of Surat (India), Ho-Chi-Minh City (Vietnam), and Abidjan (Ivory Coast). The slope, land use, exclusion, urban, transportation, hillshade (SLEUTH) model was selected as a baseline indicator for the performance evaluation. The statistical results from the receiver operating characteristic curve (ROC) demonstrate a good ability of the STM to facilitate the prediction of future settlement growth and its transferability to different cities, with area under the curve (AUC) values greater than 0.85. Compared with SLEUTH, the STM-based model achieved higher AUC in all of the test cases, while being independent of the additional datasets for the restricted and the preferential development areas. [ABSTRACT FROM AUTHOR]

Dual centrifugation (DC) is a novel in-vial homogenization technique for the preparation of liposomes in small batch sizes under gentle and sterile conditions which allows encapsulation efficiencies ( EE ) for water soluble compounds of >50%. Since liposome size, size distribution (PDI), and EE depend on the lipid concentration used in the DC process, a screening method to find optimal lipid concentrations for a defined lipid composition was developed. Four lipid mixtures consisting of cholesterol, hydrogenated or non-hydrogenated egg PC, and/or PEG-DSPE were screened and suitable concentration ranges could be identified for optimal DC homogenization. In addition to the very fast and parallel liposome preparation of up to 40 samples, the screening process was further accelerated by the finding that DC generates homogeneously mixed liposomes from a macroscopic lipid mixture without the need to initially prepare a molecularly mixed lipid film from an organic solution of all components. This much simpler procedure even works for cholesterol containing lipid blends, which could be explained by a nano-milling of the cholesterol crystals during DC homogenization. Furthermore, EE determination was performed by time-resolved fluorescence measurements of calcein-loaded liposomes without removing the non-entrapped calcein. The new strategy allows the rapid characterization of a certain lipid composition for the preparation of liposomes within a working day.