Statistical characterization of the sea ice extent during different winter scenarios in the Gulf of Riga (Baltic Sea) using optical remote-sensing imagery

This study focuses on the statistical characterization of ice conditions (extent, sea ice occurrence probability (SIOP), and length of ice season) in the Gulf of Riga, Baltic Sea, using remote-sensing data. The optical remote-sensing data with 250 m resolution acquired by a Moderate Resolution Imaging Spectroradiometer (MODIS) during 2002–2011 were used for statistical characterization of sea ice. A method based on bimodal histogram analysis of remote-sensing reflectance data was developed to discriminate ice from water. In general, ice extent information obtained from MODIS data agrees with the official ice chart data (synthetic aperture radar (SAR) and in situ measurements) and multi-sensor product containing data from microwave and infrared instruments (R² >0.83). However, in case of severe winters and extremely mild winters there are differences in the dates when maximum ice extent is registered. MODIS data can be used for detailed analysis of ice extent in specific basins of Baltic Sea. Depending on the year, the ice season length in the Gulf of Riga ranged from 68 to 146 days, and the maximum ice extent varied greatly from 329 to 15,350 km². SIOP and number of ice days increased significantly in areas where the depth is less than 15 m. Based on negative-degree days and ice cover characteristics (SIOP and ice season length), three winter scenarios were defined: severe (2003, 2006, 2010, and 2011), medium (2004 and 2005), and mild (2007, 2008, and 2009).     

Analysis of natural background and dredging-induced changes in TSM concentration from MERIS images near commercial harbours in the Estonian coastal sea

Medium Resolution Imaging Spectrometer (MERIS) products with 300 m resolution from 2006 to 2011 were used to evaluate the local background of total suspended matter (TSM) in the vicinity of commercial harbours located along the Estonian coastline in the Baltic Sea. The difference between background TSM maps (mainly influenced by spring bloom, cyanobacterial bloom, resuspension, and river inflow) and dredging period mean maps was used for the estimation of dredging-induced turbidity at the time of dredging operations. Validation of Case II Regional (C2 R) and Free University of Berlin (FUB) MERIS processors with point measurements showed that both processors represent the changes in TSM concentration adequately. C2 R processors showed better statistics (R² = 0.61, root mean square error = 0.82 mg l^–1, SD = 0.77 mg l^–1, mean bias = –0.28 mg l^–1) compared to the FUB processor. Analysis of monthly mean TSM maps revealed that the variability of TSM concentration, showing the resilience level of the local ecosystem, is very different along the Estonian coastline – varying between 0.75 and 2.60 mg l^–1 near the Port of Tallinn, located in the Gulf of Finland, and between 10.04 and 24.23 mg l^–1 near the Port of Pärnu, located in the Gulf of Riga. The viability of the method for dredging impact detection was tested by evaluating the dredging-induced turbidity on monthly mean TSM maps for the dredging period in autumn 2008 in Pakri Bay, which is an environmentally sensitive area. A threshold TSM concentration value of >2.26 mg l^–1 difference from background TSM was defined as a criterion for dredging impact detection for Pakri Bay. The area of dredging-induced turbidity was between 0.56 and 1.25 km² and did not reach the environmentally sensitive NATURA 2000 region adjoining Paldiski South Harbour.     

Simultaneous utilization of ammonia,free amino acids and peptides during fermentative growth of Saccharomyces cerevisiae

The efficiency of nitrogen use by yeast is one of the key determinants of the successful completion of alcoholic fermentations. In this work the growth of Saccharomyces cerevisiae S288c in a synthetic medium containing ammonia and free amino acids, supplemented with yeast hydrolysate, was studied. Experiments with ¹⁵NH₄Cl and ¹⁵N‐labelled yeast hydrolysate were carried out to gain insight into which of these three classes of assimilable nitrogen sources yeast cells prefer. Co‐consumption of all three sources was observed; approximately 40% of the total nitrogen in the yeast protein fraction originated from yeast hydrolysate, while free amino acids and ammonia contributed 40 and 20%, respectively. The results indicate that several amino acids are more readily obtained from peptides, most likely when the uptake of their free forms is competitively inhibited and/or repressed. During the second half of each fermentation, a decrease in the incorporation of yeast hydrolysate‐derived nitrogen was observed. These results highlight the nutritional role of peptides in various yeast fermentations. Copyright © 2016 The Institute of Brewing & Distilling     

Fibroblast growth on micro- and nanopatterned surfaces prepared by a novel sol–gel phase separation method

Physical characteristics of the growth substrate including nano- and microstructure play crucial role in determining the behaviour of the cells in a given biological context. To test the effect of varying the supporting surface structure on cell growth we applied a novel sol–gel phase separation-based method to prepare micro- and nanopatterned surfaces with round surface structure features. Variation in the size of structural elements was achieved by solvent variation and adjustment of sol concentration. Growth characteristics and morphology of primary human dermal fibroblasts were found to be significantly modulated by the microstructure of the substrate. The increase in the size of the structural elements, lead to increased inhibition of cell growth, altered morphology (increased cytoplasmic volume), enlarged cell shape, decrease in the number of filopodia) and enhancement of cell senescence. These effects are likely mediated by the decreased contact between the cell membrane and the growth substrate. However, in the case of large surface structural elements other factors like changes in the 3D topology of the cell’s cytoplasm might also play a role.