Oil spill Hazard maps

This report contains the description of the methodology to produce coastal oil spill hazard mapping for the Atlantic Ocean coastlines and the description of the Web Portal used to disseminate the informatio

Catchment land cover and soil as predictors of organic carbon, nitrogen, and phosphorus levels in temperate lakes : [presentation]

The presentation took place at the 10th International Conference on Shallow Lakes in 2021.This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 951963. This study was funded by the Estonian Research Council grants PUTJD954, PRG705, and PRG709, and by the European Regional Development Fund through Estonian University of Life Sciences ASTRA project “Value-chain based bio-economy”. The Estonian Ministry of Environment and the Estonian Environment Agency supported data collection in the national monitoring program.This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 951963. This study was funded by the Estonian Research Council grants PUTJD954, PRG705, and PRG709, and by the European Regional Development Fund through Estonian University of Life Sciences ASTRA project “Value-chain based bio-economy”. The Estonian Ministry of Environment and the Estonian Environment Agency supported data collection in the national monitoring program

Complement C3 variant and the risk of age-related macular degeneration

Background: Age-related macular degeneration is the most common cause of blindness in Western populations. Susceptibility is influenced by age and by genetic and environmental factors. Complement activation is implicated in the pathogenesis.Methods: We tested for an association between age-related macular degeneration and 13 single-nucleotide polymorphisms (SNPs) spanning the complement genes C3 and C5 in case subjects and control subjects from the southeastern region of England. All subjects were examined by an ophthalmologist and had independent grading of fundus photographs to confirm their disease status. To test for replication of the most significant findings, we genotyped a set of Scottish cases and controls.Results: The common functional polymorphism rs2230199 (Arg80Gly) in the C3 gene, corresponding to the electrophoretic variants C3S (slow) and C3F (fast), was strongly associated with age-related macular degeneration in both the English group (603 cases and 350 controls, P=5.9 x 10(sup -5)) and the Scottish group (244 cases and 351 controls, P=5.0 x 10(sup -5)). The odds ratio for age-related macular degeneration in C3 S/F heterozygotes as compared with S/S homozygotes was 1.7 (95% confidence interval [CI], 1.3 to 2.1); for F/F homozygotes, the odds ratio was 2.6 (95% CI, 1.6 to 4.1). The estimated population attributable risk for C3F was 22%.Conclusions: Complement C3 is important in the pathogenesis of age-related macular degeneration. This finding further underscores the influence of the complement pathway in the pathogenesis of this disease

Utilizing stimulated Raman scattering microscopy to study intracellular distribution of label-free ponatinib in live cells

Stimulated Raman scattering (SRS) microscopy represents a powerful method for imaging label-free drug dis-tribution with high resolution. SRS was applied to image label-free ponatinib with high sensitivity and speci-ficity in live human chronic myeloid leukemia (CML) cell lines. This was achieved at biologically relevant, na-nomolar concentrations; allowing determination of ponatinib uptake and sequestration into lysosomes during the development of acquired drug resistance and an improved understanding of target engagement

Industry-scale application and evaluation of deep learning for drug target prediction

Artificial intelligence (AI) is undergoing a revolution thanks to the breakthroughs of machine learning algorithms in computer vision, speech recognition, natural language processing and generative modelling. Recent works on publicly available pharmaceutical data showed that AI methods are highly promising for Drug Target prediction. However, the quality of public data might be different than that of industry data due to different labs reporting measurements, different measurement techniques, fewer samples and less diverse and specialized assays. As part of a European funded project (ExCAPE), that brought together expertise from pharmaceutical industry, machine learning, and high-performance computing, we investigated how well machine learning models obtained from public data can be transferred to internal pharmaceutical industry data. Our results show that machine learning models trained on public data can indeed maintain their predictive power to a large degree when applied to industry data. Moreover, we observed that deep learning derived machine learning models outperformed comparable models, which were trained by other machine learning algorithms, when applied to internal pharmaceutical company datasets. To our knowledge, this is the first large-scale study evaluating the potential of machine learning and especially deep learning directly at the level of industry-scale settings and moreover investigating the transferability of publicly learned target prediction models towards industrial bioactivity prediction pipelines.Web of Science121art. no. 2

A Future Tale of Two Winters? Sediment-water interface nitrogen dynamics in Lake Võrtsjärv (Estonia) during the ice-free winter 2019/2020 : [presentation]

The presentation took place at the Lahti Lakes 2021 Symposium.This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 95196. Estonian University of Life Sciences ASTRA project “Value-chain based bio-economy”.This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 95196. Estonian University of Life Sciences ASTRA project “Value-chain based bio-economy”

COST 733 - WG4: Applications of weather type classification

The main objective of the COST Action 733 is to achieve a general numerical method for assessing, comparing and classifying typical weather situations in the European regions. To accomplish this goal, different workgroups are established, each with their specific aims: WG1: Existing methods and applications (finished); WG2: Implementation and development of weather types classification methods; WG3: Comparison of selected weather types classifications; WG4: Testing methods for various applications. The main task of Workgroup 4 (WG4) in COST 733 implies the testing of the selected weather type methods for various classifications. In more detail, WG4 focuses on the following topics:• Selection of dedicated applications (using results from WG1), • Performance of the selected applications using available weather types provided by WG2, • Intercomparison of the application results as a results of different methods • Final assessment of the results and uncertainties, • Presentation and release of results to the other WGs and external interested • Recommend specifications for a new (common) method WG2 Introduction In order to address these specific aims, various applications are selected and WG4 is divided in subgroups accordingly: 1.Air quality 2. Hydrology (& Climatological mapping) 3. Forest fires 4. Climate change and variability 5. Risks and hazards Simultaneously, the special attention is paid to the several wide topics concerning some other COST Actions such as: phenology (COST725), biometeorology (COST730), agriculture (COST 734) and mesoscale modelling and air pollution (COST728). Sub-groups are established to find advantages and disadvantages of different classification methods for different applications. Focus is given to data requirements, spatial and temporal scale, domain area, specifi

Remodeling the skeletal muscle extracellular matrix in older age—Effects of acute exercise stimuli on gene expression

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. With advancing age, the skeletal muscle extracellular matrix (ECM) undergoes fibrotic changes that may lead to increased muscle stiffness, injury susceptibility and strength loss. This study tested the potential of different exercises to counter these changes by stimulating the activity of genes associated with ECM remodeling. Twenty-six healthy men (66.9 ± 3.9 years) were stratified to two of four groups, performing unilateral (i) conventional resistance exercise, (ii) conventional resistance exercise followed by self-myofascial release (CEBR), (iii) eccentric-only exercise (ECC) or (iv) plyometric jumps (PLY). The non-trained leg served as control. Six hours post-exercise, vastus lateralis muscle biopsy samples were analyzed for the expression of genes associated with ECM collagen synthesis (COL1A1), matrix metallopeptidases (collagen degradation; MMPs) and peptidase inhibitors (TIMP1). Significant between-group differences were found for MMP3, MMP15 and TIMP1, with the greatest responses in MMP3 and TIMP1 seen in CEBR and in MMP15 in ECC. MMP9 (3.24–3.81-fold change) and COL1A1 (1.47–2.40-fold change) were increased in CEBR and PLY, although between-group differences were non-significant. The expression of ECM-related genes is exercise-specific, with CEBR and PLY triggering either earlier or stronger remodeling than other stimuli. Training studies will test whether execution of such exercises may help counter age-associated muscle fibrosis