Geobotanical and sozological valorization of natural habitats in selected areas of the Blue-Green Network

One of the key components of The Blue-Green Network in Łódź are valuable natural areas like the relicts of the natural wildlife (called “Green Treasures of Łódź”) which parts have been preserved in Łódź in spite of two hundred years, very intense urbanization processes. The result of years of geobotanical research in the city was establishing 23 areas of nature protection and proposing of 12 additional natural areas which need to be protected (8 areas of landscape protection and 4 ecological sites). Existing and proposed areas of nature protection, including river valleys, build the wildlife system of Łódź. Predominantly the important role in this concept play the Łódź’s river valleys with their vegetation potential. The Sokolowka River Valley which is located in the Northern-West part of Łódź was the exemplary research field for geobotanical and sozological valorization of the natural habitat of the Blue-Green Network. Within the Sokolowka valley there are retained fragments of precious nature ecosystems.Zadanie pt. „Digitalizacja i udostępnienie w Cyfrowym Repozytorium Uniwersytetu Łódzkiego kolekcji czasopism naukowych wydawanych przez Uniwersytet Łódzki” nr 885/P-DUN/2014 dofinansowane zostało ze środków MNiSW w ramach działalności upowszechniającej naukę

Characterization of the cofactor-binding site in the SPOUT-fold methyltransferases by computational docking of S-adenosylmethionine to three crystal structures

BACKGROUND: There are several evolutionarily unrelated and structurally dissimilar superfamilies of S-adenosylmethionine (AdoMet)-dependent methyltransferases (MTases). A new superfamily (SPOUT) has been recently characterized on a sequence level and three structures of its members (1gz0, 1ipa, and 1k3r) have been solved. However, none of these structures include the cofactor or the substrate. Due to the strong evolutionary divergence and the paucity of experimental information, no confident predictions of protein-ligand and protein-substrate interactions could be made, which hampered the study of sequence-structure-function relationships in the SPOUT superfamily. RESULTS: We used the computational docking program AutoDock to identify the AdoMet-binding site on the surface of three MTase structures. We analyzed the sequence divergence in two distinct lineages of the SPOUT superfamily in the context of surface features and preferred cofactor binding mode to propose specific function for the conserved residues. CONCLUSION: Our docking analysis has confidently predicted the common AdoMet-binding site in three remotely related proteins structures. In the vicinity of the cofactor-binding site, subfamily-conserved grooves were identified on the protein surface, suggesting location of the target-binding/catalytic site. Functionally important residues were inferred and a general reaction mechanism, involving conformational change of a glycine-rich loop, was proposed

Periostin in exhaled breath condensate and in serum of asthmatic patients : relationship to upper and lower airway disease

PURPOSE: Periostin is considered a biomarker for eosinophilic airway inflammation and have been associated with NSAID-Exacerbated Respiratory Disease (NERD) and chronic rhinosinusitis (CRS). In this study, we aimed to evaluate periostin in exhaled breath condensate (EBC) and in serum of patients with various asthma phenotypes. METHODS: The study included 40 asthmatic patients (22 with NERD) and 17 healthy controls. All the procedures (questionnaire, spirometry, FeNO, nasal swabs, EBC collecting, and blood sampling) were performed on the same day. Periostin concentrations were measured using an ELISA kit. RESULTS: Periostin was detected in EBC from 37 of 40 asthmatics and in 16 from 17 of controls. The concentration of periostin in EBC did not differ between the study groups and was not associated with NERD or asthma severity. However, the EBC periostin was significantly higher in asthmatics with CRS as compared to those without (3.1 vs 2 ng/mL, P=0.046). Patients with positive bacterial culture from nasal swabs had higher EBC periostin concentrations than those without (3.2 vs 2.1 ng/mL; P=0.046). The mean serum periostin level was higher in asthmatics with a 1-year history of exacerbation than in those without (3.2 vs 2.3 ng/mL, P=0.045). Asthmatics with skin manifestation of NSAIDs hypersensitivity had higher serum periostin levels as compared to those without (3.5 vs 2.3 ng/mL; P=0.03). CONCLUSIONS: EBC periostin levels seem to reflect intensity of upper airway disease in asthmatics, while serum levels of periostin are associated with asthma activity (exacerbations or FeNO) or NERD subphenotypes

The ESCAPE project : Energy-efficient Scalable Algorithms for Weather Prediction at Exascale

In the simulation of complex multi-scale flows arising in weather and climate modelling, one of the biggest challenges is to satisfy strict service requirements in terms of time to solution and to satisfy budgetary constraints in terms of energy to solution, without compromising the accuracy and stability of the application. These simulations require algorithms that minimise the energy footprint along with the time required to produce a solution, maintain the physically required level of accuracy, are numerically stable, and are resilient in case of hardware failure. The European Centre for Medium-Range Weather Forecasts (ECMWF) led the ESCAPE (Energy-efficient Scalable Algorithms for Weather Prediction at Exascale) project, funded by Horizon 2020 (H2020) under the FET-HPC (Future and Emerging Technologies in High Performance Computing) initiative. The goal of ESCAPE was to develop a sustainable strategy to evolve weather and climate prediction models to next-generation computing technologies. The project partners incorporate the expertise of leading European regional forecasting consortia, university research, experienced high-performance computing centres, and hardware vendors. This paper presents an overview of the ESCAPE strategy: (i) identify domain-specific key algorithmic motifs in weather prediction and climate models (which we term Weather & Climate Dwarfs), (ii) categorise them in terms of computational and communication patterns while (iii) adapting them to different hardware architectures with alternative programming models, (iv) analyse the challenges in optimising, and (v) find alternative algorithms for the same scheme. The participating weather prediction models are the following: IFS (Integrated Forecasting System); ALARO, a combination of AROME (Application de la Recherche a l'Operationnel a Meso-Echelle) and ALADIN (Aire Limitee Adaptation Dynamique Developpement International); and COSMO-EULAG, a combination of COSMO (Consortium for Small-scale Modeling) and EULAG (Eulerian and semi-Lagrangian fluid solver). For many of the weather and climate dwarfs ESCAPE provides prototype implementations on different hardware architectures (mainly Intel Skylake CPUs, NVIDIA GPUs, Intel Xeon Phi, Optalysys optical processor) with different programming models. The spectral transform dwarf represents a detailed example of the co-design cycle of an ESCAPE dwarf. The dwarf concept has proven to be extremely useful for the rapid prototyping of alternative algorithms and their interaction with hardware; e.g. the use of a domain-specific language (DSL). Manual adaptations have led to substantial accelerations of key algorithms in numerical weather prediction (NWP) but are not a general recipe for the performance portability of complex NWP models. Existing DSLs are found to require further evolution but are promising tools for achieving the latter. Measurements of energy and time to solution suggest that a future focus needs to be on exploiting the simultaneous use of all available resources in hybrid CPU-GPU arrangements