Differential Roles for STIM1 and STIM2 in Store-Operated Calcium Entry in Rat Neurons

The interaction between Ca2+ sensors STIM1 and STIM2 and Ca2+ channel-forming protein ORAI1 is a crucial element of store-operated calcium entry (SOCE) in non-excitable cells. However, the molecular mechanism of SOCE in neurons remains unclear. We addressed this issue by establishing the presence and function of STIM proteins. Real-time polymerase chain reaction from cortical neurons showed that these cells contain significant amounts of Stim1 and Stim2 mRNA. Thapsigargin (TG) treatment increased the amount of both endogenous STIM proteins in neuronal membrane fractions. The number of YFP-STIM1/ORAI1 and YFP-STIM2/ORAI1 complexes was also enhanced by such treatment. The differences observed in the number of STIM1 and STIM2 complexes under SOCE conditions and the differential sensitivity to SOCE inhibitors suggest their distinct roles. Endoplasmic reticulum (ER) store depletion by TG enhanced intracellular Ca2+ levels in loaded with Fura-2 neurons transfected with YFP-STIM1 and ORAI1, but not with YFP-STIM2 and ORAI1, which correlated well with the number of complexes formed. Moreover, the SOCE inhibitors ML-9 and 2-APB reduced Ca2+ influx in neurons expressing YFP-STIM1/ORAI1 but produced no effect in cells transfected with YFP-STIM2/ORAI1. Moreover, in neurons transfected with YFP-STIM2/ORAI1, the increase in constitutive calcium entry was greater than with YFP-STIM1/ORAI1. Our data indicate that both STIM proteins are involved in calcium homeostasis in neurons. STIM1 mainly activates SOCE, whereas STIM2 regulates resting Ca2+ levels in the ER and Ca2+ leakage with the additional involvement of STIM1

High-resolution fire danger forecast for Poland based on the Weather Research and Forecasting Model

Due to climate change and associated longer and more frequent droughts, the risk of forest fires increases. To address this, the Institute of Meteorology and Water Management implemented a system for forecasting fire weather in Poland. The Fire Weather Index (FWI) system, developed in Canada, has been adapted to work with meteorological fields derived from the high-resolution (2.5 km) Weather Research and Forecasting (WRF) model. Forecasts are made with 24- and 48-h lead times. The purpose of this work is to present the validation of the implemented system. First, the results of the WRF model were validated using in situ observations from ∼70 synoptic stations. Second, we used the correlation method and Eastaugh\u27s percentile analysis to assess the quality of the FWI index. The data covered the 2019 fire season and were analysed for the whole forest area in Poland. Based on the presented results, it can be concluded that the FWI index (calculated based on the WRF model) has a very high predictive ability of fire risk. However, the results vary by region, distance from human habitats, and size of fire

Best Practices.COOP-TRAF JLS/2005/AGIS/156. AGIS Programme, 2005

This research has been conducted by eight partners in four European countries: in Spain, four partners have participated: Centro de Investigación en Criminología - Universidad de Castilla-La Mancha, the NGO Proyecto Esperanza, Two national police forces represented by the law enforcement units in charge of the fight against trafficking in persons: Cuerpo Nacional de Policía (Comisaría General de Extranjería y ocumentación) and Guardia Civil (Unidad de Policía Judicial). From Portugal, our partner has been the Instituto Nacional de Policia e Ciencias Criminaes. From Poland, two partners have participated: The NGO La Strada Foundation and the Warsaw University, and finally, from Italy, the NGO On the Road has been our partner. The aim of the project was to elaborate a best practices guide in order to improve preventive strategies to fight against the phenomenon of THBSE and to improve social integration and support for the victims. Public (members of law enforcement units and members of Judiciary) and private (members of the NGOs) practitioners have participated in two focus group in every country to find strategies to improve cooperation between them and to integrate their experiences and practices in proactive activities to reduce THBSE and to promote victims’ social integratio

Towards Reliable Velocities of Permanent GNSS Stations

In the modern geodesy the role of the permanent station is growing constantly. The proper treatment of the time series from such station lead to the determination of the reliable velocities. In this paper we focused on some pre-analysis as well as analysis issues, which have to be performed upon the time series of the North, East and Up components and showed the best, in our opinion, methods of determination of periodicities (by means of Singular Spectrum Analysis) and spatio-temporal correlations (Principal Component Analysis), that still exist in the time series despite modelling. Finally, the velocities of the selected European permanent stations with the associated errors determined following power-law assumption in the stochastic part is presented

DERIVING COMMON SEASONAL SIGNALS IN GPS POSITION TIME SERIES BY USING MULTICHANNEL SINGULAR SPECTRUM ANALYSIS

International audienceWe estimated the common seasonal signal (annual oscillation) included in the Global Positioning System (GPS) vertical position time series by using Multichannel Singular Spectrum Analysis (MSSA). We employed time series from 24 International GNSS Service (IGS) stations located in Europe which contributed to the newest ITRF2014 (International Terrestrial Reference Frame). The MSSA method has an advantage over the traditional modelling of seasonal signals by the Least-Squares Estimation (LSE) and Singular Spectrum Analysis (SSA) approaches because it can extract time-varying and common seasonal oscillations for stations located in the considered area. Having estimated the annual curve with LSE, we may make a misfit of 3 mm when a peak-to-peak variations of seasonal signals are to be estimated due to the time-variability of seasonal signal. A variance of data modelled as annual signal with SSA and MSSA differs of 3 % at average what proves that the MSSA-curves contain only time-varying and common seasonal signal and leave the station-specific part, local phenomena and power-law noise intact. In contrast to MSSA, these effects are modelled by SSA. The differences in spectral indices of power-law noise between MSSA and LSE estimated with Maximum Likelihood Estimation (MLE) are closer to zero than the ones between SSA and LSE, which means that MSSA curves do not contain site-specific noise as much as the SSA curves do

Multichannel Singular Spectrum Analysis in the Estimates of Common Environmental Effects Affecting GPS Observations

International audienc

Estimates of Vertical Velocity Errors for IGS ITRF2014 Stations by Applying the Improved Singular Spectrum Analysis Method and Environmental Loading Models

International audienc

Impact of Meteorological Conditions on the Dynamics of the COVID-19 Pandemic in Poland

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by the novel coronavirus. The role of environmental factors in COVID-19 transmission is unclear. This study aimed to analyze the correlation between meteorological conditions (temperature, relative humidity, sunshine duration, wind speed) and dynamics of the COVID-19 pandemic in Poland. Data on a daily number of laboratory-confirmed COVID-19 cases and the number of COVID-19-related deaths were gatheredfrom the official governmental website. Meteorological observations from 55 synoptic stations in Poland were used. Moreover, reports on the movement of people across different categories of places were collected. A cross-correlation function, principal component analysis and random forest were applied. Maximum temperature, sunshine duration, relative humidity and variability of mean daily temperature affected the dynamics of the COVID-19 pandemic. An increase intemperature and sunshine hours decreased the number of confirmed COVID-19 cases. The occurrence of high humidity caused an increase in the number of COVID-19 cases 14 days later. Decreased sunshine duration and increased air humidity had a negative impact on the number of COVID-19-related deaths. Our study provides information that may be used by policymakers to support the decision-making process in nonpharmaceutical interventions against COVID-19