28 research outputs found
Threat of allergenic airborne grass pollen in Szczecin, NW Poland: the dynamics of pollen seasons, effect of meteorological variables and air pollution
The dynamics of Poaceae pollen season, in particularly that of the Secale genus, in Szczecin (western Poland) 2004–2008 was analysed to establish a relationship between the meteorological variables, air pollution and the pollen count of the taxa studied. Consecutive phases during the pollen season were defined for each taxon (1, 2.5, 5, 25, 50, 75, 95, 97.5, 99% of annual total), and duration of the season was determined using the 98% method. On the basis of this analysis, the temporary differences in the dynamics of the seasons were most evident for Secale in 2005 and 2006 with the longest main pollen season (90% total pollen). The pollen season of Poaceae started the earliest in 2007, when thermal conditions were the most favourable. Correlation analysis with meteorological factors demonstrated that the relative humidity, mean and maximum air temperature, and rainfall were the factors influencing the average daily pollen concentrations in the atmosphere; also, the presence of air pollutants such as ozone, PM10 and SO2 was statistically related to the pollen count in the air. However, multiple regression models explained little part of the total variance. Atmospheric pollution induces aggravation of symptoms of grass pollen allergy
Characterization of cis- and trans-acting elements in the imprinted human SNURF-SNRPN locus
The imprinted SNRPN locus is a complex transcriptional unit that encodes the SNURF and SmN polypeptides as well as multiple non-coding RNAs. SNRPN is located within the Prader-Willi and Angelman syndrome (PWS/AS) region that contains multiple imprinted genes, which are coordinately regulated by a bipartite imprinting center (IC). The SNRPN 5′ region co-localizes with the PWS-IC and contains two DNase I hypersensitive sites, DHS1 at the SNRPN promoter, and DHS2 within intron 1, exclusively on the paternally inherited chromosome. We have examined DHS1 and DHS2 to identify cis- and trans-acting regulatory elements within the endogenous SNRPN 5′ region. Analysis of DHS1 by in vivo footprinting and chromatin immunoprecipitation identified allele-specific interaction with multiple regulatory proteins, including NRF-1, which regulates genes involved in mitochondrial and metabolic functions. DHS2 acted as an enhancer of the SNRPN promoter and contained a highly conserved region that showed allele-specific interaction with unphosphorylated RNA polymerase II, YY1, Sp1 and NRF-1, further suggesting a key role for NRF-1 in regulation of the SNRPN locus. We propose that one or more of the regulatory elements identified in this study may also contribute to PWS-IC function
Transcriptional and Post-Transcriptional Regulation of SPAST, the Gene Most Frequently Mutated in Hereditary Spastic Paraplegia
Hereditary spastic paraplegias (HSPs) comprise a group of neurodegenerative disorders that are characterized by progressive spasticity of the lower extremities, due to axonal degeneration in the corticospinal motor tracts. HSPs are genetically heterogeneous and show autosomal dominant inheritance in ∼70–80% of cases, with additional cases being recessive or X-linked. The most common type of HSP is SPG4 with mutations in the SPAST gene, encoding spastin, which occurs in 40% of dominantly inherited cases and in ∼10% of sporadic cases. Both loss-of-function and dominant-negative mutation mechanisms have been described for SPG4, suggesting that precise or stoichiometric levels of spastin are necessary for biological function. Therefore, we hypothesized that regulatory mechanisms controlling expression of SPAST are important determinants of spastin biology, and if altered, could contribute to the development and progression of the disease. To examine the transcriptional and post-transcriptional regulation of SPAST, we used molecular phylogenetic methods to identify conserved sequences for putative transcription factor binding sites and miRNA targeting motifs in the SPAST promoter and 3′-UTR, respectively. By a variety of molecular methods, we demonstrate that SPAST transcription is positively regulated by NRF1 and SOX11. Furthermore, we show that miR-96 and miR-182 negatively regulate SPAST by effects on mRNA stability and protein level. These transcriptional and miRNA regulatory mechanisms provide new functional targets for mutation screening and therapeutic targeting in HSP
Prediction of the birch pollen season characteristics in Cracow, Poland using an 18-year data series
Predicting tree pollen season start dates using thermal conditions
Thermal conditions at the beginning of the year determine the timing of pollen seasons of early flowering trees. The aims of this study were to quantify the relationship between the tree pollen season start dates and the thermal conditions just before the beginning of the season and to construct models predicting the start of the pollen season in a given year. The study was performed in Krakow (Southern Poland); the pollen data of Alnus, Corylus and Betula were obtained in 1991–2012 using a volumetric method. The relationship between the tree pollen season start, calculated by the cumulated pollen grain sum method, and a 5-day running means of maximum (for Alnus and Corylus) and mean (for Betula) daily temperature was found and used in the logistic regression models. The estimation of model parameters indicated their statistically significance for all studied taxa; the odds ratio was higher in models for Betula, comparing to Alnus and Corylus. The proposed model makes the accuracy of prediction in 83.58 % of cases for Alnus, in 84.29 % of cases for Corylus and in 90.41 % of cases for Betula. In years of model verification (2011 and 2012), the season start of Alnus and Corylus was predicted more precisely in 2011, while in case of Betula, the model predictions achieved 100 % of accuracy in both years. The correctness of prediction indicated that the data used for the model arrangement fitted the models well and stressed the high efficacy of model prediction estimated using the pollen data in 1991–2010