123 research outputs found

    Block forest (roso pendulinae-tilietum cordarae), a new forest community of the carpathian basin (Cerová Vrachovina, Slovakia)

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    A new plant association (Roso pendulinea-Tilietum cordatae), similar to the Poo nemoralis Tilietutm cordatae Firbas et Sigmud 1928 (Central European siliceous block field forest), has been dexcribed. This forest commuity develops on the periglacial block fields of southern Slovakia (cerová Vrchovina, syn.: Nógrád-Gömör basalt region). The community has been separated from the Mercuriali-Tilietum Zólyomi et Jakucs 1958 common in the submontane belt of the Pannonicum using phytocoenological comparative analyses.The ecological demand and the species combination cleary distinguish this association from the older forest communities described earlier from northern periglacial block fields of Hungary

    Arterial stiffness may predict renal and cardiovascular prognosis in autosomal-dominant polycystic kidney disease

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    Background and aims Autosomal-dominant polycystic kidney disease (ADPKD) is one of the most common causes of end-stage renal disease (ESRD). The most important cause of death among ADPKD patients is cardiovascular (CV). The aim of this study was to examine the prognostic significance of arterial stiffness on CV and renal outcomes in ADPKD. Methods A total of 55 patients with ADPKD were examined. Pulse wave velocity was determined and stiffness index (SIDVP) was calculated. Combined primary endpoints (CV and renal) were major CV events (myocardial infarction, stroke, and CV intervention) as CV endpoints, and attaining of ESRD or start of renal replacement therapy as renal endpoints. Secondary endpoints were CV or renal endpoints separately. Results The mean age of those 55 ADPKD patients was 45 ± 12 years, 21 patients were male. The average value of the SIDVP was 11.11 ± 2.22 m/s. The patients were divided into two groups by the cutoff value of 11 m/s of SIDVP and then outcomes were analyzed. In the higher arterial stiffness group (SIDVP > 11 m/s), occurrence of combined primary endpoint (CV and renal) was significantly higher than in the group with more elastic arteries (p = 0.033). A statistically significant difference was found in the renal endpoints (p = 0.018), but not in the CV endpoints (p = 0.952) between the two groups. Conclusions Increased arterial stiffness predicts the onset of ESRD in ADPDK. Assessment of SIDVP appears to be a useful method for estimating the renal and CV prognosis in ADPKD

    Vegetation-based landscape regions of Hungary.

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    he first version of the map of the Hungarian vegetation-based landscape regions were prepared at the scale of 1 : 200,000 (1 km or higher resolution). The primary goal of the map was to provide an exact background for the presentation and evaluation of the data of theMÉTA database. Secondly, we intended to give an up-to-date and detailed vegetation-based division of Hungary with a comprehensive nomenclature of the regions. Regions were primarily defined on the basis of their present zonal vegetation, or their dominant extrazonal or edaphic vegetation. Where this was not possible, abiotic factors that influence the potential vegetation, the flora were taken into consideration, thus, political and economical factors were ignored. All region borders were defined by local expert botanists, mainly based on their field knowledge. The map differs in many features from the currently used, country- wide, flora- or geography-based divisions in many features. We consider our map to be temporary (i.e. a work map), and we plan to refine and improve it after 5 years of testing

    Ancient genomes reveal origin and rapid trans-Eurasian migration of 7<sup>th</sup> century Avar elites

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    The Avars settled the Carpathian Basin in 567/68 CE, establishing an empire lasting over 200 years. Who they were and where they came from is highly debated. Contemporaries have disagreed about whether they were, as they claimed, the direct successors of the Mongolian Steppe Rouran empire that was destroyed by the Turks in ∼550 CE. Here, we analyze new genome-wide data from 66 pre-Avar and Avar-period Carpathian Basin individuals, including the 8 richest Avar-period burials and further elite sites from Avar’s empire core region. Our results provide support for a rapid long-distance trans-Eurasian migration of Avar-period elites. These individuals carried Northeast Asian ancestry matching the profile of preceding Mongolian Steppe populations, particularly a genome available from the Rouran period. Some of the later elite individuals carried an additional non-local ancestry component broadly matching the steppe, which could point to a later migration or reflect greater genetic diversity within the initial migrant population.- Introduction - Results -- Ancient DNA dataset and quality control -- The genomic structure of the pre-Avar-period population -- The genomic structure of the Avar-period population -- Modeling the eastern steppe ancestry of the elites in the core of the Avar empire -- The heterogeneous ancestry in the regions surrounding the Avar empire’s core - Discussion -- Limitations of the study - Star Method

    New national and regional bryophyte records, 52

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    Marchantia paleacea is a new species for the Umbria Region and is rare in central and southern Italy. This record is in a Site of Community Importance (SCI) IT5220017 and a Special Area of Conservation (SAC) of the Natura 2000 EU-wide network due to the presence of the 7220* ‘Petrifying springs with tufa formation (Cratoneurion)’ Annexe I priority habitat. The particular environment, with a gorge and waterfall, created a very special microclimate that allowed the establishment of interesting liverworts and mosses

    Age-dependent parathormone levels and different CKD-MBD treatment practices of dialysis patients in Hungary - results from a nationwide clinical audit

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    BACKGROUND: Achieving target levels of laboratory parameters of bone and mineral metabolism in chronic kidney disease (CKD) patients is important but also difficult in those living with end-stage kidney disease. This study aimed to determine if there are age-related differences in chronic kidney disease-mineral and bone disorder (CKD-MBD) characteristics, including treatment practice in Hungarian dialysis patients. METHODS: Data were collected retrospectively from a large cohort of dialysis patients in Hungary. Patients on hemodialysis and peritoneal dialysis were also included. The enrolled patients were allocated into two groups based on their age (=65 years). Characteristics of the age groups and differences in disease-related (epidemiology, laboratory, and treatment practice) parameters between the groups were analyzed. RESULTS: A total of 5008 patients were included in the analysis and the mean age was 63.4+/-14.2 years. A total of 47.2% of patients were women, 32.8% had diabetes, and 11.4% were on peritoneal dialysis. Diabetes (37.9% vs 27.3%), bone disease (42.9% vs 34.1%), and soft tissue calcification (56.3% vs 44.7%) were more prevalent in the older group than the younger group (p<0.001 for all). We found an inverse relationship between age and parathyroid hormone (PTH) levels (p<0.001). Serum PTH levels were lower in patients with diabetes compared with those without diabetes below 80 years (p<0.001). Diabetes and age were independently associated with serum PTH levels (interaction: diabetes x age groups, p=0.138). Older patients were more likely than younger patients to achieve laboratory target ranges for each parameter (Ca: 66.9% vs 62.1%, p<0.001; PO4: 52.6% vs 49.2%, p<0.05; and PTH: 50.6% vs 46.6%, p<0.01), and for combined parameters (19.8% vs 15.8%, p<0.001). Older patients were less likely to receive related medication than younger patients (66.9% vs 79.7%, p<0.001). CONCLUSIONS: The achievement of laboratory target ranges for bone and mineral metabolism and clinical practice in CKD depends on the age of the patients. A greater proportion of older patients met target criteria and received less medication compared with younger patients

    Distribution maps of vegetation alliances in Europe

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    Aim The first comprehensive checklist of European phytosociological alliances, orders and classes (EuroVegChecklist) was published by Mucina et al. (2016, Applied Vegetation Science, 19 (Suppl. 1), 3–264). However, this checklist did not contain detailed information on the distribution of individual vegetation types. Here we provide the first maps of all alliances in Europe. Location Europe, Greenland, Canary Islands, Madeira, Azores, Cyprus and the Caucasus countries. Methods We collected data on the occurrence of phytosociological alliances in European countries and regions from literature and vegetation-plot databases. We interpreted and complemented these data using the expert knowledge of an international team of vegetation scientists and matched all the previously reported alliance names and concepts with those of the EuroVegChecklist. We then mapped the occurrence of the EuroVegChecklist alliances in 82 territorial units corresponding to countries, large islands, archipelagos and peninsulas. We subdivided the mainland parts of large or biogeographically heterogeneous countries based on the European biogeographical regions. Specialized alliances of coastal habitats were mapped only for the coastal section of each territorial unit. Results Distribution maps were prepared for 1,105 alliances of vascular-plant dominated vegetation reported in the EuroVegChecklist. For each territorial unit, three levels of occurrence probability were plotted on the maps: (a) verified occurrence; (b) uncertain occurrence; and (c) absence. The maps of individual alliances were complemented by summary maps of the number of alliances and the alliance–area relationship. Distribution data are also provided in a spreadsheet. Conclusions The new map series represents the first attempt to characterize the distribution of all vegetation types at the alliance level across Europe. There are still many knowledge gaps, partly due to a lack of data for some regions and partly due to uncertainties in the definition of some alliances. The maps presented here provide a basis for future research aimed at filling these gaps

    Distribution maps of vegetation alliances in Europe

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    Aim The first comprehensive checklist of European phytosociological alliances, orders and classes (EuroVegChecklist) was published by Mucina et al. (2016, Applied Vegetation Science, 19 (Suppl. 1), 3–264). However, this checklist did not contain detailed information on the distribution of individual vegetation types. Here we provide the first maps of all alliances in Europe. Location Europe, Greenland, Canary Islands, Madeira, Azores, Cyprus and the Caucasus countries. Methods We collected data on the occurrence of phytosociological alliances in European countries and regions from literature and vegetation-plot databases. We interpreted and complemented these data using the expert knowledge of an international team of vegetation scientists and matched all the previously reported alliance names and concepts with those of the EuroVegChecklist. We then mapped the occurrence of the EuroVegChecklist alliances in 82 territorial units corresponding to countries, large islands, archipelagos and peninsulas. We subdivided the mainland parts of large or biogeographically heterogeneous countries based on the European biogeographical regions. Specialized alliances of coastal habitats were mapped only for the coastal section of each territorial unit. Results Distribution maps were prepared for 1,105 alliances of vascular-plant dominated vegetation reported in the EuroVegChecklist. For each territorial unit, three levels of occurrence probability were plotted on the maps: (a) verified occurrence; (b) uncertain occurrence; and (c) absence. The maps of individual alliances were complemented by summary maps of the number of alliances and the alliance–area relationship. Distribution data are also provided in a spreadsheet. Conclusions The new map series represents the first attempt to characterize the distribution of all vegetation types at the alliance level across Europe. There are still many knowledge gaps, partly due to a lack of data for some regions and partly due to uncertainties in the definition of some alliances. The maps presented here provide a basis for future research aimed at filling these gaps
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