River Sediments Downstream of Villages in a Karstic Watershed Exhibited Increased Numbers and Higher Diversity of Nontuberculous Mycobacteria.

The impact of residential villages on the nontuberculous mycobacteria (NTM) in streams flowing through them has not been studied in detail. Water and sediments of streams are highly susceptible to anthropogenic inputs such as surface water flows. This study investigated the impact of seven residential villages in a karst watershed on the prevalence and species spectrum of NTM in water and sediments. Higher NTM species diversity (i.e., 19 out of 28 detected) was recorded downstream of the villages and wastewater treatment plants (WWTPs) compared to sampling sites upstream (i.e., 5). Significantly, higher Zn and lower silicon concentrations were detected in sediments inside the village and downstream of the WWTP's effluents. Higher phosphorus concentration in sediment was downstream of WWTPs compared to other sampling sites. The effluent from the WWTPs had a substantial impact on water quality parameters with significant increases in total phosphorus, anions (Cl-and N-NH3-), and cations (Na+ and K+). The results provide insights into NTM numbers and species diversity distribution in a karst watershed and the impact of urban areas. Although in this report the focus is on the NTM, it is likely that other water and sediment microbes will be influenced as well.

A holistic model of health inequalities for health policy and state administration: a case study in the regions of the Czech Republic.

BACKGROUND: Health inequities exist within and between societies at different hierarchical levels. Despite overall improvements in health status in European Union countries, disparities persist among socially, economically, and societally disadvantaged individuals. This study aims to develop a holistic model of health determinants, examining the complex relationship between various determinants of health inequalities and their association with health condition. METHODS: Health inequalities and conditions were assessed at the territorial level of Local Administrative Units (LAU1) in the Czech Republic. A dataset of 57 indicators was created, categorized into seven determinants of health and one health condition category. The necessary data were obtained from publicly available databases. Comparisons were made between 2001-2003 and 2016-2019. Various methods were employed, including composite indicator creation, correlation analysis, the Wilcoxon test, aggregate index calculation, cluster analysis, and data visualization using the LISA method. RESULTS: The correlation matrix revealed strong relationships between health inequality categories in both periods. The most significant associations were observed between Economic status and social protection and Education in the first period. However, dependencies weakened in the later period, approaching values of approximately 0.50. The Wilcoxon test confirmed variations in determinant values over time, except for three specific determinants. Data visualization identified persistently adverse or worsening health inequalities in specific LAU1, focusing on categories such as Economic status and social protection, Education, Demographic situation, Environmental status, Individual living status, and Road safety and crime. The health condition indices showed no significant change over time, while the aggregate index of health inequalities improved with widened differences. CONCLUSION: Spatial inequalities in health persist in the Czech Republic, influenced by economic, social, demographic, and environmental factors, as well as local healthcare accessibility. Both inner and outer peripheries exhibit poor health outcomes, challenging the assumption that urban areas fare better. The combination of poverty and vulnerabilities exacerbates these inequalities. Despite the low rates of social exclusion and poverty, regional health inequalities persist in the long term. Effectively addressing health inequalities requires interdisciplinary collaboration and evidence-based policy interventions. Efforts should focus on creating supportive social and physical environments, strengthening the healthcare system, and fostering cooperation with non-medical disciplines.

Socio-Economic and Environmental Factors Related to Spatial Differences in Human Non-Tuberculous Mycobacterial Diseases in the Czech Republic.

Non-tuberculous mycobacteria (NTM) are ubiquitous environmental bacteria that can induce pulmonary and non-pulmonary diseases in susceptible persons. It is reported that the prevalence of NTM diseases is increasing in developed countries, but this differs by regions and countries. NTM species distribution and the rate of diseases caused by NTM vary widely in the historical territories of Moravia and Silesia (Czech Republic). This epidemiologic study of NTM diseases covers the period 2012-2018, reviews isolates obtained from patients with clinical disease and investigates correlations with related socio-economic and environmental factors. Individual NTM patients were included only once during the studied period and results were presented as incidence rate per year. The most frequently isolated NTM meeting the microbiological and clinical criteria in the study were the Mycobacterium avium-intracellulare complex, followed by Mycobacteriumkansasii and Mycobacteriumxenopi. A previously described endemic incidence of M.kansasii in the Karviná district and M.xenopi in the Ostrava district was also observed in this study. The incidence of NTM patients in the whole studied territory was 1.10/100,000 inhabitants (1.33/100,000 in men and 0.88/100,000 in women). The annual incidence of lymphadenitis in children (≤5 years of age) was 2.35/100,000 of the population of children during the 7 year period but increased in the year 2018 to 5.95/100,000. The rate of human tuberculosis in the studied area was 1.97/100,000 inhabitants. The incidence of NTM pulmonary diseases correlated with a lower socio-economic status (r = 0.63) and a higher concentration of benzo[a]pyrene pollution in the air (r = 0.64).

Nontuberculous mycobacteria in the environment of Hranice Abyss, the world's deepest flooded cave (Hranice karst, Czech Republic).

Nontuberculous mycobacteria (NTM) are widely distributed in the environment. On one hand, they are opportunistic pathogens for humans and animals, and on the other hand, they are effective in biodegradation of some persistent pollutants. Following the recently recorded large abundance of NTM in extreme geothermal environments, the aim of the study was to ascertain the occurrence of NTM in the extreme environment of the water zone of the Hranice Abyss (HA). The HA mineral water is acidic, with large concentrations of free CO2, and bacterial slimes creating characteristic mucilaginous formations. Both culture and molecular methods were used to compare the mycobacterial diversity across the linked but distinct ecosystems of HA and the adjacent Zbrasov Aragonite Caves (ZAC) with consideration of their pathogenic relevance. Six slowly growing NTM species (M. arupense, M. avium, M. florentinum, M. gordonae, M. intracellulare) and two rapidly growing NTM species (M. mucogenicum, M. sediminis) were identified in the water and in the dry zones at both sites. Proteobacteria were dominant in all the samples from both the HA and the ZAC. The bacterial microbiomes of the HA mineral water and HA slime were similar, but both differed from the microbiome in the ZAC mineral water. Actinobacteria, a phylum containing mycobacteria, was identified in all the samples at low proportional abundance. The majority of the detected NTM species belong among environmental opportunistic pathogens.

Discrimination between acute and chronic decline of Central European forests using map algebra of the growth condition and forest biomass fuzzy sets: A case study.

Forest decline is either caused by damage or else by vulnerability due to unfavourable growth conditions or due to unnatural silvicultural systems. Here, we assess forest decline in the Czech Republic (Central Europe) using fuzzy functions, fuzzy sets and fuzzy rating of ecosystem properties over a 1×1km grid. The model was divided into fuzzy functions of the abiotic predictors of growth conditions (Fpred including temperature, precipitation, acid deposition, soil data and relative site insolation) and forest biomass receptors (Frec including remote sensing data, density and volume of aboveground biomass, and surface humus chemical data). Fuzzy functions were designed at the limits of unfavourable, undetermined or favourable effects on the forest ecosystem health status. Fuzzy sets were distinguished through similarity in a particular membership of the properties at the limits of the forest status margins. Fuzzy rating was obtained from the least difference of Fpred-Frec. Unfavourable Fpred within unfavourable Frec indicated chronic damage, favourable Fpred within unfavourable Frec indicated acute damage, and unfavourable Fpred within favourable Frec indicated vulnerability. The model in the 1×1km grid was validated through spatial intersection with a point field of uniform forest stands. Favourable status was characterised by soil base saturation (BS)>50%, BCC/Al>1, Corg>1%, MgO>6g/kg, and nitrogen deposition<1200mol(H+)/ha·year. Vulnerable forests had BShumus 46-60%, BCC/Al 9-20 and NDVI≈0.42. Chronic forest damage occurs in areas with low temperatures, high nitrogen deposition, and low soil BS and Corg levels. In the Czech Republic, 10% of forests were considered non-damaged and 77% vulnerable, with damage considered acute in 7% of forests and chronic in 5%. The fuzzy model used suggests that improvement in forest health will depend on decreasing environmental load and restoration concordance between growth conditions and tree species composition.