Petra Pokorná

Source apportionment of size resolved particulate matter at a European air pollution hot spot

Positive Matrix Factorization-PMF was applied to hourly resolved elemental composition of fine (PM0.15-1.15) and coarse (PM1.15-10) aerosol particles to apportion their sources in the airshed of residential district, Ostrava-Radvanice and Bartovice in winter 2012. Multiple-site measurement by PM2.5 monitors complements the source apportionment. As there were no statistical significant differences amongst the monitors, the source apportionment derived for the central site data is expected to apply to whole residential district. The apportioned sources of the fine aerosol particles were coal combustion (58.6%), sinter production-hot phase (22.9%), traffic (15%), raw iron production (3.5%), and desulfurization slag processing (<0.5%) whilst road dust (47.3%), sinter production-cold phase (27.7%), coal combustion (16.8%), and raw iron production (8.2%) were resolved being sources of the coarse aerosol particles. The shape and elemental composition of size-segregated aerosol airborne-sampled by an airship aloft presumed air pollution sources helped to interpret the PMF solution.

Particulate matter source apportionment in a village situated in industrial region of Central Europe

The bilinear receptor model positive matrix factorization (PMF) was used to apportion particulate matter with an aerodynamic diameter of 1–10 μm (PM1–10) sources in a village, Březno, situated in an industrial region of northern Bohemia in Central Europe. The receptor model analyzed the data sets of 90- and 60-min integrations of PM1–10 mass concentrations and elemental composition for 27 elements. The 14-day sampling campaigns were conducted in the village in summer 2008 and winter 2010. Also, to ensure seasonal and regional representativeness of the data sets recorded in the village, the spatial-temporal variability of the 24-hr PM10 and PM1–10 within 2008–2010 in winter and summer across the multiple sites was evaluated. There were statistically significant interseasonal differences of the 24-hr PM data, but not intrasummer or intrawinter differences of the 24-hr PM1–10 data across the multiple sites. PMF resolved seven sources of PM1–10. They were high-temperature coal combustion; combustion in local heating boilers; marine aerosol; mineral dust; primary biological/wood burning; road dust, car brakes; and gypsum. The main summer factors were assigned to mineral dust (38.2%) and primary biological/wood burning (33.1%). In winter, combustion factors dominated (80%) contribution to PM1–10. The conditional probability function (CPF) helped to identified local sources of PM1–10. The source of marine aerosol from the North Sea and English Channel was indicated by the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT). Implications: This is the first application of PMF to highly time/size resolved PM data in Czech Republic. The coarse aerosol fraction, PM1–10, was chosen with regard to industrial character of the region, sampling site near the coal strip mine and coal power stations. Contrary to expectation, source apportionment did not show dominance of emissions from the coal strip mine. The results will enable local authorities and state bodies responsible for air quality assessment to focus on sources most responsible for air pollution in this industrial region. Supplemental Materials: Supplemental materials are available for this paper. Go to the publishers online edition of the Journal of the Air & Waste Management Association for (1) details of measurement campaigns; (2) CPF for each of the sources contributing to PM1–10; (3) factors contribution to PM1–10 resolved by PMF; (4) diurnal pattern of road dust, car brake factor in summer and winter; (5) trajectories during the marine aerosol episode in winter 2010; and (6) temporal temperature, concentration, and wind speed relationships during the summer 2008 campaign and winter 2010 campaign.

An insight into the complex roles of metallothioneins in malignant diseases with emphasis on (sub)isoforms/isoforms and epigenetics phenomena

ABSTRACT Metallothioneins (MTs) belong to a group of small cysteine‐rich proteins that are ubiquitous throughout all kingdoms. The main function of MTs is scavenging of free radicals and detoxification and homeostating of heavy metals. In humans, 16 genes localized on chromosome 16 have been identified to encode four MT isoforms labelled by numbers (MT‐1–MT‐4). MT‐2, MT‐3 and MT‐4 proteins are encoded by a single gene. MT‐1 comprises many (sub)isoforms. The known active MT‐1 genes are MT‐1A, ‐1B, ‐1E, ‐1F, ‐1G, ‐1H, ‐1M and ‐1X. The rest of the MT‐1 genes (MT‐1C, ‐1D, ‐1I, ‐1J and ‐1L) are pseudogenes. The expression and localization of individual MT (sub)isoforms and pseudogenes vary at intra‐cellular level and in individual tissues. Changes in MT expression are associated with the process of carcinogenesis of various types of human malignancies, or with a more aggressive phenotype and therapeutic resistance. Hence, MT (sub)isoform profiling status could be utilized for diagnostics and therapy of tumour diseases. This review aims on a comprehensive summary of methods for analysis of MTs at (sub)isoforms levels, their expression in single tumour diseases and strategies how this knowledge can be utilized in anticancer therapy.

Impact of Mining Activities on the Air Quality in The Village Nearby a Coal Strip Mine

The objective of the presented study was to estimate a share of atmospheric aerosol emitted by coal strip mine on PM10 or PM1-10, mass concentration of aerosol particles < 10μm or 1-10μm in aerodynamic diameter respectively, in the village situated in proximity to the mine. Parallel measurements were conducted in the mine and village situated in the northern part of the Czech Republic from the 15th to 27th November 2012. Three size fractions, consisting PM10, were sampled by a Davis rotating-drum impactor and analysed for 27 elements by Synchrotron-XRF with time resolution 1 hour. Appropriate hourly PM10 were measured by a Beta attenuation monitor in the village and calculated from 5 minute values by a nephelometer in the mine. Also, 24 hour aerosol samples for five size fractions were sampled by a personal cascade impactor sampler and viewed by scanning electron microscopy - SEM. Meteorological parameters were also recorded. Average contribution of coarse aerosol, PM1-10, to PM10 was 70% (119 +59 μgm-3) in the mine and 20% (12 + 10 μgm-3) in the village. The SEM revealed solely soil particles in the mine samples but bioaerosol, ash and aggregates of ultrafine particles in the village samples. Databases of hourly elemental and mass concentrations from the two localities were analysed by EPA PMF 5.0. There were revealed following sources/average contribution to local PM10: wood burning/34%, resuspended dust/30%, coal combustion/22%, industry/11% and gypsum/3% in the village while resuspended dust/43%, coal combustion/37%, gypsum/16% and mining technologies/4% in the mine. Based on factor chemical profiles, the mine was found to contribute to PM1-10 and PM10 in the village by 6% and 20%, respectively.

Bevacizumab with chemotherapy in patients with KRAS wild-type metastatic colorectal cancer: Czech registry data

AIM This retrospective analysis investigated the effectiveness of combination therapy with bevacizumab and chemotherapy in the first-line treatment of patients with KRAS wild-type metastatic colorectal cancer. PATIENTS & METHODS Patients with KRAS wild-type metastatic colorectal cancer in the CORECT registry who initiated treatment with bevacizumab between 2008 and 2012 were enrolled. Overall survival and progression-free survival were the main effectiveness end points. RESULTS A total of 981 patients were enrolled. Median progression-free survival was 11.3 months (95% CI: 10.7-11.8) and median overall survival was 28.4 months (95% CI: 26.2-30.6). The most common adverse events were thromboembolic disease (4%) and hypertension (3.5%). CONCLUSION This retrospective analysis shows the effectiveness of bevacizumab with chemotherapy in patients with KRAS wild-type metastatic colorectal cancer.