Fugitive emissions in Moravian-Silesian Region

Import 22/07/2015Predložená práca sa zaoberá fugitívnymi emisiami na území priemyselnej aglomerácie Ostravska. Fugitívny prach predstavuje hlavnú časť atmosférických aerosólov, zvýšená pozornosť je mu venovaná kvôli významným dopadom na zmenu klímy, kvalitu ovzdušia a zdravie ľudí a ekosystémov. Hlavná časť práce je venovaná štúdiu vertikálnej distribúcie PM1 vo výške až 500 m n. m., ktorá bola sledovaná vo vybraných lokalitách Ostravy v jarnom a letnom období 2014, za použitia metódy merania balónom. Pozornosť bola venovaná závislosti koncentrácie PM1 na výške a meteorologických podmienkach. Ďalej bolo zisťované rozloženie organických látok vo vertikálnych profiloch atmosféry v najzaťaženejších miestach Ostravy použitím metódy Py-GC/MS a pomocou matematických metód boli identifikované príspevky zdrojov znečistenia.This thesis deals with the topic of fugitive emissions in the industrial agglomeration of Ostrava region. Fugitive dust is a major part of atmospheric aerosols, increased attention is given to it due to its significant impact on climate change, air quality and human health, and ecosystems. The main part is focused on the study of the vertical distribution of PM1 of up to 500 m a. s. l. which was monitored at selected locations during spring and summer seasons of 2014 using the balloon measuring method. Attention was given to influence of meteorological parameters on PM1 concentrations. Furthermore, distribution of organic matter in the vertical profiles of the atmosphere in the most exposed places was studied using the Py-GC/MS and, using the mathematical methods, contributions of the sources of pollution were identified.Prezenční546 - Institut environmentálního inženýrstvívýborn

Identification of Novel Reference Genes Suitable for qRT-PCR Normalization with Respect to the Zebrafish Developmental Stage

<div><p>Reference genes used in normalizing qRT-PCR data are critical for the accuracy of gene expression analysis. However, many traditional reference genes used in zebrafish early development are not appropriate because of their variable expression levels during embryogenesis. In the present study, we used our previous RNA-Seq dataset to identify novel reference genes suitable for gene expression analysis during zebrafish early developmental stages. We first selected 197 most stably expressed genes from an RNA-Seq dataset (29,291 genes in total), according to the ratio of their maximum to minimum RPKM values. Among the 197 genes, 4 genes with moderate expression levels and the least variation throughout 9 developmental stages were identified as candidate reference genes. Using four independent statistical algorithms (delta-CT, geNorm, BestKeeper and NormFinder), the stability of qRT-PCR expression of these candidates was then evaluated and compared to that of <i>actb1</i> and <i>actb2</i>, two commonly used zebrafish reference genes. Stability rankings showed that two genes, namely <i>mobk13 (mob4)</i> and <i>lsm12b</i>, were more stable than <i>actb1</i> and <i>actb2</i> in most cases. To further test the suitability of <i>mobk13</i> and <i>lsm12b</i> as novel reference genes, they were used to normalize three well-studied target genes. The results showed that <i>mobk13</i> and <i>lsm12b</i> were more suitable than <i>actb1</i> and <i>actb2</i> with respect to zebrafish early development. We recommend <i>mobk13</i> and <i>lsm12b</i> as new optimal reference genes for zebrafish qRT-PCR analysis during embryogenesis and early larval stages.</p></div

mTOR mediated miR-99a antitumor activity in breast cancer cells.

<p>(A) mTOR depletion-mediated cell viability and apoptosis. MCF-7 cells were transfected with MOCK, NC and mTOR siRNA respectively. An MTT cell viability assay was performed at 0, 12, 24, 48 and 72 h. Cell apoptosis was analyzed at 72 h post-transfection, as described in Materials and methods. (B) Cell survival analysis by overexpression of mTOR in breast cancer cells. MDA-MB-231 cells were transfected with MOCK, NC and mTOR cDNA plasmid without the 3′-UTR respectively. (C) miR-99a-mediated cell survival and mTOR rescue analysis in breast cancer cells. MCF-7 cells were co-transfected by miR-99a mimics and mTOR cDNA plasmid without the 3′-UTR followed by MTT assay and apoptosis analysis, as described in Materials and methods.</p

The inhibitory effect of miR-99a mimics on human breast cancer cells.

<p>(A) Cell viability MTT assay. The cell viability curve was constructed consecutively for up to 72 h after transfection of MCF-7 and MDA-MB-231 cells with Lipofectamine 2000 only (MOCK), scrambled negative control (NC) and miR-99a mimics. (B) Flow cytometry analysis of cell cycle. At 72 h post-transfection, MCF-7 and MDA-MB-231 cell lines treated with miR-99a mimics showed a remarkable increased sub-G1 phase population compared with MOCK and NC groups. (C) Flow cytometry analysis of apoptosis. After 72 h treatment, transfection of miR-99a mimics into MCF-7 and MDA-MB-231 cell lines resulted in a significant increase percentage of apoptotic cells compared with the control. (D) The tumors shown are from the final time point (30_day). Xenograft sizes from six representative nude mice from three treatment groups (MDA-MB-231 cells with CMV-miR-99a, CMV-NC and MOCK). (E) The xenograft growth analysis after breast cancer cell inoculation. The average size of the tumors was measured every 5 days and shown in the curves (P<0.05 compared to the control cells).</p

Mean CT and SD distribution of the six genes evaluated.

<p>Each set of charts shows the mean CT and SD for each gene evaluated. OP and RP groups are shown in light and dark grey, respectively. The short bars represent positive standard deviation values (SD).</p

Normalization of three target genes with 4 reference genes.

<p>For the target genes, the real-time qRT-PCR derived relative expression levels (A, D and G for OP group. C, F and I for RP group), and the RPKM values (B, E and H) are shown. For the qRT-PCR results, the black circles and the line represent the relative expression levels normalized by <i>actb1</i>, the red circles and the line show those normalized by <i>actb2</i>, while the green and the blue ones represent those normalized by <i>lsm12b</i> and <i>mobk13</i>, respectively. The high consistency between RPKM values and the qRT-PCR derived expression levels suggests that all the four reference genes were appropriate for <i>szl</i> normalization, while <i>lsm12b</i>and <i>mobk13</i> are the best for <i>fzd7a</i> and <i>sox7</i> normalization, respectively.</p

Characteristic expression of the tested genes.

<p>(A) A heatmap was used to visualize the expression pattern of the six tested genes at nine stages in zebrafish development. (B) Expression levels and variations of the tested genes at the 9 stages. As shown in four candidate genes, namely <i>ssr2</i>, <i>C1H16orf72</i>, <i>lsm12b</i> and <i>mobk13</i>, were more stable than the commonly used reference genes <i>actb1</i> and <i>actb2</i> during early development.</p

miR-99a regulated expression of mTOR downstream signaling pathway genes p-4E-BP1 and p-S6K1.

<p>(A-C) Immunoblot analyses of total and phosphorylated 4E-BP1 and S6K1 from MCF-7 breast cancer cells transfected with miR-99a mimics (A), mTOR siRNA(B), and co-transfection of both miR-99a mimics and mTOR cDNA plasmid without the 3′-UTR(C). Levels of p-4E-BP1 and p-S6K1 proteins were both markedly decreased after miR-99a mimics transfection in MCF-7 cells, Knockdown of mTOR expression using mTOR siRNA also distinctly reduced levels of p-4E-BP1 and p-S6K1 proteins, however, total 4E-BP1 and S6K1 protein showed no change; The inhibitory effects of miR-99a mimics on p-4E-BP1 and p-S6K1 could be negated by re-expression of mTOR.</p

Characterization of the six tested genes.

<p>Characterization of the six tested genes.</p

Statistical correlation between the expression levels of miR-99a and mTOR protein in breast cancer tissues and cell lines (A) mTOR protein was analyzed by Western blotting in 10 pairs of breast cancer tissues.

<p>(B) mTOR protein was analyzed in four different breast cancer cell lines and a breast epithelial cell line. Data were normalized to GAPDH protein and represent the mean <u>±</u> SD of three independent duplicate experiments. *, P<0.05 significant differences from HBL-100. (C) The inverse correlation in breast cancer tissues was analyzed by Pearson's correlation method.</p