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Exposure to Particles and Nitrogen Dioxide Among Workers in the Stockholm Underground Train System
N. Plato,C. Bigert,B.-M. Larsson,M. Alderling,M. Svartengren,P. Gustavsson 한국산업안전보건공단 산업안전보건연구원 2019 Safety and health at work Vol.10 No.3
Objectives: Exposure to fine particles in urban air has been associated with a number of negative health effects. High levels of fine particles have been detected at underground stations in big cities. We investigated the exposure conditions in four occupational groups in the Stockholm underground train system to identify high-exposed groups and study variations in exposure. Methods: PM1 and PM2.5 were measured during three full work shifts on 44 underground workers. Fluctuations in exposure were monitored by a real-time particle monitoring instrument, pDR, DataRAM. Qualitative analysis of particle content was performed using inductively coupled plasma mass spectrometry. Nitrogen dioxide was measured using passive monitors. Results: For all underground workers, the geometric mean (GM) of PM1 was 18 mg/m3 and of PM2.5 was 37 mg/m3. The particle exposure was highest for cleaners/platform workers, and the GM of PM1 was 31.6 mg/m3 [geometric standard deviation (GSD), 1.6] and of PM2.5 was 76.5 mg/m3 (GSD, 1.3); the particle exposure was lowest for ticket sellers, and the GM of PM1 was 4.9 mg/m3 (GSD, 2.1) and of PM2.5 was 9.3 mg/m3 (GSD, 1.5). The PM1 and PM2.5 levels were five times higher in the underground system than at the street level, and the particles in the underground had high iron content. The train driver’s nitrogen dioxide exposure level was 64.1 mg/m3 (GSD, 1.5). Conclusions: Cleaners and other platform workers were statistically significantly more exposed to particles than train drivers or ticket sellers. Particle concentrations (PM2.5) in the Stockholm underground system were within the same range as in the New York underground system but were much lower than in several older underground systems around the world.
Exposure to Particles and Nitrogen Dioxide Among Workers in the Stockholm Underground Train System
Plato, N.,Bigert, C.,Larsson, B.M.,Alderling, M.,Svartengren, M.,Gustavsson, P. Occupational Safety and Health Research Institute 2019 Safety and health at work Vol.10 No.3
Objectives: Exposure to fine particles in urban air has been associated with a number of negative health effects. High levels of fine particles have been detected at underground stations in big cities. We investigated the exposure conditions in four occupational groups in the Stockholm underground train system to identify high-exposed groups and study variations in exposure. Methods: $PM_1$ and $PM_{2.5}$ were measured during three full work shifts on 44 underground workers. Fluctuations in exposure were monitored by a real-time particle monitoring instrument, pDR, DataRAM. Qualitative analysis of particle content was performed using inductively coupled plasma mass spectrometry. Nitrogen dioxide was measured using passive monitors. Results: For all underground workers, the geometric mean (GM) of $PM_1$ was $18{\mu}g/m^3$ and of $PM_{2.5}$ was $37{\mu}g/m^3$. The particle exposure was highest for cleaners/platform workers, and the GM of $PM_1$ was $31.6{\mu}g/m^3$ [geometric standard deviation (GSD), 1.6] and of $PM_{2.5}$ was $76.5{\mu}g/m^3$ (GSD, 1.3); the particle exposure was lowest for ticket sellers, and the GM of $PM_1$ was $4.9{\mu}g/m^3$ (GSD, 2.1) and of $PM_{2.5}$ was $9.3{\mu}g/m^3$ (GSD, 1.5). The $PM_1$ and $PM_{2.5}$ levels were five times higher in the underground system than at the street level, and the particles in the underground had high iron content. The train driver's nitrogen dioxide exposure level was $64.1{\mu}g/m^3$ (GSD, 1.5). Conclusions: Cleaners and other platform workers were statistically significantly more exposed to particles than train drivers or ticket sellers. Particle concentrations ($PM_{2.5}$) in the Stockholm underground system were within the same range as in the New York underground system but were much lower than in several older underground systems around the world.
Unraveling the Biological Roles of Reactive Oxygen Species
Murphy, Michael P.,Holmgren, A.,Larsson, N.G.,Halliwell, B.,Chang, Christopher J.,Kalyanaraman, B.,Rhee, S.,Thornalley, Paul J.,Partridge, L.,Gems, D.,Nystrom, T.,Belousov, V.,Schumacker, Paul T.,Wint Cell Press 2011 Cell metabolism Vol.13 No.4
Reactive oxygen species are not only harmful agents that cause oxidative damage in pathologies, they also have important roles as regulatory agents in a range of biological phenomena. The relatively recent development of this more nuanced view presents a challenge to the biomedical research community on how best to assess the significance of reactive oxygen species and oxidative damage in biological systems. Considerable progress is being made in addressing these issues, and here we survey some recent developments for those contemplating research in this area.
Cho, Y.,Cole, R.,Ikaga, T.,Larsson, N.,Moro, A.,Rovers, R.,Shin, S. Sustainable Building Research Center 2010 International journal of sustainable building tech Vol.1 No.1
The purpose of the discussion is to enhance the understanding of importance of sustainable development in the industry and to expand the international relation on the technology of sustainable architecture. The theme of SB10 SEOUL conference, "Sustainable Building Assessment Technology and Strategies for Higher Education" is selected to expand the knowledge of the current condition and the direction of future in sustainable building assessment technology.
Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation
Malta, Tathiane M.,Sokolov, Artem,Gentles, Andrew J.,Burzykowski, Tomasz,Poisson, Laila,Weinstein, John N.,Kamiń,ska, Boż,ena,Huelsken, Joerg,Omberg, Larsson,Gevaert, Olivier,Colaprico, Anto Elsevier 2018 Cell Vol.173 No.2
<P><B>Summary</B></P> <P>Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovative one-class logistic regression (OCLR) machine-learning algorithm to extract transcriptomic and epigenetic feature sets derived from non-transformed pluripotent stem cells and their differentiated progeny. Using OCLR, we were able to identify previously undiscovered biological mechanisms associated with the dedifferentiated oncogenic state. Analyses of the tumor microenvironment revealed unanticipated correlation of cancer stemness with immune checkpoint expression and infiltrating immune cells. We found that the dedifferentiated oncogenic phenotype was generally most prominent in metastatic tumors. Application of our stemness indices to single-cell data revealed patterns of intra-tumor molecular heterogeneity. Finally, the indices allowed for the identification of novel targets and possible targeted therapies aimed at tumor differentiation.</P> <P><B>Video Abstract</B></P> <P>Display Omitted</P> <P><B>Highlights</B></P> <P> <UL> <LI> Epigenetic and expression-based stemness indices measure oncogenic dedifferentiation </LI> <LI> Immune microenvironment content and PD-L1 levels associate with stemness indices </LI> <LI> Stemness index is increased in metastatic tumors and reveals intratumor heterogeneity </LI> <LI> Applying stemness indices reveals potential drug targets for anti-cancer therapies </LI> </UL> </P> <P><B>Graphical Abstract</B></P> <P>[DISPLAY OMISSION]</P>
Terzioglu, M.,Ruzzenente, B.,Harmel, J.,Mourier, A.,Jemt, E.,Lopez, M.,Kukat, C.,Stewart, James B.,Wibom, R.,Meharg, C.,Habermann, B.,Falkenberg, M.,Gustafsson, Claes M.,Park, C.,Larsson, N.G. Cell Press 2013 Cell metabolism Vol.17 No.4
Mitochondrial transcription termination factor 1, MTERF1, has been reported to couple rRNA gene transcription initiation with termination and is therefore thought to be a key regulator of mammalian mitochondrial ribosome biogenesis. The prevailing model is based on a series of observations published over the last two decades, but no in vivo evidence exists to show that MTERF1 regulates transcription of the heavy-strand region of mtDNA containing the rRNA genes. Here, we demonstrate that knockout of Mterf1 in mice has no effect on mitochondrial rRNA levels or mitochondrial translation. Instead, loss of Mterf1 influences transcription initiation at the light-strand promoter, resulting in a decrease of de novo transcription manifested as reduced 7S RNA levels. Based on these observations, we suggest that MTERF1 does not regulate heavy-strand transcription, but rather acts to block transcription on the opposite strand of mtDNA to prevent transcription interference at the light-strand promoter.