Metabolic Profiling as Well as Stable Isotope Assisted Metabolic and Proteomic Analysis of RAW 264.7 Macrophages Exposed to Ship Engine Aerosol Emissions: Different Effects of Heavy Fuel Oil and Refined Diesel Fuel

Exposure to air pollution resulting from fossil fuel combustion has been linked to multiple short-term and long term health effects. In a previous study, exposure of lung epithelial cells to engine exhaust from heavy fuel oil (HFO) and diesel fuel (DF), two of the main fuels used in marine engines, led to an increased regulation of several pathways associated with adverse cellular effects, including pro-inflammatory pathways. In addition, DF exhaust exposure was shown to have a wider response on multiple cellular regulatory levels compared to HFO emissions, suggesting a potentially higher toxicity of DF emissions over HFO. In order to further understand these effects, as well as to validate these findings in another cell line, we investigated macrophages under the same conditions as a more inflammationrelevant model. An air-liquid interface aerosol exposure system was used to provide a more biologically relevant exposure system compared to submerged experiments, with cells exposed to either the complete aerosol (particle and gas phase), or the gas phase only (with particles filtered out). Data from cytotoxicity assays were integrated with metabolomics and proteomics analyses, including stable isotope-assisted metabolomics, in order to uncover pathways affected by combustion aerosol exposure in macrophages. Through this approach, we determined differing phenotypic effects associated with the different components of aerosol. The particle phase of diluted combustion aerosols was found to induce increased cell death in macrophages, while the gas phase was found more to affect the metabolic profile. In particular, a higher cytotoxicity of DF aerosol emission was observed in relation to the HFO aerosol. Furthermore, macrophage exposure to the gas phase of HFO leads to an induction of a pro-inflammatory metabolic and proteomic phenotype. These results validate the effects found in lung epithelial cells, confirming the role of inflammation and cellular stress in the response to combustion aerosols

Emissions from a modern log wood masonry heater and wood pellet boiler : Composition and biological impact on air-liquid interface exposed human lung cancer cells

The consumption of wood fuel is markedly increasing in developing and industrialized countries. Known side effects of wood smoke inhalation manifest in proinflammatory signaling, oxidative stress, DNA damage and hence increased cancer risk. In this study, the composition and acute biological impact of emissions of state-of-the-art wood combustion compliances: masonry heater (MH) and pellet boiler (PB) were investigated. Therefore A549 cells were exposed to emission aerosols in an automated air-liquid interface exposure station followed by cytotoxicity, transcriptome and proteome analyses. In parallel, aerosols were subjected to a chemical and physical haracterization. Compared to PB, the MH combustion at the same dilution ratio resulted in a 3-fold higher particle mass concentration (PM2.5) and deposited dose (PB: 27 $\pm$ 2 ng/cm2, MH; 73 $\pm$ 12 ng/cm2). Additionally, the MH aerosol displayed a substantially larger concentration of aldehydes, polycyclic aromatic hydrocarbons (PAH) or oxidized PAH. Gene ontology analysis of transcriptome of A549 cells exposed to MH emissions revealed the activation of proinflammatory response and key signaling cascades MAP kinase and JAK-STAT. Furthermore, CYP1A1, an essential enzyme in PAH metabolism, was induced. PB combustion aerosol activated the proinflammatory marker IL6 and different transport processes. The proteomics data uncovered induction of DNA damage-associated proteins in response to PB and DNA doublestrand break processing proteins in response to MH emissions. Taking together, the MH produces emissions with a higher particle dose and more toxic compounds while causing only mild biological responses. This finding points to a significant mitigating effect of antioxidative compounds in MH wood smoke

Tactile Feedback for Artery Detection in Minimally Invasive Robotic Surgery –Preliminary Results of a New Approach

Minimally invasive robotic surgery (MIRS) entails total absence of haptic feedback due to the spatial separation of patient and surgeon. In conventional surgery, however, palpation to detect superficial arteries by a slight pulsation is an important, commonly applied, and security-relevant procedure. Therefore, an ultrasound based unidirectional sensor for MIRS was developed feeding back kinesthetic impulses to the surgeon-sided haptic input device

Determination of Relative Ionization Cross Sections for Resonance Enhanced Multiphoton Ionization of Polycyclic Aromatic Hydrocarbons

Resonance enhanced multiphoton ionization (REMPI) is a powerful method for the sensitive determination of polycyclic aromatic hydrocarbons (PAHs) in gaseous mixtures via mass spectrometry (MS). In REMPI, ions are produced by the absorption of at least two photons including defined electronic intermediate states. As a result—unlike other laser-based ionization techniques—spectroscopic selectivity is involved into the ionization process. Nevertheless, these wavelength-dependent ionization rates impede the quantification using REMPI. For this purpose, relative photoionization cross sections (relPICS) give an easy-to-use approach to quantify REMPI-MS measurements. Hereby, the ionization behavior of a single compound was compared to that of a reference substance of a given concentration. In this study, relPICS of selected single-core aromatics and PAHs at wavelengths of 266 nm and 248 nm were determined using two different time-of-flight mass spectrometric systems (TOFMS). For PAHs, relPICS were obtained which showed a strong dependence on the applied laser intensity. In contrast, for single-core aromatics, constant values of relPICS were determined. Deviations of relPICS between both TOFMS systems were found for small aromatics (e.g., benzene), which can be assigned to the differences in UV generation in the particular system. However, the relPICS of this study were found to be in good agreement with previous results and can be used for system-independent quantification

In situ detection of munition compounds in coastal waters

Disposal of munitions at dumpsites in coastal seas was conducted after WW I and II. Also, large amounts of unexploded munitions from wartime activities litter the seafloor. Corrosion of munition shells causes release of toxic munition compounds (MCs). Furthermore, explosion risks increase due to large-scale economic developments in coastal waters. Seafloor munition clearance by commercial and military entities form an ongoing task to eliminate environmental and security risks. Munition detection primarily relies on geophysical techniques. However, these methods do not provide unequivocal signatures for ordnance and suffer from false positives. Here we assess chemical approaches using spectroscopic and spectrometric methods for ordnance detection in seawater with a primary focus on MCs, but also including chemical warfare agents. We discuss novel analytical techniques suitable for near real-time munition detection at sea, incorporating pre-concentration and matrix removal steps of seawater samples. We also describe emerging real-time technologies for on-site MC detection in coastal waters

Publisher Correction: Nanoplasmonic electron acceleration by attosecond-controlled forward rescattering in silver clusters

The original PDF version of this Article contained an error in Equation 1. The original HTML version of this Article contained errors in Equation 2 and Equation 4. These errors have now been corrected in both the PDF and the HTML versions of the Article

Publisher Correction: Nanoplasmonic electron acceleration by attosecond-controlled forward rescattering in silver clusters (Nature communications (2017) 8 1 (1181))

The original PDF version of this Article contained an error in Equation 1. The original HTML version of this Article contained errors in Equation 2 and Equation 4. These errors have now been corrected in both the PDF and the HTML versions of the Article. The original PDF version of this Article contained an error in Equation 1. A dot over the first occurrence of the variable ri was missing, and incorrectly read: (Formula Presented). The correct form of Equation 1 is as follows: (Formula Presented). This has now been corrected in the PDF version of the Article. The HTML version was correct from the time of publication. The original HTML version of this Article contained errors in Equation 2 and Equation 4. In Equation 2, a circle over the first occurrence of the variable ri replaced the intended dot, and incorrectly read: (Formula Presented). The correct form of Equation 2 is as follows: (Formula Presented). In Equation 4, circles over the first and fifth occurrences of the variable ri replaced the intended dots, and incorrectly read: (Formula Presented). The correct form of Equation 4 is as follows: (Formula Presented). This has now been corrected in the HTML version of the Article. The PDF version was correct from the time of publication