Oxygenated organic functional groups and their sources in single and submicron organic particles in MILAGRO 2006 campaign

Fourier Transform Infrared (FTIR) and X-ray Fluorescence (XRF) were used to measure organic functional groups and elements of submicron particles collected during MILAGRO in March 2006 on three platforms: the Mexico City urban area (SIMAT), the high altitude site at 4010 m (Altzomoni), and the NCAR C130 aircraft. Scanning Transmission X-ray Microscopy (STXM) and Near-Edge X-ray Absorption Fine Structure (NEXAFS) were applied to single particle organic functional group abundance analysis of particles simultaneously collected at SIMAT and C130. Correlations of elemental concentrations showed different groups of source-related elements at SIMAT, Altzomoni, and C130, suggesting different processes affecting the air masses sampled at the three platforms. Cluster analysis resulted in seven distinct clusters of FTIR spectra, with the last three clusters consisting of spectra collected almost exclusively on the C130 platform, reflecting the variety of sources contributing to C130 samples. Positive Matrix Factorization (PMF) of STXM-NEXAFS spectra identified three main factors representing soot, secondary, and biomass burning type spectra. PMF of FTIR spectra resulted in two fossil fuel combustion factors and one biomass burning factor, the former representative of source regions to the northeast and southwest of SIMAT. Alkane, carboxylic acid, amine, and alcohol functional groups were mainly associated with combustion related sources, while non-acid carbonyl groups were likely from biomass burning events. The majority of OM and O/C was attributed to combustion sources, although no distinction between direct emissions and atmospherically processed OM could be identified

Biogenic and biomass burning organic aerosol in a boreal forest at Hyytiälä, Finland, during HUMPPA-COPEC 2010

Submicron aerosol particles were collected during July and August 2010 in Hyytiälä, Finland, to determine the composition and sources of aerosol at that boreal forest site. Submicron particles were collected on Teflon filters and analyzed by Fourier transform infrared (FTIR) spectroscopy for organic functional groups (OFGs). Positive matrix factorization (PMF) was applied to aerosol mass spectrometry (AMS) measurements and FTIR spectra to identify summertime sources of submicron aerosol mass at the sampling site. The two largest sources of organic mass (OM) in particles identified at Hyytiälä were (1) biogenic aerosol from surrounding local forest and (2) biomass burning aerosol, transported 4–5 days from large wildfires burning near Moscow, Russia, and northern Ukraine. The robustness of this apportionment is supported by the agreement of two independent analytical methods for organic measurements with three statistical techniques. FTIR factor analysis was more sensitive to the chemical differences between biogenic and biomass burning organic components, while AMS factor analysis had a higher time resolution that more clearly linked the temporal behavior of separate OM factors to that of different source tracers even though their fragment mass spectrum were similar. The greater chemical sensitivity of the FTIR is attributed to the nondestructive preparation and the functional group specificity of spectroscopy. The FTIR spectra show strong similarities among biogenic and biomass burning factors from different regions as well as with reference OM (namely olive tree burning organic aerosol and α-pinene chamber secondary organic aerosol (SOA)). The biogenic factor correlated strongly with temperature and oxidation products of biogenic volatile organic compounds (BVOCs), included more than half of the oxygenated OFGs (carbonyl groups at 29% and carboxylic acid groups at 22%), and represented 35% of the submicron OM. Compared to previous studies at Hyytiälä, the summertime biogenic OM is 1.5 to 3 times larger than springtime biogenic OM (0.64 μg m^−3 and 0.4 μg m^−3, measured in 2005 and 2007, respectively), even though it contributed only 35% of OM. The biomass burning factor contributed 25% of OM on average and up to 62% of OM during three periods of transported biomass burning emissions: 26–28 July, 29–30 July, and 8–9 August, with OFG consisting mostly of carbonyl (41%) and alcohol (25%) groups. The high summertime terrestrial biogenic OM (1.7 μg m^−3) and the high biomass burning contributions (1.2 μg m^−3) were likely due to the abnormally high temperatures that resulted in both stressed boreal forest conditions with high regional BVOC emissions and numerous wildfires in upwind regions

Interconnections of Reactive Oxygen Species Homeostasis and Circadian Rhythm in Neurospora crassa.

Abstract Significance: Both circadian rhythm and the production of reactive oxygen species (ROS) are fundamental features of aerobic eukaryotic cells. The circadian clock enhances the fitness of organisms by enabling them to anticipate cycling changes in the surroundings. ROS generation in the cell is often altered in response to environmental changes, but oscillations in ROS levels may also reflect endogenous metabolic fluctuations governed by the circadian clock. On the other hand, an effective regulation and timing of antioxidant mechanisms may be crucial in the defense of cellular integrity. Thus, an interaction between the circadian timekeeping machinery and ROS homeostasis or signaling in both directions may be of advantage at all phylogenetic levels. Recent Advances: The Frequency-White Collar-1 and White Collar-2 oscillator (FWO) of the filamentous fungus Neurospora crassa is well characterized at the molecular level. Several members of the ROS homeostasis were found to be controlled by the circadian clock, and ROS levels display circadian rhythm in Neurospora. On the other hand, multiple data indicate that ROS affect the molecular oscillator. Critical Issues: Increasing evidence suggests the interplay between ROS homeostasis and oscillators that may be partially or fully independent of the FWO. In addition, ROS may be part of a complex cellular network synchronizing non-transcriptional oscillators with timekeeping machineries based on the classical transcription-translation feedback mechanism. Future Directions: Further investigations are needed to clarify how the different layers of the bidirectional interactions between ROS homeostasis and circadian regulation are interconnected. Antioxid. Redox Signal. 00, 000-000

Influence of crustal dust and sea spray supermicron particle concentrations and acidity on inorganic NO_3^- aerosol during the 2013 Southern Oxidant and Aerosol Study

Inorganic aerosol composition was measured in the southeastern United States, a region that exhibits high aerosol mass loading during the summer, as part of the 2013 Southern Oxidant and Aerosol Study (SOAS) campaign. Measurements using a Monitor for AeRosols and GAses (MARGA) revealed two periods of high aerosol nitrate (NO_^3−) concentrations during the campaign. These periods of high nitrate were correlated with increased concentrations of supermicron crustal and sea spray aerosol species, particularly Na^+ and Ca^(2+), and with a shift towards aerosol with larger (1 to 2.5 μm) diameters. We suggest this nitrate aerosol forms by multiphase reactions of HNO_3 and particles, reactions that are facilitated by transport of crustal dust and sea spray aerosol from a source within the United States. The observed high aerosol acidity prevents the formation of NH_4NO_3, the inorganic nitrogen species often dominant in fine-mode aerosol at higher pH. Calculation of the rate of the heterogeneous uptake of HNO_3 on mineral aerosol supports the conclusion that aerosol NO_3^− is produced primarily by this process, and is likely limited by the availability of mineral cation-containing aerosol surface area. Modeling of NO_3^− and HNO_3 by thermodynamic equilibrium models (ISORROPIA II and E-AIM) reveals the importance of including mineral cations in the southeastern United States to accurately balance ion species and predict gas–aerosol phase partitioning

Selected reactive oxygen species and antioxidant enzymes in common bean after Pseudomonas syringae pv. phaseolicola and Botrytis cinerea infection

Phaseolus vulgaris cv. Korona plants were inoculated with the bacteria Pseudomonas syringae pv. phaseolicola (Psp), necrotrophic fungus Botrytis cinerea (Bc) or with both pathogens sequentially. The aim of the experiment was to determine how plants cope with multiple infection with pathogens having different attack strategy. Possible suppression of the non-specific infection with the necrotrophic fungus Bc by earlier Psp inoculation was examined. Concentration of reactive oxygen species (ROS), such as superoxide anion (O2 -) and H2O2 and activities of antioxidant enzymes such as superoxide dismutase (SOD), catalase (CAT) and peroxidase (POD) were determined 6, 12, 24 and 48 h after inoculation. The measurements were done for ROS cytosolic fraction and enzymatic cytosolic or apoplastic fraction. Infection with Psp caused significant increase in ROS levels since the beginning of experiment. Activity of the apoplastic enzymes also increased remarkably at the beginning of experiment in contrast to the cytosolic ones. Cytosolic SOD and guaiacol peroxidase (GPOD) activities achieved the maximum values 48 h after treatment. Additional forms of the examined enzymes after specific Psp infection were identified; however, they were not present after single Bc inoculation. Subsequent Bc infection resulted only in changes of H2O2 and SOD that occurred to be especially important during plant–pathogen interaction. Cultivar Korona of common bean is considered to be resistant to Psp and mobilises its system upon infection with these bacteria. We put forward a hypothesis that the extent of defence reaction was so great that subsequent infection did not trigger significant additional response

Ethylene Synthesis and Regulated Expression of Recombinant Protein in Synechocystis sp PCC 6803

The ethylene-forming enzyme (EFE) from Pseudomonas syringae catalyzes the synthesis of ethylene which can be easily detected in the headspace of closed cultures. A synthetic codon-optimized gene encoding N-terminal His-tagged EFE (EFEh) was expressed in Synechocystis sp. PCC 6803 (Synechocystis) and Escherichia coli (E. coli) under the control of diverse promoters in a self-replicating broad host-range plasmid. Ethylene synthesis was stably maintained in both organisms in contrast to earlier work in Synechococcus elongatus PCC 7942. The rate of ethylene accumulation was used as a reporter for protein expression in order to assess promoter strength and inducibility with the different expression systems. Several metal-inducible cyanobacterial promoters did not function in E. coli but were well-regulated in cyanobacteria, albeit at a low level of expression. The E. coli promoter P(trc) resulted in constitutive expression in cyanobacteria regardless of whether IPTG was added or not. In contrast, a Lac promoter variant, P(A1lacO-1), induced EFE-expression in Synechocystis at a level of expression as high as the Trc promoter and allowed a fine level of IPTG-dependent regulation of protein-expression. The regulation was tight at low cell density and became more relaxed in more dense cultures. A synthetic quorum-sensing promoter system was also constructed and shown to function well in E. coli, however, only a very low level of EFE-activity was observed in Synechocystis, independent of cell density

Tolerance has its limits: how the thymus copes with infection

The thymus is required for T cell differentiation; a process that depends on which antigens are encountered by thymocytes, the environment surrounding the differentiating cells, and the thymic architecture. These features are altered by local infection of the thymus and by the inflammatory mediators that accompany systemic infection. Although once believed to be an immune privileged site, it is now known that antimicrobial responses are recruited to the thymus. Resolving infection in the thymus is important because chronic persistence of microbes impairs the differentiation of pathogen-specific T cells and diminishes resistance to infection. Understanding how these mechanisms contribute to disease susceptibility, particularly in infants with developing T cell repertoires, requires further investigation.We thank Joana Neves and Nadine Santos for critical reading of the manuscript. This work was supported by Portuguese Foundation for Science and Technology (FCT) grant PTDC/SAU-MII/101663/2008 and individual fellowships to CN-A and CN. SMB was supported by National Institutes of Health Grant R01 R56 AI067731

Predicting ambient aerosol thermal-optical reflectance (TOR) measurements from infrared spectra: organic carbon

Organic carbon (OC) can constitute 50% or more of the mass of atmospheric particulate matter. Typically, organic carbon is measured from a quartz fiber filter that has been exposed to a volume of ambient air and analyzed using thermal methods such as thermal-optical reflectance (TOR). Here, methods are presented that show the feasibility of using Fourier transform infrared (FT-IR) absorbance spectra from polytetrafluoroethylene (PTFE or Teflon) filters to accurately predict TOR OC. This work marks an initial step in proposing a method that can reduce the operating costs of large air quality monitoring networks with an inexpensive, non-destructive analysis technique using routinely collected PTFE filter samples which, in addition to OC concentrations, can concurrently provide information regarding the composition of organic aerosol. This feasibility study suggests that the minimum detection limit and errors (or uncertainty) of FT-IR predictions are on par with TOR OC such that evaluation of long-term trends and epidemiological studies would not be significantly impacted. To develop and test the method, FT-IR absorbance spectra are obtained from 794 samples from seven Interagency Monitoring of PROtected Visual Environment (IMPROVE) sites collected during 2011. Partial least-squares regression is used to calibrate sample FT-IR absorbance spectra to TOR OC. The FTIR spectra are divided into calibration and test sets by sampling site and date. The calibration produces precise and accurate TOR OC predictions of the test set samples by FT-IR as indicated by high coefficient of variation (R-2; 0.96), low bias (0.02 mu g m(-3), the nominal IMPROVE sample volume is 32.8 m(3)), low error (0.08 mu g m(-3)) and low normalized error (11%). These performance metrics can be achieved with various degrees of spectral pretreatment (e.g., including or excluding substrate contributions to the absorbances) and are comparable in precision to collocated TOR measurements. FT-IR spectra are also divided into calibration and test sets by OC mass and by OM / OC ratio, which reflects the organic composition of the particulate matter and is obtained from organic functional group composition; these divisions also leads to precise and accurate OC predictions. Low OC concentrations have higher bias and normalized error due to TOR analytical errors and artifact-correction errors, not due to the range of OC mass of the samples in the calibration set. However, samples with low OC mass can be used to predict samples with high OC mass, indicating that the calibration is linear. Using samples in the calibration set that have different OM / OC or ammonium / OC distributions than the test set leads to only a modest increase in bias and normalized error in the predicted samples. We conclude that FT-IR analysis with partial least-squares regression is a robust method for accurately predicting TOR OC in IMPROVE network samples - providing complementary information to the organic functional group composition and organic aerosol mass estimated previously from the same set of sample spectra (Ruthenburg et al., 2014)

Model selection for partial least squares calibration and implications for analysis of atmospheric organic aerosol samples with mid-infrared spectroscopy

In developing partial least squares calibration models, selecting the number of latent variables used for their construction to minimize both model bias and model variance remains a challenge. Several metrics exist for incorporating these trade-offs, but the cost of model parsimony and the potential for underfitting on achievable prediction errors are difficult to anticipate. We propose a metric that penalizes growing model variance against decreasing bias as additional latent variables are added. The magnitude of the penalty is scaled by a user-defined parameter that is formulated to provide a constraint on the fractional increase in root mean square error of cross-validation (RMSECV) when selecting a parsimonious model over the conventional minimum RMSECV solution. We evaluate this approach for quantification of four organic functional groups using 238 laboratory standards and 750 complex atmospheric organic aerosol mixtures with mid-infrared spectroscopy. Parametric variation of this penalty demonstrates that increase in prediction errors due to underfitting is bounded by the magnitude of the penalty for samples similar to laboratory standards used for model training and validation. Imposing an ensemble of penalties corresponding to a 0-30% allowable increase in RMSECV through sum of ranking differences leads to the selection of a model that increases the actual RMSECV up to 20% for laboratory standards but achieves an 85% reduction in the mean error in predicted concentrations for environmental mixtures. Partial least squares models developed with laboratory mixtures can provide useful predictions in complex environmental samples, but may benefit from protection against overfitting. (C) 2015 The Authors. Journal of Chemometrics published by John Wiley & Sons Ltd