Recent experiments have shown that dry and fresh leaves, other plant matter, as well as several structural plant components, emit methane upon irradiation with UV light. Here we present the source ...isotope signatures of the methane emitted from a range of dry natural plant leaves and structural compounds. UV-induced methane from organic matter is strongly depleted in both
13C and D compared to the bulk biomass. The isotopic content of plant methoxyl groups, which have been identified as important precursors of aerobic methane formation in plants, falls roughly halfway between the bulk and CH
4 isotopic composition. C3 and C4/CAM plants show the well-established isotope difference in bulk
13C content. Our results show that they also emit CH
4 with different
δ
13C value. Furthermore,
δ
13C of methoxyl groups in the plant material, and ester methoxyl groups only, show a similar difference between C3 and C4/CAM plants. The correlation between the
δ
13C of emitted CH
4 and methoxyl groups implies that methoxyl groups are not the only source substrate of CH
4.
Interestingly,
δD values of the emitted CH
4 are also found to be different for C3 and C4 plants, although there is no significant difference in the bulk material. Bulk
δD analyses may be compromised by a large reservoir of exchangeable hydrogen, but no significant
δD difference is found either for the methoxyl groups, which do not contain exchangeable hydrogen. The
δD difference in CH
4 between C3 and C4 plants indicates that at least two different reservoirs are involved in CH
4 emission. One of them is the OCH
3 group, the other one must be significantly depleted, and contribute more to the emissions of C3 plants compared to C4 plants. In qualitative agreement with this hypothesis, CH
4 emission rates are higher for C3 plants than for C4 plants.
Long term methane flux measurements have been mostly performed with plant or soil enclosure techniques on specific components of an ecosystem. New fast response methane analyzers make it possible to ...use the eddy covariance (EC) technique instead. The EC technique is advantageous because it allows continuous flux measurements integrating over a larger and more representative area including the complete ecosystem, and allows fluxes to be observed as environmental conditions change naturally without disturbance. We deployed the closed-path Fast Methane analyzer (FMA) from Los Gatos Research Ltd and demonstrate its performance for EC measurements at a Ponderosa pine plantation at the Blodgett Forest site in central California. The fluctuations of the CH4 concentration measured at 10 Hz appear to be small and their standard deviation is comparable to the magnitude of the signal noise (±5 ppbv). Consequently, the power spectra typically have a white noise signature at the high frequency end (a slope of +1). Nevertheless, in the frequency range important for turbulent exchange, the cospectra of CH4 compare very well with all other scalar cospectra confirming the quality of the FMA measurements are good for the EC technique. We furthermore evaluate the complications of combined open and closed-path measurements when applying the Webb-Pearman-Leuning (WPL) corrections (Webb et al., 1980) and the consequences of a phase lag between the water vapor and methane signal inside the closed path system. The results of diurnal variations of CH4 concentrations and fluxes are summarized and compared to the monthly results of process-based model calculations.
The short-chain non-methane hydrocarbons (NMHC) are mostly emitted into the atmosphere by anthropogenic processes. Recent studies have pointed out a tight linkage between the atmospheric mole ...fractions of the NMHC ethane and the atmospheric growth rate of methane. Consequently, atmospheric NMHC are valuable indicators for tracking changes in anthropogenic emissions, photochemical ozone production, and greenhouse gases. This study investigates the 1950-2010 Northern Hemisphere atmospheric C2-C5 NMHC ethane, propane, i-butane, n-butane, i-pentane, and n-pentane by (a) reconstructing atmospheric mole fractions of these trace gases using firn air extracted from three boreholes in 2008 and 2009 at the North Greenland Eemian Ice Drilling (NEEM) site and applying state-of-the-art models of trace gas transport in firn, and by (b) considering eight years of ambient NMHC monitoring data from five Arctic sites within the NOAA Global Monitoring Division (GMD) Cooperative Air Sampling Network. Results indicate that these NMHC increased by ~40-120% after 1950, peaked around 1980 (with the exception of ethane, which peaked approximately 10 yr earlier), and have since dramatically decreased to be now back close to 1950 levels. The earlier peak time of ethane vs. the C3-C5 NMHC suggests that different processes and emissions mitigation measures contributed to the decline in these NMHC. The 60 yr record also illustrates notable increases in the ratios of the isomeric iso-/n-butane and iso-/n-pentane ratios. Comparison of the reconstructed NMHC histories with 1950-2000 volatile organic compounds (VOC) emissions data and with other recently published ethane trend analyses from ambient air Pacific transect data showed (a) better agreement with North America and Western Europe emissions than with total Northern Hemisphere emissions data, and (b) better agreement with other Greenland firn air data NMHC history reconstructions than with the Pacific region trends. These analyses emphasize that for NMHC, having atmospheric lifetimes on the order of < 2 months, the Greenland firn air records are primarily a representation of Western Europe and North America emission histories.
Monoterpene fluxes have been measured over an 11 month period from June 2003 to April 2004. During all seasons ambient air temperature was the environmental factor most closely related to the ...measured emission rates. The monoterpene flux was modeled using a basal emission rate multiplied by an exponential function of a temperature, following the typical practice for modelling temperature dependent biogenic emissions. A basal emission of 1.0 μmol h−1 m−2 (at 30°C, based on leaf area) and a temperature dependence (β) of 0.12°C−1 reproduced measured summer emissions well but underestimated spring and winter measured emissions by 60–130%. The total annual monoterpene emission may be underestimated by ~50% when using a model optimized to reproduce monoterpene emissions in summer. The long term dataset also reveals an indirect connection between non-stomatal ozone and monoterpene flux beyond the dependence on temperature that has been shown for both fluxes.
Myopia is one of most common eye diseases in the world and affects 1 in 4 Americans. It is a complex disease caused by both environmental and genetics effects; the genetics effects are still not well ...understood. In this study, we performed genetic linkage analyses on Ashkenazi Jewish families with a strong familial history of myopia to elucidate any potential causal genes.
Sixty-four extended Ashkenazi Jewish families were previously collected from New Jersey. Genotypes from the Illumina ExomePlus array were merged with prior microsatellite linkage data from these families. Additional custom markers were added for candidate regions reported in literature for myopia or refractive error. Myopia was defined as mean spherical equivalent (MSE) of -1D or worse and parametric two-point linkage analyses (using TwoPointLods) and multi-point linkage analyses (using SimWalk2) were performed as well as collapsed haplotype pattern (CHP) analysis in SEQLinkage and association analyses performed with FBAT and rv-TDT.
Strongest evidence of linkage was on 1p36(two-point LOD = 4.47) a region previously linked to refractive error (MYP14) but not myopia. Another genome-wide significant locus was found on 8q24.22 with a maximum two-point LOD score of 3.75. CHP analysis also detected the signal on 1p36, localized to the LINC00339 gene with a maximum HLOD of 3.47, as well as genome-wide significant signals on 7q36.1 and 11p15, which overlaps with the MYP7 locus.
We identified 2 novel linkage peaks for myopia on chromosomes 7 and 8 in these Ashkenazi Jewish families and replicated 2 more loci on chromosomes 1 and 11, one previously reported in refractive error but not myopia in these families and the other locus previously reported in the literature. Strong candidate genes have been identified within these linkage peaks in our families. Targeted sequencing in these regions will be necessary to definitively identify causal variants under these linkage peaks.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
A West ‐East crossing of the Tropical Atlantic during Meteor cruise 55 included measurements of organic species within the atmospheric marine boundary layer and the upper ocean. Acetone, methanol, ...acetonitrile and DMS were measured between 10–0°N and 35°W–5°E, on either side of the ITCZ. Methanol and acetone concentrations were higher in the northern hemisphere, both in surface seawater and the atmosphere whereas acetonitrile and DMS showed no significant interhemispheric gradient. Three depth profiles from 0–200 m for these species were measured. Acetone, methanol, DMS and acetonitrile generally decreased with depth with the sharpest decrease in concentration in all profiles being found at the bottom of the mixed layer. The average air mixing ratios and surface seawater concentrations for the whole dataset are respectively: acetone 0.53 nmol/mol and 17.6 nmol/L; acetonitrile 0.11 nmol/mol and 6.19 nmol/L; methanol 0.89 nmol/mol and 118.4 nmol/L; and DMS 0.05 nmol/mol and 1.66 nmol/L.
Genetic data have become increasingly complex within the past decade, leading researchers to pursue increasingly complex questions, such as those involving epistatic interactions and protein ...prediction. Traditional methods are ill-suited to answer these questions, but machine learning (ML) techniques offer an alternative solution. ML algorithms are commonly used in genetics to predict or classify subjects, but some methods evaluate which features (variables) are responsible for creating a good prediction; this is called feature importance. This is critical in genetics, as researchers are often interested in which features (e.g., SNP genotype or environmental exposure) are responsible for a good prediction. This allows for the deeper analysis beyond simple prediction, including the determination of risk factors associated with a given phenotype. Feature importance further permits the researcher to peer inside the black box of many ML algorithms to see how they work and which features are critical in informing a good prediction. This review focuses on ML methods that provide feature importance metrics for the analysis of genetic data. Five major categories of ML algorithms: k nearest neighbors, artificial neural networks, deep learning, support vector machines, and random forests are described. The review ends with a discussion of how to choose the best machine for a data set. This review will be particularly useful for genetic researchers looking to use ML methods to answer questions beyond basic prediction and classification.
Oxygenated volatile organic compounds (OVOC) can dominate atmospheric organic chemistry, but they are difficult to measure reliably at low levels in complex mixtures. Several techniques that have ...been used to speciate nonmethane organic compounds (NMOC) including OVOC were codeployed/intercompared in well‐mixed smoke generated by 47 fires in the U.S. Department of Agriculture Forest Service Fire Sciences Combustion Facility. The agreement between proton transfer reaction mass spectrometry (PTR‐MS) and open‐path Fourier transform infrared spectroscopy (OP‐FTIR) was excellent for methanol (PT/FT = 1.04 ± 0.118) and good on average for phenol (0.843 ± 0.845) and acetol (∼0.81). The sum of OP‐FTIR mixing ratios for acetic acid and glycolaldehyde agreed (within experimental uncertainty) with the PTR‐MS mixing ratios for protonated mass 61 (PT/FT = 1.17 ± 0.34), and the sum of OP‐FTIR mixing ratios for furan and isoprene agreed with the PTR‐MS mixing ratios for protonated mass 69 (PT/FT = 0.783 ± 0.465). The sum of OP‐FTIR mixing ratios for acetone and methylvinylether accounted for most of the PTR‐MS protonated mass 59 signal (PT/FT = 1.29 ± 0.81), suggesting that one of these compounds was underestimated by OP‐FTIR or that it failed to detect other compounds that could contribute at mass 59. Canister grab sampling followed by gas chromatography (GC) with mass spectrometry (MS), flame ionization detection (FID), and electron capture detection (ECD) analysis by two different groups agreed well with OP‐FTIR for ethylene, acetylene, and propylene. However, these propylene levels were below those observed by PTR‐MS (PT/FT = 2.33 ± 0.89). Good average agreement between PTR‐MS and GC was obtained for benzene and toluene. At mixing ratios above a few parts per billion the OP‐FTIR had advantages for measuring sticky compounds (e.g., ammonia and formic acid) or compounds with low proton affinity (e.g., hydrogen cyanide and formaldehyde). Even at these levels, only the PTR‐MS measured acetonitrile and acetaldehyde. Below a few ppbv only the PTR‐MS measured a variety of OVOC, but the possibility of fragmentation, interference, and sampling losses must be considered.
We present results that demonstrate a possible bias in the fractioning of total carbon (TC) into elemental carbon (EC) and organic carbon (OC) for measurements with the Sunset Laboratory Inc. ...Thermal/Optical Carbon Aerosol Analyser. The bias is caused by an unstable laser transmission signal. The transmission signal during the analysis of an instrument blank filter can give an indication of the possible bias. If the transmission signal around the OC/EC split point deviates from its initial value, the EC attribution is altered. In a sensitivity study, we show that for a deviation of 10% the EC content is substantially biased.
•Unstable laser transmission signal in Sunset can lead to a bias in EC attribution.•An instability of more than 10% around the split point leads to a substantial bias.•An experiment checks the relevance of an instability during the cooling phase.•Systematic monitoring of the laser transmission signal is strongly recommended.
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