Search for: All records

Quantifying ecosystem resilience to disturbance is important for understanding the effects of disturbances on ecosystems, especially in an era of rapid global change. However, there are few studies that have used standardized experimental disturbances to compare resilience patterns across abiotic gradients in real‐world ecosystems. Theoretical studies have suggested that increased return times are associated with increasing variance during recovery from disturbance. However, this notion has rarely been explicitly tested in field, in part due to the challenges involved in obtaining long‐term experimental data. In this study, we examined resilience to disturbance of 12 coastal marsh sites (five low‐salinity and seven polyhaline [=salt] marshes) along a salinity gradient in Georgia, USA. We found that recovery times after experimental disturbance ranged from 7 to >127 months, and differed among response variables (vegetation height, cover and composition). Recovery rates decreased along the stress gradient of increasing salinity, presumably due to stress reducing plant vigor, but only when low‐salinity and polyhaline sites were analyzed separately, indicating a strong role for traits of dominant plant species. The coefficient of variation of vegetation cover and height in control plots did not vary with salinity. In disturbed plots, however, the coefficient of variation (CV) was consistently elevated during the recovery period and increased with salinity. Moreover, higher CV values during recovery were correlated with slower recovery rates. Our results deepen our understanding of resilience to disturbance in natural ecosystems, and point to novel ways that variance can be used either to infer recent disturbance, or, if measured in areas with a known disturbance history, to predict recovery patterns.

 

MHC Class I protein plays an important role in immunotherapy by presenting immunogenic peptides to anti-tumor immune cells. The repertoires of peptides for various MHC Class I proteins are distinct, which can be reflected by their diverse binding motifs. To characterize binding motifs for MHC Class I proteins, in vitro experiments have been conducted to screen peptides with high binding affinities to hundreds of given MHC Class I proteins. However, considering tens of thousands of known MHC Class I proteins, conducting in vitro experiments for extensive MHC proteins is infeasible, and thus a more efficient and scalable way to characterize binding motifs is needed.

We presented a de novo generation framework, coined PepPPO, to characterize binding motif for any given MHC Class I proteins via generating repertoires of peptides presented by them. PepPPO leverages a reinforcement learning agent with a mutation policy to mutate random input peptides into positive presented ones. Using PepPPO, we characterized binding motifs for around 10 000 known human MHC Class I proteins with and without experimental data. These computed motifs demonstrated high similarities with those derived from experimental data. In addition, we found that the motifs could be used for the rapid screening of neoantigens at a much lower time cost than previous deep-learning methods.

The software can be found in https://github.com/minrq/pMHC.

Supplementary data are available at Bioinformatics online.

 

Abstract On single-cell RNA-sequencing data, we consider the problem of assigning cells to known cell types, assuming that the identities of cell-type-specific marker genes are given but their exact expression levels are unavailable, that is, without using a reference dataset. Based on an observation that the expected over-expression of marker genes is often absent in a nonnegligible proportion of cells, we develop a method called scSorter. scSorter allows marker genes to express at a low level and borrows information from the expression of non-marker genes. On both simulated and real data, scSorter shows much higher power compared to existing methods. 

Abstract. Extensive airborne measurements of non-methane organic gases (NMOGs), methane, nitrogen oxides, reduced nitrogen species, and aerosol emissions from US wild and prescribed fires were conducted during the 2019 NOAA/NASA Fire Influence on Regional to Global Environments and Air Quality campaign (FIREX-AQ). Here, we report the atmospheric enhancement ratios (ERs) and inferred emission factors (EFs) for compounds measured on board the NASA DC-8 research aircraft for nine wildfires and one prescribed fire, which encompass a range of vegetation types. We use photochemical proxies to identify young smoke and reduce the effects of chemical degradation on our emissions calculations. ERs and EFs calculated from FIREX-AQ observations agree within a factor of 2, with values reported from previous laboratory and field studies for more than 80 % of the carbon- and nitrogen-containing species. Wildfire emissions are parameterized based on correlations of the sum of NMOGs with reactive nitrogen oxides (NOy) to modified combustion efficiency (MCE) as well as other chemical signatures indicative of flaming/smoldering combustion, including carbon monoxide (CO), nitrogen dioxide (NO2), and black carbon aerosol. The sum of primary NMOG EFs correlates to MCE with an R2 of 0.68 and a slope of −296 ± 51 g kg−1, consistent with previous studies. The sum of the NMOG mixing ratios correlates well with CO with an R2 of 0.98 and a slope of 137 ± 4 ppbv of NMOGs per parts per million by volume (ppmv) of CO, demonstrating that primary NMOG emissions can be estimated from CO. Individual nitrogen-containing species correlate better with NO2, NOy, and black carbon than with CO. More than half of the NOy in fresh plumes is NO2 with an R2 of 0.95 and a ratio of NO2 to NOy of 0.55 ± 0.05 ppbv ppbv−1, highlighting that fast photochemistry had already occurred in the sampled fire plumes. The ratio of NOy to the sum of NMOGs follows trends observed in laboratory experiments and increases exponentially with MCE, due to increased emission of key nitrogen species and reduced emission of NMOGs at higher MCE during flaming combustion. These parameterizations will provide more accurate boundary conditions for modeling and satellite studies of fire plume chemistry and evolution to predict the downwind formation of secondary pollutants, including ozone and secondary organic aerosol.

 

The first near IR fluorescent probe for the chemoselective and enantioselective recognition of arginine in aqueous solution is reported in this work. This probe, made of a 1,1’‐binaphthyl‐based chiral aldehyde unit and a rhodamine‐based near IR chromophore, in combination with La³⁺exhibits highly chemoselective as well as enantioselective fluorescent enhancement with arginine at λ=764 nm upon excitation at λ=690 nm. Little or no fluorescent response is observed toward the chirality miss‐matched arginine enantiomer or other common amino acids and their enantiomers. This probe also allows visual discrimination of the arginine enantiomers because of its fast and distinct color change upon interaction with the substrate.

 

Abstract. Organic nitrate (RONO2) formation in the atmosphere represents a sink of NOx(NOx = NO + NO2) and termination of the NOx/HOx(HOx = HO2 + OH) ozone formation and radical propagation cycles, can act as a NOx reservoirtransporting reactive nitrogen, and contributes to secondary organic aerosol formation. While some fraction of RONO2 is thought to reside in the particle phase, particle-phase organic nitrates (pRONO2) are infrequently measured and thus poorly understood. There is anincreasing prevalence of aerosol mass spectrometer (AMS) instruments, which have shown promise for determining the quantitative total organic nitratefunctional group contribution to aerosols. A simple approach that relies on the relative intensities of NO+ and NO2+ ions inthe AMS spectrum, the calibrated NOx+ ratio for NH4NO3, and the inferred ratio for pRONO2 hasbeen proposed as a way to apportion the total nitrate signal to NH4NO3 and pRONO2. This method is increasingly beingapplied to field and laboratory data. However, the methods applied have been largely inconsistent and poorly characterized, and, therefore, adetailed evaluation is timely. Here, we compile an extensive survey of NOx+ ratios measured for variouspRONO2 compounds and mixtures from multiple AMS instruments, groups, and laboratory and field measurements. All data and analysispresented here are for use with the standard AMS vaporizer. We show that, in the absence of pRONO2 standards, thepRONO2 NOx+ ratio can be estimated using a ratio referenced to the calibrated NH4NO3 ratio, aso-called “Ratio-of-Ratios” method (RoR = 2.75 ± 0.41). We systematically explore the basis for quantifyingpRONO2 (and NH4NO3) with the RoR method using ground and aircraft field measurements conducted over a largerange of conditions. The method is compared to another AMS method (positive matrix factorization, PMF) and other pRONO2 andrelated (e.g., total gas + particle RONO2) measurements, generally showing good agreement/correlation. A broad survey of ground andaircraft AMS measurements shows a pervasive trend of higher fractional contribution of pRONO2 to total nitrate with lower totalnitrate concentrations, which generally corresponds to shifts from urban-influenced to rural/remote regions. Compared to ground campaigns,observations from all aircraft campaigns showed substantially lower pRONO2 contributions at midranges of total nitrate(0.01–0.1 up to 2–5 µg m−3), suggesting that the balance of effects controlling NH4NO3 and pRONO2formation and lifetimes – such as higher humidity, lower temperatures, greater dilution, different sources, higher particle acidity, andpRONO2 hydrolysis (possibly accelerated by particle acidity) – favors lower pRONO2 contributions for thoseenvironments and altitudes sampled. 

We report two highly fluorinated Cu-based imaging agents, CuL1 and CuL2 , for detecting cellular hypoxia as nanoemulsion formulations. Both complexes retained their initial quenched 19 F MR signals due to paramagnetic Cu 2+ ; however, both complexes displayed a large signal increase when the complex was reduced. DLS studies showed that the CuL1 nanoemulsion ( NE CuL1 ) had a hydrodiameter of approximately 100 nm and that it was stable for four weeks post-preparation. Hypoxic cells incubated with NE CuL1 showed that 40% of the Cu 2+ taken up was reduced in low oxygen environments.