Photo-tautomerization of acetaldehyde as a photochemical source of formic acid in the troposphere

Organic acids play a key role in the troposphere, contributing to atmospheric aqueous-phase chemistry, aerosol formation, and precipitation acidity. Atmospheric models currently account for less than half the observed, globally averaged formic acid loading. Here we report that acetaldehyde photo-tautomerizes to vinyl alcohol under atmospherically relevant pressures of nitrogen, in the actinic wavelength range, λ = 300–330 nm, with measured quantum yields of 2–25%. Recent theoretical kinetics studies show hydroxyl-initiated oxidation of vinyl alcohol produces formic acid. Adding these pathways to an atmospheric chemistry box model (Master Chemical Mechanism) demonstrates increased formic acid concentrations by a factor of ~1.7 in the polluted troposphere and a factor of ~3 under pristine conditions. Incorporating this mechanism into the GEOS-Chem 3D global chemical transport model reveals an estimated 7% contribution to worldwide formic acid production, with up to 60% of the total modeled formic acid production over oceans arising from photo-tautomerization

Rice_Phospho 1.0: a new rice-specific SVM predictor for protein phosphorylation sites

Experimentally-determined or computationally-predicted protein phosphorylation sites for distinctive species are becoming increasingly common. In this paper, we compare the predictive performance of a novel classification algorithm with different encoding schemes to develop a rice-specific protein phosphorylation site predictor. Our results imply that the combination of Amino acid occurrence Frequency with Composition of K-Spaced Amino Acid Pairs (AF-CKSAAP) provides the best description of relevant sequence features that surround a phosphorylation site. A support vector machine (SVM) using AF-CKSAAP achieves the best performance in classifying rice protein phophorylation sites when compared to the other algorithms. We have used SVM with AF-CKSAAP to construct a rice-specific protein phosphorylation sites predictor, Rice-Phospho 1.0 (http://bioinformatics.fafu.edu.cn/rice-phospho1.0). We measure the Accuracy (ACC) and Matthews Correlation Coefficient (MCC) of Rice-Phospho 1.0 to be 82.0% and 0.64, significantly higher than those measures for other predictors such as Scansite, Musite, PlantPhos and PhosphoRice. Rice-Phospho 1.0 also successfully predicted the experimentally identified phosphorylation sites in LOC-Os03g51600.1, a protein sequence which did not appear in the training dataset. In summary, Rice-phospho 1.0 outputs reliable predictions of protein phosphorylation sites in rice, and will serve as a useful tool to the community

Muc2 Protects against Lethal Infectious Colitis by Disassociating Pathogenic and Commensal Bacteria from the Colonic Mucosa

Despite recent advances in our understanding of the pathogenesis of attaching and effacing (A/E) Escherichia coli infections, the mechanisms by which the host defends against these microbes are unclear. The goal of this study was to determine the role of goblet cell-derived Muc2, the major intestinal secretory mucin and primary component of the mucus layer, in host protection against A/E pathogens. To assess the role of Muc2 during A/E bacterial infections, we inoculated Muc2 deficient (Muc2−/−) mice with Citrobacter rodentium, a murine A/E pathogen related to diarrheagenic A/E E. coli. Unlike wildtype (WT) mice, infected Muc2−/− mice exhibited rapid weight loss and suffered up to 90% mortality. Stool plating demonstrated 10–100 fold greater C. rodentium burdens in Muc2−/− vs. WT mice, most of which were found to be loosely adherent to the colonic mucosa. Histology of Muc2−/− mice revealed ulceration in the colon amid focal bacterial microcolonies. Metabolic labeling of secreted mucins in the large intestine demonstrated that mucin secretion was markedly increased in WT mice during infection compared to uninfected controls, suggesting that the host uses increased mucin release to flush pathogens from the mucosal surface. Muc2 also impacted host-commensal interactions during infection, as FISH analysis revealed C. rodentium microcolonies contained numerous commensal microbes, which was not observed in WT mice. Orally administered FITC-Dextran and FISH staining showed significantly worsened intestinal barrier disruption in Muc2−/− vs. WT mice, with overt pathogen and commensal translocation into the Muc2−/− colonic mucosa. Interestingly, commensal depletion enhanced C. rodentium colonization of Muc2−/− mice, although colonic pathology was not significantly altered. In conclusion, Muc2 production is critical for host protection during A/E bacterial infections, by limiting overall pathogen and commensal numbers associated with the colonic mucosal surface. Such actions limit tissue damage and translocation of pathogenic and commensal bacteria across the epithelium

Roadmap on dynamics of molecules and clusters in the gas phase

This roadmap article highlights recent advances, challenges and future prospects in studies of the dynamics of molecules and clusters in the gas phase. It comprises nineteen contributions by scientists with leading expertise in complementary experimental and theoretical techniques to probe the dynamics on timescales spanning twenty order of magnitudes, from attoseconds to minutes and beyond, and for systems ranging in complexity from the smallest (diatomic) molecules to clusters and nanoparticles. Combining some of these techniques opens up new avenues to unravel hitherto unexplored reaction pathways and mechanisms, and to establish their significance in, e.g. radiotherapy and radiation damage on the nanoscale, astrophysics, astrochemistry and atmospheric science

Beyond direct simulation Monte Carlo (DSMC) modelling of collision environments

Direct simulation Monte Carlo (DSMC) models have been successfully adopted and adapted to describe gas flows in a wide range of environments since the method was first introduced by Bird in the 1960s. We propose a new approach to modelling collisions between gas-phase particles in this work – operating in a similar way to the DSMC model, but with one key difference. Particles move in a mean field, generated by all previously propagated particles, which removes the requirement that all particles be propagated simultaneously. This yields a significant reduction in computation effort and lends itself to applications for which DSMC becomes intractable, such as when a species of interest is only a minor component of a large gas mixture

A variable time step self-consistent mean field DSMC model for three-dimensional environments.

A self-consistent mean field direct simulation Monte Carlo (SCMFD) algorithm was recently proposed for simulating collision environments for a range of one-dimensional model systems. This work extends the one-dimensional SCMFD approach to three dimensions and introduces a variable time step (3D-vt-SCMFD), enabling the modeling of a considerably wider range of different collision environments. We demonstrate the performance of the augmented method by modeling a varied set of test systems: ideal gas mixtures, Poiseuille flow of argon, and expansion of gas into high vacuum. For the gas mixtures, the 3D-vt-SCMFD method reproduces the properties (mean free path, mean free time, collision frequency, and temperature) in excellent agreement with theoretical predictions. From the Poiseuille flow simulations, we extract flow profiles that agree with the solution to the Navier-Stokes equations in the high-density limit and resemble free molecular flow at low densities, as expected. The measured viscosity from 3D-vt-SCMF is ∼15% lower than the theoretical prediction from Chapman-Enskog theory. The expansion of gas into vacuum is examined in the effusive regime and at the hydrodynamic limit. In both cases, 3D-vt-SCMDF simulations produce gas beam density, velocity, and temperature profiles in excellent agreement with analytical models. In summary, our tests show that 3D-vt-SCMFD is robust and computationally efficient, while also illustrating the diversity of systems the SCMFD model can be successfully applied to

Production of cold beams of ND3 with variable rotational state distributions by electrostatic extraction of He and Ne buffer-gas-cooled beams.

The measurement of the rotational state distribution of a velocity-selected, buffer-gas-cooled beam of ND3 is described. In an apparatus recently constructed to study cold ion-molecule collisions, the ND3 beam is extracted from a cryogenically cooled buffer-gas cell using a 2.15 m long electrostatic quadrupole guide with three 90° bends. (2+1) resonance enhanced multiphoton ionization spectra of molecules exiting the guide show that beams of ND3 can be produced with rotational state populations corresponding to approximately T(rot) = 9-18 K, achieved through manipulation of the temperature of the buffer-gas cell (operated at 6 K or 17 K), the identity of the buffer gas (He or Ne), or the relative densities of the buffer gas and ND3. The translational temperature of the guided ND3 is found to be similar in a 6 K helium and 17 K neon buffer-gas cell (peak kinetic energies of 6.92(0.13) K and 5.90(0.01) K, respectively). The characterization of this cold-molecule source provides an opportunity for the first experimental investigations into the rotational dependence of reaction cross sections in low temperature collisions

Evolutionary algorithm optimization of Zeeman deceleration: is it worthwhile for longer decelerators?

In Zeeman deceleration, only a small subset of low-field-seeking particles in the incoming beam possess initial velocities and positions that place them within the phase-space acceptance of the device. In order to maximize the number of particles that are successfully decelerated to a selected final velocity, we seek to optimize the phase-space acceptance of the decelerator. Three-dimensional particle trajectory simulations are employed to investigate the potential benefits of using a covariance matrix adaptation evolutionary strategy (CMA-ES) optimization method for decelerators longer than 12 stages and for decelerating species other than H atoms. In all scenarios considered, the evolutionary algorithm-optimized sequences yield vastly more particles within the target velocity range. This is particularly evident in scenarios where standard sequences are known to perform poorly; simulations show that CMA-ES optimization of a standard sequence decelerating H atoms from an initial velocity of 500 ms–1 down to a final velocity of 200 ms–1 in a 24-stage decelerator produces a considerable 5921% (or 60-fold) increase in the number of successfully decelerated particles. Particle losses that occur with standard pulse sequences—for example, arising from the coupling of longitudinal and transverse motion—are overcome in the CMA-ES optimization process as the passage of all particles through the decelerator is explicitly considered and focusing effects are accounted for in the optimization process