Comparison of continuous and pulsed labeling amide hydrogen exchange/mass spectrometry for studies of protein dynamics

AbstractIn contrast to the rigid structures portrayed by X-ray diffraction, proteins in solution display constant motion which leads to populations that are momentarily unfolded. To begin to understand protein dynamics, we must have experimental methods for determining rates of folding and unfolding, as well as for identifying structures of folding and unfolding intermediates. Amide hydrogen exchange has become an important tool for such measurements. When urea is used to stabilize unfolded forms of proteins, the refolding rates may become slower than the rates of isotope exchange. In such cases, the intermolecular distribution of deuterium among the entire population of molecules may become bimodal, giving rise to a bimodal distribution of isotope peaks in mass spectra of the protein or its peptic fragments. When the protein is exposed continuously to D2O, the relative intensities of the two envelopes of isotope peaks give an integrated account of populations participating in the folding/unfolding process. However, when the protein is exposed only briefly to D2O, the relative intensities of the two envelopes of isotope peaks give an instantaneous measure of the folded/unfolded populations. Application of these two labeling methods to a large protein, aldolase, is described along with a discussion of specific parameters required to optimize these experiments

Chemistry-climate interactions: Boundary layer ozone in the United States and free tropospheric methanesulfonic acid over the tropics

This work presents a multi-scale modeling analysis approach to explore two subtopics pertaining to the chemistry-climate interaction: (1) ground-level ozone pollution in the United States and (2) the marine sulfur chemistry over the tropical oceans. To understand the drivers for high ozone episodes during the fall over the Southeast US, we use a 3-D chemical transport model to analyze the month of October 2010, the most recent ozone extreme over the Southeast in October. In addition to enhanced photochemical production and suppressed pollution ventilation, modeling analysis shows that the high ozone concentrations are also due to enhanced emission of biogenic isoprene under a dry and warm weather condition from water stressed plants, which is corroborated by recent field and laboratory studies. This finding implicates that a drying and warming future, projected by climate models, will likely lead to an extended ozone season from summer to fall and an increase of secondary organic aerosols in the Southeast US. We also use vertical profiles observed in the DISCOVER-AQ aircraft campaign in July 2011 to examine how NOx, an important ozone precursor, distributes vertically in the boundary layer. The observed average vertical profile of NOx shows a large negative gradient with increasing altitude in the boundary layer. Our analysis suggests that the magnitude of the NOx gradient is highly sensitive to meteorological factors such as atmospheric stability. Using a 1-D chemical transport model, we reasonably reproduce the vertical profiles of NOx under different boundary layer stability conditions. We then use the model to assess the impact of parameterizations of the boundary layer and land-surface processes on vertical profiles. Using model simulations, we evaluate the impact of boundary layer NOx gradient on the calculation of the ozone production rate and satellite NO2 retrieval. Using the 1-D model, we also examine the sulfur chemistry during the PASE mission in the tropical Pacific, with a focus on methanesulfonic acid (MSA). The observed sharp decrease in MSA from the surface to 600m implies a surface source of 4.0×10^7 molecules/cm2/s. We also find that the observed large increase of MSA from the boundary layer into the lower free troposphere (1000-2000 m) results mainly from the degassing of MSA from dehydrated aerosols. We estimate a source of 1.2×10^7 molecules/cm2/s to the free troposphere through this pathway. This source of soluble MSA could potentially provide an important precursor for new particle formation in the free troposphere over the tropics, affecting the climate system through aerosol-cloud interactions.Ph.D

Estimate haplotype frequencies in pedigrees

BACKGROUND: Haplotype analysis has gained increasing attention in the context of association studies of disease genes and drug responsivities over the last years. The potential use of haplotypes has led to the initiation of the HapMap project which is to investigate haplotype patterns in the human genome in different populations. Haplotype inference and frequency estimation are essential components of this endeavour. RESULTS: We present a two-stage method to estimate haplotype frequencies in pedigrees, which includes haplotyping stage and estimation stage. In the haplotyping stage, we propose a linear time algorithm to determine all zero-recombinant haplotype configurations for each pedigree. In the estimation stage, we use the expectation-maximization (EM) algorithm to estimate haplotype frequencies based on these haplotype configurations. The experiments demonstrate that our method runs much faster and gives more credible estimates than other popular haplotype analysis software that discards the pedigree information. CONCLUSION: Our method suggests that pedigree information is of great importance in haplotype analysis. It can be used to speedup estimation process, and to improve estimation accuracy as well. The result also demonstrates that the whole haplotype configuration space can be substituted by the space of zero-recombinant haplotype configurations in haplotype frequency estimation, especially when the considered haplotype block is relatively short

Preparation and Characterization of Superhydrophobic Modification of Polyvinylidene Fluoride Membrane by Dip-Coating

The superhydrophobicity polyvinylidene fluoride (PVDF) membranes were modified via reducing surface energy by dip-coating perfluoroalkyl methacrylic copolymer (Zonyl 8740) onto the membranes prepared on mat glass. The chemical component of the unmodified and modified PVDF membranes surface was investigated by ATR-FTIR. Morphology and hydrophobicity of the unmodified and modified PVDF membranes were examined by scanning electronic microscopy and water contact angle, respectively. The effects of concentration of Zonyl 8740, coating time, conditions of heat treatment on hydrophobic capability of PVDF membranes were investigated. The results showed that the water contact angle increased from 141˚ to 151˚ by the dip-coating modification, therefore getting superhydrophobic PVDF membrane. Moreover, the porosity and the morphology of modified PVDF membrane were unchanged by the dip-coating modification. This results suggested that the hydrophobicty stability of the modified PVDF membrane was also good

Entropy Measures for Interval-Valued Intuitionistic Fuzzy Sets and Their Application in Group Decision-Making

Entropy measure is an important topic in the fuzzy set theory and has been investigated by many researchers from different points of view. In this paper, two new entropy measures based on the cosine function are proposed for intuitionistic fuzzy sets and interval-valued intuitionistic fuzzy sets. According to the features of the cosine function, the general forms of these two kinds of entropy measures are presented. Compared with the existing ones, the proposed entropy measures can overcome some shortcomings and be used to measure both fuzziness and intuitionism of these two fuzzy sets; as a result, the uncertain information of which can be described more sufficiently. These entropy measures have been applied to assess the experts’ weights and to solve multicriteria fuzzy group decision-making problems

Hybrid AHS: A Hybrid of Kalman Filter and Deep Learning for Acoustic Howling Suppression

Deep learning has been recently introduced for efficient acoustic howling suppression (AHS). However, the recurrent nature of howling creates a mismatch between offline training and streaming inference, limiting the quality of enhanced speech. To address this limitation, we propose a hybrid method that combines a Kalman filter with a self-attentive recurrent neural network (SARNN) to leverage their respective advantages for robust AHS. During offline training, a pre-processed signal obtained from the Kalman filter and an ideal microphone signal generated via teacher-forced training strategy are used to train the deep neural network (DNN). During streaming inference, the DNN's parameters are fixed while its output serves as a reference signal for updating the Kalman filter. Evaluation in both offline and streaming inference scenarios using simulated and real-recorded data shows that the proposed method efficiently suppresses howling and consistently outperforms baselines.Comment: submitted to INTERSPEECH 2023. arXiv admin note: text overlap with arXiv:2302.0925