Determination of Equilibrium Constants for the Reaction between Acetone and HO_2 Using Infrared Kinetic Spectroscopy

The reaction between the hydroperoxy radical, HO_2, and acetone may play an important role in acetone removal and the budget of HO_x radicals in the upper troposphere. We measured the equilibrium constants of this reaction over the temperature range of 215–272 K at an overall pressure of 100 Torr using a flow tube apparatus and laser flash photolysis to produce HO_2. The HO_2 concentration was monitored as a function of time by near-IR diode laser wavelength modulation spectroscopy. The resulting [HO_2] decay curves in the presence of acetone are characterized by an immediate decrease in initial [HO_2] followed by subsequent decay. These curves are interpreted as a rapid (<100 μs) equilibrium reaction between acetone and the HO_2 radical that occurs on time scales faster than the time resolution of the apparatus, followed by subsequent reactions. This separation of time scales between the initial equilibrium and ensuing reactions enabled the determination of the equilibrium constant with values ranging from 4.0 × 10^(–16) to 7.7 × 10^(–1)8 cm^3 molecule^(–1) for T = 215–272 K. Thermodynamic parameters for the reaction determined from a second-law fit of our van’t Hoff plot were Δ_(r)H°_(245) = −35.4 ± 2.0 kJ mol^(–1) and Δ_(r)S°_(245) = −88.2 ± 8.5 J mol^(–1) K^(–1). Recent ab initio calculations predict that the reaction proceeds through a prereactive hydrogen-bonded molecular complex (HO_2–acetone) with subsequent isomerization to a hydroxy–peroxy radical, 2-hydroxyisopropylperoxy (2-HIPP). The calculations differ greatly in the energetics of the complex and the peroxy radical, as well as the transition state for isomerization, leading to significant differences in their predictions of the extent of this reaction at tropospheric temperatures. The current results are consistent with equilibrium formation of the hydrogen-bonded molecular complex on a short time scale (100 μs). Formation of the hydrogen-bonded complex will have a negligible impact on the atmosphere. However, the complex could subsequently isomerize to form the 2-HIPP radical on longer time scales. Further experimental studies are needed to assess the ultimate impact of the reaction of HO_2 and acetone on the atmosphere

Functionalized coatings by electrospinning for anti-oxidant food packaging

The development of advanced formulations used for food packaging applications, which behave as protection or preservation materials and improve consumers’ health offers a route to reduced food wastage. The present study deals with investigations on the possibility of obtaining functionalized coatings by electrospinning of poly(ɛ-caprolactone), a synthetic biodegradable polymer together with vitamin E (α-tocopherol), selected as plant-based phenolic antioxidant. In this approach electrospinning allows the production of high surface area materials and thus offering an increased antioxidant activity. The electrospun fibres of poly(ɛ-caprolactone)/vitamin E were obtained, studied and their antioxidant properties were evaluated by measuring the fibre reactivity with 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical. The potential for extending the shelf-life of food products by using this approach is discussed

Subset- and tissue-defined STAT5 thresholds control homeostasis and function of innate lymphoid cells

Innate lymphoid cells (ILCs) patrol environmental interfaces to defend against infection and protect barrier integrity. Using a genetic tuning model, we demonstrate that the signal-dependent transcription factor (TF) STAT5 is critical for accumulation of all known ILC subsets in mice and reveal a hierarchy of STAT5 dependency for populating lymphoid and nonlymphoid tissues. We apply transcriptome and genomic distribution analyses to define a STAT5 gene signature in natural killer (NK) cells, the prototypical ILC subset, and provide a systems-based molecular rationale for its key functions downstream of IL-15. We also uncover surprising features of STAT5 behavior, most notably the wholesale redistribution that occurs when NK cells shift from tonic signaling to acute cytokine-driven signaling, and genome-wide coordination with T-bet, another key TF in ILC biology. Collectively, our data position STAT5 as a central node in the TF network that instructs ILC development, homeostasis, and function and provide mechanistic insights on how it works at cellular and molecular levels

Developmental Acquisition of Regulomes Underlies Innate Lymphoid Cell Functionality

Innate lymphoid cells (ILCs) play key roles in host defense, barrier integrity, and homeostasis and mirror adaptive CD4(+) T helper (Th) cell subtypes in both usage of effector molecules and transcription factors. To better understand the relationship between ILC subsets and their Th cell counterparts, we measured genome-wide chromatin accessibility. We find that chromatin in proximity to effector genes is selectively accessible in ILCs prior to high-level transcription upon activation. Accessibility of these regions is acquired in a stepwise manner during development and changes little after in vitro or in vivo activation. Conversely, dramatic chromatin remodeling occurs in naive CD4(+) T cells during Th cell differentiation using a type-2-infection model. This alteration results in a substantial convergence of Th2 cells toward ILC2 regulomes. Our data indicate extensive sharing of regulatory circuitry across the innate and adaptive compartments of the immune system, in spite of their divergent developing pathways

Protein complex compositions predicted by structural similarity

Proteins function through interactions with other molecules. Thus, the network of physical interactions among proteins is of great interest to both experimental and computational biologists. Here we present structure-based predictions of 3387 binary and 1234 higher order protein complexes in Saccharomyces cerevisiae involving 924 and 195 proteins, respectively. To generate candidate complexes, comparative models of individual proteins were built and combined together using complexes of known structure as templates. These candidate complexes were then assessed using a statistical potential, derived from binary domain interfaces in PIBASE (). The statistical potential discriminated a benchmark set of 100 interface structures from a set of sequence-randomized negative examples with a false positive rate of 3% and a true positive rate of 97%. Moreover, the predicted complexes were also filtered using functional annotation and sub-cellular localization data. The ability of the method to select the correct binding mode among alternates is demonstrated for three camelid VHH domain—porcine α–amylase interactions. We also highlight the prediction of co-complexed domain superfamilies that are not present in template complexes. Through integration with MODBASE, the application of the method to proteomes that are less well characterized than that of S.cerevisiae will contribute to expansion of the structural and functional coverage of protein interaction space. The predicted complexes are deposited in MODBASE ()

MODBASE, a database of annotated comparative protein structure models and associated resources.

MODBASE (http://salilab.org/modbase) is a database of annotated comparative protein structure models. The models are calculated by MODPIPE, an automated modeling pipeline that relies primarily on MODELLER for fold assignment, sequence-structure alignment, model building and model assessment (http:/salilab.org/modeller). MODBASE currently contains 5,152,695 reliable models for domains in 1,593,209 unique protein sequences; only models based on statistically significant alignments and/or models assessed to have the correct fold are included. MODBASE also allows users to calculate comparative models on demand, through an interface to the MODWEB modeling server (http://salilab.org/modweb). Other resources integrated with MODBASE include databases of multiple protein structure alignments (DBAli), structurally defined ligand binding sites (LIGBASE), predicted ligand binding sites (AnnoLyze), structurally defined binary domain interfaces (PIBASE) and annotated single nucleotide polymorphisms and somatic mutations found in human proteins (LS-SNP, LS-Mut). MODBASE models are also available through the Protein Model Portal (http://www.proteinmodelportal.org/)

DBAli tools: mining the protein structure space

The DBAli tools use a comprehensive set of structural alignments in the DBAli database to leverage the structural information deposited in the Protein Data Bank (PDB). These tools include (i) the DBAlit program that allows users to input the 3D coordinates of a protein structure for comparison by MAMMOTH against all chains in the PDB; (ii) the AnnoLite and AnnoLyze programs that annotate a target structure based on its stored relationships to other structures; (iii) the ModClus program that clusters structures by sequence and structure similarities; (iv) the ModDom program that identifies domains as recurrent structural fragments and (v) an implementation of the COMPARER method in the SALIGN command in MODELLER that creates a multiple structure alignment for a set of related protein structures. Thus, the DBAli tools, which are freely accessible via the World Wide Web at http://salilab.org/DBAli/, allow users to mine the protein structure space by establishing relationships between protein structures and their functions

Effect of Ventricular Shock Strength on Cardiac Hemodynamics

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75115/1/j.1540-8167.1998.tb00118.x.pd

The interplay of microscopic and mesoscopic structure in complex networks

Not all nodes in a network are created equal. Differences and similarities exist at both individual node and group levels. Disentangling single node from group properties is crucial for network modeling and structural inference. Based on unbiased generative probabilistic exponential random graph models and employing distributive message passing techniques, we present an efficient algorithm that allows one to separate the contributions of individual nodes and groups of nodes to the network structure. This leads to improved detection accuracy of latent class structure in real world data sets compared to models that focus on group structure alone. Furthermore, the inclusion of hitherto neglected group specific effects in models used to assess the statistical significance of small subgraph (motif) distributions in networks may be sufficient to explain most of the observed statistics. We show the predictive power of such generative models in forecasting putative gene-disease associations in the Online Mendelian Inheritance in Man (OMIM) database. The approach is suitable for both directed and undirected uni-partite as well as for bipartite networks