Role of Specific Cations and Water Entropy on the Stability of Branched DNA Motif Structures

DNA three-way junctions (TWJs) are important intermediates in various cellular processes and are the simplest of a family of branched nucleic acids being considered as scaffolds for biomolecular nanotechnology. Branched nucleic acids are stabilized by divalent cations such as Mg2+, presumably due to condensation and neutralization of the negatively charged DNA backbone. However, electrostatic screening effects point to more complex solvation dynamics and a large role of interfacial waters in thermodynamic stability. Here, we report extensive computer simulations in explicit water and salt on a model TWJ and use free energy calculations to quantify the role of ionic character and strength on stability. We find that enthalpic stabilization of the first and second hydration shells by Mg2+ accounts for 1/3 and all of the free energy gain in 50% and pure MgCl2 solutions, respectively. The more distorted DNA molecule is actually destabilized in pure MgCl2 compared to pure NaCl. Notably, the first shell, interfacial waters have very low translational and rotational entropy (i.e., mobility) compared to the bulk, an entropic loss that is overcompensated by increased enthalpy from additional electrostatic interactions with Mg2+. In contrast, the second hydration shell has anomalously high entropy as it is trapped between an immobile and bulklike layer. The nonmonotonic entropic signature and long-range perturbations of the hydration shells to Mg2+ may have implications in the molecular recognition of these motifs. For example, we find that low salt stabilizes the parallel configuration of the three-way junction, whereas at normal salt we find antiparallel configurations deduced from the NMR. We use the 2PT analysis to follow the thermodynamics of this transition and find that the free energy barrier is dominated by entropic effects that result from the decreased surface area of the antiparallel form which has a smaller number of low entropy waters in the first monolayer.

Model independent bounds on the modulus of the pion form factor on the unitarity cut below the omega pi threshold

We calculate upper and lower bounds on the modulus of the pion electromagnetic form factor on the unitarity cut below the omega pi inelastic threshold, using as input the phase in the elastic region known via the Fermi-Watson theorem from the pi pi P-wave phase shift, and a suitably weighted integral of the modulus squared above the inelastic threshold. The normalization at t = 0, the pion charge radius and experimental values at spacelike momenta are used as additional input information. The bounds are model independent, in the sense that they do not rely on specific parametrizations and do not require assumptions on the phase of the form factor above the inelastic threshold. The results provide nontrivial consistency checks on the recent experimental data on the modulus available below the omega pi threshold from e(+)e(-) annihilation and tau-decay experiments. In particular, at low energies the calculated bounds offer a more precise description of the modulus than the experimental data.

Experiments and zero D modeling studies using specific Wiebe coefficients for producer gas as fuel in spark-ignited engines

The paper addresses experiments and modeling studies on the use of producer gas, a bio-derived low energy content fuel in a spark-ignited engine. Producer gas, generated in situ, has thermo-physical properties different from those of fossil fuel(s). Experiments on naturally aspirated and turbo-charged engine operation and subsequent analysis of the cylinder pressure traces reveal significant differences in the heat release pattern within the cylinder compared with a typical fossil fuel. The heat release patterns for gasoline and producer gas compare well in the initial 50% but beyond this, producer gas combustion tends to be sluggish leading to an overall increase in the combustion duration. This is rather unexpected considering that producer gas with nearly 20% hydrogen has higher flame speeds than gasoline. The influence of hydrogen on the initial flame kernel development period and the combustion duration and hence on the overall heat release pattern is addressed. The significant deviations in the heat release profiles between conventional fuels and producer gas necessitates the estimation of producer gas-specific Wiebe coefficients. The experimental heat release profiles are used for estimating the Wiebe coefficients. Experimental evidence of lower fuel conversion efficiency based on the chemical and thermal analysis of the engine exhaust gas is used to arrive at the Wiebe coefficients. The efficiency factor a is found to be 2.4 while the shape factor m is estimated at 0.7 for 2% to 90% burn duration. The standard Wiebe coefficients for conventional fuels and fuel-specific coefficients for producer gas are used in a zero D model to predict the performance of a 6-cylinder gas engine under naturally aspirated and turbo-charged conditions. While simulation results with standard Wiebe coefficients result in excessive deviations from the experimental results, excellent match is observed when producer gas-specific coefficients are used. Predictions using the same coefficients on a 3-cylinder gas engine having different geometry and compression ratio(s) indicate close match with the experimental traces highlighting the versatility of the coefficients.

Splicing Functions and Global Dependency on Fission Yeast Slu7 Reveal Diversity in Spliceosome Assembly

The multiple short introns in Schizosaccharomyces pombe genes with degenerate cis sequences and atypically positioned polypyrimidine tracts make an interesting model to investigate canonical and alternative roles for conserved splicing factors. Here we report functions and interactions of the S. pombe slu7(+) (spslu7(+)) gene product, known from Saccharomyces cerevisiae and human in vitro reactions to assemble into spliceosomes after the first catalytic reaction and to dictate 3' splice site choice during the second reaction. By using a missense mutant of this essential S. pombe factor, we detected a range of global splicing derangements that were validated in assays for the splicing status of diverse candidate introns. We ascribe widespread, intron-specific SpSlu7 functions and have deduced several features, including the branch nucleotide-to-3' splice site distance, intron length, and the impact of its A/U content at the 5' end on the intron's dependence on SpSlu7. The data imply dynamic substrate-splicing factor relationships in multiintron transcripts. Interestingly, the unexpected early splicing arrest in spslu7-2 revealed a role before catalysis. We detected a salt-stable association with U5 snRNP and observed genetic interactions with spprp1(+), a homolog of human U5-102k factor. These observations together point to an altered recruitment and dependence on SpSlu7, suggesting its role in facilitating transitions that promote catalysis, and highlight the diversity in spliceosome assembly.

Bilinear tension softening diagrams of concrete mixes corresponding to their size-independent specific fracture energy

The study of the fracture behaviour of concrete structures using the fictitious crack model requires two fracture properties of the concrete mix, namely, the size-independent specific fracture energy G(F). and the corresponding tension softening relation sigma(w) between the residual stress carrying capacity sigma and the crack opening w in the fracture process zone ahead of a real crack. In this paper, bi-linear tension softening diagrams of three different concrete mixes, ranging in compressive strength from 57 to 122 MPa whose size-independent specific fracture energy has been previously determined, have been constructed in an inverse manner based on the concept of a non-linear hinge from the load-crack mouth opening plots of notched three-point bend beams. (C) 2013 Elsevier Ltd. All rights reserved.

Multi-task learning using shared and task specific information

Multi-task learning solves multiple related learning problems simultaneously by sharing some common structure for improved generalization performance of each task. We propose a novel approach to multi-task learning which captures task similarity through a shared basis vector set. The variability across tasks is captured through task specific basis vector set. We use sparse support vector machine (SVM) algorithm to select the basis vector sets for the tasks. The approach results in a sparse model where the prediction is done using very few examples. The effectiveness of our approach is demonstrated through experiments on synthetic and real multi-task datasets.

Reaction dynamics under confinement: an exact path integral treatment of a two-stage model of stochastic gene expression

Gene expression in living systems is inherently stochastic, and tends to produce varying numbers of proteins over repeated cycles of transcription and translation. In this paper, an expression is derived for the steady-state protein number distribution starting from a two-stage kinetic model of the gene expression process involving p proteins and r mRNAs. The derivation is based on an exact path integral evaluation of the joint distribution, P(p, r, t), of p and r at time t, which can be expressed in terms of the coupled Langevin equations for p and r that represent the two-stage model in continuum form. The steady-state distribution of p alone, P(p), is obtained from P(p, r, t) (a bivariate Gaussian) by integrating out the r degrees of freedom and taking the limit t -> infinity. P(p) is found to be proportional to the product of a Gaussian and a complementary error function. It provides a generally satisfactory fit to simulation data on the same two-stage process when the translational efficiency (a measure of intrinsic noise levels in the system) is relatively low; it is less successful as a model of the data when the translational efficiency (and noise levels) are high.

Solid-solid collapse transition in a two dimensional model molecular system

Solid-solid collapse transition in open framework structures is ubiquitous in nature. The real difficulty in understanding detailed microscopic aspects of such transitions in molecular systems arises from the interplay between different energy and length scales involved in molecular systems, often mediated through a solvent. In this work we employ Monte-Carlo simulation to study the collapse transition in a model molecular system interacting via both isotropic as well as anisotropic interactions having different length and energy scales. The model we use is known as Mercedes-Benz (MB), which, for a specific set of parameters, sustains two solid phases: honeycomb and oblique. In order to study the temperature induced collapse transition, we start with a metastable honeycomb solid and induce transition by increasing temperature. High density oblique solid so formed has two characteristic length scales corresponding to isotropic and anisotropic parts of interaction potential. Contrary to the common belief and classical nucleation theory, interestingly, we find linear strip-like nucleating clusters having significantly different order and average coordination number than the bulk stable phase. In the early stage of growth, the cluster grows as a linear strip, followed by branched and ring-like strips. The geometry of growing cluster is a consequence of the delicate balance between two types of interactions, which enables the dominance of stabilizing energy over destabilizing surface energy. The nucleus of stable oblique phase is wetted by intermediate order particles, which minimizes the surface free energy. In the case of pressure induced transition at low temperature the collapsed state is a disordered solid. The disordered solid phase has diverse local quasi-stable structures along with oblique-solid like domains. (C) 2013 AIP Publishing LLC.

Active Dendrites Regulate Spectral Selectivity in Location-Dependent Spike Initiation Dynamics of Hippocampal Model Neurons

How does the presence of plastic active dendrites in a pyramidal neuron alter its spike initiation dynamics? To answer this question, we measured the spike-triggered average (STA) from experimentally constrained, conductance-based hippocampal neuronal models of various morphological complexities. We transformed the STA computed from these models to the spectral and the spectrotemporal domains and found that the spike initiation dynamics exhibited temporally localized selectivity to a characteristic frequency. In the presence of the hyperpolarization-activated cyclic nucleotide-gated (HCN) channels, the STA characteristic frequency strongly correlated with the subthreshold resonance frequency in the theta frequency range. Increases in HCN channel density or in input variance increased the STA characteristic frequency and its selectivity strength. In the absence of HCN channels, the STA exhibited weak delta frequency selectivity and the characteristic frequency was related to the repolarization dynamics of the action potentials and the recovery kinetics of sodium channels from inactivation. Comparison of STA obtained with inputs at various dendritic locations revealed that nonspiking and spiking dendrites increased and reduced the spectrotemporal integration window of the STA with increasing distance from the soma as direct consequences of passive filtering and dendritic spike initiation, respectively. Finally, the presence of HCN channels set the STA characteristic frequency in the theta range across the somatodendritic arbor and specific STA measurements were strongly related to equivalent transfer-impedance-related measurements. Our results identify explicit roles for plastic active dendrites in neural coding and strongly recommend a dynamically reconfigurable multi-STA model to characterize location-dependent input feature selectivity in pyramidal neurons.

Specific Sequence of a Beta Turn in Human La Protein May Contribute to Species Specificity of Hepatitis C Virus

Human La protein is known to be an essential host factor for translation and replication of hepatitis C virus (HCV) RNA. Previously, we have demonstrated that residues responsible for interaction of human La protein with the HCV internal ribosomal entry site (IRES) around the initiator AUG within stem-loop IV form a beta-turn in the RNA recognition motif (RRM) structure. In this study, sequence alignment and mutagenesis suggest that the HCV RNA-interacting beta-turn is conserved only in humans and chimpanzees, the species primarily known to be infected by HCV. A 7-mer peptide corresponding to the HCV RNA-interacting region of human La inhibits HCV translation, whereas another peptide corresponding to the mouse La sequence was unable to do so. Furthermore, IRES-mediated translation was found to be significantly high in the presence of recombinant human La protein in vitro in rabbit reticulocyte lysate. We observed enhanced replication with HCV subgenomic and full-length replicons upon overexpression of either human La protein or a chimeric mouse La protein harboring a human La beta-turn sequence in mouse cells. Taken together, our results raise the possibility of creating an immunocompetent HCV mouse model using human-specific cell entry factors and a humanized form of La protein.

Residue specific contributions to stability and activity inferred from saturation mutagenesis and deep sequencing

Multiple methods currently exist for rapid construction and screening of single-site saturation mutagenesis (SSM) libraries in which every codon or nucleotide in a DNA fragment is individually randomized. Nucleotide sequences of each library member before and after screening or selection can be obtained through deep sequencing. The relative enrichment of each mutant at each position provides information on its contribution to protein activity or ligand-binding under the conditions of the screen. Such saturation scans have been applied to diverse proteins to delineate hot-spot residues, stability determinants, and for comprehensive fitness estimates. The data have been used to design proteins with enhanced stability, activity and altered specificity relative to wild-type, to test computational predictions of binding affinity, and for protein model discrimination. Future improvements in deep sequencing read lengths and accuracy should allow comprehensive studies of epistatic effects, of combinational variation at multiple sites, and identification of spatially proximate residues.

PMV model is insufficient to capture subjective thermal response from Indians

A controlled laboratory experiment was carried out on forty Indian male college students for evaluating the effect of indoor thermal environment on occupants' response and thermal comfort. During experiment, indoor temperature varied from 21 degrees C to 33 degrees C, and the variables like relative humidity, airflow, air temperature and radiant temperature were recorded along with subject's physiological parameters (skin (T-sk) and oral temperature (T-c)) and subjective thermal sensation responses (TSV). From T-sk and T-c, body temperature (T-b) was evaluated. Subjective Thermal Sensation Vote (TSV) was recorded using ASHRAE 7-point scale. In PMV model, Fanger's T-sk equation was used to accommodate adaptive response. Step-wise regression analysis result showed T-b was better predictor of TSV than T-sk and T-c. Regional skin temperature response, suppressed sweating without dipping, lower sweating threshold temperature and higher cutaneous threshold for sweating were observed as thermal adaptive responses. These adaptive responses cannot be considered in PMV model. To incorporate subjective adaptive response, mean skin temperature (T-sk) is considered in dry heat loss calculation. Along with these, PMV-model and other two methodologies are adopted to calculate PMV values and results are compared. However, recent literature is limited to measure the sweat rate in Indians and consideration of constant Ersw in PMV model needs to be corrected. Using measured T-sk in PMV model (Method(1)), thermal comfort zone corresponding to 0.5 <= PMV <= 0.5 was evaluated as (22.46-25.41) degrees C with neutral temperature of 23.91 degrees C, similarly while using TSV response, wider comfort zone was estimated as (23.25-26.32) degrees C with neutral temperature at 24.83 degrees C, which was further increased to with TSV-PPDnew, relation. It was observed that PMV-model overestimated the actual thermal response. Interestingly, these subjects were found to be less sensitive to hot but more sensitive to cold. A new TSV-PPD relation (PPDnew) was obtained from the population distribution of TSV response with an asymmetric distribution of hot-cold thermal sensation response from Indians. The calculations of human thermal stress according to steady state energy balance models used on PMV model seem to be inadequate to evaluate human thermal sensation of Indians. Relevance to industry: The purpose of this paper is to estimate thermal comfort zone and optimum temperature for Indians. It also highlights that PMV model seems to be inadequate to evaluate subjective thermal perception in Indians. These results can be used in feedback control of HVAC systems in residential and industrial buildings. (C) 2014 Elsevier B.V. All rights reserved.

In vitro exposure of tobacco specific nitrosamines decreases the rat lung phospholipids by enhanced phospholipase A(2) activity

Tobacco-specific nitrosamines (TSNA) have implications in the pathogenesis of various lung diseases and conditions are prevalent even in non-smokers. N-nitrosonornicotine (NNN) and 4-(methyl nitrosamino)-1-(3-pyridyl)-1-butanone (NNK) are potent pulmonary carcinogens present in tobacco product and are mainly responsible for lung cancer. TSNA reacts with pulmonary surfactants, and alters the surfactant phospholipid. The present study was undertaken to investigate the in vitro exposure of rat lung tissue slices to NNK or NNN and to monitor the phospholipid alteration by P-32]orthophosphate labeling. Phospholipid content decreased significantly in the presence of either NNK or NNN with concentration and time dependent manner. Phosphatidylcholine (PC) is the main phospholipid of lung and significant reduction was observed in PC similar to 61%, followed by phosphatidylglycerol (PG) with 100 mu M of NNK, whereas NNN treated tissues showed a reduction in phosphatidylserine (PS) similar to 60% and PC at 250 mu M concentration. The phospholipase A(2) assays and expression studies reveal that both compounds enhanced phospholipid hydrolysis, thereby reducing the phospholipid content. Collectively, our data demonstrated that both NNK and NNN significantly influenced the surfactant phospholipid level by enhanced phospholipase A(2) activity. (C) 2014 Elsevier Ltd. All rights reserved.

Mycobacterium tuberculosis DinG Is a Structure-specific Helicase That Unwinds G4 DNA IMPLICATIONS FOR TARGETING G4 DNA AS A NOVEL THERAPEUTIC APPROACH

The significance of G-quadruplexes and the helicases that resolve G4 structures in prokaryotes is poorly understood. The Mycobacterium tuberculosis genome is GC-rich and contains >10,000 sequences that have the potential to form G4 structures. In Escherichia coli, RecQ helicase unwinds G4 structures. However, RecQ is absent in M. tuberculosis, and the helicase that participates in G4 resolution in M. tuberculosis is obscure. Here, we show that M. tuberculosis DinG (MtDinG) exhibits high affinity for ssDNA and ssDNA translocation with a 5' -> 3' polarity. Interestingly, MtDinG unwinds overhangs, flap structures, and forked duplexes but fails to unwind linear duplex DNA. Our data with DNase I footprinting provide mechanistic insights and suggest that MtDinG is a 5' -> 3' polarity helicase. Notably, in contrast to E. coli DinG, MtDinG catalyzes unwinding of replication fork and Holliday junction structures. Strikingly, we find that MtDinG resolves intermolecular G4 structures. These data suggest that MtDinG is a multifunctional structure-specific helicase that unwinds model structures of DNA replication, repair, and recombination as well as G4 structures. We finally demonstrate that promoter sequences of M. tuberculosis PE_PGRS2, mce1R, and moeB1 genes contain G4 structures, implying that G4 structures may regulate gene expression in M. tuberculosis. We discuss these data and implicate targeting G4 structures and DinG helicase in M. tuberculosis could be a novel therapeutic strategy for culminating the infection with this pathogen.

Combining data sets of satellite-retrieved products for basin-scale water balance study: 2. Evaluation on the Mississippi Basin and closure correction model

In this study, we applied the integration methodology developed in the companion paper by Aires (2014) by using real satellite observations over the Mississippi Basin. The methodology provides basin-scale estimates of the four water budget components (precipitation P, evapotranspiration E, water storage change Delta S, and runoff R) in a two-step process: the Simple Weighting (SW) integration and a Postprocessing Filtering (PF) that imposes the water budget closure. A comparison with in situ observations of P and E demonstrated that PF improved the estimation of both components. A Closure Correction Model (CCM) has been derived from the integrated product (SW+PF) that allows to correct each observation data set independently, unlike the SW+PF method which requires simultaneous estimates of the four components. The CCM allows to standardize the various data sets for each component and highly decrease the budget residual (P - E - Delta S - R). As a direct application, the CCM was combined with the water budget equation to reconstruct missing values in any component. Results of a Monte Carlo experiment with synthetic gaps demonstrated the good performances of the method, except for the runoff data that has a variability of the same order of magnitude as the budget residual. Similarly, we proposed a reconstruction of Delta S between 1990 and 2002 where no Gravity Recovery and Climate Experiment data are available. Unlike most of the studies dealing with the water budget closure at the basin scale, only satellite observations and in situ runoff measurements are used. Consequently, the integrated data sets are model independent and can be used for model calibration or validation.