Isotopomer fractionation in the UV photolysis of N_2O: 2. Further comparison of theory and experiment

Wavelength-dependent fractionation of various isotopomers in the photodissociation of N_2O is studied. The absorption cross sections are calculated by a time-independent reflection principle, related to the Prakash et al. (2005) treatment but now with an inclusion of the NN stretching coordinate and both the 2A′ and 1A″ electronic excited states. The added 1A″ state is found to have little effect on both the absorption cross section and the fractionation. The improvements include more physical details in the photodissociation of N_2O, while maintaining an advantage of a treatment in the work by Prakash et al. (2005) that was not computationally intensive. The present calculated fractionation, without a significant adjustable parameter, gives good agreement with experiments in the absorption cross section in the low-energy region, the important region for the experimentally observed isotopic fractionation

Isotopomer fractionation in the UV photolysis of N_2O: Comparison of theory and experiment

In the photodissociation of N_2O, absorption cross sections differ with isotopic substitution, leading to a wavelength-dependent fractionation of the various isotopomers. Several models ranging from shifts by zero-point energy differences to propagation of wave packets on the excited electronic state potential energy surface have been proposed to explain the observed fractionations. We present time-independent fractionation calculations for the isotopomers 447, 448, 456, 546, and 556. Besides largely agreeing with the experimental data, these calculations have the advantage of not being computationally intensive, as well as satisfying the physical facts that the asymmetric stretch and the doubly degenerate bending vibration are the principal Franck-Condon active modes in the photodissociation. The latter is reflected in the actual dissociation and in the high rotational excitation and lack of vibrational excitation of the N_2 product. The calculations are based on a multidimensional reflection principle using an ab initio potential energy surface. The theory for the absorption cross section and isotopomer fractionation accompanying photodissociation is described. The absolute value of the theoretically calculated absorption cross section is very close (90%) to the experimentally observed value. The present computations also provide data for the slope of a three-isotope plot of the fractionation of 447/446 relative to 448/446, using the fractionations at different wavelengths. The resulting slope is compared with a perturbation theoretical expression for direct photodissociation given elsewhere

Modelling a pandemic with asymptomatic patients, impact of lockdown and herd immunity, with applications to SARS-CoV-2

The SARS-CoV-2 is a type of coronavirus that has caused the pandemic known as the Coronavirus Disease of 2019, or COVID-19. In traditional epidemiological models such as SEIR (Susceptible, Exposed, Infected, Removed), the exposed group E does not infect the susceptible group S. A distinguishing feature of COVID-19 is that, unlike with previous viral diseases, there is a distinct “asymptomatic” group A, which does not show any symptoms, but can nevertheless infect others, at the same rate as infected symptomatic patients. This situation is captured in a model known as SAIR (Susceptible, Asymptomatic, Infected, Removed), introduced in Robinson and Stillianakis (2013). The dynamical behavior of the SAIR model is quite different from that of the SEIR model. In this paper, we use Lyapunov theory to establish the global asymptotic stabililty of the SAIR model, both without and with vital dynamics. Then we develop compartmental SAIR models to cater to the migration of population across geographic regions, and once again establish global asymptotic stability. Next, we go beyond long-term asymptotic analysis and present methods for estimating the parameters in the SAIR model. We apply these estimation methods to data from several countries including India, and demonstrate that the predicted trajectories of the disease closely match actual data. We show that “herd immunity” (defined as the time when the number of infected persons is maximum) can be achieved when the total of infected, symptomatic and asymptomatic persons is as low as 25% of the population. Previous estimates are typically 50% or higher. We also conclude that “lockdown” as a way of greatly reducing inter-personal contact has been very effective in checking the progress of the disease. © 2020 The Author(s

Modelling the COVID-19 Pandemic: Asymptomatic Patients, Lockdown and Herd Immunity

The SARS-Cov-2 is a type of coronavirus that has caused the COVID-19 pandemic. In traditional epidemiological models such as SEIR (Susceptible, Exposed, Infected, Removed), the exposed group E does not infect the susceptible group S. A distinguishing feature of COVID-19 is that, unlike with previous viruses, there is a distinct "asymptomatic"group A, who do not show any symptoms, but can nevertheless infect others, at the same rate as infected patients. This situation is captured in a model known as SAIR (Susceptible, Asymptomatic, Infected, Removed), introduced in Robinson and Stilianakis (2013). The dynamical behavior of the SAIR model is quite different from that of the SEIR model. In this paper, we use Lyapunov theory to establish the global asymptotic stabiilty of the SAIR model. Next, we present methods for estimating the parameters in the SAIR model. We apply these estimation methods to data from several countries including India, and show that the predicted trajectories of the disease closely match actual data. ©2020 The Authors.This is an open access article under the CC BY-NC-ND license

Development of Broad Spectrum and Durable Bacterial Blight Resistant Variety through Pyramiding of Four Resistance Genes in Rice

Not AvailableBacterial blight (BB) disease caused by Xanthomonas oryzae pv. oryzae is a major biotic constraint on obtaining higher grain yields in rice. Marker-assisted backcross breeding (MABB) was performed by the pyramiding of Xa4, xa5, xa13 and Xa21 resistance genes in the popular variety, Ranidhan. A foreground selection in BC1F1, BC2F1, and BC3F1 progenies detected all the target genes in 12, 7 and 16 progenies by using the closely linked markers from a population size of 426, 410, and 530, respectively. The BB-positive progenies carrying the target genes with a maximal similarity to the recipient parent was backcrossed in each backcross generation. A total of 1784 BC3F2 seeds were obtained from the best BC3F1 progeny. The screening of the BC3F2 progenies for the four target genes resulted in eight plants carrying all the four target genes. A bioassay of the pyramided lines conferred very high levels of resistance to the predominant isolates of bacterial blight disease. In addition, these pyramided lines were similar to Ranidhan in 16 morpho-quality traits, namely, plant height, filled grains/panicle, panicles/plant, grain length, grain breadth, grain weight, milling, head rice recovery, kernel length after cooking, water uptake, the volume expansion ratio, gel consistency,alkali-spreading value, and the amylose content.Not Availabl

Deep2Full: Evaluating strategies for selecting the minimal mutational experiments for optimal computational predictions of deep mutational scan outcomes.

Performing a complete deep mutational scan with all single point mutations may not be practical, and may not even be required, especially if predictive computational models can be developed. Computational models are however naive to cellular response in the myriads of assay-conditions. In a realistic paradigm of assay context-aware predictive hybrid models that combine minimal experimental data from deep mutational scans with structure, sequence information and computational models, we define and evaluate different strategies for choosing this minimal set. We evaluated the trivial strategy of a systematic reduction in the number of mutational studies from 85% to 15%, along with several others about the choice of the types of mutations such as random versus site-directed with the same 15% data completeness. Interestingly, the predictive capabilities by training on a random set of mutations and using a systematic substitution of all amino acids to alanine, asparagine and histidine (ANH) were comparable. Another strategy we explored, augmenting the training data with measurements of the same mutants at multiple assay conditions, did not improve the prediction quality. For the six proteins we analyzed, the bin-wise error in prediction is optimal when 50-100 mutations per bin are used in training the computational model, suggesting that good prediction quality may be achieved with a library of 500-1000 mutations

Dielectric dispersion interpretation of single enzyme dynamic disorder, spectral diffusion, and radiative fluorescence lifetime

A formulation based on measurable dielectric dispersion of enzymes is developed to estimate fluctuations in electrostatic interaction energy on time scales as long as milliseconds to seconds at a local site in enzymes. Several single molecule experimental observations occur on this time scale, currently unreachable by real time computational trajectory simulations. We compare the experimental results on the autocorrelation function of the fluctuations of catalysis rate with the calculations using the dielectric dispersion formulation. We also discuss the autocorrelation functions of the fluorescence lifetime and of spectral diffusion. We use a previously derived relation between the observables and the electric field fluctuations and calculate the latter using dielectric dispersion data for the proteins and the Onsager regression hypothesis

Probing the Mechanism of pH-Induced Large-Scale Conformational Changes in Dengue Virus Envelope Protein Using Atomistic Simulations

One of the key steps in the infection of the cell by dengue virus is a pH-induced conformational change of the viral envelope proteins. These envelope proteins undergo a rearrangement from a dimer to a trimer, with large conformational changes in the monomeric unit. In this article, metadynamics simulations were used to enable us to understand the mechanism of these large-scale changes in the monomer. By using all-atom, explicit solvent simulations of the monomers, the stability of the protein structure is studied under low and high pH conditions. Free energy profiles obtained along appropriate collective coordinates demonstrate that pH affects the domain interface in both the conformations of E monomer, stabilizing one and destabilizing the other. These simulations suggest a mechanism with an intermediate detached state between the two monomeric structures. Using further analysis, we comment on the key residue interactions responsible for the instability and the pH-sensing role of a histidine that could not otherwise be studied experimentally. The insights gained from this study and methodology can be extended for studying similar mechanisms in the E proteins of the other members of class II flavivirus family