In silico characterization of five novel disease-resistance proteins in Oryza sativa sp. japonica against bacterial leaf blight and rice blast diseases.

In the current study, gene network analysis revealed five novel disease-resistance proteins against bacterial leaf blight (BB) and rice blast (RB) diseases caused by Xanthomonas oryzae pv. oryzae (Xoo) and Magnaporthe oryzae (M. oryzae), respectively. In silico modeling, refinement, and model quality assessment were performed to predict the best structures of these five proteins and submitted to ModelArchive for future use. An in-silico annotation indicated that the five proteins functioned in signal transduction pathways as kinases, phospholipases, transcription factors, and DNA-modifying enzymes. The proteins were localized in the nucleus and plasma membrane. Phylogenetic analysis showed the evolutionary relation of the five proteins with disease-resistance proteins (XA21, OsTRX1, PLD, and HKD-motif-containing proteins). This indicates similar disease-resistant properties between five unknown proteins and their evolutionary-related proteins. Furthermore, gene expression profiling of these proteins using public microarray data showed their differential expression under Xoo and M. oryzae infection. This study provides an insight into developing disease-resistant rice varieties by predicting novel candidate resistance proteins, which will assist rice breeders in improving crop yield to address future food security through molecular breeding and biotechnology. Supplementary Information: The online version contains supplementary material available at 10.1007/s13205-023-03893-5.

Spontaneous layering and power-law order in the three-dimensional fully packed hard-plate lattice gas.

We obtain the phase diagram of fully packed hard plates on the cubic lattice. Each plate covers an elementary plaquette of the cubic lattice and occupies its four vertices, with each vertex of the cubic lattice occupied by exactly one such plate. We consider the general case with fugacities s_{µ} for "µ plates," whose normal is the µ direction (µ=x,y,z). At and close to the isotropic point, we find, consistent with previous work, a phase with long-range sublattice order. When two of the fugacities s_{µ_{1}} and s_{µ_{2}} are comparable, and the third fugacity s_{µ_{3}} is much smaller, we find a spontaneously layered phase. In this phase, the system breaks up into disjoint slabs of width two stacked along the µ_{3} axis. µ_{1} and µ_{2} plates are preferentially contained entirely within these slabs, while plates straddling two successive slabs have a lower density. This corresponds to a twofold breaking of translation symmetry along the µ_{3} axis. In the opposite limit, with µ_{3}≫µ_{1}∼µ_{2}, we find a phase with long-range columnar order, corresponding to simultaneous twofold symmetry breaking of lattice translation symmetry in directions µ_{1} and µ_{2}. The spontaneously layered phases display critical behavior, with power-law decay of correlations in the µ_{1} and µ_{2} directions when the slabs are stacked in the µ_{3} direction, and represent examples of "floating phases" discussed earlier in the context of coupled Luttinger liquids and quasi-two-dimensional classical systems. We ascribe this remarkable behavior to the constrained motion of defects in this phase, and we sketch a coarse-grained effective field theoretical understanding of the stability of power-law order in this unusual three-dimensional floating phase.

From classical to quantum stochastic processes.

In this paper, we construct quantum analogs starting from classical stochastic processes, by replacing random "which path" decisions with superpositions of all paths. This procedure typically leads to nonunitary quantum evolution, where coherences are continuously generated and destroyed. In spite of their transient nature, these coherences can change the scaling behavior of classical observables. Using the zero temperature Glauber dynamics in a linear Ising spin chain, we find quantum analogs with different domain growth exponents. In some cases, this exponent is even smaller than for the original classical process, which means that coherence can play an important role to speed up the relaxation process.

Evaluation of e-OSPE as compared to traditional OSPE: A pilot study.

Objectively Structured Clinical/Practical Examination (OSCE/OSPE) has been the backbone of the assessment system of graduate medical education for over three decades. We have developed an electronic Objectively Structured Practical Examination (e-OSPE) in Medical Biochemistry using the freely available Google forms to mitigate the academic disruption posed by COVID-19 pandemic in our resource-poor setting. Ten e-OSPE stations created, interlinked, and time-restricted. Fifty undergraduate students appeared for the e-OSPE examination on a prefixed date and time. Learner feedback was collected immediately after the completion of the examination. Facilitator feedback was also collected. Students' mean scores in e-OSPE and traditional OSPE were 78.15% and 74.56%, respectively. Their difference was not statistically significant (paired t-test two-tailed p-value 0.0979). Thus, the results of e-OSPE are reliable as compared to traditional OSPE. Bland Altman Plot revealed 92% of students had scores that were in the agreeable limit of both traditional OSPE and e-OSPE. Both the learners and facilitators were in consensus that the online format of e-OSPE is a good alternative for assessment (0.67 and 0.82); their experience was good (0.72 and 0.92) and conduction was well organized (0.73 and 0.86). Several suggestions were also received to make e-OSPE even more effective. In conclusion, this pilot study showed e-OSPE can be an effective alternative to traditional OSPE when "in-person" evaluation is not possible such as in the current era of COVID-19 even in resource-limited settings.

SARS-CoV-2 and other human coronaviruses: Mapping of protease recognition sites, antigenic variation of spike protein and their grouping through molecular phylogenetics.

In recent years, a total of seven human pathogenic coronaviruses (HCoVs) strains were identified, i.e., SARS-CoV, SARS-CoV-2, MERS-CoV, HCoV-OC43, HCoV-229E, HCoV-NL63, and HCoV-HKU1. Here, we performed an analysis of the protease recognition sites and antigenic variation of the S-protein of these HCoVs. We showed tissue-specific expression pattern, functions, and a number of recognition sites of proteases in S-proteins from seven strains of HCoVs. In the case of SARS-CoV-2, we found two new protease recognition sites, each of calpain-2, pepsin-A, and caspase-8, and one new protease recognition site each of caspase-6, caspase-3, and furin. Our antigenic mapping study of the S-protein of these HCoVs showed that the SARS-CoV-2 virus strain has the most potent antigenic epitopes (highest antigenicity score with maximum numbers of epitope regions). Additionally, the other six strains of HCoVs show common antigenic epitopes (both B-cell and T-cell), with low antigenicity scores compared to SARS-CoV-2. We suggest that the molecular evolution of structural proteins of human CoV can be classified, such as (i) HCoV-NL63 and HCoV-229E, (ii) SARS-CoV-2, and SARS-CoV and (iii) HCoV-OC43 and HCoV-HKU1. In conclusion, we can presume that our study might help to prepare the interventions for the possible HCoVs outbreaks in the future.

The transition from objectively structured practical examination (OSPE) to electronic OSPE in the era of COVID-19.

The coronavirus (COVID-19) pandemic is forcing the medical educators to innovate and embrace online education and assessment platform. One of the most significant challenges we are facing is the formative assessment of practical skills in the undergraduate medical biochemistry education. We have designed the electronic objectively structured practical examination to facilitate the formative assessment.

Zero-temperature ordering dynamics in a two-dimensional biaxial next-nearest-neighbor Ising model.

We investigate the dynamics of a two-dimensional biaxial next-nearest-neighbor Ising model following a quench to zero temperature. The Hamiltonian is given by H=-J_{0}∑_{i,j=1}^{L}[(S_{i,j}S_{i+1,j}+S_{i,j}S_{i,j+1})-κ(S_{i,j}S_{i+2,j}+S_{i,j}S_{i,j+2})]. For κ<1, the system does not reach the equilibrium ground state and keeps evolving in active states forever. For κ≥1, though, the system reaches a final state, but it does not reach the ground state always and freezes to a striped state with a finite probability like a two-dimensional ferromagnetic Ising model and an axial next-nearest-neighbor Ising (ANNNI) model. The overall dynamical behavior for κ>1 and κ=1 is quite different. The residual energy decays in a power law for both κ>1 and κ=1 from which the dynamical exponent z has been estimated. The persistence probability shows algebraic decay for κ>1 with an exponent θ=0.22±0.002 while the dynamical exponent for ordering z=2.33±0.01. For κ=1, the system belongs to a completely different dynamical class with θ=0.332±0.002 and z=2.47±0.04. We have computed the freezing probability for different values of κ. We have also studied the decay of autocorrelation function with time for a different regime of κ values. The results have been compared with those of the two-dimensional ANNNI model.

Rich structure in the correlation matrix spectra in non-equilibrium steady states.

It has been shown that, if a model displays long-range (power-law) spatial correlations, its equal-time correlation matrix will also have a power law tail in the distribution of its high-lying eigenvalues. The purpose of this paper is to show that the converse is generally incorrect: a power-law tail in the high-lying eigenvalues of the correlation matrix may exist even in the absence of equal-time power law correlations in the initial model. We may therefore view the study of the eigenvalue distribution of the correlation matrix as a more powerful tool than the study of spatial Correlations, one which may in fact uncover structure, that would otherwise not be apparent. Specifically, we show that in the Totally Asymmetric Simple Exclusion Process, whereas there are no clearly visible correlations in the steady state, the eigenvalues of its correlation matrix exhibit a rich structure which we describe in detail.

Ballistic annihilation with superimposed diffusion in one dimension.

We consider a one-dimensional system with particles having either positive or negative velocity, and these particles annihilate on contact. Diffusion is superimposed on the ballistic motion of the particle. The annihilation may represent a reaction in which the two particles yield an inert species. This model has been the subject of previous work, in which it was shown that the particle concentration decays faster than either the purely ballistic or the purely diffusive case. We report on previously unnoticed behavior for large times when only one of the two species remains, and we also unravel the underlying fractal structure present in the system. We also consider in detail the case in which the initial concentration of right-going particles is 1/2+ɛ, with ɛ≠0. It is shown that remarkably rich behavior arises, in which two crossover times are observed as ɛ→0.

Exit probability in inflow dynamics: nonuniversality induced by range, asymmetry, and fluctuation.

Probing deeper into the existing issues regarding the exit probability (EP) in one-dimensional dynamical models, we consider several models where the states are represented by Ising spins and the information flows inwards. At zero temperature, these systems evolve to either of two absorbing states. The EP, E(x), which is the probability that the system ends up with all up spins starting with x fraction of up spins, is found to have the general form E(x)=xα/xα+(1-x)α. The EP exponent α strongly depends on r, the range of interaction, the symmetry of the model, and the induced fluctuation. Even in a nearest-neighbor model, a nonlinear form of the EP can be obtained by controlling the fluctuations, and for the same range, different models give different results for α. Nonuniversal behavior of the EP is thus clearly established and the results are compared to those of existing studies in models with outflow dynamics to distinguish the two dynamical scenarios.

Opinion dynamics model with weighted influence: exit probability and dynamics.

We introduce a stochastic model of binary opinion dynamics in which the opinions are determined by the size of the neighboring domains. The exit probability here shows a step function behavior, indicating the existence of a separatrix distinguishing two different regions of basin of attraction. This behavior, in one dimension, is in contrast to other well known opinion dynamics models where no such behavior has been observed so far. The coarsening study of the model also yields novel exponent values. A lower value of persistence exponent is obtained in the present model, which involves stochastic dynamics, when compared to that in a similar type of model with deterministic dynamics. This apparently counterintuitive result is justified using further analysis. Based on these results, it is concluded that the proposed model belongs to a unique dynamical class.

Effect of the nature of randomness on quenching dynamics of the Ising model on complex networks.

Randomness is known to affect the dynamical behavior of many systems to a large extent. In this paper we investigate how the nature of randomness affects the dynamics in a zero-temperature quench of the Ising model on two types of random networks. In both networks, which are embedded in a one-dimensional space, the first-neighbor connections exist and the average degree is 4 per node. In random model A the second-neighbor connections are rewired with a probability p, while in random model B additional connections between neighbors at a Euclidean distance l(l > 1) are introduced with a probability P(l) proportionally l(-α). We find that for both models, the dynamics leads to freezing such that the system gets locked in a disordered state. The point at which the disorder of the nonequilibrium steady state is maximum is located. The behavior of dynamical quantities such as residual energy, order parameter, and persistence are discussed and compared. Overall, the behavior of physical quantities are similar, although subtle differences are observed due to the difference in the nature of randomness.

Model of binary opinion dynamics: Coarsening and effect of disorder.

We propose a model of binary opinion in which the opinion of the individuals changes according to the state of their neighboring domains. If the neighboring domains have opposite opinions then the opinion of the domain with the larger size is followed. Starting from a random configuration, the system evolves to a homogeneous state. The dynamical evolution shows a scaling behavior with the persistence exponent theta approximately 0.235 and dynamic exponent z approximately 1.02 + or - 0.02. Introducing disorder through a parameter called rigidity coefficient rho (probability that people are completely rigid and never change their opinion), the transition to a heterogeneous society at rho=0(+) is obtained. Close to rho=0, the equilibrium values of the dynamic variables show power-law scaling behavior with rho. We also discuss the effect of having both quenched and annealed disorder in the system.

Zero-temperature dynamics in the two-dimensional axial next-nearest-neighbor Ising model.

We investigate the dynamics of a two-dimensional axial next-nearest-neighbor Ising model following a quench to zero temperature. The Hamiltonian is given by H= -J_(0) summation operator(L)_(i,j=1)S_(i,j)S_(i+1,j)-J_(1)summation operator_(i,j=1)(S_{i,j}S_{i,j+1}-kappaS_{i,j}S_{i,j+2}) . For kappa<1 , the system does not reach the equilibrium ground state but slowly evolves to a metastable state. For kappa>1 , the system shows a behavior similar to that of the two-dimensional ferromagnetic Ising model in the sense that it freezes to a striped state with a finite probability. The persistence probability shows algebraic decay here with an exponent theta=0.235+/-0.001 while the dynamical exponent of growth z=2.08+/-0.01 . For kappa=1 , the system belongs to a completely different dynamical class; it always evolves to the true ground state with the persistence and dynamical exponent having unique values. Much of the dynamical phenomena can be understood by studying the dynamics and distribution of the number of domain walls. We also compare the dynamical behavior to that of a Ising model in which both the nearest and next-nearest-neighbor interactions are ferromagnetic.