Stochastic kinetics of viral capsid assembly based on detailed protein structures

We present a generic computational framework for the simulation of viral capsid assembly which is quantitative and specific. Starting from PDB files containing atomic coordinates, the algorithm builds a coarse grained description of protein oligomers based on graph rigidity. These reduced protein descriptions are used in an extended Gillespie algorithm to investigate the stochastic kinetics of the assembly process. The association rates are obtained from a diffusive Smoluchowski equation for rapid coagulation, modified to account for water shielding and protein structure. The dissociation rates are derived by interpreting the splitting of oligomers as a process of graph partitioning akin to the escape from a multidimensional well. This modular framework is quantitative yet computationally tractable, with a small number of physically motivated parameters. The methodology is illustrated using two different viruses which are shown to follow quantitatively different assembly pathways. We also show how in this model the quasi-stationary kinetics of assembly can be described as a Markovian cascading process in which only a few intermediates and a small proportion of pathways are present. The observed pathways and intermediates can be related a posteriori to structural and energetic properties of the capsid oligomers

The evolving SARS-CoV-2 epidemic in Africa: insights from rapidly expanding genomic surveillance

Investment in SARS-CoV-2 sequencing in Africa over the past year has led to a major increase in the number of sequences generated, now exceeding 100,000 genomes, used to track the pandemic on the continent. Our results show an increase in the number of African countries able to sequence domestically, and highlight that local sequencing enables faster turnaround time and more regular routine surveillance. Despite limitations of low testing proportions, findings from this genomic surveillance study underscore the heterogeneous nature of the pandemic and shed light on the distinct dispersal dynamics of Variants of Concern, particularly Alpha, Beta, Delta, and Omicron, on the continent. Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve, while the continent faces many emerging and re-emerging infectious disease threats. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance.

Investment in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing in Africa over the past year has led to a major increase in the number of sequences that have been generated and used to track the pandemic on the continent, a number that now exceeds 100,000 genomes. Our results show an increase in the number of African countries that are able to sequence domestically and highlight that local sequencing enables faster turnaround times and more-regular routine surveillance. Despite limitations of low testing proportions, findings from this genomic surveillance study underscore the heterogeneous nature of the pandemic and illuminate the distinct dispersal dynamics of variants of concern-particularly Alpha, Beta, Delta, and Omicron-on the continent. Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve while the continent faces many emerging and reemerging infectious disease threats. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Practical equivalent continuum characterization of jointed rock masses

A simple practical method to characterize the strength and stiffness of jointed rock masses is presented in this paper. The empirical relations for the strength and stiffness of rock masses have been arrived based on the statistical analysis of a large amount of experimental data, which are used for representing the jointed rock mass as an equivalent continuum. The effect of joints in the rock mass is taken into account by a joint factor. These obtained relations are incorporated in a non-linear FEM code to represent the equivalent continuum analysis. The equivalent continuum model has been validated against experimental results for jointed rock masses with different joint fabric and joint orientation and also with the results from explicit modeling of joints using FEM. The developed model has also been applied to calculate the deformation around a large power station cavern in rhyolite rock at 200 m depth

Micromechanical modelling of monotonic drained and undrained shear behaviour of granular media using three dimensional DEM

In this paper, numerical simulation results of isotropic compression and triaxial static shear tests under drained and undrained stress paths on polydisperse assembly of loose and dense spheres are presented. An examination of the micromechanical behaviour of loose and dense assemblies under drained and undrained conditions, considering the particulate nature of granular materials, has been carried out to explain micromechanically the granular material behaviour at the grain scale level. The numerical simulations have been carried out using a discrete element model (DEM) which considers a 1000 sphere particle polydisperse assembly with periodic space representing an infinite three-dimensional space. In this paper, we present how DEM simulations can contribute to developments in constitutive modelling of granular materials through micromechanical approach using information on microstructure evolution. A series of numerical tests are performed using DEM on 3-D assemblages of spheres to study the evolution of the internal variables such as average co-ordination number and induced anisotropy during deformation along with the macroscopic behaviour of the assemblage in drained and undrained shear tests. In a qualitative sense, the macroscopic stress-strain results and stress path evolution in these simulations using 3-D assemblies demonstrate that DEM simulations are capable of reproducing ealistic compression and shear behaviour of granular materials

Trajectory Planning of Robot Manipulators in Noisy Work Spaces Using Stochastic Automata

We consider the problem of a robot manipulator operating in a noisy work space. The robot is assigned the task of moving from Pi to Pf. Because Pi is its initial position, this position can be known fairly accurately. However, because Pf is usu ally obtained as a result of a sensing operation, possibly vision sensing, we assume that Pf is noisy. We propose a so lution to achieve the motion that involves a new learning automaton, called the Discretized Linear Reward-Penalty (DLRP) automaton. The strategy we propose does not involve the computation of any inverse kinematics. Alternatively, an automaton is positioned at each joint of the robot, and by processing repeated noisy observations of Pf the automata operate in parallel to control the motion of the manipulator

An alternative method for probabilistic seismic-hazard assessment: A case study of three cities

Abstract not available