Importance sampling within configuration space integration for adsorbate thermophysical properties: a case study for CH3/Ni(111).

A new strategy is presented for computing anharmonic partition functions for the motion of adsorbates relative to a catalytic surface. Importance sampling is compared with conventional Monte Carlo. The importance sampling is significantly more efficient. This new approach is applied to CH3* on Ni(111) as a test case. The motion of methyl relative to the nickel surface is found to be anharmonic, with significantly higher entropy compared to the standard harmonic oscillator model. The new method is freely available as part of the Minima-Preserving Neural Network within the ADTHERM package.

Pynta─An Automated Workflow for Calculation of Surface and Gas-Surface Kinetics.

Many important industrial processes rely on heterogeneous catalytic systems. However, given all possible catalysts and conditions of interest, it is impractical to optimize most systems experimentally. Automatically generated microkinetic models can be used to efficiently consider many catalysts and conditions. However, these microkinetic models require accurate estimation of many thermochemical and kinetic parameters. Manually calculating these parameters is tedious and error prone, involving many interconnected computations. We present Pynta, a workflow software for automating the calculation of surface and gas-surface reactions. Pynta takes the reactants, products, and atom maps for the reactions of interest, generates sets of initial guesses for all species and saddle points, runs all optimizations, frequency, and IRC calculations, and computes the associated thermochemistry and rate coefficients. It is able to consider all unique adsorption configurations for both adsorbates and saddle points, allowing it to handle high index surfaces and bidentate species. Pynta implements a new saddle point guess generation method called harmonically forced saddle point searching (HFSP). HFSP defines harmonic potentials based on the optimized adsorbate geometries and which bonds are breaking and forming that allow initial placements to be optimized using the GFN1-xTB semiempirical method to create reliable saddle point guesses. This method is reaction class agnostic and fast, allowing Pynta to consider all possible adsorbate site placements efficiently. We demonstrate Pynta on 11 diverse reactions involving monodenate, bidentate, and gas-phase species, many distinct reaction classes, and both a low and a high index facet of Cu. Our results suggest that it is very important to consider reactions between adsorbates adsorbed in all unique configurations for interadsorbate group transfers and reactions on high index surfaces.

Evaluation of the effectiveness of foot-and-mouth disease vaccination of animals in the buffer zone of the Republic of Armenia in 2016-2020.

BACKGROUND: Foot-and-mouth disease (FMD) is a high impact viral disease of livestock for which vaccines are extensively used for limiting the spread of infection. Armenia shares a border with both Turkey and Iran where FMD is endemic, making vaccination an important component of Armenia's control strategy. Additionally, Armenian veterinary services utilize both passive and active monitoring for prevention control. METHODS: We sought to determine the immune status of animals vaccinated against FMD and to evaluate the effectiveness of our vaccination policy in Armenia. This was conducted in three regions including Shirak, Armavir, and Ararat Region which are located in the buffer zones that border Turkey and Iran. Through active monitoring in 2020, we studied blood serum samples from cattle and sheep using an enzyme immunoassay to determine the level of immune animals in these regions following the use of a polyvalent inactivated vaccine containing FMDV serotypes A, O, and Asia-1 that are relevant for this region. ELISA titers were assessed at 28, 90, and 180 days after vaccination in cattle of three age groups at the time of initial vaccination: 4-6 months, 6-18 months and ≥ 24 months of age with sheep of all ages. RESULTS: The 3 age groups of cattle had similarly high levels of immunity with over 90% of the cattle showing a ≥ 50% protective titer 28 days after the first vaccination. By day 90, titers in cattle from the initial 4-18-month age groups dropped below 58% across the 3 serotypes and at or below 80% for the oldest cattle ≥ 24 months. Re-vaccination of cattle at 120 days did improve protective titers but never reached the level of immunity of the first vaccination. Sheep showed a similar rapid drop to less than 50% having a ≥ 50% protective titer at 90 days emphasizing the need for continual revaccination. CONCLUSIONS: The results of this study have important implications for the current FMD vaccine policy in Armenia and improves our understanding of the rapid loss of protective titers over short periods. Since small ruminants are only vaccinated once per year and vaccination titers drop rapidly by 90 days suggests that they are vulnerable to FMD and that vaccination protocols need to be updated. Cattle should continue to be vaccinated every 3-6 months depending on their age to maintain a protective level of antibodies to protect them from FMD. More studies are needed to understand the possible role of small ruminants in the epidemiology of FMD and to evaluate revaccination at shorter intervals. These results show the concerns of rapid loss of protection to both cattle and small ruminants following 1 or more doses of commercial vaccines and that additional vaccines need to be evaluated in both groups to know how often they must be vaccinated to provide full protection. The addition of challenge studies should also be considered to better understand the level of protection as measured by serology and how it relates to protection from challenge. These results should be considered by anyone using these vaccines in cattle and sheep at longer than 3 month intervals.

Geometry optimization speedup through a geodesic approach to internal coordinates.

We present a new geodesic-based method for geometry optimization in a basis set of redundant internal coordinates. Our method updates the molecular geometry by following the geodesic generated by a displacement vector on the internal coordinate manifold, which dramatically reduces the number of steps required to converge to a minimum. Our method can be implemented in any existing optimization code, requiring only implementation of derivatives of the Wilson B-matrix and the ability to numerically solve an ordinary differential equation.

Duration of Immunity in Cattle to Lumpy Skin Disease Utilizing a Sheep Pox Vaccine.

The transmission of lumpy skin disease (LSD) occurs through ticks, mosquitoes, and flies. The most effective way to combat LSD is to conduct large-scale vaccination, covering the entire cattle population with safe and effective vaccines, while introducing restrictions on the movement of livestock. The first and only LSD cases that occurred in Armenia happened in 2015,and they were controlled with the use of a once yearly heterologous sheep pox vaccine for cattle in high-risk areas. We have previously reported on the safety and immunogenicity of this vaccine in cattle, but information on the duration of immunity is lacking. Our aim was to determine the duration of immunity to the LSD virus (LSDV) in cattle when utilizing a heterologous sheep pox vaccine. We have evaluated antibodies in cattle blood prior to and post-vaccination (1, 6, and 11 months). We have utilized an enzyme-linked immunosorbent assay to follow the development and waning of LSDV antibodies in vaccinated cattle in two age groups: 1) young unvaccinated cattle ≤12 months of age and 2) adult cattle that had previously been vaccinated. Our results were consistent with our previous study in Armenia, showing a high level of population immunity, 80.0-83.3%, in both age groups at 1 month, with a significant (p = 0.001) drop for young cattle at 6 months. Previously vaccinated adult cattle showed a longer duration of immunity at 11 months for this heterologous sheep pox vaccine. Based on these data, we advise that young cattle receive an additional booster vaccination 4-6 months after their first vaccination, and then yearly vaccinations in high-risk areas.

The Serological Response in Cattle following Administration of a Heterologous Sheep Pox Virus Strain Vaccine for Protection from Lumpy Skin Disease; Current Situation in Armenia.

Lumpy skin disease (LSD) is a highly infectious viral disease of cattle caused by LSD virus (LSDV), which was first reported in Armenia in late 2015. It was identified in pasture-raised cattle near the border with Iran. Currently, vaccination plays a key role in preventing further incursion of disease in high-risk areas. The purpose of this work was to assess the quality of vaccination currently used in Armenia by determining the immune response of the heterologous dry culture sheep pox virus-based vaccine against LSD in cattle. Seroprevalence and seroconversion testing was carried out using an ELISA to detect specific antibodies against LSD before and 30 days after vaccination in three adjacent regions of Armenia (Ararat, Armavir, Gegharkunik). Ixodes ticks were also examined for the presence of LSDV via real-time PCR. We found that the heterologous vaccine used in Armenia creates a high level of population immunity of 86.09% (83.83-87.97%) and no adverse side effects were observed in cattle. Of the 6 types of Ixodes ticks identified and tested, we found no evidence of LSDV circulating in these vectors. These results suggest that regular serological monitoring via ELISA and heterologous vaccination should continue in areas of Armenia at high risk for incursion of LSD to reduce the spread of this highly infectious transboundary disease.

Sources of cell-to-cell variability in canonical nuclear factor-κB (NF-κB) signaling pathway inferred from single cell dynamic images.

The canonical nuclear factor-κB (NF-κB) signaling pathway controls a gene network important in the cellular inflammatory response. Upon activation, NF-κB/RelA is released from cytoplasmic inhibitors, from where it translocates into the nucleus, subsequently activating negative feedback loops producing either monophasic or damped oscillatory nucleo-cytoplasmic dynamics. Although the population behavior of the NF-κB pathway has been extensively modeled, the sources of cell-to-cell variability are not well understood. We describe an integrated experimental-computational analysis of NF-κB/RelA translocation in a validated cell model exhibiting monophasic dynamics. Quantitative measures of cellular geometry and total cytoplasmic concentration and translocated RelA amounts were used as priors in Bayesian inference to estimate biophysically realistic parameter values based on dynamic live cell imaging studies of enhanced GFP-tagged RelA in stable transfectants. Bayesian inference was performed on multiple cells simultaneously, assuming identical reaction rate parameters, whereas cellular geometry and initial and total NF-κB concentration-related parameters were cell-specific. A subpopulation of cells exhibiting distinct kinetic profiles was identified that corresponded to differences in the IκBα translation rate. We conclude that cellular geometry, initial and total NF-κB concentration, IκBα translation, and IκBα degradation rates account for distinct cell-to-cell differences in canonical NF-κB translocation dynamics.

Pathology of porcine peripheral white blood cells during infection with African swine fever virus.

BACKGROUND: African swine fever virus (ASFV) is the causative agent of African swine fever (ASF) that is the significant disease of domestic pigs. Several studies showed that ASFV can influence on porcine blood cells in vitro. Thus, we asked ourselves whether ASFV infection results in changes in porcine blood cells in vivo. A series of experiments were performed in order to investigate the effects of ASFV infection on porcine peripheral white blood cells. Nine pigs were inoculated by intramuscular injection with 104 50% hemadsorbing doses of virus (genotype II) distributed in Armenia and Georgia. The total number of fifteen cell types was calculated during experimental infection. RESULTS: Although band-to-segmented neutrophils ratio became much higher (3.5) in infected pigs than in control group (0.3), marked neutropenia and lymphopenia were detected from 2 to 3 days post-infection. In addition to band neutrophils, the high number of other immature white blood cells, such as metamyelocytes, was observed during the course of infection. From the beginning of infection, atypical lymphocytes, with altered nuclear shape, arose and became 15% of total cells in the final phase of infection. Image scanning cytometry revealed hyperdiploid DNA content in atypical lymphocytes only from 5 days post-infection, indicating that DNA synthesis in pathological lymphocytes occurred in the later stages of infection. CONCLUSION: From this study, it can be concluded that ASFV infection leads to serious changes in composition of white blood cells. Particularly, acute ASFV infection in vivo is accompanied with the emergence of immature cells and atypical lymphocytes in the host blood. The mechanisms underlying atypical cell formation remain to be elucidated.

Sella, an Open-Source Automation-Friendly Molecular Saddle Point Optimizer.

We present a new algorithm for the optimization of molecular structures to saddle points on the potential energy surface using a redundant internal coordinate system. This algorithm automates the procedure of defining the internal coordinate system, including the handling of linear bending angles, for example, through the addition of dummy atoms. Additionally, the algorithm supports constrained optimization using the null-space sequential quadratic programming formalism. Our algorithm determines the direction of the reaction coordinate through iterative diagonalization of the Hessian matrix and does not require evaluation of the full Hessian matrix. Geometry optimization steps are chosen using the restricted step partitioned rational function optimization method, and displacements are realized using a high-performance geodesic stepping algorithm. This results in a robust and efficient optimization algorithm suitable for use in automated frameworks. We have implemented our algorithm in Sella, an open-source software package designed to optimize atomic systems to saddle point structures. We also introduce a new benchmark test comprising 500 molecular structures that approximate saddle point geometries and show that our saddle point optimization algorithm outperforms the algorithms implemented in several leading electronic structure theory packages.

Quantifying the Impact of Parametric Uncertainty on Automatic Mechanism Generation for CO2 Hydrogenation on Ni(111).

Automatic mechanism generation is used to determine mechanisms for the CO2 hydrogenation on Ni(111) in a two-stage process while considering the correlated uncertainty in DFT-based energetic parameters systematically. In a coarse stage, all the possible chemistry is explored with gas-phase products down to the ppb level, while a refined stage discovers the core methanation submechanism. Five thousand unique mechanisms were generated, which contain minor perturbations in all parameters. Global uncertainty assessment, global sensitivity analysis, and degree of rate control analysis are performed to study the effect of this parametric uncertainty on the microkinetic model predictions. Comparison of the model predictions with experimental data on a Ni/SiO2 catalyst find a feasible set of microkinetic mechanisms within the correlated uncertainty space that are in quantitative agreement with the measured data, without relying on explicit parameter optimization. Global uncertainty and sensitivity analyses provide tools to determine the pathways and key factors that control the methanation activity within the parameter space. Together, these methods reveal that the degree of rate control approach can be misleading if parametric uncertainty is not considered. The procedure of considering uncertainties in the automated mechanism generation is not unique to CO2 methanation and can be easily extended to other challenging heterogeneously catalyzed reactions.

Characterization of partially observed epidemics through Bayesian inference: application to COVID-19.

We demonstrate a Bayesian method for the "real-time" characterization and forecasting of partially observed COVID-19 epidemic. Characterization is the estimation of infection spread parameters using daily counts of symptomatic patients. The method is designed to help guide medical resource allocation in the early epoch of the outbreak. The estimation problem is posed as one of Bayesian inference and solved using a Markov chain Monte Carlo technique. The data used in this study was sourced before the arrival of the second wave of infection in July 2020. The proposed modeling approach, when applied at the country level, generally provides accurate forecasts at the regional, state and country level. The epidemiological model detected the flattening of the curve in California, after public health measures were instituted. The method also detected different disease dynamics when applied to specific regions of New Mexico.

Accelerated Saddle Point Refinement through Full Exploitation of Partial Hessian Diagonalization.

Identification and refinement of first order saddle point (FOSP) structures on the potential energy surface (PES) of chemical systems is a computational bottleneck in the characterization of reaction pathways. Leading FOSP refinement strategies for modestly sized molecular systems require calculation of the full Hessian matrix, which is not feasible for larger systems such as those encountered in heterogeneous catalysis. For these systems, the standard approach to FOSP refinement involves iterative diagonalization of the Hessian, but this comes at the cost of longer refinement trajectories due to the lack of accurate curvature information. We present a method for incorporating information obtained by an iterative diagonalization algorithm into the construction of an approximate Hessian matrix that accelerates FOSP refinement. We measure the performance of our method with two established FOSP refinement benchmarks and find a 50% reduction on average in the number of gradient evaluations required to converge to a FOSP for one benchmark and a 25% reduction on average for the second benchmark.

Multiparameter spectral representation of noise-induced competence in Bacillus subtilis.

In this work, the problem of representing a stochastic forward model output with respect to a large number of input parameters is considered. The methodology is applied to a stochastic reaction network of competence dynamics in Bacillus subtilis bacterium. In particular, the dependence of the competence state on rate constants of underlying reactions is investigated. We base our methodology on Polynomial Chaos (PC) spectral expansions that allow effective propagation of input parameter uncertainties to outputs of interest. Given a number of forward model training runs at sampled input parameter values, the PC modes are estimated using a Bayesian framework. As an outcome, these PC modes are described with posterior probability distributions. The resulting expansion can be regarded as an uncertain response function and can further be used as a computationally inexpensive surrogate instead of the original reaction model for subsequent analyses such as calibration or optimization studies. Furthermore, the methodology is enhanced with a classification-based mixture PC formulation that overcomes the difficulties associated with representing potentially nonsmooth input-output relationships. Finally, the global sensitivity analysis based on the multiparameter spectral representation of an observable of interest provides biological insight and reveals the most important reactions and their couplings for the competence dynamics