Search

Abstract The fusion of viruses with cellular membranes is a critical step in the life cycle of enveloped viruses. This process is facilitated by viral fusion proteins, many of which are conformationally pH-sensitive. The specifics of how changes in pH initiate this fusion have remained largely elusive. This study presents the cryo-electron microscopy (cryo-EM) structures of a prototype class III fusion protein, GP64, in its prefusion and early intermediate states, revealing the structural intermediates accompanying the membrane fusion process. The structures identify the involvement of a pH-sensitive switch, comprising H23, H245, and H304, in sensing the low pH that triggers the initial step of membrane fusion. The pH sensing role of this switch is corroborated by assays of cell-cell syncytium formation and dual dye-labeling. The findings demonstrate that coordination between multiple histidine residues acts as a pH sensor and activator. The involvement of a multi-histidine switch in viral fusion is applicable to fusogens of human-infecting thogotoviruses and other viruses, which could lead to strategies for developing anti-viral therapies and vaccines.

The data-driven phenomenological models based on deformation measurements have been widely utilized to predict the slope failure time (SFT). The observational and model uncertainties could lead the predicted SFT calculated from the phenomenological models to deviate from the actual SFT. Currently, very limited study has been conducted on how to evaluate the effect of such uncertainties on SFT prediction. In this paper, a comprehensive slope failure database was compiled. A Bayesian machine learning (BML)-based method was developed to learn the model and observational uncertainties involved in SFT prediction, through which the probabilistic distribution of the SFT can be obtained. This method was illustrated in detail with an example. Verification studies show that the BML-based method is superior to the traditional inverse velocity method (INVM) and the maximum likelihood method for predicting SFT. The proposed method in this study provides an effective tool for SFT prediction.

There will be great damage in the process of harvesting, transporting, and storing after grain matures. The injury rate is as high as 8% to 12%. After damage, the germination rate of the grain becomes lower, the quality decreases, and it is easily infected with pests and molds. This study of the grain-crushing characteristics is of great significance to ensure grain quality, and an accurate crushing model is a prerequisite for effectively simulating crushing characteristics. This paper studies the shattering characteristics of wheat grains. Two-dimensional slices of wheat grain were obtained using X-ray tomography technology. Then, an accurate three-dimensional outer contour model of the wheat particle was constructed using image filtering and segmentation algorithms. The particle filling process was conducted using EDEM 2018 software to establish a wheat particle simulation model based on the Hertz–Mindlin with a Bonding contact model. Using the DOE experimental design method, single-factor experiments, Plackett–Burman experiments, steepest-climb experiments, and Box–Behnken were designed to study the fragmentation characteristics of wheat particles combined with parameter calibration and physical experiments. The test results show that the normal stiffness per unit area is 7.392 × 1010 N/m3, critical normal stress is 5.293 × 106 Pa, critical tangential stress is 5.001 × 106 Pa, and the relative error about 3%, which verifies the reliability of the simulation parameters in the discrete-element crushing model of wheat grain. This study focuses on two essential aspects: 1. establishing an accurate wheat-grain contour model; and 2. calibrating the bonding parameters of the discrete-element simulation model of wheat grain. The wheat grain discrete-element crushing model and the calibration of its bonding parameters are constructed to provide a foundation for the study of wheat-grain crushing characteristics. It is of great significance to study the situation of wheat grains and where cracks are produced. In this paper, an accurate model of the wheat-grain contour is established, and the bonding parameters of the discrete-element simulation model of the wheat grain are calibrated. The calibration of the model of the discrete elements of wheat-grain fragmentation and its bonding parameters will provide a basis for studying the crushing characteristics of wheat grain. Understanding the condition of wheat grains and the causes of cracks carries significant academic significance.