Geological surface reconstruction from 3D point clouds

Post-translational modifications of histone and non-histone proteins in epigenetic regulation and translational applications in alcohol-associated liver disease: Challenges and research opportunities

Epigenetic regulation is a process that takes place through adaptive cellular pathways influenced by environmental factors and metabolic changes to modulate gene activity with heritable phenotypic variations without altering the DNA sequences of many target genes. Epigenetic regulation can be facilitated by diverse mechanisms: many different types of post-translational modifications (PTMs) of histone and non-histone nuclear proteins, DNA methylation, altered levels of noncoding RNAs, incorporation of histone variants, nucleosomal positioning, chromatin remodeling, etc. These factors modulate chromatin structure and stability with or without the involvement of metabolic products, depending on the cellular context of target cells or environmental stimuli, such as intake of alcohol (ethanol) or Western-style high-fat diets. Alterations of epigenetics have been actively studied, since they are frequently associated with multiple disease states. Consequently, explorations of epigenetic regulation have recently shed light on the pathogenesis and progression of alcohol-associated disorders. In this review, we highlight the roles of various types of PTMs, including less-characterized modifications of nuclear histone and non-histone proteins, in the epigenetic regulation of alcohol-associated liver disease (ALD) and other disorders. We also describe challenges in characterizing specific PTMs and suggest future opportunities for basic and translational research to prevent or treat ALD and many other disease states.

An Intelligent Analysis Method for 3D Wheat Grain and Ventral Sulcus Traits Based on Structured Light Imaging

The wheat grain three-dimensional (3D) phenotypic characters are of great significance for final yield and variety breeding, and the ventral sulcus traits are the important factors to the wheat flour yield. The wheat grain trait measurements are necessary; however, the traditional measurement method is still manual, which is inefficient, subjective, and labor intensive; moreover, the ventral sulcus traits can only be obtained by destructive measurement. In this paper, an intelligent analysis method based on the structured light imaging has been proposed to extract the 3D wheat grain phenotypes and ventral sulcus traits. First, the 3D point cloud data of wheat grain were obtained by the structured light scanner, and then, the specified point cloud processing algorithms including single grain segmentation and ventral sulcus location have been designed; finally, 28 wheat grain 3D phenotypic characters and 4 ventral sulcus traits have been extracted. To evaluate the best experimental conditions, three-level orthogonal experiments, which include rotation angle, scanning angle, and stage color factors, were carried out on 125 grains of 5 wheat varieties, and the results demonstrated that optimum conditions of rotation angle, scanning angle, and stage color were 30°, 37°, black color individually. Additionally, the results also proved that the mean absolute percentage errors (MAPEs) of wheat grain length, width, thickness, and ventral sulcus depth were 1.83, 1.86, 2.19, and 4.81%. Moreover, the 500 wheat grains of five varieties were used to construct and validate the wheat grain weight model by 32 phenotypic traits, and the cross-validation results showed that the R 2 of the models ranged from 0.77 to 0.83. Finally, the wheat grain phenotype extraction and grain weight prediction were integrated into the specialized software. Therefore, this method was demonstrated to be an efficient and effective way for wheat breeding research.