The unique optical properties of microplastic particles have a significant impact on atmospheric radiative forcing. Based on the generalized multi-particle Mie theory, this paper presents a comparative study of the extinction properties and absorption properties of single-component and mixed aerosol clusters composed of microplastics, dust, and black carbon in different structural forms and particle sizes. The results show that the structure, particle size, mixing arrangement, and orientation of aerosol particles containing microplastics will directly affect their optical properties. As the incident wavelength increases, significant differences are observed in the extinction and absorption cross-sections of microplastic and dust particle chains with different structures, although they exhibit similar trends. However, black carbon particle chains show a distinct variation pattern. In the mixed particle chains with different particle sizes, as the incident wavelength increases, the extinction and absorption cross-sections are significantly larger than those of the particle chains with the same particle size, indicating that the particle size has a remarkable influence on their optical properties. The different mixing forms and orientations of aerosol clusters also significantly affect their extinction and absorption cross-sections. These findings provide a new theoretical perspective for environmental optics and remote sensing monitoring of aerosols.

Some numerical simulations of drained and undrained triaxial tests on granular materials with different initial densities are carried out with the three-dimensional discrete element method. An in-depth particle-scale analysis is performed quantitatively to illustrate the physical mechanism of the shear mechanical behaviors, with a special attention paid to the characteristics of quasi-steady state and critical state. The simulation results show that the initial density and shear drainage condition both have significant effects on the evolution of stress-strain, coordination number, fabric anisotropy factor, force chains and clusters. The chained grains ratio and the mean length of force chains in the specimens are constantly adjusted to bear and transfer the changing external loads. The transitions between small clusters and large clusters are also continually taking place in varying degrees, correlating to volumetric contraction or dilation. For the loose undrained triaxial specimen presenting quasi-steady state during shearing, the coordination number decreases obviously to nearly 4 and then increases again; the chained grains ratio decreases after a slight increase in the initial loading stage, and then begin to increase again after a period of lower value of around 0.285; the volume ratio of small, submedium and medium clusters all first decreases and then increase gradually, meanwhile volume ratio of large clusters increases sharply to as much as 0.28 and then decreases gradually. The macroscopic critical state of granular materials is a comprehensively external manifestation when the microscopic coordination number and mesoscopic force chains and clusters all evolute to a dynamic equilibrium. At the critical state, the deviator stress, void ratio, coordination number, fabric anisotropy factor, and the volume ratio of small clusters and large clusters all manifest a respectively unique linear relationship with the mean effective stress.

In this work, we numerically investigate the quasi -static shear behavior of ellipsoids under triaxial compression using the level set discrete element method (LS-DEM). Assemblies composed of ellipsoids with various aspect ratios are prepared at the densest states and then sheared to the critical state. Macroscopically, the stress and dilation behaviors are strongly affected by the particle shape, with the spheres having the least shear strength and dilatancy. At the particle scale, more ellipsoidal particles are more resistant to particle rotations and can effectively increase friction mobilizations.We identify the clusters in assemblies via the three-dimensional cluster labeling algorithm and then analyze the structural and mechanical properties of clusters. Based on our analysis, we find that the clusters exhibit the power -law decay in the cluster size distribution and have fractal structures. Upon shearing, the clusters tend to self -organize to gain mechanical stability, indicated by the increasing cluster stress ratio, and mainly support the deviatoric stresses in the assemblies. The mean cluster stress ratio is found to be linearly related to the macroscopic shear strength at the critical state, where more ellipsoidal shapes can gain higher cluster stress ratios, contributing to higher shear strength for the granular assembly. Microscopically, the cluster contributes more significantly to geometrical anisotropy terms while comparably to mechanical ones compared to the non -cluster.

Bacterial secondary metabolites serve as an important source of molecules for drug discovery. They also play an important function in mediating the interactions of microbial producers with their living environment and surrounding organisms. However, little is known about the genetic novelty, distribution, and community-level impacts of soil bacterial biosynthetic potential on a large geographic scale. Here, we constructed the first catalog of 11,149 biosynthetic gene clusters (BGCs) from agricultural soils across China and unearthed hidden biosynthetic potential for new natural product discovery from the not-yet-cultivated soil bacteria. Notably, we revealed soil pH as the strongest environmental driver of BGC biogeography and predicted that soil acidification and global climate change could damage the biosynthetic potential of the soil microbiome. The co-occurrence network of bacterial genomes revealed two BGC-rich species, i.e., Nocardia niigatensis from Actinobacteriota and PSRF01 from Acidobacteriota, as the module hub and connector, respectively, indicating their keystone positions in the soil microbial communities. We also uncovered a dominant role of BGC-inferred biotic interactions over environmental drivers in structuring the soil microbiome. Overall, this study achieved novel insights into the BGC landscape in agricultural soils of China, substantially expanding our understanding of the diversity and novelty of bacterial secondary metabolism and the potential role of secondary metabolites in microbiota assembly. IMPORTANCE Bacterial secondary metabolites not only serve as the foundation for numerous therapeutics (e.g., antibiotics and anticancer drugs), but they also play critical ecological roles in mediating microbial interactions (e.g., competition and communication). However, our knowledge of bacterial secondary metabolism is limited to only a small fraction of cultured strains, thus restricting our comprehensive understanding of their diversity, novelty, and potential ecological roles in soil ecosystems. Here, we used culture-independent metagenomics to explore biosynthetic potentials in agricultural soils of China. Our analyses revealed a high degree of genetic diversity and novelty within biosynthetic gene clusters in agricultural soil environments, offering valuable insights for biochemists seeking to synthesize novel bioactive products. Furthermore, we uncovered the pivotal role of BGC-rich species in microbial communities and the significant relationship between BGC richness and microbial phylogenetic turnover. This information emphasizes the importance of biosynthetic potential in the assembly of microbial communities.

The harsh climatic conditions of deserts may lead to unique adaptations of microbes, which could serve as potential sources of new metabolites to cope with environmental stresses. However, the mechanisms governing the environmental adaptability and antimicrobial activity of desert Streptomyces remain inadequate, especially in extreme temperature differences, drought conditions, and strong radiation. Here, we isolated a Streptomyces strain from rocks in the Kumtagh Desert in Northwest China and tested its antibacterial activity, resistance to UV-C irradiation, and tolerance to hydrogen peroxide (H2O2). The whole-genome sequencing was carried out to study the mechanisms underlying physiological characteristics and ecological adaptation from a genomic perspective. This strain has a growth inhibitory effect against a variety of indicator bacteria, and the highest antibacterial activity recorded was against Bacillus cereus. Moreover, strain D23 can withstand UV-C irradiation up to 100 J/m(2) (D10 = 80 J/m(2)) and tolerate stress up to 70 mM H2O2. The genome prediction of strain D23 revealed the mechanisms associated with its adaptation to extreme environmental and stressful conditions. In total, 33 biosynthetic gene clusters (BGCs) were predicted based on anti-SMASH. Gene annotation found that S. huasconensis D23 contains several genes and proteins associated with the biosynthesis of factors required to cope with environmental stress of temperature, UV radiation, and osmotic pressure. The results of this study provide information about the genome and BGCs of the strain S. huasconensis D23. The experimental results combined with the genome sequencing data show that antimicrobial activity and stress resistance of S. huasconensis D23 was due to the rich and diverse secondary metabolite production capacity and the induction of stress-responsive genes. The environmental adaptability and antimicrobial activity information presented here will be valuable for subsequent work regarding the isolation of bioactive compounds and provide insight into the ecological adaptation mechanism of microbes to extreme desert environments.