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Ion composition critically determines the basic kinetic characteristics of plasma and affects energy transmission of the magnetosphere. However, it exhibits significant variations with altitude, latitude, local time, longitude, and also with geomagnetic and solar activity. Equatorial noise (EN) emissions, a frequently observed electromagnetic wave in the inner magnetosphere, propagate across magnetic field lines, and thus can reach magnetosphere‐ionosphere‐coupling (MIC) region near the magnetic equator, where their evolution depends on local ion composition. Here we utilize polarization reversal of EN emissions observed near the perigees of Van Allen Probes to in turn derive the compositions of helium and oxygen ions and provide comprehensive ion composition distributions by statistical analysis of EN emissions. Comparisons with the International Reference Ionosphere model and in situ plasma measurements validate the reliability of the estimated results. These findings advance MIC plasma models, and our method provides an indirect tool for plasma diagnostics on other planets.

In this study, we statistically analyze the wave properties of plasmaspheric hiss using data from the Van Allen Probes. The magnetic power spectral densities of hiss waves exhibit dependence on magnetic local time, geomagnetic activity, and the L$L$ ‐shell. Based on variations in wave properties—including normal angle, electromagnetic planarity, and the net Poynting flux direction Rs$\\left({R}_{s}\\right)$ —with L$L$ ‐shell and normalized frequency (the ratio of wave frequency to electron cyclotron frequency), hiss waves are categorized into four distinct regions. Waves with frequencies above 0.1fce$0.1{f}_{ce}$exhibit characteristics of locally generated plasmaspheric hiss. Furthermore, the statistical distribution of suprathermal electron fluxes shows that the upper energy of injected energetic electrons matches well with the minimum resonant energy corresponding to the lower frequency of locally generated hiss. This study identifies locally generated hiss waves, which are well supported by the electron distributions. Plain Language Summary Whistler‐mode plasmaspheric hiss waves occur in near‐Earth space and are named for their distinct hiss‐like sound. These waves primarily exist in dense plasma regions and play a critical role in electron loss of Earth's radiation belts, particularly by scattering high‐energy electrons. Plasmaspheric hiss waves are crucial for understanding Earth's radiation belt dynamics, though their potential generation mechanisms remain under active investigation. In this study, we used data from the Van Allen Probes to analyze how wave properties depend on the L$L$shell and normalized frequency, identifying regions of locally generated plasmaspheric hiss. We also incorporated statistical data on electron distributions to confirm that hiss waves above approximately 0.1 times the electron cyclotron frequency at large L$L$shells are locally generated. This study validates the mechanism of local generation and provides insights to support future research on the origins of plasmaspheric hiss. Key Points The locally generated hiss waves are identified based on the wave properties The suprathermal electron features in the plasmasphere are statistically analyzed The distributions of suprathermal electrons and corresponding growth rates well support the local generation of identified hiss

Cereals are the main food for mankind. The grain shape extraction and filled/unfilled grain recognition are meaningful for crop breeding and genetic analysis. The conventional measuring method is mainly manual, which is inefficient, labor-intensive and subjective. Therefore, a novel method was proposed to extract the phenotypic traits of cereal grains based on point clouds. First, a structured light scanner was used to obtain the grains point cloud data. Then, the single grain segmentation was accomplished by image preprocessing, plane fitting, region growth clustering. The length, width, thickness, surface area and volume was calculated by the specified analysis algorithms for grain point cloud. To demonstrate this method, experimental materials included rice, wheat and corn were tested. Compared with manual measurement results, the average measurement error of grain length, width and thickness was 2.07%, 0.97%, 1.13%, and the average measurement efficiency was about 9.6 s per grain. In addition, the grain identification model was conducted with 25 grain phenotypic traits, using 6 machine learning methods. The results showed that the best accuracy for filled/unfilled grain classification was 90.184%.The best accuracy for indica and japonica identification was 99.950%, while for different varieties identification was only 47.252%. Therefore, this method was proved to be an efficient and effective way for crop research.

Research on water-soluble vitamins has evolved from discovery to the development of renewable biosynthesis that can replace traditional extraction and chemical synthesis by more sustainable production methods.Microbial cell factories, empowered by synthetic biotechnology such as pathway optimization, gene editing, and strain selection, can achieve more sustainable production of water-soluble vitamins and reduce environmental impact.Biosensors for water-soluble vitamins enable high-throughput screening by more efficient and reliable automated platforms, thereby accelerating the discovery of production strains and the optimization of bio-intelligent production conditions.Bio-intelligent platforms integrating artificial intelligence (AI) and biological systems hold promise in addressing challenges in water-soluble vitamin production to enable accurate prediction and intelligent control of production processes. Given the crucial role of water-soluble vitamins in the human body and the rising demand for natural sources, their biosynthesis has gained the attention of researchers. This review offers a comprehensive look at recent progress in water-soluble vitamin biosynthesis, emphasizing synthetic biotechnology for green biomanufacturing. Specifically, it encompasses the optimization of biological components, pathways, and systems, as well as energy metabolism regulation, stress-tolerance enhancement, high-throughput screening, and the upscaling of production processes. It also envisages intelligent biomanufacturing platforms, highlighting the role of systems biology and artificial intelligence (AI), and proposes future research directions, such as integrating AI-driven metabolic models, enzyme engineering, and cell-free systems, to address limitations in the efficiency, toxicity, and scalability of water-soluble vitamin production. Given the crucial role of water-soluble vitamins in the human body and the rising demand for natural sources, their biosynthesis has gained the attention of researchers. This review offers a comprehensive look at recent progress in water-soluble vitamin biosynthesis, emphasizing synthetic biotechnology for green biomanufacturing. Specifically, it encompasses the optimization of biological components, pathways, and systems, as well as energy metabolism regulation, stress-tolerance enhancement, high-throughput screening, and the upscaling of production processes. It also envisages intelligent biomanufacturing platforms, highlighting the role of systems biology and artificial intelligence (AI), and proposes future research directions, such as integrating AI-driven metabolic models, enzyme engineering, and cell-free systems, to address limitations in the efficiency, toxicity, and scalability of water-soluble vitamin production.

Plasmaspheric hiss waves play a key role in scattering energetic electrons and are often modeled in the inner magnetosphere using empirical hiss power maps parameterized by L shell. In this study, we compare the dependence of hiss power on both L shell (2 ≤ L ≤ 6) and the ratio of electron plasma frequency to electron gyrofrequency (ωpe/Ωce) using observations from the Van Allen Probes. The statistical comparison spans a wide range of magnetic local times, frequency bands, and substorm activity levels. Hiss power shows a stronger correlation with ωpe/Ωce than with L shell, especially at low frequencies and during periods of enhanced substorm activity. These results indicate that ωpe/Ωce is a more physically meaningful parameter for describing plasmaspheric hiss and should be considered in radiation belt modeling. Plain Language Summary Plasmaspheric hiss waves are a type of electromagnetic wave in the inner magnetosphere, named for the hiss sound when converted to audio. These waves are mainly found in the plasmasphere and play a critical role in regulating the radiation belts. By scattering high‐energy electrons through wave‐particle interactions, plasmaspheric hiss contributes to the loss of electrons to the atmosphere and the formation of the slot region, a low‐radiation zone between the inner and outer belts. In this study, we use observations from NASA's Van Allen Probes to investigate how hiss wave intensity varies with both L shell and local plasma conditions. In particular, we examine the ratio of electron plasma frequency to electron gyrofrequency, which reflects electron density and magnetic field strength. Our analysis shows that hiss wave power is more strongly related to the frequency ratio than to the L shell, especially at lower frequencies and during enhanced substorm activity. These results hold significant implications, challenging the adequacy of current magnetospheric models that primarily consider radial distance as their fundamental organizing parameter. Key Points The first statistical comparison of hiss wave power dependence on L shell and ωpe/Ωce is performed Hiss wave power correlates more strongly with ωpe/Ωce than with L shell or ne The ωpe/Ωce dependence is strongest at low frequencies and during enhanced substorm activity

In a fusion reactor, an in-vessel loss of coolant accident (LOCA) involving the helium-cooled blanket will lead to the resuspension and migration of tritiated and micron-sized tungsten dust deposited at the bottom of the vacuum vessel under high-speed helium jets, significantly increasing the radiological release hazard. Drag force dominates particle transport dynamics, yet conventional computational fluid dynamics (CFD) fails to accurately characterize particle-fluid interactions in high-speed and rarefied flow fields. This study proposes a hybrid framework combining CFD with the Maxwell slip boundary and direct simulation Monte Carlo to simulate micron-particle drag force during in-vessel LOCA. The Cunningham drag correction formula accounting for wide-range Knudsen number (Kn) rarefied helium flow (0.01 < Kn < 2 × 104) was established using nonlinear least-squares fitting. Furthermore, by incorporating compressibility effects induced by high-Mach flow, a symbolic regression-based drag model was established as a function of Mach number (Ma) (0.033 < Ma < 1.31) and particle Reynolds number (1 × 10−4 < Rep < 50). This model provides critical engineering guidance for predicting radioactive dust migration in fusion reactors and the proposed framework could be extendable to loss of vacuum accidents and other engineering applications involving particle drag in high-Mach rarefied gas flows.

δ-Tocotrienol, an isomer of vitamin E with anti-inflammatory, neuroprotective and anti-coronary arteriosclerosis properties, is widely used in health care, medicine and other fields. Microbial synthesis of δ-tocotrienol offers significant advantages over plant extraction and chemical synthesis methods, including increased efficiency, cost-effectiveness and environmental sustainability. However, limited precursor availability and low catalytic efficiency of key enzymes remain major bottlenecks in the biosynthesis of δ-tocotrienol. In this study, we assembled the complete δ-tocotrienol biosynthetic pathway in Yarrowia lipolytica and enhanced the precursor supply, resulting in a titre of 102.8 mg/L. The catalytic efficiency of the rate-limiting steps in the pathway was then enhanced through various strategies, including fusion expression of key enzymes homogentisate phytyltransferaseand and tocopherol cyclase, semi-rational design of SyHPT and multi-copy integration of pathway genes. The final a δ-tocotrienol titre in a 5 L bioreactor was 466.8 mg/L following fed-batchfermentation. This study represents the first successful de novo biosynthesis of δ-tocotrienol in Y. lipolytica, providing valuable insights into the synthesis of vitamin E-related compounds. [Display omitted]

Gluconobacter oxydans is an important Gram-negative industrial microorganism that produces vitamin C and other products due to its efficient membrane-bound dehydrogenase system. Its incomplete oxidation system has many crucial industrial applications. However, it also leads to slow growth and low biomass, requiring further metabolic modification for balancing the cell growth and incomplete oxidation process. As a non-model strain, G. oxydans lacks efficient genome editing tools and cannot perform rapid multi-gene editing and complex metabolic network regulation. In the last 15 years, our laboratory attempted to deploy multiple CRISPR/Cas systems in different G. oxydans strains and found none of them as functional. In this study, Cpf1-based or dCpf1-based CRISPRi was constructed to explore the targeted binding ability of Cpf1, while Cpf1–FokI was deployed to study its nuclease activity. A study on Cpf1 found that the CRISPR/Cpf1 system could locate the target genes in G. oxydans but lacked the nuclease cleavage activity. Therefore, the CRISPR/Cpf1–FokI system based on FokI nuclease was constructed. Single-gene knockout with efficiency up to 100% and double-gene iterative editing were achieved in G. oxydans. Using this system, AcrVA6, the anti-CRISPR protein of G. oxydans was discovered for the first time, and efficient genome editing was realized.

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.

L‐Sorbosone dehydrogenase (SNDH) is a key enzyme involved in the biosynthesis of 2‐keto‐L‐gulonic acid , which is a direct precursor for the industrial scale production of vitamin C. Elucidating the structure and the catalytic mechanism is essential for improving SNDH performance. By solving the crystal structures of SNDH from Gluconobacter oxydans WSH‐004, a reversible disulfide bond between Cys295 and the catalytic Cys296 residues is discovered. It allowed SNDH to switch between oxidation and reduction states, resulting in opening or closing the substrate pocket. Moreover, the Cys296 is found to affect the NADP + binding pose with SNDH. Combining the in vitro biochemical and site‐directed mutagenesis studies, the redox‐based dynamic regulation and the catalytic mechanisms of SNDH are proposed. Moreover, the mutants with enhanced activity are obtained by extending substrate channels. This study not only elucidates the physiological control mechanism of the dehydrogenase, but also provides a theoretical basis for engineering similar enzymes.