Search Results (87)

Background: Pseudorabies virus (PRV), a critical porcine herpesvirus, induces severe diseases in both livestock and wildlife, imposing an incalculable burden and economic losses in livestock production. In this study, we investigated the evolutionary mechanisms and host adaptation strategies of the PRV gB gene through genomic alignment. The gB gene is highly conserved in PRV, and its encoded gB protein exhibits functional interchangeability across different herpesvirus species. Notably, the gB protein elicits the production of both complement-dependent and complement-independent neutralizing antibodies in animals, while also being closely associated with syncytium formation. Methods: Phylogenetic analysis and codon usage pattern analysis were performed in this study. A total of 110 gB gene sequences were analyzed, which were collected from [2011 to 2024] across the following regions: [Fujian, Shanxi, Guangxi, Guangdong, Chongqing, Henan, Shaanxi, Heilongjiang, Sichuan, Jiangsu, Jilin, Huzhou, Shandong, Hubei, Jiangxi, Beijing, Shanghai, Chengdu (China)], [Budapest, Szeged (Hungary)], [Tokyo (Japan)], [London (United Kingdom)], [Athens (Greece)], [Berlin (Germany)], and [New Jersey (United States)]. Results: The gB gene of PRV employs an evolutionary “selective optimization” strategy to maintain a dynamic balance between ensuring functional expression and evading host immune pressure, with this core trend strongly supported by its codon usage bias and mutation characteristics. First, the gene exhibits significant codon usage bias [Effective Number of Codons (ENC) = 27.94 ± 0.1528], driven primarily by natural selection rather than mere mutational pressure. Second, phylogenetic analysis shows that the second codon position of gB has the highest mutation rate (1.0586)—a feature closely linked to its antigenic variation and immune escape capabilities, further reflecting adaptive evolution against host immune pressure. Additionally, ENC-GC3 plot analysis reveals the complex regulatory mechanisms underlying codon bias formation, providing molecular evidence for the “selective optimization” strategy and clarifying PRV’s core evolutionary path to balance functional needs and immune pressure over time. Conclusions: Our study findings deepen our understanding of the evolutionary mechanisms of PRV and provide theoretical support for designing vaccines and assessing the risk of cross-species transmission. Full article

Methane (CH₄), the second-largest global greenhouse gas and a key driver of tropospheric ozone formation, critically influences climate change and air quality. As the world’s largest CH₄ emitter, China must develop targeted mitigation strategies to support its carbon peak and neutrality goals while reducing ozone pollution. Here, we analyzed the spatiotemporal evolution of provincial CH₄ emissions in China from 2000 to 2023 using spatial autocorrelation, hotspot detection, trend analysis, and K-means clustering. Our results revealed a triphasic emission trajectory—rapid growth followed by stabilization and a recent resurgence—with all provinces except Tibet showing increasing trends. The energy sector emerged as the primary contributor, particularly in Inner Mongolia, Shanxi, and Shaanxi, whereas agricultural emissions dominated in pastoral regions, such as Inner Mongolia and Sichuan, and rice-growing areas, such as Hunan and Hubei. Coastal provinces, including Shandong, Jiangsu, and Guangdong, exhibited waste disposal as their predominant CH₄ source. Based on these patterns, we classified the emission zones into four distinct typologies: coal-dominant, waste-dominant, oil-agriculture composite, and multifactorial systems, proposing tailored mitigation frameworks that integrate CH₄ and ozone co-reduction. This study provides a spatially resolved foundation for synergistic climate and air quality governance in China. Full article

Datong in Shanxi Province, known as the “Daylily Capital of China,” still primarily relies on traditional propagation by division for daylily seedling production. Although traditional seedling propagation methods are simple and low-cost, they suffer from limitations such as low propagation efficiency, which restricts large-scale production. The application of tissue culture in seedling production not only enables rapid large-scale propagation but also helps maintain desirable genetic traits through virus elimination. This study aimed to establish an efficient in vitro regeneration system for Hemerocallis citrina ‘Datong Huanghua’ through optimization of key culture stages using scape explants. The results demonstrated that during the stages of callus induction, adventitious bud differentiation, and proliferation culture, the best results were achieved using MS medium supplemented with 3 mg/L zeatin (ZT) and 0.3 mg/L α-naphthylacetic acid (NAA), yielding a callus induction rate of 83.33%, an adventitious bud differentiation rate of 83.40%, and a proliferation coefficient of 4.05. For root induction, MS medium containing 0.25 mg/L indole-3-butyric acid (IBA) and 0.25 mg/L NAA resulted in an average of 4.7 roots per plantlet with a 100% rooting rate. In addition, endogenous hormone analysis showed that lower ABA/GA₃ and ABA/ZR ratios in scape explants promoted callus formation during the induction and differentiation stages. Full article

Hydrocarbon-generation intensity (HGI) is a critical indicator for evaluating shale gas potential in source rocks. This study proposes a practical method to estimate HGI by integrating experimental pyrolysis data, EasyRo-based maturity transformation, kinetic modeling, and geological parameters. Using core samples from the Shanxi Formation in the eastern margin of the Ordos Basin, gold tube pyrolysis experiments were conducted under closed-system conditions to obtain gas yield data. The EasyRo model was applied to transform temperature to maturity, and a kinetic model was constructed to simulate hydrocarbon generation. Total organic carbon (TOC), maturity (Ro), thickness, and true density were used to calculate HGI at different depths. Spatial prediction of HGI was achieved using Kriging interpolation. Results indicate that although carbonaceous mudstones have higher TOC (14.2%) and gas yields (up to 155.84 mg/g TOC), black mudstones exhibit a 24.77% higher HGI due to greater thickness (average 67.2 m). This highlights the dominant role of formation thickness in controlling. Notably, black mudstones in the deeper western subregion exhibit greater gas-generation potential. These findings offer a robust quantitative basis for evaluating deep coal-measure shale gas resources in the Ordos Basin. Full article

The evolution of mining-induced overburden fractures (MIOFs) and their dynamic monitoring are critical for preventing roof water hazards and gas disasters in coal mines. Conventional methods often fail to provide sufficient accuracy under the thin soft–hard interbedded roof strata, necessitating advanced alternatives. Here, we address this challenge by proposing a borehole resistivity method (BRM) based on Back-Propagation Neural Network full-space inversion (BPNN-FSI). Based on the Carboniferous Taiyuan Formation in the North China Coalfield, geoelectric models of MIOFs were established for different mining stages. Finite element simulations generated apparent resistivity responses to train and validate the BPNN-FSI model. At the 9-204 working face of Dianping Coal Mine (Shanxi Province), we compared the proposed BRM based on BPNN-FSI with an empirical formula, numerical simulation, similarity physical simulation, and underground inclined drilling water-loss observations (UIDWLOs). Results demonstrate that the BRM based on BPNN-FSI achieves sub-1% error in height of MIOF (HMIOF) monitoring, with a maximum detected fracture height of 52 m—significantly outperforming conventional methods. This study validates the accuracy and robustness of BRM based on BPNN-FSI for MIOF monitoring in thin soft–hard interbedded roof strata, offering a reliable tool for roof hazard prevention and sustainable mining practices. Full article

As a strategic crop of dry farming in northern China, the photosynthetic characteristics and stress resistance of foxtail millet (Setaria italica L.) are crucial to yield formation. This study aimed to explore the physiological characteristics of various foxtail millet varieties and screen high-efficiency varieties adapted to semi-arid climates. In the agro-pastoral ecotone of northern Shanxi Province, the physiological and ecological parameters, etc. of six cultivars were measured. The results showed that different cultivars had bimodal diurnal photosynthetic curves with distinct peak values and midday depression degrees, reflecting varied responses to high midday temperature and light stress. Dabaigu and Jingu 21 performed superiorly, with mean daily net photosynthetic rates (Pn) of 22.99 and 20.72 µmol·m⁻²·s⁻¹, significantly higher than Jinmiao K1 (12.87 µmol·m⁻²·s⁻¹). Chlorophyll fluorescence analysis showed Dabaigu had higher potential activity (F_v/F₀) of 3.98 than Jinmiao K1 (2.40). Jingu 21 synergistically optimized plant height, stem diameter, and biomass accumulation. Dabaigu and Jingu 21 are elite cultivars for the agro-pastoral ecotone of northern Shanxi Province due to high photosynthetic efficiency, strong photoprotection, and morphological plasticity. Full article

Marine–continental transitional shale is a promising unconventional gas reservoir, playing an increasingly important role in China’s energy portfolio. However, compared to marine shale, research on marine–continental transitional shale’s fractal characteristics of pore structure and complete pore size distribution remains limited. In this work, high-pressure mercury intrusion, N₂ adsorption, and CO₂ adsorption techniques, combined with fractal geometry modeling, were employed to characterize the pore structure of the Shanxi Formation marine–continental transitional shale. The shale exhibits generally high TOC content and abundant clay minerals, indicating strong hydrocarbon-generation potential. The pore size distribution is multi-modal: micropores and mesopores dominate, contributing the majority of the specific surface area and pore volume, whereas macropores display a single-peak distribution. Fractal analysis reveals that micropores have high fractal dimensions and structural regularity, mesopores exhibit dual-fractal characteristics, and macropores show large variations in fractal dimension. Characteristics of pore structure is primarily controlled by TOC content and mineral composition. These findings provide a quantitative basis for evaluating shale reservoir quality, understanding gas storage mechanisms, and optimizing strategies for sustainable of oil and gas development in marine–continental transitional shales. Full article

The Carboniferous–Permian tight sandstone gas reservoirs in the Shenfu area of the Ordos Basin in China are characterized by the widespread development of multiple formations. However, significant differences exist among the tight sandstones of different formations, and their formation mechanisms and key controlling factors remain unclear, hindering the effective selection and development of favorable tight gas intervals in the study area. Through comprehensive analysis of casting thin section (CTS), scanning electron microscopy (SEM), cathodoluminescence (CL), X-ray diffraction (XRD), particle size and sorting, porosity and permeability data from Upper Paleozoic tight sandstone samples, combined with insights into depositional environments, burial history, and chemical reaction processes, this study clarifies the characteristics of tight sandstone reservoirs, reveals the key controlling factors of reservoir quality, confirms the differential evolutionary mechanisms of tight sandstone of different formations, reconstructs the diagenetic sequence, and constructs an evolution model of reservoir minerals and porosity. The research results indicate depositional processes laid the foundation for the original reservoir properties. Sandstones deposited in tidal flat and deltaic environments exhibit superior initial reservoir qualities. Compaction is a critical factor leading to the decline in reservoir quality across all formations. However, rigid particles such as quartz can partially mitigate the pore reduction caused by compaction. Early diagenetic carbonate cementation reduces reservoir quality by occupying primary pores and hindering the generation of secondary porosity induced by acidic fluids, while later-formed carbonate further densifies the sandstone by filling secondary intragranular pores. Clay mineral cements diminish reservoir porosity and permeability by filling intergranular and intragranular pores. The Shanxi and Taiyuan Formations display relatively poorer reservoir quality due to intense illitization. Overall, the reservoir quality of Benxi Formation is the best, followed by Xiashihezi Formation, with the Taiyuan and Shanxi Formations exhibiting comparatively lower qualities. Full article

Shale and coal in the transitional marine–continental facies of the Ordos Basin serve as unconventional natural gas reservoirs, with their pore structures controlling gas adsorption characteristics and occurrence states. To quantitatively characterize the pore structure features and differences between these two reservoirs, this study takes the Shanxi Formation shale and coal in the Daning–Jixian area on the eastern margin of the Ordos Basin as examples. Field-emission scanning electron microscopy (FE-SEM), high-pressure mercury intrusion, low-temperature N₂ adsorption, and low-pressure CO₂ adsorption experiments were employed to analyze and compare the full-scale pore structures of the shale and coal reservoirs. Combined with methane isothermal adsorption experiments, the gas adsorption capacity and its differences in these reservoirs were investigated. The results indicate that the average total organic carbon (TOC) content of shale is 2.66%, with well-developed organic pores, inorganic pores, and microfractures. Organic pores are the most common, typically occurring densely and in clusters. The average TOC content of coal is 74.22%, with organic gas pores being the dominant pore type, significantly larger in diameter than those in transitional marine–continental facies shale and marine shale. In coal, micropores contribute the most to pore volume, while mesopores and macropores contribute less. In shale, mesopores dominate, followed by micropores, with macropores being underdeveloped. Both coal and shale exhibit a high SSA primarily contributed by micropores, with organic matter serving as the material basis for micropore development. The methane adsorption capacity of coal is 8–29 times higher than that of shale. Coal contains abundant organic micropores, providing a large SSA and numerous adsorption sites for methane, facilitating gas adsorption and storage. This study comprehensively reveals the similarities and differences in pore structures between transitional marine–continental facies shale and coal reservoirs in the Ordos Basin at the microscale, providing a scientific basis for the precise evaluation and development of unconventional oil and gas resources. Full article

The mechanism of low- to middle-rank coal seam gas accumulation in the Baode block on the eastern edge of the Ordos Basin is well understood. However, exploration efforts in the Shizuishan area on the western edge started later, and the current understanding of enrichment and accumulation rules is unclear. It is important to systematically study enrichment and accumulation, which guide the precise exploration and development of coal seam gas resources in the western wing of the basin. The coal seam collected from the Shizuishan area of Ningxia was taken as the target. Based on drilling, logging, seismic, and CBM (coalbed methane) test data, geological conditions were studied, and factors and reservoir formation modes of CBM enrichment were summarized. The results are as follows. The principal coal-bearing seams in the study area are coal seams No. 2 and No. 3 of the Shanxi Formation and No. 5 and No. 6 of the Taiyuan Formation, with thicknesses exceeding 10 m in the southwest and generally stable thickness across the region, providing favorable conditions for CBM enrichment. Spatial variations in burial depth show stability in the east and south, but notable fluctuations are observed near fault F1 in the west and north. These burial depth patterns are closely linked to coal rank, which increases with depth. Although the southeastern region exhibits a lower coal rank than the northwest, its variation is minimal, reflecting a more uniform thermal evolution. Lithologically, the roof of coal seam No. 6 is mainly composed of dense sandstone in the central and southern areas, indicating a strong sealing capacity conducive to gas preservation. This study employs a system that fuses multi-source geological data for analysis, integrating multi-dimensional data such as drilling, logging, seismic, and CBM testing data. It systematically reveals the gas control mechanism of “tectonic–sedimentary–fluid” trinity coupling in low-gentle slope structural belts, providing a new research paradigm for coalbed methane exploration in complex structural areas. It creatively proposes a three-type CBM accumulation model that includes the following: ① a steep flank tectonic fault escape type (tectonics-dominated); ② an axial tectonic hydrodynamic sealing type (water–tectonics composite); and ③ a gentle flank lithology–hydrodynamic sealing type (lithology–water synergy). This classification system breaks through the traditional binary framework, systematically explaining the spatiotemporal matching relationships of the accumulated elements in different structural positions and establishing quantitative criteria for target area selection. It systematically reveals the key controlling roles of low-gentle slope structural belts and slope belts in coalbed methane enrichment, innovatively proposing a new gentle slope accumulation model defined as “slope control storage, low-structure gas reservoir”. These integrated results highlight the mutual control of structural, thermal, and lithological factors on CBM enrichment and provide critical guidance for future exploration in the Ningxia Autonomous Region. Full article

Traditional coal quality assessment methods rely exclusively on the laboratory testing of physical samples, which impedes detailed stratigraphic evaluation and limits the integration of intelligent precision mining technologies. To resolve this challenge, this study investigates geophysical logging as an innovative method for coal quality prediction. By integrating scanning electron microscopy (SEM), X-ray analysis, and optical microscopy with interdisciplinary methodologies spanning mathematics, mineralogy, and applied geophysics, this research analyzes the coal quality and mineral composition of the Shanxi Formation coal seams in northern Jiangsu, China. A predictive model linking geophysical logging responses to coal quality parameters was established to delineate relationships between subsurface geophysical data and material properties. The results demonstrate that the Shanxi Formation coals are gas coal (a medium-metamorphic bituminous subclass) characterized by low sulfur content, low ash yield, low fixed carbon, high volatile matter, and high calorific value. Mineralogical analysis identifies calcite, pyrite, and clay minerals as the dominant constituents. Pyrite occurs in diverse microscopic forms, including euhedral and semi-euhedral fine grains, fissure-filling aggregates, irregular blocky structures, framboidal clusters, and disseminated particles. Systematic relationships were observed between logging parameters and coal quality: moisture, ash content, and volatile matter exhibit an initial decrease, followed by an increase with rising apparent resistivity (LLD) and bulk density (DEN). Conversely, fixed carbon and calorific value display an inverse trend, peaking at intermediate LLD/DEN values before declining. Total sulfur increases with density up to a threshold before decreasing, while showing a concave upward relationship with resistivity. Negative correlations exist between moisture, fixed carbon, calorific value lateral resistivity (LLS), natural gamma (GR), short-spaced gamma-gamma (SSGG), and acoustic transit time (AC). In contrast, ash yield, volatile matter, and total sulfur correlate positively with these logging parameters. These trends are governed by coalification processes, lithotype composition, reservoir physical properties, and the types and mass fractions of minerals. Validation through independent two-sample t-tests confirms the feasibility of the neural network model for predicting coal quality parameters from geophysical logging data. The predictive model provides technical and theoretical support for advancing intelligent coal mining practices and optimizing efficiency in coal chemical industries, enabling real-time subsurface characterization to facilitate precision resource extraction. Full article

Lithology identification during drilling plays a vital role in geological and geotechnical exploration, as it facilitates the early detection of formation-related hazards and supports the development of optimized mining strategies. Traditional lithology identification research involves problems such as fuzzy indicator characteristics and unbalanced sample quantities, which affect the accuracy and interpretability of model identification. In order to solve these problems, the Shanxi Guoqiang Coal Mine was taken as the research object, and a combined machine learning model was used to conduct a study on lithology identification during drilling. First, the least absolute shrinkage and selection operator (LASSO) algorithm was used to screen the independent variables and retain the parameters that contributed the most to lithology identification. Then, the synthetic minority oversampling technique (SMOTE) algorithm was used to expand the data samples, increase the amounts of minority sample data, and keep the ratios of various lithology data at 1:1. Then, the Bayesian optimization (BO) algorithm was used to optimize the penalty factor C and kernel function hyperparameter γ—two important parameters of the support vector machine (SVM) model—and the BO-SVM lithology identification model was established. Finally, the data samples were processed, and the results were compared with those of single models and unbalanced sample processing to evaluate their effect. The results showed the following: during the drilling process, the four indicators of drilling speed, mud pressure, slurry flow rate, and torque are strongly correlated with the lithology and can be used for lithology identification and classification research. After the data set was oversampled using the SMOTE algorithm, each model had better robustness and generalization ability; the classification result evaluation indicators were also greatly improved, especially for the random forest model, which had a poor original evaluation effect. The BO algorithm was used to optimize the parameters of the SVM model and establish a combined model that correctly identified 95 groups of data out of 96 groups of test samples with an identification accuracy rate of 99%, which was better than that of the traditional machine learning model. The evaluation results were compared with measured data, which confirmed the reliability of the combined model classification method and its potential to be extended to lithology identification and classification work. Full article

The fractal dimension quantitatively describes the complexity of the shale pore structure and serves as a powerful tool for characterizing the evolution of shale reservoirs. Thermal simulation experiments were conducted on the low-maturity transitional shale from the Shanxi Formation in the Ordos Basin. The initial samples consisted mainly of quartz (39.9%) and clay minerals (49.9%) with moderate-to-good hydrocarbon generation potential. Samples from different thermal maturation stages were analyzed through geochemical, mineralogical, and pore structure experiments to reveal the evolution of mineral compositions and pore structure parameters. The fractal dimensions of the pore structure were calculated using both the FHH and capillary bundle models. Correlation coefficients and principal component analysis (PCA) were employed to explore the factors influencing the fractal dimension and its evolutionary patterns during reservoir development. The results indicate that (1) with increasing thermal maturity, the quartz content gradually increases while the contents of clay minerals, carbonate minerals, pyrite, and feldspar decrease. (2) The evolution of porosity follows five stages: a slow decrease (0.78 < Ro < 1.0%), a rapid increase (1.0% < Ro < 2.0%), a relatively stable phase (2.0% < Ro < 2.7%), a rapid rise (2.7% < Ro < 3.2%), and a slow decline (Ro > 3.2%). The evolution of the pore volume (PV) and specific surface area (SSA) indicates that the proportion of pores in the 5–20 nm and 20–60 nm ranges gradually increases while the proportion of pores smaller than 5 nm decreases. (3) The fractal dimension of shale pores (D₁, average value 2.61) derived from the FHH model is higher than D₂ (average value 2.56). This suggests that the roughness of pore surfaces is greater than the complexity of the internal pore structure at various maturities. The D_M distribution range calculated from the capillary bundle model was broad (between 2.47 and 2.94), with an average value of 2.84, higher than D₁ and D₂. This likely indicates that larger pores have more complex structures. (4) D₁ shows a strong correlation with porosity, PV, and SSA and can be used to reflect pore development. D₂ correlates well with geochemical parameters (TOC, HI, etc.) and minerals prone to diagenetic alteration (carbonates, feldspar, and pyrite), making it useful for characterizing the changes in components consumed during pore structure evolution. (5) Based on the thermal maturation process of organic matter, mineral composition, diagenesis, and pore structure evolution, an evolutionary model of the fractal dimension for transitional shale was established. Full article

The eighth member of the Permian Shihezi Formation is one of the main tight sandstone gas layers in the Longdong Area of Ordos Basin, and the source rocks are dark mudstones and shales located in the Shanxi Formation and Taiyuan Formation of the Permian. The tight muddy sandstone at the top provides shielding conditions and constitutes traps. The lithology is mainly lithic quartz sandstone, followed by lithic sandstone. The reservoir space is mainly dissolved pores, inter crystalline pores, intergranular pores and so on. Clay minerals are the main interstitial materials, and chlorite has the highest content in it, a product of alkaline, moderate- to high-temperature, reducing conditions, effectively inhibited quartz cementation and enhanced secondary porosity development during mesodiagenesis. The average porosity of the reservoir is about 4.01%, and the average permeability is about 0.5 × 10⁻³ μm³, which is a typical low porosity and ultra-low permeability tight reservoir. The thickness of the sandstone reservoir in the study area is from 5 m to more than 25 m, mainly in the NE direction. The sand bodies are distributed in lenses on the plane. Full article

Soluble sugars are essential components in the physiology and metabolism of soybeans (Glycine max), playing a critical role in regulating key processes such as development, germination, and flavor formation. The soluble sugar content in soybean seeds is primarily composed of stachyose, raffinose, sucrose, and glucose. This study aims to elucidate the genetic mechanisms underlying variation in the composition of soluble sugars in soybean seeds. A 128 recombinant inbred line (RIL) population was used, and concentrations of these four sugars were quantified across three years (2015, 2016, and 2017 in Shanxi). The analysis revealed that Jin Da 53 exhibited significantly higher sucrose and total sugar contents compared to Ping Nan, while stachyose levels were notably elevated in Ping Nan. Except for glucose content in 2017 and 2019, the RIL population’s traits all exhibited a normal distribution, making it suitable for QTL analyses. A total of twenty QTLs were identified for the four sugar components: five for glucose, four for raffinose, four for sucrose, three for stachyose, and four for total sugar, all with LOD > 2.5. Notably, three QTLs located on chromosome 10 (S10_37101443-S10_38298307, S10_38681635-S10_39134900, and S10_36697685-S10_36697916) were found to be associated with stachyose content, identifying one candidate gene, Glyma.10g154400, which was implicated in carbohydrate metabolic processes; a QTL located on chromosome 11 (96.881–105.5 cM) was identified in 2019 as a significant locus influencing sucrose content, identifying another candidate gene, Glyma.11g136200, which was linked to sugar/inositol transporter activity. Expression analysis of these candidate genes demonstrated the Glyma.10g154400 gene exhibited higher expression levels in varieties with lower stachyose content, whereas Glyma.11g136200 showed increased expression in lines with elevated sucrose levels. This study provides an important genetic basis for the breeding of soybean varieties with increased sugar content. Full article