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Net nitrogen mineralization (Nmin) and nitrification regulate soil N availability and loss after severe wildfires in boreal forests experiencing slow vegetation recovery. Yet, how microorganisms respond to postfire phosphorus (P) enrichment to alter soil N transformations remains unclear in N-limited boreal forests. Here, we investigated postfire N-P interactions using an intensive regional-scale sampling of 17 boreal forests in the Greater Khingan Mountains (Inner Mongolia-China), a laboratory P-addition incubation, and a continental-scale meta-analysis. We found that postfire soils had an increased risk of N loss by accelerated Nmin and nitrification along with low plant N demand, especially during the early vegetation recovery period. The postfire N/P imbalance created by P enrichment acts as a "N retention" strategy by inhibiting Nmin but not nitrification in boreal forests. This strategy is attributed to enhanced microbial N-use efficiency and N immobilization. Importantly, our meta-analysis found that there was a greater risk of N loss in boreal forest soils after fires than in other climatic zones, which was consistent with our results from the 17 soils in the Greater Khingan Mountains. These findings demonstrate that postfire N-P interactions play an essential role in mitigating N limitation and maintaining nutrient balance in boreal forests.

Metagenomic binning is an essential technique for genome-resolved characterization of uncultured microorganisms in various ecosystems but hampered by the low efficiency of binning tools in adequately recovering metagenome-assembled genomes (MAGs). Here, we introduce BASALT (Binning Across a Series of Assemblies Toolkit) for binning and refinement of short- and long-read sequencing data. BASALT employs multiple binners with multiple thresholds to produce initial bins, then utilizes neural networks to identify core sequences to remove redundant bins and refine non-redundant bins. Using the same assemblies generated from Critical Assessment of Metagenome Interpretation (CAMI) datasets, BASALT produces up to twice as many MAGs as VAMB, DASTool, or metaWRAP. Processing assemblies from a lake sediment dataset, BASALT produces ~30% more MAGs than metaWRAP, including 21 unique class-level prokaryotic lineages. Functional annotations reveal that BASALT can retrieve 47.6% more non-redundant opening-reading frames than metaWRAP. These results highlight the robust handling of metagenomic sequencing data of BASALT.

Increasing evidence shows the oncogenic function of FAM83D in human cancer, but how FAM83D exerts its oncogenic function remains largely unclear. Here, we investigated the importance of FAM83D/FBXW7 interaction in breast cancer (BC). We systematically mapped the FBXW7-binding sites on FAM83D through a comprehensive mutational analysis together with co-immunoprecipitation assay. Mutations at the FBXW7-binding sites on FAM83D led to that FAM83D lost its capability to promote the ubiquitination and proteasomal degradation of FBXW7; cell proliferation, migration, and invasion in vitro; and tumor growth and metastasis in vivo, indicating that the FBXW7-binding sites on FAM83D are essential for its oncogenic functions. A meta-evaluation of FAM83D revealed that the prognostic impact of FAM83D was independent on molecular subtypes. The higher expression of FAM83D has poorer prognosis. Moreover, high expression of FAM83D confers resistance to chemotherapy in BCs, which is experimentally validated in vitro. We conclude that identification of FBXW7-binding sites on FAM83D not only reveals the importance for FAM83D oncogenic function, but also provides valuable insights for drug target.

Abstract Cytosine base editing is a powerful tool for making precise single nucleotide changes in cells and model organisms like zebrafish, which are valuable for studying human diseases. However, current base editors struggle to edit cytosines in certain DNA contexts, particularly those with GC and CC pairs, limiting their use in modelling disease-related mutations. Here we show the development of zevoCDA1, an optimized cytosine base editor for zebrafish that improves editing efficiency across various DNA contexts and reduces restrictions imposed by the protospacer adjacent motif. We also create zevoCDA1-198, a more precise editor with a narrower editing window of five nucleotides, minimizing off-target effects. Using these advanced tools, we successfully generate zebrafish models of diseases that were previously challenging to create due to sequence limitations. This work enhances the ability to introduce human pathogenic mutations in zebrafish, broadening the scope for genomic research with improved precision and efficiency.

To investigate the distribution of flavor components in Luzhou-flavor base baijiu from different aged cellars, the aroma components in 18 samples of Luzhou-flavor base baijiu from three cellars of different ages were identified and quantified by direct injection (DI), liquid-liquid extraction (LLE) or vortex-assisted surfactant-enhanced emulsification liquid-liquid microextraction (VSLLME) combined with gas chromatography (GC) and gas chromatography-mass spectrometry (GC-MS). The differences in flavor among different base baijiu samples was analyzed by chemometrics methods such as principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), and Spearman’s correlation coefficient. The results suggested that 151, 154 and 159 volatile compounds were identified in base baijiu from freshly prepared cellar and those aged over 30 and 100 years. In total, 148 aroma compounds were common to the three base baijiu, accounting for 93.1% of the total number of identified compounds. The quantitative analysis of 61 major aroma compounds showed that the concentrations of ethyl caproate, ethyl butyrate, hexanoic acid, butyric acid and acetic acid in base baijiu from each cellar exceeded 100 mg/L. The concentration of ethyl caproate was the highest, ranging from 1 156.4 to 2 142.2 mg/L. Chemometric results indicated that the flavor similarity of base baijiu between the new and over-30-year-old cellars was higher when compared with the cellar aged over 100 years. This findings further strengthen the baijiu industry’s conventional knowledge of the influence of cellar age on the flavor of Luzhou-flavor baijiu.

Abstract Ligusticum sinense cv. Chuanxiong (L. Chuanxiong), one of the widely used traditional Chinese medicines (TCM), is currently facing the problem of excessive cadmium (Cd) content. This problem has significantly affected the quality and safety of L. Chuanxiong and become a vital factor restricting its clinical application and international trade development. Currently, to solve the problem of excessive Cd, it is essential to research the response mechanisms of L. Chuanxiong to Cd stress. However, there are few reports on its physiological and biochemical responses under Cd stress. In this study, we conducted the hydroponic experiment under 25 μM Cd stress, based on the Cd content of the genuine producing areas soil. The results showed that 25 μM Cd stress not only had no significant inhibitory effect on the growth of L. Chuanxiong seedlings but also significantly increased the chlorophyll a content (11.79%) and root activity (51.82%) compared with that of the control, which might be a hormesis effect. Further results showed that the absorption and assimilation of NH4 + increased in seedlings under 25 μM Cd stress, which was associated with high photosynthetic pigments. Here, we initially hypothesized and confirmed that Cd exceedance in the root system of L. Chuanxiong was due to the thickening of the root cell wall, changes in the content of the cell wall components, and chelation of Cd by GSH. There was an increase in cell wall thickness (57.64 %) and a significant increase in cellulose (25.48%) content of roots under 25 μM Cd stress. In addition, L. Chuanxiong reduced oxidative stress caused by 25 μM Cd stress mainly through the GSH/GSSG cycle. Among them, GSH-Px (48.26%) and GR (42.64%) activities were significantly increased, thereby maintaining a high GSH/GSSG ratio. This study preliminarily reveals the response of L. Chuanxiong to Cd stress and the mechanism of Cd enrichment. It provides a theoretical basis for solving the problem of Cd excessive in L. Chuanxiong. Graphical Abstract Physiological and biochemical mechanisms of L. Chuanxiong seedlings under Cd stress.

Abstract Ground settlement prediction for highway subgrades is crucial in related engineering projects. When predicting the ground settlement, sparse sample data are often encountered in practice, which greatly affects the prediction accuracy. However, this has been seldom explored in previous studies. To resolve it, this paper proposes a regression Kriging (RK)—based method for ground settlement prediction with sparse data. Under the framework of RK, the stationarity of sample residual and trend structure are key factors for prediction accuracy. It is found that the use of Box–Cox transformation, which can help to achieve stationarity of sample residual, leads to significant increase of the prediction accuracy with sparse data. Specifically, the various evaluation metrics (i.e., root mean square error (RMSE), mean absolute error (MAE), mean arctangent absolute percent error (MAAPE) and scatter index (SCI)) are significantly decreased when the Box–Cox transformation is incorporated. In addition, the first-order polynomial trend structure is found to be more appropriate than those with higher orders for predicting settlements resulting from primary consolidation. Moreover, comparative study is conducted among the proposed RK method, classical prediction methods and back propagation neural network (BPNN). It is found that the evaluation metrics obtained by the RK method are significantly smaller than those obtained by the other methods, indicating its highest accuracy. By contrast, BPNN has the worst performance among the various methods, because the sparse data are inadequate to establish a satisfactory BPNN model.

Abstract Hereditary hemorrhagic telangiectasia (HHT) is an autosomal dominant disorder characterized by epistaxis, gastrointestinal bleeding, iron deficiency anemia, and arteriovenous malformations (AVMs) affecting the lungs, liver, and brain. Owing to its rarity and diagnostic challenges, early identification is often elusive. Underdiagnosis and prolonged diagnostic delays are prevalent. Here, we present the case of a 63-year-old male who presented with chest pain and was diagnosed with an ST-elevation myocardial infarction (STEMI). Subsequently, he underwent placement of a drug-eluting stent in the right coronary artery (RCA). However, recurrent postoperative epistaxis resulted in severe anemia, prompting further investigation leading to the diagnosis of hereditary hemorrhagic telangiectasia through comprehensive medical history and genetic testing. Future studies are warranted to evaluate reperfusion strategies in HHT patients presenting with myocardial infarction.

Abstract Silicon steel sheets (SSSs), serving as the principal constituent of the magnetic circuit in electric machines, necessitates precise modelling and accurate computation using magnetic circuit theory as a prerequisite for analysing the characteristics of electric machines. Nevertheless, the conventional magnetic circuit theory, limited to a single reluctance component, fails to address the phase relationship between magnetomotive force and magnetic flux, and inadequately represents the magnetic flux distribution observed under high‐frequency conditions. Consequently, the existing magnetic circuit model for SSSs remains imperfect in its current state. Fortuitously, the advent of magductance has effectively addressed these challenges. Building upon magductance, this study deduces the fundamental laws and theorem within the vector magnetic circuit theory. Subsequently, a distributed parameter vector magnetic circuit model for the SSSs is constructed, accompanied by the derivation of expressions pertaining to its reluctance and magductance. The authors propose the transfer function composed of reluctance and magductance parameters, successfully resolving the phase between the magnetic circuit vectors, the magnetic flux distribution, and the magnetic circuit loss under different frequencies for SSSs. Finally, experimental findings affirm the efficacy and validity of the distributed parameter vector magnetic circuit model for SSSs. The proposal of vector magnetic circuit theory opens a whole new door for the analysis, computation, and optimisation of electric machines.

Introduction: The diagnosis of Fabry disease (FD) with genetic variants of unknown significance (VUSs) is relatively difficult. We explored patients with novel VUS variants and concomitant immunoglobulin A nephropathy (IgAN) to improve the understanding of VUS. Methods: The study retrospectively investigated patients with genetically confirmed FD. Probands with VUS were selected from the database of FD patients who underwent genetic analysis. Demographic, clinicopathological, and laboratory data from probands and family members were collected and analyzed. Results: Fourteen probands and their family members were included in the study. The probands were divided into group 1 (patients with VUS, n = 5) and group 2 (patients with pathologic/likely pathologic variants, n = 9). The group 1 included 2 missense mutations and 1 deletion mutation, while the group 2 included 6 missense mutations and 2 deletion mutations. There were no significant differences in gender, age, serum creatinine, eGFR, and proteinuria between the two groups. IgA deposition with myeloid bodies was found in all VUS patients. The cardiac involvement in group 2 was more severe than that in group 1. Seven families performed the pedigree analysis, and after the comprehensive evaluation, two GLA variants (c.479C>A, p.Ala160Asp; c.1032-1058 del, p.Ser345_Met353del) were upgraded from VUS to the likely pathogenic. Conclusion: The clinical manifestations of FD are heterogeneous. FD often coexists with nephrotic disorders, such as IgAN and MCD. Comprehensive evaluation, especially tissue-specific biopsy, is necessary for patients with GLA-VUSs. Two GLA variants (c.479C>A, p.Ala160Asp; c.1032-1058 del, p.Ser345_Met353del) were upgraded from VUS to the likely pathogenic after the comprehensive evaluation.

Abstract Ammonia‐oxidizing archaea (AOA) play crucial roles in marine carbon and nitrogen cycles by fixing inorganic carbon and performing the initial step of nitrification. Evaluation of carbon and nitrogen metabolism popularly relies on functional genes such as amoA and accA. Increasing studies suggest that quorum sensing (QS) mainly studied in biofilms for bacteria may serve as a universal communication and regulatory mechanism among prokaryotes; however, this has yet to be demonstrated in marine planktonic archaea. To bridge this knowledge gap, we employed a combination of metabolic activity markers (amoA, accA, and grs) to elucidate the regulation of AOA‐mediated nitrogen, carbon processes, and their interactions with the surrounding heterotrophic population. Through co‐transcription investigations linking metabolic markers to potential key QS genes, we discovered that QS molecules could regulate AOA's carbon, nitrogen, and lipid metabolisms under different conditions. Interestingly, specific AOA ecotypes showed a preference for employing distinct QS systems and a distinct QS circuit involving a typical population. Overall, our data demonstrate that QS orchestrates nitrogen and carbon metabolism, including the exchange of organic metabolites between AOA and surrounding heterotrophic bacteria, which has been previously overlooked in marine AOA research.

Abstract Background Traditional Chinese medicine (TCM) has been hailed as a rich source of medicine, but many types of herbs and their functions still need to be rapidly discovered and elucidated. HerboChip, a target-based drug screening platform, is an array of different fractions deriving from herbal extracts. This study was designed to identify effective components from TCM that interact with vascular endothelial growth factor (VEGF) as a target using HerboChip. Methods Selected TCMs that are traditionally used as remedies for cancer prevention and wound healing were determined and extracted with 50% ethanol. Biotinylated-VEGF was hybridized with over 500 chips coated with different HPLC-separated fractions from TCM extracts and straptavidin-Cy5 was applied to identify plant extracts containing VEGF-binding fractions. Cytotoxicity of selected herbal extracts and their activities on VEGF-mediated angiogenic functions were evaluated. Results Over 500 chips were screened within a week, and ten positive hits were identified. The interaction of the identified herbal extracts with VEGF was confirmed in cultured endothelial cells. The identified herbs promoted or inhibited VEGF-mediated cell proliferation, migration and tube formation. Results from western blotting analysis demonstrated the identified herbal extracts significantly affected VEGF-triggered phosphorylations of eNOS, Akt and Erk. Five TCMs demonstrated potentiating activities on the VEGF response and five TCMs revealed suppressive activities. Conclusions The current results demonstrated the applicability of the HerboChip platform and systematically elucidated the activity of selected TCMs on angiogenesis and its related signal transduction mechanisms.

In the black soil region of Northeast China, the issue of gully erosion persists as a significant threat, resulting in extensive damage to farmland, severe degradation of the black soil, and decreased productivity. It is therefore of utmost importance to accurately identify areas that are susceptible to gully erosion to effectively prevent and control its negative impact. This study tried to utilize geographical detectors (geodetectors) as a means to identify the factors that contribute to the distribution of gullies and assess the risk of gully erosion (GER) in five catchments within the region, with areas ranging from approximately 80 km2–200 km2. By employing the geodetectors method, fourteen geo-environmental factors were analyzed, including topographic attributes (such as aspect, catchment area, convergence index, elevation, plan curvature, profile curvature, slope length, slope, stream power index, and topographic wetness index), channel network distance, vegetation index (NDVI and EVI), as well as land use/land cover (LULC). The modeling of GER was conducted using the random forest algorithm (RFA). Out of the fourteen examined geo-environmental factors, only a subset, comprising less than or equal to 50%, demonstrated a significant (p

Abstract Background Hemoptysis resulting from rupture of the pulmonary artery pseudoaneurysm (PAP) is massive and fatal, while factor contributing to the rupture of pseudoaneurysm remains elusive. This study aimed to elucidate the clinical and radiological features of PAP and identify the risk factors associated with rupture. Methods Patients who developed hemoptysis with PAP were collected from January 2019 to December 2022 retrospectively. Clinical data of the demographic characteristics, radiological findings, treatment strategies, and prognosis were collected. A comparative analysis was performed on the characteristics in the ruptured and non-ruptured cases. Results A total of 58 PAPs were identified in the 50 patients. The most common causes were infection (86%) and cancer (8%). The PAPs were located predominantly in the upper lobes of both lungs, and 57 (99.3%) were distributed in the segmental or subsegmental pulmonary arteries. The median diameter was 6.1(4.3–8.7) mm. A total of 29 PAPs were identified adjacent to pulmonary cavitations, with the median diameter of the cavity being 18.9 (12.4–34.8) mm. Rupture of pseudoaneurysm occurred in 21 cases (42%). Compared to unruptured group, the ruptured group had a significantly higher proportion of massive hemoptysis (57.1% vs. 6.9%, p

Abstract In recent years, lightwave has stood out as an ultrafast, non-contact control knob for developing compact superconducting circuitry. However, the modulation efficiency is limited by the low photoresponse of superconductors. Plasmons, with the advantages of strong light-matter interaction, present a promising route to overcome the limitations. Here we achieve effective modulation of superconductivity in thin-film NbSe2 via near-field coupling to plasmons in gold nanoparticles. Upon resonant plasmon excitation, the superconductivity of NbSe2 is substantially suppressed. The modulation factor exceeds 40% at a photon flux of 9.36 × 1013 s−1mm−2, and the effect is significantly diminished for thicker NbSe2 samples. Our observations can be theoretically interpreted by invoking the non-equilibrium electron distribution in NbSe2 driven by the plasmon-associated evanescent field. Finally, a reversible plasmon-driven superconducting switch is realized in this system. These findings highlight plasmonic tailoring of quantum states as an innovative strategy for superconducting electronics.

Abstract Advancements in CRISPR technology, particularly the development of base editors, revolutionize genetic variant research. When combined with model organisms like zebrafish, base editors significantly accelerate and refine in vivo analysis of genetic variations. However, base editors are restricted by protospacer adjacent motif (PAM) sequences and specific editing windows, hindering their applicability to a broad spectrum of genetic variants. Additionally, base editors can introduce unintended mutations and often exhibit reduced efficiency in living organisms compared to cultured cell lines. Here, we engineer a suite of adenine base editors (ABEs) called ABE-Ultramax (Umax), demonstrating high editing efficiency and low rates of insertions and deletions (indels) in zebrafish. The ABE-Umax suite of editors includes ABEs with shifted, narrowed, or broadened editing windows, reduced bystander mutation frequency, and highly flexible PAM sequence requirements. These advancements have the potential to address previous challenges in disease modeling and advance gene therapy applications.

Abstract With an increasing prevalence of thyroid nodules globally, this study investigates the potential correlation between the use of Bluetooth headsets and the incidence of thyroid nodules, considering the cumulative effects of non-ionizing radiation (NIR) emitted by these devices. In this study, we analyzed 600 valid questionnaires from the WenJuanXing platform using Propensity Score Matching (PSM) and the XGBOOST model, supplemented by SHAP analysis, to assess the risk of thyroid nodules. PSM was utilized to balance baseline characteristic differences, thereby reducing bias. The XGBOOST model was then employed to predict risk factors, with model efficacy measured by the area under the Receiver Operating Characteristic (ROC) curve (AUC). SHAP analysis helped quantify and explain the impact of each feature on the prediction outcomes, identifying key risk factors. Initially, 600 valid questionnaires from the WenJuanXing platform underwent PSM processing, resulting in a matched dataset of 96 cases for modeling analysis. The AUC value of the XGBOOST model reached 0.95, demonstrating high accuracy in differentiating thyroid nodule risks. SHAP analysis revealed age and daily Bluetooth headset usage duration as the two most significant factors affecting thyroid nodule risk. Specifically, longer daily usage durations of Bluetooth headsets were strongly linked to an increased risk of developing thyroid nodules, as indicated by the SHAP analysis outcomes. Our study highlighted a significant impact relationship between prolonged Bluetooth headset use and increased thyroid nodule risk, emphasizing the importance of considering health impacts in the use of modern technology, especially for devices like Bluetooth headsets that are frequently used daily. Through precise model predictions and variable importance analysis, our research provides a scientific basis for the formulation of public health policies and personal health habit choices, suggesting that attention should be paid to the duration of Bluetooth headset use in daily life to reduce the potential risk of thyroid nodules. Future research should further investigate the biological mechanisms of this relationship and consider additional potential influencing factors to offer more comprehensive health guidance and preventive measures.

Abstract The data scale keeps growing by leaps and the majority of it is high‐dimensional imbalanced data, which is hard to classify. Data missing often happens in software which further aggravates the difficulty of classifying the data. In order to resolve high‐dimensional imbalanced mixed‐variables missing data classification problem, a novel method based on particle swarm optimization is developed. It has three original components including multiple feature selection, mixed attribute imputation, and quantum oversampling. Multiple feature selection uses a two‐stage strategy to obtain stable relevant features. Mixed attribute imputation separates features into continuous and discrete features and fills missing values with different models. Quantum oversampling chooses instances to balance data based on the quantum operator. Furthermore, particle swarm optimization is employed to optimize the parameters of the components to obtain preferable classification results. Six representative classification datasets, six typical algorithms, and four measures are taken to conduct exhaust experiments, and results indicate that the proposed method is superior to the comparison algorithms.

Background The aim of this study was to develop and validate a prediction model for predicting the risk of preoperative asymptomatic lower extremity venous thrombosis (LEVT) in patients with knee osteoarthritis (KOA). Methods Patients with KOA diagnosed at our hospital between March 2022 and July 2023 were included in this study. Five factors were identified as independent risk factors for the development of preoperative asymptomatic LEVT in patients with KOA by univariate and multivariate logistic regression analysis and a prediction model was constructed by analyzing the results. The performance of the model was evaluated using receiver operating characteristic (ROC) curves. The accuracy of the model and its predictive ability were evaluated using calibration curves. The clinical application value of the prediction model was evaluated using decision curve analysis (DCA). Results A total of 354 patients diagnosed with KOA were included in the study. Multivariate logistic regression analysis revealed HDL 0.55 mg/L ( P = 0.049 ) were the independent risk factors for the occurrence of preoperative asymptomatic LEVT in patients with KOA. The combined-variable ROC curve suggested greater predictability and accuracy (AUC = 0.843, specificity = 90.3%, sensitivity = 71.4%). The calibration curve showed good model agreement and DCA suggested good clinical value of the model. Conclusion Low HDL, high LDL, Na + , Ca 2+ , and D-dimer levels can be used as independent risk factors for the preoperative prediction of asymptomatic LEVT in patients with KOA, and the present study also provides a simple prediction model for clinicians and patients.

Abstract The unprecedented habitat fragmentation or loss has threatened the existence of many species. Therefore, it is essential to understand whether and how these species can pace with the environmental changes. Recent advantages in landscape genomics enabled us to identify molecular signatures of adaptation and predict how populations will respond to changing environments, providing new insights into the conservation of species. Here, we investigated the pattern of neutral and putative adaptive genetic variation and its response to changing environments in a tertiary relict tree species, Taxus cuspidata Sieb. et Zucc, which is distributed in northeast China and adjacent regions. We investigated the pattern of genetic diversity and differentiation using restriction site‐associated DNA sequencing (RAD‐seq) and seven nuclear microsatellites (nSSRs) datasets. We further explored the endangered mechanism, predicted its vulnerability in the future, and provided guidelines for the conservation and management of this species. RAD‐seq identified 16,087 single nucleotide polymorphisms (SNPs) in natural populations. Both the SNPs and nSSRs datasets showed high levels of genetic diversity and low genetic differentiation in T. cuspidata. Outlier detection by FST outlier analysis and genotype‐environment associations (GEAs) revealed 598 outlier SNPs as putative adaptive SNPs. Linear redundancy analysis (RDA) and nonlinear gradient forest (GF) showed that the contribution of climate to genetic variation was greater than that of geography, and precipitation played an important role in putative adaptive genetic variation. Furthermore, the genetic offset and risk of non‐adaptedness (RONA) suggested that the species at the northeast edge may be more vulnerable in the future. These results suggest that although the species has maintained high current genetic diversity in the face of recent habitat loss and fragmentation, future climate change is likely to threaten the survival of the species. Temperature (Bio03) and precipitation (Prec05) variables can be potentially used as predictors of response of T. cuspidata under future climate. Together, this study provides a theoretical framework for conservation and management strategies for wildlife species in the context of future climate change.

As a typical structural weak surface, bedding is ubiquitous in coal seams. The relative mechanical properties between coal seam bedding and coal matrix are the key to determining the effect of enhancing permeability by microwave in coal seams with bedding development. To this end, a self-developed microwave irradiation (MI) test device was used to carry out microwave fracturing coal experiments on coal samples with an angle of 0°, 30°, 45°, 60° and 90° between the bedding plane and the loading direction. The evolution characteristics of microscopic pore structure and microscopic cracks of coal samples with different bedding directions were explored, and the influence of bedding structure on the number, scale, and connectivity of coal pores and fractures under MI was revealed. The gas permeability characteristics of coal in different bedding directions before and after MI were compared and analyzed. The variation law of coal permeability under the influence of coal seam bedding and fracturing coal by microwave was clarified, and the influence mechanism of coal seam bedding on fracturing coal and enhancing permeability by microwave was revealed. The results show that the coal seam bedding has a significant effect on the effect of fracturing coal and enhancing permeability by microwave. The larger the angle between the bedding plane and the loading direction, the greater the reduction of the bound pores and the growth of the connected fractures of the coal under MI. Compared with the original coal samples, the order of magnitude difference between the permeability of coal samples in different bedding directions after MI is effectively reduced, and the permeability anisotropy is obviously weakened. The development of meso-cracks in coal under MI has a significant bedding effect. The specific evolution process is first to expand the original cracks along the bedding plane, followed by the initiation of new cracks along the bedding plane, and finally to expand the cracks intersecting with the bedding plane. The difference of dielectric loss and heat transfer properties between coal matrix and bedding plane makes the thermal stress distribution of coal subject to the bedding plane. When the bedding plane is perpendicular or parallel to the loading direction, the coal body is dominated by tensile failure. When the bedding plane is oblique to the loading direction, the coal body is dominated by shear slip failure.

Abstract The consumption of a high-fat diet (HFD) has been linked to osteoporosis and an increased risk of fragility fractures. However, the specific mechanisms of HFD-induced osteoporosis are not fully understood. Our study shows that exposure to an HFD induces premature senescence in bone marrow mesenchymal stem cells (BMSCs), diminishing their proliferation and osteogenic capability, and thereby contributes to osteoporosis. Transcriptomic and chromatin accessibility analyses revealed the decreased chromatin accessibility of vitamin D receptor (VDR)-binding sequences and decreased VDR signaling in BMSCs from HFD-fed mice, suggesting that VDR is a key regulator of BMSC senescence. Notably, the administration of a VDR activator to HFD-fed mice rescued BMSC senescence and significantly improved osteogenesis, bone mass, and other bone parameters. Mechanistically, VDR activation reduced BMSC senescence by decreasing intracellular reactive oxygen species (ROS) levels and preserving mitochondrial function. Our findings not only elucidate the mechanisms by which an HFD induces BMSC senescence and associated osteoporosis but also offer new insights into treating HFD-induced osteoporosis by targeting the VDR-superoxide dismutase 2 (SOD2)-ROS axis.