Search Results (70)

As a critical ecologicalbarrier in the semi-arid to semi-humid transition zone of northern China, the interaction between afforestation and climatic stressors in the Yellow River Basin constitutes a pivotal scientific challenge for regional sustainable development. However, the synthesis effects of afforestation and climate on primary productivity require further investigation. Integrating multi-source remote sensing data (2000–2020), meteorological observations with the Standardized Precipitation Evapotranspiration Index (SPEI) and an improved CASA model, this study systematically investigates spatiotemporal patterns of vegetation net primary productivity (NPP) responses to extreme drought events while quantifying vegetation coverage’s regulatory effects on ecosystem drought sensitivity. Among drought events identified using a three-dimensional clustering algorithm, high-intensity droughts caused an average NPP loss of 23.2 gC·m⁻² across the basin. Notably, artificial irrigation practices in the Hetao irrigation district significantly mitigated NPP reduction to −9.03 gC·m⁻². Large-scale afforestation projects increased the NDVI at a rate of 3.45 × 10⁻⁴ month⁻¹, with a contribution rate of 78%, but soil moisture competition from high-density vegetation reduced carbon-sink benefits. However, mixed forest structural optimization in the Three-North Shelterbelt Forest Program core area achieved local carbon-sink gains, demonstrating that vegetation configuration alleviates water competition pressure. Drought amplified the suppressive effect of afforestation through stomatal conductance-photosynthesis coupling mechanisms, causing additional NPP losses of 7.45–31.00 gC·m⁻², yet the April–July 2008 event exhibited reversed suppression effects due to immature artificial communities during the 2000–2004 baseline period. Our work elucidates nonlinear vegetation-climate interactions affecting carbon sequestration in semi-arid ecosystems, providing critical insights for optimizing ecological restoration strategies and climate-adaptive management in the Yellow River Basin. Full article

This study investigated how Moso bamboo (Phyllostachys edulis)–broadleaf mixed forests influence soil properties and microbial communities to support ecological function and sustainable bamboo forest management. Three forest types were examined: pure Moso bamboo stands (MB) and mixed stands with Liquidambar formosana (LB) or Phoebe chekiangensis (PB). Soil chemical properties, microbial diversity, and community composition were assessed using high-throughput sequencing, and functional taxa were correlated with soil nutrients. The results showed that mixed forests significantly influenced soil chemical properties. PB showed the lowest pH and highest total nitrogen (TN), while MB exhibited the highest soil organic matter (SOM) and total potassium (TK). LB maintained moderate TN, high SOM and TK, and stable pH, indicating a balanced nutrient profile. Although α-diversity did not differ significantly, β-diversity analysis revealed distinct microbial community structure (p < 0.01). LB was enriched with carbon-decomposing taxa (Terriglobales and Sphingomonas), PB with acid-tolerant, nitrogen-cycling groups (Candidatus Binatus), and MB with nitrogen-fixing taxa (Nitrobacteraceae and Bradyrhizobium). Co-occurrence network and functional pathway analyses indicated group-specific microbial associations and greater metabolic diversity in LB and PB. In conclusion, mixed Moso bamboo with broadleaf species significantly modified soil chemical properties and microbial community structure, with the Moso bamboo—L. formosana combination showing potential for improving soil nutrient status and microbial function. Full article

The main protease of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), known as 3CL^pro, is crucial in the virus’s life cycle and plays a pivotal role in COVID-19. Understanding how small molecules inhibit 3CL^pro’s activity is vital for developing anti-COVID-19 therapeutics. To this end, we employed Gaussian accelerated molecular dynamics (GaMD) simulations to enhance the sampling of 3CL^pro conformations and conducted correlation network analysis (CNA) to explore the interactions between different structural domains. Our findings indicate that a CNA-identified node in domain II of 3CL^pro acts as a conduit, transferring conformational changes from the catalytic regions in domains I and II, triggered by the binding of inhibitors (7YY, 7XB, and Y6G), to domain III, thereby modulating 3CL^pro’s activity. Normal mode analysis (NMA) and principal component analysis (PCA) revealed that inhibitor binding affects the structural flexibility and collective movements of the catalytic sites and domain III, influencing 3CL^pro’s function. The binding free energies, predicted by both MM-GBSA and QM/MM-GBSA methods, showed a high correlation with experimental data, validating the reliability of our analyses. Furthermore, residues L27, H41, C44, S46, M49, N142, G143, S144, C145, H163, H164, M165, and E166, identified through residue-based free energy decomposition, present promising targets for the design of anti-COVID-19 drugs and could facilitate the development of clinically effective 3CL^pro inhibitors. Full article

The model error is a direct reflection of the accuracy of the model simulation. However, it is challenging to estimate the model error due to the presence of numerous uncertainties inherent to the atmospheric and soil data, as well as the structure and parameters of the model itself. This paper addresses the fundamental issue of error estimation in the simulation of soil moisture by the Variable Infiltration Capacity (VIC) model, with a particular focus on the continental United States from 2010 to 2020. The paper develops a model error estimation method based on the Triple Collocation (TC) error estimation and in situ data validation of the VIC model at different temporal and spatial scales. Furthermore, it addresses the issue of failing to consider the variability of temporal and spatial scales in model error estimations. Furthermore, it generates the standard product data on soil moisture simulation errors for the VIC model in the continental United States. The mean of the simulation error variance of the VIC model, estimated using the TC method for spatially scaled soil moisture in the continental United States, is found to be 0.0045 (m³/m³)², with a median value of 0.0042 (m³/m³)². The mean time-scale error variance of the VIC model, validated using ground station data, is 0.0096 (m³/m³)², with a median value of 0.0078 (m³/m³)². Concurrently, the paper employs Köppen climate classification and land cover data as supplementary data, conducting a comprehensive investigation and analysis of the characteristics and alterations of the VIC model error in the study area from both temporal and spatial perspectives. The findings indicate a proclivity for reduced error rates during the summer months and elevated rates during the winter, with lower rates observed in the western region and higher rates in the eastern region. The objective of this study is twofold: firstly, to conduct a quantitative assessment and analysis of the VIC model’s simulation capabilities; secondly, to validate the accuracy and quality of the soil moisture products simulated by the model. The accurate estimation of model errors is a fundamental prerequisite for the numerical simulation and data assimilation of models, which has a vast range of applications in numerical meteorological and hydrological forecasting, natural environment monitoring, and other fields. Full article

Selecting high-quality varieties with disease resistance by artificial crossbreeding is the most fundamental way to address the damage caused by Calonectria spp. in eucalypt plantations. However, understanding the mechanism of disease-resistant heterosis occurrence in eucalypts is crucial for successful crossbreeding. Two eucalypt hybrids, the susceptible EC333 (H1522 × unknown) and the resistant EC338 (W1767 × P9060), were screened through infection with Calonectria isolates, a pathogen that causes eucalypt leaf blight. RNA-Seq was performed on the susceptible hybrid, the disease-resistant hybrid, and their parents. The gene differential expression analysis showed that there were 3912 differentially expressed genes between EC333 and EC338, with 1631 up-regulated and 2281 down-regulated genes. The expression trends of the differential gene sets in P9060 and EC338 were similar. However, the expression trend of W1767 was opposite that of EC338. The similarity of the expression and the advantage of stress resistance in E. pellita suggested that genes with significant differences in expression likely relate to disease resistance. A GSEA based on GO annotations revealed that the carbohydrate binding pathway genes were differentially expressed between EC338 and EC333. The gene pathways that were differentially expressed between EC338 and EC333 revealed by the GSEA based on KEGG annotations were the sesquiterpenoid and triterpenoid biosynthesis pathways. The alternative splicing analysis demonstrated that an AS event between EC338 and EC333 occurred in LOC104426602. According to our SNP analysis, EC338 had 626 more high-impact mutation loci than the male parent P9060 and 396 more than the female parent W1767; W1767 had 259 more mutation loci in the downstream region than EC338, while P9060 had 3107 fewer mutation loci in the downstream region than EC338. Additionally, EC338 had 9631 more mutation loci in the exon region than EC333. Modules were found via WGCNA that were strongly and oppositely correlated with EC338 and EC333, such as module MEsaddlebrown, likely associated with leaf blight resistance. The present study provides a detailed explanation of the genetic basis of eucalypt leaf blight resistance, providing the foundation for exploring genes related to this phenomenon. Full article

Bromodomain-containing protein 9 (BRD9) is a key player in chromatin remodeling and gene expression regulation, and it is closely associated with the development of various diseases, including cancers. Recent studies have indicated that inhibition of BRD9 may have potential value in the treatment of certain cancers. Molecular dynamics (MD) simulations, Markov modeling and principal component analysis were performed to investigate the binding mechanisms of allosteric inhibitor POJ and orthosteric inhibitor 82I to BRD9 and its allosteric regulation. Our results indicate that binding of these two types of inhibitors induces significant structural changes in the protein, particularly in the formation and dissolution of α-helical regions. Markov flux analysis reveals notable changes occurring in the α-helicity near the ZA loop during the inhibitor binding process. Calculations of binding free energies reveal that the cooperation of orthosteric and allosteric inhibitors affects binding ability of inhibitors to BRD9 and modifies the active sites of orthosteric and allosteric positions. This research is expected to provide new insights into the inhibitory mechanism of 82I and POJ on BRD9 and offers a theoretical foundation for development of cancer treatment strategies targeting BRD9. Full article

Inhibiting MDM2-p53 interaction is considered an efficient mode of cancer treatment. In our current study, Gaussian-accelerated molecular dynamics (GaMD), deep learning (DL), and binding free energy calculations were combined together to probe the binding mechanism of non-peptide inhibitors K23 and 0Y7 and peptide ones PDI6W and PDI to MDM2. The GaMD trajectory-based DL approach successfully identified significant functional domains, predominantly located at the helixes α2 and α2’, as well as the β-strands and loops between α2 and α2’. The post-processing analysis of the GaMD simulations indicated that inhibitor binding highly influences the structural flexibility and collective motions of MDM2. Calculations of molecular mechanics–generalized Born surface area (MM-GBSA) and solvated interaction energy (SIE) not only suggest that the ranking of the calculated binding free energies is in agreement with that of the experimental results, but also verify that van der Walls interactions are the primary forces responsible for inhibitor–MDM2 binding. Our findings also indicate that peptide inhibitors yield more interaction contacts with MDM2 compared to non-peptide inhibitors. Principal component analysis (PCA) and free energy landscape (FEL) analysis indicated that the piperidinone inhibitor 0Y7 shows the most pronounced impact on the free energy profiles of MDM2, with the piperidinone inhibitor demonstrating higher fluctuation amplitudes along primary eigenvectors. The hot spots of MDM2 revealed by residue-based free energy estimation provide target sites for drug design toward MDM2. This study is expected to provide useful theoretical aid for the development of selective inhibitors of MDM2 family members. Full article

CDK6 plays a key role in the regulation of the cell cycle and is considered a crucial target for cancer therapy. In this work, conformational transitions of CDK6 were identified by using Gaussian accelerated molecular dynamics (GaMD), deep learning (DL), and free energy landscapes (FELs). DL finds that the binding pocket as well as the T-loop binding to the Vcyclin protein are involved in obvious differences of conformation contacts. This result suggests that the binding pocket of inhibitors (LQQ and AP9) and the binding interface of CDK6 to the Vcyclin protein play a key role in the function of CDK6. The analyses of FELs reveal that the binding pocket and the T-loop of CDK6 have disordered states. The results from principal component analysis (PCA) indicate that the binding of the Vcyclin protein affects the fluctuation behavior of the T-loop in CDK6. Our QM/MM-GBSA calculations suggest that the binding ability of LQQ to CDK6 is stronger than AP9 with or without the binding of the Vcyclin protein. Interaction networks of inhibitors with CDK6 were analyzed and the results reveal that LQQ contributes more hydrogen binding interactions (HBIs) and hot interaction spots with CDK6. In addition, the binding pocket endures flexibility changes from opening to closing states and the Vcyclin protein plays an important role in the stabilizing conformation of the T-loop. We anticipate that this work could provide useful information for further understanding the function of CDK6 and developing new promising inhibitors targeting CDK6. Full article

Accurate diagnostic techniques and effective therapeutic methods are required to treat H. pylori. The application of chicken single-chain variable fragment (scFv) antibodies may diagnose and treat H. pylori. This study used the phage display technique to construct a chicken-derived immune scFv antibody library against H. pylori. Total RNA was extracted from the spleens of five immunized chickens and reverse transcribed into cDNA. A fragment of scFv was produced by overlap extension PCR and cloned into a pHEN2 phagemid vector. After the package with the M13KO7 helper phage, the recombinant HpaA protein was used as a target antigen to validate the screening ability of our antibody library by bio-panning. The dilution counting results showed that the size of the primary antibody library was estimated to be 1 × 10⁹ cfu/mL. PCR analysis of 47 clones from the library revealed that about 100% of the clones were positive with scFv fragments, and there were no identical sequences, indicating the good diversity of the antibody library. After three rounds of bio-panning, high-affinity antibodies against recombinant HpaA protein were successfully obtained. The selected antibody specifically recognized HpaA protein in nine different H. pylori strains, confirming the screening ability of our library. The chicken immune scFv antibody library against H. pylori was successfully constructed, and the antibody library’s screening ability was validated by selecting specific scFv antibodies against recombinant HpaA and clinical strains. It provided a simple and rapid method to obtain antibodies against H. pylori for diagnosis or treatment. Full article

Halo-alkali soil threatens agriculture, reducing growth and crop yield worldwide. In this study, physicochemical and molecular techniques were employed to explore the potential of halo-alkali-tolerant endophytic bacteria strains Sphingomonas sp. pp01, Bacillus sp. pp02, Pantoea sp. pp04, and Enterobacter sp. pp06 to enhance the growth of hybrid Pennisetum under varying saline conditions. The strains exhibited tolerance to high salt concentrations, alkaline pH, and high temperatures. Under controlled conditions, all four strains showed significant growth-promoting effects on hybrid Pennisetum inoculated individually or in combination. However, the effects were significantly reduced in coastal saline soil. The best growth-promoting effect was achieved under greenhouse conditions, increasing shoot fresh and dry weights of hybrid Pennisetum by up to 457.7% and 374.7%, respectively, using irrigating trials. Metagenomic sequencing analysis revealed that the diversity and composition of rhizosphere microbiota underwent significant changes after inoculation with endophytic bacteria. Specifically, pp02 and co-inoculation significantly increased the Dyella and Pseudomonas population. Firmicutes, Mycobacteria, and Proteobacteria phyla were enriched in Bacillus PP02 samples. These may explain the best growth-promoting effects of pp02 and co-inoculation on hybrid Pennisetum under greenhouse conditions. Our findings reveal the performance of endophytic bacterial inoculants in enhancing beneficial microbiota, salt stress tolerance, and hybrid Pennisetum growth. Full article

The phosphorylation of different sites produces a significant effect on the conformational dynamics of KRAS. Gaussian accelerated molecular dynamics (GaMD) simulations were combined with deep learning (DL) to explore the molecular mechanism of the phosphorylation-mediated effect on conformational dynamics of the GTP-bound KRAS. The DL finds that the switch domains are involved in obvious differences in conformation contacts and suggests that the switch domains play a key role in the function of KRAS. The analyses of free energy landscapes (FELs) reveal that the phosphorylation of pY32, pY64, and pY137 leads to more disordered states of the switch domains than the wild-type (WT) KRAS and induces conformational transformations between the closed and open states. The results from principal component analysis (PCA) indicate that principal motions PC1 and PC2 are responsible for the closed and open states of the phosphorylated KRAS. Interaction networks were analyzed and the results verify that the phosphorylation alters interactions of GTP and magnesium ion Mg²⁺ with the switch domains. It is concluded that the phosphorylation pY32, pY64, and pY137 tune the activity of KRAS through changing conformational dynamics and interactions of the switch domains. We anticipated that this work could provide theoretical aids for deeply understanding the function of KRAS. Full article

Bromodomain 4 and 9 (BRD4 and BRD9) have been regarded as important targets of drug designs in regard to the treatment of multiple diseases. In our current study, molecular dynamics (MD) simulations, deep learning (DL) and binding free energy calculations are integrated to probe the binding modes of three inhibitors (H1B, JQ1 and TVU) to BRD4 and BRD9. The MD trajectory-based DL successfully identify significant functional function domains, such as BC-loop and ZA-loop. The information from the post-processing analysis of MD simulations indicates that inhibitor binding highly influences the structural flexibility and dynamic behavior of BRD4 and BRD9. The results of the MM-GBSA calculations not only suggest that the binding ability of H1B, JQ1 and TVU to BRD9 are stronger than to BRD4, but they also verify that van der Walls interactions are the primary forces responsible for inhibitor binding. The hot spots of BRD4 and BRD9 revealed by residue-based free energy estimation provide target sites of drug design in regard to BRD4 and BRD9. This work is anticipated to provide useful theoretical aids for the development of selective inhibitors over BRD family members. Full article

The current increase in resistance to antifungal drugs indicates that there is an urgent need to explore novel antifungal drugs with different mechanisms of action. Phosundoxin is a biphenyl aliphatic amide using a TPP-targeting strategy which targets mitochondria. To provide insights into the antifungal activities of phosundoxin, the antifungal susceptibility testing of phosundoxin was conducted on 158 pathogenic fungi and compared to that of traditional azole drugs. Phosundoxin displayed a broad-spectrum antifungal activity on all the tested yeast-like and filamentous fungi ranging from 2 to 16 mg/L. In particular, azole-resistant clinical isolates of Candida albicans were susceptible to phosundoxin with the same MICs as azole-susceptible C. albicans. Transcriptome analysis on azole-resistant C. albicans identified 554 DEGs after treatment with phosundoxin. By integrating GO and KEGG pathway enrichment analysis, the antifungal activity of phosundoxin was related to impairment of mitochondrial respiratory chain function. Acute oral and percutaneous toxicity of phosundoxin to rats showed that the compound phosundoxin were mild toxicity and LD₅₀ was above 5000 mg/kg body weight in rats. This study demonstrated the potential of phosundoxin as an antifungal agent for the treatment of common fungal infection and contributed to providing insights into the mechanisms of action of phosundoxin against C. albicans. Full article

The data hierarchical Ciphertext-Policy Attribute-Based Encryption (CP-ABE) scheme implements multiple hierarchical data encryption of a single access policy, which reduces the computation and storage overhead. However, existing data hierarchical CP-ABE schemes have some problems, such as the leakage of personal privacy information through access policies or user attributes in plaintext form, and these schemes grant enough privileges to a single authorization center. If the authorization center is untrusted or attacked, keys can be used to illegally access data, which is the key escrow problem. To solve these problems, we propose an Attribute Hiding and Multiple Authorization Centers-based Data Hierarchical Encryption Scheme (AH-MAC-DHE). Firstly, we propose an Attribute Convergence Hiding Mechanism (ACHM). This mechanism solves the problem of personal privacy information leakage by hiding access policies and user attributes. Secondly, we design Privilege-Dispersed Multiple Authorization Centers (PD-MAC). PD-MAC solves the problem of key escrow by dispersing the privileges of the single authorization center to the user authorization center and attribute authorization center. Finally, we prove that AH-MAC-DHE is secure under the decisional q-parallel Bilinear Diffie-Hellman Exponent (BDHE) assumption, which also satisfies anti-collusion and privacy security. The experimental results indicate that compared with existing schemes, AH-MAC-DHE performs well. Full article

Guanidine disinfectants are important chemical agents with a broad spectrum of activity that are effective against most microorganisms. Chlorhexidine, one of the most used guanidine disinfectants, is added to shampoo and mouthwash and applied in medical device sterilization. During the use of chlorhexidine, aerosols with micron particle size may be formed, which may cause inhalation toxicity. To assess the toxicity of inhaled chlorhexidine aerosol, mice underwent the intratracheal instillation of different concentrations of chlorhexidine (0, 0.125%, 0.25%, 0.5%, and 1%) using a MicroSprayer Aerosolizer. The mice were exposed for eight weeks and then sacrificed to obtain lung tissue for subsequent experiments. Histopathology staining revealed damaged lung tissues and increased collagen exudation. At the same time, pulmonary function tests showed that chlorhexidine exposure could cause restrictive ventilatory dysfunction, consistent with pulmonary fibrosis. The results of transcriptome analyses suggest that chlorhexidine may trigger an inflammatory response and promote the activation of pathways related to extracellular matrix deposition. Further, we identified that chlorhexidine exposure might enhance mucus secretion by up-regulating Muc5b and Muc5ac genes, thereby inducing fibrosis-like injury. These findings underscore the need for standardized use of disinfectants and the assessment of their inhalation toxicity. Full article