Search Results (26,967)

Fragaria pentaphylla, a unique wild strawberry species in China, is rich in various fruit colors and a valuable resource for studying color genes. Fruits of different colors from F. pentaphylla were selected as the experimental material. Liquid chromatography-mass spectrometry (LC-MS) and high-throughput RNA sequencing (RNA-seq) were employed to identify key genes responsible for the development of different fruit colors. Metabolite analysis revealed that 3249 metabolites were detected, including nine differential metabolites related to anthocyanin synthesis and five biological pathways. Additionally, an analysis combining transcriptome and metabolome data showed that the structural genes FpDFR, FpCHS, FpCHI, and FpUFGT were upregulated in red fruit, with significantly higher expression levels compared to pink and white fruits, actively promoting anthocyanin production in red fruit. Conversely, genes FpANR and FpLAR were upregulated in white fruit, enhancing catechin synthesis and inhibiting anthocyanin formation. The gene FpPAL was upregulated in pink fruit. Transcription factors FpbHLH18, FpMYB1, FpMYB24, and FpMYB114 collaborate with structural genes to enhance the synthesis of anthocyanins in red fruit. The findings improve our understanding of the molecular mechanisms that control anthocyanin production in F. pentaphylla. The identified key candidate genes may be utilized in the molecular breeding of strawberries. Full article

Janus particles (JPs), as a special material with anisotropic chemical or physical partitioning, show great potential for application in the fields of material science, biomedicine, energy, and environment. How to achieve fine structural control and large-scale synthesis of JPs is the key point and difficulty for JPs. Seeded emulsion polymerization, as a simple and efficient method, plays an important role in the controlled fabrication of JPs. Here, we provide a comprehensive review of the research progress in the preparation of JPs via seeded emulsion polymerization. We systematically summarize the process mechanisms and key parameters influencing the formation of Janus structures, with particular emphasis on the effects of seed characteristics, polymerization conditions, and component selection on particle morphology and anisotropy. Full article

Dengue fever is a mosquito-borne viral disease that annually affects 100–400 million people worldwide. Early detection of dengue enables easy treatment planning and helps reduce mortality rates. This study proposes three Swarm-based Metaheuristic Algorithms, Golden Jackal Optimization, Fox Optimizer, and Sea Lion Optimization, for feature selection and hyperparameter tuning, and an Extreme Gradient Boost classifier to forecast dengue fever using the Predictive Clinical Dengue dataset. Several existing models have been proposed for dengue fever classification, with some achieving high predictive performance. However, most of these studies have overlooked the importance of feature reduction, which is crucial to building efficient and interpretable models. Furthermore, prior research has lacked in-depth analysis of model behavior, particularly regarding the underlying causes of misclassification. Addressing these limitations, this study achieved a 10-fold cross-validation mean accuracy of 99.89%, an F-score of 99.92%, a precision of 99.84%, and a perfect recall of 100% by using only two features: WBC Count and Platelet Count. Notably, FOX-XGBoost and SLO-XGBoost achieved the same performance while utilizing only four and three features, respectively, demonstrating the effectiveness of feature reduction without compromising accuracy. Among these, GJO-XGBoost demonstrated the most efficient feature utilization while maintaining superior performance, emphasizing its potential for practical deployment in dengue fever diagnosis. SHAP analysis identified WBC Count as the most influential feature driving model predictions. Furthermore, DiCE explanations support this finding by showing that lower WBC Counts are associated with dengue-positive cases, whereas higher WBC Counts are indicative of dengue-negative individuals. SHAP interpreted the reasons behind misclassifications, while DiCE provided a correction mechanism by suggesting the minimal changes needed to convert incorrect predictions into correct ones. Full article

The impact of green fiscal policies on forestry new quality productivity (FNQP) development and the mechanisms behind this are explored in this study. A scientific basis for the promotion of FNQP development through green fiscal policies is intended to be provided. In addition, novel perspectives on the high-quality development of forestry are offered. Panel data from 31 Chinese provinces between 2011 and 2022 are collected and discrepancies between green fiscal policies and the level of FNQP are examined. By constructing a two-way fixed-effects model and employing econometric methods, the significant promotion of FNQP by green fiscal policies is indicated. Indirect promotion of FNQP development through the upgrading of the forestry industrial structure and the intensification of environmental regulation by green fiscal policies is demonstrated by indirect impact analysis results. Furthermore, a positive spatial spillover effect of green finance on forestry new quality productivity is documented. For policy selection, regional economic development level heterogeneity characteristics should be taken into account. Based on the findings of this study, some recommendations have been given for responses to green fiscal policy for forestry new quality productivity in the future. Full article

Elucidating the evolutionary origins of social behavior remains a major challenge due to the complexity of social systems across taxa. Here, we examine social behavior through the lens of competition and cooperation across the three domains of life—Bacteria, Archaea, and Eukarya. By focusing on gene-based mechanisms, we propose that sociality arises from conserved molecular pathways shaped by similar selective pressures, even in phylogenetically distant organisms. This cross-domain perspective highlights the potential for convergent evolutionary solutions and offers a foundation for identifying invariant principles underlying the emergence and maintenance of social behavior. Full article

The following article presents the results of research on the assessment of the effect of FDM printing process conditions on the properties of the obtained products. During the research, unmodified PLA and a PLA/PHA mixture were subjected to comparative analysis. Both materials exhibit excellent processability under standard FDM process conditions; however, the PLA/PHA blend is gaining attention due to its potential as a more thermally resistant and less brittle alternative to unmodified PLA. The printing procedure conducted at high bed platform temperature confirmed that for standard PLA varieties and the PLA/PHA blend, it is possible to obtain improved thermomechanical properties only by modifying the machine parameters of the printing process. The increase in the Vicat softening temperature value was about 80 °C, reaching above 130 °C. Interestingly, for materials based on pure PLA, most mechanical properties exhibit noticeable improvement, with the improvement in impact strength being particularly beneficial. For most materials, the measurements revealed significant anisotropy of properties within the tested samples, which was particularly due to the use of different bed platform temperatures. The apparent effect of this was the change in the thermal conditions of the PLA phase crystallization process, with crystallinity levels ranging from 17 to 33% for selected samples. The obtained results confirm that PLA/PHA blends are an interesting alternative for the PLA-based material; however, further research is needed to improve the application potential further. Full article

When considering an urban agglomeration as a unit, promoting the coupling and coordination of the land price gradient and industrial gradient is crucial for achieving regional integrated development. We selected the Beijing–Tianjin–Hebei Urban Agglomeration (BTHUA) as a case study; constructed a three-dimensional analytical framework involving static coupling, dynamic coupling, and spatial matching; theoretically clarified the coupling mechanism between the land price gradient and industrial gradient; and systematically assessed their spatial-temporal patterns and coupling characteristics. The results indicate that from 2012 to 2022, both the land price gradient and industrial gradient within the BTHUA exhibited a “core-periphery” spatial distribution, gradually forming an over-all pattern of “one core, multiple nodes, and multi-level rings.” For the Beijing–Tianjin–Hebei urban agglomeration, overall static coupling and spatial matching exhibit an evolutionary trajectory of “first rising, then declining.” By contrast, dynamic coupling remains relatively weak, exhibiting a corridor-shaped distribution along core and sub-core cities. All three indicators consistently show that core cities outperform peripheral cities. Nonlinear mechanism analysis based on the gradient boosting decision tree method showed that “second-nature” factors like economic development and public utilities significantly promote multidimensional coupling. Conversely, “first-nature” factors, such as geographic conditions, have limited impacts with threshold effects; surpassing these thresholds results in inhibitory effects. Based on the research findings, this study proposes that regional integration should serve as the guiding principle, emphasizing the cultivation of regional development corridors, the implementation of flexible and functionally aligned land supply policies, the strengthening of land use performance audits, and the reorientation of fiscal and financial policies toward structural and qualitative improvements. These measures can provide valuable references for promoting coordinated industrial development and balanced land allocation in urban agglomerations. Full article

In high-concentration tailings backfilling, the stability of the backfill largely depends on the slurry’s self-weighted siltation behavior. Red mud—the strongly alkaline by-product of the Bayer process and a mixture of coarse and fine particles—requires a clear understanding of its self-weight settling–consolidation mechanisms to ensure safe and efficient backfilling. In this study, red mud slurry was selected as the research object, and a multi-scale approach combining sedimentation column tests and microstructural image analysis was employed to reveal the intrinsic relationships among the sediment layer height, sedimentation rate, and pore structure changes during self-weighted siltation. The results show that the flocculated structure of red mud slurry exhibits distinct stratification during self-weighted siltation, including a clarified layer, a structural transition layer, and a dense sediment layer. During the siltation process, the sediment layer height, sedimentation rate, and floc structure of red mud evolve nonlinearly. The addition of flocculants significantly enhances the formation rate of flocculated structures but increases the porosity of the sediment body. At the macroscopic level, this results in a shortened self-weighted siltation time and increased final sediment layer height. To describe the regulatory effect of flocculants on red mud floc structure, a macro–micro predictive model for the sediment layer height was established by introducing a structural enhancement coefficient, considering the effect of flocculants. The model achieved a prediction error within 16%. These findings provide theoretical support for structural control technologies and process optimization of high-concentration fine tailings backfilling, thereby contributing to the sustainable utilization of red mud and the development of environmentally responsible backfilling practices. Full article

The global issues of resource depletion and environmental pollution have led to increased interest in a circular bioeconomy focusing on converting renewable biomass into functional biomaterials. This article explores the transformative potential of hemicellulosic biogels as a sustainable platform to address critical societal challenges, such as water scarcity, food solutions and environmental pollution. Derived from hemicelluloses, an abundant and underutilized polysaccharide in lignocellulose biomass, these biogels offer a fundamentally new approach to developing high-performance, ecofriendly based materials. The review examines their development, characterization, and diverse applications in water treatment, food, agriculture, adhesive and coating systems. In water treatment, these gels exhibit exceptional performance, demonstrating a maximum NaCl uptake of 0.26 g/g and rapid pseudo-second-order adsorption kinetics for desalination. They also show high selectivity for heavy metal removal, with a remarkable binding capacity for lead if 2.9 mg/g at pH 5. For adhesive and coating applications, hemicellulose crosslinked with ammonium zirconium carbonate (AZC) forms water-resistant gels that significantly enhance paper properties, including gloss, smoothness, liquid resistance, and adhesive strength. Furthermore, hemicellulosics exhibit controlled biodegradation in physiological solutions while maintaining their mechanical integrity, underscoring their broad application promise. Overall, this review highlights how hemicellulose-based hydrogels can transform a low-value byproduct from biorefinery into high-performance solutions, contributing significantly to a sustainable economy. Full article

Background/Objectives: Temporizin-1, a hybrid antimicrobial peptide derived from the combination of Temporin A, Gramicidin peptide, and a poly-leu sequence, has strong trypanocide activity against Trypanosoma cruzi and moderate cytotoxicity towards mammalian cells. In this study, we investigated the mode of action of the peptide upon interaction with protozoan and eukaryotic membranes. Methods: To this end, we conducted a series of biophysical assays using liposomes as biomimetic models, along with fluorescence-based experiments such as lipid mixing, membrane leakage, and assays involving Thioflavin and Laurdan. Results: Temporizin-1 displayed potent membranolytic activity on protozoan and eukaryotic membranes, causing significant membrane fusion and leakage with consequent pore formation. In addition, we also performed structural studies on liposome interaction, where we observed a helical structure that is conserved during membrane interaction. The NMR study confirms all the data obtained, providing both the structure of free Temporizin-1 in solution and the way it interacts with micelles. Moreover, Temporizin-1 demonstrated high selectivity against intracellular forms of T. cruzi and exhibited an additive effect when combined with benznidazole, highlighting its promising therapeutic activity. Conclusions: In conclusion, elucidating the mechanism of action of Temporizin-1 is essential for optimizing its structure and improving target selectivity, and driving the rational design of next-generation antimicrobial peptides by applying chemical strategies and delivery system’s conjugation. Full article

Automatic crater detection is crucial for planetary science, but still faces several long-standing challenges. The morphological characteristics of craters exhibit significant variability; combined with complex lighting conditions, this makes feature extraction difficult, especially for small or severely degraded features. These difficulties are further compounded by incomplete ground truth annotations, which limit the effectiveness of supervised learning. In addition, achieving a balance between detection accuracy and computational efficiency remains a critical bottleneck, especially in large-scale planetary surveys. Traditional postprocessing algorithms also often struggle to resolve complex spatial hierarchies in densely cratered regions, leading to substantial omissions and misclassifications. To address these interrelated challenges, we propose Crater-MASN, a lightweight adaptive detection framework specifically designed for lunar crater analysis. The architecture employs a compact GhostNet backbone to balance efficiency and accuracy, while enhancing multi-scale feature representation through a novel bidirectional integration and fusion module (BIFM) to better capture the morphological diversity of craters. To mitigate the impact of incomplete annotations, we introduce an adaptive semantic contrastive sampling (ASCS) mechanism which dynamically mines unlabeled craters through semantic clustering and contrastive learning. Additionally, we design the hierarchical soft NMS (H-SoftNMS) algorithm, a geometry-aware postprocessing method that selectively suppresses non-hierarchical overlaps to preserve nested craters, thereby achieving more accurate crater retention in dense regions. Experiments on a dedicated lunar crater dataset demonstrate the effectiveness of Crater-MASN. The model achieves an mAP50 of 91.0% with only 2.1 million parameters. When combined with H-SoftNMS, it achieves a recall rate of 95.0% and new discovery rate ${\mathcal{P}}_{\mathrm{NDR}}$ of 89.6%. These results highlight the potential of Crater-MASN as a scalable and reliable tool for high-precision crater cataloging and planetary surface analysis. Full article

Amyotrophic lateral sclerosis (ALS) is a fatal type of neurodegenerative disease marked by progressive and selective degeneration of motor neurons (MNs) present in the spinal cord, brain stem and motor cortex. However, the intricate molecular mechanisms underlying primary cell death pathways, including ferroptosis-related genes (FRGs) mediating MN dysfunction in ALS, remain elusive. Ferroptosis, a novel type of iron-dependent cell death with the accumulation of lipid peroxidation products, stands distinct from apoptotic-related stress and other cell death mechanisms. Although growing advances have highlighted the role of iron deposition, apoptosis and alteration of antioxidant systems in ALS pathogenesis, there is little data at the systems biology level. Therefore, we performed a comprehensive bioinformatic analysis of bulk RNA-sequencing (RNA-seq) data by systematically comparing the gene expression profiles from iPSC-derived MNs of ALS patients and healthy controls using our datasets as well as from the GEO database to reveal the role of ferroptosis-related gene alterations in ALS, especially in selective MN vulnerability of FUSED IN SARCOMA (FUS) mutations. In this study, we first identified differentially expressed genes (DEGs) between FUS mutant and healthy controls. Subsequently, the crossover genes between DEGs and FRGs were selected as differentially expressed ferroptosis-related genes (DEFRGs). Functional enrichment and protein–protein interaction (PPI) analysis of DEFRGs identified that DNA damage, stress response and extra cellular matrix (ECM) were the most significantly dysregulated functions/pathways in FUS-ALS causing mutations compared to healthy controls. While GSEA analysis showed enrichment of genes associated with apoptosis, the degree of ferroptosis and iron ion homeostasis/response to iron of FUS MNs was lower. Altogether, our findings may contribute to a better understanding of the relevant role of cell death pathways underlying selective vulnerability of MNs to neurodegeneration in FUS-ALS pathophysiology. Full article

The dynamic load caused by vehicle vibration due to an uneven pavement surface is a primary factor affecting the structural performance and service life of asphalt pavement. As the principles of vibration mechanics, in conjunction with the coherence function of the vehicle’s left and right wheels, along with the lag between front and rear wheels, the entire vehicle vibration model for three-axle and four-axle heavy-load vehicles was developed using Simulink software. Through simulation, the root-mean-square value of the dynamic load and the dynamic load coefficient of the vehicle with different pavement roughness grades, speeds, loads, and cornering radii were analyzed. The outcomes demonstrate that a nonlinear rise in the wheel dynamic load occurs when pavement roughness increases. The greater the speed, the greater the impact of pavement roughness on the dynamic load. An increase in vehicle load tends to reduce vehicle vibrations. The interaction between vehicle vibration frequency and road excitation frequency is essential in figuring out the loads, and a negative influence on the pavement structure should be given more attention when the vehicle is driving at low speed. The dynamic load coefficient of the left and right wheels is greatly affected when the vehicle is in a lateral tilt. The findings offer valuable insights for selecting appropriate loads in pavement structure design. By constructing 11 degrees of freedom for a three-axle vehicle and 16 degrees of freedom for a four-axle heavy-duty vehicle model, the dynamic load variation law under different roughness excitation conditions is systematically analyzed. The results can be applied to the selection of vehicle load in asphalt pavement design to make it closer to the actual driving state, which will be helpful for improving accuracy in the design of pavement structure and avoiding early damage to the pavement. Full article

Natural product-derived drugs represent a cornerstone of modern pharmacotherapy, with many serving as essential therapeutic agents across diverse medical conditions. Recent advances in structural biology have provided unprecedented insights into the molecular mechanisms underlying their biological activities. This review presents a comprehensive structural analysis of five representative natural product-derived drugs: digoxin, simvastatin, morphine, paclitaxel, and penicillin. Through an examination of high-resolution crystal structures and cryo-electron microscopy (cryo-EM) data, we elucidate how these compounds interact with their respective protein targets and modulate biological functions. The structural data reveal diverse binding mechanisms—ranging from competitive inhibition and covalent modification to allosteric modulation via conformational selection and induced fit—demonstrating how natural products achieve their therapeutic effects through precise molecular recognition. These structural insights provide a molecular foundation for understanding natural product pharmacology and offer valuable guidance for structure-based drug design approaches in developing next-generation therapeutics. Full article

Chronic lymphocytic leukemia (CLL) is the most common type of leukemia in Western populations and remains incurable despite significant therapeutic advancements. Over the past decade, the treatment landscape has evolved from traditional chemoimmunotherapy to targeted oral agents, including Bruton’s tyrosine kinase inhibitors (BTKis) and BCL2 inhibitors (BCL2is), which have demonstrated superior efficacy and tolerability, especially in elderly patients. Venetoclax, a BCL2i, induces apoptosis in CLL cells through selective inhibition of the anti-apoptotic BCL2 protein, while BTKis, such as ibrutinib and its next-generation analogs, disrupt B-cell receptor signaling critical to CLL cell survival. However, resistance to both drug classes has emerged, including mutations in BTK and BCL2, prompting the exploration of novel therapeutic strategies. This review outlines the molecular basis and clinical implications of these resistance mechanisms, as well as emerging therapeutic solutions, including non-covalent BTKis like pirtobrutinib and BTK-targeting PROTAC degraders such as BGB-16673 and NX-2127. Additionally, we discuss promising combination therapies incorporating BTKis, BCL2is, and anti-CD20 monoclonal antibodies. Finally, we highlight the growing role of measurable residual disease (MRD) as a biomarker to guide treatment duration and evaluate therapeutic success. As resistance mechanisms continue to emerge, tailoring therapy based on underlying biology will be critical to sustaining disease control and enhancing outcomes in patients with CLL. Full article