Search Results (4,148)

Blooming time is an important basis for constructing plant landscapes. The short flowering period of Osmanthus fragrans, recognized as one of the ten traditional flowers in China, considerably constrains the further utilization of its resources. To clarify O. fragrans flowering regulation, this study focused on OfCOR27, conducting cloning, expression analysis, and functional verification to explore its effects on O. fragrans flowering time. A COR27 phylogenetic tree was built across six species; OfCOR27 physicochemical properties, conserved structures, and promoter cis-elements were analyzed. OfCOR27 CDS was cloned, fusion vectors were transformed into Nicotiana benthamiana, and organ-specific expression was tested in two O. fragrans cultivars. Overexpression vectors were transformed into Arabidopsis thaliana, with qRT-PCR verifying gene function. Five OfCOR27s were identified, showing evolutionary conservation. OfCOR27, which localizes to the nucleus and is associated with flowering regulation, shows higher expression in ‘Sijigui’ than in ‘XiaoyeSugui’. Overexpression of OfCOR27 promoted flowering in A. thaliana, whereas the AtCOR27 mutant flowered later. This confirms OfCOR27 is a positive regulator of plant flowering, which may promote flowering by enhancing the expression of flowering-promoting genes and altering hormone levels, providing a theoretical basis and candidate gene for the genetic improvement of flowering traits in woody ornamental plants. Full article

Semiconductor defect inspection is frequently hindered by data scarcity and the resulting class imbalance in supervised learning. This study proposes a CycleGAN-based data augmentation pipeline designed to synthesize realistic defective CD-SEM images from abundant normal patterns, incorporating a quantitative quality control mechanism. Using an ADI CD-SEM dataset, we conducted a sensitivity analysis by cropping original 1024 × 1024 micrographs into 512 × 512 and 256 × 256 inputs. Our results indicate that increasing the effective defect-area ratio is critical for improving generative stability and defect visibility. To ensure data integrity, we applied a screening protocol based on the Structural Similarity Index (SSIM) and a median absolute deviation noise metric to exclude low-fidelity outputs. When integrated into the training of XceptionNet classifiers, this filtered augmentation strategy yielded substantial performance gains on a held-out test set, specifically improving the Recall and F1 score while maintaining a near-ceiling AUC. These results demonstrate that controlled CycleGAN augmentation, coupled with objective quality filtering, effectively mitigates class imbalance constraints and significantly enhances the robustness of automated defect detection. Full article

Lignin pyrolysis is a pivotal route for biomass valorization, yet the intricate radical reaction network involved results in ambiguous hydrogen/oxygen transfer pathways and product formation mechanisms, severely impeding precise control over directed conversion processes. This study employed a combination of multi-isotope tracing techniques and GC-MS analysis to elucidate the formation mechanisms of four phenolic products during the 500 °C hydrothermal pyrolysis of dealkaline lignin. Experiments using D₂O and H₂¹⁸O revealed that the M + 2 signal was predominantly derived from double deuterium substitution, with an abundance difference spanning 13–81 folds. Phenol exhibited the highest M + 1 abundance (3.947) due to the full exposure of its exchangeable hydrogen sites, while its M + 2 abundance ranked second only to that of 2-methylphenol. For 2-methylphenol, the hyperconjugation effect of the ortho-methyl group activated the phenolic structure, leading to the highest M + 2 abundance among all products (M + 2/M + 1 = 2.3). In contrast, 3-methylphenol showed relatively low abundances (M + 2/M + 1 = 1.67) because the meta-methyl group lacked activating effects and introduced steric hindrance. For guaiacol, the steric hindrance of the methoxy group completely overshadowed its electronic activation effect, resulting in the lowest M + 2 abundance (1.545). CD₃OD tracing experiments and the absence of detectable M + 3 peaks confirmed that the methyl groups in 2-methylphenol and 3-methylphenol were entirely endogenous to the structural units of lignin itself. By precisely tracking the migration pathways of hydrogen and oxygen, this study revealed that hydrogen transfer dominated the pyrolysis process, while oxygen transfer was hindered and methyl groups exhibited endogenous characteristics. These findings establish a mechanistic foundation for designing efficient catalysts tailored to lignin pyrolysis and for rationally steering product selectivity. Full article

Soil cadmium (Cd) pollution poses a significant threat to rice production and food safety. Although lime amendment is known to reduce Cd bioavailability in soils, the optimal growth stage for its application remains unclear. This study employed pot experiments with the rice cultivar Wuyouhuazhan as the test material to investigate the effects of lime (Ca(OH)₂) application during four critical rice growth stages, namely seedling (LS), tillering (LT), booting (LB), and filling (LF), on Cd availability, soil properties, and Cd accumulation in rice. Results showed that lime application at all stages significantly reduced soil-available Cd by 53–63%, primarily by promoting the transformation of exchangeable Cd into more stable residual forms. Lime also increased biomass across rice tissues by 1–153%, with the most pronounced effects observed when applied at the seedling stage. Following lime application at different stages, Cd concentrations in all rice tissues showed a decreasing trend. Compared to CK (without lime application), Cd concentrations decreased by 2–26% in roots, 33–80% in stems, and 8–62% in grains. Among the treatments, LS was the most effective in reducing Cd levels, while LT, LB, and LF exhibited progressively weaker reductions. Structural equation modeling indicated that soil pH and stem Cd concentrations were key factors influencing grain Cd accumulation. These findings demonstrate that lime application at the early seedling stage is most effective in mitigating Cd uptake by rice, providing a practical strategy for safe rice production in Cd-contaminated soils. Full article

Sustainable land use requires precise monitoring of soil pollution, yet accurately predicting the spatial distribution of heavy metals often relies on post hoc accuracy comparisons with limited a priori diagnosis. To address the challenge of cost effective environmental monitoring, we conducted a PRISMA guided systematic review (2000–2024) and synthesized 135 studies to develop a mechanism-informed, context aware method selection framework. Evidence revealed three regularities: (i) element–driver coupling is structured (Pb/Cd/Zn predominantly anthropogenic; Cr/Ni geogenic; As/Hg mixed), with dominant influence scales from local to regional; (ii) model performance hinges on alignment between algorithmic assumptions, and context hybrid machine learning models integrating multi-source covariates tend to excel under strong, non-stationary anthropogenic heterogeneity, whereas kriging variants are more robust when geogenic continuity holds; and (iii) applicability is jointly constrained by environmental context, data foundations, and management objectives. Building on these insights, we propose a three-step decision workflow—goal definition, contextual diagnosis, and method matching. This framework serves as a decision support tool that shifts selection from trial and error to a priori alignment, optimizing resource allocation and enhancing the reliability of pollution assessments for sustainable soil remediation and policymaking. Full article

Phytochelatin synthase (PCS) is crucial for synthesizing phytochelatins, cysteine-rich peptides vital for heavy metal detoxification in plants. Potato, a key staple crop in China, faces risks from soil heavy metal contamination, yet the genes involved in its detoxification, particularly PCS genes, remain underexplored. This study systematically identified and characterized the StPCS gene family in potato using genomic databases, uncovering five StPCS members distributed across three of the 12 potato chromosomes. Phylogenetic analysis classified StPCS proteins into three clades, while gene structure and motif analyses revealed high conservation in domain organization. Promoter region investigations identified stress-responsive elements in nearly all StPCS genes. Under cadmium (Cd) stress conditions, qPCR analysis indicated a significant upregulation of StPCS1 (5.73-fold) and StPCS2 (1.61-fold) transcript levels after 21 days compared to the control, whereas no obvious differences were observed at 7 days post-stress. Subsequent functional verification in yeast revealed that StPCS1 overexpression markedly improved Cd tolerance in transgenic yeast. In addition, analysis of cis-acting elements in the StPCS gene promoter combined with qPCR verification under MeJA and ABA stress conditions suggested that StPCS1 might be involved in Cd stress responses in potato through certain hormone signaling pathways. This study represents the first comprehensive analysis of the StPCS gene family in potato, clarifying its structural characteristics and characterizing the function of StPCS1 as a long-term Cd stress-responsive gene, which lays a solid foundation for investigating its role in heavy metal detoxification. Full article

Adipose tissue macrophages (ATMs) are key mediators of obesity-induced inflammation and insulin resistance. However, the contribution of lysosomal dysfunction to ATM inflammatory activation remains poorly defined. Here, we characterized lysosomal structural and functional alterations in ATMs during obesity and examined whether pharmacological restoration of lysosomal function using 2-hydroxypropyl-β-cyclodextrin (HPβCD) ameliorates metabolic inflammation. In diet-induced obese C57BL/6J male mice, adipose tissue exhibited increased lysosomal abundance, accompanied by reduced cathepsin L+V expression, modestly increased lysosomal acid lipase levels, and decreased expression of transcription factor EB (TFEB), a master regulator of lysosomal biogenesis. Despite expanded lysosomal content, ATMs displayed impaired lysosomal acidification, indicating functional lysosomal dysfunction. Intraperitoneal administration of HPβCD for two weeks significantly improved glucose tolerance and insulin sensitivity without affecting body weight. Flow cytometric analysis revealed reduced pro-inflammatory M1 ATMs and CD8⁺ T lymphocytes in visceral adipose tissue, whereas immune cell populations in subcutaneous adipose tissue, blood, and spleen remained unchanged. In vitro, HPβCD suppressed pro-inflammatory gene expression in both classically and metabolically activated macrophages and attenuated inflammatory responses induced by lysosomal stressors, including bafilomycin A1 and chloroquine, while restoring TFEB expression. Collectively, these findings demonstrate that obesity is associated with lysosomal dysfunction in ATMs and that restoration of lysosomal function alleviates adipose tissue inflammation and metabolic dysfunction, highlighting lysosomal regulation in ATMs as a potential therapeutic target for obesity-associated metabolic diseases. Full article

Circular RNA (circRNA) has emerged as a promising vector for drug delivery because, unlike linear mRNA, it does not require costly chemical modifications and offers greater stability and sustained expression in cells. Lacking the canonical 5′ cap structure, circRNA relies primarily on internal ribosome entry sites (IRES) to initiate translation, but IRES-mediated initiation is less efficient than cap-dependent translation. To overcome this limitation, we devised a dual-IRES strategy that introduces a second IRES to drive translation of the coding sequence (CDS). By testing several IRES elements known for high translational activity, this study shows that IRESs derived from the EMCV (Encephalomyocarditis virus) family can enhance expression when placed at the 3′ of the CDS, in coordination with the 5′ EMCV-derived IRES. The optimal dual-IRES combinations identified in this study display compatibility with two different coding sequences, offering a useful strategy to enhance circRNA translation. Full article

Detecting minute defects, such as spurs on the surface of a Printed Circuit Board (PCB), is extremely challenging due to their small size (average size < 20 pixels), sparse features, and high dependence on circuit topology context. The original Mosaic data augmentation method faces significant challenges with semantic adaptability when dealing with such tasks. Its unrestricted random cropping mechanism easily disrupts the topological structure of minute defects attached to the circuits, leading to the loss of key features. Moreover, a splicing strategy without domain constraints struggles to simulate real texture interference in industrial settings, making it difficult for the model to adapt to the complex and variable industrial inspection environment. To address these issues, this paper proposes a Context-aware and Domain-consistent Mosaic (CD-Mosaic) augmentation algorithm. This algorithm abandons pure randomness and constructs an adaptive augmentation framework that synergizes feature fidelity, geometric generalization, and texture perturbation. Geometrically, an intelligent sampling and dynamic integrity verification mechanism, driven by “utilization-centrality”, is designed to establish a controlled sample quality distribution. This prioritizes the preservation of the topological semantics of dominant samples to guide feature convergence. Meanwhile, an appropriate number of edge-truncated samples are strategically retained as geometric hard examples to enhance the model’s robustness against local occlusion. For texture, a dual-granularity visual perturbation strategy is proposed. Using a homologous texture library, a hard mask is generated in the background area to simulate foreign object interference, and a local transparency soft mask is applied in the defect area to simulate low signal-to-noise ratio imaging. This strategy synthesizes visual hard examples while maintaining photometric consistency. Experiments on an industrial-grade PCB dataset containing 2331 images demonstrate that the YOLOv11m model equipped with CD-Mosaic achieves a significant performance improvement. Compared with the native Mosaic baseline, the core metrics mAP@0.5 and Recall reach 0.923 and 86.1%, respectively, with a net increase of 8.3% and 8.8%; mAP@0.5:0.95 and AP_small, which characterize high-precision localization and small target detection capabilities, are improved to 0.529 (+3.0%) and 0.534 (+3.3%), respectively; the comprehensive metric F1-score jumps to 0.903 (+6.2%). The experiments prove that this method effectively solves the problem of missed detections of industrial minute defects by balancing sample quality and detection difficulty. Moreover, the inference speed of 84.9 FPS fully meets the requirements of industrial real-time detection. Full article

The rapid progress of remote sensing (RS) and computer vision has greatly advanced change detection (CD), and hybrid architectures combining Transformers and convolutional neural networks (CNNs) have shown strong potential in recent years. Nevertheless, reliable CD for very high-resolution (VHR) imagery remains challenging due to large appearance variations across acquisition times, complex background clutter, and target structural diversity. These factors often hinder the modeling of fine edge textures, the maintenance of feature continuity, and the suppression of false changes caused by illumination fluctuations. To address these issues, this paper proposes a Cross-layer Feature Fusion Framework (CLFF) that achieves more accurate and stable change detection by explicitly enhancing the collaborative fusion capability of multi-layer features. The core component of this framework is the Multi-level Interaction Perception Block (MP-Block), which organizes effective interactions among features of different semantic levels. Based on the embedded Multi-branch Interaction Fusion Mechanism (MIFM), the MP-Block accomplishes collaborative refinement and reorganization of cross-layer features through two parallel paths for feature reconstruction and recalibration: the Response-aware Feature Reconstruction Branch (RFRB) and Adaptive Channel Group Fusion Branch (ACGF). Additionally, a lightweight position-aware attention module is introduced to adaptively modulate spatial responses, further suppressing background interference and highlighting key information related to changes. This method effectively mitigates the limitations of traditional CNNs, such as limited receptive fields and insufficient multi-layer feature interaction, while significantly enhancing the ability to collaboratively model multi-layer contextual information. To verify its effectiveness, systematic experiments were conducted on four widely used change detection benchmark datasets: LEVIR, WHU, SYSU and HRCUS. The results show that, compared to corresponding baseline models, CLFF achieves performance improvements of 1.35%, 2.78%, 3.54% and 4.85% in the IoU metric, respectively. Full article

Aiming at the differences in spatial spectral attributes between forested land and cultivated land on remote sensing images, and the deficiencies of existing remote sensing change detection methods that are difficult to capture fine edge structures and distinguish pseudo changes, this paper introduces an Edge Enhanced Hierarchical Dual Gated Change Detection (EHDCD) model for forested land and cultivated land, aiming to meet the demand for representing the complex features of these two land types. The model designs an Edge Enhanced Channel Attention Module (EECA) to strengthen the edge recognition ability and suppress the noise interference; proposes a High-Low Level Dynamic Adaptation Strategy (HiLo) to realize the balanced expression of detail information and semantic features; and constructs a Dual Gated Feature Compensation Module (DGFM) to effectively reduce the misdetection rate of change detection. Experiments show that the F1 scores of the model on the self-constructed forest and agricultural dataset FC-CD and public datasets CLCD and SYSU-CD reach 89.06%, 83.37%, and 85.06%, respectively, which can more accurately support the dynamic monitoring applications of forest land and cropland. Full article

We present an optical deformation sensor additively manufactured via an embedded printing process that enables the direct integration of colloidal quantum dots into multimode silicone (PDMS) waveguides. The sensor consists of two parallel waveguide strands, one of which is locally functionalized with CdSe/CdS quantum dots serving as fluorescent emitters. When narrow-band UV light at 405 nm is coupled into the non-functionalized strand, structural deformation alters the conditions of total internal reflection, thereby changing the optical interaction between both strands. This leads to a deformation-dependent variation in the fluorescence shift-affected intensity ratio, which serves as a self-referenced signal for angle determination. Using ratiometric evaluation, angular deflections of up to 9.5° are detected with a resolution below 1° ($2\sigma$ confidence), representing the performance of an initial functional prototype. The embedded printing process allows the voxel-wise adjustment of the material composition within a viscoplastic support medium and thus the spatially resolved integration of quantum dot-functionalized silicone. Attenuation losses of $0.81\pm 0.02\mathrm{dB}/\mathrm{cm}$ at 625 nm confirm the optical suitability of the printed waveguides. This approach combines optical sensing and structural flexibility within a single manufacturing step and establishes a pathway toward fully integratable deformation-sensing elements for soft robotic and wearable systems. Full article

Cadmium (Cd) contamination in agricultural soils severely impairs plant growth, disrupts microbial communities, and threatens food safety due to its high toxicity and mobility. Conventional remediation methods are often expensive and environmentally unsustainable. In contrast, plant–microbiome interactions offer an eco-friendly solution to reduce Cd accumulation and improve plant growth. Arbuscular mycorrhizal fungi (AMF) and mycorrhiza helper bacteria (MHB) are known to improve plant growth and resilience in Cd-contaminated soils. However, the mechanisms by which AMF and MHB co-inoculation could reduce soil Cd contamination by altering the rhizosphere fungal community remain unclear. This study aimed to evaluate how co-inoculation with AMF (Funneliformis mosseae) and MHB (Alcaligenes faecalis) affects plant Cd uptake and soil Cd content, and how it reshapes the cucumber rhizosphere fungal community. A greenhouse experiment was conducted with four treatments: CK (no inoculation), Fm (AMF inoculation), Af (MHB inoculation), and FA (AMF + MHB co-inoculation). Co-inoculation with AMF and MHB (FA) significantly reduced Cd concentrations in both plant tissues and soil. Fungal communities were profiled using Illumina MiSeq sequencing of the ITS region, and diversity metrics and structural changes were assessed through PCoA and DESeq2. Co-inoculation (FA) significantly reshaped the fungal community, increasing the relative abundances of beneficial phyla such as Mortierellomycota, Basidiomycota and Glomeromycota, while decreasing the abundance of potentially pathogenic Ascomycota. Double inoculation with AMF and MHB also enhanced fungal diversity, as measured by the Simpson index, and enriched specific OTUs. This study uncovers the mechanisms through which AMF–MHB co-inoculation reduces Cd concentrations in both plants and soil by altering the cucumber rhizosphere fungal community composition. These findings demonstrate that AMF–MHB co-inoculation is an effective, biologically driven strategy for remediating Cd-contaminated soils by restructuring cucumber rhizosphere fungal communities. Full article

Background/Objectives: Nature has evolved millions of venom-derived peptides with diverse biological functions, a substantial fraction of which target complex membrane proteins such as G-protein-coupled receptors and ion channels. Many of these peptides are stabilized by multiple disulfide bonds, endowing them with exceptional structural stability and favorable pharmacological properties. Methods: Leveraging this natural diversity, we developed a robust venom peptide therapeutics discovery system built on phage display technology and constructed a library using approximately 482 venom-derived scaffolds. The library design was guided by a machine learning (ML) model capable of predicting mutation-tolerant residues that preserve peptide foldability, maximizing structural integrity and sequence diversity. Results: The resulting VCX library was evaluated through screening against four diverse targets (CD47, DLL3, IL33, and P2X7R), yielding strong binders for all four, a success rate of 100%. Furthermore, by integrating high-throughput recombinant expression of thioredoxin–venom fusion proteins along with ML-assisted affinity maturation, we rapidly identified potential leads for DLL3 binders. Conclusions: This venom-based discovery platform offers significant advantages in both functionality and developability compared with conventional peptide discovery approaches. By combining natural structural diversity, ML-guided design, and recombinant expression, it enables efficient identification of “antibody-like” binders with molecular weights much smaller than those of antibodies. Consequently, it provides a powerful strategy for developing next-generation peptide therapeutics targeting challenging protein–protein interactions and complex membrane proteins. Full article

Background: Folate is essential for one-carbon metabolism, yet deficiency remains common in non-fortified populations. Bitter-taste-receptor genetics may influence vegetable intake and thus folate status, but the cumulative impact of sensory genetics, diet, and sociodemographic factors is unclear. This study aimed to investigate how taste-related genetic variants, aggregated into a polygenic score (PGS), together with dietary behavior and sociodemographic factors, modulate serum folate levels in a Hungarian adult population, including Roma ethnic minority participants. Methods: In a cross-sectional sample of 626 adults (312 from the Hungarian general population and 314 from the Roma ethnic minority), serum folate was quantified by chemiluminescent immunoassay, and eight taste-related single-nucleotide polymorphisms (SNPs) were genotyped. A four-SNP PGS (TAS2R19 rs10772420, OR10G4 rs1527483, TRPV1 rs8065080, and CD36 rs1761667) was optimized via the stepwise method (ΔR² criterion, FDR q < 0.05). Multivariable linear regression was used to assess associations with continuous folate, and logistic models were used to evaluate deficiency risk (≤13 µmol/L; area under the curve, AUC). Interaction terms were tested for effect modification by education and vegetable intake, and mediation pathways were examined by structural equation modeling with 1000 bootstrap replications. Results: TAS2R19 rs10772420 was found to be the strongest predictor of serum folate level. This effect remained significant even after adjusting for vegetable intake (β = 1.12 nmol/L; p = 0.003), suggesting a persistent genetic association independent of vegetable intake. The taste-related PGS exhibited a significant dose–response relationship with folate levels (p < 0.001) but had only modest discriminatory power for deficiency (AUC = 0.569). Higher educational attainment amplified the associations between the PGS and folate levels (p for interaction < 0.05), whereas vegetable intake did not mediate genetic effects. The associations were consistent across Hungarian general and Roma population subgroups. Conclusions: Bitter-taste-receptor genetics are associated with serum folate levels in a pattern not substantially mediated by self-reported vegetable intake, and this influence is further modified by education. These findings support the development of genome-informed, culturally tailored nutrition strategies for non-fortified populations. Full article