Search Results (1,261)

Magnetic anomaly detection is vulnerable to environmental noise and insufficient prior target information, making non-periodic anomaly signals difficult to detect at low-signal-to-noise-ratio (SNR) conditions. This paper proposes a detection method based on a multi-parameter-constrained mirror dual-branch biased monostable stochastic resonance (SR) system. Nonlinear odd-order bias terms are introduced into the conventional biased monostable potential function to build a multi-parameter-controllable SR model. This improves regulation of potential-well width, depth, and wall morphology, enhancing noise-energy utilization and responses to non-periodic features. Considering peak-type, valley-type, and bipolar anomaly morphologies, a mirror dual-branch SR structure is developed to cooperatively detect features with different polarities. To preserve temporal waveforms and time–frequency structures during parameter optimization, a composite metric combining the correlation coefficient and wavelet-domain image structural similarity index is constructed. Multi-fidelity robust Bayesian optimization is used to obtain a unified robust parameter set for the magnetic anomaly signal family. Experiments with simulated colored noise and measured geomagnetic noise show that the proposed method effectively recovers magnetic anomaly features under strong noise. At −19 dB SNR, its detection probability remains above 80%. Compared with orthogonal basis function decomposition, empirical mode decomposition, and complete ensemble empirical mode decomposition with adaptive noise, the method achieves better noise suppression, feature preservation, and detection performance under low-SNR conditions. Full article

Plant architecture optimization is central to high-yield crop breeding. The number of branches in Brassica napus (B. napus) determines canopy structure, light use efficiency, and yield. The transcription factor BRANCHED1 (BRC1) integrates multiple signals to negatively regulate branching. This study characterized five BnaBRC1 homologs in B. napus via bioinformatics, expression profiling, and CRISPR/Cas9 editing. All BnaBRC1s contain a conserved TCP domain, and their promoters are enriched with light-responsive and hormone-responsive cis-acting elements. BnaA01.BRC1 is highly expressed in leaves, stem nodes, roots, and siliques, and its transcription is coordinately regulated by low light, sucrose, and exogenous cytokinin, and gibberellin (GA) signals. Functional analysis showed that overexpression of BnaA01.BRC1 suppressed branching, whereas CRISPR/Cas9-mediated knockout of BnaBRC1 substantially increased branch number. In basal axillary buds, high BnaBRC1 expression was accompanied by upregulation of GA-inactivating GIBBERELLIN 2 OXIDASEs and the GA signaling negative regulator SPINDLY, and no direct interaction was detected between BnaA01.BRC1 and DELLA proteins, suggesting indirect regulation of branching via GA homeostasis. Collectively, this study demonstrates the pivotal role of BnaA01.BRC1 in branching regulation and provides a genetic resource and theoretical basis for plant architecture optimization and multi-branch germplasm innovation in B. napus. Full article

Circular RNAs (circRNAs) are key regulators in the onset and progression of complex diseases, offering promise as diagnostic and prognostic biomarkers. However, most putative circRNA–disease associations remain experimentally unverified, largely due to the cost and time demands of wet-lab approaches. To bridge this gap, we present STRCDA (Sparse Topological Representation learning for CircRNA–Disease Associations). The pipeline first constructs fused similarity profiles for circRNAs and diseases by integrating diverse biological attributes. These initial matrices are then refined via random walk with restart to capture local features. Subsequently, a sparse-constrained dual-branch graph autoencoder extracts holistic topological embeddings from the refined local features and the known interaction network. Finally, an XGBoost classifier scores potential circRNA–disease pairs. On the CircR2Disease dataset, STRCDA achieves an AUC of 0.9771 and an AUPR of 0.9826 under five-fold cross-validation. Notably, 18 of the top 20 predicted associations were confirmed by independent experimental evidence, highlighting STRCDA’s efficacy as a robust tool for uncovering circRNA function in disease. Full article

Climate change has intensified the occurrence of combined abiotic stresses such as drought, salinity, heat, and waterlogging, thereby threatening cereal productivity and global food security. Root systems play a central role in plant adaptation to these interacting stresses by regulating water uptake, ion balance, nutrient acquisition, and stress signaling. However, many previous studies have primarily focused on individual stress factors rather than integrated stress environments. This review synthesizes current knowledge regarding root-mediated adaptive mechanisms in cereal crops under combined abiotic stresses, with emphasis on barley (Hordeum vulgare), wheat (Triticum aestivum), and oats (Avena sativa). The review highlights how root system architecture, including root depth, branching density, and aerenchyma formation, contributes to stress resilience under interacting environmental conditions. Physiological and molecular mechanisms involving ion transporters, aquaporins, transcription factors, and auxin-regulated root plasticity are also discussed. In barley, deeper and steeper root systems improve water acquisition under combined drought and heat stress, while wheat genotypes carrying the HKT1;5 allele exhibit enhanced sodium exclusion under drought–salinity interactions. Oats respond to waterlogging and salinity through adventitious root formation and enhanced oxygen transport. Overall, this review emphasizes the importance of root-targeted approaches for improving cereal adaptation under increasingly complex multi-stress environments. Full article

Background: The residues of Camphora officinarum c.t. borneol after essential oil extraction are often discarded, causing resource waste and environmental pollution, while the edible fungi industry is facing a shortage of traditional cultivation substrates. Methods: This study integrated UPLC-MS/MS and GC-MS to comprehensively profile volatile and non-volatile metabolites. Samples included fresh branches and leaves (ZSXY) and residues after steam distillation (ZSZL), boiling combined with distillation (ZSSZ), and sun-drying after distillation (ZSSG). Results: In total, 2454 metabolites across 25 categories were detected. PCA revealed clear separation between fresh samples and all processed samples, with ZSZL and ZSSZ exhibiting similar metabolic profiles that were distinctly separated from ZSSG. Compared with ZSXY, most metabolites decreased after processing. ZSSG exhibited the strongest degradation, with 1408 down-regulated and only 146 up-regulated metabolites, and total terpenoid content decreased by 92.27%. ZSZL retained the highest levels of nutrients (e.g., amino acids and nucleotides) and bioactive compounds (e.g., phenolic acids, flavonoids, terpenoids), with 322 up-regulated metabolites. Among the specific comparisons, 113, 212, and 487 differentially accumulated metabolites were identified in ZSXY vs. ZSZL, ZSXY vs. ZSSZ, and ZSXY vs. ZSSG, respectively. KEGG enrichment revealed distinct pathway alterations: monoterpenoid degradation and biosynthesis pathways were activated in ZSZL, nitrogen metabolism-related pathways were disturbed in ZSSZ, and both limonene and pinene degradation and aminoacyl-tRNA biosynthesis pathways were enriched in ZSSG. Conclusions: Based on metabolomic profiling, steam distillation residues exhibited favorable retention of nutrients and bioactive compounds, whereas sun-drying led to excessive metabolite loss. These findings support the valorization of processing residues and promote circular agriculture. However, whether these residues can serve as effective substrates for edible fungi cultivation remains to be tested in dedicated cultivation trials. Full article

Tryptophan (TRP) metabolism has emerged as a critical interface linking inflammation, immune regulation, oxidative stress, and cellular energetics. The kynurenine pathway, the predominant route of TRP degradation, is highly responsive to inflammatory stimuli and generates a spectrum of bioactive metabolites with divergent and context-dependent biological effects. Indoleamine 2,3-dioxygenase 1 (IDO1)-mediated TRP catabolism integrates immune activation with downstream metabolic signaling, influencing redox homeostasis, endothelial function, and mitochondrial energetics, in part by regulating nicotinamide adenine dinucleotide (NAD⁺) synthesis. Alterations in TRP metabolism are consistently observed across cardiometabolic diseases, including obesity, type 2 diabetes (T2D), atherosclerosis, myocardial infarction (MI), and heart failure with preserved ejection fraction (HFpEF), where they are associated with disease severity and adverse outcomes. Importantly, emerging data suggest that cardiometabolic phenotypes are determined not by pathway activation alone, but by the relative distribution of flux across downstream metabolic branches. Depending on the tissue compartment and stage of the disease, different biological effects may be contributed by redox-active kynurenine 3-monooxygenase (KMO)/3-hydroxykynurenine (3-HK)/quinolinic acid (QA) pathways, 3-hydroxyanthranilic acid (3-HAA)-mediated lipid and inflammasome regulation, microbiome-derived indoles, and NAD⁺-generating pathways. This review synthesizes current evidence using a branch-specific and context-dependent framework. We discuss the utility and limitations of the kynurenine-to-tryptophan ratio (KTR) as an upstream biomarker, the need for downstream metabolite panels, and therapeutic opportunities aimed at pathway modulation rather than broad inhibition. Future studies integrating temporal profiling, spatial and cell-specific approaches, large-animal models, and pathway-informed clinical trials will be essential to define causal mechanisms and enable precision therapeutic translation. Full article

As a significant branch of nanotechnology, carbon-based nanomaterials (CNMs) have garnered extensive attention for their broad application potential in agriculture, attributed to their unique structural and physicochemical properties. They are considered one of the important tools for promoting sustainable agricultural development. Among them, carbon nanotubes (CNTs), owing to their excellent mechanical properties, electrical characteristics, and high specific surface area, have recently attracted considerable interest in plant growth regulation and the development of agricultural inputs. This article systematically reviews the research progress of CNMs, especially CNTs, in agriculture. Firstly, it outlines the structural characteristics and physicochemical properties of different types of CNMs. Subsequently, from a plant physiological perspective, it focuses on analyzing their mechanisms of action in nutrient uptake, photosynthesis regulation, and antioxidant defense. Based on this, it summarizes the application progress of CNMs in plant growth promotion, nano-pesticide and fertilizer delivery, and precision agriculture sensing. Furthermore, this article emphasizes the dose-dependent biphasic effect (hormesis) of CNMs on plants: at relatively low, system-specific doses, they can promote growth and enhance stress resistance, whereas at higher or supra-optimal doses, they may induce oxidative stress, cellular damage, and photosynthesis inhibition. However, significant variations in responses exist depending on the material type, physicochemical properties, and plant species, and a unified understanding of the underlying mechanisms has not yet been established. Finally, this article discusses green synthesis strategies for CNMs and their potential ecological risks and points out that future research should focus on key issues such as precise dose regulation, long-term environmental behavior, and multi-scale mechanism analysis. This review aims to provide a systematic reference for understanding CNM–plant interactions and their safe application in agriculture. Full article

The FAR-RED IMPAIRED RESPONSE 1 (FAR1) and FAR-RED ELONGATED HYPOCOTYL 3 (FHY3) transcription factors, together with other members of the FAR1-RELATED SEQUENCE (FRS) and FRS-RELATED FACTOR (FRF) families, represent a striking example of transposable element domestication in plants. Derived from ancient Mutator-like element (MULE) transposases, these proteins have been repurposed as transcriptional regulators throughout the plant kingdom. FHY3 and FAR1 were first identified in Arabidopsis thaliana as positive regulators of phytochrome A (phyA) signaling. They participate in the coordination of light signaling with the circadian clock, chlorophyll biosynthesis, hormone pathways, stress responses, flowering time, shoot branching, leaf senescence, seed dormancy, and phosphate homeostasis. At the molecular level, FHY3 and FAR1 regulate gene expression mainly by binding to the conserved FHY3/FAR1-binding site, FBS, with the sequence CACGCGC, in the promoters of target genes. They also act through protein interactions with key signaling regulators, including HY5, PIFs, EIN3, TOC1, and SPL transcription factors. In this review, we summarize the molecular basis of FHY3/FAR1 gene family function, discuss the roles and mutant phenotypes of characterized family members, and highlight recent advances from other plant species beyond Arabidopsis. Collectively, this gene family illustrates how domesticated transposase-derived proteins have evolved into key regulators of plant development and environmental adaptation. Full article

To address critical challenges in maritime ship detection within complex surveillance imagery, including severe background interference, extreme scale variation, and fine-grained category confusion, this study proposes Maritime Scene Collaborative You Only Look Once (MSC-YOLO), an improved detection model for fixed-location maritime surveillance scenarios. First, a Maritime Scene Adaptive Attention Module (MSAM) is introduced to suppress water-surface clutter and enhance structurally informative ship responses through bidirectional feature regulation, thereby strengthening feature representation in background-complex scenes. In addition, a Scale-aware Dynamic Head (SDA-Head) is designed by integrating deformable convolution with parallel scale-aware prediction branches to improve detection coverage for vessels under pronounced scale variation. Furthermore, a Class Prototype Guided (CPG) module is developed, incorporating class-level prototypes and category-similarity priors to improve the discriminative representation of visually similar ship categories and component states. Experimental results on the constructed maritime surveillance dataset show that MSC-YOLO achieves 0.9723 mAP@50, 0.7315 mAP@50–95, 0.8903 Precision, and 0.9883 Recall. Compared with YOLOv11n, the proposed model improves mAP@50 by 17.77%, Precision by 21.82%, and Recall by 8.16%, indicating clear advantages in target discovery, clutter robustness, and difficult-target coverage in complex maritime surveillance scenes. Visualization and confusion-matrix analyses further show reduced background interference and stronger class-wise discrimination. Overall, MSC-YOLO demonstrates effective and reliable performance for complex maritime surveillance scenarios. Full article

Skin health depends on the coordinated maintenance of barrier integrity, immune homeostasis, redox balance, microbial ecology, and systemic metabolic status. Among dietary constituents, polysaccharides have attracted increasing attention because they represent a structurally heterogeneous class of complex carbohydrates whose biological behavior is shaped by molecular weight, monosaccharide composition, glycosidic linkage patterns, branching, higher-order conformation, and physicochemical properties. However, many current skin-related studies remain primarily phenomenon-driven, with insufficient attention to how specific structural features influence biological function and dermatologic relevance. From a structure–function perspective, key structural features of dietary polysaccharides may influence several skin-relevant biological processes, including microbiota-associated signaling, immune regulation, barrier homeostasis, oxidative balance, and extracellular matrix protection. The relevance of these structure-linked functions differs across dermatologic contexts: it appears most direct in photoaging, more conditional in atopic dermatitis, and relatively indirect in psoriasis, whereas wound-repair-related settings are less closely aligned with strict dietary relevance. Current evidence therefore supports structure–function associations more strongly than direct associations between specific structural features and dermatologic outcomes. Dietary polysaccharides are not functionally interchangeable in skin-related contexts, and their skin-related effects depend on structural background, disease setting, and mode of application. Where non-dietary evidence is discussed, it serves primarily as mechanistic or translational contextualization rather than as a basis for nutritional recommendation. Clarifying these relationships may support future mechanistic research and facilitate more rational nutritional applications of dietary polysaccharides in skin health. Full article

Hyperspectral image (HSI) classification enables precise classification of land-cover types from rich spectral and spatial information. Recent methods combine convolutional neural network (CNN) and Mamba branches to exploit their complementary local and global modeling capabilities for HSI classification. However, most of these methods treat all spectral channels uniformly in feature fusion, failing to account for the discriminability differences across spectral bands. Moreover, most methods rely on a single classification head at the final layer, which may lead to vanishing gradients in shallow layers. To address these limitations, a spectral group-wise gated CNN–Mamba network with cross-stage mutual distillation, called SGGCMNet, is proposed. To address the first limitation, a CNN–Mamba spectral group-wise gating block (CMSB) is designed at the feature-fusion level. Specifically, the CMSB partitions channels into multiple sub-groups along the spectral dimension. Each sub-group learns its own fusion weights that balance local spectral–spatial cues produced by a CNN pathway with long-range context produced by a Mamba pathway. To address the second limitation, two loss-level optimization strategies are proposed jointly: A progressive deep supervision strategy with uncertainty-based dynamic weighting is proposed to attach classification heads at all network stages. A temperature-regulated cross-stage mutual-distillation mechanism is further designed to enable bidirectional knowledge transfer among classification heads at different stages. On three benchmark HSI datasets, SGGCMNet achieves state-of-the-art accuracy. Full article

NG2 glia, also known as oligodendrocyte progenitor cells, represent a unique population of glial cells characterized by dynamic morphology and the ability to extend branched processes that actively contact neurons and other cellular elements. These structural and functional interactions enable NG2 glia to contribute to the regulation of axonal excitability, electrical activity, and axonal architecture. Unlike most other glial cells, NG2 glia receive direct synaptic input from neurons and can generate action potentials, defining their distinctive physiological status. A particularly important feature of this cell population is the expression of the chondroitin sulfate proteoglycan NG2/CSPG4, which serves as a key molecular marker and plays an essential role in intercellular interactions. Following spinal cord injury (SCI), NG2 glia rapidly become activated, undergo phenotypic changes, and engage in extensive interactions with neurons, astrocytes, microglia, and endothelial cells. These interactions form a complex regulatory network that influences both the severity of secondary injury and the effectiveness of remodeling and repair processes. Mechanisms of particular importance include the secretion of chondroitin sulfate proteoglycans and alterations in extracellular matrix properties. Finally, this review highlights potential therapeutic approaches aimed at modulating NG2 glial activity and their intercellular interactions. The focus is on strategies designed to reduce the inhibitory effects of proteoglycans while enhancing the remyelinating and neuroprotective potential of these cells, thereby opening new perspectives for regenerative therapies after SCI. Full article

The gut microbiota produces chemically diverse metabolites whose levels fluctuate depending on the time of day, driven by bidirectional coupling between host intestinal circadian clocks and intrinsic microbial oscillators. Although short-chain fatty acids have received the most attention as microbial circadian effectors, a broad class of metabolites, including secondary bile acids, indole derivatives, and branched-chain fatty acids, engage distinct epithelial receptors and transcriptional programs through mechanisms that are, to varying degrees, subject to circadian regulation. However, the mechanisms by which these metabolite classes collectively regulate barrier integrity, mucosal immune tone, and stem cell-driven renewal, as well as the consequences of their rhythmicity loss under circadian misalignment, have not been systematically reviewed. This review constructs a mechanistic framework linking microbial metabolite rhythmicity to the circadian regulation of intestinal epithelial homeostasis and evaluates dietary and probiotic interventions that modulate this axis as chronobiotic strategies. Convergent mechanisms, unresolved questions, and translational opportunities are identified across in vitro, preclinical, and clinical evidence. Full article

Wheat (Triticum aestivum L.) is a crucial global food crop that plays a central role in agricultural production and food security. The spike number per unit area (SN) is one of the three component factors of grain yield. In this study, we combined the UG-Map with 27 environments of a recombinant inbred line (RIL) population, and mapped a quantitative trait locus (QTL) for SN, QSn-7A-9048, in which the meta-QTL interval contains only one candidate gene, TraesCS7A02G-364700 (TaKMT-7A). Using the CRISPR/Cas9 system, we generated two homozygous mutant lines, aa-1 and aa-2 of TaKMT-7A, which resulted in frameshift mutations, leading to the premature termination of the translation process. The SN values for the wild type (WT), aa-1, and aa-2 were 4.48, 3.43, and 3.48, respectively. Compared with the WT, the SN of the two mutant lines significantly decreased, and no significant differences for grain number per spike (GNS) and thousand-grain weight (TGW) were detected. We also obtained two overexpression (OE) lines of TaKMT-7A, OE-1 and OE-2. The SN values for the negative control (NC), OE-1, and OE-2 were 2.31, 3.33, and 3.00, respectively. Compared with NC, the SN values in the OE lines significantly increased. The phenotypes of the knockout (KO) lines and OE lines demonstrate that TaKMT-7A acts as a positive regulator of SN in wheat. We performed RNA-Seq analysis using young tiller buds from the WT and aa-1 mutant lines at the tillering stage, and a total of 2315 differentially expressed genes (DEGs) were identified. We screened 22 wheat genes, of which 18 orthologous genes have previously been cloned and are associated with branching in rice and Arabidopsis. These genes included nitrogen transporter, amino metabolism, auxin transporter, auxin homeostasis, auxin response, auxin biosynthesis, strigolactone biosynthesis, and repress gibberellin responses. These genes may represent potential downstream targets of TaKMT-7A. Full article

Second-life lithium-ion batteries offer strong potential for sustainable stationary energy storage, but their practical reuse is limited by cell-to-cell heterogeneity, non-uniform heat-generation, and the resulting thermal safety risks. Conventional battery thermal management systems (BTMSs), which rely on fixed and uniformly distributed coolant flow, are not well-suited to the asymmetric thermal behaviour of aged battery packs. In this study, an adaptive liquid-cooling framework with locally regulated branch-level flow allocation is proposed for second-life prismatic LiFePO₄ battery modules. A three-dimensional transient conjugate heat transfer model was developed in COMSOL Multiphysics. The analysis was conducted on a 3 × 3 battery module under nine thermal heterogeneity scenarios, followed by a larger 5 × 4 module to evaluate scalability. The results show that thermal severity depends not only on heat-generation magnitude but also on the spatial arrangement of degraded cells. Under the most critical 3 × 3 configuration, the adaptive BTMS reduced the maximum temperature from 37.16 °C to 28.77 °C, corresponding to a reduction of about 8.38 °C, while limiting the cell-to-cell temperature difference to approximately 1.16 °C. A comparison with a conventional constant-flow cooling configuration in the larger 5 × 4 module further showed that adaptive branch-level coolant redistribution improves thermal uniformity under heterogeneous thermal loading by selectively directing cooling capacity toward thermally stressed regions. The results demonstrate the potential of demand-driven flow allocation as a distributed thermal-management strategy for heterogeneous second-life battery systems. Full article