Search Results (18,400)

Maternal nutrient restriction (MNR) heightens disease susceptibility in offspring through epigenetic modifications that alter the development of essential organs. This study investigates how restriction alters the fetal sheep hepatic methylome and its potential regulatory influence on gene expression. Using a monozygotic twin model generated through embryo splitting, we examined hepatic DNA methylation responses to maternal nutrient restriction (50% vs. 100% NRC nutritional requirements; n = 4 per group) from gestational day (GD) 35 to 135 in pregnant sheep. At GD 135, conceptus (fetal–placental unit) development was assessed; although fetal weight was unaffected (p > 0.10), restricted fetuses exhibited reduced liver mass (p < 0.05). Whole-genome bisulfite sequencing (WGBS) of fetal liver identified 1,636,305 differentially methylated CpG sites (dmCpGs) in the Group-Level Analyses and 42,231 dmCpGs in the Twin-Pair Analyses. At the Group-Level, 40,533 promoter, 126,667 exonic, and 785,381 intronic sites were identified, whereas the Twin-Pair subset contained 1314, 7116, and 22,239, respectively. Site-level shifts and functional enrichment across features highlighted GPCR–cAMP/calcium–PI3K/AKT signaling, phosphoinositide metabolism, ECM/integrin–focal adhesion networks, thyroid hormone signaling, and Rho-family GTPases. These findings indicate that maternal nutrient restriction modifies the fetal hepatic methylome through coordinated signaling, metabolic, and structural reconfigurations that create conditions conducive to metabolic disease. Full article

Cadmium (Cd) toxicity threatens global food security and agricultural sustainability. Transcription factors (TFs) act as master regulators of the complex molecular networks involved in Cd detoxification. This review provides a focused synthesis of the molecular mechanisms governing Cd tolerance in plants, encompassing antioxidant defense, Cd chelation and sequestration, Cd uptake and transport, signal transduction, and damage repair pathways. We highlight the pivotal roles of key TFs in these specific processes, such as OsMYB45 in antioxidant defense, OsIRO2 in regulating chelation and storage, OsNAC5 in modulating Cd transport, and OsE2F in facilitating the repair of DNA and protein damage. Furthermore, we evaluate the potential of harnessing these TF-mediated regulatory mechanisms for developing low-Cd rice varieties. By delineating precise correlations between specific TFs and detoxification pathways, this review proposes actionable molecular strategies to mitigate Cd contamination, thereby contributing to ecological and food safety. Full article

Glutamine metabolism has emerged as one of the most critical bioenergetic and biosynthetic programs sustaining leukemic cell growth, survival, stemness and therapeutic resistance. In both acute and chronic leukemias, including acute myeloid leukemia (AML) and acute lymphoblastic leukemia (ALL), malignant cells display a strong dependency on extracellular glutamine to support mitochondrial respiration, anabolic biosynthesis and redox homeostasis. This dependency is reinforced by oncogenic signaling networks, post-transcriptional metabolic regulation and microenvironmental adaptation within the bone marrow niche. Therapeutic strategies targeting glutamine utilization, including glutaminase inhibition, transporter blockade and enzymatic glutamine depletion, have demonstrated robust antileukemic activity in preclinical models, and early clinical efforts have begun to explore glutamine-directed interventions in myeloid neoplasms. However, metabolic plasticity, microenvironment-derived nutrient buffering and systemic toxicity remain significant limitations to clinical translation. This review provides a detailed synthesis of the biochemical framework of glutamine metabolism in leukemia, the molecular mechanisms enforcing glutamine addiction, the downstream functional consequences on proliferation, redox balance and leukemic stem cell biology, the current landscape of therapeutic strategies and emerging directions aimed at overcoming resistance and improving clinical efficacy. Full article

Pseudorabies (PR) is an acute and highly contagious disease caused by the pseudorabies virus (PRV). This virus has a wide range of susceptible hosts and has caused major economic losses to the global swine industry. While rosmarinic acid possesses broad antioxidant and antiviral properties, its efficacy against PRV has remained unexplored. Therefore, this study aimed to evaluate the anti-PRV activity of rosmarinic acid and to elucidate its underlying mechanism, with a focus on the nuclear factor erythroid 2-related factor 2 (Nrf2) signaling pathway. The results revealed that rosmarinic acid exhibited potent, concentration-dependent antiviral activity in vitro, with a half-maximal inhibitory concentration (IC50) of 0.02654 mg/mL, a half-maximal cytotoxic concentration (CC50) of 0.1043 mg/mL, and a selectivity index (SI) of 3.9. Rosmarinic acid inhibited virus adsorption, entry, and intracellular replication. It also significantly suppressed the expression of the gB protein. In a mouse model, rosmarinic acid treatment (200 mg/kg) significantly enhanced the survival rate to 28.5%. This treatment reduced the viral load in the brain, lungs, kidneys, heart, and spleen. It also alleviated the tissue damage caused by PRV infection. Furthermore, rosmarinic acid counteracted PRV-induced oxidative stress by elevating the activity of the antioxidant factors SOD and CAT and reducing the level of the oxidative factor MDA. Combined network pharmacology and molecular docking analyses predicted the Nrf2 signaling pathway as a key target for rosmarinic acid. Subsequent mechanistic studies confirmed that rosmarinic acid upregulated the expression of the Nrf2, HO-1, GPX, SOD, and CAT genes, as well as Nrf2 and HO-1 proteins, thereby promoting the nuclear translocation of Nrf2. These results identify rosmarinic acid as a promising anti-PRV agent that acts through multi-phase viral inhibition and activation of the Nrf2-mediated antioxidant defense, suggesting its potential as a novel pharmacological strategy against PRV. Full article

Hypera postica (Gyllenhal) is a major pest of alfalfa. We combined mitochondrial COI and CytB gene sequences to characterize the genetic diversity of 20 geographic populations of H. postica across Xinjiang, China, and to elucidate their lineage relationships at both regional and global scales. We found that Nucleotide diversity (Pi) was markedly higher in western Xinjiang populations (Pi > 0.016), specifically Wusu (0.023), Tekes (0.023), Jinghe (0.023), Wenquan (0.021), Bole (0.021), Habahe (0.020), Nilka (0.020), Tacheng (0.019), Toli (0.018), Altay (0.017), Emin (0.016), Xinyuan (0.016), and Zhaosu (0.016), whereas central Xinjiang populations exhibited substantially lower diversity (Pi < 0.014), including Shawan 0.014), Qitai (0.011), Jimsar (0.007), Urumqi (0.004), Hutubi (0.003), Fukang (0.001), and Manas (0.001). Pairwise F_ST analysis revealed pronounced genetic divergence between the western Xinjiang group (Altay, Bole, Wenquan, Tacheng, Emin, Toli, Nilka, Xinyuan, Tekes, Zhaosu) and the central Xinjiang group (Qitai, Urumqi, Fukang, Habahe, Hutubi, Jimsar, Shawan, Manas). At the global level, H. postica can be divided into two major phylogroups: the Western and Eastern lineages. All Xinjiang populations belong to the Eastern lineage. Haplotype network analysis identified two distinct sublineages, western and central Xinjiang, with H2 and H26 as their respective dominant shared haplotypes; both are unique to China. Both maximum likelihood (ML) and Bayesian phylogenetic trees robustly support the central Xinjiang lineage as a distinct clade. Neutrality tests provided strong evidence of recent demographic expansion across the Xinjiang H. postica population as a whole (Fu’s Fs = −21.987, p < 0.05), with particularly pronounced signals in Hutubi (HTB: Tajima’s D = −1.966, Fu’s Fs = −0.781, p < 0.05), Jimsar (JMSE: Tajima’s D = −2.176, Fu’s Fs = −0.962, p < 0.01), and Wenquan (WQ: Fu’s Fs = −11.159, p < 0.01). Our results reveal a clear phylogeographic split within Xinjiang H. postica populations, comprising western and central sub-lineages, with the western sub-lineage likely representing ancestral lineage. The western Xinjiang sub-lineage appears to be shaped primarily by mountainous topography, whereas the central Xinjiang sub-lineage likely results from the combined effects of piedmont plain geography and infection with the endosymbiont Wolbachia strain wHypera4. Full article

Ocimum (basil) is a globally significant medicinal and culinary herb. While its bioactive secondary metabolites are well-studied, the medicinal potential of its abundant primary metabolites (amino acids, vitamins, carbohydrates, steroids) remains largely unexplored. To address this gap, we employed an integrated multi-omics strategy. First, UPLC-MS/MS-based metabolomics quantified primary metabolites across six distinct Ocimum accessions (Ocimum × africanum, Ocimum tenuiflorum, Ocimum gratissimum). Profiling identified 291 primary metabolites, revealing significant interspecific variation, with 273 differential accumulated metabolites (DAMs). Subsequent network pharmacology analysis of 61 high-impact DAMs predicted 516 potential targets. Protein–protein interaction refinement yielded 28 core targets, predominantly integrins (ITGB1, ITGB3, ITGA4, ITGA2B, ITGAV) and kinases (IGF1R, PIK3CA, SRC). Enrichment analysis implicated these targets in focal adhesion, ECM-receptor interaction, and PI3K-Akt signaling pathways. Molecular docking confirmed strong potential binding (binding energy < −7 kcal/mol) between key tripeptides (e.g., Met-Ser-Tyr, Phe-Cys-Gln) and integrin subunits. Antioxidant assays (DPPH, ABTS, FRAP) further showed significant genotypic variation. This study systematically deciphers the primary metabolome of Ocimum and, through a multi-omics approach, reveals novel integrin-mediated mechanisms underpinning its potential therapeutic value, providing a foundation for developing basil-based nutraceuticals and pharmaceuticals. Full article

This study evaluated the effects of dietary supplementation with N-Carbamylglutamate (NCG) on growth performance, immune function, intestinal metabolites, and microbiota in Danzhou chickens. In a 35-day feeding trial, a total of 480 one-day-old female chicks were randomly assigned to a control group (basal diet) and three experimental groups supplemented with 400, 800, or 1200 mg/kg NCG, with 120 chicks in each group (n = 120). The results demonstrated that NCG, particularly at 400 mg/kg, significantly improved growth parameters, including average daily gain and feed conversion ratio, while enhancing immune function by increasing serum levels of immunoglobulins (IgA, IgY) and malate dehydrogenase (p < 0.05). Metabolomic analysis revealed that NCG modulated key pathways such as sphingolipid metabolism and mTOR signaling pathway, leading to significant changes in metabolites including L-arginine, ceramide, and docosahexaenoic acid (p < 0.05). 16S rDNA sequencing indicated that NCG induced structural shifts in the gut microbiota, primarily affecting Bacteroidota and Firmicutes, with several bacterial genera showing strong correlations with the observed metabolic changes (p < 0.05). Mechanistically, NCG promotes growth by facilitating arginine synthesis via the urea cycle and activating the mTOR signaling pathway, while its regulation of sphingolipid metabolism enhances immunomodulatory capacity. In conclusion, NCG enhances feed efficiency and immune competence by orchestrating the gut microbiota-metabolite network, demonstrating its potential for poultry production. Full article

With the increasing penetration of renewable energy sources and power-electronic devices, modern power systems exhibit pronounced wideband oscillation characteristics with large frequency spans, strong modal coupling, and significant time-varying behaviors. Accurate identification and classification of wideband oscillation patterns have therefore become critical challenges for ensuring the secure and stable operation of “dual-high” power systems. Existing methods based on signal processing or single-modality deep-learning models often fail to fully exploit the complementary information embedded in heterogeneous data representations, resulting in limited performance when dealing with complex oscillation patterns.To address these challenges, this paper proposes a multimodal attention-based fusion network for wideband oscillation classification. A dual-branch deep-learning architecture is developed to process Gramian Angular Difference Field images and raw time-series signals in parallel, enabling collaborative extraction of global structural features and local temporal dynamics. An improved Inception module is employed in the image branch to enhance multi-scale spatial feature representation, while a gated recurrent unit network is utilized in the time-series branch to model dynamic evolution characteristics. Furthermore, an attention-based fusion mechanism is introduced to adaptively learn the relative importance of different modalities and perform dynamic feature aggregation. Extensive experiments are conducted using a dataset constructed from mathematical models and engineering-oriented simulations. Comparative studies and ablation studies demonstrate that the proposed method significantly outperforms conventional signal-processing-based approaches and single-modality deep-learning models in terms of classification accuracy, robustness, and generalization capability. The results confirm the effectiveness of multimodal feature fusion and attention mechanisms for accurate wideband oscillation classification, providing a promising solution for advanced power system monitoring and analysis. Full article

We present the single-cell transcriptomic analysis of peripheral blood mononuclear cells (PBMC) from individuals during acute HIV-1 infection caused by viral strains circulating in Russia and the Former Soviet Union (FSU) countries. Using 10x Genomics single-cell RNA sequencing (scRNA-seq) on the Illumina NextSeq 550 platform, we have analyzed scRNA-seq data from three treatment-naive patients (viral load > 1 × 10⁶ copies/mL, estimated infection duration ≤ 4 weeks) and three healthy donors. Data integration (Seurat, Harmony), automated cell-type annotation (CellTypist), and GeneOntology (GO) enrichment analysis for highly expressed and low-expressed genes revealed a profound reorganization of transcriptional programs across key immune populations, including memory CD4⁺ and CD8⁺ T cells, non-classical monocytes and natural killer cells (NK-cells). We observed signatures of hyperactivation of pro-inflammatory pathways (NF-kB, TNF, and type I/II interferon signaling), upregulation of genes associated with cellular migration (CXCR4, CCR7) and metabolic adaptation (oxidative phosphorylation components), alongside a mixed pro- and anti-apoptotic expression profile. Notably, our data pointed to a pronounced dysregulation of the TGF-β and mTOR signaling cascades, disrupted intercellular communication networks—particularly between cytotoxic cells and their regulators—altered expression of genes implicated in disease progression (OLR1, SERPINB2, COPS9) and viral persistence control (NEAT1, NAF1). This work provides an initial single-cell transcriptional atlas characterizing early immune responses to HIV-1 sub-subtypes A6 and CRF63_02A6, the predominant drivers of the HIV epidemic across the FSU region. Full article

Glycogen synthase kinase 3 (GSK3/Shaggy-like) is a highly conserved serine/threonine kinase that orchestrates growth, hormone signaling, and abiotic stress responses in both animals and plants, yet its role in watermelon remains unexplored. In this study, we conducted a whole-genome identification, identifying a total of eight members of the GSK3 gene family (ClGSK3) distributed across seven chromosomes. Phylogenetic and synteny analyses resolved the eight ClGSK3s into four subfamilies that display one-to-one or one-to-many orthology with Arabidopsis and rice GSK3 genes, indicating conserved genomic micro-collinearity across dicots and monocots. Predictions of cis-acting elements and transcriptome data analysis indicate that ClGSK3s may be involved in hormone- and stress-responsive conditions. Protein–protein interaction networks predicted 53 candidate partners for five ClGSK3 proteins; yeast two-hybrid assays subsequently confirmed that ClSK21 associates with three of them—orthologs of the core brassinosteroid (BR)-signaling components BKI1 and BZR1. qRT-PCR revealed that ClSK21, ClSK31, and ClSK41 are rapidly and significantly reprogrammed by BR treatment. Collectively, our data suggest that ClGSK3s modulate fruit development and stress tolerance by integrating hormone-related pathways, especially BR signaling. Future studies are encouraged to integrate genetics and multi-omics approaches to systematically validate the roles of ClGSK3s in hormone signaling and abiotic stress responses. Full article

L-theanine is a bioactive non-protein amino acid predominantly derived from tea plants (Camellia sinensis), widely recognized for its potential benefits in mood regulation and psychological health. Despite its promising neuropsychological profile, the specific molecular targets and mechanisms underlying its antidepressant activity remain incompletely understood. In the present study, an integrated network pharmacology strategy, combined with molecular docking and molecular dynamics (MD) simulations, was employed to systematically elucidate the potential antidepressant mechanisms of L-theanine. By intersecting predicted drug targets with depression-related genes, 40 potential targets were identified. Protein–protein interaction (PPI) network analysis subsequently pinpointed five hub targets: PRKACA, GRIA2, GRIN1, GRIA1, and HTR1A. Functional enrichment analyses (KEGG and GO) indicated that these targets are primarily implicated in critical pathological processes of depression, including neurotransmitter regulation, glutamatergic synaptic transmission, stress response signaling, and neurotrophin-related pathways. Molecular docking revealed favorable binding affinities between L-theanine and the key targets. Furthermore, MD simulations and binding free energy calculations corroborated the structural stability and thermodynamic favorability of these protein–ligand complexes. Overall, this study provides hypothesis-generating insights into the antidepressant mechanisms of L-theanine from a multi-target perspective, offering a theoretical foundation to guide future experimental validation in depression research. Full article

Serrated adenocarcinoma (SAC) represents a molecularly heterogeneous subtype of colorectal carcinoma (CRC) linked to the serrated pathway. It is aimed to clarify the molecular mechanisms underlying SAC development. Digital slides from The Cancer Genome Atlas (TCGA) colorectal adenocarcinoma Firehose Legacy dataset (632 cases) were reviewed, and cases were classified as SAC, partial-SAC, or classical CRC. Genomic alterations, mRNA expression, and DNA hypermethylation were compared using cBioPortal. Enrichment analyses were performed via WebGestalt, and protein–protein interaction (PPI) networks with hub genes were identified using STRING and Cytoscape. Statistical significance was defined as p < 0.05 and q < 0.05. The results revealed that the groups showed significant differences in the expression of 327 genomic alterations, 20 mRNAs, and 21 methylated genes (p < 0.0001, q < 0.0001). Hub genes were PSMC1, FLT3LG, SNW1, H3C2, H1-2, H2BC14, H1-5, RPS16, SUPT5H, and MYOD1. The pathways associated with differently expressed genes were the following: cell structure and morphology (phagocytic vesicle, microvillus, endocytosis, and immobile cilium), protein kinase activity (particularly MAPK), and immunological mechanisms. The hub genes act as molecular bridges connecting the observed genomic and epigenetic variations, particularly driving chromatin-related regulation and MAPK signaling pathways. In particular, PSMC1, SNW1, H3C2, H1-2, and H2BC14 genes offer promising molecular targets for future therapeutic approaches in SACs. Full article

As the threat from malicious UAVs continues to intensify, accurate identification of individual UAVs has become a critical challenge in regulatory and security domains. Existing single-signal analysis methods suffer from limited recognition accuracy. To address this issue, this paper proposes a high-precision individual identification method for UAVs based on FFS-SPWVD and DIR-YOLOv11. The proposed method first employs a frame-by-frame search strategy combined with the smoothing pseudo-Wigner–Ville distribution (SPWVD) algorithm to obtain effective time–frequency feature representations of flight control signals. Building on this foundation, the YOLOv11n network is adopted as the baseline architecture. To enhance the extraction of time–frequency texture features from UAV signals in complex environments, a Multi-Branch Auxiliary Multi-Scale Fusion Network is incorporated into the neck network. Meanwhile, partial space–frequency selective convolutions are introduced into selected C3k2 modules to alleviate the increased computational burden caused by architectural modifications and to reduce the overall number of model parameters. Experimental results on the public DroneRFb-DIR dataset demonstrate that the proposed method effectively extracts flight control frames and performs high-resolution time–frequency analysis. In individual UAV identification tasks, the proposed approach achieves 96.17% accuracy, 97.82% mAP50, and 95.29% recall, outperforming YOLOv11, YOLOv12, and YOLOv13. This study demonstrates that the proposed method achieves both high accuracy and computational efficiency in individual UAV recognition, providing a practical technical solution for whitelist identification and group size estimation in application scenarios such as border patrol, traffic control, and large-scale events. Full article

This paper explores the feasibility of using acoustic wave propagation, particularly in the ultrasonic range, as a solution for data transmission in environments where traditional radio frequency (RF) communication is ineffective due to signal attenuation—such as in liquids or dense media like metal or stone. Leveraging GNU Radio and commercially available audio hardware, a low-cost, SDR (Software Defined Radio) system was developed to transmit data blocks (e.g., images, text, and audio) through various substances. The system employs BFSK (Binary Frequency Shift Keying) and BPSK (Binary Phase Shift Keying), operates at ultrasonic frequencies (typically 40 kHz), and has performance validated under real-world conditions, including water, viscous substances, and flammable liquids such as hydrocarbon fuels. Experimental results demonstrate reliable, continuous communication at Nyquist–Shannon sampling rates, with effective demodulation and file reconstruction. The methodology builds on concepts originally developed for Ad Hoc Sensor Networks in shipping containers, extending their applicability to submerged and RF-hostile environments. The modularity and flexibility of the GNU Radio platform allow for rapid adaptation across different media and deployment contexts. This work provides a reproducible and scalable communication solution for scenarios where RF transmission is impractical, offering potential applications in underwater sensing, industrial monitoring, railways, and enclosed infrastructure diagnostics. Across controlled laboratory experiments, the system achieved 100% successful reconstruction of transmitted image files up to 100 kB and sustained packet delivery success exceeding 98% under stable coupling conditions. Full article

Steatosis extends beyond the liver to the pancreas, heart, and skeletal muscle, yet prevailing definitions remain narrowly organ-focused. This narrative review introduces the Metabolic Steatotic Axis (MSA) as a framework that captures the dynamic, bidirectional interactions among these organs, driving systemic metabolic dysfunction. We synthesize evidence linking lipotoxicity, inflammatory signaling, and endocrine cross-talk into a self-amplifying network accelerating insulin resistance, β-cell failure, and cardiometabolic risk. The MSA concept provides a rationale for axis-based staging systems and composite biomarker panels to quantify cumulative disease burden better and refine risk stratification. We highlight phenotypic heterogeneity within MSA stages, the possible hierarchy of organ vulnerability, and the implications for prognosis and therapy. Viewing pharmacological and lifestyle interventions through the MSA lens reframes them as systemic modulators rather than organ-specific treatments, underscoring the need for multi-organ endpoints in clinical trials. Finally, we outline priorities for longitudinal imaging, multi-omics integration, and global harmonization to translate the MSA from a conceptual construct to a clinically actionable paradigm. By unifying fragmented observations into a systemic model, the MSA has the potential to reshape disease classification, therapeutic strategies, and precision medicine in metabolic disorders. Full article