Search Results (426)

Sleep disturbances are early hallmarks of Alzheimer’s disease (AD) and other dementias, yet the molecular mechanisms remain poorly understood. We previously showed that dipeptidyl aminopeptidase-like protein 6-knockout (DPP6-KO) mice exhibit accelerated neurodegeneration with synaptic loss, neuronal death, and circadian dysfunction resembling AD pathology. Here, we investigate whether DPP6 deficiency directly causes sleep dysregulation and assess age-dependent effects using wireless EEG/EMG telemetry, behavioral monitoring, and body temperature recordings. We found striking age-dependent sleep phenotypes in DPP6-KO mice. Adult (3-month) DPP6-KO mice showed hyperactivity-driven REM sleep increases, while aged (12-month) DPP6-KO mice developed insomnia with fragmented sleep architecture. Critically, aged DPP6-KO mice exhibited decreased REM latency, a biomarker of depression, which we confirmed by behavioral assays. Conversely, DPP6 overexpression in aged wild-type mice increased NREM duration and reduced sleep fragmentation, demonstrating a protective effect. Throughout aging, DPP6-KO mice showed dysregulated locomotor activity and body temperature rhythms, suggesting broader disruption of circadian and metabolic homeostasis. These findings establish DPP6 as a critical regulator of sleep architecture whose loss recapitulates key sleep disturbances observed in AD/dementia. The progressive nature of sleep dysfunction in DPP6-KO mice, from REM abnormalities to insomnia, parallels human disease progression and positions DPP6 as a potential therapeutic target for sleep-related symptoms in neurodegenerative disorders. Full article

Despite the endangered status of the Oriental Stork (Ciconia boyciana) on the IUCN Red List, a critical lack of contemporary mitochondrial genomic data from its core distribution areas in mainland China has hindered our understanding of the species’ long-term evolutionary stability and spatiotemporal variation. This study addresses this gap by sequencing and assembling the complete mitogenome (17,608 bp) of a contemporary individual from Hongze Lake, Jiangsu (PX682155), and conducting a rigorous comparative analysis against a historical reference sequence published 25 years ago in Japan (NC_002196). Our results demonstrate striking structural and functional conservation across a quarter-century span; the 13 protein-coding genes exhibit highly synchronized gene arrangements, base composition biases, and Relative Synonymous Codon Usage (RSCU) patterns, indicative of stringent purifying selection maintaining oxidative phosphorylation efficiency. While phylogenetic analysis reinforces its sister-group relationship with the White Stork (C. ciconia), significant length polymorphisms were identified within the D-loop control region, primarily driven by microsatellite repeat variations. These findings provide a vital genomic benchmark for mainland populations, offering high-resolution molecular markers essential for future large-scale assessments of geographic isolation and the refinement of targeted conservation strategies for this flagship wetland species. Full article

This study presents a comprehensive investigation of OPE residues, distribution patterns, and dietary exposure risks in crustaceans from southeast China. OPEs were detected in over 90% of samples, with mean total concentrations (ΣOPEs) of 5.80 μg/kg wet weight (ww) in freshwater shrimp, 6.52 μg/kg ww in marine prawn, and 1.25 μg/kg ww in marine crab. Tributyl phosphate (TiBP), triethyl phosphate (TEP), and tris(2-chloroethyl) phosphate (TCEP) emerged as the dominant congeners, accounting for 68.1% of ΣOPEs, which indicates inputs from industrial emissions, plastic waste leaching, and aquaculture equipment. Spatial analysis revealed striking regional differences: coastal industrial cities (Zhoushan, Taizhou) exhibited ΣOPE levels up to 12-fold higher than inland mountainous areas (Quzhou, Lishui), while no significant temporal variations were observed. Human health risk evaluation, based on estimated daily intake (EDI) and target hazard quotient (THQ), demonstrated negligible non-carcinogenic risks for the general population (HI < 1), though children and frequent seafood consumers have slightly elevated exposure. These findings indicate the value of crustaceans as bioindicators for OPE contamination and require long-term monitoring of emerging OPEs and their synergistic effects with co-occurring pollutants. Full article

Side-scan sonar (SSS) serves as the primary perceptual instrument for Autonomous Underwater Vehicles (AUVs) in large-scale marine search and rescue (SAR) operations. However, the detection of critical targets is frequently hindered by severe hydro-acoustic noise, the spatial discontinuity of wreckage, and the weak visual signatures of small targets. To surmount these challenges, this paper presents WPG-DetNet. First, we introduce a Wavelet-Embedded Residual Backbone (WERB) to reconstruct the conventional downsampling paradigm. By substituting standard pooling with the Discrete Wavelet Transform (DWT), this architecture explicitly disentangles high-frequency noise from structural information in the frequency domain, thereby achieving the adaptive preservation of edge fidelity for large human-made targets while filtering out speckle interference. Then, addressing the distinct challenge of discontinuous aircraft wreckage, the framework further incorporates a Debris Graph Reasoning Module (D-GRM). This module models scattered fragments as nodes in a topological graph to capture long-range semantic dependencies, transforming isolated instance recognition into context-aware scene understanding. Finally, to bridge the gap between AI and underwater physics, we design a Shadow-Aided Decoupling Head (SADH) equipped with a physics-informed geometric loss. By enforcing mathematical consistency between target height and acoustic shadow length, this mechanism establishes a rigorous discriminative criterion capable of distinguishing weak-echo human bodies from seabed rocks based on shadow geometry. Experiments on the SCTD dataset demonstrate that WPG-DetNet achieves a mean Average Precision ($mA{P}_{50}$) of 97.5% and a Recall of 96.9%. Quantitative analysis reveals that our framework outperforms the classic Faster R-CNN by a margin of 12.8% in $mA{P}_{50}$ and surpasses the Transformer-based RT-DETR-R18 by 5.6% in high-precision localization metrics ($mA{P}_{50:95}$). Simultaneously, WPG-DetNet maintains superior efficiency with an inference speed of 62.5 FPS and a lightweight parameter count of 16.8 M, striking an optimal balance between robust perception and the real-time constraints of AUV operations. Full article

Myasthenia gravis (MG) is a prevalent autoimmune disorder affecting neuromuscular junctions, typically characterized by muscle weakness due to autoantibodies targeting acetylcholine receptors (AChR) or muscle-specific kinase (MuSK). Generalized MG is a more severe form of the condition than ocular MG. Although MG can strike at any age, young adult women are typically affected, especially in their reproductive years. MG is rare during pregnancy, with the first trimester and the postpartum period being the most common times for exacerbations. The influence of MG on pregnancy outcomes remains ambiguous, with some studies finding larger prevalence of issues such as preterm birth and small-for-gestational-age babies, while others indicate results similar to the general population. Management of MG during pregnancy necessitates careful monitoring and drug adjustments. Teratogenic concerns make several immunosuppressive drugs, such mycophenolate mofetil and methotrexate, contraindicated. In contrast, medications like prednisolone and pyridostigmine are generally recognized as safe. Women with MG may have flare-ups after giving birth, and infants may have transient neonatal myasthenia gravis. Comprehensive prenatal treatment and multidisciplinary assistance are crucial for promoting maternal and fetal health during pregnancy in women with MG. This paper examines the relevance of immunological biomarkers, RNAs, and other novel biomarkers in myasthenia gravis (MG). It emphasizes the need for more investigation to determine their role in the pathogenesis of MG, evaluate biomarker profiles across subgroups, and look at changes after treatment. The study also underlines the significance of high-throughput investigations to detect new biomarkers and reveal genetic variables impacting MG pathogenesis. Full article

Engineering drawings are fundamental to industries such as oil and gas, construction, and manufacturing. However, current practices relying on manual design or rigid parametric templates often suffer from inefficiency and layout inconsistencies. To address these issues, the layout task is formulated as the Orthogonal Rectangle Packing Problem with Multiple Configurations and Complex Constraints (ORPPMC). The Deep Reinforcement Learning for Multi-Configuration Drawing Layout (DRL-MCDL) framework is proposed, which integrates the Pointer Network for Drawing Element Sequencing (PN-DES) with the Target-Type-Matching-based Multi-Pattern Positioning Strategy (TTM-MPPS). Within this framework, PN-DES employs deep reinforcement learning and feature fusion to combine element attributes with layout configurations for optimal sequence inference, while TTM-MPPS performs precise positioning in accordance with industrial rules to ensure strict adherence to aesthetic requirements. Ablation experiments validate the contribution of each module. Experimental results on real-world engineering drawings demonstrate that DRL-MCDL achieves a Feasibility Rate (FR) exceeding 98.5% on standard instances (12–40 elements), significantly outperforming traditional methods. Furthermore, it maintains a high inference efficiency with an Average Time (AT) of less than 0.3 s, striking an optimal balance between layout quality and computational speed. Full article

This study provides a comprehensive assessment of 12 metal(loid)s in the muscle tissue of the commercially vital shrimp, Penaeus semisulcatus, from four stations (Bozyazi, Silifke, Karatas, and Iskenderun) along the Northeastern Mediterranean. Metal concentrations were evaluated separately for males and females, utilizing Estimated Weekly Intake (EWI), Target Hazard Quotient (THQ), Carcinogenic Risk (CR), and Selenium Health Benefit Value (HBV_Se) indices. While the species is generally safe for consumption across the region, a striking, localized bioaccumulation of Chromium (Cr) was identified specifically in Iskenderun Bay, where male shrimps exhibited concentrations (1.209 mg/kg wet weight) approximately 10-fold higher than females, highlighting a sex-specific sensitivity likely linked to metabolic and physiological differences. By adopting a precautionary risk assessment framework—considering the region’s intense industrial profile—this localized spike resulted in a Total Carcinogenic Risk (∑CR = 5.15 × 10⁻⁴) for this group, exceeding the priority threshold. Furthermore, widespread Lead (Pb) contamination was detected across all stations, with several samples surpassing EU maximum levels (0.50 mg/kg). Regarding Arsenic (As), while high total concentrations led to THQ values > 1 across the regional gradient, this was characterized as a conservative modeling artifact rather than a physiological threat, as Arsenic in crustaceans is predominantly in the non-toxic organic form. Conversely, any potential risk from Mercury (Hg) was conclusively mitigated by an overwhelming molar excess of Selenium (Se) at all locations, confirmed by consistently positive HBV_Se values (0.312–0.658). In conclusion, our findings demonstrate that seafood safety is conditional and region-specific. The study underscores that localized contamination “hotspots” can be easily masked by non-sex-specific sampling and emphasizes the necessity of moving beyond simplistic risk models by incorporating selenium-mercury antagonism and precautionary risk assumptions for industrial pollutants. Full article

Most falls occur while walking, making gait quality a logical therapeutic target. Many temporo-spatial variables have been implicated in increased fall risk, but these are dependent upon kinematic parameters of the joints involved in the gait cycle. The widespread availability of wearable sensors has made the acquisition of kinematic data feasible, and those related to the ankle are most relevant, as they relate most closely to causes of falls, trips, slips, and mis-steps. The purpose of this study is to estimate the extent to which measures of ankle angular velocity (AV) during walking are associated with falls. This is a comparative study of ankle AV metrics between people who have or have not experienced a fall in the past year. Data came from experimental use of the Heel2Toe™ sensor in a variety of settings, including demonstrations and clinical research studies. The sample comprised 387 participants, of whom 68 (17.6%) self-reported falling in the past year. Logistic regression with a natural cubic spline with 3 degrees of freedom identified AV of the angle at heel strike to discriminate between fallers and non-fallers, and the regression parameters were used to propose an algorithm to estimate fall risk. Applying the algorithm to the existing data yielded a range of probabilities from 0.0480 to 0.7245 depending on age of the person assessed. Further testing of this algorithm in different samples is warranted. Full article

Oat (Avena sativa L.) is increasingly recognized as a functional food due to its unique profile of antioxidant and health-promoting compounds. Beyond its traditional role, our study reveals that Mediterranean landraces and related species harbour exceptional variability in both their nutritional and bioactive traits, offering untapped potential for functional food development. We analysed 126 genotypes, including landraces and cultivars, from 18 Mediterranean and European countries, quantifying the β-glucans, arabinoxylans, phenolic acids (soluble and cell wall bound), avenanthramides (AVAs: A, B, and C), carbon (C), nitrogen (N), C:N ratio, and protein content. The protein levels ranged from 9.5% to 18.5%, with several genotypes exceeding 17%, far above typical oat averages. The β-glucans reached clinically relevant thresholds (>5%) in multiple accessions, while the arabinoxylans surpassed 2% in selected genotypes. The phenolic acids and avenanthramides showed striking diversity, with some landraces accumulating more than 2000 µg/g of total AVAs. The species and phenology strongly influenced the grain composition. Thus, A. strigosa exhibited the highest β-glucan and avenanthramide contents, while early-heading genotypes had doubled avenanthramide levels compared to late-heading ones. A correlation analysis revealed synergistic patterns among the β-glucans, avenanthramides, and proteins, suggesting multi-component interactions that could enhance antioxidant functionality. These findings underscore the strategic value of Mediterranean oat germplasm for breeding programs targeting high-protein, fibre-rich, and antioxidant-enhanced cultivars. By exploiting this diversity, oats could play a pivotal role in preventing chronic diseases and advancing sustainable, health-oriented food systems. Full article

Strike-slip faults and their associated fractures in the ultra-deep marine carbonate reservoirs of the Fuman Oilfield, Tarim Basin, hold significant petroleum geological importance, with the developmental characteristics of fractures being a key factor controlling reservoir productivity. This study targets the F_I17 strike-slip fault zone within the oilfield, where a comprehensive evaluation of fracture effectiveness was performed by integrating geological methods, including core and thin section observation, fluid inclusion thermometry, geophysical fracture identification approaches using imaging logging and seismic data, and geomechanical simulations. The results showed that: (1) structural fractures were developed in at least three stages, predominantly high-angle fractures with their strikes obliquely intersecting the main fault at a small angle, and were affected by multiple episodes of fluid activity, while early-phase fractures exhibited severe filling whereas late-phase fractures had good effectiveness; (2) ultra-deep carbonate rocks contained well-developed stylolites, with extensive horizontal stylolites reducing fracture effectiveness; (3) mechanical effectiveness evaluation parameters were proposed by integrating normal stress, shear stress, and formation pressure, with slip tendency as the dominant indicator, and referenced to the leakage factor and dilation tendency to characterize fracture effectiveness; (4) dynamic effectiveness was assessed using closure/opening pressures, defining a reasonable formation pressure range for hydrocarbon exploitation. The findings of this study can provide theoretical guidance for the further exploration and development of ultra-deep reservoirs in the Fuman Oilfield. Full article

The rapid adoption of large language models (LLMs) and foundation models is reshaping machinery health monitoring. This shift moves the field beyond task-specific deep learning (DL) toward more generalist and multimodal intelligence. Addressing this transition’s fragmented methodology, this systematic review uniquely shifts the focus from purely algorithmic performance to practical industrial deployment. It achieves this by mapping the evolution of text-centric LLMs into autonomous, cyber-physical industrial agents. Following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) 2020 guidelines, an analysis of 58 Scopus studies published between 2022 and early 2026 was conducted to answer six core research questions (RQs). The synthesized literature demonstrates striking quantitative gains. Multimodal foundation models improve out-of-distribution accuracy to 71.95%, up from 18.25% in conventional models. Furthermore, they achieve approximately 98% fault diagnosis accuracy using merely 1.2% labeled samples. To ensure reliability, integrating retrieval-augmented generation (RAG) and knowledge graphs (KGs) mitigates hallucinations. Meanwhile, autonomous agentic architectures within digital twins (DTs) reduce false positive alarms by up to 67%. Despite generative artificial intelligence (GenAI) tackling data scarcity via synthetic data generation, challenges remain regarding real-time determinism, corpus poisoning, and edge deployment. Ultimately, real-world adoption demands targeted physics-AI hybridization and hardware-embedded DTs over generic compression. Full article

Soybean seed quality is defined by an inverse relationship between oil and protein content. Understanding the spatiotemporal regulation of this trade-off is crucial for breeding. This study aims to dissect the transcriptomic networks governing carbon and nitrogen partitioning during seed development. Here, transcriptomic and co-expression network analyses were performed on cotyledon and seedcoat tissues of high-protein (HP) and low-protein (LP) soybean cultivars across three seed developmental stages. We identified 4910 HP/LP-specific differentially expressed genes (DEGs), with striking transcriptional alterations in the early developmental stage. Notably, some important DEGs were enriched in carbon/lipid metabolism, protein folding, and hormone/circadian signaling pathways, among which key gene families (e.g., OLEs, SWEETs, HSPs), core regulators (e.g., LACS, L1L, ABF1), and QTL-localized candidate genes (e.g., FA9) were characterized. Mechanistically, C/VIF1-mediated post-translational inhibition of CWINV1 may restrict carbon flux to oil synthesis in HP seeds; upstream circadian/hormone signaling and L1L-sHSPs jointly promote protein deposition, uncoupling the oil–protein trade-off and enabling HP trait formation. In contrast, LP cultivars upregulated SWEETs, OLEs, and LTPs to facilitate high carbon flux into lipid biosynthesis and storage. These findings provide valuable genetic targets for precision breeding programs aimed at optimizing resource allocation. Full article

Hepatocellular carcinoma (HCC) exhibits a striking male predominance, particularly in Hepatitis B Virus (HBV) endemic regions. While lifestyle factors and estrogen protection are traditional explanations, they fail to fully account for this disparity. This review elucidates the molecular mechanisms driving this gender gap, focusing on the interplay between the Androgen Receptor (AR), viral replication, and the suppression of NKG2D-mediated immune surveillance. We synthesized experimental and clinical findings linking AR signaling, the viral protein HBx, and the regulation of NKG2D ligands (MICA/MICB). Current evidence identifies a positive feedback loop where AR enhances HBV replication, while HBx amplifies AR activity. Crucially, this axis systematically dismantles innate immunity: AR signaling represses MICA/B transcription via miRNA networks and upregulates ADAM metalloproteases, leading to ligand shedding and the release of soluble MICA (sMICA), effectively blinding Natural Killer (NK) cells. We propose that historical failures of anti-androgen monotherapy likely stemmed from ignoring this immune modulation. Consequently, targeting the AR-NKG2D axis represents a promising strategy to sensitize tumors to immunotherapy, suggesting that future therapeutic approaches should combine AR modulation with immune checkpoint inhibitors or shedding-blockade. Full article

Phytopathogens threaten natural ecosystems and global food security. Horticultural trade is the main long-distance pathway that causes the spread of these organisms and disease outbreaks worldwide. Most inspections for disease symptoms are conducted visually, but this is insufficient given the large number of plants and the prevalence of asymptomatic infections. Therefore, there is increasing interest in the use of high-throughput sequencing (HTS) and environmental DNA (eDNA) for plant health surveillance. Many studies have used these technologies to detect phytopathogens, but fewer have done so in horticultural settings. Furthermore, much work has focused on the molecular and bioinformatic approaches for this work, with relatively little attention given to sample collection. This systematic review therefore provides an overview of the available sampling methods and their target plant pathogens, with a particular focus on the utility of these sampling methods in horticultural nurseries. It highlights some striking gaps in the literature and opportunities for further research: for example, the detection of bacterial phytopathogens using eDNA has received little attention despite having considerable potential as a surveillance and/or diagnostic tool. Full article

Domestic cats are among the most popular companion animals worldwide, with steadily increasing ownership and life expectancy. Paradoxically, despite their high prevalence and shared environmental exposures with humans, cats remain markedly underrepresented in molecular oncology research. Cancer is a leading cause of feline mortality, and alimentary lymphoma (AL) has emerged as one of the most common feline malignancies, yet its molecular landscape remains poorly characterized. This review summarizes current knowledge on feline AL, including epidemiology, risk factors, classification schemes, diagnostic challenges, treatment outcomes, and survival, with particular emphasis on low-grade alimentary lymphoma (LGAL), the most prevalent subtype. We discuss the complex relationship between chronic inflammatory enteropathies and lymphoma, highlighting diagnostic ambiguities and the inflammatory–neoplastic continuum. Importantly, we provide a critical overview of existing genomic, transcriptomic, epigenomic, proteomic, and metabolomic studies in feline AL, revealing a striking paucity of high-throughput, multi-omics analyses based on clinical material. Recent advances in feline genome assembly and annotation offer new opportunities to address these gaps. Furthermore, we compare feline AL with its human gastrointestinal T-cell lymphoma counterparts, demonstrating substantial molecular homology across key oncogenic pathways, including JAK/STAT signaling. This comparative perspective underscores the potential of feline AL as a naturally occurring model for the human disease. We conclude that comprehensive molecular characterization of feline AL is urgently needed to improve diagnostics, prognostication, and targeted therapies, with likely translational benefits for both veterinary and human oncology. Aim: The goal of this review is to summarize the current knowledge on feline alimentary lymphoma, including its origin, risk, classification, treatment approaches, and especially molecular landscape, which still remains poorly investigated with modern high-throughput techniques. Full article