Search Results (798)

Recent studies suggest that prolonged participation in formal music programs may be associated with the cultivation of resilience and locus of control (LoC) in music students. Brazilian musicians, who were attending or had attended community-based music programs, and a group of matched, untrained individuals from disadvantaged, urban communities completed the Connor–Davidson Scale of Resilience (RISC), the Craig Locus of Control Scale, and the ABEP 2022—Brazilian Criteria of Economic Classification questionnaire. Results suggested that while musical participation alone was not associated with resilience and LoC scores (model 1), a conditional restriction of the same model (model 2) showed a significant interaction between musical participation, age, and RISC and LoC scores, after controlling for SES. Among musicians, higher age was associated with higher resilience scores and internal LoC. Findings from this exploratory study are discussed in light of the multifaceted nature of community-based music programs, the building blocks of resilience and LoC. We also comment on the potential links between resilience and LoC in relation to musical participation and well-being. Limitations of this study are discussed alongside implications for future research. Full article

Microbial contamination in aquatic environments poses severe threats to aquaculture sustainability, ecological balance and public health. Traditional culture-based detection methods, while standardized, are time-consuming and labor-intensive, often failing to meet the urgent need for rapid on-site monitoring required to prevent disease outbreaks and manage water quality effectively. By integrating latest research advances (2020–2025), this study reviews advances in rapid detection technologies for aquatic microorganisms, including the evolution of nucleic acid amplification strategies, with a focused comparison of the analytical sensitivity and field deployability of quantitative polymerase chain reaction (qPCR) and mainstream isothermal amplification techniques (loop-mediated isothermal amplification, LAMP; recombinase polymerase amplification, RPA). Furthermore, this study reports on the emergence of Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR)-associated protein (Cas) systems as next-generation diagnostic tools, highlighting their integration with microfluidic Lab-on-a-Chip (LOC) platforms to achieve attomolar sensitivity. We also consider the application of portable nanopore sequencing for real-time pathogen identification and the growing role of Artificial Intelligence (AI) in analyzing complex diagnostic datasets. Advanced molecular methods have achieved significant reductions in time consumption—from days to less than one hour—while challenges regarding sample preparation and environmental matrix inhibition remain. The future of aquatic monitoring lies in integrated, automated systems that combine the specificity of CRISPR-Cas diagnostics with the connectivity of IoT-enabled biosensors. Comparative analysis indicates that isothermal amplification methods (LAMP, RPA) coupled with CRISPR-Cas systems offer the optimal balance of sensitivity, speed, and field deployability for point-of-care aquaculture diagnostics, while qPCR/dPCR remain indispensable for quantitative regulatory applications. We propose a structured technology selection framework to guide researchers and practitioners in choosing appropriate detection modalities based on specific sensitivity, cost, throughput, and deployment requirements. Full article

Optimizing tillage and fertilization practices is of vital importance for enhancing soil carbon retention, improving soil quality and increasing crop productivity in the intensive wheat (Triticum aestivum L.)–maize (Zea mays L.) double cropping system (WM). However, the combined effects of subsoiling (ST) and liquid manure (LM) application on yield sustainability and the dynamic changes in labile organic carbon (LOC) fractions (LOCs) remain insufficiently quantified in WM in the North China Plain (NCP). A two-year field experiment evaluated the responses of grain yields, the sustainable yield index (SYI), soil organic carbon (SOC), LOCs, C pool management indexes (CPMIs), and the soil quality index (SQI) to both patterns of tillage [conventional shallow rotary tillage (RT) and ST] and fertilization [conventional fertilization (CF), LM broadcast (LMB), and LM injection (LMI)] in WM in the NCP. Compared with RT, ST significantly enhanced crop grain yields (3.5~4.1%) and the annual SYI (4.1%) (p < 0.05). The contents of SOC, total labile OC (TLOC), high LOC (HLOC), and medium LOC (MLOC) and the values of SQI were higher in soil layers at both 0–20 cm and 20–40 cm under ST than those under RT. Compared with CF, LMI significantly enhanced grain yields (5.8~6.1%) and the annual SYI (5.4%). LMI significantly increased the contents of SOC, TLOC, HLOC, and MLOC and the SQI values in both soil layers relative to CF, while no significant difference was observed for grain yields, the annual SYI, and the SQI between LMB and CF. The higher contents of SOC and LOC led to an increase in the values of CPMIs based on TLOC (TCPMI), HLOC (HCPMI), and MLOC (MCPMI). The combination of both ST and LMI enhanced SOC retention through the increase in recalcitrant organic carbon (ROC) content and the transformation process of LOCs. It was obvious that HLOC and MLOC affected SOC, HCPMI, and MCPMI in the soil layers at both 0–20 cm and 20–40 cm, and thus can be regarded as sensitive indicators reflecting the dynamic changes in SOC and soil quality. Therefore, the combination of subsoiling and liquid manure injection can promote labile OC transformation, SOC retention, soil quality, and yield sustainability, providing an effective management strategy for the achievement of sustained agricultural production in the NCP or other regions with similar conditions. Full article

Citrus genomes as storehouses of genetic information of immense commercial utility remain untapped for the improvement of fruit quality traits and other production-related stresses. With the rapid expansion of transcriptomic datasets, integrative meta-analysis has further aided in uncovering interspecies molecular mechanisms associated with fruit quality development. In this study, we performed a cross-project RNA-Seq meta-analysis, integrating multiple publicly available BioProjects encompassing diverse citrus species, viz., Citrus sinensis, C. reticulata, C. maxima, C. clementina, C. japonica, and C. papeda, known to dominate the morphogenetic evolution of the citrus industry. High-throughput RNA-Seq data were processed using various bioinformatics tools. A total of 15 interspecies comparisons identified 676 unique DEGs, enriched in pathways related to secondary juice yield and processing quality traits. We also established that domestication aided in metabolism, oxidative stress responses, phenylpropanoid and flavonoid biosynthesis, and hormone-mediated signaling. Multivariate analyses (PCA and heatmap visualization) highlighted distinct yet overlapping expression patterns across these citrus species. By combining differential expression, co-expression network analysis and QTL-GWAS integration, we identified 19 high-confidence candidate genes responsible for transcriptomic variation associated with measurable fruit quality traits. Genes such as LOC102612823 and LOC102607495, which co-localized with seed number QTLs on chromosome 1, represented strong candidates regulating reproductive development and seed formation, the traits that directly influence fruit texture and market acceptability. Genes linked to juice content QTLs, including LOC102611137 and LOC102612553 on chromosome 5, suggested their roles in metabolic regulations behind juice accumulation. These loci provided definitive breeding clues for enhancing the reshaping of citrus fruit transcriptomes while retaining key ancestral regulatory components. Full article

Large language models (LLMs) offer new opportunities for lesson planning, remediation, and personalized practice, but deploying them in real educational settings remains challenging for two reasons. First, direct use of learner interaction traces can expose sensitive information about student knowledge states and behavioral patterns. Second, unconstrained generation can produce recommendations that are pedagogically inconsistent with the adopted curriculum, such as skipping prerequisite concepts or drifting outside the prescribed textbook scope. We propose PrivPath, a stage–subject–textbook-aligned framework for privacy-preserving curriculum planning that explicitly separates on-device learner modeling from server-side content generation. Its core module, Tri-Index Private Path Planning (TIPP), first restricts planning to a scoped curriculum graph defined by the target educational context, then privatizes learner mastery summaries under local differential privacy before transmission, and finally computes a curriculum-feasible instructional path that is coupled with evidence-grounded constrained generation. This design preserves personalization while reducing reliance on raw student traces and improving controllability of the generated teaching sequence. Experiments on three educational interaction datasets paired with open-textbook curriculum graphs show that PrivPath substantially improves structural validity and privacy robustness. In particular, it raises graph feasibility from 82.5% to 99.2% relative to TriIndex-RAG, improves the offline pedagogical utility proxy $\Delta$AUC from 0.013 to 0.018, and lowers membership inference AUC from 0.74 to 0.52 at ${\epsilon }_{\mathrm{loc}}=1.0$. These results suggest that curriculum-aligned path planning, privacy-preserving learner adaptation, and practically useful LLM-based educational generation can be achieved within a unified framework. Full article

Objective: To develop and validate an artificial intelligence (AI) system for automated lens opacities classification system III (LOCS III)-based grading of all three major cataract subtypes using anterior segment optical coherence tomography (AS-OCT). Methods: This is a single-center cross-sectional study. AS-OCT images were collected and manually graded by ophthalmologists according to LOCS III. The dataset was randomly split into training, validation, and test sets. We propose a novel multi-granularity mask-guided network (MMNet) that jointly performs lens substructure segmentation and severity grading. The model’s performance was assessed on an independent test set for automatic grading of cortical cataract (CC), nuclear cataract (NC), and posterior subcapsular cataract (PSC) and the grading performance of the proposed method against ophthalmologists was also evaluated. The model’s interpretability was assessed via attention heatmaps and feature visualization. Results: The proposed MMNet exhibited high agreement with ground truth conducted through gold standard. The proportions of predictions with an absolute error < 1.0 for three subtypes range from 83.02% to 89.94%. The model’s grading accuracy for cataract subtypes was between 82.20 ± 1.41% and 89.76 ± 1.31% among the three subtypes, the Area Under the Curve (AUC) was between 0.954 (95% CI, 0.952–0.969; p < 0.001) and 0.973 (95% CI, 0.964–0.985; p < 0.001). The MMNet shows a satisfactory mean absolute error (MAE) of 0.14 ± 0.35 in CC, 0.10 ± 0.30 in NC, and 0.17 ± 0.38 in PSC grading. It also achieved a fast grading speed of 0.0178 s/image against manual grading. Conclusions: The proposed AI model presented advanced performance on AS-OCT images in automated LOCS III-based cataract grading for CC and NC, and also showed feasibility in PSC assessment. Full article

Background/Objectives: Having longer mesocotyls is beneficial for the deep-sowing tolerance of rice, which is important for seedling establishment. Methods: Here, we performed transcriptome analysis of the elongating mesocotyl of Zhengdao 209 in response to three different sowing depths to identify the pivotal genes regulating rice mesocotyl elongation. Results: Three groups with different mesocotyl lengths were compared using transcriptome analysis, and 60 common differentially expressed genes were detected. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses revealed that these genes are primarily involved in phenylpropanoid biosynthesis, cutin suberine and wax biosynthesis, the plant mitogen-activated protein kinase signaling pathway, diterpenoid biosynthesis, cyanoamino acid metabolism, carbon fixation in photosynthetic organisms, flavonoid biosynthesis, and glutathione metabolism. Furthermore, weighted gene co-expression network and hierarchical clustering analyses showed that most of the differentially expressed genes are implicated in phenylpropanoid biosynthesis, carbon metabolism, photosynthesis antenna proteins, and plant–pathogen interactions. Among the genes involved in phenylpropanoid biosynthesis processes, the expression levels of OsPHT3 and LOC_Os04g59260 increased, while OsCCR1, OsPGIP4, and LOC_Os01g45110 expression decreased with increasing sowing depth. Among the genes involved in the mitogen-activated protein kinase signaling pathway, the expression levels of LOC_Os07g03319 and LOC_Os07g03580 increased, while LOC_Os07g03409 decreased with increasing sowing depth. Among the genes involved in diterpenoid biosynthesis processes, the expression levels of OsCYP76M5 and OsCYP71Z2 decreased, while OsCYP71Z21 increased with increasing sowing depth. Furthermore, the expression levels of these genes were analyzed using quantitative real-time polymerase chain reaction, which confirmed the transcriptome analysis results. Conclusions: This study identified candidate genes governing rice mesocotyl length and provides novel insights into the molecular regulatory mechanisms underlying mesocotyl elongation in rice. Full article

One of the common issues in the R&D of new drugs is the failure of clinical trials caused by the species-specific inadequacy of animal models to assess drugs’ efficiency and safety. Therefore, systems like organ-on-a-chip and, particularly, liver-on-a-chip (LOC) can be an efficient tool for recapitulating in vivo-like human physiology at the microscale. This review focuses on discussing LOC design, emphasizing its architecture and validation to reveal the trends in searching for a balance between biomimetics and functionality. We found that the huge variety of already published models can be divided into five groups based on their configuration complexity: flat one-channel, flat two-channel, vertically stacked multilayered, hexagonal-patterned, and multi-well chips. While researchers attempt to recapitulate the liver’s histology and its functions in detail by increasing the complexity of devices’ architectonics, industrial companies prefer to promote more simple and flexible solutions. Thus, the LOC designs of the future require neglecting some liver characteristics to make them standardizable and sustainable, which could facilitate their introduction into the market and clinics. Full article

Sunflower is a globally important oilseed crop. Improving its fatty acid composition is crucial for enhancing oil quality and nutritional value. To dissect the genetic basis of quality traits, we performed genome resequencing on 203 sunflower inbred lines and conducted a genome-wide association study (GWAS) for five traits—oil content, stearic acid, palmitic acid, oleic acid, and linoleic acid—across three environments. We identified 103 significant single-nucleotide polymorphisms (SNPs) and 154 candidate genes. Notably, several associated loci were co-localized for multiple traits, suggesting pleiotropic effects or close genetic linkages. Integration with transcriptome data from developing seeds revealed that 66 candidate genes were expressed within 30 days after pollination, of which 12 showed significant differential expression between high- and low-oleic acid varieties. Functional characterization of a selected candidate, the ω-6 fatty acid desaturase gene (LOC110938218, designated HaDES8.11), demonstrated that the HaDES8.11-eGFP fusion protein localizes to the endoplasmic reticulum. Heterologous expression of HaDES8.11 in Arabidopsis thaliana significantly increased seed linoleic acid content while decreasing oleic acid content, confirming its role in fatty acid desaturation. Our study provides novel genetic insights and valuable candidate genes for the molecular breeding of sunflower with optimized oil quality. Full article

Objectives: Peduncle length (PL) is a critical agronomic trait in sorghum [Sorghum bicolor (L.) Moench], influencing mechanical harvesting efficiency. Exploration of the PL genetic mechanism and the PL major genes of sorghum can provide a reference for breeding of sorghum suitable for mechanization and PL genetic research of other graminaceous crops. Methods: Here, we conducted genetic analysis, transcriptome analysis, and candidate major gene screening of PL using long-peduncle (KY133B) and short-peduncle (KY123B) parents, as well as their constructed F2 segregated populations. Results: Genetic analysis revealed that PL trait may be controlled by two major genes with additive-dominant effects, showing a heritability of 69.638%. At the early stage of sorghum peduncle elongation, the young panicle of the parents was sampled and performed transcriptome analysis. DEGs 3603 genes were obtained. With the short peduncle parent (F) as the control, 2204 upregulated genes and 1399 downregulated genes were expressed in the long peduncle parent (M). We compared the 1161 genes obtained by BSA-seq from the laboratory in the early stage with the DEGs obtained by RNA-seq, and obtained 148 co-localized genes. Through the high DEGs screening criteria (|Log₂FC(M/F)| ≥ 5, p < 0.0001), we further identified 36 genes with highly significant expression differences between parents. Functional annotation identified four candidate major genes strongly associated with PL: LOC8056900 (MIZU-KUSSEI 1), LOC8065075 (ethylene-responsive transcription factor WIN1), LOC8083493 (GDSL esterase/lipase), and LOC8085367 (auxin-responsive protein IAA21). qPCR validated their expression trends, corroborating RNA-seq results. Conclusions: The comprehensive information presented here provides a reference for understanding the PL mechanism of sorghum and provides some important candidate major genes related to PL. This study laid the foundation for subsequent gene functional verification and mechanism analysis of sorghum peduncle length major genes. Full article

Visual localization plays a critical role for mobile robots to estimate their position and orientation in GPS-denied environments. However, its efficiency, robustness, and generalization are fundamentally undermined by severe viewpoint changes and dramatic appearance variations, which present persistent challenges for image-based feature representation and pose estimation under real-world conditions. Recently, map-free visual relocalization (MFVR) has emerged as a promising paradigm for lightweight deployment and privacy isolation on edge devices, while how to learn compact and invariant image tokens without relying on structural 3D maps still remains a core problem, particularly in highly dynamic or long-term scenarios. In this paper, we propose the Debiased Multiplex Tokenizer as a novel method (termed as DMT-Loc) for efficient and versatile MFVR to address these issues. Specifically, DMT-Loc is built upon a pretrained vision Mamba encoder and integrates three key modules for relative pose regression: First, Multiplex Interactive Tokenization yields robust image tokens with non-local affinities and cross-domain descriptions. Second, Debiased Anchor Registration facilitates anchor token matching through proximity graph retrieval and autoregressive pointer attribution. Third, Geometry-Informed Pose Regression empowers multi-layer perceptrons with a symmetric swap gating mechanism operating inside each decoupled regression head to support accurate and flexible pose prediction in both pair-wise and multi-view modes. Extensive evaluations across seven public datasets demonstrate that DMT-Loc substantially outperforms existing baselines and ablation variants in diverse indoor and outdoor environments. Full article

Lab-on-a-Chip (LoC) and microfluidic technologies are rapidly reshaping the development pipeline for nano drug delivery systems (DDSs) by enabling precise control of physicochemical properties, high-throughput screening, and integrated biological evaluation within miniaturized platforms. This review synthesizes recent advances in microfluidic principles, fabrication strategies, and sensing modalities that facilitate continuous flow synthesis, real-time characterization, and adaptive formulation of nanoparticles. We highlight how LoC-enabled systems improve monodispersity, reproducibility, and tunability of liposomes, polymeric nanoparticles, and metallic nanocarriers, while providing powerful tools for assessing pharmacokinetics, drug release, and systemic responses using organ-on-chip (OoC) models. Emerging trends, including AI-driven autonomous optimization, stimuli-responsive materials, 3D-printed hybrid architectures, and self-powered portable devices, are discussed in the context of future integrated nano-pharmaceutics platforms. Despite existing challenges related to biocompatibility, standardization, data integration, and translation to industrial and clinical applications, the synergistic evolution of LoC engineering and nanomedicine holds transformative potential for personalized and next-generation therapeutic strategies. Full article

Secure cross-domain UAV authentication is challenging because identity verification alone is insufficient to guarantee safe operation. In many UAV applications, it is equally critical to verify that a UAV is currently located within an authorized geographic region. Existing approaches often expose precise GPS coordinates, rely on static identifiers that enable tracking, or fail to guarantee the freshness and authenticity of location evidence. These weaknesses allow replay, location spoofing, and trajectory inference attacks, especially in multi-domain environments. To address these limitations, we propose PrivLocAuth, a zero-knowledge-based cross-domain UAV authentication protocol that enforces geofence restrictions without revealing actual locations. In PrivLocAuth, UAVs encode their current coordinates into fresh Pedersen commitments, which are attested by the home Local Domain Server (LDS) using short-lived Schnorr signatures. Based on these attested commitments, UAVs generate Bulletproof range proofs to demonstrate compliance with cross-domain server-defined geofences. This design ensures that UAVs operate within authorized airspace while preserving strong location privacy. PrivLocAuth further incorporates a lightweight elliptic curve cryptography (ECC) and Schnorr signature-based credential framework that enables unlinkable authentication across-domains, preventing session correlation and identity tracking. Formal security analysis demonstrates resistance to impersonation, replay, geofence-bypass, and linkage attacks. Experimental evaluation shows low computational latency and minimal communication overhead, confirming the protocol’s suitability for resource-constrained UAV platforms operating in dynamic cross-domain environments. Full article

Rapid Visco Analyzer (RVA) profile characteristics are important indicators of rice (Oryza sativa L.) eating quality. In this study, based on the high-density genetic linkage map constructed under the genetic background of Yuexianghzan (YXZ) and Shengbasimiao (SBSM), combined with the RVA profile characteristic data of recombinant inbred lines (RILs) grown in two environments, QTL scanning was performed using the ridge regression analysis method. A total of 59 QTLs associated with RVA profile characteristics were detected across 11 chromosomes in the two environments, with individual QTLs explaining 0.12% to 85.16% of the phenotypic variation. Moreover, 11 QTLs were repeatedly detected in two environments with large effects. The QTL located in the 1.44–1.85 Mb interval on chromosome 6 simultaneously controlled eight RVA profile characteristics and contained the cloned waxy (Wx) gene. Additionally, the intervals 20.58–20.70 Mb on chromosome 5 and 24.96–25.42 Mb on chromosome 8 were repeatedly mapped and influenced multiple RVA characteristics. Based on gene annotation information, a total of nine candidate genes (LOC_Os05g34730, LOC_Os05g34830, LOC_Os05g34854, LOC_Os06g03910, LOC_Os06g04200, LOC_Os06g42720, LOC_Os08g39830, LOC_Os08g39850, and LOC_Os08g39860) that directly or indirectly influence the starch synthesis pathway were identified. The results of this study lay a foundation for further map-based cloning of genes related to rice RVA profile characteristics and molecular design breeding. Full article

Yield-related traits of rice (Oryza sativa L.) are pivotal to safeguarding global food security. As a powerful and efficient strategy, genome-wide association study (GWAS) has identified numerous genes for yield-related traits in rice over recent decades, providing critical resources for germplasm improvement. Most yield-related traits are complex quantitative traits controlled by multiple genes with diverse effect sizes, and traditional GWAS approaches have limited power to detect small-effect loci. In this study, we employed Fast3VmrMLM, a compressed mixed linear model integrating genome-wide scanning and machine learning, to perform GWAS for 10 key yield-related traits using a panel of 529 rice accessions and 4,945,006 single-nucleotide polymorphisms (SNPs). The traits included heading date, plant height, panicle number, effective panicle number, yield per plant, spikelet length, grain length, grain width, grain weight, and grain thickness. We detected 141 significant quantitative trait nucleotides (QTNs) associated with target traits and identified 92 previously validated genes located near these QTNs. As a key environmental regulator, photoperiod directly controls flowering and indirectly modulates yield-related traits, and we further identified 182 photoperiod-responsive candidate genes via differential expression and Gene Ontology (GO) enrichment analysis. Through tissue-specific expression analysis, homology analysis with Arabidopsis genes, and haplotype-phenotype differential analysis, six pleiotropic candidate genes were confirmed; notably, LOC_Os02g02210 appears to contribute substantially to grain width and yield-related traits. In conclusion, Fast3VmrMLM proved effective for dissecting the genetic basis of yield-related traits, especially in detecting small-effect loci. These results not only establish a potential genetic link between photoperiod regulation and rice yield formation but also provide high-confidence candidate genes and loci that will accelerate functional genomic studies and precision molecular breeding for high-yield rice. Full article