Search Results (1,804)

Objective: We aimed to examine the longitudinal associations between lifestyle behaviors, academic achievement, and physical diseases in adolescents. Study Design: Longitudinal cohort study. Methods: We recruited participants (n = 4330; mean age of 14.0 (SD = 1.51) years at the first time point and 16.0 (1.51) years at the second time point) from 16 districts in Shanghai, China, who completed a survey in 2021 (T1) and 2023 (T2). We employed a cross-lagged panel network model to explore the interconnected relationships among lifestyle behaviors, academic achievement, and physical condition (i.e., obesity, high blood pressure, high myopia, depressive symptoms). Results: Among the cross-lagged associations, the predictive effects of T1 obesity on T2 high blood pressure (OR = 2.39), T1 breakfast skipping on T2 TV screen time (OR = 1.49), (in cross-domain relationships) T1 symptoms of depression on T2 low fruit and vegetable consumption (OR = 2.43), T1 obesity on T2 TV screen time (OR = 1.53), and T1 computer time on T2 high BP (OR = 1.31) were particularly prominent. Nonetheless, the observed cross-lagged effect sizes were small. Based on the sum of expected influence on their connecting nodes, obesity, depressive symptoms, and breakfast skipping demonstrated their paramount roles in the network metrics. We found breakfast skipping showed the strongest bridging effect among all factors in association with coexisting conditions and academic performance in children. Conclusions: Our findings identified breakfast skipping as the pivotal bridge node with the highest centrality within the network of modifiable lifestyle factors. Although this does not imply direct causality, its prominent bridge effect highlights its essential role in maintaining network stability and mediating interactions across distinct variable clusters. Full article

Background and Objectives: The combination of resistant hypertension (RHTN) and type 2 diabetes mellitus (T2DM) accelerates the development of chronic kidney disease (CKD), which may be largely associated with sympathetic hyperactivity. Distal renal denervation (dRDN) effectively reduces sympathetic flow to the kidneys, causing renal vasodilation and increased renal perfusion. However, this effect may be limited by nephrotoxicity due to the multiple increase in the number of contrast injections, as well as a significant blood pressure (BP) reduction, which naturally worsens renal perfusion. This study aimed to test the hypothesis that dRDN prevents the progressive decline in kidney function in patients with RHTN and T2DM. Materials and Methods: The prospective interventional study (REFRAIN, NCT04948918) included men and women > 20 y.o. with true RHTN. Eligible patients underwent dRDN. The primary endpoint was a change in eGFR from baseline to 12 months. Secondary endpoints were changes in 24 h BP, serum lipocalin-2, cystatin C, 24 h urinary albumin excretion, renal blood flow, and kidney volumes (by MRI). Multiple regression analysis was used to find independent predictors of individual estimated glomerular filtration rate (eGFR) change. Results: A total of 29 patients with RHTN and T2DM were included in the study (61.6 ± 7.2 y.o., 10 males, mean 24 h ambulatory BP: 158.1 ± 21.4/81.8 ± 12.4 mmHg (systolic/diastolic, respectively)), HbA1c: 7.8 ± 1.4%, and eGFR 56.7 ± 19.9 mL/min/1.73 m², 23 (79%) patients with CKD, and 2 patients with albuminuria only. There were no perioperative complications. Twenty-seven (93%) participants completed 12 month follow-up. eGFR did not change from baseline: +1.3 mL/min/1.73 m² [95% CI: −9.6, 12.1], despite the expected decrease due to a significant decrease in 24 h systolic BP (−18.2 mmHg [95% CI: −28.6, −7.8]). No changes in other secondary endpoints were observed. Independent predictors of individual eGFR change were baseline 24 h pulse pressure (p = 0.030) and HbA1c (p = 0.010). Conclusions: Distal RDN demonstrates a substantial nephroprotective effect in patients with RHTN and T2DM, which may be partly mediated by a reduction in arterial stiffness and is negatively dependent on baseline hyperglycemia. Full article

Multidrug-resistant (MDR) Escherichia coli (E. coli) at the poultry–human interface motivates evaluating strictly lytic bacteriophages as targeted biocontrol candidates. A lytic E. coli phage (GADS24) was isolated from poultry waste in Saudi Arabia. Plaque formation and host range were assessed against 10 clinical E. coli isolates. Virion morphology was examined by transmission electron microscopy (TEM). Whole-genome sequencing (Illumina) and annotation (Prokka/RAST) were followed by comparative genomics (BLASTn 2.15.0, ANI JSpeciesWS: 2014–2025 Ribocon GmbH—Version: 5.0.3, dDDH GGDC: GGDC 3.0 and phylogenetic/proteomic analyses for taxonomic placement. GADS24 formed clear plaques and lysed 5 of 10 clinical E. coli isolates tested. TEM revealed an icosahedral capsid (~72.6 nm) and a contractile tail (~131.7 nm), consistent with Tevenvirinae/Mosigvirus morphology. The dsDNA genome is 168,896 bp (GC 43.8%) with 268 predicted ORFs and two tRNA genes (tRNA-Arg and tRNA-Met); no lysogeny-related genes were detected. The closest relative was Escherichia phage JN02 (98.44% ANI; 57.8% dDDH), supporting assignment to Mosigvirus while indicating a genome-resolved distinct lineage. The genome is available in GenBank (OQ703618). GADS24 represents a genome-resolved, strictly lytic Mosigvirus with in vitro biocontrol-relevant phenotyping against E. coli, supporting follow-up development for poultry-associated infection control and deeper phage–host interaction studies. Full article

Background: Evidence-based practice (EBP) has become a foundational component of modern healthcare globally. In Saudi Arabia, the understanding and application of EBP by respiratory therapists (RTs) remains underexplored. This study aimed to assess RTs’ behaviors, attitudes, awareness, knowledge, and barriers related to EBP. Methods: A previously validated online questionnaire was distributed to RTs across Saudi Arabia between February and July 2025. The survey collected sociodemographic data and included 14 items assessing behaviors, attitudes, awareness, knowledge, prior formal EBP training, and perceived barriers to EBP implementation. Results: A total of 301 RTs participated, with 290 completing the survey. Most participants (75.2%) held a bachelor’s degree. Overall, respondents demonstrated positive attitudes toward EBP, with more than 60% agreeing that understanding research methods is essential to respiratory therapy practice. The most frequently used resources for clinical decision-making were personal experience (67.3%), expert opinion (65.5%), and national or international guidelines (65.5%). Awareness of core EBP concepts was moderate; approximately 30% of participants reported a good understanding of terms such as “systematic review,” “quality of evidence,” and “risk of bias.” Several barriers to EBP implementation were identified, most commonly limited access to resources (25.2%), insufficient research knowledge and skills (23.8%), and lack of interest (21.0%). Conclusions: RTs in Saudi Arabia generally support EBP principles and use evidence-based resources in clinical decision-making. However, gaps in training, access to resources, and research competency limit full EBP implementation. Targeted strategies, including integrating mandatory EBP education, expanding professional development, and enhancing access to research resources, are recommended. Full article

Methyl farnesoate (MF) is a sesquiterpenoid hormone that controls a variety of physiological processes in crustaceans, including morphogenesis, development, reproduction, and molting. MF action is mediated by a transcriptional signaling cascade consisting of Methoprene-tolerant (Met), Steroid receptor coactivator (Src), Krüppel homolog 1 (Kr-h1), and Ecdysone response gene 93 (E93) transcription factors (TFs), and transcriptional co-regulators CREB-binding protein (CBP) and C-terminal-binding protein (CtBP). Phylogenetic and sequence analyses revealed that these genes were highly conserved across pancrustacean species. Met and Src were characterized as basic helix-loop-helix, Period (Per)-Aryl Hydrocarbon Nuclear Translocator (ARNT)-Single-minded (Sim) protein (bHLH-PAS) TFs; Kr-h1 was characterized as a C₂H₂ zinc finger TF with seven zinc finger motifs; E93 was characterized as a helix-turn-helix, pipsqueak (HTH_Psq) TF. CBP was identified by several zinc finger-binding regions with Transcription Adaptor Zinc Finger 1 and 2, Really Interesting New Gene, Plant homeodomain, and Z-type zinc finger domains; the Kinase-inducible Domain Interacting-transcription factor docking site; the Bromodomain-acetylated lysine recognition and binding site; the histone acetyltransferase domain; and a C-terminal CREB-binding region containing a nuclear receptor co-activator-binding domain. CtBP had a dehydrogenase domain with arginine-glutamate-histidine catalytic triad. 81 Met contigs, 45 Src contigs, 136 Kr-h1 contigs, 66 E93 contigs, 60 CBP contigs, and 172 CtBP contigs were identified across pancrustacean taxa, including decapod crustaceans. Bioinformatic identification and annotation of these TFs and co-regulators in brachyuran Y-organ (YO) transcriptomes suggests that MF signaling influences YO ecdysteroidogenesis; functional tests in the YO are needed to establish causality. Full article

Orbea is a morphologically diverse lineage within the subtribe Stapeliinae, yet plastome evolution in Arabian taxa remains insufficiently characterized. This study reports the first complete chloroplast genomes of Orbea sprengeri subsp. commutata and O. wissmannii var. eremastrum and investigates plastome structure, sequence variability, and phylogenetic relationships across tribe Ceropegieae. Chloroplast genomes were assembled, annotated, and compared with 13 published plastomes representing major Ceropegieae lineages. Both Arabian plastomes displayed the typical quadripartite structure and identical gene content of 114 unique genes, including 80 protein-coding genes, 30 transfer RNA genes, and four ribosomal RNA genes. However, O. wissmannii var. eremastrum exhibited pronounced structural divergence, possessing the largest plastome recorded for the tribe (170,054 bp), an 8.9 kb expansion of the inverted repeat regions, and an 8.4 kb inversion spanning the ndhG–ndhF region. Comparative analyses revealed conserved gene order across Ceropegieae but identified six highly variable loci (accD, clpP, ndhF, ycf1, psbM–trnD, and rpl32–trnL) as potential DNA barcodes. Selection pressure analyses indicated strong purifying selection across most genes, with localized adaptive signals in accD, ndhE, ycf1, and ycf2. Phylogenomic reconstruction consistently resolved the two Arabian Orbea taxa as a distinct clade separate from the African O. variegata. This study fills a gap in Ceropegieae plastid genomics and underscores the importance of sequencing additional Orbea species to capture the full extent of genomic variation within this diverse genus. Full article

Accurate measurement of semantic similarity between geographic terms is a fundamental challenge in geographic information science, directly influencing tasks such as knowledge retrieval, ontology-based reasoning, and semantic search in geographic information systems (GIS). Traditional ontology-based approaches primarily rely on a narrow set of features (e.g., semantic distance or depth), which inadequately capture the multidimensional and context-dependent nature of geographic semantics. To address this limitation, this study proposes an ontology-driven semantic similarity model that integrates a backpropagation (BP) neural network with multiple ontological features—hierarchical depth, node distance, concept density, and relational overlap. The BP network serves as a nonlinear optimization mechanism that adaptively learns the contributions of each feature through cross-validation, balancing interpretability and precision. Experimental evaluations on the Geo-Terminology Relatedness Dataset (GTRD) demonstrate that the proposed model outperforms traditional baselines, including the Thesaurus–Lexical Relatedness Measure (TLRM), Word2Vec, and SBERT (Sentence-BERT), with Spearman correlation improvements of 4.2%, 74.8% and 80.1%, respectively. Additionally, comparisons with Linear Regression and Random Forest models, as well as bootstrap analysis and error analysis, confirm the robustness and generalization of the BP-based approach. These results confirm that coupling structured ontological knowledge with data-driven learning enhances robustness and generalization in semantic similarity computation, providing a unified framework for geographic knowledge reasoning, terminology harmonization, and ontology-based information retrieval. Full article

Background. Eriobotrya seguinii (Lév.) Cardot ex Guillaumin (Rosaceae, Maleae) is native to China and inhabits various altitudes within the subtropical biome of the Yunnan-Guizhou Plateau. The complexity of the plant mitogenome has impeded a systematic description of this species, leading to a limited understanding of its evolutionary position. Methods. In this study, we constructed, annotated, characterized, and compared the complete E. seguinii mitogenome with previously reported Eriobotrya japonica. Results. The E. seguinii mitogenome exhibited a typical circular architecture, spanning 372,899 bp in length, with a GC content of 46%, making it the smallest and highest GC content of any known Eriobotrya species. It encodes 71 unique genes, comprising 47 protein-coding genes, 20 transfer RNA (tRNA) genes, and 4 ribosomal RNA (rRNA) genes. The genome contains rich repetitive sequences, with mononucleotides, A/T bias, and forward and palindromic repeats being the most prevalent. The predominant codons were GCU (Ala) and UAU (Tyr), with frequencies of 1.54 and 1.53, respectively. Thirteen genes (atp9, atp6, atp1, rps14, sdh4, sdh3, rps12, rnaseH, nad1, nad6, nad7, rpl16, and mttB) demonstrated high Pi values, ranging from 0.84 to 1. The evolutionary lineage of E. seguinii was explored using mitogenome data from 19 genera within the Rosaceae family, revealing that Eriobotrya species are monophyletic and closely related to E. japonica (MN481990). Conclusions. Understanding the mitogenome characteristics of E. seguinii enhances our understanding of its genesis and classification based on mitochondrial genome data. This study provides additional evidence for future research on the evolutionary relationships among species in the Rosaceae family. Full article

The presence of aberrant double-stranded DNA (dsDNA) in the cytoplasm of cells is sensed by unique pattern recognition receptors (PRRs) to trigger innate immune response. The cyclic GMP–AMP synthase (cGAS)–stimulator of interferon genes (STING) signaling pathway is activated by the presence of non-self or mislocalized self-dsDNA from nucleus or mitochondria released in response to DNA damage or cellular stress in the cytoplasm. Activation of cGAS leads to the synthesis of the second messenger cyclic GMP–AMP (cGAMP), which binds and activates STING, triggering downstream signaling cascades that result in the production of type I interferons (IFNs) and proinflammatory cytokines. Here, we show that diverse immunostimulatory dsDNA ligands and chemotherapy agents like Doxorubicin and Taxol trigger the integrated stress response (ISR) by activating endoplasmic reticulum (ER) stress kinase, protein kinase RNA-like ER kinase (PERK), in addition to the canonical IFN pathways. PERK-mediated phosphorylation and inactivation of the alpha subunit of eukaryotic translation initiation factor-2 (eIF2α) result in the formation of stress granules (SGs). SG formation by dsDNA was significantly reduced in PERK knockout cells or by inhibiting PERK activity. Transcriptional induction of IFNβ and cytokines, ISR signaling, and SG formation by dsDNA was dampened in cells lacking PERK activity, STING, or key stress-granule nucleating protein, Ras-GAP SH3 domain-binding protein 1 (G3BP1), demonstrating an important role of the signal transduction pathway mediated by STING and SG assembly. Lastly, STING regulates reactive oxygen species (ROS) production in response to DNA damage, highlighting the crosstalk between DNA sensing and oxidative stress pathways. Together, our data identify STING–PERK–G3BP1 signaling axis that couples cytosolic DNA sensing to stress response pathways in maintaining cellular homeostasis. Full article

Coal and gas outbursts constitute a major hazard for mining safety, which is critical for the sustainable development of China’s energy industry. Rapid, accurate, and reliable pre-diction is pivotal for preventing and controlling outburst incidents. Nevertheless, the mechanisms driving coal and gas outbursts involve highly complex influencing factors. Four main geological indicators were identified by examining the attributes of these factors and their association to outburst intensity. This study developed a machine learning-based prediction model for outburst risk. Five algorithms were evaluated: K Nearest Neighbors (KNN), Back Propagation (BP), Random Forest (RF), Support Vector Machine (SVM), and eXtreme Gradient Boosting (XGBoost). Model optimization was performed via Bayesian hyperparameter (BO) tuning. Model performance was assessed by the Receiver Operating Characteristic (ROC) curve; the optimized XGBoost model demonstrated strong predictive performance. To enhance model transparency and interpretability, the SHapley Additive exPlanations (SHAP) method was implemented. The SHAP analysis identified geological structure was the most important predictive feature, providing a practical decision support tool for mine executives to prevent and control outburst incidents. Full article

The rising global demand for prosthetic limbs, driven by approximately 185,000 amputations annually in the United States, underscores the need for innovative and cost-efficient solutions. This study explores the integration of hybrid materials, advanced 3D printing techniques, and smart sensing technologies to enhance prosthetic finger production. A Taguchi-based design of experiments (DoE) approach using an L09 orthogonal array was employed to systematically evaluate the effects of infill density, infill pattern, and print speed on the tensile behavior of FDM-printed PLA components. Findings reveal that higher infill densities (90%) and hexagonal patterns significantly enhance yield strength, ultimate tensile strength, and stiffness. Additionally, the rheological properties of polydimethylsiloxane (PDMS) were optimized at various temperatures (30–70 °C), characterizing its viscosity, shear-thinning factors, and stress behaviors for 3D bioprinting of flexible sensors. Barium titanate (BaTiO₃) was incorporated into PDMS to fabricate a flexible tactile sensor, achieving reliable open-circuit voltage readings under applied forces. Structural and functional components of the finger prosthesis were fabricated using FDM, stereolithography (SLA), and extrusion-based bioprinting (EBP) and assembled into a functional prototype. This research demonstrates the feasibility of integrating hybrid materials and advanced printing methodologies to create cost-effective, high-performance prosthetic components with enhanced mechanical properties and embedded sensing capabilities. Full article

The oil and gas sector operates in a high-risk environment defined by capital intensity, regulatory uncertainty, and volatile commodity prices. Although Artificial Intelligence (AI) is widely promoted as a lever for profitability, the mechanisms through which AI adoption translate into financial outcomes remain insufficiently specified in the oil and gas literature. Grounded in the Resource-Based View and Technology Adoption Theory, this study combines bibliometric mapping of 201 Scopus-indexed publications (2010–2025) with a focused comparative case analysis of important players (BP and Shell), based on publicly reported operational and financial indicators (e.g., operating cost, uptime-related evidence, and return on average capital employed—ROACE). Keyword co-occurrence analysis identifies five thematic clusters showing that efficiency-oriented AI use cases (optimization, automation, predictive maintenance, and digital twins) dominate the research landscape. A thematic synthesis of five highly cited studies further indicates that AI-enabled operational improvements are most consistently linked to measurable cost, productivity, or revenue effects. Case evidence suggests that large-scale predictive maintenance and digital twin programs can support capital efficiency by reducing unplanned downtime and structural costs, contributing to more resilient ROACE trajectories amid price swings. Overall, the findings support a conceptual pathway in which operational efficiency is a primary channel through which AI can create financial value, while underscoring the need for future firm-level empirical mediation tests using standardized KPIs. Full article

Understanding the influence of the morphological mechanisms of Mei Gui chairs on the emotional preferences of female users is crucial for achieving perceptual resonance in design. This study aims to investigate/explore the relationship between user preferences and design features to create furniture with greater emotional resonance. (1) Background: To develop a scientifically validated model for predicting user preferences in Mei Gui chair design by emotional factors and morphological mechanisms. (2) Methods: (a) Data Collection: Establish a dataset of Mei Gui chair morphological mechanisms based on the visual sequences of female users using the KJ method, factor analysis, K-means clustering, and triangular fuzzy numbers. (b) Preference Analysis: Use Eye-tracking Technology to identify female users’ preference areas for Mei Gui chair morphology and construct a morphological element preference library. (c) Feature Classification: Categorize the extracted feature elements into five classes. (d) Neural Activation Analysis: Utilize near-infrared brain functional imaging technology to conduct paired-sample T-tests on the five classes of features, identifying preferred backrest characteristics. (e) Model Validation: Integrate three factors (elegance, delicacy, comfort) into the final design scheme and compare the performance of the proposed EMD-KPCA-LSTM model with traditional BP neural network, SVM, and CNN models. (3) Results: The EMD-KPCA-LSTM model outperforms traditional models in capturing the relationship between user preferences and morphological mechanism design features, demonstrating higher predictive accuracy, better generalization ability, and stronger robustness. (4) Conclusions: The proposed model effectively integrates user preferences with Mei Gui chair design, providing a scientifically validated method for perceptual prediction in furniture design. Full article

Seawater has attracted increasing attention as a promising resource for hydrogen production via electrolysis. However, multivalent ions present in seawater can reduce the efficiency of direct seawater electrolysis (DSWE) by forming inorganic precipitates at the cathode. Bipolar membranes (BPMs) can mitigate precipitate formation by regulating local pH, thereby enhancing DSWE efficiency. Accordingly, this study focuses on the fabrication of a high-performance BPM for DSWE applications. The water-splitting performance of BPMs is strongly dependent on the properties of the catalyst at the bipolar junction. Herein, iron oxide (Fe₃O₄) nanoparticles were coated with cross-linked chitosan to improve solvent dispersibility and catalytic activity. The resulting core–shell catalyst exhibited excellent dispersibility, facilitating uniform incorporation into the BPM. Water-splitting flux measurements identified an optimal catalyst loading of approximately 3 μg cm⁻². The BPM containing Fe₃O₄–chitosan nanoparticles achieved a water-splitting flux of 26.2 μmol cm⁻² min⁻¹, which is 18.6% higher than that of a commercial BPM (BP-1E, Astom Corp., Tokyo, Japan). DSWE tests using artificial seawater as the catholyte and NaOH as the anolyte demonstrated lower cell voltage and stable catholyte acidification over 100 h compared to the commercial membrane. Full article

This study investigates the neutronic performance of burnable poisons (BPs) in an epithermal spectrum supercritical carbon dioxide (S-CO₂)-cooled reactor. Twelve candidate BP materials are systematically evaluated, including rare-earth oxides (e.g., HfO₂, Er₂O₃, Eu₂O₃, etc.) and boron-based compounds (B₄C and PACS). The deterministic neutron transport code KYLIN-I with the ENDF/B VI 45-group cross-section library is employed for analysis. According to the calculation results, Eu₂O₃ effectively suppresses the initial k_inf of the epithermal-spectrum fuel assembly to ~1.2 with a relatively low weight fraction (~2.6%) while maintaining a total temperature coefficient (TTC) lower than −1.4 pcm/K throughout the entire burnup period. HfO₂ and Er₂O₃, at approximately 15% weight fraction, achieve TTC values better than −2 pcm/K. Furthermore, both Eu₂O₃ and HfO₂ contribute to maintaining a low, stable power peaking factor (PPF) below 1.24 throughout the burnup process. This study provides a theoretical foundation and technical support for designing an efficient and safe S–CO₂-cooled nuclear reactor. It highlights the importance of selecting BP materials that are well-adapted to the neutron spectrum and optimizing the fuel assembly configuration accordingly. Full article