Search Results (4,630)

Bile acids, the primary constituents of mammalian bile, are synthesized in the liver from cholesterol and secreted into the intestine to perform essential physiological functions. Primary bile acid synthesis is the principal pathway for cholesterol catabolism and whole-body cholesterol homeostasis, occurring predominantly via the classical and alternative pathways. To elucidate the effects of altitude on serum bile acid profiles and synthesis pathways in SD rats, this study utilized UPLC-MS/MS to analyze serum bile acid composition in animals housed at high and low altitudes. Additionally, qRT-PCR and Western blotting assessed mRNA transcription and protein expression of key genes involved in primary bile acid synthesis in the liver and intestinal tissues (ileum, duodenum, and colon). Results showed that serum levels of total and primary bile acids significantly decreased with increasing altitude. Furthermore, hepatic mRNA and protein expression of Cyp7a1, Cyp8b1, Cyp27a1, and Cyp7b1 were significantly downregulated. Fxr mRNA expression in the liver, ileum, duodenum, and colon was significantly decreased with increasing altitude. Meanwhile, the protein expression of both FGF15 and SHP showed a downward trend, with a significant decrease for FGF15 and a non-significant decrease for SHP. These findings suggest that primary bile acid synthesis in SD rats is dominated by the classical pathway. As altitude increases, bile acid synthesis in SD rats is significantly inhibited, indicating that high-altitude hypobaric hypoxia is the primary inhibitory factor. This study provides critical data for elucidating the adaptive mechanisms of bile acid metabolism in mammals exposed to high-altitude hypoxia, thereby establishing a theoretical foundation for investigating the regulation of host lipid metabolism influenced by such conditions. Full article

Diet form is increasingly recognized as a welfare-relevant factor in intensive aquaculture, yet the effects of feed cooking on fish behavioral and physiological welfare remain poorly characterized. Juvenile southern catfish (Silurus meridionalis; 6.18 ± 0.52 g) were reared for 6 weeks in an indoor recirculating aquaculture system and fed either raw grass carp (Ctenopharyngodon idella) muscle (fish fed raw muscle, FR) or cooked grass carp muscle (fish fed cooked muscle, FC; 15 min ramp to ~100 °C followed by 2–3 min at ~100 °C). Locomotor activity and anxiety-like behavior were assessed using the open-field test and an annular light–dark preference assay, respectively. Flow-through respirometry further revealed a significantly lower standard metabolic rate (SMR) in FC fish than in FR fish, decreasing from 10.30 to 6.83, which represents a 33.7% reduction. Endocrine and biochemical analyses showed that cooking significantly decreased serum total triiodothyronine (T3) by 23.8%, whereas routine serum biochemical indices remained unchanged. In brain tissue, dopamine (DA) was significantly reduced by 7.2% in the FC group, and RT-qPCR analysis of dopamine-related genes further showed a significant downregulation of the rate-limiting synthesis gene th. These results indicate that cooking primarily downshifts the activity-energy axis in southern catfish and is accompanied by coordinated thyroid and dopaminergic changes. To our knowledge, this is the first integrated study to evaluate the behavioral, metabolic, and neuroendocrine effects of cooked feed in S. meridionalis, providing a short-term phenotypic baseline for assessing welfare-relevant feeding scenarios in aquaculture. Full article

Optical-fibre daylighting systems (OFDS) harvest solar energy as a renewable lighting resource by delivering sunlight deep into green buildings. This emerging technology for sustainable infrastructure reduces electric-lighting demand; however, reported performance is difficult to compare across heterogeneous designs, metrics, and validation practices. Therefore, a PRISMA 2020–reported systematic literature review (SLR) of OFDS studies from three databases (Google Scholar, Scopus, and Web of Science; 2000–2025) was conducted, synthesising primary research that quantifies system- or component-level performance, with a focus on (i) plastic optical fibre (POF) transmission characteristics; and (ii) POF-based illuminance model validation. After de-duplication and screening, 106 primary studies were included, and two meta-analyses were performed where data were harmonised from 29 studies in total. Across reported POF configurations, attenuation ranged from 150 to 800 dB/km with a pooled mean of 332.8 dB/km, corresponding to a mean 1 m transmission of 92.7% and median design length scales of ∼3.7 m for 80% transmission and ∼11.6 m to half-power. Across illuminance validation datasets, models showed high linear agreement with experimental measurements (coefficient of determination ($R^2$) = 0.99; slope = 0.99) but typically underpredicted illuminance (geometric mean ratio = 1.16; mean absolute error (MAE) = 27.3 lux; mean absolute percentage error (MAPE) = 17.6%). These findings underscore the need for a standardised evaluation framework, including consistent metric definitions, robust uncertainty reporting, and reusable validation datasets to enable variance-weighted synthesis, while also identifying short-run POF routing as a key lever for improving system efficiency. In addition to providing the OFDS research agenda, this study serves as a roadmap for the industrial development of daylighting systems for green buildings based on harvesting solar energy, with its novelty lying in the PRISMA-guided evidence synthesis and quantitative meta-analytic consolidation of POF transmission and illuminance-validation performance. Full article

Background: Current endometriosis classification systems have important limitations in accurately describing total disease burden and predicting clinical outcomes. Existing staging frameworks often fail to integrate adenomyosis and do not adequately distinguish between genital and extragenital disease involvement. The aim of this article was to introduce the AGCES (American & Global College of Endometriosis Specialists) classification system, a novel framework designed to provide a more comprehensive and clinically meaningful approach to staging endometriosis. Methods: The AGCES classification system was developed through an expert consensus process involving scientific members of the American & Global College of Endometriosis Specialists (AGCES), informed by extensive surgical experience on thousands of endometriosis surgeries, synthesis of published evidence on disease pathophysiology and anatomical distribution, and systematic analysis of the limitations of existing classification systems (rASRM, ENZIAN, AAGL, EFI). Results: The framework integrates adenomyosis as a component of endometriosis staging and separates genital and extragenital disease into independent staging categories. Disease burden is reported using three parallel components representing adenomyosis (A), genital endometriosis (G), and extragenital endometriosis (E). A standardized operative reporting template and digital implementation through web-based applications were also developed to support clinical use. Conclusions: The AGCES classification system introduces a novel approach to endometriosis staging by integrating adenomyosis and separating genital and extragenital disease components. This framework provides a more complete assessment of disease burden and has the potential to improve clinical documentation, surgical planning, and research standardization in endometriosis care. Full article

To analyze, in an analytical cross-sectional observational study, the relationship between the plasma microRNA (miRNA) expression profile in children living with obesity and their metabolic health status. Based on body mass index percentiles (BMIp), the children were grouped into a control group (C) or an obesity group (Ob). Glucose, insulin, and low- and high-density lipoproteins (LDLs and HDLs, respectively), triacylglycerols (TG), and total cholesterol (TC) were measured. RNA from plasma was used for miRNA sequencing analysis (NextSeq 2000 platform). Differential miRNA expression was determined using counts obtained from the reference genome. Fifty controls (BMIp: 50.4 ± 23) and fifty children with obesity (BMIp: 97.54 ± 1.46) were included. The obese group presented hyperinsulinemia and insulin resistance. Sequencing revealed nine underexpressed and six overexpressed miRNAs in the obese group. In silico analysis suggested that these miRNAs may participate in regulating insulin secretion, protein synthesis, apoptosis, and the glycolytic pathway in pancreatic β-cells. Childhood obesity was associated with altered circulating levels of microRNAs linked to glucose metabolism, insulin resistance (IR) and β-cell survival. Reduced plasma levels of miR-126-3p, let-7a-5p, and miR-16-5p showed a high predictive value for hypertriglyceridemia and insulin resistance, indicating their potential relevance as early biomarkers or therapeutic targets in pediatric metabolic dysfunction. Full article

Peptaibols, predominantly secreted by Trichoderma species, are a class of linear peptides composed of five to twenty amino acid residues, synthesized non-ribosomally and enriched with α-amino isobutyric acid. These unique peptides appear to be highly effective in mediating the interactions between Trichoderma and plant pathogenic fungi. In this study, Ultra-Performance Liquid Chromatography–Quadrupole Time-Of-Flight Mass Spectrometry/Mass Spectrometry (UPLC-QTOF-MS/MS) technology was used to detect peptaibols profiles of Trichoderma strains during their interactions with the pathogen Fusarium graminearum. MS investigations of crude extracts derived from in vitro confrontations of Trichoderma atroviride T23 and its genetically modified counterparts, dual-culture assays of Mlae1, Mvel1, OElae1, and OEvel1 with F. graminearum were performed to shed light on the regulatory role of the velvet complex composed of LAE1&VEL1 in the synthesis of peptaibols during the microbial interaction. These results revealed intriguing variations in the total peptaibols produced during the interactions, as well as some differences in the specific peptaibol profiles between the confrontation and control tests. The overexpression strains, OElae1 and OEvel1, distinguished themselves by their proficiency in inducing long-residue peptaibols synthesis, attaining an impressive biocontrol index of up to 76%. The crude extracts containing peptaibols of OElae1 and OEvel1 demonstrated a capability to enhance cell membrane permeability and decrease DON toxin production in F. graminearum, and the crude extracts of OElae1 strains exhibited more effectiveness in reducing DON toxin production. In conclusion, the interaction with F. graminearum significantly impacted the peptaibol production in the examined Trichoderma strain, emphasizing the intricate interplay and reciprocal influence of genetic factors and environmental stimuli. Full article

Advances in dental material science over recent decades have significantly improved the mechanical, physical, esthetic, and adhesive properties of restorative systems. As clinical performance and durability have reached high standards, research has progressively shifted from purely mechanical replacement toward the development of bioactive materials capable of interacting beneficially with biological tissues. Rather than functioning solely as passive restoratives, contemporary materials are increasingly designed to contribute to disease prevention and tissue repair. Bioactive functionality encompasses both bioprotective and biopromotive effects, including antimicrobial activity, reinforcement of the dental substrate, promotion of remineralization, modulation of inflammatory responses, and stimulation of regenerative pathways. In this context, the surface pre-reacted glass ionomer (S-PRG) particle has emerged as a multifunctional bioactive technology. Its unique three-layer structure enables sustained release of multiple ions, fluoride, strontium, boron, sodium, silicate, and aluminum, associated with mineralization, biofilm inhibition, inflammatory regulation, and activation of cellular signaling pathways. An integrative review was conducted through a literature search in PubMed, SciELO and Scopus using the descriptors “Surface-reaction-type prereacted glass ionomer” and “S-PRG.” Experimental studies evaluating antimicrobial, anti-inflammatory, remineralizing, cellular, or regenerative effects of S-PRG-containing materials were considered eligible. A total of 49 studies met the inclusion criteria and were analyzed through descriptive synthesis. The available evidence indicates that the biological activity of S-PRG-containing materials extends beyond caries prevention, including modulation of inflammatory responses, enhancement of mineralization processes, and stimulation of cellular pathways related to tissue repair. These findings highlight the potential of S-PRG technology as a promising strategy for the development of restorative materials with regenerative and preventive properties. Full article

The renewable energy transition is a central component of global strategies to mitigate climate change and achieve sustainable development. However, the large-scale integration of renewable energy sources introduces significant challenges related to variability, system complexity, and operational efficiency. In recent years, artificial intelligence (AI) has emerged as a promising enabler for addressing these challenges through advanced data-driven forecasting, optimization, and decision-support capabilities. This study presents a systematic bibliometric and thematic review of peer-reviewed research on AI applications in the renewable energy transition published between 2015 and 2025, and was conducted following the PRISMA framework. Using the Scopus database, a total of 595 journal articles were analyzed through bibliometric performance indicators, network analysis, and thematic synthesis. The results reveal a rapidly growing and highly collaborative research field, characterized by strong international co-authorship and increasing methodological diversity. Early research predominantly focused on prediction and forecasting tasks, while more recent studies emphasize system-level optimization, energy management, and integrative AI applications across renewable technologies. The review further highlights key research trends, conceptual framing, and methodological orientations shaping the field. By consolidating dispersed literature and mapping its evolution, this study provides a structured overview that supports future research, policy development, and practical implementation of AI-enabled solutions for a sustainable energy transition. Full article

Roselle beverage residue (RBR), a by-product of Hibiscus sabdariffa L. processing, retains bioactive compounds, including soluble and insoluble dietary fiber and polyphenols. Its antihyperglycemic effect in type 2 diabetes mellitus (T2DM) has been previously demonstrated; however, its role in lipid metabolism remains unknown. This study assessed the preventive and therapeutic potential of RBR on dyslipidemia and hepatic steatosis in a rodent model of late-stage T2DM characterized by hyperglycemia and hypoinsulinemia. Male Wistar rats with T2DM induced by a high-fat and high-fructose diet combined with streptozotocin received 6% RBR supplementation as either a preventive intervention (starting at week 1 in healthy rats or week 9 in insulin-resistant rats) or a therapeutic intervention (starting at week 14 in diabetic rats). After 17 weeks, RBR supplementation significantly reduced serum triglycerides and total cholesterol, attenuating hepatic lipid accumulation regardless of the timing of intervention. Hepatic Acadm expression, involved in fatty acid β-oxidation, was significantly upregulated in rats treated with RBR from week 1 and 9, whereas no significant modulation was observed for genes related to fatty acid synthesis or uptake. These findings suggest that RBR supplementation may contribute to improving lipid metabolism and hepatic steatosis in a rat model of late-stage T2DM. Full article

Background/Objectives: The significant negative correlation between protein and oil content in soybean seeds is a long-standing bottleneck for conventional breeding. Its root cause lies in insufficient understanding of related molecular regulatory processes. Methods: We selected the CSSL_R19, a chromosome segment substitution line, to thoroughly investigate the intrinsic effects of the substituted segment on the high seed storage protein (SSP) and low fatty acid (FA) phenotype. Transcriptomic, proteomic, and metabolomic analyses were performed on the recurrent parent and R19. Results: A total of 1821 differentially expressed genes (DEGs), 12 differentially expressed proteins (DEPs), and 10 differentially accumulated metabolites (DEMs) were detected. Subsequently, an integrative examination of the data demonstrated that 28 DEGs, 5 DEPs, and 4 DEMs participated in biological processes such as carbohydrate metabolism, lipid degradation, as well as protein synthesis and transport. Mechanistically, down-regulation of PGM reduces the carbon source supply for FA synthesis; up-regulation of LOX, LACS, ACX, and KAT promotes FA degradation. SRP, SAR1, and HSP70 are involved in the synthesis and transport of SSP. Crucially, qRT-PCR validation performed on all 28 core DEGs showed that their expression trends were highly consistent with the transcriptome data, confirming the reliability of the findings. Conclusions: In conclusion, we propose a potential regulatory network that enhances SSP accumulation and reduces FA content. Altogether, these findings advance our understanding of storage compound accumulation in soybeans and guide future breeding strategies. Full article

With the increasing penetration of converter-based devices, harmonic distortion has become a major challenge for power quality monitoring in large-scale power systems. This study presents a systematic review of methods for modeling harmonic sources and their applicability to real-time monitoring of power distribution systems. The review was conducted following PRISMA guidelines, considering literature published between 2000 and 2026. Searches were performed across Scopus, IEEE Xplore, Web of Science, ScienceDirect, and MDPI using predefined keywords. A total of 128 peer-reviewed journal articles were included. Potential sources of bias were qualitatively assessed, including selection, retrieval, and classification bias; however, residual bias may still arise from database selection, keyword design, and study classification. A structured comparative framework is introduced, based on a six-dimension coverage scoring scheme and maturity analysis, enabling consistent evaluation across both methodological and deployment aspects. The robustness of this framework was evaluated using leave-one-out and perturbation analyses, indicating low variability in coverage scores and stable rankings across both corpora. A taxonomy of harmonic source modeling approaches is proposed. Comparative synthesis indicates that measurement-based approaches, particularly those leveraging distribution-level PMUs, show strong potential for real-time monitoring. Key challenges include D-PMU placement, data integration, and computational scalability. Future work should focus on physics-informed AI and digital twin-based monitoring. Full article

Load-redistribution false-data-injection (LR-FDI) attacks can degrade power-system operation by reshaping the perceived nodal demand pattern, thereby inducing congestion-aware redispatch and economic inefficiency while preserving the net system load. Prior LR-FDI studies commonly adopt bilevel/Stackelberg formulations with a continuous attack vector and an embedded operator response; however, these formulations often (i) do not represent explicit compromised-load selection, (ii) become computationally restrictive when combinatorial target sets are considered, and (iii) offer limited transparency for structured, stage-wise attack planning. This paper proposes a sequential two-stage attacker–operator framework for LR-FDI vulnerability assessment that integrates sparse load compromise decisions with screening-regularized attack synthesis and post-attack operational evaluation. In Stage-1, a mixed-integer nonlinear program identifies economically influential load buses via binary selection and determines admissible perturbation magnitudes under total-load conservation and proportional shift bounds. To confine the attacker-side search region and avoid economically exaggerated solutions, a screening-derived conservative operating-cost ceiling is first estimated through a parametric load-sensitivity analysis and then used to regularize the attack-synthesis step. In Stage-2, the system operator’s corrective redispatch is evaluated by solving an active-power-oriented economic dispatch model with nonlinear network-consistent assessment of operational outcomes. Using the IEEE 24-bus RTS, results show that the hourly operating-cost deviation reaches ≈0.2% in the most adverse feasible cases, and the cumulative daily impact approaches ≈5% only under selectively realizable compromised-load patterns, accompanied by a nearly 80% increase in total active-power transmission losses relative to the base case. Overall, the framework yields a practically grounded quantification of conditionally severe economic and network stress under coordinated LR-FDI scenarios and provides actionable insight for prioritizing vulnerable load locations for protection and monitoring. Full article

Satellite remote sensing has become essential for water quality assessment across inland and coastal environments, with rapid improvements in recent years. Significant advances have been made in detecting optically active parameters (such as chlorophyll-a, suspended matter, and turbidity), showing consistently strong performance across multiple studies. Specifically, the median validation performance (R²) derived from the quantitative synthesis indicates R² = 0.82 for chlorophyll-a (interquartile range—IQR: 0.75–0.90), R² = 0.80 for total suspended matter (IQR: 0.78–0.85), and R² = 0.88 for turbidity (IQR: 0.85–0.90). Conversely, the retrieval of optically inactive parameters (such as nutrients like total phosphorus and total nitrogen) remains more context dependent. It exhibits moderate, more variable results, with median R² = 0.68 (IQR: 0.64–0.74) for total phosphorus and R² = 0.75 (IQR: 0.70–0.80) for total nitrogen. These findings clearly illustrate the varying success of retrievals of optically active and inactive parameters and underscore the inherent difficulties of indirect estimation methods. However, high reported accuracy has yet to translate into transferable, uncertainty-informed, and operational monitoring systems. This gap stems from structural issues in validation design, physics integration, uncertainty management, and multi-sensor compatibility rather than data limitations alone. We present a PRISMA-guided, distribution-aware quantitative synthesis of 152 peer-reviewed studies (1980–2025), based on a systematic search protocol, to evaluate satellite-based retrievals of both optically active and inactive parameters. Instead of simply averaging performance, we analyse the empirical distributions of validation metrics, considering the validation protocol, sensor type, parameter category, degree of physics integration, and uncertainty quantification. The synthesis demonstrates that validation strategy often influences reported results more than the algorithm class itself, with accuracy inflated under non-independent cross-validation methods and notable variability between studies concealed by mean-based reports. Across four decades, four persistent structural challenges remain: limited transferability across sites and sensors beyond calibration areas; weak or implicit physical integration in many data-driven models; lack of or inconsistency in uncertainty quantification; and fragmented multi-sensor harmonisation that restricts operational scalability. To address these issues, we introduce two evidence-based coding frameworks: a physics-integration taxonomy (P0–P4) and an uncertainty-quantification hierarchy (U0–U4). Applying these frameworks shows that most studies remain focused on low-to-moderate levels of physics integration and primarily consider uncertainty at the prediction stage, with limited attention to upstream sources throughout the observation and inference process. Building on this structured synthesis, we propose a transferable, physics-informed, and uncertainty-aware conceptual framework that links model architecture, validation robustness, and probabilistic uncertainty to well-founded design principles. By shifting satellite water quality modelling from isolated algorithm demonstrations towards integrated, evidence-based system design, this study promotes scalable, decision-grade environmental monitoring amid the accelerating impacts of climate change. Full article

Fatty acids play critical roles in plant growth and stress adaptation, primarily through modulating membrane fluidity. This study combined bioinformatics (genome-wide identification and chromosomal localization) with experimental techniques (RT-qPCR, VIGS, and GC) to investigate the ARF family in Paeonia rockii. Seventeen PrARF genes were identified, showing evolutionary collinearity with Arabidopsis thaliana and Vitis vinifera and uneven chromosomal distribution. Among these, PrARF9 was specifically and highly expressed during late seed development, exhibiting a pattern highly consistent with the fatty acid synthesis key gene PrFAD3 and the accumulation trend of α-linolenic acid (ALA). In Nicotiana benthamiana, transient overexpression of PrARF9 upregulated its homologous gene NbFAD3, resulting in increased total fatty acid content and elevated lipid droplet accumulation. In contrast, in Paeonia rockii, silencing of PrARF9 downregulated PrFAD3 expression and reduced fatty acid levels, whereas overexpression of PrARF9 produced the opposite effect. We present a comprehensive analysis of the ARF gene family in P. rockii, combined with functional verification of a candidate gene regulating lipid synthesis. In summary, PrARF9 positively regulates PrFAD3, thereby participating in oil accumulation and ALA synthesis in P. rockii. Full article

Two mineral-based solid residues, namely coal gangue (CG) and phosphorus tailings (PT), two of the largest solid waste streams in the mining industry, were used as the sole metal feedstocks to fabricate a novel MgCaFeAl layered double hydroxide (LDH-GT) via a 700 °C calcination, acid leaching and hydrothermal coprecipitation route, with simultaneous synthesis of white carbon black from the reaction byproducts. Under optimized conditions (total metal load is 150 mg kg⁻¹, LDH-GT dose is 0.09 g, pH from 6 to 7), the synthesized material achieved concurrent immobilization efficiencies of 76.28%, 99.96%, and 99.95% for Cr (VI), Cd (II) and Ni (II), respectively, within a 24 h reaction period. TCLP leachability decreased by 82 to 91% relative to the untreated soil. After three wetting, drying and freeze–thaw cycles, the leached concentrations of all three metals remained below 0.3 mg L⁻¹, confirming excellent long-term stability. Mechanistic analyses revealed that Cr (VI) was mainly sequestered through interlayer anion exchange and surface complexation, whereas Cd (II) and Ni (II) were immobilized via isomorphic substitution into the LDH lattice, precipitation as carbonates, and incorporation into Fe/Mn oxides. A 7-day mung bean bioassay showed that LDH-GT amendment increased seed germination from 50% to 73%, enhanced root and shoot biomass by 1.1- to 1.6-fold, and decreased plant Cr, Cd, and Ni contents by over 80%. The 16S rRNA sequencing further demonstrated that LDH-GT reversed the decline in microbial α diversity induced by heavy metal stress, restored aerobic chemoheterotrophic and sulfur cycling functional guilds, and reduced pathogenic signatures. This study provides the demonstration of a waste-to-resource LDH that achieves efficient, durable remediation of multi-metal-contaminated soils, offering a scalable route for coupling solid waste valorization with in situ site restoration. Full article