Search Results (168)

Background/Objectives: Xanthones from the tropical fruit mangosteen (Garcinia mangostana) have been reported to modulate oxidative stress and inflammatory responses. This work explored the anti-inflammatory potential of mangosteen in the form of tinctures. Methods: Tinctures were prepared from the pericarp and leaves, characterized for their major constituents, and evaluated for their in vitro, anti-inflammatory and antioxidant potential. Results: HPLC analysis revealed eight major isoprenylated xanthones whose concentrations increased with an increasing alcohol percentage. α-Mangostin and γ-mangostin, two major xanthones present in the tinctures, were stable for 12 weeks at room and elevated (40 °C) temperatures, indicating stability of the tincture. In vitro luciferase reporter assays using HepG2-ARE revealed an alcohol concentration-dependent activation of Nrf2 by pericarp and leaf tinctures. The tinctures inhibited lipopolysaccharide (LPS)-induced production of nitric oxide (NO) and reactive oxygen species (ROS) in RAW264.7 cells. Garcinone C (GarC) and garcinone D (GarD) caused significant inhibition of LPS-induced NO production and iNOS expression. GarC and GarD also induced nuclear translocation of Nrf2 and upregulated heme oxygenase 1 (HO-1), NAD(P)H quinone dehydrogenase 1 (NQO1), and glutathione S-transferase Pi 1 (GSTP1) in RAW264.7 cells. Conclusions: Taken together, mangosteen tinctures are a significant source of prenylated xanthones with anti-inflammatory and antioxidant potential. Full article

Strategies to suppress methanogenesis must preserve the functional integrity of the rumen microbial ecosystem. Essential oils (EOs) have emerged as promising modulators of rumen microbial function, though their responses vary widely with chemical structure and inclusion level. This study evaluated the efficacy of selected EOs using detailed in vitro fermentation assays. Nine EOs—cinnamon, lavender, garlic (GAR), lemongrass (LEG), peppermint (PPM), eucalyptus, coriander, oregano, and ginger (GIN)—were evaluated for their effects on rumen fermentation and methane (CH₄) production using a 24 h in vitro batch culture system. Eight EOs were tested at two doses (Low and High) specific to each EO, while GIN was evaluated at a single dose. All treatments were incubated in a rumen fluid–buffer mix (1:1 for fermentation parameters and 1:4 for gas and CH₄ measurements) with a 55:45 forage-to-concentrate substrate (pH 6.9). Overall treatment effects were significant for all measured fermentation parameters (p < 0.01). Most treatments reduced total gas production, CH₄ emissions, and CH₄/total gas ratios compared with the control (p < 0.05), although several responses were dose-dependent or directly divergent. Essential oils showed clear, composition-dependent responses: non-terpenoid EOs produced the strongest but also the most variable antimethanogenic effects, with GAR, particularly at the lower dose, consistently achieving the greatest CH₄ inhibition while maintaining a favorable fermentation pattern. Conversely, terpenoid-based EOs induced moderate, dose-responsive CH₄ reductions with minimal effects on overall fermentation. At the higher dose, PPM suppressed CH₄ without altering major volatile fatty acid (VFA) patterns aside from increases in valerate and branched-chain VFA, whereas LEG reduced CH₄ only when accompanied by marked fermentation depression. Monensin validated its role as an effective positive control. Overall, GAR, characterized by sulfur-based bioactives, emerged as the most effective candidate for CH₄ mitigation under the tested in vitro conditions, highlighting the importance of chemical composition and inclusion level in determining efficacy and reinforcing the need for in vivo validation. Full article

This paper develops a quantitative framework for climate–financial risk measurement that combines a spatially explicit jump–diffusion asset–loss model with prudentially aligned risk metrics. The approach connects regional physical hazards and transition variables derived from climate-consistent pathways to asset returns and credit parameters through the use of climate-adjusted volatilities and jump intensities. Fat tails and geographic heterogeneity are captured by it, which conventional diffusion-based or purely narrative stress tests fail to reflect. The framework delivers portfolio-level Spatial Climate Value-at-Risk (SCVaR) and Expected Shortfall (ES) across scenario–horizon matrices and incorporates an explicit robustness layer (block bootstrap confidence intervals, unconditional/conditional coverage backtests, and structural-stability tests). All ES measures are understood as Conditional Expected Shortfall (CES), i.e., tail expectations evaluated conditional on climate stress scenarios. Applications to bank loan books, pension portfolios, and sovereign exposures show how climate shocks reprice assets, alter default and recovery dynamics, and amplify tail losses in a region- and sector-dependent manner. The resulting, statistically validated outputs are designed to be decision-useful for Internal Capital Adequacy Assessment Process (ICAAP) and Pillar 2: climate-adjusted capital buffers, scenario-based stress calibration, and disclosure bridges that complement alignment metrics such as the Green Asset Ratio (GAR). Overall, the framework operationalises a move from exposure tallies to forward-looking, risk-sensitive, and auditable measures suitable for supervisory dialogue and internal risk appetite. Full article

Accurate representation of structural geometry, physical properties, and boundary conditions remains a major challenge in the finite element (FE) modeling of jacket structures. To address these difficulties, this study proposes a multi-source data synchronous updating framework for FE models based on the Genetic Aggregated Response Surface (GARS) and the Non-dominated Sorting Genetic Algorithm III (NSGA-III). First, vibration and strain tests were simultaneously conducted on an indoor jacket platform structure to obtain its natural frequencies and local dynamic strain responses. The measured data were processed to extract the first three natural frequencies and dynamic strain time histories at two critical locations, which served as reference data for model updating. An initial FE model of the jacket platform structure was then established, and sensitivity analysis was performed to identify the parameters requiring updating. Based on the simulation results, GARS was employed to construct response surface models describing the relationship between structural responses (natural frequencies and local strains) and the parameters to be updated, replacing FE analyses during optimization. Finally, NSGA-III was utilized to achieve synchronous updating of the FE model using multi-source data, and the updated geometric parameters were experimentally validated. The results demonstrate that errors in the first three natural frequencies of the FE model were reduced from 3.44%, −7.31%, and 5.88% to −0.02%, −0.43%, and 0.08%, respectively. Strain errors in the local region decreased from 12.96% and 10.33% to 1.4% and 2.1%. The corrected geometric parameters showed errors less than 1.85% when compared with actual measurements. These findings verify the accuracy and applicability of the proposed method for updating jacket platform FE models, providing an effective reference for model updating of in-service offshore structures. Full article

Drivetrain systems operate under varying operating conditions (OCs), which often obscure early-stage fault signatures and hinder robust condition monitoring (CM). This work introduces an AI digital platform developed during the EEDRIVEN project, featuring a holistic CM framework that integrates statistical time series methods—using Generalized AutoRegressive (GAR) models in a multiple model fault diagnosis scheme—with deep learning approaches, including autoencoders and convolutional neural networks, enhanced through a dedicated decision fusion methodology. The platform addresses all key CM tasks, including fault detection, fault type identification, fault severity characterization, and remaining useful life (RUL) estimation, which is performed using a dynamics-informed health indicator derived from GAR parameters and a simple linear Wiener process model. Training for the platform relies on a limited set of experimental vibration signals from the physical drivetrain, augmented with high-fidelity multibody dynamics simulations and surrogate-model realizations to ensure coverage of the full space of OCs and fault scenarios. Its performance is validated on hundreds of inspection experiments using confusion matrices, ROC curves, and metric-based plots, while the decision fusion scheme significantly strengthens diagnostic reliability across the CM stages. The results demonstrate near-perfect fault detection (99.8%), 97.8% accuracy in fault type identification, and over 96% in severity characterization. Moreover, the method yields reliable early-stage RUL estimates for the outer gear of the drivetrain, with normalized errors < 20% and consistently narrow confidence bounds, which confirms the platform’s robustness and practicality for real-world drivetrain systems monitoring. Full article

This work investigates the viability of using NNs to select an appropriate controller for a dynamic system based on its current state. To this end, this work proposes a method for training a controller-scheduling policy using several learning algorithms, including deep reinforcement learning and evolutionary strategies. The performance of these scheduler-based approaches is evaluated on an inverted pendulum, and the results are compared with those of NNs that operate directly in a continuous action space and a backpropagation-based Control Scheduling Neural Network. The results demonstrate that machine learning can successfully train a policy to choose the correct controller. The findings highlight that evolutionary strategies offer a compelling trade-off between final performance and computational time, making them an efficient alternative among the scheduling methods tested. Full article

This paper addresses semi-supervised anomaly detection in settings where only a small subset of normal data can be labeled. Such conditions arise, for example, in industrial quality control of windshield wiper noise, where expert labeling is costly and limited. Our objective is to learn a one-class decision boundary that leverages the geometry of unlabeled data while remaining robust to contamination and scarcity of labeled normals. We propose a graph-attention-regularized deep support vector data description (GAR-DSVDD) model that combines a deep one-class enclosure with a latent k-nearest-neighbor graph whose edges are weighted by similarity- and score-aware attention. The resulting loss integrates (i) a distance-based enclosure on labeled normals, (ii) a graph smoothness term on squared distances over the attention-weighted graph, and (iii) a center-pull regularizer on unlabeled samples to avoid over-smoothing and boundary drift. Experiments on a controlled simulated dataset and an industrial windshield wiper acoustics dataset show that GAR-DSVDD consistently improves the F1 score under scarce label conditions. On average, F1 increases from 0.78 to 0.84 on the simulated benchmark and from 0.63 to 0.86 on the industrial case study relative to the best competing baseline. Full article

The tropical gar (Atractosteus tropicus) has significant ecological, economic, and cultural importance in southeast Mexico, where aquaculture is increasing and fish are frequently exposed to stress. In this sense, feed additives such as sage (Salvia officinalis) strengthen organisms’ growth, immune systems, antioxidant capacities, and digestive capabilities. A 30-day experiment was conducted on larvae to determine the effect of different concentrations of sage essential oil (0%, 0.5%, 1%, 1.5%, and 2% treatments) supplemented in balanced diets. Significant differences (p < 0.05) between 0.5% and 2% sage oil supplement treatments for average weight were found. The highest acid and alkaline proteases, chymotrypsin, leucine aminopeptidase, amylase, and lipase activities were obtained for the sage oil-supplemented treatments. In contrast, trypsin showed the highest activity for treatment 0%, followed by diets with 0.5% and 2% sage oil. Regarding the antioxidant enzymatic activity for GPx, CAT and SOD, the highest activity was obtained in the diet with 1% sage oil, while in PEROx, the highest activity was recorded in the treatment with 0%, 1.5% and 2% S. officinalis supplementation. On the other hand, for relative gene expression, the highest expression was observed in sage-supplemented treatments for the nod, zo-1, zo-2, and occ genes. In contrast, the lowest expression was found in supplemented treatments for the il-10 and muc2 genes. These findings suggest that incorporating sage essential oil into the diets of tropical gar larvae, particularly at concentrations of 1.66% and 1.77%, holds potential for enhancing aquaculture practices for this important species. Full article

Edible coatings enriched with antioxidants offer a promising approach to prolong the shelf life of oxidation-sensitive foods such as nuts. Nonetheless, not all formulations provide the expected protection, and understanding why is equally important. The aim of this study was to assess the effect of an Arabic gum/gelatin/ascorbyl palmitate (GAR/GEL/AP) coating on the quality of hazelnut kernels during storage at 23 °C and ~40% relative humidity. The coating was applied by dipping hazelnuts in a 20% ethanolic solution containing GAR/GEL 75/25 blend (10% w/w), glycerol (1% w/w), Tween 80 (0.25% w/w), and AP (2% w/w), followed by drying. Control (uncoated) and coated hazelnuts were stored in plastic containers and evaluated at 1, 2, 4, 8, and 16 weeks for weight loss, moisture content, hardness, color, 2,2-diphenyl-1-picrylhydrazyl radical (DPPH*) scavenging activity, acid and peroxide values, and thiobarbituric acid reactive substances (TBARS) level. Coated hazelnuts showed higher initial moisture content (8.17%), stabilizing at 4.80% after one week, compared to 3.35% in uncoated samples. This increased moisture led to greater storage-related weight loss. The coating darkened the nuts and reduced their yellow hue. It had no significant effect on hardness, peroxide value, or TBARS index, but notably enhanced the antiradical potential. After 16 weeks, coated nuts had an acid value ~10 mg KOH/g lower than the control. In conclusion, the coating improved antioxidant capacity and reduced hydrolytic, but not oxidative, rancidity in hazelnuts. Therefore, further optimization of the coating formulation or application method is necessary to more effectively improve the shelf life of hazelnuts. Full article

The tropical gar (Atractosteus tropicus Gill, 1863) is a prehistoric fish of high nutritional value in southern Mexico and Central America. However, some aspects related to the effects caused by alternative protein sources, such as insect meal, as a substitute for fish meal on the growth and expression of digestive enzyme genes, are still unknown. A total of 225 juveniles of A. tropicus were used and fed five experimental diets, each in triplicate, with different levels of substitution of fishmeal (FM) protein with house cricket meal (HCM) protein. A control diet that contained no HCM (T1-0% HCM) was used, and substitutions ranged from 25 to 100% of FM protein by HCM (T2-25% HCM, T3-50% HCM, T4-75% HCM, and T5-100% HCM) for 45 days. The results of this study indicate that T4-75% HCM showed the best growth indices, such as feed efficiency (EF), feed conversion ratio (FCR), specific growth rate (SGR), as well as higher gene expression of pepsin and trypsin, while chymotrypsin showed higher expression in T3. The higher performance achieved in T4-75% HCM may be due to the fact that, in the early stages, insects are part of the natural diet of A. tropicus. The inclusion of cricket meal as a partial substitute for fish meal is not recommended in quantities greater than T4-75%. Full article

Chromosome transmission fidelity is vital for organism fitness. Yet, extrinsic and intrinsic changes can affect this process, leading to aneuploidy, the loss/gain of chromosomes, which is a hallmark of cancer. Here, using a haploid fission yeast Schizosaccharomyces pombe strain with a segmental aneuploidy, we assayed genome stability under different temperatures and altered gene dosage. We find that S. pombe genome stability is temperature-dependent and is unexpectedly modulated by intracellular levels of inorganic polyphosphate polymers (polyP). The vtc4⁺ gene, encoding a subunit of the polyP-generating VTC complex, is present twice due to the segmental aneuploidy resulting in a gene-dosage-coupled increase in polyP. Using strains with different amounts of polyP, we find a direct negative correlation between polyP and chromosome segregation fidelity. PolyP modulates the function of the conserved CCAN kinetochore subcomplex, as the abnormal growth phenotype caused by the mutant CCAN protein Fta2-291 was rescued in the absence of polyP, while extra polyP had the opposite effect. Importantly, this appears to occur in part by modulation of the nucleolin Gar2. Gar2 is the functional homolog of the Saccharomyces cerevisiae Nsr1 protein, whose function is modulated by posttranslational polyP-mediated polyphosphorylation. Thus, polyP modulates genome stability, linking cellular metabolism to chromosome transmission fidelity. Full article

Background/Objectives: Following the recent publication of reassuring outcomes from the ARA MED 330 protocol regarding long-term insulin use in pilots, combined with continuous advancements in diabetes technology, European aeromedical examiners are increasingly optimistic about establishing more flexible medical requirements for insulin-treated aviation professionals. These professionals have historically been considered unfit for duty due to hypoglycemic risks. According to current research, hypoglycemia, the primary incapacitation risk for flight crew, is considered virtually non-existent among air traffic controllers (ATCOs). Additionally, stress-induced hyperglycemia also represents a low-frequency risk in these professionals, who are experienced in managing highly stressful operational environments. This study presents a narrative review examining stress and its metabolic effects in healthy individuals, ATCOs, and people with diabetes (PwD). Methods: This narrative review was conducted based on a comprehensive PubMed search performed by two independent reviewers (GAR and AM) spanning January 2023 to January 2025. The search strategy focused on English-language, peer-reviewed studies involving human participants and addressed stress, glucose regulation, and occupational factors in ATCOs and people with diabetes. Additional relevant articles were identified through reference screening. A total of 33 studies met the inclusion criteria. Studies focusing solely on oxidative or molecular mechanisms were excluded from the analysis. Results: Stressful events consistently triggered the expected hyperglycemic reaction in both healthy individuals and PwD. However, the literature indicates ATCOs demonstrate remarkable stress resilience and adaptation to the demanding conditions of their work environment, suggesting a unique occupational profile regarding metabolic stress responses. Conclusions: These findings contribute valuable insights to ongoing discussions regarding aeromedical fitness standards. The evidence suggests that ATCOs may not face the same metabolic risks as flight crews, indicating that current medical certification processes for insulin-treated aviation professionals warrant reconsideration in light of this emerging evidence. This research supports the potential for more individualized, occupation-specific aeromedical standards that better reflect the actual risk profiles of different aviation roles. Full article

The Qinghai-Tibet Plateau, known as the “third pole” of the Earth with an average elevation of approximately 4500 m, offers a unique natural laboratory for probing the dynamic behavior of the global electric circuit. In this study, we conduct a comprehensive analysis of near-surface vertical atmospheric electric field (AEF) measurements collected at the Gar Station (80.1° E, 32.5° N; 4259 m a.s.l.) on the western Tibetan Plateau, spanning the period from November 2021 to December 2024. Fair-weather conditions are imposed. The annual mean AEF at Gar is ∼0.331 kV/m, significantly higher than values observed at lowland and plain sites, indicating a pronounced enhancement in atmospheric electricity associated with high-altitude conditions. Moreover, the AEF exhibits marked seasonal variability, peaking in December (∼0.411–0.559 kV/m) and valleying around July–August (∼0.150–0.242 kV/m), yielding an overall amplitude of approximately 0.3 kV/m. We speculate that this seasonal pattern is primarily driven by variations in aerosol concentration. During winter, increased aerosol loading from residential heating and vehicle emissions due to incomplete combustion reduces atmospheric conductivity by depleting free ions and decreasing ion mobility, thereby enhancing the near-surface AEF. In contrast, lower aerosol concentrations in summer lead to weaker AEF. This seasonal decline in aerosol levels is likely facilitated by stronger winds and more frequent rainfall in summer, which enhance aerosol dispersion and wet scavenging, whereas weaker winds and limited precipitation in winter favor near-surface aerosol accumulation. On diurnal timescales, the Gar AEF curve deviates significantly from the classical Carnegie curve, showing a distinct double-peak and double-trough structure, with maxima at ∼03:00 and 14:00 UT and minima near 00:00 and 10:00 UT. This deviation may partly reflect local influences related to sunrise and sunset. This study presents the longest ground-based AEF observations over the Qinghai–Tibet Plateau, providing a unique reference for future studies on altitude-dependent AEF variations and their coupling with space weather and climate processes. Full article

Class IId bacteriocins are linear, unmodified antimicrobial peptides produced by Gram-positive bacteria, and often display potent, narrow-spectrum inhibition spectra. Garvicin Q (GarQ) is a class IId bacteriocin produced by the lactic acid bacterium Lactococcus garvieae. It stands out for its unusual broad-spectrum antimicrobial activity against various bacterial species, including Listeria monocytogenes, Pediococcus pentosaceus, Carnobacterium maltaromaticum, Enterococcus faecalis, and Lactococcus spp. Its protein target is the mannose phosphotransferase system (Man-PTS) of susceptible bacterial strains, though little is known about the precise molecular mechanism behind GarQ’s unusual broad spectrum of activity. In this work, ¹³C- and ¹⁵N-labelled GarQ was recombinantly produced using our previously described “sandwiched” protein expression system in Escherichia coli. We also developed a protocol to purify a uniformly labelled sample of the small ubiquitin-like modifier His₆-SUMO, which is produced as a byproduct of the expression procedure. We demonstrated its use as a “free” protein standard for 3D NMR experiment calibrations. The GarQ solution structure was solved using triple-resonance nuclear magnetic resonance (NMR) spectroscopy and was compared with the structures of other Man-PTS-targeting bacteriocins. GarQ adopts a helix–hinge–helix fold, which is contrary to its structural predictions according to AlphaFold 3. Full article

Background: Autism Spectrum Disorder (ASD) encompasses a range of neurodevelopmental conditions characterized by impairments in social communication, restricted and repetitive behaviors, and sensory sensitivities. Despite increased awareness, timely diagnosis in Türkiye remains limited due to the lack of culturally appropriate, psychometrically robust assessment tools. Objective: This study aimed to develop, validate, and standardize the Autism Behavior Assessment Scale (ABAS) as a reliable and culturally adapted tool for assessing ASD-related behaviors in individuals aged 3–24 years in Türkiye. Methods: Employing a three-phase, nine-step scale development framework, data were gathered from 1275 informants (parents and professionals) across 14 provinces. The ABAS comprises 36 items rated on a three-point Likert scale, spanning four subscales: Restricted Repetitive Behaviors & Sensory Sensitivity (RRBSS), Social Interaction (SI), Social Communication (SC), and Non-Developmental Speech (NDS). Psychometric analyses included exploratory and confirmatory factor analysis, reliability testing, and validation against established instruments. Results: The four-factor structure was confirmed via EFA and CFA with excellent model fit. The ABAS demonstrated strong internal consistency (α = 0.91–0.96), test–retest reliability (r = 0.83), and criterion validity (r = 0.93 with GARS-2-TV; r = 0.84 with U-ODKL). Discriminant validity analyses showed that the ABAS accurately differentiated individuals with ASD from individuals with intellectual disabilities (ID) and individuals with hearing impairments (AUC = 0.99). Conclusions: The ABAS is a psychometrically sound, developmentally sensitive, and culturally grounded instrument for identifying and monitoring ASD-related behaviors in Türkiye. It holds promise for improving early detection and guiding educational and clinical interventions. Full article