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23 pages, 2968 KB  
Article
Coordinated Growth and Physiological Adaptations to Cadmium Stress in Pomegranate (Punica granatum L.) Seedlings
by Hongfang Ren, Fan Cheng, Yuying Wang, Jingyi Huang, Xueqing Zhao and Zhaohe Yuan
Horticulturae 2025, 11(11), 1400; https://doi.org/10.3390/horticulturae11111400 (registering DOI) - 19 Nov 2025
Abstract
Phytoremediation utilizing woody plants represents a promising approach for mitigating cadmium (Cd) contamination; however, the potential of ornamental species such as Punica granatum L. (pomegranate) remains insufficiently characterized. This study evaluated the growth performance, physiological responses, and Cd accumulation patterns of pomegranate seedlings [...] Read more.
Phytoremediation utilizing woody plants represents a promising approach for mitigating cadmium (Cd) contamination; however, the potential of ornamental species such as Punica granatum L. (pomegranate) remains insufficiently characterized. This study evaluated the growth performance, physiological responses, and Cd accumulation patterns of pomegranate seedlings exposed to increasing Cd concentrations (T1–T6) in a hydroponic system. High Cd levels (≥T4) markedly suppressed plant growth, as evidenced by reductions in biomass, root necrosis, leaf wilting, and chlorosis. Photosynthetic efficiency was severely compromised, indicated by significant declines in chlorophyll content and key chlorophyll fluorescence parameters (Fv/Fm, ΦPSII, and qP). Simultaneously, increases in the chlorophyll a/b ratio, carotenoid content, and non-photochemical quenching (NPQ) reflected the activation of photoprotective mechanisms. A reduction in stomatal conductance (Gs) and net photosynthetic rate (Pn), coupled with elevated intercellular CO2 concentration (Ci), suggested that non-stomatal limitations were primarily responsible for photosynthetic inhibition. Cd exposure also triggered oxidative stress, as shown by increased levels of malondialdehyde (MDA) and hydrogen peroxide (H2O2). In response, seedlings activated antioxidative and osmotic adjustment pathways, including elevated peroxidase (POD) activity and the accumulation of glutathione (GSH), proline, soluble proteins, and sugars. Notably, pomegranate displayed a root-based Cd sequestration strategy, with high root accumulation (bioconcentration factor, BCF > 271) and minimal translocation to aerial tissues (translocation factor, TF < 0.17). These findings demonstrate that pomegranate seedlings exhibit pronounced tolerance to Cd stress and substantial bioaccumulation capacity, supporting their potential application as ornamental woody species for phytoremediation of Cd-contaminated environments. Full article
(This article belongs to the Special Issue Advances in Cultivation and Breeding of Woody Plants)
13 pages, 12778 KB  
Article
Data-Driven Planning Phase of Maritime SAR Using Satellite Observations
by Hengameh R. Dehkordi and Majid Forghani-elahabad
Appl. Sci. 2025, 15(22), 12299; https://doi.org/10.3390/app152212299 (registering DOI) - 19 Nov 2025
Abstract
Maritime search and rescue operations rely on accurate drift predictions to define effective search areas for missing persons. Existing systems often depict uncertainty using statistical ellipses or ensemble-based probability maps, which may not effectively capture directional biases and underlying flow structures. In this [...] Read more.
Maritime search and rescue operations rely on accurate drift predictions to define effective search areas for missing persons. Existing systems often depict uncertainty using statistical ellipses or ensemble-based probability maps, which may not effectively capture directional biases and underlying flow structures. In this study, we introduce a geometric framework that constructs possible object trajectories directly from the drift dynamics. Starting from the last known position, we integrate the translational and rotational drift components with arbitrary perturbations to model realistic scenarios. The resulting envelope of the trajectories defines a reachable set that adapts to the flow without relying on sampling or covariance estimations. Using satellite-derived wind and current data, we demonstrat that this approach produces envelopes that are physically consistent and operationally relevant. Our method offers a mathematically grounded alternative to ensemble techniques, enhancing interpretability and improving the SAR planning efficiency. We illustrate its effectiveness with examples that simulate real-world scenarios. Full article
26 pages, 3197 KB  
Article
Design and Fabrication of a Compact Evaporator–Absorber Unit with Mechanical Enhancement for LiBr–H2O Vertical Falling-Film Absorption, Part I: Experimental Validation
by Genis Díaz-Flórez, Carlos Alberto Olvera-Olvera, Santiago Villagrana-Barraza, Luis Octavio Solís-Sánchez, Héctor A. Guerrero-Osuna, Teodoro Ibarra-Pérez, Ramón Jaramillo-Martínez, Hans C. Correa-Aguado and Germán Díaz-Flórez
Technologies 2025, 13(11), 538; https://doi.org/10.3390/technologies13110538 (registering DOI) - 19 Nov 2025
Abstract
Compact, low-power absorption cooling supports decentralized refrigeration needs and is positioned here as a sustainable approach within environmental technologies. This paper presents the design, fabrication, and experimental validation of a compact LiBr–H2O evaporator–absorber, in which a low-energy fan assists in transporting [...] Read more.
Compact, low-power absorption cooling supports decentralized refrigeration needs and is positioned here as a sustainable approach within environmental technologies. This paper presents the design, fabrication, and experimental validation of a compact LiBr–H2O evaporator–absorber, in which a low-energy fan assists in transporting refrigerant vapor from the evaporator to the absorber within a single vertical falling-film vessel. Twelve heat-load phases were tested with the fan OFF/ON, while temperatures, pressures, and flow rates were continuously monitored. The analysis focuses on temperature and pressure separation metrics, as well as a dimensionless separation index. Results show that fan assistance stabilizes thermal and pressure differentials and attenuates oscillations across grouped loads. The most significant benefits are observed at low to intermediate heat inputs, whereas the effect becomes marginal at higher loads, indicating the dominance of natural transport mechanisms. The compact unit remains thermally stable under all tested conditions. These findings indicate that a simple, low-power mechanical enhancement can improve controllability in an integrated evaporator–absorber without complex internal geometries. Protected under a Mexican utility model (IMPI, MX 4573 B), this prototype provides a replicable experimental basis for supporting compact, low-power solutions for sustainable, decentralized cooling in the field of environmental technologies. Full article
(This article belongs to the Section Manufacturing Technology)
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15 pages, 1479 KB  
Article
Mortality Prediction in Diffuse Large B-Cell Lymphoma Using Supervised Machine Learning Models—A Retrospective Study
by Cosmin-Daniel Minciuna, Dorina Minciuna, Angela-Smaranda Dascalescu, Amalia Titieanu, Vlad-Andrei Cianga, Ion Antohe, Ingrid-Andrada Vasilache, Catalin-Doru Danaila and Lucian Miron
J. Clin. Med. 2025, 14(22), 8216; https://doi.org/10.3390/jcm14228216 (registering DOI) - 19 Nov 2025
Abstract
Background/Objectives: Diffuse large B-cell lymphoma (DLBCL) is a biologically and clinically heterogeneous malignancy with variable outcomes. Accurate risk prediction at diagnosis remains essential to guide treatment and follow-up strategies. In this retrospective study we aimed to assess the performance of multiple modeling [...] Read more.
Background/Objectives: Diffuse large B-cell lymphoma (DLBCL) is a biologically and clinically heterogeneous malignancy with variable outcomes. Accurate risk prediction at diagnosis remains essential to guide treatment and follow-up strategies. In this retrospective study we aimed to assess the performance of multiple modeling approaches to predict death by 26 months of follow-up in patients with DLBCL using data available in the diagnostic stage. Methods: In this study we included 412 patients with DLBCL who were evaluated, treated, and followed-up at the Regional Institute of Oncology in Iasi, Romania, between 2015 and 2023. Clinical and paraclinical data determined at baseline examination was used to train and test six machine learning models (logistic regression, random forest—RF, support vector machine with a radial-basis kernel—SVM-RBF, multilayer perceptron neural network—MLP, random survival forest—RSF, and extreme gradient boosting—XGBoost) and to compare their performance to the Cox proportional hazards model. Results: Among the models, RF achieved the highest discrimination (AUC = 0.9060), with balanced performance (accuracy = 0.833; F1 = 0.902), followed by XGBoost (AUC = 0.8335) and MLP (AUC = 0.7861; accuracy = 0.849). RF and logistic regression demonstrated the best calibration (Brier = 0.360 and 0.377). The Cox model achieved moderate discrimination (time-dependent AUC = 0.5561; C-index = 0.55). Conclusions: Our findings align with contemporary reports showing that machine learning frameworks can outperform classical prediction approaches. Full article
(This article belongs to the Section Hematology)
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27 pages, 1804 KB  
Article
Urea-N Activated Biochar Effectively Suppresses CO2 and N2O Emissions from Farmland Soil
by Xiao Wang, Yudong Zheng, Xuetong Liu, Dan Liu, Caiyun Cao, Kejiang Li, Ping Lu, Peiling Yang, Huiguang Wang, Chunlian Zheng and Hongkai Dang
Agronomy 2025, 15(11), 2655; https://doi.org/10.3390/agronomy15112655 (registering DOI) - 19 Nov 2025
Abstract
The inconsistent efficacy of biochar in mitigating agricultural greenhouse gas emissions remains a major barrier to its widespread adoption and the realization of its environmental benefits. This study aimed to develop a stable and efficient mitigation strategy by optimizing biochar physicochemical properties through [...] Read more.
The inconsistent efficacy of biochar in mitigating agricultural greenhouse gas emissions remains a major barrier to its widespread adoption and the realization of its environmental benefits. This study aimed to develop a stable and efficient mitigation strategy by optimizing biochar physicochemical properties through urea-N activation (corn stover: urea mass ratios of 5:1 and 15:1). Five treatments were established: CK (control), GC (fertilization), GB (fertilization + raw biochar), GAB5 (fertilization + low-N activated biochar), and GAB15 (fertilization + high-N activated biochar). Mechanisms were elucidated by monitoring soil profile (0–20 cm) gas concentrations and surface fluxes, combined with a comprehensive analysis of soil physicochemical properties, enzyme activities, and microbial biomass. Results demonstrated that activated biochar, particularly GAB15, significantly reduced cumulative CO2 (9.4%, p < 0.05) and N2O (45.2%, p < 0.05) emissions and their concentrations in the 0–10 cm layer. This superior efficacy was linked to profound improvements in key soil properties: GAB15 significantly enhanced soil cation exchange capacity (CEC, increased by 17.3%, p < 0.05), NH4+-N content (increased by 88.2%, p < 0.05), Mean Weight Diameter (MWD, increased by 13.0%), the content of water-stable aggregates >0.25 mm (R>0.25 mm, increased by 57.3%) (p < 0.05), dissolved organic carbon (DOC), and the MBC (microbial biomass carbon)/MBN (soil microbial biomass nitrogen) ratio. Redundancy analysis (RDA) and structural equation modeling (SEM) revealed core mechanisms: CO2 mitigation primarily stemmed from the physical protection of organic carbon within macroaggregates and a negative priming effect induced by an elevated MBC/MBN ratio; N2O mitigation was attributed to weakened nitrogen mineralization due to enhanced aggregate stability and reduced substrate (inorganic N) availability for nitrification/denitrification via strong adsorption at the biochar–soil interface. This study confirms that urea-activated biochar produced at a 15:1 corn stover-to-urea mass ratio (GAB15) effectively overcomes the inconsistent efficacy of conventional biochar by targeted physicochemical optimization, offering a promising and technically feasible approach for mitigating agricultural greenhouse gas emissions. Full article
(This article belongs to the Special Issue Crop Management in Water-Limited Cropping Systems)
22 pages, 683 KB  
Review
Can Myokines Serve as Supporters of Muscle–Brain Connectivity in Obesity and Type 2 Diabetes? Potential of Exercise and Nutrition Interventions
by Heaji Lee and Yunsook Lim
Nutrients 2025, 17(22), 3615; https://doi.org/10.3390/nu17223615 (registering DOI) - 19 Nov 2025
Abstract
Background/Objectives: Skeletal muscle–derived myokines have emerged as pivotal mediators of the muscle–brain axis, linking peripheral metabolic regulation with central nervous system function. These molecules may influence skeletal muscle maintenance, neuroplasticity, neuroinflammation, and cognitive performance, and their dysregulation is increasingly associated with metabolic and [...] Read more.
Background/Objectives: Skeletal muscle–derived myokines have emerged as pivotal mediators of the muscle–brain axis, linking peripheral metabolic regulation with central nervous system function. These molecules may influence skeletal muscle maintenance, neuroplasticity, neuroinflammation, and cognitive performance, and their dysregulation is increasingly associated with metabolic and cognitive impairment. In obesity (OB) and type 2 diabetes mellitus (T2DM), dysregulated myokine profiles characterized by reduced levels of irisin, brain-derived neurotrophic factor (BDNF), and cathepsin B (CTSB) have been reported and may contribute to the development of both sarcopenia and cognitive impairment. This review aims to summarize current evidence on myokine alterations in OB and T2DM and to evaluate how exercise- and nutrition-based interventions may modulate the muscle–brain axis to support metabolic and cognitive health. Methods: This narrative review synthesizes experimental, clinical, and translational studies examining (1) alterations in circulating myokines in OB and T2DM, (2) associations between myokines, skeletal muscle function, and neurocognitive outcomes, and (3) the modulatory effects of exercise and specific nutrients on myokine-mediated muscle–brain communication. Results: Available evidence indicates that OB and T2DM are frequently accompanied by reduced circulating levels of beneficial myokines such as irisin, BDNF, and CTSB, which may impair skeletal muscle integrity and contribute to cognitive decline. Restoring favorable myokine signaling through physical activity appears to enhance skeletal muscle maintenance, neuroplasticity, and metabolic homeostasis. Emerging data further suggest that selected nutrients can mimic or potentiate some exercise-induced myokine responses, thereby supporting both muscle and brain function. Collectively, these findings imply that combined exercise and nutrition strategies may exert synergistic or additive effects by reinforcing inter-organ communication along the muscle–brain axis. Conclusions: This review outlines current evidence on myokine alterations observed in OB and T2DM and discusses how exercise- and nutrition-based approaches may modulate the muscle–brain axis to mitigate metabolic dysfunction and preserve cognitive health. Targeting beneficial myokine pathways through tailored lifestyle interventions represents a promising avenue to support both skeletal muscle and neurocognitive function in individuals with metabolic disease. Full article
(This article belongs to the Special Issue Nutrition, Exercise, and Health: Nutritional Supplements, Exercise Training, Skeletal Muscle Health, and Performance)
23 pages, 14455 KB  
Article
Analysis of LightGlue Matching for Robust TIN-Based UAV Image Mosaicking
by Sunghyeon Kim, Seunghwan Ban, Hongjin Kim and Taejung Kim
Remote Sens. 2025, 17(22), 3767; https://doi.org/10.3390/rs17223767 (registering DOI) - 19 Nov 2025
Abstract
Recent advances in UAV (Unmanned Aerial Vehicle)-based remote sensing have significantly enhanced the efficiency of monitoring and managing agricultural and forested areas. However, the low-altitude and narrow-field-of-view characteristics of UAVs make robust image mosaicking essential for generating large-area composites. A TIN (triangulated irregular [...] Read more.
Recent advances in UAV (Unmanned Aerial Vehicle)-based remote sensing have significantly enhanced the efficiency of monitoring and managing agricultural and forested areas. However, the low-altitude and narrow-field-of-view characteristics of UAVs make robust image mosaicking essential for generating large-area composites. A TIN (triangulated irregular network)-based mosaicking framework is herein proposed to address this challenge. A TIN-based mosaicking method constructs a TIN from extracted tiepoints and the sparse point clouds generated by bundle adjustment, enabling rapid mosaic generation. Its performance strongly depends on the quality of tiepoint extraction. Traditional matching combinations, such as SIFT with Brute-Force and SIFT with FLANN, have been widely used due to their robustness in texture-rich areas, yet they often struggle in homogeneous or repetitive-pattern regions, leading to insufficient tiepoints and reduced mosaic quality. More recently, deep learning-based methods such as LightGlue have emerged, offering strong matching capabilities, but their robustness under UAV conditions involving large rotational variations remains insufficiently validated. In this study, we applied the publicly available LightGlue matcher to a TIN-based UAV mosaicking pipeline and compared its performance with traditional approaches to determine the most effective tiepoint extraction strategy. The evaluation encompassed three major stages—tiepoint extraction, bundle adjustment, and mosaic generation—using UAV datasets acquired over diverse terrains, including agricultural fields and forested areas. Both qualitative and quantitative assessments were conducted to analyze tiepoint distribution, geometric adjustment accuracy, and mosaic completeness. The experimental results demonstrated that the hybrid combination of SIFT and LightGlue consistently achieved stable and reliable performance across all datasets. Compared with traditional matching methods, this combination detected a greater number of tiepoints with a more uniform spatial distribution while maintaining competitive reprojection accuracy. It also improved the continuity of the TIN structure in low-texture regions and reduced mosaic voids, effectively mitigating the limitations of conventional approaches. These results demonstrate that the integration of LightGlue enhances the robustness of TIN-based UAV mosaicking without compromising geometric accuracy. Furthermore, this study provides a practical improvement to the photogrammetric TIN-based UAV mosaicking pipeline by incorporating a LightGlue matching technique, enabling more stable and continuous mosaicking even in challenging low-texture environments. Full article
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25 pages, 2461 KB  
Article
Cafeteria and Fast-Food Diets Induce Neuroinflammation, Social Deficits, but a Different Cardiometabolic Phenotype
by Andrej Feješ, Petronela Sušienková, Lucia Mihalovičová, Veronika Kunšteková, Radana Gurecká, Veronika Borbélyová, Peter Celec and Katarína Šebeková
Nutrients 2025, 17(22), 3614; https://doi.org/10.3390/nu17223614 (registering DOI) - 19 Nov 2025
Abstract
Background: Obesity is a risk factor for several non-communicable diseases and premature death. The Western-type diet, rich in calories and diverse in tastes, smells, and textures, promotes the onset and progression of obesity. We compared the effects of two Western-style palatable obesogenic diets—the [...] Read more.
Background: Obesity is a risk factor for several non-communicable diseases and premature death. The Western-type diet, rich in calories and diverse in tastes, smells, and textures, promotes the onset and progression of obesity. We compared the effects of two Western-style palatable obesogenic diets—the cafeteria (CAF) diet, which allows for self-selection of calorie-dense food items consumed by humans, and the fast-food diet (FFD)—composed of a fixed combination of cheeseburgers and fries—on the manifestation of obesity-related complications. Methods: 3-month-old female rats consumed either the control (CTRL), FFD, or CAF diet for 12 months. Body weight was monitored weekly. At the end of the experiment, rats underwent metabolic and behavioral testing. Cardiometabolic markers and those characterizing glycoxidative and carbonyl stress, inflammatory status, and tryptophan metabolism were determined. Results: The CAF rats gain most weight (CTRL: +111 ± 40 g; FFD: +211 ± 77 g; CAF: 316 ± 87 g). CAF feeding produced a classical metabolic syndrome–like profile with severe obesity, insulin resistance, dyslipidemia, and liver steatosis, whereas the FFD model led to moderate obesity with preserved insulin sensitivity but elevated blood pressure and hepatic cholesterol accumulation. Thus, the CAF group developed a severe metabolic syndrome-like pathology assessed as continuous metabolic syndrome z-core (CTRL: −2.3 ± 1.0; FFD: −0.4 ± 1.9; CAF: 3.0 ± 2.4). Despite these differences, both diets promoted neuroinflammation and social deficits, likely mediated through gut microbiota–derived metabolites such as 5-HIAA and indoxyl sulfate. Conclusions: In female rats, self-selected CAF diet drives more severe and distinct pattern of metabolic syndrome-like pathology than a fixed FFD. Full article
(This article belongs to the Special Issue Pathophysiology of Glucose and Lipid Metabolism in Noncommunicable Diseases (NCDs))
27 pages, 2752 KB  
Article
Harnessing Machine Learning for Multiclass Seismic Risk Assessment in Reinforced Concrete Structures
by Ali Erhan Yilmaz, Omer Faruk Cinar, Alper Aldemir, Burcu Güldür Erkal and Onur Coskun
Buildings 2025, 15(22), 4185; https://doi.org/10.3390/buildings15224185 (registering DOI) - 19 Nov 2025
Abstract
The objective of this study is to develop an artificial intelligence algorithm that can predict both the risk level and damage level of reinforced concrete structures through classification and proportioning. This algorithm identifies buildings that require preventive measures before an earthquake and buildings [...] Read more.
The objective of this study is to develop an artificial intelligence algorithm that can predict both the risk level and damage level of reinforced concrete structures through classification and proportioning. This algorithm identifies buildings that require preventive measures before an earthquake and buildings that require immediate repair or demolition after an earthquake. A key aspect of the approach is calculating each building’s risk level as the ratio of its risky story to the total number of stories. That calculation provides a normalized figure, enabling comparison between buildings of varying sizes and complexities in an equitable way. The dataset of this study includes 100 buildings affected by previous earthquakes in Türkiye and 782 buildings with detailed seismic analysis. Thirteen different building parameters, structural, seismic, and geometric, have been considered within the scope of this study. Rapid visual screening (RVS) methods were applied for structural integrity analysis, and machine learning models were used for improvement in accuracy and efficiency. In the comparison of the model sets, the approach achieved the highest accuracy of 77% with an ensemble of four models. The results demonstrate the value of blending AI with traditional methodologies for risk analysis. It shows a viable and scalable mechanism for prioritization of retrofit and inspections and helps engineers and policymakers enhance disaster preparedness. By identifying structures at high risk, this work contributes towards overall aims for earthquake resilience in buildings. This study introduces a Pearson-correlation-based feature analysis and a Random Oversampling strategy to enhance model balance. The ensemble model achieved 83% external accuracy and outperformed the traditional RVS method (68%), reducing computation time from minutes to seconds. Full article
(This article belongs to the Section Building Structures)
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37 pages, 1957 KB  
Article
Top-K Feature Selection for IoT Intrusion Detection: Contributions of XGBoost, LightGBM, and Random Forest
by Brou Médard Kouassi, Abou Bakary Ballo, Kacoutchy Jean Ayikpa, Diarra Mamadou and Minfonga Zié Jérôme Coulibaly
Future Internet 2025, 17(11), 529; https://doi.org/10.3390/fi17110529 (registering DOI) - 19 Nov 2025
Abstract
The rapid growth of the Internet of Things (IoT) has created vast networks of interconnected devices that are increasingly exposed to cyberattacks. Ensuring the security of such distributed systems requires efficient and adaptive intrusion detection mechanisms. However, conventional methods face limitations in processing [...] Read more.
The rapid growth of the Internet of Things (IoT) has created vast networks of interconnected devices that are increasingly exposed to cyberattacks. Ensuring the security of such distributed systems requires efficient and adaptive intrusion detection mechanisms. However, conventional methods face limitations in processing large and complex feature spaces. To address this issue, this study proposes an optimized intrusion detection approach based on Top-K feature selection combined with ensemble learning models, evaluated on the CICIoMT2024 dataset. Three algorithms, XGBoost, LightGBM, and Random Forest, were trained and tested on IoT datasets using three feature configurations: Top-10, Top-15, and the complete feature set. The results show that the Random Forest model provides the best balance between accuracy and computational efficiency, achieving 91.7% accuracy and an F1-score of 93% with the Top-10 subset while reducing processing time by 35%. These findings demonstrate that the Top-K selection strategy enhances the interpretability and performance of IDSs in IoT environments. Future work will extend this framework to real-time adaptive detection and edge computing integration for large-scale IoT deployments. Full article
(This article belongs to the Special Issue Machine Learning and Internet of Things in Industry 4.0)
17 pages, 1046 KB  
Article
Three-Dimensional Simulation on the Influence of Coated Rubber Chips on Concrete Properties
by Yisihak Gebre Tarekegn, Tom Lahmer, Abrham Gebre Tarekegn and Esayas Gebreyouhannes Ftwi
Buildings 2025, 15(22), 4186; https://doi.org/10.3390/buildings15224186 (registering DOI) - 19 Nov 2025
Abstract
Rubber chips, when used as a partial replacement for coarse aggregates in concrete, tend to increase ductility, absorb energy, and can be beneficial due to their ability to reduce impact forces and dampen vibrations. However, they lead to a substantial decrease in compressive [...] Read more.
Rubber chips, when used as a partial replacement for coarse aggregates in concrete, tend to increase ductility, absorb energy, and can be beneficial due to their ability to reduce impact forces and dampen vibrations. However, they lead to a substantial decrease in compressive strength compared to ordinary concrete. Due to the weak bond between rubber particles and the concrete matrix, sand-coating surface treatment was applied to enhance the interfacial properties of the rubber surface. In this research, a detailed numerical analysis was conducted in order to predict the mechanical and dynamic behavior of concrete by incorporating partially replaced coarse aggregates with uncoated and sand-coated rubber chips. The study also seeks to examine the effects of rubber inclusion on key parameters such as damping ratio and compressive strength, thereby providing insights into the effectiveness of using recycled rubber as a sustainable alternative material in concrete production. The compressive strength and damping ratio of concrete were examined through a three-dimensional numerical simulation using ABAQUS/CAE 6.14-1. The results demonstrated that the optimal compressive strength was achieved with a 15% sand-coated rubber replacement, resulting in a 15.67% increment. Furthermore, the maximum improvements in damping ratios were observed to be 48.42% for uncoated rubber chips and 25% for coated ones, when compared to conventional concrete. These enhancements highlight the potential of both coated and uncoated rubber inclusions, due to rubber’s high elasticity. Moreover, at optimized levels, improved concrete properties can be achieved while promoting sustainability through material reuse. Full article
(This article belongs to the Section Building Materials, and Repair & Renovation)
26 pages, 819 KB  
Article
Healthcare Professionals’ Perceptions and Acceptance of Telemonitoring During Pregnancy and Early Labor: A Single-Center Survey
by Julia Jockusch, Sophie Schneider, Andrea Hochuli, Marianne Simone Joerger-Messerli, Daniel Surbek and Anda-Petronela Radan
Int. J. Environ. Res. Public Health 2025, 22(11), 1753; https://doi.org/10.3390/ijerph22111753 (registering DOI) - 19 Nov 2025
Abstract
The use of health monitoring software applications (apps) and devices is gaining popularity in obstetrics. The attitude and acceptance of different healthcare professionals regarding telemonitoring during pregnancy and the early phase of labor have not been sufficiently investigated. This study aims to assess [...] Read more.
The use of health monitoring software applications (apps) and devices is gaining popularity in obstetrics. The attitude and acceptance of different healthcare professionals regarding telemonitoring during pregnancy and the early phase of labor have not been sufficiently investigated. This study aims to assess healthcare professionals’ views on telemonitoring during pregnancy and childbirth, as well as data processing in the telemonitoring process. The study is part of an international project called `Newlife`, funded by the European Council and nationally funded by the Swiss State Secretariat for Education, Research and Innovation and Innosuisse. Eleven physicians from the fields of obstetrics and neonatology and five prenatal care nurses and five midwives were interviewed. First, participants were asked to fill out a written questionnaire with open and closed-ended answers, containing questions with a 5-point Likert scale. In a second step, a personal oral interview was conducted with all respondents. The study had an exploratory, qualitative focus. Questionnaire responses were summarized using descriptive statistics, while interview recordings were transcribed verbatim and systematically coded to identify recurring themes. Of the respondents (n = 20), five (25.0%) reported previous experience with telemonitoring in their professional practice, and all of them considered it useful. Regarding attitudes and acceptance, 57.1% (n = 12) of respondents would welcome telemonitoring during pregnancy and 52.4% (n = 11) during the early phase of labor, while 33.3% expressed no clear opinion. Rejection of telemonitoring was indicated by 9.6% (n = 2) during pregnancy, and 19.0% (n = 4) during early labor. In terms of perceived benefits, respondents highlighted early detection of problems (n = 13, 61.9%), improved prenatal care (n = 11, 52.4%), and better opportunities for data analysis and research (n = 12, 47.1%). Perceived risks included technical challenges and susceptibility to errors (n = 14, 66.7%), the lack of human contact and personal support (n = 14, 66.7%), and potentially inaccurate measurements (n = 12, 57.1%). This study offers insights into healthcare professionals’ attitudes and acceptance of telemonitoring in healthcare during pregnancy and the early stages of labor. There is a generally positive outlook but concerns and preferences exist. Addressing these considerations is essential for developing effective and user-friendly telemonitoring systems that benefit both healthcare professionals and pregnant women Full article
21 pages, 6125 KB  
Article
Climate Impact on the Seasonal and Interannual Variation in NDVI and GPP in Mongolia
by Justinas Kilpys, Egidijus Rimkus, Oyunsanaa Byambasuren, Jambajamts Lkhamjav and Tseren-Ochir Soyol-Erdene
Atmosphere 2025, 16(11), 1307; https://doi.org/10.3390/atmos16111307 (registering DOI) - 19 Nov 2025
Abstract
This study examined the influence of climate variability on vegetation dynamics in Mongolia from 2000 to 2024, using ERA5-Land reanalysis data together with the Normalized Difference Vegetation Index (NDVI) and Gross Primary Productivity (GPP) indicators. The results show a statistically significant mean annual [...] Read more.
This study examined the influence of climate variability on vegetation dynamics in Mongolia from 2000 to 2024, using ERA5-Land reanalysis data together with the Normalized Difference Vegetation Index (NDVI) and Gross Primary Productivity (GPP) indicators. The results show a statistically significant mean annual air temperature increase of 0.94 °C, with the most pronounced warming occurring in March (>1.5 °C/10 years). Annual precipitation increased by 32 mm (~13%), mainly in the northern and eastern regions. At the same time, the maximum NDVI increased at a rate of 0.025 units/10 years, particularly in the north and east, while no change or slight decline was observed in the central steppes during May–June. During the study period, the average annual GPP increased by 38%, from 0.25 to 0.35 kgCm−2, with the highest gains observed in northern forests and eastern steppes. Correlation analysis revealed that NDVI is most sensitive to temperature in early spring (r = 0.31) and to precipitation in summer (r = 0.45–0.50). GPP primarily is driven by temperature in spring (r = 0.68) and by precipitation during summer (r = 0.30). The results of this study indicate that vegetation productivity in Mongolia is sensitive to seasonal climate variability, with temperature being the primary factor influencing spring growth and precipitation controlling summer growth. Full article
(This article belongs to the Section Climatology)
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20 pages, 1312 KB  
Article
Cross-Subject Cognitive State Assessment for Unmanned System Operators Based on Brain Functional Connectivity
by Jun Chen, Fanzhou Zhao, Xinyu Zhang, Xiaoyu Hu and Kailun Ji
Drones 2025, 9(11), 808; https://doi.org/10.3390/drones9110808 (registering DOI) - 19 Nov 2025
Abstract
During the operation of Unmanned Aerial Vehicles (UAVs), the cognitive state of operators is prone to decline, posing a risk to task performance. However, many existing cognitive state assessment methods rely directly on raw electroencephalography (EEG) signals, yet exhibit limited robustness when applied [...] Read more.
During the operation of Unmanned Aerial Vehicles (UAVs), the cognitive state of operators is prone to decline, posing a risk to task performance. However, many existing cognitive state assessment methods rely directly on raw electroencephalography (EEG) signals, yet exhibit limited robustness when applied across different individuals. To address this limitation and leverage the spatial information and inter-electrode relationships effectively captured by brain functional connectivity networks, this paper proposes an assessment method based on functional connectivity networks. Data from ten participants under three cognitive states were used to train and test various models on a per-subject basis, where each participant’s data was partitioned into separate training and testing sets. The results demonstrate that the proposed method achieves a mean recognition accuracy of 98.76% with a variance of 0.0113, representing an improvement of at least 7.01% in accuracy and a reduction of at least 0.0191 in variance compared to conventional approaches. This approach facilitates timely cognitive state identification, thereby enhancing the reliability of human–machine interaction in unmanned systems. Full article
(This article belongs to the Topic International Conference on Autonomous Unmanned Systems (5th ICAUS 2025))
18 pages, 2285 KB  
Review
Harvest Recovery of a North Atlantic Intertidal Seaweed, Ascophyllum nodosum: Experimental Design Issues
by Allison A. Snow, David Porter, David J. Garbary and Herb Vandermeulen
J. Mar. Sci. Eng. 2025, 13(11), 2207; https://doi.org/10.3390/jmse13112207 (registering DOI) - 19 Nov 2025
Abstract
As the global demand for seaweed products increases, resource managers, conservation groups, and other stakeholders strive to protect wild seaweed populations and the ecosystem services they provide from the damaging effects of over-harvesting. Ascophyllum nodosum (rockweed) is a slow-growing, intertidal brown alga of [...] Read more.
As the global demand for seaweed products increases, resource managers, conservation groups, and other stakeholders strive to protect wild seaweed populations and the ecosystem services they provide from the damaging effects of over-harvesting. Ascophyllum nodosum (rockweed) is a slow-growing, intertidal brown alga of the North Atlantic that is commercially harvested for crop biostimulants, soil conditioners, and other products. Rockweed is considered a foundation species due to its high abundance, tall canopy, habitat characteristics, and role in detrital food webs. Rockweed shoots survive after harvesting if the holdfast remains intact, but rates of canopy and biomass recovery depend on the intensity of harvesting. In Maine, USA, and eastern Canada, little is known about how harvesting rockweed at various intensities affects recovery rates of algal height or biomass. Herein, we evaluate published studies and suggest improved experimental designs. Most experimental studies focus on a single harvest event, often with incomplete data on control plots, amount of biomass removed, or previous harvesting history at study sites. Much has been learned from previous work, but more rigorous studies are needed to develop harvest recommendations that address both commercial and conservation-related goals. Importantly, experimental studies of the effects of repeated harvesting on rockweed beds are lacking. Full article
(This article belongs to the Section Marine Biology)
18 pages, 2881 KB  
Article
A European Début: The Asian Parasitoid Encarsia nipponica Targets the Invasive Aleurocanthus spiniferus in Northern Italy
by Elena Costi, Daniele Giannetti, Michele Cesari, Carmelo Rapisarda, Andrew Polaszek, Robert L. Kresslein and Lara Maistrello
Insects 2025, 16(11), 1181; https://doi.org/10.3390/insects16111181 (registering DOI) - 19 Nov 2025
Abstract
In this study, the invasive orange spiny whitefly (“OSW”; Aleurocanthus spiniferus) and a species of Encarsia parasitising its puparia were studied in three different areas of the province of Modena (Emilia-Romagna, northern Italy): a pear orchard in Bomporto, an organic pear orchard [...] Read more.
In this study, the invasive orange spiny whitefly (“OSW”; Aleurocanthus spiniferus) and a species of Encarsia parasitising its puparia were studied in three different areas of the province of Modena (Emilia-Romagna, northern Italy): a pear orchard in Bomporto, an organic pear orchard in Carpi, and the semi-natural botanical garden “La Pica” in San Felice sul Panaro. The material of both species was collected for taxonomic and molecular studies. The abundance of OSW and parasitoid activity were surveyed in whitefly puparia, with a focus on the botanical garden. A total of 1800 leaves of Malus domestica, Pyrus communis and Vitis vinifera were sampled to assess whitefly infestation. The results showed a significant variation in the abundance of A. spiniferus puparia, with the highest infestation observed in V. vinifera. Morphological and molecular analyses, including mitochondrial COI and rRNA 16S for whiteflies and COI and 28S for parasitoids, confirmed the identity of A. spiniferus and identified the parasitoid as Encarsia nipponica. Molecular data also revealed the presence of three haplotypes of A. spiniferus, including a haplotype from China, new to Europe. The parasitisation rate by E. nipponica was low (0.015%). Our results provide the first European record of E. nipponica and new genetic data on the invasion pathways of A. spiniferus. Collectively, these findings offer a critical baseline for monitoring their ecological interactions and developing future pest management strategies. Full article
(This article belongs to the Collection Biocontrol and Behavioral Approaches to Manage Invasive Insects)
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18 pages, 3174 KB  
Article
Hydration Properties and Modeling of Ternary Systems of Mechanically Modified Municipal Solid Waste Incineration Fly Ash–Blast Furnace Slag–Cement
by Zedong Qiu, Ziling Peng, Zhen Hu, Sha Wan, Gang Li, Xintong Xiao, Kun Liu, Zhicheng Xiang and Xian Zhou
Processes 2025, 13(11), 3736; https://doi.org/10.3390/pr13113736 (registering DOI) - 19 Nov 2025
Abstract
Municipal solid waste incineration fly ash (MSWIFA) can be reused as an admixture in cementitious materials, but its low activity limits its utilization as a resource. In this study, we systematically investigated the mineral and grinding characteristics of MSWIFA and then studied its [...] Read more.
Municipal solid waste incineration fly ash (MSWIFA) can be reused as an admixture in cementitious materials, but its low activity limits its utilization as a resource. In this study, we systematically investigated the mineral and grinding characteristics of MSWIFA and then studied its pretreatment and activation via mechanical force–surface modification. The results indicate that the fineness and angle of repose of MSWIFA during grinding are inversely proportional to grinding time, while specific surface area and powder fluidity increase. Agglomeration occurs in the later stage, and particle size fluctuates. Gray correlation analysis shows that MSWIFA powder with a particle size of 16–45 μm contributes most to compressive strength improvement. The composite surface modifier TEA-STPP benefits grinding, shortens ball-milling time, and increases active particle size content, thereby promoting hydration activity. The best process regarding the modifier was determined. MSWIFA and blast furnace slag (BFS) accelerate early hydration of ordinary Portland cement (OPC) and increase its reaction participation, promoting the generation of calcium chloroaluminate (Friedel’s salt) and monosulfate-aluminate phases (SO4-AFm) and significantly enhancing the hydration of tricalcium aluminate (C3A) in OPC. Full article
(This article belongs to the Section Chemical Processes and Systems)
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14 pages, 857 KB  
Systematic Review
Network Meta-Analysis of Bevacizumab Gamma Versus Competing Interventions for Treating Neovascular Age-Related Macular Degeneration in the United Kingdom
by Maria Lorenzi, Stephen Ebohon, Jennifer Kissner, Jedd Comiskey, Mayke Paap, Christine Bouchet, Andy Garnham and Erika Wissinger
J. Mark. Access Health Policy 2025, 13(4), 58; https://doi.org/10.3390/jmahp13040058 (registering DOI) - 19 Nov 2025
Abstract
This study aimed to determine the relative efficacy of bevacizumab gamma (an ophthalmic formulation of bevacizumab) versus alternative interventions relevant to the treatment of neovascular age-related macular degeneration (nAMD) in the United Kingdom (UK) via a systematic literature review (SLR) and network meta-analysis [...] Read more.
This study aimed to determine the relative efficacy of bevacizumab gamma (an ophthalmic formulation of bevacizumab) versus alternative interventions relevant to the treatment of neovascular age-related macular degeneration (nAMD) in the United Kingdom (UK) via a systematic literature review (SLR) and network meta-analysis (NMA). An SLR was conducted to identify randomized controlled trials (RCTs) of anti-vascular endothelial growth factor (anti-VEGF) therapies for the treatment of nAMD in adult patients relevant to the UK context. The included anti-VEGF treatments were ranibizumab, aflibercept, faricimab, and bevacizumab gamma. Bayesian NMA models were used to estimate relative efficacy in terms of change from baseline (CFB) in best-corrected visual acuity (BCVA) at 12 months, the proportion of patients gaining 15 or more letters at 12 months, and the proportion of patients losing less than 15 letters at 12 months. Twenty-two relevant RCTs were included in the NMA. At 12 months, all anti-VEGF treatments were similarly efficacious to ranibizumab 0.5 mg every four weeks (Q4W) in terms of CFB in BCVA, the proportion of patients gaining 15 or more letters, and the proportion of patients losing less than 15 letters (except for ranibizumab 0.5 mg every 12 weeks [Q12W] and ranibizumab 0.5 mg pro re nata [PRN]). Bevacizumab gamma provided similar improvements in visual acuity to other anti-VEGF treatments. Full article
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16 pages, 8568 KB  
Article
An Automatic System for Remote Monitoring of Bactrocera dorsalis Population
by Shao-Ping Chen, Shi-Lei Zhu, Rong-Zhou Qiu, Mei-Xiang Chi, Yan Shi, Jia-Xiong Chen, Yong Liang and Jian Zhao
Agriculture 2025, 15(22), 2391; https://doi.org/10.3390/agriculture15222391 (registering DOI) - 19 Nov 2025
Abstract
Bactrocera dorsalis (Hendel, 1912) is a highly destructive pest affecting fruits and vegetables, making population monitoring essential for farmers to implement timely control measures. In recent years, although automatic monitoring systems for B. dorsalis have been introduced, challenges such as limited accuracy, difficulty [...] Read more.
Bactrocera dorsalis (Hendel, 1912) is a highly destructive pest affecting fruits and vegetables, making population monitoring essential for farmers to implement timely control measures. In recent years, although automatic monitoring systems for B. dorsalis have been introduced, challenges such as limited accuracy, difficulty in accurately identifying the target pest using infrared interruption sensors alone, and high labor requirements persist. This study presents an automatic monitoring system consisting of intelligent bait equipment (IBE), an advanced detection model based on YOLOv8, and an online monitoring platform. The developed IBE is equipped with cameras, attractant-based lures, and an automatic removal mechanism for B. dorsalis. Field tests demonstrated the IBE exhibited an attractiveness to B. dorsalis comparable to conventional traps, achieved a near-perfect cleaning efficiency (~100%), and maintained a reliable wireless transmission system. The YOLOv8l-based automatic pest detection model outperformed other YOLOv8 variants (n, s, m, x), achieving the highest precision (95.17%), recall (94.15%) and F1 score (94.66%), underscoring its effectiveness in pest detection. Further analysis of the impact of B. dorsalis density on YOLOv8l’s detection performance revealed a decline in accuracy as density increased; however, even at high densities, the model maintained a strong F1 score of 93.36%, demonstrating robustness. Finally, the automatic pest detection model was integrated into ‘YunShanPu’, an online platform for real-time pest monitoring. The proposed method has demonstrated promising performance in the automatic identification and counting of B. dorsalis and has potential for monitoring B. dorsalis populations continuously, providing early warning and forecasting for integrated pest management. Full article
(This article belongs to the Section Crop Protection, Diseases, Pests and Weeds)
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34 pages, 2440 KB  
Review
Nano-Biotechnology in Soil Remediation: Use of Nanomaterials to Promote Plant Growth and Stress Tolerance
by Xunfeng Chen, Shuoqi Wang, Huijuan Lai, Linjing Deng, Qin Zhong, Charles Obinwanne Okoye, Qijian Niu, Yanping Jing, Juncai Wang and Jianxiong Jiang
Nanomaterials 2025, 15(22), 1743; https://doi.org/10.3390/nano15221743 (registering DOI) - 19 Nov 2025
Abstract
Soil degradation and pollution pose significant threats to global agricultural sustainability and food security. Conventional remediation methods are often constrained by low efficiency, high cost, and potential secondary pollution. Nanobiotechnology, an emerging interdisciplinary field, offers innovative solutions by integrating functional nanomaterials with plant–microbe [...] Read more.
Soil degradation and pollution pose significant threats to global agricultural sustainability and food security. Conventional remediation methods are often constrained by low efficiency, high cost, and potential secondary pollution. Nanobiotechnology, an emerging interdisciplinary field, offers innovative solutions by integrating functional nanomaterials with plant–microbe interactions to advance soil remediation and sustainable agriculture. This review systematically elaborates on the mechanisms and applications of nanomaterials in soil remediation and enhanced plant stress resilience. For contaminant removal, nanomaterials such as nano-zero-valent iron (nZVI) and carbon nanotubes effectively immobilize or degrade heavy metals and organic pollutants through adsorption, catalysis, and other reactive mechanisms. In agriculture, nanofertilizers facilitate the regulated release of nutrients, thereby markedly enhancing nutrient use efficiency. Concurrently, certain nanoparticles mitigate a range of abiotic stresses—such as drought, salinity, and heavy metal toxicity—through the regulation of phytohormone balance, augmentation of photosynthetic performance, and reinforcement of antioxidant defenses. However, concerns regarding the environmental behavior, ecotoxicity, and long-term safety of nanomaterials remain. Future research should prioritize the development of smart, responsive nanosystems, elucidate the complex interactions among nanomaterials, plants, and microbes, and establish comprehensive life-cycle assessment and standardized risk evaluation frameworks. These efforts are essential to ensuring the safe and scalable application of nanobiotechnology in environmental remediation and green agriculture. Full article
(This article belongs to the Special Issue The Role of Nanomaterials in Soils and Plants)
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28 pages, 641 KB  
Article
An Integrated Approach Using Temperature–Humidity Index, Productivity, and Welfare Indicators for Herd-Level Heat Stress Assessment in Dairy Cows
by Roman Mylostyvyi and Olena Izhboldina
Animals 2025, 15(22), 3341; https://doi.org/10.3390/ani15223341 (registering DOI) - 19 Nov 2025
Abstract
The temperature–humidity index (THI) remains one of the most widely used tools for assessing heat stress in dairy farming; however, its application is often limited by methodological inconsistencies and insufficient integration with welfare indicators. This study proposes a unified analytical framework for evaluating [...] Read more.
The temperature–humidity index (THI) remains one of the most widely used tools for assessing heat stress in dairy farming; however, its application is often limited by methodological inconsistencies and insufficient integration with welfare indicators. This study proposes a unified analytical framework for evaluating thermal load at the herd level by combining daily THI values with productivity, feed intake, and clinical indicators such as mastitis and lameness. The analysis was based on two years of herd-level data from a commercial dairy farm with naturally ventilated barns. General linear models (GLM) were applied to assess both direct and delayed effects of heat stress and to compare model reproducibility across years. The results confirmed that maximum daily THI had the strongest association with milk composition and dry matter intake, while cumulative heat load and elevated night-time THI contributed to increased mastitis and lameness incidence. The inclusion of welfare indicators substantially improved the explanatory power of THI-based models, providing a more biologically relevant assessment of heat stress. The proposed framework enhances the accuracy of herd-level monitoring and supports the development of predictive models for welfare-oriented management in dairy systems. Full article
(This article belongs to the Special Issue Heat Stress in Farm Animals: The Impacts of Climate Change on Animal Comfort Conditions)
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55 pages, 1586 KB  
Review
Non-Coding RNA in Type 2 Diabetes Cardio–Renal Complications and SGLT2 Inhibitor Response
by Elena Rykova, Elena Shmakova, Igor Damarov, Tatiana Merkulova and Julia Kzhyshkowska
Int. J. Mol. Sci. 2025, 26(22), 11198; https://doi.org/10.3390/ijms262211198 (registering DOI) - 19 Nov 2025
Abstract
Type 2 diabetes mellitus (T2DM) is characterized by an uncontrolled increase in blood glucose levels and insulin resistance in cells of various tissues. Vascular complications in T2DM have an inflammatory nature. Drugs with different mechanisms of action have been developed and used to [...] Read more.
Type 2 diabetes mellitus (T2DM) is characterized by an uncontrolled increase in blood glucose levels and insulin resistance in cells of various tissues. Vascular complications in T2DM have an inflammatory nature. Drugs with different mechanisms of action have been developed and used to treat T2DM, initially aimed at controlling blood glucose levels. Among them, sodium-glucose cotransporter 2 inhibitors (SGLT2-i) were developed as specific inhibitors of glucose reabsorption in the kidneys, but along with lowering blood glucose levels, they demonstrated multiple (including non-glycemic) positive effects in the treatment of T2DM related to their beneficial effects on the immune system. SGLT2 inhibitors can reduce the risk of diabetic cardiomyopathy (DCM) and chronic kidney disease (CKD) development in patients with and without diabetes. SGLT2-is improve cardio-renal complications through a number of signaling pathways, including those dependent on the involvement of non-coding RNAs (ncRNAs) and their targets. The best-studied classes of ncRNAs are microRNAs, which are short (less than 200 bases) RNAs (miRNAs), long non-coding RNAs (lncRNAs) (more than 200 bases), and circular RNAs (circRNAs). The regulatory effect of ncRNAs has broad physiological significance, and changes in the ncRNAs’ expression are associated with the pathogenesis of different diseases, including T2DM. RNA-seq allows the construction of networks of interactions of lncRNA/circRNA-miRNA-mRNA called competitive endogenous RNA (ceRNA) networks, to identify clinically significant molecular markers, to improve the mechanistic understanding of pathogenesis, and to contribute to the development of new diagnostics and therapies. Our review summarizes the role of non-coding RNA in the action of SGLT2 inhibitors in cardio-renal complications in T2DM. We focus on methods of detection, genetics, and the effects of non-coding RNA. Specific attention is given to the role of non-coding RNAs in the inflammatory reactions of innate immune cells in relation to the SGLT2 inhibitors. Full article
(This article belongs to the Special Issue 25th Anniversary of IJMS: Updates and Advances in “Molecular Immunology”)
19 pages, 3083 KB  
Article
Molecular Regulatory Networks Underlying Root Growth and Development in Crested Wheatgrass (Agropyron cristatum L.)
by He Zhu, Xinyu Li, Yanran Xu, Xiaxiang Zhang, Ruicai Long, Wang Ding, Ruyue Li, Yan Zhao, Xuemin Wang and Mingna Li
Agriculture 2025, 15(22), 2392; https://doi.org/10.3390/agriculture15222392 (registering DOI) - 19 Nov 2025
Abstract
Crested wheatgrass (Agropyron cristatum) is a perennial forage species characterized by extensive root systems that contribute to ecological restoration and stress resilience. This study aimed to elucidate the regulatory mechanisms of root growth and development through transcriptome analysis at three developmental [...] Read more.
Crested wheatgrass (Agropyron cristatum) is a perennial forage species characterized by extensive root systems that contribute to ecological restoration and stress resilience. This study aimed to elucidate the regulatory mechanisms of root growth and development through transcriptome analysis at three developmental stages (20, 28, and 42 days after germination). Morphological analyses revealed progressive increases in root length, biomass, and surface area over time. Transcriptomic profiling identified 28,518 differentially expressed genes (DEGs) between R-28 and R-20, 35,581 DEGs between R-42 and R-20, and 24,418 DEGs between R-42 and R-28, indicating extensive transcriptional reprogramming during root development. Functional enrichment analyses highlighted pathways involved in ribosome biogenesis, phenylpropanoid metabolism, and energy regulation. Notably, 45 bHLH, 57 NAC, 56 WRKY, and 6 GRAS genes were differentially expressed and well-annotated, underscoring their regulatory roles in root system development. Furthermore, 65 nitrogen metabolism-related genes and multiple hormone signaling pathways, including auxin, abscisic acid, and ethylene, exhibited dynamic expression patterns coordinating developmental and stress-responsive processes. Collectively, these findings provide novel insights into the regulatory networks governing A. cristatum root development and offer valuable genetic resources for functional genomics studies, ecological restoration efforts, and breeding programs. Full article
(This article belongs to the Section Crop Genetics, Genomics and Breeding)
14 pages, 17931 KB  
Article
Chemical Inactivation of Bacillus subtilis Endospores Preserves Recombinant Protein Antigenic Properties
by Amalia A. Saperi, Atiqah Hazan, Nurfatihah Zulkifli, Hai Yen Lee and Sazaly AbuBakar
Microorganisms 2025, 13(11), 2629; https://doi.org/10.3390/microorganisms13112629 (registering DOI) - 19 Nov 2025
Abstract
Recombinant Bacillus subtilis endospores are promising bacterial expression platforms for oral protein delivery, such as oral vaccines. A simple and effective spore inactivation method that preserves protein functionality, however, is needed to prevent potential shedding into the environment. This study evaluated iron or [...] Read more.
Recombinant Bacillus subtilis endospores are promising bacterial expression platforms for oral protein delivery, such as oral vaccines. A simple and effective spore inactivation method that preserves protein functionality, however, is needed to prevent potential shedding into the environment. This study evaluated iron or copper combined with EDTA and ethanol as sporicidal solutions for the inactivation of recombinant spores expressing the 1PR82 gene. Immunoblot and immunofluorescence (IF) assay confirmed the presence of antigenic proteins post-treatment, while electron microscopy (SEM/TEM) assessed spore morphology. Mice immunization tested immunogenicity, and fecal analysis monitored gastrointestinal persistence. Iron ethanol treatment completely inactivated the spores while maintaining recombinant protein detection using antibody-based assays. SEM/TEM revealed morphological damage, yet antigenicity was preserved, as evidenced by robust IgG responses in immunized mice. Fecal analysis showed no prolonged spore shedding, confirming effective inactivation. These findings demonstrate that iron ethanol efficiently inactivates recombinant B. subtilis spores without compromising protein antigenicity. Despite structural damage, the recombinant protein remained immunogenic, and inactivated spores posed no environmental persistence risk. This inactivation method supports the safe use of Bacillus subtilis recombinant spores for oral delivery applications, balancing inactivation efficacy with functional protein preservation. Further research could optimize this approach for clinical or industrial applications. Full article
(This article belongs to the Section Microbial Biotechnology)
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14 pages, 1816 KB  
Article
Sage Essential Oil as a Natural Antigenotoxic Agent: Comet Assay Findings and Pharmacological Relevance
by Sara Diogo Gonçalves, Igor Koval, Rita S. Matos and Ana Caramelo
Appl. Biosci. 2025, 4(4), 54; https://doi.org/10.3390/applbiosci4040054 (registering DOI) - 19 Nov 2025
Abstract
Oxidative stress is a major contributor to genomic instability and a key factor in the etiology of various chronic diseases. Natural compounds with antioxidant and DNA-protective properties are increasingly being explored as potential preventive agents. In this study, we investigated the antigenotoxic potential [...] Read more.
Oxidative stress is a major contributor to genomic instability and a key factor in the etiology of various chronic diseases. Natural compounds with antioxidant and DNA-protective properties are increasingly being explored as potential preventive agents. In this study, we investigated the antigenotoxic potential of Salvia sclarea L. (sage) essential oil in human peripheral blood mononuclear cells exposed to hydrogen peroxide-induced oxidative stress. The DNA damage was assessed using the in vivo Comet assay, and five concentrations of sage essential oil (0.2–3%) were evaluated, both with and without co-exposure to H2O2. The results show a dose-dependent reduction in DNA damage in cells treated with the essential oil, with significant protection observed at all tested concentrations. Chemical characterization of the essential oil revealed a high content of linalyl acetate (62.63%) and linalool (22.22%), compounds known for their antioxidant activities. These findings demonstrate the antigenotoxic capacity of S. sclarea essential oil and strengthen the evidence supporting its role as a natural agent capable of protecting human cells from oxidative DNA damage. The study contributes to the growing body of evidence on essential oils as multifunctional bioactive agents and highlights the importance of incorporating natural compounds into strategies aimed at mitigating oxidative DNA damage. Full article
(This article belongs to the Special Issue Plant Natural Compounds: From Discovery to Application (2nd Edition))
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24 pages, 13043 KB  
Article
Source and Precipitation Process of Gold in the Linglong Gold Deposit, Jiaodong Peninsula: Constraints from Trace Elements of Pyrite and S-Pb Isotopes
by Fei Ren, Zheng-Jiang Ding, Zhong-Yi Bao, Jun-Wei Wang, Shun-Xi Ma, Tao Niu, Kai-Qiang Geng, Bin Wang, Chao Li, Gui-Jie Li and Shan-Shan Li
Minerals 2025, 15(11), 1220; https://doi.org/10.3390/min15111220 (registering DOI) - 19 Nov 2025
Abstract
Jiaodong Gold Province is a globally rare giant gold cluster, with ongoing debates regarding its metallogenic material sources and mineralization mechanisms. This study focuses on the Linglong quartz-vein-type gold deposit within the Zhaoping Fault Zone, conducting in situ trace element and S-Pb isotope [...] Read more.
Jiaodong Gold Province is a globally rare giant gold cluster, with ongoing debates regarding its metallogenic material sources and mineralization mechanisms. This study focuses on the Linglong quartz-vein-type gold deposit within the Zhaoping Fault Zone, conducting in situ trace element and S-Pb isotope analyses of pyrite from different mineralization stages. The trace element characteristics were investigated to explore the sources of metallogenic materials, the evolution of ore-forming fluids, and the mechanisms of gold precipitation. The main findings are as follows: (1) In the Linglong gold deposit, gold primarily enters the pyrite lattice as a solid solution (Au+) through Au-As coupling. From the Py1 to Py3 stages, Co and Ni contents significantly decrease, while Cu, As, Au, and polymetallic element contents continuously increase. Additionally, Cu mainly replaces Fe2+ in the form of Cu2+, whereas Pb predominantly exists as micro inclusions of galena. (2) The S isotope (Py1: δ34S = +7.60‰–+8.25‰, Py2: δ34S = +6.15‰–+8.15‰, Py3: δ34S = +6.90‰–+9.10‰) and Pb isotope (206Pb/204Pb = 16.95–17.715, 207Pb/204Pb = 15.472–15.557, 208Pb/204Pb = 37.858–38.394) systems collectively constrain the ore-forming materials such that they are dominated by metasomatized enriched lithospheric mantle, with simultaneous mixing of crustal materials. (3) The ore-forming fluid underwent a continuous evolution process characterized by persistently decreasing temperatures and a transition from mantle-dominated to crust–mantle mixed sources. The Py1 stage was predominantly composed of mantle-derived magmatic fluids uncontaminated by crustal materials, representing a high-temperature, closed environment. In the Py2 stage, the fluid system transitioned to an open system with the incorporation of crustal materials. Through coupled substitution of “As3+ + Au+ → Fe2+” and dissolution–reprecipitation processes, gold was initially activated and enriched. During the Py3 stage, pyrite underwent dissolution–reprecipitation under tectonic stress and fluid activity, promoting extraordinary element enrichment and serving as the primary mechanism for gold precipitation. Concurrently, bismuth–tellurium melt interactions further facilitated the precipitation of gold minerals. Full article
(This article belongs to the Special Issue Gold–Polymetallic Deposits in Convergent Margins)
11 pages, 1428 KB  
Article
Design of a Novel Class of N-Heterocyclic Carbene Cycloplatinated Complexes Containing Pyrene Chromophores
by Zeping Zhang, Yaping Cheng, Geoffrey Gontard, Tim Riesebeck, Sandy Fornal, Thomas Strassner and Hani Amouri
Molecules 2025, 30(22), 4473; https://doi.org/10.3390/molecules30224473 (registering DOI) - 19 Nov 2025
Abstract
Cycloplatinated complexes incorporating pyrene chromophores of the formulae (C^C*)Pt(acac) (3, 4), (C^C* = Pyrenyl-NHC, acac = acetylacetonate) were prepared and fully characterized. For comparison, two regioisomeric complexes were prepared following synthetic procedures developed by us. One isomer has the Pt(II) [...] Read more.
Cycloplatinated complexes incorporating pyrene chromophores of the formulae (C^C*)Pt(acac) (3, 4), (C^C* = Pyrenyl-NHC, acac = acetylacetonate) were prepared and fully characterized. For comparison, two regioisomeric complexes were prepared following synthetic procedures developed by us. One isomer has the Pt(II) center attached to the 2-position of the pyrene chromophore, while the other regioisomer has the metal center attached at the 1-position of the organic chromophore. The molecular structures of 3 and 4 were ascertained by X-ray diffraction, and they prove the identity of the targeted compounds. Both complexes are emissive at room temperature in the red part of the spectrum in poly(methyl methacrylate) (PMMA), as well as at 77 K in 2-methyltetrahydrofuran (2-MeTHF). The regioisomer containing the Pt(II) at the 1-position shows enhanced emissive properties compared to the other regioisomer. Full article
(This article belongs to the Special Issue Inorganic Chemistry in Europe 2025)
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