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16 pages, 909 KiB  
Article
Is the Soil in Allotment Gardens Healthy Enough?—Relation Between Organic Matter Content and Selected Heavy Metals
by Dariusz Gruszka, Katarzyna Szopka, Iwona Gruss and Maja Złocka
Sustainability 2025, 17(16), 7424; https://doi.org/10.3390/su17167424 (registering DOI) - 16 Aug 2025
Abstract
This study was conducted in nine allotment garden complexes in Wrocław, West Poland (Central Europe). Soil samples were collected from each garden and analyzed for their total concentrations of Zn, Cu, Pb and Cd, alongside the percentage of organic carbon C. Contaminant levels [...] Read more.
This study was conducted in nine allotment garden complexes in Wrocław, West Poland (Central Europe). Soil samples were collected from each garden and analyzed for their total concentrations of Zn, Cu, Pb and Cd, alongside the percentage of organic carbon C. Contaminant levels varied widely between sites: Zn ranged from 101.1 to 3464.5 mg/kg, Cu from 24.93 to 322.45 mg/kg, Cd from 0.51 to 6.31 mg/kg, and Pb from 19.92 to 401.85 mg/kg. The highest metal contamination was found for the garden complex placed on the former impact of the Hutmen. The organic carbon content ranged from 2.12% to 7.64%, indicating substantial variability in organic matter levels across the studied sites. This variability may significantly influence the soils’ capacity to retain heavy metals. A significant positive correlation was observed between soil organic carbon and the total concentrations of Pb, Cu and Zn, suggesting that soils richer in organic matter may retain higher levels of heavy metals. These findings underscore the dual role of organic matter as both a beneficial soil component and a potential contributor to heavy metal retention in urban garden soils. Protecting and enhancing SOM in polluted soils is a beneficial strategy, remediating environmental damage while aligning with global sustainability goals. Full article
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16 pages, 2245 KiB  
Article
Health Risk Assessment of Toluene and Formaldehyde Based on a Short-Term Exposure Scenario: A Comparison of the Reference Concentration, Reference Dose, and Minimal Risk Level
by Ji-Eun Moon, Si-Hyun Park, Young-Hyun Kim, Hyeok Jang, Ji-Yun Jung, Sung-Won Yoon and Cheol-Min Lee
Toxics 2025, 13(8), 683; https://doi.org/10.3390/toxics13080683 (registering DOI) - 16 Aug 2025
Abstract
Conventional health risk assessments do not adequately reflect short-term exposure characteristics following chemical accidents. We aimed to evaluate the efficacy of existing assessment methods and propose a more suitable risk assessment approach for short-term exposure to hazardous chemicals. We analyzed foundational studies used [...] Read more.
Conventional health risk assessments do not adequately reflect short-term exposure characteristics following chemical accidents. We aimed to evaluate the efficacy of existing assessment methods and propose a more suitable risk assessment approach for short-term exposure to hazardous chemicals. We analyzed foundational studies used to derive reference concentration (RfC), reference dose (RfD), and minimal risk level (MRL) values and applied these health guidance values (HGVs) to a hypothetical chemical accident scenario. An analysis of the studies underlying each HGV revealed that, except for the RfC for formaldehyde and the RfD for toluene, all values were derived under research conditions comparable to their respective exposure durations. Given the differing toxicity mechanisms between acute and chronic exposures, MRLs that were aligned with the corresponding exposure durations supported more appropriate risk management decisions. The health risk assessment results showed that RfC/RfD-based hazard quotients (HQs) were consistently higher than MRL-based HQs across all age groups and both substances, indicating that RfC/RfD values tend to yield more conservative risk estimates. For formaldehyde, the use of RfC instead of MRL resulted in an additional 208 tiles (2.08 km2) being classified as areas of potential concern (HQ > 1) relative to the MRL-based evaluation. These findings highlighted that the selection of HGVs can significantly influence the spatial extent of areas of potential concern, potentially altering health risk determinations for large population groups. This study provides a scientific basis for improving exposure and risk assessment frameworks under short-term exposure conditions. It also serves as valuable foundational data for developing effective and rational risk management strategies during actual chemical accidents. To the best of our knowledge, this is the first study to apply MRLs to a short-term chemical accident scenario and directly compare them with traditional reference values. Full article
(This article belongs to the Section Exposome Analysis and Risk Assessment)
12 pages, 2516 KiB  
Article
Low-Profile, Shoe-Type Ankle–Foot Orthosis with Active Variable Ankle Stiffness via Wire–Fabric Compression Mechanism
by Eunbin Choe, Junyoung Moon, Jaewook Ryu, Seungtae Yang, Alireza Nasirzadeh, Sejin Kong, Youngsuk Choi and Giuk Lee
Biomimetics 2025, 10(8), 539; https://doi.org/10.3390/biomimetics10080539 (registering DOI) - 16 Aug 2025
Abstract
Acute ankle sprains frequently lead to chronic ankle instability and muscle atrophy by causing immobilization, which necessitates real-time stiffness modulation for ankle–foot orthoses (AFOs). This paper proposes Active Variable Compression Shoes (AVC-Shoes), an ankle support system inspired by the “heel-lock taping” technique, which [...] Read more.
Acute ankle sprains frequently lead to chronic ankle instability and muscle atrophy by causing immobilization, which necessitates real-time stiffness modulation for ankle–foot orthoses (AFOs). This paper proposes Active Variable Compression Shoes (AVC-Shoes), an ankle support system inspired by the “heel-lock taping” technique, which employs a wire–fabric compression mechanism to selectively stiffen ankle joints at crucial points in the gait cycle. The experimental results confirmed that AVC-Shoes achieve variable ankle stiffness in all directions, demonstrating dorsiflexion and plantarflexion stiffness ranges of up to 8.3 and 5.9 Nm/rad, respectively. Additionally, preliminary human testing involving three healthy participants revealed that the gastrocnemius muscle activity during the push-off phase in the active compression mode was significantly higher (by 19%) than that in the brace mode. By selectively increasing stiffness at heel strikes, AVC-Shoes represent a promising advancement toward next-generation AFOs capable of stabilizing the ankle while preventing muscle atrophy, which is associated with prolonged brace use. Full article
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31 pages, 2084 KiB  
Article
Spatial-Temporal Forecasting of Air Pollution in Saudi Arabian Cities Based on a Deep Learning Framework Enabled by AI
by Rafat Zrieq, Souad Kamel, Faris Al-Hamazani, Sahbi Boubaker, Rozan Attili and Marcos J. Araúzo-Bravo
Toxics 2025, 13(8), 682; https://doi.org/10.3390/toxics13080682 (registering DOI) - 16 Aug 2025
Abstract
Air pollution is steadily increasing due to industrialization, economic activities, and transportation. High levels pose a significant threat to human health and well-being worldwide. Saudi Arabia is a growing country with air quality indices ranging from moderate to unhealthy. Although there are many [...] Read more.
Air pollution is steadily increasing due to industrialization, economic activities, and transportation. High levels pose a significant threat to human health and well-being worldwide. Saudi Arabia is a growing country with air quality indices ranging from moderate to unhealthy. Although there are many monitoring stations distributed throughout the country, mathematical modeling of air pollution is still crucial for health and environmental decision-making. From this perspective, in this study, a data-driven approach based on pollutant records and a Deep Learning (DL) Long Short-Term Memory (LSTM) algorithm is carried out to perform temporal modeling of selected pollutants (PM10, PM2.5, CO and O3) based on time series combined with a spatial modeling focused on selected cities (Riyadh, Jeddah, Mecca, Rabigh, Abha, Dammam and Taif), covering ~48% of the total population of the country. The best forecasts were provided by LSTM in cases where the datasets used were of relatively large size. Numerically, the obtained performance metrics such as the coefficient of determination (R2) ranged from 0.2425 to 0.8073. The best LSTM results were compared to those provided by two ensemble methods, Random Forest (RF) and eXtreme Gradient Boosting (XGBoost), where the merits of LSTM were confirmed mainly in terms of its ability to capture hidden relationships. We also found that overall, meteorological factors showed a weak association with pollutant concentrations, with ambient temperature exerting a moderate influence. However, incorporating ambient temperature into LSTM models did not lead to a significant improvement in predictive accuracy. The developed approach can be used to support decision-making in environmental and health domains, as well as to monitor pollutant concentrations based on historical time series records. Full article
71 pages, 8414 KiB  
Systematic Review
Towards Maintenance 5.0: Resilience-Based Maintenance in AI-Driven Sustainable and Human-Centric Industrial Systems
by Lech Bukowski and Sylwia Werbinska-Wojciechowska
Sensors 2025, 25(16), 5100; https://doi.org/10.3390/s25165100 (registering DOI) - 16 Aug 2025
Abstract
Industry 5.0 introduces a new paradigm where digital technologies support sustainable and human-centric industrial development. Within this context, resilience-based maintenance (RBM) emerges as a forward-looking maintenance strategy focused on system adaptability, fault tolerance, and recovery capacity under uncertainty. This article presents a systematic [...] Read more.
Industry 5.0 introduces a new paradigm where digital technologies support sustainable and human-centric industrial development. Within this context, resilience-based maintenance (RBM) emerges as a forward-looking maintenance strategy focused on system adaptability, fault tolerance, and recovery capacity under uncertainty. This article presents a systematic literature review (SLR) on RBM in the context of Maintenance 5.0. The review follows the PRISMA methodology and incorporates bibliometric and content-based analyses of selected publications. Key findings highlight the integration of AI methods, such as machine learning and digital twins, in enhancing system resilience. The results demonstrate how RBM aligns with the pillars of Industry 5.0, sustainability, and human-centricity, by reducing resource consumption and improving human–machine interaction. Research gaps are identified in AI explainability, sector-specific implementation, and ergonomic integration. The article concludes by outlining directions for developing Maintenance 5.0 as a strategic concept for resilient, intelligent, and inclusive industrial systems. Full article
(This article belongs to the Special Issue Human-Centred Smart Manufacturing - Industry 5.0)
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33 pages, 1826 KiB  
Article
Comprehensive Evaluation of Probiotic Effects on Laying Hen Physiology: From Performance to Bone and Gut Morphology
by E. Ebru Onbaşılar, Sakine Yalçın, Caner Bakıcı, Barış Batur, Yeliz Kaya Kartal, Ozan Ahlat, İhsan Berat Kılıçlı and Suzan Yalçın
Animals 2025, 15(16), 2408; https://doi.org/10.3390/ani15162408 (registering DOI) - 16 Aug 2025
Abstract
This study investigated the effects of probiotic supplementation on performance, egg quality, antioxidant capacity, gut morphology, fecal microbiota, and bone morphology in Lohmann Brown laying hens aged 44 weeks over a 16-week period. Ninety-six hens were randomly divided into control and probiotic groups [...] Read more.
This study investigated the effects of probiotic supplementation on performance, egg quality, antioxidant capacity, gut morphology, fecal microbiota, and bone morphology in Lohmann Brown laying hens aged 44 weeks over a 16-week period. Ninety-six hens were randomly divided into control and probiotic groups (n = 48 each). The probiotic group received probiotic supplement containing Lactobacillus acidophilus KUEN 1607 and Pediococcus acidilactici KUEN 1608 via drinking water at 0.5%. Probiotic supplementation significantly improved feed conversion ratio (FCR), eggshell strength and thickness, and albumen quality (p < 0.001) and reduced the incidence of cracked and shell-less eggs (p < 0.05). Yolk and serum cholesterol levels decreased (p < 0.001), and antioxidant parameters improved, along with elevated serum IgG (p < 0.001). Histological analysis showed an increased ratio of villus height to crypt depth (p < 0.001) in the jejunum, indicating enhanced intestinal health. Fecal samples revealed increased Lactobacillus spp. and reduced coliform counts (p < 0.001), suggesting improved gut microbiota balance. While bone volume and surface area showed no significant difference, 3D geometric morphometric analysis identified subtle shape changes in long bones, especially the femur and tibiotarsus. These findings demonstrate that the selected probiotic combination supports nutrient utilization, egg quality, gut integrity, immune status, and skeletal health, offering a sustainable strategy to enhance productivity and welfare in laying hens. Full article
(This article belongs to the Section Animal Nutrition)
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14 pages, 711 KiB  
Systematic Review
Clinical Characteristics and Outcomes of SMARCA4-Mutated or Deficient Malignancies: A Systematic Review of Case Reports and Series
by Ryuichi Ohta, Natsumi Yamamoto, Kaoru Tanaka, Chiaki Sano and Hidetoshi Hayashi
Cancers 2025, 17(16), 2675; https://doi.org/10.3390/cancers17162675 (registering DOI) - 16 Aug 2025
Abstract
Background/Objectives: SMARCA4-deficient or SMARCA4-mutated cancers are rare but highly aggressive tumors with poor differentiation, resistance to conventional treatments, and limited clinical guidance. While thoracic SMARCA4-deficient undifferentiated tumors are relatively well described, the full spectrum of SMARCA4-altered cancers across different organs and their therapeutic [...] Read more.
Background/Objectives: SMARCA4-deficient or SMARCA4-mutated cancers are rare but highly aggressive tumors with poor differentiation, resistance to conventional treatments, and limited clinical guidance. While thoracic SMARCA4-deficient undifferentiated tumors are relatively well described, the full spectrum of SMARCA4-altered cancers across different organs and their therapeutic responses remains poorly understood. This study aimed to systematically review published case reports and case series to clarify the clinical characteristics, molecular features, treatment patterns, and survival outcomes of SMARCA4-altered malignancies. Methods: We conducted a systematic review of case reports and case series published between 2015 and 2025 using PubMed, Embase, and Web of Science. Eligible studies included adult patients with immunohistochemically or genetically confirmed SMARCA4-deficient or SMARCA4-mutated tumors. Key clinical, pathological, molecular, therapeutic, and outcome-related data were extracted. Descriptive statistics were used, and exploratory subgroup analyses were performed based on tumor type and treatment modality. The review protocol was registered in PROSPERO (CRD420251088805). Results: A total of 109 studies reporting 160 individual patients were included. Most tumors arose in the thorax (40.0%), followed by gastrointestinal (17.5%) and gynecologic sites (15.6%). The median age was 58 years, with a male predominance (70.0%) and frequent smoking history (44.4%). Platinum-based chemotherapy was administered in 62.5% of cases, and immune checkpoint inhibitors (ICIs) were used in 25.6%. Among ICI-treated patients, partial responses or stable disease were observed in 80.5%. The median progression-free survival (PFS) was 4.0 months, and the median overall survival (OS) was 5.0 months. Conclusions: SMARCA4-altered cancers are clinically and molecularly diverse but uniformly aggressive, with limited therapeutic benefit from conventional chemotherapy. Immune checkpoint inhibitors may offer improved outcomes in select patients, particularly those with thoracic tumors. Early molecular profiling, rare tumor registries, and biomarker-driven trials are crucial for guiding future treatment strategies. Full article
(This article belongs to the Section Clinical Research of Cancer)
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37 pages, 1295 KiB  
Review
Optimal Operation of Combined Cooling, Heating, and Power Systems with High-Penetration Renewables: A State-of-the-Art Review
by Yunshou Mao, Jingheng Yuan and Xianan Jiao
Processes 2025, 13(8), 2595; https://doi.org/10.3390/pr13082595 (registering DOI) - 16 Aug 2025
Abstract
Under the global decarbonization trend, combined cooling, heating, and power (CCHP) systems are critical for improving regional energy efficiency. However, the integration of high-penetration variable renewable energy (RE) sources introduces significant volatility and multi-dimensional uncertainties, challenging conventional operation strategies designed for stable energy [...] Read more.
Under the global decarbonization trend, combined cooling, heating, and power (CCHP) systems are critical for improving regional energy efficiency. However, the integration of high-penetration variable renewable energy (RE) sources introduces significant volatility and multi-dimensional uncertainties, challenging conventional operation strategies designed for stable energy inputs. This review systematically examines recent advances in CCHP optimization under high-RE scenarios, with a focus on flexibility-enabled operation mechanisms and uncertainty-aware optimization strategies. It first analyzes the evolving architecture of variable RE-driven CCHP systems and core challenges arising from RE intermittency, demand volatility, and multi-energy coupling. Subsequently, it categorizes key flexibility resources and clarifies their roles in mitigating uncertainties. The review further elaborates on optimization methodologies tailored to high-RE contexts, along with their comparative analysis and selection criteria. Additionally, it details the formulation of optimization models, model formulation, and solution techniques. Key findings include the following: Generalized energy storage, which integrates physical and virtual storage, increases renewable energy utilization by 12–18% and reduces costs by 45%. Hybrid optimization strategies that combine robust optimization and deep reinforcement learning lower operational costs by 15–20% while strengthening system robustness against renewable energy volatility by 30–40%. Multi-energy synergy and exergy-efficient flexibility resources collectively improve system efficiency by 8–15% and reduce carbon emissions by 12–18%. Overall, this work provides a comprehensive technical pathway for enhancing the efficiency, stability, and low-carbon performance of CCHP systems in high-RE environments, supporting their scalable contribution to global decarbonization efforts. Full article
(This article belongs to the Special Issue Distributed Intelligent Energy Systems)
29 pages, 2711 KiB  
Article
Methodological Development of a Test for Salivary Proteome Analysis Useful in Lung Cancer Screening
by Leonarda Barra, Elena Carestia, Giulia Ferri, Mohammad Kazemi, Massoumeh Ramahi, Uditanshu Priyadarshi, Velia Di Resta, Fabrizio Di Giuseppe, Renata Ciccarelli, Achille Lococo and Stefania Angelucci
Int. J. Mol. Sci. 2025, 26(16), 7924; https://doi.org/10.3390/ijms26167924 (registering DOI) - 16 Aug 2025
Abstract
Early diagnosis of lung cancer, essential for reducing its high mortality rate, is currently challenging, partly due to the lack of specific biomarkers. Here, we attempted to develop a noninvasive and potentially sensitive screening method based on the proteomic analysis of unstimulated and [...] Read more.
Early diagnosis of lung cancer, essential for reducing its high mortality rate, is currently challenging, partly due to the lack of specific biomarkers. Here, we attempted to develop a noninvasive and potentially sensitive screening method based on the proteomic analysis of unstimulated and stimulated saliva samples, collected by passive drooling and salivary swabs, respectively, from healthy heavy smokers enrolled in a nonprofit screening project. Protein content analyzed before and after sample cryopreservation for various periods and the associated two-dimensional electrophoresis revealed that protein extraction after short-term cryopreservation prevented the loss of detectable proteins. Mass spectrometric analysis of these electrophoretically resolved proteins revealed the presence of salivary proteins whose levels may be dysregulated in various types of lung cancer. Finally, in pilot experiments conducted on stimulated saliva from a patient with a lung cancer nodule, we detected altered content or selective presence of proteins involved in lung carcinogenesis, such as serpin B3 or the proteins S100A14 and aldoketoreductase-A1, respectively. While acknowledging that these findings require further validation, we believe that the use of saliva and related proteomic analyses may contribute to the identification of potential early lung cancer biomarkers, which could hopefully improve clinical management of the tumor and patient survival. Full article
(This article belongs to the Section Molecular Biology)
19 pages, 6626 KiB  
Article
Evaluation of the Quality of Welded Joints After Repair of Automotive Frame Rails
by Andrzej Augustynowicz, Mariusz Prażmowski, Wiktoria Wilczyńska and Mariusz Graba
Materials 2025, 18(16), 3849; https://doi.org/10.3390/ma18163849 (registering DOI) - 16 Aug 2025
Abstract
Passenger cars have unibody constructions, which means that their collision damage often involves key structural components. Successful repair requires the selection of appropriate technology and adherence to quality standards, which directly affects the safety of the vehicle’s continued operation. A commonly used method [...] Read more.
Passenger cars have unibody constructions, which means that their collision damage often involves key structural components. Successful repair requires the selection of appropriate technology and adherence to quality standards, which directly affects the safety of the vehicle’s continued operation. A commonly used method is a system of replacing damaged components with new ones, while repair by molding and forming is also possible—provided the original structural features are preserved. Automotive body repairs require advanced welding techniques and high precision. Methods such as MIG, TIG, as well as brazing and soldering have replaced older techniques, providing more efficient joining of HSS and HSLA components. Maintaining quality workmanship is crucial, as repair errors can weaken a vehicle’s structure and compromise passenger safety. This article presents the results of a study on the evaluation of the quality, microstructure, and mechanical properties of welded joints of a passenger car frame rail section made of high-strength, low-alloy steel—HSLA 320. The joints were made by three welding methods: MMA, MAG, and TIG, using different technological parameters. Microstructural analysis, non-destructive testing, and microhardness measurements made it possible to assess the impact of the chosen technology on the quality and strength of the joints. The best results were obtained for the TIG method, characterized by the highest repeatability and precision. Full article
(This article belongs to the Section Mechanics of Materials)
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24 pages, 2067 KiB  
Article
Effect of Wine Yeast (Saccharomyces sp.) Strains on the Physicochemical, Sensory, and Antioxidant Properties of Plum, Apple, and Hawthorn Wines
by František Lorenc, Markéta Jarošová, Jan Bedrníček, Vlastimil Nohejl, Eliška Míková and Pavel Smetana
Foods 2025, 14(16), 2844; https://doi.org/10.3390/foods14162844 (registering DOI) - 16 Aug 2025
Abstract
Fruit wines have become a popular alternative to grape wines for their variability of sensory properties and unique chemical profiles, offering interesting biological activities. Winemaking also utilizes fruits, which are usually sensitive to biological deterioration, thus reducing post-harvest losses. The quality of wines [...] Read more.
Fruit wines have become a popular alternative to grape wines for their variability of sensory properties and unique chemical profiles, offering interesting biological activities. Winemaking also utilizes fruits, which are usually sensitive to biological deterioration, thus reducing post-harvest losses. The quality of wines depends on the fermentation conditions, including the wine yeast selection. In this study, we observed the effect of three common Saccharomyces wine yeast strains on the physicochemical characteristics (color, pH, ethanol content), antioxidant potential (total polyphenol content—TPC, DPPH, and ABTS antioxidant assays), and sensory properties and their relations within plum, apple, and hawthorn wines. Generally, we observed quite-wide ranges in physicochemical properties (pH: 2.8–3.8, ethanol content: 9.0–16.2%) and antioxidant potential parameters (TPC: 0.5–2.4 mg/GAE, DPPH: 0.3–1.4 mg/AAE, 0.5–3.0 mg/AAE), which were affected by the fruit, yeast, and sampling term. The yeast strain significantly affected physicochemical properties and the antioxidant potential on a minor scale. The highest impact of yeast was observed within sensory analyses, where the hawthorn and apple wines fermented by yeast strain Fruit Red exhibited a different sensory profile than those fermented by the Buket and Special strains. A positive correlation between antioxidant potential parameters and their relationship with wine color was confirmed. Moreover, the overall acceptability grew with sweet taste intensity, and panelists preferred wines with lower ethanol content. In general, this study proved the significant impact of wine yeast strain selection on certain qualitative parameters of fruit wines. Full article
(This article belongs to the Special Issue Winemaking: Innovative Technology and Sensory Analysis)
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16 pages, 647 KiB  
Article
Socio-Economic Structure of Sheep Enterprises in Türkiye: A Micro-Level Analysis
by Alperen Varalan, Burak Barit, Burak Mat, Mustafa Bahadır Çevrimli and Aytekin Günlü
Ruminants 2025, 5(3), 39; https://doi.org/10.3390/ruminants5030039 (registering DOI) - 16 Aug 2025
Abstract
This study aims to analyze the technical and economic infrastructure of sheep farming enterprises operating in Türkiye. It assesses the demographic characteristics of enterprise owners, enterprise scales, production objectives, marketing strategies, and economic performance. Primary data were collected through face-to-face surveys conducted with [...] Read more.
This study aims to analyze the technical and economic infrastructure of sheep farming enterprises operating in Türkiye. It assesses the demographic characteristics of enterprise owners, enterprise scales, production objectives, marketing strategies, and economic performance. Primary data were collected through face-to-face surveys conducted with 201 sheep farming enterprises during the 2023 production period. The sample was selected based on information provided by the Provincial Directorates of Agriculture and Forestry and the Breeding Sheep and Goat Breeders’ Associations. Data analysis was performed using SPSS 27. Categorical data related to enterprise characteristics and the demographic profiles of enterprise owners were examined. The findings indicate that the majority of enterprise owners are middle-aged or older individuals, have a low level of education, and operate predominantly within an extensive production system. The producers’ marketing methods rely mainly on direct sales. In conclusion, ensuring the sustainability of the sheep farming sector requires encouraging young producers to enter the industry, expanding educational programs, and adopting modern production techniques. Full article
(This article belongs to the Special Issue Feature Papers of Ruminants 2024–2025)
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50 pages, 5154 KiB  
Review
Applications of Tailored Mesoporous Silicate Nanomaterials in Regenerative Medicine and Theranostics
by Jean Fotie
Int. J. Mol. Sci. 2025, 26(16), 7918; https://doi.org/10.3390/ijms26167918 (registering DOI) - 16 Aug 2025
Abstract
Tailored mesoporous silicate nanomaterials have attracted significant interest due to their exceptional surface properties, including high interfacial toughness, tunable thickness, customizable topology, optical transparency, and adjustable hydrophobicity. These characteristics enable them to exhibit a wide range of functional behaviors, such as antibacterial, anti-fouling, [...] Read more.
Tailored mesoporous silicate nanomaterials have attracted significant interest due to their exceptional surface properties, including high interfacial toughness, tunable thickness, customizable topology, optical transparency, and adjustable hydrophobicity. These characteristics enable them to exhibit a wide range of functional behaviors, such as antibacterial, anti-fouling, anti-fogging, lubricating, and abrasion-resistant properties, to name just a few. With recent advances in surface-modified nanosystems for bioengineering and biomedical applications, silica-based nanomaterials have emerged as promising candidates owing to their ease of surface functionalization, bioactivity, biocompatibility, biodegradability, and bioavailability. Consequently, they have been widely explored in various therapeutic contexts. This review provides a concise and concentrated summary of recent advances and applications of tailored mesoporous silicate nanomaterials in regenerative medicine and theranostics, with the primary focus being on how endogenous or exogenous triggers can be leveraged to achieve selective and precise delivery of various biomolecules and active therapeutics across diverse cellular environments, by harnessing the intrinsic properties of mesoporous silicate nanoparticles. This focus also guided the selection of specific examples provided to highlight their wide range of applications, with the report concluding with some perspectives and remaining challenges. Full article
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14 pages, 8373 KiB  
Article
Machine-Learning-Based Multi-Site Corn Yield Prediction Integrating Agronomic and Meteorological Data
by Chenyu Ma, Zhilan Ye, Qingyan Zi and Chaorui Liu
Agronomy 2025, 15(8), 1978; https://doi.org/10.3390/agronomy15081978 (registering DOI) - 16 Aug 2025
Abstract
Accurate maize yield forecasting under climate uncertainty remains a critical challenge for global food security, yet existing studies predominantly rely on single-model frameworks, limiting generalizability and actionable insights. This study selected three regions, specifically Dali, Lijiang, and Zhaotong, and collected data on 12 [...] Read more.
Accurate maize yield forecasting under climate uncertainty remains a critical challenge for global food security, yet existing studies predominantly rely on single-model frameworks, limiting generalizability and actionable insights. This study selected three regions, specifically Dali, Lijiang, and Zhaotong, and collected data on 12 agronomic traits of 114 varieties, along with eight sets of meteorological data, covering the period from 2019 to 2023. We employed three machine learning models: Random Forest (RF), Support Vector Machine (SVM), and XGBoost. The results revealed a strong correlation between yield and multiple agronomic traits, particularly grain weight per spike (GWPS) and hundred-kernel weight (HKW). Notably, the XGBoost model emerged as the top performer across all three regions. The model achieved the lowest RMSE (0.22–191.13) and a good R2 (0.98–0.99), demonstrating exceptional predictive accuracy for yield-related traits. The comparative analysis revealed that XGBoost exhibited superior accuracy and stability compared to RF and SVM. Through feature importance analysis, four critical determinants of yield were identified: GWPS, shelling percentage (SP), growth period (GP), and plant height (PH). Furthermore, partial dependence plots (PDPs) provided deeper insights into the nonlinear interactive effects between GWPS, SP, GP, PH, and yield, offering a more comprehensive understanding of their complex relationships. This study presents an innovative, data-driven methodology designed to accurately forecast corn yield across diverse locations. This approach offers valuable scientific insights that can significantly enhance precision agricultural practices by enabling the precise tailoring of fertilizer usage and irrigation strategies. The results highlight the importance of integrating agronomic and meteorological data in yield forecasting, paving the way for development of agricultural decision-support systems in the context of future climate change scenarios. This study presents an innovative, data-driven methodology designed to accurately forecast corn yield across diverse locations. This approach offers valuable scientific insights that can significantly enhance precision agricultural practices by enabling the precise tailoring of fertilizer usage and irrigation strategies. Full article
(This article belongs to the Section Precision and Digital Agriculture)
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10 pages, 381 KiB  
Communication
Multiwave Locked System Laser Treatment Reduces the Bacterial Load in the Gingival Sulcus of Dogs After Plaque Removal
by Ivana Pallante, Paolo Squarzoni, Elisa Mazzotta, Nicola Pozzato and Monica Monici
Vet. Sci. 2025, 12(8), 767; https://doi.org/10.3390/vetsci12080767 (registering DOI) - 16 Aug 2025
Abstract
Periodontal disease is a prevalent condition in companion animals. It is crucial to prevent the plaque and bacteria on tooth surfaces to avoid gingivitis and the more harmful periodontitis. The aim of the present study was to assess the impact of MLS laser [...] Read more.
Periodontal disease is a prevalent condition in companion animals. It is crucial to prevent the plaque and bacteria on tooth surfaces to avoid gingivitis and the more harmful periodontitis. The aim of the present study was to assess the impact of MLS laser treatment on the bacterial load by analyzing the gingival swabs of a total of 16 owned dogs with no history of dental disease that were selected from a cohort of patients admitted for plaque removal and dental hygiene procedures. Following each dental hygiene session, each dog received a single MLS laser therapy treatment (808–905 nm diode laser, frequency 36 Hz, and fluence 0.16 J/cm2). Swabs were collected from the two upper premolars before and after the laser treatment. These were submitted for mesophilic bacteria counts, and microbiological analysis was conducted on 10 positive cultures to evaluate the changes in the oral bacterial microbiota. MLS laser therapy statistically significantly reduced the mesophilic bacteria count by 1 log, with higher pre-laser treatment counts (n = 0.44; 5.77 ± 0.21 95%CI) in comparison to post-laser treatment counts (n = 0.73; 4.80 ± 0.346 95%CI). The MLS laser therapy was found to reduce the bacterial load in 80% of the subjects (p < 0.05). No significant differences pre- and post-laser treatment were observed in the bacteria species isolated from the microbiological cultures. MLS laser therapy appears to be a useful, non-invasive method for reducing the bacterial load in the treatment and prophylaxis of periodontal disease in dogs. Full article
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