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56 pages, 38537 KB

Open AccessReview

BIF Hosted-Iron Ore Deposits in West Africa: A Comprehensive Literature Review

by Mohamed Yacouba Kallo, Mustapha El Ghorfi, Oumar Barou Kaba, Abdessamad Khalil, Yassine Ait Khouia, Daouda Keita, Foued Souissi, Grace Kabulanda Balambula, Cynthia Fataki Fatuma, Mohamed Samuel Moriah Conté, Oussama Khadiri-Yazami and Mostafa Benzaazoua

Minerals 2026, 16(10), 976; https://doi.org/10.3390/min16100976 - 22 Sep 2026

Abstract

The West African Craton hosts some of the world’s largest BIF-hosted iron ore deposits and represents a globally important iron province. Compilation of data from Guinea, Liberia, Sierra Leone, Mauritania, and Nigeria reveals marked regional variability, from high-grade hematite-rich direct-shipping ores to lower-grade [...] Read more.

The West African Craton hosts some of the world’s largest BIF-hosted iron ore deposits and represents a globally important iron province. Compilation of data from Guinea, Liberia, Sierra Leone, Mauritania, and Nigeria reveals marked regional variability, from high-grade hematite-rich direct-shipping ores to lower-grade magnetite-rich itabirites. At the province scale, Guinea is dominated by high-grade hematite ores, Liberia contains both hematite and magnetite-bearing ores, Sierra Leone hosts large magnetite-rich and hematite-rich resources, Mauritania combines Archean magnetite-rich and Paleoproterozoic high-grade hematite systems, whereas Nigerian deposits are generally smaller and lower-grade. Their mineralogical and geochemical characteristics record multistage evolution, involving primary sedimentation, metamorphic and structural reworking, hypogene alteration, and supergene enrichment. Geochemical discrimination diagrams indicate broad Algoma- and Superior-type affinities but are not uniquely diagnostic of ore genesis. Airborne geophysics, remote sensing, and geochemistry emerge as complementary exploration tools, particularly for delineating concealed BIFs and alteration zones regionally. Ore variability results in contrasting beneficiation requirements, and four generalized flowsheets link the principal ore types to appropriate processing routes. Major research gaps concern correlations between BIF belts, primary depositional signatures, fluid sources, enrichment timing, prioritized isotopic geochemistry, rare earth element systematics and the limited integration of mineralogical variability with beneficiation performance. Full article

(This article belongs to the Special Issue Geochemical, Isotopic, and Biotic Records of Banded Iron Formations)

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19 pages, 1422 KB

Open AccessArticle

Field-Scale Estimation of Maize Leaf Area Index from UAV Multispectral Imagery Using Compact Spectral and Texture Predictors

by Yu Zhang, Yanying Bai, Hongxin Li, Yang Xu, Zimao Chen, Jiahua Yan and Yongmei Wang

Sensors 2026, 26(19), 6008; https://doi.org/10.3390/s26196008 - 22 Sep 2026

Abstract

Leaf area index (LAI) is an important indicator of canopy development and is widely used for crop diagnosis and field-scale monitoring. We developed a UAV multispectral approach to estimate and map maize LAI in Tumed Right Banner, Inner Mongolia, China. The dataset comprised [...] Read more.

Leaf area index (LAI) is an important indicator of canopy development and is widely used for crop diagnosis and field-scale monitoring. We developed a UAV multispectral approach to estimate and map maize LAI in Tumed Right Banner, Inner Mongolia, China. The dataset comprised 488 paired observations from 122 georeferenced locations in 13 fixed plots, measured repeatedly at four growth stages. Vegetation indices and gray-level co-occurrence matrix texture features were derived from the green, red, red-edge, and near-infrared bands. Five models were evaluated using a single 70:30 split. Model robustness was further examined through 100 repeated stage-stratified splits, leave-one-plot-out validation, leave-one-growth-stage-out validation, and RF-based feature ablation. In the single-split benchmark, RF achieved R² = 0.889, RMSE = 0.249, and RRMSE = 0.082. Across the repeated splits, the corresponding values were R² = 0.876 ± 0.016, RMSE = 0.258 ± 0.018, and RRMSE = 0.085 ± 0.006. Leave-one-plot-out validation gave R² = 0.878 ± 0.062, whereas leave-one-growth-stage-out testing revealed weaker, stage-dependent transferability (RF R², −0.542 to 0.441). Feature ablation showed that vegetation indices provided most of the predictive information; adding the two NIR texture variables increased R² by 0.010 relative to vegetation indices alone. Because the field platform lacked independent plot replication, the maps are interpreted as descriptions of canopy heterogeneity rather than evidence of treatment effects. The approach is suitable for site-specific maize canopy monitoring, but broader application requires independent validation across years and locations. Full article

(This article belongs to the Special Issue Sensors and Data-Driven Precision Agriculture—Second Edition)

31 pages, 10370 KB

Open AccessArticle

Experimental Evaluation of the Influence of Drill String Axial Compliance on Rotary Drilling Performance in Hard Rock Formation

by Ibrahim Futheiz, Abdelsalam Abugharara, Jianming (James) Yang and Stephen D. Butt

Appl. Sci. 2026, 16(19), 9440; https://doi.org/10.3390/app16199440 - 22 Sep 2026

Abstract

Improving drilling performance in hard formations remains a key challenge for mining, geothermal, carbon storage, and petroleum applications. This study experimentally investigates the effect of axial compliance, introduced through a Belleville spring stack above the drill bit, on rotary drilling performance, compared against [...] Read more.

Improving drilling performance in hard formations remains a key challenge for mining, geothermal, carbon storage, and petroleum applications. This study experimentally investigates the effect of axial compliance, introduced through a Belleville spring stack above the drill bit, on rotary drilling performance, compared against a conventional rigid drill string. Tests were conducted on fully characterized Fine-Grained Gabbro (UCS approximately 152 MPa) using a Large-Scale Drilling Simulator, at 60 and 120 RPM across a WOB range of 5–15 kN with a bit configured of six PDC cutters. Performance was evaluated through the Rate of Penetration (ROP), depth of cut (DOC), torque, and Mechanical Specific Energy (MSE), with axial displacement measurements characterizing drill string vibration. The compliant configuration consistently outperformed the rigid configuration, with the average ROP improved by 15% at 60 RPM and 25% at 120 RPM, while the average MSE was reduced by up to 27%. These gains began once the WOB exceeded a threshold level and grew stronger with rotational speed, indicating the improvement is driven by the number of oscillation cycles rather than displacement magnitude alone. These results show that axial compliance can meaningfully improve drilling performance relative to a rigid drill string under the tested conditions. Full article

(This article belongs to the Section Energy Science and Technology)

20 pages, 988 KB

Open AccessArticle

Prediction of Chemical Composition of Alfalfa Blocks Using FTIR Spectroscopy and Machine Learning Models

by Haijun Du, Yanhua Ma, Liying Cao, Hongzhou Liu, He Su and Xiangbo Liu

Foods 2026, 15(19), 3375; https://doi.org/10.3390/foods15193375 - 22 Sep 2026

Abstract

Alfalfa blocks are an important commercial roughage, and their crude protein (CP), starch, fat, neutral detergent fibre (NDF), and acid detergent fibre (ADF) contents are key indicators of nutritional quality. This study investigated Fourier-transform infrared (FTIR) spectroscopy combined with machine learning for rapid [...] Read more.

Alfalfa blocks are an important commercial roughage, and their crude protein (CP), starch, fat, neutral detergent fibre (NDF), and acid detergent fibre (ADF) contents are key indicators of nutritional quality. This study investigated Fourier-transform infrared (FTIR) spectroscopy combined with machine learning for rapid quantitative prediction of these constituents. Different spectral preprocessing strategies and variable-selection methods were compared using partial least squares regression (PLSR), random forest regression (RFR), and back-propagation (BP) neural networks. The effects of spectral preprocessing and preceding baseline correction varied among constituents, indicating that baseline correction did not uniformly improve predictive performance. Competitive adaptive reweighted sampling (CARS) reduced spectral dimensionality, and the resulting PLSR models outperformed the RFR and BP models for all five constituents in the reported comparisons, with values reported as mean ± standard deviation across 20 repeated data partitions. For CP, the PLSR model combining first-derivative Savitzky–Golay preprocessing with CARS (SG1D-CARS-PLSR) achieved a prediction-set coefficient of determination (R²) of 0.961 ± 0.021 and a residual predictive deviation (RPD) of 5.629 ± 1.245. For starch, SG1D-CARS-PLSR achieved an R² of 0.877 ± 0.023 and an RPD of 2.959 ± 0.291. For NDF, the PLSR model combining adaptive iteratively reweighted penalised least-squares baseline correction with CARS (BC-airPLS-CARS-PLSR) achieved an R² of 0.986 ± 0.006 and an RPD of 9.355 ± 1.947. For ADF, BC-airPLS-CARS-PLSR achieved an R² of 0.839 ± 0.031 and an RPD of 2.591 ± 0.287. For fat, BC-MSC-CARS-PLSR achieved an R² of 0.697 ± 0.058 and an RPD of 2.1.883 ± 0.164, and did not deliver the expected stable prediction performance as predefined. These findings highlight the importance of constituent-specific preprocessing and variable selection and demonstrate that the optimised FTIR-based models provide a rapid for estimating the five constituents from a single spectrum, with an analysis time considerably shorter than that of the reference wet-chemistry methods. Full article

(This article belongs to the Topic AI in Optical Spectroscopy Analysis)

33 pages, 1435 KB

Open AccessFeature PaperArticle

A Hybrid Memetic Algorithm for Asymmetric Vehicle Routing with Topographic Constraints: Quantifying the Orographic Gap in Mountain Urban Networks

by Alejandra María Restrepo-Franco, Orlando Valencia-Rodriguez, Eliana Mirledy Toro-Ocampo and Omar Danilo Castrillón-Gómez

Algorithms 2026, 19(10), 812; https://doi.org/10.3390/a19100812 - 22 Sep 2026

Abstract

Classical vehicle routing models assume flat, symmetric road networks, yet mountain cities exhibit gravitational asymmetry and steep gradients that invalidate two-dimensional cost estimates and may produce mechanically infeasible routes. This study formalizes the Asymmetric Capacitated Vehicle Routing Problem with Topographic Constraints (ACVRP-TC) and [...] Read more.

Classical vehicle routing models assume flat, symmetric road networks, yet mountain cities exhibit gravitational asymmetry and steep gradients that invalidate two-dimensional cost estimates and may produce mechanically infeasible routes. This study formalizes the Asymmetric Capacitated Vehicle Routing Problem with Topographic Constraints (ACVRP-TC) and introduces a generalized cost function (GCF) that linearizes direction-dependent energy consumption into an impedance metric within a mixed-integer linear programming (MILP) formulation. A hybrid memetic algorithm coupled with stochastic large neighborhood search (H-MA-LNS) is proposed to solve this NP-hard variant, combining evolutionary global exploration with structured local intensification. Benchmark validation yields a mean improvement of

9.4 %

over the state of the art on flat reference instances. An extensive computational evaluation on 24 real geospatial instances from Seoul (Republic of Korea), enriched with satellite elevation data, reveals a topographic gap of 14.1% for this urban network (Wilcoxon: p = 0.002), quantifying the cost underestimation that orography imposes on theoretical planning in the studied setting. Furthermore, the feasibility-based arc pruning reduces the search space by

51 %

, accelerating convergence and inducing a shift toward radial route structures in high-density environments. Full article

(This article belongs to the Special Issue Optimization and Evaluation Methods for Complex Transportation Systems)

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24 pages, 422 KB

Open AccessArticle

The Predominant Role of Traditional Architecture as a Construct of Intangible Cultural Heritage Tourism: Empirical Evidence from China

by Rob Kim Marjerison, Vincent Peu Duvallon and George Kuan

Heritage 2026, 9(10), 382; https://doi.org/10.3390/heritage9100382 - 22 Sep 2026

Abstract

This study investigates how generational differences and regional levels of economic development moderate interest in Intangible Cultural Heritage (ICH) tourism, focusing on four key facets: traditional food, crafts, local dialects, and architecture. Drawing on survey data from 409 respondents across multiple economic tiers [...] Read more.

This study investigates how generational differences and regional levels of economic development moderate interest in Intangible Cultural Heritage (ICH) tourism, focusing on four key facets: traditional food, crafts, local dialects, and architecture. Drawing on survey data from 409 respondents across multiple economic tiers in China, the study employs one-way ANOVAs, structural equation modeling (SEM), and linear regression-based moderation analyses. The results indicate that while the overall perceived importance of ICH is uniformly high across generations, significant variation emerges in the level of interest toward specific ICH elements. In particular, younger generations tend to show greater interest in experiential, visually oriented heritage, such as food, while older generations tend to show a stronger attachment to crafts and dialects. Traditional architecture, however, emerges as a culturally universal form of heritage, demonstrating no significant differences across either generational or economic contexts. To strengthen analytical robustness, the study cross-validates findings through SEM and moderation analyses using interaction terms. These findings highlight the joint roles of generational identity and structural context in shaping cultural tourism preferences and offer actionable insights for designing region-specific and generation-sensitive ICH engagement strategies. Full article

(This article belongs to the Section Cultural Heritage)

50 pages, 1125 KB

Open AccessArticle

Artificial Intelligence-Driven Inverse Identification of Fractional Epidemic Models with Generalized Incidence Functions

by Zied Elleuch, Younes Brahim Oumedjber, Omar Kahouli, Adel Ouannas, Sulaiman Almohaimeed, Lilia El Amraoui, Mohamed Ayari and Mohamed Arbi Khlifi

Fractal Fract. 2026, 10(10), 662; https://doi.org/10.3390/fractalfract10100662 - 22 Sep 2026

Abstract

We present an identifiability-aware inverse-learning workflow for a dimensionally consistent Caputo fractional-order SEAIHRD epidemic model incorporating generalized incidence, asymptomatic transmission, hospitalization dynamics, waning immunity, and an ordinary cumulative-death balance. For the autonomous system, we establish positivity, forward invariance, global well-posedness, threshold and stability [...] Read more.

We present an identifiability-aware inverse-learning workflow for a dimensionally consistent Caputo fractional-order SEAIHRD epidemic model incorporating generalized incidence, asymptomatic transmission, hospitalization dynamics, waning immunity, and an ordinary cumulative-death balance. For the autonomous system, we establish positivity, forward invariance, global well-posedness, threshold and stability results, endemic-equilibrium existence and uniqueness, and sensitivity properties. To infer unobserved dynamics, we combine practical-identifiability screening, multistart fractional calibration, profile likelihood, bootstrap analysis, and constrained PINN state reconstruction. In the matched-information synthetic inverse benchmark, conventional fractional calibration outperforms direct joint-PINN parameter fitting for retained-parameter recovery and hidden-state error: hidden-state RMSE is 0.00142 versus 0.161 on clean data, 0.0203 versus 0.142 at 2% noise, and 0.0207 versus 0.139 at 5% noise. In the separate fixed-parameter reconstruction task, adding the governing-equation residual reduces mean hidden-state RMSE by 49–51% relative to the matched no-dynamics-residual ablation, although the resulting absolute mean hidden-state RMSE remains 0.129–0.144 and susceptible-state RMSE remains 0.336–0.348. In Italian COVID-19 data, a stock-consistent observation model yields admissible reconstructions, but the real-data scalar inverse problem is practically non-identifiable; the reconstructed latent states are a model-conditioned decomposition of the reported active-positive stock under a unit reporting factor, not a census of unreported community infection. Rolling-origin constant-endpoint-

β

forecasts underperform simple baselines on average. Adding the governing-equation residual, therefore, regularizes latent-state reconstruction relative to the matched constrained neural ablation under the tested design, without guaranteeing unique parameter identification or forecast superiority. Full article

(This article belongs to the Special Issue New Perspectives on Epidemic Modeling Through Fractional Calculus)

19 pages, 1319 KB

Open AccessArticle

Mules and Hinnies Weight Estimation Using Morphological Measures

by João B. Rodrigues, Stuart L. Norris, Katharina Habeck, Ahmed Khairoun, Claudia Valderrama, María Alejandra Torres-Medina, Juan Sebastián Galecio, Miriam Alva Trujillo, Sarah Worth, Holly A. Little and Tamara A. Tadich

Animals 2026, 16(19), 2985; https://doi.org/10.3390/ani16192985 - 22 Sep 2026

Abstract

Hybrid equids such as mules and hinnies play a critical role in supporting livelihoods in low- and middle-income countries but remain underrepresented in veterinary research. One key challenge is the absence of a practical and internally validated method for estimating body weight in [...] Read more.

Hybrid equids such as mules and hinnies play a critical role in supporting livelihoods in low- and middle-income countries but remain underrepresented in veterinary research. One key challenge is the absence of a practical and internally validated method for estimating body weight in mules and hinnies, which is essential for accurate dosing and management, particularly in the absence of a weighbridge. This study aimed to evaluate the performance of existing equid weight estimation models on mules and hinnies and to develop a new mules and hinnies -specific model to improve predictive accuracy and field usability. Three hundred and sixteen healthy mules and hinnies were assessed across nine countries. Sixteen morphological measurements were collected, and body weight was recorded using a digital weighbridge. Existing models were tested for their feasibility, and linear regression model was developed to predict mules and hinnies’ weighbridge body weight from morphological measurements. Model performance was assessed using repeated cross-validation and standard error metrics. Machine learning methods were used as a secondary analysis to explore feature importance. Morphological predictors showed strong associations with weighbridge weight. Linear models demonstrated reliable predictive performance, with low prediction error across weight ranges. The new mules and hinnies-specific model based on heart girth, chest width, and forearm girth, achieved an adjusted r² of 0.94 (p < 0.001), providing estimates of live-weight without requiring classification by sex, conformation, or type. These findings demonstrate that simple morphological measurements can provide good estimates of body weight of mules and hinnies in field settings, greatly supporting the daily management of mules and hinnies in different contexts, and contribute to improve their health and welfare globally. Full article

(This article belongs to the Special Issue Current Research on Donkeys and Mules: Second Edition)

15 pages, 3448 KB

Open AccessArticle

Large Scale Physical Modeling of Shale Fracture Propagation Under Different Controllable Shock Wave and Perforation Operation Schemes

by Bobo Xie, Jingchen Zhang, Xi Chen, Yajun Zhang, Jiawen Li, Qiuguo Li, Jinchi Teng and Jing Guo

Processes 2026, 14(19), 3041; https://doi.org/10.3390/pr14193041 - 22 Sep 2026

Abstract

To address the relatively high near-wellbore fracture-initiation resistance and the tendency of hydraulic fractures to propagate along a dominant path under conventional perforation-based hydraulic fracturing, three large-scale hydraulic-fracturing experiments were conducted using a 10,000-ton ultra-large true-triaxial hydraulic-fracturing physical simulation system to investigate the [...] Read more.

To address the relatively high near-wellbore fracture-initiation resistance and the tendency of hydraulic fractures to propagate along a dominant path under conventional perforation-based hydraulic fracturing, three large-scale hydraulic-fracturing experiments were conducted using a 10,000-ton ultra-large true-triaxial hydraulic-fracturing physical simulation system to investigate the effects of different controllable shock-wave–perforation operation schemes on shale fracture initiation and propagation. Natural shale outcrop blocks from the Jimsar shale oil reservoir, each measuring 2.0 m × 2.0 m × 1.0 m, were used. Three operation schemes were investigated: conventional perforation–hydraulic fracturing, shock wave–perforation–hydraulic fracturing, and perforation–shock wave–hydraulic fracturing. Post-fracturing fracture observations, three-dimensional fracture reconstruction, and wellhead-pressure responses were jointly analyzed to characterize fracture initiation and propagation under the different operation schemes. The results showed that, under conventional perforation–hydraulic fracturing, fracture propagation was dominated by a principal fracture, with only limited secondary fractures, and the wellhead breakdown pressure reached 21.2 MPa. After breakdown, the pressure remained at a relatively high level and exhibited sustained fluctuations, indicating large and continuously varying fracture-propagation resistance. When one 100 kJ shock was applied before perforation, several large-scale dominant fracture surfaces developed, and the breakdown pressure decreased to 6.6 MPa, representing a reduction of 68.9% relative to the conventional case. The post-breakdown pressure gradually stabilized, indicating reduced variation in fracture-propagation resistance. When two successive 100 kJ shocks were applied after perforation, fractures propagated in multiple directions with more pronounced bending, deflection, and branching. The breakdown pressure further decreased to 4.6 MPa, 78.3% lower than that of the conventional case. Fractures continued to propagate under relatively low pressure, followed by a late-stage pressure increase. The dynamic disturbance induced by controllable shock waves altered the near-wellbore stress distribution and rock-failure conditions, reduced hydraulic-fracture initiation resistance, and modified subsequent fracture-propagation paths. These results reveal the coupled mechanism of near-wellbore stress redistribution and dynamic fracture propagation induced by controllable shock-wave–perforation operations, and provide experimental support for fracture-initiation control and optimization of integrated stimulation parameters in the Jimsar shale oil reservoir. Full article

(This article belongs to the Section Petroleum and Low-Carbon Energy Process Engineering)

26 pages, 1025 KB

Open AccessArticle

Multi-Source Data-Driven Day-Ahead Load Forecasting for a Provincial Power Grid: A Case Study in Hunan, China

by Changlong Wu, Rui Xiang, Jun Huang, Xueshan Ai, Qihang Gong, Yangxin Yu and Hao Hu

Energies 2026, 19(19), 4502; https://doi.org/10.3390/en19194502 - 22 Sep 2026

Abstract

Accurate day-ahead load forecasting at the provincial scale is a basic input to unit commitment, reserve scheduling and market settlement, but the forecast has to capture periodic load behaviour, spatially distributed weather sensitivity and historically conditioned operating regimes together. This paper develops a [...] Read more.

Accurate day-ahead load forecasting at the provincial scale is a basic input to unit commitment, reserve scheduling and market settlement, but the forecast has to capture periodic load behaviour, spatially distributed weather sensitivity and historically conditioned operating regimes together. This paper develops a multi-source forecasting model that couples a TimeXer backbone with a full-grid encoder for five-channel archived ECMWF IFS HRES fields over the service territory, an availability-controlled similar-pattern retrieval whose output is mediated by a learned correction gate, and a validation-selected daily-cycle level correction. The model is evaluated on one year of 15-min Hunan provincial load under a chronological train–validation–test split with 61 daily test origins and five random seeds. It attains a 726.2 MW MAE, 2.04% MAPE,

R^{2} = 0.9699

and 207.8 MW mean quantile loss, ranking first on a six-metric mean-rank criterion, with lower mean MAE and MQL values than the hyperparameter-tuned and level-corrected DLinear and iTransformer comparators. A staged ablation shows that the gridded weather field supplies the largest MAE reduction (308.6 MW), while the similar-pattern prior produces the largest mean-rank movement (3.17 to 2.25); the eight learned weather tokens receive 90.5% of the averaged cross-attention weight. Over the 22 origins spanned by five documented large-scale cooling events, the model retains the best mean rank among the twelve compared models that produce a predictive distribution. These results indicate that multi-source information fusion supports accurate and computationally feasible day-ahead forecasting for the Hunan provincial system. Full article

(This article belongs to the Special Issue Forecasting Electricity Demand Using AI and Machine Learning)

30 pages, 4210 KB

Open AccessArticle

Government–Industry–University Collaboration and Perceived Zero-Carbon Community Performance: The Mediating Role of Alliance Mechanisms from a Triple Helix Perspective

by Yanling Zhang, Guoqiang Zhang, Shun Li and Zhengxuan Liu

Sustainability 2026, 18(19), 9724; https://doi.org/10.3390/su18199724 - 22 Sep 2026

Abstract

The development of zero-carbon communities has become an important pathway for advancing urban carbon neutrality. However, the transition toward zero-carbon development is no longer a process driven solely by technological innovation; rather, it has evolved into a complex governance process involving the collaborative [...] Read more.

The development of zero-carbon communities has become an important pathway for advancing urban carbon neutrality. However, the transition toward zero-carbon development is no longer a process driven solely by technological innovation; rather, it has evolved into a complex governance process involving the collaborative participation of multiple stakeholders. Grounded in Triple Helix theory, this study develops an integrated analytical framework to examine the associations between government–industry–university (GIU) collaboration and perceived zero-carbon community performance with particular attention to the mediating roles of strategic alliance, organizational alliance, and knowledge alliance. Based on survey data from 350 stakeholders in China, covariance-based structural equation modeling (CB-SEM) was employed to systematically examine the direct and indirect statistical associations among GIU collaboration, alliance mechanisms, and perceived zero-carbon community performance (PZCP). The results indicate that government support and industry participation are not significantly associated with perceived zero-carbon community performance through direct paths but show significant indirect associations through strategic alliance, suggesting an indirect-only mediation pattern. In contrast, university engagement shows a significant positive direct association with perceived zero-carbon community performance and also shows a significant indirect association through strategic alliance, indicating a complementary mediation pattern. Among the three alliance mechanisms examined, only strategic alliance exhibits a significant indirect association, suggesting that shared strategic objectives, strategic alignment, and long-term collaborative relationships are particularly important in linking GIU collaboration with PZCP. These findings highlight the differentiated roles of government, industry, and university actors and the importance of strategic alignment as a key collaborative mechanism for zero-carbon community development. Full article

(This article belongs to the Section Sustainable Urban and Rural Development)

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22 pages, 1788 KB

Open AccessArticle

Seasonal Nutrient Dynamics in Flowers and Leaves of Sweet Cherry (Prunus avium L.) Across Altitudinal and Agro-Environmental Gradients: Implications for Site-Specific Fertilization

by Elena Nieto-Serrano, Carlos Pérez, Valme González, Carlos Campillo, Henar Prieto and Víctor Blanco

Horticulturae 2026, 12(10), 1198; https://doi.org/10.3390/horticulturae12101198 - 22 Sep 2026

Abstract

Sweet cherry (Prunus avium L.) production in mountainous Mediterranean regions is characterized by strong altitudinal gradients, heterogeneous soils, and short phenological cycles, which complicate nutrient management and the interpretation of conventional foliar analyses. This study aimed to evaluate the seasonal dynamics of [...] Read more.

Sweet cherry (Prunus avium L.) production in mountainous Mediterranean regions is characterized by strong altitudinal gradients, heterogeneous soils, and short phenological cycles, which complicate nutrient management and the interpretation of conventional foliar analyses. This study aimed to evaluate the seasonal dynamics of macro- and micronutrient concentrations in flowers and leaves of sweet cherry orchards located in the Jerte Valley (Spain) in order to refine nutritional diagnosis under mountain conditions. Flower samples at full bloom and leaf samples at 30, 60, 90, and 120–150 days after full bloom (DAFB) were collected from early, mid-season, and late-maturing cultivars during two consecutive seasons. Nutrient concentrations were analyzed using linear mixed models and multivariate analyses. Sampling date and cultivar maturation cycle were the main factors explaining nutrient variation. Despite large differences in yield, fruit quality, and irrigation inputs among orchards and seasons, the seasonal trajectories of nutrient concentrations remained consistent within cultivars. This consistency suggests phenological development and internal nutrient cycling may play an important role in shaping seasonal nutrient patterns, while local management, soil, and environmental conditions may modulate nutrient supply. Nitrogen, phosphorus, and potassium concentrations declined progressively throughout the season, with N decreasing from approximately 3.8–4.0% in flowers to 2.0–2.1% at 120–150 DAFB, whereas calcium and magnesium increased with leaf age. Micronutrients, particularly manganese and iron, showed marked temporal variability. The lowest overall median nutrient variability was observed at 60 DAFB (CV = 10.1%), supporting the 60–90 DAFB interval as the most informative window for foliar diagnosis in mountainous orchards, whereas the generally weak flower–leaf relationships indicated that flower analysis has limited diagnostic capacity and may serve only as a preliminary early-season screening tool for selected nutrients. Comparison of measured foliar nutrient concentrations in the Jerte Valley agroecosystem with published sweet cherry reference values revealed the need for region-specific calibration. While N concentrations broadly matched established benchmarks (2.5%), phosphorus (0.21%), potassium (1.95%), and iron (70 mg kg⁻¹) showed consistently negative Deviation from Optimum Percentage (DOP) values relative to published reference values (DOP = +1%, −38%, −18%, and −75%, respectively). This work highlights that phenology-based nutritional diagnostics can improve nutrient monitoring and provide a framework for developing site-adapted fertilization strategies in mountain sweet cherry production systems. Full article

(This article belongs to the Special Issue Improving Cherry Crop Systems: Toward Sustainable and Resilient Production)

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18 pages, 5629 KB

Open AccessArticle

Image Integration in IFC Models: Leveraging Texture Mapping for Structural Data Visualization

by Davide Avogaro, Carlo Zanchetta, Giorgia Marcellino and Giulia De Cet

Buildings 2026, 16(19), 3778; https://doi.org/10.3390/buildings16193778 - 22 Sep 2026

Abstract

Not all data derived from structural analysis or experimental testing can be effectively encoded using Industry Foundation Classes (IFC) properties or attributes, even if custom-made. In many cases, visual outputs—such as images—represent the only practical means of conveying complex analytical results. However, the [...] Read more.

Not all data derived from structural analysis or experimental testing can be effectively encoded using Industry Foundation Classes (IFC) properties or attributes, even if custom-made. In many cases, visual outputs—such as images—represent the only practical means of conveying complex analytical results. However, the current literature provides limited guidance on systematically integrating images within IFC models, with practitioners often relying on external formats or auxiliary technologies. This study investigates how the IFC standard supports the visualization of textures applied to geometric entities, focusing on the relevant classes and their interrelationships. Building on this theoretical framework, a prototype is developed within the Bonsai environment, leveraging Blender 4.5 and its add-on architecture. The prototype enables the creation of planar geometries in 3D space and the application of image-based textures, enabling visual information to be associated with IFC geometry through standard texture-mapping entities and an external image reference. A case study involving the visualization of structural testing results demonstrates the approach. By keeping the visual output registered to the model geometry, the approach has the potential to enhance analytical interpretation, communication among stakeholders, and data visualization within the built environment domain. Full article

(This article belongs to the Section Construction Management, and Computers & Digitization)

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19 pages, 2595 KB

Open AccessArticle

Multifunctional Cellulose Acetate-Based Composite Membranes Incorporating Hydroxyapatite, Magnetic Nanoparticles and Ketoprofen with Improved Mineralization Properties

by Ruxandra Mihaela Oprea, Andreea Madalina Pandele, Adrian Ionut Nicoara, Stefan Ioan Voicu and Madalina Oprea

Ceramics 2026, 9(10), 105; https://doi.org/10.3390/ceramics9100105 - 22 Sep 2026

Abstract

In this study, cellulose acetate-based composite membranes incorporating hydroxyapatite and ketoprofen-functionalized Fe/Ni magnetic nanoparticles (HA–NP–KP) were successfully fabricated by the phase inversion technique. FTIR and XPS analyses confirmed the successful incorporation of the bioactive fillers into the cellulose acetate matrix, while thermal analysis [...] Read more.

In this study, cellulose acetate-based composite membranes incorporating hydroxyapatite and ketoprofen-functionalized Fe/Ni magnetic nanoparticles (HA–NP–KP) were successfully fabricated by the phase inversion technique. FTIR and XPS analyses confirmed the successful incorporation of the bioactive fillers into the cellulose acetate matrix, while thermal analysis demonstrated that their addition did not compromise the thermal stability of the membranes. The incorporation of HA–NP–KP significantly enhanced the mineralization performance of the membranes. Taguchi mineralization studies revealed a progressive increase in calcium phosphate deposition with increasing filler content, while EDS analysis showed Ca/P ratios approaching the stoichiometric value of hydroxyapatite, indicating the formation of biologically relevant mineral phases. Among the investigated formulations, the CA/HA–NP–KP 2% membrane exhibited the highest mineralization ability, demonstrating the beneficial synergistic effect of hydroxyapatite and functionalized magnetic nanoparticles on apatite nucleation and growth. In addition, the composite membranes exhibited controlled ketoprofen release over a clinically relevant time frame, meaning they could provide localized anti-inflammatory activity without compromising their physicochemical properties. The combination of enhanced mineralization with sustained drug delivery highlights the multifunctional character of the developed membranes. Overall, these findings demonstrate that HA–NP–KP-functionalized cellulose acetate membranes represent potential candidates for implant surface modification, with the ability to simultaneously promote osseointegration and modulate the early inflammatory response following implantation. Future work will focus on biological evaluation, including cell response and anti-inflammatory performance, to investigate their suitability for orthopedic and dental applications. Full article

(This article belongs to the Special Issue Ceramics Containing Active Molecules for Biomedical Applications)

25 pages, 7414 KB

Open AccessReview

SWOT Wide-Swath Altimetry for Inland-Water Remote Sensing: Applications, Challenges, and Prospects—A Systematic Bibliometric and Thematic Review

by Zhuolin Zhang, Yonghua Sun, Zhixin Jiang, Shiyan Gao, Dinglin Xu, Xue Yang, Ruozeng Wang and Jinkun Zong

Remote Sens. 2026, 18(19), 3274; https://doi.org/10.3390/rs18193274 - 22 Sep 2026

Abstract

The Surface Water and Ocean Topography (SWOT) mission represents a major advance in satellite hydrology by extending conventional nadir altimetry to two-dimensional wide-swath observations of the inland-water surface elevation, extent, width, and slope. This review combines a bibliometric analysis of 556 publications indexed [...] Read more.

The Surface Water and Ocean Topography (SWOT) mission represents a major advance in satellite hydrology by extending conventional nadir altimetry to two-dimensional wide-swath observations of the inland-water surface elevation, extent, width, and slope. This review combines a bibliometric analysis of 556 publications indexed in the Web of Science Core Collection from January 2019 to April 2026 with a thematic synthesis of representative post-launch studies. In contrast to earlier reviews centered largely on mission preparation or individual application domains, we examine the evolution of SWOT research together with study-level evidence on data products, water-surface-elevation retrieval, river-discharge estimation, hydrological applications, uncertainty, and multi-mission integration. The literature shows a clear transition from pre-launch algorithm development and simulation toward post-launch validation and application. Reported water-surface-elevation performance is strongly context dependent: representative studies include a mean RMSE of 0.29 m across Yangtze River stations, MAE below 0.10 m for Tibetan Plateau lakes against ICESat-2, and MAE of 6.7 cm for 1 km²-averaged elevations in herbaceous wetlands. These values should be interpreted as study-specific evidence rather than as single mission-wide accuracy because the validation design, spatial support, environmental conditions, and processing strategies differ substantially among studies. River-discharge estimation remains more uncertain because the bathymetry, roughness, channel geometry, slope estimation, and temporal sampling introduce additional uncertainty. Major remaining challenges concern observation constraints, processing and product uncertainty, transferability, operational implementation, and uneven validation evidence. Future progress will depend on standardized and reproducible processing, uncertainty-aware validation, cross-regional benchmarking, and the integration of SWOT with complementary satellite observations and hydrological or hydraulic models. Full article

(This article belongs to the Topic Advances in Hydrological Remote Sensing, 2nd Edition)

14 pages, 1359 KB

Open AccessArticle

Amino Acid Utilization During Twelve Consecutive Industrial Repitching Cycles of Saccharomyces pastorianus in Lager Beer Fermentation

by Ksenija Obrovnik, Miha Ocvirk, Nataša Kočar Mlinarič and Iztok Jože Košir

Foods 2026, 15(19), 3373; https://doi.org/10.3390/foods15193373 - 22 Sep 2026

Abstract

Amino acids are key assimilable nitrogen sources for brewing yeast and important precursors of beer flavor compounds. This study investigated amino acid utilization during 12 consecutive industrial lager fermentations with Saccharomyces pastorianus under serial repitching conditions. Samples were collected throughout fermentation and analyzed [...] Read more.

Amino acids are key assimilable nitrogen sources for brewing yeast and important precursors of beer flavor compounds. This study investigated amino acid utilization during 12 consecutive industrial lager fermentations with Saccharomyces pastorianus under serial repitching conditions. Samples were collected throughout fermentation and analyzed by HPLC. Fermentation performance remained comparatively stable across all repitching cycles, with little variation in final alcohol content, real degree of fermentation, apparent extract, and pH. Later cycles reached comparable terminal states approximately one day earlier. Exploratory principal component analysis showed that PC1 accounted for 75.29% of total amino-acid-profile variance and primarily reflected the progression of samples from early to later fermentation stages; principal components were not assigned directly to experimental factors. Terminal-value regressions identified the strongest cycle-associated trend for aspartate (nominal p < 0.001; adjusted R² = 0.71), which remained statistically supported after false-discovery-rate correction. Nominal trends observed for asparagine and serine did not remain significant after correction for multiple testing. Overall, conventional fermentation performance and the global structure of amino acid utilization remained comparatively stable across the twelve-cycle industrial sequence. Because the experiment comprised a single consecutive repitching sequence rather than independently replicated generations, cycle-associated changes should be regarded as exploratory process-level observations. Full article

(This article belongs to the Special Issue Development and Application of Analytical Strategies to Characterize Food Quality and Safety of Novel Food Products)

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26 pages, 753 KB

Open AccessArticle

Barriers to Dairy Product Consumption: The Role of Information and Promotional Activities from the Perspective of Polish Physicians

by Agnieszka Komor, Aneta Jarosz-Angowska, Anna Goliszek, Anna Nowak, Artur Krukowski, Sebastian Białoskurski, Bartosz G. Sołowiej, Katarzyna E. Przybyłowicz, Katarzyna Staniewska and Aneta Dąbrowska

Foods 2026, 15(19), 3374; https://doi.org/10.3390/foods15193374 - 22 Sep 2026

Abstract

This study aimed to identify and evaluate physicians‘ perceptions of the key barriers that limit the consumption of dairy products, as well as the information sources and measures that could be implemented in marketing and educational practices to increase dairy product consumption. The [...] Read more.

This study aimed to identify and evaluate physicians‘ perceptions of the key barriers that limit the consumption of dairy products, as well as the information sources and measures that could be implemented in marketing and educational practices to increase dairy product consumption. The study is based on a survey conducted among Polish doctors. Data were analysed using measures of central tendency and variability, rank analysis, and the principal component method. According to the surveyed physicians, the most important barriers were lack of proper eating habits and insufficient knowledge of the health benefits of dairy products, followed by concerns related to food adulteration and information about potential health risks for certain consumer groups. Based on principal component analysis of the surveyed physicians’ assessments, the perceived barriers to dairy product consumption were grouped into three dimensions: educational and cultural barriers, ethical and environmental barriers, and pragmatic and health-related barriers. According to respondents, doctors and recommendations from family members and friends are important sources of information about dairy products. In the physicians’ view, digital communication channels are perceived to have a greater influence on consumer attitudes and behaviours than traditional media. The surveyed doctors suggested several measures that could increase consumer interest in dairy products, including disseminating expert-endorsed messages, running social campaigns to raise awareness among children and parents, publicising recommendations issued by scientific institutions on the benefits of consuming dairy products and educating consumers about quality certification labels. This study addresses a research gap by providing an integrated assessment of dairy consumption barriers, information sources, and promotional and educational activities from the perspective of Polish physicians, thereby complementing previous consumer-focused research with a professional medical perspective. The study’s results also enable the identification of measures to increase demand for dairy products by leveraging doctors’ influence on consumer opinions in the marketing communication process. Full article

(This article belongs to the Topic Food Security and Healthy Nutrition)

20 pages, 478 KB

Open AccessArticle

Combined Transcranial Direct Current Stimulation and Transcutaneous Cervical Vagus Nerve Stimulation for Anxiety and Depression: An Exploratory Pilot Study

by Maria Marchiș, Magdalena Iorga, Iustina-Gabriela Mihăianu and Maria-Manuela Apostol

Brain Sci. 2026, 16(10), 1004; https://doi.org/10.3390/brainsci16101004 - 22 Sep 2026

Abstract

Anxiety and depressive disorders are among the leading causes of disability worldwide, yet current treatments remain limited by modest efficacy and restricted accessibility; non-invasive neuromodulation techniques such as transcranial direct current stimulation (tDCS) and transcutaneous cervical vagus nerve stimulation (tcVNS) have emerged as [...] Read more.

Anxiety and depressive disorders are among the leading causes of disability worldwide, yet current treatments remain limited by modest efficacy and restricted accessibility; non-invasive neuromodulation techniques such as transcranial direct current stimulation (tDCS) and transcutaneous cervical vagus nerve stimulation (tcVNS) have emerged as promising alternatives whose combination may produce complementary clinical effects. Methods: This proof-of-concept pilot study evaluated the feasibility, tolerability, and preliminary clinical effects of a multimodal three-component protocol comprising tDCS and tcVNS delivered alongside supportive psychological counseling in 12 adults (Mage = 54.75 ± 17.47 years) with clinically significant anxiety and depressive symptoms. Participants received 10 consecutive sessions of anodal tDCS over the left dorsolateral prefrontal cortex (2 mA, 30 min) followed by tcVNS with PEMF, with symptoms assessed using the Beck Anxiety Inventory (BAI) and Beck Depression Inventory (BDI) and pre–post comparisons performed via the Wilcoxon signed-rank test. Results: Significant reductions were observed for both outcomes: BAI scores decreased by 52.0% (Z = −3.059, p_exact < 0.001, p_asymp = 0.002, r = 0.883) and BDI scores by 55.9% (Z = −3.059, p_exact < 0.001, p_asymp = 0.002, r = 0.883); the proportion of participants in the minimal BDI-II symptom range rose from 8.3% to 83.3%, and no adverse events were reported. Standard clinical response rates (≥50% score reduction from baseline) were achieved by 50.0% of participants for depression (BDI) and 41.7% for anxiety (BAI), with 25.0% demonstrating a concurrent dual response on both measures. Exploratory profiling and multivariable continuous modeling indicated that higher cumulative improvement was descriptively observed in older participants with greater baseline symptom severity, with baseline anxiety showing the strongest continuous standardized association (β = 0.548, p = 0.104). These are hypothesis-generating observations only. Conclusions: The combined three-component package (tDCS, tcVNS, and concurrent supportive counseling) appears feasible, well tolerated, and associated with pre–post symptom reductions that, in the absence of a control condition, cannot be causally attributed to the intervention, warranting further investigation in adequately powered randomized sham-controlled trials. Full article

(This article belongs to the Special Issue Depression, Anxiety and Related Psychiatric Disorders: Clinical Advances and Future Directions)

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25 pages, 365 KB

Open AccessReview

Sugar-Sweetened Beverages and Childhood Obesity: A Life-Course Perspective

by Bianca Simionescu, Ancuța Lupu, Alexandra Sidoreac, Vasile Valeriu Lupu, Elena Roxana Buzilă, Raluca Olariu, Bogdan Novac, Ileana Ioniuc, Mihaela Monica Alexoae, Roxana Șerban, Otilia Novac, Emil Anton and Oana Raluca Temneanu

Nutrients 2026, 18(19), 3118; https://doi.org/10.3390/nu18193118 - 22 Sep 2026

Abstract

Background/Objectives: Childhood obesity represents a major global health challenge. Sugar-sweetened beverages (SSBs) remain an important modifiable dietary exposure; however, adolescent beverage behavior is often examined independently of dietary patterns established earlier in life. This narrative review examines SSB consumption and adiposity across [...] Read more.

Background/Objectives: Childhood obesity represents a major global health challenge. Sugar-sweetened beverages (SSBs) remain an important modifiable dietary exposure; however, adolescent beverage behavior is often examined independently of dietary patterns established earlier in life. This narrative review examines SSB consumption and adiposity across the life course, particularly during the first 1000 days as a sensitive period for developing dietary habits. Methods: Targeted literature searches were conducted in PubMed, Scopus, and Web of Science (January 2021–13 August 2026). We prioritized systematic reviews, meta-analyses, prospective cohort studies, randomized trials, and mechanistically informative studies. Study selection was purposive, and causal language was reserved for rigorous designs. Results: SSB intake is associated with higher body mass index, waist circumference, body fat percentage, and pediatric obesity. Potential mechanistic pathways include incomplete energy compensation for liquid calories, fructose-related hepatic de novo lipogenesis under conditions of high exposure, and insulin resistance; however, the independent contribution of fructose remains difficult to disentangle from excess energy intake, beverage form, and the broader dietary matrix. SSB consumption patterns may emerge early and track through childhood, influenced by family, socioeconomic, and commercial determinants. Evidence does not consistently support the hypothesis that repeated sweetness exposure increases subsequent sweetness liking. Metabolic consequences include dyslipidemia, hypertension, and metabolic dysfunction-associated steatotic liver disease (MASLD). Prevention approaches include family- and school-based interventions, beverage reformulation, and fiscal policies. Conclusions: A life-course perspective supports shaping beverage environments early, strengthening healthy home food environments, and implementing structural public-health interventions rather than addressing unhealthy patterns only after they become established. However, policy effects may vary across pediatric subgroups. Full article

(This article belongs to the Special Issue Optimizing Nutrition in Pediatrics: From Preterm Infants to Adolescents)

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26 pages, 2645 KB

Open AccessArticle

Instructor-Personalized WolframAlpha-Supported Instruction for Learning Mathematical Functions: A Longitudinal Quasi-Experimental Learning Analytics Study

by Clodoaldo Ramos Pando, Teófilo Félix Valentín Melgarejo, Flaviano Armando Zenteno Ruiz, Armando Isaías Carhuachín Marcelo, Raúl Malpartida Lovatón, Víctor Luis Albornoz Dávila, Ulises Espinoza Apolinario, Rogelio Amancio Landaveri Martínez, Pablo Lolo Valentín Melgarejo, Wilmer Napoleón Guevara Vásquez, Nely Teresa Aldana Taniguche, Pablo Lenin La Madrid Vivar, Liz Ketty Bernaldo Faustino and José Rovino Alvarez Lopez

Multimodal Technol. Interact. 2026, 10(10), 99; https://doi.org/10.3390/mti10100099 - 22 Sep 2026

Abstract

Computational knowledge tools are increasingly integrated into higher education, but their educational value may depend less on the technology itself than on the pedagogical structure surrounding its use. This longitudinal study compared four instructional conditions for undergraduate learning of mathematical functions: traditional instruction [...] Read more.

Computational knowledge tools are increasingly integrated into higher education, but their educational value may depend less on the technology itself than on the pedagogical structure surrounding its use. This longitudinal study compared four instructional conditions for undergraduate learning of mathematical functions: traditional instruction (TI), unstructured WolframAlpha use (UWA), scaffolded WolframAlpha-supported instruction (SWA), and instructor-personalized WolframAlpha-supported instruction (IPWA). WolframAlpha was treated as a non-adaptive computational knowledge engine rather than as an autonomous adaptive tutoring system. In IPWA, personalization was implemented by instructors through predefined pedagogical responses to observed learner indicators and was not generated autonomously by WolframAlpha. A longitudinal four-arm quasi-experimental study was conducted with 600 first-semester undergraduate students at the National Daniel Alcides Carrión University, Peru. The eight-week intervention comprised traditional instruction, unstructured WolframAlpha use, scaffolded WolframAlpha-supported instruction, and instructor-personalized WolframAlpha-supported instruction, followed by retention and transfer assessments at Weeks 16 and 20. Learning outcomes were assessed across five occasions, and behavioral records were collected during WolframAlpha-supported sessions. The instructor-personalized condition showed the highest adjusted achievement trajectories and stronger maintenance of learning at the follow-up assessments. Self-regulated learning, reflection frequency, prompt complexity, and prior achievement were positively associated with mathematics achievement, whereas mathematics anxiety was negatively associated. Platform-interaction analyses identified transitions toward more exploratory and verification-oriented patterns; however, these records did not capture learning activities undertaken outside WolframAlpha. The findings suggest that instructor-mediated personalization surrounding a computational tool may support mathematics learning, although the quasi-experimental design does not permit definitive causal conclusions. Full article

(This article belongs to the Special Issue Online Learning to Multimodal Era: Interfaces, Analytics and User Experiences)

17 pages, 7882 KB

Open AccessArticle

Molecular Mechanisms Underlying α-Linolenic Acid-Enhanced Reproductive Performance in Male Blue Foxes

by Chongshan Yuan, Shuai Qi, Yu Tian, Wenhui Cao, Jia Wang, Min Wu, Gongqing Wei, Xingyuan Zhu, Xinyan Cao and Aiwu Zhang

Animals 2026, 16(19), 2984; https://doi.org/10.3390/ani16192984 - 22 Sep 2026

Abstract

α-Linolenic acid (ALA), an essential n-3 polyunsaturated fatty acid, exerts critical effects on animal reproductive function. However, the molecular mechanisms by which dietary ALA regulates reproductive performance in male blue foxes remain largely unclear. In the present study, 16 male blue foxes of [...] Read more.

α-Linolenic acid (ALA), an essential n-3 polyunsaturated fatty acid, exerts critical effects on animal reproductive function. However, the molecular mechanisms by which dietary ALA regulates reproductive performance in male blue foxes remain largely unclear. In the present study, 16 male blue foxes of similar age and condition were assigned to four dietary groups (n = 4 per group) receiving a basal diet supplemented with 0, 0.5, 1.25, or 2 g/kg of ALA. q-PCR validation further confirmed that medium-dose ALA supplementation significantly upregulated mRNA levels of steroid synthesis-related genes (StAR, LHCGR, INSL3) and antioxidant gene GPX3, while inhibiting the calcium-signaling gene GRIN1. Untargeted liquid chromatography–mass spectrometry (LC–MS) metabolomics of seminal plasma and RNA-seq transcriptomics of testicular tissue were combined to explore the underlying molecular pathways of ALA in terms of its modulating male blue fox reproduction. A total of eight significantly altered seminal plasma metabolites were screened out through metabolomics: mainly arachidonic acid, anandamide, oxaloacetic acid, guanine, lactic acid, dihydrodaidzein, stearic acid, and valylisoleucine. Transcriptomic analysis identified seven differentially expressed genes (DEGs), including FRAS1, COL1A1, CDH17, CLDN4, CTH, KYAT1, and GRIN1, enriched in three core KEGG pathways: ECM-receptor interaction, cell-adhesion molecules and selenocompound metabolism. Spearman correlation analysis revealed extensive significant correlations between seminal-plasma differential metabolites and testicular genes, indicating complicated metabolite-gene crosstalk. Collectively, appropriate dietary ALA remodels the seminal-plasma metabolic microenvironment, stabilizes testicular tissue structure, enhances gonadal antioxidant capacity and facilitates testicular steroidogenesis, thereby improving the reproductive potential of male blue foxes. This study elucidates the nutritional regulatory mechanism of ALA in breeding male blue foxes and provides theoretical references for the application of ALA as a functional feed additive in the production of canines. Full article

(This article belongs to the Section Animal Genetics and Genomics)

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24 pages, 1019 KB

Open AccessReview

Natural Modulators of the PPARγ–Adiponectin Axis in Insulin Resistance: Structural Pharmacology, Receptor-State Selectivity, and Translational Readiness

by Pirscoveanu Denisa Floriana Vasilica, Diana-Maria Trasca, Adina Maria Kamal, Renata Maria Varut, Romeo Popa, Pluta Ion Dorin, Dirnu Rodica, Maria Stoica, Coanca Staicu Cristina Teodora and George-Alin Stoica

Pharmaceuticals 2026, 19(10), 1507; https://doi.org/10.3390/ph19101507 - 22 Sep 2026

Abstract

Insulin resistance reflects maladaptive communication among adipose tissue, the liver, skeletal muscle, immune cells, and the vasculature. Peroxisome proliferator-activated receptor gamma (PPARγ) is a validated insulin-sensitizing target, but classical full agonism couples metabolic efficacy to weight gain, fluid retention, and skeletal liability. This [...] Read more.

Insulin resistance reflects maladaptive communication among adipose tissue, the liver, skeletal muscle, immune cells, and the vasculature. Peroxisome proliferator-activated receptor gamma (PPARγ) is a validated insulin-sensitizing target, but classical full agonism couples metabolic efficacy to weight gain, fluid retention, and skeletal liability. This critical narrative review evaluates plant-derived and dietary molecules through a receptor-state framework that distinguishes direct binding from reporter activation and separates full agonism, partial agonism, selective modulation, antagonism with retained metabolic function, and post-translational control of PPARγ. Adiponectin is considered a functional inter-organ circuit linking adipocyte PPARγ activity to AdipoR1/AdipoR2 signaling, AMPK, PPARα, ceramide metabolism, glucose disposal, and fatty-acid oxidation. Amorfrutins provide the most coherent target-led natural-product evidence, whereas chelerythrine offers a structurally defined selective-modulation benchmark; honokiol, diosmin, betulinic acid, valerenic acid, punicic acid, alkamides, and defined extracts show heterogeneous mechanistic and translational maturity. Human evidence linking natural PPARγ ligands to verified target engagement and improved insulin sensitivity remains limited. We therefore propose a seven-stage translational roadmap connecting chemical identity, orthogonal binding, receptor-state pharmacology, cellular function, tissue exposure, mechanism-matched safety, and randomized human proof. Full article

(This article belongs to the Special Issue Effects of Natural Products to Manage Metabolic Syndrome-Associated Pathologies)

20 pages, 1042 KB

Open AccessArticle

Assessment of Antioxidant Capacity, Phytochemical Phenolic Composition, Cholinesterase and α-Glucosidase Inhibitory Ac-tivities, and Antimicrobial Potential of Tribulus terrestris

by Ashwell R. Ndhlala, Emrah Dikici, Sevgi Altın, Arzu Kavaz Yüksel, Mesut Işık and Ekrem Köksal

Molecules 2026, 31(19), 3370; https://doi.org/10.3390/molecules31193370 - 22 Sep 2026

Abstract

Tribulus terrestris (TT) is a medicinal plant traditionally utilized in the management of various health conditions, including inflammation, edema, and hypertension. The present study aimed to investigate the phenolic profile of the ethanolic extract of TT and to evaluate its antioxidant, antimicrobial, anticholinesterase, [...] Read more.

Tribulus terrestris (TT) is a medicinal plant traditionally utilized in the management of various health conditions, including inflammation, edema, and hypertension. The present study aimed to investigate the phenolic profile of the ethanolic extract of TT and to evaluate its antioxidant, antimicrobial, anticholinesterase, and α-glucosidase inhibitory properties. Phenolic analysis revealed several quantified compounds, including vanillic acid, resveratrol, fumaric acid, acetohydroxamic acid, quercetin, hydroxybenzoic acid, salicylic acid, butein, caffeic acid, and catechin hydrate, while phloridzin dihydrate was detected below the quantification limit. Among the detected compounds, vanillic acid was found to be the predominant phenolic component. Biological activity assays demonstrated that the extract possessed remarkable cholinesterase inhibitory potential, exhibiting IC₅₀ values of 9.11 ± 2.12 μg mL⁻¹ and 8.77 ± 0.62 μg mL⁻¹ against acetylcholinesterase (AChE) and butyrylcholinesterase (BChE), respectively. Furthermore, antioxidant capacity was confirmed through FRAP and CUPRAC assays, with corresponding values of 0.136 and 0.296. The antimicrobial efficacy of the extract was evaluated against Staphylococcus aureus, Escherichia coli, and Salmonella Typhimurium, revealing inhibitory effects against all tested bacterial strains. Overall, the findings indicate that the TT represents a promising natural source of phenolic compounds with significant antioxidant, antibacterial, and enzyme inhibitory activities, supporting its potential application in the development of pharmaceutical and therapeutic products. Full article

(This article belongs to the Special Issue Natural Products and Microbiology in Human Health, 2nd Edition)

23 pages, 2179 KB

Open AccessArticle

Early and Multimodal Care for Patients with Lung Cancer: Findings from the ACCEPT Study

by Christian Grah, Shiao Li Oei, Felix Kindler, Alexander Krabbe, Hannah Wüstefeld, Marcus Reif, Anja Thronicke, Steven Ngandeu Schepanski, Georg Seifert and Friedemann Schad

Cancers 2026, 18(19), 3081; https://doi.org/10.3390/cancers18193081 - 22 Sep 2026

Abstract

Objective: Treating lung cancer with a combination of targeted cancer therapy, supportive, and psychosocial treatments is important in modern oncology. The ACCEPT study investigated the efficacy of a 12-week early multimodal supportive care program on quality of life. Methods: ACCEPT was [...] Read more.

Objective: Treating lung cancer with a combination of targeted cancer therapy, supportive, and psychosocial treatments is important in modern oncology. The ACCEPT study investigated the efficacy of a 12-week early multimodal supportive care program on quality of life. Methods: ACCEPT was a single-center, non-randomized, prospective, open-label trial, with a pragmatic real-world design guided by patient choice. Patients with newly diagnosed, stage II-IV lung cancer participated in the outpatient ACCEPT program (psycho-oncology, health education, and training-based interventions alongside standard care). Longitudinal patient-reported outcome measures (PROMs) were collected. The primary outcome was the change in quality of life at 12 weeks measured by the Trial Outcome Index (TOI). Secondary outcomes included further exploratory PROM changes and overall survival. Results: Between April 2018 and August 2021, 214 lung cancer patients (median age 67, 53% male, 57% stage IV) were enrolled, with 116 patients evaluable for longitudinal PROM changes at 12 weeks. Participation in the multimodal ACCEPT program was associated with up to 17% improvement in the TOI, psychological distress, and sleep quality (p < 0.0001). Multivariate analyses revealed that greater session attendance was significantly and dose-dependently associated with improvements in the TOI as well as reductions in depression and anxiety. Higher engagement in multimodal sessions was also linked to reduced fatigue. Furthermore, exploratory signals of improved overall survival were observed among the 40 patients (18.7%) who fully completed the ACCEPT program. Conclusions: This pragmatic, patient-centered, multimodal supportive care program for lung cancer patients was associated with dose-dependent improvements in quality of life and psychological distress. While exploratory signals of improved survival were observed, multicenter randomized controlled trials are required to confirm these findings and firmly establish the role of such supportive care programs in routine oncology. Full article

(This article belongs to the Special Issue Non-Pharmacological Interventions in Oncology Supportive and Palliative Care)

18 pages, 4595 KB

Open AccessArticle

Evaluation of Key Economic Traits in a Green Mutant of Neopyropia yezoensis: A Promising Candidate for Commercial Cultivation with Superior Umami Taste

by Yinyin Deng, Cuicui Tian, Li-En Yang, Tao Zhang, Wei Zhou and Chuanming Hu

Foods 2026, 15(19), 3372; https://doi.org/10.3390/foods15193372 - 22 Sep 2026

Abstract

Developing Neopyropia breeding lines with superior flavor qualities is crucial to meet the market demand for premium seaweed products. In this study, we evaluated the key economic traits of Y-G001, a stable chemically induced green mutant of Neopyropia yezoensis. Agronomic performance was [...] Read more.

Developing Neopyropia breeding lines with superior flavor qualities is crucial to meet the market demand for premium seaweed products. In this study, we evaluated the key economic traits of Y-G001, a stable chemically induced green mutant of Neopyropia yezoensis. Agronomic performance was assessed in fresh thalli, while photosynthetic pigment and flavor profiles were evaluated in both fresh thalli and dried sheets after the thermal drying process. Compared to the high-yielding wild-type cultivar (ST-2), Y-G001 exhibited comparable growth rate and archeospore-releasing capacity, indicating its suitability for large-scale cultivation. The distinctive green coloration of Y-G001 resulted from an exceptionally low phycoerythrin-to-phycocyanin ratio (PE/PC = 0.04) and remained stable after the drying process. Notably, Y-G001 possessed a superior flavor profile, driven by a 12.13% increase in umami free amino acids and a 16.44% increase in umami nucleotides. Thermal drying further enhanced these taste-active compounds, acting as a flavor amplifier. Consequently, the equivalent umami concentrations (EUCs) of fresh and dried Y-G001 were 68.27% and 59.77% higher than those of their wild-type counterparts, respectively. Pearson correlation analysis further revealed distinct concurrent accumulation patterns among these key flavor metabolites in the mutant. These findings demonstrate that Y-G001 is a promising breeding line integrating unique coloration, robust agronomic traits, and a superior umami taste, offering substantial commercial potential for the Neopyropia industry. Full article

(This article belongs to the Section Food Nutrition)

13 pages, 459 KB

Open AccessOpinion

Beyond Crude IVF KPIs: A Stepwise Framework for Denominator-Aware and Case-Mix-Adjusted Performance Interpretation

by Péter Mauchart, Emese Wágner and Ákos Várnagy

Reprod. Med. 2026, 7(4), 52; https://doi.org/10.3390/reprodmed7040052 - 22 Sep 2026

Abstract

Performance monitoring is central to assisted reproductive technology (ART), yet crude in vitro fertilization (IVF) key performance indicators (KPIs) are strongly influenced by denominator selection, patient prognosis, treatment strategy, case mix and sample size. This opinion article examines the methodological limitations of conventional [...] Read more.

Performance monitoring is central to assisted reproductive technology (ART), yet crude in vitro fertilization (IVF) key performance indicators (KPIs) are strongly influenced by denominator selection, patient prognosis, treatment strategy, case mix and sample size. This opinion article examines the methodological limitations of conventional IVF KPIs and proposes a denominator-aware, step-specific and case-mix-adjusted framework for their interpretation. Concepts from international KPI consensus frameworks, outcome-reporting literature, clinic-comparison methods and reproductive prediction models were integrated into a conceptual quality management framework. IVF was treated as a sequence of linked biological and clinical transitions. The framework links five elements: specification of the performance question, validation of the denominator, estimation of expected outcomes from temporally appropriate patient- and cycle-level factors, comparison of observed and expected outcomes, and uncertainty-aware interpretation of step-specific process patterns. A hypothetical worked example demonstrates stage-specific crude rates, expected events and observed/expected (O/E) ratios. The process-pattern labels are conceptual descriptors rather than validated classifications, and signals require multidisciplinary review. The framework has the potential to support more context-aware and biologically coherent performance review. It should complement, not replace, conventional KPIs; whether it improves fairness, transparency or quality management remains to be established in prospective multicentre validation. Full article

23 pages, 3437 KB

Open AccessArticle

Red–Blue Light-Emitting Diode Spectral Composition Enhances Growth, Yield and Functional Metabolites in Brassicaceae Microgreens: Red Radish (‘Red Rambo’ Raphanus sativus) and Red Mustard (Brassica juncea, MR 408)

by Noxolo P. Mbandlwa-Mthembu, Semakaleng Mpai and Dharini Sivakumar

Horticulturae 2026, 12(10), 1197; https://doi.org/10.3390/horticulturae12101197 - 22 Sep 2026

Abstract

This study evaluated the effects of different light-emitting diode (LED) wavelengths on growth, yield, and phytochemical composition of Brassicaceae microgreens, aiming to identify lighting strategies that enhance both biomass production and nutritional quality in controlled-environment agriculture. Red radish (Raphanus sativus ‘Red Rambo’) [...] Read more.

This study evaluated the effects of different light-emitting diode (LED) wavelengths on growth, yield, and phytochemical composition of Brassicaceae microgreens, aiming to identify lighting strategies that enhance both biomass production and nutritional quality in controlled-environment agriculture. Red radish (Raphanus sativus ‘Red Rambo’) and red mustard (Brassica juncea ‘MR 408’) were grown under red (R), blue (B), green (G), white (W), and combined LED spectra (R+B, R+G, and G+B) at a constant photosynthetic photon flux density (PPFD) of 300 μmol/m²/s. The R+B treatment produced the best growth performance, resulting in the shortest hypocotyls (red radish: 11.17 cm; red mustard: 7.17 cm) and highest fresh weights (red radish: 92.33 g; red mustard: 54.00 g). The W- light significantly enhanced the anthocyanin accumulation in red radish, including cyanidin-3,5-diglucoside (545.08 mg/100 g dry weight DW) and malvidin-3-glucoside (81.92 mg/100 g DW). In contrast, R+B lighting enhanced carotenoid accumulation in both species, including lutein, trans-β-carotene, and cis-β-carotene, and increased ferulic acid (red radish: 595.02 mg/100 g DW; red mustard: 65.25 mg/100 g DW), epicatechin (radish: 97.63 mg/100 g DW; mustard: 63.21 mg/100 g DW), total glucosinolates (red radish:341.02; red mustard 272.36 μmol/g DW, and ascorbic acid (red radish: 658.78 mg/100 g DW; red mustard: 967.83 mg/100 g DW). Antioxidant activity responded in a species-specific manner, peaking under white light in red radish and under R+B light in red mustard. The results demonstrate that LED spectral composition strongly influences both plant growth and secondary metabolism and that species-specific responses determine the optimal lighting strategy. The R+B lighting is effective for improving biomass production and accumulation of carotenoids, glucosinolates, and ascorbic acid, whereas white light is more effective for enhancing anthocyanin content in red radish. These findings provide a basis for developing lighting strategies to produce high-value Brassicaceae microgreens with targeted nutritional attributes. Full article

(This article belongs to the Special Issue Horticultural Crops Responses to LED Lighting)

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