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20 pages, 6372 KB

Open AccessArticle

Land Transition Pathways Govern Carbon Storage Dynamics in an Olympic Host Region: A PLUS–InVEST Simulation in Yanqing District

by Min Wang, Hui Zhang and Quan Zhou

Land 2026, 15(9), 1632; https://doi.org/10.3390/land15091632 (registering DOI) - 3 Sep 2026

Abstract

Mega-events can accelerate land–use/land cover change (LULCC) through infrastructure development and ecological interventions, but the carbon consequences of different land transition pathways remain unclear. Using Yanqing District, a host region of the Beijing 2022 Winter Olympics, as a case study, this study investigates [...] Read more.

Mega-events can accelerate land–use/land cover change (LULCC) through infrastructure development and ecological interventions, but the carbon consequences of different land transition pathways remain unclear. Using Yanqing District, a host region of the Beijing 2022 Winter Olympics, as a case study, this study investigates LULC transitions, carbon storage dynamics, and future land management. A coupled PLUS–InVEST framework integrating transition attribution and trajectory analysis was applied to 10-m LULC datasets (2018, 2021, and 2024) to reconstruct historical transitions and simulate four land management scenarios for 2035. Results indicated that total carbon storage increased continuously from 41.19 × 10⁶ t C in 2018 to 42.14 × 10⁶ t C in 2024 despite concurrent urban expansion. This increase resulted from distinct transition processes across the two periods: cropland-to-rangeland conversion contributed most to carbon gains during 2018–2021, whereas rangeland-to-trees conversion dominated gains during 2021–2024. Pixel-level trajectory analysis further revealed that these dominant transitions rarely formed a continuous restoration sequence at the same locations, with rangeland–rangeland–trees trajectories accounting for 76.2% of trajectories leading to trees-class gains. Future simulations showed that the Urban Development Scenario would reduce carbon storage by 5.6%, whereas the Ecological Protection Scenario would increase carbon storage by 2.3% relative to the 2024 baseline. These results indicate that regional carbon dynamics depend not only on LULC composition but also on transition pathways, providing insights into how transition pathways can inform ecological restoration and sustainable land management. Full article

(This article belongs to the Section Land Use, Impact Assessment and Sustainability)

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17 pages, 5208 KB

Open AccessArticle

Temporal, Spatial, and Environmental Variation in Virus-like Particle Abundance in the Northwestern Arabian Gulf

by Awatef Almutairi, Dhia Al-Bader and Mashael Al-Mutairi

Viruses 2026, 18(9), 969; https://doi.org/10.3390/v18090969 (registering DOI) - 3 Sep 2026

Abstract

Marine viruses are important components of microbial communities and influence their structure and dynamics, yet their variability remains poorly documented in the northwestern Arabian Gulf. Virus-like particle (VLP) abundance was monitored over four years at three coastal sites representing different environmental settings in [...] Read more.

Marine viruses are important components of microbial communities and influence their structure and dynamics, yet their variability remains poorly documented in the northwestern Arabian Gulf. Virus-like particle (VLP) abundance was monitored over four years at three coastal sites representing different environmental settings in Kuwait. Surface and depth samples were collected during each sampling period, along with physicochemical and nutrient data. VLP abundance fluctuated throughout the study and differed among sites and between depths. VLP counts tended to be higher at the southern site and near the surface, while the lowest values were recorded in Kuwait Bay. The three sites had distinct environmental characteristics, but relationships between VLP abundance and individual physicochemical variables varied among sites and seasons. When environmental, spatial, and temporal variables were considered together, Random Forest identified season, dissolved oxygen, and nutrients, particularly nitrate, among the important predictors of VLP abundance. Dissolved oxygen showed a nonlinear association with VLP abundance in the generalized additive model (GAM), and lower abundance at depth remained significant after accounting for the measured environmental variables, while site effects were not significant in this model. Overall, VLP abundance showed marked spatial and temporal variability across Kuwait coastal waters, with patterns associated with multiple environmental and seasonal factors. This four-year record provides a baseline for viral abundance in the northwestern Arabian Gulf and supports further investigation of the biological and environmental processes influencing viral dynamics in this highly variable coastal system. Full article

(This article belongs to the Special Issue Virioplankton and Climate Change)

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37 pages, 5549 KB

Open AccessReview

Programming Hydrogel Release Kinetics to Tissue Healing Phases: From Network Design to Therapeutic Synchronization

by Qiao Chen, Tong Wang, Lusi Zou and Qi Dong

Gels 2026, 12(9), 805; https://doi.org/10.3390/gels12090805 (registering DOI) - 3 Sep 2026

Abstract

The sequential phases of tissue healing—inflammation, proliferation, and remodeling—demand distinct pharmacokinetic profiles that conventional drug delivery systems fail to provide, creating a “chronotherapy gap” that contributes to chronic wound pathologies. Hydrogels, with their highly tunable network structures, offer a unique platform to program [...] Read more.

The sequential phases of tissue healing—inflammation, proliferation, and remodeling—demand distinct pharmacokinetic profiles that conventional drug delivery systems fail to provide, creating a “chronotherapy gap” that contributes to chronic wound pathologies. Hydrogels, with their highly tunable network structures, offer a unique platform to program release kinetics in synchrony with these healing timelines. This review systematically examines design strategies for phase-synchronized hydrogel systems, categorized into three hierarchical paradigms: intrinsic network control (crosslinking density, degradation kinetics, and architectural engineering) that pre-programs release profiles; extrinsic/responsive control (endogenous pH/ROS/MMP/glucose and exogenous NIR/ultrasound/electro/magnetic triggers) that enables on-demand phase-shifting; and integrated systems that combine passive spatial compartmentalization with active responsiveness. We survey representative applications across cutaneous wounds, bone defects, cartilage, tendon, myocardial, and neural tissues, highlighting both common design principles and tissue-specific adaptations. Key translational bottlenecks—including in vivo–in vitro discrepancies, cargo stability, sterilization challenges, and regulatory complexity—are critically examined, alongside emerging frontiers such as closed-loop biosensing, artificial intelligence-driven design, and four-dimensional printing. We conclude that the field is evolving from passive drug depots toward active therapeutic synchronizers, where material programming is set to the body’s biological clock, offering a transformative paradigm for regenerative medicine. Full article

(This article belongs to the Special Issue Novel Hydrogels for Drug Delivery and Regenerative Medicine)

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17 pages, 3384 KB

Open AccessArticle

A Three-Phase Progressive Multi-Beam Scheduling Algorithm for Large-Scale LEO Constellation TT&C Operations

by Rongzhen Zhu, Yongqiang Li, Chenbin Wang, Xin Wen, Kunqi Li, Xiangyao Liu, Haibo Zhang and Jichao Wang

Aerospace 2026, 13(9), 804; https://doi.org/10.3390/aerospace13090804 (registering DOI) - 3 Sep 2026

Abstract

The multi-beam tracking, telemetry, and command (TT&C) scheduling problem for large-scale low Earth orbit (LEO) constellations carrying thousands of satellites brings formidable challenges. Strict resource limitations and visibility constraints trigger combinatorial explosion of feasible scheduling solutions. This paper proposes a three-phase progressive multi-beam [...] Read more.

The multi-beam tracking, telemetry, and command (TT&C) scheduling problem for large-scale low Earth orbit (LEO) constellations carrying thousands of satellites brings formidable challenges. Strict resource limitations and visibility constraints trigger combinatorial explosion of feasible scheduling solutions. This paper proposes a three-phase progressive multi-beam scheduler (3PMS), which disassembles the complex integrated scheduling problem into hierarchically tractable subproblems. Phase I adopts a priority-aware first-come-first-served (FCFS) strategy combined with a dual-heap preemption mechanism to guarantee the execution of emergency tasks. Phase II implements load-balanced beam allocation based on a load-balance scoring function. Phase III introduces optimal execution window selection within visible arcs. Experiments are performed on two LEO constellation scenarios: the first is a single-shell orbital configuration with 1500 satellites, and the second is a three-shell architecture comprising 6080 satellites. Under extremely limited beam resources (1 beam), the worst-case single-beam capacity is 708 tasks per day, assuming every task consumes the maximum duration of 120 s, corresponding to 47.2% coverage for 1500 satellites and 11.6% for 6080 satellites. As the number of beams increases to five, all algorithms achieve 100% coverage for the 1500-satellite constellation, while the 6080-satellite constellation requires twenty beams for near-complete coverage. 3PMS demonstrates significant advantages in load balancing (Gini coefficient reduced from 0.0993 to 0.0003) and link quality (C/N improved by 5.5 dB). This paper verifies the feasibility of multi-beam scheduling algorithms for TT&C missions of large-scale satellite mega-constellations. Full article

(This article belongs to the Section Astronautics & Space Science)

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24 pages, 2780 KB

Open AccessArticle

Wood–Water Relations of Thermally Treated Pleated Beech and Oak Wood

by Róbert Németh, Mátyás Báder, Bíbor Júlia Horváth and Miklós Bak

Forests 2026, 17(9), 1049; https://doi.org/10.3390/f17091049 (registering DOI) - 3 Sep 2026

Abstract

Pleating (20% compression) is a thermo-hydromechanical modification that improves wood pliability but markedly increases longitudinal dimensional instability. This study evaluates the combined effects of pleating, fixation (maintaining the compressed state for 5 h), and subsequent thermal treatment (160 and 200 °C) on the [...] Read more.

Pleating (20% compression) is a thermo-hydromechanical modification that improves wood pliability but markedly increases longitudinal dimensional instability. This study evaluates the combined effects of pleating, fixation (maintaining the compressed state for 5 h), and subsequent thermal treatment (160 and 200 °C) on the wood–water relations of beech (Fagus sylvatica L.) and sessile oak (Quercus petraea (Matt.) Liebl.). Density, equilibrium moisture content, swelling, shrinking, anisotropy, and anti-swelling efficiency were determined over two soaking–drying cycles. Thermal modification substantially reduced equilibrium moisture content from approximately 10.3%–10.4% in untreated wood to 7.8%–8.0% at 160 °C and 4.9%–5.0% at 200 °C. In contrast, mechanical modification largely mitigated the density loss caused by thermal treatment. Although pleating and fixation greatly increased longitudinal dimensional changes, thermal treatment effectively compensated for this effect. Treatment at 200 °C provided the greatest dimensional stability but was accompanied by more extensive chemical degradation. The results demonstrate that combining pleating with moderate thermal treatment may offer an effective, chemical-free approach to improving the dimensional stability of compressed hardwoods. Full article

(This article belongs to the Special Issue Wood Treatments and Modification Technologies—2nd Edition)

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14 pages, 3765 KB

Open AccessArticle

Benchmarking Large Language Models on Long-Tail Plant Taxonomic Knowledge with PTTB-600

by Jian He, Jiamin Xiao, Hong Qu and Lei Xie

Diversity 2026, 18(9), 541; https://doi.org/10.3390/d18090541 (registering DOI) - 3 Sep 2026

Abstract

Plant taxonomic knowledge contains a long tail of infrequently encountered names, diagnostic characters, and nomenclatural decisions, yet model reliability across this distribution remains unclear. We developed the Chinese-language PTTB-600, comprising 200 general, 300 ordinary specialized, and 100 long-tail fill-in questions, and evaluated 31 [...] Read more.

Plant taxonomic knowledge contains a long tail of infrequently encountered names, diagnostic characters, and nomenclatural decisions, yet model reliability across this distribution remains unclear. We developed the Chinese-language PTTB-600, comprising 200 general, 300 ordinary specialized, and 100 long-tail fill-in questions, and evaluated 31 large language models (LLMs) or run modes under closed-book conditions without retrieval augmentation. The first author drafted the question bank and answer key; three coauthors with doctorates in plant taxonomy reviewed them independently. All models scored at least 197/200 on general questions, and 21 achieved full marks. The six highest-scoring models answered 291–297/300 ordinary specialized questions (97.0–99.0%) but achieved 63.0–90.0% accuracy on long-tail fill-in questions. Gemini 3.1 Pro Preview ranked first at 587/600; ranks two through six formed a closely spaced cluster with no significant adjacent differences after Holm correction. Across 11 within-family comparisons, thinking-mode runs yielded 20–65 additional correct answers, chiefly on specialized and fill-in tasks. Factual errors were uncommon in routine undergraduate content and concentrated in the generation of rare genus names, fine diagnostic distinctions, and alternative nomenclatural treatments. Top-performing LLMs can provide reliable support for routine teaching under instructor oversight, whereas long-tail identifications and nomenclatural decisions require verification against authoritative sources. Full article

(This article belongs to the Section Plant Diversity)

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28 pages, 1006 KB

Open AccessArticle

Numerical Valuation of Time Fractional Black–Scholes Equation in Financial Markets

by Omid Nikan, Mehdi Alaeiyan and Suhad Yousef

Mathematics 2026, 14(17), 3173; https://doi.org/10.3390/math14173173 (registering DOI) - 3 Sep 2026

Abstract

The time-fractional Black–Scholes model (TFBSM) is used to describe option price dynamics within a fractional diffusion model. It provides a mathematical model for valuing European and American call and put options on non-dividend-paying stocks. In this paper, the TFBSM is solved numerically for [...] Read more.

The time-fractional Black–Scholes model (TFBSM) is used to describe option price dynamics within a fractional diffusion model. It provides a mathematical model for valuing European and American call and put options on non-dividend-paying stocks. In this paper, the TFBSM is solved numerically for European and American option pricing using a local meshless interpolation approach. The time-fractional derivative is approximated by a finite difference scheme with accuracy of order

2 - α

for

0 < α < 1

, while the spatial derivatives are discretized using the local radial point interpolation method (LRPIM). Theoretical analysis establishes the unconditional stability and convergence of the time-semi-discrete scheme in the

L^{2}

norm. Numerical examples are presented to confirm the theoretical results and demonstrate the accuracy and performance of the proposed method for fractional option pricing problems. Full article

(This article belongs to the Special Issue Fractional Calculus: Advances and Applications)

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33 pages, 817 KB

Open AccessReview

Molecular Insights into Adsorption Mechanisms of Micro- and Nanoplastics on Effective Adsorbent Materials

by Angelo Fenti and Pasquale Iovino

Molecules 2026, 31(17), 3089; https://doi.org/10.3390/molecules31173089 (registering DOI) - 3 Sep 2026

Abstract

Existing reviews on micro- and nanoplastic (MNP) removal from water rarely link adsorbent structural features to the molecular interactions governing removal performance. This review addresses this gap by examining MNP adsorption from a mechanism-oriented perspective, mapping six canonical interaction pathways across five adsorbent [...] Read more.

Existing reviews on micro- and nanoplastic (MNP) removal from water rarely link adsorbent structural features to the molecular interactions governing removal performance. This review addresses this gap by examining MNP adsorption from a mechanism-oriented perspective, mapping six canonical interaction pathways across five adsorbent classes. Adsorption emerges as a system-dependent process governed by the interplay between polymer properties and surface chemistry rather than by the material alone. Interactions such as π–π stacking and hydrophobic affinity dominate for non-functionalized polymers on carbon-rich surfaces, while electrostatic forces and hydrogen bonding become more relevant for oxidised particles. Pore structure becomes significant when particle size and porosity match, whereas chemisorption provides a stronger and faster pathway in systems containing reactive metal sites. Across material classes, differences relate more closely to scalability and sustainability than to intrinsic adsorption capacity. Bio-based materials offer a favourable balance between performance and practical implementation, while more advanced systems provide greater control but remain limited by synthesis complexity. Laboratory capacities often overestimate real performance, and removal efficiency in complex matrices is a more reliable metric. Future progress will depend on improved standardisation, integration with modelling, and validation under realistic conditions to support the transition from laboratory studies to practical applications. Full article

(This article belongs to the Special Issue Advanced Adsorbent Materials for Environmental Applications)

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17 pages, 2774 KB

Open AccessArticle

A Data-Driven Small-Signal Stable Operating Boundary Assessment Method for Grid-Connected Converter Systems

by Qiang Ye, Xuehai Lv, Yueping Xiang, Luoyi Li, Yanqiu Hou, Hongcheng Xie, Ming Nie and Xiaojuan Zhu

Processes 2026, 14(17), 2829; https://doi.org/10.3390/pr14172829 (registering DOI) - 3 Sep 2026

Abstract

Some grid-connected converters in practice are “black-box” devices with proprietary internal structures and parameters, rendering traditional model-based stability assessment infeasible. To address this issue, this paper proposes a data-driven small-signal stable operating boundary assessment method. A continuous stability evaluation index is established based [...] Read more.

Some grid-connected converters in practice are “black-box” devices with proprietary internal structures and parameters, rendering traditional model-based stability assessment infeasible. To address this issue, this paper proposes a data-driven small-signal stable operating boundary assessment method. A continuous stability evaluation index is established based on the generalized Nyquist criterion (GNC), and then the relationship between the measurable operating variables and the quantitative stability index is established by a backpropagation (BP) neural network. This mapping allows stability evaluation to rely solely on the converter’s operating states, without requiring any internal information. By implementing the stability evaluation in predefined operating scenarios, the critical stability points that reflect the small-signal stable operating boundary of the converter can be assessed. The proposed method requires only 0.0179 s to complete a single stability assessment, with an error of less than 0.25% in predicting the stable operating boundary. Simulation verifications in MATLAB/Simulink under multiple operating conditions confirm the effectiveness and accuracy of the proposed method. Full article

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19 pages, 9580 KB

Open AccessArticle

A Skeleton-Line-Based Spiral Coverage Path Planning Method for UAV Inspection of Three-Dimensional Structures

by Qiang Zhang, Nan Zhang, Yue Liu and Yunlong Wang

Appl. Sci. 2026, 16(17), 8743; https://doi.org/10.3390/app16178743 (registering DOI) - 3 Sep 2026

Abstract

UAV-based visual inspection has become an effective approach for acquiring surface information from three-dimensional building structures. However, existing coverage path planning methods usually treat viewpoint planning and path sequencing as two separate stages, which may introduce redundant viewpoints, long connection paths, and high [...] Read more.

UAV-based visual inspection has become an effective approach for acquiring surface information from three-dimensional building structures. However, existing coverage path planning methods usually treat viewpoint planning and path sequencing as two separate stages, which may introduce redundant viewpoints, long connection paths, and high computational cost. To address this problem, this paper proposes a skeleton-guided spiral coverage path planning method for UAV inspection of 3D structures. The target building model is first converted into a watertight triangular mesh, from which a one-dimensional skeleton line is extracted to guide both viewpoint generation and path construction. Surface sampling points are generated using rotating radial rays along the skeleton line, and UAV viewpoints are obtained by offsetting these points according to a predefined viewing distance. The ordered viewpoints are then connected to construct spiral coverage paths, while visibility checking, safety-distance constraints, and collision detection are incorporated to ensure path feasibility. Parameter sensitivity analysis shows that the sampling interval has a dominant influence on coverage performance and path cost, while the angular increment mainly affects path compactness and construction efficiency. Comparative experiments on the Christ, Wind Turbine, and Big Ben models demonstrate that the proposed method achieves high coverage rates of 96.62%, 97.72%, and 99.67%, respectively, while generating shorter paths and requiring substantially less computation time than ACO−OPD and Zhao’s method. These simulation results indicate that the proposed method can generate compact coverage paths with substantially lower computation time for UAV coverage inspection of 3D structures. Full article

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10 pages, 4865 KB

Open AccessSystematic Review

The Impact of Glucagon-like Peptide-1 (GLP-1) Receptor Agonists on Body Composition in Individuals with Overweight and Obesity: A Systematic Review and Meta-Analysis

by Miłosz Woźniak, Zofia Tarcz, Gabriela Pyczek, Julia Bogacka, Andrzej Diniejko, Alina Kuryłowicz, Artur Mamcarz and Daniel Śliż

J. Clin. Med. 2026, 15(17), 6818; https://doi.org/10.3390/jcm15176818 (registering DOI) - 3 Sep 2026

Abstract

Background/Objectives: Excess adipose tissue is associated with adverse changes in muscle metabolism and body composition. GLP-1 receptor agonists (GLP-1 RA) have transformed the treatment of obesity; however, concerns remain regarding the potential impact of treatment-associated weight loss on lean mass. This study [...] Read more.

Background/Objectives: Excess adipose tissue is associated with adverse changes in muscle metabolism and body composition. GLP-1 receptor agonists (GLP-1 RA) have transformed the treatment of obesity; however, concerns remain regarding the potential impact of treatment-associated weight loss on lean mass. This study aimed to evaluate the effects of GLP-1 RA on body composition in adults with obesity without type II diabetes mellitus (T2DM), with a particular focus on changes in lean mass. Methods: A database search of Medline Ultimate, Scopus, Web of Science, PubMed, and Embase was conducted to identify studies published up to December 30, 2024. Randomized controlled trials involving adults with obesity and without T2DM who received GLP-1 RA and reported changes in body composition were included. The protocol was registered with PROSPERO (CRD42025645378). Random-effects meta-analysis was performed using inverse-variance weighting. Results: A total of 2776 articles were identified, of which three trials comprising 171 participants met the inclusion criteria. Compared with controls, participants receiving GLP-1 RA treatment experienced greater reductions in lean mass (MD = −0.78 kg, 95% CI: [−1.37 to −0.16], I² = 63.2%). GLP-1 RA treatment was also associated with a significant reduction in fat mass (MD = −3.43 kg, 95% CI: [−5.94 to −0.93], I² = 78.2%). Conclusions: The loss of lean mass was greater in patients treated with GLP-1 RA than in the control group. These results highlight the importance for clinicians to incorporate lifestyle interventions, including physical activity and nutritional support, alongside therapy with GLP-1 RA. Full article

(This article belongs to the Section Pharmacology)

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23 pages, 2530 KB

Open AccessArticle

A Deep Mixed-Image Augmentation Strategy for Few-Shot Image Classification

by Rui Wang and Xiaomin Liu

Computers 2026, 15(9), 578; https://doi.org/10.3390/computers15090578 (registering DOI) - 3 Sep 2026

Abstract

Few-shot image classification suffers from severe data scarcity and unstable generalization. Existing data augmentation strategies still have three major limitations: pixel-level fusion strategies are incompatible with the support–query structure of episodic learning, category selection for cropping-based augmentation is overly simplistic, and most approaches [...] Read more.

Few-shot image classification suffers from severe data scarcity and unstable generalization. Existing data augmentation strategies still have three major limitations: pixel-level fusion strategies are incompatible with the support–query structure of episodic learning, category selection for cropping-based augmentation is overly simplistic, and most approaches rely on a single augmentation method, limiting robustness. To address these issues, this study proposes a deep mixed data augmentation framework that jointly enhances both the support set and the query set. The method first performs global pixel-level fusion to construct fused support and query sets. A Hopfield network then turns fused-support similarities into a pairing matrix

H

, which assigns a different-class gallery partner for query-side cropping–mixing. Finally, cropping–mixing produces an enhanced query set for model training. The framework is validated using ResNet18+BDC as the backbone. Experimental results on MiniImageNet demonstrate that the proposed method is competitive in few-shot classification, attaining a five-seed test mean of

73.25

%/

81.88

% under 5-way 1-shot and 5-shot. A single complementary run on FC100 attains

66.63

%/

77.80

% and is not a same-backbone ranking against heterogeneous published protocols. Full article

33 pages, 1518 KB

Open AccessArticle

How Does Tourism Development Shape Carbon Emissions in the Long-Run? An Empirical Investigation for Western Balkan Economies

by Fjona Kurteshi and Ledjon Shahini

Economies 2026, 14(9), 378; https://doi.org/10.3390/economies14090378 (registering DOI) - 3 Sep 2026

Abstract

Tourism, despite being popularly regarded as a leisure activity, is shaped by a complex set of influencing factors and itself generates complex consequences—economic, societal, and environmental. The interaction between economic growth, tourism, and the environment is a crucial policy challenge for transitional economies [...] Read more.

Tourism, despite being popularly regarded as a leisure activity, is shaped by a complex set of influencing factors and itself generates complex consequences—economic, societal, and environmental. The interaction between economic growth, tourism, and the environment is a crucial policy challenge for transitional economies striving to achieve sustainable development. This paper analyzes the impact of income, international tourism receipts, and energy use on CO₂ emissions as a proxy for environmental deterioration for five Western Balkan economies over the period of 2007–2022. The empirical investigation is conducted following the Autoregressive Distributed Lag (ARDL)—Pooled Mean Group (PMG) approach, favoring a long-run relationship among all the variables with a moderate convergence towards the long-run equilibrium. Tourism development and energy use are significantly and positively associated with carbon emissions in the region, with energy use emerging as the most robust long-run driver of emissions. The results do not support the conventional Environmental Kuznets Curve (EKC). Instead, a U-shaped income–emissions relationship is found, with income levels in all the five economies lying above the corresponding thresholds implied by the common long-run relationship by the end of the sample period. These results call for urgent policy action towards sustainable tourism development and energy transition in the Western Balkan countries. Full article

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23 pages, 5542 KB

Open AccessArticle

Dietary Lycium barbarum Polysaccharide Supplementation Modulates Serum Metabolomic Profiles and Gut Microbiota in Felines

by Xiao Zhang, Hua Yang, Xinda Liu, Weipeng Tian, Lei Pu, Liang Hong, Renjie Qin, Zhicheng Ning and Jianbin Zhang

Animals 2026, 16(17), 2765; https://doi.org/10.3390/ani16172765 (registering DOI) - 3 Sep 2026

Abstract

Functional pet foods are increasingly being developed to support host metabolism and intestinal health. Lycium barbarum polysaccharide (LBP), a major bioactive component of goji berries, has been reported to possess antioxidant, anti-inflammatory, immunomodulatory, and gut microbiota-regulatory activities; however, its effects in domestic cats [...] Read more.

Functional pet foods are increasingly being developed to support host metabolism and intestinal health. Lycium barbarum polysaccharide (LBP), a major bioactive component of goji berries, has been reported to possess antioxidant, anti-inflammatory, immunomodulatory, and gut microbiota-regulatory activities; however, its effects in domestic cats remain unclear. This study investigated the effects of dietary LBP supplementation on serum metabolomic profiles and gut microbiota in adult cats. Twenty-four healthy adult Chinese domestic cats (1.50 ± 0.50 years old; 3.70 ± 0.80 kg) were allocated to four groups using a body-weight-balanced procedure (n = 6 per group): a basal diet group (C) and basal diet supplemented with 0.2% (L), 0.3% (M), or 0.4% (H) LBP. After a 1-week adaptation period, the formal feeding trial lasted 8 weeks. Growth-related indices, health scores, hematological and serum biochemical parameters, untargeted serum metabolomics, and fecal 16S rRNA sequencing were evaluated. LBP supplementation did not significantly affect body weight, average daily feed intake, body condition score, fecal score, coat score, hematological indices, or serum biochemical parameters. Metabolomic analysis showed that LBP mainly affected lipid metabolism, unsaturated fatty acid biosynthesis, branched-chain amino acid metabolism, lysine degradation, and protein digestion and absorption-related pathways. Microbiota analysis showed changes in alpha diversity, community structure, and the relative abundance of taxa such as Olsenella, Bifidobacterium, Catenibacterium, Peptoclostridium, Collinsella, and Clostridium. Correlation analysis suggested potential associations between key bacterial genera and serum metabolites related to fatty acid and amino acid metabolism. Overall, dietary LBP altered serum metabolic signatures and gut microbial composition without causing adverse effects in adult cats, These exploratory findings require confirmation in larger feline studies and do not establish an optimal supplementation level. Full article

(This article belongs to the Topic Research on Companion Animal Nutrition)

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20 pages, 661 KB

Open AccessArticle

Bank Efficiency and Its Determinants in a Small Island Developing Economy: Evidence from Fiji Using Data Envelopment Analysis and a Two-Limit Tobit Approach

by Shasnil Avinesh Chand, Abinesh Goundar, Temalesi Tora, Sarjeet Kaur, Ashwin Deo and Moreen Maharaj

J. Risk Financ. Manag. 2026, 19(9), 672; https://doi.org/10.3390/jrfm19090672 (registering DOI) - 3 Sep 2026

Abstract

This study examines the efficiency of Fiji’s banking sector from 2000 to 2025 using a two-stage analytical framework. First, data envelopment analysis (DEA) under the variable returns to scale (VRS) assumption is employed to estimate the efficiency scores of seven financial institutions: five [...] Read more.

This study examines the efficiency of Fiji’s banking sector from 2000 to 2025 using a two-stage analytical framework. First, data envelopment analysis (DEA) under the variable returns to scale (VRS) assumption is employed to estimate the efficiency scores of seven financial institutions: five commercial banks—four foreign-owned and one locally owned—and two locally owned non-bank financial institutions. Second, a two-limit Tobit model is used to investigate whether the estimated efficiency scores are associated with credit risk, return on assets (ROA), return on equity (ROE), bank size, foreign ownership, loan-loss provisions relative to net income, and real GDP growth. The balanced panel comprises 182 institution-year observations over 26 years. The DEA results indicate a high mean efficiency score of 0.923, although meaningful variation is observed across institutions and over time. Foreign-owned banks record a marginally higher mean efficiency score than locally owned institutions (0.924 compared with 0.921); however, foreign ownership is not statistically significant in the multivariate Tobit model. ROA has a positive and statistically significant association with efficiency, whereas ROE has a negative and statistically significant association, suggesting that asset profitability and equity profitability capture distinct balance-sheet and capital-structure channels. Bank size is positively associated with efficiency, while credit risk, loan-loss provisioning, and real GDP growth are statistically insignificant. Overall, the findings suggest that Fiji’s financial institutions operate relatively close to the estimated best-practice frontier. Nevertheless, the small number of institutions and the resulting dense DEA frontier warrant cautious interpretation. The study concludes that policies aimed at strengthening institutional efficiency should prioritise cost discipline, productive asset utilisation, appropriate capital management, and technology diffusion rather than ownership status alone. Full article

(This article belongs to the Special Issue Banking Profitability and Efficiency in Emerging Economies)

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23 pages, 4215 KB

Open AccessArticle

Phenomic Diversity and Population–Province Variation in Aromatic Coconut in Southern Thailand Revealed by On-Farm Survey

by Chandrasekhar Manikala, Thanet Khomphet, Noer Rahmi Ardiarini, Chandra Kurnia Setiawan and Pijug Summpunn

Biology 2026, 15(17), 1513; https://doi.org/10.3390/biology15171513 (registering DOI) - 3 Sep 2026

Abstract

Coconut is an important livelihood and industrial crop for coastal communities in Thailand; however, limited information is available on the phenotypic diversity of traditional aromatic coconut populations cultivated by smallholders in southern Thailand. An on-farm survey was conducted in Phang Nga, Trang, Krabi, [...] Read more.

Coconut is an important livelihood and industrial crop for coastal communities in Thailand; however, limited information is available on the phenotypic diversity of traditional aromatic coconut populations cultivated by smallholders in southern Thailand. An on-farm survey was conducted in Phang Nga, Trang, Krabi, and Nakhon Si Thammarat, evaluating 27 palms representing nine populations (three palms per population) for 28 quantitative morphological, reproductive, fruit, yield, and coconut-water quality traits. A hierarchical linear mixed model, with province treated as a fixed effect and populations nested within province, was used to characterize phenotypic variation and obtain adjusted population-level BLUPs. Substantial phenotypic variation was observed among the surveyed populations. Var7 in Krabi recorded the highest fruit weight (2039 g) and kernel thickness; Var6 in Trang had the highest number of fruits per bunch (13.3); Var2 in Phang Nga had the highest water volume (430 mL); and Var9 in Nakhon Si Thammarat had the highest number of female flowers (20). Principal component analysis showed that the first five components explained 72.6% of the total phenotypic variation, with fruit, reproductive, water, and vegetative traits contributing strongly to population differentiation. Correlation network analysis further identified coordinated associations among vegetative vigor, leaf morphology, and fruit and yield traits. The study provides a baseline phenotypic characterization of Nam Hom coconut populations under smallholder conditions and identifies population–province combinations with promising trait profiles for further evaluation. Full article

(This article belongs to the Section Plant Science)

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35 pages, 11307 KB

Open AccessArticle

Pantograph Arc Detection for Condition Monitoring of 3-kV DC Railway Infrastructure

by Palesa H. Kubayi and Bonginkosi A. Thango

Infrastructures 2026, 11(9), 312; https://doi.org/10.3390/infrastructures11090312 (registering DOI) - 3 Sep 2026

Abstract

Pantograph arcing is both a vehicle current-collection problem and a railway-infrastructure condition-monitoring problem because repeated loss of electrical contact can accelerate wear of the overhead contact wire and pantograph strip, degrade traction power quality, and increase maintenance demand. This study develops a leakage-safe [...] Read more.

Pantograph arcing is both a vehicle current-collection problem and a railway-infrastructure condition-monitoring problem because repeated loss of electrical contact can accelerate wear of the overhead contact wire and pantograph strip, degrade traction power quality, and increase maintenance demand. This study develops a leakage-safe diagnostic framework for 3-kV DC railway operation using 13 independent high-frequency recordings from the public Trenitalia E464 pantograph-arcing dataset. Because the repository does not provide synchronized optical/contact-force ground truth, the machine-learning target is consistently treated as a physics-guided candidate interval rather than an independently verified arc label. Pantograph voltage, pantograph current, filter voltage, and braking-rheostat current were sampled at 50 kSa/s and transformed into 207 event-preserving analysis windows. A total of 849 candidate features were extracted across time, frequency, time-frequency, nonlinear, and physics-informed electrical domains. The strongest leave-one-recording-out configuration was Extra Trees with frequency-domain features, with mean event-level accuracy of 0.9936, balanced accuracy of 0.9952, Macro-F1 of 0.9932, MCC of 0.9874, ROC-AUC of 0.9994, and PR-AUC of 0.9989. Ten-repeat grouped five-fold validation, with complete recordings retained as groups, produced a mean Macro-F1 of 0.9910 (SD 0.0193) across 50 grouped test folds. Five hundred recording-grouped bootstrap resamples yielded a Macro-F1 mean of 0.9893 with a 95% confidence interval of 0.9694–1.0000. A dedicated guard audit found zero candidate-interval overlap in all 138 retained normal 100 ms feature windows. Sensitivity analysis showed that 100 ms spectral features were materially more stable than 20 ms features, while 25% and 50% candidate-overlap thresholds produced nearly identical performance. The dataset does not contain long-duration independently verified arc-free operation, chainage/GPS catenary position, or synchronized contact-force measurements; consequently, the results are interpreted as proof-of-concept electrical screening of candidate current-collection disturbances rather than fleet-wide ground-truth arc detection. Full article

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16 pages, 669 KB

Open AccessArticle

Environmental Glyphosate Exposure Is Associated with Lower Serum 25-Hydroxyvitamin D Concentrations: A Cross-Sectional Analysis of NHANES 2013–2018

by Zsolt Gáll, Lénárd Farczádi and Melinda Kolcsar

Biology 2026, 15(17), 1510; https://doi.org/10.3390/biology15171510 (registering DOI) - 3 Sep 2026

Abstract

Glyphosate is an herbicide used to control plant growth and ripen specific crops. Glyphosate exposure has been associated with cancer, metabolic and neurological diseases, and reproductive issues in humans. A common element linking these disorders could be vitamin D deficiency. However, the relationship [...] Read more.

Glyphosate is an herbicide used to control plant growth and ripen specific crops. Glyphosate exposure has been associated with cancer, metabolic and neurological diseases, and reproductive issues in humans. A common element linking these disorders could be vitamin D deficiency. However, the relationship between glyphosate exposure and vitamin D status in the general population remains unclear. This analysis focused on the association between urinary glyphosate levels and serum 25-hydroxy vitamin D [25(OH)D] concentrations in a large representative sample of U.S. adults. Data from 4284 participants in the National Health and Nutrition Examination Survey (NHANES) between 2013–2018 were analyzed. Serum 25(OH)D levels were modeled using multivariable weighted linear regression, with adjustment for age, sex, race/ethnicity, body mass index, season, education, income, physical activity, smoking, and kidney function. Urinary glyphosate concentration was inversely associated with serum 25(OH)D in both the design-based univariate weighted analysis (β = −3.537, p = 0.035) and adjusted survey-weighted models for major confounding factors (β = −4.208, p = 0.009), using Taylor linearization for variance estimation to account for the complex NHANES survey design. In stratified analysis, the relationship between total vitamin D intake and serum 25(OH)D was found to be significantly modified by glyphosate exposure, with stronger dietary dependence observed in the high-exposure tertile (β = 12.88, p < 0.0066) than in the low-exposure tertile (β = 7.41, p < 0.0165). Higher urinary glyphosate concentration was associated with lower serum 25(OH)D levels in U.S. adults, suggesting it may represent an unrecognized risk factor for vitamin D deficiency. Longitudinal and experimental studies are needed to clarify causality, the underlying mechanisms, and public health implications. Full article

(This article belongs to the Special Issue Effects of Environmental Exposures on Thyroid Function, Development, Reproduction and Metabolic Health)

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20 pages, 351 KB

Open AccessArticle

Cariogenic Risk Modifies the Effect of Marginal Adaptation on Caries Adjacent to Posterior Composite Restorations: A Stratified Multivariate Analysis

by Andrei Georgescu, Sorin Andrian, Cristina-Angela Ghiorghe, Galina Pancu, Claudiu Topoliceanu, Ionuţ Tărăboanţă, Irina Nica, Răzvan Brânzan, Cristina Dascălu, Maria-Alexandra Mârţu and Mihaela Sălceanu

Clin. Pract. 2026, 16(9), 163; https://doi.org/10.3390/clinpract16090163 (registering DOI) - 3 Sep 2026

Abstract

Background/Objectives: Caries adjacent to restorations or sealants (CARS) is among the most frequent biological causes of composite restoration failure, resulting from the interplay between the patient’s cariogenic risk and restoration-related factors such as marginal adaptation. The study aimed to investigate whether cariogenic risk [...] Read more.

Background/Objectives: Caries adjacent to restorations or sealants (CARS) is among the most frequent biological causes of composite restoration failure, resulting from the interplay between the patient’s cariogenic risk and restoration-related factors such as marginal adaptation. The study aimed to investigate whether cariogenic risk modifies the effect of marginal adaptation on the occurrence of caries adjacent to posterior composite restorations (CARS), using risk-stratified univariate analysis and a clustering-adjusted approach, to identify associated clinical, socio-demographic, and local risk factors. Methods: This retrospective cross-sectional study evaluated 453 posterior direct composite resin restorations (Class I, Class II) in 88 patients at the Faculty of Dental Medicine, “Grigore T. Popa” University, Iași, Romania. CARS and marginal adaptation were assessed using FDI Criteria. Patients were classified as high or low cariogenic risk using a multifactorial institutional protocol. Univariate analysis and Generalized Estimating Equations (GEE) accounting for within-patient clustering were performed. Results: CARS prevalence was 27.9% in high cariogenic risk patients versus 3.15% in low cariogenic risk patients. Univariate analysis identified high cariogenic risk (OR = 11.904), deficient marginal adaptation (OR = 25.929–69.475), restoration age of 3–5 years (OR = 3.045), and Class II configuration (OR = 2.597) as significant risk factors. GEE analysis, adjusted for clustering of restorations within patients, confirmed high cariogenic risk (OR = 12.597) and deficient marginal adaptation (OR = 121.320) as independent correlates of CARS. A significant interaction between the two (p < 0.001) showed that marginal adaptation remained the dominant local risk factor in low cariogenic risk patients, while its association with CARS was largely attenuated in high-risk patients. Conclusions: GEE analysis confirmed high cariogenic risk and deficient marginal adaptation as independent correlates of CARS, with marginal adaptation acting as the dominant local risk factor only in low-risk patients. Full article

24 pages, 2540 KB

Open AccessReview

Hyperbaric Oxygen Therapy in Cancer: Friend, Foe, or Context-Dependent Modulator?

by Turan Demircan, Serkan Ergözen, Berna Yıldırım, Halil İbrahim Ünsal and Ayhan Bilir

Biology 2026, 15(17), 1512; https://doi.org/10.3390/biology15171512 (registering DOI) - 3 Sep 2026

Abstract

Hyperbaric oxygen therapy (HBOT) increases tissue oxygen availability through the administration of near-pure oxygen under elevated atmospheric pressure. Although HBOT is clinically established for several hypoxia-related conditions and selected radiation-induced tissue injuries, its role in oncology remains controversial. This review evaluates HBOT as [...] Read more.

Hyperbaric oxygen therapy (HBOT) increases tissue oxygen availability through the administration of near-pure oxygen under elevated atmospheric pressure. Although HBOT is clinically established for several hypoxia-related conditions and selected radiation-induced tissue injuries, its role in oncology remains controversial. This review evaluates HBOT as a context-dependent modulator of tumor and normal-tissue biology by integrating evidence on hypoxia-inducible factor signaling, redox homeostasis, tumor metabolism, vascular remodeling, immune regulation, extracellular matrix organization, cancer stemness, and treatment sensitivity. Available preclinical and clinical evidence does not support the historical assumption that HBOT universally accelerates tumor growth, recurrence, or metastasis, but current evidence is also insufficient to support HBOT as a broadly applicable standalone anticancer therapy. The strongest clinical evidence concerns late radiation-induced normal-tissue injury, particularly radiation cystitis, whereas evidence for direct antitumor activity or treatment sensitization remains predominantly preclinical and context-dependent. Selected experimental models suggest that transient reoxygenation may attenuate hypoxia-dependent signaling, alter redox and metabolic adaptation, and enhance sensitivity to radiotherapy or systemic anticancer treatment, while other models demonstrate increased proliferation or vascular responses. Future studies should incorporate standardized HBOT protocols, direct or surrogate measurements of tumor oxygenation, mechanistic biomarkers, patient stratification based on measurable tumor characteristics such as baseline hypoxia, redox phenotype, and microenvironmental features, and precise treatment scheduling. HBOT may ultimately be most relevant as a biomarker- and timing-guided pharmacodynamic reoxygenation strategy in tumors in which a transient reoxygenation window can be therapeutically exploited. Full article

(This article belongs to the Section Cancer Biology)

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29 pages, 733 KB

Open AccessSystematic Review

Mathematical Programming Models for Agricultural Water: A Systematic Review

by Elisa Belfiore and Davide Viaggi

Water 2026, 18(17), 2174; https://doi.org/10.3390/w18172174 (registering DOI) - 3 Sep 2026

Abstract

This study provides a systematic review of mathematical programming models applied to agricultural water management, with a focus on their relevance for policy design addressing water scarcity and agricultural pollution. Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology, 42 [...] Read more.

This study provides a systematic review of mathematical programming models applied to agricultural water management, with a focus on their relevance for policy design addressing water scarcity and agricultural pollution. Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology, 42 peer-reviewed studies were selected from an initial sample of 438 records and analysed using a multi-dimensional framework covering research context, economic objectives and policy orientation, and model features. The analysis reveals a pronounced geographical and thematic segmentation: water scarcity studies are concentrated in Asia, while water quality studies are predominantly European and regulatory-driven, with limited mutual influence. While deterministic optimisation approaches remain prevalent, models increasingly integrate biophysical processes through coupling with agro-hydrological components. However, policy applicability is often constrained by the limited representation of farmers’ behavioural responses, trade-offs between model complexity and usability, and difficulties in transferring results across institutional contexts. Emerging policy instruments remain limited in the sample. Progress in this field depends less on technical elaboration within existing frameworks and more on integration across disciplinary approaches. A suitable pathway would be the development of models that treat water availability and quality as jointly determined outcomes and embed institutional design within the optimisation framework. Full article

(This article belongs to the Section Water, Agriculture and Aquaculture)

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16 pages, 2382 KB

Open AccessArticle

Melatonin Mitigates the Impacts of Recurrent Water Deficit in Robusta Coffee Plants by Modulating Photosynthesis and Biomass Partitioning

by Cristhiane Tatagiba Franco Brandão, Matheus Vieira dos Santos, Vinicius de Souza Oliveira, Ana Júlia Câmara Jeveaux-Machado, Fernando Gomes Hoste, Edlaine Lacerda Araújo, Thayanne Rangel Ferreira, Janyne Soares Braga Pires, Simone Alves Fernandes, Johnatan Jair de Paula Marchiori, Carla da Silva Dias, José Altino Machado Filho, Lúcio de Oliveira Arantes and Sara Dousseau-Arantes

Water 2026, 18(17), 2175; https://doi.org/10.3390/w18172175 (registering DOI) - 3 Sep 2026

Abstract

Melatonin (N-acetyl-5-methoxytryptamine) is a regulatory molecule with potential to increase plant tolerance to water stress by modulating stomatal function, redox balance, and photosynthetic efficiency. However, its physiological effects depend on dose, species, and stress intensity, and studies on Coffea canephora under recurrent drought [...] Read more.

Melatonin (N-acetyl-5-methoxytryptamine) is a regulatory molecule with potential to increase plant tolerance to water stress by modulating stomatal function, redox balance, and photosynthetic efficiency. However, its physiological effects depend on dose, species, and stress intensity, and studies on Coffea canephora under recurrent drought are scarce. This study evaluated the effects of exogenous melatonin (0, 100, 200, 300, and 400 µM) on young plants of conilon coffee genotype 02 (Clone V12) subjected to three consecutive cycles of water deficit and rehydration. The experiment was conducted in a greenhouse using a randomized block design, with evaluations of gas exchange, water potential, and biomass allocation. Melatonin improved physiological recovery after rehydration, particularly at 100 and 300 µM during the second stress cycle, when photosynthesis reached values similar to the irrigated control. The 400 µM treatment maintained root dry mass close to the control under prolonged deficit, suggesting preferential biomass allocation to the root system. Overall, melatonin effects were more pronounced during recovery than stress, indicating a possible priming action. These results highlight the potential of melatonin as a phytoprotective agent in C. canephora, although responses depend on dose and stress cycle. Full article

(This article belongs to the Section Water, Agriculture and Aquaculture)

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22 pages, 1762 KB

Open AccessArticle

Non-Invasive Voice-Based Early Detection of Parkinson’s Disease via Spectral Feature Analysis and Machine Learning Techniques

by Yojhansen Omar Varela-Arellano, Manuel A. Soto-Murillo, Vanessa Alcalá-Ramírez, Karen E. Villagrana-Bañuelos, L. Rafael Salas-Rodriguez, Alejandra Cepeda-Argüelles, Ricardo Villagrana-Bañuelos, Jorge I. Galván-Tejada, Jose G. Arceo-Olague and Carlos E. Galván-Tejada

Bioengineering 2026, 13(9), 1026; https://doi.org/10.3390/bioengineering13091026 (registering DOI) - 3 Sep 2026

Abstract

Background: Parkinson’s disease (PD) is a chronic, slowly progressive, and irreversible neuropathological disorder characterized by the progressive degeneration of specific neurons responsible for producing neurotransmitters essential for motor control. Although PD primarily affects motor function, various non-motor symptoms commonly emerge during the prodromal [...] Read more.

Background: Parkinson’s disease (PD) is a chronic, slowly progressive, and irreversible neuropathological disorder characterized by the progressive degeneration of specific neurons responsible for producing neurotransmitters essential for motor control. Although PD primarily affects motor function, various non-motor symptoms commonly emerge during the prodromal phase. These include autonomic dysfunction, cognitive and neurobehavioral disorders, and sensory and sleep abnormalities. Notably, speech and voice alterations, particularly hypokinetic dysarthria, are frequent manifestations. This research presents a methodology to distinguish between individuals with PD and healthy controls using voice signals through speech recognition and machine learning (ML) techniques. A dataset comprising 81 voice samples (41 healthy controls and 40 PD patients) was utilized to extract two types of cepstral features: Mel-frequency cepstral coefficients (MFCCs) and subband-based cepstral coefficients (SBCs). These extracted features were used to train and evaluate three ML algorithms: Random Forest (RF), K-Nearest Neighbors (KNN), and Support Vector Machines (SVM). Results: Among the algorithms evaluated, the SVM-SBC model exhibited the highest performance, achieving an accuracy of 79%, a sensitivity of 75.5%, and an Area Under the ROC Curve (AUC-ROC) of 84%. Conclusions: This study highlights the potential of integrating cepstral features with machine learning algorithms to develop reliable, non-invasive tools for the early detection of PD. Full article

(This article belongs to the Special Issue Next-Generation Diagnostic and Therapy Systems for Neurodegenerative Diseases)

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16 pages, 1845 KB

Open AccessArticle

Enhanced Phosphorus Acquisition Contributes Substantially to Arbuscular Mycorrhizal Fungus-Mediated Drought Tolerance in Trifoliate Orange

by Liu Yang, Manqi Wu, Yali Feng, Qian Cheng, Jie He, Jia Peng, Yiwei Tang, Yuqi Huang, Shuhan Dong and Chunyan Liu

Horticulturae 2026, 12(9), 1102; https://doi.org/10.3390/horticulturae12091102 (registering DOI) - 3 Sep 2026

Abstract

Arbuscular mycorrhizal fungi (AMF) have been widely recognized for their ability to enhance plant drought tolerance. However, the contribution of improved phosphorus (P) nutrition to AMF-mediated drought tolerance in citrus and its relationship with other physiological processes remain unclear. Here, we investigated the [...] Read more.

Arbuscular mycorrhizal fungi (AMF) have been widely recognized for their ability to enhance plant drought tolerance. However, the contribution of improved phosphorus (P) nutrition to AMF-mediated drought tolerance in citrus and its relationship with other physiological processes remain unclear. Here, we investigated the physiological mechanisms underlying AMF-mediated drought tolerance in trifoliate orange (Poncirus trifoliata) by combining AMF inoculation with exogenous phosphorus supplementation under drought stress. AMF inoculation markedly alleviated drought-induced growth inhibition, increased plant biomass, enhanced root and rhizosphere phosphatase activities, promoted phosphorus accumulation, and strongly induced the expression of the mycorrhiza-specific phosphate transporter genes PtaPT4 and PtaPT5. Exogenous phosphorus supplementation largely mimicked the beneficial effects of AMF on plant growth and drought tolerance, indicating that enhanced phosphorus acquisition contributes substantially to AMF-mediated drought tolerance in trifoliate orange. However, the combined application of AMF and exogenous phosphorus conferred greater drought tolerance than phosphorus supplementation alone, suggesting that, in addition to improved phosphorus nutrition, AMF further enhances drought adaptation through the regulation of multiple physiological processes. Furthermore, AMF promoted the accumulation of growth-related phytohormones, enhanced antioxidant capacity, and reduced reactive oxygen species (ROS) accumulation, thereby further improving plant drought tolerance. These findings demonstrate that enhanced phosphorus acquisition is an important component of AMF-mediated drought tolerance in trifoliate orange, whereas coordinated regulation of phytohormone homeostasis and antioxidant defense provides additional protection against drought stress. Full article

(This article belongs to the Special Issue Plant–Microbe Interactions and Their Importance for Horticultural Crop Productivity)

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15 pages, 12446 KB

Open AccessArticle

A Robust Electrochemical Aptasensor Based on a AuNP/Chitosan Conductive Network for Saxitoxin Detection in Freshwater Samples

by Luyang Zhang, Zongyu Yan, Zaiyu Zhang, Ziran Wang and Guorui Zhao

Biosensors 2026, 16(9), 489; https://doi.org/10.3390/bios16090489 (registering DOI) - 3 Sep 2026

Abstract

Saxitoxin (STX) is a highly potent marine biotoxin, and trace contamination in aquatic environments can pose serious risks to human health. Therefore, reliable detection of low-concentration STX is crucial for water safety monitoring. Here, we developed a robust electrochemical aptasensor based on a [...] Read more.

Saxitoxin (STX) is a highly potent marine biotoxin, and trace contamination in aquatic environments can pose serious risks to human health. Therefore, reliable detection of low-concentration STX is crucial for water safety monitoring. Here, we developed a robust electrochemical aptasensor based on a gold nanoparticle/chitosan (AuNP/CS) conductive network for STX detection in freshwater samples. The chitosan matrix provides a three-dimensional scaffold for aptamer immobilization, while interconnected AuNPs create efficient electron-transfer pathways across the sensing interface. This integrated architecture improves interfacial conductivity and supports stable target-induced aptamer recognition. The aptasensor exhibits a linear response from 1 to 1000 nM and a limit of detection of 0.74 nM, with an apparent dissociation constant K_d = 70.29 ± 29.2 nM, together with high batch-to-batch consistency and long-term stability, retaining 93% of its initial response after 25 days. In spiked freshwater samples, the aptasensor achieved recoveries ranging from 99.10% to 111.33%, demonstrating the practical potential of this platform for monitoring STX contamination in aquatic environments. Full article

(This article belongs to the Special Issue Aptamer-Based Biosensing: Innovations in Molecular Recognition, Signal Transduction, and Applications)

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18 pages, 1411 KB

Open AccessArticle

Financial Literacy and Business Performance: Evidence from Rural Female Micro-Entrepreneurs in Khorezm, Uzbekistan

by Dilafruz Kuchkorova, Raufhon Salahodjaev and Dostonbek Eshpulatov

Analytics 2026, 5(3), 34; https://doi.org/10.3390/analytics5030034 (registering DOI) - 3 Sep 2026

Abstract

This study examines how distinct dimensions of financial literacy relate to the business performance of rural female micro-entrepreneurs in a transition economy. Drawing on the Resource-Based View, Human Capital Theory, and Entrepreneurial Capability Theory, financial literacy is conceptualized as four separable capabilities: financial [...] Read more.

This study examines how distinct dimensions of financial literacy relate to the business performance of rural female micro-entrepreneurs in a transition economy. Drawing on the Resource-Based View, Human Capital Theory, and Entrepreneurial Capability Theory, financial literacy is conceptualized as four separable capabilities: financial education, cash forecasting, bookkeeping practice, and financial self-efficacy. Survey data were collected from 200 women micro-entrepreneurs sampled at random in Shovot District, Khorezm region, Uzbekistan, and 173 usable responses were analysed with partial least squares structural equation modelling (PLS-SEM). After validation and refinement of the measurement model, the results show that bookkeeping practice (β = 0.407) and financial education (β = 0.294) are positively and significantly associated with business performance, as is financial self-efficacy (β = 0.155), whereas cash forecasting shows no significant unique association. The findings are robust to alternative construct and outcome specifications and to endogeneity checks, and they suggest that, where formal financial infrastructure is thin, record-keeping and foundational financial knowledge appear to be the capabilities most closely associated with micro-enterprise performance; because the measurement model was refined on these data, these associations are exploratory and await confirmation on independent samples. Full article

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7 pages, 559 KB

Open AccessBrief Report

Educational Intervention Improves Antimicrobial Stewardship Knowledge but Reveals Persistent Barriers in Rural Hospitals

by Jack H. Lambert, Rayven Todd, Thomas W. Bagwell, Damani Andre, Raybun Spelts, Fantasia Gorham, Jamie Woods, Ayomide H. Adeyemi, Shondia Evans, Rafael Ponce-Terashima and Kenneth I. Onyedibe

Antibiotics 2026, 15(9), 859; https://doi.org/10.3390/antibiotics15090859 (registering DOI) - 3 Sep 2026

Abstract

Background/Objectives: Antimicrobial resistance threatens public health globally, and critical access hospitals (CAHs) serving rural communities face structural barriers to implementing antibiotic stewardship programs (ASPs). This study evaluated whether a regional educational intervention could improve antimicrobial stewardship knowledge and implementation among rural healthcare [...] Read more.

Background/Objectives: Antimicrobial resistance threatens public health globally, and critical access hospitals (CAHs) serving rural communities face structural barriers to implementing antibiotic stewardship programs (ASPs). This study evaluated whether a regional educational intervention could improve antimicrobial stewardship knowledge and implementation among rural healthcare professionals. Methods: A quantitative, quasi-experimental repeated cross-sectional evaluation was conducted following Antibiotic Stewardship conferences in 2023 and 2024. Participants from 38 rural and critical access hospitals completed pre-conference, post-conference, 6-month follow-up, and implementation surveys. Quantitative data were analyzed using descriptive statistics and unpaired chi-square tests, with Fisher’s exact test substituted where expected cell counts were below 5, with significance set at p < 0.05. Results: Seventy healthcare professionals participated across both years. Correct identification of the use of an antibiogram to guide empiric (rather than definitive) therapy improved from 27% pre-conference to 58% post-conference (p = 0.029). Confidence in antibiogram interpretation increased from 67% to 100% post-intervention (p = 0.004, Fisher’s exact) but declined to 50% (5 of 10) at 6-month follow-up. Knowledge of the minimum isolate threshold required to construct an antibiogram improved from 23% (7 of 30) pre-conference to 64% (7 of 11) at 6-month follow-up (p = 0.026, Fisher’s exact). Despite this, prescribing intent for conditions where antibiotics are typically unnecessary showed minimal improvement: recommendations for antibiotic use in middle ear infections decreased from 50% to 36.84%, and for mpox from 20% to 15.79%. All participants reported intent to modify clinical practice; however, time constraints, technology limitations, and lack of resources were consistently cited as primary barriers for implementation across both survey years. Conclusions: A regional educational intervention improved short-term antimicrobial stewardship knowledge and confidence among rural healthcare professionals, but knowledge retention declined over time and structural barriers persisted. Education alone is insufficient; sustained reinforcement and rural-adapted ASP models incorporating protected ASP time, decision-support tools and external partnerships are needed to translate knowledge gains into consistent stewardship practice. Full article

(This article belongs to the Special Issue Current Challenges in Antimicrobial Stewardship)

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