Search Results (293)

Periodontitis is a chronic inflammatory disease driven by microbial dysbiosis and an exacerbated host immune response. This leads to progressive breakdown of periodontal tissues. Although scaling and root planing remains the standard treatment, its capacity to fully restore immune balance and host–microbiota homeostasis is limited. Probiotics have emerged as promising adjunctive strategies to modulate pathways involved in periodontal disease progression. This review aimed to evaluate current clinical evidence on the use of probiotics as adjuncts in periodontal therapy. The review followed the Scale for the Assessment of Narrative Review Articles criteria, applied exclusively as a reporting-quality framework. A literature search was conducted in MEDLINE via PubMed for manuscripts indexed through January/2026, using MeSH terms related to periodontitis and probiotics. Probiotics demonstrate potential as adjunctive agents in periodontal therapy, as evidenced by improvements in clinical parameters (probing depth, clinical attachment level, and/or bleeding on probing) reported in clinical studies. However, the findings remain heterogeneous across trials. Variability in probiotic strains, CFU concentrations, administration routes, and treatment durations highlights the need for standardized clinical protocols to improve comparability and reproducibility and better establish their clinical efficacy. Stronger, long-term evidence is required to standardize therapeutic protocols. Full article

Fast charging of electric vehicles can introduce phase-dependent harmonic distortion and voltage unbalance in low-voltage feeders, which may reduce admissible charging capacity even when voltage magnitudes remain within conventional limits. This paper proposes a phase-aware predictive scheduling framework for harmonic hosting management in feeders with a high penetration of electric vehicle charging. The proposed method formulates feeder operation as a predictive decision problem that jointly determines charging power levels, phase allocation, and the selective activation of multifunctional compensation resources under harmonic distortion, voltage unbalance, and neutral-current constraints. Unlike previous studies centered on harmonic characterization, static hosting assessment, or local converter-level mitigation, the proposed approach treats harmonic hosting as an active feeder-level network management problem. The framework is evaluated through time-series harmonic power-flow simulations using charger harmonic emission profiles and realistic feeder parameters. The numerical results indicate that coordinated phase-aware scheduling can increase admissible charging capacity, improve compliance margins for power-quality indices, and reduce mitigation efforts with respect to uncontrolled charging and non-coordinated compensation strategies. Overall, the results support the use of phase-aware scheduling as a feeder-level strategy to improve electric vehicle charging integration under harmonic and unbalanced constraints. Full article

The dynamism of adventure tourism necessitates the precise identification of areas with suitable natural, infrastructural, and service capacities for hosting activities. The aim of this study is to assess the multi-scenario spatial suitability for the sustainable development of adventure tourism camps using a Geographic Information System (GIS)-based Multi-Criteria Decision-Making (MCDM) approach. The datasets used included topographic, climatic, environmental, accessibility, natural and cultural attraction, and service infrastructure indicators. The relevant criteria were first standardized, and their weights were determined using the Analytic Hierarchy Process (AHP). Subsequently, the layers were integrated through a Weighted Linear Combination (WLC) model. Four scenarios were designed for sensitivity analysis: the first scenario with balanced weight distribution (S_bal), the second prioritizing accessibility (S_acc), the third focusing on natural attractions (S_att), and the fourth emphasizing services (S_serv). The results indicated that approximately 21% and 9% of Chaharmahal and Bakhtiari province have high and very high potential for adventure activities, respectively, which were selected as initial options for the multi-scenario analysis. In the balanced (S_bal) scenario, 31% and 13% of the area of these options fell into high and very high suitability classes, respectively. The Service-Based Scenario (S_serv) increased the share of high and very high suitability areas to 34% and 19%, while Accessibility-Based Scenario (S_acc) reduced these classes to 27% and 10%. In the Attraction-Based Scenario (S_att), the areas in the high and very high suitability classes were 30% and 12%, respectively. The findings demonstrate that altering the priority of components can significantly change the spatial pattern of suitability, and sustainable planning of adventure tourism activities should be conducted based on management objectives and regional capacities. The proposed framework is generalizable to other regions and can serve as a basis for decision-making in balanced development, optimal infrastructure allocation, and sustainable management of adventure tourism. Full article

A central goal of carbon (C) management and a critical outcome of sustainable land stewardship is reducing greenhouse gas (GHG) emissions from agriculture, forestry, and other land uses. Integrating GHG considerations into management can take many forms, but C credit markets are increasingly providing sources of private capital to offset the often high costs of stewardship. In Hawaiʻi, participation in voluntary C credit markets and the establishment of jurisdictional compliance C markets are constrained by a lack of institutional capacity, successful demonstrations, and high-quality data, making private capital for C market-based approaches in Hawaiʻi difficult to access. The State of Carbon in Hawaiʻi Hui (hui translates to partnership in ʻŌlelo Hawaiʻi, the Hawaiian language) convened landowners, researchers, federal and state government professionals, and for-profit and not-for-profit organization staff to better understand limitations to implementing C management in Hawaiʻi. This paper describes why the State of Carbon in Hawaiʻi Hui was formed, how we planned for, hosted, and assessed the success of a C-focused summit, and what outcomes resulted from this process. A Pathway Forward document, a decision support tool, and this article are outcomes. These products will serve as resources for those considering Hawaiʻi-based forest C projects, as well as contributing towards the legislated goal of reducing greenhouse gas emissions in Hawaiʻi. Our knowledge exchange process is readily replicable and can support a variety of efforts in environmental conservation and beyond. Full article

The widespread integration of rooftop solar photovoltaic systems into electricity distribution networks often leads to poor voltage regulation at user connection points, potentially breaching system voltage standards. Therefore, it is important for distribution network service providers to thoroughly assess such real and potential impacts to ensure compliant and safe operation of their power systems. The conventional approach of non-linear power flow-based voltage estimation using model-based methods is complex and time-intensive. Consequently, there is an increasing research interest towards model-free voltage estimation methods as a reliable alternative. This paper proposes and compares two distinct model-free voltage estimation approaches that can be utilised for effective hosting capacity estimation of residential solar photovoltaic systems in low voltage distribution networks. One approach utilises linear regression based on linearised power flow equations, while the other employs neural networks to capture non-linear power flow dynamics. The study developed 16 linear regression models and 648 neural network models utilising historical data collected from residential smart electricity metres in a real low voltage distribution network and compared their efficacy against conventional model-based, non-linear power flow simulations. Results indicate that the proposed model-free voltage estimation approaches can estimate voltages at user connection points in a similarly accurate but faster manner compared to the model-based approach. Observations show that the proposed linear regression-based voltage estimation approach is superior to the proposed neural network-based voltage estimation approach in terms of interpretability and practicality. Full article

Background/Objectives: Enteropathogenic Escherichia coli O157:H7 infection disrupts intestinal homeostasis, causing dysbiosis, barrier dysfunction, and inflammation. This study aimed to evaluate the protective efficacy and mechanisms of a novel probiotic, Bacteroides thetaiotaomicron type strain ATCC 29148, isolated from goat feces, against E. coli O157:H7-induced colitis. Methods: This study assessed the protective potential of the probiotic strain Bacteroides thetaiotaomicronBT6 and BT7 in vitro for GI tolerance, adhesion, and no adverse effects were observed. For the in vivo experiment, male C57BL/6J mice were divided into groups treated with Bacteroides thetaiotaomicron (BT6), PBS, E. coli O157:H7, or a combination. We employed integrated analyses including 16S rRNA gene sequencing, antioxidant status, cytokine profiling, and short-chain fatty acid (SCFA) measurement. Results: In vitro, Bacteroides thetaiotaomicron (BT6 and BT7) showed high gastrointestinal tolerance (71.89–93.22% survival). In vivo, it significantly mitigated infection-associated weight loss and disease activity (p < 0.05). Probiotic treatment enhanced barrier integrity, reduced colonic inflammation, and modulated systemic immune responses, notably increasing anti-inflammatory IL-10 while decreasing pro-inflammatory cytokines TNF-α, IL-1β, and IL-6 (p < 0.05). It also alleviated oxidative stress by reducing malondialdehyde (MDA) and elevating antioxidant enzymes (SOD, CAT, GSH) and ATP. Fecal SCFA profiling revealed increased propionic and butyric acid. 16S sequencing indicated that B. thetaiotaomicron (BT6) administration increased beneficial families (Lactobacillaceae, Muribaculaceae) and suppressed pathobionts. Conclusions: B. thetaiotaomicron (BT6) probiotic with potential for mitigating enteropathogenic infection, an effect mainly determined by its capacity to reestablish the intestinal epithelial barrier and enhance global host health, and modulating the inflammatory response. Full article

Silver nanoparticle (AgNP)-based products have been increasingly applied in aquaculture due to their antimicrobial properties and capacity to modulate host immunity. This study investigated the biological activities of synthesized silver nanowires (AgNWs), with particular emphasis on their anti-Vibrio efficacy and immunomodulatory effects, to evaluate their potential application in shrimp aquaculture. Antibacterial activity was assessed using nonlinear regression analysis to determine minimum inhibitory concentrations (MICs) against three major Vibrio pathogens, while cytotoxicity and immune responses were evaluated using white shrimp hemocytes through cell viability assays and in vitro gene expression analysis, respectively. AgNWs exhibited antibacterial effects on Vibrio parahaemolyticus, Vibrio alginolyticus, and Vibrio harveyi, with MIC values of 873.7, 58.78, and 672.1 μg/mL, respectively. Hemocyte viability remained above 90% at AgNW concentrations of up to 1000 mg/L, indicating good biocompatibility. AgNWs significantly upregulated immune-related lipopolysaccharide and β-1,3-glucan-binding protein (LGBP) and Toll gene expression at specific concentrations, indicating immunostimulation. These results suggest that AgNWs possess antibacterial activity and immunomodulatory potential with low cytotoxicity, supporting their promise as a novel functional agent for shrimp disease management. Full article

The European Union aims to cut greenhouse gas emissions by 55% by 2030 and reach climate neutrality by 2050, targets that depend on expanding renewable generation in the European energy system. While photovoltaic (PV) capacity has grown quickly in several member states, others remain far behind. This paper frames that divergence as a systems planning problem: installed MW expands through diffusion-like dynamics, but the conversion of investment into energizable capacity is filtered by grid-integration constraints and institutional throughput. The study develops a macro-level framework for systems-level assessment and decision support to guide PV capacity planning and budget allocation using official 2012–2022 data for 22 EU countries. We combine (i) unsupervised clustering of standardized national deployment trajectories, (ii) bounded logistic fits interpreted as an operational diffusion-with-saturation representation that yield comparable growth parameters and maturity years (80–90% of the estimated ceiling), and (iii) a proportional reallocation scenario for countries below 5 GW in 2022. Three clusters emerge—steady growth, early plateau, and atypical paths—and an analytically tractable maturity indicator integrates capacity, rate, and timing in a single measure. In a 10 GW reallocation scenario, average progress toward the 5 GW benchmark rises from 9.8% to 23.1%, closing about 14.8% of the aggregate shortfall. The allocation experiment reveals a clear asymmetry: systems with an existing installed base convert additional MW into benchmark progress more efficiently than very low-baseline systems, where binding constraints are more likely to sit in permitting, interconnection queues, and hosting capacity rather than in finance alone. Turning these allocations into usable capacity depends on timely interconnection and power-electronics integration and on grid-enablement constraints such as interconnection readiness, inverter compliance, and local hosting capacity in high-penetration areas. The contribution is a transparent, updateable decision-support pipeline that links observed trajectory regimes to a maturity “clock” and an auditable allocation baseline, making the trade-off between closing capacity gaps and respecting feasibility filters explicit in an EU system with heterogeneous national subsystems. The proposed approach links macro-level maturity clusters to operational feasibility signals in the grid integration layer, showing that modeling-based allocation can improve system progress but cannot substitute grid-enablement measures, highlighting the importance of regional coordination in the EU energy system under heterogeneous national trajectories. Full article

Schistosomiasis japonicum transmission in Indonesia has declined substantially over recent decades, placing it in the last miles of elimination in the Western Pacific Region. As programmes transition from control to interruption of transmission, surveillance systems must be capable of detecting residual transmission. This study synthesised routine epidemiological data from 2015 to 2025 to assess Indonesia’s readiness for elimination and to identify key surveillance gaps in near-elimination settings. Descriptive quantitative analysis was conducted using national surveillance data from two endemic districts in Central Sulawesi, complemented by programme reports on mass drug administration, human diagnosis, animal reservoir surveillance, and snail surveys. Results showed that while prevalence in humans has remained low and responsive to mass drug administration, transmission persists through infected animal reservoirs and intermediate snail hosts. Surveillance performance is constrained by limited diagnostic capacity, inconsistent snail survey coverage, fragmented paper-based reporting systems, and weak integration across human, animal, and environmental sectors. These findings indicated that low prevalence in humans alone is insufficient to demonstrate interruption of transmission, particularly in zoonotic schistosomiasis. In conclusion, Indonesia’s experience highlights the need to strengthen near-elimination surveillance through sensitive diagnostics, integrated One Health approaches, and digitally enabled data systems to sustain elimination and support future verification of schistosomiasis transmission interruption. Full article

Honey bees are exposed to a wide range of environmental and ecological stressors that threaten individual health and colony sustainability. Growing evidence suggests that many of these stressors converge on a common target: the gut microbiome and its metabolic functions. The honey bee microbiome–metabolome axis represents a central regulatory system linking microbial symbionts with host nutrition, detoxification, immune competence, neural signaling, and social behavior. This review synthesizes current knowledge on how major stressors—including pesticides, antibiotics, pathogens, nutritional imbalance, thermal stress, habitat change, and environmental contaminants—reprogram honey bee chemistry by disrupting microbial community structure and, importantly, microbial and host metabolic pathways. We highlight recurring patterns consistent with functional dysbiosis, characterized by impaired energy metabolism, reduced production of short-chain fatty acids, altered amino acid and lipid metabolism, compromised antioxidant and detoxification capacity, and weakened immune regulation. However, much of the current evidence is correlative and derived from short-term or laboratory-focused studies; longitudinal and multi-site field validation of causal links remains limited. Importantly, emerging multi-omics studies suggest that profound metabolic disturbances can occur even when taxonomic changes in the microbiome are modest, emphasizing the need to move beyond descriptive community profiling toward functional and mechanistic assessments. We further discuss how stress-induced metabolic reprogramming at the individual level scales up to influence behavior, division of labor, and colony-level resilience. Finally, we propose a conceptual model illustrating how diverse stressors converge to disrupt the microbiome–metabolome axis, potentially leading to functional dysbiosis and host impairment. Full article

Background/Aim: Dental caries is a multifactorial disease influenced by dietary habits, lifestyle factors, and host biochemical processes. Oxidative stress and advanced glycation end products (AGEs) have been implicated in oral and systemic pathophysiology, but their combined association with caries experience remains unclear. This study aimed to evaluate the relationships between caries indices, diet, smoking, oxidative stress markers, and AGEs in adults. Materials and Methods: A cross-sectional study was conducted on adults enrolled in the SALIVAGES project (2018–2020). Dental status was assessed using the DMFT index. Dietary habits and smoking status were recorded using a validated questionnaire. Oxidative stress parameters (TAC, TOS, OSI, NO, MDA, total thiols) and AGEs (FruLys, MG-H1, CML, CEL, Pyr, Arg, Lys) were quantified in saliva and plasma. Associations were analyzed using correlation tests and multivariable regression models (α = 0.05). Results: The mean DMFT was 21.89 ± 7.13, with missing teeth predominating. Caries experience was significantly associated with oxidative stress, AGEs, diet, and lifestyle. Higher decay scores were associated with increased NO and total thiols and reduced antioxidant capacity. Several salivary AGE-related biomarkers (FruLys, MG-H1, CML, and CEL) were negatively associated with the decay index. Sugary beverages, refined carbohydrates, pastries, and donuts were strongly positively associated with the decay index, whereas wholemeal bread showed an inverse association with caries indices. Smoking was independently associated with higher decay and DMFT values, corresponding to an approximately three-unit higher DMFT score. Conclusions: Caries experience in adults is associated with dietary, lifestyle, and biochemical factors. Sugar intake and smoking showed the strongest associations with caries indices, while oxidative stress parameters and selected salivary AGE-related biomarkers showed weaker but significant inverse associations with decay. These findings support preventive strategies targeting diet quality, smoking cessation, and redox balance to reduce oral disease burden. Full article

Accumulating studies have identified the pivotal role of long non-coding RNAs (lncRNAs) in participating in host–virus interactions during virus infections. However, the regulatory roles of lncRNAs in influenza A virus (IAV) infection are still not fully elucidated. In this study, using high-throughput sequencing, we comprehensively compared the expression profiles of lncRNAs and mRNAs in mouse lungs infected either with the nonpathogenic parental (SDL124) H7N9 virus or its moderately pathogenic mouse-adapted (S8) variant. A total of 7636 significantly differentially expressed (SDE) lncRNAs were obtained in the S8-infected group compared to the mock group. As for the SDL124 group, 1042 SDE lncRNAs were identified. Subsequently, the mRNAs co-expressed with SDE lncRNAs were subjected to functional annotation and pathway enrichment analysis. The results indicated that the target mRNAs regulated by the S8 virus were mainly enriched in various immunological processes and exhibited a strong correlation with inflammatory-related signaling pathways. Moreover, 12 lncRNAs and 10 mRNAs co-expressed with SDE lncRNAs were selected and successfully verified by RT-qPCR. Among these lncRNAs, NONMMUG032982.2 and NONMMUG032328.2 exhibited strong antiviral activity against IAV. Additionally, these two lncRNAs were chosen for further in-depth bioinformatics analysis, including transcription factor prediction, coding capacity assessment, genomic location, construction of secondary structure, and prediction of potential interacting proteins. Taken together, these findings provide a cluster of lncRNAs probably associated with the virulence of IAV in mice and shed light on the anti-IAV effects of two functional lncRNAs, establishing a molecular foundation for further exploring the regulatory mechanisms of lncRNAs in IAV infection. Full article

Enhancing the carrying capacity of the ecological environment serves as a pivotal pathway to achieving sustainable development and also constitutes a concrete response to the UN SDGs. Based on a provincial panel dataset covering 30 Chinese provinces spanning 2011–2023, the present work examines how digital finance shapes EECC and explores the corresponding transmission mechanisms. Findings from the empirical analysis confirm that digital finance exerts a significant positive effect in boosting ecological environmental carrying capacity. Heterogeneity tests further show that this catalytic influence is most salient in eastern China, while it lacks statistical significance or even turns negative in the central and western areas. Meanwhile, the catalytic function of digital finance becomes more distinct in highly urbanized areas. Mechanism analysis verifies that digital finance assumes a partial mediating function by cutting down energy consumption intensity and boosting human capital accumulation. Further analysis reveals that as digital finance matures, the above impact exhibits increasing marginal returns. Our spatial spillover assessment further indicates that digital finance contributes to stronger EECC within host provinces, while also facilitating coordinated improvements in this key indicator across neighboring jurisdictions. Accordingly, we propose that economies speed up the building of digital-related infrastructure, expand the outreach of digital finance, and properly steer the orderly movement of population, thus facilitating the eco-friendly sustainable advancement of the natural environment. Full article

The Mabi Block is located in the southern Qinshui Basin, representing an underexplored region with high-rank coal seams that host significant Coalbed Methane (CBM) potential. Despite extensive CBM development in the nearby Anze and Zheng Zhuang blocks, the geological and geophysical controls on Coalbed Methane enrichment in Mabi remain insufficiently constrained. This study integrates the core data (63 samples) of isothermal adsorption tests, well-logging data from (13 wells), and 3D seismic attributes to systematically evaluate the key controlling factors, such as burial depth, roof and floor lithology, and sealing capacity, in the horizons of the No.3# and No.15# coal seams. Lithology is characterized using natural gamma ray (GR), acoustic (AC), deep resistivity (RD), compensated neutron log (CNL), and seismic wave impedance inversion. Coal quality parameters, ash content, and the Langmuir volume (V_L) are correlated with gas content, and structural controls are mapped using curvature, fault interpretation, and burial depth analysis. The results show that thick mudstone and limestone roofs, moderate burial depth (1100–1350 m), synclinal structural lows, and thicker coal seams (6–9 m) collectively enhance methane preservation. The ash content (%) exhibits a moderate negative correlation with the Langmuir volume (R² = 0.4) and gas content. Structural curvature (syncline) and fault intensity strongly govern lateral sealing integrity, where anticline zones and faulted regions display notable degassing. This integrated assessment contributes to a refined CBM optimization model for the Mabi Block and guides targeted future drilling, reservoir evaluation, and production optimization. Full article

The principal difficulty in studying the physico-mechanical and filtration-capacity properties of coals and host rocks under laboratory conditions using core samples lies in reproducing natural thermodynamic conditions characteristic of in situ depths. To address this issue, specialized equipment and methodologies for transferring measurement results are employed, including the Hoek–Brown failure criterion, the structural weakening coefficient, and the development of thermodynamic models. The reliability and accuracy of such measurements are determined by the degree of conformity between the adopted laboratory conditions and natural in situ conditions, the number of samples representing different lithological varieties, and the adequacy of sampling procedures ensuring representativeness. Particular challenges arise when sampling cleated and fractured coals formed under natural stress–strain conditions and contain methane, which significantly influences their physical properties. These difficulties are especially pronounced in prepared-for-mining high-gas-content coal seams of the Karaganda Basin at depths of approximately 700 m, where obtaining representative samples is technically complicated. Reliable values of the physico-mechanical properties of the coal–rock mass are essential for geomechanical calculations aimed at ensuring safe mining of high-gas-content seams through risk assessment of geodynamic phenomena, particularly in zones of geological disturbances, floor heave, and roof collapse. In this context, the use of a comprehensive suite of geophysical logging data from exploration boreholes makes it possible to obtain continuous, high-precision information on physico-mechanical and filtration-capacity properties. These methods are particularly important for characterizing the coal–rock mass in operating mines, since the natural state of host rocks and prepared coal seams is altered due to stress relief caused by mine workings, preliminary degasification measures, and hydraulic fracturing. The problem addressed is the need for reliable assessment of rock and coal seam parameters under natural thermodynamic stress–strain conditions, taking into account lithological composition, structural heterogeneity, fracture development, stratigraphic differentiation, and gas saturation. The aim of this study is to ensure efficient and safe coal extraction based on geomechanical calculations utilizing physico-mechanical and filtration-capacity properties of host rocks and gas-bearing coal seams, whether prepared for mining or not yet extracted. The research methods are based on an integrated complex of geophysical logging of exploration wells, specialized software tools, and statistical processing techniques to identify patterns in physico-mechanical and filtration-capacity properties of host rocks and coal seams under natural stress–strain conditions, as well as to determine the nature of changes in these properties within coal seams and roof and floor rocks in prepared mining areas. The physico-mechanical and filtration-capacity properties of host rocks and coals from the Lenin and Kazakhstanskaya mines were determined. Regularities governing the application of these parameters to coals of different formations and depths were established; fracture orientations and characteristics were evaluated; and relationships between changes in coal seam parameters and gas content were identified. A comprehensive methodological framework for studying the physical and capacity properties of the coal–rock mass under natural thermodynamic conditions has been developed. Its primary application is the investigation of coal seams prepared for mining to support geomechanical calculations for efficient and safe coal extraction, the implementation of degasification measures for high-gas-content seams, and the assessment of gas-dynamic risks based on the character of variations in physical parameters. Full article