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29 pages, 1629 KB  
Article
Solving Fully Intuitionistic Fuzzy Multi-Level Multi-Objective Fractional Optimization Problems via Two Different Approaches
by Mohamed A. El Sayed, Haitham Elwahsh, Julian Hoxha, Tarek Khalifa, Farahat A. Farahat, Mohamed A. Elsisy and Fawzy A. Bukhari
Fractal Fract. 2025, 9(10), 675; https://doi.org/10.3390/fractalfract9100675 (registering DOI) - 20 Oct 2025
Abstract
Uncertainty is the biggest issue when modeling real-world multi-level fractional optimization problems. In this paper, a fully intuitionistic fuzzy multi-level multi-objective fractional programming problem (FIF-MLMOFPP) is tackled via two different approaches. Because of the ambiguity introduced in the model, all the parameters and [...] Read more.
Uncertainty is the biggest issue when modeling real-world multi-level fractional optimization problems. In this paper, a fully intuitionistic fuzzy multi-level multi-objective fractional programming problem (FIF-MLMOFPP) is tackled via two different approaches. Because of the ambiguity introduced in the model, all the parameters and decision variables in each objective function and feasible domain are intuitionistic fuzzy numbers (IFNs). Firstly, FIF-MLMOFPP is converted into a non-fractional fully intuitionistic fuzzy multi-level multi-objective programming problem (FIF-MLMOPP) utilizing a series of transformations. The accuracy functions and ordering relations of IFNs are employed to transform the non-fractional FIF-MLMOPP into a deterministic variant. An interactive approach is first applied to solve the problem by transforming it into discrete multi-objective optimization problems (MOOPs). Each separate MOOP addresses the ϵ-constraint methodology and the goal of satisfactoriness. Neutrosophic fuzzy goal programming (NFGP) is the second approach applied to solve the FIF-MLMOFPP, as the marginal evaluations of predetermined neutrosophic fuzzy objectives for all functions at each level are attained through various membership functions, including degrees of truth, indeterminacy, and falsehood, within neutrosophic uncertainty. The NFGP algorithm is presented to achieve optimal levels for each marginal evaluation objective by minimizing their deviation variables, thus yielding a suitable solution. To confirm and approve the two suggested approaches, a numerical example and a comparison between them are presented. Finally, recommendations for additional research are given. Full article
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16 pages, 2954 KB  
Article
SARS-CoV-2 Infection of Lung Epithelia Leads to an Increase in the Cleavage and Translocation of RNase-III Drosha; Loss of Drosha Is Associated with a Decrease in Viral Replication
by Michael T. Winters, Emily S. Westemeier-Rice, Travis W. Rawson, Kiran J. Patel, Gabriel M. Sankey, Maya Dixon-Gross, Olivia R. McHugh, Nasrin Hashemipour, McKenna L. Carroll, Isabella R. Wilkerson and Ivan Martinez
Genes 2025, 16(10), 1239; https://doi.org/10.3390/genes16101239 (registering DOI) - 20 Oct 2025
Abstract
Background/Objectives: Since its emergence, COVID-19—caused by the novel coronavirus SARS-CoV-2—has affected millions globally and led to over 1.2 million deaths in the United States alone. This global impact, coupled with the emergence of five new human coronaviruses over the past two decades, underscores [...] Read more.
Background/Objectives: Since its emergence, COVID-19—caused by the novel coronavirus SARS-CoV-2—has affected millions globally and led to over 1.2 million deaths in the United States alone. This global impact, coupled with the emergence of five new human coronaviruses over the past two decades, underscores the urgency of understanding its pathogenic mechanisms at the molecular level—not only for managing the current pandemic but also preparing for future outbreaks. Small non-coding RNAs (sncRNAs) critically regulate host and viral gene expression, including antiviral responses. Among the molecular regulators implicated in antiviral defense, the microRNA-processing enzyme Drosha has emerged as a particularly intriguing factor. In addition to its canonical role, Drosha also exerts a non-canonical, interferon-independent antiviral function against several RNA viruses. Methods: To investigate this, we employed q/RT-PCR, Western blot, and immunocytochemistry/immunofluorescence in an immortalized normal human lung/bronchial epithelial cell line (NuLi-1), as well as a human colorectal carcinoma Drosha CRISPR knockout cell line. Results: In this study, we observed a striking shift in Drosha isoform expression following infection with multiple SARS-CoV-2 variants. This shift was absent following treatment with the viral mimetic poly (I:C) or infection with other RNA viruses, including the non-severe coronaviruses HCoV-OC43 and HCoV-229E. We also identified a distinct alteration in Drosha’s cellular localization post SARS-CoV-2 infection. Moreover, Drosha ablation led to reduced expression of SARS-CoV-2 genomic and sub-genomic targets. Conclusions: Together, these observations not only elucidate a novel aspect of Drosha’s antiviral role but also advance our understanding of SARS-CoV-2 host–pathogen interactions, highlighting potential therapeutic avenues for future human coronavirus infections. Full article
(This article belongs to the Section RNA)
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16 pages, 1815 KB  
Article
Formulation and Systematic Optimisation of Polymeric Blend Nanoparticles via Box–Behnken Design
by Basant Salah Mahmoud and Christopher McConville
Pharmaceutics 2025, 17(10), 1351; https://doi.org/10.3390/pharmaceutics17101351 - 20 Oct 2025
Abstract
Background/Objectives: Despite the advantages of polycaprolactone (PCL) for drug delivery, it still lacks effective approaches to enhance its encapsulation of drugs. Blending PCL with less hydrophobic polymers can tailor physicochemical properties to overcome these limitations. This study, for the first time, integrates two [...] Read more.
Background/Objectives: Despite the advantages of polycaprolactone (PCL) for drug delivery, it still lacks effective approaches to enhance its encapsulation of drugs. Blending PCL with less hydrophobic polymers can tailor physicochemical properties to overcome these limitations. This study, for the first time, integrates two beneficial approaches—polymer blending and Box–Behnken design (BBD) optimisation—to develop PCL-based blend nanoparticles (NPs) with enhanced encapsulation efficiency (EE), controlled particle size, and improved stability through surface charge modulation. Methods: Drug-loaded blend NPs were developed using a double emulsion method, with different polymer ratios. A BBD model was employed to investigate the influential factors that control the size, charge, and EE. Results: Blending PCL with a less hydrophobic polymer significantly improved EE, achieving 60.96% under optimal conditions. The BBD model successfully predicted conditions for obtaining NPs with optimum size, negative charge, and enhanced drug encapsulation. The drug amount was identified as the most influential factor for EE, while polymer amounts significantly impacted size and charge. Conclusions: Careful control of polymer ratios, drug amount, and surfactant levels was shown to significantly influence particle size, surface charge, and EE, with the balanced 50:50 PCL:PLGA blend achieving optimal physicochemical performance. Using the BBD, the study identified the predicted optimal formulation consisting of 162 mg polymer blend, 8.37 mg drug, and 8% surfactant, which is expected to yield NPs with a size of 283.06 nm, zeta potential of −31.54 mV, and EE of 70%. The application of BBD allowed systematic evaluation of the factors and their interactions, providing robust predictive models. Full article
(This article belongs to the Section Nanomedicine and Nanotechnology)
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25 pages, 2621 KB  
Article
Analysis of a Driving Simulator’s Steering System for the Evaluation of Autonomous Vehicle Driving
by Juan F. Dols, Samuel Boix, Jaime Molina, Sara Moll, Francisco J. Camacho and Griselda López
Sensors 2025, 25(20), 6471; https://doi.org/10.3390/s25206471 (registering DOI) - 20 Oct 2025
Abstract
The integration of autonomous vehicles (AVs) into road transport requires robust experimental tools to analyze the human–machine interaction, particularly under conditions of system disengagement. This study presents the primary controls calibration and virtual scenario validation of the EVACH autonomous driving simulator, designed to [...] Read more.
The integration of autonomous vehicles (AVs) into road transport requires robust experimental tools to analyze the human–machine interaction, particularly under conditions of system disengagement. This study presents the primary controls calibration and virtual scenario validation of the EVACH autonomous driving simulator, designed to reproduce the SAE Level 2 and Level 3 driving modes in rural road scenarios. The simulator was customized through hardware and software developments including a dedicated data acquisition system to ensure the accurate detection of braking, steering, and other critical control inputs. Calibration tests demonstrated high fidelity, with minor errors in brake and steering control measurements, consistent with values observed in production vehicles. To validate the virtual driving rural environment, comparative experiments were conducted between naturalistic road tests and simulator-based autonomous driving, where five volunteers participated in the preliminary pilot test. Results showed that average speeds in the simulation closely matched those recorded on real roads, with differences of less than 1 km/h with minimum standard deviation and confidence values. These findings confirm that the EVACH simulator provides a stable and faithful reproduction of autonomous driving conditions. The experimental platform offers valuable support for current and future research on the safe deployment of automated vehicles. Full article
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23 pages, 2800 KB  
Article
Timing, Tools, and Thinking: H5P-Driven Engagement in Flipped Veterinary Education
by Nieves Martín-Alguacil, Rubén Mota-Blanco, Luis Avedillo, Mercedes Marañón-Almendros and Miguel Gallego-Agundez
Vet. Sci. 2025, 12(10), 1013; https://doi.org/10.3390/vetsci12101013 - 20 Oct 2025
Abstract
Traditional lectures in veterinary anatomy often limit student engagement and higher-order thinking. The flipped classroom (FC) model shifts foundational content to independent study using interactive tools such as H5P® and Wooclap®, reserving classroom time for collaborative problem-solving. Objective: To evaluate [...] Read more.
Traditional lectures in veterinary anatomy often limit student engagement and higher-order thinking. The flipped classroom (FC) model shifts foundational content to independent study using interactive tools such as H5P® and Wooclap®, reserving classroom time for collaborative problem-solving. Objective: To evaluate the impact of the FC model on student engagement, preparation habits, and cognitive performance in veterinary anatomy, focusing on the respiratory and cardiovascular systems. Methodology: The intervention was implemented over two academic years (2023/24 and 2024/25) and included continuous assessment, cognitive-level evaluations based on Marzano’s taxonomy, platform analytics, and anonymous student surveys. Results: Platform data showed high engagement, with completion rates exceeding 90%. Students who prepared 2–3 days in advance performed better on application and integration tasks. Survey responses indicated a shift from passive video viewing to active learning strategies, such as structured note-taking and strategic time management. By 2024/25, 85% of students dedicated 30+ min to preparation, compared to 48% the previous year. Conclusion: The FC model fostered autonomy, spatial reasoning, and clinical contextualization. Aligned with constructivist principles, it supported Intended Learning Outcomes through adaptive scaffolding. Despite institutional challenges, the model proved scalable and pedagogically coherent, warranting further longitudinal research and broader curricular integration. Full article
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33 pages, 8048 KB  
Article
Using Markov Chains and Entropy to Explain Value at Risk in European Electricity Markets
by Oscar Walduin Orozco-Cerón, Orlando Joaqui-Barandica and Diego F. Manotas-Duque
J. Risk Financial Manag. 2025, 18(10), 591; https://doi.org/10.3390/jrfm18100591 (registering DOI) - 20 Oct 2025
Abstract
The increasing complexity of energy systems amid the global push for decarbonization raises important questions about how transitions in the energy matrix affect financial risk in electricity markets. This study investigates the relationship between structural changes in national energy matrices and the systemic [...] Read more.
The increasing complexity of energy systems amid the global push for decarbonization raises important questions about how transitions in the energy matrix affect financial risk in electricity markets. This study investigates the relationship between structural changes in national energy matrices and the systemic risk associated with electricity prices in Europe from 2015 to 2022. Using daily electricity price data, we calculate log returns and estimate the Value at Risk (VaR) at the 1% level as a measure of extreme financial loss. We incorporate energy market variables, including the volatility of Brent oil and coal prices, and an entropy-based indicator derived from the Shannon index, which captures the degree of technological dispersion in the energy mix over time. A fixed-effects panel regression model is applied across 21 European countries to identify the drivers of energy-related financial risk. Results show that higher volatility in Brent and coal prices significantly increases the VaR, and that greater entropy reflecting a more complex and dynamic energy transition also correlates with higher systemic risk. These findings suggest that while energy diversification is a goal of sustainability, it may entail short-term instability. The study contributes to the understanding of how structural transformations in energy systems interact with financial vulnerabilities in liberalized electricity markets. Full article
(This article belongs to the Section Economics and Finance)
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29 pages, 7216 KB  
Article
Thymoquinone Protective Effect Against Mercury-Induced Reproductive Derangement in Rats: In Vivo and In Silico Investigation
by Solomon Owumi, Moses Otunla, Pelumi Akindipe, Uche Arunsi, Jesutosin O. Babalola, Chioma E. Irozuru, Ahmad Altayyar, Bayode Oluwawibe, Olatunde Owoeye and Adegboyega K. Oyelere
Toxics 2025, 13(10), 896; https://doi.org/10.3390/toxics13100896 (registering DOI) - 19 Oct 2025
Abstract
Mercury exposure has been linked to male infertility. Given that mercury chloride (HgCl2) may promote an oxido-inflammatory milieu associated with pathophysiological derangements, it is hypothesised that Thymoquinone (TQ), an antioxidant and anti-inflammatory agent, may mitigate the gradual harmful effects of mercury [...] Read more.
Mercury exposure has been linked to male infertility. Given that mercury chloride (HgCl2) may promote an oxido-inflammatory milieu associated with pathophysiological derangements, it is hypothesised that Thymoquinone (TQ), an antioxidant and anti-inflammatory agent, may mitigate the gradual harmful effects of mercury exposure on rat testes, epididymis, and hypothalamus, as these organs are vital to reproductive function. To test this hypothesis, 40 rats (strain: Wistar; sex: male) were randomly assigned to five cohorts of eight rats each. After a 7-day acclimation, treatments were dispensed for 28 consecutive days accordingly: Cohort I: distilled water only, as control; Cohort II: HgCl2 only (20 µg/mL); Cohort III: TQ only (2.5 mg/kg); Cohort IV: HgCl2 + TQ (20 µg/mL + 2.5 mg/kg); and Cohort V: HgCl2 + TQ (20 µg/mL + 5 mg/kg). Co-treatment with TQ preserved the body and organ weight of the HgCl2 exposed animals. However, TQ did not reduce HgCl2-induced dysfunction in sperm function and morphology. The serum follicle-stimulating hormone (FSH), luteinising hormone (LH), and testosterone were increased significantly (p < 0.05) by TQ co-treatment, while decreasing the prolactin level. TQ administration also increased (p < 0.05) testicular enzymes, including alkaline phosphatase (ALP), lactate dehydrogenase (LDH), acid phosphatase (ACP), and glucose-6-phosphate dehydrogenase (G6PD) activities, which HgCl2 decreased. TQ administration increased (p < 0.05) HgCl2-induced decreases in catalase (CAT), superoxide dismutase (SOD), glutathione peroxidase (GPx), glutathione (GSH), glutathione-s-transferase (GST), and total sulfhydryl group (TSH) levels in the testes, epididymis, and hypothalamus of experimental rats. Further, TQ reduced HgCl2-mediated increases in RONS-reactive oxygen and nitrogen species; LPO–lipid peroxidation; PC–protein carbonyl formation; and XO–xanthine oxidase activity. Furthermore, levels of inflammatory biomarkers, including tumour necrosis factor alpha (TNF-α), nitric oxide (NO), interleukin-1 beta (IL-1β), and myeloperoxidase (MPO), were decreased (p < 0.05) in the co-treated groups, with a higher dose of TQ (5.0 mg/kg) showing a more pronounced protective effect. Additionally, TQ co-administration increased Bax and decreased Bcl-2 and p53 protein levels (p < 0.05), thereby protecting the rats’ testes, epididymis, and hypothalamus from HgCl2-induced apoptosis. Molecular docking simulation analysis revealed TQ interaction dynamics with PPAR-α and PPAR-δ to suppress NF-kB-mediated pro-inflammatory sequela as well as activate Nrf-2-mediated antioxidant defence system. These predicted biological effects of TQ resonate with the findings from the in vivo studies. Therefore, supplementation with TQ may help reduce chemical-induced toxicities, including HgCl2‘s reproductive toxicity. Full article
(This article belongs to the Section Novel Methods in Toxicology Research)
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21 pages, 1588 KB  
Review
Ecotoxicological Impacts of Heavy Metals on Medicinal Plant Quality and Rhizosphere Microbial Communities
by Hexigeduleng Bao, Yu Wang, Hainan Bao, Feijuan Wang, Qiong Jiang, Xiaoqi He, Hua Li, Yanfei Ding and Cheng Zhu
Plants 2025, 14(20), 3214; https://doi.org/10.3390/plants14203214 (registering DOI) - 19 Oct 2025
Abstract
With the rapid expansion of industrial activities, the accumulation of heavy metals in the environment has become a serious threat to ecological security and public health. Rhizosphere microorganisms play a crucial role in supporting the growth and quality of medicinal plants by facilitating [...] Read more.
With the rapid expansion of industrial activities, the accumulation of heavy metals in the environment has become a serious threat to ecological security and public health. Rhizosphere microorganisms play a crucial role in supporting the growth and quality of medicinal plants by facilitating nutrient uptake and regulating hormonal balance. However, medicinal plants can absorb heavy metals from contaminated soils during growth, resulting in toxic metal accumulation in plant tissues and reduced efficacy of active compounds. At the same time, excessive heavy metal levels suppress rhizosphere microbial growth and activity, disrupt community structure and function, and weaken their beneficial interactions with plants. These processes collectively lead to soil fertility decline, hindered plant development, and compromised safety and quality of medicinal materials. This review systematically summarizes the mechanisms by which heavy metals affect medicinal plants and their rhizosphere microbiota, and highlights that future research should focus on elucidating these interactions, developing advanced remediation technologies, and establishing comprehensive monitoring systems for the quality and safety of medicinal plants, thereby providing a scientific basis for their safe utilization and quality improvement. Full article
(This article belongs to the Special Issue Soil Heavy Metal Pollution and Agricultural Product Quality)
24 pages, 4033 KB  
Article
Integrating PC Splitting Design and Construction Organization Through Multi-Agent Simulation for Prefabricated Buildings
by Yi Shen, Jing Wang and Guan-Hang Jin
Buildings 2025, 15(20), 3773; https://doi.org/10.3390/buildings15203773 (registering DOI) - 19 Oct 2025
Abstract
Prefabricated building projects represent industrialized and intelligent construction through factory production, standardized design, and mechanized assembly. This study presents a multi-agent simulation approach to model the prefabricated construction process, allowing for the concurrent optimization of the prefabricated component (PC) splitting design and the [...] Read more.
Prefabricated building projects represent industrialized and intelligent construction through factory production, standardized design, and mechanized assembly. This study presents a multi-agent simulation approach to model the prefabricated construction process, allowing for the concurrent optimization of the prefabricated component (PC) splitting design and the construction organization plan through iterative simulation. (1) Employing a questionnaire survey, it identifies critical factors affecting schedule and cost from a design–construction coordination perspective. (2) Based on these findings, an agent-based model was developed incorporating PC installation, crane operations, and storage yard spatial constraints, along with interaction rules governing these agents. (3) Data interoperability was achieved among Revit, NetLogo3D and Navisworks. This integrated environment offers project managers digital management of design and construction plans, simulation support, and visualization tools. Simulation results confirm that a hybrid resource allocation strategy utilizing both tower cranes and mobile cranes enhances resource leveling, accelerates schedule performance, and improves cost efficiency. Full article
(This article belongs to the Special Issue Advanced Research on Intelligent Building Construction and Management)
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13 pages, 1437 KB  
Review
HPV Oncoproteins and Mitochondrial Reprogramming: The Central Role of ROMO1 in Oxidative Stress and Metabolic Shifts
by Eva Tsoneva and Angel Yordanov
Cells 2025, 14(20), 1629; https://doi.org/10.3390/cells14201629 - 19 Oct 2025
Abstract
High-risk human papillomaviruses (HPVs), particularly types 16 and 18, drive carcinogenesis by rewiring host metabolism and mitochondrial function. The oncoproteins E5, E6, and E7 collectively induce mitochondrial fragmentation, increase reactive oxygen species (ROS), and promote a metabolic shift from oxidative phosphorylation (OXPHOS) to [...] Read more.
High-risk human papillomaviruses (HPVs), particularly types 16 and 18, drive carcinogenesis by rewiring host metabolism and mitochondrial function. The oncoproteins E5, E6, and E7 collectively induce mitochondrial fragmentation, increase reactive oxygen species (ROS), and promote a metabolic shift from oxidative phosphorylation (OXPHOS) to glycolysis (the Warburg effect). A redox-sensitive mitochondrial protein, Reactive Oxygen Species Modulator 1 (ROMO1), has emerged as a key mediator of these processes. ROMO1 contributes to mitochondrial morphology, regulates ROS homeostasis, and interacts with key stress-response pathways. While ROMO1 is overexpressed in many cancers and correlates with poor prognosis, recent data suggest that HPV-associated cervical lesions exhibit a unique biphasic expression pattern, with high ROMO1 levels in early stages and reduced expression in advanced tumors. The underlying molecular mechanisms remain unclear, but may involve HPV genome integration, NF-κB suppression, or epigenetic silencing. Key mechanisms such as how HPV modulates ROMO1 expression and how this contributes to stage-dependent metabolic vulnerability remain incompletely understood. This review highlights the current understanding of how HPV oncoproteins impact mitochondrial structure and function, emphasizes the role of ROMO1 in this context, and compares findings with other cancer types. Although no ROMO1-targeted therapies currently exist, the protein may serve as a redox-sensitive biomarker and potential vulnerability in HPV-driven tumors. We propose that targeting mitochondrial fragmentation, ROS signaling, or metabolic reprogramming may offer new avenues for therapeutic intervention. Further research is needed to clarify ROMO1’s dual role in early vs. late-stage disease and to validate its relevance as a clinical target. Our review fills a gap in the current literature by being the first to systematically explore ROMO1’s contribution to HPV-induced mitochondrial dysfunction and metabolic rewiring, and we outline research priorities for future studies. Full article
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14 pages, 927 KB  
Perspective
Polypharmacy as a Chronic Condition: A Diagnostic Mindset for Safer and Smarter Care
by Waseem Jerjes and Azeem Majeed
J. Clin. Med. 2025, 14(20), 7388; https://doi.org/10.3390/jcm14207388 (registering DOI) - 19 Oct 2025
Abstract
Polypharmacy is typically seen as an unavoidable consequence of multimorbidity and aging, with clinicians addressing complex medication lists unsystematically. In this perspective, we argue that polypharmacy should be managed as a chronic condition. Like diabetes or hypertension, for example, the medication burden shows [...] Read more.
Polypharmacy is typically seen as an unavoidable consequence of multimorbidity and aging, with clinicians addressing complex medication lists unsystematically. In this perspective, we argue that polypharmacy should be managed as a chronic condition. Like diabetes or hypertension, for example, the medication burden shows persistence, progression in its absence despite active management, predictable complications (such as falls, delirium, renal injury, functional decline), and a need for structured surveillance. We introduce a pragmatic diagnostic framework that moves beyond pill counts to modality-agnostic, regimen-level risk across prescribed and non-prescribed medicines. Diagnosis rests on prolonged exposure, composite burden indices (e.g., anticholinergic/sedative load), medication-related complications or prescribing cascades, and the need for a planned review. As biologics, gene therapies and long-acting formulations can lower tablet numbers while increasing monitoring, administration, and interaction complexity. We treat polypharmacy as cumulative pharmacodynamic and operational burden. We advocate stage matched care with unique, functional aims—decreasing the harmful burden instead of mass deprescribing—and position a structured medication review as the standard for polypharmacy with support from pharmacists, shared decision making, and safety netted taper plans. The framework fosters patient-centred care, embedding continuity and equity, and outlines a concise outcome set that integrates pharmacometric measures with patient-reported function and treatment burden. At the systems level, the framework enables registries, recall systems, decision support, and audit/feedback mechanisms to shift from sporadic medication list clean-up to a structured, measurable long-term program. Redefining polypharmacy in this way aligns clinical practice, education, and policy with real-world evidence, fostering a cohesive pathway to safer, streamlined, and more patient-centred care in community settings. Full article
(This article belongs to the Section Pharmacology)
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21 pages, 992 KB  
Article
DD-CC-II: Data Driven Cell–Cell Interaction Inference and Its Application to COVID-19
by Heewon Park and Satoru Miyano
Int. J. Mol. Sci. 2025, 26(20), 10170; https://doi.org/10.3390/ijms262010170 - 19 Oct 2025
Abstract
Cell–cell interactions play a pivotal role in maintaining tissue homeostasis and driving disease progression. Conventional Cell–cell interactions modeling approaches depend on ligand–receptor databases, which often fail to capture context-specific or newly emerging signaling mechanisms. To address this limitation, we propose a data-driven computational [...] Read more.
Cell–cell interactions play a pivotal role in maintaining tissue homeostasis and driving disease progression. Conventional Cell–cell interactions modeling approaches depend on ligand–receptor databases, which often fail to capture context-specific or newly emerging signaling mechanisms. To address this limitation, we propose a data-driven computational framework, data-driven cell–cell interaction inference (DD-CC-II), which employs a graph-based model using eigen-cells to represent cell groups. DD-CC-II uses eigen-cells (i.e., functional module within the cell population) to characterize cell groups and construct correlation coefficient networks to model between-group associations. Correlation coefficient networks between eigen-cells are constructed, and their statistical significance is evaluated via over-representation analysis and hypergeometric testing. Monte Carlo simulations demonstrate that DD-CC-II achieves superior performance in inferring CCIs compared with ligand–receptor-based methods. The application to whole-blood RNA-seq data from the Japan COVID-19 Task Force revealed severity stage-specific interaction patterns. Markers such as FOS, CXCL8, and HLA-A were associated with high severity, whereas IL1B, CD3D, and CCL5 were related to low severity. The systemic lupus erythematosus pathway emerged as a potential immune mechanism underlying disease severity. Overall, DD-CC-II provides a data-centric approach for mapping the cellular communication landscape, facilitating a better understanding of disease progression at the intercellular level. Full article
(This article belongs to the Special Issue Advances in Biomathematics, Computational Biology, and Bioengineering)
29 pages, 5221 KB  
Article
Urbanization, Digital–Intelligent Integration, and Carbon Productivity: Spatiotemporal Dynamics in the Middle Reaches Urban Agglomeration of the Yellow River
by Jiayu Ru, Jiahui Li, Lu Gan, Jingbing Sun and Sai Wang
Land 2025, 14(10), 2087; https://doi.org/10.3390/land14102087 - 19 Oct 2025
Abstract
This study investigates the interaction between digital–intelligent integration and carbon productivity in 23 prefecture-level cities across the middle reaches of the Yellow River from 2013 to 2022, focusing on a resource-dependent region transitioning towards low-carbon development. The aim is to examine how digital [...] Read more.
This study investigates the interaction between digital–intelligent integration and carbon productivity in 23 prefecture-level cities across the middle reaches of the Yellow River from 2013 to 2022, focusing on a resource-dependent region transitioning towards low-carbon development. The aim is to examine how digital technologies contribute to improving carbon productivity and reducing environmental pollution. An entropy-weighted index system was used to assess digital–intelligent transformation and carbon productivity. A coupling coordination model was applied to measure their joint performance, with spatial autocorrelation and spillover analyses used to detect regional patterns and intercity linkages. Data were sourced from official yearbooks, environmental bulletins, and urban big-data platforms. The results show a steady improvement in coordination between digital–intelligent integration and carbon productivity, with significant progress in 2018 and 2020 following national policy initiatives. Core cities showed higher coordination and generated positive spillovers, while peripheral cities lagged, resulting in noticeable spatial agglomeration. These findings highlight the growing coupling between digital–intelligent development and carbon productivity, reinforced by policy initiatives but accompanied by regional disparities. This study suggests that policies should focus on enhancing data infrastructure in core cities, improving regional cooperation, and bridging gaps in peripheral areas. It offers insights into the role of digital technologies in achieving low-carbon development in resource-dependent urban regions. Full article
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23 pages, 2479 KB  
Article
Coupling and Coordination of Art Intervention and Community Resilience in Urban Villages: Evidence from Three Cases in Beijing
by Mengyao Yuan, Yun Qian, Yaqi Zhao and Shaojie Zhang
Buildings 2025, 15(20), 3769; https://doi.org/10.3390/buildings15203769 (registering DOI) - 19 Oct 2025
Abstract
Art intervention has emerged as an innovative pathway for community regeneration, significantly enhancing physical and socio-economic conditions, yet its specific impacts on community resilience remain underexplored. This study proposes an evaluation framework that integrates the BRIC community resilience model with key dimensions of [...] Read more.
Art intervention has emerged as an innovative pathway for community regeneration, significantly enhancing physical and socio-economic conditions, yet its specific impacts on community resilience remain underexplored. This study proposes an evaluation framework that integrates the BRIC community resilience model with key dimensions of art intervention. Taking three typical art villages in suburban Beijing (Feijia, Xiaopu, and Xinzhuang) as cases, 452 questionnaires were conducted. The coupling and coordination model was used to analyze interactions between subsystems, and the obstacle factor model was employed to identify barriers to their synergistic development. The results show that: (1) There is a significant positive correlation between the degree of art intervention and community resilience. (2) The coupling and coordination degree exhibits distinct stage differentiation, with art intervention directly affecting its level. Xiaopu Village has the highest coupling and coordination degree (0.8004), followed by Xinzhuang Village (0.6914) and Feijia Village (0.6400). (3) Key obstacles include participation in art activities (9.2%), influence of interactions (9.0%), cultural literacy (8.5%), use of art spaces (7.2%), and industrial influence (6.3%). This study establishes a novel theoretical framework for the synergy between art intervention and community resilience, offering practical strategies for sustainable urban village revitalization. Full article
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24 pages, 2026 KB  
Article
Mixture Effects of Commonly Applied Herbicides on County Level Obesity Rates in the United States: An Exploratory Ecologic Study (2013–2018)
by Sarah Otaru, Laura E. Jones and David O. Carpenter
Toxics 2025, 13(10), 894; https://doi.org/10.3390/toxics13100894 (registering DOI) - 19 Oct 2025
Abstract
Metabolic disorders such as obesity have increased globally in recent decades and are a major public health concern. Previous research suggests that herbicide exposures may contribute to metabolic dysfunction, but few studies have examined mixture effects of multiple herbicides on obesity at a [...] Read more.
Metabolic disorders such as obesity have increased globally in recent decades and are a major public health concern. Previous research suggests that herbicide exposures may contribute to metabolic dysfunction, but few studies have examined mixture effects of multiple herbicides on obesity at a population level. Using county-level data from 2013 to 2018, we examined the associations between obesity rates and the application of 13 commonly applied herbicides in the U.S. We first conducted adjusted single-pollutant mixed-effects models and then used quantile-based g-computation mixture modeling to assess combined herbicide mixture effects on county-level obesity rates. Models were adjusted for demographic and socioeconomic covariates and accounted for geographic clustering. Significant positive associations were identified between county-level obesity rates and applications of glyphosate, 2,4-D, atrazine, acetochlor, metolachlor, and several other herbicides in adjusted single-pollutant models. Glyphosate showed one of the strongest individual associations (β = 0.29 per standard deviation increase, 95% CI: 0.21–0.36). Increases in herbicide mixture were significantly associated with higher obesity rates (Psi = 0.71 per quantile exposure mixture, 95% CI: 0.65–0.76) from mixture modeling. Inclusion of significant interaction terms did not appreciably increase the mixture effect. Glyphosate, 2,4-D, metolachlor, dimethenamid-P, and glufosinate contributed most strongly to the weighted mixture effect. Mixture effects varied by rurality, with stronger associations observed in rural counties, particularly in micropolitan regions. Our findings highlight the importance of considering cumulative herbicide mixture exposures rather than individual chemicals in isolation. The observed rural–urban disparities emphasize the need for targeted public health interventions and policy actions in rural communities, which may be particularly vulnerable to the adverse metabolic impacts of herbicide mixtures. Full article
(This article belongs to the Section Human Toxicology and Epidemiology)
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