MDPI - Publisher of Open Access Journals

13 pages, 1306 KB

Open AccessReview

Plant-Derived miRNAs as Potential Cross-Kingdom Cancer Regulators

by Aizhan Rakhmetullina, Zuzanna Lubas and Piotr Zielenkiewicz

Genes 2025, 16(12), 1441; https://doi.org/10.3390/genes16121441 (registering DOI) - 2 Dec 2025

MicroRNAs (miRNAs) are key posttranscriptional regulators of gene expression that influence cancer initiation, progression, and therapeutic response. While most studies have focused on endogenous miRNAs, emerging evidence has highlighted the role of plant-derived miRNAs as exogenous dietary regulators capable of cross-kingdom gene modulation. [...] Read more.

MicroRNAs (miRNAs) are key posttranscriptional regulators of gene expression that influence cancer initiation, progression, and therapeutic response. While most studies have focused on endogenous miRNAs, emerging evidence has highlighted the role of plant-derived miRNAs as exogenous dietary regulators capable of cross-kingdom gene modulation. This review summarises current knowledge regarding plant-derived miRNAs and their ability to regulate human cancer-related genes. Experimental findings indicate that plant miRNAs can withstand gastrointestinal digestion, enter the circulation, and regulate the expression of oncogenes, tumour suppressors, long noncoding RNAs, and immune checkpoint molecules via canonical RNA-induced silencing mechanisms. Specific examples include miR-156a, miR-159a-3p, miR-166a, miR-167e-5p, miR-171, miR-395e, miR-2911, miR-4995 and miR-5754, which exhibit anticancer activities across various cancer types and modulate key signalling pathways in mammalian cells, highlighting their potential as cross-kingdom regulators with therapeutic relevance. In addition to these characterised miRNAs, certain plant groups, which are rich in bioactive compounds, remain unexplored as sources of functional miRNAs, representing a promising avenue for future research. Collectively, these studies underscore the ability of plant-derived miRNAs to modulate mammalian gene expression and suggest their potential as diet-based or synthetic therapeutic agents. Further investigations into their bioavailability, target specificity, and functional relevance could inform innovative strategies for cancer prevention, integrating nutritional, molecular biological, and therapeutic approaches. Full article

(This article belongs to the Special Issue Function and Regulatory Mechanism of MicroRNAs in Cancers)

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19 pages, 741 KB

Open AccessArticle

Age and the Green Intention: A Serial Mediation Model of Sustainability Knowledge, Attitude, and Behavior

by Vesna Sesar and Ivana Martinčević

Systems 2025, 13(12), 1087; https://doi.org/10.3390/systems13121087 (registering DOI) - 2 Dec 2025

Abstract

As the global context for sustainable actions increases continuously, understanding the psychological and demographic factors that influence green purchase intention (GPI) is vital for promoting sustainable consumer behavior. This study addresses the gap in the literature regarding how age affects sustainability consciousness (SC) [...] Read more.

As the global context for sustainable actions increases continuously, understanding the psychological and demographic factors that influence green purchase intention (GPI) is vital for promoting sustainable consumer behavior. This study addresses the gap in the literature regarding how age affects sustainability consciousness (SC) and then influences GPI. The study employs a multidimensional construct measuring perception of people’s attitudes, knowledge, and behavior with respect to the economic, social, and environmental domain. The purpose of the study was to examine the direct and indirect effects of age on GPI through the mediators of sustainability knowledge (SKNOW), sustainability attitude (SATT), and sustainable behavior (SBEH). A serial mediation model (Model 6) developed by Hayes was applied using the PROCESS macro in SPSS version 26. Data were collected from a general adult population with purchasing power who independently make purchasing decisions in their household from Varazdin County, located in the northern part of the Republic of Croatia, representing different age groups and analyzed to test the hypothesis. In total 323 respondents participated. Results revealed that age had no direct effect on GPI, but significant indirect effects were found through the serial mediation. Specifically, the older groups showed stronger sustainability behavior, which significantly predicted GPI. The findings support the multidimensional structure of SC and highlight the importance of educational and behavioral strategies in promoting sustainable consumption, particularly tailored to specific age groups. This research contributes to sustainability and consumer behavior literature by demonstrating how age influences green purchase intention through serial mediation pathways. Full article

(This article belongs to the Special Issue Systems Modeling and Analysis of Consumer Behavior and Business Management)

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21 pages, 13872 KB

Open AccessArticle

An Improved Lightweight Model for Protected Wildlife Detection in Camera Trap Images

by Zengjie Du, Dasheng Wu, Qingqing Wen, Fengya Xu, Zhongbin Liu, Cheng Li and Ruikang Luo

Sensors 2025, 25(23), 7331; https://doi.org/10.3390/s25237331 (registering DOI) - 2 Dec 2025

Abstract

Effective monitoring of protected wildlife is crucial for biodiversity conservation. While camera traps provide valuable data for ecological observation, existing deep learning models often suffer from low accuracy in detecting rare species and high computational costs, hindering their deployment on edge devices. To [...] Read more.

Effective monitoring of protected wildlife is crucial for biodiversity conservation. While camera traps provide valuable data for ecological observation, existing deep learning models often suffer from low accuracy in detecting rare species and high computational costs, hindering their deployment on edge devices. To address these challenges, this study proposes YOLO11-APS, an improved lightweight model for protected wildlife detection. It enhances the YOLO11n by integrating the self-Attention and Convolution (ACmix) module, the Partial Convolution (PConv) module, and the SlimNeck paradigm. These improvements strengthen feature extraction under complex conditions while reducing computational costs. Experimental results demonstrate that YOLO11-APS achieves superior detection performance compared to the baseline model, attaining a precision of 92.7%, a recall of 87.0%, an mAP@0.5 of 92.6% and an mAP@0.5:0.95 of 62.2%. In terms of model lightweighting, YOLO11-APS reduces the number of parameters, floating-point operations, and model size by 10.1%, 11.1%, and 9.5%, respectively. YOLO11-APS achieves an optimal balance between accuracy and model complexity, outperforming existing mainstream lightweight detection models. Furthermore, tests on unseen wildlife data confirm its strong transferability and robustness. This work provides an efficient deep learning tool for automated wildlife monitoring in protected areas, facilitating the development of intelligent ecological sensing systems. Full article

(This article belongs to the Special Issue Image Processing and Pattern Recognition Based on Deep Learning for Sensing Applications—3rd Edition)

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9 pages, 591 KB

Open AccessArticle

An Environmentally Benign Solvent for the Cationic Polymerization of Low Ceiling Temperature Polyaldehydes

by Jose C. Lopez Ninantay, Anthony C. Engler, Jared M. Schwartz and Paul A. Kohl

Polymers 2025, 17(23), 3210; https://doi.org/10.3390/polym17233210 (registering DOI) - 2 Dec 2025

Abstract

The synthesis of phthalaldehyde-based polymers has exclusively been carried out in dichloromethane, which causes environmental problems due to its halogen content and ozone-depleting attributes. In this study, an alternative solvent for the polymerization of o-phthalaldehyde-based polyaldehydes is disclosed. Ethyl acetate, a solvent [...] Read more.

The synthesis of phthalaldehyde-based polymers has exclusively been carried out in dichloromethane, which causes environmental problems due to its halogen content and ozone-depleting attributes. In this study, an alternative solvent for the polymerization of o-phthalaldehyde-based polyaldehydes is disclosed. Ethyl acetate, a solvent that is widely used in consumer products, dissolves a sufficient amount of reactants and polymer product at the reaction conditions, −86 °C, to provide a comparable yield to synthesis in dichloromethane. A significant learning from this study is that the reaction solvent does not have to fully dissolve all the reactants and products to produce stable polymer, compared to dichloromethane, which fully dissolves reactants and products. The polymer product precipitated from the ethyl acetate solution as the polymer formed. Although the reactants and products were not fully soluble in ethyl acetate, they retained sufficient mobility to allow the catalyst to initiate polymer chains and achieve molecular weights as high as 83.4 kg/mol. The synthesis of cyclic copolymers from o-phthalaldehyde and aliphatic aldehydes is also possible in ethyl acetate if the catalyst is added at a temperature below the ceiling temperature of the monomers and above the point where they crystallize from solution. Full article

(This article belongs to the Section Polymer Applications)

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16 pages, 621 KB

Open AccessArticle

Patients’ Knowledge and Perceptions Towards Digital Technologies in Dentistry: A Cross-Sectional Study

by Aliona Dodi, Alecsandru Ionescu, Mihaela Anca Marin and Marina Imre

Dent. J. 2025, 13(12), 569; https://doi.org/10.3390/dj13120569 (registering DOI) - 2 Dec 2025

Abstract

Background/Objectives: The accelerated digitalisation of dental practice is significantly influencing how patients perceive and accept modern treatments. This study uses a structured questionnaire to evaluate patients’ knowledge of, and attitudes towards, digital technologies in dentistry, adopting an original, patient-centred perspective within routine clinical [...] Read more.

Background/Objectives: The accelerated digitalisation of dental practice is significantly influencing how patients perceive and accept modern treatments. This study uses a structured questionnaire to evaluate patients’ knowledge of, and attitudes towards, digital technologies in dentistry, adopting an original, patient-centred perspective within routine clinical settings. Methods: Non-parametric statistical methods (Mann–Whitney U test, Kruskal–Wallis H test and Spearman correlations) were employed to analyse the responses of 397 participants. To reduce selection bias, a systematic sampling technique was employed, and thorough validation ensured the consistency of the instrument. The questionnaire covered socio-demographic information, prior dental experience and opinions regarding specific digital applications (intraoral scanning (IOS), cone-beam computed tomography (CBCT), CAD-CAM workflows, 3D printing). Knowledge was operationalised as awareness; no keyed objective knowledge test was administered. Results: The findings show that patients generally accept digital technologies, with perceptions of costs, prior experience of digital dental procedures and educational level having a significant impact. The duration of the patient–clinician relationship, the patient’s dental health, and the history of orthodontic and prosthetic procedures also impacted the acceptance of digital technologies. Notably, clinical staff members were the main source of information, highlighting the importance of professional–patient communication. Conclusions: The results highlight the importance of patient-friendly communication in healthcare and provide a solid basis for the implementation of patient-centred digital dentistry. Future plans should focus on creating specialised educational materials, improving digital literacy, and promoting equal access to cutting-edge technologies in urban and disadvantaged communities. Full article

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22 pages, 4528 KB

Open AccessArticle

Optimization Algorithms Embedded in the Engine Control Unit for Energy Management and Hydrogen Fuel Economy in Fuel Cell Electric Vehicles

by Ioan Sorin Sorlei, Nicu Bizon and Gabriel-Vasile Iana

World Electr. Veh. J. 2025, 16(12), 657; https://doi.org/10.3390/wevj16120657 (registering DOI) - 2 Dec 2025

Abstract

The controller of the energy management system must be capable of meeting the rapid and dynamic demands of fuel cell electric vehicles (FCEVs) without compromising its performance and durability. The performance of FCEVs can be enhanced through powertrain hybridization with battery and ultracapacitor [...] Read more.

The controller of the energy management system must be capable of meeting the rapid and dynamic demands of fuel cell electric vehicles (FCEVs) without compromising its performance and durability. The performance of FCEVs can be enhanced through powertrain hybridization with battery and ultracapacitor systems. The overall dynamic optimization of the energy between the batteries/ultracapacitors and the Proton Exchange Membrane Fuel Cell (PEMFC) output can play an important role in hydrogen fuel economy and the durability of vehicle systems. The present study investigates the system’s efficiency and fuel consumption in European Drive Cycles when employing diverse energy management strategies. This investigation utilizes a novel switch real-time strategy (SWA_RTO), which is founded on an A-factor algorithm that alternates between the most effective Real Time Optimization (RTO) strategies. The objective of this paper is to underscore the significance of algorithmic optimization by presenting the optimal results obtained for the fuel economy of the SWA_RTO strategy. These results are compared with the basic RTO strategy and the static Feed-Forward (sFF) reference strategy. The load demand during driving cycles is primarily determined by the PEMFC system. Minor discrepancies in power balance are addressed by the hybrid battery and ultracapacitor system. Consequently, the lifespan of the subject will increase, and the state of charge (SOC) will no longer be a factor in monitoring. Full article

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13 pages, 5000 KB

Open AccessCommunication

Synthesis of Few-Layer Graphene from Lignin and Its Application for the Creation of Thermally Conductive and UV-Protective Coatings

by Aleksei Vozniakovskii, Alexander Voznyakovskii, Anna Neverovskaya, Nikita Podlozhnyuk, Sergey Kidalov and Evgeny Auchynnikau

Materials 2025, 18(23), 5429; https://doi.org/10.3390/ma18235429 (registering DOI) - 2 Dec 2025

Abstract

Coatings based on graphene nanostructures exhibit high thermal conductivity and are capable of effectively protecting materials from the negative effects of ultraviolet radiation. However, due to the imperfections of the methods for synthesizing graphene nanostructures and coatings based on them, the practical application [...] Read more.

Coatings based on graphene nanostructures exhibit high thermal conductivity and are capable of effectively protecting materials from the negative effects of ultraviolet radiation. However, due to the imperfections of the methods for synthesizing graphene nanostructures and coatings based on them, the practical application of such coatings remains unprofitable. This paper presents the results of a study of the thermal conductivity and UV-protective properties of coatings synthesized by chemically crosslinking few-layer graphene particles on ABS plastic substrates. Few-layer graphene particles synthesized under self-propagating high-temperature synthesis conditions were used as the starting material for the coating synthesis. The synthesized coatings were found to have a thermal conductivity of 244 W/(m × K) and are capable of effectively protecting ABS plastic substrates from the negative effects of UV radiation, allowing the products to maintain their required strength characteristics. The high productivity of the method for synthesizing few-layer graphene (up to 10 kg/month at the laboratory production level), as well as the simplicity of the method for synthesizing coatings based on it, allows us to hope for the cost-effectiveness of such coatings. Full article

(This article belongs to the Special Issue Functional/Structural Polymers and Composites Produced by the Addition of Plant Biomass or Waste Materials Using Various Production Technologies)

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20 pages, 26650 KB

Open AccessReview

Advancements in Optical Diffraction Neural Networks

by Tianyu Han, Jiawei Sun and Xibin Yang

Photonics 2025, 12(12), 1187; https://doi.org/10.3390/photonics12121187 (registering DOI) - 2 Dec 2025

Abstract

Optical diffraction neural networks (ODNNs) represent a promising advancement in computational optics, with significant potential for applications in image classification, image reconstruction, and biomedical imaging. By using the principles of light diffraction for neural network computations, ODNNs enable low-power, real-time data processing without [...] Read more.

Optical diffraction neural networks (ODNNs) represent a promising advancement in computational optics, with significant potential for applications in image classification, image reconstruction, and biomedical imaging. By using the principles of light diffraction for neural network computations, ODNNs enable low-power, real-time data processing without the need for traditional electronic computing units. This review provides an overview of the foundational concepts behind ODNNs, starting with the principles of artificial neurons and progressing to the specific implementation of optical diffraction in neural network architectures. We examine recent advancements in key components of ODNNs, including optical signal processing, activation functions, and training algorithms. Additionally, we highlight the practical applications of ODNNs in areas such as signal analysis, optical imaging, image processing, and high-dimensional optical communications. This paper concludes with a discussion of the current challenges and future directions for ODNN research, emphasizing the potential for overcoming existing limitations and further expanding their capabilities. Full article

(This article belongs to the Special Issue AI for Photonics: Intelligent Imaging, Learning-Driven Optics, and Photonic Computing)

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24 pages, 1549 KB

Open AccessReview

From Nature to Science: A Review of the Applications of Pectin-Based Hydrogels

by Karla Nohemi Rubio-Martin del Campo, María Fernanda Rivas-Gastelum, Luis Eduardo Garcia-Amezquita, Maricruz Sepulveda-Villegas, Edgar R. López-Mena, Jorge L. Mejía-Méndez and Angélica Lizeth Sánchez-López

Macromol 2025, 5(4), 58; https://doi.org/10.3390/macromol5040058 (registering DOI) - 2 Dec 2025

Abstract

Pectin is widely used in different areas like biomedical, pharmaceutical, food, and environmental industries thanks to its gelling properties. Pectin hydrogels are of great interest because of their wide biomedical applications in drug delivery, tissue engineering, wound healing, the food industry, agriculture, and [...] Read more.

Pectin is widely used in different areas like biomedical, pharmaceutical, food, and environmental industries thanks to its gelling properties. Pectin hydrogels are of great interest because of their wide biomedical applications in drug delivery, tissue engineering, wound healing, the food industry, agriculture, and cosmetic products because of their biocompatibility, biodegradability, and non-toxic nature. This review provides an understanding of pectin-based hydrogels and their applications in various industrial areas. In addition, an overview of emerging technologies and recent applications of pectin hydrogels is provided, including the controlled and targeted release of bioactive compounds or drugs. They are used as a scaffold for cell growth, as a wound dressing to promote healing, as a fat replacer in food, and as a texturizer in skin-care products. It also serves as a coating for seeds to improve their germination and growth. This paper also identifies knowledge gaps and future research direction for optimizing pectin hydrogels. Full article

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19 pages, 3581 KB

Open AccessReview

Radicular Aberrations of Mandibular Third Molars: Relevance for Oral Surgery—A Comprehensive Narrative Review

by Fabrizio Zaccheo, Giulia Petroni and Andrea Cicconetti

Appl. Sci. 2025, 15(23), 12756; https://doi.org/10.3390/app152312756 (registering DOI) - 2 Dec 2025

Abstract

Background: Mandibular third molars (MTMs) are the most frequently impacted teeth and a common indication for oral surgery. Anatomical root variations can complicate extractions and increase intra- and postoperative risks. Methods: This narrative review analyzes the most frequent MTM root anomalies—supernumerary roots, fusion, [...] Read more.

Background: Mandibular third molars (MTMs) are the most frequently impacted teeth and a common indication for oral surgery. Anatomical root variations can complicate extractions and increase intra- and postoperative risks. Methods: This narrative review analyzes the most frequent MTM root anomalies—supernumerary roots, fusion, taurodontism, C-shaped canals, hypercementosis, and apical dilacerations—focusing on their clinical implications and the diagnostic role of cone-beam computed tomography (CBCT). Results: Root anomalies markedly influence surgical complexity. Supernumerary roots and fusions may hinder elevator use and require modified sectioning. Taurodontism and hypercementosis prolong procedures and increase incomplete extraction risk. C-shaped canals and severe apical curvatures raise the likelihood of root fracture, displacement, or nerve injury. Panoramic radiographs, though common, provide limited two-dimensional detail and may underestimate anomalies. CBCT, by contrast, offers three-dimensional visualization, enhancing diagnosis, planning, and safety. Conclusions: Knowledge of MTM root anomalies, combined with selective CBCT use, is essential for optimizing surgical strategies, minimizing complications, and improving outcomes. Full article

(This article belongs to the Special Issue Advanced Dental Materials and Its Applications)

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18 pages, 3174 KB

Open AccessArticle

Clustering of Civil Aviation Occurrences in Brazil: Operational Patterns and Critical Contexts

by Felipe Duarte Santana, Daniel Alberto Pamplona, Mateus Habermann, Lila Kacedan and Marcelo Xavier Guterres

Future Transp. 2025, 5(4), 185; https://doi.org/10.3390/futuretransp5040185 (registering DOI) - 2 Dec 2025

Abstract

This study applied clustering algorithms to reveal latent structures in 9791 Brazilian civil aviation occurrences recorded from 2007 to 2023. We tested K-means, hierarchical clustering, and K-medoids, using aircraft type, flight phase, and severity as variables in different configurations. The K-medoids method with [...] Read more.

This study applied clustering algorithms to reveal latent structures in 9791 Brazilian civil aviation occurrences recorded from 2007 to 2023. We tested K-means, hierarchical clustering, and K-medoids, using aircraft type, flight phase, and severity as variables in different configurations. The K-medoids method with Manhattan distance produced the best separation. It formed clusters that isolated accidents involving helicopters, ultralights, and critical phases such as takeoff and landing. It also highlighted a specific group of specialized operations. Results confirm that occurrences with similar operational profiles tend to group together, which may help prioritize investigation and prevention actions. The analysis also shows that combining different types of aviation in the same dataset reduces specificity, as heterogeneous operations are mixed. Even so, the findings provide a first overview of safety dynamics in Brazilian civil aviation. The study concludes that clustering can expose latent structures not detected by traditional descriptive analyses and may support the development of more targeted safety policies. Full article

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23 pages, 4476 KB

Open AccessFeature PaperArticle

Methanol Oxidation over Pd-Doped Co- and/or Ag-Based Catalysts: Effect of Impurities (H₂O and CO)

by Eleni Pachatouridou, Angelos Lappas and Eleni Iliopoulou

Catalysts 2025, 15(12), 1129; https://doi.org/10.3390/catal15121129 (registering DOI) - 2 Dec 2025

Abstract

The methanol oxidation reaction was investigated on Co- and/or Ag-based γ-Al₂O₃ catalysts, which were prepared by different methods (WI: wet impregnation and SI: spray impregnation) and further doped with noble metals (Pd, Pt). During the present study, three different reaction [...] Read more.

The methanol oxidation reaction was investigated on Co- and/or Ag-based γ-Al₂O₃ catalysts, which were prepared by different methods (WI: wet impregnation and SI: spray impregnation) and further doped with noble metals (Pd, Pt). During the present study, three different reaction pathways were revealed. The complete oxidation of methanol to CO₂ and H₂O was achieved on Pd-doped catalysts prepared by the spray impregnation method (Pd-Co/Al-SI and Pd-Ag/Al-SI), while partial oxidation to intermediates such as formaldehyde was observed for Ag/alumina catalysts. The dehydration reaction of methanol to dimethyl ether was carried out on Co/alumina, Ag-Co/alumina, and Pt-Co/alumina catalysts. The improved reducibility of the 5Co/Al-SI catalyst with the incorporation of Pd, combined with the easier surface oxygen desorption, resulted in higher catalytic activity compared to the Pt-doped catalyst. On the other hand, the incorporation of Pd into Ag/Al-SI enhanced the well-dispersed Ag₂O species, mainly affecting the structural properties of the catalyst, thus resulting in partial oxidation of methanol. The 0.5 wt.% Pd-5 wt.% Co/γ-Al₂O₃ catalyst, prepared by the spray impregnation method, exhibited the highest methanol oxidation efficiency (T₅₀: 43 °C) and was further evaluated in the presence of H₂O and CO in the feed for several hours on stream and at reaction temperature of 230 °C. The presence of impurities initially reduced the catalyst’s activity from 100% methanol conversion (in the absence of H₂O and CO in the feed) to 80%; however, over time complete methanol oxidation was regained (achieving again 100% methanol conversion after 12 h on stream). Characterization of the used catalyst (after the stability experiment) revealed that in addition to the Co₃O₄ phase, initially formed in the fresh, as-prepared catalyst, some Co₃O₄ species were reduced to CoO under the reaction conditions, suggesting that the active phase of the 0.5Pd-5Co/Al-SI catalyst for the methanol oxidation reaction in the presence of the impurities (such as H₂O and CO) is probably a mixture of Co₃O₄ and CoO phases. Full article

(This article belongs to the Section Environmental Catalysis)

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31 pages, 1661 KB

Open AccessReview

HCMV as an Oncomodulatory Virus in Ovarian Cancer: Implications of Viral Strain Heterogeneity, Immunomodulation, and Inflammation on the Tumour Microenvironment and Ovarian Cancer Progression

by Chrissie Giatrakis, Apriliana E. R. Kartikasari, Thomas A. Angelovich, Katie L. Flanagan, Melissa J. Churchill, Clare L. Scott, Srinivasa Reddy Telukutla and Magdalena Plebanski

Biomolecules 2025, 15(12), 1685; https://doi.org/10.3390/biom15121685 (registering DOI) - 2 Dec 2025

Abstract

The complex relationship between human cytomegalovirus (HCMV) and cancer has been of interest since the 1960s. As a highly prevalent human β-herpesvirus, HCMV establishes lifelong latency in CD34+ myeloid progenitor cells and has been implicated as an oncomodulatory virus in various cancers, including [...] Read more.

The complex relationship between human cytomegalovirus (HCMV) and cancer has been of interest since the 1960s. As a highly prevalent human β-herpesvirus, HCMV establishes lifelong latency in CD34+ myeloid progenitor cells and has been implicated as an oncomodulatory virus in various cancers, including glioblastoma multiforme, breast, prostate, colorectal, and ovarian cancer (OC). Recently, discussions have emerged regarding the classification of HCMV as an eighth oncovirus due to the persistence of its nucleic acids and proteins in many tumour types. As one of the deadliest gynaecological cancers, OC is often characterised as the ‘silent killer’ with less than half of women surviving for 5 years, a rate that drops below 20% when detected at advanced stages. Reported effects of HCMV vary between cancers, likely due to differences in tumour type, viral strain, and disease stage. While HCMV infection has been linked to poor OC patient outcomes, its impact on the OC tumour microenvironment (TME) and immune system remains less understood. Investigating HCMV’s potential oncogenic role could provide critical insights into OC progression. This review discusses recent developments on HCMV’s multifaceted roles in OC, including strain heterogeneity, immunomodulation of the TME, dysregulation of inflammatory signalling pathways, and potential therapeutic approaches targeting HCMV in anti-cancer immunotherapies. Full article

(This article belongs to the Section Molecular Biomarkers)

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18 pages, 11393 KB

Open AccessArticle

What Do Single-Cell Models Already Know About Perturbations?

by Andreas Bjerregaard, Iñigo Prada-Luengo, Vivek Das and Anders Krogh

Genes 2025, 16(12), 1439; https://doi.org/10.3390/genes16121439 (registering DOI) - 2 Dec 2025

Abstract

Background: Virtual cells are embedded in widely used single-cell generative models. Nonetheless, the models’ implicit knowledge of perturbations remains unclear. Methods: We train variational autoencoders on three gene expression datasets spanning genetic, chemical, and temporal perturbations, and infer perturbations by differentiating [...] Read more.

Background: Virtual cells are embedded in widely used single-cell generative models. Nonetheless, the models’ implicit knowledge of perturbations remains unclear. Methods: We train variational autoencoders on three gene expression datasets spanning genetic, chemical, and temporal perturbations, and infer perturbations by differentiating decoder outputs with respect to latent variables. This yields vector fields of infinitesimal change in gene expression. Furthermore, we probe a publicly released scVI decoder trained on the

CELL \times GENE

Discover Census (

\sim 5.7

M mouse cells) and score genes by the alignment between local gradients and an empirical healthy-to-disease axis, followed by a novel large language model-based evaluation of pathways. Results: Gradient flows recover known transitions in Irf8 knockout microglia, cardiotoxin-treated muscle, and worm embryogenesis. In the pretrained Census model, gradients help identify pathways with stronger statistical support and higher type 2 diabetes relevance than an average expression baseline. Conclusions: Trained single-cell decoders already contain rich perturbation-relevant information that can be accessed by automatic differentiation, enabling in-silico perturbation simulations and principled ranking of genes along observed disease or treatment axes without bespoke architectures or perturbation labels. Full article

(This article belongs to the Special Issue Machine Learning in Cancer and Disease Genomics)

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17 pages, 1652 KB

Open AccessArticle

Boron-Doped Bamboo-Derived Porous Carbon via Dry Thermal Treatment for Enhanced Electrochemical Performance

by Hyeon-Hye Kim, Cheol-Ki Cho, Ju-Hwan Kim, Hye-Min Lee, Kay-Hyeok An, Dong-Cheol Chung and Byung-Joo Kim

Batteries 2025, 11(12), 443; https://doi.org/10.3390/batteries11120443 (registering DOI) - 2 Dec 2025

Abstract

In this study, boron was introduced into bamboo-derived porous carbon (BPC) through dry thermal treatment using boric acid. During heat treatment, boric acid was converted to B₂O₃, which subsequently interacted with the oxygen-containing surface groups of BPC, leading to [...] Read more.

In this study, boron was introduced into bamboo-derived porous carbon (BPC) through dry thermal treatment using boric acid. During heat treatment, boric acid was converted to B₂O₃, which subsequently interacted with the oxygen-containing surface groups of BPC, leading to the formation and evolution of B–O–B and B–C bonds. This boron-induced bonding network reconstruction enhanced π-electron delocalization and surface polarity, while maintaining the intrinsic microporous framework of BPC. Among the prepared samples, B-BPC-1 exhibited an optimized balance between the conductive domains and defect concentration, resulting in lower internal resistance and improved ion transport behavior. Correspondingly, B-BPC-1 delivered a better capacitive performance than both undoped BPC and commercial activated carbon. These results indicate that controlling boron incorporation under appropriate heat-treatment conditions effectively improves charge-transfer kinetics while maintaining a stable pore morphology. The proposed dry thermal doping method provides a practical and environmentally benign route for developing high-performance porous carbon electrodes for electric double-layer capacitor applications. Full article

(This article belongs to the Special Issue Advanced Carbon-Based Materials for Next-Generation Batteries and Supercapacitors—2nd Edition)

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21 pages, 34821 KB

Open AccessArticle

The Study and Application of Quadrilateral Space-Time Absolute Nodal Coordinate Formulation Cable Element

by Dekun Chen, Jia Feng, Naidan Hou and Zhou Huang

Machines 2025, 13(12), 1112; https://doi.org/10.3390/machines13121112 (registering DOI) - 2 Dec 2025

Abstract

The construction of a high-order shape function is a key and difficulty for unstructured grid mesh and sliding boundary problems. In this paper, a construction method of space-time absolute nodal coordinate formulation quadrilateral cable (SACQ) is proposed, and the accuracy of the SACQ [...] Read more.

The construction of a high-order shape function is a key and difficulty for unstructured grid mesh and sliding boundary problems. In this paper, a construction method of space-time absolute nodal coordinate formulation quadrilateral cable (SACQ) is proposed, and the accuracy of the SACQ element is studied and verified with three different applications. First, the shape function of SACQ is constructed with spatiotemporal reduction coordinates, and the action integral of SACQ is composed with the Lagrangian function and discrete with perspective transformation. Second, the numerical convergence region is discussed and determined with the Courant number. Furthermore, a space-time nodal dislocation and its relation with the Courant number are studied. The simulation and verification are focusing on some realistic problems. Finally, a one-sided impact, a free-flexible pendulum, a taut string with a sliding boundary and a deployable guyed mast under an impact transverse wave are simulated. In these problems, an unstructured grid meshed with SACQ has similar energy convergence and accuracy to a structured grid but shows better efficiency. Full article

(This article belongs to the Section Advanced Manufacturing)

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25 pages, 1437 KB

Open AccessReview

The Irreversible March of Time: Ischemic Delay and Impact on Outcomes in ST-Segment Elevation Myocardial Infarction

by Artur Dziewierz, Barbara Zdzierak, Wojciech Wańha, Giuseppe De Luca and Tomasz Rakowski

J. Cardiovasc. Dev. Dis. 2025, 12(12), 474; https://doi.org/10.3390/jcdd12120474 (registering DOI) - 2 Dec 2025

Abstract

ST-segment elevation myocardial infarction (STEMI) represents a time-critical medical emergency where complete coronary artery occlusion initiates progressive myocardial necrosis. The fundamental principle of modern STEMI care—“Time is Muscle”—establishes that ischemic duration directly determines infarct size and clinical outcomes. Each minute of delay correlates [...] Read more.

ST-segment elevation myocardial infarction (STEMI) represents a time-critical medical emergency where complete coronary artery occlusion initiates progressive myocardial necrosis. The fundamental principle of modern STEMI care—“Time is Muscle”—establishes that ischemic duration directly determines infarct size and clinical outcomes. Each minute of delay correlates with increased mortality, larger infarcts, and a higher risk of heart failure development. Total ischemic time encompasses both patient-mediated delays (often the largest component) and system-related delays, each influenced by distinct factors requiring targeted interventions. This comprehensive review analyzes the components of total ischemic time, quantifies the clinical consequences of delay, and evaluates evidence-based mitigation strategies. We examine the evolution from fibrinolysis to primary percutaneous coronary intervention and the resulting logistical challenges. System-level interventions—including public awareness campaigns, regionalized STEMI networks, pre-hospital ECG acquisition, and standardized hospital protocols—have dramatically reduced treatment times. However, persistent disparities based on geography, presentation timing, sex, race, and age remain problematic. Emerging technologies, particularly artificial intelligence for ECG interpretation, offer promise for further time reduction. Full article

(This article belongs to the Special Issue 2nd Edition: Interventional Therapies and Management in Coronary Artery Disease)

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16 pages, 1906 KB

Open AccessArticle

Characteristics of Hazardous Air Pollutants in Atmosphere for Complex Industrial Area at Southern Taiwan

by Jiun-Horng Tsai, Pei-Chi Yeh, Shih-Yu Lin and Hung-Lung Chiang

Atmosphere 2025, 16(12), 1369; https://doi.org/10.3390/atmos16121369 (registering DOI) - 2 Dec 2025

Abstract

Using the Ministry of Environment’s fixed-site air quality monitoring network, we analyzed multiple hazardous air pollutants (HAPs)—including volatile organic compounds (VOCs), polycyclic aromatic hydrocarbons (PAHs), and heavy metals—during 2021–2024 and compared their concentrations with internationally reported levels. Pronounced spatial heterogeneity was observed across [...] Read more.

Using the Ministry of Environment’s fixed-site air quality monitoring network, we analyzed multiple hazardous air pollutants (HAPs)—including volatile organic compounds (VOCs), polycyclic aromatic hydrocarbons (PAHs), and heavy metals—during 2021–2024 and compared their concentrations with internationally reported levels. Pronounced spatial heterogeneity was observed across stations, particularly for VOCs and heavy metals. Stations A, E, and F were dominated by alkanes, whereas stations B, C, and D exhibited higher proportions of oxygenated VOCs (mainly aldehydes and ketones). Across the network, formaldehyde (0.015 μg/m³), dichloromethane (2.60 μg/m³), toluene (2.53 μg/m³), and acetaldehyde (0.004 μg/m³) were identified as the most abundant species. Stations A and E served as VOC hotspots—formaldehyde peaked at station A and toluene at station E—likely due to nearby industrial and port activities. Concentrations of BTEX generally decreased throughout the study period, with a minor rebound at station C in 2022. Regarding heavy metals, elevated concentrations of lead (16.83 ng/m³), nickel (4.71 ng/m³), and arsenic (1.29 ng/m³) were observed at station A, again suggesting influences from industrial or port-related emissions. Overall, formaldehyde, benzene, and 1,2-dichloroethane were identified as key pollutants of concern, with station A representing the most critical hotspot in the monitoring network. Full article

(This article belongs to the Section Air Quality)

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19 pages, 698 KB

Open AccessArticle

Evaluation of Childhood Atopic Dermatitis and Environmental Factors in Turkey with Decision Tree Model

by Nesrullah Ayşin, Mehmet Bulduk, Veysel Can, Eda Nur Muhafiz, Bahattin Bulduk and Emine Kurt Can

Int. J. Environ. Res. Public Health 2025, 22(12), 1812; https://doi.org/10.3390/ijerph22121812 (registering DOI) - 2 Dec 2025

Abstract

Objective: This study aims to examine the relationship between atopic dermatitis (AD), one of the most common dermatological conditions in children, and environmental factors, including meteorological variables and air pollution. Methods: This retrospective cross-sectional study analyzed the medical records of 21,407 pediatric patients [...] Read more.

Objective: This study aims to examine the relationship between atopic dermatitis (AD), one of the most common dermatological conditions in children, and environmental factors, including meteorological variables and air pollution. Methods: This retrospective cross-sectional study analyzed the medical records of 21,407 pediatric patients aged 0 to 18 years who presented to the city hospital in Agri, Turkey, between 2020 and 2024. Admission dates were matched with meteorological data (wind speed, atmospheric pressure, humidity, temperature) and air pollution indicators (PM₁₀, SO₂, NO₂, NOx, NO, O₃). Statistical analyses included t-tests, correlation analyses, binary logistic regression, and a CHAID decision tree model. Results: AD accounted for 10.1% of all dermatology-related visits. AD admissions increased particularly during the first half of the year and were significantly associated with higher O₃ levels, whereas increased PM₁₀ levels were associated with a lower likelihood of AD admissions. Logistic regression showed that age, sex, semiannual period, atmospheric pressure, PM₁₀, and O₃ were significant predictors of AD. The decision tree model identified age, period, and O₃ as the strongest discriminating variables for AD. Conclusion: AD was found to be more sensitive to environmental and seasonal variations compared with other dermatitis types. In particular, elevated ozone levels and temporal factors played a notable role in increasing AD presentations. These findings may inform environmental risk management and preventive strategies for children with AD. Full article

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28 pages, 4153 KB

Open AccessReview

Interspecies Transmission of Animal Rotaviruses to Humans: Reassortment-Driven Adaptation

by Toyoko Nakagomi and Osamu Nakagomi

Pathogens 2025, 14(12), 1230; https://doi.org/10.3390/pathogens14121230 (registering DOI) - 2 Dec 2025

Abstract

Rotavirus alphagastroenteritidis (rotavirus) infects a broad range of hosts, including humans and various animal species. Its genome comprises 11 segments of double-stranded RNA, making it highly prone to genetic diversity through gene reassortment. Although rotavirus strains are typically host-specific, novel human strains with [...] Read more.

Rotavirus alphagastroenteritidis (rotavirus) infects a broad range of hosts, including humans and various animal species. Its genome comprises 11 segments of double-stranded RNA, making it highly prone to genetic diversity through gene reassortment. Although rotavirus strains are typically host-specific, novel human strains with global impact often originate from interspecies transmission of animal rotaviruses. This review explores the critical role of interspecies transmission coupled with genetic reassortment in rotavirus adaptation to humans, contextualizing key studies and methodological advances. Central to this progress was the development of tools to analyse entire genomes and distinguish homologous from heterologous strains. We trace the evolution from RNA-RNA hybridisation to whole-genome sequencing, which underpins genotype constellation and sub-genotype phylogeny. A decade-long surveillance of the bovine-like G8 rotavirus in Vietnam offers a compelling model: for an animal rotavirus to become a successful human pathogen, it must replace its animal-derived genes with human-derived counterparts through reassortment. Retaining the animal-origin G8 VP7 gene is enabled by acquiring a compatible human VP4 gene (specifically P[8]) and DS-1-like backbone genes. Building on this model of reassortment-driven adaptation, our investigation into the unusual G1P[6] strain AU19, of wholly porcine origin, supports the hypothesis that the predominant human G1 rotavirus also evolved from a successful interspecies transmission event. Phylogenetic analysis suggests the ancestral human G1 gene emerged from a porcine rotavirus between 1915 and 1948, later reassorting with human strains to acquire Wa-like backbone genes, ultimately becoming a stable and dominant part of the human rotavirus population. In conclusion, genetic reassortment is a key mechanism transforming sporadic zoonotic events into sustained human-pathogens, although other factors remain to be fully defined. We conclude by highlighting key areas for further research. Full article

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36 pages, 6895 KB

Open AccessArticle

Machine-Learning Algorithms for Remote-Control and Autonomous Operation of the Very-Small, Long-Life, Modular (VSLLIM) Microreactor

by Mohamed S. El-Genk, Timothy M. Schriener and Ahmad N. Shaheen

J. Nucl. Eng. 2025, 6(4), 54; https://doi.org/10.3390/jne6040054 (registering DOI) - 2 Dec 2025

Abstract

This work investigated machine-learning algorithms for remote-control and autonomous operation of the Very-Small, Long-Life, Modular (VSLLIM) microreactor. This walk-away safe reactor can continuously generate 1.0–10 MW of thermal power for 92 and 5.6 full power years, respectively, is cooled by natural circulation of [...] Read more.

This work investigated machine-learning algorithms for remote-control and autonomous operation of the Very-Small, Long-Life, Modular (VSLLIM) microreactor. This walk-away safe reactor can continuously generate 1.0–10 MW of thermal power for 92 and 5.6 full power years, respectively, is cooled by natural circulation of in-vessel liquid sodium, does not require on-site storage of either fresh or spent nuclear fuel, and offers redundant means of control and passive decay heat removal. The two ML algorithms investigated are Supervised Learning with Long Short-Term Memory networks (SL-LSTM) and Soft-Actor Critic with Feedforward Neural Networks (SAC-FNN). They are trained to manage the movement of the control rods in the reactor core during various transients including startup, shutdown, and to change the reactor steady state power up to 10 MW. The trained algorithms are incorporated into a Programmable Logic Controller (PLC) coupled to a digital twin dynamic model of the VSLLIM microreactor. Although the SL-LSTM algorithms demonstrate high prediction accuracy of up to 99.95%, they demonstrate inferior performance when incorporated into the PLC. Conversely, the PLC with SAC-FNN algorithm accurately adjusts the control rods positions during the reactor startup transients to within ±1.6% of target values. Full article

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22 pages, 4416 KB

Open AccessArticle

A Numerical Case Study on the Design of a Multi-Porosity Heat Exchanger for VRF Air Conditioning Applications

by Hela Guesmi and Hacen Dhahri

Processes 2025, 13(12), 3892; https://doi.org/10.3390/pr13123892 (registering DOI) - 2 Dec 2025

Abstract

This study proposes a novel multi-porous heat exchanger (MPHEX) as a passive, sustainable alternative to variable refrigerant flow (VRF) air conditioning systems, addressing the growing environmental burden of cooling demand. Through high-fidelity Lattice Boltzmann Method simulations of coupled heat and fluid transport, the [...] Read more.

This study proposes a novel multi-porous heat exchanger (MPHEX) as a passive, sustainable alternative to variable refrigerant flow (VRF) air conditioning systems, addressing the growing environmental burden of cooling demand. Through high-fidelity Lattice Boltzmann Method simulations of coupled heat and fluid transport, the MPHEX design is optimized to minimize exergy destruction. A case study for Tunisian conditions demonstrates that permeability optimization, when combined with solar-assisted preheating, reduces total exergy destruction by over 60% and increases the coefficient of performance (COP) by up to 20%, all while eliminating active mechanical regulation. The numerical results confirm strong experimental feasibility, positioning the MPHEX as a scalable, low-energy, and low-maintenance cooling solution for sun-rich regions. Full article

(This article belongs to the Special Issue Advances in Computational Fluid Dynamics (CFD) Simulation of Thermal Chemical Processes)

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14 pages, 1392 KB

Open AccessArticle

Sensitivity Analysis of Water Vapor in Near-Space Based on the SCIATRAN Atmospheric Radiative Transfer Model

by Yongying Gan, Shuang Liu, Song Ye, Zhen Wang, Xinqiang Wang, Jiejun Wang and Jian Liao

Appl. Sci. 2025, 15(23), 12754; https://doi.org/10.3390/app152312754 (registering DOI) - 2 Dec 2025

Abstract

To achieve high-precision retrieval of water vapor concentration profiles in the near-space region, this study utilizes the high-resolution spectral radiative transfer model SCIATRAN to simulate water vapor observation spectra under different observational geometric parameters and atmospheric aerosol conditions. A comprehensive analysis is conducted [...] Read more.

To achieve high-precision retrieval of water vapor concentration profiles in the near-space region, this study utilizes the high-resolution spectral radiative transfer model SCIATRAN to simulate water vapor observation spectra under different observational geometric parameters and atmospheric aerosol conditions. A comprehensive analysis is conducted on the influence of these parameters on spectral radiance. The results demonstrate that when the tangent height exceeds 40 km, water vapor absorption features significantly weaken. Spectral data acquired under conditions combining small solar zenith angles with large relative azimuth angles exhibit greater stability. Middle and upper atmospheric aerosols, predominantly composed of volcanic ash and particulate matter, induce strong sensitivity of water vapor spectral radiance to stratospheric and mesospheric aerosols. Notably, under extreme volcanic aerosol loading conditions, the differential-to-background ratio of spectral radiance surpasses 2000%. This investigation identifies key sensitive parameters and their mechanistic influences on near-space water vapor observation spectra. The findings provide a theoretical foundation for optimizing the design parameters of near-space sounders, while offering scientific guidance for formulating data screening strategies and conducting error traceability analysis during water vapor concentration retrieval processes. Full article

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18 pages, 428 KB

Open AccessArticle

Analyzing Students’ Academic Performance Based on Fuzzy Inference System

by Hayrünnisa Ergin and Efendi Nasibov

Appl. Sci. 2025, 15(23), 12755; https://doi.org/10.3390/app152312755 (registering DOI) - 2 Dec 2025

Abstract

Evaluating students’ knowledge and competencies to achieve the desired learning goals is one of the most important stages of the teaching process. The purpose of this study is to create a dataset consisting of programming questions and determine the level of these questions [...] Read more.

Evaluating students’ knowledge and competencies to achieve the desired learning goals is one of the most important stages of the teaching process. The purpose of this study is to create a dataset consisting of programming questions and determine the level of these questions according to the Bloom taxonomy and the weight of each concept they contain, by taking expert opinion. The student’s score, question difficulty, and complexity levels are considered to determine the extent to which the student has learned a concept. A total of 96 students participated in this study, 51 in the experimental group and 45 in the control group. Random design for a pre-test–post-test control group was used to measure the students’ learning performance and self-efficacy regarding programming. While the experimental group students were given detailed feedback on how much they learned a concept, the control group students were only informed about the total score they received from the exam. The learning performance and self-efficacy perception regarding programming were analyzed using the paired samples t-test. Results show that the learning performance and self-efficacy perception regarding programming of the experimental group students improved significantly compared to the control group. Full article

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17 pages, 3622 KB

Open AccessFeature PaperArticle

BIM as a Social Technology to Enhance Governmental Decision-Making in Social Housing Programming

by Cristiano Saad Travassos do Carmo, Renata Gonçalves Faisca, Vitória Franco Benayon Menezes, Antonio Elias Amil Lisboa, Felipe Almeida de Sousa, Marcelo Jasmim Meirino and Patrícia Maria Quadros Barros

Real Estate 2025, 2(4), 20; https://doi.org/10.3390/realestate2040020 (registering DOI) - 2 Dec 2025

Abstract

The housing deficit in developing countries is a common challenge, primarily impacting low-income populations. This paper investigated interinstitutional workflows using Building Information Modelling (BIM) as a social technology to improve the efficiency of design and construction stages in social housing projects. Following a [...] Read more.

The housing deficit in developing countries is a common challenge, primarily impacting low-income populations. This paper investigated interinstitutional workflows using Building Information Modelling (BIM) as a social technology to improve the efficiency of design and construction stages in social housing projects. Following a systematic literature review, process maps were developed and applied in a case study within a Brazilian urban community, located in a coastal city with a demographic density of 3602 inhabitants per square kilometre, involving a collaboration framework between a university and municipal authorities. Based on the party’s collaboration and precise cost estimation, the results indicate that this BIM-enabled collaboration supports the governmental decision-making process and leads to more effective resource management and optimised design costs, mainly during the design and construction phases. Therefore, this study concludes that digital modelling workflows are a powerful strategy for developing social housing projects because they facilitate the inclusion of families in the design and decision-making processes. Expanding this approach through integration with geospatial and public agency data is a promising area for future research, using such models in risk assessment policies and city urban planning. Full article

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13 pages, 389 KB

Open AccessArticle

The Role of Social Determinants of Health and Diabetes Self-Management on Glycemic Indices: A Cross-Sectional Analysis

by Cherlie Magny-Normilus, Sangchoon Jeon, Jeffrey L. Schnipper, Bei Wu and Robin Whittemore

Diabetology 2025, 6(12), 154; https://doi.org/10.3390/diabetology6120154 (registering DOI) - 2 Dec 2025

Abstract

Background/Objectives: Type 2 diabetes (T2D) is a substantial health burden on foreign-born Haitian Americans (FBHAs) in the United States, who experience poorer health outcomes for T2D, in particular, cardiovascular disease and diabetes nephropathy. Understanding the factors that contribute to these disparities is essential. [...] Read more.

Background/Objectives: Type 2 diabetes (T2D) is a substantial health burden on foreign-born Haitian Americans (FBHAs) in the United States, who experience poorer health outcomes for T2D, in particular, cardiovascular disease and diabetes nephropathy. Understanding the factors that contribute to these disparities is essential. The purpose of this study was to examine the association between demographic, clinical, diabetes self-management, and social determinants of health (SDoH) factors with continuous glucose monitor (CGM-derived) glycemic indices in adult FBHAs with T2D. Methods: A cross-sectional exploratory correlation study was conducted in two urban health clinics, focusing on FBHAs aged 21 or older who had T2D for at least one year. Data were analyzed using SAS 6.4, employing descriptive statistics, bivariate correlations, and multiple regression models. Results: The study included 59 participants (49.2% male; mean age = 51.7 years, SD = 9.9), with an average T2D duration of 7.7 years (SD = 6.8) and an average of 1.63 (SD = 1.30) chronic diseases. A total of 29% were overweight while 21% had obesity with a mean HbA_1c of 58 mmol/mol (7.5%). A higher body weight and poorer dietary habits were associated with elevated glucose levels (standardized β ≈ 0.25 and −0.24). Greater race-related stress was correlated with greater glucose variability (β ≈ 0.46). Conclusions: These findings highlight the importance of addressing SDoH, such as race-related stress and food insecurity, to improve T2D self-management among FBHAs. Assessing and mitigating these risk factors can enhance glycemic control and health outcomes. Additionally, the findings demonstrate that CGM is feasible and acceptable for this population, showing exploratory findings and preliminary effect sizes that provide a strong basis for future, large-scale investigations. Full article

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