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18 pages, 1645 KB

Open AccessArticle

Impact of Stalled Life Expectancy on Health and Economic Inactivity in the UK and the Case for Prevention

by Leslie D. Mayhew

Risks 2025, 13(11), 211; https://doi.org/10.3390/risks13110211 (registering DOI) - 2 Nov 2025

We use partial life expectancy to show the existence in the UK of an asymmetric relationship between life span and health span in five-year age brackets over the life course. Using comparable data from other advanced economies, we investigate why years of improvement [...] Read more.

We use partial life expectancy to show the existence in the UK of an asymmetric relationship between life span and health span in five-year age brackets over the life course. Using comparable data from other advanced economies, we investigate why years of improvement in life expectancy after 2010 have come to a halt, and what would have happened if austerity and the COVID pandemic had not occurred. We find that the UK does worse than other countries except for the US. We show that deprivation is a major source of disparities between health and life span and is a key contributing factor. A one-year decrease in life expectancy leads to a 2.5-year reduction in health expectancy, resulting in a 21-year disparity between health and life span in the most deprived area. The resultant gap places a considerable burden on public finances and slows economic growth. Impacts include lower economic activity rates, higher healthcare costs, greater immigration, and upward financial pressures on the state pension. The unresolved policy issue is how to slow the current trend, given the rapidly ageing UK population. Full article

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55 pages, 3225 KB

Open AccessSystematic Review

Integrating AI with Biosensors and Voltammetry for Neurotransmitter Detection and Quantification: A Systematic Review

by Ibrahim Moubarak Nchouwat Ndumgouo, Mohammad Zahir Uddin Chowdhury, Silvana Andreescu and Stephanie Schuckers

Biosensors 2025, 15(11), 729; https://doi.org/10.3390/bios15110729 (registering DOI) - 2 Nov 2025

Abstract

Background: The accurate and timely diagnosis of neurodegenerative disorders such as Parkinson’s disease, Alzheimer’s disease, and major depressive disorder critically depends on real-time monitoring and precise interpretation of authentic neurotransmitter (NT) signal dynamics in complex biological fluids (CBFs), including cerebrospinal fluid. These NT [...] Read more.

Background: The accurate and timely diagnosis of neurodegenerative disorders such as Parkinson’s disease, Alzheimer’s disease, and major depressive disorder critically depends on real-time monitoring and precise interpretation of authentic neurotransmitter (NT) signal dynamics in complex biological fluids (CBFs), including cerebrospinal fluid. These NT dynamics are governed by both the type and concentration of NTs present in the CBFs. However, current biosensors face significant limitations in sensitivity and selectivity, thereby hindering reliable estimation (detection and quantification) of NTs. Though nanomaterials and bioenzymes have been utilized to modify sensor interfaces for enhanced performance, issues like signal convolution, electrode fouling, and inter-NT crosstalk persist. Objectives: This review aims to evaluate and synthesize current research on the use of artificial intelligence (AI), particularly machine learning (ML), pattern recognition (PR), and deep learning (DL), to improve the automated detection and quantification of neurotransmitters from complex biological fluids. Design: A systematic review of 33 peer-reviewed studies was conducted, focusing on the integration of AI methods in neurotransmitter estimation. The review includes an analysis of commonly studied NTs, the methodologies for their detection, data acquisition techniques, and the AI algorithms applied for signal processing and interpretation. Results: The studies reviewed demonstrate that AI-based approaches have shown considerable potential in overcoming traditional biosensor limitations by effectively deconvoluting complex, multiplexed NT signals. These techniques allow for more accurate NT estimation in real-time monitoring scenarios. The review categorizes AI methodologies by their application and performance in NT signal analysis. Conclusions: AI-enhanced NT monitoring represents a promising direction for advancing diagnostic and therapeutic capabilities in neurodegenerative diseases. Despite current challenges, such as sensor stability and NT interaction complexity, AI integration, particularly in applications like closed-loop deep brain stimulation (CLDBS), offers significant potential for more effective and personalized treatments. Full article

(This article belongs to the Special Issue In Honor of Prof. Evgeny Katz: Biosensors: Science and Technology)

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21 pages, 1041 KB

Open AccessArticle

Biochemical Effects of Natural and Nanoparticle Fish and Algal Oils in Gilt Pregnancy Diets on Base Excision Repair Enzymes in Newborn Piglets—Socioeconomic Implications for Regional Pig Farming—Preliminary Results

by Paweł Kowalczyk, Monika Sobol, Joanna Makulska, Andrzej Węglarz, Apoloniusz Kurylczyk, Mateusz Schabikowski and Grzegorz Skiba

Int. J. Mol. Sci. 2025, 26(21), 10676; https://doi.org/10.3390/ijms262110676 (registering DOI) - 2 Nov 2025

Abstract

Base excision repair (BER) is an important mechanism for maintaining genomic integrity and preventing DNA damage and mutations induced by oxidative stress. This study aimed to examine the relationship between oxidative stress and BER activity in newborn piglets by supplementing their mothers’ diets [...] Read more.

Base excision repair (BER) is an important mechanism for maintaining genomic integrity and preventing DNA damage and mutations induced by oxidative stress. This study aimed to examine the relationship between oxidative stress and BER activity in newborn piglets by supplementing their mothers’ diets during pregnancy with long-chain n-3 polyunsaturated fatty acids (PUFAs) from algal and fish oils, provided either in natural form or as nanoparticles. BER enzyme activity was assessed using a nicking assay, and their gene expression levels by RT-qPCR in the livers of pregnant gilts and their offspring. Preliminary results indicated that maternal supplementation with oils rich in long-chain n-3 PUFAs significantly reduced (by 32%) BER capacity in the livers of their offspring. A corresponding decrease in mRNA expression of BER genes (TDG, MPG, OGG1) was observed in piglets from gilts receiving fish and algal oil supplements. Maternal supplementation with long-chain n-3 PUFAs may protect foetuses and neonates against oxidative stress, reducing DNA damage and enhancing genomic stability, which could positively influence early postnatal growth. The observed reduction in BER enzyme activity in newborn piglets likely reflected improved DNA integrity, and natural oil forms appeared more effective than their nanoparticle formulations. Disparities in socioeconomic areas related to access to functional foods with health-promoting properties highlight the importance of targeted strategies that integrate local systems and promote nutritional equity. Full article

(This article belongs to the Special Issue Molecular Progression of Genetics in Breeding of Farm Animals)

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19 pages, 2771 KB

Open AccessArticle

Influence of Electrical Transients and A/D Converter Dynamics on Thermal Resistance Measurements of Power MOSFETs

by Krzysztof Górecki and Krzysztof Posobkiewicz

Sensors 2025, 25(21), 6691; https://doi.org/10.3390/s25216691 (registering DOI) - 2 Nov 2025

Abstract

When designing power electronic systems, it is crucial to correctly estimate the junction temperature of semiconductor devices, particularly power MOSFETs, under actual operating conditions. Thermal resistance is a parameter that characterizes the ability of these devices to dissipate internally generated heat under steady-state [...] Read more.

When designing power electronic systems, it is crucial to correctly estimate the junction temperature of semiconductor devices, particularly power MOSFETs, under actual operating conditions. Thermal resistance is a parameter that characterizes the ability of these devices to dissipate internally generated heat under steady-state conditions. Determining the value of this parameter under specific cooling conditions requires dedicated measurements. This paper considers the widely used indirect electrical method of measuring thermal resistance. The influence of the dynamic properties of the measurement system, including the A/D converter, on the measurement error of the thermal resistance of power MOSFETs was analyzed. Using the constructed measurement system, it was demonstrated that, depending on the semiconductor material of the tested transistors, different error values were obtained, even with the same system configuration. The largest errors were observed for transistors made of silicon carbide. It was further shown that, with the applied A/D converter module, the measurement error can be limited to a few percent if recording of the thermal sensitive electrical parameter (TSEP) begins soon enough after the transients caused by the switchover from heating to TSEP measurement have fully decayed. Full article

(This article belongs to the Section Electronic Sensors)

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25 pages, 1185 KB

Open AccessReview

The Critical Role of IoT for Enabling the UK’s Built Environment Transition to Net Zero

by Ioannis Paraskevas, Diyar Alan, Anestis Sitmalidis, Grant Henshaw, David Farmer, Richard Fitton, William Swan and Maria Barbarosou

Energies 2025, 18(21), 5779; https://doi.org/10.3390/en18215779 (registering DOI) - 2 Nov 2025

Abstract

The built environment contributes approximately 25% of the UK’s total greenhouse gas emissions, positioning it as a critical sector in the national net-zero strategy. This review investigates the enabling role of the domestic smart metering infrastructure combined with other IoT systems in accelerating [...] Read more.

The built environment contributes approximately 25% of the UK’s total greenhouse gas emissions, positioning it as a critical sector in the national net-zero strategy. This review investigates the enabling role of the domestic smart metering infrastructure combined with other IoT systems in accelerating the decarbonisation of residential buildings. Drawing from experience gained from governmental and commercially funded R&D projects, the article demonstrates how smart metering data can be leveraged to assess building energy performance, underpin cost-effective carbon reduction solutions, and enable energy flexibility services for maintaining grid stability. Unlike controlled laboratory studies, this review article focuses on real-world applications where data from publicly available infrastructure is accessed and utilised, enhancing scalability and policy relevance. The integration of smart meter data with complementary IoT data—such as indoor temperature, weather conditions, and occupancy—substantially improves built environment digital energy analytics. This capability was previously unattainable due to the absence of a nationwide digital energy infrastructure. The insights presented in this work highlight the untapped potential of the UK’s multibillion-pound investment in smart metering, offering a scalable pathway for low-carbon innovation for the built environment, thus supporting the broader transition to a net-zero future. Full article

(This article belongs to the Section B: Energy and Environment)

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23 pages, 1737 KB

Open AccessArticle

Arc Flow Formulation for Efficient Uniform Parallel Machine Scheduling

by Khaled Bamatraf and Anis Gharbi

Symmetry 2025, 17(11), 1839; https://doi.org/10.3390/sym17111839 (registering DOI) - 2 Nov 2025

Abstract

This paper considers the scheduling problem of uniform parallel machines. The objective is to minimize the makespan. This problem holds practical significance and is inherently NP-hard. Therefore, solutions of the exact formulation are limited to small-sized instances. As the problem size increases, the [...] Read more.

This paper considers the scheduling problem of uniform parallel machines. The objective is to minimize the makespan. This problem holds practical significance and is inherently NP-hard. Therefore, solutions of the exact formulation are limited to small-sized instances. As the problem size increases, the exact formulation struggles to find optimal solutions within a reasonable time. To address this challenge, an arc flow formulation is proposed, aiming to solve larger instances. The arc flow formulation creates a pseudo-polynomial number of variables, with its size being significantly influenced by the problem’s bounds. Therefore, bounds from the literature are utilized, and symmetry-breaking rules are applied to reduce the size of the arc flow graph. To test the effectiveness of the proposed arc flow formulation, it was compared with a mathematical formulation from the literature on small instances with up to 30 jobs. Computational results showed that the arc flow formulation outperforms the mathematical formulation from the literature, solving all cases within a few seconds. Additionally, on larger benchmark instances, the arc flow formulation solved 84.27% of the cases to optimality. The maximum optimality gap does not exceed 0.072% for the instances not solved to optimality. Full article

(This article belongs to the Special Issue Symmetry/Asymmetry in Operations Research)

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20 pages, 857 KB

Open AccessSystematic Review

Enablers, Barriers and Systems for Organizational Change for Adopting and Implementing Local Governments’ Climate Mitigation Strategies: A Systematic Literature Review

by Mark Goudsblom and Amelia Clarke

Climate 2025, 13(11), 228; https://doi.org/10.3390/cli13110228 (registering DOI) - 2 Nov 2025

Abstract

By 2050, the global population will be predominantly living in urban areas, and climate change mitigation planning will be crucial for addressing the climate emergency. Local governments are well-positioned to lead in adopting effective climate mitigation strategies. This systematic literature review examines the [...] Read more.

By 2050, the global population will be predominantly living in urban areas, and climate change mitigation planning will be crucial for addressing the climate emergency. Local governments are well-positioned to lead in adopting effective climate mitigation strategies. This systematic literature review examines the barriers, enablers, and systems that local governments will need to consider when implementing climate mitigation and strategies. A search across Scopus, Web of Science, and ProQuest databases yielded 411 results, from which 28 articles were selected for detailed analysis. Using Covidence and NVivo 14 software, the study employed a combination of deductive and inductive coding to identify key themes. The study identified themes specific to enablers, such as technology, collaboration, leadership, and management culture, as well as barrier themes, including short-term thinking, uncertainty avoidance, lack of knowledge among decision-makers, resource shortages, and organizational challenges. The findings underscore the importance of addressing organizational issues and allocating appropriate resources to bolster local-level systems change in support of climate change mitigation efforts. Full article

(This article belongs to the Collection Adaptation and Mitigation Practices and Frameworks)

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17 pages, 8568 KB

Open AccessArticle

Mechanistic Study of Surface Nanocrystallization for Surface Modification in High-Strength Low-Alloy Steel

by Yiyang Jin, Feng Ge, Pengfei Wei, Yixuan Li, Lingli Zuo and Yunbo Chen

Coatings 2025, 15(11), 1270; https://doi.org/10.3390/coatings15111270 (registering DOI) - 2 Nov 2025

Abstract

This study systematically investigates the surface nanocrystallization of 35CrMo steel induced by Ultrasonic Surface Rolling Processing (USRP). It reveals the formation of a gradient nanostructure, where martensite lath fragmentation under high-frequency impacts leads to a surface layer of equiaxed nanocrystals and high-density dislocations. [...] Read more.

This study systematically investigates the surface nanocrystallization of 35CrMo steel induced by Ultrasonic Surface Rolling Processing (USRP). It reveals the formation of a gradient nanostructure, where martensite lath fragmentation under high-frequency impacts leads to a surface layer of equiaxed nanocrystals and high-density dislocations. This novel microstructure yields exceptional surface integrity: roughness is minimized to 0.029 μm due to plastic flow, residual stress is transformed into high compressive stress, and surface microhardness is significantly enhanced by 32.3%, primarily governed by grain refinement and dislocation strengthening. Consequently, the treated material exhibits a 28.9% reduction in wear mass loss, which is directly attributed to the combined effects of the strengthened gradient layer’s improved load-bearing capacity and the effective suppression of crack initiation by compressive residual stresses. Our findings not only provide direct microstructural evidence for classic strengthening theories but also offer a practical guide for optimizing the surface performance of high-strength alloy components. Full article

(This article belongs to the Section Surface Characterization, Deposition and Modification)

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30 pages, 4326 KB

Open AccessArticle

Experimental Study on Zeolite–Polyester-Coated Jute–Sisal Fibre Back Sheets for Improved Efficiency of Solar Panels: A Renewable Composite Material Strategy

by Aishwarya Sathyanarayanan, Balasubramanian Murugesan and Narayanamoorthi Rajamanickam

J. Compos. Sci. 2025, 9(11), 599; https://doi.org/10.3390/jcs9110599 (registering DOI) - 2 Nov 2025

Abstract

This study examines the potential of jute–sisal (JS) fibre, both coated and uncoated, as a sustainable alternative to solar panels with polyethylene terephthalate (PET) back sheets. The coated version was developed using a zeolite–polyester resin composite to enhance thermal performance. The investigation was [...] Read more.

This study examines the potential of jute–sisal (JS) fibre, both coated and uncoated, as a sustainable alternative to solar panels with polyethylene terephthalate (PET) back sheets. The coated version was developed using a zeolite–polyester resin composite to enhance thermal performance. The investigation was carried out in two phases: controlled laboratory testing using a solar-cell tester and a 90-day real-world evaluation under natural environmental conditions. In controlled conditions, solar panels with coated JS (CJS) fibre back sheets exhibited improved electrical performances compared to PET panels, including higher current (1.23 A), voltage (12.79 V), maximum power output (14.79 W), efficiency (13.47%), and fill factor (94.03%). Lower series resistance and higher shunt resistance further indicated superior electrical characteristics. Under real-world conditions, CJS panels consistently outperformed PET-based panels, showing a 6% increase in current and an 8% increase in voltage. The model showed strong agreement with the experimental results. These findings suggest that coated JS fibre is a viable, eco-friendly alternative to PET for back sheets in solar panels. Further research should examine its long-term durability, environmental resistance, and commercial scalability. Full article

(This article belongs to the Section Fiber Composites)

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26 pages, 3560 KB

Open AccessArticle

Intelligent Identification Method of Valve Internal Leakage in Thermal Power Station Based on Improved Kepler Optimization Algorithm-Support Vector Regression (IKOA-SVR)

by Fengsheng Jia, Tao Jin, Ruizhou Guo, Xinghua Yuan, Zihao Guo and Chengbing He

Computation 2025, 13(11), 251; https://doi.org/10.3390/computation13110251 (registering DOI) - 2 Nov 2025

Abstract

Valve internal leakage in thermal power stations exhibits a strong concealed nature. If it cannot be discovered and predicted of development trend in time, it will affect the safe and economical operation of plant equipment. This paper proposed an intelligent identification method for [...] Read more.

Valve internal leakage in thermal power stations exhibits a strong concealed nature. If it cannot be discovered and predicted of development trend in time, it will affect the safe and economical operation of plant equipment. This paper proposed an intelligent identification method for valve internal leakage that integrated an Improved Kepler Optimization Algorithm (IKOA) with Support Vector Regression (SVR). The Kepler Optimization Algorithm (KOA) was improved using the Sobol sequence and an adaptive Gaussian mutation strategy to achieve self-optimization of the key parameters in the SVR model. A multi-step sliding cross-validation method was employed to train the model, ultimately yielding the IKOA-SVR intelligent identification model for valve internal leakage quantification. Taking the main steam drain pipe valve as an example, a simulation case validation was carried out. The calculation example used Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE) and determination coefficient (R²) as performance evaluation metrics, and compared and analyzed the training and testing dataset using IKOA-SVR, KOA-SVR, Particle Swarm Optimization (PSO)-SVR, Random Search (RS)-SVR, Grid Search (GS)-SVR, and Bayesian Optimization (BO)-SVR methods, respectively. For the testing dataset, the MSE of IKOA-SVR is 0.65, RMSE is 0.81, MAE is 0.49, and MAPE is 0.0043, with the smallest values among the six methods. The R² of IKOA-SVR is 0.9998, with the largest value among the six methods. It indicated that IKOA-SVR can effectively solve problems such as getting stuck in local optima and overfitting during the optimization process. An Out-Of-Distribution (OOD) test was conducted for two scenarios: noise injection and Region-Holdout. The identification performance of all six methods decreased, with IKOA-SVR showing the smallest performance decline. The results show that IKOA-SVR has the strongest generalization ability and robustness, the best effect in improving fitting ability, the smallest identification error, the highest identification accuracy, and results closer to the actual value. The method presented in this paper provides an effective approach to solve the problem of intelligent identification of valve internal leakage in thermal power station. Full article

(This article belongs to the Topic Intelligent Optimization Algorithm: Theory and Applications)

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17 pages, 318 KB

Open AccessArticle

Influence of Marital and Parental Status on Public Reactions to Stuttering in Chile: A Socio-Demographic Study

by Yasna Sandoval, Carlos Rojas, Bárbara Farías, Gabriel Lagos, Ángel Roco-Videla, Arnaldo Carocca and Goncalo Leal

Int. J. Environ. Res. Public Health 2025, 22(11), 1662; https://doi.org/10.3390/ijerph22111662 (registering DOI) - 2 Nov 2025

Abstract

Stuttering is a communication disorder that significantly impacts individuals’ quality of life. This study examines public reactions towards stuttering within the Latin American context, specifically in Chile, using the Public Opinion Survey of Human Attributes-Stuttering. Data were collected from 400 adults, revealing that [...] Read more.

Stuttering is a communication disorder that significantly impacts individuals’ quality of life. This study examines public reactions towards stuttering within the Latin American context, specifically in Chile, using the Public Opinion Survey of Human Attributes-Stuttering. Data were collected from 400 adults, revealing that married individuals and parents exhibit heightened sensitivity and concern towards stuttering, especially regarding close family members. For instance, 56.86% of married respondents expressed worry about a stuttering sibling, contrasting sharply with only 27.18% of single respondents. Moreover, parents were notably anxious about stuttering in their family. This study underscores the significant role of marital status and parental responsibilities in shaping public attitudes towards stuttering. Additionally, it emphasizes the influence of family-centric values, advocating for the need for comprehensive educational initiatives to combat prevailing stigma towards individuals with stuttering. Full article

31 pages, 5397 KB

Open AccessArticle

Experimental and Analytical Evaluation of GFRP-Reinforced Concrete Bridge Barriers at the Deck–Wall Interface

by Hamidreza Khederzadeh, Khaled Sennah, Hamdy M. Afefy and Kousai Razouk

J. Compos. Sci. 2025, 9(11), 600; https://doi.org/10.3390/jcs9110600 (registering DOI) - 2 Nov 2025

Abstract

This study investigates the structural performance of TL-5 concrete bridge barriers reinforced with glass fiber-reinforced polymer (GFRP) bars at the critical deck–wall interface. Five full-scale barrier models were subjected to static load testing until failure. The wall reinforcement included four barriers with high- [...] Read more.

This study investigates the structural performance of TL-5 concrete bridge barriers reinforced with glass fiber-reinforced polymer (GFRP) bars at the critical deck–wall interface. Five full-scale barrier models were subjected to static load testing until failure. The wall reinforcement included four barriers with high- and standard-modulus GFRP bars using headed-end, bent, and hooked anchorage, and one with conventional steel reinforcement. The objective was to assess the load-bearing capacity, failure modes, and deformation behavior of GFRP-reinforced barriers with respect to the Canadian Highway Bridge Design Code (CHBDC) requirements. Results revealed that all GFRP-reinforced models achieved ultimate flexural capacities surpassing CHBDC design limits, with diagonal tension cracking at the corner joint emerging as the predominant failure mode. A set of new equations was developed to predict diagonal tension failure and determine minimum reinforcement ratios to mitigate such failure. Comparisons with experimental findings validated the proposed analytical approach. Among the configurations tested, barriers with headed-end high-modulus GFRP bars offered the most cost-effective and structurally sound solution. These findings support the incorporation of GFRP bars in bridge barrier design and establish a framework for future code development regarding GFRP-reinforced barrier systems. Full article

(This article belongs to the Special Issue Advanced Composite Materials from Natural and Synthetic Sources: Fabrication, Characterization and Practical Application, 3rd Edition)

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16 pages, 427 KB

Open AccessReview

Molecular Pathology of Pancreatic Ductal Adenocarcinoma

by Akram Shalaby, Navid Sadri and Yue Xue

Cancers 2025, 17(21), 3549; https://doi.org/10.3390/cancers17213549 (registering DOI) - 2 Nov 2025

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer that frequently presents at an advanced stage with limited effective treatment options and a dismal prognosis. It is a highly heterogenous disease driven by various genetic and epigenetic alterations. Recent advances in sequencing modalities have [...] Read more.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer that frequently presents at an advanced stage with limited effective treatment options and a dismal prognosis. It is a highly heterogenous disease driven by various genetic and epigenetic alterations. Recent advances in sequencing modalities have significantly improved our understanding of the genetics of PDAC, which could lead to promising and novel therapeutic strategies. In this review, we summarize the most up-to-date literature on the molecular landscape of PDAC and its precursor lesions, as well as recent advances in targeted therapy. Full article

(This article belongs to the Section Cancer Pathophysiology)

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22 pages, 827 KB

Open AccessArticle

Unilateral Resistance Training Strategies for Boosting Rehabilitation: An Expert Survey

by Ioana Mădălina Petre, Mircea Boșcoianu and Petronela Mocanu

J. Funct. Morphol. Kinesiol. 2025, 10(4), 425; https://doi.org/10.3390/jfmk10040425 (registering DOI) - 2 Nov 2025

Abstract

Objectives: This research paper proposes an innovative framework for developing adaptive and dedicated rehabilitation strategies based on the perceptions of specialists in sports rehabilitation (RT), sports training (AR) and with mixed expertise (RT+AR) regarding advanced resistance training methods, including Effort-Based Training (EBT-3/7), Cluster [...] Read more.

Objectives: This research paper proposes an innovative framework for developing adaptive and dedicated rehabilitation strategies based on the perceptions of specialists in sports rehabilitation (RT), sports training (AR) and with mixed expertise (RT+AR) regarding advanced resistance training methods, including Effort-Based Training (EBT-3/7), Cluster Training (CT), Rest-Pause Training (RPT) and Post-Activation Potentiation (PAP). The aim of this paper was to develop a tailored strategy for rehabilitation programs, grounded in a targeted selection of training methods, short-term periodization and exercises structured around key training variables such as frequency, intensity and volume. Methods: In order to reach this objective, a quantitative research method is proposed, aiming to identify the experts’ opinion on the way of managing and integrating Unilateral Resistance Training Exercise (URTE). Data processing and analysis were conducted by means of specific tests supplied by the SPSS Statistics for Windows (version 20.0, IBM Corp., Armonk, NY, USA)Results: The findings indicate that EBT-3/7 is perceived as the most effective method for rehabilitation with minimal injury risk, whereas CT and PAP are associated with performance benefits but higher perceived injury risk. RT+AR specialists reported more frequent use of these methods and higher perceived effectiveness. Additionally, they demonstrated superior operational and dynamic capabilities compared to single-domain specialists. Conclusions: According to specialists’ opinions, URTE is effective for post-injury rehabilitation, with combined rehabilitation and training expertise enhancing utilization, perceived effectiveness and implementation of personalized, performance-oriented strategies. Full article

(This article belongs to the Special Issue Strength Training and Performance Enhancement in Athletes, 3rd Edition)

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24 pages, 1005 KB

Open AccessArticle

Privacy-Preserving AI Collaboration on Blockchain Using Aggregate Signatures with Public Key Aggregation

by Mohammed Abdelhamid Nedioui, Ali Khechekhouche, Konstantinos Karampidis, Giorgos Papadourakis and Talal Guia

Appl. Sci. 2025, 15(21), 11705; https://doi.org/10.3390/app152111705 (registering DOI) - 2 Nov 2025

Abstract

The integration of artificial intelligence (AI) and blockchain technology opens new avenues for decentralized, transparent, and secure data-driven systems. However, ensuring privacy and verifiability in collaborative AI environments remains a key challenge, especially when model updates or decisions must be recorded immutably on-chain. [...] Read more.

The integration of artificial intelligence (AI) and blockchain technology opens new avenues for decentralized, transparent, and secure data-driven systems. However, ensuring privacy and verifiability in collaborative AI environments remains a key challenge, especially when model updates or decisions must be recorded immutably on-chain. In this paper, we propose a novel privacy-preserving framework that leverages an ElGamal-based aggregate signature scheme with aggregate public keys to enable secure, verifiable, and unlinkable multi-party contributions in blockchain-based AI ecosystems. This approach allows multiple AI agents or data providers to jointly sign model updates or decisions, producing a single compact signature that can be publicly verified without revealing the identities or individual public keys of contributors. The design is particularly well-suited to resource-constrained or privacy-sensitive applications such as federated learning in healthcare or finance. We analyze the security of the scheme under standard assumptions and evaluate its efficiency in different terms. The study and experimental results demonstrate the potential of our framework to enhance trust and privacy in AI collaborations over decentralized networks. Full article

(This article belongs to the Special Issue Blockchain Technologies: Trends, Challenges, Potentials and Applications)

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21 pages, 64275 KB

Open AccessArticle

Characterization on Mode-I/II Interlaminar Strength and Fracture Toughness of Co-Cured Fiber–Metal Laminates

by Mingjie Wang, Hongyi Hao, Qinghao Liu, Xinyue Miao, Ziye Lai, Tianqi Yuan, Guohua Zhu and Zhen Wang

Polymers 2025, 17(21), 2937; https://doi.org/10.3390/polym17212937 (registering DOI) - 2 Nov 2025

Abstract

This study systematically evaluates the mode-I (opening) and mode-II (shearing) interlaminar strength and fracture toughness of four co-cured fiber–metal laminates (FMLs): AL–CF (aluminum–carbon fiber fabric), AL–GF (aluminum–glass fiber fabric), AL–HC (aluminum–carbon/glass hybrid fabric), and AL–HG (aluminum–glass/carbon hybrid fabric). Epoxy adhesive films were interleaved [...] Read more.

This study systematically evaluates the mode-I (opening) and mode-II (shearing) interlaminar strength and fracture toughness of four co-cured fiber–metal laminates (FMLs): AL–CF (aluminum–carbon fiber fabric), AL–GF (aluminum–glass fiber fabric), AL–HC (aluminum–carbon/glass hybrid fabric), and AL–HG (aluminum–glass/carbon hybrid fabric). Epoxy adhesive films were interleaved between metal and composite plies to enhance interfacial bonding. Mode-I interlaminar tensile strength (ILTS) and mode-II interlaminar shear strength (ILSS) were measured using curved beam and short beam tests, respectively, while mode-I and mode-II fracture toughness (

G_{I c}

and

G_{I I c}

) were obtained from double cantilever beam (DCB) and end-notched flexure (ENF) tests. Across laminates, interlaminar tensile strength (ILTS) values lie in a narrow band of 31.6–31.8 MPa and interlaminar shear strength (ILSS) values in 41.0–41.9 MPa. The mode-I initiation (

G_{I c, i n i t}

) and propagation (

G_{I c, p r o p}

) toughnesses are 0.44–0.56 kJ/m² and 0.54–0.64 kJ/m², respectively, and the mode-II toughness (

G_{I I c}

) is 0.65–0.79 kJ/m². Scanning electron microscopy reveals that interlaminar failure localizes predominantly at the metal–adhesive interface, displaying river-line features under mode-I and hackle patterns under mode-II, whereas the adhesive–composite interface remains intact. Collectively, the results indicate that, under the present processing and test conditions, interlaminar strength and toughness are governed by the metal–adhesive interface rather than the composite reinforcement type, providing a consistent strength–toughness baseline for model calibration and interfacial design. Full article

(This article belongs to the Special Issue Advanced Fiber-Reinforced Polymer Composites: Design, Manufacturing, Characterization, and Application)

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14 pages, 1919 KB

Open AccessArticle

Crunchiness of Osmotically Dehydrated Freeze-Dried Strawberries

by Agata Marzec, Jolanta Kowalska, Marcin Korolczuk and Hanna Kowalska

Appl. Sci. 2025, 15(21), 11704; https://doi.org/10.3390/app152111704 (registering DOI) - 2 Nov 2025

Abstract

Consumers prefer snacks that are tasty, healthy, and crunchy. However, optimizing crunchiness using sensory methods is time-consuming and expensive. Therefore, this paper proposes a new approach to measuring instrumental crunchiness. Whole strawberries of the “Honeoya” variety were osmotic dehydrated in a sucrose solution [...] Read more.

Consumers prefer snacks that are tasty, healthy, and crunchy. However, optimizing crunchiness using sensory methods is time-consuming and expensive. Therefore, this paper proposes a new approach to measuring instrumental crunchiness. Whole strawberries of the “Honeoya” variety were osmotic dehydrated in a sucrose solution or chokeberry juice concentrate for 1, 2, and 3 h before freeze-drying. Texture was analyzed using acoustic emission (AE) and a compression test. The crunchiness index was calculated taking into account the number of AE events and mechanical energy. The content of bioactive substances, water activity, and porosity of the freeze-dried products were also assessed. Freeze-dried fruits that were osmotically dehydrated in chokeberry juice concentrate were characterized by lower final water activity and higher content of bioactive substances, but their crunchiness was the lowest. The crunchiest, loudest, and least hard were freeze-dried strawberries osmotically dehydrated in the sucrose solution. The tested freeze-dried strawberries differed in the range of sound frequencies generated, which indicates a different cracking mechanism. Full article

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

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24 pages, 5791 KB

Open AccessArticle

AI-Driven Prediction of Building Energy Performance and Thermal Resilience During Power Outages: A BIM-Simulation Machine Learning Workflow

by Mohammad H. Mehraban, Shayan Mirzabeigi, Setare Faraji, Sameeraa Soltanian-Zadeh and Samad M. E. Sepasgozar

Buildings 2025, 15(21), 3950; https://doi.org/10.3390/buildings15213950 (registering DOI) - 2 Nov 2025

Abstract

Power outages during extreme heat events threaten occupant safety by exposing buildings to rapid indoor overheating. However, current building thermal resilience assessments rely mainly on physics-based simulations or IoT sensor data, which are computationally expensive and slow to scale. This study develops an [...] Read more.

Power outages during extreme heat events threaten occupant safety by exposing buildings to rapid indoor overheating. However, current building thermal resilience assessments rely mainly on physics-based simulations or IoT sensor data, which are computationally expensive and slow to scale. This study develops an Artificial Intelligence (AI)-driven workflow that integrates Building Information Modeling (BIM)-based residential models, automated EnergyPlus simulations, and supervised Machine Learning (ML) algorithms to predict indoor thermal trajectories and calculate thermal resilience against power failure events in hot seasons. Four representative U.S. residential building typologies were simulated across fourteen ASHRAE climate zones to generate 16,856 scenarios over 45.8 h of runtime. The resulting dataset spans diverse climates and envelopes and enables systematic AI training for energy performance and resilience assessment. It included both time-series of indoor thermal conditions and static thermal resilience metrics such as Passive Survivability Index (PSI) and Weighted Unmet Thermal Performance (WUMTP). Trained on this dataset, ensemble boosting models, notably XGBoost, achieved near-perfect accuracy with an average R² of 0.9994 and nMAE of 1.10% across time-series (indoor temperature, humidity, and cooling energy) recorded every 3 min for a 5-day simulation period with 72 h of outage. It also showed strong performance for predicting static resilience metrics, including WUMTP (R² = 0.9521) and PSI (R² = 0.9375), and required only 1148 s for training. Feature importance analysis revealed that windows contribute 74.3% of the envelope-related influence on passive thermal response. This study demonstrates that the novelty lies not in the algorithm itself, but in applying the model to resilience context of power outages, to reduce computations from days to seconds. The proposed workflow serves as a scalable and accurate tool not only to support resilience planning, but also to guide retrofit prioritization and inform building codes. Full article

(This article belongs to the Special Issue Digital Transformation and Resilience in Construction Management: Technologies, Strategies, and Applications)

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17 pages, 306 KB

Open AccessArticle

A Structural Study of Generalized

[m, C]

-Symmetric Extension Operators

by Sid Ould Ahmed Mahmoud, El Moctar Ould Beiba, Sid Ahmed Ould Beinane and Nura Alotaibi

Symmetry 2025, 17(11), 1836; https://doi.org/10.3390/sym17111836 (registering DOI) - 2 Nov 2025

Abstract

This manuscript introduces and investigates a new class of operators, termedn-quasi-

[m, C]

-symmetric operators, which generalize and extend the existing notions of

[m, C]

-symmetric and n-quasi-

[m, C]

-isometric [...] Read more.

This manuscript introduces and investigates a new class of operators, termedn-quasi-

[m, C]

-symmetric operators, which generalize and extend the existing notions of

[m, C]

-symmetric and n-quasi-

[m, C]

-isometric operators. Specifically, given a conjugation

C

on a Hilbert space, an operator

Q \in B (K)

is said to be n-quasi-

[m, C]

-symmetric if it satisfies the relation

Q^{* n} (\sum_{0 \leq j \leq m} {(- 1)}^{j} (\binom{m}{j}) C Q^{m - j} C Q^{j}) Q^{n} = 0

. Our study systematically explores the algebraic properties and structural characterization of n-quasi-

[m, C]

-symmetric operators through matrix representations, providing a deeper understanding of their internal structure. Moreover, we establish sufficient conditions under which the powers and products of such operators inherit the n-quasi-

[m, C]

-symmetric property. Additionally, we investigate the tensor products of n-quasi-

[m, C]

-symmetric operators. Finally, we identify conditions that distinguish n-quasi-

[m, C]

-symmetric operators from n-quasi-

[m - 1; C]

-symmetric operators. Full article

(This article belongs to the Section Mathematics)

16 pages, 246 KB

Open AccessArticle

The Cardio-Oncology Patients—What They Know and What They Should Know

by Aneta Klotzka, Barbara Gawłowska and Ewelina Chawłowska

Curr. Oncol. 2025, 32(11), 613; https://doi.org/10.3390/curroncol32110613 (registering DOI) - 2 Nov 2025

Abstract

The growing number of patients after oncological treatment makes knowledge about potential cardiovascular complications of cancer therapy particularly important. Early recognition of symptoms enables the rapid initiation of appropriate therapy and improves outcomes. Education in this field increases awareness of the need for [...] Read more.

The growing number of patients after oncological treatment makes knowledge about potential cardiovascular complications of cancer therapy particularly important. Early recognition of symptoms enables the rapid initiation of appropriate therapy and improves outcomes. Education in this field increases awareness of the need for regular cardiology follow-up and adherence to health recommendations. It is advisable for patient education on the risk of cardiotoxicity to be included during visits with both the oncologist and the cardiologist. A self-developed questionnaire was used. It consisted of 40 questions (including 16 from the Health Behavior Scale) and 8 additional sociodemographic questions. An anonymous questionnaire was completed by 243 patients of the cardio-oncology outpatient clinic operating within the Department of Cardiology in Poland. In the survey conducted, patients were asked to define the concept of cardio-oncology; only 23.5% of respondents provided a correct answer. The highest level of awareness was observed among individuals under the age of 40 (p = 0.001) and of higher education levels (p < 0.001). Better knowledge was also noted among respondents who recalled being informed by their doctor about complications (p < 0.001) and among those who had undergone cardiological examinations (p = 0.005). The findings further revealed that respondents who recognized the importance of cardiac monitoring following therapy were significantly more likely to engage in health behaviors (p < 0.001). Particularly concerning was the limited communication regarding cardiovascular risks associated with cancer treatment. Only 24.3% of patients reported having been informed (or recalled being informed) by their oncologist about the potential cardiotoxic effects of anticancer drugs. Approximately one-third of respondents (32%) had not been referred for a cardiology consultation during their cancer treatment. Despite this, an overwhelming majority (95.5%) expressed the belief that a cardiologist should assess all oncology patients. These findings underscore critical deficiencies in patients’ education within the field of cardio-oncology. Health education interventions during oncological follow-up visits are needed Full article

35 pages, 1304 KB

Open AccessReview

Probiotic Potential of Traditional and Emerging Microbial Strains in Functional Foods: From Characterization to Applications and Health Benefits

by Chijioke Christopher Uhegwu and Christian Kosisochukwu Anumudu

Microorganisms 2025, 13(11), 2521; https://doi.org/10.3390/microorganisms13112521 (registering DOI) - 2 Nov 2025

Abstract

Global consumer demand for probiotic-enriched functional foods has increased as consumers become increasingly aware of the connection between what they eat and its role in their long-term health. Compared with conventional foods that primarily deliver fundamental nutrients, functional foods include biologically active compounds [...] Read more.

Global consumer demand for probiotic-enriched functional foods has increased as consumers become increasingly aware of the connection between what they eat and its role in their long-term health. Compared with conventional foods that primarily deliver fundamental nutrients, functional foods include biologically active compounds capable of influencing physiological processes. While traditionally used probiotic strains like Lactobacillus and Bifidobacterium are still at the center of this trend, there is growing interest in the exploration of emerging and novel microbial candidates that harbor new functional properties. This review addresses the characterization, modes of action, technological limitations, regulatory guidelines, and prospective health benefits of new probiotic strains in functional foods. The review further highlights the need for precise strain selection, novel encapsulation technologies for viability, and strict safety assessments in accordance with EFSA’s QPS (Qualified Presumption of Safety) and the United States FDA GRAS (Generally Recognized As Safe) specifications. Current research focuses on the classical benefits of probiotics, including gut microbiota modulation, immunomodulation, antimicrobial activity, lowering of cholesterol, and mental health. However, long-term clinical validation, strain specificity, personalized application, and effective communication to consumers are some areas where gaps remain. Addressing these challenges through the incorporation of omics technologies, synthetic biology, and more detailed microbiome–host interaction studies will be the key to unlocking the full potential of next-generation probiotics and sustaining consumer trust in this emerging market. Full article

(This article belongs to the Special Issue Microbial Safety and Beneficial Microorganisms in Foods)

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19 pages, 10756 KB

Open AccessArticle

Solution of Fraction Navier–Stokes Equation Using Homotopy Analysis Method

by Hamza Mihoubi and Awatif Muflih Alqahtani

AppliedMath 2025, 5(4), 148; https://doi.org/10.3390/appliedmath5040148 (registering DOI) - 2 Nov 2025

Abstract

In the present study, we aimed to derive analytical solutions of the homotopy analysis method (HAM) for the time-fractional Navier–Stokes equations in cylindrical coordinates in the form of a rapidly convergent series. In this work, we explore the time-fractional Navier–Stokes equations by replacing [...] Read more.

In the present study, we aimed to derive analytical solutions of the homotopy analysis method (HAM) for the time-fractional Navier–Stokes equations in cylindrical coordinates in the form of a rapidly convergent series. In this work, we explore the time-fractional Navier–Stokes equations by replacing the standard time derivative with the Katugampola fractional derivative, expressed in the Caputo form. The homotopy analysis method is then employed to obtain an analytical solution for this time-fractional problem. The convergence of the proposed method to the solution is demonstrated. To validate the method’s accuracy and effectiveness, two examples of time-fractional Navier–Stokes equations modeling fluid flow in a pipe are presented. A comparison with existing results from previous studies is also provided. This method can be used as an alternative to obtain analytic and approximate solutions of different types of fractional differential equations applied in engineering mathematics. Full article

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27 pages, 915 KB

Open AccessReview

Sex-Specific Molecular and Genomic Responses to Endocrine Disruptors in Aquatic Species: The Central Role of Vitellogenin

by Faustina Barbara Cannea, Cristina Porcu, Maria Cristina Follesa and Alessandra Padiglia

Genes 2025, 16(11), 1317; https://doi.org/10.3390/genes16111317 (registering DOI) - 2 Nov 2025

Abstract

Endocrine-disrupting chemicals (EDCs) are widespread contaminants that interfere with hormonal signaling and compromise reproductive success in aquatic organisms. Vitellogenin (VTG) is one of the most widely established biomarkers of estrogenic exposure, especially in males and juveniles. However, evidence from multi-omics studies indicates that [...] Read more.

Endocrine-disrupting chemicals (EDCs) are widespread contaminants that interfere with hormonal signaling and compromise reproductive success in aquatic organisms. Vitellogenin (VTG) is one of the most widely established biomarkers of estrogenic exposure, especially in males and juveniles. However, evidence from multi-omics studies indicates that VTG induction occurs within broader transcriptional and regulatory networks, involving genes such as cyp19a1 (aromatase), cyp1a (cytochrome P4501A), and other stress-responsive genes, underscoring the complexity of endocrine disruption. This review focuses on nuclear receptor isoforms, including estrogen receptor alpha (ERα), estrogen receptor beta (ERβ), and androgen receptor (AR) variants. We examine the diversification of vtg gene repertoires across teleost genomes and epigenetic mechanisms, such as DNA methylation and microRNAs, that modulate sex-dependent sensitivity. In addition, we discuss integrative approaches that combine VTG with transcriptomic, epigenetic, and histological endpoints. Within the Adverse Outcome Pathway (AOP) and weight-of-evidence (WoE) frameworks, these strategies provide mechanistic links between receptor activation and reproductive impairment. Finally, we outline future directions, focusing on the development of sex-specific biomarker panels, the integration of omics-based data with machine learning, and advances in ecogenomics. Embedding molecular responses into ecological and regulatory contexts will help bridge mechanistic insights with environmental relevance and support sustainability goals such as SDG 14 (Life Below Water). Full article

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

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17 pages, 716 KB

Open AccessArticle

Retrospective Trial on Cetuximab Plus Radiotherapy in Elderly Patients with Head and Neck Squamous Cell Cancer

by Morena Fasano, Francesco Perri, Mario Pirozzi, Chiara Lucrezia Deantoni, Davide Valsecchi, Alessio Cirillo, Raffaele Addeo, Pasquale Vitale, Francesca De Felice, Paolo Tralongo, Stefano Farese, Beatrice Ruffilli, Fabrizio Romano, Mathilda Guizzardi, Leone Giordano, Monica Pontone, Maria Luisa Marciano, Fabiana Raffaella Rampetta, Francesco Longo, Fortunato Ciardiello and Aurora Mirabile Show full author list Hide full author list

Cancers 2025, 17(21), 3550; https://doi.org/10.3390/cancers17213550 (registering DOI) - 2 Nov 2025

Abstract

Background: A wide percentage (25–40%) of patients affected by head and neck squamous cell carcinoma (HNSCC) are over 70 years old, and they present with different characteristics if compared to younger patients. Elderly patients often receive less intensive, non-surgical, and non-multimodal treatments. Although [...] Read more.

Background: A wide percentage (25–40%) of patients affected by head and neck squamous cell carcinoma (HNSCC) are over 70 years old, and they present with different characteristics if compared to younger patients. Elderly patients often receive less intensive, non-surgical, and non-multimodal treatments. Although age does not mean frailty, the elderly are at a higher risk of developing toxicity. In fact, several studies enrolling patients treated with cisplatin + radiotherapy (CISPLATIN + RT) or cetuximab + radiotherapy (Cet + RT) showed reduced efficacy over 65 years. Methods: We conducted a multicenter retrospective analysis in patients with Locally Advanced HNSCC aged over 65 years, who underwent Cet-RT, diagnosed in the period between 2017 and 2024. The primary endpoint was to describe Overall Survival (OS), the secondary endpoints were Progression Free Survival (PFS) and the percentage and type of Adverse Events (AEs). Patients received a geriatric assessment using the G8 questionnaire. Results: Data regarding Eighty-Two (82) patients were analyzed, median age was 74 years (range 65–84), most patients had oral cavity (26.8%) and laryngeal cancer (37.8%). Fifty-six point one (56.1%) of patients were smokers, and 17.1% reported alcohol consumption. All patients completed radiotherapy, and 80.5% of them developed AEs, which in 25.6% of cases were G3–4 toxicities. No relationship was found between G3–4 AEs and age (p = 0.596), G8score < 14 (p = 0.804), and smoking (p = 0.245)/drinking habits (p = 0.341). Median OS was 58 months, with a slightly non-significant positive trend in OS for patients who were non-smokers and those who did not develop G3–4 AEs (p = 0.786 and 0.799, respectively). Association between folliculitis and OS was statistically significant (p = 0.001). Conclusions: In elderly patients, Cet-RT represents a feasible, well-tolerated option, although further prospective studies are needed. Full article

(This article belongs to the Section Methods and Technologies Development)

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27 pages, 4682 KB

Open AccessArticle

Expression Profile and Clinical Relevance of ADAR Family Genes in Head and Neck Squamous Cell Carcinoma

by Tomasz Kolenda, Piotr Białas, Paulina Poter, Marlena Janiczek-Polewska, Anna Zapłata, Kacper Guglas, Patrycja Mantaj, Anna Przybyła, Urszula Kazimierczak, Ewa Leporowska, Zefiryn Cybulski and Anna Teresiak

Genes 2025, 16(11), 1316; https://doi.org/10.3390/genes16111316 (registering DOI) - 2 Nov 2025

Abstract

Background: ADAR1 (ADAR), ADAR2 (ADARB1), and ADAR3 (ADARB2) are deaminase adenosine RNA-specific enzymes that play a significant role in RNA metabolism. ADAR1 (ADAR) and ADAR2 (ADARB1) catalyze A-to-I editing and ADAR3 (ADARB2 [...] Read more.

Background: ADAR1 (ADAR), ADAR2 (ADARB1), and ADAR3 (ADARB2) are deaminase adenosine RNA-specific enzymes that play a significant role in RNA metabolism. ADAR1 (ADAR) and ADAR2 (ADARB1) catalyze A-to-I editing and ADAR3 (ADARB2) plays a regulatory role. The role of these three genes still remains unknown in head and neck cancers (HNSCC). The aim of this study is to reveal the role of deaminase adenosine RNA-specific enzymes in pathomechanisms of HNSCC and to investigate their potential utility as diagnostic and/or prognostic biomarkers. Methods: The quantitative PCR analysis was conducted using RNA isolated from 22 pairs of matched tumor and adjacent normal tissues, 76 formalin-fixed paraffin-embedded (FFPE) tumor samples, and a panel of HNSCC cell lines (DOK, SCC-25, SCC-40, FaDu, and CAL-27). In parallel, transcriptomic and clinical data from the Cancer Genome Atlas HNSCC cohort were analyzed. Patients were stratified into high- and low-expression groups, and statistical assessments included overall survival and progression-free interval analyses, evaluation of gene expression in relation to clinicopathological parameters, correlation with other genes, and functional pathway exploration using gene set enrichment analysis. Results: ADARB2 was significantly downregulated in HNSCC tumor tissues compared to adjacent normal mucosa (p = 0.044), with discriminatory potential to distinguish malignant from non-malignant tissues (AUC = 0.692, p = 0.029). TCGA data confirmed ADAR (p < 0.0001) and ADARB1 (p < 0.0001) upregulation in tumors, while ADARB2 was markedly reduced (p = 0.04). Patients with high ADARB2 expression showed significantly longer overall survival (pa = 0.0121; pb = 0.0098), with a trend toward improved progression-free survival (pb = 0.0681). Subsite analysis revealed high ADAR expression correlated with poor OS in pharyngeal tumors (p < 0.05), whereas high ADARB2 expression was linked to improved DFS (pa = 0.0023, pb = 0.0047). GSEA indicated that low ADARB2 expression was enriched in oncogenic pathways, including Wnt/β-catenin (p = 0.006), MYC targets (p = 0.009), and TGF-β1 (p = 0.009). Conclusions: ADARB2 expression was significantly reduced in HNSCC tumor tissues compared to normal mucosa and demonstrated strong discriminatory power for distinguishing malignant from non-malignant samples. High ADARB2 expression was associated with markedly improved overall survival, whereas low expression correlated with enrichment of oncogenic pathways, including Wnt/β-catenin, Notch, and Hedgehog, consistent with a poorer clinical prognosis. These findings highlight ADARB2 as a promising diagnostic biomarker and independent prognostic factor in HNSCC. Full article

(This article belongs to the Section Human Genomics and Genetic Diseases)

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16 pages, 2708 KB

Open AccessArticle

Comparing Handcrafted Radiomics Versus Latent Deep Learning Features of Admission Head CT for Hemorrhagic Stroke Outcome Prediction

by Anh T. Tran, Junhao Wen, Gaby Abou Karam, Dorin Zeevi, Adnan I. Qureshi, Ajay Malhotra, Shahram Majidi, Niloufar Valizadeh, Santosh B. Murthy, Mert R. Sabuncu, David Roh, Guido J. Falcone, Kevin N. Sheth and Seyedmehdi Payabvash

BioTech 2025, 14(4), 87; https://doi.org/10.3390/biotech14040087 (registering DOI) - 2 Nov 2025

Abstract

Handcrafted radiomics use predefined formulas to extract quantitative features from medical images, whereas deep neural networks learn de novo features through iterative training. We compared these approaches for predicting 3-month outcomes and hematoma expansion from admission non-contrast head CT in acute intracerebral hemorrhage [...] Read more.

Handcrafted radiomics use predefined formulas to extract quantitative features from medical images, whereas deep neural networks learn de novo features through iterative training. We compared these approaches for predicting 3-month outcomes and hematoma expansion from admission non-contrast head CT in acute intracerebral hemorrhage (ICH). Training and cross-validation were performed using a multicenter trial cohort (n = 866), with external validation on a single-center dataset (n = 645). We trained multiscale U-shaped segmentation models for hematoma segmentation and extracted (i) radiomics from the segmented lesions and (ii) two latent deep feature sets—from the segmentation encoder and a generative autoencoder trained on dilated lesion patches. Features were reduced with unsupervised Non-Negative Matrix Factorization (NMF) to 128 per set and used—alone or in combination—for six machine-learning classifiers to predict 3-month clinical outcomes and (>3, >6, >9 mL) hematoma expansion thresholds. The addition of latent deep features to radiomics numerically increased model prediction performance for 3-month outcomes and hematoma expansion using Random Forest, XGBoost, Extra Trees, or Elastic Net classifiers; however, the improved accuracy only reached statistical significance in predicting >3 mL hematoma expansion. Clinically, these consistent but modest increases in prediction performance may improve risk stratification at the individual level. Nevertheless, the latent deep features show potential for extracting additional clinically relevant information from admission head CT for prognostication in hemorrhagic stroke. Full article

(This article belongs to the Special Issue Advances in Bioimaging Technology)

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26 pages, 707 KB

Open AccessReview

Application of Multispectral Imagery and Synthetic Aperture Radar Sensors for Monitoring Algal Blooms: A Review

by Vikash Kumar Mishra, Himanshu Maurya, Fred Nicolls and Amit Kumar Mishra

Phycology 2025, 5(4), 71; https://doi.org/10.3390/phycology5040071 (registering DOI) - 2 Nov 2025

Abstract

Water pollution is a growing concern for aquatic ecosystems worldwide, with threats like plastic waste, nutrient pollution, and oil spills harming biodiversity and impacting human health, fisheries, and local economies. Traditional methods of monitoring water quality, such as ground sampling, are often limited [...] Read more.

Water pollution is a growing concern for aquatic ecosystems worldwide, with threats like plastic waste, nutrient pollution, and oil spills harming biodiversity and impacting human health, fisheries, and local economies. Traditional methods of monitoring water quality, such as ground sampling, are often limited in how frequently and widely they can collect data. Satellite imagery is a potent tool in offering broader and more consistent coverage. This review explores how Multispectral Imagery (MSI) and Synthetic Aperture Radar (SAR), including polarimetric SAR (PolSAR), are utilised to monitor harmful algal blooms (HABs) and other types of aquatic pollution. It looks at recent advancements in satellite sensor technologies, highlights the value of combining different data sources (like MSI and SAR), and discusses the growing use of artificial intelligence for analysing satellite data. Real-world examples from places like Lake Erie, Vembanad Lake in India, and Korea’s coastal waters show how satellite tools such as the Geostationary Ocean Colour Imager (GOCI) and Environmental Sample Processor (ESP) are being used to track seasonal changes in water quality and support early warning systems. While satellite monitoring still faces challenges like interference from clouds or water turbidity, continued progress in sensor design, data fusion, and policy support is helping make remote sensing a key part of managing water health. Full article

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