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Recent Articles  

26 pages, 1770 KB  
Article
Advanced Steering Stability Controls for Autonomous Articulated Vehicles Based on Differential Braking
by Jesus Felez
Electronics 2026, 15(3), 610; https://doi.org/10.3390/electronics15030610 (registering DOI) - 30 Jan 2026
Abstract
Articulated vehicles are essential for global freight transportation but are highly susceptible to instability phenomena such as jackknifing, trailer sway, and rollover, particularly under high-speed or emergency maneuvers. These challenges become even more critical in the context of autonomous driving, where stability must [...] Read more.
Articulated vehicles are essential for global freight transportation but are highly susceptible to instability phenomena such as jackknifing, trailer sway, and rollover, particularly under high-speed or emergency maneuvers. These challenges become even more critical in the context of autonomous driving, where stability must be guaranteed without human intervention. Conventional systems like Electronic Stability Control (ESC) and Roll Stability Control (RSC) provide reactive interventions but lack predictive capability, while other advanced methods often address isolated objectives. To overcome these limitations, this paper proposes a Model Predictive Control (MPC)-based control strategy that integrates trajectory tracking, yaw stability, and longitudinal speed regulation within a unified optimization framework, using differential braking as the primary actuator. A dynamic model of a tractor–semitrailer combination was developed, and the proposed controller was validated through high-fidelity simulations under varying operating conditions, including speeds exceeding the critical threshold of 31.04 m/s. Results demonstrate that the MPC-based system effectively mitigates instability, reduces articulation angle and yaw rate deviations, and maintains accurate path tracking while proactively managing vehicle speed. These findings highlight MPC’s potential as a cornerstone technology for safe and reliable autonomous operation of articulated vehicles. Future work will focus on experimental validation and multi-actuator coordination to further enhance performance. Full article
(This article belongs to the Special Issue Digital Twins and Artificial Intelligence in Transportation Systems)
15 pages, 7858 KB  
Article
Dimensional Priming Reprograms Adipose-Derived Stromal Cells to Promote Pancreatic Cancer Progression
by Bo Han, Zhi Yang, Shuqing Zhao, Thomas Schmittgen, Jamel Ali and Ba Xuan Hoang
Cancers 2026, 18(3), 460; https://doi.org/10.3390/cancers18030460 (registering DOI) - 30 Jan 2026
Abstract
Background: The tumor microenvironment (TME) plays a central role in pancreatic ductal adenocarcinoma (PDAC) progression, yet how mechanical cues shape stromal cell behavior remains poorly defined. Here, we investigate how dimensional priming of adipose-derived stromal cells (ADSCs) alters their immunomodulatory functions and subsequent [...] Read more.
Background: The tumor microenvironment (TME) plays a central role in pancreatic ductal adenocarcinoma (PDAC) progression, yet how mechanical cues shape stromal cell behavior remains poorly defined. Here, we investigate how dimensional priming of adipose-derived stromal cells (ADSCs) alters their immunomodulatory functions and subsequent impact on PDAC growth. Methods: ADSCs were cultured under two-dimensional (2D) or three-dimensional (3D) conditions and evaluated using in vitro co-culture systems with PDAC organoids and in vivo xenograft models. Stromal phenotype, cytokine secretion, tumor growth, invasion, and immune cell infiltration were assessed. Results: ADSCs cultured in three-dimensional (3D) hydrogels exhibited reduced Caveolin-1 (CAV-1) expression and reprogramming toward a stress-adapted, CAF-like phenotype compared with two-dimensional (2D) cultures. In vitro, 2D-primed ADSCs constrained PDAC organoid growth, increased MMP-2 activity, and required direct cell–cell contact to suppress tumor viability. By contrast, 3D-primed ADSCs preserved organoid structure but markedly enhanced tumor cell migration through soluble factors, accompanied by increased IL-6 and TNF-α and reduced IL-10 secretion during co-culture. In vivo, 3D-primed ADSCs promoted the largest tumors with aggressive invasion and loss of Col-Tgel containment associated with tumor expansion, whereas 2D-primed ADSCs suppressed tumor growth and maintained gel boundaries. Immunohistochemistry confirmed elevated Ki-67 in tumors containing 3D-primed ADSCs, while macrophage infiltration (F4/80+) was highest in 2D-primed tumors and lowest in 3D-primed tumors. Conclusions: Dimensional priming fundamentally reprograms ADSC phenotype and alters their stromal–immune interactions, generating a tumor-permissive state that accelerates PDAC progression. These findings identify mechanical cues as critical regulators of stromal plasticity and highlight dimensional priming as a potentially targetable axis within the PDAC microenvironment. Full article
(This article belongs to the Special Issue Advances in Cellular Heterogeneity and Plasticity in the Tumor Microenvironment)
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14 pages, 13741 KB  
Article
Visual Screening of Genetic Polymorphisms in eae Gene of Escherichia coli O157:H7 with Single-Nucleotide Resolution by ARMS-PCR-Mediated Lateral Flow Strip
by Noor Fatima, Liangliang Jiang, Siying Sun, Li Yao, Yubo Peng, Daoli Chen and Wei Chen
Sensors 2026, 26(3), 907; https://doi.org/10.3390/s26030907 (registering DOI) - 30 Jan 2026
Abstract
Development of rapid, precise and fieldable detection methods for foodborne pathogens is one of the essential requirements in food safety and public health. In this research, the single-nucleotide polymorphisms (SNPs) in the eae gene of Escherichia coli O157:H7 are well visually identified with [...] Read more.
Development of rapid, precise and fieldable detection methods for foodborne pathogens is one of the essential requirements in food safety and public health. In this research, the single-nucleotide polymorphisms (SNPs) in the eae gene of Escherichia coli O157:H7 are well visually identified with the designed amplification refractory mutation system–polymerase chain reaction (ARMS-PCR) mediated lateral flow strip (LFS). Allele-specific primers were designed and optimized to discriminate the mutant-type genes from wild-type genes with single-nucleotide resolution in a simple visual format. The single-nucleotide variation in the eae gene could be easily differentiated by the observation of an optical signal on the T line of the LFS without any devices. Assay performance results show that it has a high sensitivity and specificity with the single-nucleotide differentiation ratio as low as 0.1%. This genetic polymorphisms screening performance could enumerate complex genetic variation into a simple and direct yes/no readout, highlighting the ultra-easy SNP screening mode and the simplicity of the result output for practical applications. This ARMS-PCR mediated LFS offers a straightforward, swift, and economical strategy for SNP identification with great potential for use in evolution of bacterial resistance genes and viral evolution under different environmental stresses. Full article
(This article belongs to the Special Issue Nucleic Acid-Based Biosensors for Molecular Diagnostics)
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16 pages, 12361 KB  
Article
Comparison of Clinical Performance Between Digital Breast Tomosynthesis and MammouS-N
by Sung Ui Shin, Mijung Jang, Bo La Yun, Su Min Cho, Yoon Yeong Choi, Bohyoung Kim, Min Jung Kim and Sun Mi Kim
Tomography 2026, 12(2), 17; https://doi.org/10.3390/tomography12020017 (registering DOI) - 30 Jan 2026
Abstract
Background/Objectives: We compared the visibility of breast cancer using the newly developed standing automated breast ultrasound system (MammouS-N) and digital breast tomosynthesis (DBT), and identified factors influencing lesion visibility. Methods: We prospectively enrolled 100 women (mean age: 51.6 years; range: 26–76 [...] Read more.
Background/Objectives: We compared the visibility of breast cancer using the newly developed standing automated breast ultrasound system (MammouS-N) and digital breast tomosynthesis (DBT), and identified factors influencing lesion visibility. Methods: We prospectively enrolled 100 women (mean age: 51.6 years; range: 26–76 years) who were diagnosed with breast cancer and were scheduled to undergo DBT between January and July 2024. They underwent DBT and an ultrasound on the same day. Two radiologists evaluated the visibility scores (0–5) of lesions corresponding to biopsy-confirmed breast cancers identified using magnetic resonance imaging. The Wilcoxon signed-rank test was used to compare the visibility scores of cancers identified on DBT and/or MammouS-N images. Results: Among the 100 women, invasive ductal carcinoma was the most common malignancy (73%). DBT findings included negative findings (7%), masses (46%), masses with calcification (29%), calcifications only (15%), and architectural distortions (3%). On MammouS-N ultrasound, most lesions were classified as masses (93%), whereas 7% were non-mass lesions. For Reviewer 1, MammouS-N demonstrated significantly higher visibility scores (higher scores: 26 on MammouS-N, seven on DBT; equal scores: 67, z = −3.234, p = 0.001). For Reviewer 2, the two modalities showed no significant difference in visibility (higher scores: 27 on MammouS-N, 28 on DBT, equal scores: 45, z = −0.040, p = 0.968). Noncalcified lesions that were obscured on DBT were better visualized on MammouS-N (p < 0.001) by both reviewers. Conclusions: MammouS-N holds promise as an imaging modality complementary to DBT in women with dense breast tissue, particularly for non-calcified lesion detection. Full article
(This article belongs to the Section Cancer Imaging)
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16 pages, 696 KB  
Article
Impact of Comorbid Generalized Anxiety Disorder on rTMS/iTBS Clinical Outcomes in Major Depression: A Multicenter Registry-Based Observational Study
by Yoshihiro Noda, Ryota Osawa, Yuya Takeda, Keiko Fujita, Takumi Tsuji and Ryosuke Kitahata
J. Pers. Med. 2026, 16(2), 68; https://doi.org/10.3390/jpm16020068 (registering DOI) - 30 Jan 2026
Abstract
Background: Major depressive disorder (MDD) is often accompanied by generalized anxiety disorder (GAD), a comorbidity linked to greater illness burden and potentially poorer outcomes. Repetitive transcranial magnetic stimulation (rTMS) and intermittent theta-burst stimulation (iTBS) are established treatments for MDD, yet the impact of [...] Read more.
Background: Major depressive disorder (MDD) is often accompanied by generalized anxiety disorder (GAD), a comorbidity linked to greater illness burden and potentially poorer outcomes. Repetitive transcranial magnetic stimulation (rTMS) and intermittent theta-burst stimulation (iTBS) are established treatments for MDD, yet the impact of comorbid GAD and concomitant medications remains unclear. This study aimed to compare rTMS/iTBS treatment outcomes between patients with MDD with and without comorbid GAD, and to examine the association between concomitant psychotropic medication use, stimulation protocol, and treatment response in a real-world clinical setting. Methods: We conducted a retrospective observational analysis using registry data from 108 patients (MDD + GAD: n = 36; MDD only: n = 72). Patients received either Left-iTBS or Right-rTMS. Baseline severity, percentage change in Montgomery–Åsberg Depression Rating Scale (MADRS) and Hamilton Depression Rating Scale (HAMD-17) scores, response, and remission were assessed. Logistic and linear regression models adjusted for age, sex, and baseline severity were applied. Sensitivity analyses stratified by stimulation protocol and benzodiazepine (BDZ) use were performed. Results: Baseline severity did not differ between groups. MADRS reduction was numerically lower in the comorbid GAD group (48.3% vs. 52.7%, p = 0.09), whereas HAMD-17 reduction was comparable. Response and remission rates did not differ significantly. Medication use and stimulation protocol did not show statistically significant independent associations with outcomes. Sensitivity analyses confirmed equivalent outcomes between Left-iTBS and Right-rTMS. BDZ users showed a non-significant trend toward lower MADRS improvement and remission. Conclusions: rTMS/iTBS produced substantial clinical improvement and was well tolerated in both patients with MDD and those with MDD comorbid with GAD. Although comorbid anxiety showed a modest tendency to attenuate MADRS score reduction, overall response and remission rates were comparable between groups. Neither concomitant medications nor stimulation protocol significantly affected treatment outcomes, while the potential influence of BDZ exposure warrants further investigation. Full article
(This article belongs to the Special Issue Depression and Anxiety: Recent Advances in Personalized Treatment and Management)
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22 pages, 1703 KB  
Article
Building Sustainable Supply Chain Resilience Through Digitalisation and Circular Practices: Evidence from Emerging Economies
by Puja Sunil Pawar and Bayan A. Alsedais
Sustainability 2026, 18(3), 1393; https://doi.org/10.3390/su18031393 (registering DOI) - 30 Jan 2026
Abstract
Amid rising climate risks, geopolitical uncertainty, and global supply disruptions, strengthening sustainable supply chain resilience has become a critical policy priority for emerging economies. This study scrutinises how digitalisation and circular-economy practices jointly shape national-level supply chain resilience and sustainability performance. Using a [...] Read more.
Amid rising climate risks, geopolitical uncertainty, and global supply disruptions, strengthening sustainable supply chain resilience has become a critical policy priority for emerging economies. This study scrutinises how digitalisation and circular-economy practices jointly shape national-level supply chain resilience and sustainability performance. Using a balanced panel of 32 emerging economies from 2010 to 2023, the analysis draws on the Resource-Based View and Dynamic Capability Theory to test a serial mediation framework linking digitalisation, circularity, resilience, and sustainability. Fixed-effects panel regressions, mediation analysis, and Structural Equation Modelling (SEM) are employed using internationally comparable indicators from the World Bank, OECD, UN SDG Database, and UNIDO. The results show that digitalisation is positively associated with circular-economy adoption and supply chain resilience, while circularity further fortifies resilience. Resilient supply chains, in turn, are strongly associated with improved sustainability performance. The serial mediation results propose that sustainability outcomes emerge through a cumulative capability-building pathway rather than isolated technological effects. The findings highlight the importance of integrated digital and circular policy frameworks for enhancing resilience and advancing sustainable development in emerging economies. Full article
(This article belongs to the Special Issue Innovations in Sustainable and Resilient Supply Chain and Logistics Management)
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24 pages, 2311 KB  
Article
Performance Evaluation of Cross-Chain Systems Based on Notary Mechanism
by Xingshuo Song, Peng Chen and Chengguo E
Sustainability 2026, 18(3), 1389; https://doi.org/10.3390/su18031389 (registering DOI) - 30 Jan 2026
Abstract
The application of blockchain technology in large-scale sustainable scenarios requires advancement. Therefore, high-performance cross-chain infrastructure is essential for domains like green supply chain management and peer-to-peer renewable energy trading. This study proposes an integrated modeling framework, whose core innovation is the combination of [...] Read more.
The application of blockchain technology in large-scale sustainable scenarios requires advancement. Therefore, high-performance cross-chain infrastructure is essential for domains like green supply chain management and peer-to-peer renewable energy trading. This study proposes an integrated modeling framework, whose core innovation is the combination of Phase-Type (PH) distribution, the GI/PH/1 queuing model, and quasi-birth-and-death (QBD) process theory to systematically describe the multi-stage service and dynamic interactions in a notary-based cross-chain system. This framework overcomes the limitations of traditional models that rely on oversimplified service assumptions. By utilizing matrix-analytic methods, it enables the precise quantification of key performance metrics, such as system throughput, response time, and rejection rate. This research provides a unified, scalable theoretical tool for cross-chain performance evaluation and establishes a methodological foundation for optimizing system resource allocation and sustainable infrastructure design. Full article
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40 pages, 581 KB  
Review
A Survey of AI-Enabled Predictive Maintenance for Railway Infrastructure: Models, Data Sources, and Research Challenges
by Francisco Javier Bris-Peñalver, Randy Verdecia-Peña and José I. Alonso
Sensors 2026, 26(3), 906; https://doi.org/10.3390/s26030906 (registering DOI) - 30 Jan 2026
Abstract
Rail transport is central to achieving sustainable and energy-efficient mobility, and its digitalization is accelerating the adoption of condition-based maintenance (CBM) strategies. However, existing maintenance practices remain largely reactive or rely on limited rule-based diagnostics, which constrain safety, interoperability, and lifecycle optimization. This [...] Read more.
Rail transport is central to achieving sustainable and energy-efficient mobility, and its digitalization is accelerating the adoption of condition-based maintenance (CBM) strategies. However, existing maintenance practices remain largely reactive or rely on limited rule-based diagnostics, which constrain safety, interoperability, and lifecycle optimization. This survey provides a comprehensive and structured review of Artificial Intelligence techniques applied to the preventive, predictive, and prescriptive maintenance of railway infrastructure. We analyze and compare machine learning and deep learning approaches—including neural networks, support vector machines, random forests, genetic algorithms, and end-to-end deep models—applied to parameters such as track geometry, vibration-based monitoring, and imaging-based inspection. The survey highlights the dominant data sources and feature engineering techniques, evaluates the model performance across subsystems, and identifies research gaps related to data quality, cross-network generalization, model robustness, and integration with real-time asset management platforms. We further discuss emerging research directions, including Digital Twins, edge AI, and Cyber–Physical predictive systems, which position AI as an enabler of autonomous infrastructure management. This survey defines the key challenges and opportunities to guide future research and standardization in intelligent railway maintenance ecosystems. Full article
(This article belongs to the Special Issue Artificial Intelligence in Intelligent Transportation Systems and Traffic Control for Smart Cities)
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16 pages, 449 KB  
Review
Applications of Food-Associated Lactobacillaceae in Fermented Foods, Health, and Emerging Biotechnologies
by Shazia Pathan, Veronika Karlegan and David Q. Shih
Fermentation 2026, 12(2), 75; https://doi.org/10.3390/fermentation12020075 (registering DOI) - 30 Jan 2026
Abstract
The family Lactobacillaceae, reclassified in 2020 into 25 genera comprising 261 species, remains one of the most extensively studied groups of lactic acid bacteria (LAB) due to its wide distribution in fermented products, commensal presence in the gastrointestinal tract, and studied health [...] Read more.
The family Lactobacillaceae, reclassified in 2020 into 25 genera comprising 261 species, remains one of the most extensively studied groups of lactic acid bacteria (LAB) due to its wide distribution in fermented products, commensal presence in the gastrointestinal tract, and studied health effects. Long classified as “generally recognized as safe (GRAS)” by the U.S. Food and Drug Administration (FDA), these organisms not only contribute to the flavor, texture, and preservation of fermented foods and beverages but also provide important health benefits as probiotics. Their metabolic versatility allows them to produce lactic acid, bacteriocins, and other bioactive compounds that inhibit pathogenic microorganisms and enhance food quality. This review provides a comprehensive overview of the functional roles of members of the Lactobacillaceae family in the context of the food matrix in fermentation, health, and biotechnology, and examines recent advances in functional genomics, metabolomics, and extracellular vesicle research to highlight future directions for leveraging these microorganisms in sustainable and innovative applications. Full article
(This article belongs to the Special Issue Application of Lactobacillus in Fermented Food and Beverages, 2nd Edition)
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20 pages, 1568 KB  
Article
Accelerated Droplet Routing on MEDA Biochips Considering Shape-Dependent Velocity Models Through Guidance and Lower-Bound Constraints
by Yuta Hamachiyo, Chiharu Shiro, Hiroki Nishikawa, Hiroyuki Tomiyama and Shigeru Yamashita
Appl. Sci. 2026, 16(3), 1421; https://doi.org/10.3390/app16031421 (registering DOI) - 30 Jan 2026
Abstract
Digital microfluidic biochips are widely used for automated biochemical and diagnostic applications such as molecular analysis, immunoassays, and point-of-care testing. Among them, micro-electrode-dot-array (MEDA) biochips enable fine-grained droplet manipulation with shape-dependent velocity, which significantly increases routing flexibility but also computational complexity. This work [...] Read more.
Digital microfluidic biochips are widely used for automated biochemical and diagnostic applications such as molecular analysis, immunoassays, and point-of-care testing. Among them, micro-electrode-dot-array (MEDA) biochips enable fine-grained droplet manipulation with shape-dependent velocity, which significantly increases routing flexibility but also computational complexity. This work proposes an efficient droplet routing method for MEDA biochips that reduces computational time while maintaining or improving solution quality. The proposed method introduces a guidance constraint that consistently directs droplets toward the target cell and integrates a solver-friendly model with a tight lower-bound design. Experimental results demonstrate that, for instances solvable by the existing method, the proposed method achieves comparable or better Routing time while reducing Solution-finding time by 72.3%. Moreover, the Solution-finding rate improves from 33.3% to 85.3% over all problem instances. Notably, for instances that cannot be solved within the time limit by the existing method, the proposed method successfully finds optimal solutions in 72.7% of the cases. These results indicate that the proposed method enables faster solution discovery, and extends solvability to previously intractable routing problems. Full article
(This article belongs to the Section Applied Biosciences and Bioengineering)
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11 pages, 282 KB  
Article
Exploring the Link Between Religiosity and COVID-19 Vaccination Attitudes in Romania
by Darie Cristea, Dragoș-Georgian Ilie and Irina Zamfirache
Societies 2026, 16(2), 46; https://doi.org/10.3390/soc16020046 (registering DOI) - 30 Jan 2026
Abstract
This study investigates the relationship between religiosity and attitudes toward COVID-19 vaccination in Romania using nationally representative survey data from the Barometer of Religious Life (December 2021). Five survey items measuring religious beliefs and practices were used to construct a Religious Practice Index, [...] Read more.
This study investigates the relationship between religiosity and attitudes toward COVID-19 vaccination in Romania using nationally representative survey data from the Barometer of Religious Life (December 2021). Five survey items measuring religious beliefs and practices were used to construct a Religious Practice Index, whose reliability and one-dimensionality were confirmed through Cronbach’s Alpha and factor analysis. Correlation analysis revealed a small but statistically significant negative association between religiosity and vaccination acceptance (r = −0.106, p = 0.001). Binary logistic regression further indicated that higher religiosity, younger age, lower income, and rural residence were significant predictors of reduced vaccination likelihood, while older age, higher income, and urban residence were associated with greater acceptance. Nevertheless, the model explained only 9.3% of the variance and correctly classified 64.4% of cases, suggesting modest predictive power. These findings indicate that religiosity influences vaccination attitudes but does not serve as a dominant predictor, highlighting the importance of other additional factors that were beyond the scope of this analysis and were not measured. Full article
19 pages, 1284 KB  
Article
Phosphorus Use Efficiency and Canopy Spectral Reflectance of Alfalfa Fertilized with Aquaculture-Derived Bio-Based Fertilizers in an Andisol
by Luis Inostroza, Juan Hirzel, Francisco Salazar, Hamza Armghan Noushahi and Gerson Monzón
Agronomy 2026, 16(3), 348; https://doi.org/10.3390/agronomy16030348 (registering DOI) - 30 Jan 2026
Abstract
Aquaculture-derived bio-based fertilizers (BBFs) represent a promising alternative to inorganic P in Andisols for sustainable alfalfa (Medicago sativa L.) cultivation. However, their agronomic performance and physiological impacts on alfalfa remain poorly understood. This study evaluated three BBFs, consisting of composted fish sludge [...] Read more.
Aquaculture-derived bio-based fertilizers (BBFs) represent a promising alternative to inorganic P in Andisols for sustainable alfalfa (Medicago sativa L.) cultivation. However, their agronomic performance and physiological impacts on alfalfa remain poorly understood. This study evaluated three BBFs, consisting of composted fish sludge (CFS), dried fish sludge (DFS), and fish bone meal (FBM), in comparison with inorganic P (InoP) and a zero-P control (NoP). Forage yield (FY), P use efficiency (PUE), spectral canopy indices, and leaf gas-exchange parameters were assessed across five harvests in a Mediterranean environment. Results showed significant differences among fertilizer types driven by their distinct P release dynamics. DFS consistently maintained stable leaf P concentrations, enhanced PUE and P uptake, and lead to higher FY, improved photosynthesis, and water use efficiency (WUE). It performs statistically similarly to the inorganic P. In contrast, CFS released P too slowly, which in turn lowered leaf P concentration, P uptake, and PUE, resulting in the lowest photosynthesis and WUE. FBM produced intermediate responses but maintained WUE comparable to inorganic fertilizer. Gas-exchange measurements demonstrated that photosynthesis ranged from 9.01 to 16.7 μmol m−2 s−1, with no significant difference between DFS and inorganic P. Transpiration remained stable across BBF treatments (mean 3.2 mmol m−2 s−1). The canopy reflectance indices such as RARS, Gite2, and PSSR proved to be strong predictors of both P concentration and PUE in alfalfa. In conclusion, DFS emerged as the most efficient BBF that matched inorganic fertilizer to enhance P nutrition, plant physiology, and FY. These findings highlight the potential of aquaculture-derived BBFs, particularly DFS as sustainable P sources for improving alfalfa productivity while reducing reliance on synthetic fertilizers. Full article
(This article belongs to the Special Issue Advances Towards Innovative Fertilizers for Sustainable Agriculture)
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24 pages, 5987 KB  
Article
Understanding the Dynamics of Urban Heritage: A Quantitative Analysis of Historic Districts Across China’s Rapid Urbanization
by Honghao Zhang, Xingming Li and Xiang Zhang
Land 2026, 15(2), 239; https://doi.org/10.3390/land15020239 (registering DOI) - 30 Jan 2026
Abstract
Understanding the spatial distribution and associated contextual factors of historic and cultural districts is essential for heritage conservation and land-based spatial planning. Previous studies have largely focused on site-level authenticity and development models, while national-scale quantitative analyses remain limited, particularly in the Chinese [...] Read more.
Understanding the spatial distribution and associated contextual factors of historic and cultural districts is essential for heritage conservation and land-based spatial planning. Previous studies have largely focused on site-level authenticity and development models, while national-scale quantitative analyses remain limited, particularly in the Chinese context. This study constructs a nationwide dataset of 1212 historic and cultural districts across 31 provincial-level regions in China and applies a GIS-based framework integrating Global Moran’s I, kernel density estimation, and standard deviation ellipse analysis. The results reveal significant spatial clustering broadly aligned with the Hu Huanyong Line, with high-density concentrations in major urban agglomerations such as the Yangtze River Delta and an overall orientation along an east–west axis at the national scale. Further analysis suggests that these spatial patterns are broadly consistent with natural geographic conditions and long-term historical–cultural contexts; river systems, dynastic capital construction, economic development, and population migration provide important interpretive backgrounds for understanding regional differentiation. By providing a national-scale quantitative characterization of designated historic and cultural districts, this study offers spatial evidence to support more differentiated, land-oriented conservation and spatial planning strategies and to facilitate comparable spatial-heritage analytics in other regions where designation lists exist. Full article
(This article belongs to the Special Issue Cultural Landscapes in Transition: Balancing Heritage, Development, and Sustainability)
12 pages, 745 KB  
Article
Cardiac Magnetic Resonance Findings and Their Association with Clinical Outcomes in Pediatric Pulmonary Arterial Hypertension: An Exploratory Study
by Meryem Beyazal, Merter Keceli, Oguzhan Dogan and Ibrahim Ece
J. Clin. Med. 2026, 15(3), 1107; https://doi.org/10.3390/jcm15031107 (registering DOI) - 30 Jan 2026
Abstract
Background: Cardiac magnetic resonance [CMR] is a non-invasive tool to assess ventricular function in pediatric pulmonary arterial hypertension [PAH]. However, CMR parameters in children remain underexplored. Methods: Thirty-six children with PAH were prospectively evaluated using CMR. Right and left ventricular volumetric [...] Read more.
Background: Cardiac magnetic resonance [CMR] is a non-invasive tool to assess ventricular function in pediatric pulmonary arterial hypertension [PAH]. However, CMR parameters in children remain underexplored. Methods: Thirty-six children with PAH were prospectively evaluated using CMR. Right and left ventricular volumetric and functional parameters, including right and left ventricular ejection fraction [RVEF, LVEF], right and left ventricular end-systolic volume indexed to body surface area [RVESVi, LVESVi], right ventricular mass index [RVMi], ventricular mass index [VMI], septal curvature duration index [SCDI], and regional area change [RAC], were assessed. Clinical variables included brain natriuretic peptide [BNP], New York Heart Association [NYHA] class, and six-minute walk distance [6MWD]. Correlations, logistic regression, and Kaplan–Meier analyses were performed to determine associated factors for mortality. Results: RVEF was negatively correlated with BNP [r = −0.538, p = 0.001], while no correlation was found with LVEF. Decreased RVEF and LVESVi and VMI were associated with mortality in univariate analysis. Patients with VMI > 0.75 or leftward septal shift had significantly lower one-year survival [p = 0.016 and p = 0.040, respectively]. SCDI and RAC were not associated with mortality. Conclusions: RVEF, LVESVi, and VMI are associated with mortality in pediatric PAH. BNP reflects right ventricular dysfunction. VMI and septal morphology are strong associated markers and may enhance risk stratification in children with PAH. Full article
(This article belongs to the Section Cardiovascular Medicine)
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25 pages, 428 KB  
Review
A Review of Power Grid Frameworks for Planning Under Uncertainty
by Tai Zhang, Stefan Borozan and Goran Strbac
Energies 2026, 19(3), 741; https://doi.org/10.3390/en19030741 (registering DOI) - 30 Jan 2026
Abstract
Power-system planning is being reshaped by rapid decarbonisation, electrification, and digitalisation, which collectively amplify uncertainty in demand, generation, technology adoption, and policy pathways. This review critically synthesises three principal optimisation paradigms used to plan under uncertainty in power systems: scenario-based stochastic optimisation, set-based [...] Read more.
Power-system planning is being reshaped by rapid decarbonisation, electrification, and digitalisation, which collectively amplify uncertainty in demand, generation, technology adoption, and policy pathways. This review critically synthesises three principal optimisation paradigms used to plan under uncertainty in power systems: scenario-based stochastic optimisation, set-based robust optimisation (including adaptive and distributionally robust variants), and minimax-regret decision models. The review is positioned to address a recurrent limitation of many uncertainty-planning surveys, namely the separation between “method reviews” and “technology reviews”, and the consequent lack of decision-operational guidance for planners and system operators. The central contribution is a decision-centric framework that operationalises method selection through two explicit dimensions. The first is an information posture, which formalises what uncertainty information is credible and usable in practice (probabilistic, set-based, or probability-free scenario representations). The second is a flexibility posture, which formalises the availability, controllability, and timing of operational recourse enabled by smart-grid technologies. These postures are connected to modelling templates, data requirements, tractability implications, and validation/stress-testing needs. Smart-grid technologies are integrated not as an appended catalogue but as explicit sources of recourse that change the economics of uncertainty and, in turn, shift the relative attractiveness of stochastic, robust, and regret-based planning. Soft Open Points, Coordinated Voltage Control, and Vehicle-to-Grid/Vehicle-to-Building are treated uniformly under this recourse lens, highlighting how device capabilities, control timescales, and implementation constraints map into each paradigm. The paper also increases methodological transparency by describing literature-search, screening, and inclusion principles consistent with a structured narrative review. Practical guidance is provided on modelling choices, uncertainty governance, computational scalability, and institutional adoption constraints, alongside revised comparative tables that embed data credibility, regulatory interpretability, and implementation maturity. Full article
(This article belongs to the Special Issue Optimization and Machine Learning Approaches for Power Systems)
19 pages, 45315 KB  
Article
A TP53-Pathway-Based Prognostic Signature for Radiotherapy and Functional Validation of TP53I3 in Non-Small-Cell Lung Cancer
by Xiang Huang, Li Jiao, Xu Cheng, Yue Fang, Jian Qi, Zongtao Hu, Bo Hong, Jinfu Nie and Hongzhi Wang
Cancers 2026, 18(3), 457; https://doi.org/10.3390/cancers18030457 (registering DOI) - 30 Jan 2026
Abstract
Background: Radiation therapy is an important treatment method for non-small-cell lung cancer (NSCLC). However, predicting patient prognosis remains challenging due to considerable interpatient heterogeneity. The TP53 signaling pathway, implicated in tumor radiosensitivity and treatment outcomes, represents a promising predictive biomarker. Accordingly, in [...] Read more.
Background: Radiation therapy is an important treatment method for non-small-cell lung cancer (NSCLC). However, predicting patient prognosis remains challenging due to considerable interpatient heterogeneity. The TP53 signaling pathway, implicated in tumor radiosensitivity and treatment outcomes, represents a promising predictive biomarker. Accordingly, in this study, we aimed to identify TP53-signaling pathway-related genes and develop a novel prognostic model for risk stratification for NSCLC patients undergoing radiation therapy. Methods: Publicly available NSCLC transcriptomic datasets were obtained from the GEO and TCGA databases. Utilizing bioinformatics approaches, we identified differentially expressed genes (DEGs) associated with the TP53 signaling pathway. Feature selection was performed using LASSO regression, followed by the construction of a multivariate-Cox-regression-based prognostic prediction model. In vitro validation was performed using a cell viability assay, colony formation, cell cycle analysis, apoptosis detection, γH2AX immunofluorescence staining and comet electrophoresis. In vivo validation was performed utilizing a subcutaneous tumor-bearing mouse model, where radiosensitivity was assessed by monitoring tumor volume post-irradiation. Results: We constructed a robust prognostic prediction model based on five TP53-signaling-pathway-related genes (MDM2, THBS1, TP53I3, ATM, and SESN3), achieving a 5-year AUC of 0.828 in the training set and a 3-year AUC of 0.824 in the validation set. The model exhibited a significant ability to stratify patients into distinct high- and low-risk groups, demonstrating good predictive performance. The poor prognosis observed in the high-risk group was associated with lower infiltration of anti-tumor immune cells but higher infiltration of immunosuppressive cells. Both in vitro and in vivo experiments demonstrated that TP53I3 knockdown significantly enhanced the radiosensitivity of NSCLC through increased DNA damage, cell cycle arrest and apoptosis. Conclusions: In this study, a five-gene signature derived from the TP53 signaling pathway was developed, and the model was shown to effectively predict the prognoses of NSCLC patients undergoing radiotherapy. This signature has the potential to be developed into a clinically applicable tool for personalizing radiotherapy regimens for NSCLC. Full article
(This article belongs to the Section Molecular Cancer Biology)
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25 pages, 4688 KB  
Article
Spectrally Negative Lévy Risk Model Under Multi-Layer Ratcheting Dividend Strategy and Capital Injections
by Fuyun Sun and Yongxia Zhao
Axioms 2026, 15(2), 101; https://doi.org/10.3390/axioms15020101 (registering DOI) - 30 Jan 2026
Abstract
In this study, we investigate the mixed n-layer ratcheting dividend and capital injection policies for a spectrally negative Lévy risk model, where dividend distributions are implemented continuously in a non-decreasing manner, and capital injections are conducted discretely at the jump instants of [...] Read more.
In this study, we investigate the mixed n-layer ratcheting dividend and capital injection policies for a spectrally negative Lévy risk model, where dividend distributions are implemented continuously in a non-decreasing manner, and capital injections are conducted discretely at the jump instants of an independent Poisson process. We incorporate both terminal values and transaction costs into the analysis, making the model more in line with practical scenarios. The value function and the Laplace transform of the ruin time are derived by leveraging Lévy fluctuation theory, and all the obtained results are formulated in terms of scale functions. Furthermore, numerical examples based on the classic risk model are provided to illustrate the theoretical findings. Full article
28 pages, 8233 KB  
Article
Supergene Alteration of Skarn and Marble at Flotouo (Ity, Ivory Coast): Controls on Gold and Trace-Metal Enrichment in the Saprolite
by Yacouba Coulibaly, Michel Cathelineau and Marie-Christine Boiron
Minerals 2026, 16(2), 162; https://doi.org/10.3390/min16020162 (registering DOI) - 30 Jan 2026
Abstract
At the Ity gold deposit (Ivory Coast), carbonate-buffered tropical weathering fundamentally controlled the redistribution and enrichment of gold and associated metals within the Flotouo weathering profile. Primary mineralisation formed through skarn development at quartz diorite contacts, followed by mesothermal stages around 2 Ga, [...] Read more.
At the Ity gold deposit (Ivory Coast), carbonate-buffered tropical weathering fundamentally controlled the redistribution and enrichment of gold and associated metals within the Flotouo weathering profile. Primary mineralisation formed through skarn development at quartz diorite contacts, followed by mesothermal stages around 2 Ga, establishing the initial Au and trace-metal endowment. Hypogene processes alone, however, cannot explain the present distribution and concentration of Au, Cu, Mo, Bi, Sn, and W. Cenozoïc tropical weathering profoundly transformed the ores through coupled sulphide oxidation and carbonate dissolution. Oxidation of sulfides releases metals into circulating fluids. At the same time, dissolution of marble lenses buffered the pH towards near-neutral conditions, limiting long-distance metal transport and favouring local residual enrichment and secondary immobilisation. These processes, together with leaching of Ca, S, and Si, increased porosity and permeability, promoted fluid flow through karstic voids and collapse breccias. A lateritic blanket extends above the saprolitised hypogene ores. A systematic vertical mineralogical zonation developed across the profile, with goethite-dominated laterite at the top, kaolinite-rich saprolite in the middle, and smectite-bearing horizons at depth. This study highlights the key role of pH-buffered tropical lateritisation in upgrading pre-existing skarn-related mineralisation and producing atypical trace-metal enrichments in Birimian gold systems, providing a mechanistic framework relevant for regional exploration models. Full article
(This article belongs to the Section Mineral Deposits)
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15 pages, 2283 KB  
Article
Enhanced Soybean Immunity to the Soybean Mosaic Virus Through RNA Interference Targeting the CP Gene
by Tao Wang, Le Gao, Liqun Wang, Rui Ren, Rui Zhai, Xu Wang, Fuming Xiao, Long Yan, Xiaotong Lei, Tongtong Jin and Haijian Zhi
Plants 2026, 15(3), 430; https://doi.org/10.3390/plants15030430 (registering DOI) - 30 Jan 2026
Abstract
The soybean mosaic virus (SMV), a significant viral pathogen impacting soybean cultivation, leads to substantial yield losses and diminishes seed quality. In a prior study, we developed a targeted silencing vector using RNA interference (RNAi) technology targeting the CP gene, which codes for [...] Read more.
The soybean mosaic virus (SMV), a significant viral pathogen impacting soybean cultivation, leads to substantial yield losses and diminishes seed quality. In a prior study, we developed a targeted silencing vector using RNA interference (RNAi) technology targeting the CP gene, which codes for the viral coat proteins in the SMV genome. This vector was delivered into soybean plants through Agrobacterium-mediated transformation. In our current research, we utilized ongoing molecular characterization and resistance screening to identify four genetically pure lines that display moderate to high resistance to SMV. Additionally, the transgenic plants exhibited resistance to three other potyviruses: the bean common mosaic virus, the recombinant soybean mosaic virus, and the watermelon mosaic virus. Greenhouse and field trials conducted with these lines demonstrated that RNAi-mediated silencing of the CP gene significantly enhanced disease resistance. It is noteworthy that, in comparison to the receptor plants, the transgenic plants exhibited no significant differences in maturity, plant height, branching number, node number, pod number, or 100-seed weight. These results offer valuable genetic resources and theoretical support for molecular breeding strategies aimed at combating SMV in soybeans, as well as for RNAi-based methods to control plant viral infections. Full article
(This article belongs to the Topic Plant Breeding, Genetics and Genomics, 2nd Edition)
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23 pages, 2232 KB  
Article
Physics-Informed Neural Networks for Three-Dimensional River Microplastic Transport: Integrating Conservation Principles with Deep Learning
by Pengjie Hu, Mengtian Wu, Jian Ma, Jingwen Zhang and Jianhua Zhao
Sustainability 2026, 18(3), 1392; https://doi.org/10.3390/su18031392 (registering DOI) - 30 Jan 2026
Abstract
Microplastic pollution in riverine systems poses critical environmental challenges, yet predictive modeling remains constrained by data scarcity and the computational limitations of traditional numerical approaches. This study develops a physics-informed neural network (PINN) framework that integrates advection–diffusion equations and turbulence modeling approaches with [...] Read more.
Microplastic pollution in riverine systems poses critical environmental challenges, yet predictive modeling remains constrained by data scarcity and the computational limitations of traditional numerical approaches. This study develops a physics-informed neural network (PINN) framework that integrates advection–diffusion equations and turbulence modeling approaches with deep learning architectures to stimulate three-dimensional microplastic transport dynamics. The methodology embeds governing partial differential equations as soft constraints, enabling predictions under sparse observational conditions (requiring approximately three times fewer observation points than conventional numerical models), while maintaining physical consistency. Applied to a representative 15 km Yangtze River reach with 12 months of monitoring data, the model achieves improved performance with a root mean square error of 0.82 particles/m3 and a Nash–Sutcliffe efficiency exceeding 0.88, representing a 34% accuracy improvement over conventional finite volume methods. The framework successfully captures size-dependent transport behavior, identifies three primary accumulation hotspots exhibiting 3–5 times elevated concentrations, and quantifies nonlinear flux–discharge relationships with 6–8-fold amplification during high-flow events. This physics-constrained approach provides practical findings for pollution management and establishes an adaptable computational framework for environmental transport modeling in data-limited scenarios across diverse riverine systems. Full article
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14 pages, 281 KB  
Article
Impact of Dermatologic Screening and Methods on Breslow Thickness in Melanoma: A Retrospective Cohort Study
by Katharina Wunderlich, Apolline Potiez, Carmen Orte Cano, Joanna Bouchat, Nancy Van Damme, Mariano Suppa, Jonathan M. White, Hassane Njimi, Elizabeth Van Eycken and Véronique Del Marmol
Cancers 2026, 18(3), 461; https://doi.org/10.3390/cancers18030461 (registering DOI) - 30 Jan 2026
Abstract
Background/Objectives: Melanoma is the most lethal cutaneous neoplasm, with Breslow thickness being a key prognostic factor. This retrospective cohort study aimed to assess the impact of screening frequency and diagnostic methods on tumour stage at diagnosis and to explore implications for risk-adapted strategies. [...] Read more.
Background/Objectives: Melanoma is the most lethal cutaneous neoplasm, with Breslow thickness being a key prognostic factor. This retrospective cohort study aimed to assess the impact of screening frequency and diagnostic methods on tumour stage at diagnosis and to explore implications for risk-adapted strategies. Methods: Between 2017 and 2024, 475 cases of melanoma were diagnosed in 397 patients. Screening frequency, diagnostic method, and patient risk were analyzed in relation to tumour stage. Results: Compared with first-visit cases, patients who underwent screening within two years prior to diagnosis were more often diagnosed with melanoma in situ (32.6% vs. 44–51%; p < 0.05) and had thinner invasive tumours (0.68–0.73 mm vs. 1.8 mm; p ≤ 0.001), though no differences were seen between screening frequencies. Full-body examination was associated with more in situ melanomas (46% vs. 34%; p = 0.016) and thinner invasive tumours (0.92 vs. 2.05 mm; p = 0.2) compared with lesion-directed screening, but this effect disappeared after excluding first-visit cases. Invasive melanomas diagnosed by mole mapping were significantly thinner than by dermoscopy (0.55 vs. 1.07; p = 0.035). In high-risk patients, tumour thickness decreased with more frequent visits (0.905 mm without screening vs. 0.40–0.55 mm with ≥1 visit; p = 0.001). Moreover, mole mapping identified thinner melanomas in the high-risk group compared with dermoscopy (0.47 vs. 0.60 mm; p = 0.02). Conclusions: Screening is associated with thinner melanomas and more in situ diagnoses. Digital mole mapping offers additional benefits, with high-risk patients profiting most, while low-risk individuals could be managed with less resource-intensive approaches. These findings support risk-adapted screening strategies focusing on intensive, digitally supported modalities for high-risk groups. Full article
(This article belongs to the Special Issue Skin Cancer Prevention: Strategies, Challenges and Future Directions)
3 pages, 157 KB  
Editorial
Special Issue “Advances in Natural Active Products Derived from Foods: Antioxidant, Antinociceptive and Anti-Inflammatory Activities”
by Ettore Novellino
Int. J. Mol. Sci. 2026, 27(3), 1395; https://doi.org/10.3390/ijms27031395 (registering DOI) - 30 Jan 2026
Abstract
In recent years, the study of naturally derived bioactive compounds present in foods has attracted increasing interest, owing to their promising potential in preventing and counteracting a wide range of health-related conditions [...] Full article
(This article belongs to the Special Issue Advances in Natural Active Products Derived from Foods: Antioxidant, Antinociceptive and Anti-inflammatory Activities)
23 pages, 2095 KB  
Article
Increased Drought Tolerance in Lagenaria siceraria by Indigenous Bacterial Isolates from Coastal Environments in Chile: Searching for the Improvement of Rootstocks for Cucurbit Production
by Rodrigo Pérez, Ariel Salvatierra, Paula Pimentel, Guillermo Toro, Antonieta Ruiz, Ricardo Aroca, Luis Villalobos, Tiare Inostroza, Felipe González, Christian Santander, Cecilia García and Pablo Cornejo
Agriculture 2026, 16(3), 341; https://doi.org/10.3390/agriculture16030341 (registering DOI) - 30 Jan 2026
Abstract
Drought is one of the most limiting abiotic stresses for agricultural production, especially in horticultural crops grown in arid and semi-arid areas. In the present study, we evaluated the potential of bacterial isolates obtained from coastal environments in Chile to improve drought tolerance [...] Read more.
Drought is one of the most limiting abiotic stresses for agricultural production, especially in horticultural crops grown in arid and semi-arid areas. In the present study, we evaluated the potential of bacterial isolates obtained from coastal environments in Chile to improve drought tolerance in Lagenaria siceraria, a plant species increasingly used as a rootstock for cucurbit cropping. Rhizosphere bacteria were isolated from Sicyos baderoa, the only native cucurbit species of the Chilean coast, from which four isolates with plant growth-promoting traits, such as indole-3-acetic acid production, phosphorus solubilization, nitrogen fixation, and siderophore production, were selected. These isolates were inoculated on two L. siceraria genotypes, Illapel and Osorno, under both normal irrigation and water deficit conditions. The results showed that Peribacillus frigoritolerans showed a clearer positive effect on biomass and net photosynthesis under water deficit in the Illapel genotype, increasing shoot biomass by up to ~75% and restoring net photosynthetic rates by up to ~260% relative to non-inoculated drought-stressed plants. In contrast, responses associated with Staphylococcus succinus and those observed in the Osorno genotype were mainly expressed as trait- and tissue-specific adjustments, consistent with a more stabilizing response rather than broad growth stimulation. Additionally, malondialdehyde levels were reduced by up to ~25%, while free proline accumulation increased by more than 100% under water deficit. In contrast, total phenolic compounds showed more variable responses, indicating genotype- and strain-specific adjustment of antioxidant metabolism. Overall, the observed responses were heterogeneous and strongly dependent on the specific strain–genotype–trait combination and, therefore, should be interpreted as preliminary evidence supporting the potential value of native rhizobacteria for improving early drought-related traits in cucurbit rootstocks. Among the tested strains, Peribacillus frigoritolerans emerged as the most promising candidate for enhancing early drought tolerance in responsive genotypes such as Illapel, while highlighting the need for follow-up studies under replicated nursery and field conditions, including grafted plants, multiple drought intensities and combined inoculant strategies. Full article
(This article belongs to the Special Issue Abiotic Stress Responses in Horticultural Crops—2nd Edition)
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24 pages, 1066 KB  
Review
Contemporary Preoperative Detection of Extraprostatic Extension in Prostate Cancer
by Jan Stępka, Tomasz Milecki, Jędrzej Ksepka, Anna Kujawska, Jaśmina Hendrysiak and Wojciech A. Cieślikowski
Cancers 2026, 18(3), 456; https://doi.org/10.3390/cancers18030456 (registering DOI) - 30 Jan 2026
Abstract
Extraprostatic extension (EPE) is an important prognostic factor in prostate cancer and influences nerve-sparing decisions during radical prostatectomy. Multiparametric MRI (mpMRI) is the standard for local staging, but its sensitivity for EPE remains limited, and its interpretation is subject to inter-reader variability. In [...] Read more.
Extraprostatic extension (EPE) is an important prognostic factor in prostate cancer and influences nerve-sparing decisions during radical prostatectomy. Multiparametric MRI (mpMRI) is the standard for local staging, but its sensitivity for EPE remains limited, and its interpretation is subject to inter-reader variability. In this narrative review, we aim to create an overview of contemporary strategies for the preoperative detection of EPE. We searched PubMed, Embase, Web of Science, and Google Scholar, focusing on studies published between 2015 and 2025 including articles evaluating clinical parameters, mpMRI features, nomograms, radiomics, machine learning, and deep learning models for EPE prediction. The analyzed literature was compared with respect to diagnostic performance, validation strategy, and clinical applicability of individual methods. Clinical parameters and traditional nomograms provide moderate accuracy for EPE detection. mpMRI improves staging, with tumor–capsule contact length as the most important single imaging marker. Radiomics-based and machine-learning models matched and occasionally outperform conventional approaches, achieving AUC values ranging from 0.75 to 0.85. Deep-learning models demonstrated similar performance by directly analyzing imaging data, although most lacked external validation and were sensitive to dataset heterogeneity. Several radiomics and deep learning models demonstrated performance comparable to, and in selected studies exceeding, expert radiologist assessment. Binary EPE classification has limited clinical value, while side-specific and graded EPE assessment offers a more clinically relevant approach. Translation of these tools into routine practice will require multimodal, side-specific, and externally validated models supported by automated segmentation and explainable artificial intelligence frameworks. Full article
(This article belongs to the Special Issue Advances in the Use of PET/CT and MRI in Prostate Cancer)
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23 pages, 495 KB  
Systematic Review
Psychosocial Aspects of Cystic Fibrosis: A Mixed-Methods Systematic Review
by Maria Inês Griff, Rita Santos, Carmen Trumello and Tânia Brandão
Healthcare 2026, 14(3), 351; https://doi.org/10.3390/healthcare14030351 (registering DOI) - 30 Jan 2026
Abstract
Background/Objectives: Cystic fibrosis (CF) is a genetic condition with an increasing life expectancy in recent years. As a result, addressing psychosocial aspects in this population has become an increasingly important concern. This mixed-methods systematic review aimed to update the current knowledge on [...] Read more.
Background/Objectives: Cystic fibrosis (CF) is a genetic condition with an increasing life expectancy in recent years. As a result, addressing psychosocial aspects in this population has become an increasingly important concern. This mixed-methods systematic review aimed to update the current knowledge on the psychosocial aspects of living with CF in adults. Methods: Following PRISMA guidelines, a literature search was conducted in November 2024 across several databases, including Scopus, ScienceDirect, Academic Search Complete, MEDLINE, Supplemental Index, Complementary Index, APA PsycInfo, Business Source Complete, SciELO, and the Directory of Open Access Journals via EBSCO. Results: Of the 701 articles retrieved, 24 were analyzed, including a total of 2023 participants (mean age: 31.2 years; 57.2% female). Quantitative findings identified optimistic coping as the most frequent strategy associated with improved survival. High social support and gratitude emerged as key factors for treatment adherence and quality of life, while depression remained the primary mental health concern. Qualitatively, the findings highlighted concerns with adult life transitions and financial stressors. Participants described experiences of social stigma and embarrassment linked to chronic symptoms, often leading to selective disclosure to avoid discrimination. Conclusions: This review confirms that psychosocial factors are central to the adult CF experience, shifting the focus beyond biological survival and highlighting areas that require clinical intervention. As life expectancy increases, clinical care must evolve to incorporate interventions that address these factors to improve mental health and overall quality of life (QoL), ensuring that patients are supported through the unique challenges of extended adulthood. Full article
(This article belongs to the Section Mental Health and Psychosocial Well-being)
34 pages, 2092 KB  
Review
Molecular Biomarkers in IgE Immunoassays Used for Grass Pollen Allergy Diagnosis in European Clinical Settings
by Lorena-Mihaela Gheorghita, Mariana Preda, Carmen-Saviana Marghidan, Miruna-Ioana Lazar, Ioana-Raluca Papacocea, Sylwia Smolinska and Florin-Dan Popescu
Int. J. Mol. Sci. 2026, 27(3), 1393; https://doi.org/10.3390/ijms27031393 (registering DOI) - 30 Jan 2026
Abstract
Grass pollen allergy has a high prevalence worldwide, making an accurate diagnosis critical in the framework of multifaceted environmental exposures. Our narrative review provides a comprehensive synopsis of component-resolved diagnosis biomarkers for pollen of Pooideae and Chloridoideae grasses, along with practical approaches in [...] Read more.
Grass pollen allergy has a high prevalence worldwide, making an accurate diagnosis critical in the framework of multifaceted environmental exposures. Our narrative review provides a comprehensive synopsis of component-resolved diagnosis biomarkers for pollen of Pooideae and Chloridoideae grasses, along with practical approaches in European clinical settings. We present a structured overview of allergen components utilized in singleplex, multiparameter, and multiplex IgE immunoassays. Molecular biomarkers have key roles in distinguishing genuine grass pollen sensitization from cross-reactivity and in assessing the risks associated with various IgE sensitization patterns, thereby enabling precise allergy diagnosis and facilitating targeted allergen immunotherapy. Diagnostic algorithms are provided to assist clinicians in making molecular biomarker-based personalized decisions. This tailored approach supports better management of patients with grass pollen sensitizations and allergies. Full article
(This article belongs to the Special Issue Molecular Research in Asthma and Allergy)
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