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20 pages, 3906 KB

Open AccessArticle

Short-Term Heat Stress Differentially Affects the Photosynthetic Thermotolerance of Cotyledons and Early Orthotropic Leaves in Coffea arabica L. Seedlings

by Tiago Vilas-Boas, Felipe Della Torre, Zachary Dalton, Maria Bernadete Lovato, José Pires de Lemos-Filho and Elizabeth R. Waters

Biology 2025, 14(12), 1659; https://doi.org/10.3390/biology14121659 (registering DOI) - 24 Nov 2025

Abstract

Coffee (Coffea spp [...] Full article

(This article belongs to the Section Plant Science)

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15 pages, 459 KB

Open AccessArticle

Epidemiological Trends and Age-Related Outcomes in Reverse Total Shoulder Arthroplasty: A U.S. Nationwide Inpatient Analysis of 9692 Patients

by Muhammad Khatib, Assil Mahamid, Hamza Murad, Feras Qawasmi, Eitan Lavon, Ali Yassin and Mustafa Yassin

J. Clin. Med. 2025, 14(23), 8340; https://doi.org/10.3390/jcm14238340 (registering DOI) - 24 Nov 2025

Abstract

Background/Objectives: Reverse total shoulder arthroplasty (RTSA) is increasingly common, but large-scale studies on age-related differences in outcomes are limited. This study aims to evaluate epidemiological trends, clinical indications, and postoperative outcomes in patients under 65 undergoing RTSA. Methods: We analyzed data [...] Read more.

Background/Objectives: Reverse total shoulder arthroplasty (RTSA) is increasingly common, but large-scale studies on age-related differences in outcomes are limited. This study aims to evaluate epidemiological trends, clinical indications, and postoperative outcomes in patients under 65 undergoing RTSA. Methods: We analyzed data from the Nationwide Inpatient Sample (NIS) from 2016–2021, including 48,460 patients aged 35–64 undergoing shoulder arthroplasty. Patients were stratified into three age groups: 35–45, 46–55, and 56–65 years. We assessed trends, clinical indications, comorbidities, hospital stay metrics, and postoperative complications using chi-square tests, ANOVA, and multivariate logistic regression. Results: Procedure volumes increased from 2016 to 2019, peaking at 2007 cases, but declined in 2020 and 2021 (924 cases). The 56–65 age group consistently comprised the majority of procedures (81.7% in 2016 to 88.3% in 2021). Comorbidities like type 2 diabetes (5.9% to 22.8%), hypertension (27.9% to 55.3%), and dyslipidemia (10.3% to 40.5%) increased with age (p < 0.001). Rotator cuff tears were more prevalent in older patients (25% to 48.5%, p < 0.001), while instability was higher in the youngest group (8.8%, p < 0.001). Osteoarthritis was the most common indication, increasing with age (56.6% to 62.5%, p < 0.001). Cardiac complications increased with age (2.2% to 5.1%, p = 0.04). Female gender (OR = 1.548, p < 0.001), private insurance (OR = 1.570, p < 0.001), and small hospital size were associated with higher odds of cardiac complications. Native American race showed lower odds (OR = 0.308, p = 0.009) compared to White patients. Conclusions: Significant age-related differences exist in comorbidities, clinical indications, and postoperative complications following RTSA. Older patients had higher rates of comorbidities and cardiac complications, while younger patients presented with instability. These findings highlight the importance of age-specific perioperative management to optimize outcomes. Full article

(This article belongs to the Section Orthopedics)

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65 pages, 2654 KB

Open AccessReview

From Semantic Modeling to Precision Radiotherapy: An AI Framework Linking Radiobiology, Oncology, and Public Health Integration

by Fernando Gomes de Souza Jr., José Maria Aliaga Jr., Paulo C. Duarte Jr., Shirley Crispilho, Carolina Delfino, Daniele Brandão and Fernando Zamprogno e Silva

Biomedicines 2025, 13(12), 2862; https://doi.org/10.3390/biomedicines13122862 (registering DOI) - 24 Nov 2025

Abstract

Background/Objectives: Radiotherapy, radiobiology, and oncology have evolved rapidly over the past six decades. This progress has generated vast but fragmented bodies of scientific evidence. The present study aimed to systematically map and interpret their conceptual and temporal development using artificial intelligence (AI)-based methods. [...] Read more.

Background/Objectives: Radiotherapy, radiobiology, and oncology have evolved rapidly over the past six decades. This progress has generated vast but fragmented bodies of scientific evidence. The present study aimed to systematically map and interpret their conceptual and temporal development using artificial intelligence (AI)-based methods. It highlights the integration between molecular mechanisms, clinical applications, and technological innovation within a precision radiotherapy framework. Methods: A corpus of 3343 unique articles (1964–2025) was retrieved from Scopus, PubMed, and Web of Science. Records were harmonized through deduplication, lemmatization, and metadata normalization. Topic modeling using Latent Dirichlet Allocation (LDA) and co-occurrence network analysis were applied to identify dominant research axes. Semantic and temporal analyses were conducted to reveal patterns, emerging trends, and translational connections across decades. Results: Three historical phases were identified. The first was a period of limited production (1964–1990). The second showed moderate growth (1991–2010). The third, from 2011 to 2024, represented exponential expansion, with publication peaks in 2020 and 2023. LDA revealed two principal axes. The first, a clinical–anatomical axis, focused on cancer sites, treatment modalities, and prognosis. The second, a mechanistic–molecular axis, centered on DNA repair, radiosensitivity, and biomarkers. Case synthesis from 2014–2025 defined five operational classes: DNA repair and molecular response; precision oncology and genomic modeling; individual radiosensitivity; mechanisms of radioresistance; and advanced technologies such as FLASH radiotherapy and optimized brachytherapy. Conclusions: AI-driven semantic and temporal analyses showed that radiotherapy has matured into an interconnected and interdisciplinary domain. The derived Precision Radiotherapy Implementation Plan translates molecular and computational insights into clinically actionable strategies. These approaches can enhance survival, reduce toxicity, and inform equitable health policies for advanced cancer care. Full article

(This article belongs to the Special Issue New Insights in Radiotherapy: Bridging Radiobiology and Oncology)

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15 pages, 1224 KB

Open AccessArticle

Extraction and Identification of Active Components from Lilium lancifolium Based on NADES-UHPLC-MS/MS Technology

by Yuliang Wang, Yingjie Ma, Zhenxu Jiang, Weiwei Tang, Chaoxing Wang, Hong Zhao and Yu Zhang

Molecules 2025, 30(23), 4531; https://doi.org/10.3390/molecules30234531 (registering DOI) - 24 Nov 2025

Abstract

The bulb of Lilium lancifolium, a traditional Chinese medicine and food-homologous material, is rich in various saponins with notable pharmacological activities. However, traditional extraction methods using single solvents suffer from low efficiency, high cost, and flammability. To address these limitations, this study [...] Read more.

The bulb of Lilium lancifolium, a traditional Chinese medicine and food-homologous material, is rich in various saponins with notable pharmacological activities. However, traditional extraction methods using single solvents suffer from low efficiency, high cost, and flammability. To address these limitations, this study developed a green and efficient extraction method using natural deep eutectic solvents (NADES). Twenty-four NADES were synthesized and screened for stability, leading to the selection of fourteen for subsequent extraction of saponins from L. lancifolium, with ethanol extraction as a control. Through optimization, NADES-15, composed of choline chloride and anhydrous citric acid (2:1), was identified as the most effective solvent. Quantitative analysis revealed that the total saponin content obtained with NADES-15 (46.6 mg/g) significantly surpassed that of ethanol. Furthermore, UHPLC-MS/MS analysis demonstrated a greater diversity of chemical components in the NADES-15 extract, wherein 31 compounds were tentatively identified, including all nine target steroidal saponins (lily saponin A–I), compared to only 17 compounds and six saponins found in the ethanol extract. This study highlights the significant advantages of NADES in enhancing both the efficiency and variety of active component extraction from L. lancifolium, offering a novel and green approach for natural product extraction. Full article

(This article belongs to the Topic Advances on the Application of Nanomaterials and 2D Materials for Sensors, Solar Cells, Microelectronics, and Optoelectronics)

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16 pages, 1648 KB

Open AccessArticle

Analysis and Optimization of a Waste Heat Recovery System from a Diesel Engine for Desalination

by Wing Yee Ng, Saiful Bari, John Milton Fielke and Habibullah

Energies 2025, 18(23), 6152; https://doi.org/10.3390/en18236152 (registering DOI) - 24 Nov 2025

Abstract

As global water scarcity intensifies, this study proposes a solution by utilizing surplus heat from a diesel generator set to enhance freshwater production through a waste heat recovery (WHR) system. The system is simulated and optimized using Engineering Equation Solver (EES) to improve [...] Read more.

As global water scarcity intensifies, this study proposes a solution by utilizing surplus heat from a diesel generator set to enhance freshwater production through a waste heat recovery (WHR) system. The system is simulated and optimized using Engineering Equation Solver (EES) to improve freshwater production efficiency. Results indicate that the WHR system can produce 13.9 million liters (ML) of freshwater annually, with a payback period of 4.63 years for freshwater alone, confirming strong viability. In addition, the system can generate 160,000 kWh of electricity, which reduces the combined payback period to 2.12 years. Key design constraints include maintaining a minimum exhaust pressure of 100 kPa (absolute) and placing the WHR system along the gen-set’s long side. These requirements demand a compact design with a minimum pinch temperature of 20 K. The system’s main components are aligned with the gen-set, resulting in a total footprint of 60.5 m² and a system weight of 25 tons, compared with 8.52 m² and 12.6 tons for the generator. Full article

(This article belongs to the Collection Advances in Heat Transfer Enhancement)

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43 pages, 1321 KB

Open AccessReview

Survey of Intra-Node GPU Interconnection in Scale-Up Network: Challenges, Status, Insights, and Future Directions

by Xiaoyong Song, Danyuan Zhou, Kai Li, Jiayuan Chen, Hao Zhang, Xiaoguang Zhang and Xuxia Zhong

Future Internet 2025, 17(12), 537; https://doi.org/10.3390/fi17120537 (registering DOI) - 24 Nov 2025

Abstract

Nowadays, driven by the exponential growth of parameters and training data of AI applications and Large Language Models, a single GPU is no longer sufficient in terms of computing power and storage capacity. Building high-performance multi-GPU systems or a GPU cluster via vertical [...] Read more.

Nowadays, driven by the exponential growth of parameters and training data of AI applications and Large Language Models, a single GPU is no longer sufficient in terms of computing power and storage capacity. Building high-performance multi-GPU systems or a GPU cluster via vertical scaling (scale-up) has thus become an effective approach to break the bottleneck and has further emerged as a key research focus. Given that traditional inter-GPU communication technologies fail to meet the requirement of GPU interconnection in vertical scaling, a variety of high-performance inter-GPU communication protocols tailored for the scale-up domain have been proposed recently. Notably, due to the emerging nature of these demands and technologies, academic research in this field remains scarce, with limited deep participation from the academic community. Inspired by this trend, this article identifies the challenges and requirements of a scale-up network, analyzes the bottlenecks of traditional technologies like PCIe in a scale-up network, and surveys the emerging scale-up targeted technologies, including NVLink, OISA, UALink, SUE, and other X-Links. Then, an in-depth comparison and discussion is conducted, and we express our insights in protocol design and related technologies. We also highlight that existing emerging protocols and technologies still face limitations, with certain technical mechanisms requiring further exploration. Finally, this article presents future research directions and opportunities. As the first review article fully focusing on intra-node GPU interconnection in a scale-up network, this article aims to provide valuable insights and guidance for future research in this emerging field, and we hope to establish a foundation that will inspire and direct subsequent studies. Full article

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19 pages, 8013 KB

Open AccessArticle

XPS Study of Nanostructured Pt Catalytic Layer Surface of Gas Sensor Dubbed GMOS

by Hanin Ashkar, Sara Stolyarova, Tanya Blank and Yael Nemirovsky

Chemosensors 2025, 13(12), 407; https://doi.org/10.3390/chemosensors13120407 (registering DOI) - 24 Nov 2025

Abstract

The long-term reliability of catalytic gas sensors is strongly influenced by changes in the chemical state and cleanliness of the catalyst surface. In this work, we investigate the surface composition and stability of the platinum (Pt) nanoparticle catalytic layer in Gas Metal-Oxide-Semiconductor (GMOS) [...] Read more.

The long-term reliability of catalytic gas sensors is strongly influenced by changes in the chemical state and cleanliness of the catalyst surface. In this work, we investigate the surface composition and stability of the platinum (Pt) nanoparticle catalytic layer in Gas Metal-Oxide-Semiconductor (GMOS) sensors under varying environmental conditions. Using X-ray Photoelectron Spectroscopy (XPS) and High-Resolution (HR) XPS, we compared fresh, aged samples, thermally treated samples, and samples stored with or without a mechanical filter. The results show that prolonged ambient storage leads to the accumulation of adventitious carbon and nitrogen-containing species, as well as partial oxidation of platinum, which reduces the number of active metallic Pt sites. Thermal treatment at 300 °C for 30 min restores metallic Pt exposure by removing surface contaminants and narrowing the Pt 4f peaks. However, recontamination occurs during subsequent storage, with significant differences depending on surface protection. Sensors equipped with a mechanical filter exhibited obvious Pt metallic peaks in HR-XPS analysis, with lower carbon and nitrogen levels, compared to unprotected samples. These findings demonstrate that while heating refreshes catalytic activity, long-term stability requires complementary filtration to prevent re-adsorption of airborne species. The combined approach of heating and filtration is thus essential to ensure reliable performance of GMOS sensors for indoor and outdoor air quality monitoring. Full article

(This article belongs to the Special Issue Innovative Nanomaterials-Based Chemosensor Devices for Air Quality Monitoring)

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30 pages, 768 KB

Open AccessReview

Minimal Residual Disease in Breast Cancer: Tumour Microenvironment Interactions, Detection Methods and Therapeutic Approaches

by Nigel P. Murray and Socrates Aedo

Int. J. Mol. Sci. 2025, 26(23), 11346; https://doi.org/10.3390/ijms262311346 (registering DOI) - 24 Nov 2025

Abstract

Breast cancer is the most common cancer in women, depending on the sub-type of breast cancer treatment options are different. After completing adjuvant therapy, there are patients who may relapse even many years later. This review examines minimal residual disease, defined as small, [...] Read more.

Breast cancer is the most common cancer in women, depending on the sub-type of breast cancer treatment options are different. After completing adjuvant therapy, there are patients who may relapse even many years later. This review examines minimal residual disease, defined as small, microscopic foci of cancer cells that have survived curative treatment, have disseminated to distant tissues, and implanted there. However, the cancer cells do not exist alone but are a small part of the tumour microenvironment, described as an ecosystem. This includes stromal cells, immunosuppressive regulatory T-cells, myeloid derived suppression cells, cancer associated fibroblasts, tumour associated macrophages. The balance of the immunosuppressive tumour microenvironment and the anti-tumour immune response will determine if there is a future relapse. The interactions between the cancer cells and the tumour microenvironment are dynamic and change with time. Most therapeutic options involve therapies directed against tumour cells, only in the last few years has there been attention on the dynamic effects of the tumour microenvironment and the cancer cells on disease progression and the possibility of decreasing the risk of metastatic disease. This article reviews the latest development in preventing metastatic disease by influencing the tumour microenvironment; at best eliminating cancer cells or at least prolonging the latent period of cancer cell dormancy. Full article

(This article belongs to the Special Issue Molecular and Cellular Aspects of Breast Cancer Metastasis)

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22 pages, 1891 KB

Open AccessArticle

BIM-Based Life Cycle Carbon Assessment and PV Strategies for Residential Buildings in Central China

by Yifeng Guo, Yexue Li, Shanshan Xie, Wanqin Mao and Xuzhi Chen

Buildings 2025, 15(23), 4232; https://doi.org/10.3390/buildings15234232 (registering DOI) - 24 Nov 2025

Abstract

Aligned with China’s “Dual Carbon” goals, this study addresses carbon emissions in the building sector. Existing research predominantly focuses on single-stage carbon emission assessment or separately examines the benefits of BIM applications and photovoltaic (PV) technology. There is a notable lack of studies [...] Read more.

Aligned with China’s “Dual Carbon” goals, this study addresses carbon emissions in the building sector. Existing research predominantly focuses on single-stage carbon emission assessment or separately examines the benefits of BIM applications and photovoltaic (PV) technology. There is a notable lack of studies that deeply integrate the BIM platform with dynamic assessment of building life cycle carbon emissions and PV carbon reduction strategies, particularly under the specific context of the hot-summer/cold-winter climate in Central China and a regional grid primarily reliant on thermal power. Moreover, localized and in-depth analyses targeting residential buildings in this region remain scarce. To address this gap, this study takes a residential building in Central China as a case study and establishes a BIM-based life cycle carbon emission assessment model to systematically quantify the carbon footprint across all stages. Results show total life cycle carbon emissions of 12600 tCO₂, with embodied carbon (4590 tCO₂, 36.6%) and the operational phase identified as the main emission sources. Through PV system integration and multi-scenario simulations, the study demonstrates significant carbon reduction potential: systems with 40–80 kW capacity can achieve annual carbon reductions ranging from 26 to 52 tCO₂. The 60 kW system shows the optimal balance with an annual reduction of 38.7 tCO₂ and a payback period of 3.53 years. The primary novelty of this work lies in its development of a dynamic BIM-LCA framework that enables real-time carbon footprint tracking, and the establishment of a first-of-its-kind quantitative model for PV strategy optimization under the specific climatic and grid conditions of Central China, providing a replicable pathway for region-specific decarbonization. Full article

(This article belongs to the Special Issue Advanced Technologies in Energy Consumption and Optimization for Residential Buildings)

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22 pages, 5402 KB

Open AccessArticle

Underwater Radiated Noise Analysis of Fixed Offshore Wind Turbines Considering the Acoustic Properties of the Western Coast of the Korean Peninsula

by Jooyoung Lee, Sangheon Lee, Cheolung Cheong, Songjune Lee and Gwang-se Lee

Energies 2025, 18(23), 6151; https://doi.org/10.3390/en18236151 (registering DOI) - 24 Nov 2025

Abstract

With continued technological advancements, the sizes of fixed-bottom offshore wind turbines have increased, resulting in increased operational noise levels. In this study, we investigated the underwater radiated noise generated by wind turbine operation along the western coast of the Korean Peninsula using numerical [...] Read more.

With continued technological advancements, the sizes of fixed-bottom offshore wind turbines have increased, resulting in increased operational noise levels. In this study, we investigated the underwater radiated noise generated by wind turbine operation along the western coast of the Korean Peninsula using numerical simulations. Using the OpenFAST software, a load analysis of the National Renewable Energy Laboratory 5 MW reference turbine with a jacket substructure was conducted for the various wind speeds defined in Design Load Case 1.2. The load analysis results and gear mesh frequency components were applied as excitation forces in a finite-element-method-based structural–acoustic coupled analysis model to evaluate underwater radiated noise, incorporating the acoustic properties of the seabed along the western coast of the Korean Peninsula and dynamic state of the sea surface. The numerical results were subsequently compared with experimental measurements of the operational noise from wind turbines supported by jacket substructures. The results indicated that, excluding certain frequency bands, the spectral levels were similar across the frequency spectrum. Full article

(This article belongs to the Special Issue Progress and Challenges in Wind Farm Optimization)

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14 pages, 788 KB

Open AccessArticle

Binaural Localization Development and the Effect of SmartSound iQ with SCAN in Children with Cochlear Implants

by Abdulaziz Alasmi, Mada Aljabr, Dalal Alrushaydan, Hassan Yalcouy and Fida Almuhawas

Audiol. Res. 2025, 15(6), 163; https://doi.org/10.3390/audiolres15060163 (registering DOI) - 24 Nov 2025

Abstract

Background: Binaural hearing is crucial for spatial auditory perception, including sound localization. Cochlear implants (CIs) are commonly used in children with congenital deafness to support binaural auditory development, but the extent to which they facilitate effective localization remains unclear. Objective: This study evaluates [...] Read more.

Background: Binaural hearing is crucial for spatial auditory perception, including sound localization. Cochlear implants (CIs) are commonly used in children with congenital deafness to support binaural auditory development, but the extent to which they facilitate effective localization remains unclear. Objective: This study evaluates the impact of CIs on binaural functional auditory development and sound localization in children with congenital deafness, considering factors such as age at implantation, hearing experience, and CI laterality. Methods: Thirty-eight CI-assisted children (aged 4–9 years) underwent directional hearing assessments using the “Erfassung des Richtungshörens bei Kindern (ERKI)” device. Localization accuracy was analyzed across various noise stimuli, and correlations with audiometric parameters and CI history were examined. Results: Localization accuracy improved with age and CI experience. Bilateral CI users outperformed unilateral users, particularly with pulse pink noise stimuli. The use of SmartSound iQ with SCAN technology enhanced localization, especially in younger children. Conclusion: CIs support binaural functional auditory development in children with congenital deafness, with localization skills improving over time. Bilateral implantation and early intervention may further enhance outcomes, warranting continued research. Full article

(This article belongs to the Section Hearing)

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38 pages, 79090 KB

Open AccessArticle

NPPCast: A Compact CNN Integrating Satellite Data for Global Ocean Net Primary Production Forecasts

by Zeming Li, Bizhi Wu, Ziqi Yin, Ruiying Chen and Shanlin Wang

Remote Sens. 2025, 17(23), 3806; https://doi.org/10.3390/rs17233806 (registering DOI) - 24 Nov 2025

Abstract

Skillful prediction of marine net primary production (NPP) on seasonal to multi-year timescales is essential for assessing the ocean’s role in the global carbon cycle and managing marine resources. We introduce NPPCast, a compact convolutional neural network using causal dilated convolutions, and compare [...] Read more.

Skillful prediction of marine net primary production (NPP) on seasonal to multi-year timescales is essential for assessing the ocean’s role in the global carbon cycle and managing marine resources. We introduce NPPCast, a compact convolutional neural network using causal dilated convolutions, and compare its performance with four representative UNet-family models (UNet, VNet, AttUNet, R2UNet). Each model is pre-trained on 36-month output from either Community Earth System Model version 2 forced-ocean–sea-ice (CESM2-FOSI) or interannual varying forcing (CESM2-GIAF) and fine-tuned using three satellite-derived NPP products (the Standard Vertically Generalized Production Model (SVGPM), the Eppley Vertically Generalized Production Model (EVGPM), and the Carbon-based Productivity Model (CbPM)) as well as their multi-product mean (MEAN). Across most tests, NPPCast outperforms the baselines, reducing global root mean square error (RMSE) by 30–56% on MEAN/EVGPM/SVGPM and improving the anomaly correlation coefficient (ACC) by 0.32–0.49 over the best UNet-based alternative. NPPCast also achieves the highest structural similarity to observations and low bias, as seen in scatter and spatial analyses, and attains the highest or tied-highest Nash–Sutcliffe efficiency (NSE) in three of four products. Crucially, NPPCast’s performance remains stable when switching between FOSI and GIAF pre-training datasets, with RMSE changing by at most 2.17%, whereas UNet-family models vary from −41.6% to +42.5%. We show that NPPCast consistently outperforms the Earth system model, sustaining significant predictive skill in contrast to the rapid decline observed in the latter. These results demonstrate that an architecture that maintains performance across different pre-training datasets (CESM2–FOSI and CESM2–GIAF) can yield more accurate and reliable long-range global NPP forecasts than UNet-family models. Full article

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18 pages, 2611 KB

Open AccessArticle

Accessing Altered Metabolic Profile in Acute Deep Vein Thrombosis Through Nuclear Magnetic Resonance Spectroscopy

by Letícia Queiroz da Silva, Thyerre Santana da Costa, Lucas Gelain Martins, Silmara Aparecida de Lima Montalvão, Stephany Cares Huber, Sandra Martins Silva Soares, Ljubica Tasic and Joyce Maria Annichino-Bizzacchi

Int. J. Mol. Sci. 2025, 26(23), 11345; https://doi.org/10.3390/ijms262311345 (registering DOI) - 24 Nov 2025

Abstract

Deep venous thrombosis (DVT) is characterized by the formation of a thrombus within deep veins. The unmet need to identify new biomarkers and causal risk factors in DVT patients has led to the use of novel techniques, such as metabolite analyses. This study [...] Read more.

Deep venous thrombosis (DVT) is characterized by the formation of a thrombus within deep veins. The unmet need to identify new biomarkers and causal risk factors in DVT patients has led to the use of novel techniques, such as metabolite analyses. This study aimed to characterize metabolic alterations in acute DVT patients using ¹H-NMR spectroscopy and determine the persistence of these changes over a six-month follow-up. Metabolomics, particularly ¹H-NMR spectroscopy, was performed on serum samples from acute DVT patients (first 30 days from diagnosis) and healthy controls (HC). Additionally, 10 plasma markers were evaluated using a Luminex kit. A total of 30 patients, with a mean age of 44 ± 12.5 years, primarily women (9 males:21 females), were included. Acute DVT patients showed elevated inflammatory markers, such as IL-6, IL-8, PDGF-AB/BB, and P-selectin, which later decreased in the follow-up group. However, adhesion molecules like sVCAM-1 and sICAM-1 have increased after six months. Metabolomics analysis revealed significantly decreased levels of glutamine, glucose, and branched-chain amino acids (BCAAs), alongside increased lactate levels in acute DVT samples. Metabolomic profiles showed only partial normalization at follow-up, indicating persistent metabolic dysregulation. Overall, the reduced glucose metabolism and increased lactate levels indicate anaerobic metabolism, likely caused by tissue hypoxia due to impaired blood flow. Glutamine, essential for DNA, ATP, and protein synthesis, was notably reduced, potentially impairing endothelial cell proliferation and vascular repair. The presence of adhesion molecules in the follow-up group confirms persistent endothelial dysfunction. These findings suggest that metabolic and endothelial alterations may persist long after acute inflammation resolves in DVT patients. In conclusion, the persistence of metabolic dysregulation suggests chronic metabolic stress in these patients, potentially resulting from ongoing endothelial damage, low-grade inflammation, or altered mitochondrial function due to past tissue hypoxia. Full article

(This article belongs to the Special Issue 25th Anniversary of IJMS: Advances in Molecular Endocrinology and Metabolism)

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23 pages, 330 KB

Open AccessFeature PaperArticle

Intergenerational Transfers in a Tractable Overlapping- Generations Setting

by James Feigenbaum, T. Scott Findley and Sepideh Raei

Mathematics 2025, 13(23), 3769; https://doi.org/10.3390/math13233769 (registering DOI) - 24 Nov 2025

Abstract

Motivated by the Generation-Skipping Transfer Tax (GSTT) in the United States, we examine how varying estate tax rates by the heir’s age affects welfare. Methodologically, we introduce a parsimonious constant elasticity of substitution (CES) bequest utility that is markedly more tractable than the [...] Read more.

Motivated by the Generation-Skipping Transfer Tax (GSTT) in the United States, we examine how varying estate tax rates by the heir’s age affects welfare. Methodologically, we introduce a parsimonious constant elasticity of substitution (CES) bequest utility that is markedly more tractable than the altruistic specifications commonly used in the literature, delivering closed-form optimal rules and transparent parameterization. Using this new framework, we provide a proof of concept showing how transfers from older to younger generations can enhance equilibrium welfare in a dynamically efficient economy à la Samuelson (1975). We embed the tractable bequest utility in a two-period overlapping-generations model with age-dependent estate tax schedules. Numerical exercises—parameterized to the fact that estate tax revenue is small relative to labor income taxation—indicate that lowering the tax rate on bequests to younger heirs (grandchildren) relative to older heirs (adult children) raises the present value of lifetime resources and overall welfare, effectively reversing the logic of the current GSTT. The findings highlight a practical avenue for implementing a “reverse social security” transfer from old to young that can improve welfare in dynamically efficient economies. Full article

(This article belongs to the Special Issue Advances in Theoretical and Empirical Economic Modeling)

26 pages, 1323 KB

Open AccessArticle

Strategic Scenario Interaction: A Computational Framework Based on Game-Theoretic and Quantum-Inspired Modeling

by Ioannis Lomis, Anna-Maria Kanzola and Panagiotis E. Petrakis

Symmetry 2025, 17(12), 2022; https://doi.org/10.3390/sym17122022 (registering DOI) - 24 Nov 2025

Abstract

Strategic foresight often involves navigating deeply uncertain futures through scenario-based reasoning. Traditional methods rely on static narratives or probabilistic models, which fail to capture the dynamic, interacting, and nonexclusive nature of competing futures. This paper introduces a quantum-inspired framework for scenario interaction grounded [...] Read more.

Strategic foresight often involves navigating deeply uncertain futures through scenario-based reasoning. Traditional methods rely on static narratives or probabilistic models, which fail to capture the dynamic, interacting, and nonexclusive nature of competing futures. This paper introduces a quantum-inspired framework for scenario interaction grounded in the mathematical formalism of superposition, interference, and contextuality. Agents are modeled as epistemic learners who iteratively update their preferences across multiple narrative pathways, which are treated as basis states in a conceptual Hilbert space. The simulation combines reinforcement learning with stochastic imitation, producing emergent distributions that resemble quantum-like collapse under feedback. Central to the model is the emergence of symmetries in the scenario structure and learning dynamics. Agents begin with neutral priors, facing a balanced reward landscape, epistemic and normative symmetry that is gradually broken through adaptive behavior. However, statistical symmetries persist at the ensemble level, as agents maintain partial preferences and oscillate among futures. These layered symmetries reflect both the cognitive realism of foresight practices and the mathematical tractability of quantum-inspired systems. The proposed model bridges strategic foresight, game-theoretic interaction, and quantum cognition, and offers a novel computational lens to study how futures are constructed, selected, and stabilized under uncertainty. Full article

(This article belongs to the Special Issue Simulation and Modelling in Natural Sciences, Biomedicine and Engineering III)

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12 pages, 1251 KB

Open AccessArticle

Chemical Profiling of Latvian Propolis: Regional Variations and Botanical Origins

by Freideriki Papakosta, Konstantia Graikou, Evgenia Panou, Fani Hatjina, Leonidas Charistos, Valters Brusbardis, Josef J. M. van der Steen and Ioanna Chinou

Molecules 2025, 30(23), 4533; https://doi.org/10.3390/molecules30234533 (registering DOI) - 24 Nov 2025

Abstract

Propolis is a resinous natural product produced by honeybees from plant exudates and beeswax. Its complex chemical composition varies significantly with geographical origin and seasonal factors. This study aimed to characterize the chemical composition of propolis samples collected from different regions of Latvia [...] Read more.

Propolis is a resinous natural product produced by honeybees from plant exudates and beeswax. Its complex chemical composition varies significantly with geographical origin and seasonal factors. This study aimed to characterize the chemical composition of propolis samples collected from different regions of Latvia using gas chromatography–mass spectrometry (GC-MS). In total, 47 metabolites were identified, with chemical profiles dominated by phenolic acids and their esters—compounds typical of European propolis. Regional variations reflected differences in local vegetation, and two samples exhibited flavonoid constituents indicative of poplar-type botanical sources. The Daugavpils sample, which showed a particularly rich chemical profile, was further fractionated chromatographically, leading to the isolation of twelve metabolites: 2’,4’,6’-trihydroxy-4-methoxy dihydrochalcone, 2’,6’,4-trihydroxy-4’-methoxy dihydrochalcone, 2’,6’-dihydroxy-4,4’-dimethoxy dihydrochalcone, 2’,6’-dihydroxy-4’-methoxy dihydrochalcone, 2’,4’,6’-trihydroxy dihydrochalcone, palmitic acid, benzyl benzoate, cinnamyl cinnamate, pinostrobin, pinostrobin chalcone, pinocembrin, and pinobanksin. Given the limited prior research on Latvian propolis, this study provides valuable insights into its chemical diversity and the influence of regional flora on its composition. Full article

(This article belongs to the Special Issue Bee Product Chemistry: Identification and Characterization of Natural Compounds, 2nd Edition)

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18 pages, 319 KB

Open AccessReview

Role of Angiogenesis in Retinal Diseases and New Advances in Drug Development

by Emma Boey, Humza Zaidi, Tina Tang and Amirfarbod Yazdanyar

Cells 2025, 14(23), 1849; https://doi.org/10.3390/cells14231849 (registering DOI) - 24 Nov 2025

Abstract

Dysregulation of angiogenesis can cause a disruption in oxygen and nutrient delivery, resulting in impaired neural retinal function. Understanding the underlying components involved in its pathophysiology is essential to develop new treatments for preserving and restoring vision. The aim of this review is [...] Read more.

Dysregulation of angiogenesis can cause a disruption in oxygen and nutrient delivery, resulting in impaired neural retinal function. Understanding the underlying components involved in its pathophysiology is essential to develop new treatments for preserving and restoring vision. The aim of this review is to describe the role of angiogenesis in different retinal and choroidal pathologies and evaluate current and emerging anti-angiogenic therapies for retinopathies. Current research articles, focusing on the latest clinical trials from the last two decades, were used to write this review. We discuss normal angiogenesis, in contrast to pathological angiogenesis, in four diseases: retinal vein occlusion (RVO), age-related macular degeneration (AMD), diabetic retinopathy (DR), and retinopathy of prematurity (ROP). Alongside these diseases, this review discusses relevant anti-angiogenic therapies that have been approved for use and are under active investigation through clinical trials for their safety and efficacy. Full article

(This article belongs to the Special Issue Decoding the Complexity of Angiogenesis: Insights into Vascular Formation and Disease)

33 pages, 708 KB

Open AccessReview

A Literature Review of Personalized Large Language Models for Email Generation and Automation

by Rodrigo Novelo, Rodrigo Rocha Silva and Jorge Bernardino

Future Internet 2025, 17(12), 536; https://doi.org/10.3390/fi17120536 (registering DOI) - 24 Nov 2025

Abstract

In 2024, a total of 361 billion emails were sent and received by businesses and consumers each day. Email remains the preferred method of communication for work-related matters, with knowledge workers spending two to five hours a day managing their inboxes. The advent [...] Read more.

In 2024, a total of 361 billion emails were sent and received by businesses and consumers each day. Email remains the preferred method of communication for work-related matters, with knowledge workers spending two to five hours a day managing their inboxes. The advent of Large Language Models (LLMs) has introduced new possibilities for personalized email automation, offering context-aware and stylistically adaptive responses. However, achieving effective personalization introduces technical, ethical, and security challenges. This survey presents a systematic review of 32 papers published between 2021 and 2025, identified using the PRISMA methodology across Google Scholar, IEEE Xplore, and the ACM Digital Library. Our analysis reveals that state-of-the-art email assistants integrate RAG and PEFT with feedback-driven refinement. User-centric interfaces and privacy-aware architectures support these assistants. Nevertheless, these advances also expose systems to new risks such as Trojan plugins and adversarial prompt injections. This highlights the importance of integrated security frameworks. This review provides a structured approach to advancing personalized LLM-based email systems, identifying persistent research gaps in adaptive learning, benchmark development, and ethical design. This work is intended to guide researchers and developers who are looking to create secure, efficient, and human-aligned communication assistants. Full article

(This article belongs to the Special Issue Generative Artificial Intelligence: Systems, Technologies and Applications)

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9 pages, 482 KB

Open AccessEditorial

Electric Arc Furnace Steelmaking

by Ville-Valtteri Visuri and Thomas Echterhof

Metals 2025, 15(12), 1285; https://doi.org/10.3390/met15121285 (registering DOI) - 24 Nov 2025

Abstract

Research and development regarding the electric arc furnace (EAF) started as early as the late 19th century [...] Full article

(This article belongs to the Special Issue Electric Arc Furnace Steelmaking)

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7 pages, 451 KB

Open AccessEditorial

Effect of the Modification of Catalysts on the Catalytic Performance: Overview of the Second Edition

by Anca Vasile, Gianina Dobrescu and Florica Papa

Catalysts 2025, 15(12), 1101; https://doi.org/10.3390/catal15121101 (registering DOI) - 24 Nov 2025

Abstract

One of the major challenges in catalysis is developing catalysts that demonstrate superior catalytic activity, selectivity, and durability [...] Full article

(This article belongs to the Special Issue Effect of the Modification of Catalysts on the Catalytic Performance, 2nd Edition)

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8 pages, 4585 KB

Open AccessCase Report

Case Report: Comprehensive Imaging and Clinical Outcomes of Chondro-Osseous Respiratory Epithelial Adenomatoid Hamartoma (COREAH) in a Dog

by Won-Keun Park, Jun-Won Yoon, Chan-Sik Nam, Dong-Min Choi, Kwang-Sup Lee, Yeon-Jin Kim, Tae-Jung Dan, Dong-Hoon Shin and Hee-Myung Park

Animals 2025, 15(23), 3389; https://doi.org/10.3390/ani15233389 (registering DOI) - 24 Nov 2025

Abstract

The aim of this case report is to describe comprehensive imaging such as CT scanning, endoscopy, histopathology, and clinical outcomes following medical and endoscopic treatment. A 5-year-old spayed female Chihuahua presented with chronic unilateral nasal discharge, congestion, and intermittent stertor, unresponsive to initial [...] Read more.

The aim of this case report is to describe comprehensive imaging such as CT scanning, endoscopy, histopathology, and clinical outcomes following medical and endoscopic treatment. A 5-year-old spayed female Chihuahua presented with chronic unilateral nasal discharge, congestion, and intermittent stertor, unresponsive to initial antibiotics and steroids. Further diagnostics, including endoscopy, revealed a cystic lesion with osseous fragments in the left nasal cavity, while CT imaging identified a soft tissue mass with associated bone resorption. Histopathology confirmed chondro-osseous respiratory epithelial adenomatoid hamartoma (COREAH), a rare benign lesion characterized by respiratory epithelium, fibrovascular proliferation, and osseous components, along with lymphoplasmacytic and eosinophilic inflammation. Clinical signs improved following endoscopic aspiration and drainage, which restored nasal cavity space. This case highlights the importance of combining endoscopy, advanced imaging, and histopathology for accurate diagnosis and effective management of COREAH, a condition with potential for recurrence. The use of endoscopy enabled real-time visualization and precise tissue sampling, distinguishing this case from others relying solely on imaging. This report contributes to the limited veterinary literature on COREAH and underscores the need for long-term monitoring due to its uncertain pathogenesis and variable presentation. Full article

(This article belongs to the Section Veterinary Clinical Studies)

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22 pages, 3366 KB

Open AccessArticle

Leveraging Meteorological Reanalysis Models to Characterize Wintertime Cold Air Pool Events Across the Western United States from 2000 to 2022

by Jacob Boomsma and Heather A. Holmes

Atmosphere 2025, 16(12), 1325; https://doi.org/10.3390/atmos16121325 (registering DOI) - 24 Nov 2025

Abstract

Wintertime cold air pools (CAPs) are common across the Western United States and result in cold, dense air trapped in valley basins. The CAPs are characterized by a stable atmospheric boundary layer, leading to cold air and low wind speeds. While CAP formation [...] Read more.

Wintertime cold air pools (CAPs) are common across the Western United States and result in cold, dense air trapped in valley basins. The CAPs are characterized by a stable atmospheric boundary layer, leading to cold air and low wind speeds. While CAP formation occurs nightly, the CAP conditions can persist into daytime and often last for multiple days (i.e., persistent cold air pool or PCAP), resulting in poor air quality in populated areas. The presence and strength of CAPs can be calculated using data from radiosondes, surface weather stations at varying elevations, and indirectly through air pollution monitors. Because vertical profile data are often limited to twice daily radiosondes, and are spatially sparse, numerical models can be a useful substitute. This work uses the European Centre for Medium-Range Weather Forecasts (ECMWFs) Reanalysis v5 (ERA) atmospheric reanalysis to provide data to classify wintertime CAP events without radiosonde observations. An automated CAP classification method using ERA outputs is evaluated using afternoon radiosonde observations in six cities (Salt Lake City, Utah; Reno, Nevada; Boise, Idaho; Denver, Colorado; Las Vegas, Nevada; Medford, and Oregon). Using this CAP determination method, days with CAP events are analyzed in 13 locations, 6 with radiosonde observations and 7 without, including the Central valley of California. The CAP classification method is evaluated at these 13 locations across the Western US over the study period of 2000–2022. The results show that the ERA model performs similarly to the radiosonde observations when used to identify CAP events. Therefore, ERA can be used to provide a reasonable estimate of CAP conditions when radiosonde data are unavailable. Providing consistent CAP classifications across space and time are necessary for regional scale CAP studies, such as human health effects modeling over large spatial and temporal scales. Full article

(This article belongs to the Section Meteorology)

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19 pages, 1656 KB

Open AccessArticle

Research on the Bandgap Characteristics and Vibration Isolation and Sound Insulation Performance of Hollowed-Out Composite Panels

by Haiyang Zhao, Zhenyu Yang and Hongbo Zhang

Appl. Sci. 2025, 15(23), 12451; https://doi.org/10.3390/app152312451 (registering DOI) - 24 Nov 2025

Abstract

This study investigates the application of phononic crystal plates for automotive vibration and noise attenuation through a combined material–structure design approach. Four materials—aluminum, lead, epoxy resin, and plexiglass—were selected to construct a composite plate with a low-density matrix and high-density metallic inclusions. Finite [...] Read more.

This study investigates the application of phononic crystal plates for automotive vibration and noise attenuation through a combined material–structure design approach. Four materials—aluminum, lead, epoxy resin, and plexiglass—were selected to construct a composite plate with a low-density matrix and high-density metallic inclusions. Finite element modeling in COMSOL Multiphysics identified organic glass–lead as the optimal configuration, balancing wide bandgap performance with low-frequency characteristics and lightweight requirements. Parametric analysis demonstrated that rectangular inclusions provide the widest bandgap under equal area conditions, and increasing their volume fraction shifts the bandgap to lower frequencies while broadening its width. The study verifies the reliability of the finite element method (FEM) and further explains the formation mechanism of the bandgap. This study proposes a phononic crystal plate structure with optimal performance: a rectangular phononic crystal plate with a length of A = 20 mm and a height of B = 10 mm serves as the matrix, and four identical rectangular inclusions each with an area of S = 16 mm² are embedded in it. The matrix material is organic glass, while the material of the inclusions is lead. The resulting optimized structure exhibits a complete Lamb wave bandgap from 6.29 to 22.03 kHz, with strong elastic wave attenuation extending over 6.00–30.00 kHz. Acoustically, it achieves sound transmission loss (STL) exceeding 130 dB within 5.85–27.91 kHz, peaking at 143.99 dB. These results verify the structure’s dual functionality in simultaneous vibration isolation and sound attenuation within the same frequency range, demonstrating the potential of phononic crystal plates for targeted noise and vibration control in automotive engines and rotating machinery. Full article

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7 pages, 2547 KB

Open AccessCase Report

Paraneoplastic Hypereosinophilia Revealing Disseminated Colorectal Signet Ring Cell Carcinoma

by Saša Rink, Sabina Škrgat, Matevž Harlander and Polona Mlakar

Gastrointest. Disord. 2025, 7(4), 74; https://doi.org/10.3390/gidisord7040074 (registering DOI) - 24 Nov 2025

Abstract

Background: Hypereosinophilia, defined as a peripheral blood eosinophil count greater than 1.5 × 10⁹/L, can arise from allergic, infectious, autoimmune, or malignant conditions. In solid tumors, it is rare and most often linked to mucin-secreting carcinomas, while on extremely rare [...] Read more.

Background: Hypereosinophilia, defined as a peripheral blood eosinophil count greater than 1.5 × 10⁹/L, can arise from allergic, infectious, autoimmune, or malignant conditions. In solid tumors, it is rare and most often linked to mucin-secreting carcinomas, while on extremely rare occasions, it accompanies signet ring cell carcinoma, a highly aggressive form of adenocarcinoma. Case Presentation: A 64-year-old woman presented with dyspnea and hypereosinophilia (2.9 × 10⁹/L). She was admitted with suspected eosinophilic pneumonia, but extensive testing was inconclusive. After bone marrow biopsy, her condition deteriorated; histology revealed metastatic signet ring cell carcinoma. PET/CT showed skeletal metastases without apparent local recurrence, although colonoscopy could not be performed to definitively rule it out. Retrospective review uncovered a 2 mm rectal polyp with signet ring cell carcinoma (SRCC) removed two years earlier. Peripheral eosinophilia progressively increased from 0.16 × 10⁹/L ten months earlier to a peak of 4.29 × 10⁹/L one month prior to admission. She died four weeks after discharge. Conclusions: To the best of our knowledge, this case represents one of the smallest reported primary colorectal SRCC lesions (2 mm) presenting with disseminated disease and paraneoplastic hypereosinophilia as the first diagnostic clue. Monitoring peripheral blood eosinophil counts may provide additional insight into disease activity and prognosis in solid tumors. Full article

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20 pages, 1749 KB

Open AccessArticle

Development of Hourly Resolution Air Temperature Across Titicaca Lake on Auxiliary ERA5 Variables and Machine Learning-Based Gap-Filling

by Jimmy W. Sirpa-Poma, Juan Calle, Elvis Uscamayta-Ferrano, Jorge Molina-Carpio, Frederic Satgé, Osmar Cuentas Toledo, Ricardo Duran, Paula Pacheco Mollinedo, Riaz Hussain and Ramiro Pillco-Zolá

Sensors 2025, 25(23), 7165; https://doi.org/10.3390/s25237165 (registering DOI) - 24 Nov 2025

Abstract

This article presents an innovative procedure that combines advanced quality control (QC) methods with machine learning (ML) techniques to produce reliable, continuous, high-resolution meteorological data. The approach was applied to hourly air temperature records from six automatic weather stations located around Lake Titicaca [...] Read more.

This article presents an innovative procedure that combines advanced quality control (QC) methods with machine learning (ML) techniques to produce reliable, continuous, high-resolution meteorological data. The approach was applied to hourly air temperature records from six automatic weather stations located around Lake Titicaca in the Altiplano region of South America. The raw dataset contained time gaps, inconsistencies, and outliers. To address these, the QC stage employed Interquartile Range, Biweight, and Local Outlier Factor (LOF) statistics, resulting in a clean dataset. Two gap-filling methods were implemented: a spatial approach using time series from nearby stations and a temporal approach based on each station’s time series and selected variables from the ERA5-Land reanalysis. Several ML models were also employed in this process: Random Forest (RF), Support Vector Machine (SVM), Stacking (STACK), and AdaBoost (ADA). Model performance was evaluated on a validation subset (30% of station data). The RF model achieved the best results, with R² values up to 0.9 and Root Mean Square Error (RMSE) below 1.5 °C. The spatial approach performed best when stations were strongly correlated, while the temporal approach was more suitable for locations with low inter-station correlation and high local variability. Overall, the procedure substantially improved data reliability and completeness, and it can be extended to other meteorological variables. Full article

(This article belongs to the Section Environmental Sensing)

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21 pages, 317 KB

Open AccessReview

The Latest Diagnostic Imaging Technologies and AI: Applications for Melanoma Surveillance Toward Precision Oncology

by Alessandro Valenti, Fabio Valenti, Stefano Giuliani, Simona di Martino, Luca Neroni, Cristina Sorino, Pietro Sollena, Flora Desiderio, Fulvia Elia, Maria Teresa Maccallini, Michelangelo Russillo, Italia Falcone and Antonino Guerrisi

Computers 2025, 14(12), 512; https://doi.org/10.3390/computers14120512 (registering DOI) - 24 Nov 2025

Abstract

In recent years, the medical field has witnessed the rapid expansion and refinement of omics and imaging technologies, which have profoundly transformed patient surveillance and monitoring strategies, with stage-adapted protocols and cross-sectional imaging important in high-risk follow-up. In the melanoma context, diagnostic imaging [...] Read more.

In recent years, the medical field has witnessed the rapid expansion and refinement of omics and imaging technologies, which have profoundly transformed patient surveillance and monitoring strategies, with stage-adapted protocols and cross-sectional imaging important in high-risk follow-up. In the melanoma context, diagnostic imaging plays a pivotal role in disease staging, follow-up and evaluation of therapeutic response. Moreover, the emergence of Artificial Intelligence (AI) has further driven the transition toward precision medicine, emphasizing the complexity and individuality of each patient: AI/Radiomics pipelines are increasingly supporting lesion characterization and response prediction within clinical workflows. Consequently, it is essential to emphasize the significant potential of quantitative imaging techniques and radiomic applications, as well as the role of AI in improving diagnostic accuracy and enabling personalized oncologic treatment. Early evidence demonstrates increased sensitivity and specificity, along with a reduction in unnecessary biopsies and imaging procedures, within selected care approaches. In this review, we will outline the current clinical guidelines for the management of melanoma patients and use them as a framework to explore and evaluate advanced imaging approaches and their potential contributions. Specifically, we compare the recommendations of major societies such as NCCN, which advocates more intensive imaging for stages IIB–IV; ESMO and AIOM, which recommend symptom-driven surveillance; and SIGN, which discourages routine imaging in the absence of clinical suspicion. Furthermore, we will describe the latest imaging technologies and the integration of AI-based tools for developing predictive models to actively support therapeutic decision-making and patient care. The conclusions will focus on the prospective role of novel imaging modalities in advancing precision oncology, improving patient outcomes and optimizing the allocation of clinical resources. Overall, the current evidences support a stage-adapted surveillance strategy (ultrasound ± elastography for lymph node regions, targeted brain MRI in high-risk patients, selective use of DECT or total-body MRI) combined with rigorously validated AI-based decision support systems to personalize follow-up, streamline workflows and optimize resource utilization. Full article

(This article belongs to the Special Issue Applications of Machine Learning and Artificial Intelligence for Healthcare)

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34 pages, 3961 KB

Open AccessReview

Cellular and Molecular Mechanisms of Wound Repair: From Biology to Therapeutic Innovation

by Caijun Jin, Yongxun Jin, Zhiyuan Ding, Kong Srey Nuch, Mira Han, JungHee Shim, Pham Ngoc Chien and Chan Yeong Heo

Cells 2025, 14(23), 1850; https://doi.org/10.3390/cells14231850 (registering DOI) - 24 Nov 2025

Abstract

Wound repair preserves tissue integrity through four overlapping phases—hemostasis, inflammation, proliferation, and remodeling—coordinated by platelets, neutrophils, macrophages, fibroblasts, keratinocytes, endothelial cells, and stem/progenitor cells acting with growth factors, chemokines, extracellular matrix, and intracellular signaling. Disruption of these programs results in chronic non-healing wounds [...] Read more.

Wound repair preserves tissue integrity through four overlapping phases—hemostasis, inflammation, proliferation, and remodeling—coordinated by platelets, neutrophils, macrophages, fibroblasts, keratinocytes, endothelial cells, and stem/progenitor cells acting with growth factors, chemokines, extracellular matrix, and intracellular signaling. Disruption of these programs results in chronic non-healing wounds or fibrotic scarring. Recent work delineates microbial influences, epigenetic and transcriptomic regulation, and cellular heterogeneity resolved by single-cell and spatial omics. Concurrent advances in biomaterials, engineered scaffolds, stem cell-derived products, and genome-targeted approaches are enabling mechanism-based therapies. Persistent challenges include wound heterogeneity, systemic modifiers such as diabetes and aging, and safe, effective delivery of biologics. This review summarizes cellular and molecular mechanisms of cutaneous repair, outlines deviations that underlie pathological healing, and evaluates emerging concepts and translational strategies. Integrating classical models with contemporary insights supports the development of precision wound medicine and personalized interventions to improve outcomes and quality of life. Full article

(This article belongs to the Special Issue Cellular and Molecular Mechanisms of Wound Repair)

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