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22 pages, 8003 KiB

Open AccessArticle

Uridine, a Therapeutic Nucleoside, Exacerbates Alcoholic Liver Disease via SRC Kinase Activation: A Network Toxicology and Molecular Dynamics Perspective

by Zhenyu Liu, Zhihao Wang, Jie Wang, Shiquan Xu and Tong Zhang

Int. J. Mol. Sci. 2025, 26(12), 5473; https://doi.org/10.3390/ijms26125473 (registering DOI) - 7 Jun 2025

Abstract

This study looked into the underlying mechanisms and causal relationship between alcoholic liver disease (ALD) and the blood metabolite uridine using a variety of analytical methods, such as Mendelian randomization and molecular dynamics simulations. We discovered uridine to be a possible hepatotoxic agent [...] Read more.

This study looked into the underlying mechanisms and causal relationship between alcoholic liver disease (ALD) and the blood metabolite uridine using a variety of analytical methods, such as Mendelian randomization and molecular dynamics simulations. We discovered uridine to be a possible hepatotoxic agent aggravating ALD by using Mendelian randomization (MR) analysis with genome-wide association study (GWAS) data from 1416 ALD cases and 217,376 controls, as well as with 1091 blood metabolites and 309 metabolite concentration ratios as exposure factors. According to network toxicology analysis, uridine interacts with important targets such as SRC, FYN, LYN, ADRB2, and GSK3B. The single-cell RNA sequencing analysis of ALD tissues revealed that SRC was upregulated in hepatocytes and activated hepatic stellate cells. Subsequently, we determined the stable binding between uridine and SRC through molecular docking and molecular dynamics simulation (RMSD = 1.5 ± 0.3 Å, binding energy < −5.0 kcal/mol). These targets were connected to tyrosine kinase activity, metabolic reprogramming, and GPCR signaling by Gene Ontology (GO) and KEGG studies. These findings elucidate uridine’s role in ALD progression via immunometabolic pathways, offering novel therapeutic targets for precision intervention. These findings highlight the necessity of systems biology frameworks in drug safety evaluation, particularly for metabolites with dual therapeutic and toxicological roles. Full article

(This article belongs to the Special Issue Network Pharmacology: An Emerging Field in Drug Discovery)

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25 pages, 1138 KiB

Open AccessReview

Harnessing Microbiome, Bacterial Extracellular Vesicle, and Artificial Intelligence for Polycystic Ovary Syndrome Diagnosis and Management

by Bhawna Kushawaha, Tial T. Rem and Emanuele Pelosi

Biomolecules 2025, 15(6), 834; https://doi.org/10.3390/biom15060834 (registering DOI) - 7 Jun 2025

Abstract

Polycystic ovary syndrome (PCOS) affects 6–19% of reproductive-age women worldwide, yet diagnosis remains challenging due to heterogeneous presentations and symptoms overlapping with other endocrine disorders. Recent studies have shown that gut dysbiosis plays a significant role in PCOS pathophysiology, with bacterial extracellular vesicles [...] Read more.

Polycystic ovary syndrome (PCOS) affects 6–19% of reproductive-age women worldwide, yet diagnosis remains challenging due to heterogeneous presentations and symptoms overlapping with other endocrine disorders. Recent studies have shown that gut dysbiosis plays a significant role in PCOS pathophysiology, with bacterial extracellular vesicles (BEVs) functioning as critical mediators of the gut–ovary axis. BEVs carry distinct cargos in PCOS patients—including specific miRNAs and inflammatory proteins—and show promise for both diagnostic and therapeutic applications. Artificial intelligence (AI) is emerging as a promising significant tool in PCOS research due to improved diagnostic accuracy and the capability to analyze complex datasets combining microbiome, BEV, and clinical parameters. These integrated approaches have the potential to better address PCOS multifactorial nature, enabling improved phenotypic classification and personalized treatment strategies. This review examines recent advances in the last 25 years in microbiome, BEV, and AI applications in PCOS research using PubMed, Web of Science, and Scopus databases. We explore the diagnostic potential of the AI-driven analysis of microbiome and BEV profiles, and address ethical considerations including data privacy and algorithmic bias. As these technologies continue to evolve, they hold increasing potential for the improvement of PCOS diagnosis and management, including the development of safer, more precise, and effective interventions. Full article

(This article belongs to the Special Issue Molecular Aspects of Female Infertility)

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17 pages, 525 KiB

Open AccessArticle

Shadow Fleets: A Growing Challenge in Global Maritime Commerce

by Emilio Rodriguez-Diaz, Juan Ignacio Alcaide and Nieves Endrina

Appl. Sci. 2025, 15(12), 6424; https://doi.org/10.3390/app15126424 (registering DOI) - 7 Jun 2025

Abstract

Shadow fleets, operating covertly in global maritime commerce, have emerged as a significant challenge to international regulatory frameworks and trade policies. This paper introduces a novel conceptual framework that distinguishes between ‘dark fleets’ and ‘gray fleets’, offering a more nuanced understanding of these [...] Read more.

Shadow fleets, operating covertly in global maritime commerce, have emerged as a significant challenge to international regulatory frameworks and trade policies. This paper introduces a novel conceptual framework that distinguishes between ‘dark fleets’ and ‘gray fleets’, offering a more nuanced understanding of these clandestine maritime activities. Through a comprehensive methodological approach integrating a literature review, case studies, and data analysis, we examine the characteristics, operational strategies, and implications of shadow fleets. Our research reveals that shadow fleets have expanded rapidly, now accounting for approximately 10% of global seaborne oil transportation. We identify key indicators of shadow fleet operations, including disabled Automatic Identification System (AIS) transmitters, inconsistent vessel information, unusual behavior patterns, obscure ownership structures, and the use of aging vessels. This paper highlights the economic disruptions caused by shadow fleets, their role in circumventing international sanctions, and the significant environmental and safety risks they pose. The study underscores the regulatory challenges in addressing shadow fleets, particularly their exploitation of flags of convenience and complex ownership structures. We propose a multifaceted approach to tackling these challenges, emphasizing the need for advanced technological solutions, enhanced international collaboration, and adaptive ocean governance frameworks. This research contributes to the evolving field of maritime security and policy, offering insights for policymakers, industry stakeholders, and researchers into developing strategies to mitigate the risks posed by shadow fleets in global maritime commerce. Full article

(This article belongs to the Special Issue Risk and Safety of Maritime Transportation)

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17 pages, 3228 KiB

Open AccessArticle

Boosting Hydroformylation via Reactant Enrichment in Covalent Triazine Frameworks with Atomically Dispersed Rh

by Xinguo Li, Xiangjie Zhang, Gaolei Qin, Peng He and Yajuan Hao

Materials 2025, 18(12), 2691; https://doi.org/10.3390/ma18122691 (registering DOI) - 7 Jun 2025

Abstract

Hydroformylation is one of the most widely applied homogeneous catalytic processes in the chemical industry, constituting the predominant manufacturing platform for aldehyde synthesis at commercial scales. Nevertheless, hydroformylation shares with traditional homogeneous catalysis the inherent limitation of difficult catalyst recovery and recycling. Developing [...] Read more.

Hydroformylation is one of the most widely applied homogeneous catalytic processes in the chemical industry, constituting the predominant manufacturing platform for aldehyde synthesis at commercial scales. Nevertheless, hydroformylation shares with traditional homogeneous catalysis the inherent limitation of difficult catalyst recovery and recycling. Developing heterogeneous catalysts for such reactions is thus critically needed. Herein, a stable nitrogen-rich covalent triazine framework (CTF) was synthesized via a mild Friedel–Crafts alkylation method and employed as a support for Rh single-atom catalysts (Rh/CTF-TPA). In the hydroformylation of 1-decene, the Rh/CTF-TPA catalyst exhibits an exceptional reaction efficiency (TOF > 1900 h⁻¹), outperforming the homogeneous Rh(CO)₂(acac). Experimental and characterization results revealed that the CTF support enhances catalytic performance through two key mechanisms: (1) strong enrichment of reactants within its special structure, and (2) efficient dispersion of Rh single-atom sites stabilized by abundant nitrogen coordination. This work demonstrates a rational design strategy for heterogeneous hydroformylation catalysts by leveraging nitrogen-rich porous frameworks to synergistically optimize metal anchoring and reactant enrichment, offering a promising alternative to conventional homogeneous systems. Full article

(This article belongs to the Special Issue Adsorption Materials and Their Applications (2nd Edition))

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15 pages, 773 KiB

Open AccessReview

Modulation of Plant Interactions with Whitefly and Whitefly-Borne Viruses by Salicylic Acid Signaling Pathway: A Review

by Shi-Xing Zhao, Su-Dan Wang, Yin-Quan Liu and Li-Long Pan

Viruses 2025, 17(6), 825; https://doi.org/10.3390/v17060825 (registering DOI) - 7 Jun 2025

Abstract

Whiteflies of the Bemisia tabaci complex, along with the plant viruses they transmit, pose significant challenges to crop production worldwide. Upon infestation or infection, intimate interactions occur between plant hosts and these pests, influencing the spread and severity of pest-related epidemics in natural [...] Read more.

Whiteflies of the Bemisia tabaci complex, along with the plant viruses they transmit, pose significant challenges to crop production worldwide. Upon infestation or infection, intimate interactions occur between plant hosts and these pests, influencing the spread and severity of pest-related epidemics in natural and agricultural ecosystems. This review explores the role of the salicylic acid (SA) signaling pathway, an essential component of plant defense, in modulating plant interactions with whiteflies and whitefly-borne viruses. We first outline the biosynthesis and signal transduction of SA. We then analyze how whitefly infestation activates the SA signaling pathway and how this defense response affects whitefly performance and preference. Next, we explore the interactions between the SA signaling pathway and whitefly-borne plant viruses, especially begomoviruses, which often activate and manipulate this pathway. We also examine how the SA signaling pathway influences plant–whitefly–virus tripartite interactions, highlighting the significant role of this defense pathway in whitefly-induced changes in plant–virus interactions and virus-induced changes in plant–whitefly interactions. Finally, we identify key areas for future research to further unravel the complexities of plant interactions with whiteflies and whitefly-borne viruses. Full article

(This article belongs to the Section Viruses of Plants, Fungi and Protozoa)

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18 pages, 5154 KiB

Open AccessArticle

Monitoring Nitrogen Nutrition in Ginkgo Using Unmanned Aerial Vehicle RGB Imagery and the Gaussian Process Regression Model

by Xinyu Tao, Fuliang Cao, Guibin Wang, Hao Liu, Saiting Qiu, Tingting Dai, Jimei Han, Sinong Yu and Kai Zhou

Forests 2025, 16(6), 965; https://doi.org/10.3390/f16060965 (registering DOI) - 7 Jun 2025

Abstract

Nitrogen nutrition monitoring is crucial in agriculture and forestry. With the development of Unmanned Aerial Vehicle (UAV) imaging technology, its application in nitrogen nutrition monitoring has gained attention. Traditional regression methods often struggle to accurately capture the nonlinear relationships between image features and [...] Read more.

Nitrogen nutrition monitoring is crucial in agriculture and forestry. With the development of Unmanned Aerial Vehicle (UAV) imaging technology, its application in nitrogen nutrition monitoring has gained attention. Traditional regression methods often struggle to accurately capture the nonlinear relationships between image features and nitrogen nutrition parameters. This study introduces Gaussian regression models to better model the relationship between UAV image features and nitrogen nutrition in Ginkgo. UAV RGB imagery of three-year-old Ginkgo biloba L. seedlings was used to extract nitrogen-related image features. Gaussian regression models were employed to select and model these features, creating regression models for nitrogen accumulation and nitrogen content in Ginkgo. The accuracy of the models was validated. Results indicated that the optimal canopy type for monitoring nitrogen accumulation in Ginkgo was the shadowed canopy, with the color feature BMR being the most important feature. For monitoring nitrogen content, sunlight and shadow canopy types were suitable, with BMR and b* being the key features. Gaussian regression demonstrated superior accuracy and robustness compared to traditional regression models. This study emphasizes the potential of Gaussian regression models to improve nitrogen monitoring through UAV imagery, offering valuable applications in precision agriculture and forestry management, particularly in supporting nitrogen fertilization and nutrition management for Ginkgo. Full article

(This article belongs to the Section Forest Inventory, Modeling and Remote Sensing)

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19 pages, 5272 KiB

Open AccessArticle

Biomechanics of Spiral Fractures: Investigating Periosteal Effects Using Digital Image Correlation

by Ghaidaa A. Khalid, Ali Al-Naji and Javaan Chahl

J. Imaging 2025, 11(6), 187; https://doi.org/10.3390/jimaging11060187 (registering DOI) - 7 Jun 2025

Abstract

Spiral fractures are a frequent clinical manifestation of child abuse, particularly in non-ambulatory infants. Approximately 50% of fractures in children under one year of age are non-accidental, yet differentiating between accidental and abusive injuries remains challenging, as no single fracture type is diagnostic [...] Read more.

Spiral fractures are a frequent clinical manifestation of child abuse, particularly in non-ambulatory infants. Approximately 50% of fractures in children under one year of age are non-accidental, yet differentiating between accidental and abusive injuries remains challenging, as no single fracture type is diagnostic in isolation. The objective of this study is to investigate the biomechanics of spiral fractures in immature long bones and the role of the periosteum in modulating fracture behavior under torsional loading. Methods: Paired metatarsal bone specimens from immature sheep were tested using controlled torsional loading at two angular velocities (90°/s and 180°/s). Specimens were prepared through potting, application of a base coat, and painting of a speckle pattern suitable for high-speed digital image correlation (HS-DIC) analysis. Both periosteum-intact and periosteum-removed groups were included. Results: Spiral fractures were successfully induced in over 85% of specimens. Digital image correlation revealed localized diagonal tensile strain at the fracture initiation site, with opposing compressive zones. Notably, bones with intact periosteum exhibited broader tensile stress regions before and after failure, suggesting a biomechanical role in constraining deformation. Conclusion: This study presents a novel integration of high-speed digital image correlation (DIC) with paired biomechanical testing to evaluate the periosteum’s role in spiral fracture formation—an area that remains underexplored. The findings offer new insight into the strain distribution dynamics in immature long bones and highlight the periosteum’s potential protective contribution under torsional stress. Full article

(This article belongs to the Section Medical Imaging)

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36 pages, 2842 KiB

Open AccessArticle

Dynamic Reconfiguration of Active Distribution Network Based on Improved Equilibrium Optimizer

by Chaoxue Wang and Yue Zhang

Appl. Sci. 2025, 15(12), 6423; https://doi.org/10.3390/app15126423 (registering DOI) - 7 Jun 2025

Abstract

To better address the reconfiguration problem of distribution networks with distributed generation (DG), a dynamic reconfiguration model is developed that accounts for the time-varying characteristics of both load demand and DG output. First, an enhanced fuzzy C-means clustering method is proposed for load [...] Read more.

To better address the reconfiguration problem of distribution networks with distributed generation (DG), a dynamic reconfiguration model is developed that accounts for the time-varying characteristics of both load demand and DG output. First, an enhanced fuzzy C-means clustering method is proposed for load period partitioning, which integrates spatiotemporal load features and optimal network structure similarity to improve clustering accuracy. Second, an adaptive ordered loop-based feasibility judgment model is developed to filter infeasible and low-quality solutions based on operational constraints. Third, an improved Equilibrium Optimizer (IEO), integrating Tent chaotic initialization, elite sorting, and mutation-crossover strategies, is proposed for multi-objective optimization. The proposed framework is validated on IEEE 33- and 69-bus systems. In the IEEE 33-bus system, it achieves a 44.8% reduction in power losses and a 35.9% improvement in voltage deviation. In the IEEE 69-bus system, power loss is reduced by 40.1%, and voltage deviation by 40.5%, demonstrating the proposed method’s robustness, adaptability, and effectiveness across systems of varying scales. Full article

17 pages, 5522 KiB

Open AccessArticle

Comparison of Selected Ensemble Supervised Learning Algorithms Used for Meteorological Normalisation of Particulate Matter (PM₁₀)

by Karolina Gora and Mateusz Rzeszutek

Sustainability 2025, 17(12), 5274; https://doi.org/10.3390/su17125274 (registering DOI) - 7 Jun 2025

Abstract

Air pollution, particularly PM₁₀ particulate matter, poses significant health risks related to respiratory and cardiovascular diseases as well as cancer. Accurate identification of PM₁₀ reduction factors is therefore essential for developing effective sustainable development strategies. According to the current state of [...] Read more.

Air pollution, particularly PM₁₀ particulate matter, poses significant health risks related to respiratory and cardiovascular diseases as well as cancer. Accurate identification of PM₁₀ reduction factors is therefore essential for developing effective sustainable development strategies. According to the current state of knowledge, machine learning methods are most frequently employed for this purpose due to their superior performance compared to classical statistical approaches. This study evaluated the performance of three machine learning algorithms—Decision Tree (CART), Random Forest, and Cubist Rule—in predicting PM₁₀ concentrations and estimating long-term trends following meteorological normalisation. The research focused on Tarnów, Poland (2010–2022), with comprehensive consideration of meteorological variability. The results demonstrated superior accuracy for the Random Forest and Cubist models (R² ~0.88–0.89, RMSE ~14 μg/m³) compared to CART (RMSE 19.96 μg/m³). Air temperature and boundary layer height emerged as the most significant predictive variables across all algorithms. The Cubist algorithm proved particularly effective in detecting the impact of policy interventions, making it valuable for air quality trend analysis. While the study confirmed a statistically significant annual decrease in PM₁₀ concentrations (0.83–1.03 μg/m³), pollution levels still exceeded both the updated EU air quality standards from 2024 (Directive (EU) 2024/2881), which will come into force in 2030, and the more stringent WHO guidelines from 2021. Full article

(This article belongs to the Section Pollution Prevention, Mitigation and Sustainability)

16 pages, 6482 KiB

Open AccessArticle

Passive Heat Stimuli as a Systemic Training in Elite Endurance Athletes: A New Strategy to Promote Greater Metabolic Flexibility

by Sergi Cinca-Morros, Martin Burtscher, Fernando Benito-López and Jesús Álvarez-Herms

J. Funct. Morphol. Kinesiol. 2025, 10(2), 220; https://doi.org/10.3390/jfmk10020220 (registering DOI) - 7 Jun 2025

Abstract

Objectives: The ability to efficiently regulate body temperature is crucial during endurance activities such as trail running, especially during competitive events in hot conditions. Over the past decade, passive hyperthermia exposure has grown significantly in popularity as a means of improving acclimatization and [...] Read more.

Objectives: The ability to efficiently regulate body temperature is crucial during endurance activities such as trail running, especially during competitive events in hot conditions. Over the past decade, passive hyperthermia exposure has grown significantly in popularity as a means of improving acclimatization and performance in hot environments. The present study aims to compare the physiological changes that occur in a group of professional athletes due to passive sauna exposure (80–90 °C) and their own response to maximal aerobic performance. Methods: Twelve professional trail runners (eight men and four women) were tested in three conditions: (i) baseline; (ii) before; and (iii) after (a) passive dry sauna exposure and (b) a maximal endurance test. In both cases, physiological parameters such as heart rate, tympanic temperature, arterial and muscle oxygen saturation, and blood concentrations of glucose, total cholesterol, high-density lipoprotein (HDL) and hemoglobin were measured. Results: Sauna exposure produced similar trends in cardiovascular and metabolic responses to those occurring during exercise, but at a much lower physiological level. Glucose and HDL levels were both significantly elevated (or tended to be so) after sauna and exercise (p < 0.03 and p < 0.01, respectively). Athletes who mobilized the sum of substrates (glucose and HDL) performed the exercise test faster (r = −0.76; p < 0.004). The response of arterial oxygen saturation (decreased) was similar during sauna and exercise, but opposite at the muscular level (increased during sauna and decreased during exercise). Additionally, inter-individual variability in responses was noted for most of the other parameters, suggesting the existence of ‘responders’ and ‘non-responders’ to thermal stimuli. Conclusions: The physiological responses of trained endurance athletes are moderately impacted by passive sauna use. However, individual changes could be correlated with endurance performance and optimizing individualization. Heat stimuli promote different physiological responses in terms of cardiac function, oxygen kinetics and substrate mobilization, albeit to a lesser extent than exercise. Greater substrate mobilization during maximal endurance exercise was found to be correlated with better performance. Further studies are needed to explore the concepts of metabolic flexibility, as described here, and how heat exposure may improve systemic health and performance. Full article

(This article belongs to the Special Issue Physiological Adaptations and Improvements in Sports Performance through Training in Adverse Environments)

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14 pages, 15575 KiB

Open AccessArticle

Quasi-Discrete Time Crystals in the Quasiperiodically Driven Lipkin–Meshkov–Glick Model

by Sk Anisur, Wensheng Vincent Liu and Sayan Choudhury

Entropy 2025, 27(6), 609; https://doi.org/10.3390/e27060609 (registering DOI) - 7 Jun 2025

Abstract

A discrete time crystal (DTC) is a remarkable non-equilibrium phase of matter characterized by the persistent sub-harmonic oscillations of physical observables in periodically driven many-body systems. Motivated by the question of whether such a temporal periodic order can persist when the drive becomes [...] Read more.

A discrete time crystal (DTC) is a remarkable non-equilibrium phase of matter characterized by the persistent sub-harmonic oscillations of physical observables in periodically driven many-body systems. Motivated by the question of whether such a temporal periodic order can persist when the drive becomes aperiodic, we investigate the dynamics of a Lipkin–Meshkov–Glick model under quasi-periodic Thue–Morse (TM) driving. Intriguingly, this infinite-range-interacting spin system can host “quasi-discrete time crystal” (quasi-DTC) phases characterized by periodic oscillations of the magnetization. We demonstrate that our model can host the quasi-DTC analog of both period-doubling DTCs as well as higher-order DTCs. These quasi-DTCs are robust to various perturbations, and they originate from the interplay of “all-to-all” interactions and the recursive structure of the TM sequence. Our results suggest that quasi-periodic driving protocols can provide a promising route for realizing novel non-equilibrium phases of matter in long-range interacting systems. Full article

(This article belongs to the Special Issue Non-Equilibrium Dynamics in Ultra-Cold Quantum Gases)

16 pages, 6101 KiB

Open AccessArticle

Deciphering Ageing Effects in Green-Dyed English Wool Carpet Yarns from the 1840s

by Terry T. Schaeffer, Jacob Mobberley and Laura Maccarelli

Heritage 2025, 8(6), 216; https://doi.org/10.3390/heritage8060216 (registering DOI) - 7 Jun 2025

Abstract

In 1842, carpet manufacturer W.H. Worth of Kidderminster, England, began assembling a sample book of wool yarns dyed with natural dyestuffs. This paper reports on a study of the “Greens” section, which contains sixteen yarn samples—six still green and ten now ranging from [...] Read more.

In 1842, carpet manufacturer W.H. Worth of Kidderminster, England, began assembling a sample book of wool yarns dyed with natural dyestuffs. This paper reports on a study of the “Greens” section, which contains sixteen yarn samples—six still green and ten now ranging from tan to dark brown. The accompanying recipes list similar ingredients: old fustic and either “mixture” or extracet of indigo. To verify whether Worth’s recipes were followed, the yarns were analyzed using HPLC-DAD and FORS. Additionally, mock-ups were prepared according to Worth’s green dye recipes and subjected to thermal ageing to explore potential causes of discoloration. Preliminary analysis of the historic samples revealed that the discoloured yarns contain both indigo and indigo carmine, while the still-green samples contain only indigo carmine. This suggests that one or more components of the indigo vat may have contributed to discoloration. To test this hypothesis, contemporary wool yarns were dyed using a Worth green recipe, with and without indigo, at varying pH levels. These were thermally aged, and their colour changes monitored. HPLC-DAD and FORS analyses of the mock-ups were compared to the historic samples to identify dyeing conditions that may have led to the observed browning. Full article

(This article belongs to the Special Issue Dyes in History and Archaeology 43)

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17 pages, 1820 KiB

Open AccessArticle

Experimental and Thermodynamic Study on the Temperature-Dependent Surface Activity of Some Polyether Siloxane Surfactants at the Water–Air Interface

by Joanna Krawczyk, Joanna Karasiewicz and Katarzyna Wojdat

Int. J. Mol. Sci. 2025, 26(12), 5472; https://doi.org/10.3390/ijms26125472 (registering DOI) - 7 Jun 2025

Abstract

Measurements of the surface tension of aqueous solutions of some trisiloxane surfactants containing various polyether groups (HOL7, HOL9, and HOL12) at 293 K, 303 K, and 313 K were performed. The studied surfactants were synthesized by hydrosilylation reaction and their structural analysis was [...] Read more.

Measurements of the surface tension of aqueous solutions of some trisiloxane surfactants containing various polyether groups (HOL7, HOL9, and HOL12) at 293 K, 303 K, and 313 K were performed. The studied surfactants were synthesized by hydrosilylation reaction and their structural analysis was carried out by the ¹H NMR, ¹³C NMR, ²⁹Si NMR, as well as FT-IR techniques. The thermal stability of HOL7, HOL9, and HOL12, as well as their molecular weight distributions, were also studied. On the basis of the obtained experimental results of the surface tension of aqueous solutions of HOL7, HOL9, and HOL12, the activity of the studied surfactants at the water–air interface was determined and discussed in the light of intermolecular interactions. Using the measured values of the surface tension, the Gibbs surface excess concentration, the area occupied by the surfactant molecule in the adsorption layer, and the standard Gibbs free energy of adsorption of the studied surfactants at the water–air interface were also calculated. Based on the obtained thermodynamic parameters of adsorption of the studied surfactants at the water–air interface, temperature, as well as a number of polyether groups in the hydrophilic part of surfactant, impact on particular surfactant adsorption was deduced. In general, the changes in the standard Gibbs free energy of adsorption of the studied surfactants at the water–air interface indicate that their adsorption tendency decreases with decreasing temperature. In addition, that tendency also diminishes as the number of the polyether groups in the hydrophilic part of the surfactant increases. Full article

(This article belongs to the Collection Feature Papers in 'Physical Chemistry and Chemical Physics')

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18 pages, 3601 KiB

Open AccessArticle

Application of COMSOL Multiphysics Model in Studying Effects of Straw Addition on Dewatering Performance of Residual Sludge During Freeze–Thaw Cycles

by Zirui Guo, Jiawei Wang, Yao Wang, Riguang Chi, Xujin Gong and Zhiqiang Chen

Water 2025, 17(12), 1727; https://doi.org/10.3390/w17121727 (registering DOI) - 7 Jun 2025

Abstract

Freeze–thaw (F/T) technology is an environmentally friendly and efficient method for residual sludge treatment. This study investigates the enhancement of sludge dewatering performance through the addition of straw during F/T cycles. A mathematical model was established using the Box–Behnken central composite design and [...] Read more.

Freeze–thaw (F/T) technology is an environmentally friendly and efficient method for residual sludge treatment. This study investigates the enhancement of sludge dewatering performance through the addition of straw during F/T cycles. A mathematical model was established using the Box–Behnken central composite design and validated via COMSOL Multiphysics simulations. The optimal conditions were identified as freezing at −16 °C for 24 h, with 12.5 freeze–thaw cycles and a straw mixing ratio of 20%, reducing the sludge moisture content from 62.7% to 35.9%. The specific resistance to filtration (SRF) and cake moisture content decreased significantly with increasing straw addition, reaching a minimum SRF of 1.30 × 10¹² m/kg at the optimal straw ratio. Straw conditioning also intensified the combustion stage of the sludge by increasing the maximum weight loss rate and elevating the thermal decomposition temperature. Numerical simulations confirmed the experimental results, demonstrating that straw addition significantly improves sludge dewaterability by modifying heat and mass transfer mechanisms. Full article

(This article belongs to the Special Issue Environmental Biotechnology Applied to Water and Wastewater Treatment Processes)

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13 pages, 3977 KiB

Open AccessArticle

Optical Properties of BaAl₂O₄ Due to Cerium Doping and Heat Treatment in Different Atmospheres

by Montserrat Nevai Coyotl Ojeda, Benito de Celis Alonso, José Eduardo Espinosa Rosales, Epifanio Cruz-Zaragoza and Martín Rodolfo Palomino Merino

Micromachines 2025, 16(6), 688; https://doi.org/10.3390/mi16060688 (registering DOI) - 7 Jun 2025

Abstract

The luminescent properties of cerium-doped barium aluminate (BaAl₂O₄) samples with varying Ce concentrations (0–1.1 mol%) prepared either in an air or nitrogen-reduced atmosphere are presented. This work provides the first detailed comparison of the material’s structural, luminescent, and chromatic [...] Read more.

The luminescent properties of cerium-doped barium aluminate (BaAl₂O₄) samples with varying Ce concentrations (0–1.1 mol%) prepared either in an air or nitrogen-reduced atmosphere are presented. This work provides the first detailed comparison of the material’s structural, luminescent, and chromatic properties at different doping levels and thermal treatments. X-ray diffraction analysis confirmed the hexagonal crystal structure of barium aluminate. Samples treated in an air atmosphere exhibited crystallite sizes of 58.5 nm for undoped samples and 45.7 nm for doped samples. In contrast, those treated under nitrogen showed smaller crystallite sizes, i.e., 39.8 nm for undoped and 42.3 nm for doped samples, respectively. XPS analysis indicated that the nitrogen-reduced atmosphere minimized Ce oxidation, favoring the presence of Ce³⁺. The bandgap values of the material were 4.0 eV and 5.6 eV for the air and for the nitrogen atmosphere, respectively. Photoluminescence spectra showed maxima at 357 nm (air) and 386 nm (nitrogen), attributed to 4f-5d transitions of Ce. The samples under air atmosphere showed longer lifetimes values (0.94 ns) compared to those in a nitrogen atmosphere (0.40 ns). These results suggest that thermal treatment in an air atmosphere promoted better structural order and higher photoluminescence efficiency, while treatment in a nitrogen-reduced atmosphere increased defect formation, shortening the lifetime. Chromaticity coordinate analysis showed that the cerium ion dopant influenced the blueish emission color in both samples. Full article

(This article belongs to the Collection Microdevices and Applications Based on Advanced Glassy Materials)

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14 pages, 330 KiB

Open AccessArticle

Does BMI Have an Impact on Endometriosis Symptoms and Endometriosis Types According to the #ENZIAN Classification?

by Elvin Piriyev, Clara Mennicken, Sven Schiermeier and Thomas Römer

J. Clin. Med. 2025, 14(12), 4040; https://doi.org/10.3390/jcm14124040 (registering DOI) - 7 Jun 2025

Abstract

Background/Objectives:The relationship between body mass index (BMI) and endometriosis symptoms or lesion types remains unclear. This study investigates the association between BMI and symptom severity as well as the anatomical distribution of endometriosis using the #ENZIAN classification. Methods: A retrospective analysis [...] Read more.

Background/Objectives:The relationship between body mass index (BMI) and endometriosis symptoms or lesion types remains unclear. This study investigates the association between BMI and symptom severity as well as the anatomical distribution of endometriosis using the #ENZIAN classification. Methods: A retrospective analysis was conducted on 219 patients with histologically confirmed endometriosis who underwent laparoscopic surgery at a tertiary endometriosis center in 2021. Preoperative symptom data were collected using standardized questionnaires. Patients were grouped by BMI categories based on WHO criteria. Endometriosis was classified intraoperatively using the #ENZIAN system. Statistical analyses included chi-square tests and one-way ANOVA. Results: Patients with low/normal BMI (<25 kg/m², n = 150) reported significantly higher intensity of chronic pelvic pain (CPP) compared to those with overweight/obesity (≥25 kg/m², n = 69; p = 0.0026). When stratified into four BMI groups, dyspareunia was significantly less frequent in obese patients (p = 0.0306), and high-intensity CPP was less common in both underweight and obese categories compared to normal-weight patients (p = 0.0069). Infertility rates increased significantly with higher BMI (p = 0.00001). No significant differences in the distribution of endometriosis lesions across #ENZIAN compartments were observed in relation to BMI. Conclusions: Our findings indicate that BMI does not significantly influence the anatomical distribution of endometriosis lesions as defined by the #ENZIAN classification, but it does correlate with some symptom intensity and infertility. These results suggest that while BMI may not predict disease localization, it plays a role in shaping the clinical phenotype of endometriosis. Full article

(This article belongs to the Section Obstetrics & Gynecology)

20 pages, 7089 KiB

Open AccessArticle

Tuning Biodegradation and Physicochemical Features of PLA/HAp Biomaterials by Incorporating Nanofibrillated Cellulose Through a Colloidal Processing Route

by Maria Eugenia Juan-Cano, Zoilo Gonzalez, Esther Rincón, Antonio Javier Sanchez-Herencia, Begoña Ferrari and Ana Ferrández-Montero

Polymers 2025, 17(12), 1595; https://doi.org/10.3390/polym17121595 (registering DOI) - 7 Jun 2025

Abstract

Biomaterials play a fundamental role in providing a porous structure that mimics the natural structure of human bone and serves as a support while tissue regenerates. With the use of biodegradable materials, it is possible to avoid unnecessary second surgeries for implant removal. [...] Read more.

Biomaterials play a fundamental role in providing a porous structure that mimics the natural structure of human bone and serves as a support while tissue regenerates. With the use of biodegradable materials, it is possible to avoid unnecessary second surgeries for implant removal. The main objective of this article has been focused on modifying the degradation rate of a biodegradable composite material based on polylactic acid (PLA) reinforced with hydroxyapatite (HAp) by incorporating nanofibrillated cellulose (NFC), capable of tuning the porosity within the matrix. To introduce NFC into the composite material, a colloidal processing approach was chosen to improve and ensure its compatibility with the polymeric matrix. The incorporation of different ratios of NFC generally decreases the mechanical properties, but by adjusting the ratio of HAp/NFC content, this parameter is normalized. The hydrophilicity of the composite is improved by HAp/NFC incorporation, and degradation tests confirm that an increase in the percentage of NFC in the matrix is directly proportional to an increase in the degradation rates of the material. These results represent a significant improvement in personalized medicine, where the design of biodegradable biomaterials with hierarchical and controlled porosity opens new paths in the development of therapies and treatments personalized for each patient. Full article

(This article belongs to the Special Issue Polymer/Ceramic Composites, 2nd Edition)

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10 pages, 396 KiB

Open AccessReview

Oncology Nurses’ Attitudes, Knowledge, and Practices in Providing Sexuality Care to Cancer Patients: A Scoping Review

by Omar Alqaisi, Maha Subih, Kurian Joseph, Edward Yu and Patricia Tai

Curr. Oncol. 2025, 32(6), 337; https://doi.org/10.3390/curroncol32060337 (registering DOI) - 7 Jun 2025

Abstract

Sexual health in cancer care is often overlooked. This study examines oncology nurses’ knowledge and practices regarding sexuality care, identifying barriers and facilitators. A Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA)-guided search of Scopus, ScienceDirect, PubMed, and EBSCO focused on studies [...] Read more.

Sexual health in cancer care is often overlooked. This study examines oncology nurses’ knowledge and practices regarding sexuality care, identifying barriers and facilitators. A Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA)-guided search of Scopus, ScienceDirect, PubMed, and EBSCO focused on studies from 2014 to 2024. Of 1735 identified studies, only 11 met inclusion criteria. Findings revealed a lack of knowledge among nurses and dissatisfaction with sexual healthcare. Barriers include time constraints, cultural factors, and personal reservations. Routine discussions are often absent due to inadequate training. Education- and system-based strategies are needed to enhance nurses’ competence in addressing sexual concerns. Implementing training programs, structured records, evaluation tools, concept maps, and system support would improve patient care and oncology nursing practices. Addressing these gaps with practical measures can enhance communication, patient satisfaction, and quality of life. This unique analysis was conducted by two experienced advanced nurses in the Middle East, where discussions about sex are often regarded as taboo. Full article

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23 pages, 411 KiB

Open AccessReview

Neurobiology of Chronic Pain, Posttraumatic Stress Disorder, and Mild Traumatic Brain Injury

by Gerald Young, Hella Thielen, Kristin Samuelson and Joel Jin

Biology 2025, 14(6), 662; https://doi.org/10.3390/biology14060662 (registering DOI) - 7 Jun 2025

Abstract

Objectives: This article describes the neurobiology of psychological injuries—chronic pain, concussion/mild traumatic brain injury (MTBI), and fear/posttraumatic stress disorder (PTSD)—toward elucidating common mechanisms in central and peripheral sensitization that contribute to their onset, exacerbation, and maintenance. Central sensitization refers to central nervous system [...] Read more.

Objectives: This article describes the neurobiology of psychological injuries—chronic pain, concussion/mild traumatic brain injury (MTBI), and fear/posttraumatic stress disorder (PTSD)—toward elucidating common mechanisms in central and peripheral sensitization that contribute to their onset, exacerbation, and maintenance. Central sensitization refers to central nervous system (CNS) and related processes, while peripheral sensitization is typically referred to as receptor field expansion. The three psychological injury diagnoses/conditions are accompanied by impairments in function after negligent events (such as motor vehicle accidents (MVAs)) that lead to tort court action. Methods: The conducted literature review involved an extensive scoping review of recent neurobiological literature on chronic pain, PTSD, and MTBI. The literature review sought biological markers that distinguish them. Results: For chronic pain, concussion/MTBI, and fear/PTSD, this article reviewed definitions and critical neurobiological research. The literature review did not find evidence of biological markers, but the role of sensitization emerged as important. Conclusions: Common therapeutic processes, such as focusing on sensitization, might be helpful for these conditions. As for causal mechanisms related to sensitization in the causality of psychological injuries, the major ones hypothesized relate to the biopsychosocial model, psychological control, and activation–inhibition coordination. Full article

(This article belongs to the Special Issue Neurobiology of Traumatic Brain Injury)

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27 pages, 4693 KiB

Open AccessReview

Observation of Multilayer Clouds and Their Climate Effects: A Review

by Jianing Xue, Cheng Yuan, Yawei Qu and Yifei Huang

Atmosphere 2025, 16(6), 692; https://doi.org/10.3390/atmos16060692 (registering DOI) - 7 Jun 2025

Abstract

Multilayer clouds, comprising vertically stacked cloud layers with distinct microphysical characteristics, constitute a critical yet complex atmospheric phenomenon influencing regional to global climate patterns. Advances in observational techniques, particularly the application of high-resolution humidity vertical profiling via radiosondes, have significantly enhanced multilayer cloud [...] Read more.

Multilayer clouds, comprising vertically stacked cloud layers with distinct microphysical characteristics, constitute a critical yet complex atmospheric phenomenon influencing regional to global climate patterns. Advances in observational techniques, particularly the application of high-resolution humidity vertical profiling via radiosondes, have significantly enhanced multilayer cloud detection capabilities. Multilayer clouds are widely distributed around the world, showing significant regional differences. Many studies have been carried out on the formation mechanism of multilayer clouds, and observational evidence indicates a close relationship between multilayer cloud development and water vapor supply, updraft, atmospheric circulation, as well as wind shear; however, a unified and comprehensive theoretical framework has not yet been constructed to fully explain the underlying mechanism. In addition, the unique vertical structure of multilayer clouds exhibits different climate effects when compared with single-layer clouds, affecting global climate patterns by regulating precipitation processes and radiative energy budgets. This article reviews the research progress related to multilayer cloud observations and their climate effects and looks forward to the research that needs to be carried out in the future. Full article

(This article belongs to the Special Issue Application of Emerging Methods in Aerosol Research)

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24 pages, 1667 KiB

Open AccessArticle

Mitigating Class Imbalance Challenges in Fish Taxonomy: Quantifying Performance Gains Using Robust Asymmetric Loss Within an Optimized Mobile–Former Framework

by Yanhe Tao and Rui Zhong

Electronics 2025, 14(12), 2333; https://doi.org/10.3390/electronics14122333 (registering DOI) - 7 Jun 2025

Abstract

Accurate fish species identification is crucial for marine biodiversity conservation, environmental monitoring, and sustainable fishery management, particularly as marine ecosystems face increasing pressures from human activities and climate change. Traditional morphological identification methods are inherently labor-intensive and resource-demanding, while contemporary automated approaches, particularly [...] Read more.

Accurate fish species identification is crucial for marine biodiversity conservation, environmental monitoring, and sustainable fishery management, particularly as marine ecosystems face increasing pressures from human activities and climate change. Traditional morphological identification methods are inherently labor-intensive and resource-demanding, while contemporary automated approaches, particularly deep learning models, often suffer from significant computational overhead and struggle with the pervasive issue of class imbalance inherent in ecological datasets. Addressing these limitations, this research introduces a novel computationally parsimonious fish classification framework leveraging the hybrid Mobile–Former neural network architecture. This architecture strategically combines the local feature extraction strengths of convolutional layers with the global context modeling capabilities of transformers, optimized for efficiency. To specifically mitigate the detrimental effects of the skewed data distributions frequently observed in real-world fish surveys, the framework incorporates a sophisticated robust asymmetric loss function designed to enhance model focus on under-represented categories and improve resilience against noisy labels. The proposed system was rigorously evaluated using the comprehensive FishNet dataset, comprising 74,935 images distributed across a detailed taxonomic hierarchy including eight classes, seventy-two orders, and three-hundred-forty-eight families, reflecting realistic ecological diversity. Our model demonstrates superior classification accuracy, achieving 93.97 percent at the class level, 88.28 percent at the order level, and 84.02 percent at the family level. Crucially, these high accuracies are attained with remarkable computational efficiency, requiring merely 508 million floating-point operations, significantly outperforming comparable state-of-the-art models in balancing performance and resource utilization. This advancement provides a streamlined, effective, and resource-conscious methodology for automated fish species identification, thereby strengthening ecological monitoring capabilities and contributing significantly to the informed conservation and management of vital marine ecosystems. Full article

(This article belongs to the Special Issue Advances in Machine Learning for Image Classification)

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25 pages, 1857 KiB

Open AccessArticle

Fuzzy Logic in Smart Meters to Support Operational Processes in Energy Management Systems

by Piotr Powroźnik, Paweł Szcześniak and Mateusz Suliga

Electronics 2025, 14(12), 2336; https://doi.org/10.3390/electronics14122336 (registering DOI) - 7 Jun 2025

Abstract

Distribution network operators face the complex challenge of maintaining stable electricity access for diverse consumers while balancing economic constraints, user comfort, and the impact of stochastic events, particularly the increasing integration of renewable energy sources and electric vehicles. To address these challenges, this [...] Read more.

Distribution network operators face the complex challenge of maintaining stable electricity access for diverse consumers while balancing economic constraints, user comfort, and the impact of stochastic events, particularly the increasing integration of renewable energy sources and electric vehicles. To address these challenges, this paper introduces a novel decision-making system for energy management within smart energy meters, leveraging a specifically designed fuzzy inference system. This fuzzy inference system autonomously interprets real-time energy consumption patterns and responds to control commands from distribution network operators, optimizing energy flow at the consumer level. Unlike generic energy management approaches, this study provides a detailed mathematical model of the proposed low-cost fuzzy inference system-based system, explicitly outlining its rule base and inference mechanisms. Simulation studies conducted under varying load conditions and renewable generation profiles demonstrate the system’s effectiveness in achieving a balanced response to grid demands and user needs, yielding a quantifiable reduction in peak demand during simulated stress scenarios. Furthermore, experimental validation on resource-constrained embedded platforms confirms the practical feasibility and real-time performance of the proposed system on low-cost smart energy meter hardware. The differential contribution of this work lies in its provision of a computationally efficient and readily implementable fuzzy logic-based solution tailored for the limitations of low-cost smart energy meters, offering a viable alternative to more complex artificial intelligence algorithms. The findings underscore the necessity and justification for optimizing algorithm code for resource-constrained smart energy meter deployments to facilitate widespread adoption of advanced energy management functionalities. Full article

(This article belongs to the Special Issue Optimal Integration of Energy Storage and Conversion in Smart Grids)

18 pages, 1875 KiB

Open AccessArticle

Modeling Pulsed Magnetic Core Behavior in LTspice

by Keegan Kelp, Dawson Wright, Jacob Stephens, James Dickens, John Mankowski, Zach Shaw and Andreas Neuber

Electronics 2025, 14(12), 2335; https://doi.org/10.3390/electronics14122335 (registering DOI) - 7 Jun 2025

Abstract

This work demonstrates a modeling technique focused on reproducing the behavior of magnetic cores subject to high voltage pulses. The working principle of the model is based on a magnetic circuit with additional elements that influence the model’s behavior. The elements include a [...] Read more.

This work demonstrates a modeling technique focused on reproducing the behavior of magnetic cores subject to high voltage pulses. The working principle of the model is based on a magnetic circuit with additional elements that influence the model’s behavior. The elements include a function that defines the response of the model depending on the applied pulse voltage and a component that dominates the transient response. These elements are necessary to replicate the experimentally observed behavior of magnetic cores. The model was developed based on the measured behavior of three nanocrystalline magnetic materials subject to a range of pulse voltages. This modeling technique was created to address the limitations of other models in accurately capturing fast pulse responses. The key limitation of traditional modeling techniques that the proposed model addresses is their inability to capture variations in core response under different applied pulse voltages (magnetization rates). The proposed model has been shown to produce accurate results for magnetization rates between 1 T/μs and 8 T/μs, with potential for further expansion. Implemented in LTspice, this model is both fast and accurate, effectively replicating the behavior of the magnetic core while maintaining simplicity. This work outlines the foundation of this modeling technique, the trends in the parameters that influence its behavior, and its application within a simple pulsed power system. The most notable feature of this model is its ability to operate across a wide range of pulse voltages without requiring adjustments to the model parameters. Full article

(This article belongs to the Special Issue Advances in Pulsed-Power and High-Power Electronics)

25 pages, 5327 KiB

Open AccessArticle

Evaluating the Cost-Effectiveness of Cervical Cancer Screening and Treatment in Western Romania

by Ion Petre, Șerban Mircea Negru, Florina Buleu, Radu Dumitru Moleriu, Marina Adriana Mercioni, Izabella Petre, Anca Bordianu, Vladiana Turi, Luciana Marc, Daian Ionel Popa and Daliborca Cristina Vlad

Curr. Oncol. 2025, 32(6), 336; https://doi.org/10.3390/curroncol32060336 (registering DOI) - 7 Jun 2025

Abstract

Background and Objectives: As a leading European country in terms of cervical cancer incidence and mortality, there has been a pressing need for Romania to upgrade its cervical cancer management. The criteria set by the International Federation of Gynecology and Obstetrics indicate that [...] Read more.

Background and Objectives: As a leading European country in terms of cervical cancer incidence and mortality, there has been a pressing need for Romania to upgrade its cervical cancer management. The criteria set by the International Federation of Gynecology and Obstetrics indicate that different treatments should have a similar trend concerning progression-free survival and overall survival at all the various stages of cervical cancer. This study aimed to assess the cost-effectiveness (CE) of the primary treatment plans related to the survival rate for cervical cancer screening in the western part of Romania and provide some recommendations. Materials and Methods: Descriptive statistics and a correlation model were used to examine costs. AI models have been developed to forecast the CE of different treatments using the above-mentioned studies on overall survival rates and treatment-related toxicity rates for five years. The costs of cervical cancer treatment were sourced from the public health department, the oncology clinic in the western region of Romania, and the County Hospital available for each stage. Results: Treatment expenses vary by cancer stage, with a significant increase from stages IA/IB to IIA, stabilizing between IIA and IIIC (about €7800–€8300), followed by a steep decline in IVA and a more pronounced decrease in IVB and in situ. The results highlight certain treatment combinations and their costs, indicating that the highest costs (exceeding €8000) are linked to multimodal treatments, which encompass surgery, chemotherapy, radiotherapy, and brachytherapy. Conclusions: Advanced cancer stages (IIA–IIIC) entail the highest treatment costs due to intricate, multimodal therapy, whereas early stages (IA, IB, in situ) and late terminal stages (IVB) are linked to considerably reduced treatment costs. Full article

(This article belongs to the Section Health Economics)

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19 pages, 2723 KiB

Open AccessReview

Chromoanagenesis in Osteosarcoma

by Guozhuang Li, Nan Wu, Jen Ghabrial, Victoria Stinnett, Melanie Klausner, Laura Morsberger, Patty Long, Ezra Baraban, John M. Gross and Ying S. Zou

Biomolecules 2025, 15(6), 833; https://doi.org/10.3390/biom15060833 (registering DOI) - 7 Jun 2025

Abstract

Chromoanagenesis is a catastrophic genomic phenomenon involving sudden, extensive rearrangements within one or a few cell cycles. In osteosarcoma, the most prevalent malignant bone tumor in children and adolescents, these events dramatically alter the genomic landscape, frequently disrupting key tumor suppressor genes like [...] Read more.

Chromoanagenesis is a catastrophic genomic phenomenon involving sudden, extensive rearrangements within one or a few cell cycles. In osteosarcoma, the most prevalent malignant bone tumor in children and adolescents, these events dramatically alter the genomic landscape, frequently disrupting key tumor suppressor genes like TP53 and RB1, amplifying oncogene expression, and propelling tumor progression and evolution. This review elucidates how key chromoanagenic mechanisms, such as chromothripsis and chromoanasynthesis, arise from replication stress and impaired DNA repair pathways, ultimately contributing to genomic instability in osteosarcoma. Chromothripsis features prominently in osteosarcoma, occurring in up to 62% of tumor regions and driving intratumoral heterogeneity through persistent genomic crises. Next-generation sequencing, optical genome mapping, and emerging technologies like single-cell sequencing empower researchers to detect and characterize these complex structural variants, demonstrating how a single catastrophic event can profoundly influence osteosarcoma progression over time. While targeted therapies for osteosarcoma have proven elusive, innovative strategies harnessing comprehensive genomic profiling and patient-derived preclinical models hold promise for uncovering tumor-specific vulnerabilities tied to chromoanagenesis. Ultimately, unraveling how these rapid, large-scale rearrangements fuel osteosarcoma’s aggressive nature will not only refine disease classification and prognosis but also pave the way for novel therapeutic approaches to enhance patient outcomes. Full article

(This article belongs to the Section Molecular Medicine)

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26 pages, 3279 KiB

Open AccessArticle

Facile One-Pot Fischer–Suzuki–Knoevenagel Microwave-Assisted Synthesis of Fluorescent 5-Aryl-2-Styryl-3H-Indoles

by Martynas Rojus Bartkus, Neringa Kleizienė, Aurimas Bieliauskas and Algirdas Šačkus

Molecules 2025, 30(12), 2503; https://doi.org/10.3390/molecules30122503 (registering DOI) - 7 Jun 2025

Abstract

In this study, novel fluorescent 5-aryl-2-styryl-3H-indole derivatives were efficiently synthesized from 4-bromophenylhydrazine hydrochloride using the microwave-accelerated one-pot technique, which includes Fischer synthesis, Suzuki cross-coupling, and Knoevenagel condensation. The structural assignments of the synthesized compounds were based on ¹H, ¹³C, [...] Read more.

In this study, novel fluorescent 5-aryl-2-styryl-3H-indole derivatives were efficiently synthesized from 4-bromophenylhydrazine hydrochloride using the microwave-accelerated one-pot technique, which includes Fischer synthesis, Suzuki cross-coupling, and Knoevenagel condensation. The structural assignments of the synthesized compounds were based on ¹H, ¹³C, ¹⁵N, and ¹⁹F NMR; IR spectroscopy; and HRMS spectral data. The optical properties of the newly obtained styryl-indole dyes were studied using UV-vis and fluorescence spectroscopy, which clearly demonstrated that the derivatives substituted with electron-donating or -withdrawing groups exhibited varying emission shifts and quantum yields ranging from negligible to high. Full article

(This article belongs to the Special Issue Novel Heterocyclic Compounds: Synthesis and Applications)

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