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12 pages, 14610 KiB

Open AccessArticle

Effect of Heat Treatment on Microstructure and Tensile Property of Laser-Powder-Bed-Melted Al–Mn–Mg–Sc–Zr Alloy

by Zhiqiang Cao, Hui Yin, Jin Jiang, Mingliang Cui, Hao Zhang and Sheng Cao

Materials 2025, 18(7), 1638; https://doi.org/10.3390/ma18071638 (registering DOI) - 3 Apr 2025

This study explored the effects of T5 and T6 heat treatments on the microstructure and tensile properties of a laser powder bed fusion (LPBF)-fabricated Al–Mn–Mg–Sc–Zr alloy. The as-built condition exhibited a bi-modal grain structure of equiaxed and columnar grains. Specimens after T5 heat [...] Read more.

This study explored the effects of T5 and T6 heat treatments on the microstructure and tensile properties of a laser powder bed fusion (LPBF)-fabricated Al–Mn–Mg–Sc–Zr alloy. The as-built condition exhibited a bi-modal grain structure of equiaxed and columnar grains. Specimens after T5 heat treatment also had a bi-modal microstructure with slight grain growth and the precipitation of secondary Al₃Sc, which enhanced the yield strength via precipitation hardening but reduced ductility. In contrast, T6 treatment triggered recrystallization, and the microstructure was only coarse equiaxed α-Al grains. This microstructure change was accompanied by coarsened primary Al₃X and Al₆(Mn, Fe) precipitates, partial Mg₂Si dissolution, and significant secondary Al₃Sc particle growth. Consequently, T6-treated specimens showed lower strength than their T5 counterparts and the poorest ductility due to brittle fracture induced by the stress concentration effect of coarse precipitates at grain boundaries. Full article

(This article belongs to the Special Issue The Additive Manufacturing of Metallic Alloys (Second Edition))

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21 pages, 2270 KiB

Open AccessReview

Role of Endophytic Fungi in the Biosynthesis of Metal Nanoparticles and Their Potential as Nanomedicines

by Hanadi Sawalha, Simon E. Moulton, Andreas Winkel, Meike Stiesch and Bita Zaferanloo

J. Funct. Biomater. 2025, 16(4), 129; https://doi.org/10.3390/jfb16040129 (registering DOI) - 3 Apr 2025

Abstract

Metal nanoparticles (MNPs) produced through biosynthesis approaches have shown favourable physical, chemical, and antimicrobial characteristics. The significance of biological agents in the synthesis of MNPs has been acknowledged as a promising alternative to conventional approaches such as physical and chemical methods, which are [...] Read more.

Metal nanoparticles (MNPs) produced through biosynthesis approaches have shown favourable physical, chemical, and antimicrobial characteristics. The significance of biological agents in the synthesis of MNPs has been acknowledged as a promising alternative to conventional approaches such as physical and chemical methods, which are confronted with certain challenges. To meet these challenges, the use of endophytic fungi as nano-factories for the synthesis of MNPs has become increasingly popular worldwide in recent times. This review provides an overview of the synthesis of MNPs using endophytic fungi, the mechanisms involved, and their important biomedical applications. A special focus on different biomedical applications of MNPs mediated endophytic fungi involved their antibacterial, antifungal, antiviral, and anticancer applications and their potential as drug delivery agents. Furthermore, this review highlights the significance of the use of endophytic fungi for the green synthesis of MNPs and discusses the benefits, challenges, and prospects in this field. Full article

(This article belongs to the Collection Feature Papers in Antibacterial Biomaterials)

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25 pages, 2026 KiB

Open AccessArticle

EEG Signal Prediction for Motor Imagery Classification in Brain–Computer Interfaces

by Óscar Wladimir Gómez-Morales, Diego Fabian Collazos-Huertas, Andrés Marino Álvarez-Meza and Cesar German Castellanos-Dominguez

Sensors 2025, 25(7), 2259; https://doi.org/10.3390/s25072259 (registering DOI) - 3 Apr 2025

Abstract

Brain–computer interfaces (BCIs) based on motor imagery (MI) generally require EEG signals recorded from a large number of electrodes distributed across the cranial surface to achieve accurate MI classification. Not only does this entail long preparation times and high costs, but it also [...] Read more.

Brain–computer interfaces (BCIs) based on motor imagery (MI) generally require EEG signals recorded from a large number of electrodes distributed across the cranial surface to achieve accurate MI classification. Not only does this entail long preparation times and high costs, but it also carries the risk of losing valuable information when an electrode is damaged, further limiting its practical applicability. In this study, a signal prediction-based method is proposed to achieve high accuracy in MI classification using EEG signals recorded from only a small number of electrodes. The signal prediction model was constructed using the elastic net regression technique, allowing for the estimation of EEG signals from 22 complete channels based on just 8 centrally located channels. The predicted EEG signals from the complete channels were used for feature extraction and MI classification. The results obtained indicate a notable efficacy of the proposed prediction method, showing an average performance of 78.16% in classification accuracy. The proposed method demonstrated superior performance compared to the traditional approach that used few-channel EEG and also achieved better results than the traditional method based on full-channel EEG. Although accuracy varies among subjects, from 62.30% to an impressive 95.24%, these data indicate the capability of the method to provide accurate estimates from a reduced set of electrodes. This performance highlights its potential to be implemented in practical MI-based BCI applications, thereby mitigating the time and cost constraints associated with systems that require a high density of electrodes. Full article

(This article belongs to the Special Issue EEG Signal Processing in Healthcare, Cognitive Neuroscience, and Medical Diagnosis)

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36 pages, 5889 KiB

Open AccessArticle

Enhancing Street-Crossing Safety for Visually Impaired Pedestrians with Haptic and Visual Feedback

by Gang Ren, Zhihuang Huang, Wenshuo Lin, Tianyang Huang, Gang Wang and Jee Hang Lee

Appl. Sci. 2025, 15(7), 3942; https://doi.org/10.3390/app15073942 (registering DOI) - 3 Apr 2025

Abstract

Safe street crossing poses significant challenges for visually impaired pedestrians, who must rely on non-visual cues to assess crossing safety. Conventional assistive technologies often fail to provide real-time, actionable information about oncoming traffic, making independent navigation difficult, particularly in uncontrolled or vehicle-based crossing [...] Read more.

Safe street crossing poses significant challenges for visually impaired pedestrians, who must rely on non-visual cues to assess crossing safety. Conventional assistive technologies often fail to provide real-time, actionable information about oncoming traffic, making independent navigation difficult, particularly in uncontrolled or vehicle-based crossing scenarios. To address these challenges, we designed and evaluated two assistive systems utilizing haptic and visual feedback, tailored for traffic signal-controlled intersections and vehicle-based crossings. The results indicate that visual feedback significantly improved decision efficiency at signalized intersections, enabling users to make faster decisions, regardless of their confidence levels. However, in vehicle-based crossings, where real-time hazard assessment is crucial, haptic feedback proved more effective, enhancing decision efficiency by enabling quicker and more intuitive judgments about approaching vehicles. Moreover, users generally preferred haptic feedback in both scenarios, citing its comfort and intuitiveness. These findings highlight the distinct challenges posed by different street-crossing environments and confirm the value of multimodal feedback systems in supporting visually impaired pedestrians. Our study provides important design insights for developing effective assistive technologies that enhance pedestrian safety and independence across varied urban settings. Full article

(This article belongs to the Section Computing and Artificial Intelligence)

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20 pages, 3225 KiB

Open AccessArticle

Merging Multiple System Perspectives: The Key to Effective Inland Shipping Emission-Reduction Policy Design

by Solange van der Werff, Fedor Baart and Mark van Koningsveld

J. Mar. Sci. Eng. 2025, 13(4), 716; https://doi.org/10.3390/jmse13040716 (registering DOI) - 3 Apr 2025

Abstract

Policymakers in the maritime sector face the challenge of designing and implementing decarbonization policies while maintaining safe navigation. Herein, the inland sector serves as a promising stepping stone due to the possibility of creating a dense energy supply infrastructure and shorter distances compared [...] Read more.

Policymakers in the maritime sector face the challenge of designing and implementing decarbonization policies while maintaining safe navigation. Herein, the inland sector serves as a promising stepping stone due to the possibility of creating a dense energy supply infrastructure and shorter distances compared to marine shipping. A key challenge is to consider the totality of all operational profiles as a result of the range of vessels and routes encountering varying local circumstances. In this study, we use a new scheme called “event table” to transform big data on vessel trajectories (AIS data) combined with energy-estimating algorithms into shipping-emission outcomes that can be evaluated from multiple perspectives. We can subsequently tie observations in one perspective (for example, large-scale spatial patterns on a map) to supporting explanations based on another perspective (for example, water currents, vessel speeds, or engine ages and their contributions to emissions). Hence, combining these outcomes from multiple perspectives and evaluation scales provides an essential understanding of how the system works and what the most effective improvement measures will be. With our approach, we can translate large quantities of data from multiple sources into multiple linked perspectives on the shipping system. Full article

(This article belongs to the Special Issue Green Shipping Corridors and GHG Emissions)

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21 pages, 27840 KiB

Open AccessArticle

Polymer-Functionalized Magnetic Nanoparticles for Targeted Quercetin Delivery: A Potential Strategy for Colon Cancer Treatment

by Júlia Borges de Macedo, Julia Narayana Schoroeder Bueno, Carla Cristine Kanunfre, José Ricardo de Arruda Miranda, Andris Figueiroa Bakuzis and Priscileila Colerato Ferrari

Pharmaceutics 2025, 17(4), 467; https://doi.org/10.3390/pharmaceutics17040467 (registering DOI) - 3 Apr 2025

Abstract

Background/Objectives: Nanoparticle-based drug delivery systems improve pharmacokinetic aspects, including controlled release and drug targeting, increasing therapeutic efficacy, and reducing toxicity in conventional colon cancer treatment. The superparamagnetism of magnetic nanoparticles (MNP) appears to be a potential alternative for magnetothermal therapy, inducing tumor [...] Read more.

Background/Objectives: Nanoparticle-based drug delivery systems improve pharmacokinetic aspects, including controlled release and drug targeting, increasing therapeutic efficacy, and reducing toxicity in conventional colon cancer treatment. The superparamagnetism of magnetic nanoparticles (MNP) appears to be a potential alternative for magnetothermal therapy, inducing tumor cell death by an external magnetic field. Therefore, this study aimed to develop chitosan (CS) and folate-chitosan (FA-CS)-coated MNP to improve the stability and targeting of the system for quercetin (Q) delivery. Methods: After FA-CS synthesis and 3² factorial design, polymer-functionalized MNPs were produced for quercetin loading, characterized, and evaluated by drug dissolution and cytotoxicity assay. Results: The factorial design indicated the positive influence of CS on MNPs’ Zeta potential, followed by the CS–temperature interaction. Optimized formulations had hydrodynamic diameters of 122.32 ± 8.56 nm, Zeta potentials of +30.78 ± 0.8 mV, and loading efficiencies of 80.45% (MNP-CS-Q) and 54.4% (MNP-FA-CS-Q). The 24 h drug release was controlled in MNP-CS-Q (up to 6.4%) and MNP-FA-CS-Q (up to 7.7%) in a simulated tumor medium, with Fickian diffusion release mechanism correlated to the Korsmeyer–Peppas model (R > 0.99). The cytotoxicity assay in HCT-116 showed a higher (p < 0.001) dose-dependent antitumor effect of quercetin-loaded MNP compared to free drug, with IC50s of 1.46 (MNP-CS) and 1.30 µg·mL⁻¹ (MNP-FA-CS). Conclusions: Therefore, this study contributes to the development of biomedical nanotechnology and the magnetic debate by highlighting the antitumor potential of quercetin magnetic nanoparticles. The experimental design allows the discussion of critical manufacturing variables and the determination of optimal parameters for the formulations. Full article

(This article belongs to the Special Issue Advancing Cancer Therapy: Magnetic Nanoparticles for Enhanced Targeted Drug Delivery)

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19 pages, 7302 KiB

Open AccessArticle

Safe and Optimal Motion Planning for Autonomous Underwater Vehicles: A Robust Model Predictive Control Framework Integrating Fast Marching Time Objectives and Adaptive Control Barrier Functions

by Zhonghe Tian and Mingzhi Chen

Drones 2025, 9(4), 273; https://doi.org/10.3390/drones9040273 (registering DOI) - 3 Apr 2025

Abstract

Autonomous Underwater Vehicles (AUVs) have shown significant promise across various underwater applications, yet face challenges in dynamic environments due to the limitations of traditional motion planning methods while Artificial Potential Field (APF)-based control barrier functions focus solely on obstacle proximity and distance-based methods [...] Read more.

Autonomous Underwater Vehicles (AUVs) have shown significant promise across various underwater applications, yet face challenges in dynamic environments due to the limitations of traditional motion planning methods while Artificial Potential Field (APF)-based control barrier functions focus solely on obstacle proximity and distance-based methods oversimplify obstacle geometries, and both fail to ensure safety and satisfy turning radius constraints for under-actuated AUVs in intricate environments. This paper proposes a robust Model Predictive Control (MPC) framework integrating an enhanced fast marching control barrier function, specifically designed for AUVs equipped with fully directional sonar systems. The framework introduces a novel improvement for moving obstacles by extending the control barrier function field propagation along the obstacle’s movement direction. This enhancement generates precise motion plans that ensure safety, satisfy kinematic constraints, and effectively handle static and dynamic obstacles. Simulation results demonstrate superior obstacle avoidance and motion planning performance in complex scenarios, with key outcomes including a minimum safety margin of 1.86 m in cluttered environments (vs. 0 m for A* and FMM) and 1.76 m in dynamic obstacle scenarios (vs. 0.13 m for MPC-APFCBF), highlighting the framework’s ability to enhance navigation safety and efficiency for real-world AUV deployments in unpredictable marine environments. Full article

(This article belongs to the Special Issue Advances in Intelligent Coordination Control for Autonomous UUVs)

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25 pages, 5923 KiB

Open AccessReview

Deciphering the Structural and Functional Paradigms of Clostridioides difficile Toxins TcdA and TcdB

by Mohammad Qutub, Amol Tatode, Ujban Md Hussain, Tanvi Premchandani, Jayshree Taksande, Milind Umekar and Deepak Thakre

Bacteria 2025, 4(2), 21; https://doi.org/10.3390/bacteria4020021 (registering DOI) - 3 Apr 2025

Abstract

Clostridioides difficile Infection (CDI) continues to be a major cause of antibiotic-associated diarrhea and pseudomembranous colitis, fueled in large measure by virulence factors TcdA and TcdB. These giant glucosyltransferase toxins interfere with host cytoskeletal integrity and inflammatory signaling by inhibiting Rho GTPase; however, [...] Read more.

Clostridioides difficile Infection (CDI) continues to be a major cause of antibiotic-associated diarrhea and pseudomembranous colitis, fueled in large measure by virulence factors TcdA and TcdB. These giant glucosyltransferase toxins interfere with host cytoskeletal integrity and inflammatory signaling by inhibiting Rho GTPase; however, the detailed structural dynamics, receptor selectivity, and subcellular trafficking mechanisms remain in part unspecified. This review integrates recent insights from cryo-electron microscopy (cryo-EM) and X-ray crystallography to describe the quaternary architecture of TcdA/B, emphasizing conformational changes key to pore formation and endosomal escape. We also examine the genomic heterogeneity of hypervirulent C. difficile strains (e.g., ribotype 027), correlating toxin gene polymorphisms (e.g., tcdC mutations) with increased toxin production and virulence. Mechanistic explanations of toxin-driven inflammasome activation and epithelial barrier dysfunction are situated within host immune evasion mechanisms, including microbiota-derived bile acid regulation of toxin stability. Subsequent innovative therapeutic strategies, encompassing the utilization of engineered neutralizing antibodies that specifically target the autoprocessing domain alongside structure-guided small-molecule inhibitors, are subjected to a rigorous evaluation. By integrating structural biology, systems-level omics, and clinical epidemiology, this review establishes a comprehensive framework for understanding C. difficile toxin pathogenesis and guiding next-generation precision antimicrobials. Full article

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24 pages, 8587 KiB

Open AccessArticle

Integrable Riesz Fractional-Order Generalized NLS Equation with Variable Coefficients: Inverse Scattering Transform and Analytical Solutions

by Hongwei Li, Sheng Zhang and Bo Xu

Fractal Fract. 2025, 9(4), 228; https://doi.org/10.3390/fractalfract9040228 (registering DOI) - 3 Apr 2025

Abstract

Significant new progress has been made in nonlinear integrable systems with Riesz fractional-order derivative, and it is impressive that such nonlocal fractional-order integrable systems exhibit inverse scattering integrability. The focus of this article is on extending this progress to nonlocal fractional-order Schrödinger-type equations [...] Read more.

Significant new progress has been made in nonlinear integrable systems with Riesz fractional-order derivative, and it is impressive that such nonlocal fractional-order integrable systems exhibit inverse scattering integrability. The focus of this article is on extending this progress to nonlocal fractional-order Schrödinger-type equations with variable coefficients. Specifically, based on the analysis of anomalous dispersion relation (ADR), a novel variable-coefficient Riesz fractional-order generalized NLS (vcRfgNLS) equation is derived. By utilizing the relevant matrix spectral problems (MSPs), the vcRfgNLS equation is solved through the inverse scattering transform (IST), and analytical solutions including n-soliton solution as a special case are obtained. In addition, an explicit form of the vcRfgNLS equation depending on the completeness of squared eigenfunctions (SEFs) is presented. In particular, the 1-soliton solution and 2-soliton solution are taken as examples to simulate their spatial structures and analyze their structural properties by selecting different variable coefficients and fractional orders. It turns out that both the variable coefficients and fractional order can influence the velocity of soliton propagation, but there is no energy dissipation throughout the entire motion process. Such soliton solutions may not only have important value for studying the super-dispersion transport of nonlinear waves in non-uniform media, but also for realizing a new generation of ultra-high-speed optical communication engineering. Full article

(This article belongs to the Special Issue Numerical and Exact Methods for Nonlinear Differential Equations and Applications in Physics, 2nd Edition)

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13 pages, 1033 KiB

Open AccessFeature PaperArticle

Mining Frequent Sequences with Time Constraints from High-Frequency Data

by Ewa Tusień, Alicja Kwaśniewska and Paweł Weichbroth

Int. J. Financial Stud. 2025, 13(2), 55; https://doi.org/10.3390/ijfs13020055 (registering DOI) - 3 Apr 2025

Abstract

Investing in the stock market has always been an exciting topic for people. Many specialists have tried to develop tools to predict future stock prices in order to make high profits and avoid big losses. However, predicting prices based on the dynamic characteristics [...] Read more.

Investing in the stock market has always been an exciting topic for people. Many specialists have tried to develop tools to predict future stock prices in order to make high profits and avoid big losses. However, predicting prices based on the dynamic characteristics of stocks seems to be a non-trivial problem. In practice, the predictive models are not expected to provide the most accurate forecasts of stock prices, but to highlight changes and discrepancies between the predicted and observed values, to warn against threats, and to inform users about upcoming opportunities. In this paper, we discuss the use of frequent sequences as well as association rules in WIG20 stock price prediction. Specifically, our study used two methods to approach the problem: correlation analysis based on the Pearson correlation coefficient and frequent sequence mining with temporal constraints. In total, 43 association rules were discovered, characterized by relatively high confidence and lift. Moreover, the most effective rules were those that described the same type of trend for both companies, i.e., rise ⇒ rise, or fall ⇒ fall. However, rules that showed the opposite trend, namely fall ⇒ rise or rise ⇒ fall, were rare. Full article

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17 pages, 1124 KiB

Open AccessReview

Pollen Food Allergy Syndrome in Southern European Adults: Patterns and Insights

by Christina Rousou, Egor Kostin, Eleni Christodoulou, Theodoros Theodorou, Zenon Pavlou and Constantinos Pitsios

Appl. Sci. 2025, 15(7), 3943; https://doi.org/10.3390/app15073943 (registering DOI) - 3 Apr 2025

Abstract

Oral Allergy Syndrome (OAS) is an allergic reaction that occurs upon contact of the mouth and throat with food, leading to symptoms primarily affecting the oral mucosa. In patients with allergic rhinitis, OAS may develop due to cross-reactivity between the pollen allergens responsible [...] Read more.

Oral Allergy Syndrome (OAS) is an allergic reaction that occurs upon contact of the mouth and throat with food, leading to symptoms primarily affecting the oral mucosa. In patients with allergic rhinitis, OAS may develop due to cross-reactivity between the pollen allergens responsible for allergic rhinitis, and specific plant-derived foods. This particular type of OAS is known as Pollen Food Allergy Syndrome (PFAS). The difference in prevalence of PFAS across different regions of the world is attributed to various factors, including environmental exposure and dietary habits. Southern Europe’s temperate climate favors the blooming of many allergenic plants, making respiratory allergies and PFAS significant public health concerns. There is a regional variation in pollen in Southern Europe, contributing to differences in the presence of panallergens—such as profilins, pathogenesis-related class 10 (PR-10) proteins and lipid transfer proteins (LTPs)—which mediate PFAS. In order to examine the epidemiology, pathogenesis, and diagnostic approaches of OAS and PFAS, focusing on their prevalence and impact in Southern European adults, a narrative review was performed. Data from Portugal, Spain, France, Italy, Albania, Greece, and Türkiye were retrieved. The main outcome of this review was that the frequency of PFAS varies across studies, not only between countries but also within the same country, due to vegetation variability across regions as well as methodological differences and the year of study. However, despite these differences, PFAS emerges as a common issue in Southern Europe, underscoring the need for effective diagnosis and management. Full article

(This article belongs to the Special Issue New Diagnostic and Therapeutic Approaches in Food Allergy)

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19 pages, 31846 KiB

Open AccessArticle

Proposal of an Integrated Method of Unmanned Aerial Vehicle and Artificial Intelligence for Crack Detection, Classification, and PCI Calculation of Airport Pavements

by Valerio Perri, Misagh Ketabdari, Stefano Cimichella, Maurizio Crispino and Emanuele Toraldo

Sustainability 2025, 17(7), 3180; https://doi.org/10.3390/su17073180 (registering DOI) - 3 Apr 2025

Abstract

Assessing the condition of airport pavements is essential to ensure operational safety and efficiency. This study presents an innovative, fully automated approach to calculate the Pavement Condition Index (PCI) by combining UAV-based aerial photogrammetry with advanced Artificial Intelligence (AI) techniques. The method follows [...] Read more.

Assessing the condition of airport pavements is essential to ensure operational safety and efficiency. This study presents an innovative, fully automated approach to calculate the Pavement Condition Index (PCI) by combining UAV-based aerial photogrammetry with advanced Artificial Intelligence (AI) techniques. The method follows three key steps: first, analyzing orthophotos of individual pavement sections using a custom-trained AI model designed for precise crack detection and classification; second, utilizing skeletonization and semantic mask analysis to measure crack characteristics; and third, automating the PCI calculation for faster and more consistent evaluations. By leveraging high-resolution Unmanned Aerial Vehicle (UAV) imagery and advanced segmentation models, this approach achieves superior accuracy in detecting transverse and longitudinal cracks. The automated PCI calculation minimizes the need for human intervention, reduces errors, and supports more efficient, data-driven decision-making for airport pavement management. This study demonstrates the transformative potential of integrating UAV and AI technologies to facilitate infrastructure maintenance and enhance safety protocols. Full article

(This article belongs to the Special Issue Next-Generation Roads: The Impact of Artificial Intelligence and Virtual Reality on the Planning, Design and Management of Sustainable Infrastructures)

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20 pages, 4479 KiB

Open AccessArticle

Exploring the Nutraceutical Potential of a Food–Medicine Compound for Metabolic-Associated Fatty Liver Disease via Lipidomics and Network Pharmacology

by Yuru Deng, Jie Cui, Yuxuan Jiang, Jian Zhang, Jinchi Jiang, Quanbin Zhang and Yonghong Hu

Foods 2025, 14(7), 1257; https://doi.org/10.3390/foods14071257 (registering DOI) - 3 Apr 2025

Abstract

Metabolic-associated fatty liver disease (MAFLD) is a prevalent global health issue closely tied to dietary habits, impacting a significant portion of the adult population. MAFLD is linked to various metabolic disorders, elevating risks of cirrhosis and hepatocellular carcinoma and severely impacting patients’ quality [...] Read more.

Metabolic-associated fatty liver disease (MAFLD) is a prevalent global health issue closely tied to dietary habits, impacting a significant portion of the adult population. MAFLD is linked to various metabolic disorders, elevating risks of cirrhosis and hepatocellular carcinoma and severely impacting patients’ quality of life. While therapeutic research has progressed, effective food-based interventions remain scarce. Natural products, rich in bioactive compounds and offering health benefits, have gained attention for their potential in managing MAFLD. This study employed network pharmacology and lipidomics to investigate the therapeutic effects of Food and Medicine Homology (FMH) on MAFLD using a high-fat-diet-induced HepG2 cell model. We identified 169 potential bioactive components from Radix Puerariae, Hericium erinaceus, Rhizoma Curcumae longae, Camellia oleifera, and Hoveniae Dulcis Semen, constructing a drug–component–target network that highlighted 34 key targets. The characteristic components of this FMH compound solution (HSD) were identified using UPLC-QTOF-MS/MS. In vitro, HSD significantly reduced intracellular lipid accumulation, decreased inflammatory markers, and mitigated hepatocyte damage. Lipidomics analysis revealed significant alterations in lipid metabolites, suggesting HSD’s potential to modulate sphingolipid and glycerophospholipid metabolism, thus improving MAFLD outcomes. This research underscores the critical role of the FMH complex in modulating lipid metabolism and inflammatory pathways, offering valuable insights for developing FMH-based dietary supplements and functional foods to alleviate MAFLD. By leveraging the synergistic effects of natural compounds, our findings hold significant implications for innovative nutritional strategies in managing this prevalent metabolic disorder. Full article

(This article belongs to the Section Nutraceuticals, Functional Foods, and Novel Foods)

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23 pages, 5210 KiB

Open AccessArticle

Pyrolysis and Combustion Kinetics of Garden Waste Pellets as Solid Biofuel for Thermochemical Energy Recovery

by Jonatan Gutiérrez and Juan F. Pérez

Materials 2025, 18(7), 1634; https://doi.org/10.3390/ma18071634 (registering DOI) - 3 Apr 2025

Abstract

The fallen leaf has the potential to be energy-valorized in cities with sustainability goals. Thermochemical characterization of garden waste through pyrolysis and combustion kinetics will establish the reactivity of this lignocellulosic biomass as biofuel for thermochemical conversion processes for energy recovery. Herein, the [...] Read more.

The fallen leaf has the potential to be energy-valorized in cities with sustainability goals. Thermochemical characterization of garden waste through pyrolysis and combustion kinetics will establish the reactivity of this lignocellulosic biomass as biofuel for thermochemical conversion processes for energy recovery. Herein, the thermal degradation of two types of pellets produced from fallen leaf (pellets without glycerol PG0, and pellets with 5 wt% glycerol PG5) are characterized under inert and oxidative atmospheres using three different approaches: thermogravimetry (TG) and differential thermogravimetry (DTG) analyses, TG-based reactivity, and reaction kinetics from three model-free isoconversional methods. The model-free isoconversional methods are Flynn–Wall–Ozawa (FWO), Kissinger–Akahira–Sunose (KAS), and Friedman, which were applied for estimating the kinetic parameters, activation energy (Eα) and pre-exponential factor, using different heating rates (20, 30, and 40 °C/min) to ensure reliable data interpretation. The pyrolysis results showed that PG5 was more reactive compared to PG0 because the addition of glycerol during the pelletizing process increased the volatile matter and oxygen content in PG5. Likewise, the higher reactivity of PG5 under pyrolysis was determined by average activation energy (Eα) with an average value of 96.82 kJ/mol compared to 106.46 kJ/mol for PG0. During the combustion process, Eα was 90.70 kJ/mol and 90.29 kJ/mol for PG0 and PG5, respectively. Finally, both materials exhibited higher reactivity under an oxidative atmosphere. Therefore, according to our results, the pellets produced from leaf litter can be used as biofuels for thermochemical processes, highlighting that using glycerol as a binder favors the reactivity of the densified garden waste. Full article

(This article belongs to the Special Issue Carbonaceous Materials: Fabrication, Characterization and Applications)

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12 pages, 3543 KiB

Open AccessArticle

Layout Design Strategies for Scaling Down Semiconductor Systems Based on Current Flow Analysis in Interconnect

by Seung Hwan Oh, Tae Yeong Hong, Sarah Eunkyung Kim, Jong Kyung Park and Seul Ki Hong

Appl. Sci. 2025, 15(7), 3944; https://doi.org/10.3390/app15073944 (registering DOI) - 3 Apr 2025

Abstract

As the demand for high-density integrated circuits increases, scaling down devices has already reached its limit, making the optimization of interconnect–via layout an important research challenge. Conventional semiconductor design adopts conservative margins to ensure process reliability, but this often results in inefficient space [...] Read more.

As the demand for high-density integrated circuits increases, scaling down devices has already reached its limit, making the optimization of interconnect–via layout an important research challenge. Conventional semiconductor design adopts conservative margins to ensure process reliability, but this often results in inefficient space utilization and degraded electrical performance. This study evaluates the possibility of optimizing design rules by analyzing the impact of reduced contact area in interconnect–via structures on the current flow and resistance. Finite element method analysis (FEM) using Ansys Workbench revealed that current is concentrated in approximately 20% of the interconnect height and the diagonal region of the via. A resistance model reflecting this current distribution demonstrated high accuracy, with an error range of 1–3% compared to simulation results. Resistance measurements of various fabricated structures produced through photolithography and lift-off processes showed a significant increase in resistance when the contact area was reduced to 50% or less, consistent with simulation results. This study demonstrates the potential to optimize both space utilization and electrical performance by minimizing the conservative margins between interconnects and vias, contributing to next-generation high-density integrated circuit design. Full article

(This article belongs to the Section Electrical, Electronics and Communications Engineering)

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15 pages, 11322 KiB

Open AccessArticle

Fast Wound Healing with a New Functional Hyaluronic Acid Dual Network Hydrogel

by Lichun Wu, Yu Zhou, Yi Zhang, Jia Hu, Yasuhiro Ikegami, Shinichi Aishima and Hiroyuki Ijima

Gels 2025, 11(4), 266; https://doi.org/10.3390/gels11040266 (registering DOI) - 3 Apr 2025

Abstract

As dressings for moist wound healing, hyaluronic acid hydrogels play a significant role in maintaining moisture and promoting wound healing. However, existing hydrogel dressings are inadequate in terms of slow gelation time, weak mechanical performance, and fast degradation, which increases the risk of [...] Read more.

As dressings for moist wound healing, hyaluronic acid hydrogels play a significant role in maintaining moisture and promoting wound healing. However, existing hydrogel dressings are inadequate in terms of slow gelation time, weak mechanical performance, and fast degradation, which increases the risk of secondary infections during treatment. Therefore, we developed a hyaluronic acid double network hydrogel (DNH). Compared to single-network hydrogels (hydrazone and Diels–Alder), DNH shows a short gelation time (25 s) and strong mechanical properties (Young’s modulus = 82 kPa). These advantages enable DNH to immediately fill the irregular shape of the wound after gelation and remain intact after being squeezed. Swelling tests indicated that DNH had a suitable swelling ratio and maintained its structural integrity after swelling. We evaluated the use of DNH as a moist dressing for full-thickness wound healing in vivo. DNH-treated wounds healed faster, with enhanced blood vessel formation and macrophage polarization than gauze-treated wounds. These findings suggest that DNH not only accelerates wound healing but also improves tissue regeneration. Therefore, DNH may be a suitable moist dressing for wound healing. Full article

(This article belongs to the Special Issue Current Directions and Prospects of Hydrogels for Biomedical Applications)

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14 pages, 939 KiB

Open AccessArticle

Synthesis and Evaluation of the Antiproliferative Activity of the Derivatives of 3,5-Diaryl-3,4-dihydro-2H-pyrrole-2-carboxilic Acids

by Vesela Mihaylova, Ivan Iliev, Anelia Vasileva, Elizabeth Mazzio, Bereket Mochona, Nelly Mateeva and Donka Tasheva

Molecules 2025, 30(7), 1602; https://doi.org/10.3390/molecules30071602 (registering DOI) - 3 Apr 2025

Abstract

The metabolic cycle of L-proline plays a crucial role in cancer cell survival, proliferation, and metastasis. A key intermediate in the biosynthesis and degradation of proline is 3,4-dihydro-2H-pyrrole-2-carboxilic acid. A direct route for synthesizing substituted derivatives of this acid involves the [...] Read more.

The metabolic cycle of L-proline plays a crucial role in cancer cell survival, proliferation, and metastasis. A key intermediate in the biosynthesis and degradation of proline is 3,4-dihydro-2H-pyrrole-2-carboxilic acid. A direct route for synthesizing substituted derivatives of this acid involves the cyclization of 2-amino-5-oxonitriles. Michael additions of [(diphenylmethylene)amino]acetonitrile to enones in a basic medium—either with aqueous sodium hydroxide or under solid–liquid phase-transfer catalysis conditions using CaO as a base—enable the synthesis of substituted 2-amino-5-oxonitriles as single diastereoisomers or as diastereoisomeric mixtures. Selective removal of the diphenylmethylene-protecting group, followed by in situ cyclization in acidic conditions, yields trans- and cis-3,5-diaryl-3,4-dihydro-2H-pyrrole-2-carbonitriles. The reaction of nitriles with HCl/dioxane/methanol followed by treatment with water produces esters and amides as by-products. In vitro screening of the synthesized compounds against multiple human cancer cell lines revealed that some compounds exhibit a good or high selectivity index. In conclusion, the synthetic schemes presented offer simple and efficient routes for the preparation of the derivatives of substituted 3,4-dihydro-2H-pyrrole-2-carboxilic acids, with some compounds exhibiting promising antiproliferative activity. Full article

(This article belongs to the Special Issue Design, Synthesis and Biological Activity of Novel Antitumor Drugs)

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18 pages, 961 KiB

Open AccessArticle

Barriers to the Adoption of Big Data Analytics in Saudi Arabia’s Manufacturing Sector: An Interpretive Structural Modeling Approach

by Almuhannad S. Alorfi and Naif Alsaadi

Systems 2025, 13(4), 250; https://doi.org/10.3390/systems13040250 (registering DOI) - 3 Apr 2025

Abstract

Big data analytics has the potential to greatly improve the operations of manufacturing industries, aid in decision making, and foster innovation. However, there exist several barriers that undermine the successful adoption of big data analytics in these industries. This paper presents a structural [...] Read more.

Big data analytics has the potential to greatly improve the operations of manufacturing industries, aid in decision making, and foster innovation. However, there exist several barriers that undermine the successful adoption of big data analytics in these industries. This paper presents a structural analysis of the barrier to big data analytics adoption in manufacturing industries. Through an extensive literature review and expert analysis, a compilation of the various barriers was made. The interpretive structure modeling (ISM) technique was then used to analyze the interplay between the barriers: this technique was used to build a hierarchy whose respective objective functions indicated how each barrier influenced the other. These findings help in the understanding of the hierarchical relationships between the various barriers and can thus help organizations in prioritizing strategies to mitigate these barriers. The results depict some barriers which do have a high-power influence over others and, as such, depict critical points that manufacturing industries need to address when adopting big data analytics. This paper also elaborates the relationships between the barriers, which will help the decision makers create strategies to mitigate them effectively. This study’s findings contribute to the existing body of knowledge on barriers to adopting big data analytics in manufacturing industries and provides an efficient approach for organizations to systematically address barriers. Full article

(This article belongs to the Section Systems Practice in Social Science)

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17 pages, 7248 KiB

Open AccessArticle

Sustainable Hydrogen Production with Negative Carbon Emission Through Thermochemical Conversion of Biogas/Biomethane

by Bin Wang, Yu Shao, Lingzhi Yang, Ke Guo, Xiao Li, Mengzhu Sun and Yong Hao

Energies 2025, 18(7), 1804; https://doi.org/10.3390/en18071804 (registering DOI) - 3 Apr 2025

Abstract

Biogas (primarily biomethane), as a carbon-neutral renewable energy source, holds great potential to replace fossil fuels for sustainable hydrogen production. Conventional biogas reforming systems adopt strategies similar to industrial natural gas reforming, posing challenges such as high temperatures, high energy consumption, and high [...] Read more.

Biogas (primarily biomethane), as a carbon-neutral renewable energy source, holds great potential to replace fossil fuels for sustainable hydrogen production. Conventional biogas reforming systems adopt strategies similar to industrial natural gas reforming, posing challenges such as high temperatures, high energy consumption, and high system complexity. In this study, we propose a novel multi-product sequential separation-enhanced reforming method for biogas-derived hydrogen production, which achieves high H₂ yield and CO₂ capture under mid-temperature conditions. The effects of reaction temperature, steam-to-methane ratio, and CO₂/CH₄ molar ratio on key performance metrics including biomethane conversion and hydrogen production are investigated. At a moderate reforming temperature of 425 °C and pressure of 0.1 MPa, the conversion rate of CH₄ in biogas reaches 97.1%, the high-purity hydrogen production attains 2.15 mol-H₂/mol-feed, and the hydrogen yield is 90.1%. Additionally, the first-law energy conversion efficiency from biogas to hydrogen reaches 65.6%, which is 11 percentage points higher than that of conventional biogas reforming methods. The yield of captured CO₂ reaches 1.88 kg-CO₂/m³-feed, effectively achieving near-complete recovery of green CO₂ from biogas. The mild reaction conditions allow for a flexible integration with industrial waste heat or a wide selection of other renewable energy sources (e.g., solar heat), facilitating distributed and carbon-negative hydrogen production. Full article

(This article belongs to the Special Issue Biomass and Bio-Energy—2nd Edition)

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28 pages, 3806 KiB

Open AccessArticle

Fourier Transform Infrared (FTIR) Database of Historical Pigments: A Comparison Between ATR-FTIR and DRIFT Modalities

by Daniel Jiménez-Desmond and José Santiago Pozo-Antonio

Appl. Sci. 2025, 15(7), 3941; https://doi.org/10.3390/app15073941 (registering DOI) - 3 Apr 2025

Abstract

The existence of historical pigments databases is important to speed up cultural heritage research. Knowledge of their chemical composition and their manufacture contributes to the study of art history and helps develop accurate conservation-restoration strategies. In this study, a total of nineteen pigments, [...] Read more.

The existence of historical pigments databases is important to speed up cultural heritage research. Knowledge of their chemical composition and their manufacture contributes to the study of art history and helps develop accurate conservation-restoration strategies. In this study, a total of nineteen pigments, among which we find silicates (Egyptian blue, natural and synthetic blue ultramarine, green earth and chrysocolla), oxides (natural and synthetic hematite, red and yellow natural ochres, and chromium green), carbonates (natural and synthetic azurite, natural and synthetic malachite, and white lead), sulphides (natural and synthetic cinnabar, and orpiment) and acetates, (verdigris) have been characterized by Fourier Transform Infrared-Spectroscopy in Attenuated Total Reflection (ATR-FTIR) and Diffuse Reflectance (DRIFT) modalities. Considering the latter, there is still a great deal of uncertainty in the interpretation of the different IR vibrational bands. Therefore, a comparative study between these two techniques has been carried out to highlight the potential of DRIFT spectroscopy as a portable and non-destructive technique that allows the differentiation and characterization of historical pigments in the field of cultural heritage. Before performing FTIR analysis, pigments were analysed using X-ray diffraction (XRD) to detect impurities and/or additives in the pigments. Differentiation between natural and synthetic pigments was possible due to the identification of impurities in natural pigments, and manufacture-related compounds or additives in synthetic pigments. Results obtained in this study have proven DRIFT to be a very useful analytical technique for in situ characterization of heritage materials. This study serves as an initial step in clarifying the challenges and uncertainties associated with interpreting spectra obtained through the DRIFT modality. However, the use of other complementary analytical techniques is required. Full article

(This article belongs to the Special Issue Solving Environmental and Cultural Heritage Issues Through Analytical Tools)

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21 pages, 3030 KiB

Open AccessArticle

Copula-Based Bayesian Model for Detecting Differential Gene Expression

by Prasansha Liyanaarachchi and N. Rao Chaganty

Analytics 2025, 4(2), 11; https://doi.org/10.3390/analytics4020011 (registering DOI) - 3 Apr 2025

Abstract

Deoxyribonucleic acid, more commonly known as DNA, is a fundamental genetic material in all living organisms, containing thousands of genes, but only a subset exhibit differential expression and play a crucial role in diseases. Microarray technology has revolutionized the study of gene expression, [...] Read more.

Deoxyribonucleic acid, more commonly known as DNA, is a fundamental genetic material in all living organisms, containing thousands of genes, but only a subset exhibit differential expression and play a crucial role in diseases. Microarray technology has revolutionized the study of gene expression, with two primary types available for expression analysis: spotted cDNA arrays and oligonucleotide arrays. This research focuses on the statistical analysis of data from spotted cDNA microarrays. Numerous models have been developed to identify differentially expressed genes based on the red and green fluorescence intensities measured using these arrays. We propose a novel approach using a Gaussian copula model to characterize the joint distribution of red and green intensities, effectively capturing their dependence structure. Given the right-skewed nature of the intensity distributions, we model the marginal distributions using gamma distributions. Differentially expressed genes are identified using the Bayes estimate under our proposed copula framework. To evaluate the performance of our model, we conduct simulation studies to assess parameter estimation accuracy. Our results demonstrate that the proposed approach outperforms existing methods reported in the literature. Finally, we apply our model to Escherichia coli microarray data, illustrating its practical utility in gene expression analysis. Full article

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12 pages, 18531 KiB

Open AccessArticle

Superficial Temporal Artery: Anatomical Variation and Its Clinical Significance

by Niccolò Fagni, Luca Valli, Giulio Nittari, Giulio Procelli, Jacopo Junio Valerio Branca, Roberto Cuomo, Marco Mandalà, Eugenio Bertelli, Sebastian Cotofana and Ferdinando Paternostro

J. Vasc. Dis. 2025, 4(2), 14; https://doi.org/10.3390/jvd4020014 (registering DOI) - 3 Apr 2025

Abstract

Background: The superficial temporal artery (STA) typically bifurcates into frontal and parietal branches in the temporal region. This study describes a rare anatomical variation identified during a cadaveric dissection where the STA presented an early cervical bifurcation. Methods: A cadaveric dissection was performed [...] Read more.

Background: The superficial temporal artery (STA) typically bifurcates into frontal and parietal branches in the temporal region. This study describes a rare anatomical variation identified during a cadaveric dissection where the STA presented an early cervical bifurcation. Methods: A cadaveric dissection was performed on a 58-year-old Caucasian female specimen injected with synthetic polymers. The STA was meticulously dissected, and anatomical findings were documented through photographs and measurements. Results: An unusual cervical bifurcation of the STA was observed. The frontal and parietal branches originated at the level of the posterior belly of the digastric muscle, ascending separately. The anterior branch, identified as the frontal branch, coursed below the facial nerve and stylomastoid artery, reaching the temporal line without further branching after giving the transverse facial artery as the only collateral branch. The posterior parietal branch extended posteriorly to the external acoustic meatus, compensating for the absence of the posterior auricular artery. This anatomical variation might influence surgical approaches to the head and neck region, particularly in parotid and reconstructive surgeries. Discussion: Variations in STA anatomy can significantly impact clinical practices, including reconstructive surgery, vascular interventions, and esthetic procedures. Imaging techniques, though useful, may not detect such rare variants. Cadaveric dissection remains a crucial tool for detailed anatomical assessment. Conclusions: This study highlights the importance of recognizing the STA’s vascular variations for safe surgical planning and improving patient outcomes. Further studies correlating imaging findings with cadaveric dissections are recommended. Full article

(This article belongs to the Section Peripheral Vascular Diseases)

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14 pages, 1326 KiB

Open AccessArticle

Maximizing Tax Revenue for Profit Maximizing Monopolist with the Cobb-Douglas Production Function and Linear Demand as a Bilevel Programming Problem

by Zrinka Lukač, Krunoslav Puljić and Vedran Kojić

AppliedMath 2025, 5(2), 37; https://doi.org/10.3390/appliedmath5020037 (registering DOI) - 3 Apr 2025

Abstract

Optimal taxation and profit maximization are two very important problems, naturally related to one another since companies operate under a given tax system. However, in the literature, these two problems are usually considered separately, either by studying optimal taxation or by studying profit [...] Read more.

Optimal taxation and profit maximization are two very important problems, naturally related to one another since companies operate under a given tax system. However, in the literature, these two problems are usually considered separately, either by studying optimal taxation or by studying profit maximization. This paper tries to link the two problems together by formulating a bilevel model in which the government acts as a leader and a profit maximizing follower acts as a follower. The exact form of the tax revenue function, as well as optimal tax amount and optimal input levels, are derived in cases when returns to scale take on values 0.5 and 1. Several illustrative numerical examples and accompanying graphical representations are given for decreasing, constant, and increasing returns to scale values. Full article

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20 pages, 10068 KiB

Open AccessArticle

Enhanced Room-Temperature Hydrogen Physisorption in Zeolitic Imidazolate Frameworks and Carbon Nanotube Hybrids

by Syedvali Pinjari, Tapan Bera and Erik Kjeang

Nanoenergy Adv. 2025, 5(2), 5; https://doi.org/10.3390/nanoenergyadv5020005 (registering DOI) - 3 Apr 2025

Abstract

In this work, zeolitic imidazolate frameworks (ZIF-8, ZIF-67, and ZC-ZIF) and their hybrid composites with carboxylate-functionalized carbon nanotubes (fCNTs) are synthesized through low-cost synthesis methods for enhanced physisorption-based hydrogen storage at room temperature. While both base and hybrid structures are designed to improve [...] Read more.

In this work, zeolitic imidazolate frameworks (ZIF-8, ZIF-67, and ZC-ZIF) and their hybrid composites with carboxylate-functionalized carbon nanotubes (fCNTs) are synthesized through low-cost synthesis methods for enhanced physisorption-based hydrogen storage at room temperature. While both base and hybrid structures are designed to improve hydrogen uptake, the base materials exhibit the most notable performance compared to their carbon hybrid counterparts. The structural analysis confirms that all samples maintain high crystallinity and exhibit well-defined rhombic dodecahedral morphologies. The hybrid composites, due to the intercalation of fCNTs, show slightly larger particle sizes than their base materials. X-ray photoelectron spectroscopy reveals strong nitrogen–metal coordination in the ZIF structures, contributing to a larger specific surface area (SSA) and optimal microporous properties. A linear fit of SSA and hydrogen uptake indicates improved hydrogen transport at low pressures due to fCNT addition. ZIF-8 achieves the highest SSA of 2023.6 m²/g and hydrogen uptake of 1.01 wt. % at 298 K and 100 bar, with 100% reversible adsorption. Additionally, ZIF-8 exhibits excellent cyclic repeatability, with only 10% capacity reduction after five adsorption/desorption cycles. Kinetic analysis reveals that hydrogen adsorption in the ZIF materials is governed by a combination of surface adsorption, intraparticle diffusion, and complex pore filling. These findings underscore the potential of ZIFs as superior materials for room-temperature hydrogen storage. Full article

(This article belongs to the Topic Hydrogen Energy Technologies, 2nd Edition)

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19 pages, 494 KiB

Open AccessReview

Subthreshold Autism and ADHD: A Brief Narrative Review for Frontline Clinicians

by Michael O. Ogundele and Michael J. S. Morton

Pediatr. Rep. 2025, 17(2), 42; https://doi.org/10.3390/pediatric17020042 (registering DOI) - 3 Apr 2025

Abstract

Background: Epidemiological studies have shown that neurodevelopmental disorders (NDDs), such as autism spectrum disorder (ASD) and attention deficit/hyperactivity disorder (ADHD) are more prevalent in the general childhood population, compared to cases that are formally diagnosed in clinical cohorts. This suggests that many children [...] Read more.

Background: Epidemiological studies have shown that neurodevelopmental disorders (NDDs), such as autism spectrum disorder (ASD) and attention deficit/hyperactivity disorder (ADHD) are more prevalent in the general childhood population, compared to cases that are formally diagnosed in clinical cohorts. This suggests that many children and youths have NDD which are never diagnosed clinically, causing impairments in some domains of their daily life. There is increasing recognition of the concept of a “subthreshold” condition, sometimes used to describe the presence of potentially impairing variations in the neurodevelopmental profile that do not meet criteria for a diagnosis. The aim of this narrative review is to appraise the published literature about common themes regarding subthreshold conditions in relation to autism and ADHD, identifying any practical lessons that may be applicable to frontline neurodevelopmental clinicians. Methods: We searched electronic databases including PMC and PubMed using various combinations of keywords, including “Subthreshold”, “subclinical”, “neurodevelopmental”, “childhood”, “ADHD” and “ASD”. Results: The identified themes include definitions, prevalence, assessment tools, lifetime impairments, NDD classification models, management, raising public awareness, and future research directions. Conclusions: The authors propose that a “subthreshold condition” should be recorded when NDDs do not meet current diagnostic criteria if there is evidence of significant, persisting impairment in at least one setting. Full article

(This article belongs to the Section Pediatric Psychology)

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