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24 pages, 3755 KB

Open AccessArticle

Annual and Spatial Variation in the Diet of Juvenile Pacific Cod in Mutsu Bay, Japan

by Anran Dong, Tetsuya Takatsu, Tomoya Ishikawa, Kenta Sasaki and Mitsuhiro Nakaya

Fishes 2026, 11(5), 302; https://doi.org/10.3390/fishes11050302 (registering DOI) - 19 May 2026

To evaluate Mutsu Bay as a nursery habitat for Pacific cod (Gadus macrocephalus Tilesius, 1810), we analyzed settled age-0 juveniles collected with a small bottom otter trawl over 10 years. The three stations with the highest juvenile densities were targeted, and prey-specific [...] Read more.

To evaluate Mutsu Bay as a nursery habitat for Pacific cod (Gadus macrocephalus Tilesius, 1810), we analyzed settled age-0 juveniles collected with a small bottom otter trawl over 10 years. The three stations with the highest juvenile densities were targeted, and prey-specific feeding intensity (SCIi), its sum (SCI), and the relative condition factor (Kn) were quantified, followed by examining their relationships with juvenile attributes and environmental variables. Diets varied among stations and shifted ontogenetically from small-sized calanoid copepods to larger planktonic and benthic prey. SCI was highest at stations where juveniles consumed medium-sized plankton (0.1–1.0 mg ind⁻¹), including Calanus pacificus, Mesocalanus tenuicornis, Metridia pacifica, Anomura zoeae, and Euphausiacea furciliae, and lower where other prey dominated. High-SCI individuals were rarely observed, likely reflecting enhanced digestion at high temperatures near the upper habitat limit (~12 °C) and consistently low prey density independent of temperature. Kn increased with body size and SCI and tended to be higher in cooler water and closer to the bay mouth, suggesting coupled environmental and physiological constraints. These results suggest that after late May, juveniles may benefit from moving toward the bay mouth, where prey encounter rates are likely higher, including relatively larger prey, which may improve feeding opportunities and condition. Full article

(This article belongs to the Special Issue Ecology of Fish: Age, Growth, Reproduction and Feeding Habits)

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10 pages, 201 KB

Open AccessEditorial

Spatial Planning and Land-Use Management—2nd Edition: Expanding the Agenda of Integrated and Multiscalar Spatial Governance

by Eduardo Gomes, Patrícia Abrantes and Eduarda Marques da Costa

Land 2026, 15(5), 877; https://doi.org/10.3390/land15050877 (registering DOI) - 19 May 2026

Abstract

This Editorial introduces the Special Issue “Spatial Planning and Land-Use Management: 2nd Edition” and discusses the eight articles published in it. Taken together, these contributions demonstrate that contemporary spatial planning and land-use management can no longer be understood as narrowly regulatory or sector-specific [...] Read more.

This Editorial introduces the Special Issue “Spatial Planning and Land-Use Management: 2nd Edition” and discusses the eight articles published in it. Taken together, these contributions demonstrate that contemporary spatial planning and land-use management can no longer be understood as narrowly regulatory or sector-specific activities. Rather, they must be approached as integrative and adaptive practices capable of mediating between ecological integrity, territorial cohesion, infrastructure provision, social justice, public health, and participatory governance. The Special Issue brings together case studies from China, the United States, Australia, Iran, Portugal, Slovakia, and Belgium, as well as comparative evidence from peri-urban landscapes, and spans a wide range of spatial scales, from neighbourhoods and urban forests to metropolitan green belts, urban agglomerations, peri-urban territories, and ecoregions. Several major lines of inquiry emerge across the volume. First, the articles reaffirm the need for multiscale planning frameworks able to connect local action with regional and supra-regional structures. Second, they broaden the understanding of infrastructure by including not only transport and urban facilities, but also ecological, green, and even nocturnal infrastructures. Third, they show that many of today’s most difficult planning questions arise in spaces of transition and overlap, especially peri-urban areas, where conflicts among land uses, ecosystem services, development pressures, and governance arrangements become particularly acute across sectors and across spatial and temporal scales. Fourth, they underline that planning effectiveness increasingly depends on participation, co-design, and cooperation among diverse actors, including civic initiatives and local communities. Overall, the Special Issue highlights spatial planning as a strategic field of action through which societies can address land-use conflicts, reconcile environmental and social objectives, and design more sustainable, resilient, and liveable territories. Full article

(This article belongs to the Special Issue Spatial Planning and Land-Use Management: 2nd Edition)

13 pages, 668 KB

Open AccessReview

Excitotoxicity and Neurological Post-COVID-19 Syndrome: Exploring Possible Connections of Pathophysiological Mechanisms

by Rodrigo Portes Ureshino, Larissa Augusta de Sousa, Rafaela Brito Oliveira, Giulia Alves Saullo, Pedro Henrique Zonaro, Louise Newson, Carla Máximo Prado and Roberta Sessa Stilhano

COVID 2026, 6(5), 85; https://doi.org/10.3390/covid6050085 (registering DOI) - 19 May 2026

Abstract

Excitotoxicity is one of the factors that participates in neurodegeneration, impairing neuronal and glial cells’ function, and leading to the development of chronic neurodegenerative diseases. The main mechanism of action lies in the overstimulation of excitatory receptors, especially the NMDA (N-methyl-D-aspartic acid) receptor, [...] Read more.

Excitotoxicity is one of the factors that participates in neurodegeneration, impairing neuronal and glial cells’ function, and leading to the development of chronic neurodegenerative diseases. The main mechanism of action lies in the overstimulation of excitatory receptors, especially the NMDA (N-methyl-D-aspartic acid) receptor, by glutamate, which promotes a massive influx of Ca²⁺ that is not sufficiently buffered by the intracellular machinery, or not released by mechanisms such as Ca²⁺ ATPase and plasma membrane Ca²⁺/Na⁺ exchanger promoting, among other toxic effects, mitochondrial damage and an increase in reactive oxygen species (ROS). Notably, many cases reported of long COVID-19 describe significant brain alterations and neuropsychiatric disorders, including delirium, depression, etc., and patients required increased use of antidepressant or anxiolytic drugs, for example. In addition, emerging evidence links neurodegeneration as a potential long-term sequelae associated with an increased number of patients with cognitive disorders. This review analyzes data from the literature regarding brain alterations associated with post-COVID-19 syndrome and explores a potential link to the excitotoxicity pathways, due to its participation in neurodegeneration by homeostatic failure, and it is clearly present in various brain conditions, such as Alzheimer’s and Parkinson’s diseases. Full article

(This article belongs to the Special Issue Exploring Neuropathology in the Post-COVID-19 Era)

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83 pages, 2755 KB

Open AccessReview

The Impact of Maternal Obesity and Diabetes on the Development of Congenital Heart Defects (CHDs) in Offspring: A Narrative Review

by Marek Zubrzycki, Mariusz Kuśmierczyk, Jan Fritz Gummert, Angelika Costard-Jäckle, Lech Paluszkiewicz, Tobias Hecht, Ingvild Birschmann, Anna Zubrzycka and Maria Zubrzycka

Metabolites 2026, 16(5), 341; https://doi.org/10.3390/metabo16050341 (registering DOI) - 19 May 2026

Abstract

Congenital heart disease (CHD) is the most common anatomical malformation occurring in live-born infants and an increasing cause of morbidity and mortality all over the world. Population-based observations have described associations between maternal cardiometabolic disorders and the risk of CHD in offspring. The [...] Read more.

Congenital heart disease (CHD) is the most common anatomical malformation occurring in live-born infants and an increasing cause of morbidity and mortality all over the world. Population-based observations have described associations between maternal cardiometabolic disorders and the risk of CHD in offspring. The present article is a narrative review. The aim of this study was to review the epidemiological evidence and clinical observations relating maternal obesity and diabetes mellitus to the risk of CHD in offspring, with particular attention paid to first trimester disturbances of fetal cardiac development and the influence of genetic, epigenetic and environmental factors. Studies have shown that maternal diabetes is a risk factor associated with nearly all subtypes of CHDs in offspring, while obesity and overweight are associated with increased risk for complex defects and outflow tract obstruction and decreased risk for ventricular septal defects. Diabetes and obesity share several phenotypes, which could be transmissible from mother to fetus via the placenta. This means that an increase in maternal glucose could be responsible for the prevalence of CHD in newborns of obese women. On the other hand, maternal diabetes may induce epigenetic modifications in the developing fetus. DNA methylation changes can impact gene expression patterns relevant to heart development. The abovementioned studies are heterogenous, express different opinions and are often difficult to compare. Therefore, the results from these meta-analyses must be interpreted with caution. Optimal diabetes control is responsible for the prevention of oxidative stress in diabetic pregnancies, and a deeper understanding of maternal risk factors holds the potential to improve both prenatal detection of CHDs by identifying at-risk pregnancies and primary prevention of diseases by improving preconception management. Full article

(This article belongs to the Section Thematic Reviews)

23 pages, 604 KB

Open AccessArticle

Loneliness and Sleep Quality Among Older Adults Living in Nursing Homes

by Rui Novais, Cláudia Rodrigues, Fátima Braga, Rui Pereira, Carlos Sequeira, Núria Albacar-Riobóo, Silvana Martins and Odete Araújo

Nurs. Rep. 2026, 16(5), 173; https://doi.org/10.3390/nursrep16050173 (registering DOI) - 19 May 2026

Abstract

Background: Population ageing has increased the number of older adults living in nursing homes, where loneliness and sleep disturbances are prevalent and negatively affect well-being. Evidence suggests a bidirectional relationship between loneliness and sleep quality, although research in institutionalised populations remains limited. Objectives: [...] Read more.

Background: Population ageing has increased the number of older adults living in nursing homes, where loneliness and sleep disturbances are prevalent and negatively affect well-being. Evidence suggests a bidirectional relationship between loneliness and sleep quality, although research in institutionalised populations remains limited. Objectives: This study aimed to characterise the sociodemographic and health profile of nursing home residents in Northern Portugal and examine associations between sleep quality, loneliness, sociodemographic and health variables. Methods: A cross-sectional study was conducted with 157 older adults (≥65 years) across 13 nursing homes. Data were collected using a sociodemographic questionnaire and the Portuguese version of UCLA Loneliness Scale, Pittsburgh Sleep Quality Index and Montreal Cognitive Assessment. Pearson correlations and hierarchical multiple regression analyses were performed. Results: Participants were predominantly female (72.6%), widowed (55.4%), and aged ≥80 years. Most reported chronic conditions (98.7%) and limitations in activities of daily living (75.2%). Age showed modest positive correlations with loneliness. Loneliness dimensions were strongly associated with poorer sleep quality and greater daytime dysfunction. Hierarchical regression revealed that sociodemographic variables explained only a small proportion of variance in sleep quality. The addition of loneliness variables increased explained variance to 38.1%, highlighting loneliness as a key psychosocial predictor. Conclusions: Loneliness significantly influences sleep quality among older adults living in nursing homes. Interventions should integrate strategies to enhance social engagement alongside sleep hygiene measures. Longitudinal studies are recommended to clarify causal pathways. Full article

(This article belongs to the Section Nursing Care for Older People)

37 pages, 7818 KB

Open AccessArticle

Immune Evasion in Prostate Cancer: Resolving the Cold Tumour Paradox via a Hybrid Discrete–Continuum Computational Framework

by Andile Kenneth Ntlokwana, Edinah Mudimu and Monde McMillan Ntwasa

Biology 2026, 15(10), 806; https://doi.org/10.3390/biology15100806 (registering DOI) - 19 May 2026

Abstract

Prostate cancer (PCa) is immunologically “cold” and resistant to immune checkpoint blockade (ICB), yet bulk analyses show low, non-prognostic PD-L1 expression. We hypothesised that this paradox reflects two overlooked dimensions: basal heterogeneity (static engine) and IFN-

γ

-driven adaptive resistance (adaptive engine). Using [...] Read more.

Prostate cancer (PCa) is immunologically “cold” and resistant to immune checkpoint blockade (ICB), yet bulk analyses show low, non-prognostic PD-L1 expression. We hypothesised that this paradox reflects two overlooked dimensions: basal heterogeneity (static engine) and IFN-

γ

-driven adaptive resistance (adaptive engine). Using TCGA-PRAD data (

n = 554

) to parameterise an agent-based model, we simulated clonal selection and extended it to a hybrid discrete-continuum framework with reaction-diffusion IFN-

γ

. Bulk PD-L1 was low (median 1.48 TPM) and non-prognostic (HR

= 1.15

,

p = 0.621

). The static engine alone produced weak immunoediting (1.10-fold enrichment), whereas the adaptive engine drove a 2.95-fold enrichment of PD-L1-high clones via protective sanctuary formation, without increasing final tumour burden. Induction knockout (

P_{max} = 0

) abrogated this advantage, while diffusion knockout (

D = 0

) had no effect. The cold tumour paradox is resolved by a hierarchical twin engine: rare genomic outliers permit initial persistence, but local IFN-

γ

/PD-L1 feedback dominates resistance, identifying induction capacity as the primary therapeutic target for JAK/STAT inhibition combined with ICB. Full article

(This article belongs to the Section Bioinformatics)

25 pages, 685 KB

Open AccessArticle

Assessing Learning Principles in Agricultural Extension Practice for Sustainable Communication of Extension Recommendations: Evidence from Egypt

by Salah S. Abd El-Ghani, Mohamed Abd Alwahab Albaz, Zain ELabedin Farrag Saad Ismail and Tamer Gamal Ibrahim Mansour

Sustainability 2026, 18(10), 5119; https://doi.org/10.3390/su18105119 (registering DOI) - 19 May 2026

Abstract

This study aimed to identify the level of awareness and application of learning principles among agricultural extension service providers when communicating extension recommendations to farmers. It also sought to determine the major constraints that may hinder the effective application of these principles in [...] Read more.

This study aimed to identify the level of awareness and application of learning principles among agricultural extension service providers when communicating extension recommendations to farmers. It also sought to determine the major constraints that may hinder the effective application of these principles in extension practice. The study adopted a descriptive analytical approach. Data were collected using a structured questionnaire designed to achieve the objectives of the research. The study was conducted on all agricultural extension service providers in Kafr El-Sheikh Governorate, totaling 55 respondents. The study focused on nine learning principles relevant to extension education: motivation, clarity of objectives, self-activity, transfer of learning, learner individuality, readiness, reinforcement, modification or relearning, and repetition. The findings revealed variation in the levels of knowledge and application of these principles among the respondents. The results indicated that 65.4% of the respondents had a moderate level of knowledge of the motivation principle, while 67.2% applied it at a moderate level. In contrast, 81.8% of the respondents had a low level of knowledge of the principle of clarity of objectives, and 85.4% applied it at a low level. The results also revealed several constraints that limit the effective application of learning principles in extension work, most notably the limited effectiveness of communication with farmers and the need to strengthen the educational competencies of extension service providers. Accordingly, the study recommends developing the instructional capacities of extension service providers through specialized training programs on learning principles and extension education methods in order to improve the effectiveness of communicating agricultural recommendations and enhance the adoption of agricultural innovations. Full article

(This article belongs to the Special Issue Adoption of New Technologies and Practices for Sustainable and Smart Agriculture: 2nd Edition)

20 pages, 1218 KB

Open AccessArticle

Multi-Species Modeling of Chloride Ingress in Heterogenous Recycled Aggregate Concrete: Bidirectional Effects of Old Mortar

by Lixuan Mao, Dewen Yao, Bin Zhang and Fuqiang He

Buildings 2026, 16(10), 2000; https://doi.org/10.3390/buildings16102000 (registering DOI) - 19 May 2026

Abstract

The structural application of Recycled Aggregate Concrete (RAC) in marine and coastal structures remains restricted by its highly variable quality and uncertain durability. Although the adhered old mortar is recognized as the most distinctive feature of RAC, its bidirectional influence on chloride transport, [...] Read more.

The structural application of Recycled Aggregate Concrete (RAC) in marine and coastal structures remains restricted by its highly variable quality and uncertain durability. Although the adhered old mortar is recognized as the most distinctive feature of RAC, its bidirectional influence on chloride transport, acting as a preferential transport pathway and a chloride-binding reservoir, has not yet been systematically elucidated. This study develops a five-phase mesoscopic numerical framework (natural aggregate, new and old mortars, new and old ITZs) to investigate the bidirectional effects on chloride ingress. The proposed model involves multi-species (K⁺, Na⁺, Cl⁻, OH⁻, Ca²⁺, SO₄²⁻) coupling and thermodynamic chloride binding on AFm and C-S-H phases, with different binding capacities in old and new mortar. This model was validated against published experimental data, demonstrating high accuracy in predicting effective diffusivity across varying replacement rates. Parametric sensitivity analyses reveal that RAC’s chloride resistance is governed by the competition between the “facilitation effect”, caused by the inherent porosity in attached old mortar, and the “retardation effect”, caused by enhanced binding capacity. This work provides new mechanistic insight into the dual effects of old mortar and establishes a robust theoretical tool for the durability design of RAC structures exposed to chloride environments. Full article

(This article belongs to the Special Issue Durability of Construction Materials in Marine and Other Harsh Environments)

28 pages, 6474 KB

Open AccessArticle

LLM-Based Modelling of AAS-Compliant Digital Twins to Describe Capabilities in Manufacturing-as-a-Service

by Marc Leon Haller, Kym Watson, Felix Schöppenthau and Ljiljana Stojanovic

Appl. Sci. 2026, 16(10), 5059; https://doi.org/10.3390/app16105059 (registering DOI) - 19 May 2026

Abstract

Disruptions threaten supply chains, creating a need for more resilient manufacturing networks. Manufacturing-as-a-Service (MaaS) has emerged as a promising Industry 4.0 approach to address this challenge. Yet, its effectiveness relies on interoperable digital twins (DTs), enabling the standardized exchange of manufacturing capabilities across [...] Read more.

Disruptions threaten supply chains, creating a need for more resilient manufacturing networks. Manufacturing-as-a-Service (MaaS) has emerged as a promising Industry 4.0 approach to address this challenge. Yet, its effectiveness relies on interoperable digital twins (DTs), enabling the standardized exchange of manufacturing capabilities across organizational boundaries. The Asset Administration Shell (AAS) standards can be used to meet this requirement. However, modeling AAS-compliant DTs is considered challenging due to the standard’s complexity. This paper, therefore, investigates the automatic generation of AAS-compliant DTs for representing manufacturing capabilities. Requirements from MaaS use cases in two research projects reveal limitations in current approaches. To address these limitations, this paper introduces an automated, LLM-supported generation process that leverages ontologies as a domain-specific knowledge base. The approach is operationalized in a modular software architecture and demonstrated through two use cases. Full article

(This article belongs to the Special Issue Digital Twin and IoT, 2nd Edition)

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24 pages, 381 KB

Open AccessArticle

Behavioral and Psychosocial Correlates of Gender Differences in Adolescent Mental Health: A Regional Cross-Sectional Study in Northern Italy

by Christian J. Wiedermann, Verena Barbieri, Giuliano Piccoliori and Doris Hager von Strobele Prainsack

Behav. Sci. 2026, 16(5), 812; https://doi.org/10.3390/bs16050812 (registering DOI) - 19 May 2026

Abstract

Background: Gender differences in adolescent mental health are well documented; however, the extent to which modifiable behavioral and psychosocial factors account for the excess of mental health problems in females remains insufficiently quantified. Methods: Data from the 2025 Corona and Psyche South Tyrol [...] Read more.

Background: Gender differences in adolescent mental health are well documented; however, the extent to which modifiable behavioral and psychosocial factors account for the excess of mental health problems in females remains insufficiently quantified. Methods: Data from the 2025 Corona and Psyche South Tyrol (COP-S) survey comprised a base sample of 2428 adolescents aged 11–19 years (51.4% males) with valid self-reported data. Multivariable regression analyses were conducted on 1448–1603 adolescents (depending on the outcome) who provided complete responses to the relevant predictor and outcome measures. Gender differences in depressive symptom scores (PHQ-2), generalized anxiety symptom scores (SCARED-GAD), and emotional/behavioral difficulties (SDQ) were examined using Mann–Whitney U and chi-square tests. Multivariable linear regression models were used to assess the associations between mental health outcomes and the ten predictors. Gender effects were quantified by comparing standardized regression coefficients from unadjusted and adjusted models. Results: Female adolescents reported higher generalized anxiety symptoms (median 6 vs. 4; rank-biserial r = 0.24), depressive symptoms (r = 0.13), and emotional/behavioral (r = 0.08) scores than male adolescents. School stress, problematic Internet use, and sleep-onset difficulties were the factors most strongly associated with all three outcomes (all p < 0.001). After multivariable adjustment, gender remained significantly associated with generalized anxiety symptoms (β = 0.18) and depressive scores (β = 0.09) but no longer reached significance for emotional/behavioral scores (β = 0.04, p = 0.078). The attenuation of the gender effect ranged from 25.3% for generalized anxiety symptoms to 37.1% for depressive symptoms and 58.5% for emotional/behavioral difficulties. Conclusions: Gender differences in adolescent mental health were substantially attenuated after adjustment for modifiable behavioral and psychosocial factors, with the gender difference in emotional/behavioral scores no longer statistically significant after adjustment. Persistent gender disparities in generalized anxiety symptoms suggest that mechanisms beyond the measured behavioral correlates may contribute to this gender difference and warrant further investigation. Full article

(This article belongs to the Special Issue Mental Health in Adolescent)

25 pages, 2708 KB

Open AccessArticle

Vibration-Based Condition Monitoring of Ground Engaging Tools Using Finite Element-Derived Modal Features

by Shasha Chen, Bernard F. Rolfe, James Griffin, Arnaldo Delli Carri and Michael P. Pereira

Vibration 2026, 9(2), 36; https://doi.org/10.3390/vibration9020036 (registering DOI) - 19 May 2026

Abstract

Ground engaging tool (GET) wear monitoring is important for mining excavator maintenance, but progressive multi-tooth wear estimation remains insufficiently explored. This study presents a vibration-based framework for GET wear estimation during operations using modal analysis, finite element (FE) modelling, and machine learning as [...] Read more.

Ground engaging tool (GET) wear monitoring is important for mining excavator maintenance, but progressive multi-tooth wear estimation remains insufficiently explored. This study presents a vibration-based framework for GET wear estimation during operations using modal analysis, finite element (FE) modelling, and machine learning as a supporting evaluation tool. A laboratory-scale mining bucket surrogate with detachable attached masses was used to represent progressive tooth wear through controlled mass-loss conditions. Experimental impact hammer tests under approximately free-free boundary conditions were conducted to validate the FE modal model through natural-frequency comparison and qualitative mode correspondence. The validated FE model was then used to generate a broader dataset of multi-tooth wear scenarios, from which the first ten natural frequencies were extracted as modal features. Linear Regression (LR) was adopted as a simple and interpretable baseline to evaluate both overall wear estimation and individual tooth wear estimation. High accuracy was obtained for overall wear estimation for both the non-symmetric and symmetry-augmented datasets, with R² values of 0.9983 and 0.9976, respectively. In contrast, individual tooth prediction was more challenging, and the symmetry-augmented results showed that mirrored tooth locations can produce non-unique frequency-based signatures. An additional asymmetric FE sensitivity study further confirmed that structural symmetry can limit local wear identifiability when only global natural frequencies are used. These findings demonstrate the potential of FE-derived modal frequency features for laboratory-scale GET wear assessment, while also highlighting the limitations of frequency-only features for unique local wear localisation in symmetric structures. This is a promising approach for wear estimation during mining operations. Full article

(This article belongs to the Special Issue New Trends in Experimental and Numerical Vibroacoustic Techniques—Physics Guided and Datas Guided Approaches)

18 pages, 457 KB

Open AccessReview

Artificial Intelligence in Cervical Cytology: Opportunities and Limitations in Screening, Triage, and Diagnostic Support

by Agata Stanek-Widera, Jędrzej Borowczak, Dominik Skiba, Michel-Edwar Mickael, Marzena Łazarczyk, Mateusz Maniewski, Łukasz Szylberg, Andrey Bychkov and Piotr Religa

Diagnostics 2026, 16(10), 1541; https://doi.org/10.3390/diagnostics16101541 (registering DOI) - 19 May 2026

Abstract

Cervical cancer remains a major global health challenge, particularly in low- and middle-income countries, where access to screening, vaccination, and timely treatment may be limited. Cervical cytology has played an important historical role in prevention, but it is labor-intensive, time-consuming, and subject to [...] Read more.

Cervical cancer remains a major global health challenge, particularly in low- and middle-income countries, where access to screening, vaccination, and timely treatment may be limited. Cervical cytology has played an important historical role in prevention, but it is labor-intensive, time-consuming, and subject to observer variability and limited sensitivity. In many contemporary screening programs, HPV testing is now used as the primary screening test, while cytology is used mainly for the triage of HPV-positive women. In recent years, artificial intelligence (AI), particularly deep learning (DL), has shown considerable potential in medical image analysis and computer-aided diagnosis. This review summarizes current applications of AI in cervical cytology and related diagnostic workflows, including automated and assisted slide screening, liquid-based cytology, the triage of equivocal or HPV-positive cases, and colposcopy support. Across these settings, AI-assisted systems may improve efficiency, standardization, and diagnostic consistency, and may reduce workload in resource-constrained environments. However, the evidence is heterogeneous, and important challenges remain, including the need for large and diverse datasets, prospective validation, regulatory approval, digital infrastructure, workflow integration, and the resolution of ethical and legal issues. AI should therefore be regarded as a promising adjunct to human expertise rather than a replacement in cervical cytology and related clinical diagnostic pathways. Full article

(This article belongs to the Section Machine Learning and Artificial Intelligence in Diagnostics)

30 pages, 3882 KB

Open AccessArticle

Shoreline and Onshore Phenological Characteristics Change Assessment of Bangladesh Delta Adjacent to the Bay of Bengal from 2021 to 2025 Using Satellite Remote Sensing

by Md. Shamsuzzoha, Sanjida Hossain Setu, Israt Zahan Oyshi, Wang Lei, Md. Anwarul Abedin, Ayesha Akter and Tofael Ahamed

Coasts 2026, 6(2), 21; https://doi.org/10.3390/coasts6020021 (registering DOI) - 19 May 2026

Abstract

Bangladesh is an extremely climate-exposed country, with erosion, accretion, tidal surges, and cyclones continuously modifying coastal districts. Shoreline change in Bangladesh is crucial for sustainable coastal management and disaster resilience. Therefore, the objectives of this research are as follows: (i) to assess accretion- [...] Read more.

Bangladesh is an extremely climate-exposed country, with erosion, accretion, tidal surges, and cyclones continuously modifying coastal districts. Shoreline change in Bangladesh is crucial for sustainable coastal management and disaster resilience. Therefore, the objectives of this research are as follows: (i) to assess accretion- and erosion-based shoreline changes of the Bangladesh delta adjacent to the Bay of Bengal for 2021–2025 using a fixed 2021 reference shoreline and a 2025 shoreline proxy extracted from Landsat 8/9 imagery, and (ii) to explore onshore change dynamics from satellite-derived NDVI, NDBI, and NDWI for 2022–2025. The study covers 14 coastal districts and integrates the 2021 baseline shoreline, Survey of Bangladesh geospatial datasets, and 17,055 Ground Reference Points (GRPs) to support geometric consistency and spatially explicit reporting at the delta scale. Three spectral indices—Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), and Normalized Difference Built-up Index (NDBI)—were applied to assess vegetation health, surface water distribution, and built-up/exposed land characteristics. Results indicate spatial variability in coastal change, with 383.49 km² of land gained through accretion and 124.12 km² lost to erosion, resulting in a neat accretion of 259.37 km² between 2021 and 2025; 8747.91 km² remained geomorphologically stable. Spectral index trends show minimal inter-annual NDVI and NDWI variability, suggesting stable vegetation cover and no long-term expansion of surface water. In contrast, a slight increase in NDBI indicates localized exposure of new sediments or small-scale land-use transitions along emerging coastal zones. Spearman correlation analysis highlights consistent negative relationships between NDVI and NDWI and moderate contrasts between NDVI and NDBI, reinforcing the coexistence of vegetation recovery, water withdrawal, and sediment-driven land emergence. The novelty of this study lies in the provision of consistent, near-real-time coastal change inventory for the full ~710 km Bangladesh delta coastline by combining a common 2021 baseline shoreline with harmonized Landsat 8/9 OLI surface reflectance (2022–2025) and linked onshore spectral-index dynamics over the same period. Overall, this short-term assessment reveals a sedimentary system that is active but balanced, with accretion surpassing erosion despite cyclone-affected disturbances, underscoring the value of operational satellite monitoring for coastal management, hazard preparedness, and climate-adaptive planning. Full article

20 pages, 2117 KB

Open AccessArticle

Recombinant Spider Silk Enhances Engineered Cartilage Formation

by Hongji Zhang, Xinyu Huang, Jinwen Zhang, Fengjie Zhang, Fei Sun and Chao Wan

J. Funct. Biomater. 2026, 17(5), 252; https://doi.org/10.3390/jfb17050252 (registering DOI) - 19 May 2026

Abstract

Articular cartilage is characterized by its avascular, aneural, and alymphatic nature, which confers a limited intrinsic capacity for self-repair. Current regenerative strategies primarily focus on alleviating pain, mitigating symptoms, and restoring joint function. However, their long-term efficacy remains uncertain. Cartilage tissue engineering has [...] Read more.

Articular cartilage is characterized by its avascular, aneural, and alymphatic nature, which confers a limited intrinsic capacity for self-repair. Current regenerative strategies primarily focus on alleviating pain, mitigating symptoms, and restoring joint function. However, their long-term efficacy remains uncertain. Cartilage tissue engineering has emerged as a promising alternative to conventional therapies, offering innovative solutions for articular cartilage regeneration. Central to this approach is the development of functional biomaterials capable of supporting chondrogenic cell adhesion, proliferation, and differentiation, thereby facilitating effective cartilage repair. In this study, we introduce a novel protein-based recombinant spider silk (RSS) as a potential biomaterial for modulating chondrocyte behavior and enabling engineered cartilage formation both in vitro and in vivo. RSS was generated through molecular cloning and processed into silk fibers using biomimetic spinning and acidic coagulation techniques. In micromass cultures of murine chondrocytes, RSS significantly promoted cell aggregation, resulting in increased cell density. Alcian blue and Oil Red O staining demonstrated that RSS-treated cultures produced abundant glycosaminoglycans, a hallmark of chondrogenic activity, while exhibiting minimal lipid accumulation. These findings suggest that RSS supports chondrogenic differentiation and suppresses adipogenic lineage commitment. Real-time PCR analysis revealed upregulation of the chondrogenesis-related gene Sox9 and downregulation of the adipogenic marker PPARγ and the hypertrophic marker Runx2 in RSS-treated micromass cultures. RNA sequencing further corroborated these observations, underscoring the role of RSS in modulating extracellular matrix (ECM) remodeling in chondrocytes. In a subcutaneous transplantation model using severe combined immunodeficiency (SCID) mice, chondrocytes encapsulated in three-dimensional hydrogel scaffolds containing RSS exhibited significantly enhanced ECM accumulation compared to RSS-free controls, indicating that RSS supports the maintenance of the chondrocyte phenotype and promotes cartilage formation in vivo, and underscoring its promising potential as a component of hydrogel composite systems. These findings highlight the potential of RSS as a functional biomaterial to preserve chondrocyte functionality and advance engineered cartilage formation, presenting a promising avenue for cartilage tissue engineering and regeneration. Full article

(This article belongs to the Section Biomaterials for Tissue Engineering and Regenerative Medicine)

16 pages, 790 KB

Open AccessSystematic Review

Surgical Techniques and Materials Used in the Treatment of Complicated Otomastoiditis: A Systematic Review

by Maria Denisa Zica, Catalina Voiosu, Andreea Rusescu, Irina Ionita, Luana Maria Gherasie, Oana Ruxandra Alius, Alexandra Bizdu Branovici, Razvan Hainarosie and Viorel Zainea

J. Clin. Med. 2026, 15(10), 3911; https://doi.org/10.3390/jcm15103911 (registering DOI) - 19 May 2026

Abstract

Background and Objectives: Complicated cholesteatomatous otomastoiditis includes a spectrum of inflammatory, suppurative, and destructive lesions affecting the temporal bone and surrounding critical structures, including the dura mater, labyrinth, facial nerve, sigmoid sinus, and skull base. The selection of appropriate surgical techniques and closure [...] Read more.

Background and Objectives: Complicated cholesteatomatous otomastoiditis includes a spectrum of inflammatory, suppurative, and destructive lesions affecting the temporal bone and surrounding critical structures, including the dura mater, labyrinth, facial nerve, sigmoid sinus, and skull base. The selection of appropriate surgical techniques and closure materials is decisive for long-term outcomes, functional preservation, and prevention of life-threatening complications. This systematic review and meta-analysis evaluates the evidence base for surgical approaches, intraoperative technologies, and autologous and synthetic closure materials used in the management of iatrogenic and disease-related fistulas in otomastoid surgery. Materials and Methods: A PRISMA 2020-compliant search was conducted across PubMed, Cochrane Library, Embase, and Scopus (2000–2024). The review was registered in PROSPERO (CRD420261370406). After the systematic screening process, 56 eligible studies involving 4218 patients were selected for inclusion. The primary outcome measures analysed were infection rates, fistula recurrence, preservation of function, and long-term integrity of the closure. Limitations include the predominance of observational studies and the absence of prospective registration prior to data extraction. Results: Autologous materials demonstrated consistently low infection rates (<10%) in contaminated operative fields and therefore remain the preferred first-line option for the reconstruction of small to moderate defects. In contrast, synthetic materials exhibited superior mechanical durability in large sterile defects, achieving closure integrity rates of 85–92% at two-year follow-up. Hybrid reconstructive constructs provided the most favourable overall outcomes, with pooled closure integrity reaching 91.6%, suggesting a synergistic advantage when combining biologic and synthetic components. Furthermore, the adjunctive use of combined microscopic–endoscopic surgical techniques was associated with a significant reduction in residual cholesteatoma rates (OR 0.56, 95% CI 0.38–0.82), supporting the growing role of endoscopic assistance in middle ear and mastoid surgery. When biologic closure strategies were appropriately selected according to defect characteristics and contamination status, functional preservation rates exceeded 90–95%, underscoring the importance of tailored reconstructive approaches. Conclusions: The durability of long-term outcomes is most strongly influenced by complete pathological clearance and by the strategic alignment of biomaterial properties with defect dimensions, contamination status, and surrounding anatomical structures. In response to these findings, an evidence-based algorithmic framework is proposed to facilitate rational intraoperative material selection. Full article

(This article belongs to the Special Issue Advances in Minimally Invasive Otolaryngology: Precision Techniques and Functional Outcomes)

15 pages, 1524 KB

Open AccessArticle

Developing Talent with Artificial Intelligence: Human–AI Symbiotic Theory (HAIST) as a Framework for AI-Mediated Learning and Talent Development

by John C. Chick and Laura Thomsen Morello

J. Intell. 2026, 14(5), 86; https://doi.org/10.3390/jintelligence14050086 (registering DOI) - 19 May 2026

Abstract

Traditional talent development models were designed before the AI revolution and do not consider artificial agents as possible sources of development. artificial intelligence is quickly infiltrating education spaces—but our thinking about learning has not caught up with how we can productively pair learners [...] Read more.

Traditional talent development models were designed before the AI revolution and do not consider artificial agents as possible sources of development. artificial intelligence is quickly infiltrating education spaces—but our thinking about learning has not caught up with how we can productively pair learners with both human and artificial intelligence. Addressing this gap, we introduce Human–AI Symbiotic Theory (HAIST), a novel theoretical framework designed for AI-facilitated environments, which posits how learners can productively leverage both humans and AI as “development partners” across the entire talent development process. We begin with a comprehensive integration of ideas and theory from the literature on talent development, AI for learning, and human–AI collaboration and use these insights to build HAIST for the specific context of talent development. HAIST comprises three mechanisms—Complementary Intelligence Activation (CIA), Dynamic Adaptive Co-Regulation (DACR), and Agency-Preserving Scaffolding (APS)—that are grounded in prior theory and research on topics like sociocultural theory, self-regulated learning, and distributed cognition. We then demonstrate how HAIST can be applied throughout all phases of talent development while highlighting implications for traditionally underserved learners like adult learners, student veterans, multilingual learners, and first-generation learners. We provide an applied example of how the three mechanisms work in tandem to support talent development and discuss points of tension that must be navigated when applying HAIST (e.g., between adaptation and optimization vs. agency). Lastly, we highlight how considerations of ethics and learner rights (algorithmic bias, learner voice, etc.) should be considered when operationalizing HAIST. Overall, HAIST can serve as a foundational theory to not only understand how talent development should occur between learners and both humans and AI, but also to consider the process of instruction design in AI-mediated learning environments. Full article

(This article belongs to the Special Issue Advances of AI in Talent Development: Synergies Between Creativity, Cognitive Intelligence, and Socio-Emotional Growth)

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31 pages, 8576 KB

Open AccessReview

Recent Advances in Searching for DNMT Inhibitors and Their Potential Application in Treating Human Diseases

by Anatoliy A. Bulygin, Anastasiia T. Davletgildeeva and Nikita A. Kuznetsov

Int. J. Mol. Sci. 2026, 27(10), 4560; https://doi.org/10.3390/ijms27104560 (registering DOI) - 19 May 2026

Abstract

DNA methylation is one of the most important epigenetic mechanisms regulating gene expression. DNA methyltransferases (DNMTs) are key players in these processes, regulating dynamic DNA methylation patterns in embryonic and adult cells. Therefore, dysfunction of DNMTs can lead to serious diseases and cancer [...] Read more.

DNA methylation is one of the most important epigenetic mechanisms regulating gene expression. DNA methyltransferases (DNMTs) are key players in these processes, regulating dynamic DNA methylation patterns in embryonic and adult cells. Therefore, dysfunction of DNMTs can lead to serious diseases and cancer due to distortions in gene methylation, including that of tumor suppressor genes. Due to the reversibility of DNA methylation, DNMTs are considered an important epigenetic target for drug development. This narrative review summarizes knowledge about DNMTs, including structural features and biological functions, and describes the development of DNMT inhibitors as therapeutics, from the earliest developments to the most modern and promising ones. Full article

(This article belongs to the Special Issue DNA Methylation Dynamics Due to Environmental Factors and in Human Diseases)

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18 pages, 781 KB

Open AccessArticle

Identifying Chronic Stressors in Residential Care for People with Intellectual Disabilities: A Concept Mapping Study

by Matthijs A. Heijstek, Vanessa C. Olivier-Pijpers, Eline E. Roelofsen, Lex Wijnroks and Marian J. Jongmans

Disabilities 2026, 6(3), 48; https://doi.org/10.3390/disabilities6030048 (registering DOI) - 19 May 2026

Abstract

Stress is increasingly recognised as a key factor underlying health and behavioural problems in people with intellectual disabilities. However, little is known about chronic stressors embedded in residential care environments. This study aimed to identify chronic stressors in residential care for people with [...] Read more.

Stress is increasingly recognised as a key factor underlying health and behavioural problems in people with intellectual disabilities. However, little is known about chronic stressors embedded in residential care environments. This study aimed to identify chronic stressors in residential care for people with intellectual disabilities from the perspective of stakeholders. A group concept mapping design was used, combining qualitative data generation with quantitative clustering analyses. Direct support workers, family members, and experts by experience generated statements describing situations perceived as stressful in residential care settings. After data cleaning, 125 unique statements were retained. Participants subsequently clustered and rated these statements on frequency, impact, and controllability. Thirty-eight statements were identified as daily stressors with high frequency and impact. Ward’s hierarchical cluster analysis grouped the statements into eight clusters representing broader conditions within residential care environments. Several clusters contained multiple high-frequency, high-impact stressors and were therefore interpreted as potential chronic stressors. These clusters reflected structural characteristics of residential care, including dependence on support staff, limited autonomy, and shared living environments. Identifying chronic stressors provides a framework for studying chronic stress in people with intellectual disabilities and may inform organisational and environmental interventions aimed at reducing exposure to such stressors. Full article

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18 pages, 1186 KB

Open AccessArticle

Autonomous Reinforcement Learning-Based Intrusion Detection for IoT Cyber Defense

by Ammar Odeh

Digital 2026, 6(2), 41; https://doi.org/10.3390/digital6020041 (registering DOI) - 19 May 2026

Abstract

The rapid proliferation of Internet of Things (IoT) devices has dramatically expanded the attack surface for cyber threats, exposing critical infrastructure to sophisticated intrusion attempts that traditional static intrusion detection systems (IDS) fail to counter effectively. This paper proposes an autonomous reinforcement learning [...] Read more.

The rapid proliferation of Internet of Things (IoT) devices has dramatically expanded the attack surface for cyber threats, exposing critical infrastructure to sophisticated intrusion attempts that traditional static intrusion detection systems (IDS) fail to counter effectively. This paper proposes an autonomous reinforcement learning (RL)-based IDS framework for dynamic IoT networks, capable of adaptive, real-time threat detection without human intervention. The proposed system integrates a Deep Q-Network (DQN) agent with a hybrid convolutional neural network–long short-term memory (CNN-LSTM) feature extractor to identify and classify malicious network traffic across 33 attack categories. We evaluate the framework on two recent, publicly available benchmark datasets: CICIoT2023, comprising 8.94 GB of traffic from 105 real IoT devices, and CIC IoT-DIAD 2024, a flow-based dataset with diverse attack and benign scenarios. Experimental results demonstrate superior detection performance compared to baseline classifiers, including SVM, Random Forest, and standalone deep learning models, with improved F1-score, reduced false alarm rate (FAR), and lower detection latency. The reward-shaping strategy explicitly penalizes false positives, addressing a key limitation of prior RL-based IDS approaches. This work contributes a scalable, dataset-agnostic autonomous defense architecture suitable for real-world IoT deployment. Full article

(This article belongs to the Special Issue Intelligent and Autonomous Cyber Defense Systems)

28 pages, 996 KB

Open AccessArticle

Improving Heart-Failure Predictive Tasks with Patient Health Knowledge Graphs and Sequential Graph Neural Networks

by Shervin Mehryar and Michel Dumontier

Electronics 2026, 15(10), 2189; https://doi.org/10.3390/electronics15102189 (registering DOI) - 19 May 2026

Abstract

Patient health knowledge graphs provide a means for high-quality and interoperable clinical data representation, while graph neural networks are a key enabler in order to learn their underlying relationships for downstream prediction tasks. In this work, we propose a sequential graph neural network [...] Read more.

Patient health knowledge graphs provide a means for high-quality and interoperable clinical data representation, while graph neural networks are a key enabler in order to learn their underlying relationships for downstream prediction tasks. In this work, we propose a sequential graph neural network (SeqGNN) framework that models patient visit trajectories for multiple binary clinical tasks, namely diagnosis, readmission, and mortality prediction. The proposed architecture integrates temporal dynamics with graph-based representations that enhances patient-level embeddings. Focusing on patients at the risk of Heart Failure (HF), our methodology achieves comparatively high accuracy and precision-versus-recall tradeoffs on highly heterogeneous graphs and imbalanced labeled data. We additionally quantify the uncertainty concerning each clinical decision making task and, compared with the state-of-the-art, show that AUROC and AUPRC scores reliably improve for onset diagnosis in particular, as high as 93.1 and 79.1 respectively. Our experiments conducted on real-world data from an intensive care unit demonstrate the potential for sequential representation learning over patient health knowledge graphs that can be provided for high-precision decision-making in clinical settings. Full article

(This article belongs to the Special Issue Knowledge Representation and Reasoning in Artificial Intelligence)

15 pages, 1308 KB

Open AccessArticle

Accuracy of Intraoral Scanners for Simulated Tooth Wear Using RMS Surface Deviation Analysis

by Maria Tsiafitsa, Petros Mourouzis, Dimitrios Dionysopoulos, Pantelis Kouros and Kosmas Tolidis

Prosthesis 2026, 8(5), 49; https://doi.org/10.3390/prosthesis8050049 (registering DOI) - 19 May 2026

Abstract

Objectives. This study evaluated the performance of three intraoral scanners with different acquisition technologies in detecting early signs of tooth wear, using micro-computed tomography (micro-CT) as the reference standard. Methods and Materials. Three IOS were examined, including an active triangulation scanner, a [...] Read more.

Objectives. This study evaluated the performance of three intraoral scanners with different acquisition technologies in detecting early signs of tooth wear, using micro-computed tomography (micro-CT) as the reference standard. Methods and Materials. Three IOS were examined, including an active triangulation scanner, a structured-light triangulation scanner, and a parallel confocal technology scanner. Ten extracted unrestored and caries-free premolars were placed in the maxillary left second premolar position of a dental mannequin and scanned at baseline, generating quadrant digital models. Micro-CT scans were also obtained at baseline. Wear was simulated by immersion in a 1% citric acid solution followed by brushing of the buccal surfaces. All specimens were rescanned with IOS and micro-CT. Micro-CT datasets were reconstructed into stereolithography models and compared with IOS models using mesh analysis software. Statistical analysis was performed in R using linear mixed-effects models to account for repeated measurements across teeth. RMS values and absolute errors relative to the micro-CT reference were analysed with device as a fixed effect and tooth as a random effect, with Tukey-adjusted pairwise comparisons. Repeatability was additionally assessed from the repeated scans using within-tooth variability. Results. Significant differences were observed among the evaluated systems in the detection of changes related to tooth wear (p < 0.001). The micro-CT reference showed the lowest RMS value, followed by Trios 3, Primescan, and Omnicam. Model-based analyses confirmed significant differences among the evaluated systems, while the magnitude and statistical support of pairwise contrasts depended on the specific outcome considered. Repeatability analysis showed that Trios 3 had the lowest within-tooth standard deviation and repeatability coefficient (0.0215 mm and 0.0595 mm, respectively), followed by Primescan (0.0290 mm and 0.0802 mm), whereas Omnicam showed the highest within-tooth variability and repeatability coefficient (0.0624 mm and 0.173 mm). Conclusions. The parallel confocal and structured-light triangulation intraoral scanners produced RMS values numerically closer to the micro-CT reference than the active triangulation scanner. However, none of the evaluated intraoral scanners demonstrated quantitative agreement sufficient to be considered interchangeable with the reference standard. Full article

(This article belongs to the Special Issue Advances in Digital Prosthodontics: Innovations in CAD-CAM Technology and Material Science)

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23 pages, 5746 KB

Open AccessArticle

Cementitious Composites with Hybrid UHMWPE and CF/PP Fiber: A Study on Compressive, Tensile, Flexural and Impact Performance

by Lihui Yang, Zhen Yang and Xiong Xing

Materials 2026, 19(10), 2131; https://doi.org/10.3390/ma19102131 (registering DOI) - 19 May 2026

Abstract

Ultra-high molecular weight polyethylene (UHMWPE) fibers have recently emerged as a promising reinforcement material in fiber-reinforced concrete (FRC). To investigate the synergistic effects and reinforcing mechanisms of fibers with different elastic moduli within the concrete matrix, a series of hybrid fiber-reinforced concrete (HFRC) [...] Read more.

Ultra-high molecular weight polyethylene (UHMWPE) fibers have recently emerged as a promising reinforcement material in fiber-reinforced concrete (FRC). To investigate the synergistic effects and reinforcing mechanisms of fibers with different elastic moduli within the concrete matrix, a series of hybrid fiber-reinforced concrete (HFRC) specimens were prepared by incorporating 0.25 vol%, 0.5 vol%, and 0.75 vol% carbon fibers (CFs) or polypropylene (PP) fibers into concrete containing 1 vol% UHMWPE fibers. The mechanical performance of the prepared composites was systematically evaluated through compressive, splitting tensile, flexural, and drop-weight impact tests. The experimental results indicate that concrete reinforced solely with UHMWPE fibers exhibits higher compressive strength but lower tensile strength, flexural strength, ductility, and impact toughness than the hybrid fiber systems. For both UHMWPE-CF and UHMWPE-PP hybrid concretes, the initial cracking impact resistance and failure impact resistance increased progressively with increasing CF or PP content. At equivalent fiber volume fractions, UHMWPE-PP hybrid concrete demonstrated superior resistance to initial cracking, whereas UHMWPE-CF hybrid concrete exhibited better post-failure impact resistance. Furthermore, fractal theory was employed to quantitatively characterize the impact damage behavior of HFRC specimens. The impact damage evolution equation is established by using the two-parameter Weibull distribution model. The findings provide theoretical and experimental support for the design and optimization of hybrid fiber-reinforced concrete subjected to impact loading. Full article

(This article belongs to the Section Construction and Building Materials)

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26 pages, 5074 KB

Open AccessArticle

Wavelet-Enhanced CNN for Breast Ultrasound Classification Under Speckle Noise

by Ratapong Onjun, Tanakorn Sritarapipat and Sayan Kaennakham

Biomedicines 2026, 14(5), 1151; https://doi.org/10.3390/biomedicines14051151 (registering DOI) - 19 May 2026

Abstract

Background/Objectives: Ultrasound is widely used for breast cancer screening and diagnosis, particularly in low- and middle-income settings, but its diagnostic reliability is often compromised by speckle noise that degrades lesion margins and tissue texture. This study proposes a compact convolutional neural network architecture [...] Read more.

Background/Objectives: Ultrasound is widely used for breast cancer screening and diagnosis, particularly in low- and middle-income settings, but its diagnostic reliability is often compromised by speckle noise that degrades lesion margins and tissue texture. This study proposes a compact convolutional neural network architecture that replaces standard max or average pooling layers with wavelet-based pooling using Symlet families, and optionally includes wavelet-domain preprocessing to suppress input noise. Methods: We conducted 108 experiments across six pooling configurations (avg, max, Sym2 ± preprocessing, Sym4 + preprocessing, Sym6 + preprocessing), two network depths, three batch sizes, and three simulated speckle levels (0%, 10%, 20%). Results: The proposed wavelet-based pooling framework showed consistently stronger in-domain performance than conventional pooling strategies across clean and speckle-corrupted settings, with the Sym2 + preprocessing configuration giving the best overall results. The model achieved 93.90% accuracy and 98.89% ROC AUC under clean internal test conditions and maintained stable performance under increased simulated noise levels. However, external validation on the independent BrEaST-Lesions-USG dataset revealed substantial performance degradation, with accuracy decreasing to 53.97% and ROC AUC to 0.4713, indicating limited cross-dataset generalization. Conclusions: These findings suggest that wavelet pooling is an effective architectural modification for improving in-domain robustness under controlled perturbation, although additional strategies are still required before reliable real-world deployment can be claimed. Full article

(This article belongs to the Special Issue AI/Machine Learning-Driven Multi-Omics Research in Oncology)

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22 pages, 401 KB

Open AccessReview

Evidence-Based Strategies for the Prevention of Cardiac Implantable Electronic Device Infections: An Up-to-Date Narrative Review

by Mantė Agnė Rimkienė, Diana Sudavičienė, Gediminas Račkauskas, Paulius Jurkuvėnas, Veronika Gorevska, Julius Stukas and Germanas Marinskis

Medicina 2026, 62(5), 991; https://doi.org/10.3390/medicina62050991 (registering DOI) - 19 May 2026

Abstract

Background and Objectives: Cardiac implantable electronic device (CIED) infections remain among the most serious complications of pacemaker, implantable cardioverter-defibrillator, and cardiac resynchronization therapy procedures. They are associated with substantial morbidity, mortality, prolonged hospitalization, system extraction, long-term antimicrobial therapy, and increased healthcare costs. [...] Read more.

Background and Objectives: Cardiac implantable electronic device (CIED) infections remain among the most serious complications of pacemaker, implantable cardioverter-defibrillator, and cardiac resynchronization therapy procedures. They are associated with substantial morbidity, mortality, prolonged hospitalization, system extraction, long-term antimicrobial therapy, and increased healthcare costs. As most infections arise from perioperative contamination or procedure-related complications, prevention has become a major priority in contemporary electrophysiology practice. This review aimed to summarize current evidence on the prevention of CIED infections, with particular emphasis on modifiable risk factors and perioperative preventive measures. Materials and Methods: A focused narrative review was undertaken using targeted searches of PubMed/MEDLINE and Scopus, supplemented by major international guideline and consensus documents, with priority given to contemporary guidelines, randomised trials, meta-analyses, and major observational studies relevant to CIED infection prevention. Results: Prevention of CIED infection requires a structured, multifactorial approach spanning the entire procedural pathway. Key preventive strategies include careful reassessment of device indication, individualized device selection, correction of modifiable risk factors, postponement of elective implantation in the presence of active infection, appropriate perioperative antibiotic prophylaxis, and optimized management of anticoagulant and antiplatelet therapy to minimize pocket hematoma. Additional relevant measures include meticulous skin antisepsis, limitation of temporary invasive devices and unnecessary hardware, appropriate venous access selection, careful generator pocket creation and wound closure, and avoidance of early reintervention whenever feasible. Antibacterial envelopes may reduce major CIED infections in selected high-risk patients, whereas routine escalation of preventive measures without proven benefit is not supported. Conclusions: CIED infection prevention is inherently multifactorial and depends on the consistent application of evidence-based measures before, during, and after device implantation. Rigorous control of modifiable risk factors, prevention of pocket hematoma, appropriate antimicrobial prophylaxis, and meticulous procedural technique remain the cornerstones of effective infection prevention in patients undergoing CIED procedures. Full article

(This article belongs to the Section Cardiology)

80 pages, 3509 KB

Open AccessSystematic Review

The Genus Alchornea (Euphorbiaceae): A Comprehensive Review of Its Taxonomy, Traditional Uses, Phytochemistry, Pharmacological Potential, and Toxicology

by Muhammad Aamer, Feibing Huang, Yi Long, Xudong Zhou, Yuqing Jian, Muhammad Iqbal Choudhary, Bin Li and Wei Wang

Molecules 2026, 31(10), 1726; https://doi.org/10.3390/molecules31101726 (registering DOI) - 19 May 2026

Abstract

The genus Alchornea Sw. belongs to the Euphorbiaceae family. Alchornea species are commonly used in traditional medicine to treat inflammation; infectious, gastrointestinal, respiratory, musculoskeletal, and dermatological disorders; as well as other diseases. This comprehensive review provides an overview of recent scientific findings on [...] Read more.

The genus Alchornea Sw. belongs to the Euphorbiaceae family. Alchornea species are commonly used in traditional medicine to treat inflammation; infectious, gastrointestinal, respiratory, musculoskeletal, and dermatological disorders; as well as other diseases. This comprehensive review provides an overview of recent scientific findings on the taxonomy, ethnomedicinal uses, phytochemistry, pharmacological potential, and toxicology of the Alchornea species. The literature was searched using SciFinderⁿ, Google Scholar, and PubMed. The taxonomy of all reported plants was authenticated using “Plants of the World Online”. Studies were examined and categorized according to the genus’s taxonomic classification, traditional uses, phytochemistry, pharmacological potential, and toxicity. Phytochemical studies have identified 396 bioactive compounds, primarily triterpenoids, alkaloids, flavonoids, and phenolics. Pharmacological studies have reported significant antimicrobial, anti-inflammatory, antioxidant, anti-plasmodial, and cytotoxic effects. Nevertheless, toxicological statistics are limited and vary among species and extracts. The genus Alchornea exhibits significant pharmacological potential, as evidenced by its traditional uses. In comparison, the genus remains underexplored in terms of detailed mechanistic pharmacological evaluation. Studies of chemical constituents and biological activities have been conducted for only approximately 17 species. To translate the pharmacological potential of the genus Alchornea into clinical practice, a strategic focus on modern plant valorization is required. Future research should focus on the valorization of Alchornea species by developing standardized oral formulations and topical preparations that harness their validated anti-inflammatory and antimicrobial effects beyond traditional uses. However, these findings suggest that further research is needed to assess the efficacy and safety of the largely unexplored genus Alchornea. Full article

(This article belongs to the Section Natural Products Chemistry)

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28 pages, 6208 KB

Open AccessReview

Effect of Diets Containing Phytoestrogen on Livestock Production: Nutrient Utilization, Carcass Traits, Lactational Performance, and Reproductive Function—A Review

by Sina Salimolnafs, Maghsoud Besharati, Deniz Azhir, Lucrezia Forte, Pasquale De Palo, Eric N. Ponnampalam, Abdelfattah Z. M. Salem and Aristide Maggiolino

Molecules 2026, 31(10), 1724; https://doi.org/10.3390/molecules31101724 (registering DOI) - 19 May 2026

Abstract

Phytoestrogens are plant-derived phenolic compounds that structurally resemble endogenous estrogens and can exert both estrogenic and anti-estrogenic effects in animals. In ruminant nutrition, the main classes of phytoestrogens (isoflavones, lignans, stilbenes, coumestans and selected flavonoids) are supplied predominantly by legume forages and soybean-based [...] Read more.

Phytoestrogens are plant-derived phenolic compounds that structurally resemble endogenous estrogens and can exert both estrogenic and anti-estrogenic effects in animals. In ruminant nutrition, the main classes of phytoestrogens (isoflavones, lignans, stilbenes, coumestans and selected flavonoids) are supplied predominantly by legume forages and soybean-based feeds, in which concentrations can reach several mg/g of dry matter. After ingestion, these compounds are extensively metabolized by the rumen microbiota to derivatives with altered biological potency, such as equol and p-ethyl-phenol, which influence endocrine, immune and metabolic pathways. Experimental and field studies in cattle, sheep and goats indicate that dietary phytoestrogens may improve nitrogen utilization, immune competence, growth performance, antioxidant status and milk yield. However, they can also impair fertility, modify hormone profiles and compromise embryo survival in a compound-, dose-, and species-dependent manner. In this review, we summarize current knowledge on the botanical and nutritional sources, ruminal metabolism and transfer of phytoestrogens in ruminants, and critically examine their effects on blood metabolites, immune responses, growth and carcass traits and lactational performance and reproductive function. A structured literature search based on PRISMA principles was used to identify and appraise experimental and observational studies in both grazing and intensive production systems up to 2025. Remaining knowledge gaps and practical implications for the safe use of phytoestrogen-rich feeds in livestock production are highlighted. Full article

(This article belongs to the Special Issue Natural Bioactives for Health: Therapeutic Promise and Safety Considerations)

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