MDPI - Publisher of Open Access Journals

15 pages, 1096 KB

Open AccessArticle

Surveillance of West Nile Virus in Tunisia: Evidence from Human and Entomological Investigation

by Walid Barhoumi, Marwa Khedhiri, Youmna M’Ghirbi, Souha Bougatef, Henda Touzi, Adel Rhim, Hela Karray, Abdelhalim Trabelsi, Maha Mastouri, Naila Hannachi, Ali Bouattour, Henda Triki, Nissaf Bouafif Ben Alaya and Wasfi Fares

Viruses 2025, 17(12), 1562; https://doi.org/10.3390/v17121562 (registering DOI) - 29 Nov 2025

Abstract

West Nile virus (WNV) is a mosquito-borne pathogen of the Flaviviridae family that poses recurring public health threats in Tunisia, where Culex pipiens is recognized as the primary vector. Identification of circulating strains in different mosquito species is essential for targeted prevention and [...] Read more.

West Nile virus (WNV) is a mosquito-borne pathogen of the Flaviviridae family that poses recurring public health threats in Tunisia, where Culex pipiens is recognized as the primary vector. Identification of circulating strains in different mosquito species is essential for targeted prevention and control. Between November 2021 and October 2022, mosquitoes were collected at four high-risk sites, and human samples were obtained through the national meningitis surveillance program. Human serum, cerebrospinal fluid (CSF), and urine samples were tested for WNV-specific IgM and IgG antibodies using ELISA, and molecular diagnosis was performed using Real-time RT-PCR (RRT-PCR). Positive samples underwent sequencing for phylogenetic characterization. Serological investigation on human serum revealed the presence of IgM and/or IgG antibodies reactive to WNV antigens, which may indicate exposure to WNV or related flaviviruses. RNA of WNV was detected in 21 mosquito pools (10.19%) belonging to Culex pipiens, Cx. perexiguus, Aedes caspius, and Ae. detritus, as well as in three human cases. Phylogenetic analysis of positive human and mosquito samples showed that all detected WNV strains belonged to sublineage 1a. The concurrent detection of WNV in vectors and humans confirms active circulation in Tunisia and underscores the role of Culex spp. Mosquitoes in transmission. Sustained multidisciplinary surveillance integrating entomological and clinical data is critical for early detection, guiding control measures, and preventing future outbreaks in humans and animals. Full article

(This article belongs to the Special Issue Current Trends in Arbovirus Outbreaks and Research)

► Show Figures

Figure 1

44 pages, 1709 KB

Open AccessReview

Epigenetic and Transcriptional Reprogramming in 3D Culture Models in Breast Cancer

by Laura Cecilia Flores-García, Karla Rubio, Eloisa Ibarra-Sierra, Macrina B. Silva-Cázares, Carlos Palma-Flores and César López-Camarillo

Cancers 2025, 17(23), 3830; https://doi.org/10.3390/cancers17233830 (registering DOI) - 29 Nov 2025

Abstract

Breast cancer remains the leading cause of cancer-related death in women worldwide. This disease is characterized by its molecular and phenotypic heterogeneity, which hinders the development of effective therapies. While two-dimensional (2D) monolayer cell cultures are widely used, they are insufficient to reproduce [...] Read more.

Breast cancer remains the leading cause of cancer-related death in women worldwide. This disease is characterized by its molecular and phenotypic heterogeneity, which hinders the development of effective therapies. While two-dimensional (2D) monolayer cell cultures are widely used, they are insufficient to reproduce the characteristics of the tumor microenvironment, thus limiting our understanding of cancer biology. In this context, three-dimensional (3D) models have emerged as representative tools that more accurately reproduce tissue architecture, cell signaling, and nutrients and oxygen gradients. These cellular models offer greater similarity to primary tissues, improving the study of relevant biological processes. Although 3D cultures provide numerous advantages in cancer research, there is no unified model that standardizes the matrix type and parameters such as gelation time or porosity, hindering the reproducibility and interpretability of the data. This review integrates evidence from various studies to evaluate the effect of epigenetic variations generated by 3D culture methods, which are regulated by mechanotransduction and, consequently, by signaling pathways such as integrin/FAK-ILK/Rho-YAP derived from interactions of cells with extracellular matrix-enriched scaffolds. This affects processes such as DNA methylation, histone coding, and the regulation of non-coding RNAs such as microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs) in different molecular subtypes of breast cancer. Overall, the evidence highlights that 3D culture methods are not equivalent but rather generate distinct epigenetic signatures at the non-coding RNA level that influence the proliferation, differentiation, therapeutic resistance, and metastatic potential of tumor cells. Furthermore, the evidence suggests that histone coding patterns, primarily through the reduction of acetylation marks, are conserved regardless of the type of 3D culture. In summary, the study highlights that the microarchitectural and compositional characteristics of 3D scaffolds are key determinants of epigenetic plasticity. Full article

(This article belongs to the Special Issue 3D Cultures and Organoids in Cancer Research)

24 pages, 26898 KB

Open AccessArticle

Developmental Toxicity of Ibrutinib: Insights from Stem Cell Dynamics and Neural Regeneration in Planarians

by Weiyun Guo, Baijie Jin, Nannan Li, Dandan Sun, Dezeng Liu, Zimei Dong and Guangwen Chen

Biomolecules 2025, 15(12), 1665; https://doi.org/10.3390/biom15121665 (registering DOI) - 29 Nov 2025

Abstract

Ibrutinib (IB), a Bruton’s tyrosine kinase (BTK) inhibitor, is widely used against B-cell malignancies. However, its adverse effects on stem cell-dependent processes and tissue homeostasis remain incompletely understood. Freshwater planarians possess pluripotent stem cells (neoblasts), which enable remarkable regeneration of various tissues, including [...] Read more.

Ibrutinib (IB), a Bruton’s tyrosine kinase (BTK) inhibitor, is widely used against B-cell malignancies. However, its adverse effects on stem cell-dependent processes and tissue homeostasis remain incompletely understood. Freshwater planarians possess pluripotent stem cells (neoblasts), which enable remarkable regeneration of various tissues, including the central nervous system. This makes them ideal in vivo models for studying chemical toxicity within a whole-organism context. Here, we utilized planarian Dugesia constrictiva to assess IB toxicity and elucidate its mechanisms, focusing on its impact on stem cell dynamics and regeneration. Our results demonstrated that exposure to IB at concentrations as low as 0.9 mg/L, far below clinical plasma levels, led to severe morphological and regenerative impairments, including disrupted neural regeneration. Mechanistically, IB disrupted stem cell dynamics by suppressing proliferation and differentiation and by inducing oxidative stress via ROS overproduction. Notably, IB exposure significantly downregulated BTK expression. Crucially, BTK RNAi caused the key toxic effects of IB exposure, including morphological and regenerative defects, suppression of stem cell proliferation and differentiation, and increased apoptosis. Therefore, we conclude that IB may exert its toxicity in planarians primarily through BTK inhibition. This finding provides direct functional evidence linking BTK inhibition to stem cell dysfunction and regenerative defects in a novel in vivo context, offering critical insights for refining the clinical safety profile of IB. Full article

(This article belongs to the Section Molecular Medicine)

► Show Figures

Graphical abstract

6 pages, 183 KB

Open AccessEditorial

Special Issue “Molecular Insights into the Developmental Origins of Health and Disease”

by Paramjit S. Tappia and Bram Ramjiawan

Int. J. Mol. Sci. 2025, 26(23), 11579; https://doi.org/10.3390/ijms262311579 (registering DOI) - 29 Nov 2025

Abstract

There is now a wealth of epidemiological, clinical, and experimental evidence that have concluded that the risk of developing chronic, noncommunicable diseases in adulthood may be influenced by molecular and genetic aspects [...] Full article

(This article belongs to the Special Issue Molecular Insights into the Developmental Origins of Health and Disease)

21 pages, 3716 KB

Open AccessArticle

Clothing-Agnostic Pre-Inpainting Virtual Try-On

by Sehyun Kim, Hye Jun Lee, Jiwoo Lee and Taemin Lee

Electronics 2025, 14(23), 4710; https://doi.org/10.3390/electronics14234710 (registering DOI) - 29 Nov 2025

Abstract

With the development of deep learning technology, virtual try-on technology has developed important application value in the fields of e-commerce, fashion, and entertainment. The recently proposed Leffa technology has addressed the texture distortion problem of diffusion-based models, but there are limitations in that [...] Read more.

With the development of deep learning technology, virtual try-on technology has developed important application value in the fields of e-commerce, fashion, and entertainment. The recently proposed Leffa technology has addressed the texture distortion problem of diffusion-based models, but there are limitations in that the bottom detection inaccuracy and the existing clothing silhouette persist in the synthesis results. To solve this problem, this study proposes CaP-VTON (Clothing-Agnostic Pre-Inpainting Virtual Try-On). CaP-VTON integrates DressCode-based multi-category masking and Stable Diffusion-based skin inflation preprocessing; in particular, a generated skin module was introduced to solve skin restoration problems that occur when long-sleeved images are converted to short-sleeved or sleeveless ones, introducing a preprocessing structure that improves the naturalness and consistency of full-body clothing synthesis and allowing the implementation of high-quality restoration considering human posture and color. As a result, CaP-VTON achieved 92.5%, which is 15.4% better than Leffa, in short-sleeved synthesis accuracy and consistently reproduced the style and shape of the reference clothing in visual evaluation. These structures maintain model-agnostic properties and are applicable to various diffusion-based virtual inspection systems; they can also contribute to applications that require high-precision virtual wearing, such as e-commerce, custom styling, and avatar creation. Full article

(This article belongs to the Special Issue Recent Advances in Applications of Machine Learning and Computer Vision)

► Show Figures

Figure 1

18 pages, 569 KB

Open AccessArticle

Sustainability of Microfinance Programmes: The Case of O. R Tambo Coastal District, Eastern Cape, South Africa

by Collins Akiy Wung and Lucius Botes

Sustainability 2025, 17(23), 10706; https://doi.org/10.3390/su172310706 (registering DOI) - 29 Nov 2025

Abstract

This paper explores the factors influencing the sustainability of microfinance programmes in the OR Tambo Coastal District (ORTCD) in the Eastern Cape, South Africa. The paper questions whether the services offered to microfinance clients can facilitate loan repayment and the sustainability of microfinance [...] Read more.

This paper explores the factors influencing the sustainability of microfinance programmes in the OR Tambo Coastal District (ORTCD) in the Eastern Cape, South Africa. The paper questions whether the services offered to microfinance clients can facilitate loan repayment and the sustainability of microfinance programmes. Precisely, the paper examines how the combination of financial and non-financial services facilitates loan repayment and the sustainability of these programmes. In the study, the recipients of microfinance loans in the OR Tambo Coastal District of the Eastern Cape were interviewed about the services offered by microfinance institutions. The study adopted a qualitative research approach and collected data through semi-structured interviews with recipients of microfinance loans in ORTCD. The collected data was analysed thematically following Braun and Clarke’s six-step approach, ensuring that codes and themes emerged inductively from participants’ narratives. The obtained results revealed that loan repayment and programme sustainability are shaped by the interdependent role of financial services (loan type and loan size) and non-financial services (technical assistance and client-institutional relationships). However, weak institutional ties and limited monitoring threaten long-term programme outcomes. The study’s findings suggest that combining financial and non-financial services improves repayment capacity, institutional confidence, and sustainability, particularly in underserved rural communities. Therefore, the study recommends strengthening training frequency, establishing continuous client evaluation mechanisms, and integrating institutional perspectives to improve the sustainability of microfinance interventions. Full article

► Show Figures

Figure 1

16 pages, 570 KB

Open AccessArticle

Prevalence and Diagnostic Determinants of Hepatitis B Infection Among Saudi Adults: Implications for Targeted Screening and Early Detection

by Mohammad A. Jareebi, Ali A. Awam, Dhiyaa A. H. Otayf, Saja A. Almraysi, Israa H. Alqamaryat, Amaal A. Alghamdi, Majed A. Ryani, Ahmed A. Bahri, Abdulwahab A. Aqeeli, Jamaludeen A. Othman, Adhari A. Alselmi, Farjah H. Algahtani, Hani A. Alghamdi, Ghazi I. Al Jowf and Aisha H. Majrashi

Diagnostics 2025, 15(23), 3050; https://doi.org/10.3390/diagnostics15233050 (registering DOI) - 29 Nov 2025

Abstract

Background/Objectives: Hepatitis B virus (HBV) remains a significant diagnostic and public health challenge worldwide. Despite widespread vaccination, underdiagnosis persists among adults in Saudi Arabia. This study estimated HBV prevalence and identified sociodemographic, clinical, and behavioral predictors relevant to improving targeted diagnostic screening. Methods [...] Read more.

Background/Objectives: Hepatitis B virus (HBV) remains a significant diagnostic and public health challenge worldwide. Despite widespread vaccination, underdiagnosis persists among adults in Saudi Arabia. This study estimated HBV prevalence and identified sociodemographic, clinical, and behavioral predictors relevant to improving targeted diagnostic screening. Methods: A cross-sectional study of 1196 Saudi adults aged ≥18 years was conducted between September 2024 and February 2025 using a structured questionnaire. Data on demographics, clinical history, and behavioral exposures were analyzed using chi-square tests and multivariate logistic regression to identify independent determinants of HBV infection. Results: The study included 1196 adults (60.0% female, mean age 31 ± 12 years). HBV prevalence was 2.0% (95% CI: 1.3–3.0%). Independent predictors included divorced/widowed marital status (OR = 3.99, p = 0.023), diabetes mellitus (OR = 3.59, p = 0.039), family history of HBV (OR = 2.55, p < 0.001), and massage exposure (OR = 3.99, p = 0.025). No significant associations were found with gender, education, or transfusion history. Conclusions: HBV infection persists among high-risk Saudi adults despite immunization success. Integrating HBV testing into diabetes care, premarital and household screening, and regulation of personal care services may enhance early diagnosis and advance national elimination goals. Full article

(This article belongs to the Special Issue Diagnosis and Management of Liver Diseases, Third Edition)

► Show Figures

Figure 1

20 pages, 832 KB

Open AccessReview

Redox-Immune Axis and Ozone Pollution: From Oxidative Stress to Thymic Involution and Neurodegeneration

by Marlen Valdés-Fuentes, Erika Rodríguez-Martínez and Selva Rivas-Arancibia

Med. Sci. 2025, 13(4), 293; https://doi.org/10.3390/medsci13040293 (registering DOI) - 29 Nov 2025

Abstract

Chronic exposure to low concentrations of ozone leads to oxidative stress, which disrupts immune regulation. The thymus gland plays a crucial role in the maturation and differentiation of T lymphocytes, cells essential for the body’s defense and immune tolerance. In the early years [...] Read more.

Chronic exposure to low concentrations of ozone leads to oxidative stress, which disrupts immune regulation. The thymus gland plays a crucial role in the maturation and differentiation of T lymphocytes, cells essential for the body’s defense and immune tolerance. In the early years of life, the thymus is highly active, but after adolescence, it undergoes a process known as thymic involution. This process involves a reduction in the size and functionality of the thymus, which is gradually replaced by adipose tissue. Ozone pollution exacerbates this involution and impairs the thymus’s proper function. Consequently, thymic cells may alter their function, leading to a decreased production and diversity of T lymphocytes. This decrease contributes to the establishment of chronic inflammatory states, autoimmunity, and a reduced capacity to respond to infections. Immune dysfunction and chronic inflammation can further result in the development and progression of neurodegenerative diseases. Moreover, thymic involution, exacerbated by environmental factors and oxidative stress, negatively impacts overall immunity and accelerates the progression of degenerative diseases over time. This review aims to explore the relationship between oxidative stress and its impact on the thymus gland. We hypothesize that understanding the relationship between ozone pollution and disruption of the redox–immune axis is crucial for understanding the role of the thymus in senescence and neurodegenerative diseases. To explore this topic, we conducted a review from 2006 to 2025, utilizing several databases, including PubMed, Scopus, Google Scholar, EBSCO, and Web of Science. Full article

(This article belongs to the Section Translational Medicine)

► Show Figures

Figure 1

47 pages, 3385 KB

Open AccessArticle

Blockchain-Native Asset Direction Prediction: A Confidence-Threshold Approach to Decentralized Financial Analytics Using Multi-Scale Feature Integration

by Oleksandr Kuznetsov, Dmytro Prokopovych-Tkachenko, Maksym Bilan, Borys Khruskov and Oleksandr Cherkaskyi

Algorithms 2025, 18(12), 758; https://doi.org/10.3390/a18120758 (registering DOI) - 29 Nov 2025

Abstract

Blockchain-based financial ecosystems generate unprecedented volumes of multi-temporal data streams requiring sophisticated analytical frameworks that leverage both on-chain transaction patterns and off-chain market microstructure dynamics. This study presents an empirical evaluation of a two-class confidence-threshold framework for cryptocurrency direction prediction, systematically integrating macro [...] Read more.

Blockchain-based financial ecosystems generate unprecedented volumes of multi-temporal data streams requiring sophisticated analytical frameworks that leverage both on-chain transaction patterns and off-chain market microstructure dynamics. This study presents an empirical evaluation of a two-class confidence-threshold framework for cryptocurrency direction prediction, systematically integrating macro momentum indicators with microstructure dynamics through unified feature engineering. Building on established selective classification principles, the framework separates directional prediction from execution decisions through confidence-based thresholds, enabling explicit optimization of precision–recall trade-offs for decentralized financial applications. Unlike traditional three-class approaches that simultaneously learn direction and execution timing, our framework uses post-hoc confidence thresholds to separate these decisions. This enables systematic optimization of the accuracy-coverage trade-off for blockchain-integrated trading systems. We conduct comprehensive experiments across 11 major cryptocurrency pairs representing diverse blockchain protocols, evaluating prediction horizons from 10 to 600 min, deadband thresholds from 2 to 20 basis points, and confidence levels of 0.6 and 0.8. The experimental design employs rigorous temporal validation with symbol-wise splitting to prevent data leakage while maintaining realistic conditions for blockchain-integrated trading systems. High confidence regimes achieve peak profits of 167.64 basis points per trade with directional accuracies of 82–95% on executed trades, suggesting potential applicability for automated decentralized finance (DeFi) protocols and smart contract-based trading strategies on similar liquid cryptocurrency pairs. The systematic parameter optimization reveals fundamental trade-offs between trading frequency and signal quality in blockchain financial ecosystems, with high confidence strategies reducing median coverage while substantially improving per-trade profitability suitable for gas-optimized on-chain execution. Full article

(This article belongs to the Special Issue Blockchain and Big Data Analytics: AI-Driven Data Science)

20 pages, 7350 KB

Open AccessArticle

Topology Optimization and Leakage Current Suppression of Photovoltaic Energy Storage Four-Leg Inverter Based on Independent Split Capacitor

by Jiang Liu, Jinyuan Wang, Dong Lin and Zicheng Li

Electronics 2025, 14(23), 4708; https://doi.org/10.3390/electronics14234708 (registering DOI) - 29 Nov 2025

Abstract

Leakage current is a prevalent issue in non-isolated photovoltaic (PV) energy storage inverter systems, which not only induces additional power losses but also poses potential safety hazards and degrades system operational efficiency. To address this critical problem, this paper proposes an improved three-phase [...] Read more.

Leakage current is a prevalent issue in non-isolated photovoltaic (PV) energy storage inverter systems, which not only induces additional power losses but also poses potential safety hazards and degrades system operational efficiency. To address this critical problem, this paper proposes an improved three-phase four-leg PV energy storage inverter topology integrated with independent split capacitors, based on the traditional three-level topology. First, an in-depth analysis of the leakage current generation mechanism is conducted, focusing on the impacts of common-mode voltage fluctuations and parasitic capacitance on leakage current paths. By establishing an equivalent mathematical model, a systematic comparative analysis is performed between the proposed topology and the traditional topology regarding key performance indicators, including leakage current suppression capability, DC-side neutral point potential stability, and power quality. Notably, the improved topology requires no additional control strategy design; under the same carrier modulation strategy and parameter configuration as the traditional topology, it can stably constrain the DC-side neutral point potential to fluctuate within an acceptable range. Experimental results demonstrate that the proposed topology reduces the peak leakage current to within 200 mA while maintaining the total harmonic distortion (THD) of the load-side current at a low level. These performance metrics comply with the relevant national and industry power quality standards for PV grid-connected systems, endowing the topology with high engineering practical value. Full article

► Show Figures

Figure 1

27 pages, 10258 KB

Open AccessArticle

Optimized Active Learning Method for High-Dimensional Industrial Regression Problems

by Clara Guilhaumon, Nicolas Hascoet, Francisco Chinesta and Marc Lavarde

Algorithms 2025, 18(12), 757; https://doi.org/10.3390/a18120757 (registering DOI) - 29 Nov 2025

Abstract

Machine learning approaches are commonly used to model physical phenomena due to their adaptability to complex systems. In general, a substantial number of samples must be collected to create a model with reliable results. However, collecting numerous data points is often costly. Moreover, [...] Read more.

Machine learning approaches are commonly used to model physical phenomena due to their adaptability to complex systems. In general, a substantial number of samples must be collected to create a model with reliable results. However, collecting numerous data points is often costly. Moreover, high-dimensional problems inherently require large amounts of data due to the curse of dimensionality. That is why new approaches based on smart sampling techniques are being investigated to optimize the acquisition of training samples, such as active learning methods. Initialization is a crucial step in active learning as it influences both performance and computational cost. Moreover, the scenarios used to select the next sample, such as classic pool-based sampling, can be highly resource- and time consuming. This study focuses on optimizing active learning methods through a comprehensive analysis of initialization strategies and scenario design, proposing and evaluating multiple approaches to determine the optimal configurations. The methods are applied to high-dimensional industrial problems with dimensions ranging from 5 to 15, where challenges associated with high dimensionality are already significant. To address this, the proposed study uses an active learning criterion that combines Sparse Proper Generalized Decomposition with Fisher information theory, specifically tailored to high-dimensional industrial settings. We illustrate the effectiveness of these techniques through examples on theoretical 5D and 15D functions, as well as a practical industrial crash simulation application. Full article

► Show Figures

Figure 1

37 pages, 969 KB

Open AccessArticle

Integrating Sustainability into Cosmetic Product Development: An ANP-QFD Framework for Balancing Technical Excellence and Environmental Performance

by Khaoula Razzouk, Fatine Elharouni and Ahmed Aamouche

Sustainability 2025, 17(23), 10705; https://doi.org/10.3390/su172310705 (registering DOI) - 29 Nov 2025

Abstract

The cosmetics industry faces mounting environmental pressure due to significant carbon emissions and pollution from daily product consumption, necessitating the systematic integration of sustainability into product development processes. This study develops an integrated decision-support framework combining Analytic Network Process (ANP) and Quality Function [...] Read more.

The cosmetics industry faces mounting environmental pressure due to significant carbon emissions and pollution from daily product consumption, necessitating the systematic integration of sustainability into product development processes. This study develops an integrated decision-support framework combining Analytic Network Process (ANP) and Quality Function Deployment (QFD) with sustainability dimensions to guide cosmetics companies toward environmentally responsible operations. Using facial moisturizer development as a case study, the methodology transforms customer ecological expectations and technical requirements into prioritized design requirements through interdependent matrices (W_C and W_A) and integrated weighting, incorporating both classical ANP priorities (α = 0.70) and sustainability E-Vector scores (β = 0.30). Statistical analysis confirms the independence of technical and sustainability dimensions (r = 0.127, p = 0.743), validating the additive integration approach. Results reveal that hybrid criteria combining regulatory compliance with environmental performance achieve top priority rankings, with the integrated model demonstrating 75–80% concordance with industry R&D priorities from leading cosmetic companies and parametric robustness across realistic weighting scenarios. The framework enables the systematic translation of consumer sustainability demands into operational strategies while preserving safety primacy. This ANP-QFD approach provides cosmetics managers with a quantitative tool for balancing environmental responsibility with market competitiveness, positioning sustainability as a strategic advantage in an evolving regulatory landscape. Full article

(This article belongs to the Special Issue A Multidisciplinary Approach to Sustainability Volume II)

► Show Figures

Figure 1

14 pages, 12425 KB

Open AccessArticle

Molecular Epidemiological Investigation and Viral Isolation of Porcine Rotavirus in Southwest China During 2024–2025

by Sirun He, Jiqiang Shi, Huanyuan Hu, Xiaozhen Zhang, Mao Ning, Wensi Wu, Yiping Wen, Yiping Wang, Rui Wu, Qin Zhao, Senyan Du, Sanjie Cao, Xiaobo Huang, Shan Zhao, Yifei Lang, Nanfang Zeng and Qigui Yan

Vet. Sci. 2025, 12(12), 1137; https://doi.org/10.3390/vetsci12121137 (registering DOI) - 29 Nov 2025

Abstract

In 2023, the detection rate of porcine rotavirus (PoRV) surpassed that of porcine epidemic diarrhea virus (PEDV) for the first time, establishing PoRV as the predominant pathogen responsible for viral diarrhea in pigs. To systematically investigate the epidemiology and molecular characteristics of PoRV [...] Read more.

In 2023, the detection rate of porcine rotavirus (PoRV) surpassed that of porcine epidemic diarrhea virus (PEDV) for the first time, establishing PoRV as the predominant pathogen responsible for viral diarrhea in pigs. To systematically investigate the epidemiology and molecular characteristics of PoRV in Southwest China, a total of 196 diarrheal clinical samples were collected from 29 large-scale pig farms across the region during 2024–2025. RT-qPCR results revealed a high PoRV positivity rate of 57.14% (112/196) with group A porcine rotavirus (PoRVA) being the most prevalent at 46.43%, representing the predominant group. Genotyping and phylogenetic analysis of the VP4 and VP7 genes indicated that the P genotype P[13] was most prevalent (77.78%, 21/27), while the major G genotypes were G4 (39.28%) and G9 (35.71%). The most common G/P combinations were G9P[13] and G4P[13]. Furthermore, a PoRV strain was successfully isolated and identified through whole-genome sequencing, indirect immunofluorescence assay (IFA), and transmission electron microscopy (TEM). The isolate was designated RVA/Pig-wt/SCLS-JW/2024/G1P[7], with a whole-genome constellation of G1-P[7]-I5-R1-C1-M1-A8-N1-T1-E1-H1. The structural proteins VP1-4 and VP6-7, along with nonstructural genes NSP1 and NSP5, shared high sequence identity with porcine strains, whereas the nonstructural genes NSP2–NSP4 clustered more closely with human rotaviruses. These findings indicate a higher prevalence of PoRV in southwestern China compared to other regions; the dominant circulating genotypes have shifted to G9 and G4; the isolated G1P[7] strain is relatively rare in China and might be a genetic recombinant of human and porcine rotaviruses. This study provides valuable data and theoretical support for understanding the current epidemiology of PoRV, and facilitates vaccine development and the formulation of prevention and control strategies. Full article

► Show Figures

Figure 1

11 pages, 2533 KB

Open AccessArticle

Dual Regulation of Corneodesmosome Formation by Shotokuseki Extract Enhances Skin Barrier Homeostasis

by Kei Tsukui, Masamitsu Suzuki, Miyu Amma, Shin-ichi Kawaguchi and Yoshihiro Tokudome

Molecules 2025, 30(23), 4592; https://doi.org/10.3390/molecules30234592 (registering DOI) - 29 Nov 2025

Abstract

Corneodesmosomes are specialized intercellular junctions that mediate adhesion between corneocytes in the stratum corneum (SC). The degradation of these structures is regulated by kallikrein-related peptidases (KLKs) and their inhibitors. This study aimed to elucidate the effects of Shotokuseki extract (SE), a substance rich [...] Read more.

Corneodesmosomes are specialized intercellular junctions that mediate adhesion between corneocytes in the stratum corneum (SC). The degradation of these structures is regulated by kallikrein-related peptidases (KLKs) and their inhibitors. This study aimed to elucidate the effects of Shotokuseki extract (SE), a substance rich in various trace elements, on molecules related to SC adhesion using a three-dimensional cultured human epidermis model. SE was applied to a three-dimensional epidermis model, and analyses were conducted on gene expression, protease activity, protein levels, and tissue structure. SE treatment significantly upregulated the mRNA expression of corneodesmosomal components (desmoglein1, desmocollin1, and corneodesmosin) and the major protease inhibitor serine peptidase inhibitor Kazal type 5. Concurrently, SE increased the mRNA expression of the trypsin-like protease KLK5,while significantly decreasing the mRNA expression and activity of the chymotrypsin-like protease KLK7. Although no significant changes were observed in the protein levels of corneodesmosomal components, histological analysis revealed that SE significantly increased the ratio of SC thickness to total epidermal thickness. These findings suggest that SE contributes to the homeostasis of the SC by simultaneously promoting the expression of genes encoding corneodesmosomal components, and regulating the balance of the protease/inhibitor system involved in their degradation. The selective suppression of KLK7 activity may appropriately regulate the final stage of desquamation, thereby stabilizing barrier function. Full article

► Show Figures

Graphical abstract

19 pages, 1657 KB

Open AccessReview

The Potential of Artificial Intelligence to Improve Selection Criteria for Liver Transplantation in HCC

by Jan-Paul Gundlach, Steffen M. Heckl, Patrick Langguth, Christian Oberkofler, Terbish Taivankhuu, Jan Henrik Beckmann, Thomas Becker, Felix Braun and Michael Linecker

Cancers 2025, 17(23), 3829; https://doi.org/10.3390/cancers17233829 (registering DOI) - 29 Nov 2025

Abstract

Despite improved therapeutic concepts, the survival of patients with hepatocellular carcinoma (HCC) is limited. Liver transplantation (LT) is the best possible treatment for suitable patients. This therapy is of particular importance, because it not only removes the cancer but also cures the underlying [...] Read more.

Despite improved therapeutic concepts, the survival of patients with hepatocellular carcinoma (HCC) is limited. Liver transplantation (LT) is the best possible treatment for suitable patients. This therapy is of particular importance, because it not only removes the cancer but also cures the underlying structural liver disease. Due to the persistent lack of donor organs, however, the oncological prognosis after LT is of particular importance for fair organ allocation. Bonus points on the organ waiting list are rewarded for tumors within a certain tumor extent. In general, macrovascular invasion and extrahepatic tumor manifestation are considered to be contraindications for LT, as survival in these patients is very low. In recent years, however, microvascular invasion and poorly differentiated tumors have also turned out to be unfavorable. Most selection criteria for LT in HCC are still based on very simple imaging criteria like size and number without utilizing additional imaging characteristics inherent to the tumor nodule, which could be processed in a “virtual biopsy”. Recently, diagnostic research has presented the clinical benefit of artificial intelligence (AI) in the use of deep-learning strategies for digital diagnosis of poorly differentiated or microvascular-infiltrated tumors. In addition, evaluation of TACE response is analyzed as a possibility to estimate LT survival. The aim of this review is to provide an overview of recent advances in HCC diagnosis and to classify the clinical relevance of these diagnostic and technical advances. Secondly, we discuss how these advances could affect the organ allocation process. Full article

(This article belongs to the Special Issue Advances and Future Developments in Liver Transplantation for Cancers: 2nd Edition)

► Show Figures

Figure 1

25 pages, 2858 KB

Open AccessArticle

Blockchain-Enabled Synchromodal Transport Network Optimization: Toward Enhanced Transparency

by Shuxia Li, Hui Jiang, Liping Liu, Yuanqing Liu and Mengling Wang

Mathematics 2025, 13(23), 3829; https://doi.org/10.3390/math13233829 (registering DOI) - 29 Nov 2025

Abstract

Blockchain technology, with its inherent decentralization and transparency, offers innovative solutions to current information-sharing challenges in synchromodal transport systems. This study first examines a synchromodal transport network under deterministic demand and investigates whether blockchain technology can enhance the connectivity among entities. An optimization [...] Read more.

Blockchain technology, with its inherent decentralization and transparency, offers innovative solutions to current information-sharing challenges in synchromodal transport systems. This study first examines a synchromodal transport network under deterministic demand and investigates whether blockchain technology can enhance the connectivity among entities. An optimization model is developed to balance transparency and cost efficiency. The analysis is then extended to scenarios with uncertain demand, modeled using triangular fuzzy numbers. Chance-constrained programming and fuzzy goal programming are employed to address demand uncertainty while balancing the model’s dual objectives. Using an Asia–Europe transportation dataset, the model is solved via the CPLEX solver. The results indicate that blockchain significantly improves transparency in synchromodal transport networks, albeit with a moderate increase in operational costs. Under uncertain demand conditions, blockchain is effective in mitigating the adverse effects of demand fluctuations. From a managerial perspective, the findings suggest that governments should promote blockchain adoption in transportation, while enterprises should carefully evaluate their operational needs before implementation. Full article

► Show Figures

Figure 1

19 pages, 2983 KB

Open AccessArticle

Structure and Functionality of Fermented Faba Bean: Influence of Particle Size and Rhizopus spp.

by Deepa Agarwal, Priyanka Kharangarh, Pengfei (Alfie) Hao, Mark I. Bradbury, Pankaj Maharjan, Yakindra P. Timilsena, Cassandra K. Walker, Monika S. Doblin and Roman Buckow

Foods 2025, 14(23), 4105; https://doi.org/10.3390/foods14234105 (registering DOI) - 29 Nov 2025

Abstract

This study investigated the influence of particle size and Rhizopus species on the fermentability, structure, and functionality of faba bean (Vicia faba L.) during controlled solid-state fermentation. Split seeds, coarse particles, and 1000–2000 µm fractions were fermented with either R. oryzae or [...] Read more.

This study investigated the influence of particle size and Rhizopus species on the fermentability, structure, and functionality of faba bean (Vicia faba L.) during controlled solid-state fermentation. Split seeds, coarse particles, and 1000–2000 µm fractions were fermented with either R. oryzae or R. oligosporus. Analyses included compositional profiling, SDS-PAGE, FTIR, DPPH antioxidant activity, phytic acid quantification, and rheological yield stress measurements. Particle size strongly affected mycelial growth and matrix structure: coarse particles supported more uniform mycelial networks, particularly with R. oryzae. After 48 h of fermentation, total protein and phytic acid contents remained largely unchanged; however, SDS-PAGE and FTIR results indicated proteolysis and alterations in secondary structure, accompanied by higher antioxidant activity. Rheological data showed significant species–particle size interactions influencing yield stress, with R. oligosporus-fermented samples exhibiting higher yield stress than those fermented with R. oryzae. Overall, these findings demonstrate that optimising particle size and fungal strain combinations can enhance the structural and functional characteristics of fermented faba bean. Full article

(This article belongs to the Special Issue Development of Plant-Based Fermented Food Products)

► Show Figures

Figure 1

23 pages, 2960 KB

Open AccessArticle

Analysis of Surface Code Algorithms on Quantum Hardware Using the Qrisp Framework

by Jan Krzyszkowski and Marcin Niemiec

Electronics 2025, 14(23), 4707; https://doi.org/10.3390/electronics14234707 (registering DOI) - 29 Nov 2025

Abstract

The pursuit of scalable quantum computing is intrinsically limited by qubit decoherence, making robust quantum error correction (QEC) techniques crucial. As a leading solution, the topological surface code offers inherent protection against local noise. This study presents the first comprehensive implementation and quantitative [...] Read more.

The pursuit of scalable quantum computing is intrinsically limited by qubit decoherence, making robust quantum error correction (QEC) techniques crucial. As a leading solution, the topological surface code offers inherent protection against local noise. This study presents the first comprehensive implementation and quantitative characterization of a full surface code pipeline, which includes encompassing lattice construction, multi-round syndrome extraction, and MWPM decoding, using the high-level Qrisp programming framework. The entire pipeline was executed on IQM superconducting quantum processors to provide an empirical assessment under current noisy intermediate-scale quantum (NISQ) conditions. Our experimental data definitively show that the system operates significantly below the fault-tolerance threshold. Crucially, a quantitative resource analysis isolates and establishes the lack of native qubit reset on the hardware as the dominant architectural bottleneck. This constraint forces the physical qubit count to scale as

d^{2} + (d^{2} - 1) T

, effectively preventing scaling to larger code distances (d) and execution times (T) on current devices. The work confirms Qrisp’s capability to support advanced QEC protocols, demonstrating that high-level abstraction can reduce implementation complexity by simplifying scheduling and mapping, thereby facilitating deeper experimental analysis of hardware limitations. Full article

(This article belongs to the Special Issue Recent Advances in Quantum Information)

► Show Figures

Figure 1

25 pages, 5569 KB

Open AccessArticle

Using K-Means-Derived Pseudo-Labels and Machine Learning Classification on Sentinel-2 Imagery to Delineate Snow Cover Ratio and Snowline Altitude: A Case Study on White Glacier from 2019 to 2024

by Wai Yin (Wilson) Cheung and Laura Thomson

Remote Sens. 2025, 17(23), 3872; https://doi.org/10.3390/rs17233872 (registering DOI) - 29 Nov 2025

Abstract

Accurate equilibrium-line altitude (ELA) estimates are a valuable proxy for evaluating glacier mass balance conditions and interpreting climate-driven change in the Canadian high Arctic, where sustained in situ observations are limited. A scalable remote-sensing framework is evaluated to extract the snow cover ratio [...] Read more.

Accurate equilibrium-line altitude (ELA) estimates are a valuable proxy for evaluating glacier mass balance conditions and interpreting climate-driven change in the Canadian high Arctic, where sustained in situ observations are limited. A scalable remote-sensing framework is evaluated to extract the snow cover ratio (SCR) and snowline altitude (SLA) on White Glacier (Axel Heiberg Island, Nunavut) and to assess the agreement with in situ ELA measurements. Ten-metre Sentinel-2 imagery (2019–2024) is processed with a hybrid pipeline comprising the principal component analysis (PCA) of four bands (B2, B3, B4, and B8), unsupervised K-means for pseudo-label generation, and a Random Forest (RF) classifier for snow/ice/ground mapping. SLA is defined based on the date of seasonal minimum SCR using (i) a snowline pixel elevation histogram (SPEH; mode) and (ii) elevation binning with SCR thresholds (0.5 and 0.8). Validation against field-derived ELAs (2019–2023) is performed; formal SLA precision from DEM and binning is quantified (

\pm 4.7

m), and associations with positive degree days (PDDs) at Eureka are examined. The RF classifier reproduces the spectral clustering structure with

> 99.9 %

fidelity. Elevation binning at

SCR \geq 0.8

yields SLAs closely matching field ELAs (Pearson

r = 0.994

,

p = 0.0006

; RMSE

= 30

m), whereas SPEH and lower-threshold binning are less accurate. Interannual variability is pronounced as follows: minimum SCR spans 0.46–0.76 and co-varies with SLA; correlations with PDDs are positive but modest. Results indicate that high-threshold elevation-bin filtering with machine learning provides a reliable proxy for ELA in clean-ice settings, with potential transferability to other data-sparse Arctic sites, while underscoring the importance of image timing and mixed-pixel effects in residual SLA–ELA differences. Full article

(This article belongs to the Special Issue AI-Driven Mapping Using Remote Sensing Data)

14 pages, 449 KB

Open AccessArticle

Infection Dynamics and Host Biomarker Identification for Spotty Liver Disease in Chickens

by Helen James, Emily Gan, Robert J. Moore, Daniel M. Andrews and Thi Thu Hao Van

Vet. Sci. 2025, 12(12), 1136; https://doi.org/10.3390/vetsci12121136 (registering DOI) - 29 Nov 2025

Abstract

Spotty liver disease (SLD), primarily caused by Campylobacter hepaticus and (less frequently) by Campylobacter bilis, significantly impacts commercial layer hens by causing liver lesions, reducing egg production, and increasing mortality, meaning it can result in serious economic losses for farmers. This study [...] Read more.

Spotty liver disease (SLD), primarily caused by Campylobacter hepaticus and (less frequently) by Campylobacter bilis, significantly impacts commercial layer hens by causing liver lesions, reducing egg production, and increasing mortality, meaning it can result in serious economic losses for farmers. This study explored the relationship between infection, liver dysfunction, and reproduction, aiming to identify host genetic markers for tracking SLD progression. Hens were orally inoculated with the C. hepaticus strain NSW44L and monitored over a seven-day period. Pathogen colonisation was quantified using qPCR across the liver, bile, caeca, spleen, and ovarian follicles, while liver lesions were scored and hepatic transcriptomes analysed using RNA-seq. C. hepaticus was detected in the liver, caeca, and spleen from one day post-inoculation (dpi) (1.44–1.68 log₁₀ CFU/mL), appeared in bile by the third dpi (3.64 log₁₀ CFU/mL), and reached the follicles by the fourth dpi (3.25 log₁₀ CFU/mL). The highest bacterial loads were found in bile on days six and seven (up to 7.18 CFU/mL). Liver lesions were first observed on the fourth dpi, reaching their peak at the sixth and seventh dpi. Gene expression analysis in liver tissue revealed a notable downregulation of yolk-precursor and metabolic genes, such as prolactin receptor (PRLR), 7-dehydrocholesterol reductase (DHCR7), and malic enzyme 1 (ME1). In contrast, from days three to seven post-infection, there was significant upregulation of avidin (AVD), a biotin-binding protein, and versican (VCAN), which is linked to tissue remodelling and inflammation. These findings correlate with the disease’s progression from initial liver infection to widespread bacterial presence, suggesting value as host biomarkers for effective SLD monitoring and the development of targeted therapies. Full article

(This article belongs to the Section Veterinary Microbiology, Parasitology and Immunology)

► Show Figures

Figure 1

20 pages, 453 KB

Open AccessArticle

State Self-Compassion as a Protective Factor Against Anxiety and Depression Symptoms Across Adults

by Eirini Karakasidou, Georgia Raftopoulou and Christiana Koundourou

Psychol. Int. 2025, 7(4), 95; https://doi.org/10.3390/psycholint7040095 (registering DOI) - 29 Nov 2025

Abstract

Background/Objectives: Self-compassion is a psychological construct that involves treating oneself with kindness, understanding, and mindfulness during times of failure or suffering. This study investigates the beneficial role of state self-compassion in relation to symptoms of anxiety and depression across different adult age groups [...] Read more.

Background/Objectives: Self-compassion is a psychological construct that involves treating oneself with kindness, understanding, and mindfulness during times of failure or suffering. This study investigates the beneficial role of state self-compassion in relation to symptoms of anxiety and depression across different adult age groups in the Greek population. Grounded in positive psychology, the research highlights state self-compassion as a protective factor for mental health. Methods: A total of 1528 adults aged 18 to 65 participated by completing a set of self-report questionnaires, including the State Self-Compassion Scale-Long Form (SSCS-L) and the Depression, Anxiety, Stress Scale (DASS-21). Results: The results showed that age was positively correlated with state self-compassion and negatively with anxiety and depression symptoms. Furthermore, state self-compassion was negatively correlated with both anxiety and depression, indicating its protective association against psychological distress. Two-way ANOVA showed that state self-compassion levels, but not age groups, had a significant effect on anxiety and depression scores. No significant interaction effects were found between state self-compassion levels and age groups for either anxiety or depression, indicating that the protective association of state self-compassion was consistent across adulthood. Multiple regression analyses revealed that higher state self-compassion and older age were significantly associated with lower levels of anxiety and depression symptoms. Moderation analyses demonstrated that age did not moderate the association between state self-compassion and either depression or anxiety symptoms, indicating that the protective association of self-compassion remained stable across adulthood. Thus, neither ANOVA nor PROCESS analyses provided evidence for moderation. Conclusions: These findings underline the importance of fostering state self-compassion to promote psychological well-being across adulthood. Implications for counselling psychology and age-sensitive mental health interventions are discussed, with recommendations for future longitudinal and intervention-based studies. Full article

► Show Figures

Figure 1

27 pages, 3904 KB

Open AccessArticle

Integrating Active Learning in an Undergraduate Corrosion Science and Engineering Course—KFUPM’s Active Learning Initiative

by Ihsan Ulhaq Toor

Sustainability 2025, 17(23), 10704; https://doi.org/10.3390/su172310704 (registering DOI) - 29 Nov 2025

Abstract

Material degradation in the form of corrosion is an important industrial problem that affects asset integrity, reliability, and sustainability in various industries. To equip engineering professionals with the knowledge required for appropriate material selection and corrosion-mitigation design, this subject forms an essential part [...] Read more.

Material degradation in the form of corrosion is an important industrial problem that affects asset integrity, reliability, and sustainability in various industries. To equip engineering professionals with the knowledge required for appropriate material selection and corrosion-mitigation design, this subject forms an essential part of the engineering curriculum at both undergraduate and graduate levels across multiple disciplines. This paper presents the design, implementation, and evaluation of an active learning (AL)-based course framework to teach a corrosion science and engineering course at the mechanical engineering department, KFUPM. A combination of AL strategies, including project-based learning (PBL), case-based inquiries, peer instruction, and think–pair–share activities, etc., was systematically integrated into the course to promote collaborative learning, conceptual enrichment, and critical thinking. Positive student feedback (>90% for most of the survey questions) with a response rate of 89% indicated increased motivation, improved understanding of complex corrosion mechanisms, and increased confidence in applying knowledge to solve engineering problems. A Cronbach’s alpha coefficient of 0.75 was obtained, reflecting strong internal reliability of the instrument. These findings suggest that integrating AL pedagogies in the corrosion course contributed towards enhanced learning outcomes and student preparation to support sustainable industrial practices using informed materials selection and corrosion management. Full article

(This article belongs to the Special Issue Inputs of Engineering Education Towards Sustainability—2nd Edition)

► Show Figures

Figure 1

14 pages, 3755 KB

Open AccessArticle

Genetic Diversity of Robinia pseudoacacia L. Populations from North-Western Romania Revealed by ISSR Markers

by Ruben Budau, Eliza Maria Agud, Vasile Laslo, Adrian Ioan Timofte and Mariana Florica Bei

Forests 2025, 16(12), 1795; https://doi.org/10.3390/f16121795 (registering DOI) - 29 Nov 2025

Abstract

This study aims to evaluate the genetic diversity of the species Robinia pseudoacacia L. using several populations selected from places located in the Crișana Region. The first six ISSRs tested gave distinct bands, with a total of 59 loci, of which 45 were [...] Read more.

This study aims to evaluate the genetic diversity of the species Robinia pseudoacacia L. using several populations selected from places located in the Crișana Region. The first six ISSRs tested gave distinct bands, with a total of 59 loci, of which 45 were polymorphic (63.85%). The percentage of polymorphic loci varied within populations from 33.33% to 100%. The average number of observed alleles (Na) is 1.7627 and the average effective number of alleles (Ne) is 1.4926, indicating that the effective variability is lower than the observed variability. For the Nei (h) gene diversity index, we recorded an average value of 0.2795, and for allelic entropy, the average value of the Shannon index (I) was 0.4137. The study finds a significant differentiation between populations, with a Gst coefficient value of 0.43 indicating that 43% of the variability is due to interpopulation differences. Full article

(This article belongs to the Special Issue Population Genetics and Molecular Evolution of Trees)

► Show Figures

Figure 1

17 pages, 3242 KB

Open AccessArticle

Dual Inhibition of PARP and Akt Induces Metabolic Collapse and Apoptosis in Breast Cancer Cells

by Nasreldeen Mohamed Karshom Adam, Eszter Vámos, Hamid Ahmadi, Geofrey Ouma Maloba, Arshi Arshi and Ferenc Gallyas Junior

Cancers 2025, 17(23), 3828; https://doi.org/10.3390/cancers17233828 (registering DOI) - 29 Nov 2025

Abstract

Background: Breast cancer is the most prevalent cancer among women worldwide, and therapeutic resistance represents a major clinical challenge. Mitochondria are key regulators of cancer metabolism, redox homeostasis, and apoptosis, making them potential therapeutic targets. Aim: This study aimed to evaluate the effects [...] Read more.

Background: Breast cancer is the most prevalent cancer among women worldwide, and therapeutic resistance represents a major clinical challenge. Mitochondria are key regulators of cancer metabolism, redox homeostasis, and apoptosis, making them potential therapeutic targets. Aim: This study aimed to evaluate the effects of combined Akt and PARP inhibition on mitochondrial metabolic function, energy production, and apoptosis in breast cancer cells. Methodology: The SRB assay was used to compare the viability of MDA-MB-231 and MCF7 cells. A colony formation assay was conducted to assess the capacity of individual cells to develop colonies, and ROS production was quantified using DHR123. Flow cytometric analysis was performed to evaluate cell death, and the Seahorse Mito stress test was used to measure ATP production and essential mitochondrial parameters. Results: The combination of Akt and PARP inhibitors impaired oxidative phosphorylation without inducing a compensatory shift to glycolysis, leading to reduced ATP production, increased ROS generation, and apoptotic cell death in breast cancer cells compared to monotherapy. Conclusions and Recommendations: These findings indicate that the combination of olaparib and capivasterib is a promising therapeutic strategy for breast cancer. Furthermore, evaluation of in vivo toxicity and antitumor effectiveness is essential to validate its potential. Full article

(This article belongs to the Section Molecular Cancer Biology)

► Show Figures

Figure 1

16 pages, 9073 KB

Open AccessArticle

Surface Ice Velocity near the Terminus of Grey Glacier in the Southern Patagonian Icefield, Based on Direct Field Measurements

by Roberto García-Esteban

Geosciences 2025, 15(12), 452; https://doi.org/10.3390/geosciences15120452 (registering DOI) - 29 Nov 2025

Abstract

Glacier mass balance and ice flow dynamics, strongly influenced by climatic variability, topography, and geological–structural controls, can be precisely characterized through in situ GPS measurements of surface ice velocity, though such data remain limited due to logistical challenges in field acquisition. This study [...] Read more.

Glacier mass balance and ice flow dynamics, strongly influenced by climatic variability, topography, and geological–structural controls, can be precisely characterized through in situ GPS measurements of surface ice velocity, though such data remain limited due to logistical challenges in field acquisition. This study presents direct measurements of surface ice velocity on Grey Glacier, a major outlet glacier of the Southern Patagonian Icefield (SPI) in Chile. Ice flow was monitored over a one-week period in late 2002 by tracking the displacement of six stakes installed on the glacier surface. The resulting velocity data reveal spatial patterns of surface flow that provide significant information for the comparison and validation of remote sensing observations, which is particularly relevant considering that the ice mass from which the data were collected has since disappeared due to glacier retreat. The combined use of ground-based and remote sensing methods is essential for advancing our understanding of glacier motion and behavior, particularly in the context of climate forcing. Full article

(This article belongs to the Section Cryosphere)

10 pages, 490 KB

Open AccessPerspective

Research Priorities for Zoonotic and Pandemic Influenza Vaccines: Evidence and Recommendations from the WHO Public Health Research Agenda for Influenza (2024 Update)

by Wenqing Zhang, Benjamin J. Cowling, John S. L. Tam, Thomas Abraham, Hualan Chen, Keenan Duggal, Wei Xin Khong, Sebastian Maurer-Stroh, Arnold S. Monto, Sergejs Nikisins, Tulio de Oliveira, Yuelong Shu, Cecile Viboud, Richard Webby, Sylvie van der Werf, Jessica Wong and Jean-Michel Heraud

Vaccines 2025, 13(12), 1206; https://doi.org/10.3390/vaccines13121206 (registering DOI) - 29 Nov 2025

Abstract

Zoonotic influenza viruses, including highly pathogenic avian influenza and swine-origin variants, continue to cause sporadic human infections with, in some cases, high case fatality rates and potential for sustained human-to-human transmission. The COVID-19 pandemic underscored both the possibilities of rapid vaccine innovation and [...] Read more.

Zoonotic influenza viruses, including highly pathogenic avian influenza and swine-origin variants, continue to cause sporadic human infections with, in some cases, high case fatality rates and potential for sustained human-to-human transmission. The COVID-19 pandemic underscored both the possibilities of rapid vaccine innovation and the persistent challenges in equitable access and public trust. This paper synthesizes the vaccine-related priorities from the 2024 update of the World Health Organization Public Health Research Agenda for Influenza, integrating evidence from systematic literature reviews commissioned, expert consultations, and analysis of lessons learned from recent health emergencies, to outline a research and policy roadmap for zoonotic and pandemic influenza vaccine preparedness. Key research priorities identified include development of broadly protective animal and human vaccines; improved understanding of correlates of protection; rapid and scalable manufacturing platforms; predictive modelling for strain selection; and targeted communication strategies to strengthen uptake. Experts have considered that implementing these priorities will require One Health integration, sustained investment, harmonized regulatory frameworks, and proactive community engagement to ensure that advances in vaccine science translate into timely, equitable public health protection. Full article

(This article belongs to the Special Issue Pandemic Influenza Vaccination)

► Show Figures

Figure 1

10 pages, 826 KB

Open AccessArticle

DNA Barcoding Protocol for Masdevallia Orchids: A Tool for CITES-Based Identification and Trade Control

by Małgorzata Karbarz, Eliza Lebioda and Agnieszka Leśko

Genes 2025, 16(12), 1423; https://doi.org/10.3390/genes16121423 (registering DOI) - 29 Nov 2025

Abstract

Background: Orchids of the Masdevallia genus are characterized by their beautiful esthetic qualities. However, they are vulnerable to habitat destruction, illegal harvesting, tourism and climate change. These extinction threats have led to the listing of all Masdevallia species in Appendix II of [...] Read more.

Background: Orchids of the Masdevallia genus are characterized by their beautiful esthetic qualities. However, they are vulnerable to habitat destruction, illegal harvesting, tourism and climate change. These extinction threats have led to the listing of all Masdevallia species in Appendix II of CITES (Convention on International Trade in Endangered Species of Wild Fauna and Flora) and their selection by the IUCN (International Union for Conservation of Nature). Orchids are sold in various forms, e.g., stems or tubers, rendering them impossible to identify based on morphology alone. DNA barcoding is a method that enables reliable identification of organisms using DNA barcodes, and it offers an excellent solution to the need for efficient identification of Masdevallia orchids. The aim of this study was to determine the most effective locus for DNA barcode identification of Masdevallia orchids in order to develop a quick and practical identification method for this genus. Such a method can be used by CITES verification authorities to detect illegal trade. This is the first focused study to validate a DNA barcoding protocol for Masdevallia for CITES enforcement purposes. Methods: Three genetic regions were analyzed: matK, rbcL, and ITS. The effectiveness of identification was verified based on results obtained from the new version of the BOLD Systems v.5 reference database. Results: Although Masdevallia is not well represented in this database, successful identification to the genus level was achieved. Conclusions: The highest identification efficiency at the genus level was achieved for the ITS region (91%). Full article

(This article belongs to the Section Plant Genetics and Genomics)

► Show Figures

Figure 1

Recent Articles

Open Access Journals

Highly Accessed Articles

Latest Books

News

Blog Posts

Topics

Selected Special Issues

Selected Collections

Journals by Subject

Further Information

Guidelines

MDPI Initiatives

Follow MDPI