Saved Queries

by Ouwais Aljabasini, Niki Tagkalidou, Martalu D. Pazos, Guillermo García-Díez, Eva Prats, Roger Seco, Xavier Berzosa, Raúl López-Arnau and Demetrio Raldua

Int. J. Mol. Sci. 2026, 27(7), 3141; https://doi.org/10.3390/ijms27073141 - 30 Mar 2026

Abstract

The rapid emergence of New Psychoactive Substances (NPS), particularly pyrrolidinophenone derivatives, poses a significant challenge for public health and forensic toxicology. While their neuropharmacological profiles as dopamine transporter inhibitors are well-documented, their cardiac toxicity remains poorly understood. This study employs a multiparametric New Approach Methodology (NAM) using zebrafish embryos to integrate neurobehavioral and cardiotoxic endpoints for comparative hazard prioritization. We evaluated nine pyrrolidine-containing cathinones, including α-PVP, MDPV, α-PiHP, MDPiHP, α-D2PV, 3-Cl-, 4-Cl-, and 3,4-Cl-α-PVP, and 4-F-3-Me-α-PVP, on locomotor activity and cardiac rhythmicity using high-speed video microscopy and dynamic pixel analysis. Across the series, compounds induced concentration-dependent negative chronotropy and, in most cases, locomotor suppression. Crucially, we identified a functional dissociation between atrial rate control and atrioventricular (AV) conduction. The 3,4-dichloro substitution (3,4-Cl-α-PVP) was the most potent inducer of negative chronotropy (EC₅₀ = 52.6 μM), whereas 4-Cl-α-PVP exhibited a distinct pro-arrhythmic liability, increasing the incidence of 2:1 AV block. Time-course locomotor profiling indicated that α-PVP and chlorinated analogs were among the most potent behavioral modifiers. Using a Functional Safety Index (AV block EC₅₀/locomotor EC₅₀-like), we show that most compounds exhibit wide separations between neurobehavioral inhibition and severe conduction impairment, while specific substitutions, particularly para-chlorination, are associated with comparatively reduced functional separation between these endpoints within the assay. Overall, these data demonstrate that subtle structural changes within the pyrrolidinophenone scaffold can shape distinct arrhythmic phenotypes and functional safety profiles, supporting zebrafish-based integrated screening as a rapid platform for prioritizing emerging synthetic cathinones with comparatively higher cardiac liability within this experimental framework. Full article

(This article belongs to the Special Issue Zebrafish as a Novel Model for Toxicological Research)

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24 pages, 5472 KB

Open AccessArticle

Ex-Situ Electrokinetic Remediation of Copper-Contaminated Vineyard Soils: Remediation Efficiency, Copper Redistribution and Fractionation Across Differing Soil pH Conditions

by Marija Poljak, Danijel Brezak, Marija Galić, Marijana Kraljić Roković, Ivica Kisić, Marina Bubalo Kovačić, Ivana Zegnal, Hrvoje Hefer, Milena Andrišić, Daniel Rašić, Manuel Matišić and Aleksandra Perčin

Agriculture 2026, 16(7), 765; https://doi.org/10.3390/agriculture16070765 - 30 Mar 2026

Abstract

Electrokinetic remediation (EKR) was evaluated in naturally contaminated vineyard soils to assess copper redistribution, treatment redistribution efficiency, and changes in copper fractions across contrasting soil pH conditions. Ten vineyard soils (five acidic, five alkaline) were subjected to a 30-day ex situ EKR experiment under a constant electric field. Total copper content was measured in the anode, cathode, and inter-electrode zones, while copper fractions were quantified only in electrode zones exhibiting the most pronounced post-remediation decrease in total copper. The findings demonstrate that the EKR process generated distinct, soil-type-dependent gradients in copper mobility. In acidic soils, copper exhibited pronounced central-zone accumulation with notable depletion toward the anode, whereas in alkaline soils, the lowest concentrations consistently occurred near the cathode and increased toward the anode. Notably, one slightly alkaline soil displayed the highest redistribution efficiency (43.0%), underscoring the strong influence of soil chemistry on EKR performance. Redistribution efficiencies averaged 29.5% in acidic soils and 12.8% in alkaline soils, although localized acidification enabled notably higher redistribution in highly contaminated samples. These trends reflected on copper fractions: acidic soils showed enhanced release from Fe/Mn oxides and carbonates, while alkaline soils experienced stronger short-term mobilization driven by cation competition and dissolution of less stable oxide phases. Fractionation results indicated that the Fe/Mn oxide-bound fraction was the most susceptible to electromigration, while both acidic and alkaline soils ultimately shifted copper toward less extractable operational fractions. Full article

(This article belongs to the Section Agricultural Soils)

16 pages, 2432 KB

Open AccessArticle

Docosahexaenoic Acid Attenuates Visceral Pain by Suppressing Spinal CXCL10/CXCR3/ERK Signaling

by Xi Yin, Anqi Jiang, Yu Han, Jianhua Qu, Jianya Zhao, Hao Gong, Xiaorong Luo, Xu Li and Ying Lu

Nutrients 2026, 18(7), 1113; https://doi.org/10.3390/nu18071113 - 30 Mar 2026

Abstract

Background: Visceral pain is the primary symptom of functional gastrointestinal disorders, yet its spinal molecular mechanisms remain poorly defined. Methods: Using a 2,4,6-trinitrobenzenesulfonic acid (TNBS)-induced chronic inflammatory visceral pain model, the role of the spinal CXCL10/CXCR3/ERK signaling axis and the analgesic effect of docosahexaenoic acid (DHA) were investigated. Results: TNBS significantly upregulated CXCL10 and CXCR3 in spinal dorsal horn neurons and increased ERK phosphorylation. Intrathecal CXCL10-neutralizing antibody or CXCR3 antagonist NBI-74330 reduced visceral hypersensitivity and suppressed spinal ERK activation in TNBS mice. Exogenous CXCL10 induced CXCR3-dependent hyperalgesia and ERK phosphorylation in the spinal cord. Intrathecal DHA attenuated TNBS-induced visceral pain, downregulated spinal CXCL10/CXCR3 expression, and inhibited ERK signaling. In Neuro-2a cells, DHA also blocked LPS-induced activation of the same pathway. Conclusions: This study suggests that the analgesic effect of DHA may involve the inhibition of the spinal CXCL10/CXCR3/ERK signaling pathway. Full article

(This article belongs to the Special Issue Nutrition and Nutraceuticals for Pain Prevention and Treatment)

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14 pages, 397 KB

Open AccessArticle

Exercise Motivation and Quality of Life in Cancer Survivors: The Impact of Exercise Intervention

by Kun-Chou Hsieh, Shyh-An Yeh, Cheng-I Hsieh, Hung-Ju Li, Yun Chen, Luo-Han Lin, Meng-Chuan Huang, Chia-Chen Chang, Yu-Ling Chen and Yu-Chieh Su

Cancers 2026, 18(7), 1119; https://doi.org/10.3390/cancers18071119 - 30 Mar 2026

Abstract

Background/Objectives: Cancer survivors often experience physical decline, fatigue, and reduced quality of life (QoL) following cancer treatment. Exercise is an important strategy in survivorship care; however, the role of exercise motivation in sustaining exercise behavior and improving QoL remains unclear. This study evaluated the effects of a structured exercise intervention on QoL, fatigue, and exercise motivation among cancer survivors. Methods: This single-arm longitudinal pre–post-intervention study recruited adult cancer survivors (median age: 55 years) with heterogeneous cancer types from E-Da Hospital, Taiwan, between October 2023 and July 2024. Participants completed a 3-month supervised exercise program consisting of weekly 60 min sessions that included aerobic, resistance, balance, and flexibility training. Assessments were conducted at baseline, immediately after the intervention, and at a 3-month follow-up. Outcome measures included physical fitness tests, fatigue scales, and the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30), and the Relative Autonomy Index for exercise motivation. Results: Thirty-nine participants completed the study. Improvements in several QoL domains were observed at the 3-month follow-up, particularly in physical and emotional functioning. Pain and fatigue symptoms decreased following the intervention, although some fatigue indicators increased again during follow-up. Female participants showed greater improvements in certain physical fitness measures. Intrinsic exercise motivation increased after the intervention, and greater motivation gains were associated with larger improvements in QoL. Conclusions: Participation in a structured exercise program may be associated with improvements in QoL, fatigue symptoms, and exercise motivation among cancer survivors. However, given the single-arm design and small sample size, these findings should be interpreted cautiously. Larger randomized controlled studies are needed to confirm the long-term benefits of exercise interventions in cancer survivorship care. Full article

(This article belongs to the Special Issue Advances in Cancer Survival Analysis)

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30 pages, 2314 KB

Open AccessReview

Replacing Meat with Plant-Based Proteins: An Analysis of Nutritional, Sustainability and Acceptability Aspects

by Ileana Cocan, Monica Negrea, Ersilia Alexa, Calin Jianu, Gabriel Heghedus-Mindru and Mihaela Cazacu

Appl. Sci. 2026, 16(7), 3356; https://doi.org/10.3390/app16073356 - 30 Mar 2026

Abstract

As the world progresses towards more sustainable food systems, an increasing number of individuals are inclined to reduce meat consumption and transition to plant-based protein sources. Given the implications of climate change and escalating public health issues, plant-based protein sources appear to be a viable alternative; yet, this transition will be challenging to implement. Legumes, cereals, oilseeds, microalgae, and mycoprotein constitute the primary sources of plant-derived protein. Each possesses distinct functional attributes; yet, they also exhibit certain nutritional constraints. The restrictions mostly pertain to the composition of essential amino acids and the body’s efficacy in utilizing micronutrients such as iron, zinc, and vitamin B₁₂. From an ecological perspective, plant-based proteins often exert a significantly lesser impact on the environment compared to conventional meat. This reduces greenhouse gas emissions and optimizes resource utilization. Recent technological advancements, including fermentation methods, shear cell structuring, and high-moisture extrusion, have significantly improved the texture and flavor of plant-based products. However, consumer perceptions of the sensory attributes of these products significantly influence their acceptance. Current research priorities include improving protein digestibility, mitigating antinutritional factors, reducing salt content, and generating robust long-term data on health effects/health benefits. Ultimately, replacing meat with plant-based proteins involves not only scientific and nutritional considerations but also requires significant cultural and societal transformations to establish a more balanced and sustainable food system. Full article

(This article belongs to the Special Issue Feature Review Papers in Section 'Food Science and Technology': 2nd Edition)

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19 pages, 801 KB

Open AccessArticle

Measuring Governance-Enabled Sustainability in Central and Eastern Europe: Development of a Corporate Governance–Sustainability Index (CGSI–CEE)

by Mariana Ciurel and Corina-Ionela Dumitrescu

Sustainability 2026, 18(7), 3350; https://doi.org/10.3390/su18073350 - 30 Mar 2026

Abstract

Corporate governance is increasingly recognised as a key mechanism supporting sustainability transparency, accountability, and long-term value creation. While prior research has examined governance–performance relationships and sustainability outcomes using proprietary ESG ratings, evidence on how governance structures enable sustainability disclosure remains limited, particularly in Central and Eastern Europe (CEE). This gap reflects heterogeneous institutional environments and uneven ESG data availability in emerging European markets. To address this limitation, this study develops and applies a Corporate Governance–Sustainability Index for Central and Eastern Europe (CGSI–CEE). The index integrates core governance mechanisms (such as board effectiveness, leadership structure and ownership discipline) with sustainability transparency indicators, namely ESG report publication and CO₂ emissions disclosure. The CGSI–CEE is constructed using publicly available firm-level data from CEE blue-chip companies over the 2018–2024 period and follows a transparent, theory-driven weighting scheme. The results reveal substantial heterogeneity in governance-enabled sustainability capacity across firms, sectors, and countries. Bivariate results indicate a negative association with short-term accounting profitability and a positive association with market valuation; however, these relationships weaken once firm-level characteristics are controlled for, reinforcing the interpretation of CGSI–CEE as a structural governance-capacity measure rather than a direct performance determinant. Full article

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22 pages, 1119 KB

Open AccessArticle

The Dual-Core Driving Mechanism of Intelligent Oilfield Development: From Data Perception to Decision-Optimized Ecosystems

by Junxiang Wang, Fei Li, Jing Hu, Xincheng Ma, Siyan Hong, Jun Luo, Tianyu Bao, Shuoyao Dong, Yuming Yang, Jun Chu, Yushin Evgeny Sergeevich and Li He

Processes 2026, 14(7), 1120; https://doi.org/10.3390/pr14071120 - 30 Mar 2026

Abstract

Intelligent oilfield development is experiencing an increasingly deep integration between localized automation and integrated, data-centric ecosystems. To systematically delineate the knowledge structure and technological trajectories within this field, this study analyzes 225 high-quality publications. This study innovatively employs a custom toolchain based on the Dart language for heterogeneous data cleaning and standardization, ensuring high accuracy and scientific rigor in the analysis samples. The investigation reveals a distinct dual-core driving mechanism underpinning recent advancements: a cognitive cluster centered on Artificial Intelligence and Deep Learning for complex data interpretation and prediction, and a decision-making cluster focused on Operational Optimization and Predictive Modeling for production enhancement. These two clusters respectively encompass eight sub-clusters: “artificial intelligence,” “machine learning,” “deep learning,” “performance,” “enhanced oil recovery,” “model,” “optimization,” and “predication.” This dual-core framework signifies a paradigm shift from experience-based practices to a synergistic “AI-enabled + mathematical optimization” approach. The analysis further explores emerging trends, including the potential of deep reinforcement learning for dynamic decision-making and the critical role of cybersecurity and model robustness in safety risk management. By mapping the current landscape and core mechanisms, this study provides a foundational reference for researchers and practitioners to navigate the future development of intelligent oilfields towards more resilient and efficient ecosystems. Full article

(This article belongs to the Special Issue Environmentally Friendly Production of Energy from Natural Gas Hydrates, 2nd Edition)

22 pages, 4794 KB

Open AccessReview

Vulvar Vascular Malformations: Diagnosis, Imaging, and Management—A Review with an Illustrative Case

by Marija Batkoska, Kristina Drusany Starič, Jernej Mlakar and Marina Jakimovska

J. Vasc. Dis. 2026, 5(2), 16; https://doi.org/10.3390/jvd5020016 - 30 Mar 2026

Abstract

Background: Vascular malformations are congenital structural abnormalities of the blood vessels that may present at any age. In the vulvovaginal region, these lesions are uncommon and frequently misdiagnosed because their clinical appearance overlaps with common gynecologic conditions, particularly Bartholin’s gland cyst or abscess. Inappropriate surgical intervention without prior vascular evaluation may result in hemorrhage, incomplete treatment, and recurrence. Methods: A structured narrative review of the literature was performed using PubMed/MEDLINE and EMBASE databases (January 2000–April 2024) to summarize the classification, pathophysiology, clinical presentation, imaging characteristics, differential diagnosis, and management of vulvovaginal vascular malformations. Publications addressing vascular anomalies in other anatomical locations were also included when clinically relevant. A representative clinical case confirmed by histopathologic and molecular analysis is presented to illustrate the diagnostic pitfalls. Results: Vulvovaginal vascular malformations are predominantly low-flow venous lesions but may include high-flow arteriovenous malformations. A clinical examination alone is insufficient for diagnosis. Doppler ultrasonography is the recommended initial imaging modality, followed by magnetic resonance imaging to define the lesion extent and flow characteristics. Misdiagnosis most commonly occurs when lesions are treated as Bartholin’s gland pathology without prior imaging. Low-flow lesions are generally managed with sclerotherapy or planned surgical excision, whereas high-flow lesions require embolization and multidisciplinary care. Hormonal and hemodynamic changes, including pregnancy, may precipitate enlargement or thrombosis. Conclusions: Vascular malformations should be considered in the differential diagnosis of atypical vulvar masses. Preoperative imaging is essential in order to avoid inappropriate surgical procedures. A structured diagnostic approach combining clinical assessment and imaging enables correct classification and guides treatment. The presented case demonstrates a typical diagnostic pitfall and emphasizes the importance of recognizing vascular lesions in gynecologic practice. Full article

(This article belongs to the Section Peripheral Vascular Diseases)

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Graphical abstract

33 pages, 1066 KB

Open AccessArticle

LLM-DSaR: LLM-Enhanced Semantic Augmentation for Temporal Knowledge Graph Reasoning

by Ruoxi Liu, Chunfang Liu and Xiangyin Zhang

Electronics 2026, 15(7), 1446; https://doi.org/10.3390/electronics15071446 - 30 Mar 2026

Abstract

Temporal Knowledge Graph Inference (TKGI) is a cornerstone for intelligent decision-making in dynamic scenarios, but existing models face critical bottlenecks, including inadequate complex-context modeling, a lack of entity importance quantification, insufficient novel-event reasoning accuracy, and weak domain adaptability. To address these issues, this study proposes a semantics-enhanced model (LLM-DSaR) integrating Large Language Models (LLMs), temporal attention networks, and optimized contrastive learning. Specifically, a two-stage LLM semantic enhancement (LLM1 + LLM2) framework first generates structured semantic analysis reports via adaptive prompt engineering, and then extracts domain-specific semantic embeddings from the last-layer hidden states through pooling and linear projection, which are further fused with TransE-based structural embeddings; meanwhile, LLM2 mitigates data sparsity in novel-event reasoning; a dynamic weight fusion (DWF) framework adaptively assigns feature weights to achieve deep feature synergy; an LLM-enhanced contrastive-learning module strengthens event clustering and discrimination. Experiments on five public datasets and a self-constructed Robotics Temporal Knowledge Graph (RTKG) show LLM-DSaR outperforms 16 baselines: on RTKG, its MRR is 10.35 percentage points higher than GCR, and Hits@10 reaches 88.87%. Ablation experiments validate core modules’ effectiveness, confirming LLM-DSaR adapts to professional scenarios like robot maintenance prediction, providing a novel technical paradigm for complex-domain TKG reasoning. Full article

(This article belongs to the Section Artificial Intelligence)

16 pages, 1089 KB

Open AccessArticle

Association Between Urinary Phthalate Metabolites and Early Spontaneous Abortion

by Lin Tao, Nian Wu, Lulu Dai, Shimin Xiong, Dengqing Liao, Yuanzhong Zhou and Xubo Shen

Toxics 2026, 14(4), 300; https://doi.org/10.3390/toxics14040300 - 30 Mar 2026

Abstract

Phthalates (PAEs) are ubiquitous endocrine-disrupting chemicals (EDCs), but their association with early pregnancy loss (gestational age ≤ 12 weeks) remains controversial. This study enrolled pregnant women aged 20–45 years in Zunyi City, China, and included 107 cases and 349 controls following propensity score matching. Logistic regression, restricted cubic spline (RCS) analysis, Bayesian kernel machine regression (BKMR), and weighted quantile sum (WQS) regression were employed to investigate associations between urinary phthalate metabolites and early pregnancy loss. We found that monoethyl phthalate (MEP), mono(2-ethylhexyl) phthalate (MEHP), monooctyl phthalate (MOP), mono(2-ethyl-5-oxohexyl) phthalate (MEOHP), and mono(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP) were associated with spontaneous abortion in early pregnancy, with corresponding odds ratios (ORs; 95% confidence intervals [CIs]) of 1.62 (1.26–2.09), 1.49 (1.07–2.09), 1.64 (1.26–2.12), 1.78 (1.27–2.50), 2.63 (1.90–3.64), 1.41 (1.11–1.79), and 5.39 (3.53–8.25). Non-linear dose–response relationships were observed between exposure to MMP, MEP, MEHP, MOP, monobenzyl phthalate (MBZP), MEOHP, MEHHP, and mono-(3-carboxypropyl) phthalate (MECPP) and early pregnancy loss (non-linear p < 0.05; overall p < 0.05). Co-exposure to multiple phthalate metabolites was also linked to a significantly non-linear elevation in the risk of early pregnancy loss (OR; 95% confidence interval [CI]) of 1.92 (1.76–2.15). Among these metabolites, MMP, MOP, MEOHP, and MECPP make the largest contribution to the correlation. In summary, our findings indicate that exposure to phthalate esters during early pregnancy is associated with early pregnancy loss, with MMP, MOP, MEOHP, and MECPP as the primary contributors. However, these results are based on a single urine sample, and caution is warranted when interpreting the findings. Full article

(This article belongs to the Special Issue Effects and Mechanism of Endocrine Disruption and Reproductive Abnormality of Emerging Pollutant)

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16 pages, 274 KB

Open AccessBrief Report

Establish Global Nutrition Research Strategies: The Meeting Report of the First SIOP Nutrition Research Forum

by Rajul M. Gala, Judy Schoeman, Raquel Revuelta Iniesta, Mirjam van den Brink, Amy L. Lovell and Minke H. W. Huibers

Nutrients 2026, 18(7), 1112; https://doi.org/10.3390/nu18071112 - 30 Mar 2026

Abstract

Despite strong evidence linking nutritional status to treatment efficacy and survival in pediatric cancer, significant knowledge gaps and practice variation persist globally. On 24th October 2025, the International Society of Paediatric Oncology (SIOP) Nutrition Network, in collaboration with Prinsess Máxima Center for Paediatric Oncology and the International Initiative for Pediatrics and Nutrition (IIPAN), convened the first global SIOP Nutrition Network Research Forum. The forum brought together 54 international experts from high-income countries and low- and middle-income countries to define global nutrition research strategies for pediatric oncology. The forum addressed six emerging domains: body composition and treatment outcomes; microbiome, micronutrient status and metabolic health; prehabilitation and rehabilitation strategies; validation of nutritional assessment tools, guideline development for high-income settings; insights from international multicentric research initiatives—the International Atomic Energy Agency (IAEA), SIOP Nutrition Network, the Adapted Resource and Implementation Application (ARIA) guide nutrition portal, the International Collaboration on Nutrition in Cancer (ICONIC) WHO knowledge portal; and IIPAN and the World Cancer Research Fund (WCRF) for funding strategies. Delegates identified three priority working groups, namely prehabilitation optimization, pharmacokinetics, and advocacy, with each outlining collaborative nutrition research priorities for the next five years. This forum represents a critical point in pediatric oncology nutrition research as it established the first coordinated and internationally endorsed roadmap to bridge gaps in cancer care and ensure standard nutrition care worldwide. The research priorities and collaborations will help in creating evidence to improve cancer treatment and survival rate for children globally. Full article

(This article belongs to the Special Issue Nutrition in Paediatric Oncology)

22 pages, 12165 KB

Open AccessArticle

Mitochondrial Graph-Based Pan-Genome Analysis of Hypsizygus marmoreus: Structural Variation, Adaptive Evolution, and Its Implications for Germplasm Resource Improvement

by Ruichen Ma, Wenyun Li, Yongmei Miao, Ruiheng Yang, Youran Shao, Junjun Shang, Yan Li, Yuan Gao, Dapeng Bao and Yingying Wu

Int. J. Mol. Sci. 2026, 27(7), 3129; https://doi.org/10.3390/ijms27073129 - 30 Mar 2026

Abstract

Mitochondria regulate nuclear genomes and their own genetic material, primarily to provide energy in eukaryotes. Currently, high-throughput sequencing technologies are being used to resolve the mitochondrial genomes of various edible fungi. However, the application of pan-genomes for the analysis of edible mushroom mitochondrial genomes remains unexplored. In this study, we conducted a comparative mitochondrial genome analysis of 31 Hypsizygus marmoreus strains (four newly sequenced monotypes and 27 public datasets), ranging from 98,284 to 111,087 bp. This variation was determined to be primarily driven by dynamic changes in non-coding regions, particularly intronic polymorphisms in the cox1 gene. Further, transfer RNA (tRNA) secondary structures exhibited atypical globular and elongated conformations alongside copy number variations. Additionally, codon usage showed a pronounced A/T bias, whereas core respiratory chain genes demonstrated an evolutionary pattern of strong purifying selection. Furthermore, the 31 mitochondrial genomes of H. marmoreus were found to harbor eight gene rearrangement patterns and five genetic clusters, and the pan-genome analysis (220,364 bp, 217 nodes) captured abundant single-nucleotide polymorphisms (SNPs), insertions/deletions (InDels), and structural variations. This study provides breeding-relevant genetic markers and a genomic framework for H. marmoreus germplasm classification, genetic improvements, and the molecular breeding of stress-resilient varieties. Full article

(This article belongs to the Special Issue Fungal Genetics and Functional Genomics Research)

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31 pages, 1343 KB

Open AccessArticle

Explainable Deep Learning for Thoracic Radiographic Diagnosis: A COVID-19 Case Study Toward Clinically Meaningful Evaluation

by Divine Nicholas-Omoregbe, Olamilekan Shobayo, Obinna Okoyeigbo, Mansi Khurana and Reza Saatchi

Electronics 2026, 15(7), 1443; https://doi.org/10.3390/electronics15071443 - 30 Mar 2026

Abstract

COVID-19 still poses a global public health challenge, exerting pressure on radiology services. Chest X-ray (CXR) imaging is widely used for respiratory assessment due to its accessibility and cost-effectiveness. However, its interpretation is often challenging because of subtle radiographic features and inter-observer variability. Although recent deep learning (DL) approaches have shown strong performance in automated CXR classification, their black-box nature limits interpretability. This study proposes an explainable deep learning framework for COVID-19 detection from chest X-ray images. The framework incorporates anatomically guided preprocessing, including lung-region isolation, contrast-limited adaptive histogram equalization (CLAHE), bone suppression, and feature enhancement. A novel four-channel input representation was constructed by combining lung-isolated soft-tissue images with frequency-domain opacity maps, vessel enhancement maps, and texture-based features. Classification was performed using a modified Xception-based convolutional neural network, while Gradient-weighted Class Activation Mapping (Grad-CAM) was employed to provide visual explanations and enhance interpretability. The framework was evaluated on the publicly available COVID-19 Radiography Database, achieving an accuracy of 95.3%, an AUC of 0.983, and a Matthews Correlation Coefficient of approximately 0.83. Threshold optimisation improved sensitivity, reducing missed COVID-19 cases while maintaining high overall performance. Explainability analysis showed that model attention was primarily focused on clinically relevant lung regions. Full article

(This article belongs to the Special Issue Image Processing Based on Convolution Neural Network: 2nd Edition)

10 pages, 2959 KB

Open AccessProceeding Paper

AI-Driven Detection, Characterization and Localization of GNSS Interference: A Comprehensive Approach Using Portable Sensors

by Yasamin Keshmiri Esfandabadi, Amir Tabatabaei and Ruediger Hein

Eng. Proc. 2026, 126(1), 43; https://doi.org/10.3390/engproc2026126043 - 30 Mar 2026

Abstract

The increasing interest in the development and integration of navigation and positioning services across a wide range of receivers has exposed them to various security threats, including GNSS jamming and spoofing attacks. Early detection of jamming and spoofing interference is crucial to mitigating these threats and preventing service degradation. This research introduces an interference detection technique leveraging an AI algorithm applied to GNSS data utilizing various methods to enhance detection accuracy and efficiency. The objective was to use modern sensors and AI to develop an effective tool that detects, characterizes, and localizes interference, thereby reducing associated risks. These sensors and algorithms enable continuous GNSS interference monitoring and support real-time Decision-making. A server plays a crucial role in managing the entire system. Its primary function is to process data collected from various sensors referred to as nodes (e.g., static, rover, drone, and space) and from (public) GNSS networks as well as to perform localization using rotating-antenna nodes. Within the interference detection module, various methods were implemented at different points in the software receiver architecture. Each method’s certainty in identifying an interference source depends on its design and capabilities, with outcomes—whether positive or negative—being subject to potential accuracy or errors. To enhance the Decision-making process, an AI-based Decision-making block has been introduced to determine the presence of interference at a given epoch. The proposed interference monitoring methods were evaluated through experiments using GNSS signals under clean, jamming, and spoofing scenarios. The results demonstrate the techniques’ applicability across diverse scenarios, achieving high performance in interference detection, characterization, and localization. Full article

(This article belongs to the Proceedings of European Navigation Conference 2025)

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14 pages, 1356 KB

Open AccessArticle

Vitamin D Status and Health Indicators in the Malagasy Population: A Pilot Study

by Milos Chudy, Petra Macounova, Nikol Gottfriedova, Adela Novotna, Klara Jaresova, Hana Tomaskova, Rastislav Madar and Marek Buzga

Healthcare 2026, 14(7), 887; https://doi.org/10.3390/healthcare14070887 - 30 Mar 2026

Abstract

Background: Vitamin D plays an important role in overall health. This study aimed to conduct a pilot screening of serum vitamin D levels in a Malagasy cohort and to compare vitamin D status groups with selected health indicators. Methods: A cross-sectional observational pilot study was performed in two geographically distinct regions of Madagascar—a coastal area and an inland area. In total, 150 individuals underwent a single health screening, including semi-quantitative assessment of serum 25-hydroxyvitamin D, as well as evaluation of glycemic and cholesterol levels, blood pressure, anthropometric parameters, and a brief personal and lifestyle questionnaire. Results: A total of 148 participants (aged 18–88 years) were analyzed. 45.9% of participants had low serum vitamin D levels (<75 nmol/L). Lower vitamin D levels and higher total cholesterol were observed in the coastal group compared to the inland group (p < 0.05). No significant differences were found for most other examined health indicators. In multivariable analysis, age was identified as an important determinant of several outcomes. Vitamin D status did not remain an independent predictor; however, a trend toward an independent association with hypercholesterolemia was observed (p = 0.07), while the association with hyperglycemia was less pronounced (p = 0.11). Conclusions: A substantial proportion of participants exhibited low vitamin D levels despite favorable geographic conditions. The results suggest a potential relationship between vitamin D status and lipid metabolism, although this association did not reach statistical significance after adjustment. These findings provide initial insight into vitamin D status and its potential associations in this setting and may inform future research and public health monitoring. Full article

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