The mechanisms linking chronic hyperglycemia to intestinal inflammation and epithelial dysfunction remain incompletely understood, highlighting an important gap in our understanding of diabetes-associated gastrointestinal pathology. In this study, we investigated the effects of sustained hyperglycemia on intestinal inflammation, endoplasmic reticulum (ER) stress, and autophagy in a translational porcine model of diabetes. Diabetes was induced in Yucatan mini pigs using a high-fat, high-carbohydrate/fructose diet (HFHFD) followed by streptozotocin administration. Intestinal tissues from the terminal ileum and sigmoid colon were analyzed using histological evaluation, quantitative real-time PCR, and immunohistochemistry. Histological analysis revealed structural alterations in diabetic animals, including villous degeneration, crypt depletion, goblet-cell loss, and increased inflammatory-cell infiltration. Gene expression analysis revealed significant upregulation of inflammatory mediators (NF-κB, TNF-α, IL-6, IL-1β), inflammasome components (NLRP3), and macrophage markers (CD68, CD86, CD163). In parallel, ER stress-related genes (ORMDL3, ATF6) and autophagy-associated genes (NOD2, ULK1, ATG4a) were significantly elevated in diabetic pigs. At the protein level, increased expression of ER stress markers was confirmed in both intestinal regions, while autophagy-related proteins showed less consistent changes and did not fully reflect the observed transcriptional patterns, suggesting a potential disconnect between transcriptional activation and functional autophagic response under diabetic conditions. Chronic hyperglycemia is associated with intestinal inflammation and disruption of cellular stress pathways, including ER stress and autophagy, in a porcine model. These findings provide mechanistic insight into how chronic hyperglycemia contributes to intestinal dysfunction through coordinated alterations in inflammatory signaling, ER stress, and autophagy pathways, identifying these processes as potential targets for therapeutic intervention in diabetes-associated gastrointestinal disease.

Cognitive impairment (CI) is common in multiple sclerosis (MS), yet the network-level mechanisms underlying CI remain poorly understood. This study aimed to clarify how the joint organization of structural and functional brain networks contributes to CI in MS, and how network-derived features change when clinical information and MRI-derived measure are added. We analyzed neuropsychological and multimodal MRI data from the Amsterdam MS cohort (N = 330) and assessed generalizability externally (N = 27). Graph-theoretical measures of brain connectivity were extracted from diffusion-weighted and resting-state functional MRI. Machine learning models classified cognitively impaired versus preserved patients. Classification performance was quantified using the area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity. Feature importance was evaluated using Shapley values. Network-derived features improved discrimination over demographic information alone (AUROC = 0.77; p < 0.001). Adding MRI-derived measures significantly improved performance (AUROC = 0.81; p < 0.001), whereas clinical variables added little additional information (AUROC = 0.79; p = 0.65). External validation demonstrated good discriminative ability (AUROC = 0.76), but low sensitivity. Structural connectivity within the dorsal attention network emerged as an informative feature. These findings suggest that network-derived features help classify cognitive status in MS and remain relevant alongside conventional features. Structural connectivity, especially within the dorsal attention network, may provide insight into systems-level correlates of CI in MS.

On poorer quality soils and in mountainous areas, red clover is an important forage crop for animal feed production. Knowing the production potential, adaptability and stability of a variety in a particular location is of utmost importance for the success of production in the future. Soil quality, weather conditions during the second mowing (the mowing in which seed production is most often carried out) and the lifespan of red clover have a major impact on seed yield. The aim of the research in this work was to determine the production potential of the yield and quality of red clover seeds on acid reaction soil, to select the best varieties because they can be expected to give high forage yields. The selection of the best varieties is also important for the production of animal feed, if a variety has a high seed yield, it can be expected that it will also have high forage yields. Research was carried out on 10 varieties of red clover in two years in the area of the Mrkonjić Grad municipality. For all tested traits, the factors of variety and year had a statistically significant influence. The highest average seed yield was achieved by the Marina variety, the highest total germination and the lowest proportion of hard seeds by the Kolubara variety. The Viva variety had the highest 1000-kernel weight and high germination. Statistically significantly higher seed yield and 1000-kernel weight were obtained in the first year of testing, and germination and proportion of hard seeds in the second year of testing. At this location, red clover seed production should be carried out in the second mowing of the second year of life, due to low seed yields, the second mowing in the third year should be used for fodder production.

This study evaluates the feasibility and technical success rate of real-time virtual sonography (RVS) for prone contrast-enhanced breast MRI sequences during second-look examinations. Usually, additional supine MRI sequences are acquired for coregistration. This single-center retrospective study was performed in a cohort of female patients who underwent contrast-enhanced prone breast MRI followed by second-look ultrasound for MRI-detected incidental lesions. RVS was used to coregister supine ultrasound and prone MRI data without requiring additional supine MRI studies. Lesion localization success, as well as lesion visibility, fusion quality, and histopathological correlation through ultrasound-guided biopsy, were assessed. A covariate analysis of factors affecting lesion localization was performed. A total of 103 female patients (mean age 48.3 ± 11.0 years) with 125 MRI-detected breast lesions were included. Of the lesions, 91.2% were successfully localized using RVS, including a high proportion of non-mass enhancements (41.6%). Ultrasound-guided biopsy was performed in 57.6% of cases, confirming malignancy in 31.9% of those. Covariate analysis identified higher breast volume as the only factor significantly associated with reduced RVS coregistration success (odds ratio 0.993, p = 0.035). RVS represents an advanced imaging approach in breast diagnostics, offering a promising solution to overcome the limitations of standalone modalities and potentially enhance diagnostic accuracy. We showed that prone MRI studies may be sufficient for RVS-based coregistration of breast lesions, potentially rendering additional supine MRI acquisitions unnecessary. This study demonstrates that real-time virtual sonography with contrast-enhanced MRI in the prone position is a feasible and effective method for localizing MRI-detected breast lesions on second-look ultrasound without the need for additional supine MRI. This approach can optimize diagnostic workflows and reduce imaging burden while maintaining high localization rates. RVS localizes MRI-detected breast lesions in the prone position without requiring additional supine MRI for co-registration. Successful localization was achieved in 91.2%, including 41.6% non-mass enhancements, with higher breast volume as the only detrimental factor. RVS enables accurate lesion localization without supine MRI, streamlining workflows, lowering imaging costs, and improving biopsy access. RVS localizes MRI-detected breast lesions in the prone position without requiring additional supine MRI for co-registration. Successful localization was achieved in 91.2%, including 41.6% non-mass enhancements, with higher breast volume as the only detrimental factor. RVS enables accurate lesion localization without supine MRI, streamlining workflows, lowering imaging costs, and improving biopsy access.

DNA barcoding has become a cornerstone for species identification and biodiversity monitoring, enabling applications from ecological research to conservation and environmental policy. The International Barcode of Life (iBOL) provides global coordination, but national nodes are essential for implementing barcoding at scale, building local capacity and translating scientific advances into practice. This paper synthesises experiences from 20 countries (17 in Europe), drawing on a survey and a workshop conducted under the Horizon Europe Biodiversity Genomics Europe project. We examine how national nodes are initiated, governed and sustained and identify common challenges, such as defining scope, securing funding, harmonising methods and engaging stakeholders. Most nodes were initiated by research communities and operate as informal networks with heterogeneous governance and staffing models. Key priorities include constructing comprehensive DNA barcode reference libraries, aligning activities with biomonitoring needs and promoting FAIR and CARE data principles. We highlight strategies for capacity building, methodological standardisation and stakeholder engagement, alongside approaches for diversifying funding and strengthening communication. Based on these insights, we present ten practical recommendations to guide the establishment and long-term success of national DNA barcoding nodes. Strengthening these infrastructures will enhance Europe’s ability to deliver robust DNA-based biodiversity monitoring, underpin metabarcoding and metagenomic studies and contribute to global efforts in species discovery, conservation and environmental management.

As a part of the Gene Bank of the Republic of Srpska, within the Institute of Genetic Resources, University of Banja Luka, field collections of autochhthonous fruit and grape varieties serve as a valuable resource for diverse scientific research, experimental studies, measurements, and long-term monitoring. In ripening season of 2024, we counducted research on traditional autochthonous apple varieties. From field collections, we selected 3 apple accsessions with good yield potential, for sampling. The apple varieties included in this study were Bjeličnik, Vidovka žuta and Kanada Švabica.  After color analyses was done, we concucted analyses of antioxidant potential in samples. Methods used for color were the LAB digital color positioning system and for antioxidant potential, it was determined using the DPPH free radical sequencing method. Results showed that EC50 value of 18.60 mg/mL places 'Vidovka žuta' at the top of the studied varieties for antioxidant potential. 'Bjeličnik' is interesting variety in the pomology of Republika Srpska, named for its characteristic pale, almost white skin (EC50 =24.19 mg/mL). Kanada švabica showed EC50 of 31.87 mg/mL, and suggests a lower relative antioxidant potency compared to 'Vidovka žuta' and 'Bjeličnik'. Color showed that Bjeličnik is also significantly lighter than the others, confirming its phenotype as the "white" apple of the collection. Yellowness (b*) indicated that Vidovka žuta and Kanada švabica are statistically similar in their yellow intensity, while Bjeličnik is significantly less yellow. Traditional apples are a rich source of dietary antioxidants. The high uniformity in 'Bjeličnik' and the superior potency of 'Vidovka žuta' justify their use in breeding programs targeting increased functional value in modern apple cultivars.

In oral squamous cell carcinoma (OSCC) surgery, inadequate tumor margins are reported in up to 85% of cases, adversely affecting outcomes. In this prospective, single-center study (n = 31; NCT04191460), we evaluated the safety and imaging feasibility of cRGD-ZW800-1, a near-infrared fluorescent integrin-targeted tracer. The secondary objective was to determine whether intraoperative fluorescence imaging could identify inadequate resection margins and inform surgical decision-making. Patients received 0.01, 0.025, or 0.05 mg/kg cRGD-ZW800-1, and tracer uptake was quantified using in vivo multi-diameter single-fiber reflectance and single-fiber fluorescence spectroscopy to optimize dosing and timing. All doses were well tolerated, achieving tumor-to-background ratios exceeding 4.5, with optimal performance at 0.025 mg/kg. Fluorescence imaging detected all 23 inadequate margins, including nine undetected by conventional assessment (sensitivity 100% versus 70%), altered surgical plans in five cases, and avoided adjuvant radiotherapy in three cases. These findings demonstrate that cRGD-ZW800-1 is safe, tumor-specific, and facilitates intraoperative margin assessment in OSCC. Incomplete tumor removal during oral cancer surgery remains a major clinical challenge. Here, the authors show, in a feasibility trial, that fluorescence imaging using the integrin-targeted tracer cRGD-ZW800 is safe, achieved a patient-level sensitivity of 100%, enabled additional fluorescence-guided resections and prevented postoperative radiotherapy in some patients with oral squamous cell carcinoma.

Background Multimorbidity refers to the presence of multiple coexisting conditions, but is often underappreciated in the context of severe asthma (SA) management. We sought to identify differences in approaches to multimorbidity management in SA, variability in access to multidisciplinary team (MDT) resources, and whether physician perspectives on multimorbidity differ between SA specialists and general respiratory physicians. Methods The Severe Heterogeneous Asthma Registry, Patient-centred (SHARP) Clinical Research Collaboration circulated an online physician survey via European national respiratory societies to assess 1) available resources to address multimorbidity and 2) physician perspectives on multimorbidity in SA. Results 495 responses from 25 European countries included 48% SA specialists and 52% general respiratory physicians. SA specialists had more experience with SA patients (20% were seeing >60 patients per month) compared to general respiratory physicians. SA specialists had greater access to multidisciplinary care – including better access to MDTs, allied health professionals and referrals to external specialists, and therefore more routinely assessed comorbidities and considered them greater influences on their practice. They also considered multimorbidity to a greater degree and rated its impact on their patients’ asthma outcomes (and general health outcomes) as more substantial. Conclusions Alongside more experience of treating SA, SA specialists have increased awareness of multimorbidity and better resources to manage it. However, access to MDTs remains a significant gap for both SA specialists and general respiratory physicians. Furthermore, both groups identified a high need for further education and training about multimorbidity. These findings highlight key areas for improvement in clinical practice, resources and training.

Checkpoint inhibitor immunotherapy (CPI) for BRAF mutant advanced melanoma first-line results in a better long-term survival compared to targeted therapy (TT), however TT induction may benefit poor prognosis groups. The parallel-arm, randomised phase II, multicentre, feasibility CAcTUS trial (Clinicaltrials.gov NCT03808441) randomised 21 patients to receive standard of care investigators choice TT or CPI, switching to the alternative upon progression (n = 10), or commencing TT and switching to CPI upon an ≥80% reduction of BRAF variant allele frequency (VAF) in circulating tumour DNA (ctDNA; n = 11). The study achieved its primary endpoints with 100% (95% confidence interval [CI]: 94-100%) of critical results provided within 7 days to inform a decision to switch and 100% of patients commencing TT achieving an ≥80% reduction of BRAF VAF (95% CI: 80-100%). Secondary outcomes included progression-free survival and overall survival. No new safety signals were observed for TT/CPI. Post-hoc analysis of clinical features, circulating cytokines and chemokines at ctDNA nadir following TT induction suggested a more favourable profile prior to CPI initiation. Longitudinal ctDNA dynamics revealed ctDNA provided an early signal of CPI benefit and that rechallenge with TT following CPI progression resulted in a further ctDNA response. These data support the utility of ctDNA to guide treatment decision-making within a clinically relevant timeframe to optimise treatment scheduling strategies. Targeted therapy (with BRAF and MEK inhibitors) and immune checkpoint blockade have improved survival for patients with advanced BRAF-mutant cutaneous melanoma, however, the optimal scheduling for these treatments remain to be further refined in poor prognosis groups. Here the authors present the results of a feasibility trial to determine the role of circulating tumour DNA in guiding a switch between targeted therapy and immune therapy in patients with advanced melanoma.

Explainable AI (XAI) is crucial for fostering human trust in deep neural network (DNN) predictions, particularly in tasks like image classification. Multiple surveys exist on XAI methodologies, however, the practical usability and reproducibility of these methods remain largely unexplored. This paper addresses this gap by conducting a systematic survey of recent XAI papers published in leading computer vision and AI conferences and journals. We categorize these works, identify prevalent datasets and evaluation metrics, and analyse the associated code repositories. Our analysis reveals that almost 95% of the surveyed codebases are research prototypes rather than published releases, and a concerning majority of two‐thirds of them exhibit inconsistencies with their corresponding publications. These findings highlight the challenges in benchmarking new XAI methods against existing ones and explain the slow adoption of state‐of‐the‐art research in real‐world applications. This paper aims to underscore the importance of releasing well‐documented, readily usable code alongside XAI research to foster a more robust and reproducible ecosystem, ultimately facilitating the development and deployment of trustworthy AI systems. The results of this study are presented on an interactive website Interactive‐XAI.

Modern smart grids rely on dense measurement infrastructures, communication links, and intelligent field devices. Although this improves supervision and control, it also increases vulnerability to cyber-physical disruptions. Operators must distinguish physical incidents, such as faults or line disturbances, from malicious actions, such as false data injection or unauthorized command execution. This chapter investigates this problem using the well-known MSU/ORNL Power System Attack Dataset. The proposed method combines machine learning with genetic-algorithm-based feature selection. The objective is twofold: to classify attack and natural events accurately, and to determine whether a reduced set of physically informative PMU/IED measurements can support reliable detection. Several baseline models are evaluated, including logistic regression, RBF-SVM, XGBoost, Random Forest, and Extra Trees. The results show that tree-based ensemble models are the most effective for the considered dataset, with Extra Trees providing the strongest full-feature baseline. After feature selection, the GA + Extra Trees model reduces the clean PMU feature space from 112 attributes to an average of 27.4 attributes over five runs, while increasing macro-F1 from 0.9118 to 0.9212 and ROC-AUC from 0.9791 to 0.9837. These results indicate that many synchronized electrical measurements are redundant. A compact subset of phasor-based features can still provide accurate and interpretable anomaly detection in smart grids.

[This corrects the article DOI: 10.1371/journal.pone.0315011.].

The Kashmir issue is a long-standing international dispute with significant regional and global implications for contemporary relations, marked by episodic tensions, sovereignty questions, and humanitarian concerns. Despite decades of negotiations, sustained United Nations engagement, and bilateral dialogue, the issue remains unresolved, while the continued involvement of international regulatory systems reflects ongoing efforts to support regional stability and constructive dialogue. By revisiting Halford Mackinder’s Heartland theory, the paper highlights the strategic significance of Kashmir within the broader Asian geographical context and security dynamics. Located at the intersection of South Asia, Central Asia, and China’s western edge, Kashmir represents a crucial focal point for India and Pakistan, a condition that further contributes to the persistence and complexity of competing claims. Methodologically, the study uses a qualitative research design that combines analysis with contextual assessment. The methodological approach includes a review of classical geopolitical theory and an examination of Kashmir's strategic location between South and Central Asia. The findings highlight the enduring significance of Kashmir not only as a geographic and strategic pivot, but also as a region that exemplifies the complex interactions between regional actors and broader international dynamics. By integrating classical geopolitical insights with an understanding of contemporary strategic considerations, the paper provides a comprehensive perspective on why Kashmir continues to shape security, diplomacy, and strategic planning in Asia.