This short paper introduces an approach to simplifying cookie banners by utilising the concept of plain language within an existing consent framework. In order to study its feasibility, we present a study in which we analysed the text of cookie banners on 200 websites and, using AI-based categorisation, classified the extracted content into standardised processing purposes. By substituting complex legal terms with simplified descriptions, we successfully demonstrated that the comprehension barrier can be lowered from a college-graduate level to a 7th-grade level. At the same time our results indicate that the effectiveness of plain language is inherently constrained by the informativeness of the original content; it cannot compensate for banners that omit legally required details.

Pipe welding involves several sequential passes to create a perfect, strong weld. The welding passes refer to the order of execution required when carrying out the pipe welding process. The four passes typically used in pipe welding include the root pass, hot pass, fill-up pass and capping. Root Passes A root pass is the first step in any welding process and involves joining two pieces to form one structure. In this step, we heat the filler metal to an exceptionally high temperature and pass it through the gap between the pipes. Utilising the root pass requires more expertise than the following passes, so it is essential to exercise caution. To ensure complete fusion, the welder should use quality control measures like backing gas. In order to complete the weld pass, you must keep the root face smooth and uniform. If there are any imperfections on the weld face, you can correct them by grinding it out, so it does not have to be smooth or uniform initially. distribution of non-critical materials in industrial settings. People typically use it for transporting water, non-combustible chemicals, and other non-hazardous materials. Because its contents are not hazardous or flammable, low-pressure pipes provide a safe and cost-effective solution for many applications.

Objectives: Adult posterior cervical spinal dysraphism, including meningocele (MC), myelomeningocele (MMC), and myelocystocele (MyCC) is exceptionally rare and remains insufficiently characterised. This study aimed to conduct the first systematic review of the literature on adult cases and report an additional illustrative case. Methods: A PRISMA 2020 systematic review of PubMed/MEDLINE, Web of Science and Scopus was conducted (PROSPERO CRD420261426944). Data were extracted at case level, grouped by the lesion label used by the original authors, and synthesised narratively. Results: Nineteen studies (18 case reports and one case series) described 23 adults (median age 24 years; 19 male): 16 MC, one MyCC and six MMC. An objective neurological abnormality was documented in 14 of 21 examined patients. Nineteen patients were operated on; among 17 with a classified outcome, ten improved, five were intact and two were stable, and none were reported worse (median follow-up 12 months). The additional case was a 62-year-old man with a radiologically diagnosed C4–C5 lesion most consistent with MMC and no objective neurological deficit, managed by observation (3 months of follow-up). Conclusions: The evidence is sparse, heterogeneous and prone to publication bias, and it is insufficient to establish natural history, optimal management or the relative merits of surgery and observation. Standardised terminology, multicentre registries and long-term follow-up are needed.

Introduction: Acute ST-segment elevation myocardial infarction (STEMI) remains a major cause of cardiovascular morbidity and mortality. Despite successful primary percutaneous coronary intervention (pPCI), early myocardial injury and stress may contribute to left ventricular dysfunction. The optimal timing of biomarker assessment after STEMI remains uncertain. Objective: To characterize the early kinetics of soluble suppression of tumorigenicity-2 (sST2), galectin-3 (Gal-3), mid-regional pro-adrenomedullin (MR-proADM), and growth differentiation factor 15 (GDF-15) during the first 96 h after STEMI and identify potentially informative sampling time points for future prognostic assessment. Secondary, exploratory objectives were to evaluate differences in biomarker concentrations according to symptom duration, left ventricular ejection fraction (LVEF), and infarct-related artery. Methods: In this prospective, single-center, exploratory pilot study, patients aged 18–75 years with first STEMI treated with pPCI within 6 h of symptom onset were enrolled between September 2024 and November 2025. Blood samples were collected at admission and 12 ± 4, 24 ± 4, 48 ± 8, and 96 ± 8 h after pPCI. Biomarkers were measured by ELISA, with high-sensitivity cardiac troponin I (hs-cTnI) as a reference marker of myocardial injury. Results: Of 46 enrolled patients, 16 were excluded, mostly due to early discharge, and 30 patients with complete samples at all five time points were included in the analysis (mean age 57.9 ± 11.1 years; 66.7% male). sST2, MR-proADM, and hs-cTnI showed significant temporal variation (all p < 0.001), with the highest measured concentrations of sST2 at 12 h and of MR-proADM at 24 h. No significant change over time was found for Gal-3 and GDF-15. In exploratory analyses, sST2 and MR-proADM concentrations were higher in patients with LVEF < 40%, and sST2 concentrations were higher in patients with left anterior descending artery (LAD) infarction. Symptom duration was not associated with biomarker concentrations. Conclusions: sST2 and MR-proADM show distinct early post-STEMI kinetics, suggesting potentially informative sampling windows for future prognostic studies. Larger prospective studies are needed to confirm these kinetics and the exploratory differences according to left ventricular function and infarct location, and to evaluate the prognostic value of these sampling windows with echocardiographic and clinical follow-up.

Purpose To compare federated learning (FL) and centralized learning (CL) performance for brain tumor classification and segmentation and examine whether specific configurations confer measurable performance advantages. Materials and Methods In this systematic review and meta-analysis, Medline, EMBASE, PubMed, Web of Science, and Scopus were searched from inception to March 4, 2026. Classification accuracy was pooled using random-effects meta-analysis, with heterogeneity quantified using I2; other metrics were summarized descriptively. Paired differences in classification accuracy and Dice similarity coefficient (DSC) were assessed using the Wilcoxon signed-rank test. Mixed-effects meta-regression and subgroup analyses evaluated whether specific configurations were associated with performance differences. Results Of 3,880 records identified, 50 studies were included (26 classification/detection, 26 segmentation; 2 in both). Within-study differences between FL and CL performance were -0.87 percentage points (pp) for classification accuracy (95% CI [-3.32, +1.44]; P = .41, k = 13) and -1.29 pp for segmentation DSC (95% CI [-4.23, +0.81]; Holm-corrected P = .50, k = 11). In unmatched single-arm analyses, pooled classification accuracy was 96.77% for FL (k = 18) versus 96.86% for CL (k = 9); the pooled DSC for segmentation was 84.95% (k = 24) versus 84.61% (k = 11). Heterogeneity was high (I2=93.3-96.5%); the 95% prediction interval for FL accuracy was 86.72-100%. Aggregation strategy, training sample size, task category, and independent and identically distributed (IID) versus non-IID partitioning were not associated with performance differences (all P ≥ .38). Conclusion There was no evidence of paired differences between FL and CL in brain tumor classification accuracy or segmentation DSC, and no specific configuration conferred a measurable performance advantage. © RSNA, 2026.

Marketing of foods high in fat, sugar and salt shapes the food preferences and intake of children and adolescents. The primary aim of this study was to culturally adapt and validate the Scale of Effects of Social Media on Eating Behavior (SESMEB) for assessing the influence of social media on the eating habits of adolescents in the Republic of Srpska, Bosnia and Herzegovina, and to examine whether this influence differs by sex, place of residence, nutritional status and school attended. A cross-sectional study was conducted in six secondary schools in the city of Doboj in May 2023 and included 362 adolescents attending the third and fourth grades. The SESMEB scale was cross-culturally adapted into Serbian through forward and back-translation, expert panel review and pre-testing. Internal consistency was assessed by Cronbach’s alpha and corrected item-total correlations, the factor structure by exploratory factor analysis, and test–retest reproducibility in a subsample of 14 respondents by the intraclass correlation coefficient (ICC). Group differences were tested by t -test and ANOVA. The adapted scale showed good internal consistency (Cronbach’s alpha = 0.865), with corrected item-total correlations from 0.346 to 0.638; the data were suitable for factor analysis (KMO = 0.857; Bartlett’s test χ 2 (153) = 2312.380; p  < 0.001). Exploratory factor analysis identified three subscales accounting for 51.5% of the variance, which could not be clearly separated. Test–retest analysis showed no significant difference between administrations ( t  = 0.552; p  = 0.591; ICC > 0.7). Mean scores for all 18 items denoted no perceived influence, with 55.0–76.8% of respondents reporting no effect on their food-related attitudes and practices. Girls scored higher than boys for following nutrition-related content ( p  < 0.05) and for the increase in the desire to eat ( p  = 0.048); differences also emerged by place of residence ( p  = 0.041) and school attended ( p  = 0.008; p  = 0.004). Adopted version of the SESMEB scale is a reliable instrument for assessing the perceived effects of social media on adolescent eating behavior. Most respondents reported no such influence, even though this population is intensively exposed to digital marketing of energy-dense products, suggesting that self-report may underestimate the actual effect of that exposure.

Background/Objectives: Diabetic cardiomyopathy (DCM) is a major cardiovascular complication of diabetes mellitus characterized by progressive myocardial remodeling driven by oxidative stress, inflammation, and fibrosis. The interleukin-33 (IL-33)/soluble suppression of tumorigenicity 2 (sST2) signaling axis has recently emerged as an important regulator of cardiac remodeling and a potential therapeutic target in DCM. N-acetylcysteine (NAC) and glycine exhibit complementary antioxidant and anti-inflammatory properties; however, their combined effects on circulating IL-33 and sST2 levels and myocardial structural remodeling in experimental diabetes remain insufficiently investigated. This study evaluated the effects of NAC and glycine, administered alone or in combination, on oxidative stress, inflammatory biomarkers, cardiac morphology, and serum sST2 levels in streptozotocin-induced diabetic rats. Methods: Thirty-four adult Wistar rats were randomly assigned to five groups: healthy controls, untreated diabetic animals, diabetic animals treated with NAC (100 mg/kg/day), glycine (250 mg/kg/day), or combined NAC and glycine for 12 weeks. Diabetes was induced by a single intraperitoneal injection of streptozotocin (55 mg/kg). Serum concentrations of sST2, IL-33, malondialdehyde (MDA), and superoxide dismutase (SOD) activity were determined. Cardiac remodeling was evaluated by stereological and histopathological analyses. Results: Experimental diabetes significantly increased serum sST2, IL-33, and MDA concentrations and induced marked myocardial remodeling characterized by expansion of the interstitial and perivascular compartments, increased connective tissue deposition, and reduced cardiomyocyte volume density. Both NAC and glycine significantly attenuated these biochemical and structural abnormalities compared with untreated diabetic animals. Treatment effects varied across outcomes. The combined NAC and glycine regimen was associated with particularly pronounced reductions in sST2 and IL-33 and with preservation of myocardial architecture, whereas the magnitude of improvement in oxidative stress markers differed between treatment groups. Conclusions: NAC and glycine, administered either alone or in combination, attenuated several biochemical and structural alterations associated with streptozotocin-induced diabetes. The magnitude of these effects varied across the assessed outcomes, with the combined regimen showing particularly favorable effects on circulating sST2 and IL-33 levels and myocardial structural remodeling, while some oxidative stress parameters showed greater improvement with NAC monotherapy. These outcome-dependent effects highlight the potential complementary actions of NAC and glycine without implying uniform superiority of the combined regimen. Overall, these findings provide an experimental basis for further investigation of NAC- and glycine-based therapeutic approaches for diabetes-associated myocardial remodeling.

MicroRNAs (miRNAs) are key post-transcriptional regulators implicated in neuroinflammatory and neurodegenerative processes underlying multiple sclerosis (MS). This study aimed to identify candidate miRNAs associated with MS and investigate their involvement in disease-related molecular pathways. An integrated in silico workflow was used to identify MS-associated genes, predict regulatory miRNAs, and characterize enriched pathways. Candidate miRNAs were validated in serum EV-enriched fractions from treated and untreated MS patients and healthy controls using quantitative polymerase chain reaction (qPCR). In silico analysis prioritized four miRNAs (miR-204-5p, miR-17-5p, miR-21-5p, and miR-106a-5p) for validation. Their predicted target genes were enriched in pathways related to immune regulation and central nervous system function, including Th17 cell differentiation, MAPK signaling, cytokine signaling, and axon guidance. qPCR revealed significant differences in miR-21-5p and miR-106a-5p expression between MS patients and healthy controls, while miR-204-5p differed between untreated MS patients and healthy controls. Among the four miRNAs evaluated, miR-21-5p was significantly associated with MS status and showed moderate discrimination between MS patients and healthy controls (AUC = 0.7204). These findings identify serum EV-enriched miRNAs as candidate biomarkers of MS, although validation in larger and longitudinal cohorts is required.

BACKGROUND Irritable Bowel Syndrome (IBS) is heterogenous disorder of gut-brain interaction, with a key role for the dysregulated host-gut microbiota interplay. IBS subtyping is based only on symptoms of bowel habits, reflecting limited insight into underlying biological mechanisms. Aims: This study aimed to define microbiota-based IBS phenotypes and to compare these to traditional stool-based subtyping. Methods: The study utilised data from the Maastricht IBS cohort. Gut microbiota composition was analysed using shotgun metagenomic sequencing. Faecal volatile organic compounds (VOCs) were measured by gas chromatography mass spectrometry. Dietary intake and gastrointestinal and mental health symptoms were assessed using a food frequency questionnaire, the Dutch Healthy Diet-15 index, the Gastrointestinal Symptom Rating Scale, and Hospital Anxiety and Depression scores, respectively. Machine-learning approaches were applied to identify microbiota-based phenotypical clusters, which were compared with established Rome III subtypes, and associated with faecal VOCs, gastrointestinal symptom severity, diet and mental health. Results: 178 IBS patients and 134 healthy controls were included. Gut microbiota composition distinguished IBS patients from healthy controls with an AUCROC 0·8. This discriminatory profile was not associated with Rome III subtypes, while statistically significant associations were found with faecal VOCs profiles (i.e. R=0·67, p=4·46e-4) and symptom severity scores of abdominal pain (p=0·05), reflux (p=0·03), and diarrhoea (p=0·01) and depression (p<0·001). Dietary associations varied across clusters. Conclusion: These results suggest that gut microbiota profiling might provide a basis to define relevant IBS endotypes. Further exploration and validation efforts into this direction are needed using longitudinal studies to refine IBS patient stratification ultimately. .

The production of plum spirits is deeply rooted in the traditions of the Balkan countries, where it ranks among the most popular types of spirit. Various plum varieties are employed to achieve the most aromatic spirit possible. This study investigated the distribution of major and minor volatile compounds in plum distillates produced by blending two plum varieties, Stanley and Požegača. Two blending approaches were evaluated: (i) blending during fermentation and (ii) maceration of fresh Požegača fruit in raw Stanley distillate followed by redistillation. The varieties were combined in three ratios, 90:10, 70:30, and 50:50, with the aim of enhancing the plum aroma of the resulting spirits. Major volatile compounds were analysed by GC-FID, while minor volatile compounds were characterised using GC × GC-MS. All distillates exhibited typical profiles of major volatile compounds. Blending plum varieties proved to be an effective strategy for improving the flavour profile of plum spirits. The relative abundance of minor volatile compounds varied mainly according to plum variety and its proportion in the blend. Fermentation blending resulted in higher relative abundances of α-terpineol, heptanal, benzaldehyde, and γ-dodecalactone, whereas maceration increased the relative abundance of benzyl alcohol, 2-phenylethanol, octanoic acid, and (E)-β-damascenone. Even though maceration blending yielded elevated relative abundances of minor volatile compounds, it did not enhance the sensory qualities of the resulting spirits. Samples containing a higher proportion of Požegača were perceived as having greater aromatic and odour intensity than those containing Stanley. In contrast, the inclusion of Stanley resulted in a more favourable mouthfeel.

Chronic non-communicable diseases are highly prevalent in older women and are associated with unfavorable changes in body composition (BC). Physical literacy (PL) and physical activity (PA) are key determinants of healthy aging but it remains unclear whether chronic illness modifies not only their levels but also the structural relationships among PL, PA, and BC. This study aimed to examine differences in PL, PA, and BC between older women with- and without-chronic-illness and to compare the structural organization of associations among these variables in two observed groups. The sample included 60 women aged 66.1±9.6 years, categorized in two groups, those with- (n=36) and without-chronic-illness (n=24). PL, and PA were assessed using the validated questionnaires (Perceived Physical Literacy Questionnaire for South Eastern Europe, and Nordic Physical Activity Questionnaire – short version), and BC via bioelectrical impedance analysis. Between-group differences were examined using Welch’s t-tests with Cohen’s d effect size (ES). Pearson correlations were calculated separately by group, and Fisher’s z-tests with FDR correction were applied (91 comparisons). Correlation networks (|r|≥0.25) were constructed to assess cross-domain integration. Women with chronic illness demonstrated lower PL-competence (moderate ES) and higher PL-confidence and PL-knowledge, as well as higher moderate-to-vigorous PA (all moderate ES). No significant differences were observed in BMI, fat mass, skeletal muscle mass, or visceral fat. Prior to correction, PA showed stronger negative associations with fat mass (r=−0.54 vs. 0.11) and visceral fat (r=−0.55 vs. 0.04) in women without-, compared to women with-chronic-illness. Network analysis indicated reduced cross-domain integration between PA and BC in the chronic-illness group. Chronic illness in older women appears to modify the structural relationships among PL, PA, and BC rather than uniformly reducing their levels. The attenuated coupling between PA and BC suggests partial behavioral–physiological decoupling in the presence of chronic disease.

Intracranial aneurysm rupture is associated with substantial morbidity and mortality, yet aneurysm detection remains challenging, particularly for small lesions and on routine non-angiographic imaging examinations. To support the development and evaluation of artificial intelligence (AI) algorithms for intracranial aneurysm detection and localization, the Radiological Society of North America (RSNA), in collaboration with the American Society of Neuroradiology (ASNR), the Society of Neurointerventional Surgery (SNIS), and the European Society of Neuroradiology (ESNR), curated the RSNA Intracranial Aneurysm (RSNA-ICA) Dataset. Developed for the 2025 RSNA Intracranial Aneurysm Detection Challenge, RSNA-ICA is a large, publicly available, expert-annotated dataset comprising 7202 CTA, MRA, and MRI series from 4278 adult patients collected across 21 institutions in 12 countries spanning five continents. The dataset includes 2566 CTA, 2166 MRA, and 2470 MRI series from patients with and without intracranial saccular aneurysms, providing substantial geographic and imaging diversity. Expert annotations indicate both aneurysm presence and location, and 178 series additionally include three-dimensional segmentations of challenge-defined vascular locations. RSNA-ICA was used to develop and evaluate algorithms in the 2025 RSNA Intracranial Aneurysm Detection Challenge. Of the 7202 image series, 5041 are publicly available through MIRA, while the remainder were used for challenge public and private test sets. The dataset is freely available to the research community for noncommercial use and provides a comprehensive resource for advancing AI-based aneurysm detection across both angiographic and routine neuroimaging examinations.