University of Missouri System

Purpose: Sleep-related symptoms in head and neck cancer are poorly characterized and often under-recognized. We examined symptom trajectories, prevalence of moderate/severe symptoms, and associations between severe sleep-related patient-reported symptoms and overall survival (OS) in oropharyngeal cancer (OPC) patients receiving radiotherapy (RT). Methods: This retrospective analysis included a longitudinal cohort of 372 patients with OPC treated with curative-intent RT (+/- chemotherapy) at a tertiary center. Symptoms were assessed at the earliest available preRT baseline, RT start, RT end, and 6 months post-RT using the MD Anderson Symptom Inventory-Head and Neck (MDASI-HN). The sleep-related symptom domains were fatigue, sleep disturbance, and drowsiness. OS was evaluated using Kaplan-Meier and multivariable Cox models. Results: Severe fatigue, sleep disturbance, and drowsiness were infrequent at baseline but peaked at RT end (26%, 15%, and 18%, respectively) and returned to near-baseline levels by 6 months (6%, 4%, and 2%). Severe longitudinal fatigue (HR 5.05), sleep disturbance (HR 3.86), and drowsiness (HR 8.24) were independently associated with worse OS. Severe symptoms at RT start were also associated with worse OS (fatigue HR 3.58; sleep disturbance HR 5.08; drowsiness HR 7.76; all p < 0.05). Aside from age, severe average daily symptom scores and severe symptoms at RT start were associated with OS after multivariable adjustment. Conclusion: Severe sleep-related symptoms peaked during RT. Severe fatigue, sleep disturbance, and drowsiness, both longitudinally and at RT start, were associated with worse OS. These observational associations do not establish causality; symptom assessment may help identify patients who warrant supportive evaluation.

Solar-driven catalytic decontamination of emerging organic pollutants is of significance for achieving environmental sustainability. The cardinal challenges in this technology are swift charge carrier reunion, weak redox capability and poor sunlight utilization capacity of photocatalysts. Here, an innovative Ag/Ag2 O/C3 N5 S-scheme heterojunction photocatalyst with plasmonic effect was developed for antibiotic decontamination by coating Ag/Ag2 O nanodots on the surface of C3 N5 nanosheets. The localized surface plasmon resonance (LSPR) effect from Ag nanodots augments sunlight response and exciton production. Meanwhile the "nanodots-on-nanosheets" 0D/0D/2D heterostructure with a plasmonic S-scheme interface significantly boosts separation and utilization of highly energetic photo-carriers. As a result, the optimized Ag/Ag2 O/C3 N5 demonstrates extraordinary stability and achieves a photocatalytic levofloxacin removal rate constant of 0.0278 min-1 , which is about 3.9-, 11.6-, and 1.9-fold greater than that of Ag2 O, C3 N5 , and Ag2 O/C3 N5, respectively. The photocatalytic decontamination mechanism and degradation route of levofloxacin over Ag/Ag2 O/C3 N5 are elucidated using LC-MS analysis and DFT calculation. This research highlights the potential of LSPR modulated S-scheme heterojunctions as robust photocatalysts for wastewater decontamination, paving the way for innovative solutions to environmental pollution challenges. (c) 2025 Published by Elsevier Ltd on behalf of The editorial office of Journal of Materials Science & Technology.

Introduction Proteinuria is a modifiable risk factor for chronic kidney disease (CKD) progression in children. Finerenone, a selective, non-steroidal, mineralocorticoid receptor antagonist (MRA) has been approved to treat adults with CKD associated with type 2 diabetes mellitus (T2DM) following results from the phase III clinical trials FIDELIO-DKD (NCT02540993) and FIGARO-DKD (NCT02545049). In a pre-specified pooled analysis of both studies ( N = 13,026), finerenone was shown to have an acceptable safety profile and was efficacious in decreasing the risk of adverse kidney and cardiovascular outcomes and of proteinuria. Objective FIONA and the associated open-label extension (OLE) study aim to demonstrate that combining finerenone with an angiotensin-converting enzyme inhibitor (ACEi) or angiotensin receptor blocker (ARB) is safe, well-tolerated, and effective in sustainably reducing urinary protein excretion in children with CKD and proteinuria. Design FIONA (NCT05196035; Eudra-CT: 2021–002071-19) is a randomized (2:1), double-blind, placebo-controlled, multicenter, phase III study of 6 months’ duration in approximately 219 pediatric patients. Patients must have a clinical diagnosis of CKD (an eGFR ≥ 30 mL/min/1.73 m 2 if ≥ 1 to < 18 years or a serum creatinine level ≤ 0.40 mg/dL for infants 6 months to < 1 year) with significant proteinuria despite ACEi or ARB usage. The primary objective is to demonstrate that finerenone, added to an ACEi or ARB, is superior to placebo in reducing urinary protein excretion. FIONA OLE (NCT05457283; Eudra-CT: 2021–002905-89) is a single-arm, open-label study, enrolling participants who have completed FIONA. The primary objective of FIONA OLE is to provide long-term safety data. FIONA has two primary endpoints: urinary protein-to-creatinine ratio (UPCR) reduction of ≥ 30% from baseline to day 180 and percent change in UPCR from baseline to day 180. A sample size of 198 participants (aged 2 to < 18 years) in FIONA will provide at least 80% power to reject the null hypothesis of either of the two primary endpoints. Conclusion FIONA is evaluating the use of finerenone in children with CKD and proteinuria. Should safety, tolerability, and efficacy be demonstrated, finerenone could become a useful additional therapeutic agent in managing proteinuria and improving kidney outcomes in children with CKD. Trial registration ClinicalTrials.gov NCT05196035. Registered on 19 January 2022.

This study evaluates the effect of two different quench practices on distortion, sensitivity to quench cracking, development and distribution of residual stress, microstructural uniformity, and hardenability of standardized test castings. Navy C-rings made of AISI 4340 were quenched in this experiment. Some rings were quenched in a conventional draft tube immersion quench bath, and others were quenched in an intensive quench spray system to compare with the results from the conventional immersion quench bath. The rings were measured with a coordinate measuring machine, for distortion and flatness, before and after quenching. Hardness profiles of the quenched rings showed through hardness of 57.0-59.0 HRC, and the microstructures were largely martensitic. DANTE modeling software was used to predict the quenched properties of the rings, simulating microstructural transformation and residual stresses for each quench practice. XRD was used to measure surface residual stress distribution of the quenched rings, and results were compared to the predicted values by the modeling software. The surface residual stress was tensile for the conventional immersion quench and compressive for the intensive spray quench. Crack initiation correlated to areas of large tensile stress concentration and microstructural heterogeneity.

Most artificial intelligence (AI) research in radiology has focused on adults. Understanding macro-level trends in pediatric radiology AI can help guide, streamline, and bolster future research. To detail the current landscape of published AI research in pediatric radiology, filling a key research gap, as most radiology AI research has focused on adults. We conducted a scoping review, with a comprehensive literature search of Medline, Embase, Web of Science, and Cochrane Library from 2005 to 2024. Literature included for review were (1) original articles, (2) investigations that focused on pediatric populations (<18 years of age), and (3) articles with direct applications to clinical radiology and AI. We extracted each article’s study information, clinical application of focus, imaging modality, and the use of AI. We used descriptive frequencies to analyze summary statistics, and Chi-square testing to determine differences between categories. In total, we found 4,376 articles and included 789 articles in the review. The top three countries most active in scholarship related to AI in pediatric radiology were China (220, 27.9