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Background: This study evaluated the diagnostic effectiveness of the AIxURO platform, an artificial intelligence–based tool, to support urine cytology for bladder cancer management, which typically requires experienced cytopathologists and substantial diagnosis time. Methods: One cytopathologist and two cytotechnologists reviewed 116 urine cytology slides and corresponding whole‐slide images (WSIs) from urology patients. They used three diagnostic modalities: microscopy, WSI review, and AIxURO, per The Paris System for Reporting Urinary Cytology (TPS) criteria. Performance metrics, including TPS‐guided and binary diagnosis, inter‐ and intraobserver agreement, and screening time, were compared across all methods and reviewers. Results: AIxURO improved diagnostic accuracy by increasing sensitivity (from 25.0%–30.6% to 63.9%), positive predictive value (PPV; from 21.6%–24.3% to 31.1%), and negative predictive value (NPV; from 91.3%–91.6% to 95.3%) for atypical urothelial cell (AUC) cases. For suspicious for high‐grade urothelial carcinoma (SHGUC) cases, it improved sensitivity (from 15.2%–27.3% to 33.3%), PPV (from 31.3%–47.4% to 61.1%), and NPV (from 91.6%–92.7% to 93.3%). Binary diagnoses exhibited an improvement in sensitivity (from 77.8%–82.2% to 90.0%) and NPV (from 91.7%–93.4% to 95.8%). Interobserver agreement across all methods showed moderate consistency (κ = 0.57–0.61), with the cytopathologist demonstrating higher intraobserver agreement than the two cytotechnologists across the methods (κ = 0.75–0.88). AIxURO significantly reduced screening time by 52.3%–83.2% from microscopy and 43.6%–86.7% from WSI review across all reviewers. Screening‐positive (AUC+) cases required more time than negative cases across all methods and reviewers. Conclusions: AIxURO demonstrates the potential to improve both sensitivity and efficiency in bladder cancer diagnostics via urine cytology. Its integration into the cytopathological screening workflow could markedly decrease screening times, which would improve overall diagnostic processes. By using The Paris System for Reporting Urinary Cytology criteria, the AIxURO tool increased sensitivity and negative predictive value for atypical urothelial cell–positive (AUC+) bladder cancer cases in urine cytology while reducing screening time. The increase in detected positive (AUC+) cases suggests that further study is needed to address the potential increase in false positives. [ABSTRACT FROM AUTHOR]

Background: Patients undergoing radiation therapy (RT) often experience anxiety, which may jeopardize the treatment success. The efficacy of music interventions in reducing anxiety remains contentious. This randomized trial aimed to evaluate the impact of music listening on anxiety symptoms in patients undergoing initial RT. Methods: First-time RT patients were randomly allocated to experimental and control groups. The Brief Symptom Rating Scale (BSRS-5), Distress Thermometer (DT), and Beck Anxiety Inventory (BAI-C) were administered pre- and post-RT. Changes in physiological anxiety symptoms were monitored over 10 consecutive days starting from the first day of RT. The experimental group received music during RT; the control group did not. The generalized linear mixed model was used to estimate the pre–post difference in the BSRS-5, DT, and BAI-C scores between the music intervention and control group. Results: This study included 50 patients each in the experimental and control groups. BSRS-5 and DT scores were significantly reduced in the experimental group post-RT (p = 0.0114 and p = 0.0023, respectively). When music listening was discontinued, these scores rebounded. While the posttest BAI-C score was significantly lower in the experimental group (p < 0.0001), the pre–post difference between the two groups was not significant (p = 0.0619). On cessation of music listening, the BAI-C score also rebounded. Conclusions: For cancer patients undergoing initial RT, music listening intervention significantly reduced anxiety symptoms measured using the BSRS-5, DT, and BAI-C scores after two weeks. Our results demonstrate the effectiveness of music listening intervention in reducing anxiety symptoms, thereby potentially improving the quality of life of cancer patients undergoing RT. [ABSTRACT FROM AUTHOR]

Highly pathogenic avian influenza (HPAI) is an important zoonotic disease. The study aims to identify farmer behaviour types to inform the design of behaviour change programmes for mitigating the transmission of HPAI. Therefore, the study utilised multivariate statistical analysis for gaining a better understanding of the relationships among farmers' 30 biosecurity behaviours, the risk of HPAI infection, and distinct features of commercial broiler farmers, which is different from using simple and few binary biosecurity measures. Convenience sampling was used to collect data from 303 Taiwan's farmers among which 40 farmers (13.2%) self-reported having had a HPAI outbreak in the study year while 16 farmers (5.3%) self-reported having had a HPAI outbreak in the past two years. Using categorical principal components analysis and a two-stage cluster analysis, four farmer clusters were identified with distinct features: 1)'Reserved' (4.6%) tended to choose 'No idea' for answering specific questions about HPAI; 2)'Secure' (76.3%) had a higher biosecurity status than the other farms; 3) 'Jeopardised' (16.8%) had a lower biosecurity status than the other farms; 4) 'No-response' (2.3%) tended to skip specific questions about HPAI. The biosecurity status of the 'Reserved' and 'No-response' clusters was undetermined, placing these farms at risk of HPAI infection. Compared to the 'Secure' cluster, the 'Jeopardised' cluster exhibited higher odds of self-reported HPAI in the study year (OR: 2.61, 95% CI: 1.22-5.58) and in the past two years (OR: 4.28, 95% CI: 1.39-13.19). Additionally, the 'Jeopardised' cluster showed increased odds of HPAI recurrence (OR: 4.01, 95% CI: 1.41-11.43). Our study demonstrates that inadequate biosecurity practices can elevate the occurrence or recurrence of HPAI outbreaks. The findings underscore the importance of distinguishing between these clusters to accurately assess the risk of HPAI infection across farms. Furthermore, understanding farmers' behaviours can inform the development of strategies aimed at behaviour change among farmers., Competing Interests: The authors declare that the research was conducted in absence of any commercial, financial, or other relationships that might be interpreted as representing a potential conflict of interest., (© 2024 The Authors. Published by Elsevier B.V.)