Background: Laryngeal cancer represents a significant global health burden with early detection being crucial for improved patient outcomes. The integration of artificial intelligence (AI) into medical diagnostics has shown tremendous potential in enhancing the accuracy and efficiency of laryngeal cancer detection through endoscopic image analysis. Objective: This narrative review comprehensively examines the current state of AI applications in laryngeal cancer diagnosis using endoscopic imaging, focusing on deep learning methodologies, diagnostic performance, clinical validation and future perspectives. Methods: A systematic analysis of peer-reviewed literature was conducted, examining studies published between 2016 and 2025 that investigated AI-based approaches for laryngeal cancer detection and classification using endoscopic images. The review encompassed various AI techniques including convolutional neural networks (CNNs), transfer learning, multimodal approaches and novel architectures applied to white light imaging, narrow-band imaging and other advanced endoscopic modalities. Results: Current AI systems demonstrate remarkable diagnostic accuracy with sensitivity ranging from 71-98% and specificity from 86-98% across different studies and methodologies. Deep learning approaches, particularly CNNs such as ResNet, DenseNet, and YOLO architectures, have shown performance comparable to or exceeding that of experienced clinicians. Multimodal AI systems combining white light and narrow-band imaging data achieve superior performance compared to single-modality approaches. Real-time processing capabilities with inference times as low as 0.01-0.03 seconds per image enable practical clinical implementation. Conclusions: AI-assisted endoscopic diagnosis represents a transformative technology for laryngeal cancer detection, offering the potential to standardize diagnostic protocols, reduce inter-observer variability and improve access to expert-level diagnostic capabilities globally.

Objectives: Chronic Rhinosinusitis (CRS) is a common inflammatory disease impacting 5-12% of the population, leading to substantial morbidity and healthcare expenses. Bacterial biofilms on the sinonasal mucosa are a key factor in CRS's development, persistence, and resistance to treatment. This review explores their role in refractory CRS, focusing on structure, formation, impact on severity, and diagnostic/therapeutic approaches. Methods: We conducted a comprehensive literature review using PubMed, Scopus, and Web of Science, searching for keywords related to CRS, bacterial biofilms, antibiotic resistance, and therapies. We prioritized studies from the last decade examining biofilms' impact on CRS pathogenesis, resistance, and novel treatments. Key findings: Biofilms, organized microbial communities within an extracellular polymeric matrix, are significantly more resistant to antibiotics and host immune responses than free-floating bacteria. They form through stages: initial attachment, proliferation, and complex 3D structure development, with quorum sensing vital for maturation. Common CRS biofilm pathogens include Staphylococcus aureus, Pseudomonas aeruginosa, and Haemophilus influenzae. Biofilms correlate with more severe disease, poorer surgical outcomes, and higher recurrence. Diagnostics include electron microscopy, confocal laser scanning microscopy (CLSM), and molecular methods. Treatment involves surgical removal, topical antibiotics, and novel strategies like phage therapy, quorum sensing inhibitors, and micro-biome-based interventions. Conclusions: Biofilms are critical in refractory CRS, causing persistence, treatment resistance, and worse outcomes. A deep understanding of biofilm mechanisms is crucial for effective diagnostics and therapies. Future research should standardize diagnostics, clarify biofilm-host interactions, and conduct trials on new, personalized biofilm-targeting treatments.

Increasing exposure to blue light is a major problem in the modern lifestyle of individuals. The increasing use of digital devices and LED lighting is recognised as a major environmental factor affecting human health. While it has a positive effect on alertness during the day, excessive or late-night exposure disrupts the circadian rhythm by affecting the intrinsically photosensitive retinal ganglion cells (ipRGCs), which regulate melatonin secretion and the sleep-wake cycle. The main negative consequences of evening blue light exposure include: disrupted sleep architecture, particularly by reducing slow-wave and REM sleep, which are essential for recovery processes, impaired cognitive performance, increased daytime sleepiness and a higher risk of mood disorders, including depression and anxiety. Interventions and prevention strategies aimed at reducing evening blue light (through filters, night mode settings or glasses) and morning exposure to bright light have been shown to be beneficial for sleep quality, circadian phase regulation and mood stabilisation. Despite progress in this area, there are still significant research gaps, particularly in relation to individual differences in light sensitivity, long-term effects and the optimal timing and intensity of interventions. This review summarises the latest results of 33 studies and provides a structured overview of the current evidence on the short- and long-term effects of blue light on circadian rhythms, sleep and mental health. It highlights practical measures to minimise harmful exposure suggesting the directions for future research to promote circadian health and general well-being in the context of modern lifestyles.

Background/Objectives: Along with cardiovascular disease, cancer is the leading cause of death worldwide. The aim of the study was to compare the clinical and echocardiographic characteristics of atrial fibrillation (AF) among patients with active cancer (study group) and those without cancer (control group). Methods: This retrospective study included patients diagnosed with both AF and active cancer referred for consultation to the Cardiac Arrhythmias Outpatient Clinic at our institution in 2022. They were matched in a 1:1 ratio, by age and sex to patients with AF without cancer. The matching criteria for the study and control groups were limited to age and gender. Variables such as comorbidities, atrial fibrillation duration, tumor stage, and treatment were not included in the matching criteria. Results: We examined 216 patients, 57.4% of whom were men. There were 110 patients in the study group with a mean age of 70 (10) years. Several parameters in the study group attracted our particular attention: N-terminal pro-B-type natriuretic peptide (NT-proBNP) was lower (703 pg/mL vs. 1549 pg/mL, p = 0.01), echocardiography revealed smaller left atrial size (43 (6) mm vs. 47 (7) mm, p = 0.015), left ventricular (LV) diastolic dimension (49 mm vs. 52 mm, p = 0.009) and better LV systolic function expressed as LV ejection fraction (54% (9%) vs. 51% (12%), p = 0.025), and global longitudinal strain (−16% (4%) vs. −13% (3%), p = 0.016). Antiarrhythmic pharmacotherapy was used less frequently in the study group, which may also have been due to physicians’ reluctance to treat AF aggressively in a more morbid population. Conclusions: Patients with cancer and atrial fibrillation may have a different clinical profile, suggesting a different pathophysiology. Understanding these differences may help reduce the incidence of AF and improve patient outcomes and prognosis during cancer treatment.

Sleep plays an essential role in physical recovery, cognitive readiness and overall performance in athletes. However, this particular group frequently experiences sleep architecture disruption. Problems may include shortened, irregular and disturbed sleep due to late training sessions, competition stress, travel across time zones and simultaneous demands of academics and sport. This narrative review integrates findings from research conducted between 2020 and 2025 examining sleep duration, sleep quality and evidence-based strategies to enhance sleep among athletes. In the article, we try to identify major influences on sleep quality, ranging from behavioral factors (evening screen use, consumption of caffeine and meal timing) to environmental factors (light, noise, temperature) and biological rhythms (chronotype, social jetlag and delayed bedtimes). We analyze current approaches to monitoring sleep pointing out strengths and limitations of technologies such as polysomnography, actigraphy, EEG head bands, wearables and subjective questionnaires (PSQI and ESS). Focusing on recovery, in the article we discuss objective markers of sleep including HRV (heart rate variability), resting heart rate, sleep latency. We describe effective sleep-optimization strategies for athletes and other groups vulnerable to sleep deprivation. The methods include light-based protocols, environmental adjustments, nutritional timing, supplementation (melatonin, tryptophan) and training and recovery scheduling. Overall, the findings emphasize that sleep is a critical and modifiable determinant of athletic success. There is a complex and integrated relationship between sleep, recovery and daily performance that can be enhanced and cared for by sleep hygiene practices, scheduling training according to individual chronotypes and using multimodal physiological monitoring.

Objectives: Syncope in athletes presents a complex diagnostic challenge requiring systematic evaluation to differentiate benign neurally-mediated causes from potentially life-threatening cardiac conditions. Unrecognized cardiovascular disease in athletes can lead to sudden cardiac death, making accurate risk stratification essential for athlete safety and appropriate return-to-play decisions. We aim to provide a comprehensive synthesis of current evidence regarding the indications, protocols, diagnostic yield, and limitations of exercise stress testing in athletes presenting with syncope. Methods: We conducted a narrative literature review of PubMed databases from 2004-2025, focusing on studies involving athletic populations and recent consensus statements from major cardiovascular and sports medicine organizations. Evidence was synthesized from observational studies, clinical guidelines, and expert consensus documents. Key findings: Exercise stress testing is strongly recommended for all athletes with exertional syncope, with sport-specific, maximal-effort protocols yielding arrhythmic or ischemic findings in 15-25% of cases. Negative predictive values approach 95% when proper protocols are employed, significantly reducing the probability of exercise-induced life-threatening events, though residual risk remains. Current evidence supports individualized testing protocols rather than generic clinical protocols designed for ischemia detection. Integration with comprehensive clinical assessment, ECG, echocardiography, and risk factor evaluation optimizes diagnostic accuracy and clinical decision-making. Conclusions: Sport-specific, effortful exercise stress testing serves as a pivotal diagnostic tool and safety gatekeeper in athletic syncope evaluation. When integrated within systematic algorithms it enables accurate risk stratification, specialist referral, and evidence-based return-to-play decisions. Future research should focus on protocol validation, long-term outcome studies, and integration of emerging technologies for further enhancement of diagnostic precision.