Search Results (1,197)

Objectives: The purpose of the current research is to examine and analyze the attitudes of healthcare service users towards the integration of remote medical services into ophthalmology in Bulgaria, including teleglaucoma. Methods: A cross-sectional survey study was conducted among 902 healthcare users during the period from May 2023 until December 2024. Descriptive statistics, parametric, and non-parametric tests for hypothesis testing were used. Results: The present study outlined predominantly positive attitudes towards the use of telemedicine services in ophthalmology, with 69.6% of respondents reporting a positive overall opinion in the final assessment. The greatest support was observed during remote consultations with a familiar doctor (77.4%) and during continuous follow-up of eye conditions (55.2%). Willingness to use such services was lower in emergencies or when contacting an unfamiliar specialist. A significant correlation was established between socio-demographic characteristics and attitudes—respondents with greater education levels (p = 0.006), men, and younger participants were more positive towards telemedicine (p < 0.05). The high level of awareness about glaucoma, particularly among those with university-level education, served as a positive prerequisite for the implementation of teleophthalmology services related to its monitoring. Mobile applications and digital solutions were evaluated as beneficial means of facilitating communication and increasing adherence to treatment. Regarding the use of artificial intelligence, certain skepticism and insufficient awareness levels were observed, which required additional efforts to increase trust and digital literacy among users. Conclusions: The implementation of telemedicine services into ophthalmology has potential but outlines the necessity of considering the individual attitudes of applying coherent quality and safety standards and of directed awareness campaigns, especially towards the groups of lower technological and healthcare literacy. Full article

Background: Viral respiratory tract infections (RTIs) frequently lead to emergency department (ED) presentations and hospital admissions, particularly among older adults and individuals with underlying health conditions. Identifying patients at increased risk for hospitalization is essential for optimizing triage and resource allocation. This study aimed to determine independent demographic, clinical, and virological predictors of hospital admission among adults presenting with confirmed viral RTIs. Methods: A retrospective cohort study was conducted at a tertiary hospital between September 2022 and May 2024. Adult patients with molecularly confirmed viral RTIs were included. Demographic, clinical, and microbiological data were extracted from electronic medical records. Predictors of admission were assessed using univariate and multivariate logistic regression. Results: Among 311 patients, 147 (47.3%) required hospitalization. Hospitalized patients were significantly older and more likely to present with fever, cough, tachypnea, dyspnea, chest pain, comorbidities, and lower or mixed respiratory tract infections (all p < 0.001). In multivariate analysis, older age, fever, cough, and lower or mixed RTIs were strong independent predictors of admission. Several viral pathogens, including human rhinovirus, non–SARS-CoV-2 coronaviruses, influenza A, and parainfluenza virus, were associated with reduced odds of hospitalization. Conclusions: Age, comorbidity burden, and lower respiratory tract involvement are key determinants of hospitalization in viral RTIs. Integrating clinical and virological data may improve risk stratification and guide ED triage during seasonal and emerging respiratory virus activity. Full article

Major traumas result from the application of multiple force components that, in adulthood, can lead to high mortality and morbidity. In forensic practice, pathological consequences arising from the rapid flexion–extension of an adult victim’s soma are observed, with typical intracranial and ophthalmological findings. The totality of these findings allows for a contribution to the definition of the Shaken Adult Syndrome (SAS). A comprehensive review, employing the PRISMA methodology, was conducted on international works pertaining to SAS. This resulted in the identification of six scientific papers, which were analyzed separately. It emerged that, for the diagnosis of SAS, the same diagnostic triad as Shaken Baby Syndrome is valid, comprising subdural hemorrhages, retinal hemorrhages, and encephalopathy. This syndrome appears to encompass a broad spectrum of pathological conditions, ranging from whiplash to diffuse axonal injury (DAI). At the conclusion of this work, we proposed a diagnostic flowchart that allows for suspected predictive diagnosis of SAS, both in live patients presenting to emergency medical services and in post-mortem cadavers. For this purpose, the collection of anamnesis and circumstantial data, the detection of external injuries, and the execution of cranial CT scans will be essential. Ultimately, microscopic examinations of the brain with specific immunomarkers and of ocular structures will enable the identification of pathognomonic findings for SAS. Full article

Ionic liquids (ILs) have emerged as multifunctional compounds with low volatility, high thermal stability, and tunable solvation capabilities, making them highly promising for biomedical applications. First explored in the late 1990s and early 2000s for enhancing the thermal stability of enzymes, antimicrobial agents, and controlled release systems, ILs have since gained significant attention in drug delivery, antimicrobial treatments, medical imaging, and biosensing. This review examines the diverse functions of ILs in contemporary therapeutics and diagnostics, highlighting their transformative capabilities in improving drug solubility, bioavailability, transdermal permeability, and pathogen inactivation. In drug delivery, ILs improve solubility of bioactive compounds, with several IL formulations achieving substantial solubility enhancements for poorly soluble drugs. Bio-ILs, in particular, show promise in enhancing drug delivery systems, such as improving transdermal permeability. ILs also exhibit significant antimicrobial and antiviral activity, offering new avenues for combating resistant pathogens. Despite their broad potential, challenges such as cytotoxicity, long-term metabolic effects, and the stability of ILs in physiological conditions persist. While much research has focused on their physicochemical properties, biological activity and in vivo studies are still underexplored. The future directions for ILs in biomedical applications include the development of bioengineered ILs and hybrid ILs, combining functional components like nanoparticles and polymers to create multifunctional materials. These ILs, derived from renewable resources, show great promise in personalized medicine and clinical applications. Further research is necessary to evaluate their pharmacokinetics, biodistribution, and long-term safety to fully realize their biomedical potential. This study emphasizes the potential of ILs to transform therapeutic and diagnostic technologies by highlighting present shortcomings and offering pathways for clinical translation, while also debating the need for continuous research to fully utilize their biomedical capabilities. Full article

The early diagnosis and treatment of civilizational diseases remain a significant challenge worldwide. Although advances in medical technology have led to the introduction of more screening options over time, these measures are still insufficient to effectively reduce mortality from deadly diseases such as lung cancer (LC), cardiovascular diseases (CVD), diabetes, and chronic obstructive pulmonary disease (COPD). These conditions pose a major public health burden, underlying the urgent need for more comprehensive and efficient prevention strategies. Recently, the concept of ‘multiscreening’ has emerged as a promising approach. Multiscreening involves the simultaneous screening for multiple diseases using integrated diagnostic methods, potentially improving early detection rates and optimizing resource utilization. In 2024, Rzyman W. et al. launched the MULTIPREVENT epidemiological study, which aims to develop and validate a low-dose computed tomography (LDCT)-based screening test for civilizational diseases. This study represents a step forward in the pursuit of more effective, minimally invasive diagnostic tools that could facilitate earlier intervention and improve patient outcomes. To better understand the potential of multiscreening approaches and their clinical utility, it is essential to evaluate the existing predictive models used for identifying individuals at high risk for these diseases. This narrative review focuses primarily on lung cancer risk prediction models used in LDCT screening while situating these approaches within the broader conceptual framework of the MULTIPREVENT project, aimed at future integration of multi-disease prevention strategies. With this analysis, we aim to provide insights that will guide the development of more accurate, integrative screening tools that could reduce the global burden of these diseases. Full article

Exercise-induced myokines have emerged as crucial mediators of the beneficial effects of physical activity on neurodegenerative diseases through complex molecular mechanisms involving oxidative stress reduction, neuroinflammation suppression, and synaptic plasticity enhancement. Among these myokines, irisin, encoded by the FNDC5 gene, has gained significant attention as a potential therapeutic target in neurodegenerative conditions due to its ability to cross the blood–brain barrier and exert pleiotropic neuroprotective effects. This review synthesizes current evidence from both preclinical and clinical studies examining the role of exercise-induced irisin in neurodegeneration, with particular emphasis on translational potential and therapeutic applications. A comprehensive search was conducted across PubMed, Web of Science, Scopus, and EMBASE databases (spanning January 2015 to December 2024) to identify peer-reviewed articles investigating irisin’s neuroprotective mechanisms in neurodegenerative diseases. Ten studies met the inclusion criteria (five rodent/primate model studies and five human clinical investigations), which were analyzed for methodological rigor, intervention protocols, biomarker quantification methods, and reported outcomes. Reviewed studies consistently demonstrated that exercise-induced endogenous irisin elevation correlates with improved cognitive function, reduced neuroinflammatory markers, enhanced synaptic plasticity, and modulation of neurodegenerative pathways, with exogenous irisin administration reproducing several neuroprotective benefits observed with exercise training in animal models. However, substantial heterogeneity exists regarding exercise prescription parameters (intensity, duration, frequency, modality), training-induced irisin quantification methodologies (ELISA versus mass spectrometry), and study designs (ranging from uncontrolled human observations to randomized controlled trials in animal models). Critical appraisal reveals that human studies lack adequate control for confounding variables including baseline physical fitness, comorbidities, concurrent medications, and potential sources of bias, while biochemical studies indicate distinct pharmacokinetics between endogenous training-induced irisin and exogenous bolus dosing, necessitating careful interpretation of therapeutic applicability. The translational potential of irisin as a therapeutic agent or drug target depends on resolving methodological standardization in biomarker measurement, conducting well-designed clinical trials with rigorous control for confounders, and integrating findings from molecular/biochemical studies to elucidate mechanisms linking irisin to disease modification. Future research should prioritize establishing clinical trial frameworks that harmonize exercise prescriptions, employ robust biomarker quantification (mass spectrometry), and stratify participants based on disease stage, comorbidities, and genetic predisposition to clarify irisin’s role as a potential therapeutic intervention in neurodegenerative disease management. Full article

Background/Objective: Glucagon-like peptide-1 receptor agonists (GLP-1RAs) have received widespread attention as effective obesity treatments. However, limited research has examined the perspectives of patients contemplating GLP-1RAs. This study explored perceptions, motivations, and barriers among individuals considering GLP-1RA therapy for obesity treatment, with the goal of informing patient-centered care and enhancing clinician engagement. Methods: Adults completed surveys and interviews between June and November 2025. In this pragmatic mixed-methods study, both survey and interview questions explored perceived benefits, barriers, and decision-making processes. Qualitative data, describing themes based on the Health Belief Model, were analyzed using Dedoose (version 9.0.107), and quantitative data were analyzed using SAS (version 9.4). Participant characteristics included marital status, income, educational attainment, employment status, insurance status, age, race/ethnicity, and sex. Anticipated length on GLP-1RA medication and selected self-reported health conditions (depression, anxiety, hypertension, heart disease, back pain, joint pain), reported physical activity level, and perceived weight loss competency were also recorded. Results: Among the 31 non-diabetic participants who were considering GLP-1RA medication for weight loss, cost emerged as the most significant barrier. Life course events, particularly (peri)menopause among women over 44, were commonly cited as contributors to weight gain. Participants expressed uncertainty about eligibility, long-term safety, and treatment expectations. Communication gaps were evident, as few participants initiated discussions and clinician outreach was rare, reflecting limited awareness and discomfort around the topic. Conclusions: Findings highlight that individuals considering GLP-1RA therapy face multifaceted emotional, financial, and informational barriers. Proactive, empathetic clinician engagement, through validation of prior efforts, clear communication of risks and benefits, and correction of misconceptions, can support informed decision-making and align treatment with patient goals. Full article

Bio-electric fields—manifested as Electroencephalogram (EEG), Electrocardiogram (ECG), Electromyogram (EMG), and Electrooculogram (EOG)—are fundamental to modern medical diagnostics but often suffer from severe data imbalance, scarcity, and environmental noise. Generative Adversarial Networks (GANs) offer a powerful, nonlinear solution to these modeling hurdles. This review presents a comprehensive survey of GAN methodologies specifically tailored for bio-electric signal processing. We first establish a theoretical foundation by detailing GAN principles, training mechanisms, and critical structural variants, including advancements in loss functions and conditional architectures. Subsequently, the paper extensively analyzes applications ranging from high-fidelity signal synthesis and noise reduction to multi-class classification. Special attention is given to clinical anomaly detection, specifically covering epilepsy, arrhythmia, depression, and sleep apnea. Furthermore, we explore emerging applications such as modal transformation, Brain–Computer Interfaces (BCI), de-identification for privacy, and signal reconstruction. Finally, we critically evaluate the computational trade-offs and stability issues inherent in current models. The study concludes by delineating prospective research avenues, emphasizing the necessity of interdisciplinary synergy to advance personalized medicine and intelligent diagnostic systems. Full article

Drowsy driving and sudden medical emergencies are major contributors to traffic accidents, necessitating continuous, non-intrusive driver monitoring. Since current technologies often struggle to balance accuracy with practicality, this study presents the design, fabrication, and validation of a smart steering wheel prototype. The device integrates dry-contact electrocardiogram (ECG), photoplethysmography (PPG), and inertial sensors to facilitate multimodal physiological monitoring. The system underwent a two-stage evaluation involving a single participant: laboratory validation benchmarking acquired signals against medical-grade equipment, followed by real-world testing in a custom electric research vehicle to assess performance under dynamic conditions. Laboratory results demonstrated that the prototype captured high-quality signals suitable for reliable heart rate variability analysis. Furthermore, on-road evaluation confirmed the system’s operational functionality; despite increased noise from motion artifacts, the ECG signal remained sufficiently robust for continuous R-peak detection. These findings confirm that the multimodal smart steering wheel is a feasible solution for unobtrusive driver monitoring. This integrated platform provides a solid foundation for developing sophisticated machine-learning algorithms to enhance road safety by predicting fatigue and detecting adverse health events. Full article

Background/Objectives: Population aging increases the healthcare burden of chronic diseases. We aimed to characterize the sociodemographic and clinical characteristics of Aged Madrid, a cohort comprising 98.6% of the population aged 75 years and older in Madrid, Spain. Methods: Observational study with a five-year retrospective baseline period (2015–2019) to assess baseline vascular and metabolic risk. Data were taken from primary care electronic medical records, hospital discharge summaries, and pharmacy records. Results: 587,603 individuals (mean age: 84 years ± 5.8 years, 61.3% women) were analysed. Obesity affected 31.3% (more frequent in women), while type 2 diabetes occurred in 23.8% (predominantly in men). Hypertension (52.8%), dyslipidaemia (61.6%), and chronic kidney disease (21.7%) were more frequent in women. Atrial fibrillation was the leading cardiovascular condition in women (15.1%), while acute myocardial infarction predominated in men (8.2%). The most prescribed drug classes were antihypertensives (53.8%), statins (44.2%), and oral antidiabetics (26.4%). Among antihypertensives, diuretics (53.9%), ACE inhibitors (27.4%), and ARBs (25.3%) were most used, often in combinations such as diuretics + ACE inhibitors (30.1%). Diabetes treatments favoured metformin and DPP-4 inhibitors; 5.2% received insulin. Conclusions: Sex-based differences emerged in biochemical, anthropometric, and lifestyle variables. Men showed a higher prevalence of cardiovascular diseases and several cardiometabolic risk factors, while women used fewer lipid-lowering and antidiabetic agents. Diuretics were the predominant antihypertensives, and antidiabetic therapy largely followed guideline recommendations. Although 60% of statin users had no prior cardiovascular disease, and their use was concentrated mainly among individuals with major cardiometabolic risk conditions and declined with advancing age, suggesting an age- and risk-sensitive prescribing pattern rather than indiscriminate use. Full article

Background and Clinical Significance: Furuncular myiasis is a tropical parasitic skin infestation caused by dipterous fly larvae, most commonly affecting travellers to endemic regions. While returning travellers typically present with one or few lesions, extensive parasitism is rare. Increased global mobility and expanding ecological range of myiasis-causing species underscores the need for clinicians in endemic and non-endemic regions to recognise, diagnose, and manage this condition promptly. Awareness of exposure risks—including soil contact, infested clothing, and poor living conditions—is essential to reducing morbidity and preventing complications like secondary bacterial infection. Case Presentation: A healthy male in his forties returned to the UK after a month-long visit to rural Ethiopia, during which he slept on dirt floors and hung his washing on a line. He developed pruritic papular lesions that progressed to erythematous furuncles with central puncta and purulent discharge, accompanied by sensations of movement. The patient self-extracted 12 larvae in Ethiopia and subsequently sought local medical attention, receiving Albendazole, after which emerging larvae were non-motile. On UK presentation, he had 27 lesions at varying stages, 3 with signs of secondary infection. Laboratory investigations revealed elevated inflammatory markers, and wound swabs grew scanty Streptococcus pyogenes. Management included wound occlusion and systemic antibiotics. No further larvae were retrieved, precluding definitive speciation. All lesions improved over subsequent reviews. Conclusions: This case illustrates an unusually extensive presentation of presumed Cordylobia spp. myiasis in a returning traveller, highlighting potential complications following larvicidal therapy. Clinicians should maintain a high index of suspicion for myiasis in patients with compatible cutaneous lesions and relevant history. Increasing travel and shifting vector distributions make familiarity with tropical dermatoses and provision of effective safety measures essential in clinical practice. Full article

Background and Objectives: Medically unexplained symptoms (MUS) represent a clinical syndrome encompassing conditions in which patients present with symptoms that cannot be adequately explained by identifiable organic pathology or do not meet established diagnostic criteria for organic disease. These symptoms pose a diagnostic and management challenge, particularly in acute care settings. The objective of this study was to determine the proportion of patients presenting with MUS to the Emergency Neurology Service of a tertiary care hospital. Materials and Methods: This retrospective study was conducted at the Emergency Neurology Service of Sveti Duh University Hospital. All patients who were triaged for neurological examination during the study period were included. Following clinical evaluation, attending neurologists assessed the extent to which each patient’s symptoms could be explained by organic disease (“organicity”). This assessment was recorded using a Likert scale ranging from “not at all explained” to “completely explained. Results: Out of 219 patients, 2.7% had symptoms that were rated as “not at all explained” by organic disease, 7.3% “somewhat explained”, 23.3% “largely explained” and 66.7% “completely explained” by organic disease. Conclusions: Approximately one-tenth of patients presenting to our Emergency Neurology Service have symptoms that are poorly explained by identifiable organic disease. Full article

Artificial Intelligence (AI)-enabled diagnosis has emerged as a promising avenue for revolutionizing medical image analysis, such as X-ray analysis, across a wide range of healthcare disciplines, including dentistry, consequently offering swift, efficient, and accurate solutions for identifying various dental conditions. In this study, we investigated the application of the YOLOv9 model, a cutting-edge object detection algorithm, to automate the diagnosis of dental diseases from X-ray images. The proposed methodology encompasses a comprehensive analysis of dental datasets, as well as preprocessing and model training. Through rigorous experimentation, remarkable accuracy, precision, recall, mAP@50, and an F1-score of 84.89%, 89.2%, 86.9%, 89.2%, and 88%, respectively, are achieved. With significant improvements over the baseline model of 17.9%, 15.8%, 18.5%, and 16.81% in precision, recall, mAP@50, and F1-score, respectively, with 7.9 ms inference time. This demonstrates the effectiveness of the proposed approach in accurately identifying dental conditions. Additionally, we discuss the challenges in automated diagnosis of dental diseases and outline future research directions to address knowledge gaps in this domain. This study contributes to the growing body of literature on AI in dentistry, providing valuable insights for researchers and practitioners. Full article

Photocatalytic water sterilization has emerged as a promising sustainable technology for addressing microbial contamination across diverse sectors including healthcare, food production, and environmental management. This review examines the fundamental mechanisms and recent advances in photocatalytic water sterilization, with a particular emphasis on the differential bactericidal pathways against Gram-negative and Gram-positive bacteria. Gram-negative bacteria undergo a two-step inactivation process involving initial outer membrane lipopolysaccharide (LPS) degradation followed by inner membrane disruption, whereas Gram-positive bacteria exhibit simpler kinetics due to direct oxidative attacks on their thick peptidoglycan layer. Escherichia coli has long been used as the gold standard in photocatalytic sterilization studies owing to its aerobic nature and suitability for the colony-counting method. In contrast, Lactobacillus casei, a facultative anaerobe, can be cultured statically and evaluated rapidly using turbidity-based optical density measurements. Therefore, both organisms serve complementary roles depending on the experimental objectives—E. coli for precise quantification and L. casei for rapid, practical assessments of Gram-positive bacterial inactivation under laboratory conditions. We also describe sterilization using light alone while comparing it to photocatalytic sterilization and then discuss two innovative suspension-based photocatalyst systems: polystyrene bead-supported TiO₂/SiO₂ composites offering balanced reactivity and separability and magnetic TiO₂-SiO₂/Fe₃O₄ nanoparticles enabling rapid magnetic recovery. Future research directions should prioritize enhancing visible-light efficiency using metal-doped TiO₂ such as Cu-doped systems; improving catalyst durability; developing new applications of photocatalysts, such as protecting RO membranes; and validating scalability across diverse industrial and medical water treatment applications. Full article

Optical fiber sensors (OFSs) have emerged as essential tools in the monitoring of physical, chemical, and bio-medical parameters in harsh situations due to their high sensitivity, electromagnetic interference (EMI) immunity, and long-term stability. However, the current literature contains scattered information in most reviews regarding individual sensing technologies or domains. This study provides a structured exploratory review in a novel inter-family analysis of both intrinsic and extrinsic configurations by analyzing more than 23,000 publications between 2019 and 2025 in five key domains: industry, medicine and biomedicine, environmental chemistry, civil/structural engineering, and aerospace. The analysis aims to critically discuss how functional principles/parameters and methods of interrogation affect the applicability of different OFS categories. The results reveal leading trends in the use of techniques like the use of fiber Bragg gratings (FBG) and distributed sensing in high-accuracy conditions or the rising role of extrinsic sensors in selective chemical situations and point out new approaches in areas like Artificial Intelligence (AI)- or Internet of Things (IoT)-integrated sensors. Further, this synthesis not only connects pieces of knowledge but also defines the technological barriers in terms of calibration cost and standardization: this provides strategic insight regarding future research and the scalability of industry deployment. Full article