Search Results (1,070)

Background and Objectives: Diabetes is a global public health challenge, with increasing prevalence worldwide. The implementation of artificial intelligence (AI) in the management of this condition offers potential benefits in improving healthcare outcomes. This study primarily investigates the barriers and facilitators perceived by healthcare professionals in the adoption of AI. Secondarily, by analyzing both quantitative and qualitative data collected, it aims to support the potential development of AI-based programs for diabetes management, with particular focus on a possible bottom-up approach. Materials and Methods: A scoping review was conducted following PRISMA-ScR guidelines for reporting and registered in the Open Science Framework (OSF) database. The study selection process was conducted in two phases—title/abstract screening and full-text review—independently by three researchers, with a fourth resolving conflicts. Data were extracted and assessed using Joanna Briggs Institute (JBI) tools. The included studies were synthesized narratively, combining both quantitative and qualitative analyses to ensure methodological rigor and contextual depth. Results: The adoption of AI tools in diabetes management is influenced by several barriers, including perceived unsatisfactory clinical performance, high costs, issues related to data security and decision-making transparency, as well as limited training among healthcare workers. Key facilitators include improved clinical efficiency, ease of use, time-saving, and organizational support, which contribute to broader acceptance of the technology. Conclusions: The active and continuous involvement of healthcare workers represents a valuable opportunity to develop more effective, reliable, and well-integrated AI solutions in clinical practice. Our findings emphasize the importance of a bottom-up approach and highlight how adequate training and organizational support can help overcome existing barriers, promoting sustainable and equitable innovation aligned with public health priorities. Full article

Human induced pluripotent stem cells (hiPSCs) are widely used in basic research because of their versatility and ability to differentiate into multiple cell types. In particular, differentiating hiPSCs into cardiac cells (hiPSC-CMs) has been an important milestone in cardiac pathophysiology studies. Although hiPSC-CMs offer a model for human cardiomyocytes, they still exhibit characteristics linked to the fetal cardiac cell phenotype. One important feature that prevents hiPSC-CMs from being identified as adult cells relates to their metabolism, which is a key factor in defining a mature phenotype capable of sustaining the workload requirements characteristic of fully differentiated cardiomyocytes. This review aims to present the most relevant strategies in terms of culture medium composition, culture times, and 3D culture methods that have been developed to promote the metabolic maturation of hiPSC-CMs, which are now widely used. Defining a standardized and universally accepted protocol would enable the creation of a cellular model for studies of cardiac pathophysiology from a patient-specific perspective and for drug screening. Full article

Human induced pluripotent stem cell-derived cardiomyocytes (iCMs) provide a powerful platform for investigating cardiac biology. However, structural, metabolic, and electrophysiological immaturity of iCMs limits their capacity to model adult cardiomyocytes. Currently, no universally accepted criteria or protocols for effective iCMs maturation exist. This study aimed to identify practical culture conditions that promote iCMs maturation, thereby generating more physiologically relevant in vitro cardiac models. We evaluated the effects of short- and long-term culture in media supplemented with various stimulatory compounds under 2D conditions, focusing on intracellular content and localization of slow skeletal troponin I (ssTnI) and cardiac troponin I (cTnI) isoforms. Our findings demonstrate that the multicomponent metabolic maturation medium (MM-1) effectively enhances the transition toward a more mature iCM phenotype, as evidenced by increased cTnI expression and formation of cross-striated myofibrils. iCMs cultured in MM-1 more closely resemble adult cardiomyocytes and are compatible with high-resolution single-cell techniques such as electron microscopy and patch-clamp electrophysiology. This work provides a practical and scalable approach for advancing the maturation of iPSC-derived cardiac models, with applications in disease modeling and drug screening. Full article

Background and Objectives: Peptide receptor radionuclide therapy (PRRT) using radiopharmaceuticals labelled with Lutetium-177 is currently a therapeutic option for patients with advanced neuroendocrine neoplasms overexpressing somatostatin receptors (SSTRs). One promising option that has gained interest for PRRT is using alpha-emitting radioisotopes such as Actinium-225. The aim of this study was to perform a systematic review and meta-analysis on the efficacy and safety of radioligand therapy with Actinium-225 DOTATATE in advanced, metastatic or inoperable neuroendocrine neoplasms. Materials and Methods: A comprehensive literature search of studies on radioligand therapy with Actinium-225 DOTATATE in neuroendocrine neoplasms was carried out. Three different bibliographic databases (Cochrane Library, Embase, and PubMed/MEDLINE) were screened up to May 2025. Eligible articles were selected, relevant data were extracted, and the main findings on efficacy and safety are summarized through a systematic review. Furthermore, proportional meta-analyses on the disease response rate and disease control rate were performed. Results: Five studies (153 patients) published from 2020 were included in the systematic review. The pooled disease response rate and disease control rate of radioligand therapy using Actinium-225 DOTATATE were 51.6% and 88%, respectively. This treatment was well-tolerated in most patients with advanced, metastatic or inoperable neuroendocrine neoplasms. Conclusions: Radioligand therapy with Actinium-225 DOTATATE in advanced, metastatic or inoperable neuroendocrine neoplasms is effective with an acceptable toxicity profile and potential advantages compared with SSTR-ligands labelled with Lutetium-177. Currently, the number of published studies on this treatment is still limited, and results from multicenter randomized controlled trials are needed to translate this therapeutic option into clinical practice. Full article

Glycated hemoglobin (HbA1c) is an important biomarker applied for the diagnosis, evaluation, and management of diabetes; therefore, its accurate determination is crucial. In this study, an innovative nanoplatform was developed, integrating carbon nanotubes (CNTs) with enhanced hydrophilicity achieved through cyclodextrin (CD) functionalization, and combined with gold nanoparticles (AuNPs) electrochemically deposited onto a screen-printed carbon electrode. The nanomaterials significantly improved the analytical performance of the sensor due to their increased surface area and high electrical conductivity. This nanoplatform was employed as a substrate for the covalent attachment of thiolated ferrocene-labeled HbA1c specific aptamer through Au-S binding. The electrochemical signal of ferrocene was covered by a stronger oxidation peak of Fe²⁺ from the HbA1c structure, leading to the elaboration of a nanostructured aptasensor capable of the direct detection of HbA1c. The electrochemical aptasensor presented a very wide linear range (0.688–11.5%), an acceptable limit of detection (0.098%), and good selectivity and stability, being successfully applied on real samples. This miniaturized, simple, easy-to-use, and fast-responding aptasensor, requiring only a small sample volume, can be considered as a promising candidate for the efficient on-site determination of HbA1c. Full article

Background/Objectives: Healthcare workers (HCW) have increased the risk of occupational stress injuries and adverse mental health outcomes, which were exacerbated during the COVID-19 pandemic. Understanding HCW psychological distress patterns and help-seeking behaviors can inform responsive resource development that may mitigate negative outcomes in future crises. This paper provides insights on monthly trends in HCW distress and support utilization at a large Canadian hospital over a 14-month period. Methods: As part of a hospital-wide wellness initiative during COVID-19, the STEADY program emailed monthly confidential wellness assessments to hospital staff from April 2020 to May 2021. The assessments included screens for burnout, anxiety, depression and posttraumatic stress, types of support accessed, and demographic information. Repeated cross-sectional data were summarized as monthly proportions and examined alongside longitudinal COVID-19 data. Results: A total of 2498 wellness assessments were submitted (M = ~168 monthly, range: 17–945). Overall, 67% of assessments had at least one positive screen for distress. Average positive screens were 44% for anxiety, 29% for depression, 31% for posttraumatic stress, and 53% for burnout. Despite high distress, most respondents used informal supports (e.g., family/friends), highlighting limited formal support use. Conclusions: HCWs experienced sustained high levels of psychological distress during the COVID-19 pandemic, with burnout remaining a predominant and persistent concern. The limited use of formal support services may indicate barriers to accessing these types of supports. Our findings underscore the need for accessible and acceptable mental health supports for HCW during prolonged crises. Full article

The economic impact of health promotion and disease prevention interventions in ageing populations remains debated, as theories of morbidity compression and expansion offer contrasting views on the relationship between life expectancy and duration of morbidity. A MEDLINE search was conducted to identify studies evaluating the economic impact of health promotion or primary or secondary prevention interventions in OECD countries, over a lifetime time horizon. Among the 29 studies included, 16 reported cost-saving interventions (reducing costs while improving health outcomes), 11 reported cost-effective interventions (health gains at an acceptable additional cost based on an established threshold), and two presented cost-ineffective interventions (costs exceeding the threshold for the health benefits achieved). Interventions targeting diabetes and obesity prevention were cost-saving; cancer screening and fall prevention strategies were cost-effective; whereas interventions targeting rare diseases were cost-ineffective. Regulatory interventions were also cost-saving, while most programme-based interventions were cost-effective. Cost-saving or cost-effective interventions generally adopted broader analytical perspectives, while cost-ineffective ones employed narrower perspectives. The four studies that incorporated competing risks—despite using a narrower healthcare sector perspective—still found the interventions to be cost-saving or cost-effective interventions. None of the included studies assessed whether interventions led to morbidity compression or expansion. Only a few studies considered equity impact; those that did reported improved outcomes for disadvantaged groups, in regulatory and community-based interventions. Further research is needed to quantify morbidity outcomes and enhance methodological consistency, particularly with respect to analytical perspectives, the integration of competing risks, and the inclusion of equity analyses. Full article

Background/Objectives: Discrepancies in diabetic retinopathy (DR) grading are well-documented, with retinal non-perfusion (RNP) quantification posing greater challenges. This study assessed intergrader agreement in DR evaluation, focusing on qualitative severity grading and quantitative RNP measurement. We aimed to improve agreement through structured consensus meetings. Methods: A retrospective analysis of 100 comparisons from 50 eyes (36 patients) was conducted. Two paired medical retina fellows graded ultra-widefield color fundus photographs (CFP) and fundus fluorescein angiography (FFA) images. CFP assessments included DR severity using the International Clinical Diabetic Retinopathy (ICDR) grading system, DR Severity Scale (DRSS), and predominantly peripheral lesions (PPL). FFA-based RNP was defined as capillary loss with grayscale matching the foveal avascular zone. Weekly adjudication by a senior specialist resolved discrepancies. Intergrader agreement was evaluated using Cohen’s kappa (qualitative DRSS) and intraclass correlation coefficients (ICC) (quantitative RNP). Bland–Altman analysis assessed bias and variability. Results: After eight consensus meetings, CFP grading agreement improved to excellent: kappa = 91% (ICDR DR severity), 89% (DRSS), and 89% (PPL). FFA-based PPL agreement reached 100%. For RNP, the non-perfusion index (NPI) showed moderate overall ICC (0.49), with regional ICCs ranging from 0.40 to 0.57 (highest in the nasal region, ICC = 0.57). Bland–Altman analysis revealed a mean NPI difference of 0.12 (limits: −0.11 to 0.35), indicating acceptable variability despite outliers. Conclusions: Structured consensus training achieved excellent intergrader agreement for DR severity and PPL grading, supporting the clinical reliability of ultra-widefield imaging. However, RNP measurement variability underscores the need for standardized protocols and automated tools to enhance reproducibility. This process is critical for developing robust AI-based screening systems. Full article

Objectives: To evaluate the psychometric properties of the Spanish version of the obstructive sleep apnea knowledge and attitudes (OSAKA) questionnaire among dental professionals in Colombia. Methods: A cross-sectional study was conducted in Manizales, Colombia, between January and June 2024. A total of 120 dental professionals, including general dentists, specialists, residents, and academic clinicians, were selected through stratified random sampling. Participants completed the Spanish-adapted OSAKA questionnaire and a structured sociodemographic survey. Internal consistency was assessed using Cronbach’s alpha (α) and McDonald’s Omega (Ω). Construct validity was examined through exploratory factor analysis (EFA), with Kaiser Meyer Olkin (KMO) values and Bartlett’s test. Results: The knowledge subscale (18 items) showed good reliability (α = 0.83; Ω = 0.83), while the attitude subscale (5 items) showed near-acceptable reliability (α = 0.68; Ω = 0.59). KMO values were 0.79 for knowledge and 0.57 for attitudes; Bartlett’s test was significant in both cases (p ≤ 0.001). EFA supported structural validity: six components with eigenvalues >1 explained 61.66% of the variance for knowledge, and two components explained 79.49% for attitudes. Significant differences in attitude scores were found among professional groups (p ≤ 0.001, η² = 0.13), with specialists scoring highest ($\overline{X}$ = 17.66) and general dentists lowest ($\overline{X}$ = 14.62). Knowledge scores did not significantly differ between groups (p = 0.47). Conclusions: The Spanish OSAKA questionnaire is a valid and reliable tool to assess knowledge and attitudes toward obstructive sleep apnea in Colombian dental professionals. Its use may support improved education, screening, and interdisciplinary collaboration in dental settings. Full article

Background/Objectives: Artificial intelligence (AI) is beginning to be applied in wound ballistics, showing preliminary potential to improve the accuracy and objectivity of forensic analyses. This review explores the current state of AI applications in forensic firearm wound analysis, emphasizing its potential to address challenges such as subjective interpretations and data heterogeneity. Methods: A systematic review adhering to PRISMA guidelines was conducted using databases such as Scopus and Web of Science. Keywords focused on AI and GSW classification identified 502 studies, narrowed down to 4 relevant articles after rigorous screening based on inclusion and exclusion criteria. Results: These studies examined the role of deep learning (DL) models in classifying GSWs by type, shooting distance, and entry or exit characteristics. The key findings demonstrated that DL models like TinyResNet, ResNet152, and ConvNext Tiny achieved accuracy ranging from 87.99% to 98%. Models were effective in tasks such as classifying GSWs and estimating shooting distances. However, most studies were exploratory in nature, with small sample sizes and, in some cases, reliance on animal models, which limits generalizability to real-world forensic scenarios. Conclusions: Comparisons with other forensic AI applications revealed that large, diverse datasets significantly enhance model performance. Transparent and interpretable AI systems utilizing techniques are essential for judicial acceptance and ethical compliance. Despite the encouraging results, the field remains in an early stage of development. Limitations highlight the need for standardized protocols, cross-institutional collaboration, and the integration of multimodal data for robust forensic AI systems. Future research should focus on overcoming current data and validation constraints, ensuring the ethical use of human forensic data, and developing AI tools that are scientifically sound and legally defensible. Full article

Background/Objectives: A dietary pattern that simply reduces animal-based foods may be more acceptable to consumers than strict vegetarian or vegan diets. The objective of this investigation was to identify the most consistently used definitions of “flexitarian” dietary patterns, or dietary patterns with a reduced amount of animal foods. Then, sets of food-based dietary guidance (FBDG) from different countries and regions were evaluated to determine whether their guidance could accommodate flexitarian diets. Methods: Literature searches yielded 86 total results on flexitarian eating after screening by title/abstract, full text availability, and English language. Definitions of “flexitarian” were extracted from each article then reviewed and summarized. FBDGs available in English were downloaded from the Food and Agriculture Organization of the United Nations website. Guidance related to reduced animal product diets was extracted from FBDGs for eating patterns closest to 2000 kcal. Results: The summary definition of flexitarian included eating at least one animal product (dairy, eggs, meat, or fish) at least once per month but less than once per week. FBDGs from n = 42 countries or regions were downloaded and data extracted. Only FBDG from Sri Lanka explicitly describe a “semi-vegetarian” eating pattern, though n = 12 FBDGs describe a vegetarian pattern and n = 14 recommend reducing meat or animal food and/or choosing meat/dairy alternatives. Conclusions: Following a flexitarian dietary pattern in terms of reducing or limiting red meat is feasible and even implicitly recommended by the official dietary guidance of several countries. Most FBDGs examined did not include recommendations to decrease dairy or fish intake. Full article

Background/Objectives: The main purpose of the present scoping review was to map and explore the efficacy of computer-controlled intraosseous anesthesia (CCIA) in comparison with conventional dental anesthesia in pediatric dental patients. Secondarily, this study aimed to compare the acceptance and preference factors between CCIA and conventional dental anesthesia in children. Given the limited and heterogeneous nature of the available literature, this review aimed to identify gaps and scope the extent of research conducted in this area, providing a foundation for future, more targeted studies. Methods: The search was conducted in 19 electronic databases, and the appropriate studies were identified according to PRISMA-ScR guidelines. Only split-mouth randomized controlled clinical trials that reported on the clinical outcomes of CCIA in children were included. Two reviewers worked independently on the screening and selection of the studies. The same two reviewers carried out the data extraction and the risk of bias assessment, using the Cochrane risk of bias tool. Due to the exploratory nature, this review focused on mapping the characteristics, outcomes, and research trends rather than synthesizing effect sizes. Results: Out of 841 papers, 2 randomized clinical trials were ultimately included in the scoping review. The outcomes were categorized as primary (including results that answered the focus question) and secondary (relating to additional quality characteristics). Regarding the primary outcomes, in both studies, intraosseous anesthesia was efficacious in achieving the adequate level of anesthesia. One of the secondary outcomes was the acceptance and preference of CCIA in comparison with conventional dental anesthesia in children. The limited number and the high risk of bias in existing studies highlight the necessity for more comprehensive and high-quality research. Conclusions: The selected studies support the assertion that CCIA is a promising technique since it results in less pain perception and is preferred by patients compared to conventional local anesthesia. However, the existing literature is limited and at high risk of bias. Thus, further targeted investigations are needed to evaluate and yield more definitive results regarding the superiority of CCIA. Full article

Although smart device use among children is increasing, most interventions overlook their cognitive and emotional development or rely too heavily on external control. Such approaches often overlook the developmental needs of children for emotional regulation and autonomy. Therefore, this study aims to propose a child-centred user experience (UX) framework to support digital self-regulation in preschool-aged children. The proposed system integrates multiple psychological theories—including Piaget’s concept of animistic thinking, executive function theory, Self-Determination Theory, and Acceptance and Commitment Therapy—to support cognitive and emotional regulation during screen use. Key features include persistent visual cues to enhance time awareness and behavioural anticipation, narrative-based character interactions to foster empathy and agency, and ritualised closure routines supported by multimodal and tangible interaction elements. Developed as a mobile prototype, the system was iteratively refined through two-stage consultations with child and adolescent psychiatrists and a developmental psychologist, including formative design feedback and follow-up expert review. Their feedback provided preliminary validation of the system’s developmental validity and emotional coherence. These findings suggest that affectively attuned UX design is a viable alternative to conventional control-based screen-time interventions in early childhood. Full article

The Undetectable = Untransmittable (U=U) message is a cornerstone of HIV-related public health communication, yet global levels of awareness and acceptance remain unclear across key populations. This study aimed to assess the global prevalence of awareness and acceptance of the U=U message among men who have sex with men (MSM), people living with HIV (PLWH), healthcare professionals, and the general population. A systematic review and meta-analysis was conducted using data from PubMed, Embase, and Google Scholar without language restrictions through 31 October 2023. Eligible studies included prospective cohort studies, randomized clinical trials, and cross-sectional studies reporting numerical data on U=U awareness and acceptance. From 1171 screened records, 43 studies were included. Data were analyzed using a random effects model. The findings showed that U=U awareness was high among PLWH, moderate among MSM and healthcare professionals, and low in the general population. Complete acceptance of U=U was low in MSM and the general population, and moderate in PLWH and healthcare professionals. Any acceptance was moderate among MSM and the general population, and high among PLWH and healthcare professionals. These results highlight the need for targeted education strategies to enhance understanding and reduce HIV-related stigma, particularly in populations with lower awareness and acceptance. Full article

Background: Diabetic retinopathy (DR) is a leading cause of visual impairment worldwide. Manual grading of fundus images is the gold standard in DR screening, although it is time-consuming. Artificial intelligence (AI)-based algorithms offer a faster alternative, though concerns remain about their diagnostic reliability. Methods: A cross-sectional pilot study among patients (≥18 years) with diabetes was established for DR and diabetic macular edema (DME) screening at the Oslo University Hospital (OUH), Department of Ophthalmology, and the Norwegian Association of the Blind and Partially Sighted (NABP). The aim of the study was to evaluate the validity (accuracy, sensitivity, specificity) and reliability (inter-rater agreement) of automated AI-based compared to manual consensus (MC) grading of DR and DME, performed by a multidisciplinary team of healthcare professionals. Grading of DR and DME was performed manually and by EyeArt (Eyenuk) software version v2.1.0, based on the International Clinical Disease Severity Scale (ICDR) for DR. Agreement was measured by Quadratic Weighted Kappa (QWK) and Cohen’s Kappa (κ). Sensitivity, specificity, and diagnostic test accuracy (Area Under the Curve (AUC)) were also calculated. Results: A total of 128 individuals (247 eyes) (51 women, 77 men) were included, with a median age of 52.5 years. Prevalence of any vs. referable DR (RDR) was 20.2% vs. 11.7%, while sensitivity was 94.0% vs. 89.7%, specificity was 72.6% was 83.0%, and AUC was 83.5% vs. 86.3%, respectively. DME was detected only in one eye by both methods. Conclusions: AI-based grading offered high sensitivity and acceptable specificity for detecting DR, showing moderate agreement with manual assessments. Such grading may serve as an effective screening tool to support clinical evaluation, while ongoing training of human graders remains essential to ensure high-quality reference standards for accurate diagnostic accuracy and the development of AI algorithms. Full article