Search Results (20,491)

Patients presenting with abdominal pain and/or distension require rapid diagnostics to narrow the differential diagnosis from a long list of obstructive gastrointestinal (GI) pathologies that may appear clinically similar but warrant distinct management. While the workup of abdominal distension currently centers around computed tomography (CT), this modality is costly, requires radiation exposure, and necessitates patient transport, potentially delaying care. In contrast, point-of-care ultrasound (POCUS) avoids ionizing radiation and the need for patient transport while providing some insight into the gastrointestinal size and function. While POCUS cannot currently replace CT in the definitive diagnosis of GI obstructive pathologies, it remains a promising tool to help with the initial triage and monitoring responses to therapy for several causes of functional and/or mechanical GI obstruction, such as gastric dilation, ileus, and small bowel obstruction. Because the obstruction severity and features can evolve over time, POCUS enables serial examinations to monitor the progression or resolution. This manuscript reviews characteristic sonographic findings that help distinguish obstructive GI conditions and highlights practical techniques for integrating gastric and intestinal POCUS to improve diagnostic accuracy and expedite treatment. Full article

The main aim of this work is to define the limits of detection (LOD) and quantification (LOQ) for polyethylene (PE) particles using a pyrolysis and oxidation-based method, the thermal Rock-Eval^® device, combined with a mathematical extrapolation procedure. The influences of particle size and shape on the thermal degradation of PE polymers are also investigated in this study. Thermal Total HC and Tpeak parameters, recently used to characterize polymer samples, are evaluated as a function of both polymer grain size and shape. Results indicate a LOD for the investigated PE polymers of around 1.7–2 μg in 60 mg of composite sediment (28–33 ppm). A conservative LOQ for the PE samples ranges between 5 and 6 μg (83–100 ppm). The LOQ is on the same order of magnitude for any size or shape of the studied PE polymers. By contrast, the LOD for the PE samples is slightly affected by both the polymer grain size and shape. Results also demonstrate that it is possible to detect PE nanoparticles of 79 nm in size. Finally, this study provides specific Rock-Eval^® parameters, linear regressions, and a mathematical extrapolation procedure that can be used to better quantify very small PE mass contents, including nanoplastics in environmental samples. Full article

Background: Nurse-manager competencies shape workforce stability, yet role-based perception gaps between managers and staff may influence staff nurses’ turnover cognitions. Objectives: To (1) compare nurse managers’ self-ratings with staff nurses’ ratings of the same managers on the Nurse Manager Competency Inventory (NMCI); (2) compare both groups’ perceptions of staff nurses’ turnover intention (EMTIS); (3) examine domain-specific links between perceived competencies and perceived turnover intention; and (4) explore demographic influences (age, education, experience) on these perceptions. Methods: Cross-sectional dual-rater study with 225 staff nurses and 171 nurse managers in two tertiary hospitals in Saudi Arabia. Data were collected from August to November 2024. Managers completed NMCI self-ratings, and staff nurses rated their managers on the same NMCI domains; both groups rated staff nurses’ turnover intention using EMTIS. Between-group differences were tested with one-way ANOVA (two-tailed α = 0.05), and associations were examined with Pearson’s r (95% CIs). Findings: Managers consistently rated themselves higher than staff rated them across all nine NMCI domains; the largest descriptive gaps were in Promoting Staff Retention, Recruit Staff, Perform Supervisory Responsibilities, and Facilitate Staff Development (e.g., overall NMCI: managers M = 3.67, SD = 0.61 vs. staff M = 3.04, SD = 0.74; F = 0.114, p = 0.73)with comparatively smaller divergence for Ensure Patient Safety and Quality. Managers and staff did not differ significantly on EMTIS (overall EMTIS: managers M = 3.16, SD = 1.28 vs. staff M = 3.00, SD = 1.15; F = 21.32, p = 0.173). Specific competency domains—retention, supervision, staff development, safety/quality leadership, and quality improvement—showed small inverse correlations with EMTIS facets (typical r ≈ −0.11 to −0.19; p < 0.05), whereas the global NMCI–overall EMTIS correlation was non-significant (r = −0.077, p = 0.124). Effect sizes were modest and should be interpreted cautiously. Conclusions: Actionable signals reside at the domain (micro-competency) level rather than in global leadership composites. Targeted, continuous, unit-embedded development in human- and development-focused competencies—tracked with dual-lens (manager–staff) measurement and linked to retention KPIs—may help nudge turnover cognitions downward. Key limitations include the cross-sectional, perception-based design and two-site setting. Findings nonetheless align with international workforce challenges and may be transferable to similar hospital contexts. Full article

Indoor sports facilities present unique challenges for air quality management due to high crowd densities and limited ventilation. This study investigated air quality in a municipal athletic facility in Komotini, Greece, focusing on concentrations of airborne particulate matter (PM_1.0, PM_2.5, PM₁₀), humidity, and temperature across spectator zones, under varying mask scenarios. Sensing devices were installed in the stands to collect high-frequency environmental data. The system, based on optical particle counters and cloud-enabled analytics, enabled real-time data capture and retrospective analysis. The main experiment investigated the impact of spectators wearing medical masks during two basketball games. The results show consistently elevated PM levels during games, often exceeding recommended international thresholds in the spectator area. Notably, the use of masks by spectators led to measurable reductions in PM_1.0 and PM_2.5 concentrations, because they seem to have limited the release of human-generated aerosols as well as the amount of movement among spectators, supporting their effectiveness in limiting fine particulate exposure in inadequately ventilated environments. Humidity emerged as a reliable indicator of occupancy and potential high-risk periods, making it a valuable parameter for real-time monitoring. The findings underscore the urgent need for improved ventilation strategies in small to medium-sized indoor sports facilities and support the deployment of low-cost sensor networks for actionable environmental health management. Full article

In this paper, the austenite grains growth behavior in the austenitizing process of Nb–Ti micro-alloyed medium manganese steel was studied through in situ observation by high temperature laser confocal microscope. The results show that the average austenite grain sizes change from about 3 μm at 1050 °C to over 50 μm at 1250 °C. When the grain boundary is a small-angle grain boundary, one grain boundary will split into several dislocations. With the extension of heating time, the lattice orientation difference further decreases, and the remaining dislocations may merge into new grain boundaries. The most suitable heating temperature for the medium manganese steel in this paper is from 1100 °C to 1150 °C, taking into account influences such as grain size, grain boundary damage, and deformation resistance. Full article

Background: Despite advances in surgical techniques and perioperative care, pancreatic resections such as pancreaticoduodenectomy (PD) and distal pancreatectomy (DP) remain high-risk procedures. Postoperative complications significantly impact morbidity, mortality, and patient quality of life. Methods: This narrative review summarizes recent literature on major complications following pancreatic surgery, including postoperative pancreatic fistula (POPF), delayed gastric emptying (DGE), and post-pancreatectomy hemorrhage (PPH), with an emphasis on incidence, risk factors, outcomes, and current preventive strategies. Results: POPF is a leading complication, occurring in 5–22% of cases and often linked with sepsis and hemorrhage. Key risk factors include high BMI, soft pancreatic texture, and small duct size. Preventive measures like Pasireotide, modified anastomosis techniques, and neoadjuvant therapy show variable success. DGE affects up to 57% of PD patients and is associated with prolonged recovery; antecolic reconstruction and erythromycin may reduce incidence. PPH, though less frequent (3–13%), can be life-threatening, particularly when secondary to POPF. Endovascular approaches are now favored for late arterial bleeding. Other complications include wound infections, abscesses, bile leaks, and pulmonary issues, all contributing to extended hospital stays and diminished quality of life. Conclusions: Pancreatic surgery continues to carry significant risks, with POPF, DGE, and PPH being the most impactful complications. While multiple interventions have shown promise, standardized protocols and predictive tools are still needed. Surgery should be performed in high-volume centers with experienced multidisciplinary teams to optimize outcomes. Full article

Spatial accessibility is a key principle in urban studies, shaping how people reach amenities and services across cities. While most research concentrates on large metropolitan areas and central urban services, small and medium-sized cities and their main amenities remain less studied. To bridge this gap, this study explores spatial accessibility to public amenities in relation to population density in Odense, a medium-sized city known for its compact layout and robust infrastructure supporting walking, cycling, and public transport. Despite Odense’s proactive planning and multimodal transport network, marked accessibility inequalities still exist, especially in peripheral neighbourhoods. This research uses a data-driven approach combining network-based travel time analysis with grid-cell-based spatial visualisation. Additionally, a multi-criteria accessibility scoring framework is introduced, including indicators such as amenity density, diversity of services, temporal thresholds for walking and cycling, and population distribution. The results show an uneven accessibility landscape, with significant gaps in outer districts, highlighting the limitations of uniform planning thresholds. By applying spatial analytical principles, the study uncovers embedded socio-spatial inequalities in everyday urban access. These insights offer practical guidance for planners and policymakers, underscoring the importance of context-sensitive multimodal infrastructure and decentralised service provision to support sustainable urban growth. Full article

As small–medium-sized enterprises (SMEs) increasingly adopt cloud technologies, understanding the factors influencing this shift is crucial as it helps to optimize cloud integration strategies, enabling SMEs to thrive in today’s digital economy. A cross-sectional, quantitative survey was conducted in February 2022 on 626 employees of SMEs in the USA, based on the TAM-2, TAM-3, and UTAUT-2 models. The questionnaire presented satisfactory reliability, as well as factorial and convergent validity. Employees presented positive behavioral intentions to use cloud technologies, particularly during the COVID-19 period. SMEs were satisfied with the use of Software as a Service (SaaS), Infrastructure as a Service (IaaS), and the public cloud development model in the wake of the COVID-19 period. Behavioral intention to use cloud technologies was linked with higher performance and effort expectancy, price, perceived enjoyment, computer self-efficacy, and social influence. A higher behavioral intention was observed in employees (a) with a mid–top-level role; (b) who worked in finance and insurance, information services data, construction, or software and in an SME with 26–500 employees; (c) who had a master’s degree; (d) were 35–44 years old; and (e) had family obligations. Higher experience with the use of cloud technologies enhanced the positive impacts of effort expectancy, computer self-efficacy, and perceived enjoyment on behavioral intention. Full article

Promoting children’s rights in early childhood education is internationally recognised as a priority, yet its practical implementation remains challenging. This qualitative study explored the perceptions of three early childhood educators in northern Portugal regarding children’s rights and how these are reflected in their practices. Guided by an interpretive paradigm, the study sought to understand participants’ beliefs through semi-structured interviews, conducted with full ethical compliance, including informed consent, withdrawal rights, and anonymity. Data were analysed using MAXQDA, through an inductively generated coding system. Findings indicate that educators acknowledge their vital role in upholding children’s rights and in fostering respectful learning environments. However, significant gaps were found in the realisation of the right to participation, with tensions between educators’ stated values and their described practices—particularly regarding children’s involvement in decision-making. A prevailing emphasis on protection often limited children’s autonomy and agency. The study highlights the complexities of translating policy frameworks, such as Portuguese legislation and the UNCRC, into consistent pedagogical action. Despite its small sample size, the study offers valuable insights into the barriers to implementing a rights-based pedagogy and underscores the need for enhanced educator training, active listening practices, and the recognition of play as a fundamental right. Full article

Early and accurate diagnosis of dementia is essential to improving patient outcomes and reducing societal burden. The Mini-Mental State Examination (MMSE) is widely used to assess cognitive function, yet traditional statistical and machine learning approaches often face limitations in capturing nonlinear interactions and subtle decline patterns. This study developed a novel deep learning-based dementia prediction model using MMSE data collected from domestic clinical settings and compared its performance with traditional machine learning models. A notable strength of this work lies in its use of item-level MMSE features combined with explainable AI (SHAP analysis), enabling both high predictive accuracy and clinical interpretability—an advancement over prior approaches that primarily relied on total scores or linear modeling. Data from 164 participants, classified into cognitively normal, mild cognitive impairment (MCI), and dementia groups, were analyzed. Individual MMSE items and total scores were used as input features, and the dataset was divided into training and validation sets (8:2 split). A fully connected neural network with regularization techniques was constructed and evaluated alongside Random Forest and support vector machine (SVM) classifiers. Model performance was assessed using accuracy, F1-score, confusion matrices, and receiver operating characteristic (ROC) curves. The deep learning model achieved the highest performance (accuracy 0.90, F1-score 0.90), surpassing Random Forest (0.86) and SVM (0.82). SHAP analysis identified Q11 (immediate memory), Q12 (calculation), and Q17 (drawing shapes) as the most influential variables, aligning with clinical diagnostic practices. These findings suggest that deep learning not only enhances predictive accuracy but also offers interpretable insights aligned with clinical reasoning, underscoring its potential utility as a reliable tool for early dementia diagnosis. However, the study is limited by the use of data from a single clinical site with a relatively small sample size, which may restrict generalizability. Future research should validate the model using larger, multi-institutional, and multimodal datasets to strengthen clinical applicability and robustness. Full article

Cannabidiol (CBD) and other phytocannabinoids are gaining attention for their therapeutic potential in cardiovascular disease (CVD), the world’s leading cause of death. This review highlights advances in understanding the endocannabinoid system, including CB1 and CB2 receptors, and the mechanisms by which CBD exerts anti-inflammatory, antioxidative, vasoprotective, and immunomodulatory effects. Preclinical and translational studies indicate that selective activation of CB2 receptors may attenuate atherogenesis, limit infarct size in ischemia–reperfusion injury, decrease oxidative stress, and lessen chronic inflammation, while avoiding the psychotropic effects linked to CB1. CBD also acts on multiple molecular targets beyond the CB receptors, affecting redox-sensitive transcription factors, vascular tone, immune function, and endothelial integrity. Early clinical trials and observational studies suggest that CBD may lower blood pressure, improve endothelial function, and reduce sympatho-excitatory peptides such as catestatin, with a favorable safety profile. However, limited bioavailability, small sample sizes, short study durations, and uncertainty about long-term safety present challenges to its clinical use. Further research is needed to standardize dosing, refine receptor targeting, and clarify the role of the endocannabinoid system in cardiovascular health. Overall, current evidence supports CBD’s promise as an adjunct in CVD treatment, but broader clinical use requires more rigorous, large-scale studies. Full article

Biofilm formation is a key factor in microbial survival and persistence, often contributing to reduced antimicrobial susceptibility. This systematic literature review investigates whether increased biofilm formation correlates with decreased antibiotic susceptibility. The literature search was conducted in the Pubmed database and we identified and screened 328 studies, with 35 ultimately meeting the inclusion criteria for detailed analysis. Findings reveal that the relationship between biofilm size and antimicrobial susceptibility is highly variable and influenced by multiple factors, including microbial species, strain-specific traits, antibiotic type, and experimental methodologies. While some studies report a positive correlation between biofilm biomass and reduced susceptibility, others show weak or no such relationships, and statistical support for a correlation is often lacking (also due to small sample sizes). The lack of standardized biofilm quantification methods and susceptibility metrics further complicates cross-study comparisons. These findings underscore the need for standardized protocols and more comprehensive datasets to clarify the complex interplay between biofilm formation and antibiotic susceptibility. Regardless of these difficulties, the available data clearly indicate that ‘bigger’ biofilms are not by definition less susceptible. Future research should prioritize diverse and sufficiently large strain collections and consistent methodologies to better understand and address biofilm-associated antimicrobial tolerance. Full article

Caenorhabditis elegans is one of the most extensively studied model organisms in biology. Its advantageous features, including genetic homology with humans, conservation of disease pathways, transparency, short lifespan, small size and ease of maintenance have established it as a powerful system for research in aging, genetics, molecular biology, disease modeling and drug discovery. However, traditional methods for worm handling, culturing, scoring and imaging are labor-intensive, low throughput, time consuming, susceptible to operator variability and environmental influences. Addressing these challenges, recent years have seen rapid innovation spanning microfluidics, robotics, imaging platforms and AI-driven analysis in C. elegans-based research. Advances include micromanipulation devices, robotic microinjection systems, automated worm assays and high-throughput screening platforms. In this review, we first summarize foundational developments prior to 2020 that shaped the field, then highlight breakthroughs from the past five years that address key limitations in throughput, reproducibility and scalability. Finally, we discuss ongoing challenges and future directions for integrating these technologies into next-generation automated C. elegans research. Full article

The recycling of glass fiber-reinforced polymer (GFRP) in cementitious materials is an interesting way of managing the end of life of this type of material. As the solutions of landfilling and incinerating have reached their limits, the material recovery by recycling approach appears to be suitable to develop cement-based materials with enhanced properties. Different recycling methods, including mechanical, thermal and chemical recycling, are commonly used for the recovery of fibers and resins. Mechanical recycling is more suitable due to its low cost and ease of implementation. Moreover, mechanical recycling has limited environmental impact and is ideal for use with cementitious materials (fiber and resin). Several studies are being conducted to find the best incorporation method, notably the incorporation of recycled GFRP of different sizes (small, medium, large and coarse) and shapes (fibrous, cubic, random) as a substitute for sand and/or aggregate in mortars and concretes or as reinforcement materials. This article aims to establish a state of the art perspective on the incorporation of rGFRP into cement-based materials. The benefits of this incorporation are highlighted as well as the limitations. The various challenges to be overcome to make this incorporation useful from a practical point of view are reported. Full article

Introduction: 3D-printing is an emerging technology in the field of prosthetics, offering advantages such as cost-effectiveness, ease of customization, and improved accessibility. While previous reviews have focused on limited aspects, the aim of this systematic review is to provide a comprehensive evaluation of the clinical outcomes of 3D-printed prostheses for both upper and lower limbs. Methods: A search was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines across six databases (PubMed, Web of Science, EBSCO, Scopus, Cochrane Library, and Sage). Studies on 3D-printed prostheses in human rehabilitation that focused on the clinical outcomes of the device were included, while studies lacking clinical data, 3D printing details, or focusing on traditional manufacturing methods were excluded. Finally, the risk of bias was assessed using the modified Downs & Black Checklist. Results: A total of 1420 studies were identified, with 11 meeting the inclusion criteria. The included studies assessed different 3D-printed prosthetic types and upper and lower limb prostheses. The main clinical outcomes analyzed were functional performance, design and material integrity, and overall effectiveness of 3D-printed prostheses. Studies on upper limb prostheses reported improved dexterity, range of motion (ROM), and user satisfaction, despite some durability limitations. Lower limb prostheses showed enhancements in comfort, gait parameters, and customization, particularly in amphibious and partial foot designs. Conclusions: 3D-printed prostheses show potential to improve functional performance, patient satisfaction, fit, and implementation feasibility compared to conventional methods. However, limitations such as small sample sizes, variability in assessment tools, and limited high-quality evidence highlight the need for further research to support broader clinical adoption. Full article