Search Results (1,608)

Age-related macular degeneration (AMD) is one of the leading causes of irreversible vision loss among the elderly, and is influenced by a combination of genetic and environmental risk factors. While genetic associations in AMD are well-established, the molecular mechanisms underlying disease onset and progression remain poorly understood. A growing body of evidence suggests that epigenetic modifications may serve as a potential missing link regulating gene–environment interactions. This review incorporates recent findings on DNA methylation, including both hypermethylation and hypomethylation patterns affecting genes such as silent mating type information regulation 2 homolog 1 (SIRT1), glutathione S-transferase isoform (GSTM), and SKI proto-oncogene (SKI), which may influence key pathophysiological drivers of AMD. We also examine histone modification patterns, chromatin accessibility, the status of long non-coding RNAs (lncRNAs) in AMD pathogenesis and in regulating pathways pertinent to the pathophysiology of the disease. While the field of ocular epigenetics remains in its infancy, accumulating evidence to date points to a burgeoning role for epigenetic regulation in AMD, pre-clinical studies have yielded promising findings for the prospect of epigenetics as a future therapeutic avenue. Full article

This study investigates the use of a Random Forest (RF), an artificial intelligence (AI) model, to estimate the planetary boundary layer height (PBLH) over Central Amazonia from climatic elements data collected during the GoAmazon experiment, held in 2014 and 2015, as it is a key metric for air quality, weather forecasting, and climate modeling. The novelty of this study lies in estimating PBLH using only surface-based meteorological observations. This approach is validated against remote sensing measurements (e.g., LIDAR, ceilometer, and wind profilers), which are seldom available in the Amazon region. The dataset includes various meteorological features, though substantial missing data for the latent heat flux (LE) and net radiation (Rn) measurements posed challenges. We addressed these gaps through different data-cleaning strategies, such as feature exclusion, row removal, and imputation techniques, assessing their impact on model performance using the Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and $r^2$ metrics. The best-performing strategy achieved an RMSE of 375.9 m. In addition to the RF model, we benchmarked its performance against Linear Regression, Support Vector Regression, LightGBM, XGBoost, and a Deep Neural Network. While all models showed moderate correlation with observed PBLH, the RF model outperformed all others with statistically significant differences confirmed by paired t-tests. SHAP (SHapley Additive exPlanations) values were used to enhance model interpretability, revealing hour of the day, air temperature, and relative humidity as the most influential predictors for PBLH, underscoring their critical role in atmospheric dynamics in Central Amazonia. Despite these optimizations, the model underestimates the PBLH values—by an average of 197 m, particularly in the spring and early summer austral seasons when atmospheric conditions are more variable. These findings emphasize the importance of robust data preprocessing and higtextight the potential of ML models for improving PBLH estimation in data-scarce tropical environments. Full article

The accurate perception of visual stimuli in human–machine systems is crucial for improving system safety, usability, and task performance. The widespread adoption of digital technology has significantly increased the importance of visual interfaces and information. Therefore, it is essential to design visual interfaces and information with user characteristics in mind to ensure accurate perception of visual information. This study employed the Cognitive Perceptual Assessment for Driving (CPAD) to evaluate and compare gender differences in the ability to perceive visual signals within complex visual stimuli. The experimental setup included a computer with CPAD installed, along with a touch monitor, mouse, joystick, and keyboard. The participants included 11 male and 20 female students, with an average age of 22 for males and 21 for females. Prior to the experiment, participants were instructed to determine whether a signal stimulus was present: if a square, presented as the signal, was included in the visual stimulus, they moved the joystick to the left; otherwise, they moved it to the right. Each participant performed a total of 40 trials. The entire experiment was recorded on video to measure overall response times. The experiment measured the number of correct detections of signal presence, response times, the number of misses (failing to detect the signal when present), and false alarms (detecting the signal when absent). The analysis of experimental data revealed no significant differences in perceptual ability or response times for visual stimuli between genders. However, males demonstrated slightly superior perceptual ability and marginally shorter response times compared to females. Analyses of sensitivity and response bias, based on signal detection theory, also indicated a slightly higher perceptual ability in males. In conclusion, although these differences were not statistically significant, males demonstrated a slightly better perception ability for visual stimuli. The findings of this study can inform the design of information, user interfaces, and visual displays in human–machine systems, particularly in light of the recent trend of increased female participation in the industrial sector. Future research will focus on diverse types of visual information to further validate these findings. Full article

This case report presents a multidisciplinary forensic investigation into a cold case involving a missing person in Italy, likely linked to a homicide that occurred in 2008. The investigation applied a standardized protocol integrating satellite imagery analysis, site reconnaissance, vegetation clearance, ground-penetrating radar (GPR), and cadaver dog (K9) deployment. A dedicated decision tree guided each phase, allowing for efficient allocation of resources and minimizing investigative delays. Although no human remains were recovered, the case demonstrates the practical utility and operational robustness of a structured, evidence-based model that supports decision-making even in the absence of positive findings. The approach highlights the relevance of “negative” results, which, when derived through scientifically validated procedures, offer substantial value by excluding burial scenarios with a high degree of reliability. This case is particularly significant in the Italian forensic context, where the adoption of standardized search protocols remains limited, especially in complex outdoor environments. The integration of geophysical, remote sensing, and canine methodologies—rooted in forensic geoarchaeology—provides a replicable framework that enhances both investigative effectiveness and the evidentiary admissibility of findings in court. The protocol illustrated in this study supports the consistent evaluation of large and morphologically complex areas, reduces the risk of interpretive error, and reinforces the transparency and scientific rigor expected in judicial settings. As such, it offers a model for improving forensic search strategies in both national and international contexts, particularly in long-standing or high-profile missing persons cases. Full article

Introduction: Although lipomas are common benign tumors found in adults, lipomas of the bladder are extremely rare. Bladder lipomas are infrequently reported in the urologic literature, with only 19 cases published worldwide. These can present as a mass on cystoscopy and cause irritative voiding symptoms, depending on their location. Upon transurethral resection, seeing fat can be concerning for a perforation, as lipoma can be mistaken for extravesical fat. Hence, familiarity with this rare entity is of paramount importance for urologists to prevent unnecessary investigations and interventions that are needed in case of a true bladder perforation. Case presentation: This study presents a case of bladder lipoma in a 73-year-old male with end-stage renal disease who presented for pretransplant urologic evaluation due to microscopic hematuria and irritative lower urinary tract symptoms (LUTS). During cystoscopy, a bladder mass was seen, and a transurethral resection of the bladder tumor (TURBT) revealed bright yellow adipose tissue immediately underneath the bladder mucosa. Concerns about perforation were obviated when seeing intact detrusor muscle underneath, visually confirming the integrity of the bladder wall. The resection was completed, and the CT scan was re-read with the radiologist, which confirmed the presence of a lipoma that was missed pre-operatively due to patient’s oliguria and collapsed bladder. No catheter drainage or cystogram was performed based on these findings. Outcome: The patient healed without any complications. Histopathology confirmed the diagnosis of a mature lipoma. The patient was cleared for transplant from a urologic standpoint and had a successful renal transplantation without delay. Discussion: This case documents the anomalous occurrence of a lipoma within the bladder and supports maintaining a broad differential, including liposarcoma, angiomyolipoma, and other non-malignant fatty tumors during the evaluation of a bladder mass. Full article

Background/Objectives: Understanding the impact of dietary habits in terms of obesity, health outcomes, and functional decline is critical in Europe’s growing elderly population. This study analyzed trends in Mediterranean diet (MD) adherence, obesity prevalence, and grip strength among middle-aged and elderly Europeans using data from the Survey of Health, Ageing and Retirement in Europe (SHARE). Methods: Data from four SHARE waves (2015–2022) across 28 countries were analyzed. Dietary patterns were assessed through food frequency questionnaires classifying participants as MD-adherent or non-adherent where adherent implies daily consumption of fruits and vegetables and occasional (3–6 times/week) intake of eggs, beans, legumes, meat, fish, or poultry (an unvalidated definition of the MD pattern). Handgrip strength, a biomarker of functional capacity, was categorized into low, medium, and high groups. Body mass index (BMI), self-perceived health (SPHUS), chronic disease prevalence, and CASP-12 scores (control, autonomy, self-realization, and pleasure evaluated on the 12-item version) were also evaluated. Statistical analyses included descriptive methods, logistic regressions, and multiple imputations to address missing data. Results: A significant majority (74–77%) consumed fruits and vegetables daily, which is consistent with MD principles; however, the high daily intake of dairy products (>50%) indicates limited adherence to the MD, which advocates for moderate consumption of dairy products. Logistic regression indicated that individuals with two or more chronic diseases were more likely to follow the MD (odds ratio [OR] = 1.21, confidence interval [CI] = 1.11–1.32), as were those individuals who rated their SPHUS as very good/excellent ([OR] = 1.42, [CI] = 1.20–1.69). Medium and high maximal handgrip were also strongly and consistently associated with higher odds of MD adherence (Medium: [OR] = 1.44, [CI] = 1.18–1.74; High: [OR] = 1.27, [CI] = 1.10–1.48). Conclusions: The findings suggest that middle-aged and older adults are more likely to adhere to the MD dietary pattern if they have more than two chronic diseases, are physically active, and have a medium or high handgrip. Although an unvalidated definition of the MD dietary pattern was used, the results highlight the importance of implementing targeted dietary strategies for middle-aged and elderly adults. Full article

The aim of this paper is to tailor the geometry and material parameters of a three-layer railway track model to achieve favorable properties for the circulation of high-speed trains at very high velocities. The three layers imply that the model should have three critical velocities for resonance. However, in many cases, some of these values are missing and must be replaced by pseudo-critical values. Since no resonance occurs at pseudo-critical velocities, even in the absence of damping, deflections never reach infinity. By using optimization techniques, it is possible to adjust the model’s parameters, so that the increase in vibrations remains minimal and does not pose a real danger. In this way, circulation velocities could be extended beyond the critical value, thereby increasing the network capacity and, consequently, improving the competitiveness of rail transport compared to other modes of transportation, thus contributing to decarbonization. The presented results are preliminary and require further analysis and validation. Several optimization techniques are implemented, leading to the establishment of designs that already have rather high pseudo-critical velocities. Further research will show how these theoretical findings can be utilized in practice. Full article

Carbapenem resistance is considered one of the greatest current threats to public health, particularly in the management of infections in clinical settings. Carbapenem resistance in bacteria is mainly due to mechanisms such as the production of carbapenemases (such as the imipenemase IMP, or other enzymes like VIM, NDM, and KPC), that can be detected by several laboratory tests, including immunochromatography and automated real-time PCR (qPCR). Methods: As part of local studies to monitor carbapenem-resistant bacteria in Costa Rica, two cases were initially identified with inconsistent IMP detection results. A possible gene drop-out in the automated qPCR test was suggested based on the negative result, contrasting with the positive result by immunochromatography and whole-genome sequencing. We hypothesized that molecular testing could be optimized through the development of tailored assays to improve the detection of IMP genes. Thus, using IMP gene sequences from the local isolates and regional sequences in databases, primers were redesigned to extend the detection of IMP alleles of regional relevance. Results: The tailored qPCR was applied to a local collection of 119 carbapenem-resistant isolates. The genomes of all 14 positive cases were sequenced, verifying the results of the custom qPCR, despite the negative results of the automated testing. Conclusions: Guided by whole-genome sequencing, it was possible to extend the molecular detection of IMP alleles circulating in Latin America using a tailored qPCR to overcome IMP gene drop-out and false-negative results in an automated qPCR. Full article

This study assessed the effects of a family function (FF) program on excessive digital behaviors—smartphone overuse (SO) and phubbing—and psychological needs—anxiety, loneliness, and fear of missing out (FoMO)—among 28 Thai female Muslim adolescents randomly assigned to the experimental (M_age = 15.7) and control (M_age = 15.2) groups. The experimental group received two 1.5 h morning sessions of the FF program weekly over four weeks (eight sessions in total). Baseline assessments confirmed group homogeneity. Using repeated-measures ANOVA with Bonferroni correction (p < 0.008), the results indicated a significant improvement in family function for the intervention group (F (1,26) = 11.91, p = 0.002, η²_p = 0.31), with a strong time-by-group interaction (F (1,26) = 19.51, p < 0.001, η²_p = 0.43). While the program did not significantly reduce SO overall, a notable interaction effect suggested group differences (F (1,26) = 10.31, p = 0.004, η²_p = 0.28). Phubbing remained unaffected. For psychological outcomes, interaction effects were found for the FoMO (F = 10.00, p = 0.004) and loneliness (F = 8.67, p = 0.007), though no main effects emerged. Anxiety levels did not significantly change after correction. These findings suggest that the program effectively enhances family functioning and partially alleviates psychosocial risks, but further refinements are needed to address digital overuse and anxiety more effectively. Full article

Background: Lysosomal storage diseases (LSDs) are a genetically and clinically heterogeneous group of inborn errors of metabolism caused by variants in genes encoding lysosomal hydrolases, membrane proteins, activator proteins, or transporters. These disease-causing variants lead to enzymatic deficiencies and the progressive accumulation of undegraded substrates within lysosomes, disrupting cellular function across multiple organ systems. While classical phenotypes typically manifest in infancy or early childhood with severe multisystem involvement, a combination of advances in molecular diagnostics [particularly next-generation sequencing (NGS)] and improved understanding of disease heterogeneity have enabled the identification of attenuated forms characterised by residual enzyme activity and later-onset presentations. These milder phenotypes often evade early recognition due to nonspecific or isolated symptoms, resulting in significant diagnostic delays and missed therapeutic opportunities. Objectives/Methods: This study characterises the clinical, biochemical, and molecular profiles of 10 adult patients diagnosed with LSDs, all representing attenuated forms, and discusses them alongside a narrative review. Results: Enzyme activity, molecular data, and phenotypic assessments are described to explore genotype–phenotype correlations and identify diagnostic challenges. Conclusions: These findings highlight the variable expressivity and organ involvement of attenuated LSDs and reinforce the importance of maintaining clinical suspicion in adults presenting with unexplained cardiovascular, neurological, ophthalmological, or musculoskeletal findings. Enhanced recognition of atypical presentations is critical to facilitate earlier diagnosis, guide management, and enable cascade testing for at-risk family members. Full article

Based on recent work outlining the transformation of professional communicator roles and the desperate search for “curators” or “agents of change” in neighboring disciplines such as management, business and economics, sustainability studies and education, we present a systematic reflection of concepts in higher education for sustainability and their (missing) fit to professional communication education in a world in crisis. The blind spots and challenges identified, especially from a communication perspective, will be filled with concepts from environmental communication pedagogy, pointing to the need for more participatory strategies and radicality in professional communication education. Concrete modalities of instruction will be discussed and supported by eight reconstruction interviews with pedagogues, educators and students from diverse cultural contexts involved in sustainability communication education. The findings show the need for more radical pedagogy and unorthodoxy. The paper finishes with suggestions for practices that materialize sustainability in co-created sites of change. Full article

A deterministic Mixed-Integer Nonlinear Programming (MINLP) model for the Integrated Generation and Transmission Expansion Planning (IGTEP) problem is presented. The proposed framework is distinguished by its foundation on the complete AC power flow formulation, which is solved to global optimality using BARON, a deterministic MINLP solver, which ensures the identification of truly optimal expansion strategies, overcoming the limitations of heuristic approaches that may converge to local optima. This approach is employed to establish a definitive, high-fidelity economic and technical benchmark, addressing the limitations of commonly used DC approximations and metaheuristic methods that often fail to capture the nonlinearities and interdependencies inherent in power system planning. The co-optimization model is formulated to simultaneously minimize the total annualized costs, which include investment in new generation and transmission assets, the operating costs of the entire generator fleet, and the cost of unsupplied energy. The model’s effectiveness is demonstrated on the IEEE 14-bus system under various dynamic load growth scenarios and planning horizons. A key finding is the model’s ability to identify the most economic expansion pathway; for shorter horizons, the optimal solution prioritizes strategic transmission reinforcements to unlock existing generation capacity, thereby deferring capital-intensive generation investments. However, over longer horizons with higher demand growth, the model correctly identifies the necessity for combined investments in both significant new generation capacity and further network expansion. These results underscore the value of an integrated, AC-based approach, demonstrating its capacity to reveal non-intuitive, economically superior expansion strategies that would be missed by decoupled or simplified models. The framework thus provides a crucial, high-fidelity benchmark for the validation of more scalable planning tools. Full article

Accurate methane emission estimates are essential for climate policy, yet current field methods often struggle with spatial constraints and source complexity. Ground-based mobile approaches frequently miss key plume features, introducing bias and uncertainty in emission rate estimates. This study addresses these limitations by using small unmanned aerial systems equipped with precision gas sensors to measure methane alongside co-released tracers. We tested whether arc-shaped flight paths and alternative ratio estimation methods could improve the accuracy of tracer-based emission quantification under real-world constraints. Controlled releases using ethane and nitrous oxide tracers showed that (1) arc flights provided stronger plume capture and higher correlation between methane and tracer concentrations than traditional flight paths; (2) the cumulative sum method yielded the lowest relative error (as low as 3.3%) under ideal mixing conditions; and (3) the arc flight pattern yielded the lowest relative error and uncertainty across all experimental configurations, demonstrating its robustness for quantifying methane emissions from downwind plume measurements. These findings demonstrate a practical and scalable approach to reducing uncertainty in methane quantification. The method is well-suited for challenging environments and lays the groundwork for future applications at the facility scale. Full article

The integration of artificial intelligence into sustainable agriculture holds significant potential to transform traditional agricultural practices. This transformation of agricultural practices through AI directly intersects with several critical sustainable development goals, such as Climate Action (SDG13), Life Below Water (SDG 14), and Life on Land (SDG 15). However, such implementations are fraught with multifaceted challenges. This study explores the technological, organizational, and environmental challenges confronting top management in the agricultural sector utilizing the technological–organizational–environmental framework. As interest in AI-enabled sustainable initiatives continues to rise globally, this exploration is timely and relevant. The study employs an interpretive case study approach, drawing insights from a carbon sequestration project within the agricultural sector where AI technologies have been integrated to support sustainability goals. The findings reveal six key challenges: sustainable policy inconsistency, AI experts lacking farming knowledge, farmers’ resistance to change, limited knowledge and expertise to deploy AI, missing links in the existing system, and transition costs, which often hinder the achievement of long-term sustainability outcomes. This study emphasizes the importance of field realities and cross-disciplinary collaboration to optimize the role of AI in sustainability efforts. Full article

Background: Social media platforms play a crucial role in contemporary healthcare, facilitating patient participation and enabling communication among healthcare workers, as well as serving as a platform for medical awareness and advocacy. Social media use among healthcare workers has increased to 91%, with 65% using it for health promotion purposes. Nonetheless, current studies have not properly and empirically explored its dimensions. Objectives: This study therefore examines social media dimensions and the productivity of healthcare workers. Methods: Leveraging the professional productivity theory and digital engagement theory, the study employs SPSS to analyze the gathered data through a partial least squares (PLS-SEM) approach to explore social media dimensions and productivity among healthcare workers in a Nigerian Tertiary Hospital. Based on a cross-sectional descriptive survey design and stratified random sampling method, 344 medical workers were analyzed. Findings: The study found that fear of missing out, information sharing, social influence, trust, and social media usage have a significant impact on the productivity of healthcare professionals. Conclusions: This research adds to the growing academic research on the capabilities of social media within the circular economic systems aimed at advancing healthcare delivery in developing economies. The research offers a method for maximizing the use of social media within healthcare settings to foster enhanced healthcare outcomes, particularly productivity. Full article