bluuebunny/crossref_metadata_2025 huggingface dataset:
Complex Relationships between Diagnostics and Survival in Chronic Lymphocytic Leukemia in Denmark, Finland, Norway, and Sweden
Authors: Hemminki Kari , Zitricky Frantisek , Försti Asta , Tapaninen Tuija , Hemminki Akseli , Juliusson Gunnar , Niemann Carsten Utoft
Published: September 2024

Background: Chronic lymphocytic leukemia (CLL) is a common hematological malignancy with highly variable clinical presentation. Many patients never require any treatment but for the others, chemotherapy, immunochemotherapy, and newer targeted therapies have changed the treatment landscape. Diagnostic age influences the applied treatment, and we thus wanted to analyze age-specific survival trends through 50 years up to 2020s. Methods: We used 1- and 5-year relative survival from the NORDCAN database, with data from Denmark (DK), Finland (FI), Norway (NO), and Sweden (SE). Because of the variable presentation of CLL, we also considered incidence and mortality trends. For comparison, US SEER data were used. Results: The large age-specific survival differences in 1972–76 almost disappeared by 2017–21. While 5-year survival in younger patients exceeded 90%, for those diagnosed at age 80–89 years, survival reached 90% in DK and SE women, 80% in NO and SE men, but only 50% in FI. DK 5-year overall survival for men was 92.4%, and for women, it was 96.3%. These survival figures were higher than age-group-specific US survival data. Conclusions: The DK data are probably global top figures for national survival which could be achieved by boosting survival even among the oldest patients. The qualification to these figures and international comparisons is that survival needs to be considered in terms of incidence, which is high in DK and NO. Low survival of the FI 80–89-year-old patients, even in the first year after diagnosis, may suggest delayed diagnosis, which should call for a closer national scrutiny.
Optimizing Hearing Outcomes in Nasopharyngeal Cancer Survivors in the Era of Modern Radiotherapy and Systemic Therapy
Authors: Ho Jason C. S. , Ma Brigette B. Y. , Chow James C. H.
Published: September 2024

Intensity-modulated radiation therapy (IMRT) improves disease control and reduces treatment-related toxicity in patients with localized nasopharyngeal carcinoma (NPC). However, due to the proximity of the auditory apparatus to the treatment volume and the frequent incorporation of cisplatin-based chemotherapy, treatment-related sensorineural hearing loss (SNHL) remains a common debilitating complication among NPC survivors. The reported crude incidence of SNHL following IMRT for NPC varies widely at 1–46% due to differences in auditory assessment methods and thresholds, follow-up durations, chemotherapy usage, and patient compositions. International guidelines and radiation dosimetric studies have recommended constraining the cochlear mean dose to less than 44–50 Gy, but the risk of SNHL remains high despite adherence to these constraints. Potential strategies to improve hearing outcomes in NPC survivors include cautious de-escalation of radiotherapy dose and volume, individualization of cochlear constraints, optimization of radiotherapy planning techniques, and the use of substitutes or alternative schedules for cisplatin-based chemotherapy. The addition of immune checkpoint inhibitors to chemoradiotherapy did not impact ototoxicity. Prospective studies that employ both objective and patient-reported auditory outcomes are warranted to test the long-term benefits of various approaches. This article aims to provide a comprehensive review of the incidence and radiation dose–toxicity relationship of SNHL in NPC survivors and to summarize potential strategies to optimize hearing outcomes in relation to nuances in radiotherapy planning and the selection of systemic therapy.
A Straightforward Electrochemical Approach for the Simultaneous Determination of Thymol and Carvacrol in Essential Oils
Authors: Maccio Sabrina Antonella , Alaniz Ruben Darío , Pierini Gastón Darío , Zon María Alicia , Arévalo Fernando Javier , Fernández Héctor , Goicoechea Héctor Casimiro , Robledo Sebastian Noel , Alcaraz Mirta Raquel
Published: September 2024

A novel, simple, rapid, and non-expensive analytical method based on square wave voltammogram at Pt-microelectrode coupled with partial least square multivariate calibration was used for the simultaneous quantitation of thymol (THY) and carvacrol (CAR) in thyme and oregano essential oils. Results demonstrated that the multivariate calibration method successfully exploited the first-order advantage, rendering highly satisfactory quantitative figures (average recoveries not statistically different than 100%). Moreover, the results agree well with those obtained from the official analytical method. Last, the method’s environmental sustainability was asserted using the AGREE metric, highlighting its eco-friendly nature. More importantly, the proposed analytical procedure does not require previous sample preparation or electrode surface modification. The results underscore the suitability of the method for determining THY and CAR in essential oils at low concentrations (LOD ~ 7.6 µM) with REP% below 5.6%, meeting the requirements of the green analytical chemistry.
Associations between Biological Maturation, Chronological Age, Body Mass Index, Sex, and Motor Competence in Prepubertal Children: A Network Analysis
Authors: Salami Sedigheh , Bandeira Paulo Felipe Ribeiro , Mashhadi Maryam Rahymian , Shamsipour Dehkordi Parvaneh , Luz Leonardo G. O. , Martins Clarice Maria de Lucena , Hardy Louise L. , Duncan Michael J.
Published: September 2024

Background: The development of motor competence (MC) during childhood is crucial for future physical activity and health outcomes, and it is affected by both biological and psychosocial factors. Most MC research has focused on children’s age, with fewer studies examining separate associations between MC and biological maturation. Methods: This cross-sectional study used network analysis to assess the nonlinear associations between biological maturation (the child’s percentage of predicted mature stature to indicate somatic maturation), chronological age, sex, BMI, and MC (Test of Gross Motor Development, third edition) in 218 children (100 boys, 118 girls) aged 7–9 years. Results: Biological maturation was not significantly associated with MC in boys and weakly associated with MC in girls for the dribble, under-hand throw, and gallop. Age was positively associated with MC in girls and boys. Centrality measures indicated that the gallop and slide in girls and the dribble, catch, and run in boys were the most important network variables. Positive associations were observed between maturation and BMI for girls (r = 0.579) and, to a lesser degree, for boys (r = 0.267). Conclusions: The findings suggest that age, rather than biological maturation, is positively associated with MC in 7- to 9-year-olds. Centrality measures showed that some skills may influence other skills.
Assessing Heatwave-Related Deaths among Older Adults by Diagnosis and Urban/Rural Areas from 1999 to 2020 in Slovenia
Authors: Perčič Simona , Bitenc Katarina , Pohar Majda , Uršič Anka , Cegnar Tanja , Hojs Ana
Published: September 2024

Background: The association between mortality and heatwaves is well documented. Heatwaves frequency, intensity, and duration increase with global climate change. The most vulnerable group for dying during heatwaves is older people. Knowing which diseases contribute to a higher number of deaths during heatwaves is important for planning appropriate public health preventive measures. Methods: We assessed the short-term association between the number of deaths for older adults (75+ years) and heatwaves in the years 1999 to 2020 in Slovenia. We estimated the relative risks (RR) with a 95% confidence interval for the number of deaths for the observed diagnosis (all causes, circulatory, respiratory) and urban vs. rural areas associated with heatwaves in Slovenia for each year, comparing the number of deaths during heatwaves with reference days. Results: Most years showed no significant increase in deaths during heatwaves for those aged 75 and older. However, in 2006, 2007, 2014, and 2015, there was a significant increase in deaths during heatwaves. For the general population, heatwaves were associated with an increase in deaths due to all causes: 10% more in 2006 and 26% more in both 2007 and 2014. For those aged 75 and older, heatwaves were associated with an increase in deaths due to all causes: 22% more in 2007, 27% more in 2014, and 28% more in 2015. For those aged 75 and older, heatwaves were associated with an increase in deaths due to circulatory system diseases: 25% more in 2006, 33% more in 2007, 30% more in 2014, and 27% more in 2015. Regarding urban vs. rural areas, in 2006 and 2012, the elderly in urban areas were more affected, with 33% and 26% more deaths, respectively. In contrast, in 2007, 2014, and 2015, old age population in rural areas was more affected, with 29%, 26%, and 31% more deaths, respectively. Conclusions: According to the literature data, older adults are most susceptible to the effects of extreme heat due to physiological changes that occur with aging, chronic diseases, certain medications, a sedentary lifestyle, and social isolation. The results of our study will help in planning appropriate preventive public health measures to better protect older adults during the next heatwaves in Slovenia.
Characterization of Water Bodies through Hydro-Physical Indices and Anthropogenic Effects in the Eastern Northeast of Brazil
Authors: Scheibel Christopher Horvath , Nascimento Astrogilda Batista do , Júnior George do Nascimento Araújo , Almeida Alexsandro Claudio dos Santos , Silva Thieres George Freire da , Silva José Lucas Pereira da , Junior Francisco Bento da Silva , Farias Josivalter Araújo de , Santos João Pedro Alves de Souza , Oliveira-Júnior José Francisco de , Silva Jhon Lennon Bezerra da , João Fernando Manuel , Deus Alex Santos de , Teodoro Iêdo , Oliveira Henrique Fonseca Elias de , Silva Marcos Vinícius da
Published: September 2024

Brazil, despite possessing the largest renewable freshwater reserves in the world (8.65 trillion m3 annually), faces growing challenges in water management due to increasing demand. Agriculture, responsible for 68.4% of water consumption, is one of the main drivers of this demand, especially in the São Francisco River Basin, where irrigation accounts for 81% of total water withdrawals. Water bodies play a crucial role in sustaining ecosystems and supporting life, particularly along the East-West axis of Alagoas, a water-rich region in the ENEB. This study aimed to map and quantify the spatiotemporal variations of water bodies in the ENEB region and assess the impacts of human activities using MODIS satellite data, applying hydrological indices such as NDWI, MNDWI, and AWEI. Between 2003 and 2022, significant variations in the extent of water bodies were observed, with reductions of up to 100 km2 during dry periods and expansions of up to 300 km2 during wet seasons compared to dry periods. AWEI and MNDWI proved to be the most effective indices for detecting water bodies with MODIS data, providing accurate insights into water dynamics. Additionally, the MapBiomas Rios dataset, despite being resampled from a 30 m to a 500 m resolution, offered the most accurate representation of water bodies due to its methodology for data acquisition. Changes in albedo and surface temperature were also detected, highlighting the influence of climate change on the region’s water resources. These findings are crucial for guiding the sustainable management of water resources, not only in Alagoas but also in other regions of Brazil and similar semi-arid areas around the world. The study demonstrates the hydrological variability in the state of Alagoas, indicating the need for adaptive strategies to mitigate the impacts of climate change and anthropogenic pressures, supporting the need for informed decision-making in water resource management at both local and national levels.
A New Process of Chemical Plating Ni-P Electromagnetic Induction Heating Activation on the Surface of Aluminium Alloy Base Material
Authors: Gao Jin , Cui Kaifang , Li Siqi , Zhong Liang , Dai Jingxiong , Yang Zhigang , Qiang Rongming
Published: September 2024

Nowadays, there are many surface treatment methods for aluminium alloys; the most commonly used of these is the chemical dip galvanizing process, which is complicated due to its use of large quantities of corrosive drugs. In order to simplify the process, this paper proposes a new electromagnetic induction heating activation method instead of the zinc dipping process. The method works as follows: The substrate is first degreased and then activated. The activation process starts by soaking the degreased substrate in an activation solution, taking it out after ten minutes, and placing it into an induction heating unit. The activation solution is sprayed onto the surface of the substrate while heating, using the energy generated by high temperatures to complete the activation reaction. The surface of the activated substrate forms a nanoscale film of nickel, which is finally utilised as a catalytic centre for ENP (an advanced surface treatment process that deposits a very uniform layer). The optimisation of important parameters of the non-destructive activation process was determined using the L9 Taguchi method. The main parameters ranged from 0.15 L/min to 0.25 L/min for spray rate, 200 °C to 400 °C for heat treatment temperature, and 1:4, 1:5, and 1:6 for Ni2+ and H2PO4− ion concentration ratios. The above data were derived from a single variable and were analysed using Minitab 20 software. Scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), energy spectrometry (EDS), and ultrasonic experiments were used to characterize and analyse the surface morphology, composition, and bond strength of the coatings. The results show that the nanoscale nickel particles can completely cover the surface of the substrate, forming a layer of nano-film. After activation and ultrasonic cleaning for 30 s at an ultrasonic frequency of 40 KHz and a power of 80 W, the surface nano-film was not destroyed, which proves that it had a high bonding strength. After the application of the plating, the plated surface had a compact microstructure, and the continuity was good. Therefore, compared with the currently commonly used zinc dipping process, this process has the advantages of being a low-cost, simple operation, and non-destructive and environmentally friendly activation process for the substrate.
Effect of SiC Contents on Wear Resistance Performance of Electro-Codeposited Ni-SiC Composite Coatings
Authors: Wang Shaoqing , Xie Faqin , Wu Xiangqing
Published: September 2024

This paper focuses on the wear resistance performance of Ni-SiC composite coatings with various contents of SiC particles. The coatings were characterized via a scanning electron microscope (SEM), X-ray diffractometer (XRD), and transmission electron microscopy (TEM), and the wear behaviors of different coatings were tested. The results show that SiC particle incorporation results in a nanocrystalline metal matrix and nanotwins in nickel nanograins. The microhardness and wear resistance Ni-SiC composite coatings increased with the increasing SiC content. Microhardness was improved due to the grain-refinement strengthening effect and the presence of a nanotwin structure. The dominant wear mechanism was described in two stages: the first stage involves the interaction of SiC particles/the counter ball, and the second stage involves the formation of the oxide film its breaking up into wear debris. A higher SiC content increased the duration of the first stage and slowed down the rate of breaking up into debris, thereby decreasing the wear rate.
A Fully Connected Network (FCN) Trained on a Custom Library of Raman Spectra for Simultaneous Identification and Quantification of Components in Multi-Component Mixtures
Authors: Zhao Jiangsan , Kusnierek Krzysztof
Published: September 2024

Raman spectroscopy provides detailed information about the molecular composition of a sample. The classical identification of components in a multi-component sample typically involves comparing the preprocessed spectrum with a known reference stored in a database using various spectral matching or machine-learning techniques or relies on universal models based on a two-step analysis including first, the component identification, and then the decomposition of the mixed signal. However, although large databases and universal models cover a wide range of target materials, they may be not optimized to the variability required in a specific application. In this study, we propose a single-step method using deep learning (DL) modeling to decompose a simulated mixture of real measurements of Raman scattering into relevant individual components regardless of noise, baseline and the number of components involved and quantify their ratios. We hypothesize that training a custom DL model for applications with a fixed set of expected components may yield better results than applying a universal quantification model. To test this hypothesis, we simulated 12,000 Raman spectra by assigning random ratios to each component spectrum within a library containing 13 measured spectra of organic solvent samples. One of the DL methods, a fully connected network (FCN), was designed to work on the raw spectra directly and output the contribution of each component of the library to the input spectrum in form of a component ratio. The developed model was evaluated on 3600 testing spectra, which were simulated similarly to the training dataset. The average component identification accuracy of the FCN was 99.7%, which was significantly higher than that of the universal custom trained DeepRaman model, which was 83.1%. The average mean absolute error for component ratio quantification was 0.000562, over one order of magnitude smaller than that of a well-established non-negative elastic net (NN-EN), which was 0.00677. The predicted non-zero ratio values were further used for component identification. Under the assumption that the components of a mixture are from a fixed library, the proposed method preprocesses and decomposes the raw data in a single step, quantifying every component in a multicomponent mixture, accurately. Notably, the single-step FCN approach has not been implemented in the previously reported DL studies.
Low-Carbon Embodied, Self-Cleaning, and Air-Purifying Building Envelope Components Using TiO2 Photocatalysis, 3D Printing, and Recycling
Authors: Maury-Ramírez Aníbal , Rinke Mario , Blom Johan
Published: September 2024

This perspective article describes the past, present, and future directions on TiO2 photocatalysis, 3D concrete printing, and recycling for developing innovative building envelope components from façade skins. Using a methodology consisting of three phases, first the historical evolution of TiO2 photocatalysis, 3D concrete printing, and recycling policies was investigated. Second, the rationale and positioning with regard to the state of the art were developed. Third, the cementitious mix design assessment for 3D printing of the building envelope components, evaluation of the photocatalytic activity, evaluation of the self-cleaning and air-purifying properties, and environmental and health assessment of the building envelope components were identified and discussed as major issues in developing innovative building envelope components that have the potential to mitigate urban air pollution, reduce building maintenance activities, and reduce building embedded carbon while, for example, recycling significant amounts of construction and demolition waste.
Parallel Attention-Driven Model for Student Performance Evaluation
Authors: Olaniyan Deborah , Olaniyan Julius , Obagbuwa Ibidun Christiana , Esiefarienrhe Bukohwo Michael , Bernard Olorunfemi Paul
Published: September 2024

This study presents the development and evaluation of a Multi-Task Long Short-Term Memory (LSTM) model with an attention mechanism for predicting students’ academic performance. The research is motivated by the need for efficient tools to enhance student assessment and support tailored educational interventions. The model tackles two tasks: predicting overall performance (total score) as a regression task and classifying performance levels (remarks) as a classification task. By handling both tasks simultaneously, it improves computational efficiency and resource utilization. The dataset includes metrics such as Continuous Assessment, Practical Skills, Presentation Quality, Attendance, and Participation. The model achieved strong results, with a Mean Absolute Error (MAE) of 0.0249, Mean Squared Error (MSE) of 0.0012, and Root Mean Squared Error (RMSE) of 0.0346 for the regression task. For the classification task, it achieved perfect scores with an accuracy, precision, recall, and F1 score of 1.0. The attention mechanism enhanced performance by focusing on the most relevant features. This study demonstrates the effectiveness of the Multi-Task LSTM model with an attention mechanism in educational data analysis, offering a reliable and efficient tool for predicting student performance.
The Influence of National Digital Identities and National Profiling Systems on Accelerating the Processes of Digital Transformation: A Mixed Study Report
Authors: Alhammadi Abdelrahman Ahmed , Alhashmi Saadat M. , Lataifeh Mohammad , Rice John Lewis
Published: September 2024

The United Arab Emirates (UAE) is a frontrunner in digitalising government services, demonstrating the successful implementation of National Digital Identity (NDI) systems. Unlike many developing nations with varying levels of success with electronic ID systems due to legal, socio-cultural, and ethical concerns, the UAE has seamlessly integrated digital identities into various sectors, including security, transportation, and more, through initiatives like UAE Pass. This study draws on the UAE’s functional digital ID systems, such as those utilised in the Dubai Smart City project, to highlight the potential efficiencies and productivity gains in public services while addressing the associated risks of cybersecurity and privacy. This paper provides a comprehensive understanding of the UAE’s NDI and its impact on the nation’s digital transformation agenda, offering a thorough analysis of the effectiveness and challenges of NDIs, explicitly focusing on the UAE’s approach.
Atraumatic Hepatic Laceration with Hemoperitoneum
Authors: Russo Gaetano Maria , Zoi Evangelia , D’Iglio Imma , Mangoni di Santo Stefano Maria Luisa
Published: September 2024

Introduction: A rare case of atraumatic liver laceration associated with hemoperitoneum is presented in a patient with amyloidosis who came to the hospital for abdominal pain. Case Presentation: The imaging findings reveal significant hepatomegaly with finely heterogeneous hepatic density and subcapsular hypo-dense streaks in segments VI and VII, likely representing lesions. Post-contrast enhancement shows a punctiform contrast medium extravasation within the subhepatic fluid collection, visible from the arterial phase and intensifying in subsequent study phases. Discussion: These imaging findings suggest an atraumatic hepatic laceration, a diagnosis confirmed by the presence of hemoperitoneum distributed bilaterally under the diaphragm, in the paracolic gutters, along the mesentery root, and predominantly in the peri-hepatic region. Conclusion: The detailed imaging analysis provided critical insights into the diagnosis and management of this rare clinical presentation.
The Role of Oxidative Stress as a Mechanism in the Pathogenesis of Acute Heart Failure in Acute Kidney Injury
Authors: Tasić Danijela , Dimitrijević Zorica
Published: September 2024

Despite a large amount of research on synchronous and mutually induced kidney and heart damage, the basis of the disease is still not fully clarified. Healthy mitochondria are essential for normal kidney and heart function. Mitochondrial dysfunction occurs when the clearance or process of generation and fragmentation of mitochondria is disturbed. The kidney is the second organ after the heart in terms of the number of mitochondria. Kidney tubules are rich in mitochondria due to the high energy requirements for absorption of large amounts of ultrafiltrate and dissolved substances. The place of action of oxidative stress is the influence on the balance in the production and breakdown of the mitochondrial reactive oxygen species. A more precise determination of the place and role of key factors that play a role in the onset of the disease is necessary for understanding the nature of the onset of the disease and the creation of therapy in the future. This underscores the urgent need for further research. The narrative review integrates results found in previously performed studies that have evaluated oxidative stress participation in cardiorenal syndrome type 3.
Computed Tomography Evaluation of Coronary Atherosclerosis: The Road Travelled, and What Lies Ahead
Authors: Ayoub Chadi , Scalia Isabel G. , Anavekar Nandan S. , Arsanjani Reza , Jokerst Clinton E. , Chow Benjamin J. W. , Kritharides Leonard
Published: September 2024

Coronary CT angiography (CCTA) is now endorsed by all major cardiology guidelines for the investigation of chest pain and assessment for coronary artery disease (CAD) in appropriately selected patients. CAD is a leading cause of morbidity and mortality. There is extensive literature to support CCTA diagnostic and prognostic value both for stable and acute symptoms. It enables rapid and cost-effective rule-out of CAD, and permits quantification and characterization of coronary plaque and associated significance. In this comprehensive review, we detail the road traveled as CCTA evolved to include quantitative assessment of plaque stenosis and extent, characterization of plaque characteristics including high-risk features, functional assessment including fractional flow reserve-CT (FFR-CT), and CT perfusion techniques. The state of current guideline recommendations and clinical applications are reviewed, as well as future directions in the rapidly advancing field of CT technology, including photon counting and applications of artificial intelligence (AI).
RDAG U-Net: An Advanced AI Model for Efficient and Accurate CT Scan Analysis of SARS-CoV-2 Pneumonia Lesions
Authors: Lee Chih-Hui , Pan Cheng-Tang , Lee Ming-Chan , Wang Chih-Hsuan , Chang Chun-Yung , Shiue Yow-Ling
Published: September 2024

Background/Objective: This study aims to utilize advanced artificial intelligence (AI) image recog-nition technologies to establish a robust system for identifying features in lung computed tomog-raphy (CT) scans, thereby detecting respiratory infections such as SARS-CoV-2 pneumonia. Spe-cifically, the research focuses on developing a new model called Residual-Dense-Attention Gates U-Net (RDAG U-Net) to improve accuracy and efficiency in identification. Methods: This study employed Attention U-Net, Attention Res U-Net, and the newly developed RDAG U-Net model. RDAG U-Net extends the U-Net architecture by incorporating ResBlock and DenseBlock modules in the encoder to retain training parameters and reduce computation time. The training dataset in-cludes 3,520 CT scans from an open database, augmented to 10,560 samples through data en-hancement techniques. The research also focused on optimizing convolutional architectures, image preprocessing, interpolation methods, data management, and extensive fine-tuning of training parameters and neural network modules. Result: The RDAG U-Net model achieved an outstanding accuracy of 93.29% in identifying pulmonary lesions, with a 45% reduction in computation time compared to other models. The study demonstrated that RDAG U-Net performed stably during training and exhibited good generalization capability by evaluating loss values, model-predicted lesion annotations, and validation-epoch curves. Furthermore, using ITK-Snap to convert 2D pre-dictions into 3D lung and lesion segmentation models, the results delineated lesion contours, en-hancing interpretability. Conclusion: The RDAG U-Net model showed significant improvements in accuracy and efficiency in the analysis of CT images for SARS-CoV-2 pneumonia, achieving a 93.29% recognition accuracy and reducing computation time by 45% compared to other models. These results indicate the potential of the RDAG U-Net model in clinical applications, as it can accelerate the detection of pulmonary lesions and effectively enhance diagnostic accuracy. Additionally, the 2D and 3D visualization results allow physicians to understand lesions' morphology and distribution better, strengthening decision support capabilities and providing valuable medical diagnosis and treatment planning tools.
Software as a Medical Device (SaMD) in Digestive Healthcare: Regulatory Challenges and Ethical Implications
Authors: Mascarenhas Miguel , Martins Miguel , Ribeiro Tiago , Afonso João , Cardoso Pedro , Mendes Francisco , Cardoso Hélder , Almeida Rute , Ferreira João , Fonseca João , Macedo Guilherme
Published: September 2024

The growing integration of software in healthcare, particularly the rise of standalone software as a medical device (SaMD), is transforming digestive medicine, a field heavily reliant on medical imaging for both diagnosis and therapeutic interventions. This narrative review aims to explore the impact of SaMD on digestive healthcare, focusing on the evolution of these tools and their regulatory and ethical challenges. Our analysis highlights the exponential growth of SaMD in digestive healthcare, driven by the need for precise diagnostic tools and personalized treatment strategies. This rapid advancement, however, necessitates the parallel development of a robust regulatory framework to ensure SaMDs are transparent and deliver universal clinical benefits without the introduction of bias or harm. In addition, the discussion highlights the importance of adherence to the FAIR principles for data management—findability, accessibility, interoperability, and reusability. However, enhanced accessibility and interoperability require rigorous protocols to ensure compliance with data protection guidelines and adequate data security, both of which are crucial for effective integration of SaMDs into clinical workflows. In conclusion, while SaMDs hold significant promise for improving patients’ outcomes in digestive medicine, their successful integration into clinical workflow depends on rigorous data protection protocols and clinical validation. Future directions include the need for adequate clinical and real-world studies to demonstrate that these devices are safe and well-suited to healthcare settings.
Asymmetric Dimethylarginine as a Potential Mediator in the Association between Periodontitis and Cardiovascular Disease: A Systematic Review of Current Evidence
Authors: Rapone Biagio , Inchingolo Francesco , Tartaglia Giulia Margherita , De Francesco Maurizio , Ferrara Elisabetta
Published: September 2024

Background: Periodontitis, a chronic inflammatory disease, has been associated with an elevated risk of cardiovascular disease (CVD). Asymmetric dimethylarginine (ADMA), an endogenous inhibitor of nitric oxide synthase, has emerged as a potential biomarker linking periodontitis, endothelial dysfunction, and CVD. This systematic review aimed to synthesize the existing evidence on the relationship between ADMA, periodontitis, and CVD, and to evaluate ADMA’s potential as a biomarker for periodontal disease progression and its correlation with endothelial dysfunction. Methods: A comprehensive literature search was conducted in PubMed, Scopus, and Web of Science databases from their inception to March 2023. Observational and interventional studies assessing ADMA levels in patients with periodontitis and/or CVD were included. The methodological quality of the included studies was evaluated using the NIH Quality Assessment Tools. Due to the heterogeneity of the included studies, a qualitative synthesis was performed. Results: Cross-sectional studies consistently demonstrated significantly elevated ADMA levels in patients with periodontitis and CVD compared to healthy controls. The prospective cohort study indicated that successful periodontal treatment was associated with a significant reduction in ADMA levels and concomitant improvement in endothelial function. The pilot cohort study reported a significant decrease in ADMA levels following periodontal therapy in patients with chronic kidney disease. However, the randomized controlled trials did not demonstrate significant alterations in ADMA levels or endothelial function subsequent to periodontal treatment in patients with periodontitis alone. Conclusions: Periodontal treatment may effectively reduce ADMA levels and improve endothelial function, particularly in patients with comorbidities. These findings suggest that ADMA is a promising biomarker linking periodontitis, endothelial dysfunction, and CVD. However, the limitations of this study include the small number of studies, heterogeneity in the study designs, and a lack of long-term follow-up data. Further high-quality, longitudinal studies are required to confirm its clinical utility and elucidate the underlying mechanisms of these relationships. The integration of periodontal care into CVD prevention and management strategies warrants consideration, as it may contribute to mitigating the cardiovascular risk associated with periodontitis.
Comprehensive Assessment of Slovakian Hospitals Using Financial and Non-Financial Criteria in the COVID-19 Context
Authors: Jenčová Sylvia , Vašaničová Petra , Miškufová Marta
Published: September 2024

Comparing hospitals using multicriteria methods facilitates a thorough assessment of performance across multiple dimensions, supports informed decision-making, promotes accountability, and drives continuous improvement in healthcare delivery. This paper aims to apply multicriteria methods to assess hospitals in Slovakia in the pre-crisis (2019), crisis (2021), and post-crisis (2023) periods of the COVID-19 pandemic. The assessment is conducted using four multicriteria methods, i.e., a ranking method, scoring method, normed variable method, and TOPSIS method, and nonmetric multidimensional scaling (NMDS). The research sample comprises a group of hospitals classified under the sector (SK) NACE 86.1—Hospital activities. Seven indicators (financial and non-financial) were entered into the analysis. The results show that the agreement among the employed multicriteria evaluation methods was statistically significant. Moreover, the findings demonstrate that Slovak hospital rankings based on the selected criteria vary over time. The perfect quality of the NMDS models, as indicated by stress values below 0.025, shows that NMDS analysis provides a highly accurate and reliable representation of hospital comparisons. By combining multicriteria methods with NMDS, we harness the strengths of each approach to improve decision-making and achieve greater insights into intricate datasets. A comprehensive assessment of hospitals allows for the identification of the system’s strengths and weaknesses, which can be utilized to formulate new improvement strategies. As an additional benefit, this paper includes a bibliometric analysis, offering a systematic evaluation and synthesis of existing research on multicriteria evaluation methods.
The Impact of Restrictive Macroprudential Policies through Borrower-Targeted Instruments on Income Inequality: Evidence from a Bayesian Approach
Authors: Zungu Lindokuhle Talent , Greyling Lorraine
Published: September 2024

This study used the panel data from 15 emerging markets to examine the impact of restrictive macroprudential policies on income inequality from 2000–2019 using Bayesian panel vector autoregression and Bayesian panel dynamics generalised method of moments models. The chosen models are suitable for addressing multiple entity dynamics, accommodating a wide range of variables, handling dense parameterisation, and optimising formativeness and heterogeneous individual-specific factors. The empirical analysis utilised various macroprudential policy proxies and income inequality measures. The results show that when the central banks tighten systems using macroprudential policy instruments to sticker debt-to-income and financial instruments for lower-income borrowers (the bottom 40% of the income distribution), they promote income inequality in these countries while reducing income inequality for high-income borrowers (the high 1 percent of the income distribution). The impact of loan-to-value ratios was found to be insignificant in these countries. Fiscal policy through government expenditure and economic development reduces income inequality, while money supply and oil-price shocks exacerbate it. The study suggests implementing a progressive debt-to-income (DTI) ratio system in emerging markets to address income inequality among lower-income borrowers. This would adjust DTI thresholds based on income brackets, allowing lenient credit access for lower-income borrowers while maintaining stricter limits for higher-income borrowers. This would improve financial stability and reduce income disparities. Additionally, targeted financial literacy programs and a petroleum-linked basic income program could be implemented to distribute oil revenue to lower-income households. A monetary supply stabilisation fund could also be established to maintain financial stability and prevent excessive inflation.
Exploring the Emergence of Chemistry in Preschool Education: A Qualitative Perspective
Authors: Christodoulakis Nikolaos , Adbo Karina
Published: September 2024

The objective of this study was to deepen our comprehension of how children develop understanding in the field of science, particularly in chemistry. Using the framework theory as a theoretical lens enabled a focus on emergence as a dynamic change and transition. According to the framework theory, children’s science learning involves a wide range of intuitive and counterintuitive scientific concepts related to ontological and epistemological perspectives. How children transition from everyday to scientific thinking during their early years of education is influenced by ontological and epistemological stances. The objective of this study is to introduce science content—including chemical concepts to preschool children—by utilizing a play-based learning approach in a longitudinal study. The exploration of verbal and non-verbal material, specifically pertaining to chemical content and individual differences, involved implementing educational experiments and real-life or animated zooming-in videos. The results indicated a well-established physical ontological framework utilized for the systematic interpretation of submicroscopic phenomena.
Drivers of Chatbot Adoption among K–12 Teachers in Saudi Arabia
Authors: Al-Amri Nada Ali , Al-Abdullatif Ahlam Mohammed
Published: September 2024

The aim of the current study was to identify the factors influencing teachers’ acceptance of using chatbots in education. To achieve this, we employed the descriptive method, applying the conceptual framework of the unified theory of acceptance and use of technology (UTAUT2) to a sample of 406 teachers from the Eastern Province in Saudi Arabia. By applying structural equation modelling (SEM), the research results revealed that the most influential factors of chatbot acceptance among Saudi teachers were artificial intelligence literacy, followed by hedonic motivation, and then social influence. Meanwhile, performance expectancy, effort expectancy, and facilitating conditions were not significant indicators of teachers’ acceptance of using chatbots in education. In light of these findings, we recommend the following actions: focusing on artificial intelligence literacy for teachers, holding specialised workshops on chatbot applications in education, enhancing teachers’ motivation to use chatbots, and forming professional communities for teachers to exchange experiences and knowledge.
A Cognitive Load Approach to Molecular Geometries: Augmented Reality Technology and Visuospatial Abilities in Chemistry
Authors: Kenneally Conor Desmond , Bentley Brendan
Published: September 2024

Within chemistry education, methods for effectively teaching students the three-dimensional spatial arrangements of matter at the molecular level remains a topical issue. As a form of geometric problem solving, it requires learners to apply mental rotation abilities as an evolved visuospatial skill to obtain subject-specific content knowledge. Recent research into the use of Cognitive Load Theory (CLT) as a framework for instructional design in conjunction with augmented reality (AR) technology as a learning tool has begun to show promise in reducing unnecessary cognitive activity to improve learning. Yet, broader conclusions remain inconclusive, especially within the context of a learner’s mental rotation abilities. This study investigated the relationship between these factors by collecting data using a 2 × 3 experimental design that divided a sample of Year 10 students (n = 42) into two groups. The intervention group (n = 24) used mobile devices utilising AR technology with instructional 3D molecular geometry content featuring design principles based on CLT to encourage hand movements to rotate three-dimensional molecular structures. The non-AR-based control group (n = 18) was taught using traditional methods. Analysis of the data revealed participants using AR technology that featured CLT design principles experienced less cognitive load and improved achievement in post-testing compared to those taught using traditional methods, suggesting under certain conditions, the use of hand movement applied to AR design material improves learning.
Assessment of the Effects of ZnO and CuO Engineered Nanoparticles on Physicochemical Properties of Volcanic Ash Soil and Phosphorus Availability
Authors: Suazo-Hernández Jonathan , Sans-Serramitjana Eulàlia , de la Luz Mora María , Fuentes Barbara , de los Ángeles Sepúlveda María , Silva-Yumi Jorge , Celletti Silvia , Celi Luisella , Rivas Sheina , Ruiz Antonieta
Published: September 2024

The presence of engineered nanoparticles (ENPs) in soil systems can modify their properties and the availability of nutrients. This study evaluated the effect of 1% CuO or ZnO ENPs on the physicochemical properties and on the phosphorus (P) adsorption–desorption processes of a volcanic ash soil (Lautaro; LAU). The dynamics of P were conducted through kinetic and isotherm batch experiments. The results showed that LAU soil with 1% CuO or ZnO ENPs increased pHH2O (from 5.67 to 6.03 and 6.82, respectively), electrical conductivity (from 0.119 to 0.143 and 0.150 dS m−1, respectively), Zn availability (597.7 times higher for LAU with 1% ZnO ENPs in relation to soil without ENPs), and Cu availability (41.8 times higher for LAU with 1% CuO ENPs in relation to soil without ENPs). Moreover, the presence of ENPs decreased Brunauer, Emmett, and Teller specific surface area. The adsorption kinetic studies of P on LAU soil without and with 1% ENPs fitted well to the Elovich model (r2 ≥ 0.923), which indicated a chemiadsorption mechanism, whereas the adsorption isotherms were described by Langmuir–Freundlich model (r2 ≥ 0.939). The desorption percentage was LAU > LAU + 1% CuO–ENPs > LAU + 1% ZnO–ENPs, demonstrating an increased stability of the P–soil surface binding with 1% ENPs. Co–existing NO3−, SeO42−, and SO42− anions did not generate a steric hindrance between P and LAU soil binding. Finally, both ENPs could alter the quality of the soil due to changes in their physicochemical properties and decrease the availability of P in volcanic ash soils.
Enhanced Foliar Litter Decomposition Rate of Pinus massoniana When Admixed with Broadleaf Species
Authors: Xie Jinjuan , Lei Pifeng , Zhu Yaping
Published: September 2024

In the global ecosystem, the slow decomposition of coniferous forest litter has caused a number of ecological problems, among which is the decay of China’s Pinus massoniana litter. It has been pointed out that converting pure P. massoniana plantations into mixed forests with broadleaf species can improve ecosystem services. Therefore, the selection of mixed species is key for the success or failure of the conversion of near-natural forests. In this study, from the perspective of apoplastic decomposition, the leaf litter of P. massoniana was mixed with three common native broadleaf species, namely Choerospondias axillaries, Cinnamomum camphora, and Cyclobalanopsis glauca, using an indoor incubation method to systematically analyse the differences in the decomposition rates of apoplastic material in each mixture, and to provide a theoretical basis for the selection and mixing of tree species for the management of near-natural forests in P. massoniana forests. After 175 days of indoor incubation of the foliar litter under dark conditions at 25 °C, the residual dry matter of the mixed apoplastic litter of P. massoniana and the three broadleaf trees was lower than that of P. massoniana. It indicated that the incorporation of broadleaf apoplastic foliage promoted litter decomposition, with the most pronounced effect in the case of admixture with C. Camphora. Compared with the group of pure P. massoniana alone, the remaining mass and residual rate decreased by 0.56 g and 9.45%, respectively. The regression equation of Olson’s negative exponential decay model showed that the P. massoniana + C. Camphora mixture had the fastest decomposition rate (k) of 1.305, an increase of 0.237, a decrease in half-life of 0.11 years, and a decrease in turnover period of 0.49 year, compared to the P. massoniana alone group. Most of the measured values throughout the incubation period were significantly lower than the predicted values, suggesting that there was a non-additive and synergistic effect of litter mixing.