bluuebunny/crossref_metadata_2025_split huggingface dataset:
USO DE LAS TECNOLOGÍAS DE COMUNICACIÓN E INFORMACIÓN DE LOS ESTUDIANTES UNIVERSITARIOS
Authors: Rivadeneira Vargas Javier Esteban , Herrera Albán Daniel Alberto , Pozo Mora Cesar Paul , Sailema Perez Yessenia de los Ángeles , Soto Ayala Mónica Patricia , Moyano Calero Willian 
Published: February 2025

Introducción: Las tecnologías de la información y la comunicación, son un conjunto de recursos, instrumentos, aplicaciones computacionales, redes y plataformas que facilitan la incorporación, manipulación, retención y difusión de la información. Objetivo: Analizar el uso y preferencias que le dan los estudiantes universitarios a las tecnologías de información y comunicación. Métodos: Enfoque cuantitativo, observacional-transversal, descriptivo. La población estuvo compuesta por los estudiantes de la Carrera de Enfermería de una Universidad pública del Ecuador, de donde se seleccionó una muestra de 238 estudiantes mediante muestreo aleatorio simple, a quienes se les aplicó un cuestionario autoadministrado compuesto por 4 dimensiones: el uso general del teléfono móvil, la utilización de las aplicaciones, de la red, y el despliegue de tecnologías tanto en el hogar como en el aula. Resultados: El 51,3% de los estudiantes informó que utilizaba sus teléfonos celulares principalmente para comunicarse con la familia y los compañeros, mientras que el 34,9% indicó que los utilizaba para actividades académicas, el WhatsApp se convirtió en la plataforma de redes sociales más utilizada a diario, con un 72,7% de uso. En el contexto de los hogares, los estudiantes reconocieron que utilizaban las tecnologías de información y comunicación para actividades de ocio, como escuchar música 53,8% y participar en tareas grupales colaborativas con compañeros de estudios 46,6%. En el aula, son usadas por su colaboración, creatividad y a la facilitación del aprendizaje. Conclusiones: Los estudiantes utilizan

las Tecnologías de la Información y Comunicación con fines de comunicación, ocio y educativos.
Patologías de la yoidad: una lectura secular de La enfermedad mortal
Authors: Rudy Hiller Fernando 
Published: February 2025

Rudy, Fernando. Patologías de la yoidad: una lectura secular de La enfermedad mortal. En este artículo abordo, con ayuda de Søren Kierkegaard, las preguntas siguientes: ¿cómo es posible que una persona cambie para mejor? y ¿cuáles son los principales obstáculos que enfrenta en su proyecto de cambio? Toda persona, sostiene Kierkegaard, es una síntesis de facticidad y posibilidad, y tiene como tarea forjarse un yo que unifique adecuadamente ambos polos de su ser. De acuerdo con él, los fallos en alcanzar una síntesis tal se manifiestan como desesperación. De acuerdo con mi análisis, en el caso de la persona que busca cambiar, la desesperación se revela como un impotente cinismo o como un omnipotente fantaseo. En el artículo diagnostico esta situación con base en La enfermedad mortal y ofrezco, asimismo, una vía de solución que procura prescindir de los elementos religiosos que apuntalan dicha obra.
ДОСЛІДЖЕННЯ РУЙНУВАННЯ ЕМУЛЬСІЇ НАФТИ З ВОДОЮ ДОЛИНСЬКОГО НАФТОВОГО РОДОВИЩА ПІД ДІЄЮ ТЕМПЕРАТУРИ І ДЕЕМУЛЬГАТОРА
Authors: Василюк Л. М. 
Published: February 2025

Наведено особливості процесу утворення нафтової емульсії при видобуванні обводненої нафтової продукції. Розглянуто типи нафтових емульсій та їхні характеристики. Охарактеризовано методи деемульсації нафти. Стосовно до умов Долинського нафтового родовища вивчено склад нафтових емульсій та їх стабільність за температур 21 °С та 50 °С. Досліджено нафтову емульсію Долинського нафтового родовища такого складу: об’ємна частка зв’язної води – 15 %, об’ємна частка механічних домішок – 0,4 %; вміст хлористих солей – 10020 мг/л; масова частка парафіну – 5,3 %; масова частка силікагелевих смол – 6,1 %; масова частка асфальтенів – 0,14 %. Досліджено термохімічний метод деемульсації нафти шляхом одночасного підігрівання емульсії до 50 °С і введення в неї деемульгаторів ПМ-А, ПМ-Б і Дісольван 2830. Дослідження деемульгаторів проводили за відомою методикою Botl test. Експериментально встановлено, що підвищення температури емульсії у можливих межах не дозволяє повністю зневоднити нафту. Ефективність руйнування емульсії залежить від типу деемульгатора і його концентрації в емульсії. За температури 50 °С і часу відстоювання утвореної емульсії 360 хв ефективність зневоднення емульсії становить: за відсутності деемульгатора – 43%, при використанні різних деемульгаторів – від 80 до 97 %. З досліджених деемульгаторів найефективнішим виявився деемульгатор марки ПМ-А з концентрацією 50 г/т. Таку саму ефективність зневоднення отримують при концентрації ПМ-А в емульсії 70 г/т, але ця концентрація є явно завищеною, оскільки аналогічний результат щодо зневоднення емульсії отримують при меншій кон-центрації даного деемульгатора (50 г/т). Деемульгатор Dissolvan 2830 характеризується меншою ефективністю зневоднення в порівнянні з деемульгаторами марки ПМ. Характерним є те, що при використанні деемульгаторів ПМ-А та ПМ-Б ефективність зневоднення емульсії різко зростає з моменту введення їх в емульсію, а потім мало змінюється, що дозволяє зменшити тривалість процесу деемульсації нафти. При використанні деемульгатора Dissolvan 2830 відбувається плавне зростання в часі ефективності зневоднення, що вимагатиме збільшення тривалості періоду деемульсації нафти. Рекомендовано здійснювати деемульсацію нафти Долинського родовища шляхом нагрівання її до 50 °С і застосування деемульгатора ПМ-А з витратою 50 г/т.
Forecasting Weekly Stock Price of PT. Aneka Tambang Tbk (ANTM) Using ARIMA Box-Jenkins Method
Authors: Wardhani Andreanne Intan Sulistyo , Yudhanegara Mokhammad Ridwan 
Published: February 2025

<p class="IJASEITAbtract">Stock price movements in the dynamic economic world require investors and companies to be able to predict future price changes. One method that can be used to predict is Autoregressive Integrated Moving Average (ARIMA). The application of the ARIMA method to forecasting the share price of PT Aneka Tambang Tbk (ANTM) for 4 weeks produces equation <em> </em>obtained from ARIMA (3,1,0) as the best model.<em></em></p>
Analysis and mitigation of fire and explosion hazards in hospital environments from a biomedical engineering perspective
Authors: Ibáñez-Cruz Augusto Jorge Antonio , Espinoza-Morriberon Dante , Vergara-Florián Alejandra Micaela Elena , Algoner William C. 
Published: February 2025

BackgroundHospitals are complex and dynamic facilities that house vulnerable people, medical equipment, and hazardous materials, making them susceptible to fires and explosions with potentially catastrophic effects. This study aims to understand and address fire and explosion risks in hospital environments using biomedical engineering, safety, and fire prevention concepts to develop effective mitigation strategies.Materials and MethodsThe study employed a mixed-methods approach, integrating quantitative and qualitative techniques. Data from an insurance and reinsurance company in Peru were analyzed, and surveys, data analysis, and interviews were conducted. The preferred reporting items for systematic review and meta-analysis (PRISMA) methodology was also applied to conduct a thorough literature review.ResultsThe results revealed the most frequent risk factors in hospital settings and identified the most effective mitigation strategies. Implementing these strategies resulted in a considerable decrease in the incidences of fires and explosions.DiscussionThe research provides a comprehensive explanation of hospital fire and explosion risks and proposes evidence-based strategies to improve the safety. These results underscore the relevance of biomedical engineering in managing risks within hospital settings. Despite certain limitations, the study lays a firm foundation for future research aimed at improving hospital safety.
Exploring precision therapeutics: computational design of antisense oligonucleotides targeting AXL gene transcripts in multiple sclerosis treatment management
Authors: Shreevatsa Bhargav , Nagaraj Abhigna , Dharmashekar Chandan , Jain Anisha , Harendra Bhavana , Siddalingegowda Siddesh V. , Al-Mazroua Haneen A. , Ahmad Sheikh F. , Prasad Shashanka K. , Srinivasa Chandrashekar , Shivamallu Chandan , Kollur Shiva Prasad 
Published: February 2025

Multiple sclerosis (MS) is a chronic autoimmune illness characterized by demyelination, neurodegeneration, and inflammation in the central nervous system. The AXL gene, which codes for a receptor tyrosine kinase, has emerged as a promising therapeutic target due to its involvement in neuroinflammation and oligodendrocyte dysfunction. In the current study, we employed in silico techniques to design Antisense Oligonucleotides (ASOs) that selectively target AXL gene transcripts to modulate AXL expression and mitigate MS pathology. Three ASOs, A1, A2, and A3, were designed to specifically target the 5′ untranslated region (5′UTR) and coding region of the AXL gene transcripts. The ASOs were optimized with a focus on stability, binding affinity, and specificity towards AXL mRNA while minimizing off-target effects. To investigate ASO-mRNA interactions and gauge their ability to alter AXL expression, Molecular Docking was performed. Our analyses showed that A1, A2, and A3 had substantial interactions with AXL mRNA, with binding affinities of −9.5 kcal/mol, −10.8 kcal/mol, and −10.6 kcal/mol, respectively. The targeting of AXL gene transcripts through ASOs shows promise in reducing MS symptoms. Precision ASO-based therapies could effectively manage MS by targeting the essential pathways involved in the disease. ASOs provide a highly targeted approach for treating MS and offer a precise therapeutic strategy for this debilitating condition. The study lays the groundwork for future in vitro and in vivo studies to confirm the therapeutic potential of these ASOs for the treatment of MS.
Gut microbiota interacting with vitamin D but not anandamide might contribute to the pathogenesis of preeclampsia: a preliminary study
Authors: Han Xiao-Qiang , Jiang Hui-Hui , Chen Meng-Ling , Han De-Yang , Zhou Su-Fen , Wang Jin-Wen , Ji Shu-Shen , Wang Ling-Yun , Lou Jing-Wei , Li Ming-Qun 
Published: February 2025

IntroductionPreeclampsia (PE) is a pregnancy-specific multisystem disorder and a leading cause of maternal and perinatal mortality globally. Despite numerous studies highlighting the potential roles of gut microbiota, anandamide (AEA), and Vitamin D (VitD) in PE, none have established them as reliable biomarkers for predicting disease onset. Moreover, their interactions in late-stage pregnancy women remain poorly understood.MethodsThirty-four preeclamptic patients (called PE group) and thirty-nine matched healthy late-pregnant women (called LP group) were involved in this case-control study. Fecal samples, which were used to acquire the diversity and composition of gut microbiota, were analyzed by 16S rRNA gene sequencing. Plasma AEA concentrations and serum VitD levels were determined by high-performance liquid chromatography-mass spectrometry (HPLC-MS) and liquid chromatography-tandem mass spectrometry (LC-MS/MS), respectively.ResultsIn this study, β diversity but not α diversity significantly differed between the LP and PE groups. Compared with the LP group, the relative abundances of Prevotella, Erysipelotrichaceae_UCG-003, and Dorea were increased dramatically in the PE group, whereas the relative abundances of Subdoligranulum, Parabacteroides, Bacteroides were significantly decreased in the PE group. Furthermore, women with PE had a substantially lower plasma level of AEA and a marked decrease in serum VitD compared to normal late-pregnant women. Lastly, although the serum level of AEA was not significantly correlated with VitD or any of the top 6 marker genera, VitD was significantly negatively correlated with the relative abundance of Dorea, a novel finding in this context.DiscussionThe gut microbiota profile of the PE group was significantly different from that of the LP group. Although no significant correlations were identified between the plasma AEA levels and serum VitD levels or any of the top 6 identified marker genera, a significant negative correlation was observed between VitD and Dorea, indicating VitD and gut microbiota have the potential to be combined targets for early diagnosis and management of PE.
Machine learning cluster analysis identifies increased 12-month mortality risk in transcatheter aortic valve replacement recipients
Authors: Meredith Thomas , Mohammed Farhan , Pomeroy Amy , Barbieri Sebastiano , Meijering Erik , Jorm Louisa , Roy David , Kovacic Jason , Feneley Michael , Hayward Christopher , Muller David , Namasivayam Mayooran 
Published: February 2025

BackgroundLong-term mortality risk is seldom re-assessed in contemporary clinical practice following successful transcatheter aortic valve implantation (TAVR). Unsupervised machine learning permits pattern discovery within complex multidimensional patient data and may facilitate recognition of groups requiring closer post-TAVR surveillance.MethodsWe analysed and differentiated routinely collected demographic, biochemical, and cardiac imaging data into distinct clusters using unsupervised machine learning. k-means clustering was performed on data from 200 patients who underwent TAVR for severe aortic stenosis (AS). Input features were ranked according to their influence on cluster assignment. Survival analyses were performed with Kaplan–Meier and Cox proportional hazards models. Nested cox models were used to identify any incremental prognostic benefit cluster assignment achieved beyond conventional risk scores.ResultsAnalysis identified two distinct clusters. Compared to Cluster 1, Cluster 2 demonstrated significantly worse all-cause mortality at 12 months (HR 6.3, p &lt; 0.01), and was characterised by more advanced cardiac remodelling with worse indices of multi-chamber cardiac function, as quantified by strain imaging. Cluster assignment demonstrated greater predictive power for 12-month mortality as compared with conventional risk and frailty calculators.Conclusionk-means clustering identified two prognostically distinct phenogroups of patients who had undergone TAVR with better discriminatory power than conventional risk and frailty calculators. Our results highlight the utility of machine learning applications for clinical risk prediction and scope to improve patient surveillance.
Adaptive learning in bionics: transforming science education
Authors: Honke Nadine , Becker-Genschow Sebastian 
Published: February 2025

IntroductionAdaptive learning platforms offer innovative teaching approaches by tailoring educational content to individual learner’s needs, abilities, and paces.MethodsThis study investigates the effects of an adaptive digital learning platform on user experience, motivation, and learning outcomes among 56 sixth-grade students from two German grammar schools. Students completed three bionics-focused modules— “polar bear”, “heat transfer”, and “temperature and heat”—integrated into science lessons. Data from questionnaires and performance tests assessed prior knowledge, learning success, cognitive activation, and situational interest.ResultsThe findings indicate that 98% of students found digital media motivating, with 81% favoring a hybrid mix of traditional and digital teaching methods. Positive emotional responses were reported by 62% of participants, though 38% experienced uncertainty. The “polar bear” module achieved the highest learning gain (+41%), followed by “heat transfer” (+23%) and “temperature and heat” (+13%) module.DiscussionThese results suggest that adaptive digital learning platforms can enhance learning outcomes and cognitive engagement, particularly when the content aligns with student interests and needs.
Training of female health workers (FHWs) to enhance the advocacy and communication skills on COVID-19 vaccine and routine Immunization in District Peshawar Khyber Pakhtunkhwa (KP) Pakistan in 2023—a report from the field
Authors: Al-Gunaid Magid , Hussain Zakir , Daoud Leen , Akram Khurram 
Published: February 2025

IntroductionIn 2021, a comprehensive evaluation was conducted across five countries, including Pakistan, to explore the factors influencing the demand for COVID-19 vaccines among priority groups. The study uncovered significant challenges, including low vaccination rates among females, limited trust in the COVID-19 vaccine, accessibility issues, and a notable gap in dose administration.MethodsTo address these challenges, a targeted pilot intervention was proposed in Peshawar, Pakistan. This intervention aimed to enhance vaccine demand among young women (aged 18–24), including pregnant and lactating women (PLWs), by equipping approximately 300 female health workers (FHWs) with improved advocacy and communication skills. These skills were designed to combat vaccine hesitancy and increase vaccine acceptance among women. Moreover, efforts were made to strengthen social support from community leaders. The pilot initiative encompassed baseline and endline evaluations to assess its impact. The baseline evaluation involved analyzing existing vaccination data, disaggregated by age and gender. Key informant interviews (KIIs) were conducted to capture qualitative insights into the perceptions of vaccines within the target population.FindingsData from the Department of Health KP and Expanded Program on Immunization Management Information System (EPIMIS) highlighted improvements in both COVID-19 and routine Expanded Program on Immunization (EPI) vaccinations across 25 union councils (UCs) in district Peshawar. KIIs with stakeholders, including health workers and community influencers, revealed enhanced knowledge and willingness to vaccinate, particularly among PLWs and females aged 18–24. The evaluation also observed increased confidence and reduced vaccine hesitancy due to advocacy sessions. Additionally, training of FHWs significantly improved their knowledge and attitudes towards COVID-19 vaccination and routine EPI, contributing to the overall success of the intervention. Monitoring visits further validated the effective conduct of advocacy sessions by trained health workers, leading to increased vaccination uptake in the community.ConclusionThe comprehensive approach undertaken in this pilot intervention aimed not only to improve vaccine uptake but also to bolster confidence in the COVID-19 vaccine within the community. The findings and outcomes of this initiative provided valuable insights for future public health strategies, particularly in addressing vaccine hesitancy and increasing vaccine acceptance among priority groups.
Interactions between NAD+ metabolism and immune cell infiltration in ulcerative colitis: subtype identification and development of novel diagnostic models
Authors: Tian Linglin , Gao Huiyang , Yao Tian , Chen Yuhao , Gao Linna , Han Jingxiang , Zhu Lanqi , Huang He 
Published: February 2025

BackgroundUlcerative colitis (UC) is a chronic inflammatory disease of the colonic mucosa with increasing incidence worldwide. Growing evidence highlights the pivotal role of nicotinamide adenine dinucleotide (NAD+) metabolism in UC pathogenesis, prompting our investigation into the subtype-specific molecular underpinnings and diagnostic potential of NAD+ metabolism-related genes (NMRGs).MethodsTranscriptome data from UC patients and healthy controls were downloaded from the GEO database, specifically GSE75214 and GSE87466. We performed unsupervised clustering based on differentially expressed NAD+ metabolism-related genes (DE-NMRGs) to classify UC cases into distinct subtypes. GSEA and GSVA identified potential biological pathways active within these subtypes, while the CIBERSORT algorithm assessed differential immune cell infiltration. Weighted gene co-expression network analysis (WGCNA) combined with differential gene expression analysis was used to pinpoint specific NMRGs in UC. Robust gene features for subtyping and diagnosis were selected using two machine learning algorithms. Nomograms were constructed and their effectiveness was evaluated using receiver operating characteristic (ROC) curves. Reverse transcription quantitative polymerase chain reaction (RT-qPCR) was conducted to verify gene expression in cell lines.ResultsIn our study, UC patients were classified into two subtypes based on DE-NMRGs expression levels, with Cluster A exhibiting enhanced self-repair capabilities during inflammatory responses and Cluster B showing greater inflammation and tissue damage. Through comprehensive bioinformatics analyses, we identified four key biomarkers (AOX1, NAMPT, NNMT, PTGS2) for UC subtyping, and two (NNMT, PARP9) for its diagnosis. These biomarkers are closely linked to various immune cells within the UC microenvironment, particularly NAMPT and PTGS2, which were strongly associated with neutrophil infiltration. Nomograms developed for subtyping and diagnosis demonstrated high predictive accuracy, achieving area under curve (AUC) values up to 0.989 and 0.997 in the training set and up to 0.998 and 0.988 in validation sets. RT-qPCR validation showed a significant upregulation of NNMT and PARP9 in inflamed versus normal colonic epithelia, underscoring their diagnostic relevance.ConclusionOur study reveals two NAD+ subtypes in UC, identifying four biomarkers for subtyping and two for diagnosis. These findings could suggest potential therapeutic targets and contribute to advancing personalized treatment strategies for UC, potentially improving patient outcomes.
Exosomes secreted by ATF3/Nrf2-mediated ferroptotic renal tubular epithelial cells promote M1/M2 ratio imbalance inducing renal interstitial fibrosis following ischemia and reperfusion injury
Authors: Tang Qiao , Xie Jiatao , Wang Yifei , Dong Chong , Sun Qian 
Published: February 2025

BackgroundSevere renal ischemia and reperfusion injury (IRI) progresses to renal interstitial fibrosis (RIF) with limited therapeutic strategies. Although ferrptosis and macrophage polarization both play important roles in this model, their specific pathogenesis and interactions have not been elucidated. Therefore, we aimed to explore the mechanisms by which ferrotosis occurs in renal tubular epithelial cells (RTECs) and ferroptotic cell-derived exosomes induce macrophage polarization in IRI-related RIF model.MethodsIn vivo, C57BL/6J mice were randomly divided into four groups: sham group, ischemia and reperfusion (IR) group, IR + Ferrostatin-1 (Fer-1) group, and IR +ATF3 knockdown (ATFKD) group. In vitro, RTECs were divided into control (CON) group, hypoxia/reoxygenation (HR) group, HR +Fer-1 group, HR + siRNA-ATF3 (siATF3) group.ResultCompared with the sham group, the IR group showed more severe kidney injury in HE staining, more collagen fibers in Masson staining, and higher α-SMA expression levels in immunohistochemistry. Total iron and MDA content increased while GSH content decreased. The IR group had more significant mitochondrial damage and higher PTGS2 and TFRC mRNA levels than those in the sham group. Compared with the IR group, the above indexes were all alleviated in the IR+Fer-1 or IR+ATF3KD groups. In addition, the protein expressions of ATF3, Nrf2 and HO-1 in the IR group were increased than those in sham group. Compared with the IR group, ATF3 expressions in the IR+Fer-1 or IR+ATF3KD groups were decreased, and the protein contents of Nrf2 and HO-1 were further increased. Moreover, there were higher levels of M2 markers (Arg1, TGF-β and IL-10 mRNA) in the IR group than those in the sham group, and lower levels in the IR+Fer-1 group or in the IR+ATF3KD group compared with the IR group. The results of in vitro experiment are consistent with those of in vivo experiment. Mechanistically, the release of exosomes carrying miR-1306-5p by the HR group promoted more M2 macrophage.ConclusionATF3 might accelerate the ferroptosis by inhibiting Nrf2/ARE pathway, and exosomes from ferroptotic cells reduced the M1/M2 macrophage ratio, promoting fibrosis.