bluuebunny/crossref_metadata_2025 huggingface dataset:
Effectiveness of Non-Pharmacological Interventions in Reducing Dental Anxiety Among Children with Special Needs: A Scoping Review with Conceptual Map
Authors: Alkahtani Zuhair Motlak
Published: January 2025

Background: Children with special needs often need tailored approaches to oral healthcare to address their unique needs effectively. It is essential to analyze the effectiveness of non-pharmacological management in reducing dental anxiety among special needs children during dental treatment. Methods: Five electronic databases, PubMed, Scopus, Web of Science, Embase, and Google Scholar, were searched from 2007 to August 2024 for randomized control trials and observational studies comparing the effectiveness of non-pharmacological techniques in reducing dental anxiety during invasive and noninvasive dental treatment. The primary outcomes of the studied intervention were reduced dental anxiety and improved behavior during dental treatment. The conceptual map was created to understand the need for assessment and behavior management for special needs children (SN). Results: Nineteen articles qualified for the final analysis from 250 screened articles. Included studies evaluated the effect of strategies applied clinically, such as audio–visual distraction, sensory-adapted environment, and virtual reality. The included studies measured the trivial to large effect of measured interventions and supported non-pharmacological interventions in clinical settings. Conclusion: Most basic non-pharmacological interventions showed a trivial to large reduction in dental anxiety among SN patients. The conceptual map developed in this study supports the need for non-pharmacological interventions as they are cost-effective and create a positive environment in dental clinics. However, more studies need to focus on non-pharmacological behavior interventions in SN children to support the findings of this scoping review.
Microbiome Modulation in Pediatric Leukemia: Impact on Graft-Versus-Host Disease and Treatment Outcomes: A Narrative Review
Authors: Todor Samuel Bogdan , Ichim Cristian
Published: January 2025

The gut microbiome significantly influences the outcomes of pediatric leukemia, particularly in patients undergoing hematopoietic stem cell transplantation (HSCT). Dysbiosis, caused by chemotherapy, antibiotics, and immune system changes, contributes to complications such as graft-versus-host disease (GVHD), gastrointestinal issues, and infections. Various microbiome-related interventions, including prebiotics, probiotics, postbiotics, and fecal microbiota transplantation (FMT), have shown potential in mitigating these complications. Specific microbial signatures have been linked to GVHD risk, and interventions like inulin, Lactobacillus, and SCFAs (short-chain fatty acids), particularly butyrate, may help modulate the immune system and improve outcomes. FMT, while showing promising results in restoring microbial balance and alleviating GVHD, still requires careful monitoring due to potential risks in immunocompromised patients. Despite positive findings, more research is needed to optimize microbiome-based therapies and ensure their safety and efficacy in pediatric leukemia care.
Effects of a Virtual Reality-Based Aggression Control Program on Children with Autism Spectrum Disorder: A Case Study
Authors: Jung Miran , Park Jaewon
Published: January 2025

Background/Objectives: Aggression is a major challenge for children with autism spectrum disorder (ASD), their family members, friends, and teachers because it can pose a threat or harm not only to the children with ASD but also to others. This study is a case study aimed at verifying the effectiveness of a virtual reality-based aggression control program for children with ASD. Methods: The participants were two children (one was a 10-year-old boy and the other was a 6-year-old girl) who participated in the ACAA (Aggression Replacement Training for Children and Adolescents with ASD) Program for eight sessions over three weeks. Results: The frequency (C1: 48 → 3; C2: 32 → 3) and severity of aggressive behaviors in both participants decreased after the intervention compared to before. Additionally, overall problematic behaviors were also reduced after the intervention (C1: 85 → 70; C2: 87 → 64). Furthermore, both participants demonstrated a slight increase in their levels of adaptation (C1: 17 → 20; C2: 16 → 18). Conclusions: The effectiveness of the ACAA program has been demonstrated in reducing levels of aggression in children with ASD. Therefore, the ACAA program may contribute to helping aggressive children with ASD live in harmony with others in society and promote independence.
From Vulnerability to Defense: The Role of Large Language Models in Enhancing Cybersecurity
Authors: Kasri Wafaa , Himeur Yassine , Alkhazaleh Hamzah Ali , Tarapiah Saed , Atalla Shadi , Mansoor Wathiq , Al-Ahmad Hussain
Published: January 2025

The escalating complexity of cyber threats, coupled with the rapid evolution of digital landscapes, poses significant challenges to traditional cybersecurity mechanisms. This review explores the transformative role of LLMs in addressing critical challenges in cybersecurity. With the rapid evolution of digital landscapes and the increasing sophistication of cyber threats, traditional security mechanisms often fall short in detecting, mitigating, and responding to complex risks. LLMs, such as GPT, BERT, and PaLM, demonstrate unparalleled capabilities in natural language processing, enabling them to parse vast datasets, identify vulnerabilities, and automate threat detection. Their applications extend to phishing detection, malware analysis, drafting security policies, and even incident response. By leveraging advanced features like context awareness and real-time adaptability, LLMs enhance organizational resilience against cyberattacks while also facilitating more informed decision-making. However, deploying LLMs in cybersecurity is not without challenges, including issues of interpretability, scalability, ethical concerns, and susceptibility to adversarial attacks. This review critically examines the foundational elements, real-world applications, and limitations of LLMs in cybersecurity while also highlighting key advancements in their integration into security frameworks. Through detailed analysis and case studies, this paper identifies emerging trends and proposes future research directions, such as improving robustness, addressing privacy concerns, and automating incident management. The study concludes by emphasizing the potential of LLMs to redefine cybersecurity, driving innovation and enhancing digital security ecosystems.
Remote Sensing-Based Assessment of the Long-Term Expansion of Shrimp Ponds Along the Coastal and Protected Areas of the Gulf of California
Authors: González-Rivas David A. , Ortega-Rubio Alfredo , Tapia-Silva Felipe-Omar
Published: January 2025

Shrimp farming has expanded over coastal areas in Mexico, particularly in the protected regions of Sonora and Sinaloa. Over the past 30 years, the economic activity associated with these farms has grown so much that the amount of shrimp produced in these ponds now exceeds that harvested from traditional shrimp fisheries. Establishing shrimp ponds has led to significant land changes. The construction of these ponds has fragmented local ecosystems, resulting in permanent alterations to areas such as floodplains, mangrove forests, and dunes, many of which are protected zones. This study aimed to investigate the long-term growth of shrimp farms from 1993 to 2022 and their impact on land-use changes in surrounding ecosystems, focusing on protected areas in the Sinaloa and Sonora coastal regions. We analyzed Landsat images using the Google Earth Engine platform. Our findings indicate that shrimp farm development over the past three decades has been extensive, with protected areas experiencing fragmentation and changes. Remote sensing and platforms like Google Earth Engine enable the effective monitoring of these spatiotemporal changes and their impacts, helping to identify the most affected areas.
Novel Winding Method for Enhanced Fault Diagnosis of IPMSMs Using Variable Reluctance Resolvers and Improved Robustness
Authors: Lee Sung-Won , Kang Jun-Kyu , Heo Jun-Hyeok , Hur Jin
Published: January 2025

Recently, the rapid proliferation of eco-friendly mobility solutions has driven an increasing demand for high-efficiency, high-power, compact, and reliable traction motors. In the eco-friendly mobility sector, electric mobility commonly employs Interior Permanent Magnet Synchronous Motors (IPMSMs) due to their high efficiency, high power, and compact size. However, ensuring reliability requires effective fault diagnosis. Among various faults, eccentricity in traction motors can degrade performance characteristics, including vibration, noise, and torque precision, thereby impairing driving performance. This paper proposes a novel winding method for Variable Reluctance (VR) resolvers and introduces a fault diagnosis approach for eccentricity using Finite Element Method (FEM) analysis. By employing this novel winding method, the direction of eccentricity occurrence can be effectively identified. Additionally, this method demonstrates robustness against defects, such as open-circuit faults, compared to a conventional winding method. Therefore, the proposed winding method contributes to improving the reliability and stability of IPMSMs through fault diagnosis and ensures robustness against open-circuit faults in the VR resolver.
Stroke Detection and Monitoring by Means of a Multifrequency Microwave Inversion Approach
Authors: Fedeli Alessandro , Schenone Valentina , Estatico Claudio , Randazzo Andrea
Published: January 2025

In the area of biomedical diagnostics, microwave imaging techniques have been recently proposed for performing brain stroke detection and monitoring. Indeed, theoretically, these techniques make it possible to meet the timeliness requirements of such a diagnosis with portable systems. Moreover, relying on the use of microwaves, they are noninvasive and allow continuous monitoring of critical patients. In this paper, the microwave imaging problem is solved by exploiting multifrequency data by an inexact-Newton method formulated in the framework of non-constant exponent Lebesgue spaces. First, the method is numerically validated with three-dimensional head models affected by anatomically-realistic strokes. Then, a further assessment through experimental data obtained with a cylindrical phantom is conducted. A quite accurate reconstruction of the variations of dielectric properties inside the patient’s head due to the insurgence of stroke is obtained in both numerical and experimental cases, showing the potentiality of the proposed approach.
Hardware Optimized Modular Reduction
Authors: Magyari Alexander , Chen Yuhua
Published: January 2025

We introduce a modular reduction method that is optimized for hardware and outperforms conventional approaches. By leveraging calculated reduction cycles and combinatorial logic, we achieve a remarkable 30% reduction in power usage, 27% reduction in Configurable Logic Blocks (CLBs), and 42% fewer look-up tables (LUTs) than the conventional implementation. Our Hardware-Optimized Modular Reduction (HOM-R) system can condense a 256-bit input to a four-bit base within a single 250 MHz clock cycle. Further, our method stands out from prevalent techniques, such as Barrett and Montgomery reduction, by eliminating the need for multipliers or dividers, and relying solely on addition and customizable LUTs. This innovative method frees up FPGA resources typically consumed by power-intensive DSPs, offering a compelling low-power, low-latency alternative for diverse design needs.
Real-Time Power Management of Plug-In Electric Vehicles and Renewable Energy Sources in Virtual Prosumer Networks with Integrated Physical and Network Security Using Blockchain
Authors: Sifakis Nikolaos , Armyras Konstantinos , Kanellos Fotis
Published: January 2025

This paper presents a blockchain-enabled Multi-Agent System (MAS) for real-time power management in Virtual Prosumer (VP) Networks, integrating Plug-in Electric Vehicles (PEVs) and Renewable Energy Sources (RESs). The proposed framework addresses critical challenges related to scalability, security, and operational efficiency by developing a hierarchical MAS architecture that optimizes the scheduling and coordination of geographically distributed PEVs and RESs. Unlike conventional business management systems, this study integrates a blockchain-based security mechanism within the MAS framework, leveraging Proof of Authority (PoA) consensus to enhance transaction security while addressing scalability and energy consumption concerns. The system further employs advanced Particle Swarm Optimization (PSO) to dynamically compute optimal power set-points, enabling adaptive and efficient energy distribution. Additionally, hierarchical aggregation of transactions at lower MAS layers enhances computational efficiency and system resilience under high-traffic and partial network failure conditions. The proposed framework is validated through large-scale simulations spanning four major cities in Greece, demonstrating its scalability, reliability, and efficiency under diverse operational scenarios. Results confirm that the system effectively balances energy supply and demand while maintaining secure and transparent transactions. Despite these advancements, practical deployment challenges remain, including synchronization delays in geographically distributed agents, legacy system integration, and blockchain energy consumption. Future research directions include investigating more advanced consensus mechanisms (e.g., Proof of Task), machine learning-driven predictive optimization, real-world large-scale testing, and federated learning models for decentralized decision-making. The proposed framework offers a scalable, secure, and efficient solution for decentralized real-time energy management in Virtual Prosumer Networks.
Study on Thermal Environment and Energy Consumption of Typical Residential Courtyards in Beijing’s Old City
Authors: Li Yuanyuan , Wang Chuang , Zhao Ziheng , An Jingjing , Shi Yang , Hao Shimeng , Ren Zhongqi , Zhang Jie
Published: January 2025

Old city courtyards are crucial elements of Beijing’s ancient capital. However, existing ones face heating problems. This study focuses on renovated and original-style courtyards. By employing ENVI-met and DeST software, we comprehensively analyzed the courtyard’s thermal environment, ventilation, indoor conditions, and energy consumption. Findings reveal that both types have thermal discomfort. Original courtyards are colder in winter and hotter in summer due to wind and radiation. They possess better ventilation but a higher winter heating load. Both require winter heating, with the original ones having a larger unit area load because of envelope heat loss and ventilation differences. Their direct electric heating consumptions, 187.6 kWh/m2 and 229.6 kWh/m2, respectively, surpass ordinary residences. This study defines issues for future green and low-carbon courtyard work.
Phenotypic Variation in Cone Scales and Seeds as Drivers of Seedling Germination Dynamics of Co-Occurring Cedar and Fir Species
Authors: Trujillo-Ríos María , Gazol Antonio , Seco José Ignacio , Linares Juan Carlos
Published: January 2025

The intraspecific trait variations in the reproductive structures and early growth of seedlings may be critical in determining further regeneration. However, modularly built organisms, such as trees, challenge our notion of the phenotype concept, as the arrays of nonidentical homologous organs, such as seed-bearing cone scales and seeds, depending on the individual capacity to produce phenotypically variable arrangements, but they also reflect abiotic selective effects. We investigated the variability in cone scale morphology, seed traits, and germination dynamics in coexisting fir (Abies marocana) and cedar (Cedrus atlantica) trees from northern Morocco. We quantified the degree of trait overlap in two co-occurring populations of both species, as a measure of population/species functional similarity. Cone scale size and seedling growth rate were species-dependent traits, as 70%–80% of the variance was explained by the species, while only 0%–2% was explained by the population. Conversely, seed weight was a tree-dependent trait, as 70% of the variation was observed among trees, while the species only explained 20% of the variation, and the contribution of the population was negligible. Species and populations showed the same characteristics in the correlations between variables, supporting different magnitudes but a constant relationship. Substantial variations in seed weight and early seedling growth occur concurrently among cones of a single tree, independently of the tree species or population. Further studies should consider both phenotype selection and inheritance of traits’ variance on the establishment, survival, and growth of seedlings in A. marocana and C. atlantica in nurseries and reforestation sites to improve adaptive capacity to changing environmental conditions.
Prediction of Color Change in Heat-Treated Wood Based on Improved Zebra Algorithm Optimized Deep Hybrid Kernel Extreme Learning Machine Model (IZOA-DHKELM)
Authors: Liang Jingjie , Wang Wei , Qu Zening , Cao Ying , Gong Jingxiang
Published: January 2025

In this study, an Improved Zebra Optimization Algorithm (ZOA) is proposed based on the search mechanism of the Sparrow Optimization Algorithm (SSA), the perturbation mechanism of the Particle Swarm Algorithm (PSO), and the adaptive function. Then, Improved Zebra Optimization Algorithm (IZOA) was used to optimize the Deep Hybrid Kernel Extreme Learning Machine Model (DHKELM), and the IZOA-DHKELM was obtained. The model has been used to predict the color of heat-treated wood for different species, temperatures, times, media, and profile types. In this article, the original DHKELM and the ZOA-DHKELM were compared to verify the validity and accuracy of the model. The results indicated that the IZOA-DHKELM decreased the mean absolute error (MAE), root mean square error (RMSE), and mean absolute percentage error (MAPE) by 56.2%, 67.4%, and 34.2%, respectively, while enhancing the coefficient of determination, R2, to 0.9952 compared to the ZOA-DHKELM. This demonstrated that the model was significantly optimized, with improved generalization ability and prediction accuracy. It can better meet the actual engineering needs.
The Effect of Hydrogen Peroxide on Biogas and Methane Produced from Batch Mesophilic Anaerobic Digestion of Spent Coffee Grounds
Authors: Sayoud Siham , Derbal Kerroum , Panico Antonio , Pontoni Ludovico , Fabbricino Massimiliano , Pirozzi Francesco , Benalia Abderrezzaq
Published: January 2025

This paper aims to explore both experimental and modeling anaerobic digestion (AD) processes as innovative methods for managing the substantial quantities of spent coffee grounds (SCG) generated in Algeria, transforming them into valuable renewable energy sources (biogas/methane). AD of SCG, while promising, is hindered by its complex lignocellulosic structure, which poses a significant challenge. This study investigates the efficacy of hydrogen peroxide (H2O2) pretreatment in addressing this issue, with a particular focus on enhancing biogas and methane production. The AD of SCG was conducted over a 46-day period, and the impact of H2O2 pretreatment was evaluated using laboratory-scale batch anaerobic reactors. Four different concentrations of H2O2 (0.5, 1, 2, and 4% H2O2 w/w) were studied in mesophilic conditions (37 ± 2) for 24 h at room temperature, providing basic data on biogas and methane production. The results showed a significant increase in soluble oxygen demand (SCOD) and total sugar solubilization in the range of 555.96–713.02% and 748.48–817.75%, respectively. The optimal pretreatment was found to be 4% H2O2 w/w resulting in 16.28% and 16.93% improvements in biogas and methane yield over the untreated SCG. Further, while previous research has established oxidative pretreatment efficacy, this study uniquely combines the empirical analysis of H2O2 pretreatment with a detailed kinetic modeling approach using the modified Gompertz (MG) and logistic function (LF) models to estimate kinetic parameters and determine the accuracy of fit. The MG model showed the most accurate prediction, thus making the present investigation a contribution to understanding the performance of the AD system under oxidative pretreatment and designing and scaling up new systems with predictability. These findings highlight the potential of H2O2-pretreated SCG as a more efficient and readily available resource for sustainable waste management and renewable energy production.
Comprehensive Extraction and Biological Activities of Mycosporine-like Amino Acids and Glyceroglycolipids Extracts from Two Macroalgae Ecklonia kurome and Ulva lactuca
Authors: Wei Xin , Hu Xiaoqi , Li Tianhuan , Li Yuxiang , Yu You , Jiang Xiujing , Wang Haonan , Yang Jie , Jiao Xue , Zhou Xinghu , Sun Yingying
Published: January 2025

Mycosporine-like amino acids (MAAs) and glyceroglycolipids have promising applications in various fields, but limited research exists on their simultaneous extraction from macroalgae. This study optimized the key parameters (liquid–solid ratio, extraction temperature and extraction time) in the extraction of MAAs and glyceroglycolipids from Ecklonia kurome and Ulva lactuca using single factor and response surface experiments. The yields of MAAs from E. kurome and U. lactuca were 169.71 mg/g and 177.33 mg/g, respectively, while glyceroglycolipids were extracted from the residue with yields of 163.51 mg/g and 213.45 mg/g, respectively. Both extracts showed concentration-dependent antioxidant activities, with the MAAs extracted from U. lactuca demonstrating the strongest effect. The addition of MAA extract to flaxseed oil significantly reduced oxidation rancidity, highlighting its potential as a natural antioxidant for oils. The glyceroglycolipid extract from E. kurome exhibited significant moisture absorption, and a water-retaining agent prepared from this extract showed excellent moisture retention and resistance to high temperatures, freezing, and pressure. A silica gel column chromatography method confirmed the presence of MGDG in the purified glyceroglycolipid extract. These findings suggested that E. kurome and U. lactuca can be converted into high-value-added compounds with potential applications in food, cosmetics, and pharmaceuticals.
Mental Health Outcomes Among Female Ukrainian Refugees in Germany—A Mixed Method Approach Exploring Resources and Stressors
Authors: Adedeji Adekunle , Kaltenbach Stella , Metzner Franka , Kovach Viktoriia , Rudschinat Stefan , Arrizabalaga Isabel Marin , Buchcik Johanna
Published: January 2025

Background: Mental health outcomes among female refugees are complex and multifaceted. This study examines the mental health outcomes and coping resources of female Ukrainian refugees in Germany using a mixed methods approach with qualitative focus groups and quantitative assessments. Methods: This study employs a mixed methods approach, combining qualitative and quantitative methodologies. Three focus group discussions with fifteen participants were conducted in Hamburg in April 2023. A stepwise qualitative data analysis was done using a deductive coding technique. The quantitative analysis focused on descriptive statistics to summarize the data and provide an overview of participants’ mental health and well-being. Results: Our findings show that 43% of participants reported anxiety symptoms, and 21% showed signs of depression—many experienced isolation and disconnection and were struggling with cultural adaptation and the emotional toll of displacement. Despite challenges, participants utilized various coping strategies, such as staying active, volunteering, and seeking community support. However, significant barriers to accessing mental health services, especially for children, were identified. Conclusions: The study underscores the need for tailored interventions, including language support, accessible mental health resources, and community engagement, to foster resilience and well-being. It highlights the importance of comprehensive support systems for refugee populations in host countries, such as active lifestyles, social support, volunteer work, and successful integration.
Recording of Historic Buildings and Monuments for FEA: Current Practices and Future Directions
Authors: Turchetti Francesca , Cuca Branka , Oreni Daniela , Agapiou Athos
Published: January 2025

Cultural heritage (CH) sites and monuments share significant historical and cultural value, but at the same time, these are highly vulnerable to deterioration due to age, construction methods, and materials used. Therefore, stability studies for CH structures through numerical analyses allow researchers and stakeholders to safeguard them against time and exposure to hazards. To obtain reliable results for stability studies, detailed and accurate geometric documentation is needed prior to any modeling or simulation. In this context, geomatics technologies like LiDAR and photogrammetry can offer great support in documenting their structural integrity, providing efficient, non-invasive data collection methods that generate 3D point clouds. Nevertheless, despite the benefits, geomatic methods remain underutilized in structural engineering due to limitations in converting 3D point clouds directly for use in finite element modeling (FEM) analysis. The paper aims to review current approaches for the generation of FE models for structural analysis employing data obtained from 3D digital surveys. Each approach is described in detail, providing examples from literature and highlighting its advantages and disadvantages. Studies show that analysis accuracy depends strongly on point cloud level of detail, underlining the importance of precise geomatic surveys. Emerging workflows and semi-automated methods enable point clouds to be integrated with BIM (building information modeling) and FEM, thereby enhancing the contribution that laser scanning techniques and 3D modeling provide for the analysis of the stability of structures belonging to cultural heritage.
The Role of Virtual Reality in Childhood Obesity Treatment: A Narrative Review
Authors: Oudat Qutaibah , Messiah Sarah E. , Ghoneum Alia Dawlat
Published: January 2025

Childhood obesity is a critical public health issue linked to long-term complications like type 2 diabetes and cardiovascular disease. This narrative review aimed to examine the effectiveness of virtual reality (VR)-based interventions in supporting key components of obesity treatment—physical activity (PA), nutrition education, and behavior change—particularly in children under 12. Using the intensive health behavior and lifestyle treatment (IHBLT) approach, we synthesized findings from studies published between 2014 and 2024. Of the studies reviewed, only one study met inclusion criteria, showing that VR-based interventions effectively increased light-intensity PA and reduced sedentary behavior in children, though these effects were not sustained long-term. The scarcity of studies limits the generalizability of these findings, emphasizing the need for caution in interpretation. Our review highlights a significant gap in the literature regarding VR’s role in childhood obesity treatment. Future research should explore the efficacy of VR in promoting PA, enhancing nutrition education, and supporting sustained behavior changes. Expanding this evidence base is vital for developing accessible and engaging interventions tailored to young children. Addressing this gap could enhance obesity treatment options, offering innovative and effective strategies to improve health outcomes in this vulnerable population.
Molecular and Physiological Responses of Plants that Enhance Cold Tolerance
Authors: Zhou Lixia , Ullah Fazal , Zou Jixin , Zeng Xianhai
Published: January 2025

Low-temperature stress, including chilling and freezing injuries, significantly impacts plant growth in tropical and temperate regions. Plants respond to cold stress by activating mechanisms that enhance freezing tolerance, such as regulating photosynthesis, metabolism, and protein pathways and producing osmotic regulators and antioxidants. Membrane stability is crucial, with cold-resistant plants exhibiting higher lipid unsaturation to maintain fluidity and normal metabolism. Low temperatures disrupt reactive oxygen species (ROS) metabolism, leading to oxidative damage, which is mitigated by antioxidant defenses. Hormonal regulation, involving ABA, auxin, gibberellins, and others, further supports cold adaptation. Plants also manage osmotic balance by accumulating osmotic regulators like proline and sugars. Through complex regulatory pathways, including the ICE1-CBF-COR cascade, plants optimize gene expression to survive cold stress, ensuring adaptability to freezing conditions. This study reviews the recent advancements in genetic engineering technologies aimed at enhancing the cold resistance of agricultural crops. The goal is to provide insights for further improving plant cold tolerance and developing new cold-tolerant varieties.
Interaction of the Vagus Nerve and Serotonin in the Gut–Brain Axis
Authors: Hwang Young Keun , Oh Jae Sang
Published: January 2025

The gut–brain axis represents an important bidirectional communication network, with the vagus nerve acting as a central conduit for peripheral signals from the various gut organs to the central nervous system. Among the molecular mediators involved, serotonin (5-HT), synthesized predominantly by enterochromaffin cells in the gut, plays a pivotal role. Gut-derived serotonin activates vagal afferent fibers, transmitting signals to the nucleus tractus solitarius (NTS) and modulating serotonergic neurons in the dorsal raphe nucleus (DRN) as well as the norepinephrinergic neurons in the locus coeruleus (LC). This interaction influences emotional regulation, stress responses, and immune modulation. Emerging evidence also highlights the role of microbial metabolites, particularly short-chain fatty acids (SCFAs), in enhancing serotonin synthesis and vagal activity, thereby shaping gut–brain communication. This review synthesizes the current knowledge on serotonin signaling, vagal nerve pathways, and central autonomic regulation, with an emphasis on their implications for neuropsychiatric and gastrointestinal disorders. By elucidating these pathways, novel therapeutic strategies targeting the gut–brain axis may be developed to improve mental and physical health outcomes.
Is DEXI a Multiple Sclerosis Susceptibility Gene?
Authors: Eriksson Anna M. , Emini Nora , Harbo Hanne F. , Berge Tone
Published: January 2025

The genetic landscape of multiple sclerosis (MS) has been extensively mapped, yielding significant insights into the molecular mechanisms of the disorder. Early studies highlighted key genes associated with the immune system, particularly T cells, as critical for MS susceptibility. Subsequent large-scale genome-wide association studies (GWASs) identified over 200 genetic variants linked to MS, revealing a complex interplay between MS risk and genes involved in various processes within adaptive and innate immune cells, as well as brain-resident microglia. Recently, a groundbreaking GWAS pinpointed the first gene variant associated with MS disease progression, distinguishing the mechanisms driving disease onset from those influencing progression. The C-type lectin domain family 16, member A (CLEC16A) gene within the 16p13 region has consistently been shown to be associated with increased risk of developing both MS and other autoimmune disorders. Notably, several autoimmune-associated genetic variants in CLEC16A introns act as expression quantitative trait loci for the dexamethasone-induced protein (DEXI gene, adding DEXI to the growing list of MS susceptibility genes. This review explores the molecular and functional characterization of DEXI with a particular focus on recent advances in understanding its role in autoimmunity, specifically in the context of multiple sclerosis. We underscore the importance of continued molecular investigation of susceptibility loci for MS identified in genetic studies, with the goal of translating this knowledge into clinical applications.
Diversity and Composition of Endophytic Fungal Communities Associated with Cocoa (Theobroma cacao L.) Fruits in the Northern Ecuadorian Amazon
Authors: Alvarez-Romero Pablo Israel , Román-Robalino Daniel Arturo , Salazar-Castañeda Eduardo Patricio , Suárez-Cedillo Sandra Elizabeth , Hinojosa-Sánchez Leonardo Anibal , Ferreira Ana Francisca Tibúrcia Amorim Ferreira e , Guallpa-Calva Miguel Angel
Published: January 2025

The study of microorganisms associated with tropical plant species, particularly fungi, has garnered significant interest due to their potential applications in biological control and the synthesis of pharmacologically active compounds. This research aimed to identify and characterize the endophytic fungal communities associated with cocoa (Theobroma cacao L.) fruits across three municipalities in the Orellana province, located within the Ecuadorian Amazon. Fungi were isolated directly from cocoa fruits and analyzed through comprehensive cultural, morphological, and molecular analyses. The diversity of fungal taxa was evaluated using metrics of relative abundance and species richness. A total of 464 fungal isolates were obtained, representing 56 distinct morphotypes and 14 genera within the phylum Ascomycota. The most abundant genera included Penicillium sp. (27.8%), Epicoccum sp. (20.5%), Lasiodiplodia sp. (10.1%), Trichoderma sp. (9.91%), and Fusarium sp. (9.70%). Notably, in the municipality of La Joya de los Sachas, a higher number of endophytic fungi was observed, encompassing 14 genera. This study provides critical insights into the diversity and distribution of fungal communities associated with cocoa fruits in the northern Ecuadorian Amazon. These findings have important implications for the management of cocoa diseases and the discovery of novel bioactive compounds. Future investigations should explore the functional roles of these fungi, particularly their potential as biocontrol agents or sources of novel pharmaceuticals. Furthermore, examining the effects of environmental variables and agricultural practices on cocoa fruit mycobiota may contribute to a deeper understanding of the ecological dynamics within this system.
Heart Failure and Worsening Renal Function: Prevalence, Risk Factors, and Impact on Hospital Readmissions in an Urban Minority Population
Authors: AlShammari Asmaa , Magdits Mariel , Majdalani Rosemarie , Devarajan Sriraman , Hughes Anna , McCann Lily , Ionescu Natalia , Raiszadeh Farbod
Published: January 2025

Background and Objectives: Heart failure (HF) often leads to worsening renal function (WRF), negatively impacting patient outcomes. This study aims to examine the incidence of WRF in HF patients, identify its risk factors, and assess its effect on readmissions. Materials and Methods: This retrospective analysis included 297 HF patients admitted to Harlem Hospital Center between January 2019 and December 2021. WRF incidence and its association with risk factors, hospital stays, and readmissions were analyzed. Data on age, type 2 diabetes, chronic kidney disease, high-dose furosemide use, and biomarkers (ProBNP, troponin T, creatinine) were collected. A risk-scoring system was developed to identify patients at higher risk for WRF. Results: WRF occurred in 27% of patients, with a significant correlation to longer hospital stays and lower cardiology follow-up adherence. Risk factors for WRF included older age, type 2 diabetes, chronic kidney disease, high-dose furosemide, and elevated ProBNP, troponin T, and creatinine levels. The risk scoring system revealed that patients scoring 6 or higher were four times more likely to develop WRF. Interestingly, WRF did not increase 30-day readmission rates. Conclusions: This study highlights the high incidence of WRF among HF patients, its impact on hospital stays and follow-up adherence, and the utility of a risk-scoring system to identify vulnerable patients. The findings offer valuable insights into improving care in minority-serving hospitals and provide a foundation for future research on WRF in HF patients.
Acute Kidney Injury in Critically Ill Children: Prevalence, Progression, Recovery Mortality, and Impact of Severity
Authors: Naeem Mohammed , Alarishi Seham , Othman Fatmah , Alfurayh Mohammed , Alkhalaf Hamad
Published: January 2025

Introduction: Acute kidney injury (AKI) among the pediatric population is considered a risk factor for mortality and morbidities during pediatric intensive care unit (PICU) admission. The association between AKI and increased mortality risk and length of stay (LOS) is still inconclusive. This retrospective cohort study aimed to evaluate the impact of AKI severity upon critical management and clinical parameters with an evaluation of severity progression among AKI patients admitted to the PICU at a tertiary care hospital. Methods: AKI, defined with the Kidney Disease Improving Global Outcomes (KDIGO) classification, was determined based on serum creatinine and urine output with respect to the patient’s baseline value. The following outcomes were examined: mortality, mechanical ventilation use, use of non-invasive ventilation, recovery at discharge, and LOS in the hospital and PICU stratified by type of AKI upon admission. Medical records of the 165 included patients were reviewed for clinical data and study outcomes. Results: The median age of the patients was 7 years (IQR 1.5–10 years), and 58% were boys; 78 (47.2%) had stage 1 AKI, 49 (29.71%) had stage 2 AKI, and 38 (23%) had stage 3 AKI at admission. The mortality rate was 26%. The median LOS in the PICU was statistically significant between AKI stages, with a higher median LOS among patients with AKI stage 3 at admission. Using the maximum KDIGO stage, there was no association between AKI and mortality (adjusted OR 1.91, 95% CI 0.05), whereas for the mechanical ventilation outcome, the adjusted OR was 1.84 (95% CI 0.42–8.1). Conclusions: The severity of AKI is not associated solely with mortality and clinical outcomes as the numbers of comorbidities and organ failures contribute to mortality. However, improving awareness of AKI and understanding the disease progression course would reduce acute and long-term morbidity and mortality.
Nanotechnology and Artificial Intelligence in Dyslipidemia Management—Cardiovascular Disease: Advances, Challenges, and Future Perspectives
Authors: Młynarska Ewelina , Bojdo Kinga , Frankenstein Hanna , Kustosik Natalia , Mstowska Weronika , Przybylak Aleksandra , Rysz Jacek , Franczyk Beata
Published: January 2025

This narrative review explores emerging technologies in dyslipidemia management, focusing on nanotechnology and artificial intelligence (AI). It examines the current treatment recommendations and contrasts them with the future prospects enabled by these innovations. Nanotechnology shows significant potential in enhancing drug delivery systems, enabling more targeted and efficient lipid-lowering therapies. In parallel, AI offers advancements in diagnostics, cardiovascular risk prediction, and personalized treatment strategies. AI-based decision support systems and machine learning algorithms are particularly promising for analyzing large datasets and delivering evidence-based recommendations. Together, these technologies hold the potential to revolutionize dyslipidemia management, improving outcomes and optimizing patient care. In addition, this review covers key topics such as cardiovascular disease biomarkers and risk factors, providing insights into the current methods for assessing cardiovascular risk. It also discusses the current understanding of dyslipidemia, including pathophysiology and clinical management. Together, these insights and technologies hold the potential to revolutionize dyslipidemia management, improving outcomes and optimizing patient care.
Vasopressor Use in Acute Spinal Cord Injury: Current Evidence and Clinical Implications
Authors: Taman Mazen , Abdulrazeq Hael , Chuck Carlin , Sastry Rahul A. , Ali Rohaid , Chen Clark C. , Malik Athar N. , Sullivan Patricia Leigh Zadnik , Oyelese Adetokunbo , Gokaslan Ziya L. , Fridley Jared S.
Published: January 2025

Acute spinal cord injury (SCI) often results in severe neurologic deficits, with hemodynamic instability contributing to secondary ischemic damage. Beyond surgical decompression, maintaining adequate mean arterial pressure (MAP) is key to enhancing spinal cord perfusion and oxygenation. Vasopressor therapy is frequently used to achieve hemodynamic stability, but optimal MAP targets and vasopressor selection remain controversial. This review explores updated guidelines and current evidence regarding MAP management and the use of vasopressors in SCI, focusing on their impact on spinal cord perfusion and neurologic outcomes. Recent studies highlight the role of durotomy in directly improving spinal cord perfusion pressure (SCPP) by reducing intraspinal pressure (ISP), offering a complementary mechanical intervention as part of pharmacologic therapies. Recent guidelines suggest an MAP range of 75–80 mmHg as a lower limit and 90–95 mmHg as an upper limit for 3–7 days post-injury, highlighting the need for personalized hemodynamic management. Norepinephrine is commonly preferred due to its balanced effects on peripheral vascular resistance and spinal cord perfusion pressure (SCPP), though dopamine, phenylephrine, and dobutamine each offer unique hemodynamic profiles suited to specific clinical scenarios. Despite their benefits, vasopressors carry significant risks, including arrhythmias and potential myocardial strain, necessitating careful selection based on individual patient factors. Further research is needed to refine vasopressor use and establish evidence-based protocols that optimize neurologic recovery, alongside continued exploration of SCPP as a potential therapeutic target.
Population Genetic Structure with Mitochondrial DNA of the Chub Mackerel Scomber japonicus in Korean Coastal Waters
Authors: Gwak Woo-Seok
Published: January 2025

Scomber japonicus, commonly known as chub mackerel, is a fish species of economic significance in Korea, China, and Japan, whose natural abundance has reduced dramatically due to overfishing and environmental changes. To investigate the genetic differentiation and population structure of S. japonicus, a 359 base pair segment of the mitochondrial DNA (mtDNA) control region sequence was analyzed in 96 individuals sampled from three locations in Korean waters. Sixty-six haplotypes were recognized, of which 61 (92.42%) were population specific, whereas only five haplotypes were shared by multiple populations (8%). Two clades were revealed with low support values, and no specific genealogical branches were recognized according to geographical locations. Significant genetic differentiations, however, were detected among the three populations, with FST values (p < 0.05). These results indicate that populations of S. japonicus in Korean waters are genetically subdivided. Migration patterns, spawning site fidelity, and current temperature could be the possible causes of this subdivision. Consequently, it is thought that each of the genetically unique S. japonicus stocks found in Korean waters requires a different approach to management.
Associations of Clinical Presentation of Coeliac Disease with Comorbidities and Complications: A Retrospective Single-Centre Analysis
Authors: Bajor Judit , Vereczkei Zsófia , Bencs Réka , Nagy Enikő , Peresztegi Míra Zsófia , Hegedűs Ivett , Farkas Nelli , Tárnok András , Szigeti Nóra , Szakács Zsolt
Published: January 2025

Background: The clinical presentation of coeliac disease (CD) is various and may influence disease course. We aimed to investigate the associations of clinical presentation with comorbidities and disease complications in a cohort of Hungarian coeliac patients. Methods: In this retrospective study, data of consecutive CD patients were analysed. Clinical presentation (classical vs. non-classical), extraintestinal manifestations and comorbidities (anaemia, metabolic bone disease, dermatitis herpetiformis, IgA deficiency, chromosomal abnormalities, autoimmune diseases and malignancy) were assessed. Student’s t-test (for age at diagnosis) and the Chi-squared test or Fisher’s exact test (for categorical variables) were applied as analyses. Results: A total of 738 patients were included. In classical vs. non-classical comparisons, classical presentation was significantly associated with metabolic bone disease (59 vs. 36%, respectively, p < 0.001), anaemia (47 vs. 38%, respectively, p = 0.027) and malignancy (6 vs. 2%, respectively, p = 0.006); however, autoimmune diseases and dermatitis herpetiformis were more common with non-classical presentation (23 vs. 31%, p = 0.02, and 5 vs. 16%, p = 0.014, respectively). Conclusions: Our findings confirm that clinical presentation is associated with certain comorbidities and complications in CD. More personalised follow-up may be recommended based on clinical presentation.
Federated Learning for privacy-Friendly Health Apps: A Case Study on Ovulation Tracking
Authors: Pavlidis Nikolaos , Sendros Andreas , Tsiolakis Theodoros , Kostamis Periklis , Karasoulas Christos , Briola Eleni , Nikolaidis Christos Chrysanthos , Perifanis Vasilis , Drosatos George , Katsiri Eleftheria , Filippidou Despoina Elisavet , Manos Anastasios , Efraimidis Pavlos S.
Published: January 2025

In an era of increasing reliance on digital health solutions, safeguarding user privacy has emerged as a paramount concern. Health applications often need to balance advanced AI functionalities with sufficient privacy measures to ensure user engagement. This paper presents the architecture of FLORA, a privacy-first ovulation-tracking application that leverages federated learning (FL), privacy-enhancing technologies (PETs), and blockchain to protect user data while delivering accurate and personalized health insights. Unlike conventional centralized systems, FLORA ensures that sensitive information remains on users’ devices, with predictive algorithms powered by local computations. Blockchain technology provides immutable consent tracking and model update transparency, further improving user trust. In addition, FLORA’s design incentivizes participation through a token-based reward system, fostering collaborative data contributions. This work illustrates how the integration of cutting-edge technologies creates a secure, scalable, and user-centric health application, setting a new standard for privacy-preserving digital health platforms.
Drifting Past Policy Coherence? Rhetoric and Realities of the Mexican Sembrando Vida Program’s Sustainability Goals
Authors: Mardero Sofia , Schmook Birgit , Calmé Sophie , Casanova Grecia , White Rehema M.
Published: January 2025

Global and interconnected sustainability challenges require systems thinking and policy coherence to support bold and coordinated action. To chart a course for action, the UN Sustainable Development Goals (SDGs) provide a suite of targets across international and national levels. Here, we explore intentions and contributions over time of the Mexican multifaceted rural-development program Sembrando Vida (SV) to the SDGs, to assess its policy coherence for sustainable development, especially in relation to climate change. We reviewed online documents and newspaper articles, interviewed key SV staff and analyzed the Mexican President’s morning conference speeches. We show that multiplicity and adaptation of stated intentions suggest opportunistic forms of policy drift with limited policy coherence. The potential of the SV program remains promising, but it requires clearer objectives, coherent strategy, expert knowledge, community support and evaluation. These results demonstrate how political context can cause policy drift and negatively impact intended policy coherence for sustainable development.