bluuebunny/crossref_metadata_2025 huggingface dataset:
Batch Reactor Design and Conception at Laboratory Scale for Solid-State Anaerobic Digestion: Practical Comparison Between 3D-Printed Digesters and Conventional Methods
Authors: Dujany Arnaud , Otaola Franco , André Laura , Naji Amar , Luart Denis , Leturia Mikel , Pauss André , Ribeiro Thierry
Published: January 2025

Solid-state anaerobic digestion (SS-AD) is a promising technology for treating organic waste and producing renewable energy. This study explores the feasibility of using 3D printing to rapidly design cost-effective laboratory-scale digesters for optimization experiments. Batch reactors were designed using fused deposition modeling (FDM) with polylactic acid (PLA) and stereolithography (SLA) with High Temp V2 resin. PLA had a negligible impact on methane yields, while raw SLA resin positively influenced methanogenic potential, likely due to residual isopropanol used in post-processing, causing a 19% increase in CH4 yield. The performance of the 3D-printed reactors was compared to that of a conventionally machined PMMA reactor using cattle manure as a substrate, showing comparable methane yields and process stability. Three-dimensional printing technologies have demonstrated remarkable efficiency in designing laboratory-scale digesters, with a 70% cost reduction for SLA technology and an 80% reduction in design time compared to conventional reactors designed by plastics processing, while maintaining comparable biogas production. FDM technologies with PLA have shown that they are not suitable for these uses. This study demonstrates the potential of additive manufacturing to accelerate SS-AD research and development. However, care must be taken in material selection and post-processing to avoid introducing experimental bias.
Deep Learning Framework for Advanced De-Identification of Protected Health Information
Authors: Aloqaily Ahmad , Abdallah Emad E. , Al-Zyoud Rahaf , Abu Elsoud Esraa , Al-Hassan Malak , Abdallah Alaa E.
Published: January 2025

Electronic health records (EHRs) are widely used in healthcare institutions worldwide, containing vast amounts of unstructured textual data. However, the sensitive nature of Protected Health Information (PHI) embedded within these records presents significant privacy challenges, necessitating robust de-identification techniques. This paper introduces a novel approach, leveraging a Bi-LSTM-CRF model to achieve accurate and reliable PHI de-identification, using the i2b2 dataset sourced from Harvard University. Unlike prior studies that often unify Bi-LSTM and CRF layers, our approach focuses on the individual design, optimization, and hyperparameter tuning of both the Bi-LSTM and CRF components, allowing for precise model performance improvements. This rigorous approach to architectural design and hyperparameter tuning, often underexplored in the existing literature, significantly enhances the model’s capacity for accurate PHI tag detection while preserving the essential clinical context. Comprehensive evaluations are conducted across 23 PHI categories, as defined by HIPAA, ensuring thorough security across critical domains. The optimized model achieves exceptional performance metrics, with a precision of 99%, recall of 98%, and F1-score of 98%, underscoring its effectiveness in balancing recall and precision. By enabling the de-identification of medical records, this research strengthens patient confidentiality, promotes compliance with privacy regulations, and facilitates safe data sharing for research and analysis.
The Time Machine: Future Scenario Generation Through Generative AI Tools
Authors: Ferrer i Picó Jan , Catta-Preta Michelle , Trejo Omeñaca Alex , Vidal Marc , Monguet i Fierro Josep Maria
Published: January 2025

Contemporary society faces unprecedented challenges—from rapid technological evolution to climate change and demographic tensions—compelling organisations to anticipate the future for informed decision-making. This case study aimed to design a digital system for end-users called the Time Machine, which enables a generative artificial intelligence (GAI) system to produce prospective future scenarios based on the input information automatically, proposing hypotheses and prioritising trends to streamline and make the formulation of future scenarios more accessible. The system’s design, development, and testing progressed through three versions of prompts for the OpenAI GPT-4 LLM, with six trials conducted involving 222 participants. This iterative approach allowed for gradual adjustment of instructions given to the machine and encouraged refinement. Results from the six trials demonstrated that the Time Machine is an effective tool for generating future scenarios that promote debate and stimulate new ideas in multidisciplinary teams. Our trials proved that GAI-generated scenarios could foster discussions on +70% of generated scenarios with appropriate prompting, and more than half included new ideas. In conclusion, large language models (LLMs) of GAI, with suitable prompt engineering and architecture, have the potential to generate useful future scenarios for organisations, transforming future intelligence into a more accessible and operational resource. However, critical use of these scenarios is essential.
Decentralized Identity Management for Internet of Things (IoT) Devices Using IOTA Blockchain Technology
Authors: Ramírez-Gordillo Tamai , Maciá-Lillo Antonio , Pujol Francisco A. , García-D’Urso Nahuel , Azorín-López Jorge , Mora Higinio
Published: January 2025

The exponential growth of the Internet of Things (IoT) necessitates robust, scalable, and secure identity management solutions to handle the vast number of interconnected devices. Traditional centralized identity systems are increasingly inadequate due to their vulnerabilities, such as single points of failure, scalability issues, and limited user control over data. This study explores a decentralized identity management model leveraging the IOTA Tangle, a Directed Acyclic Graph (DAG)-based distributed ledger technology, to address these challenges. By integrating Decentralized Identifiers (DIDs), Verifiable Credentials (VCs), and IOTA-specific technologies like IOTA Identity, IOTA Streams, and IOTA Stronghold, we propose a proof-of-concept framework that enhances security, scalability, and privacy in IoT ecosystems. Our implementation on resource-constrained IoT devices demonstrates the feasibility of this approach, highlighting significant improvements in transaction efficiency, real-time data exchange, and cryptographic key management. Furthermore, this research aligns with Web 3.0 principles, emphasizing decentralization, user autonomy, and data sovereignty. The findings suggest that IOTA-based solutions can effectively advance secure and user-centric identity management in IoT, paving the way for broader applications in various domains, including smart cities and healthcare.
Three-Dimensional Aeroelastic Investigation of a Novel Convex Bladed H-Darrieus Wind Turbine Based on a Two-Way Coupled Computational Fluid Dynamics and Finite Element Analysis Approach
Authors: Elbeji Tarek , Ben Amira Wael , Souaissa Khaled , Ghiss Moncef , Bentaher Hatem , Ben Fredj Nabil
Published: January 2025

H-Darrieus vertical-axis wind turbines (VAWTs) capture wind regardless of its direction and operate effectively even in challenging and turbulent wind conditions. As a result, the blades operate under erratic and intricate aerodynamic loads, which cause them to bend. The performance of the H-Darrieus rotor will therefore be impacted by the blade’s deflection. This study aims at investigating the dynamic aerostructure influence on a novel convex-bladed H-Darrieus geometry. The results are compared to a straight-bladed baseline rotor. To do so, a two-way fluid–structure interaction (FSI)-coupled approach is performed to accurately address this issue. This approach allows for the simultaneous resolution of the fluid flow around the rotor and the mechanical structure responses inside the blades. The turbulent flows are resolved using the k-ω-SST model together with the URANS equations through computational fluid dynamics (CFD), while the structural deflections of the blades are assessed using finite element analysis (FEA). The results show that the performance of both H-Darrieus turbines decreases with increasing deformation. In addition, the study found that the carbon fiber composite (M1) material has the least deformation in the convex and straight blades, with values of 9.1 mm and 20.331 mm, respectively. The glass-fiber-reinforced epoxy composite (M3) material shows the most significant deflection across both types, with displacements of 32.50 mm and 73.78 mm for the straight blade and 19.02 mm and 43.03 mm for the convex blade. This study also reveals that the straight blade has a peak displacement of 73.785 mm when using the M3 material at TSR = 3, while the convex blade has a minimum displacement of 20.331 mm when using the M1 material, highlighting the varying performance characteristics of the materials. The maximum stress observed occurs in the straight blade, registering at 324.1 MPa with TSR = 3, which aligns closely with the peak displacement values, particularly for the aluminum alloy material (M2). In contrast, the convex blade made from the first material (M1) exhibits the lowest stress levels among the tested configurations.
Machine Learning Model for Gas–Liquid Interface Reconstruction in CFD Numerical Simulations
Authors: Nakano Tamon , Bucci Michele Alessandro , Gratien Jean-Marc , Faney Thibault
Published: January 2025

The volume of fluid (VoF) method is widely used in multiphase flow simulations to track and locate the interface between two immiscible fluids. The relative volume fraction in each cell is used to recover the interface properties (i.e., normal, location, and curvature). Accurate computation of the local interface curvature is essential for evaluation of the surface tension force at the interface. However, this interface reconstruction step is a major bottleneck of the VoF method due to its high computational cost and low accuracy on unstructured grids. Recent attempts to apply data-driven approaches to this problem have outperformed conventional methods in many test cases. However, these machine learning-based methods are restricted to computations on structured grids. In this work, we propose a machine learning-enhanced VoF method based on graph neural networks (GNNs) to accelerate interface reconstruction on general unstructured meshes. We first develop a methodology for generating a synthetic dataset based on paraboloid surfaces discretized on unstructured meshes to obtain a dataset akin to the configurations encountered in industrial settings. We then train an optimized GNN architecture on this dataset. Our approach is validated using analytical solutions and comparisons with conventional methods in the OpenFOAM framework on a canonical test. We present promising results for the efficiency of GNN-based approaches for interface reconstruction in multiphase flow simulations in the industrial context.
Arabidopsis thaliana DNA Damage Response Mutants Challenged with Genotoxic Agents—A Different Experimental Approach to Investigate the TDP1α and TDP1β Genes
Authors: Bertoncini Anna , Pagano Paola , Macovei Anca
Published: January 2025

Background/Objectives: DNA damage response (DDR) is a highly conserved and complex signal transduction network required for preserving genome integrity. DNA repair pathways downstream of DDR include the tyrosyl-DNA phosphodiesterase1 (TDP1) enzyme that hydrolyses the phosphodiester bond between the tyrosine residue of topoisomerase I (TopI) and 3′-phosphate end of DNA. A small TDP1 subfamily, composed of TDP1α and TDP1β, is present in plants. The aim of this work was to investigate the role of the two TDP1 genes in the DDR context. Methods: A series of Arabidopsis thaliana DDR single and double mutants defective in the sog1, e2fb, pol2A, atm, and atr genes, treated with the genotoxic agents camptothecin (CPT, inhibitor of TopI) and NSC120686 (NSC, inhibitor of TDP1), were used. These compounds were specifically used due to their known impact on the TDP1 function. The effect of the treatments was assessed via phenotypic analyses that included germination percentage, speed, and seedling growth. Subsequently, the expression of the TDP1α and TDP1β genes was monitored through qRT-PCR. Results: Overall, the gathered data indicate that the atm mutant was highly sensitive to NSC120686, both phenotypically and concerning the TDP1α gene expression profiles. Alternatively, the upregulation of TDP1β in e2fb, pol2a, and atr supports its implication in the replication stress response. Conclusions: The current study demonstrates that genotoxic stress induced by CPT and NSC has a genotype-dependent effect reflected by a differential expression of TDP1 genes and early phenotypic development.
The Epigenetic Machinery and Energy Expenditure: A Network to Be Revealed
Authors: Prada Elisabetta , Marchetti Giulia Bruna , Pires Marafon Denise , Mazzocchi Alessandra , Scuvera Giulietta , Pezzani Lidia , Agostoni Carlo , Milani Donatella
Published: January 2025

Mendelian disorders of the epigenetic machinery (MDEMs) include a large number of conditions caused by defective activity of a member of the epigenetic machinery. MDEMs are characterized by multiple congenital abnormalities, intellectual disability and abnormal growth. that can be variably up- or down-regulated. Background/Objectives: In several MDEMs, a predisposition to metabolic syndrome and obesity since childhood has been reported. Methods: To investigate the metabolic bases of this abnormal growth, we collected physical data from a heterogeneous pool of 38 patients affected by MDEMs. Thirty-five patients performed indirect calorimetry (as a measure of resting energy expenditure, REE) and blood tests to monitor plasmatic nutritional parameters. Conclusions: Although limited by a small-sized and heterogeneous sample, our study demonstrates a linear correlation between REE and physical parameters, OFC, height and weight, and observed a slight imbalance on several plasmatic spies of metabolic syndrome predisposition. Furthermore, we demonstrated a significantly higher REE in Sotos Syndrome type 1 patients compared to the controls, which resulted independent from height, suggesting that impaired metabolism in these patients may go beyond overgrowth.
Transcriptome Reveals the Differential Regulation of Sugar Metabolism to Saline–Alkali Stress in Different Resistant Oats
Authors: Chen Naiyu , Xing Shuya , Song Jiaxin , Lu Shutong , Ling Lei , Qu Lina
Published: January 2025

Background: Saline–alkali stress is a major factor limiting the growth of oats. Sugar is the primary carbon and energy source in plants which regulates plant development and growth by regulating enzyme activity and gene expression. Sucrose, glucose, and fructose are ubiquitous plant-soluble sugars that act as signalling molecules in the transcriptional regulation of various metabolic and defence-related genes. Methods: In this study, soluble sugars, fructose, sucrose, and starch contents were measured, and transcriptomics was used to determine the differentially expressed genes (DEGs) in saline-sensitive and saline-tolerant oats after 6, 12, 24, and 48 h. DEGs annotated to carbohydrates were selected using the Kyoto Encyclopedia of Genes and Genomes. Results: DEGs involved in carbohydrate metabolism were mainly enriched in the glycolysis/gluconeogenesis and pentose phosphate pathways, fructose and mannose metabolism, and starch and sucrose metabolism. GAPDH, SUPI, SUS2, ATP-PEK, HXK6, FBA4, TBA4, TKT, ISA3, PPDK1, and BAM2 were significantly expressed, and a quantitative reverse transcription polymerase chain reaction verified the transcriptome sequencing results. Conclusions: In this study, oats with different salinity tolerances were used to determine sugar contents under four salinity stress durations, and transcriptome sequencing was used to explore the regulatory mechanism of sugars and provide a reference for elucidating the sugar signalling regulatory mechanism under abiotic stress.
Origin and Genealogy of Rare mtDNA Haplotypes Detected in the Serbian Population
Authors: Davidović Slobodan , Aleksić Jelena M. , Tanasković Marija , Erić Pavle , Stevanović Milena , Kovačević-Grujičić Nataša
Published: January 2025

Background: The Balkan Peninsula has served as an important migration corridor between Asia Minor and Europe throughout humankind’s history and a refugium during the Last Glacial Maximum. Past migrations such as the Neolithic expansion, Bronze Age migrations, and the settlement of Slavic tribes in the Early Middle Ages, are well known for their impact on shaping the genetic pool of contemporary Balkan populations. They have contributed to the high genetic diversity of the region, especially in mitochondrial DNA (mtDNA) lineages. Serbia, located in the heart of the Balkans, reflects this complex history in a broad spectrum of mtDNA subhaplogroups. Methods: To explore genetic diversity in Serbia and the wider Balkan region, we analyzed rare mtDNA subclades—R0a, N1a, N1b, I5, W, and X2—using publicly available data. Our dataset included already published sequences from 3499 HVS-I/HVS-II and 1426 complete mitogenomes belonging to West Eurasian and African populations, containing both contemporary and archaeological samples. We assessed the parameters of genetic diversity found in different subclades across the studied regions and constructed detailed phylogeographic trees and haplotype networks to determine phylogenetic relationships. Results: Our analyses revealed the observable geographic structure and identified novel mtDNA subclades, some of which may have originated in the Balkan Peninsula (e.g., R0a1a5, I5a1, W1c2, W3b2, and X2n). Conclusions: The geographic distribution of rare subclades often reveals patterns of past population movements, routes, and gene flows. By tracing the origin and diversity of these subclades, our study provided new insights into the impact of historical migrations on the maternal gene pool of Serbia and the wider Balkan region, contributing to our understanding of the complex genetic history of this important European crossroads.
Public Support for Flood Risk Management: Insights from an Italian Alpine Survey Using Systems Thinking
Authors: Scolozzi Rocco , Scolobig Anna , Borga Marco
Published: January 2025

This study presents the results of a survey on flood risk awareness conducted in the Italian Alps, examining the impacts of a major weather event on public perception and trust. It develops a systems-thinking framework to analyse dynamic feedback loops influencing flood risk management support over time. The survey data collection overlapped with a severe storm event in Central Europe, the storm “Adrian” (also known as “Vaia”). This provided a unique pre- and post-event perspective. Results highlight the critical role of individual knowledge, trust in authorities, and social group dynamics in shaping risk perception processes. The study shows how major weather events can change perceptions, sense of safety, and institutional trust within local communities, and more interestingly, these changes can vary spatially. The findings are summarised using a systems-thinking framework, which helps to identify possible feedback loops between flood risk management interventions and long-term public support. The study emphasizes the importance of forward-looking, systems-thinking approaches in the design, monitoring, and evaluation of flood risk management plans. These approaches allow one to account for often-overlooked dynamics, such as spatially varying feedback loops and counter-intuitive effects, ultimately improving the long-term effectiveness of flood risk management.
An Integrative Path Model of Healthcare Utilization Determinants in Traditional Korean Medicine and Western Medicine Based on the Anderson Behavioral Model
Authors: Park Minjung
Published: January 2025

Background: This study aimed to elucidate the determinants of healthcare utilization in South Korea’s dual healthcare system, encompassing both Western medicine and Korean medicine, through the Andersen Model. An integrative non-recursive path model of healthcare utilization determinants was proposed and analyzed. Methods: A path analysis using structural equation modeling, followed by mediation analysis, was conducted to determine the magnitude of the effect for each pathway. The 2020 data from the Korea Health Panel were used. Results: Structural equation modeling revealed that need factors, such as chronic diseases, disability, and self-rated health status, were the most significant drivers of both WM and KM utilization, while enabling factors significantly impacted WM utilization. Interestingly, WM and KM utilization were found to positively influence each other, contradicting the assumption of substitutional healthcare use. Mediation analysis further highlighted the interconnected nature of healthcare utilization pathways, with enabling and need factors showing significant indirect effects on utilization via the counterpart system. These findings underscore the importance of considering mutual influences in healthcare policy and resource allocation to enhance accessibility and efficiency. While the cross-sectional nature of the data limits causal inference, this study offers a robust theoretical framework and practical insights for addressing the complexities of healthcare utilization in dual-system contexts. Conclusion: The findings reveal that when traditional medicine functions within the national healthcare system, both Western medicine and traditional medicine are influenced by similar determinants in the same environment. Future research should explore longitudinal data to confirm these findings and investigate potential moderating effects of predisposing and enabling factors on WM and KM interactions.
An Overlooked Challenge: A Retrospective Audit of Overnutrition in Hospital Rehabilitation Wards
Authors: Olufson Hannah T. , Ellick Jennifer , McCoy Simone , Barrimore Sally E. , Knowlman Tracy , Young Adrienne M.
Published: January 2025

Background/Objective: Research shows that obesity has risen among rehabilitation patients. Despite this, nutrition care in subacute rehabilitation wards focuses primarily on preventing and treating protein-energy malnutrition. The continued provision of energy-dense meals during lengthy rehabilitation admissions may present a risk of overnutrition for some patients, which can adversely affect functional outcomes. However, overnutrition is not routinely monitored in practice. This study summarizes the initial findings of a multi-site investigation of overnutrition incidence across five rehabilitation wards to scope the need for future research. Methods: A retrospective audit was conducted, including all inpatients admitted over 3 months to the study wards with a complete dataset (total sample n = 199). Data were collected from the medical record and menu management system to determine overnutrition, defined as an average daily energy intake equal to or greater than 1000 kJ above estimated requirements and weight gain of equal to or greater than 1 kg over the admission. Results: The incidence of overnutrition in the total sample was 12.1%. Of those patients deemed at low risk of malnutrition (n = 124), 19.4% developed overnutrition during their rehabilitation admission. Those who developed overnutrition during their admission gained an average of 2.9 kg, with a mean excess energy intake of 2456 kJ/day above estimated requirements. They also consumed a high intake of discretionary items (mean of 3156 kJ/day). Conclusions: The findings suggest that further research is needed to investigate the etiology and impact of the overlooked problem of overnutrition in subacute rehabilitation settings. Future investigation is essential to ensure that the planning and delivery of subacute dietetic and food services meet the nutrition needs of patients in longer-stay inpatient settings.
A Retrospective Observational Study on Post-Pandemic Effects of Endogenous and Exogenous Factors on Prematurity in Pregnant Women Under 18 Years of Age
Authors: Țovîrnac Florin , Călin Alina Mihaela , Elkan Eva Maria , Țovîrnac Nicoleta Andreea , Antohi Valentin Marian , Nechifor Alexandru
Published: January 2025

Background/Objectives: This research investigates the impact of exogenous and endogenous factors on fetal health in pregnant women under the age of 18, with a special focus on the influence of educational level, adherence to vices (smoking and alcohol), comorbidities (diabetes and hypertension), and poor sanitary conditions. Methods: The study uses retrospective data collected from a medical institution in the Southeast region of Romania, including a sample of 3639 births during the post-pandemic period (2022–2023). This period was considered to be a reference period for the study because, as a result of measures to combat the spread of COVID-19 disease in the pandemic, there was an increase in the birth rate among patients under 18 years of age. The APGAR clinical score was evaluated at 5, 10, and 20 min after birth and measured on an inverted scale to reflect the increased risk to fetal health. Results: The results indicate that lack of education is a significant exogenous factor associated with an increased risk of preterm births and a lower APGAR score. Additionally, adherence to vices is more pronounced among pregnant women with low educational levels and smoking and alcohol consumption negatively impact fetal health. Regarding comorbidities, diabetes did not significantly affect the short-term APGAR score, while hypertension had a complex effect, though medical interventions mitigated the associated risks. Conclusions: The conclusions of the research emphasize the need for appropriate educational and medical interventions to reduce the risks associated with preterm births and newborn health in adolescent pregnancies, especially in disadvantaged environments. The study suggests future research directions to expand the analysis to other geographical regions and for long-term monitoring of newborn health.
Edible Coatings Enhance Storability and Preserve Quality of Kiwiberry (Actinidia arguta L.) cv. Ken’s Red
Authors: Guerreiro Adriana C. , Gago Custódia , Passos Dário , Martins Jaime , Cruz Sandra , Veloso Fernão , Guerra Rui , Antunes Maria D.
Published: January 2025

Kiwiberries, an emerging fruit variety with increasing consumer demand, face significant commercialization challenges due to their short shelf life. This study evaluates the effectiveness of edible alginate-based coatings in extending the shelf life of kiwiberries. Two emulsion types—coarse (Coarse) and nanoemulsions (Nano)—and two application methods—spraying (Spray) and dipping (Dip)—were tested. Additionally, the use of visible/near-infrared (Vis-NIR) spectroscopy for non-destructive quality monitoring was explored. Coatings were prepared with 2% (w/v) alginate (SAlg) enriched with eugenol (Eg) and citral (Ct) at their minimum inhibitory concentrations (MICs) of 0.10% and 0.15%, respectively, as well as at double these concentrations. This resulted in a total of ten different treatments. The fruits were stored at approximately 5 °C, with evaluations conducted after 5 days, 2 weeks, and 4 weeks. Quality parameters, including color, firmness, soluble solid content (SSC), dry matter, weight loss, decay, total phenolic content (TPC), flavonoids, DPPH, FRAP, and malondialdehyde (MDA) levels, were analyzed. Over the storage period, color and SSC increased, while firmness decreased. Weight loss and MDA levels showed the most significant changes, particularly in treatments with higher essential oil concentrations. Notably, treatments such as SAlg Spray, SAlg Dip, SAlg Ct 0.15 + Eg 0.1 Nano Spray, SAlg Ct 0.15 + Eg 0.1 Nano Dip, and SAlg Ct 0.15 + Eg 0.1 Coarse Dip demonstrated superior preservation of kiwiberry quality. Moreover, Vis-NIR spectroscopy proved valuable for distinguishing between coating treatments, highlighting its potential for non-destructive quality assessment.
Properties and Applications of Nanoparticles and Nanomaterials
Authors: Li Xiaogang
Published: January 2025

Nanomaterials have rapidly developed and attention surrounding their use has increased in recent years [...]
Cellular Signaling of Amino Acid Metabolism in Prostate Cancer
Authors: Yao Ping , Cao Shiqi , Zhu Ziang , Wen Yunru , Guo Yawen , Liang Wenken , Xie Jianling
Published: January 2025

Prostate cancer is one of the most common malignancies affecting men worldwide and a leading cause of cancer-related mortality, necessitating a deeper understanding of its underlying biochemical pathways. Similar to other cancer types, prostate cancer is also characterised by aberrantly activated metabolic pathways that support tumour development, such as amino acid metabolism, which is involved in modulating key physiological and pathological cellular processes during the progression of this disease. The metabolism of several amino acids, such as glutamine and methionine, crucial for tumorigenesis, is dysregulated and commonly discussed in prostate cancer. And the roles of some less studied amino acids, such as histidine and glycine, have also been covered in prostate cancer studies. Aberrant regulation of two major signalling pathways, mechanistic target of rapamycin (mTOR) and general amino acid control non-depressible 2 (GCN2), is a key driver of reshaping the amino acid metabolism landscape in prostate cancer. By summarising our current understanding of how amino acid metabolism is modulated in prostate cancer, here, we provide further insights into certain potential therapeutic targets for managing prostate cancer through metabolic interventions.
Role of miRNAs in Regulating Ascending Aortic Dilation in Bicuspid Aortic Valve Patients Operated for Aortic Stenosis
Authors: Sanchez-Garcia Antonio de Jesús , Soule-Egea Mauricio , Fuentevilla-Alvarez Giovanny , Vargas-Alarcon Gilberto , Hernández-Mejia Benjamín Iván , Martínez-Hernández Humberto , Mora-Canela Sergio Luis , Santibanez-Escobar Felipe , Ávila-Martinez Valeria , Castrejón-Tellez Vicente , Alvarez-León Edith , de la Mora-Cervantes Regina , Pérez-Torres Israel , Soto María Elena
Published: January 2025

Deregulation of micro-RNAs (miRNAs) may contribute to mechanisms of injury in the bicuspid aortic valve (BAV). Our objective was to investigate the expression of miRNAs in aortic tissue from patients who underwent aortic valve replacement for aortic stenosis and its relationship with aortic dilatation. The study included 78 patients, 40 with bicuspid aortic valve (BAV) and 38 with tricuspid aortic valve (TAV). The expression of miRNA-17-5p, hsa-let-7e, and miRNA-196a-5p in human aortic tissue was evaluated by a reverse transcriptase polymerase chain reaction (RT-qPCR). Comparative analysis between patients with BAV and controls with TAV explored the association between the miRNAs and aortic dilatation (AD), calcification, valve dysfunction, and stenosis. The results showed that the expression levels of miRNA-Let-7e-5p and miRNA-196-5p were mostly increased in patients with BAV and aortic dilatation (p = 0.01 and p = 0.01), respectively. In contrast, the levels of miRNA-17a-5p (p < 0.20) were lower but without a statistically significant difference. The downregulation of miRNA-17a-5p and the upregulation of miR-Let-7e-5p and miR-196-5p were related to an increased risk of AD risk. Subjects with BAVs with or without double aortic lesions had higher expression levels of Let-7e-5p and miRNA-17a-5p vs. TAV. In all patients, we found an inverse correlation of MiRNA-196-5p with High-Density Lipoprotein-Cholesterol (HDL-C) and indexed valvular area. In subjects with a higher expression of miRNA196, lower levels of HDL-C correlation (r2) [r2 0.27 (p = 0.02)] and a lower indexed valvular area [r2 0.28 (p = 0.05)] were observed. In the specific analysis for each patient group, it was found that in control subjects with tricuspid aortic valve (TAV), miRNA-196-5p had a positive correlation with valvular calcification (r2 = 0.60, p = 0.02). Deregulation of miRNAs in the aortic tissue of a BAV may influence valvular stenosis, dysfunction, and concomitant aortic dilation. This information could help to define potential therapeutic target strategies to improve the prognosis and treatment of BAV.
Transcriptome of Arabidopsis thaliana Plants Exposed to Human Parasites Cryptosporidium parvum and Giardia lamblia
Authors: Ilnytskyy Yaroslav , Golubov Andrey , Byeon Boseon , Kovalchuk Igor
Published: January 2025

Pathogen infection in animals and plants is recognized in a relatively similar manner by the interaction of pattern recognition receptors on the host cell surface with pathogen-associated molecular patterns on the pathogen surface. Previous work demonstrates that animal pathogenic bacteria can be recognized by plant receptors and alter transcriptome. In this work, we have hypothesized that exposure to human parasites, Cryptosporidium parvum and Giardia lamblia, would also trigger pathogen response in plants, leading to changes in transcriptome. Detached Arabidopsis leaves were exposed for one hour to heat-inactivated Cryptosporidia or Giardia. The transcriptome profile showed large changes in gene expression with significant overlap between two parasites, including upregulated GO terms “cellular response to chitin”, “response to wounding”, “response to oomycetes”, “defense response to fungus”, “incompatible interaction”, and “activation of innate immune response”, and downregulated GO terms “positive regulation of development”, “cell surface”, “regulation of organ growth”, “wax biosynthetic process”, “leaf and shoot morphogenesis”. Uniquely downregulated GO terms in response to Cryptosporidia were GO terms related to chromatin remodelling, something that was not reported before. To conclude, it appears that while Cryptosporidia or Giardia are not pathogens of Arabidopsis, this plant possesses various mechanisms of recognition of pathogenic components of parasites.
Dual Model for International Roughness Index Classification and Prediction
Authors: Molinero-Pérez Noelia , Montalbán-Domingo Laura , Sanz-Benlloch Amalia , García-Segura Tatiana
Published: January 2025

Existing models for predicting the international roughness index (IRI) of a road surface often lack adaptability, struggling to accurately reflect variations in climate, traffic, and pavement distresses—factors critical for effective and sustainable maintenance. This study presents a novel dual-model approach that integrates pavement condition index (PCI), pavement distress types, climatic, and traffic data to improve IRI prediction. Using data from the Long-Term Pavement Performance database, a dual-model approach was developed: pavements were classified into groups based on key factors, and tailored regression models were subsequently applied within each group. The model exhibits good predictive accuracy, with R2 values of 0.62, 0.72, and 0.82 for the individual groups. Furthermore, the validation results (R2 = 0.89) confirm that the combination of logistic regression and linear regression enhances the precision of IRI value predictions. This approach enhances adaptability and practicality, offering a versatile tool for estimating IRI under diverse conditions. The proposed methodology has the potential to support more effective, data-driven decisions in pavement maintenance, fostering sustainability and cost efficiency.
SP-YOLO: A Real-Time and Efficient Multi-Scale Model for Pest Detection in Sugar Beet Fields
Authors: Tang Ke , Qian Yurong , Dong Hualong , Huang Yuning , Lu Yi , Tuerxun Palidan , Li Qin
Published: January 2025

Beet crops are highly vulnerable to pest infestations throughout their growth cycle, which significantly affects crop development and yield. Timely and accurate pest identification is crucial for implementing effective control measures. Current pest detection tasks face two primary challenges: first, pests frequently blend into their environment due to similar colors, making it difficult to capture distinguishing features in the field; second, pest images exhibit scale variations under different viewing angles, lighting conditions, and distances, which complicates the detection process. This study constructed the BeetPest dataset, a multi-scale pest dataset for beets in complex backgrounds, and proposed the SP-YOLO model, which is an improved real-time detection model based on YOLO11. The model integrates a CNN and transformer (CAT) into the backbone network to capture global features. The lightweight depthwise separable convolution block (DSCB) module is designed to extract multi-scale features and enlarge the receptive field. The neck utilizes the cross-layer path aggregation network (CLPAN) module, further merging low-level and high-level features. SP-YOLO effectively differentiates between the background and target, excelling in handling scale variations in pest images. In comparison with the original YOLO11 model, SP-YOLO shows a 4.9% improvement in mean average precision (mAP@50), a 9.9% increase in precision, and a 1.3% rise in average recall. Furthermore, SP-YOLO achieves a detection speed of 136 frames per second (FPS), meeting real-time pest detection requirements. The model demonstrates remarkable robustness on other pest datasets while maintaining a manageable parameter size and computational complexity suitable for edge devices.
Direct Axillary Artery Cannulation as Standard Perfusion Strategy in Minimally Invasive Coronary Artery Bypass Grafting
Authors: Sellin Christian , Belmenai Ahmed , Demianenko Volodymyr , Grossmann Marius , Dörge Hilmar
Published: January 2025

Objective: Cardiopulmonary bypass (CPB) via the right axillary artery (RAA) has become an alternative perfusion strategy, especially in complex aortic procedures. This study delineates our technique and outcome with direct axillary cannulation utilizing the Seldinger technique, which we adopted as the standard perfusion strategy in the sternum-sparing minimally invasive total coronary revascularization via left anterior thoracotomy (TCRAT) using CPB. Methods: From November 2019 to December 2023, a total of 413 consecutive patients underwent nonemergent isolated coronary artery bypass grafting (CABG) via left anterior minithoracotomy on CPB with peripheral cannulation via the RAA and cardioplegic cardiac arrest, using this technique as a default strategy in the daily routine. All patients had multivessel coronary artery disease. The primary outcome was intraoperative cannulation-related complications (bleeding, revision, ischemia, wound healing complications). The secondary outcome was cannulation-related events during follow-up (blood pressure differences, incidence of brachial plexus injury, clinical signs of circulatory problems of arm and hand, re-interventions). Mean midterm follow-up was 18.7 ± 12.3 [1.1–51.2] months. During follow-up, 16 patients died. Overall, a total of 397 patients (344 male; 67.6 ± 9.7 [32–88]) were included for follow-up (100%). Results: The RAA was successfully cannulated in 100% of patients. A cannula size of 16 Fr was used in 34.6%, 18 Fr in 63.9% and 20 Fr in 1.5% of all patients. There was no intraoperative bleeding complication. In two patients, intraoperative revision of the RAA was required, necessitating a venous patch repair. At follow-up, there were no differences between the systolic and diastolic blood pressure or the pressure gradients between the right and left arm. Transient numbness of the right hand was observed in two patients. Permanent numbness was not observed. No patient needed further intervention or surgical revision of the RAA. Conclusions: The right axillary cannulation is feasible and safe in terms of vascular injury and brachial plexus injury with excellent in-hospital and follow-up outcome.
The Role of Anterior Vaginal Prolapse in Co-Existent Underactive Overactive Bladder Syndrome—A Retrospective Cohort Study
Authors: Baruch Yoav , Barba Marta , Cola Alice , Frigerio Matteo
Published: January 2025

Background: CUOB (co-existent underactive overactive bladder) syndrome is a clinical entity that embraces storage and emptying symptoms, not strictly correlated with urodynamic findings. We assessed the differences between patients diagnosed with CUOB with/without cystocele. Methods: The study group was allocated from 2000 women who underwent urodynamic studies between 2008 and 2016. The demographic and clinical data of 369 patients with complaints consistent with CUOB were retrieved. The study group was subdivided using the Pelvic Organ Prolapse Quantification System. The International Consultation on Incontinence Questionnaire Short Form (ICIQ-UI SF) was used to quantify LUTS severity. Results: A total of 185 women had no or grade I cystocele (group 1), and 185 had grade II or III cystocele (group 2). No difference in mean age was computed. Patients from group 1 had a higher BMI (27 vs. 25, p = 0.02). Risk factors for prolapse, such as parity (1.7 vs. 2.1, p = 0.001) and maximal birthweight (3460 g vs. 3612 g, p = 0.049), were higher in group 2. Pelvic Organ Prolapse symptoms were 4.5 times more frequent in group 2 [n = 36/185 (19.5%) vs. n = 162/184 (88%) p < 0.001]. The rate of stress (70.8% vs. 55.4%, p = 0.002) and urge (64.9% vs. 50%, p = 0.04), urinary incontinence, and ICIQ-UI-SF scores (8 vs. 5, p < 0.001) were higher in group 1. Qmax measured lower in group 2 (17 vs. 15 mL/s, p = 0.008). Detrusor pressure at maximum flow was identical (24 cm H2O). The Bladder Contractility Index (BCI) was higher in group 1 (108 vs. 96.5, p = 0.017), and weak contraction (BCI < 100) was more common in group 2 (73/185; 39.5% vs. 95/184; 52.7%, p = 0.011). Conclusions: Based on our results, we assume that CUOB could be further subdivided based on its association with cystocele. The effect of prolapse repair in women with CUOB and cystocele remains to be evaluated in order to afford better counseling in the future.
Dental Rehabilitation After Microvascular Reconstruction of Segmental Jaw Defects: A Ten-Year Follow-Up
Authors: Zeman-Kuhnert Katharina , Gaggl Alexander J. , Bottini Gian B. , Walch Benjamin , Steiner Christoph , Zimmermann Georg , Brandtner Christian
Published: January 2025

Background/Objectives: Defects in maxillary and mandibular continuity are common in maxillofacial practice. They can occur after trauma, osteonecrosis, congenital jaw deformities, or surgical resection of benign or malignant tumours. Reconstruction with microvascular bone flaps and subsequent prosthetic rehabilitation is considered the contemporary first line treatment. This study assessed the extent to which the underlying disease influences the treatment course of microvascular segmental jaw reconstruction. Methods: A retrospective review of prospectively collected data from all patients who underwent microvascular segmental jaw reconstruction from January 2011 to December 2020 was completed. The course of treatment as well as the process of dental rehabilitation was assessed. Results: Two hundred patients were included in the study. A total of 15.5% of patients were fitted with a conventional removable prosthesis, and implant-supported prosthetic restoration could be realized in 53.5% of patients. However, dental rehabilitation was not possible in 31.0% of patients. The outcomes of prosthetic restoration showed a statistically significant difference between the different underlying diseases (p < 0.0001). About 50% of patients with malignant diseases and osteonecrosis remained without dental rehabilitation. In contrast, more than 90% of patients with jaw continuity defects, due to benign diseases or malformations, were able to receive an implant-supported prosthesis. Among the diagnostic groups, there was a significant difference regarding the number of implants placed (p < 0.0001). There was a significant correlation between increased incidence of complications and the size of the bone flaps. Conclusions: The underlying disease influenced significantly the treatment course and the outcome of dental rehabilitation after microvascular jaw reconstruction.
Dispatcher-Assisted CPR in Italy: A Nationwide Survey of Current Practices and Future Challenges in Emergency Medical Communication Centers
Authors: Imbriaco Guglielmo , Canova Giacomo Sebastiano , Righi Lorenzo , Tararan Sara , Di Mario Giorgia , Ramacciati Nicola
Published: January 2025

Background/Objectives: Dispatcher-assisted cardiopulmonary resuscitation (DA-CPR) is widely recognized as a critical intervention that significantly reduces no-flow time, improving survival rates in out-of-hospital cardiac arrests (OHCAs). This study evaluates current practices and the organization of DA-CPR in Italian emergency medical communication centers (EMCCs) and identifies areas for improvement. Methods: A cross-sectional survey was conducted between April and May 2024 among all Italian EMCCs, achieving a 92.6% response rate (62 out of 67) and covering 95.5% of the population. Data were collected on the availability of DA-CPR, additional medical instructions provided, standardized protocols, integration into dispatch software, availability of video call systems, and follow-up programs. Results: All responding EMCCs provide DA-CPR, with 79.1% (n = 49) initiating these protocols more than five years ago. In adult cardiac arrest, 74.2% (n = 46) provide instructions for chest compressions only. Standardized protocols are used in 69.4% (n = 43) of EMCCs, and 53.2% (n = 33) have these protocols integrated into their dispatch software. Additionally, 93.5% (n = 58) provide dispatcher-assisted instructions for other medical conditions, including pediatric CPR (90.3%, n = 56), neonatal CPR (90.3%, n = 56), foreign body airway obstruction (85.5%, n = 53), labor (56.5%, n = 35), and massive bleeding (41.9%, n = 26). A training path for DA-CPR is available in 48 EMCCs (77.4%), and in most cases, it is included in the basic dispatcher course (56.5%, n = 36), with 50% conducting periodic retraining. Moreover, 33.9% (n = 21) utilize video call systems to support dispatcher-assisted instructions. Data on DA-CPR are collected by 46.8% of EMCCs (n = 29), primarily on relevant cases, but only 25.8% (n = 16) have a follow-up path for patients. Conclusions: This study highlights a widespread implementation of DA-CPR across Italian EMCCs. However, regional disparities, mainly in protocols and technological support, indicate areas requiring urgent attention. Enhancing training programs and standardizing protocols could improve DA-CPR effectiveness and patient outcomes, thus guaranteeing equitable care nationwide. Future initiatives should focus on integrating support tools like video calls, expanding retraining programs, and establishing follow-up and debriefing paths.
Blink Detection Using 3D Convolutional Neural Architectures and Analysis of Accumulated Frame Predictions
Authors: Nousias George , Delibasis Konstantinos K. , Labiris Georgios
Published: January 2025

Blink detection is considered a useful indicator both for clinical conditions and drowsiness state. In this work, we propose and compare deep learning architectures for the task of detecting blinks in video frame sequences. The first step is the training and application of an eye detector that extracts the eye regions from each video frame. The cropped eye regions are organized as three-dimensional (3D) input with the third dimension spanning time of 300 ms. Two different 3D convolutional neural networks are utilized (a simple 3D CNN and 3D ResNet), as well as a 3D autoencoder combined with a classifier coupled to the latent space. Finally, we propose the usage of a frame prediction accumulator combined with morphological processing and watershed segmentation to detect blinks and determine their start and stop frame in previously unseen videos. The proposed framework was trained on ten (9) different participants and tested on five (8) different ones, with a total of 162,400 frames and 1172 blinks for each eye. The start and end frame of each blink in the dataset has been annotate by specialized ophthalmologist. Quantitative comparison with state-of-the-art blink detection methodologies provide favorable results for the proposed neural architectures coupled with the prediction accumulator, with the 3D ResNet being the best as well as the fastest performer.