bluuebunny/crossref_metadata_2025 huggingface dataset:
Ambient Air Pollution and Congenital Heart Disease: Updated Evidence and Future Challenges
Authors: Gorini Francesca , Tonacci Alessandro
Published: January 2025

Congenital heart disease (CHD) represents the major cause of infant mortality related to congenital anomalies globally. The etiology of CHD is mostly multifactorial, with environmental determinants, including maternal exposure to ambient air pollutants, assumed to contribute to CHD development. While particulate matter (PM) is responsible for millions of premature deaths every year, overall ambient air pollutants (PM, nitrogen and sulfur dioxide, ozone, and carbon monoxide) are known to increase the risk of adverse pregnancy outcomes. In this literature review, we provide an overview regarding the updated evidence related to the association between maternal exposure to outdoor air pollutants and CHD occurrence, also exploring the underlying biological mechanisms from human and experimental studies. With the exception of PM, for which there is currently moderate evidence of its positive association with overall CHD risk following exposure during the periconception and throughout pregnancy, and for ozone which shows a signal of association with increased risk of pooled CHD and certain CHD subtypes in the periconceptional period, for the other pollutants, the data are inconsistent, and no conclusion can be drawn about their role in CHD onset. Future epidemiological cohort studies in countries with different degree of air pollution and experimental research on animal models are warranted to gain a comprehensive picture of the possible involvement of ambient air pollutants in CHD etiopathogenesis. While on the one hand this information could also be useful for timely intervention to reduce the risk of CHD, on the other hand, it is mandatory to scale up the use of technologies for pollutant monitoring, as well as the use of Artificial Intelligence for data analysis to identify the non-linear relationships that will eventually exist between environmental and clinical variables.
Named Entity Recognition Method Based on Multi-Feature Fusion
Authors: Huang Weidong , Yu Xinhang
Published: January 2025

Nowadays, user-generated content has become a crucial channel for obtaining information and authentic feedback. However, due to the varying cultural and educational levels of online users, the content of online reviews often suffers from inconsistencies in specification and the inclusion of arbitrary information. Consequently, the task of extracting key information from online reviews has become a prominent area of research. This paper proposes a combined entity recognition model for online reviews, aiming to improve the accuracy of Named Entity Recognition (NER). Initially, the Non-negative Matrix Factorization (NMF) model is employed to perform thematic clustering on the review texts, and entity types are extracted based on the clustering results. Subsequently, we introduce an entity recognition model utilizing the pre-trained BERT model as an embedding layer, with BiLSTM and DGCNN incorporating residual connection and gating mechanisms as feature extraction layers. The model also leverages multi-head attention for feature fusion, and the final results are decoded using a Conditional Random Field (CRF) layer. The model achieves an F1 score of 86.8383% on a collected dataset of online reviews containing eight entity categories. Experimental results demonstrate that the proposed model outperforms other mainstream NER models, effectively identifying key entities in online reviews.
A Green AI Methodology Based on Persistent Homology for Compressing BERT
Authors: Balderas Luis , Lastra Miguel , Benítez José M.
Published: January 2025

Large Language Models (LLMs) like BERT have gained significant prominence due to their remarkable performance in various natural language processing tasks. However, they come with substantial computational and memory costs. Additionally, they are essentially black-box models, being challenging to explain and interpret. In this article, Persistent BERT Compression and Explainability (PBCE) is proposed, a Green AI methodology to prune BERT models using persistent homology, aiming to measure the importance of each neuron by studying the topological characteristics of their outputs. As a result, PBCE can compress BERT significantly by reducing the number of parameters (47% of the original parameters for BERT Base, 42% for BERT Large). The proposed methodology has been evaluated on the standard GLUE Benchmark, comparing the results with state-of-the-art techniques achieving outstanding results. Consequently, PBCE can simplify the BERT model by providing explainability to its neurons and reducing the model’s size, making it more suitable for deployment on resource-constrained devices.
Exploring BiomedCLIP’s Capabilities in Medical Image Analysis: A Focus on Scoliosis Detection and Severity Assessment
Authors: Polis Bartosz , Zawadzka-Fabijan Agnieszka , Fabijan Robert , Kosińska Róża , Nowosławska Emilia , Fabijan Artur
Published: January 2025

Background/Objectives: Open-source artificial intelligence models (OSAIMs), such as BiomedCLIP, hold great potential for medical image analysis. While OSAIMs are increasingly utilized for general image interpretation, their adaptation for specialized medical tasks, such as evaluating scoliosis on posturographic X-ray images, is still developing. This study aims to evaluate the effectiveness of BiomedCLIP in detecting and classifying scoliosis types (single-curve and double-curve) and in assessing scoliosis severity. Methods: The study was conducted using a dataset of 262 anonymized posturographic X-ray images from pediatric patients (ages 2–17) with diagnosed scoliosis. The images were collected between January 2021 and July 2024. Two neurosurgical experts manually analyzed the Cobb angles and scoliosis stages (mild, moderate, severe). BiomedCLIP’s performance in detecting scoliosis and its type was evaluated using metrics such as accuracy, sensitivity, specificity, and AUC (Area Under the Curve). Statistical analyses, including Pearson correlation and ROC curve analysis, were applied to assess the model’s performance. Results: BiomedCLIP demonstrated moderate sensitivity in detecting scoliosis, with stronger performance in severe cases (AUC = 0.87). However, its predictive accuracy was lower for mild and moderate stages (AUC = 0.75 and 0.74, respectively). The model struggled with correctly identifying single-curve scoliosis (sensitivity = 0.35, AUC = 0.53), while it performed better in recognizing double-curve cases (sensitivity = 0.78, AUC = 0.53). Overall, the model’s predictions correlated moderately with observed Cobb angles (r = 0.37, p < 0.001). Conclusions: BiomedCLIP shows promise in identifying advanced scoliosis, but its performance is limited in early-stage detection and in distinguishing between scoliosis types, particularly single-curve scoliosis. Further model refinement and broader training datasets are essential to enhance its clinical applicability in scoliosis assessment.
Experimental Investigation on Unloading-Induced Sliding Behavior of Dry Sands Subjected to Constant Shear Force
Authors: Dang Wengang , Tao Kang , Fu Jinyang , Wu Bangbiao
Published: January 2025

Infilled joints or faults are often subjected to long-term stable shear forces, and nature surface processes of normal unloading can change the frictional balance. Therefore, it is essential to study the sliding behavior of such granular materials under such unloading conditions, since they are usually the filling matter. We conducted two groups of normal unloading direct shear tests considering two variables: unloading rate and the magnitude of constant shear force. Dry sands may slide discontinuously during normal unloading, and the slip velocity does not increase uniformly with unloading time. Due to horizontal particle interlacing and normal relaxation, there will be sliding velocity fluctuations and even temporary intermissions. At the stage of sliding acceleration, the normal force decreases with a higher unloading rate and increases with a larger shear force at the same sliding velocity. The normal forces obtained from the tests are less than those calculated by Coulomb’s theory in the conventional constant-rate shear test. Under the same unloading rate, the range of apparent friction coefficient variation is narrower under larger shear forces. This study has revealed the movement patterns of natural granular layers and is of enlightening significance in the prevention of corresponding geohazards.
Nuclear Hyperfine Mixing Effect in Highly Charged 205Pb Ions
Authors: Wang Wu , Li Yong , Wang Xu
Published: January 2025

In highly charged ions, significant nuclear hyperfine mixing (NHM) effects can arise when the electromagnetic field generated by the electrons interacts strongly with the nucleus, leading to mixing of nuclear states. While previous studies have primarily attributed the NHM effect to unpaired valence electrons, we present a reformulation of the theoretical framework using dressed hyperfine states and investigate the NHM effect in 205Pb76+, 205Pb75+, 205Pb74+, and 205Pb73+ ions. Our numerical results show that significant NHM effects occurred in all of the studied ions, even in the absence of unpaired valence electrons in 205Pb76+ and 205Pb74+. We found that the lifetime of the isomeric state was reduced by 2–4 orders of magnitude compared with the bare 205Pb nucleus, depending on the charge state of the ion. These results indicate that it is the active valence electrons rather than unpaired electrons which play a key role in the NHM effect, thereby deepening our understanding of this phenomenon.
Advanced Machine Learning and Deep Learning Approaches for Estimating the Remaining Life of EV Batteries—A Review
Authors: de la Iglesia Daniel H. , Corbacho Carlos Chinchilla , Dib Jorge Zakour , Alonso-Secades Vidal , López Rivero Alfonso J.
Published: January 2025

This systematic review presents a critical analysis of advanced machine learning (ML) and deep learning (DL) approaches for predicting the remaining useful life (RUL) of electric vehicle (EV) batteries. Conducted in accordance with PRISMA guidelines and using a novel adaptation of the Downs and Black (D&B) scale, this study evaluates 89 research papers and provides insights into the evolving landscape of RUL estimation. Our analysis reveals an evolving landscape of methodological approaches, with different techniques showing distinct capabilities in capturing complex degradation patterns in EV batteries. While recent years have seen increased adoption of DL methods, the effectiveness of different approaches varies significantly based on application context and data characteristics. However, we also uncover critical challenges, including a lack of standardized evaluation metrics, prevalent overfitting problems, and limited dataset sizes, that hinder the field’s progress. To address these, we propose a comprehensive set of evaluation metrics and emphasize the need for larger and more diverse datasets. The review introduces an innovative clustering approach that provides a nuanced understanding of research trends and methodological gaps. In addition, we discuss the ethical implications of DL in RUL estimation, addressing concerns about privacy and algorithmic bias. By synthesizing current knowledge, identifying key research directions, and suggesting methodological improvements, this review serves as a central guide for researchers and practitioners in the rapidly evolving field of EV battery management. It not only contributes to the advancement of RUL estimation techniques but also sets a new standard for conducting systematic reviews in technology-driven fields, paving the way for more sustainable and efficient EV technologies.
NF-κB-Inducing Kinase Is Essential for Effective c-Rel Transactivation and Binding to the Il12b Promoter in Macrophages
Authors: Cuesta Natalia , Staniszewska Anna D. , Moreno Cristóbal , Punzón Carmen , Fresno Manuel
Published: January 2025

This study investigates the role of NIK in activating specific inflammatory genes in macrophages, focusing on the effect of a mutation in NIK found in alymphoplasia (aly/aly) mice. Mouse peritoneal macrophages from aly/aly mice showed a severe defect in the production of some pro-inflammatory cytokines, such as IL-12. This effect seemed to take place at the transcriptional level, as shown by the reduced transcription of Il12b and Il12a in aly/aly macrophages after exposure to the TLR4 agonist LPS. Immunoprecipitation studies showed that the binding of NIK to c-Rel was not efficient in RAW 264.7 cells over-expressing the aly/aly mutation. In addition, the shuttling of c-Rel to the nucleus was shown to be impaired in aly/aly macrophages in response to LPS. When looking more specifically at the regulation of the Il12b promoter, we found that c-Rel bound to the NF-kB consensus sequence in macrophages from WT mice 1 hr. after LPS challenge, whereas in aly/aly macrophages, the transcription factor bound to the promoter was p65. These findings indicate that NIK is essential for efficient c-Rel activation and proper inflammatory responses. NIK dysfunction could lead to weakened immune responses, and targeting this pathway may help in developing therapies for immune-related conditions.
Nanotherapeutics for Meningitis: Enhancing Drug Delivery Across the Blood-Brain Barrier
Authors: Sharma Hitaishi , Narayanan Kannan Badri , Ghosh Shampa , Singh Krishna Kumar , Rehan Prarthana , Amist Aparajita Dasgupta , Bhaskar Rakesh , Sinha Jitendra Kumar
Published: January 2025

Meningitis is the acute or chronic inflammation of the protective membranes, surrounding the brain and spinal cord, and this inflammatory process spreads throughout the subarachnoid space. The traditional drug delivery methods pose a disadvantage in limiting the capacity of crossing the blood–brain barrier (BBB) to reach the central nervous system (CNS). Hence, it is imperative to develop novel approaches that can overcome these constraints and offer efficient therapy for meningitis. Nanoparticle (NP)-based therapeutic approaches have the potential to address the limitations such as penetrating the BBB and achieving targeted drug release in specific cells and tissues. This review highlights recent advancements in nanotechnology-based approaches, such as functionalized polymeric nanoparticles, solid lipid nanoparticles (SLNs), nanostructured lipid carriers, nanoemulsions, liposomes, transferosomes, and metallic NPs for the treatment of meningitis. Recently, bionics has emerged as a next-generation technology in the development of novel ideas from biological principles, structures, and interactions for neurological and neuroinfectious diseases. Despite their potential, more studies are needed to ensure the safety and efficacy of NP-based drug delivery systems focusing on critical aspects such as toxicity, immunogenicity, and pharmacokinetics. Therefore, this review addresses current treatment strategies and innovative nanoparticle approaches, and it discusses future directions for efficient and targeted meningitis therapies.
A Framework for Informing Complete Street Planning: A Case Study in Brazil
Authors: Rosa Ashiley Adelaide , Lima Fernando
Published: January 2025

The concept of Complete Streets prompts a re-evaluation of the road design paradigm of the past century, which prioritized vehicles over human-centered use. It seeks to integrate land-use planning with urban mobility, focusing on a safer, more accessible allocation of street space that supports diverse transportation modes, stimulates local economic development, encourages active mobility, and reinforces place identity while recognizing each street’s unique purpose. However, Complete Streets have competing planning demands that vary according to their context and capacity to serve different functions and users. Identifying these priorities and street types is crucial for managing the trade-offs between functions according to each street’s role. This article presents a framework for assessing a street’s purpose and guiding interventions, focusing on the first two of the three key functions of Complete Streets: place, movement, and environment. The proposed framework is flexible and objective while allowing qualitative and subjective insights to be integrated. The preliminary results align with the empirical analysis of street segments, indicating the framework’s potential for diagnosing and evaluating street completeness. The developed experiment helped identify the framework’s limitations and its value as a tool for urban planning and design.
Investigating the Construction Procedure and Safety Oversight of the Mechanical Shaft Technique: Insights Gained from the Guangzhou Intercity Railway Project
Authors: Li Jianwang , Qi Wenrui , Li Xinlong , Liu Gaoyu , Chen Jian , Tong Huawei
Published: January 2025

Currently, subway and underground engineering projects are vital for alleviating urban congestion and enhancing citizens’ quality of life. Among these, excavation engineering for foundation pits involves the most accidents in geotechnical engineering. Although there are various construction methods, most face issues such as a large footprint, high investments, resource waste, and low mechanization. Addressing these, this paper focuses on a subway foundation pit project in Guangzhou using mechanical shaft sinking technology. Using intelligent cloud monitoring, we analyzed the stress–strain patterns of the cutting edge and segments. The results showed significant improvements in construction efficiency, cost reduction, safety, and resource conservation. Based on this work, this paper makes the following conclusions: (1) The mechanical shaft sinking method offers advantages such as small footprint, high mechanization, minimal environmental impact, and cost-effectiveness. The achievements include a 22.22% reduction in construction time, a 20.27% decrease in investment, and lower worker risk. (2) Monitoring confirmed that all cutting edge and segment values remained safe, demonstrating the method’s feasibility and rationality. (3) Analyzing shaft monitoring data and field uncertainties, this study proposes recommendations for future work, including precise segment lowering control and introducing high-precision total stations and GPS technology to mitigate tunneling and assembly inaccuracies. The research validates the mechanical shaft sinking scheme’s scientific and logical nature, ensuring safety and contributing to technological advancements. It offers practical insights, implementable suggestions, and significant economic benefits, reducing project investment by RMB 41,235,600. This sets a benchmark for subway excavation projects in South China and beyond, providing reliable reference values. Furthermore, the findings provide valuable insights and guidance for industry peers, enhancing overall efficiency and sustainable development in subway construction.
Use of Nicotinamide Mononucleotide as Non-Natural Cofactor
Authors: Naaz Tahseena , Kim Beom Soo
Published: January 2025

Nicotinamide mononucleotide (NMN) has emerged as a promising non-natural cofactor with significant potential to transform biocatalysis, synthetic biology, and therapeutic applications. By modulating NAD⁺ metabolism, NMN offers unique advantages in enzymatic reactions, metabolic engineering, and regenerative medicine. This review provides a comprehensive analysis of NMN’s biochemical properties, mechanisms of action, and diverse applications. Emphasis is placed on its role in addressing challenges in multi-enzyme cascades, biofuel production, and the synthesis of high-value chemicals. The paper also highlights critical research gaps, including the need for scalable NMN synthesis methods, improved integration into enzymatic systems, and comprehensive toxicity studies for therapeutic use. Emerging technologies such as AI-driven enzyme design and CRISPR-based genome engineering are discussed as transformative tools for optimizing NMN-dependent pathways. Furthermore, the synergistic potential of NMN with synthetic biology innovations, such as cell-free systems and dynamic regulatory networks, is explored, paving the way for precise and modular biotechnological solutions. Looking forward, NMN’s versatility as a cofactor positions it as a pivotal tool in advancing sustainable bioprocessing and precision medicine. Addressing current limitations through interdisciplinary approaches will enable NMN to redefine the boundaries of metabolic engineering and therapeutic innovation. This review serves as a roadmap for leveraging NMN’s potential across diverse scientific and industrial domains.
CAR-T Therapy Beyond B-Cell Hematological Malignancies
Authors: Canichella Martina , de Fabritiis Paolo
Published: January 2025

Despite the advances of CAR-T cells in certain hematological malignancies, mostly from B-cell derivations such as non-Hodgkin lymphomas, acute lymphoblastic leukemia and multiple myeloma, a significant portion of other hematological and non-hematological pathologies can benefit from this innovative treatment, as the results of clinical studies are demonstrating. The clinical application of CAR-T in the setting of acute T-lymphoid leukemia, acute myeloid leukemia, solid tumors, autoimmune diseases and infections has encountered limitations that are different from those of hematological B-cell diseases. To overcome these restrictions, strategies based on different molecular engineering platforms have been devised and will be illustrated below. The aim of this manuscript is to provide an overview of the CAR-T application in pathologies other than those currently treated, highlighting both the limits and results obtained with these settings.
A Case Study on Integrating an AI System into the Fuel Blending Process in a Chemical Refinery
Authors: Abdul Jameel Abdul Gani
Published: January 2025

Fuel blending plays a very important role in petroleum refineries, because it directly affects the quality of the end products, as well as the overall profitability of the refinery. This process of blending involves a combination of various hydrocarbon streams to make fuels that meet specific performance standards and comply with regulatory guidelines. For many decades, most refineries have been dependent on linear programming (LP) models for developing recipes for blending optimization. However, most LP models normally fail to capture the complex nonlinear interaction of blend components with fuel properties, leading to off-specification products that may necessitate re-blending. This work discusses a case study of a hybrid artificial intelligence (AI)-based method for gasoline blending based on a genetic algorithm (GA) combined with an artificial neural network (ANN). AI-based blending systems are more flexible and will enable the refineries to meet the product specifications regularly and result in cost reduction owing to the fall in quality giveaways. The AI-powered process discussed can predict, with much better accuracy, critical combustion properties of gasoline such as the Research Octane Number (RON), Motor Octane Number (MON), and Antiknock Index (AKI), compared to the classical LP models, with the added advantage of optimization of the blend ratio in real time. The results showed that the AI-integrated fuel blending system was able to produce fuel recipes with a mean absolute error (MAE) of 1.4 for the AKI. The obtained MAE is close to the experimental uncertainty of 0.5 octane. A high coefficient of determination (R2) of 0.99 was also obtained when the system was validated with a new set of 57 fuels comprising primary reference fuels and real gasoline blends. The study highlights the potential of AI-integrated systems in transforming traditional fuel blending practices towards sustainable and economically viable refinery operations.
Serum hsa-miR-22-3p, hsa-miR-885-5p, Lipase-to-Amylase Ratio, C-Reactive Protein, CA19-9, and Neutrophil-to-Lymphocyte Ratio as Prognostic Factors in Advanced Pancreatic Ductal Adenocarcinoma
Authors: Wnuk Jakub , Hudy Dorota , Strzelczyk Joanna Katarzyna , Michalecki Łukasz , Dybek Kamil , Gisterek-Grocholska Iwona
Published: January 2025

Pancreatic cancer (PC) is the seventh most common cause of cancer-related death worldwide. The low survival rate may be due to late diagnosis and asymptomatic early-stage disease. Most patients are diagnosed at an advanced stage of the disease. The search for novel prognostic factors is still needed. Two miRNAs, miR-22-3p and miR-885-5p, which show increased expression in PC, were selected for this study. The aim of this study was to evaluate the utility of these miRNAs in the prognosis of PC. Other prognostic factors such as lipase-to-amylase ratio (LAR), neutrophil-to-lymphocyte ratio (NLR), and carbohydrate antigen 19-9 (CA19-9) were also evaluated in this study. This study was conducted in 50 patients previously diagnosed with pancreatic ductal adenocarcinoma in clinical stage (CS) III and IV. All patients underwent a complete medical history, physical examination, and routine laboratory tests including a complete blood count, C-reactive protein (CRP), CA19-9, lipase, and amylase. Two additional blood samples were taken from each patient to separate plasma and serum. Isolation of miRNA was performed using TRI reagent with cel-miR-39-3p as a spike-in control. Reverse transcription of miRNA was performed using a TaqMan Advanced miRNA cDNA Synthesis Kit. The relative expression levels of miR-22-3p and miR-885-5p were measured using RT-qPCR. Serum hsa-miR-22-3p was detected in 22 cases (44%), while hsa-miR-885-5p was detected in 33 cases (66%). There were no statistically significant differences in serum or plasma miRNA expression levels between patient groups based on clinical stage, gender, or BMI. There were no statistically significant differences in LAR between patients with different CS. For NLR, CRP and CA19-9 thresholds were determined using ROC analysis (6.63, 24.7 mg/L and 4691 U/mL, respectively). Cox’s F test for overall survival showed statistically significant differences between groups (p = 0.002 for NLR, p = 0.007 for CRP and p = 0.007 for CA19-9). Utility as prognostic biomarkers was confirmed in univariate and multivariate analysis for CA19-9, CRP, and NLR. The selected miRNAs and LAR were not confirmed as reliable prognostic markers in PC.
TBC Development on Ti-6Al-4V for Aerospace Application
Authors: Takahashi Renata Jesuina , Assis João Marcos Kruszynski de , Fazan Leonardo Henrique , Rodríguez Laura Angélica Ardila , Capella Aline Gonçalves , Reis Danieli Aparecida Pereira
Published: January 2025

The Ti-6Al-4V alloy is widely utilized in the aerospace industry for applications such as turbine blades, where it is valued for its mechanical strength at high temperatures, low specific gravity, and resistance to corrosion and oxidation. This alloy provides crucial protection against oxidation and thermal damage. A thermal barrier coating (TBC) typically consists of a metallic substrate, a bond coating (BC), a thermally grown oxide (TGO), and a topcoat ceramic (TC). This study aimed to investigate laser parameters for forming a TBC with a NiCrAlY bond coating and a zirconia ceramic topcoat, which contains 16.0% equimolar yttria and niobia. The coatings were initially deposited in powder form and then irradiated using a CO2 laser. The parameters of laser power and beam scanning speed were evaluated using scanning electron microscopy and X-ray diffraction. The results indicated that the optimal laser scanning speed and power for achieving the best metallurgical bonding between the substrate/BC and the BC-TGO/TC layers were 70 mm/s at 100 W and 550 mm/s at 70 W, respectively. Laser-based layer formation has proven to be a promising technique for the application of TBC.
Deep-Learning-Based Reconstruction of Single-Breath-Hold 3 mm HASTE Improves Abdominal Image Quality and Reduces Acquisition Time: A Quantitative Analysis
Authors: Kubicka Felix , Tan Qinxuan , Meyer Tom , Nickel Dominik , Weiland Elisabeth , Wagner Moritz , Marticorena Garcia Stephan Rodrigo
Published: January 2025

Purpose: Breath-hold T2-weighted half-Fourier acquisition single-shot turbo spin echo (HASTE) magnetic resonance imaging (MRI) of the upper abdomen with a slice thickness below 5 mm suffers from high image noise and blurring. The purpose of this prospective study was to improve image quality and accelerate imaging acquisition by using single-breath-hold T2-weighted HASTE with deep learning (DL) reconstruction (DL-HASTE) with a 3 mm slice thickness. Method: MRI of the upper abdomen with DL-HASTE was performed in 35 participants (5 healthy volunteers and 30 patients) at 3 Tesla. In a subgroup of five healthy participants, signal-to-noise ratio (SNR) analysis was used after DL reconstruction to identify the smallest possible layer thickness (1, 2, 3, 4, 5 mm). DL-HASTE was acquired with a 3 mm slice thickness (DL-HASTE-3 mm) in 30 patients and compared with 5 mm DL-HASTE (DL-HASTE-5 mm) and with standard HASTE (standard-HASTE-5 mm). Image quality and motion artifacts were assessed quantitatively using Laplacian variance and semi-quantitatively by two radiologists using five-point Likert scales. Results: In the five healthy participants, DL-HASTE-3 mm was identified as the optimal slice (SNR 23.227 ± 3.901). Both DL-HASTE-3 mm and DL-HASTE-5 mm were assigned significantly higher overall image quality scores than standard-HASTE-5 mm (Laplacian variance, both p < 0.001; Likert scale, p < 0.001). Compared with DL-HASTE-5 mm (1.10 × 10−5 ± 6.93 × 10−6), DL-HASTE-3 mm (1.56 × 10−5 ± 8.69 × 10−6) provided a significantly higher SNR Laplacian variance (p < 0.001) and sharpness sub-scores for the intestinal tract, adrenal glands, and small anatomic structures (bile ducts, pancreatic ducts, and vessels; p < 0.05). Lesion detectability was rated excellent for both DL-HASTE-3 mm and DL-HASTE-5 mm (both: 5 [IQR4–5]) and was assigned higher scores than standard-HASTE-5 mm (4 [IQR4–5]; p < 0.001). DL-HASTE reduced the acquisition time by 63–69% compared with standard-HASTE-5 mm (p < 0.001). Conclusions: DL-HASTE is a robust abdominal MRI technique that improves image quality while at the same time reducing acquisition time compared with the routine clinical HASTE sequence. Using ultra-thin DL-HASTE-3 mm results in an even greater improvement with a similar SNR.
Current Status of CT Imaging Before Common Transcatheter Interventions for Structural Heart Disease
Authors: Salgado Rodrigo , Cadour Farah , Cau Riccardo , Saba Luca
Published: January 2025

Background: Over the past decade, several trials and observational studies have validated the use of minimally invasive cardiac interventions as viable treatment options for various cardiac diseases. Transcatheter techniques for severe aortic valve stenosis have rapidly emerged as alternatives to surgical aortic valve replacement in certain patient populations. Additionally, non-surgical treatment options have expanded for conditions affecting other cardiac valves, such as the mitral valve. These emerging minimally invasive interventions complement already well-established endovascular techniques for, among others, atrial septal defect closure, left atrial appendage occlusion and pulmonary vein isolation in patients with atrial fibrillation. Given their non-surgical nature and lack of direct visualisation of the targeted anatomy, these procedures heavily rely on precise pre-procedural radiological imaging for optimal patient selection and procedural success. Method: This paper is based on the expert opinion of the authors and an exhaustive literature research. Results: This manuscript reviews the most commonly employed minimally invasive cardiac interventions, highlighting the essential pre-procedural imaging information and key aspects that must be included in radiological reports to mitigate potential complications. Conclusion: Accurate pre-procedural imaging is crucial for ensuring safe and effective minimally invasive cardiac interventions, underscoring the importance of the radiologist in the pre-procedural work-up of these patients.
Variations and Asymmetry in Sacral Ventral Rami Contributions to the Bladder
Authors: Overton Rebeccah R. , Tamas Istvan P. , Day Emily P. , Frara Nagat , Pontari Michel A. , Fecho Susan B. , Popoff Steven N. , Barbe Mary F.
Published: January 2025

Background/Objectives: We have demonstrated in human cadavers and canines that nerve transfer to bladder vesical nerve branches is technically feasible for bladder reinnervation after nerve injury. We further clarify here that sacral (S) ventral rami contribute to these vesical branches in 36 pelvic sides (in 22 human cadavers). Methods: Gross post-mortem visualization and open anterior abdominal approaches were used, as was micro-CT of sacral nerve bundles, for further confirmation when needed. Results: Considerable between and within-subject variation was observed. Sacral (S) ventral rami contributions to vesical nerves were observed as shared contributions from several rami or, in a few cases, from single rami: S2 alone (6%), S3 alone (6%), S2 and S3 (28%), S3 and S4 (28%), S2–S4, 14%, L5 in combination with S1–S4 (6%), S1 and S2 (6%), and S3–S5 (3%). The most common contributor to these shared or single rami contributions was from the S3 ventral ramus, which contributed 100% of the time on the left side and 79% on the right side. Side-to-side asymmetry was observed in 10 of 14 cadavers examined bilaterally (71%). Conclusions: This characterization of the anatomical variation in sacral ventral rami contributions to the bladder will ultimately aid in developing therapeutics for patients with bladder dysfunction.
Pedagogical Leaders’ Approaches to Promoting Inclusion of Children with Autism in Norwegian Kindergartens
Authors: Boquist Trine Andrea , Ødegård Magnar , Pesonen Henri Valtteri
Published: January 2025

It is well recognized that Norwegian kindergartens have an important role in ensuring inclusion among all children, but the actual implementation of inclusive practices can vary greatly in early childhood education. Particularly how the inclusion of children with Autism Spectrum Disorder (ASD) is supported in kindergartens has raised concerns, and research focusing on the current circumstances in Norway is scarce. To fill in this gap in research, our study examined pedagogical leaders’ approaches to promoting inclusion of children with autism in kindergartens. The method of empathy-based stories (MEBS) was used to collect stories from 32 participants working in kindergartens. Qualitative analysis of participant produced stories revealed that inclusion of children with autism consisted of two themes: (1) professional framework for inclusion and (2) empathetic approaches to inclusion. The findings provide suggestions for further research and development work related to inclusion of children with ASD in early childhood education.
Strategic Reduction Method for Energy Input and CO2 Emissions: Direct Supply of Underground Seawater for Land-Based Aquaculture Systems in South Korea
Authors: Baek Seungyeop , Jeon Byungchil , Oh Sebong , Choi Wontak , Choi Seunggi , Sung Yonmo
Published: January 2025

This study addresses the challenges of and opportunities for achieving the ambitious greenhouse gas emissions reduction target of the fishery sector of the Republic of Korea, set at 96% by 2030. We also focus on the current status of land-based aquaculture and underground seawater resource development, quantitatively compare energy inputs for land-based fish cultivation, and evaluate the potential of underground seawater to reduce CO2 emissions. Since 2010, 762 underground seawater boreholes have been developed, yielding a cumulative daily pumpage of 125,780 m3. Jeollanam-do was found to have the highest daily pumpage, with an annual energy requirement of 131,205,613 Mcal. Despite the fact that the energy demands for underground seawater are higher in some months, it provides a 22.6% reduction in total annual energy consumption compared to surface water. The use of underground seawater for heating or cooling resulted in a 24.1% reduction in the required input energy. However, energy requirements increase due to the relatively high surface water temperature in some regions and seasons. This study also highlights the utilization of underground seawater in heating or cooling surface water via indirect applications using geothermal heat pumps. This innovative research broadens the methods of greenhouse gas mitigation, particularly in the agriculture, livestock, and fisheries industries.
Diagnostic Sensitivity of Phytophthora ×alni from Environmental Samples Using Conventional and Real-Time PCR
Authors: Trzewik Aleksandra , Orlikowska Teresa
Published: January 2025

The study aims to compare the sensitivity of conventional and real-time PCR in detecting Phytophthora ×alni DNA in plants, peat substrate, and water. The accuracy of the detection of DNA isolated from pure cultures of P. ×alni and the influence of DNA isolated from Alnus tissue and peat substrate on the sensitivity of P. ×alni detection are assessed. Real-time PCR is 100-fold more sensitive than conventional PCR in the reaction with DNA extracted from plants and peat. Adding 1 µL and 3 µL of plant and peat DNA, respectively, reduces the sensitivity of P. ×alni detection by 100 times when using conventional PCR and by 10 times when using real-time PCR. The conventional PCR technique allows for the detection of P. ×alni on the day the first necrosis symptoms become visible or two days before they appear on artificially inoculated shoots. The real-time PCR technique allows for the detection of P. ×alni, depending on the zoospore concentration and isolate, 2, 4, 6, 8, and 12 days before necrosis appears. Conventional and real-time PCR allow for the detection of 250 and 100 P. ×alni zoospores, respectively, in a 0.5 g peat substrate sample and 25 and 10 spores, respectively, in 100 µL water.
Residual Nitrite, Nitrate, and Volatile N-Nitrosamines in Organic and Conventional Ham and Salami Products
Authors: Bak Kathrine H. , Bauer Susanne , Eisenreich Christoph , Paulsen Peter
Published: January 2025

Nitrite and nitrate in meat products may be perceived negatively by consumers. These compounds can react to form carcinogenic volatile N-nitrosamines. “Nitrite-free” (i.e., uncured) organic meat products may contain nitrate from natural sources (e.g., spices and water). We studied the quality of ham and salami (conventional cured; organic cured; organic uncured). Residual nitrite and nitrate, volatile N-nitrosamines, microbial load, surface color, water activity, and pH were determined, considering one week of refrigerated storage in open or unopened packages. Residual nitrite and nitrate in organic, uncured salami were similar to cured salami, presumably from the addition of herbs and spices and nitrate reduction by nitrate reductase from microorganisms. For cooked ham, residual nitrite was significantly lower in the organic, uncured sample, while residual nitrate was not detected. N-nitrosodiphenylamine was detected in all samples at day 0, exceeding, in three out of five cured and both uncured products, the US legal limit of 10 µg/kg of volatile N-nitrosamines in foods. This finding warrants further investigation. The microbial load in salami products was dominated by bacteria from starter cultures. In ham, a slight increase in total aerobic count and lactic acid bacteria during storage was noted. Overall, the microbial quality of the products was as expected for the respective product types.
Fatty Acids of European Sardine (Sardina pilchardus) White Muscle Can Discriminate Geographic Origin Along the Iberian Atlantic Coast
Authors: Calado Ricardo , Palma Marcos , Domingues Maria Rosário , Ricardo Fernando , Rey Felisa
Published: January 2025

The European sardine (Sardina pilchardus) ranks among the most valuable species of Iberian fisheries, and the accurate tracing of its geographic origin, once landed, is paramount to securing sustainable management of fishing stocks and discouraging fraudulent practices of illegal, unreported, and unregulated (IUU) fishing. The present study investigated the potential use of S. pilchardus white muscle fatty acids (FAs) to successfully discriminate the geographic origin of samples obtained in seven commercially important fishing harbors along the Iberian Atlantic Coast. While 35 FAs were identified using gas chromatography–mass spectrometry in the white muscle of S. pilchardus, the following, as determined by the Boruta algorithm, were key for sample discrimination: 14:0, 22:6n-3, 22:5n-3, 18:0, 20:5n-3, 16:1n-7, 16:0, and 18:1n-7 (in increasing order of relevance). An average 83% correct allocation of landed specimens was achieved, with some landing locations presenting 100% correct allocation (e.g., Ría de Pontevedra in northern Spain and Peniche in central Portugal). Linear discriminant analysis revealed a separation of samples from northern Spain and Peniche, and a partial overlap of all other locations. The present results highlight the potential of using FAs of S. pilchardus white muscle to reliably discriminate the geographic origin of landed individuals along the Iberian Atlantic coast.
Simultaneous Encapsulation of Probiotic Bacteria (Lactococcus lactis, and Lactiplantibacillus plantarum) in Calcium Alginate Hydrogels
Authors: Vinceković Marko , Maslov Bandić Luna , Oštarić Fabijan , Kiš Marta , Zdolec Nevijo , Marić Ivan , Šegota Suzana , Zelić Hana , Mikulec Nataša
Published: January 2025

Encapsulation in alginate hydrogel microspheres is an effective method for protecting and improving the survival of lactic acid bacteria in different environments. This research aims to expand the knowledge about the structure/property relationship of calcium alginate microspheres loaded with a mixture of autochthonous probiotic bacteria (Lactococcus lactis and Lactiplantibacillus plantarum). A novel hydrogel formulation (FORMLAB) was prepared by ionic gelation and the molecular interactions between the FORMLAB constituents, surface morphology, structure, swelling degree, and release profile were characterized. The simultaneous encapsulation of two bacterial cultures in the same compartment does not diminish their viability. The binding of calcium ions to bacterial cells creates favorable conditions for the propagation of the encapsulated bacteria. The molecular interactions between the FORMLAB constituents are complex, involving mainly hydrogen bonds and electrostatic interactions. With a very high degree of swelling followed by low crosslinking, the surface of the microspheres covered with bacterial cells and diffusion through the hydrogel matrix allow for the delivery of probiotics at the right time. The findings suggest that bacterial cells are efficiently delivered from calcium alginate microspheres, offering promising applications in the development of functional foods, especially in cheese production.
The Genetic Determinants of Listeria monocytogenes Resistance to Bacteriocins Produced by Lactic Acid Bacteria
Authors: Zawiasa Anna , Olejnik-Schmidt Agnieszka
Published: January 2025

Background: Listeria monocytogenes is a Gram-positive bacterium responsible for listeriosis, a serious foodborne disease that can lead to serious health complications. Pregnant women, newborns, the elderly, and patients with weakened immune systems are particularly susceptible to infection. Due to the ability of L. monocytogenes to survive in extreme environmental conditions, such as low temperatures, high salinity, and acidity, this bacterium poses a serious threat to food production plants and is particularly difficult to eliminate from these plants. One of the promising solutions to reduce the presence of this bacterium in food products is bacteriocins as natural control agents. These are substances with antibacterial activity produced by other bacteria, mainly lactic acid bacteria (LAB), which can effectively inhibit the development of pathogens such as L. monocytogenes. The use of bacteriocins in the food industry is beneficial due to their natural origin, specificity of action, and consumer safety. However, the problem of resistance to these substances exists. Results: This review focuses on the mechanisms of bacteriocin resistance, such as modifications of bacteriocin docking receptors, changes in the structure of the cell wall and membrane, and the occurrence of cross-resistance to different bacteriocins. Genetic factors determining these mechanisms and strategies to cope with the problem of resistance are also presented. Conclusions: Research on this issue is crucial for developing effective preventive methods that will enable the safe and long-term use of bacteriocins in food production.
Using a Safe System Framework to Examine the Roadway Mortality Increase Pre-COVID-19 and in the COVID-19 Era in New York State
Authors: Pressley Joyce C. , Aziz Zarah , Pawlowski Emilia , Hines Leah , Roberts Aisha , Guzman Jancarlos , Bauer Michael
Published: January 2025

Roadway mortality increased during COVID-19, reversing a multi-decade downward trend. The Fatality Analysis Reporting System (FARS) was used to examine contributing factors pre-COVID-19 and in the COVID-19 era using the five pillars of the Safe System framework: (1) road users; (2) vehicles; (3) roadways; (4) speed; and (5) post-crash care. Two study time periods were matched to control for seasonality differences pre-COVID-19 (n = 1725, 1 April 2018–31 December 2019) and in the COVID-19 era (n = 2010, 1 April 2020–31 December 2021) with a three-month buffer period between the two time frames excluded. Four of the five pillars of the safe system had road safety indicators that worsened during the pandemic. Mortality was 19.7% higher for motor vehicle occupants and 45.1% higher for riders of motorized two-wheeled vehicles. In adjusted analyses, failure to use safety equipment (safety belts/helmets) was associated with 44% higher mortality. Two road user groups, non-motorized bicyclists and pedestrians, did not contribute significantly to higher mortality. Urban roadway crashes were higher compared to rural crashes. Additional scientific inquiry into factors associated with COVID-19-era mortality using the Safe System framework yielded important scientific insights to inform prevention efforts. Motorized two-wheeled vehicles contribute disproportionately to pandemic-era higher mortality and constitute an emerging road safety issue that deserves further attention.
Association of Novel Pathogenic Variant (p. Ile366Asn) in PLA2G6 Gene with Infantile Neuroaxonal Dystrophy
Authors: Cheema Asma Naseer , Shi Ruyu , Kamboh M. Ilyas
Published: January 2025

A couple presented to the office with an apparently healthy infant for a thorough clinical assessment, as they had previously lost two male children to a neurodegenerative disorder. They also reported the death of a male cousin abroad with a comparable condition. We aimed to evaluate a novel coding pathogenic variant c.1097T>A, PLA2G6, within the affected family, previously identified in a deceased cousin, but its clinical significance remained undetermined. A 200 bp PCR product of target genome (including codon 366 of PLA2G6) was amplified followed by enzymatic digestion (MboI) and sequencing. Structural pathogenic variant analysis was performed using PyMOL 2.5.4. In RFLP analysis, the mutant-type allele produced a single band of 200 bp, and the wild-type allele manifested as two bands of 112 bp and 88 bp. The pathogenic variant was identified in nine family members, including two heterozygous couples with consanguineous marriages resulting in affected children. It was predicted to be deleterious by multiple bioinformatic tools. The substitution of nonpolar isoleucine with polar asparagine of iPLA2 (Ile366Asn) resulted in a eense pathogenic variant (ATC>AAC). A missense variant (p. Ile366Asn) in the PLA2G6 gene is associated with clinically evident infantile neuroaxonal dystrophy, which is transmitted in an autosomal recessive pattern, and is also predicted to be dysfunctional by bioinformatic analyses.