bluuebunny/crossref_metadata_2025 huggingface dataset:
Knowledge, attitudes, and practices toward leishmaniasis and one health: a cross-sectional study among medical and veterinary professionals
Authors: Khan Yasir , Lin I-Chen , Khan Sundus , Kanwal Mehtab , Wajid Abdul , Khan Aamir , Noor Fazal , Almajwal Ali Madi , Chen Chien-Chin , Qadeer Abdul
Published: January 2025

Leishmaniasis is a significant zoonotic infection with global health implications, particularly in regions where human and animal health are closely interconnected. This cross-sectional study assessed the knowledge, attitudes, and practices (KAP) of 5,074 participants regarding leishmaniasis and the One Health concept. The socio-demographic data revealed that most respondents were young (82.6%), male (82.3%), and from rural areas (50.8%), with a majority based in Khyber Pakhtunkhwa (57.4%). Veterinary professionals (42.1%) and students (27.4%) constituted the primary respondents, with 32.4% working in government hospitals. Knowledge about leishmaniasis was high, with 97.5% of participants recognizing Leishmania and 86% correctly identifying it as a protozoan disease. The majority (71.8%) believed in the zoonotic transmission of Leishmania from animals to humans. Attitudes toward the One Health concept were positive, with 90.2% of respondents aware of it, and 95.5% acknowledged the zoonotic nature of the disease. Practices for controlling sandfly populations were observed by 56.4% of participants, with bed nets (44.9%) being the most common preventive measure. Results showed that younger participants had significantly better knowledge, attitude, and perception regarding leishmaniasis and One Health compared to older individuals. Veterinarians and government hospital staff demonstrated better KAP toward VL. This study underscores the importance of educational interventions and community-based control measures to enhance understanding and prevention of leishmaniasis, with the One Health approach playing a crucial role.
In silico development of a multi-epitope-based vaccine against Burkholderia cepacia complex using reverse vaccinology
Authors: Ghorbani Donya , Beig Masoumeh , Noori Goodarzi Narjes , Sholeh Mohammad , Shahbazi Behzad , Moghaddam Yaser , Badmasti Farzad
Published: January 2025

Background

Multidrug-resistant Burkholderia cenocepacia and Burkholderia multivorans have emerged as significant pathogens, particularly in patients with cystic fibrosis (CF) and chronic granulomatous disease (CGD).

Objective

Given the absence of approved vaccines, this study aimed to identify potential vaccine candidates against these pathogens.

Methods

The complete genomes of B. cenocepacia and B. multivorans were retrieved from the GenBank. Surface-exposed proteins that were antigenic, non-allergenic, and non-homologous to human proteins were selected for further analysis. The conserved domains of the selected proteins were analyzed, and their presence was examined across 68 genomes. Subsequently, linear and conformational B-cell epitopes and human MHC II binding sites were identified. Highly conserved and immunogenic B-cell epitopes from outer membrane proteins (OMPs) were incorporated into a multi-epitope vaccine (MEV). Molecular docking analysis was performed to assess the interaction of the selected proteins. Finally, molecular dynamics (MD) simulations were conducted using GROMACS 2019 to evaluate the feasibility and dynamics of the interactions between the chimeric MEV and Toll-like receptor complexes, TLR2 and TLR4.

Results

Of 16,723 proteins identified in B. multivorans and B. cenocepacia strains, nine proteins (six OMPs and three extracellular) were selected as ideal candidates based on established criteria. These proteins had a molecular weight of 110 kDa and were present in ≥ 75% of the dataset of B. multivorans and B. cenocepacia genomes. In addition, molecular docking and MD indicated stable and feasible interactions between MEV and TLRs. The MEV-TLR4 system demonstrates the greatest stability and tightly bound interaction, with minimal fluctuations and high structural integrity. In contrast, the MEV-only system exhibits significant flexibility and dynamic behavior as a free ligand, while the MEV-TLR2 system balances stability and flexibility, showing a dynamic but stable interaction.

Conclusion

Nine potential immunogenic proteins were identified as viable targets for vaccine development. An optimized MEV was explicitly designed for B. multivorans and B. cenocepacia. The novel MEV platform exhibited high binding affinity to immune receptors and favorable molecular docking characteristics. Although these findings are encouraging, additional in vitro and in vivo testing is necessary to validate the vaccine’s effects.
Experimental Investigation of Dual-Path Inline Mixing System for Sprayers in Corn-Soybean Strip Intercropping Mode
Authors: Zhang Zhenyu , Guo Peijie , Ma Hongying , Chen Yuxiang , Chen Yu
Published: January 2025

Corn-soybean strip intercropping, which fully utilizes land resources and has high total yield and soil fertility, has become a modern agricultural cultivation mode that is actively promoted. In order to solve the weed problem in corn-soybean strip intercropping, the agricultural technology requirements cannot be met by traditional pre-mixed spraying machines, so a direct injection dual-path inline mixing system was designed for the corn-soybean strip intercropping mode. The system was integrated to improve its installation convenience and universality, and was capable of fulfilling the requirements for the simultaneous application of two types of pesticides at varying mixing ratios. The system mainly consists of a water solvent injection module, glyphosate (pesticide for corn) inline mixing module, and a fomesafen (soybean pesticide) inline mixing module. First, the detection rules of the mixing ratio of related pesticides based on the electrical conductivity measurement principle were studied. Then, the working characteristics of the designed direct injection dual-path inline mixing system were studied through experiments using different pesticides and mixing ratio adjustment ranges. The mixing uniformity test showed that the designed direct injection dual-path inline mixing system had good mixing uniformity, and the maximum uniformity coefficient of the mixing ratio was 9.7%. The stability test showed that the mixing ratio of the designed dual-path inline mixing system was relatively stable, with the maximum standard deviation of the mixing ratio accounting for about 2.2% of its average value, and the maximum average deviation was less than 1.5%. The precision and response time test showed that the designed dual-path inline mixing system had an average deviation of the mixing ratio of less than 2.7% under the condition of a step signal target mixing ratio, and the response time was a maximum of 3.4 s. The results show that the designed dual-path inline mixing system has good performance, and the research findings provide a reference for the design and optimization of inline mixing systems.
Effect of Short-Term Storage in Modified Atmosphere Packaging (MAP) and Controlled Atmosphere (CA) on Total Polyphenol Content and Antioxidant Activity in Juices from Haskap Berry (Lonicera caerulea L.)
Authors: Kowalczyk Barbara Anna , Bieniasz Monika , Błaszczyk Jan
Published: January 2025

This article focuses on analysing the properties of six varieties of haskap berry (honeyberry) as a valuable raw material for producing health-promoting juices. Significant differences in the content of bioactive compounds were observed between juices derived from fruits of the same species. This study demonstrated that controlled atmosphere (CA) conditions (20% CO2 and 5% O2) and modified atmosphere packaging (MAP) in Xtend bags affected juice quality by minimising nutritional losses. The analysis of polyphenol content in the juices revealed significant differences between varieties and years (2021 and 2022), primarily due to varying weather conditions. In 2022, the polyphenol content of the varieties ‘Usłada’, ‘Candy Blue’, ‘Boreal Beauty’, and ‘Boreal Beast’ was from 69% to twice as high compared to values recorded in 2021. CA and MAP storage conditions were found to be more effective than normal atmosphere (NA) in preserving bioactive components, and thus the antioxidant activity of the fruits, as measured by the DPPH method. The variety ‘Sinij Utes’ had the highest total polyphenol contents and their lowest loss during storage. Conversely, the variety ‘Boreal Beauty’ contained the lowest polyphenol levels both after harvest and storage. This study confirmed the importance of proper storage conditions for maintaining the antioxidant properties of haskap berries.
Evaluation of Honey as a Rooting Adjuvant for Cutting Propagation of Three Common Nursery Crops
Authors: Bowden Anthony T. , Knight Patricia R. , Ryals Jenny B. , Coker Christine E. H. , Langlois Scott A. , Broderick Shaun R. , Blythe Eugene K. , Sakhanokho Hamidou F.
Published: January 2025

Plant propagation is a labor-intensive process in the nursery and greenhouse industry, with labor accounting for 41.4% of expenditures in 2019—$4.8 billion of the $11.6 billion total. Labor availability remains a critical issue, and current methods of applying root-promoting compounds to cuttings often yield inconsistent rooting responses. This research investigated honey as a rooting adjuvant and its effects on rooting in Red Cascade™ miniature rose (Rosa ‘MOORcap’), common camellia (Camellia japonica), and southern magnolia (Magnolia grandiflora ‘Little Gem’). For Red Cascade™ rose, adding honey to water-soluble indole-3-butyric acid (IBA) solutions did not improve root counts compared to IBA alone. However, 1000 µL∙L⁻1 IBA produced more roots than 250 µL∙L⁻1 IBA. Camellia and magnolia cuttings were treated with multiflora, Manuka, or commercial honey, alongside IBA rates of 0 to 4500 µL∙L⁻1. In camellia, honey type or auxin rate did not significantly affect rooting, but local and multiflora honey combined with higher IBA rates increased root counts. For magnolia, multiflora honey improved both root number and quality, outperforming other treatments. While honey showed limited benefits for camellia and rose, multiflora honey demonstrated potential economic advantages for magnolia propagation, enhancing root quality and quantity for producers.
Effects of Different Rates of Nitrogen Fertilisation and Biological Preparations to Increase Nitrogen Use Efficiency on Yield Structure Elements in Maize
Authors: Liakas Vytautas , Marcinkevičienė Aušra , Rudinskienė Aušra , Steponavičienė Vaida
Published: January 2025

The soil used for the field experiment was PLb-g4 Endohipogleyic Eutric Planasol. The research aimed to investigate the effects of different nitrogen fertilisation rates and biological preparations on yield structure elements and partial factor productivity of nitrogen in maize (Zea mays L.) grown for grain production. The factors studied were Factor A—nitrogen (N) fertiliser rates: (1) 100 kg ha−1, (2) 140 kg ha−1, and (3) 180 kg ha−1, and Factor B—use of biofertilisers: (1) no biological preparations (BP) used, (2) biological preparation (AB)—nitrogen bacteria Paenibacillus polymyxa (1.0 L ha−1), (3) biological preparations (AB + C)—nitrogen bacteria Paenibacillus polymyxa (1.0 L ha−1) and cytokinin, and (4) biological preparations (AB + H)—nitrogen bacteria Paenibacillus polymyxa (1.0 L ha−1) and humic acids. The research showed that the yield of maize grain was significantly increased not only by increasing the rates of nitrogen fertilisation but also by using biological preparations. The highest maize grain yield (11.5 t ha−1) was obtained in 2020 using N180 fertilisation, in combination with biological preparations AB + H. In all cases, the biological preparations and their combinations significantly increased the maize grain yield compared to the control field (no use of BP). The biological preparations in combination with N significantly increased the weight of 1000 grains and thus the grain yield per plant. The highest maize grain yield per plant (154.6 g) was obtained in 2020 using N180 fertilisation, in combination with biological preparations AB + H. In most cases, positive, strong, very strong, and statistically significant correlations were observed between the different rates of nitrogen fertilisation and the indicators studied: r = 0.76–0.94 (p < 0.01, p < 0.05). No statistically significant correlation was found between nitrogen fertilisation rates and the number of grains per cob (p > 0.05). The highest partial factor productivity of nitrogen fertiliser (92.0 kg of maize kg−1 of N) was obtained in 2020 using N100 fertilisation, in combination with AB + H. Increasing the nitrogen fertiliser rates and not using biological preparations resulted in a decrease in the partial factor productivity of nitrogen fertiliser.
Optimizing Fungicide Seed Treatments for Early Foliar Disease Management in Wheat Under Northern Great Plains Conditions
Authors: Bugingo Collins , Ali Shaukat , Yabwalo Dalitso , Byamukama Emmanuel
Published: January 2025

Tan spot (Pyrenophora tritici-repentis) and stripe rust (Puccinia striiformis f. sp. tritici) are major foliar diseases of wheat, causing significant yield losses globally. This study evaluated the efficacy of fungicide seed treatments in managing these diseases during early growth stages under greenhouse, growth chamber, and field conditions in the Northern Great Plains. Winter and spring wheat cultivars were treated with pyraclostrobin or combinations of thiamethoxam, difenoconazole, mefenoxam, fludioxonil, and sedaxane, among others. Greenhouse and growth chamber plants were inoculated with the respective pathogens, while field trials relied on natural inoculum. Fungicide treatments significantly reduced stripe rust severity (up to 36%) (p ≤ 0.05) and moderately reduced tan spot severity during early growth stages (15–20%). Treated plants demonstrated a 30–40% improvement in plant vigor, and a 25–50% increase in winter survival. Additionally, grain yield in treated plots increased by 25–50% (p ≤ 0.05), with test weight and protein content improving by 10% and 15%, respectively. These findings demonstrate the potential of fungicide seed treatments as an integrated pest (or pathogen) management (IPM) strategy to enhance early foliar disease control and wheat productivity.
GeoSAE: A 3D Stratigraphic Modeling Method Driven by Geological Constraint
Authors: Yang Yongpeng , Zhou Jinbo , Ruan Ming , Xiao Haiqing , Hua Weihua , Wei Wencheng
Published: January 2025

Deep learning outperforms traditional interpolation methods in 3D geological modeling due to its ability to model nonlinear relationships and its flexibility in incorporating diverse geological data. However, acquiring geological data for practical applications is challenging, and the quality of the data can vary significantly, which limits the effectiveness of purely data-driven deep learning models in 3D geological modeling. To address this challenge, this paper introduces GeoSAE, a geoconstraint-driven 3D geological modeling method. GeoSAE improves potential field prediction by employing a stacked autoencoder network (SAE) and incorporating geological constraints as a loss function during model training. This approach generates a geologically consistent, smooth, and continuous 3D stratigraphic model. To validate the method, this study applies it to a 60-square-kilometer region in Jiangdong new district, Haikou city, China. Stratigraphic interface points were utilized to predict the 3D potential field, with PyVista (version 0.44.2) enabling the accurate extraction of stratigraphic interfaces. Model quality was evaluated through comprehensive assessments of loss function analysis, data fitting, and the verification of stratigraphic smoothness constraints. Results indicate that the stratigraphic model generated by GeoSAE closely aligns with the actual data, accurately capturing stratigraphic geometry. Additionally, incorporating smoothness constraints enhances model smoothness, minimizes irregular stratigraphic fluctuations, and produces a more natural and continuous stratigraphic morphology.
Reproducibility and Accuracy of Two Facial Scanners: A 3D In Vivo Study
Authors: Pellitteri Federica , Calza Marta , Baldi Giacomo , De Maio Matteo , Lombardo Luca
Published: January 2025

Aim: This study aimed to compare the accuracy and reproducibility of the EinScan H2 (SHINING 3D, Hangzhou, China) with the Vectra M3 3D Imaging System (Canfield Scientific, Parsippany, NJ, USA) and with direct anthropometric measurements. Methods: Twenty subjects were scanned with two different facial scanning systems. Linear measurements were compared with direct anthropometric measurements taken on the patient’s face, while area analysis (forehead, tip of the nose, chin, right and left cheek) was performed by overlaying scans after best-fit alignment using the Geomagic Control X v2020.1.1 program. Statistical analysis was conducted using IBM SPSS v28 software, except for the power analysis, which was conducted using R v4.2.1. Results: The intraclass correlation coefficient (ICC) showed high repeatability for both the linear and point measurements, with all values exceeding 0.90. The paired-sample Wilcoxon test revealed no significant differences (p > 0.05) between the linear measurements, indicating consistency across the three measurement methods. Point analysis using the single-sample Wilcoxon test also showed no significant differences (p > 0.05) in the median values. The differences between the two scanning instruments for cephalometric points ranged from 0.5 mm to −0.5 mm, except for the subnasal point (0.73 mm). Over 70% of the surface areas analyzed showed overlapping within the highly reproducible range (0.5 mm to −0.5 mm). Conclusion: Both scanning systems investigated in this study proved to be accurate and reliable for capturing 3D images of the patient’s face.
Combining Multi-Scale Fusion and Attentional Mechanisms for Assessing Writing Accuracy
Authors: Liu Renyuan , Shi Yunyu , Tang Xian , Liu Xiang
Published: January 2025

Traditional methods of assessing handwritten characters are often too subjective, inefficient, and lagging in feedback, which makes it difficult for educators to achieve fully objective writing assessments and for writers to receive timely suggestions for improvement. In this paper, we propose a convolutional neural network (CNN) architecture that combines the attention mechanism with multi-scale feature fusion; specifically, the features are weighted by designing a bottleneck layer that combines the Squeeze-and-Excitation (SE) attention mechanism to highlight the important information and by applying a multi-scale feature fusion method to enable the network to capture both the global structure and the local details of Chinese characters. Finally, a high-quality dataset containing 26,800 images of handwritten Chinese characters is constructed based on the application scenario of the writing grade test, covering the common Chinese characters in the writing grade exam; The experimental results show that the proposed method achieves 98.6% accuracy on the writing grade exam dataset and 97.05% on the ICDAR-2013 public dataset, significantly improving recognition accuracy. The constructed dataset and improved model are suitable for application scenarios such as writing grade exams, which helps to improve marking efficiency and accuracy.
RTACompensator: Leveraging AraBERT and XGBoost for Automated Road Accident Compensation
Authors: El Moussaoui Taoufiq , Karim Awatif , Loqman Chakir , Boumhidi Jaouad
Published: January 2025

Road traffic accidents (RTAs) are a significant public health and safety concern, resulting in numerous injuries and fatalities. The growing number of cases referred to traffic accident rooms in courts has underscored the necessity for an automated solution to determine victim indemnifications, particularly given the limited number of specialized judges and the complexity of cases involving multiple victims. This paper introduces RTACompensator, an artificial intelligence (AI)-driven decision support system designed to automate indemnification calculations for road accident victims. The system comprises two main components: a calculation module that determines initial compensation based on factors such as age, salary, and medical assessments, and a machine learning (ML) model that assigns liability based on police accident reports. The model uses Arabic bidirectional encoder representations from transformer (AraBERT) embeddings to generate contextual vectors from the report, which are then processed by extreme gradient boosting (XGBoost) to determine responsibility. The model was trained on a purpose-built Arabic corpus derived from real-world legal judgments. To expand the dataset, two data augmentation techniques were employed: multilingual bidirectional encoder representations from transformers (BERT) and Gemini, developed by Google DeepMind. Experimental results demonstrate the model’s effectiveness, achieving accuracy scores of 97% for the BERT-augmented corpus and 97.3% for the Gemini-augmented corpus. These results underscore the system’s potential to improve decision-making in road accident indemnifications. Additionally, the constructed corpus provides a valuable resource for further research in this domain, laying the groundwork for future advancements in automating and refining the indemnification process.
Assessment of Natural Radioactivity and Trace Element Composition of Coals and Ash and Slag Waste in Kazakhstan
Authors: Pak Yuriy , Pak Dmitriy , Ibragimova Diana , Matonin Vladimir , Tebayeva Anar
Published: January 2025

This article systematizes research data on the natural radioactivity of fossil coals and of ash and slag waste from coal power engineering in the context of radioecological safety. The relatively low energy efficiency of the operating thermal power plants in Kazakhstan has a significant impact on the environment. In addition to natural radioactive elements (U238 and its decay products, Th232 and its decay products, and K40), coal combustion waste also contains a significant amount of trace elements that have a negative impact on the atmosphere and the environment. In Kazakhstan, about 67% of electricity is generated by coal power engineering. However, in the process of burning coals, radioactive nuclides are concentrated in ash and slag waste. In the fuel power industry of Kazakhstan, high-ash coals with low concentrations of radionuclides are mainly used. The average contents of uranium and thorium are close to the clarke values. The natural radioactivity of coal and of ash and slag waste from Karaganda GRES-1, which consumes Ekibastuz coals with an ash content of 32–39%, was studied. The average values of the specific activities of U238, Th232, and K40 in 25 coal samples were 27.9 Bq/kg, 19.5 Bq/kg, and 81.0 Bq/kg, respectively. In ash and slag waste, the concentrations of these radionuclides were several times higher. The concentration coefficients of the studied radionuclides varied within the ranges of 4.7–5.5 for U, 3.8–5.7 for Th, and 4.2–8.6 for K40. It was established that during coal combustion in thermal power plants, due to carbon combustion and the removal of volatile compounds, not only natural radionuclides but also many microelements, including toxic ones (Mn, Cd, Ni, Co, Zn, etc.), are concentrated in the ash.
New Fixed-Point Results in Controlled Metric Type Spaces with Applications
Authors: Souayah Nizar , Hidri Lotfi
Published: January 2025

In this manuscript, we present several novel results in fixed-point theory for a complete controlled metric space. The first presented result is inspired from the Caristi contraction where we explore the existence and uniqueness of fixed points under specific conditions. Furthermore, we propose a graphical form of it by endowing the considered space with a graph and develop a new fixed-point theorem, which is illustrated by two examples. Also, we establish a theorem for the α-admissible mapping. To demonstrate its effectiveness, the last theorem proposes an approach to solve a second-order differential equation.
A Future Picture: A Review of Current Generative Adversarial Neural Networks in Vitreoretinal Pathologies and Their Future Potentials
Authors: Remtulla Raheem , Samet Adam , Kulbay Merve , Akdag Arjin , Hocini Adam , Volniansky Anton , Kahn Ali Shigufa , Qian Cynthia X.
Published: January 2025

Machine learning has transformed ophthalmology, particularly in predictive and discriminatory models for vitreoretinal pathologies. However, generative modeling, especially generative adversarial networks (GANs), remains underexplored. GANs consist of two neural networks—the generator and discriminator—that work in opposition to synthesize highly realistic images. These synthetic images can enhance diagnostic accuracy, expand the capabilities of imaging technologies, and predict treatment responses. GANs have already been applied to fundus imaging, optical coherence tomography (OCT), and fluorescein autofluorescence (FA). Despite their potential, GANs face challenges in reliability and accuracy. This review explores GAN architecture, their advantages over other deep learning models, and their clinical applications in retinal disease diagnosis and treatment monitoring. Furthermore, we discuss the limitations of current GAN models and propose novel applications combining GANs with OCT, OCT-angiography, fluorescein angiography, fundus imaging, electroretinograms, visual fields, and indocyanine green angiography.
Well-Preserved Urinary Bladder Anatomy in Rats After Minimally Invasive Surgery
Authors: Giaquinto Daniela , Palladino Antonio , Cummaro Annunziata , De Felice Elena , Esposito Vincenzo , Moretta Rosalba , Castaldo Sigismondo , Di Maro Eva , de Girolamo Paolo , D’Angelo Livia , Attanasio Chiara
Published: January 2025

Background: The setup of experimental protocols able to preserve the anatomical integrity also in terms of organ microarchitecture is mandatory to ensure result translatability. Also, the maintenance of structural integrity perfectly aligns with the refinement implementation aiming to reduce procedure severity, a key issue in animal studies deemed compulsory from both ethical and legal standpoints. Here we report a detailed description of all peri-operative and post-operative care and clinical evaluation in a surgical rat model to test the efficacy of a catheter functionalized by a peptide coating with antimicrobial and antibiofilm properties, whose efficacy was previously tested in vitro. Methods: We used male and female adult Fischer 344 rats (tot n = 44, n = 22 each sex), which were divided into four experimental groups. Each animal underwent refined surgery for the implantation of a functionalized or standard catheter, depending on the group, and was observed for 7 and 14 days. The surgical refinement strategy was based on the placement of the catheter into the bladder lumen rather than in the urethra. Still in the refinement perspective, ultrasound examination of the bladder was conducted to confirm the in situ position of the medical device at an intermediate time point, 4 or 10 days post-surgery depending on the group, while, at the same time, but also at days 0, 7, or 14 post-surgery, an ultrasound-guided cystocentesis was performed to collect sterile urine. The imaging approach was used in place of metabolic cages to minimize distress to the animals and to ensure reliable and unbiased scientific outcomes. Hematological and biochemical parameters were monitored along the preclinical trial; namely, blood sampling was performed at the beginning (day 0) and at the end of the trial (day 7 or 14 post-surgery depending on the group). Results: Clinical scores and biochemical analyses of all animals did not reveal signs of distress or disease. At the endpoints, histological analyses of urinary bladder displayed a well-preserved anatomical structure of the organ without significant signs of inflammatory infiltration into the urothelium. Conclusions: Our model represents a refined strategy to achieve the scientific goals required by the preclinical setting related to catheter-associated urinary tract infections. In particular, it ensures the preservation of bladder morphology and urothelium microarchitecture, maintaining an adequate level of animal health and welfare while monitoring the onset of urinary tract infections through the sterile collection of urine in long-lasting experiments.
Neuroanatomical Insights: Convergence and Divergence of Tinnitus with Normal or Mild Hearing Loss
Authors: Shen Xingqian , Li Jing , Pan Hui , Wang Linlin , Leng Yangming , Xiao Hongjun , Liu Bo , Fan Wenliang
Published: January 2025

Objectives: To explore the neuroanatomical abnormalities in idiopathic tinnitus patients by voxel-based morphometry (VBM) and surface-based morphometry (SBM) techniques. To elucidate the central plasticity in tinnitus patients with normal or mild hearing loss from the neuroanatomical insights. Methods: A total of 74 patients with idiopathic tinnitus (43 with normal hearing and 31 with mild hearing loss) and 98 healthy subjects were enrolled. VBM and SBM were employed to analyze neuroimaging data and identify neuroanatomical differences. Results: Our analysis revealed a reduction in gray matter volume and a distinctive pattern of changes in cortical surface features in patients with idiopathic tinnitus, especially in brain regions closely related to the limbic system, such as the bilateral parahippocampal gyrus, bilateral entorhinal cortex, and insula. Tinnitus patients with mild hearing loss have more extensive gray matter volume reduction, and more complex changes in cortical surface features compared to tinnitus patients with normal hearing. In addition, we also found a significant correlation between the Self-Rating Anxiety Scale (SAS), the Self-Rating Depression Scale (SDS), and Montreal Cognitive Assessment (MoCA) scores of patients with idiopathic tinnitus and cortical characteristic parameters in the above brain regions. Conclusions: There are extensive neuroanatomical alterations in tinnitus patients. Mild hearing loss may aggravate the reduction of gray matter volume and change the surface characteristics of the cortex. Anxiety, depression, and cognitive impairment in patients with idiopathic tinnitus may be related to neuroanatomical alterations in specific brain regions.
Mindfulness, Loving-Kindness, and Compassion-Based Meditation Interventions and Adult Attachment Orientations: A Systematic Map
Authors: Gazder Taranah , Drummond Erica Ruby , Gelegen Mine , Stanton Sarah C. E.
Published: January 2025

Meditation interventions have important benefits, including potentially helping those with higher attachment anxiety and avoidance enjoy better personal and relational growth. This preregistered and reproducible systematic map sought to identify the extent and scope of experimental evidence investigating the role of mindfulness, loving-kindness, and compassion-based multi-session meditation interventions in (a) moderating the effects of attachment orientations on outcomes over time and/or (b) changing attachment orientations over time. We conducted a systematic map, as the literature on meditation interventions and attachment is nascent. We searched 5 databases, screening 725 studies. We extracted data from four journal articles and one dissertation (five studies in total) which met our inclusion criteria. Four studies examined the effects of meditation interventions on buffering attachment insecurity and one examined attachment security enhancement. All five studies included a mindfulness meditation intervention, and one included a loving-kindness meditation intervention. All studies were conducted in Western cultures. Studies primarily found evidence for interventions benefitting those with higher attachment anxiety, although some evidence emerged for higher attachment avoidance. Our systematic map highlights a critical need for further application of meditation interventions in an attachment and personal growth context, given the promising nature of early work in this area.
Analysis of the Influence of Excavated Soil Sand Characteristics on the Rheological and Mechanical Properties of Hydraulic Mortars
Authors: Saad Lara , Nouri Mustapha , Tahlaiti Mahfoud , Khelidj Abdelhafid , Fruchet Julien , Suraneni Prannoy
Published: January 2025

This work investigates the effects of substituting natural sand with excavated soil sand in the formulation of hydraulic mortar developed from a self-compacting concrete (SCC). Four excavated soil sand deposits were studied to assess their physicochemical properties. Subsequently, a reference mortar (RM) was designed using the concrete equivalent mortar method. Furthermore, the effect of incorporating 30% of excavation soil sand under different moisture conditions (natural storage conditions, dry and saturated surface dry state) on the properties of mortar is studied. Spreading tests were carried out to observe how the rheological properties evolve over time. The study includes compressive and flexural strength tests at 2, 7, 14 and 28 days. The results showed that some sands had densities similar to those of natural alluvial sand, while others had lower densities. Water absorption values varied considerably from one sand to another, with some showing values ranging from 1% to 6%, while other sands had values of up to 10%. The results of spreading tests indicate that mortar made with sand in a saturated dry-surface state is more fluid than mortar made with sand in a dry state. Under all conditions, all mortars lose their fluidity over time. The variation in compressive strength among all excavated soil sand mortars compared to the reference mortar remained below 10% at 2 and 28 days, except for one sand with a high clay content. The incorporation of excavated soil sand at this percentage as a substitute for river sand led to an enhancement in the flexural strength of the mortar, with improvements of 40% and 50% observed for certain types of excavated sand. The statistical study revealed a strong relationship between the properties of the sand (in particular, the fines content and their nature, as well as the sand skeleton) and its saturation state, the flowability and the compressive strength of the mortar.
Green Infrastructure as an Urban Landscape Strategy for the Revaluation of the Ite Wetlands in Tacna
Authors: Raymundo Vanessa , Vargas Carlos , Alcalá Claudia , Marin Silvana , Jaulis Clarisse , Esenarro Doris , Huerta Elias , Fernandez Diego , Martinez Pedro
Published: January 2025

This study is focused on proposing a green infrastructure design that revalues the Ite Wetlands in Tacna. Currently, the Ite Wetlands are experiencing significant degradation mainly due to water pollution in the wetland and other associated environmental and social impacts. This situation is exacerbated by nearby mining activity, which includes the discharge of mining tailings that negatively affect water quality and the surrounding natural environment. An exhaustive diagnosis was conducted, considering multiple urban and environmental aspects, such as topography, road networks, climatic conditions, and biological diversity. The green infrastructure and revaluation project for the Ite Wetlands in Tacna has generated significant results, highlighted by the careful design of green corridors. The implementation of interpretive trails, rest areas, birdwatching viewpoints, and botanical gardens has transformed the wetlands into a multifunctional environment that promotes environmental conservation and biodiversity. This initiative has not only revitalized the area but strengthened the cultural and social identity of the region. The proposal provides a sustainable development model that can serve as inspiration for other natural areas facing degradation.
Multi-Objective Optimization Design of PCS Box Girder Bridges with Small and Medium Spans Using Genetic Algorithms
Authors: Li Zhijie , Qi Jianan , Wang Jingquan
Published: January 2025

With the development of algorithms for autonomous decision-making in the field of structural engineering, the design of precast concrete segment (PCS) box girder bridges faces new challenges. This paper proposes using a multi-objective optimization method based on genetic algorithms for the rapid design of PCS box girder bridges with small and medium spans. By considering 20 design parameters such as the physical dimensions of the box girder cross-section, material properties, and prestressing parameters, the paper formulates and quantifies three objective functions: cost, safety, and structural performance. The multi-objective optimization was conducted using four optimization algorithms (NSGA-II, NSGA-III, GDE3, and PSO). An optimization evaluation index (φ[F(x)]) was established and weights were assigned to different optimization objectives. A specific design case based on the general diagram of a 3 × 25 m-long continuous PCS box girder bridge was carried out. The results indicate that genetic algorithms performed exceptionally well on this problem, with the NSGA-III algorithm achieving the best φ[F(x)] value of 0.2789 among all algorithms. A performance analysis was conducted on various optimization models using box plots and sensitivity studies. Scatter plots and surface plots of the Pareto front of the optimized solutions were generated, and corresponding cross-sectional design drawings were created based on the two proposed solutions. Compared with the general graph, the design cases provided by the NSGA-III algorithm model have a change rate of 8.03%, −0.29%, and 75.49% in the three optimization objectives, respectively, indicating a significant improvement effect. The research content of this paper provides a reasonable direction for future studies on intelligent bridge design methodologies.
Physical Test and Numerical Analysis of Damage Mechanism of Rocky Foundation with Parallel Structural Surfaces
Authors: Zhang Ziguang , Li Wanyu , Hu Ankang , Wu Liang
Published: January 2025

The growth of rock structural surfaces makes the deformation and stability analysis of rock pits more complex and challenging than that of soil pits. To investigate the damage mechanism of this foundation and provide ideas for foundation support, the paper constructed a simplified model by approximate plane analysis and dimensionless analysis of the similarity principle. The physical model was constructed from a mixture of materials, and then foundation excavation and loading tests were completed. The strain value of the strain gauges increased in stages in the range of 0–250. Excavation of the structural surface resulted in an increased number of deformation mutations. This type of rocky foundation damage underwent three stages: overburden crack development, cumulative deformation of the S-S, and collapse of the sliding body. Furthermore, numerical simulations corresponding to the physical model tests were set and used to validate and complement the physical tests. When the line loads reached 70.83 kN/m and 127.5 kN/m, the plastic zone of the structural surface was completely penetrated and the sliding body collapsed. The results of the studies can serve as a useful reference and guide for the excavation and support design of real-world rock foundation projects that are similar.
E. coli Biomolecules Increase Glycolysis and Invasive Potential in Lung Adenocarcinoma
Authors: Vega Alexis A. , Shah Parag P. , Rouchka Eric C. , Clem Brian F. , Dean Calista R. , Woodrum Natassja , Tanwani Preeti , Siskind Leah J. , Beverly Levi J.
Published: January 2025

Introduction: Recent studies have discovered that lung cancer subtypes possess distinct microbiome profiles within their tumor microenvironment. Additionally, the tumor-associated microbiome exhibits altered bacterial pathways, suggesting that certain bacterial families are more capable of facilitating tumor progression than others. We hypothesize that there exists a crosstalk between lung adenocarcinoma (LUAD) cells and bacterial cells. Methods and Materials: RNA sequencing (RNA-seq) was performed on LUAD cell lines to explore the paracrine signaling effects of bacterial biomolecules. Based on our RNA-seq data, we investigated glycolysis by measuring glucose uptake and lactate production, invasive potential through invasion assays, and epithelial-to-mesenchymal transition (EMT) markers. Since lipopolysaccharides (LPS), abundant on the cell walls of Gram-negative bacteria, can activate toll-like receptor 4 (TLR4), we inhibited TLR4 with C34 to assess its relationship with the observed phenotypic changes. To identify the bacterial biomolecules responsible for these changes, we treated the media with RNAse enzyme, charcoal or dialyzed away molecules larger than 3 kDa. Results and Discussion: RNA-seq revealed 948 genes upregulated in the presence of E. coli biomolecules. Among these, we observed increased expression of Hexokinase II (HKII), JUN proto-oncogene, and Snail Family Transcriptional Repressor 1. We verified the elevation of glycolytic enzymes through Western blot and saw elevation of 2-deoxyglucose uptake and lactate production in LUAD cell lines incubated in E. coli biomolecules. In addition to E. coli elevating glycolysis in LUAD cell lines, E. coli exposure enhanced invasive potential as demonstrated by Boyden chamber assays. Notably, inhibition of TLR4 did not reduce the impact of E. coli biomolecules on glycolysis or the invasive potential of LUAD. Modulating the E. coli-supplemented media with RNAse enzyme or dextran-coated charcoal or using a spin column to remove biomolecules smaller than 3 kDa resulted in changes in HKII and Claudin protein expression. These findings suggest a direct relationship between E. coli and LUAD, wherein several cancer hallmarks are upregulated. Future studies should further investigate these bacterial biomolecules and their role in the tumor microenvironment to fully understand the impact of microbial shifts on cancer progression.
Anti-PTK7 Monoclonal Antibodies Suppresses Oncogenic Phenotypes in Cellular and Xenograft Models of Triple-Negative Breast Cancer
Authors: Kim Min Ho , Park Mi Kyung , Park Han Na , Ham Seung Min , Lee Ho , Lee Seung-Taek
Published: January 2025

Protein tyrosine kinase 7 (PTK7), a catalytically defective receptor protein tyrosine kinase, is frequently upregulated in various cancers, including triple-negative breast cancer (TNBC), and is associated with poor clinical outcomes. Analysis of The Cancer Genome Atlas (TCGA) data confirmed that PTK7 mRNA expression is significantly higher in TNBC tumor tissues compared with adjacent normal tissues and non-TNBC breast cancer subtypes. Kaplan–Meier survival analysis demonstrated a strong correlation between high PTK7 expression and worse relapse-free survival in TNBC patients (HR = 1.46, p = 0.015). In vitro, anti-PTK7 monoclonal antibodies (mAbs) significantly reduced proliferation, wound healing, migration, and invasion in TNBC MDA-MB-231 cells. Ki-67 immunofluorescence assays revealed substantial decreases in cell proliferation following treatment with PTK7 mAbs (32-m, 43-m, 50-m, and 52-m). Moreover, actin polymerization, a critical process in cell migration and invasion, was markedly impaired upon PTK7 mAb treatment. In vivo, PTK7 mAbs significantly reduced tumor volume and weight in a TNBC xenograft mouse model compared with controls. Treated tumors exhibited decreased expression of Ki-67 and vimentin, indicating reduced proliferation and epithelial-to-mesenchymal transition. These findings highlight PTK7 as a promising therapeutic target in TNBC and demonstrate the potent anti-cancer effects of PTK7-neutralizing mAbs both in vitro and in vivo. Further exploration of PTK7-targeted therapies, including humanized mAbs and antibody-drug conjugates, is warranted to advance treatment strategies for PTK7-positive TNBC.
Developmental Patterns in Autism and Other Neurodevelopmental Disorders in Preschool Children
Authors: Martelli Maria Eugenia , Gigliotti Federica , Giovannone Federica , Lentini Giuliana , Manti Filippo , Sogos Carla
Published: January 2025

Background: Neurodevelopmental disorders (NDDs) encompass an inclusive group of conditions that appear during the developmental period but continue to persist in adulthood, ranging from particular difficulties to a global impairment of social, cognitive, and emotional functioning. The developmental trajectories associated with these conditions are highly heterogeneous. This study aimed to analyze and compare developmental and adaptive profiles of preschool-aged children with different NDDs to better characterize their developmental trajectories. Methods: We analyzed data from the initial global evaluation of 196 children with NDDs (aged 20 to 71 months), enrolled in three subgroups: 108 with autism spectrum disorder (ASD), 52 with language disorder (LD), and 36 with mixed specific developmental disorder (MSDD). A comprehensive neuropsychiatric evaluation was performed using standardized tools (Griffiths-III, ADOS-2, VABS-II, and ADI-R), and the parents completed the DP-3 and the CBCL 1½-5. Results: Our results showed that all NDDs exhibited poor psychomotor skills, with children with ASD being the most impaired, although their profiles were comparable to those of MSDD in communication and motor areas. CBCL’s pervasive developmental problem scale has been shown to provide relevant information for distinguishing children with ASD. Furthermore, DP-3 and VABS-II measure highly differentiated developmental profiles of each diagnostic group. Conclusions: Our results highlighted the importance of including parents’/caregivers’ perspectives in defining children’s functioning and the possibility of using DP-3 as a screening tool for different neurodevelopmental disorders.
The Role of Artificial Intelligence in Urogynecology: Current Applications and Future Prospects
Authors: Oliveira Maria Beatriz Macedo de , Mendes Francisco , Martins Miguel , Cardoso Pedro , Fonseca João , Mascarenhas Teresa , Saraiva Miguel Mascarenhas
Published: January 2025

Artificial intelligence (AI) is the new medical hot topic, being applied mainly in specialties with a strong imaging component. In the domain of gynecology, AI has been tested and shown vast potential in several areas with promising results, with an emphasis on oncology. However, fewer studies have been made focusing on urogynecology, a branch of gynecology known for using multiple imaging exams (IEs) and tests in the management of women’s pelvic floor health. This review aims to illustrate the current state of AI in urogynecology, namely with the use of machine learning (ML) and deep learning (DL) in diagnostics and as imaging tools, discuss possible future prospects for AI in this field, and go over its limitations that challenge its safe implementation.
Promising Strategies for the Management of Burn-Wound-Associated Pruritus
Authors: Tenenhaus Mayer , Rennekampff Hans-Oliver
Published: January 2025

Patients who have been injured by burns often suffer from persistent and debilitating post burn pruritus. Despite a myriad of therapeutic interventions and medications, this complex condition remains particularly difficult to ameliorate. Recently, a new generation of antipruritic medications has demonstrated clinical success in managing pruritus in a number of dermatologic, nephritic and hepatic disease states, targeting unique aspects of the pruritic pathways. While specific trials demonstrating efficacy and safety are currently lacking, the purported mechanisms of action and similarities to the targeted inflammatory markers, pruritogens and neural pathways of these new medications, in concert with clinical evidence, hold promise for burn patients.