bluuebunny/crossref_metadata_2025 huggingface dataset:
EXACT-Net: Framework for EHR-Guided Lung Tumor Auto-Segmentation for Non-Small Cell Lung Cancer Radiotherapy
Authors: Hooshangnejad Hamed , Huang Gaofeng , Kelly Katelyn , Feng Xue , Luo Yi , Zhang Rui , Xu Ziyue , Chen Quan , Ding Kai
Published: December 2024

Background/Objectives: Lung cancer is a devastating disease with the highest mortality rate among cancer types. Over 60% of non-small cell lung cancer (NSCLC) patients, accounting for 87% of lung cancer diagnoses, require radiation therapy. Rapid treatment initiation significantly increases the patient’s survival rate and reduces the mortality rate. Accurate tumor segmentation is a critical step in diagnosing and treating NSCLC. Manual segmentation is time- and labor-consuming and causes delays in treatment initiation. Although many lung nodule detection methods, including deep learning-based models, have been proposed. Most of these methods still have a long-standing problem of high false positives (FPs). Methods: Here, we developed an electronic health record (EHR)-guided lung tumor auto-segmentation called EXACT-Net (EHR-enhanced eXACtitude in Tumor segmentation), where the extracted information from EHRs using a pre-trained large language model (LLM) was used to remove the FPs and keep the TP nodules only. Results: The auto-segmentation model was trained on NSCLC patients’ computed tomography (CT), and the pre-trained LLM was used with the zero-shot learning approach. Our approach resulted in a 250% boost in successful nodule detection using the data from ten NSCLC patients treated in our institution. Conclusions: We demonstrated that combining vision-language information in EXACT-Net multi-modal AI framework greatly enhances the performance of vision only models, paving the road to multimodal AI framework for medical image processing.
Estimating the Benefits of Oral Cancer Screening: Challenges and Opportunities
Authors: Farina Francesca , Cirillo Nicola
Published: December 2024

Screening is widely believed to facilitate early detection and improve health outcomes; however, recent evidence questions its overall benefits, highlighting the need for a critical assessment of cancer screening programs. The simplicity of clinical oral examination and the easy accessibility of the oral cavity make oral cancer a suitable candidate for opportunistic screening. Despite this uniqueness, studies that solidly assess the efficacy and cost-effectiveness of oral cancer screening are scanty, and the only large randomized trial undertaken so far shows limited evidence of mortality reduction through population screening. Research indicates that while early detection rates following screening may increase, they do not necessarily translate into decreased oral cancer deaths. This article emphasizes the need for a nuanced understanding of the benefits of screening, awareness of deceptive metrics and inherent biases in the context of early detection, and the importance of improving dentist education and introducing new technologies to enhance clinical decision-making. The review calls for a balanced and evidence-based approach to oral cancer screening, integrating it with broader oral health initiatives to maximize public health outcomes.
Classification and Prognostic Stratification Based on Genomic Features in Myelodysplastic and Myeloproliferative Neoplasm- and Their Overlapping Conditions
Authors: Lee Jong-Mi , Lee Ginkyeng , Kim Taeksang , Ahn Ari , Jung Jin , Kim Yoo-Jin , Park Silvia , Kwag Daehun , Lee Sung-Eun , Park Sung-Soo , Kim Tong-Yoon , Cho Bin , Chung Nack-Gyun , Lee Jae Wook , Yoo Jae Won , Jo Suejung , Kim Yonggoo , Kim Myungshin
Published: December 2024

Background/Objectives: Myeloid neoplasms encompass a diverse group of disorders. In this study, we aimed to analyze the clinical and genomic data of patients with myeloproliferative neoplasm (MPN), myelodysplastic neoplasm (MDS), and their overlapping conditions, such as MDS/MPN and aplastic anemia (AA), to help redefine the disease classification. Methods: Clinico-genomic data of 1585 patients diagnosed with MPN (n = 715), MDS (n = 698), MDS/MPN (n = 78), and AA (n = 94) were collected. Patterns of 53 recurrent genomic abnormalities were compartmentalized into 10 groups using a Dirichlet process (DP). Results: These genomic groups were correlated with specific genomic features, survival outcomes, and disease subtypes. Groups DP1 and DP5, characterized by JAK2 and CALR mutations, respectively, showed very favorable prognoses among the patients with MPN. Groups DP2, DP7, and DP9 demonstrated very adverse prognoses across the disease subtypes. DP2 included patients with MDS harboring TP53 mutations and complex karyotypes; DP9 comprised patients with acute myeloid leukemia-related mutations, including NPM1; and DP7 included patients with SETBP1 mutations. Groups DP10 and DP8, linked to SF3B1 and DDX41 mutations or chromosome 1q derivatives, presented a favorable risk profile. Improved survival was observed with transplantation in groups DP2, DP7, and DP9. Conclusions: These findings highlight the role of genomic classifications in guiding personalized treatment strategies, ultimately enhancing the understanding and management of myeloid neoplasms.
Exosome-Derived microRNAs in Hypertrophic Cardiomyopathy
Authors: Wang Brian Xiangzhi
Published: December 2024

Hypertrophic cardiomyopathy (HCM), characterized by myocardial hypertrophy and an increased risk of sudden cardiac death, poses a significant health burden worldwide. Recent studies have revealed the involvement of exosome-derived microRNAs (miRNAs) in the pathogenesis of HCM, shedding light on novel regulatory mechanisms in cardiac remodeling and dysfunction. This literature review synthesizes current evidence on the role of exosome-derived miRNAs in HCM. It discusses key miRNAs identified from diverse cellular origins, including cardiomyocytes, stem cells, and conduction cells, elucidating their contributions to hypertrophic signaling pathways, fibrosis, and changes in cellular metabolism. Notable miRNAs highly expressed in exosomes such as miR-1, miR-133, and miR-208 are highlighted for their implications in HCM pathophysiology. Moreover, this review explores the diagnostic and therapeutic potential of exosome-derived miRNAs as biomarkers and therapeutic targets in HCM management. The studies summarized in this review demonstrate that exosome-derived miRNAs play a crucial role in orchestrating the molecular events underlying HCM, offering new insights into disease mechanisms and potential therapeutic avenues. Understanding the intricate interplay between exosome-mediated miRNA communication and HCM pathophysiology holds promise for the development of personalized diagnostic tools and targeted therapies to improve patient outcomes in HCM.
Synthesis of Bimetallic Pd/Pt Truncated Nanocubes and Their Catalytic Performance in Selective Hydrogenation of Acetophenone
Authors: Bai Jingjing , Yang Xinkai , Chen Jianyu , Yue Bin , Chen Xueying , He Heyong
Published: December 2024

A series of bimetallic Pd/Pt truncated nanocube catalysts with similar morphologies and particle sizes but different platinum contents were successfully synthesized using a colloidal method without using any capping agents. Their hydrogenation properties were systematically studied and compared with their monometallic Pd or Pt nanocrystal counterparts. The results of EDX-mapping and line scanning show that platinum was relatively uniformly distributed on the surface of the Pd/Pt bimetallic nanocrystals and was not selectively deposited at the corners of the nanocrystals. The results of the selective hydrogenation of acetophenone demonstrate that the hydrogenation rate and the carbonyl selectivity of bimetallic Pd/Pt truncated nanocube catalysts are generally much higher than those of their monometallic Pd or Pt nanocrystal counterparts. It was found that the electronic interaction between palladium and platinum in the bimetallic Pd/Pt truncated nanocube catalysts and the corresponding hydrogenation activity in the selective hydrogenation of acetophenone are closely related to the molar ratio between platinum and palladium and the thickness of the platinum layer in the bimetallic Pd/Pt truncated nanocube catalyst. With an increase in the Pt/Pd molar ratio in the bimetallic Pd/Pt truncated nanocube catalysts, the activity and carbonyl selectivity in the acetophenone hydrogenation reaction increase first, reach a maximum when the molar ratio of Pt/Pd is 0.02 and the theoretical thickness of Pt is 1.3 atomic layers, and then decrease with a further increase in the Pt/Pd ratio. The hydrogenation rate of acetophenone on the Pd/Pt0.02 catalyst reaches 1.07 × 103 mmol·h−1·gcat.−1, which is 79 and 75 times larger than that of the monometallic Pd and Pt nanocrystal catalysts, respectively. The maximum yield of the target product 1-phenylethanol on the Pd/Pt0.02 truncated nanocube catalyst reaches 97.2%, which is 6.6% and 16.7% higher than that of the monometallic Pd and Pt nanocrystal catalysts, respectively.
Genome Instability and Senescence Are Markers of Cornelia de Lange Syndrome Cells
Authors: Di Nardo Maddalena , Krantz Ian D. , Musio Antonio
Published: December 2024

Cornelia de Lange syndrome (CdLS) is a rare, dominantly inherited multisystem developmental disorder. Pathogenic variants in genes encoding the structural subunits and regulatory proteins of the cohesin complex (NIPBL, SMC1A, SMC3, HDAC8, and RAD21) are the primary contributors to the pathogenesis of CdLS. Pathogenic variations in these genes disrupt normal cohesin function, leading to the syndrome’s diverse and complex clinical presentation. In this study, we discovered that cells harboring variants in the NIPBL, SMC1A and HDAC8 genes exhibit spontaneous genome instability, elevated oxidative stress and premature cellular aging. These findings suggest that cohesin plays a critical role in maintaining proper cellular function and highlight its contribution to the pathophysiology seen in the related diagnoses.
Interplay Between Metabolic Pathways and Increased Oxidative Stress in Human Red Blood Cells
Authors: Spinelli Sara , Marino Angela , Morabito Rossana , Remigante Alessia
Published: December 2024

Red blood cells (RBCs) are highly specialized cells with a limited metabolic repertoire. However, it has been demonstrated that metabolic processes are affected by the production of reactive oxygen species (ROS), and critical enzymes allied to metabolic pathways can be impaired by redox reactions. Thus, oxidative stress-induced alternations in the metabolic pathways can contribute to cell dysfunction of human RBCs. Herein, we aim to provide an overview on the metabolic pathways of human RBCs, focusing on their pathophysiological relevance and their regulation in oxidative stress-related conditions.
Polysiloxane-Based Composite Coatings with Bactericidal Additives
Authors: Chihota Rukudzo , Szymanowski Hieronim , Kaczorowski Witold , Grabarczyk Jacek , Jastrzębska Aleksandra , Niedzielski Piotr , Los Katerina , Sobczyk-Guzenda Anna
Published: December 2024

This paper examines the effect of both natural and synthetic additives of different concentrations to a polysiloxane matrix in order to obtain bactericidal composites. Natural additives such as black cumin, cloves, and turmeric were compared with silver, a well-known antiseptic, and with graphene, which has potential bactericidal properties. The first stage of the research included the production of polysiloxane composites with the above-mentioned powders in the form of bulk solid samples, and then a series of tests were carried out on them to not only assess their bactericidal properties but also determine their effect on physicochemical properties such as chemical structure, surface wettability, roughness, hardness, and surface morphology. Based on the obtained results, the most promising composite recipes were selected, and coatings were produced from them on a super-smooth substrate, which had been previously cleaned using a plasma chemical method. The obtained results indicated that all obtained materials were characterized by high bactericidal activity. The conducted studies also showed a significant effect of the introduced additives on the mechanical properties of the polysiloxane matrix, including graphene, which improved the hardness of the composites. Plasma chemical modification of the substrates increased the adhesion of the tested coatings to them. In addition, the effect of the used additive was also visible in this area.
A Coordination Approach to Support Crowdsourced Software-Design Process
Authors: Alhagbani Ohoud , Alyahya Sultan
Published: December 2024

Crowdsourcing software design (CSD) is the completion of specific software-design tasks on behalf of a client by a large, unspecified group of external individuals who have the specialized knowledge required by an open call. Although current CSD platforms have provided features to improve coordination in the CSD process (such as email notifications, chat, and announcements), these features are insufficient to solve the coordination limitations. A lack of appropriate coordination support in CSD activities may cause delays and missed opportunities for participants, and thus the best quality of design contest results may not be guaranteed. This research aims to support the effective management of the CSD process through identifying the key activity dependencies among participants in CSD platforms and designing a set of process models to provide coordination support through managing this activity. In order to do this, a five-stage approach was used: First, the current CSD process was investigated by reviewing 13 CSD platforms. Second, the review resulted in the identification of 17 possible suggestions to improve CSD. These suggestions were evaluated in stage 3 through distributing a survey to 41 participants who had experience in using platforms in the field of CSD. In stage 4, we designed ten process models that could meet the requirements of suggestions, while in stage 5, we evaluated these process models through interviews with domain experts. The result shows that coordination support in the activities of the CSD can make valuable contributions to the development of CSD platforms.
A Comparative Study of Decoders for Liver and Tumor Segmentation Using a Self-ONN-Based Cascaded Framework
Authors: Gul Sidra , Khan Muhammad Salman , Hossain Md Sakib Abrar , Chowdhury Muhammad E. H. , Sumon Md. Shaheenur Islam
Published: December 2024

Background/Objectives: Accurate liver and tumor detection and segmentation are crucial in diagnosis of early-stage liver malignancies. As opposed to manual interpretation, which is a difficult and time-consuming process, accurate tumor detection using a computer-aided diagnosis system can save both time and human efforts. Methods: We propose a cascaded encoder–decoder technique based on self-organized neural networks, which is a recent variant of operational neural networks (ONNs), for accurate segmentation and identification of liver tumors. The first encoder–decoder CNN segments the liver. For generating the liver region of interest, the segmented liver mask is placed over the input computed tomography (CT) image and then fed to the second Self-ONN model for tumor segmentation. For further investigation the other three distinct encoder–decoder architectures U-Net, feature pyramid networks (FPNs), and U-Net++, have also been investigated by altering the backbone at the encoders utilizing ResNet and DenseNet variants for transfer learning. Results: For the liver segmentation task, Self-ONN with a ResNet18 backbone has achieved a dice similarity coefficient score of 98.182% and an intersection over union of 97.436%. Tumor segmentation with Self-ONN with the DenseNet201 encoder resulted in an outstanding DSC of 92.836% and IoU of 91.748%. Conclusions: The suggested method is capable of precisely locating liver tumors of various sizes and shapes, including tiny infection patches that were said to be challenging to find in earlier research.
Machine and Deep Learning Models for Hypoxemia Severity Triage in CBRNE Emergencies
Authors: Nanini Santino , Abid Mariem , Mamouni Yassir , Wiedemann Arnaud , Jouvet Philippe , Bourassa Stephane
Published: December 2024

Background/Objectives: This study develops machine learning (ML) models to predict hypoxemia severity during emergency triage, particularly in Chemical, Biological, Radiological, Nuclear, and Explosive (CBRNE) scenarios, using physiological data from medical-grade sensors. Methods: Tree-based models (TBMs) such as XGBoost, LightGBM, CatBoost, Random Forests (RFs), Voting Classifier ensembles, and sequential models (LSTM, GRU) were trained on the MIMIC-III and IV datasets. A preprocessing pipeline addressed missing data, class imbalances, and synthetic data flagged with masks. Models were evaluated using a 5-min prediction window with minute-level interpolations for timely interventions. Results: TBMs outperformed sequential models in speed, interpretability, and reliability, making them better suited for real-time decision-making. Feature importance analysis identified six key physiological variables from the enhanced NEWS2+ score and emphasized the value of mask and score features for transparency. Voting Classifier ensembles showed slight metric gains but did not outperform individually optimized models, facing a precision-sensitivity tradeoff and slightly lower F1-scores for key severity levels. Conclusions: TBMs were effective for real-time hypoxemia prediction, while sequential models, though better at temporal handling, were computationally costly. This study highlights ML’s potential to improve triage systems and reduce alarm fatigue, with future plans to incorporate multi-hospital datasets for broader applicability.
A Multi-Attribute Decision-Making Approach for Critical Node Identification in Complex Networks
Authors: Zhao Xinyun , Zhang Yongheng , Zhai Qingying , Zhang Jinrui , Qi Lanlan
Published: December 2024

Correctly identifying influential nodes in a complex network and implementing targeted protection measures can significantly enhance the overall security of the network. Currently, indicators such as degree centrality, closeness centrality, betweenness centrality, H-index, and K-shell are commonly used to measure node influence. Although these indicators can identify critical nodes to some extent, they often consider node attributes from a narrow perspective and have certain limitations. Therefore, evaluating the importance of nodes using most existing indicators remains incomplete. In this paper, we propose the multi-attribute CRITIC-TOPSIS network decision indicator, or MCTNDI, which integrates closeness centrality, betweenness centrality, H-index, and network constraint coefficients to identify critical nodes in a network. This indicator combines information from multiple perspectives, including local neighborhood importance, network topological location, path centrality, and node mutual information, thereby solving the issue of the one-sided perspective of single indicators and providing a more comprehensive measure of node importance. Additionally, MCTNDI is validated through the analysis of several real-world networks, including the Contiguous USA network, Dolphins network, USAir97 network, and Tech-routers-rf network. The validation is conducted from four aspects: the results of simulated network attacks, the distribution of node importance, the monotonicity of rankings, and the similarity of indicators, illustrating MCTNDI’s effectiveness in real networks.
Digital Twin-Based Smart Feeding System Design for Machine Tools
Authors: Yuce Baris , Li Haobing , Wang Linlin , Sucala Voicu Ion
Published: December 2024

With the continuous development of intelligent manufacturing technology, the application of intelligent feed systems in modern machine tools is becoming increasingly widespread. Digital twin technology achieves the monitoring and optimization of the entire life cycle of a physical system by constructing a virtual image of the system, while neural network controllers, with their powerful nonlinear fitting ability, can accurately capture and simulate the dynamic behavior of complex systems, providing strong support for the optimization control of intelligent feed systems. This article discusses the design and implementation of an intelligent feed system based on digital twins and neural network controllers. Firstly, this article establishes a mathematical model based on the traditional ball screw structure and analyzes the dynamic characteristics and operating mechanism of the system. Subsequently, the mathematical model is fitted using a neural network controller to improve control accuracy and system response speed. The experimental results demonstrate that the neural network controller shows good consistency in fitting traditional mathematical models, not only effectively capturing the nonlinear characteristics of the system but also maintaining stable control performance under complex operating conditions.
Multichannel Wavelet Kernel Network for High Dimensional Inverse Modeling of Microwave Filters
Authors: Zhang Di , Zhou Min , Wang Zhiyu , Chen Hua
Published: December 2024

This paper proposes a multichannel wavelet kernel network (MWKN) modeling technique with a two-stage training technique for high-dimensional inverse modeling of microwave filters. The real and imaginary parts of the transmission and reflection characteristics are used as the model inputs, while the geometric parameters of the filter are designated as the outputs. Since the electrical signal in microwave inverse modeling encompasses multiple frequency components and complex information arising from the subtle dimensional changes in the metal pattern, the wavelet transform is introduced by leveraging its powerful multi-scale and approximate detail features to form the discrete wavelet convolution layer in the proposed MWKN. To adapt to the learning of approximate detailed features at different scales, the learnable parameters of this layer and the weights of the backbone network are adjusted in stages through a two-stage training strategy based on particle swarm optimization (PSO), which jointly promotes the rapid convergence of the model. Three numerical examples demonstrate the effectiveness and robustness of the proposed MWKN model. Compared with the traditional design method using electromagnetic (EM) simulation, this approach significantly and substantially reduces the repeated calculation time and is capable of predicting the geometry that meets the design specifications within 0.42 s.
A Fault Diagnosis Method for Turnout Switch Machines Based on Sound Signals
Authors: Li Yong , Tao Xinyi , Sun Yongkui
Published: December 2024

The turnout switch machine, a vital outdoor component of railway signaling, controls train steering amidst complex operations and high frequencies. Its malfunction significantly disrupts train operations, potentially causing derailments. This paper proposes a sound-based fault diagnosis method, termed ERS (a method combining EMD, ReliefF, and SVM), for effective monitoring and detection of turnout switch machines. The method employs Eigenmode Decomposition (EMD) to smooth the sound signal, reduce noise, and extract key statistical parameters of both the time and frequency domains. To address redundant information in high-dimensional features, the ReliefF algorithm is utilized for feature selection, dimension reduction, and fault classification based on weighted parameters. Subsequently, the selected feature parameters are used to train the Support Vector Machine (SVM). A comparison with results obtained without ReliefF feature selection demonstrates the necessity of this step. The results show that the fault diagnosis accuracy reaches 98% in the positioning work mode and 95.67% in the reversing work mode, verifying the method’s effectiveness and feasibility.
Optimizing Privacy in Set-Valued Data: Comparing Certainty Penalty and Information Gain
Authors: Kim Soonseok
Published: December 2024

The increase in set-valued data such as transaction records and medical histories has introduced new challenges in data anonymization. Traditional anonymization techniques targeting structured microdata comprising single-attribute- rather than set-valued records are often insufficient to ensure privacy protection in complex datasets, particularly when re-identification attacks leverage partial background knowledge. To address these limitations, this study proposed the Local Generalization and Reallocation (LGR) + algorithm to replace the Normalized Certainty Penalty loss measure (hereafter, NCP) used in traditional LGR algorithms with the Information Gain Heuristic metric (hereafter, IGH). IGH, an entropy-based metric, evaluates information loss based on uncertainty and provides users with the advantage of balancing privacy protection and data utility. For instance, when IGH causes greater information-scale data annotation loss than NCP, it ensures stronger privacy protection for datasets that contain sensitive or high-risk information. Conversely, when IGH induces less information loss, it provides better data utility for less sensitive or low-risk datasets. The experimental results based on using the BMS-WebView-2 and BMS-POS datasets showed that the IGH-based LGR + algorithm caused up to 100 times greater information loss than NCP, indicating significantly improved privacy protection. Although the opposite case also exists, the use of IGH introduces the issue of increased computational complexity. Future research will focus on optimizing efficiency through parallel processing and sampling techniques. Ultimately, LGR+ provides the only viable solution for improving the balance between data utility and privacy protection, particularly in scenarios that prioritize strong privacy or utility guarantees.
A Tight Load Regulation Hysteretic Boost Converter with Compact and Energy-Efficient Anti-Phase Emulated Current Control
Authors: Hu Xiaohui , Qu Wanyuan , Yang Xu , Ding Yong
Published: December 2024

This paper presents a novel, compact, and energy-efficient hysteretic boost converter that employs an anti-phase AC-coupling emulate current control. The proposed scheme utilizes a two-transistor current emulator and a comparator, which allow for fast transient responses and tight closed-loop regulations. This converter was fabricated using a 180 nm CMOS process and was capable of regulating a 5 V output with a 400 mA load capacity from an input voltage range of 2.7 V to 4.5 V. The experimental results demonstrate that the proposed anti-phase AC-coupling emulate current controlling and single hysteretic comparator controlling scheme show lower power/circuit complexity and better static and transient performance. Specifically, under load transitions ranging from 0 mA to 300 mA, the converter exhibits over/undershoot voltages of 38 mV and −42 mV, respectively. Furthermore, the measured load and line regulation performances are 5 mV/A and 2.3 mV/V, respectively. Overall, this study offers a practical and efficient solution for boosting voltage levels while maintaining stable and precise regulation.
Modeling Cork Yield, Thickness, Price, and Gross Income in the Portuguese Cork Oak Montado
Authors: Mata Fernando , Dos-Santos Maria
Published: December 2024

The cork oak (Quercus suber L.) woodlands, known as montados in Portugal, hold significant economic, cultural, social, and environmental value. They are found in the Mediterranean Sea basin, particularly in the Iberian Peninsula, and sustain various activities like silvopastoralism, with cork being a primary product. Despite its economic significance, challenges such as climate change threaten its sustainability. This study aimed to analyze the edaphoclimatic variables affecting cork yield, thickness, price, and gross income in the Alentejo region of Portugal. A total of 35 farmers were selected for the data collection included in this study. Multivariable linear regressions were performed to establish relationships between cork yield, thickness, price, and gross income as dependent variables, various edaphoclimatic factors, and tree densities. A higher tree density correlates with an increased cork yield but a decreased cork thickness. Soil pH affects cork yield and thickness, with a lower pH favoring higher cork yields but thinner cork. A higher clay and silt content in horizon soil C enhances cork thickness and raises the price but reduces the cork yield. Higher accumulated precipitation and temperatures contribute to higher yields and thicknesses of cork. It is concluded that the relationships between the dependent and the independent variables are complex but partially explainable. Understanding these relationships is paramount to ensure sustainable management practices are adopted that are capable of addressing issues raised in the current context of climate change.
Comparative Study of Numerical Simulation on Short-Term Creep Behavior of Steam-Pretreated White Oak (Quercus alba L.) Wood
Authors: Zhang Xingying , Cen Junjie , Zhang Yuge , Han Shenjie , Gu Kongjie , Yu Youming , Hou Junfeng
Published: December 2024

This paper investigates the effects of steam pretreatment temperature (100~120 °C), test temperature (20~80 °C), and earlywood vessel belt on parameters associated with the bending creep properties of white oak (Quercus alba L.) wood. The Burger model, Five-parameter model, and Six-parameter model are used for short-term simulation and comparative analysis of the bending creep curve of steam-pretreated white oak wood, and creep fitting curves and viscoelastic parameters are obtained. The advantages and disadvantages of different viscoelastic mathematical models for fitting the bending creep curve of white oak are analyzed. The results indicate that the Six-parameter model is more consistent with the creep behavior of wood in simulating and predicting the creep behavior of wood than that of the Burger and Five-parameter model and can reflect the short-term deformation characteristics of wood.
Isotone Classes of Social Choice Functions with Binary Range
Authors: Basile Achille , Bhaskara Rao K. P. S. , De Simone Anna , Tarantino Ciro
Published: December 2024

Recently, it has been shown that the characterizations of different classes of non-manipulable social choice functions with binary range can be reduced to a common functional form. In the present paper, we investigate the reasons why this happens. We show that all the classes considered share a common mathematical property. We name this property, which is lattice theoretical in nature, isotonicity.
Revealing the Dynamic History of Parasitic Plant Plastomes via Structural Characterization, Comparative Analysis, and Phylogenomics
Authors: Lubna  , Asaf Sajjad , Jan Rahmatullah , Asif Saleem , Bilal Saqib , Kim Kyung-Min , Lee In-Jung , AL-Harrasi Ahmed
Published: December 2024

Background: The shift to a parasitic lifestyle in plants often leaves distinct marks on their plastid genomes, given the central role plastids play in photosynthesis. Studying these unique adaptations in parasitic plants is essential for understanding the mechanisms and evolutionary patterns driving plastome reduction in angiosperms. By exploring these changes, we can gain deeper insights into how parasitism reshapes the genomic architecture of plants. Method: This study analyzed and compared the plastomes of 113 parasitic plants from different families. Results: The Orobanchaceae family (hemiparasitic plants) displayed the largest plastome size, while Apodanthaceae exhibited the shortest. Additionally, Orobanchaceae showcased little to no gene loss in their plastomes. However, holoparasitic species typically had reduced plastome sizes. Convolvulaceae exhibited significantly reduced plastome sizes due to high gene loss, and Apodanthaceae retained only a few genes. Gene divergence among different families was also investigated, and rps15, rps18, and rpl33 in Orobanchaceae; accD and ycf1 in Convolvulaceae; atpF and ccsA in Loranthaceae; and rpl32 in Santalaceae showed greater divergence. Additionally, Orobanchaceae had the highest numbers of all repeat types, whereas Loranthaceae and Convolvulaceae exhibited the lowest repeat numbers. Similarly, more simple sequence repeats were reported in Loranthaceae and Santalaceae. Our phylogenetic analysis also uncovered a distinct clade comprising Loranthaceae, with a single Schoepfiaceae species clustering nearby. Contrary to expectations, parasitic and hemiparasitic plants formed mixed groupings instead of segregating into separate clades. Conclusions: These findings offer insights into parasitic plants’ evolutionary relationships, revealing shared and divergent genomic features across diverse lineages.
Immune-Related Gene Expression Responses to In Ovo Stimulation and LPS Challenge in Two Distinct Chicken Genotypes
Authors: Slawinska Anna , Dunisławska Aleksandra , Kowalczyk Artur , Łukaszewicz Ewa , Siwek Maria
Published: December 2024

Background: In ovo stimulation introduces bioactive compounds, such as prebiotics, probiotics, or synbiotics into incubating eggs to enhance gut health and immune system development in chickens. This study aimed to determine the genetic and environmental effects modulating responses to in ovo stimulation in commercial broilers and Green-legged Partridge-like (GP) native chickens. Methods: Eggs were stimulated on day 12 of incubation with prebiotics (GOS—galactooligosaccharides), probiotics (Lactococcus lactis subsp. cremoris), or synbiotics (GOS + L. lactis), with controls being mock-injected. Hatched chicks were reared in group pens and challenged with lipopolysaccharide (LPS) on day 42 post-hatching. Cecal tonsils (CT) and spleens were harvested 2 h post-challenge. RT-qPCR was used to analyze the relative gene expression of cytokine genes: IL-1β, IL-2, IL-4, IL-6, IL-10, IL-12p40, and IL-17. Results: The results show that genotype influenced the expression of all immune-related genes, with broiler chickens exhibiting stronger innate inflammatory responses than native chickens. LPS induced both mucosal (CT) and systemic (spleen) immune responses in broilers but only systemic (spleen) responses in native chickens. Conclusions: In ovo stimulation had less of an impact on cytokine gene expression than LPS challenge. Broilers expressed higher inflammatory immune responses than GP native chickens.
Impacts of an Artificial Sandbar on Wave Transformation and Runup over a Nourished Beach
Authors: Kuang Cuiping , Chen Liyuan , Han Xuejian , Wang Dan , Cao Deping , Zou Qingping
Published: December 2024

Due to increasing coastal flooding and erosion in changing climate and rising sea level, there is a growing need for coastal protection and ecological restoration. Artificial sandbars have become popular green coastal infrastructure to protect coasts from these natural hazards. To assess the effect of an artificial sandbar on wave transformation over a beach under normal and storm wave conditions, a high-resolution non-hydrostatic model based on XBeach is established at the laboratory scale. Under normal wave conditions, wave energy is mainly concentrated in short wave frequency bands. The wave setup is negligible on the shoreface but becomes more significant over the beach face, and wave nonlinearity increases with decreasing water depth. The artificial sandbar reduces the wave setup by 22% and causes considerable changes in wave skewness, wave asymmetry, and flow velocity. Under storm wave conditions, as the incident wave height increases, the wave energy in the long wave frequency bands rises, while it decreases in the short wave frequency bands. The wave dissipation coefficient of an artificial sandbar increases first and then decreases with increasing incident wave height, and the opposite is true with the transmission coefficient. It features that the effect of an artificial sandbar on wave energy dissipation strengthens first and then weakens with increasing incident wave height. Additionally, an empirical formula for the wave runup was proposed based on the model results of the wave runup for storm wave conditions. The study reveals the complex processes of wave–structure–coast interactions and provides scientific evidence for the design of an artificial sandbar in beach nourishment projects.
Exploratory Qualitative Study to Investigate Factors Influencing Men’s Utilization of Sexual and Reproductive Health Services in Kwa-Zulu Natal
Authors: Nyalela Mpumelelo , Dlungwane Thembelihle Patricia
Published: December 2024

Sexual and reproductive health (SRH) is essential for men’s health, but a large body of research has indicated that the underutilization of most SRH services by men is a persistent issue that needs to be addressed. Men’s reluctance to access sexual and reproductive health services is one of the factors that leads to high morbidity and mortality rates among men, although their diseases may have been prevented or cured. This study aimed to explore factors that influence the decision of men who resided in men’s hostels and who accessed urology clinics in KwaZulu-Natal to seek help for their sexual and reproductive health issues. An exploratory qualitative approach was adopted using focus group discussions. We interviewed seventy-two men of ages above 15 years. The data were analyzed thematically. The Biomedical Research Ethics Committee (BREC) of UKZN granted ethical clearance (BE 347/19). Of the 72 interviewed men, thirty-three men attended urology clinics in the selected hospitals, and thirty-nine men resided in the hostels around Durban in KZN. Seven themes (lack of awareness of SRH services; participants’ reluctance to access SRH services; influence of culture and religion; lack of financial resources; influence of relationship dynamics; perceived low risk of individual sexual behaviors; and healthcare factors that discourage men from accessing SRH services) emerged from the data that were identified as barriers to SRH service utilization by men, whilst three themes (healthcare enabling factors; access to general information on SRH services; and personal motivational factors) emerged as factors that encouraged the participants to access these services. The participants’ reluctance to access SRH services was attributed to the lack of awareness of available SRH services, the influence of culture and religion, lack of financial resources, relationship dynamics, the perceived low risk of sexual behaviors for individuals, and healthcare workers’ negative attitude towards men requiring SRH services. The availability of healthcare resources, the appointment of more male healthcare workers, and more positive attitudes among healthcare workers will encourage men to utilize SRH services. The exposure of various barriers to SRH service utilization by this investigation warrants urgent attention from the government to impart knowledge about this phenomenon to men.
A 3D Model-Based Framework for Real-Time Emergency Evacuation Using GIS and IoT Devices
Authors: Tyagi Noopur , Singh Jaiteg , Singh Saravjeet , Sehra Sukhjit Singh
Published: December 2024

Advancements in 3D modelling technology have facilitated more immersive and efficient solutions in spatial planning and user-centred design. In healthcare systems, 3D modelling is beneficial in various applications, such as emergency evacuation, pathfinding, and localization. These models support the fast and efficient planning of evacuation routes, ensuring the safety of patients, staff, and visitors, and guiding them in cases of emergency. To improve urban modelling and planning, 3D representation and analysis are used. Considering the advantages of 3D modelling, this study proposes a framework for 3D indoor navigation and employs a multiphase methodology to enhance spatial planning and user experience. Our approach combines state-of-the art GIS technology with a 3D hybrid model. The proposed framework incorporates federated learning (FL) along with edge computing and Internet of Things (IoT) devices to achieve accurate floor-level localization and navigation. In the first phase of the methodology, Quantum Geographic Information System (QGIS) software was used to create a 3D model of the building’s architectural details, which are required for efficient indoor navigation during emergency evacuations in healthcare systems. In the second phase, the 3D model and an FL-based recurrent neural network (RNN) technique were utilized to achieve real-time indoor positioning. This method resulted in highly precise outcomes, attaining an accuracy rate over 99% at distances of no less than 10 metres. Continuous monitoring and effective pathfinding ensure that users can navigate safely and effectively during emergencies. IoT devices were connected with the building’s navigation software in Phase 3. As per the performed analysis, it was observed that the proposed framework provided 98.7% routing accuracy between different locations during emergency situations. By improving safety, building accessibility, and energy efficiency, this research addresses the health and environmental impacts of modern technologies.
Peroxisome Proliferator-Activated Receptor Alpha Stimulation Preserves Renal Tight Junction Components in a Rat Model of Early-Stage Diabetic Nephropathy
Authors: Rosas-Martínez Lorena , Rodríguez-Muñoz Rafael , Namorado-Tonix María del Carmen , Missirlis Fanis , del Valle-Mondragón Leonardo , Sánchez-Mendoza Alicia , Reyes-Sánchez José L. , Cervantes-Pérez Luz Graciela
Published: December 2024

Chronic hyperglycemia results in morphological and functional alterations of the kidney and microvascular damage, leading to diabetic nephropathy (DN). Since DN progresses to irreversible renal damage, it is important to elucidate a pharmacological strategy aimed for treating DN in the early stage. Here, we used the type 2 diabetic rat model to induce DN and show a nephroprotective effect following the stimulation of PPAR-α, which stabilized renal tight junction components claudin-2, claudin-5, and claudin-16. At 14 weeks old, streptozotocin-induced DN, evidenced by elevated creatinine clearance, proteinuria, and electrolyte excretion, was followed by an elevation in oxidative stress and increasing MMP activities affecting the integrity of claudin-2 and claudin-5. Treatment with a PPAR-α agonists decreased glucose levels in diabetic rats. In addition, we found that the expressions of CLDN-5 in glomeruli, CLDN-2 in proximal tubules, and CLDN-16 in the thick ascending limb of the loop of Henle were increased after treatment. As a result, renal function improved, while the oxidative stress and enzymatic activity of MMP-2 and MMP-9 decreased. In conclusion, PPAR-α stimulation prevented the decrease in claudins through a mechanism involving a correction of hyperglycemia, decreasing it in kidney oxidative stress and MMP-2 and MMP-9 activities, showing a promising nephroprotective action in the early stage of DN.
Comprehensive Analysis of the OASTL Gene Family in Potato (Solanum tuberosum L.) and Its Expression Under Abiotic Stress
Authors: Tian Ting , Zhu Jinyong , Li Zhitao , Wang Weilu , Bao Minmin , Qiu Xiaoqiang , Yao Panfeng , Bi Zhenzhen , Sun Chao , Li Yuanming , Liu Zhen , Liu Yuhui
Published: December 2024

O-acetylserine (thiol) lyase is a pivotal enzyme in plant cysteine biosynthesis, which is crucial for promoting plant growth, development, and resisting abiotic stress. However, the related studies on the potato OASTL gene family (StOASTL) have not been reported. In the present study, we identified 11 members of the StOASTL gene family, conducting a thorough analysis encompassing chromosome distribution, protein physicochemical properties, gene structure, protein-conserved motifs, and gene replication events. Phylogenetic scrutiny delineated these 11 StOASTLs into five distinct subfamilies. Using RNA-seq from the Potato Genome Sequencing Consortium (PGSC), we investigated the expression profile of StOASTLs in different tissues of DM (double-monoploid) potato and under abiotic/biotic stress, hormone treatment, and biostimulant treatment. The results showed that one of the StOASTLs (Soltu09G024390) was differentially expressed under different abiotic stresses and hormone treatments. Our findings showcased the differential response of one StOASTL (Soltu09G024390) to a spectrum of abiotic stresses and hormone treatments. Soltu09G024390 was earmarked as a candidate gene and successfully cloned. Functional validation through yeast stress assays demonstrated that the heterologous expression of Soltu09G024390 bolstered yeast tolerance to salt and cadmium stresses. This study provides a theoretical basis for revealing the role of the StOASTL family in potato response to abiotic stress and valuable insights for further study of the biological functions of StOASTL.
Maternal Metal Ion Status Along Pregnancy and Perinatal Outcomes in a Group of Mexican Women
Authors: Vásquez-Procopio Johana , Torres-Torres Johnatan , Rojas-Lima Elodia , Espino-y-Sosa Salvador , Solis-Paredes Juan Mario , Sánchez-Martínez Maribel , Tolentino-Dolores Mari-Cruz , Perichart-Perera Otilia , Missirlis Fanis , Estrada-Gutierrez Guadalupe
Published: December 2024

Pregnancy increases the demand for essential metal ions to support fetal development, making the maternal metal ion status a critical determinant of perinatal outcomes. This prospective cohort study examined changes in metal ion levels across the three trimesters, evaluated the influence of preexisting metabolic conditions on the metal ion status, and assessed the associations between maternal metal ion levels and perinatal outcomes in 206 pregnant women from the Biochemical and Epigenetic Origin of Overweight and Obesity (OBESO) cohort receiving care at the Instituto Nacional de Perinatología in Mexico City from 2017 to 2020. Six essential metal ions (iron, zinc, copper, calcium, magnesium, and phosphorus) were measured in blood samples using inductively coupled plasma optic emission spectrometry. Significant variations in the metal ion levels were observed across the trimesters, with notable decreases in iron and magnesium and increases in copper as pregnancies progressed. Maternal hypothyroidism was associated with significantly low levels of zinc and magnesium during pregnancy. Regression analyses revealed robust associations between maternal metal ion levels and perinatal outcomes. For instance, declining magnesium levels as pregnancies progressed were positively associated with gestational diabetes (OR: 2.92, p = 0.04; OR: 2.72, p = 0.03). The maternal metal ion status significantly influences perinatal outcomes.
Carotenoid Cleavage Dioxygenase Gene CCD4 Enhances Tanshinone Accumulation and Drought Resistance in Salvia miltiorrhiza
Authors: Tian Qian , Han Wei , Zhou Shuai , Yang Liu , Wang Donghao , Zhou Wen , Wang Zhezhi
Published: December 2024

Danshen (Salvia miltiorrhiza Bunge) is a perennial herbaceous plant of the Salvia genus in the family Lamiaceae. Its dry root is one of the important traditional Chinese herbal medicines with a long officinal history. The yield and quality of S. miltiorrhiza are influenced by various factors, among which drought is one of the most significant types of abiotic stress. Based on the transcriptome database of S. miltiorrhiza, our research group discovered a carotenoid cleavage dioxygenase gene, SmCCD4, belonging to the carotenoid cleavage oxygenase (CCO) gene family which is highly responsive to drought stress on the basis of our preceding work. Here, we identified 26 CCO genes according to the whole-genome database of S. miltiorrhiza. The expression pattern of SmCCD4 showed that this gene is strongly overexpressed in the aboveground tissue of S. miltiorrhiza. And by constructing SmCCD4 overexpression strains, it was shown that the overexpression of SmCCD4 not only promotes the synthesis of abscisic acid and increases plant antioxidant activity but also regulates the synthesis of the secondary metabolites tanshinone and phenolic acids in S. miltiorrhiza. In summary, this study is the first in-depth and systematic identification and investigation of the CCO gene family in S. miltiorrhiza. The results provide useful information for further systematic research on the function of CCO genes and provide a theoretical basis for improving the yield and quality of S. miltiorrhiza.