bluuebunny/crossref_metadata_2025 huggingface dataset:
Impacts of Climate Change on Suitable Habitat Areas of Larix chinensis in the Qinling Mountains, Shaanxi Province, China
Authors: Deng Ruixiong , Chen Xin , Xiao Kaitong , Yu Ciai , Zhang Qiang , Ning Hang , Wu Lin , Xiao Qiang
Published: February 2025

Larix chinensis Mill., the sole tree species that can form pure forests at the timberline of the Qinling Mountains, plays a crucial role in maintaining the stability of high-altitude ecosystems. Owing to its special habitat requirements and fragmented distribution pattern, populations of L. chinensis are in a clear degenerating stage. Numerous studies have underscored the significant effect of climate change on high-altitude vegetation. However, studies focusing on the shifts in the distribution of L. chinensis habitats and the key environmental factors hindering their suitable distribution remain limited. Therefore, this study aimed to explore the influence of climate change on the future potential distribution of L. chinensis in order to understand the response of timberlines to climate change. In this study, random forest algorithms were applied to project the future potential distribution of L. chinensis across the Qinling Mountains. The results found that temperature and precipitation play crucial roles in limiting the distribution of L. chinensis, particularly in cold–humid climates and rainy, foggy environments, which contribute to its patchy distribution pattern. Currently, L. chinensis populations are distributed in Taibai Mountain and its surrounding alpine areas, concentrated at elevations of 2900–3300 m and on southern slopes of 15–35°, covering approximately 3361 km2. The ecological niche of L. chinensis is relatively narrow in terms of these environmental variables differing from the prevailing climate in the Qinling Mountains. During past climatic conditions or the last interglacial period (LIG period), the potential distribution range of L. chinensis gradually reduced, especially in low-elevation areas, nearly disappearing altogether. Projections under future climate scenarios suggest the contraction and fragmentation of suitable habitats for L. chinensis. The response of L. chinensis to the RCP 8.5 scenario exhibited the most pronounced changes, followed by the RCP 4.5 scenario. Under all climate scenarios in the 2050s, L. chinensis-suitable distribution exhibited varying degrees of reduction. Under the RCP 8.5 scenario, a significant decrease in suitable distribution is projected. Suitable distribution will continually decrease by the 2070s, with the most significant decline projected under the RCP 2.6 scenario. In conclusion, our findings not only offer management strategies for the populations of L. chinensis amidst climate change but also serve as crucial references for some endangered tree species in climate-sensitive areas.
Nicotinamide Counteracts Ultraviolet-B-Induced Cytotoxic Effects and Aquaporins Overexpression in the A375 Melanoma Cell Line
Authors: Camillo Lara , Esposto Elia , Gironi Laura Cristina , Zavattaro Elisa , Savoia Paola
Published: February 2025

Background/objectives: Ultraviolet-B (UVB) represents a major extrinsic factor in skin cancer development, causing cellular changes that are not yet fully understood. Aquaporins (AQPs) are a family of transmembrane proteins that favor water transport and are involved in several pathways. Nicotinamide (NAM), a vitamin B3 derivate, is a safe molecule able to reduce UVB-induced damages. This study aims to verify whether AQP expression is affected by UVB exposure at different dosages and times and to evaluate NAM’s effects against UVB-induced damages. Methods: A375 cells were exposed to 40, 100, and 200 mJ/cm2 UVB doses and analyzed 0, 1, 18, and 24 h post-irradiation. Results: We found that the 40 mJ/cm2 UVB dose, 24 h post-irradiation, caused the most detrimental effects an overall overexpression and dimerization of AQPs. However, in the presence of NAM 25 μM, the cell cycle was restored, leading to improved cell viability and proliferation, reduced ROS levels, and reduced DNA damage. Moreover, we found decreased AQPs expression and dimerization. Conclusions: Overall, NAM effectively mitigates UVB-induced cellular damage, including AQPs overexpression, and may serve as a protective agent against UVB-related skin damage.
Performance of Large Language Models ChatGPT and Gemini on Workplace Management Questions in Radiology
Authors: Leutz-Schmidt Patricia , Palm Viktoria , Mathy René Michael , Grözinger Martin , Kauczor Hans-Ulrich , Jang Hyungseok , Sedaghat Sam
Published: February 2025

Background/Objectives: Despite the growing popularity of large language models (LLMs), there remains a notable lack of research examining their role in workplace management. This study aimed to address this gap by evaluating the performance of ChatGPT-3.5, ChatGPT-4.0, Gemini, and Gemini Advanced as famous LLMs in responding to workplace management questions specific to radiology. Methods: ChatGPT-3.5 and ChatGPT-4.0 (both OpenAI, San Francisco, CA, USA) and Gemini and Gemini Advanced (both Google Deep Mind, Mountain View, CA, USA) generated answers to 31 pre-selected questions on four different areas of workplace management in radiology: (1) patient management, (2) imaging and radiation management, (3) learning and personal development, and (4) administrative and department management. Two readers independently evaluated the answers provided by the LLM chatbots. Three 4-point scores were used to assess the quality of the responses: (1) overall quality score (OQS), (2) understandabilityscore (US), and (3) implementability score (IS). The mean quality score (MQS) was calculated from these three scores. Results: The overall inter-rater reliability (IRR) was good for Gemini Advanced (IRR 79%), Gemini (IRR 78%), and ChatGPT-3.5 (IRR 65%), and moderate for ChatGPT-4.0 (IRR 54%). The overall MQS averaged 3.36 (SD: 0.64) for ChatGPT-3.5, 3.75 (SD: 0.43) for ChatGPT-4.0, 3.29 (SD: 0.64) for Gemini, and 3.51 (SD: 0.53) for Gemini Advanced. The highest OQS, US, IS, and MQS were achieved by ChatGPT-4.0 in all categories, followed by Gemini Advanced. ChatGPT-4.0 was the most consistently superior performer and outperformed all other chatbots (p < 0.001–0.002). Gemini Advanced performed significantly better than Gemini (p = 0.003) and showed a non-significant trend toward outperforming ChatGPT-3.5 (p = 0.056). ChatGPT-4.0 provided superior answers in most cases compared with the other LLM chatbots. None of the answers provided by the chatbots were rated “insufficient”. Conclusions: All four LLM chatbots performed well on workplace management questions in radiology. ChatGPT-4.0 outperformed ChatGPT-3.5, Gemini, and Gemini Advanced. Our study revealed that LLMs have the potential to improve workplace management in radiology by assisting with various tasks, making these processes more efficient without requiring specialized management skills.
Epidemiology of Celiac Disease in Cantabria, Spain
Authors: Blanco-García Alejandra , López-Hoyos Marcos , Irure-Ventura Juan , Muñoz-Cacho Pedro
Published: February 2025

Background/Objectives: Celiac disease is an enteropathy caused by a systemic autoimmune process of genetic predisposition to the ingestion of gluten. It is a public health problem worldwide because there are often long delays between the onset of symptoms and diagnosis. Our main objective is to describe the prevalence of celiac disease in our community, Cantabria, located in northern Spain. We start with an analytical database, with data collected from 2007 to 2016. We describe the possible differences in terms of age, sex, and geographic areas; family aggregation; and disease-associated comorbidities. Methods: The data for this research were obtained from a database from the Immunology Laboratory at the Marqués de Valdecilla University Hospital (HUMV), a reference laboratory for the entire Autonomous Community of Cantabria, located in northern Spain. The data were obtained from the analytical results collected from this database from January 2007 to January 2016, within this Community of 566,898 inhabitants in 2016. The data collected in this database consist of immunological tests, HLA-DQ2 or HLA-DQ8 antigenic patterns, focused on diagnosing celiac disease in the community of Cantabria, which have been positive during this period of time. Results: The prevalence of celiac disease in Cantabria is 0.14%. The mean age of diagnosis was 17.92 years. A higher percentage has been observed in the female sex and in children. Conclusions: The present study shows that celiac disease in the community of Cantabria is underdiagnosed. It is an important fact to consider when evaluating patients with symptoms that could be related to this disease to avoid increased use of medical consultations until a diagnosis is reached, in addition to avoiding long-term complications with this disease.
YOLO-DentSeg: A Lightweight Real-Time Model for Accurate Detection and Segmentation of Oral Diseases in Panoramic Radiographs
Authors: Hua Yue , Chen Rui , Qin Hang
Published: February 2025

Panoramic radiography is vital in dentistry, where accurate detection and segmentation of diseased regions aid clinicians in fast, precise diagnosis. However, the current methods struggle with accuracy, speed, feature extraction, and suitability for low-resource devices. To overcome these challenges, this research introduces a unique YOLO-DentSeg model, a lightweight architecture designed for real-time detection and segmentation of oral dental diseases, which is based on an enhanced version of the YOLOv8n-seg framework. First, the C2f(Channel to Feature Map)-Faster structure is introduced in the backbone network, achieving a lightweight design while improving the model accuracy. Next, the BiFPN(Bidirectional Feature Pyramid Network) structure is employed to enhance its multi-scale feature extraction capabilities. Then, the EMCA(Enhanced Efficient Multi-Channel Attention) attention mechanism is introduced to improve the model’s focus on key disease features. Finally, the Powerful-IOU(Intersection over Union) loss function is used to optimize the detection box localization accuracy. Experiments show that YOLO-DentSeg achieves a detection precision (mAP50(Box)) of 87%, segmentation precision (mAP50(Seg)) of 85.5%, and a speed of 90.3 FPS. Compared to YOLOv8n-seg, it achieves superior precise and faster inference times while decreasing the model size, computational load, and parameter count by 44.9%, 17.5%, and 44.5%, respectively. YOLO-DentSeg enables fast, accurate disease detection and segmentation, making it practical for devices with limited computing power and ideal for real-world dental applications.
Towards Effective Guidance of Smart Contract Fuzz Testing Based on Static Analysis
Authors: Park Jeongwon , Choi Jaeseung
Published: February 2025

In smart contract fuzz testing, it is crucial to consider the inter-dependencies between the contract functions. To effectively test the business logic of a contract, its functions must be invoked in a meaningful order. In this paper, we propose techniques that utilize static analysis on Ethereum bytecode to tackle this challenge. When compared with the current state-of-the-art, our approach takes Solidity compiler’s variable packing optimization into account and allows more precise analysis of the data-flows between functions. In addition, we devise a novel test case initialization algorithm for fuzz testing, which minimizes the redundancy in the generated seed set. Our algorithm reduces test cases that share similar function call patterns and leads to more effective testing of the contract code during the fuzz testing. Experimental results show that the proposed techniques improve the effectiveness of smart contract fuzz testing for vulnerability detection. Specifically, our techniques enabled the fuzz testing tool to trigger the target bugs in the benchmark 3.0 times faster on average.
Towards a Multi-Objective and Contextual Multi-Criteria Recommender System for Enhancing User Well-Being in Sustainable Smart Homes
Authors: Stitini Oumaima , Kaloun Soulaimane
Published: February 2025

Smart homes have become an important part of our daily lives, changing our habits to make them easier to live with in a sustainable way. This study highlights a context-sensitive system that continuously adapts to the user’s current activities and physiological habits in order to preserve physical and mental health while achieving sustainability goals. The system uses Internet of Things (IoT) sensors and smart home devices to measure indicators such as physical activity, heart rate, stress levels, and sleep quality. Based on these real-time measurements, the device offers personalized recommendations for a healthier lifestyle, such as physical activity reminders, stress management techniques, and sleep quality adjustments. By balancing the novelty and precision of its recommendations, the model aims to actively involve users without overloading them, thus promoting gradual and lasting behavioral changes. The architecture also incorporates multi-criteria evaluation measures, including accuracy and novelty-based diversity, to ensure an optimized user experience that is both accurate and adaptable. This paper proposes an advanced recommendation system for enhanced health monitoring by integrating multi-criteria decision-making and contextual awareness in order to have multi-objective results. The proposed system makes the personal recommendations with dynamic user categorization, using different kinds of notifications: reminder to exercise, monitoring heart health, and how to handle the stress. This approach is targeted to be scalable and adaptive to real-world conditions to enhance the overall effectiveness of health recommendations and strategies for preventive healthcare. The use of IoT will help in presenting a sound framework for personalized health interventions, enabling user engagement and better health outcomes.
Improving Cyber Defense Against Ransomware: A Generative Adversarial Networks-Based Adversarial Training Approach for Long Short-Term Memory Network Classifier
Authors: Wang Ping , Lin Hsiao-Chung , Chen Jia-Hong , Lin Wen-Hui , Li Hao-Cyuan
Published: February 2025

The rapid proliferation of ransomware variants necessitates more effective detection mechanisms, as traditional signature-based methods are increasingly inadequate. These conventional methods rely on manual feature extraction and matching, which are time-consuming and limited to known threats. This study addresses the escalating challenge of ransomware threats in cybersecurity by proposing a novel deep learning model, LSTM-EDadver, which leverages Generative Adversarial Networks (GANs) and Carlini and Wagner (CW) attacks to enhance malware detection capabilities. LSTM-EDadver innovatively generates adversarial examples (AEs) using sequential features derived from ransomware behaviors, thus training deep learning models to improve their robustness and accuracy. The methodology combines Cuckoo sandbox analysis with conceptual lattice ontology to capture a wide range of ransomware families and their variants. This approach not only addresses the shortcomings of existing models but also simulates real-world adversarial conditions during the validation phase by subjecting the models to CW attacks. The experimental results demonstrate that LSTM-EDadver achieves a classification accuracy of 96.59%. This performance was achieved using a dataset of 1328 ransomware samples (across 32 ransomware families) and 519 normal instances, outperforming traditional RNN, LSTM, and GCU models, which recorded accuracies of 90.01%, 93.95%, and 94.53%, respectively. The proposed model also shows significant improvements in F1-score, ranging from 2.49% to 6.64% compared to existing models without adversarial training. This advancement underscores the effectiveness of integrating GAN-generated attack command sequences into model training.
Tensor-Based Uniform and Discrete Multi-View Projection Clustering
Authors: Ma Linlin , Li Haomin , Zang Wenke , Liu Xincheng , Sun Minghe
Published: February 2025

Multi-view graph clustering (MVGC) utilizes affinity graphs to efficiently obtain information between views. Although various excellent MVGC methods have been proposed, they still have many limitations. To surmount these limitations, this work develops a novel tensor-based unified and discrete multi-view projection clustering (TUDMPC) approach. Specifically, TUDMPC uses projection and the L2,1-norm for feature selection to reduce the effects of redundancy and noise. Meanwhile, the differences among similar graphs are minimized through the tensor kernel norm to better leverage information across views and capture high-order correlations. In addition, the rank constraint is applied to keep the affinity graphs with a discrete cluster structure, and the clustering results are obtained directly in a unified joint framework. Finally, an efficient optimization algorithm is proposed to obtain the clustering results. Experiments are conducted to compare the clustering results of TUDMPC with seven baseline methods. The results show that TUDMPC outperforms the existing methods.
A Review of Multi-Agent Reinforcement Learning Algorithms
Authors: Liang Jiaxin , Miao Haotian , Li Kai , Tan Jianheng , Wang Xi , Luo Rui , Jiang Yueqiu
Published: February 2025

In recent years, multi-agent reinforcement learning algorithms have demonstrated immense potential in various fields, such as robotic collaboration and game AI. This paper introduces the modeling concepts of single-agent and multi-agent systems: the fundamental principles of Markov Decision Processes and Markov Games. The reinforcement learning algorithms are divided into three categories: value-based, strategy-based, and actor–critic algorithms, and the algorithms and applications are introduced. Based on differences in reward functions, multi-agent reinforcement learning algorithms are further classified into three categories: fully cooperative, fully competitive, and mixed types. The paper systematically reviews and analyzes their basic principles, applications in multi-agent systems, challenges faced, and corresponding solutions. Specifically, it discusses the challenges faced by multi-agent reinforcement learning algorithms from four aspects: dimensionality, non-stationarity, partial observability, and scalability. Additionally, it surveys existing algorithm-training environments in the field of multi-agent systems and summarizes the applications of multi-agent reinforcement learning algorithms across different domains. Through this discussion, readers can gain a comprehensive understanding of the current research status and future trends in multi-agent reinforcement learning algorithms, providing valuable insights for further exploration and application in this field.
Challenges and Opportunities for Aquifer Thermal Energy Storage (ATES) in EU Energy Transition Efforts—An Overview
Authors: Marojević Katarina , Kurevija Tomislav , Macenić Marija
Published: February 2025

Aquifer Thermal Energy Storage (ATES) systems are a promising solution for sustainable energy storage, leveraging underground aquifers to store and retrieve thermal energy for heating and cooling. As the global energy sector faces rising energy demands, climate change, and the depletion of fossil fuels, transitioning to renewable energy sources is imperative. ATES systems contribute to these efforts by reducing greenhouse gas (GHG) emissions and improving energy efficiency. This review uses the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) methodology as a systematic approach to collect and analyze relevant literature. It highlights trends, gaps, and advancements in ATES systems, focusing on simulation methods, environmental impacts, and economic feasibility. Tools like MODFLOW, FEFLOW, and COMSOL Multiphysics are emphasized for optimizing design and system performance. Europe is identified as a continent with the most favorable predispositions for ATES implementation due to its diverse and abundant aquifer systems, strong policy frameworks supporting renewable energy, and advancements in subsurface energy technologies.
Investigation on Thermal Performance of a Battery Pack Cooled by Refrigerant R134a in Ribbed Cooling Channels
Authors: Gao Tieyu , Wang Jiadian , Sha Haonan , Yang Hao , Lai Chenguang , Fu Xiaojin , Zhai Guangtao , Zeng Junxiong
Published: February 2025

This study numerically investigates the thermal performance of a refrigerant-based battery thermal management system (BTMS) under various operating conditions. A validated numerical model is used to examine the effects of cooling channel rib configurations (rib spacing and rib angles) and refrigerant parameters (mass flow rate and saturation temperature) on battery thermal behavior. Additionally, the impact of discharge C-rates is analyzed. The results show that a rib spacing of 11 mm and a rib angle of 60° reduce the maximum battery temperature by 0.8 °C (cooling rate of 2%) and improve temperature uniformity, though at the cost of a 130% increase in pressure drop. Increasing the refrigerant mass flow rate lowers the maximum temperature by up to 10%, but its effect on temperature uniformity diminishes beyond 20 kg/h. A lower saturation temperature enhances cooling but increases internal temperature gradients, while a higher saturation temperature improves uniformity at the expense of a slightly higher maximum temperature. Under high discharge rates (12C), the system’s cooling capacity becomes limited, leading to significant temperature rises. These findings provide insights that can aid in optimizing BTMS design to balance cooling performance, energy efficiency, and temperature uniformity.
Exploring Trigeneration in MSW Gasification: An Energy Recovery Potential Study Using Monte Carlo Simulation
Authors: Pegg Katarina , Wilson Grant , Al-Duri Bushra
Published: February 2025

This study evaluates the potential of gasification-based energy-from-waste (EfW) as a sustainable alternative to the current incineration facility in an industrial zone of a major UK city. The city generates approximately 475,000 tonnes of municipal solid waste (MSW) annually, with around 285,000 tonnes suitable for gasification-based energy recovery. Using a Monte Carlo type approach, we assess energy outputs across three scenarios: electricity-focused; balanced; hydrogen-focused. Results show that the industrial zone’s annual demand for heat and electricity are covered by all three scenarios, although the analysis does not seek to balance supply and demand over sub-annual timeframes. This suggests that energy-from-waste can support local energy demand and enable industrial symbiosis. At the city scale, however, only 7% of annual electricity demand is covered by the electricity-focused scenario with the balanced scenario only covering 4%. The hydrogen-focused scenario yields enough hydrogen annually to power up to 3400 buses, well beyond the current fleet of 144 and the target fleet of 480 by 2035, positioning the area as a potential hydrogen hub. The balanced scenario offers adaptable energy outputs, supporting diverse energy needs and reducing dependency on conventional incineration.
Land Degraded by Gold Mining in the Ecuadorian Amazon: A Proposal for Boosting Ecosystem Restoration Through Induced Revegetation
Authors: Mena-Quintana Fiodor N. , Álvarez Willin , Franco Wilfredo , Moncayo Luis , Tipán Myriam , Ayala Jholaus
Published: February 2025

Deforestation caused by gold mining in the Ecuadorian Amazon has increased by 300% in the last decade, leading to severe environmental degradation of water and land resources. Effective remediation and revegetation technologies are still needed to address this issue. This study aimed to foster revegetation on 0.5 hectares of degraded land in Naranjalito, a mining site in the Ecuadorian Amazon, by applying plant-based biocompost and biochar and planting Ochroma pyramidale and Arachis pintoi, two pioneer species. The project’s objective was to evaluate the impact of these treatments on vegetation cover recovery through physicochemical and microbiological improvements in the soil. Four blocks and sixteen experimental plots were established: eight plots received treatments with varying doses of biocompost+biol (BIOC), four plots included plantations without biocompost (Not-BIOC), and four served as control plots (bare land). Over six months, dasometric characteristics of O. pyramidale and the expansion of A. pintoi were recorded. The data were analyzed using multivariate methods. The results revealed significant differences between treatments, with BIOC plots T4 and T1 showing greater improvements in vegetation development compared to Not-BIOC plots T3 and T2, confirming the positive influence of biocompost+biol. The BIOC treatment favored not only the planted species but also the secondary successional plant communities including certain grasses, leguminous plants, and other shrub and tree species, thus accelerating the revegetation process. This study demonstrates that biocompost application is an effective strategy to enhance plant recolonization on land severely degraded by gold mining in the Ecuadorian Amazon.
A Review on the Extraction, Structural Analysis, and Antitumor Mechanisms of Sanghuangporus Polysaccharides
Authors: Liang Huaiyin , Ma Yanrui , Zhao Yan , Qayyum Nageena , He Fatao , Tian Jiewei , Sun Xiyun , Li Bin , Wang Yuehua , Wu Maoyu , Liu Guangpeng
Published: February 2025

In recent years, the bioactive compounds extracted from Sanghuangporus, especially polysaccharides, phenols, and triterpenoids, have attracted great interest from people due to their extensive biological activity. Among them, polysaccharides are mainly extracted from the seed bodies, mycelium, and fermentation broth of Sanghuangyuan, exhibiting notable effects including immunomodulation, antitumor properties, and hypoglycemic effects. This article provides a comprehensive review of the extraction process, structural characteristics, and antitumor mechanism of Sanghuangyuan polysaccharides. First, the different extraction methods, such as hot water extraction, enzyme-assisted extraction, and ultrasonic-assisted extraction, are summarized. Then, the structure of the Sanghuangporus polysaccharide is studied in detail. Moreover, the antitumor mechanisms demonstrate significant inhibitory impacts on various malignant tumors, spanning gastric, hepatic, colorectal, breast, and prostate cancers. This groundbreaking revelation is of great significance for both the food and pharmaceutical sectors, presenting innovative pathways for Sanghuangyuan utilization and potentially inducing advancements in product development, treatment modalities, and therapeutic interventions.
Influence of Peanut Flour Enrichment and Eggs on Muffin Protein Aggregation
Authors: Rutigliano Mariacinzia , Liberatore Maria Teresa , Dilucia Flavia , Quinto Maurizio , Kacmaz Sibel , Di Luccia Aldo , la Gatta Barbara
Published: February 2025

Protein–protein interactions were investigated, evaluating the influence of eggs and peanut flour on the chemical features of muffin samples. Electrophoretic, immunochemical, and chromatographic analyses were carried out to evaluate how different proteins can interact with one another, determining changes in their extractability. In this context, two extraction buffers were employed to study the rate of protein aggregate formation. Egg coagulation properties were found to affect the rate of wheat protein solubility, while the extractability of roasted peanut flour protein was less influenced and proportional to its amount in the formulation (i.e., 4% and 20%). The findings of this investigation allowed us to assume a complex form of protein organization, characterized by a “core” of wheat and egg proteins surrounded by peanut proteins, linked together through covalent reducible bonds and hydrophobic interactions. Nevertheless, the occurrence of other types of crosslinking could not be excluded.
Mechanical Response and Damage Characteristics of Frozen–Thawed Sandstone Across Various Temperature Ranges Under Impact Loads
Authors: Liu Dejun , Pu Hai , Xue Kangsheng , Xu Junce , Ni Hongyang
Published: February 2025

Freeze–thaw action is a key factor in the deterioration of the dynamic mechanical behavior of rocks in cold regions. This study used yellow sandstone, which is prevalent in the seasonally cold region of Xinjiang, China. The yellow sandstone samples were subjected to various temperatures and a range of freeze–thaw cycles. Impact mechanical tests were performed using a Split Hopkinson Pressure Bar (SHPB) system on the treated samples. The effects of freezing temperature and changes in impact load on the mechanical properties of frozen–thawed sandstone were examined. Additionally, the damage fractal characteristics of the sandstone were analyzed using fractal theory. The results indicate that as the freezing temperature decreases, the stress–strain curves of frozen–thawed specimens exhibit a clear initial compaction stage. The dynamic strength of the specimens decreases with lower freezing temperatures and shows a logarithmic relationship with the loading strain rate; however, the dynamic deformation modulus exhibits no significant correlation with the strain rate. The fractal dimension is positively correlated with the strain rate, indicating that lower freezing temperatures correspond to a higher rate of increase in the fractal dimension. These findings offer valuable insights into the damage deterioration characteristics of frozen–thawed rocks under varying temperature conditions.
Editorial for Special Issue “Hydrogelated Matrices: Structural, Functional and Applicative Aspects”
Authors: Gallo Enrico , Diaferia Carlo
Published: February 2025

Gel-based materials have found important applications in fields such as food, healthcare, cosmetics, and bioanalysis [...]
“My Dad Is Racist as Hell:” Navigating Racism, Monoracism, and White Privilege by Proxy in Multiracial Families
Authors: Waring Chandra D. L.
Published: February 2025

While the dominant narrative of multiracial families in society is that they are atypical, the implicit narrative is that they are racially progressive. In this article, I show how multiracial people with different backgrounds, although all have white ancestry, experience family life in nuanced ways that include racial discrimination and unearned privileges. While research has documented racism and monoracism in multiracial families, scholars have yet to analyze how inequality interacts with the unearned privileges that accompany a white parent. This study explores how 30 multiracial people experience racism, monoracism, and white privilege by proxy in their family lives. First, I center my respondents’ experiences with racism and monoracism, and how these experiences are shaped by the role of the family member (i.e., parent, grandparent, etc.). Second, I explain how white privilege by proxy is influenced by the intersectional identities of my participants’ white parent. Lastly, I outline how and under what conditions this form of privilege can be restricted or revoked. These findings present a new narrative of multiracial family life that more accurately reflects the intersectional and complex realities of multiracial people.
Exploring the Genotoxic Stress Response in Primed Orphan Legume Seeds Challenged with Heat Stress
Authors: Pagano Andrea , Dueñas Conrado , Bedotto Nicolò , Elleuch Amine , Khemakhem Bassem , El Abed Hanen , Tani Eleni , Goufa Maria , Chachalis Dimosthenis , Balestrazzi Alma
Published: February 2025

Background/Objectives: The increased frequency of extreme weather events related to climate change, including the occurrence of extreme temperatures, severely affects crop yields, impairing global food security. Heat stress resulting from temperatures above 30 °C is associated with poor germination performance and stand establishment. The combination of climate-resilient crop genotypes and tailored seed priming treatments might represent a reliable strategy to overcome such drawbacks. This work explores the potential of hydropriming as a tool to mitigate the heat-stress-mediated impact on germination performance in orphan legumes. Methods: For each tested species (Lathyrus sativus L., Pisum sativum var. arvense and Trigonella foenum-graecum L.), two accessions were investigated. Germination tests were performed at 25 °C, 30 °C, 35 °C and 40 °C to assess the heat stress tolerance threshold. Hydropriming was then applied and germination tests were performed at 40 °C to test the impact of the treatment on the seeds’ ability to cope with heat stress. An alkaline comet assay and Quantitative Real Time-Polymerase Chain Reaction were performed on embryos excised from primed and control seeds. Results: Phenotyping at the germination and seedling development stage highlighted the accession-specific beneficial impact of hydropriming under heat stress conditions. In L. sativus seeds, the alkaline comet assay revealed the dynamics of heat stress-induced DNA damage accumulation, as well as the repair patterns promoted by hydropriming. The expression patterns of genes involved in DNA repair and antioxidant response were consistently responsive to the hydropriming and heat wave conditions in L. sativus accessions.
The Relationship Between Genetic Variants at Loci 9p21, 6q25.1, and 2q36.3 and the Development of Cardiac Allograft Vasculopathy in Heart Transplant Patients
Authors: Dlouha Dana , Janouskova Kristyna , Vymetalova Jevgenija , Novakova Sarka , Chytilova Sarka , Lukasova Marianna , Hubacek Jaroslav A.
Published: February 2025

Background: Cardiac allograft vasculopathy (CAV) is an accelerated form of coronary artery disease (CAD) that is characterized by concentric fibrous intimal hyperplasia along the length of coronary vessels, and is recognized as long-term complication after heart transplantation. The chromosomal loci 9p21, 6q25.1, and 2q36.3, represented by their respective leading variants rs10757274, rs6922269 and rs2943634, have been linked with a history of CAD by genome-wide association studies. We aimed to investigate the associations of genetic variants at the loci 9p21, 6q25.1, and 2q36.3 with CAV as genetic risk factors for early prediction. Methods: Genomic DNA was extracted from paired aortic samples of 727 heart recipients (average age 50.8 ± 12.2 years; 21.3% women) and corresponding donors (average age 39.7 ± 12.0 years; 26.1% women). The variants within the loci 9p21, 6q25.1, and 2q36.3 were genotyped using PCR-RFLP. Results: The recipients’ variants of 9p21 (OR 1.97; 95% CI, 1.21-3.19 for GG vs. +A comparison, p = 0.0056) and 2q36.3 (OR 2.46; 95% CI, 1.12–6.17 for +C vs. AA comparison, p = 0.0186) were associated with higher incidence of CAV during the first year following heart transplantation. No such association was found for donor genotypes. Conclusions: Our data suggest that variants at the locus 9p21 (rs10757274) and 2q36.3 (rs2943634) are associated with early CAV development.
Molecular Characteristics and Role of Buffalo SREBF2 in Triglyceride and Cholesterol Biosynthesis in Mammary Epithelial Cells
Authors: Dao Wenbin , Chen Hongyan , Ouyang Yina , Huang Lige , Fan Xinyang , Miao Yongwang
Published: February 2025

Background/Objectives: Sterol regulatory element-binding transcription factor 2 (SREBF2) is a key transcription factor involved in regulating cholesterol homeostasis. However, its role in buffalo mammary gland lipid metabolism remains unclear. Methods: To address this, we isolated and characterized the SREBF2 gene from buffalo mammary glands and performed an in-depth analysis of its molecular characteristics, tissue-specific expression, and functional roles in buffalo mammary epithelial cells (BuMECs). Additionally, we investigated the single nucleotide polymorphisms (SNPs) of SREBF2 in both river and swamp buffalo. Results: The coding sequence (CDS) of buffalo SREBF2 is 3327 bp long and encodes a protein of 1108 amino acid residues. Bioinformatics analysis revealed that the molecular characteristics of buffalo SREBF2 were highly similar across Bovidae species, with collinearity being observed among them. An expression profile analysis revealed that SREBF2 is expressed in all 11 tested tissues of buffalo, with its expression level in the mammary gland being higher during lactation than in the dry period. The knockdown of SREBF2 in BuMECs during lactation led to a significant reduction in the expression of genes involved in triglyceride (TAG) and cholesterol synthesis, including PI3K, AKT, mTOR, SREBF1, PPARG, INSIG1, ACACA, SCD, DGAT1, LPL, CD36, HMGCR, and SQLE. This knockdown led to a 23.53% and 94.56% reduction in TAG and cholesterol levels in BuMECs, respectively. In addition, a total of 22 SNPs were identified in both buffalo types, of which four non-synonymous substitutions (c.301G>C, c.304A>T, c.1240G>A, and c.2944G>A) were found exclusively in the SREBF2 CDS of swamp buffalo, and the assessment revealed that these substitutions had no impact on SREBF2 function. Conclusions: These findings emphasize the critical role of SREBF2 in regulating both triglyceride and cholesterol biosynthesis, providing valuable insights into its functions in buffalo mammary glands.
Long-Term Effects of Municipal Solid Waste Leachate on Soil Hydraulic Properties
Authors: Chihi Feten , Varga Gabriella , Kopecskó Katalin
Published: February 2025

This experimental study examines the effects of landfill leachate contamination on soil hydraulic conductivity over a 12-month period, addressing the current lack of long-term experimental data in this field. Laboratory permeability tests were performed on sandy clayey silt samples contaminated with leachate at concentrations ranging from 5% to 25%. Microstructural and mineralogical analyses were conducted using SEM and XRD to identify the mechanisms behind observed changes. The results identify a critical threshold at 15% contamination, where soil behavior transitions from granular to cohesive characteristics. Hydraulic conductivity increases at low contamination levels (5–10%, up to 1.2 × 10−7 m/s) but decreases significantly at higher levels (4.172 × 10−8 m/s at 15%, 8.545 × 10−9 m/s at 20%). These changes are controlled by contamination level rather than exposure time, with values remaining stable throughout the 12-month period. The study provides essential parameters for landfill design and contamination assessment, demonstrating how leachate concentration affects long-term soil hydraulic properties through mineral formation and structural modification.
What Is Heritable: Power, Magic and Spirit in Marie-Elena John’s Unburnable
Authors: Mordecai Rachel L.
Published: February 2025

In Marie-Elena John’s 2006 novel Unburnable, Lillian Baptiste returns to Dominica from the United States intending to confront the secrets and traumas of her maternal family line. The novel structures Lillian’s developing apprehension of who her mother and grandmother were and what they endured in late-colonial Dominica around a series of revelations regarding each woman’s imbrication within the realm of the magico-spiritual, which includes magic, Obeah and their cognates; Catholicism; spells and curses; ghosts and other spirit manifestations; and extra-sensory perception. The reader comes to understand Lillian as (and sometimes before) Lillian comes to understand herself: the last in a line of magico-spiritually powerful women whose encounters with colonial catastrophe and its heteropatriarchal, racist–classist machinations are both figured through and navigated by way of that power. Where socioeconomic and political power may conventionally be regarded as the proper subject of realist fiction and social-science inquiry, and magico-spiritual power as within the ambit of magical-realist fiction and folklore studies, Unburnable proposes worldly and magico-spiritual power as inhabiting the same material, political and psycho-social plane of Caribbean reality: as mutually entangled, co-constituting, reciprocally illuminating and, above all, dually heritable forces. In this way, the novel issues an invitation to rethink questions of power in the shadow of the Caribbean plantation and consider anew the ways in which it is, on the one hand, hoarded, bequeathed and weaponized against the vulnerable and, on the other, fluid, arcane in its sources and workings, and susceptible to insurgent counter-deployments.
Towards More Reliable Measures for “Perceived Urban Diversity” Using Point of Interest (POI) and Geo-Tagged Photos
Authors: He Zongze , Zhang Xiang
Published: February 2025

Urban diversity is essential for promoting urban vitality and achieving sustainable urban development. However, existing studies rely on static and non-visual data and seldom incorporate human perception aspects in the diversity estimation. Together with the modifiable areal unit problem (MAUP) in the traditional entropy-based approach, urban diversity is prone to be biased or underestimated. In this study, we use urban function (from POI) and visual semantics (from geo-tagged photos) to estimate what we call “perceived urban diversity”. More importantly, we propose to improve the traditional entropy-based diversity measures by addressing the MAUP issue using area- and accessibility-based extensions. Empirical analysis using Shenzhen, China, as a case study reveals that our “perceived diversity” indicators display stronger correlations to urban vitality. Furthermore, combining different data sources (e.g., geo-tagged photos) provides a more comprehensive portrayal of urban diversity. Finally, our results suggest that neighborhoods dominated by residential or commercial land uses would benefit the most from enhanced diversity. These findings are useful for a refined assessment of urban diversity and offer valuable insights for urban planning and community design.
Impact of Shared Bicycle Spatial Patterns During Public Health Emergencies: A Case Study in the Core Area of Beijing
Authors: Wen Zheng , Hu Lujin , Hu Jing
Published: February 2025

During public health emergencies, studying the travel characteristics and influencing factors of shared bicycles during different time periods on weekdays can provide valuable insights for urban transportation planning and offer recommendations for bike-sharing systems (BSS) affected by such events. Utilizing bike-sharing data, this study initiated the analysis by scrutinizing the spatial flow patterns in the core area of Beijing, employing network indicators within the framework of complex network theory. Subsequently, influencing factors associated with bike-sharing trips were pinpointed using the exponential random graph model (ERGM). Using COVID-19 as an example, it examines the impact of public health emergencies on bike-sharing during multiple time periods. Supported by the network analysis method, our findings revealed that the majority of travel activities occurred between adjacent areas. Throughout weekdays, a consistent level of travel activity was observed, exhibiting distinct patterns during daytime and nighttime. The period from 4:00 to 8:00 emerged as the peak time, characterized by heightened traffic and temperature changes. Morning commuting extended until 8:00–12:00, followed by a transition period from 12:00–16:00. The most active travel time, encompassing various purposes, was identified as 16:00–20:00. Additionally, the presence of hospitals and train stations amplified travel within the pandemic-affected area. Finally, variants of ERGMs were employed to assess the influence of finance, shopping, dining, education, transportation, roads, and COVID-19 on bike-sharing activities. The road network emerged as the most critical factor, exhibiting a significant negative impact. Conversely, COVID-19 had the most pronounced positive influence, with transportation stops and educational institutions also contributing significantly in a positive manner. This research provides valuable transportation planning insights for addressing public health emergencies and promotes the effective utilization of bike-sharing systems.
In-Situ Purification of Non-Ribosomal Peptide Synthetases Assembly Line for Structural and Biochemical Studies
Authors: Cao Wei , Chen Shyue Leh , Wu Suen Kit , Wang Jialiang , Deng Zixin , Liang Jingdan , Wang Zhijun
Published: February 2025

Nonribosomal peptide synthetases (NRPS) are essential for the biosynthesis of therapeutically valuable molecules, including antibiotics, immunosuppressants, and anticancer agents. The assembly-line mechanism of NRPS offers significant potential for engineering novel natural products through reprogramming. However, the challenging purification of NRPS proteins has impeded the investigation of their assembly and catalytic mechanisms. In this study, we employed homologous recombination to insert a purification tag at the C-terminus of the NRPS gene within the chromosome. This genetic modification enabled efficient purification of NRPS proteins from the tagged mutant strain using a one-step affinity chromatography approach. Additionally, we discovered that MbtH-like proteins (MLPs) form stable complexes with all pyoverdine (PVD) NRPS subunits, allowing for the purification of the entire NRPS assembly line via tagged MLP. Negative stain electron microscopy analysis revealed that the purified PVD NRPS proteins exist as dynamically linear monomers. Our in-situ tag-based purification method enhances NRPS research in both biochemical and structural biology, providing a robust platform for further investigations into NRPS mechanisms and applications.
Pharmacogenetics in Response to Biological Agents in Inflammatory Bowel Disease: A Systematic Review
Authors: Ballesta-López Octavio , Gil-Candel Mayte , Centelles-Oria María , Megías-Vericat Juan Eduardo , Solana-Altabella Antonio , Ribes-Artero Hugo , Nos-Mateu Pilar , García-Pellicer Javier , Poveda-Andrés José Luis
Published: February 2025

Inflammatory bowel diseases (IBDs) are chronic inflammatory disorders influenced by microbial, environmental, genetic, and immune factors. The introduction of biological agents has transformed IBD therapy, improving symptoms, reducing complications, and enhancing patients’ quality of life. However, approximately 30% of patients exhibit primary non-response, and 50% experience a loss of response over time. Genetic and non-genetic factors contribute to variability in treatment outcomes. This systematic review aims to thoroughly analyze and assess existing studies exploring the relationships between genetic variations and individual responses to biologic drugs, in order to identify genetic markers that are predictive of treatment efficacy, risk of adverse effects, or drug toxicity, thereby informing clinical practice and guiding future research. PubMed and EMBASE papers were reviewed by three independent reviewers according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses [PRISMA] guidelines. Of the 883 records screened, 99 met the inclusion criteria. The findings of this review represent an initial step toward personalized medicine in IBD, with the potential to improve clinical outcomes in biological therapy.