bluuebunny/crossref_metadata_2025 huggingface dataset:
Tissue Doppler Imaging Provides Incremental Value in Predicting Six Months In-Stent Restenosis in Patients with Coronary Artery Disease
Authors: Yeh Jih-Kai , Wu Victor Chien-Chia , Lin Fen-Chiung , Hsieh I-Chang , Chang Po-Cheng , Chen Chun-Chi , Yang Chia-Hung , Chen Wen-Pin , Hung Kuo-Chun
Published: February 2025

Background: Invasive coronary angiography is the gold standard for assessing in-stent restenosis (ISR) in patients with coronary artery disease. However, the predictive value of non-invasive Tissue Doppler Imaging (TDI) to evaluate patients with ISR has not been studied extensively. Methods: A total of 41 patients (19 with acute myocardial infarction and 22 with stable angina pectoris) who received percutaneous coronary intervention (PCI) were enrolled in the study. Time-to-peak velocities (TpV) of 12 non-apical segments of the left ventricle, by pulse wave TDI echocardiography, were obtained within two days prior to the PCI and six months later. Results: A 12-segmental mean TpV ≥ 279.6 ms at six months after PCI was able to detect ISR (odds ratio: 2.09, 95% CI 1.004–4.352, p = 0.049). Moreover, a significant decrease in the standard deviation of TpV was demonstrated in patients without ISR (85.8 ± 44.8 vs. 60.3 ± 31.7 ms, p = 0.001), but not in patients with ISR (97.7 ± 53.3 vs. 91.2 ± 52.6 ms, p = 0.57). Conclusions: Pulse-wave TDI echocardiography is a promising tool in the detection of ISR six months after PCI in patients with coronary artery disease.
Cooperative Path Planning for Multiple UAVs Based on APF B-RRT* Algorithm
Authors: Wu Cailong , Guo Zhengyu , Zhang Jian , Mao Kai , Luo Delin
Published: February 2025

Aiming at the path planning problem of an unmanned aerial vehicle (UAV) in a complex unknown environment, this paper proposes a cooperative path planning algorithm for multiple UAVs. Using the local environment information, several rolling path plannings are carried out by the Artificial Potential Field Bidirectional-Rapidly exploring Random Trees (APF B-RRT*) algorithm. The APF B-RRT* algorithm optimizes the search space by pre-sampling and adapts with an adaptive step while fusing with the APF algorithm for guiding sampling. Then, the generated path is trimmed and smoothed to obtain the optimized path. Then, through the sampling constraint, several paths can be planned at the same time, which are guaranteed not to collide. The model predictive control (MPC) is used to realize the cooperative control of the UAVs, that is, the UAVs reached the destination simultaneously along the planned path. This algorithm achieves some progress in solving the problems of slow convergence speed, an unstable result and an unsmooth path in UAV path planning. Simulation and comparison show that the APF B-RRT* algorithm has certain advantages in algorithm performance.
Maxwellian Distribution-Based Hall Transport Coefficients for Charged Particles in Magnetic Disk Array
Authors: An Linlin , Fan Peifeng
Published: February 2025

This study explores Hall transport phenomena by expanding upon prior research on magnetic disk arrays (MDAs). We examine the dynamics of charged particles using collision models akin to those in Lorentzian plasma. Previously, we derived transport coefficients under isotropic and mono-kinetic conditions. In this study, we adopt an anisotropic framework, enhanced by Fourier transformation, and employ the local Maxwellian distribution function. These assumptions allow us to calculate the Hall diffusivity, electrical conductivity, and thermal Hall conductivity tensors. Our findings contribute to a deeper understanding of the Hall transport in magnetic disk arrays and chiral active systems.
How to Be a Copenhagenistic-QBistic Everettist
Authors: Wieśniak Marcin
Published: February 2025

The measurement problem in quantum mechanics (QM) is related to the inability to include learning about the properties of a quantum system by an agent in the formalism of quantum theory. It includes questions about the physical processes behind the measurement, uniqueness, and randomness of obtained outcomes and an ontic or epistemic role of the state. These issues have triggered various interpretations of quantum theory. They vary from refusing any connection between physical reality and a measurement process to insisting that a collapse of the wave-function is real and possibly involves consciousness. On the other hand, the actual mechanism of a measurement is not extensively discussed in these interpretations. This essay attempts to investigate the quantum measurement problem from the position of the scientific consensus. We begin with a short overview of the development of sensing in living organisms. This is performed for the purpose of stressing the relation between reality and our experience. We then briefly present different approaches to the measurement problem in chosen interpretations. We then state three philosophical assumptions for further consideration and present a decomposition of the measurement act into four stages: transformation, conversion, amplification and broadcasting, and, finally, perception. Each of these stages provides an intuition about the physical processes contributing to it. These conclusions are then used in a discussion about, e.g., objectivity, the implausibility of reversing a measurement, or the epistemic status of the wave-function. Finally, we argue that those in favor of some of the most popular interpretations can find an overlap between their beliefs and the consequences of considerations presented here.
Quantitative Evaluation of Residual Acid Invasion and Flowback in Fractured-Vuggy Carbonate Reservoirs Using Microfluidics
Authors: Cai Jianchao , Yang Jin , Huang Zhiwen , Xu Sai , Zhang Lufeng , Wang Han
Published: February 2025

Acid fracturing has become a crucial technology for developing carbonate reservoirs, playing a particularly significant role in enhancing oil and gas recovery. However, the retention and flowback behaviors of residual acid in fractured-vuggy carbonate reservoirs after acid fracturing remain poorly understood, and this uncertainty significantly hinders the efficient development of such reservoirs. In this study, the micro-computed tomography images of carbonate rocks were used to extract actual fracture–vug structures. A microscopic flow model for fractured-vuggy carbonate reservoirs was then designed and fabricated using wet etching techniques. Microfluidic experiments were performed to investigate the invasion and flowback behavior of residual acid within these reservoirs. This study introduces a novel approach by integrating actual fracture-vuggy structures from micro-CT images into a microfluidic model, providing a more realistic representation of fractured-vuggy carbonate reservoirs compared to previous studies that relied on simplified or idealized geometries. Additionally, the invasion coefficient (the ratio of acid invaded area to total pore area) and flowback rate (the proportion of residual acid expelled during flowback) were introduced to quantitatively assess the efficiency of acid invasion and flowback under varying flow rates, viscosities, and the presence or absence of surfactants. The results demonstrate that the invasion coefficient of residual acid increases with the injection rate, while the flowback rate decreases as the injection rate is reduced. A higher viscosity of the oil phase hinders acid invasion and results in slower flowback due to increased flow resistance in the micro model. However, the final flowback rate is higher with a higher viscosity oil phase compared to a lower viscosity phase. The addition of surfactants enhances the efficiency of acid invasion and flowback, increasing the invasion coefficient by up to 5% and the flowback rate by up to 3%.
Artificial Intelligence for Non-Destructive Imaging in Composite Materials
Authors: Seckin Mine , Demircioglu Pinar , Seckin Ahmet Cagdas , Bogrekci Ismail , Aksoy Serra
Published: February 2025

(1) Background: The purpose of this review is to explore how advanced sensor technologies and AI-driven methods, like machine learning and image processing, are shaping non-destructive imaging (NDI) systems. NDI plays a vital role in ensuring the strength and reliability of composite materials. Recent advancements in sensor technologies and AI-driven methods, such as machine learning and image processing, have opened up new ways to improve NDI systems, offering exciting opportunities for better performance. (2) Methods: This review takes a close look at how advanced sensor technologies and machine learning techniques are being integrated into NDI systems. The review evaluates how effective these technologies are at detecting defects and examines their strengths, limitations, and challenges. (3) Results: Combining sensor technologies with AI methods has shown a clear boost in defect detection accuracy and efficiency. However, challenges like high computational requirements and integration costs remain. Despite these hurdles, the potential for these technologies to revolutionize NDI systems is significant. (4) Conclusions: By synthesizing the latest research, this review offers a comprehensive understanding of how sensor technologies are enhancing NDI. The findings highlight their importance for improving defect detection and their broader impact on research and industry, while also pointing out areas where further development is needed for future growth.
Numerical Investigation of the Influence of Temperature on Fluidization Behavior: Importance of Particle Collision Parameters and Inter-Particle Forces
Authors: Mihajlović Milan , Ramírez Juan G. , Campos Velarde Ildefonso , Van Sint Annaland Martin , Roghair Ivo
Published: February 2025

Fluidized bed reactors (FBRs) are integral to various industries due to their exceptional capability in facilitating efficient gas–solid interactions, resulting in superior mixing and heat and mass transfer. This research delves into the impact of temperature on fluidization dynamics, particularly focusing on the collisional properties of particles within the bed. The investigation builds upon foundational research, notably Geldart’s classification of fluidization regimes and recent advancements in high-temperature experimental techniques, such as High-Temperature Endoscopic-Laser particle image velocimetry/digital image analysis. To explore these temperature effects, a coupled Discrete Element Method and Computational Fluid Dynamics (cfd–dem) model was employed. This approach enables a detailed examination of gas–particle and particle–particle interactions under varying temperature conditions. The simulations in this study explore the friction coefficient, as well as changes in both tangential and normal restitution coefficients, which affect the fluidization behavior. These changes were systematically analyzed to determine their influence on minimum fluidization velocity and bubble formation. The numerical results are compared with experimental data from high-temperature fluidization studies, highlighting the necessity of incorporating inter-particle forces to fully capture the observed phenomena. The findings underscore the critical role of particle collisional properties in high-temperature fluidization and suggest the potential increasing role of inter-particle forces. Overall, this paper provides new insights into the complex dynamics of fluidized beds at elevated temperatures, emphasizing the need for further experimental–numerical research to enhance the reliability and understanding of these systems in industrial applications.
Geographical Origin Identification of Chinese Red Jujube Using Near-Infrared Spectroscopy and Adaboost-CLDA
Authors: Wu Xiaohong , Yang Ziteng , Yang Yonglan , Wu Bin , Sun Jun
Published: February 2025

Red jujube is a nutritious food, known as the “king of all fruits”. The quality of Chinese red jujube is closely associated with its place of origin. To classify Chinese red jujube more correctly, based on the combination of adaptive boosting (Adaboost) and common vectors linear discriminant analysis (CLDA), Adaboost-CLDA was proposed to classify the near-infrared (NIR) spectra of red jujube samples. In the study, the NIR-M-R2 spectrometer was employed to scan red jujube from four different origins to acquire their NIR spectra. Savitzky–Golay filtering was used to preprocess the spectra. CLDA can effectively address the “small sample size” problem, and Adaboost-CLDA can achieve an extremely high classification accuracy rate; thus, Adaboost-CLDA was performed for feature extraction from the NIR spectra. Finally, K-nearest neighbor (KNN) and Bayes served as the classifiers for the identification of red jujube samples. Experiments indicated that Adaboost-CLDA achieved the highest identification accuracy in this identification system for red jujube compared with other feature extraction algorithms. This demonstrates that the combination of Adaboost-CLDA and NIR spectroscopy significantly enhances the classification accuracy, providing an effective method for identifying the geographical origin of Chinese red jujube.
Exploring the Core Functional Microbiota Related to Flavor Compounds in Douchi from the Sichuan–Chongqing Region
Authors: Tu Dawei , Kang Junhan , Li Qingqing , Deng Meilin , Liu Meiyan , Liu Wenjun , Ming Jian , Brennan Margaret , Brennan Charles , You Linfeng
Published: February 2025

Douchi is a traditional Chinese fermented soybean product. In the Sichuan–Chongqing region, Mucor-type douchi was particularly famous for its distinctive flavor. Nevertheless, the association between microorganisms and douchi flavor is still poorly understood. In this study, high-throughput sequencing, amino acid analysis, and gas chromatography-mass spectrometry (GC-MS) were used to investigate the bacterial and fungal profiles as well as the flavor compounds (sixteen amino acids and one-hundred volatile flavor compounds) of seven different types of douchi. High levels of glutamic and aspartic acids were observed. Microbial analysis found that Bacillus, Tetragenococcus, Weissella, Aspergillus, Mucor, and Penicillium were the prime microorganisms. In total, 100 volatile components were detected; however, none of them was common to all the douchi products, although most volatile components had the aromas of flowers, fruits, caramel, and cocoa. An analysis of the flavor compounds was conducted using two-way orthogonal partial least-squares discriminant analysis (O2PLS-DA). Based on the analysis, it was found that Glu had negative correlations with most microorganisms, and Aspergillus had positive correlations with 2-pentylfuran and phenylacetaldehyde. This study provides a theoretical foundation for the regulation and enhancement of douchi flavor.
Functional Properties of Gelatin–Alginate Hydrogels for Use in Chronic Wound Healing Applications
Authors: Maikovych Olha , Pasetto Pamela , Nosova Nataliia , Kudina Olena , Ostapiv Dmytro , Samaryk Volodymyr , Varvarenko Serhii
Published: February 2025

In this study, a hydrogel material based on porcine gelatin and sodium alginate was synthesized for use as a dressing for chronic wound treatment. The hydrogels were covalently cross-linked using polyethylene glycol diglycidyl ether (PEGDE 500), and the interaction between the components was confirmed via FTIR. The properties of the resulting hydrogels were examined, including gel-fraction volume, swelling degree in different media, mechanical properties, pore size, cytotoxicity, and the ability to absorb and release analgesics (lidocaine, novocaine, sodium diclofenac). The hydrogel’s resistance to enzymatic action by protease was enhanced both through chemical cross-linking and physical interactions between gelatin and alginate. The absorption capacity of the hydrogels, reaching 90 g per dm2 of the hydrogel dressing, indicates their potential for absorbing wound exudates. It was demonstrated that the antiseptic (chlorhexidine) contained in the structured gelatin–alginate hydrogels can be released into an infected substrate, resulting in a significant inhibition of pathogenic microorganisms (Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, and Aspergillus niger). These results clearly demonstrate that the obtained hydrogel materials can serve as non-traumatic dressings for the treatment of chronic and/or infected wounds.
Feasibility of Using Patient Portal to Enhance Patient Engagement and Patient-Generated Data in Tertiary Hospital
Authors: Alfurayh Ghaliah H. , Alanazi Abdullah T. , Aldalham Hanin S.
Published: February 2025

Objectives: This study aimed to evaluate the experiences of patients using a patient portal at a tertiary hospital in Riyadh, Saudi Arabia, focusing on engagement, usability, and patient-generated data. Methods: A descriptive cross-sectional study was conducted using an online survey distributed to 244 patients using the patient portal between September and December 2023. Data collected included sociodemographic characteristics, health literacy, internet and smartphone usage, and patient engagement with the portal. Results: Among the 244 respondents, 99.6% were smartphone users, and 85% reported using the patient portal. The most frequently used functionalities included scheduling appointments (60.1%) and viewing laboratory results. Significant associations were found between general satisfaction and perceptions of ease of login, information comprehension, and increased engagement (p < 0.05). High satisfaction was reported among those updating personal information (88.6%) and allergy status (78.1%) through the portal. Barriers to use included internet access limitations and privacy concerns. Age significantly influenced the need for training to enhance portal usage (p < 0.05). Conclusions: Patient engagement with the portal was high, indicating its potential as a tool for enhancing healthcare delivery. Improving usability, addressing identified barriers, and providing tailored training could further optimize patient engagement and utilization of health services.
Transcriptomic Analyses Reveal Light-Induced Anthocyanin Accumulation in Lycium ruthenicum Murray
Authors: Chen Shengrong , He Tao , Gu Wenyi , Li Ruimin , Qi Yinyan
Published: February 2025

Light plays a crucial role in anthocyanin biosynthesis and color development in plants. Anthocyanins found in Lycium ruthenicum Murray are crucial for the plant’s defense against UV light and environmental stress, as well as for their economic value in functional foods and nutraceuticals due to their high antioxidant content. Despite this, the molecular mechanisms underlying this process remain incompletely understood. This study explores the molecular mechanisms that drive light-regulated anthocyanin accumulation in L. ruthenicum berries by conducting shading treatments and analyzing the transcriptomic data. Results indicated that shading from 5 to 25 days post-flowering greatly impedes the synthesis of anthocyanin, even if light exposure is increased afterward. This suggests that the early stages of fruit development are crucial for anthocyanin accumulation. In regular lighting conditions, a total of 22 anthocyanin types were detected, with Delphinidin-3-O-(p-coumaroyl)-glucoside (611) and Petunidin-3-O-rutinoside (933) being the most prevalent. When berries were exposed to early light, there was a greater presence of Petunidin-3-O-rutinoside (933), resulting in a black appearance, whereas those not exposed had a lighter color with higher levels of Delphinidin-3-O-(p-coumaroyl)-glucoside (611). RNA-Seq analysis showed a notable decrease in the expression of genes involved in the anthocyanin biosynthesis pathway (such as CHS, CHI, F3H, F3′H, F3′5′H, DFR, and ANS) following shading. Key regulatory genes like GRAS, HD-ZIP, MADS, and mTERF were involved in anthocyanin accumulation in response to light. A proposed model has been developed to elucidate the mechanism by which light controls the biosynthesis of anthocyanin, providing insights into light signal regulation. Our findings provide data to improve the understanding of light-induced anthocyanin accumulation in L. ruthenicum berries.
Drug Resistance in Late-Stage Epidermal Growth Factor Receptor (EGFR)-Mutant Non-Small Cell Lung Cancer Patients After First-Line Treatment with Tyrosine Kinase Inhibitors
Authors: Lee Ching-Yi , Lee Shih-Wei , Hsu Yi-Chiung
Published: February 2025

The development of tyrosine kinase inhibitors (TKIs) for late-stage epidermal growth factor receptor (EGFR)-mutant non-small cell lung cancer (NSCLC) represented a drastic change in the treatment of late-stage lung cancer. Drug resistance develops after a certain period of first-line TKI treatment, which has led to decades of changing treatment guidelines for EGFR-mutant NSCLC. This study discussed the potential mechanisms of drug resistance against first-line TKI treatment and potential successive treatment strategies. Next-generation sequencing (NGS) may play a role in the evaluation of drug resistance in first-line TKI treatment. Emerging combination regimens and ongoing trials were discussed. Potential future strategies for treatment and for the management of drug resistance were proposed in this study.
Leptin Levels and Bone Mineral Density: A Friend or a Foe for Bone Loss? A Systematic Review of the Association Between Leptin Levels and Low Bone Mineral Density
Authors: Cosme Dina , Gomes Ana Cordeiro
Published: February 2025

The introduction of CFTR modulators in the clinics has improved body mass index in cystic fibrosis (CF) individuals. Leptin is a major regulator of appetite and energy expenditure but is also involved in bone metabolism. Whether circulating leptin levels are associated with low bone mineral density (BMD) and fracture risk in CF remains unknown. Therefore, the present study aims to analyze and integrate the current evidence linking leptin and bone loss in CF. As no scientific evidence was found, we focused on secondary dysregulations of bone loss in CF that may be linked to pathologies that are similar to the various dysregulations and multisystemic manifestations in CF. Studies published from 2001 to 2022 were identified through the PubMed, Scopus, and Web of Science databases, and screening was performed following the PRISMA guidelines. The included studies were assessed using a quality checklist. From the 774 records identified, 28 studies met the inclusion criteria. Although no evidence has been found directly related to bone loss in CF individuals, some studies revealed a positive association between leptin levels and BMD, while others found an inverse association. Current evidence suggests that for circulating leptin levels to be a predictive biomarker of bone health, further research will be needed to reveal the direct and indirect mechanisms behind leptin and bone loss and to understand whether changes in leptin levels correlate with changes in BMD. Of note, studies with CF people would be of high importance to understand the role of leptin in CF-related bone disease.
Molecular Insights into Cardiovascular Disease: Unraveling Pathways for Diagnosis and Treatment
Authors: Yamanouchi Dai
Published: February 2025

Cardiovascular diseases remain a leading cause of morbidity and mortality worldwide, with aneurysmal diseases standing out as particularly insidious threats [...]
Epigenetic Regulation of ZNF687 by miR-142a-3p and DNA Methylation During Osteoblast Differentiation and Mice Bone Development and Aging
Authors: Varela Débora , Varela Tatiana , Conceição Natércia , Cancela M. Leonor
Published: February 2025

Zinc finger protein 687 (ZNF687), a transcription factor implicated in osteoblast/osteoclast differentiation and linked to Paget’s disease of bone, has unclear mechanisms in bone metabolism. Epigenetic disruptions can affect bone cell activity and contribute to bone-related diseases. This work aimed to elucidate the regulatory role of epigenetics in modulating Zfp687 expression throughout osteoblast differentiation and bone growth/aging in mice. Differentiation of the mouse-derived osteoblast precursor cell line (MC3T3-E1) showed increased expression of osteogenic markers and decreased Zfp687 expression. In the hindlimb bones of C57BL/6J mice, the expression of most bone-forming genes decreased from youth to adulthood, while Zfp687 and Runx2 expression was maintained, being only significantly reduced in old mice in comparison to young mice. Bisulfite sequencing revealed hypomethylation of the Zfp687 promoter during MC3T3-E1 differentiation and bone growth/aging. Bioinformatics predicted miR-142a-3p, miR-122b-5p, and miR-124-3p binding sites in Zfp687 3′UTR, and RT-qPCR analysis showed higher expression of these miRNAs in mature osteoblasts. Transfection of a miR-142-3p mimic reduced luciferase activity in the wildtype Zfp687 3′UTR but not the mutant 3′UTR and downregulated the Zfp687 gene and protein levels. In conclusion, miR-142a-3p directly targets the Zfp687 3′UTR, promoting its downregulation during osteoblastogenesis. Furthermore, DNA methylation does not appear to regulate Zfp687 during osteoblast differentiation or bone development in mice.
Nanoplastics as Gene and Epigenetic Modulators of Endocrine Functions: A Perspective
Authors: Aloisi Massimo , Poma Anna Maria Giuseppina
Published: February 2025

Nanoplastics (NPs) represent a major challenge in environmental contamination resulting from the physical, chemical, and biological degradation of plastics. Their characterization requires advanced and expensive methods, which limit routine analyses. The biological effects of NPs depend on their chemical and physical properties, which influence toxicity and interactions with biological systems. Studies in animal models, such as Daphnia magna and Danio rerio, show that NPs induce oxidative stress, inflammation, DNA damage, and metabolic alterations, often related to charge and particle size. NPs affect endocrine functions by acting as endocrine disruptors, interfering with thyroid and sex hormones and showing potential transgenerational effects through epigenetic modifications, including DNA hyper- and hypomethylation. Behavioral and neurofunctional alterations have been observed in Danio rerio and mouse models, suggesting a link between NP exposure and neurotransmitters such as dopamine and serotonin. Despite limited human studies, the presence of NPs in breast milk and placenta underscores the need for further investigation of health effects. Research focusing on genetic and epigenetic markers is encouraged to elucidate the molecular mechanisms and potential risks associated with chronic exposure.
Machine Learning Methods for Classifying Multiple Sclerosis and Alzheimer’s Disease Using Genomic Data
Authors: Arnal Segura Magdalena , Bini Giorgio , Krithara Anastasia , Paliouras Georgios , Tartaglia Gian Gaetano
Published: February 2025

Complex diseases pose challenges in prediction due to their multifactorial and polygenic nature. This study employed machine learning (ML) to analyze genomic data from the UK Biobank, aiming to predict the genomic predisposition to complex diseases like multiple sclerosis (MS) and Alzheimer’s disease (AD). We tested logistic regression (LR), ensemble tree methods, and deep learning models for this purpose. LR displayed remarkable stability across various subsets of data, outshining deep learning approaches, which showed greater variability in performance. Additionally, ML methods demonstrated an ability to maintain optimal performance despite correlated genomic features due to linkage disequilibrium. When comparing the performance of polygenic risk score (PRS) with ML methods, PRS consistently performed at an average level. By employing explainability tools in the ML models of MS, we found that the results confirmed the polygenicity of this disease. The highest-prioritized genomic variants in MS were identified as expression or splicing quantitative trait loci located in non-coding regions within or near genes associated with the immune response, with a prevalence of human leukocyte antigen (HLA) gene annotations. Our findings shed light on both the potential and the challenges of employing ML to capture complex genomic patterns, paving the way for improved predictive models.
Rodent Models of Diabetic Neuropathy, Role of Calcium Homeostasis in Pain and KB-R7943 as a Potential Therapeutic
Authors: Ivanova Natasha , Hristov Milen , Gateva Pavlina
Published: February 2025

Diabetic neuropathy (DN) is characterized by nerve damage as a consequence of diabetes mellitus. Diabetes causes high blood glucose and triglyceride levels, which destroy the nerve blood vessels over time and trigger DN. Peripheral neuropathy is the most common type of DN, which encompasses a broad range of symptoms. One fourth of patients with diabetes suffer from neuropathic pain, which decreases their quality of life and puts them at high risk for emotional disturbances and depression. Finding an adequate therapy is an essential element in the cure of painful DN (PDN). Since the pathophysiology of this disease still needs to be elucidated, this has led to the development of various in vivo diabetic models. Animal models of DN not only provide insights into this disease but also are significant drivers for treatment assessment and improvement. In this review, we present the major features of the most commonly used chemically and diet-induced models of PDN in rodents and their progress to date, which are utilized for a better understanding of the disease mechanism for finding novel therapeutics. Considering the role of Ca2+ homeostasis in pain, we also review our recent research data on the Na+/Ca2+ exchanger blocker KB-R7943, which is a potential neuropathic pain reliever in a rodent model of DN.
The Multifaceted Role of Macrophages in Biology and Diseases
Authors: Brancewicz Jan , Wójcik Natalia , Sarnowska Zuzanna , Robak Julia , Król Magdalena
Published: February 2025

Macrophages are highly adaptable immune cells capable of responding dynamically to diverse environmental cues. They are pivotal in maintaining homeostasis, orchestrating immune responses, facilitating tissue repair, and, under certain conditions, contributing to disease pathogenesis. This review delves into the complex biology of macrophages, highlighting their polarization states, roles in autoimmune and inflammatory diseases, involvement in cancer progression, and potential as therapeutic targets. By understanding the context-dependent functional plasticity of macrophages, we can better appreciate their contributions to health and disease, paving the way for innovative therapeutic strategies.
Lumbopelvic Fixation: How to Be Less Invasive When You Cannot Be Minimally Invasive—A New Subcutaneous Supra-Fascial Approach to Minimize Open Iliac Screwing
Authors: Brembilla Carlo , Stucchi Emanuele , De Robertis Mario , Cracchiolo Giorgio , Baram Ali , Capo Gabriele , Rossini Zefferino , Franzini Andrea , Riva Marco , Pessina Federico , Fornari Maurizio
Published: February 2025

Background/Objectives: Lumbopelvic fixation (LPF) is essential for stabilizing the lumbosacral junction (LSJ) in cases of trauma, tumors, and other pathologies. While minimally invasive percutaneous techniques are preferred when feasible, open LPF remains necessary when direct sacral access is required. This study describes a modified open LPF technique designed to minimize invasiveness while maintaining effective stabilization. Methods: We present a case of sacral metastasis requiring LPF. The surgical technique involves a linear midline incision, meticulous subfascial dissection to preserve the Longissimus thoracis and Iliocostalis lumborum muscles, and a subcutaneous supra-fascial approach for iliac screw placement guided by intraoperative CT navigation. A U-shaped cross-link is used for final construct stability. The case illustrates the application of this technique in a 56-year-old female patient with metastatic breast carcinoma involving the sacrum, complicated by nerve compression and urinary retention. Results: The patient underwent successful LPF with nerve root decompression and partial tumor resection. Postoperatively, she experienced no new neurological deficits and demonstrated progressive improvement in sphincter function. The described surgical approach minimized soft tissue disruption, blood loss, and potential complications associated with more extensive dissection. Six-month follow-up CT scans confirmed the stability of the LPF construct and the residual lesion. Conclusions: When open LPF is unavoidable, the described subcutaneous supra-fascial approach for iliac screw placement, combined with muscle preservation and a U-shaped cross-link, offers a less invasive alternative that minimizes soft tissue trauma, reduces potential complications, and facilitates faster patient recovery. This technique can be particularly beneficial in patients with sacral metastases requiring nerve decompression and tumor resection.
The Temporal Distribution and Microbial Spectrum in Infectious Keratitis: A Comprehensive Single-Center Study
Authors: Yamada Naoyuki , Iwamoto Nanako , Sakuma Ayano , Sunada Junki , Aoki Ren , Mikuni Masanori , Higashijima Fumiaki , Yoshimoto Takuya , Morita Yukiko , Kimura Kazuhiro
Published: February 2025

Purpose: To elucidate pathogen-specific seasonal patterns in infectious keratitis through a comprehensive long-term analysis of microbiologically proven cases in a Japanese tertiary care center. Methods: This retrospective study analyzed 500 consecutive cases of culture-proven infectious keratitis diagnosed and treated by corneal specialists at Yamaguchi University Hospital between 2009 and 2021. Seasonal distribution patterns were analyzed for each pathogen category and specific microorganisms. Results: Among the 500 cases, bacteria were identified in 249 eyes (49.8%), viruses in 173 eyes (34.6%), fungi in 51 eyes (10.2%), and Acanthamoeba in 27 eyes (5.4%). The top 10 causative microorganisms constituted 80.4% of all cases. Distinct seasonal patterns emerged: bacterial keratitis peaked during winter months (October–March), Pseudomonas aeruginosa infections clustered in late summer (August–September), Acanthamoeba keratitis showed summer predominance (June–August), and HSV keratitis was most frequent in winter to spring (January–May). Overall incidence peaked from January to March and reached its nadir in June. Conclusions: This long-term study revealed distinct seasonal patterns for specific pathogens causing infectious keratitis in Japan. The findings suggest that geographical location and climate may influence the temporal distribution of corneal infections. These pathogen-specific seasonal trends could aid in the preliminary diagnosis and empirical treatment of infectious keratitis.
Effects of Scanning Strategies, Part Orientation, and Hatching Distance on the Porosity and Hardness of AlSi10Mg Parts Produced by Laser Powder Bed Fusion
Authors: Dejene Naol Dessalegn , Tucho Wakshum Mekonnen , Lemu Hirpa G.
Published: February 2025

Laser powder bed fusion (L-PBF) shows potential in metal additive manufacturing for producing complex components. However, achieving ideal hardness and minimizing porosity poses a significant challenge. This study explores the impact of part orientation, scanning methods, and hatching distance on the hardness and porosity of AlSi10Mg alloy produced through L-PBF. Utilizing a Box–Behnken design of experiments (DOE), cubic samples were systematically produced. Hardness was quantitatively assessed using Vickers hardness tests, while porosity measurements involved 2D image analysis of polished scanning electron microscopy (SEM) samples, the porosity percentages analyzed using ImageJ software. The results demonstrate that both scanning strategy and hatching distance significantly influence hardness and porosity. The spiral scanning pattern notably enhances hardness and reduces porosity. In contrast, the bidirectional scanning strategy results in lower hardness and more pronounced porosity formations. An inverse correlation between grain size distribution and hardness was observed, with finer grain sizes leading to higher hardness values, indicating that grain refinement improves mechanical properties. Additionally, a negative relationship between hardness and porosity was established, emphasizing the importance of minimizing porosity to enhance material hardness. These findings contribute to the overall understanding of the L-PBF additive manufacturing process, providing valuable insights for optimizing material properties and ensuring the mechanical integrity of high-performance L-PBF produced metal parts.
A Study on the Application of Shore-Side Power as a Method to Reduce the Emissions of Greenhouse Gases by Cruise Ships
Authors: Rogosic Mislav , Stanivuk Tatjana , Lucaci David
Published: February 2025

The essence of this work is to explore the potential of shore-side power as a sustainable and efficient solution for mitigating greenhouse gas emissions from passenger ships during their berthing periods in ports. Cruise ships—including both cruise liners and ferries—are significant contributors to port-based emissions because they rely on onboard auxiliary engines to generate power while docked. This practice results in the continuous release of greenhouse gases, such as carbon dioxide, and other pollutants, including nitrogen oxides and sulfur oxides, which contribute to environmental degradation and pose public health concerns in port cities. The objective of this study is to highlight the critical role of shore-side power in decarbonizing the maritime industry and in helping achieve global climate targets. By addressing environmental, technical, and economic aspects, the research aims to provide a comprehensive framework for decision-makers, port authorities, and shipping companies to adopt this technology as a key measure for reducing emissions from cruise ships. Furthermore, this study investigates the multifaceted impacts of shore-side electricity—focusing on its long-term environmental, economic, and social implications—by analyzing case studies from ports that have successfully implemented this technology and by examining the barriers to its broader adoption. Ultimately, this research seeks to provide actionable insights for policymakers, port authorities, and shipping companies.
Development of a Power Calculation Model of Hybrid-Sized Wave Energy Converter Arrays
Authors: Fan Anru , Zhang Huibo , Zhang Yijia , Liu Junchen , Yao Jinming
Published: February 2025

Because of its reliability, large reserves, and high safety standards, wave energy power generation has become an important part of the renewable energy industry. Hybrid-sized wave energy converter arrays consist of floats of different sizes. They have higher output power and stability and are the future development direction of wave power generation. However, the energy-absorbing floats in existing power calculation models are still in a traditional uniform-size configuration and cannot accurately calculate the energy generated by hybrid-sized wave energy converter arrays. In this paper, a time-domain power calculation model of hybrid-sized wave energy converter arrays is proposed. Based on linear wave theory, a frequency-domain hydrodynamic model is constructed and transformed into a time-domain model. The time-domain characteristics and influencing factors of wave energy converters are analyzed. Finally, a time-domain power calculation model of hybrid-sized wave energy converter arrays is established. Based on the irregular model setting and water entry conditions, an experimental verification study on the power calculation model is carried out using the wave energy converter previously developed by the research team. The results show that the average error of the power calculation model proposed in this paper is less than 10%, demonstrating the accuracy of the model.
Order Book Liquidity on Crypto Exchanges
Authors: Angerer Martin , Gramlich Marius , Hanke Michael
Published: February 2025

We analyze intraday liquidity for a range of cryptocurrencies across different exchanges. Among the liquidity measures used, order book variation is most interesting for crypto traders, as it directly impacts their profit/loss. We find evidence that order book variation can be explained by liquidity measures indicating that trades are timed. We report various liquidity patterns that allow traders to increase their profits by minimizing liquidity-dependent trading costs. We further find indications that crypto exchanges can control liquidity by the number of offered currency pairs.
Strategic Approaches to Sustainable Rural Development by Harnessing Endogenous Resources to Improve Residents’ Quality of Life
Authors: Iagăru Romulus , Concioiu Nicolae , Șipoș Anca , Iagăru Pompilica , Băluță Achim Daniel , Vasile Andrei
Published: February 2025

The sustainable development of the Romanian countryside follows strategies outlined in the Common Agricultural Policy. This policy aims to ensure the sustainability of agricultural and non-agricultural businesses, improving inhabitants’ quality of life. Achieving sustainable development is the objective of every rural locality in Romania. This is accomplished by determining the state of endogenous resources and identifying potential conservation and sustainable exploitation alternatives by developing relevant strategic options. The purpose of this research is to develop relevant strategic options for the sustainable rural development of Gușoeni Commune, Vâlcea County, by using the case study methodology and involving stakeholders and community members. In this study, we develop an integrated and dynamic model based on information from a secondary analysis of statistical data and the specialized literature, with the help of the PESTEL (political, economic, social, technological, ecological, legislative), SWOT (strengths, weaknesses, opportunities, and threats), problem tree, objective tree, and DFPSIR (drivers, pressure, status, impact, response) diagnostic models.
Influence of Thinning on Carbon Balance in Natural Regeneration of Pinus pinaster in Portugal
Authors: Sandim André , Lopes Domingos , Louzada José Luis , Silva Maria Emília
Published: February 2025

The maritime pine (Pinus pinaster) is the main conifer species in Portugal, occurring mainly in the central and northern regions of the country. In addition to its environmental significance, it plays an important socio-economic role, supported by a robust forest sector. In the face of climate change driven by the release of CO2 into the atmosphere, forests play an essential role in mitigating these changes by storing large amounts of carbon in their biomass. This study assesses the impact of forest management, focusing on thinning, on carbon accumulation in naturally regenerating maritime pine forests in the municipality of Boticas, Portugal and compares scenarios with and without forest intervention. To simulate forest growth scenarios, the Modispinaster software is used, and through mathematical models adjusted for the species and input of initial field data, it generates scenarios of forest evolution regarding biomass and carbon accumulation. Additionally, it allows for the visualization of the forest’s dendrometric characteristics throughout the cycle, enabling the creation of the carbon balance and its analysis across multiple scenarios. The results demonstrate that management based on thinning increases carbon retention, reducing early mortality and promoting the growth of larger diameter trees. Although natural forests initially accumulate more carbon, the reduction in competition in managed forests allows for greater carbon accumulation from the 24th year onwards, reaching 178 tons at the end of the cycle, in contrast to 143 tons in unmanaged areas. The carbon balance result in the unmanaged (natural) forest was negative (−18 tons), while in the managed forest, the result was positive (54 tons). This supports the thesis that thinning, although more intense and less frequent than mortality events, is more effective than the absence of interventions. Thinned forests optimize the carbon balance in Pinus pinaster, improving long-term retention by reducing competition and mortality. Managed forests show a positive carbon balance, highlighting the importance of sustainable management in mitigating climate change and strengthening ecological resilience.
Hydrogen Embrittlement of a T95 Low-Alloy Steel Charged by Electrochemical Method
Authors: Paterlini Luca , Vergani Laura , Ormellese Marco , Curia Arianna , Re Giorgio , Bolzoni Fabio
Published: February 2025

The hydrogen embrittlement of a typical Oil Country Tubular Good (OCTG) steel, API 5CT T95, was investigated through electrochemical hydrogen pre-charging followed by mechanical testing. J-integral and tensile tests were performed on electrochemically pre-charged samples, with varying charging conditions to simulate different hydrogen environmental exposure. Hydrogen concentration profiles during the electrochemical hydrogen charging process and subsequent mechanical testing in air were calculated with the support of hydrogen permeation tests and Finite Elements Method (FEM) mass diffusion analysis. This approach enabled a deeper understanding of the actual impact of hydrogen on the assessed mechanical properties. The results were compared with tests performed in air and with data available in the literature and were critically analyzed and discussed. A toughness reduction of up to 60% was observed under the most severe charging conditions; however, the alloy retained good ductility with a critical stress intensity factor of 124 MPa√m, well above the minimum values required for pipelines in high-pressure hydrogen gas and sour service applications, 55 MPa√m and 30 MPa√m, respectively, as specified by current ASME Standard and EFC Guidelines. Tensile tests on pre-charged specimens exhibited certain limitations due to the rapid hydrogen desorption rate with respect to the time required to conduct proper slow strain-rate tests.
Melting of AuPd Nanoparticles Revisited: Geometry and Size Effects
Authors: Soria-Sánchez Andrés , Rayas Miguel Angel , Ruiz-Aldana Antonio , de la Rosa-Abad Juan Andrés , Mejía-Rosales Sergio
Published: February 2025

The thermal stability of bimetallic nanoparticles plays a crucial role in their performance in applications in catalysis, biotechnology, and materials science. In this study, we employ molecular dynamics simulations to investigate the melting behavior of Au-Pd nanoparticles with cuboctahedral, icosahedral, and decahedral geometries. Using a tight-binding potential, we systematically explore the effects of particle size and composition on the melting transition. Our analysis, based on caloric curves, Lindemann coefficients, and orientational order parameters, reveals distinct premelting behaviors influenced by geometry. Larger particles exhibit a coexistence of a pseudo-crystalline core and a partially melted shell, but, in decahedra and icosahedra, melting of the core occurs unevenly, with twin boundaries promoting the melting of one or two of the tetrahedral subunits before the rest of the particle. Notably, icosahedral nanoparticles display higher thermal stability, while both icosahedral and decahedral structures exhibit localized melting within twin boundaries. Additionally, we generate HAADF-STEM simulations to aid the interpretation of in situ electron microscopy experiments.