bluuebunny/crossref_metadata_2025 huggingface dataset:
The Mechanical Power in Patients with Acute Respiratory Distress Syndrome Undergoing Prone Positioning Can Predict Mortality
Authors: Chang Ko-Wei , Leu Shaw-Woei , Hu Han-Chung , Chan Ming-Cheng , Liang Shinn-Jye , Yang Kuang-Yao , Chiu Li-Chung , Fang Wen-Feng , Sheu Chau-Chyun , Chien Ying-Chun , Peng Chung-Kan , Huang Ching-Tzu , Kao Kuo-Chin
Published: January 2025

Background/Objectives: Mechanical power (MP) refers to ventilator-delivered energy to the lungs, which may induce lung injury. We examined the relationship between MP and mortality in patients with acute respiratory distress syndrome (ARDS) who underwent prone positioning. Methods: This multicenter retrospective study included data on all patients admitted to the intensive care units of eight referral hospitals in Taiwan from October 2015 to March 2016, and in Chang Gung Memorial Hospital Linkou branch from January 2017 to October 2023. The data were obtained from the electronic medical records of each hospital by using a standard case report form. MP was calculated as follows: MP (J/min) = 0.098 × VT × RR × (Ppeak − 1/2 × ΔP). Results: We included 135 patients who underwent prone positioning. Among them, 28-day survivors had significantly lower MP (22.6 ± 6.5 vs. 25.3 ± 6.2 J/min, p = 0.024), MP/predicted body weight (PBW) (396.9 ± 118.9 vs. 449.3 ± 118.8 10−3 J/min/kg, p = 0.018), MP/compliance values (0.8 ± 0.3 vs. 1.1 ± 0.4 J/min/mL/cmH2O, p = 0.048) after prone positioning, and significantly lower changes in MP, MP/PBW, and MP/compliance (−0.6 ± 5.7 vs. 2.5 ± 7.4 J/min, p = 0.007; −9.2 ± 97.5 vs. 42.1 ± 127.9 10−3 J/min/kg, p = 0.010; −0.1 ± 0.3 vs. 0.2 ± 0.3 J/min/mL/cmH2O, p < 0.001, respectively). Multivariate Cox regression revealed that the change in MP/compliance (HR: 7.972, p < 0.001) was an independent predictive factor for 28-day mortality. Conclusions: In ARDS patients treated with prone positioning, MP/compliance, and change in MP, MP/PBW, and MP/compliance after prone positioning differed significantly between 28-day survivors and nonsurvivors. Further randomized controlled research is required to elucidate the potential causality of decreased MP and improved clinical outcomes.
Factors Influencing the Development of Metachronous Fractures in Patients with Osteoporotic Vertebral Fractures Treated with Conservative Management or Vertebroplasty
Authors: Ruiz Santiago Fernando , Bueno Caravaca Lucía , Garrido Sanz Francisco , Jiménez Gutiérrez Paula María , Luengo Gómez David , Rivera Izquierdo Mario , Benítez José Manuel , Láinez Ramos-Bossini Antonio Jesús
Published: January 2025

Objectives: We aimed to analyze potential predictors for the development of metachronous fractures (MFs) after osteoporotic vertebral fractures (OVFs), with particular focus on radiological variables obtained at initial X-rays and computed tomography (CT) examinations, treatment applied (conservative management [CM] versus percutaneous vertebroplasty [PV]), and fractures located at the thoracolumbar junction (T11-L2). Methods: We conducted a two-center, observational retrospective study, including patients with single-level OVFs treated with CM or VP. We collected socio-demographic, radiological and treatment-related variables. We performed descriptive and contrastive bivariate analyses based on the presence of MFs and univariate and multivariate logistic regression analyses to obtain adjusted and crude odds ratios (aOR and cOR, respectively) for predicting MFs. Finally, we performed receiver-operating characteristic (ROC) curve analyses to determine the discriminative power of the models obtained. Results: Of the 90 patients included, 20 (22.2%) developed one or more MFs (15 in CM and 5 in PV groups, respectively; p = 0.037). The treatment group (aOR for PV, 0.087; 95%CI, 0.015–0.379), presence of intravertebral cleft (aOR, 5.62; 95%CI, 1.84–19.2) and difference in posterior height loss between X-rays and CT (aOR, 0.926; 95%CI, 0.856–0.992) were identified as significant predictors for MFs, while Genant’s numerical classification showed a trend toward significance (aOR, 1.97; 95%CI, 0.983–4.19; p = 0.064). A multivariate model combining these four variables showed optimal fitting and correctly discriminated over 80% of cases (AUC, 0.828; 95%CI, 0.725–0.930). Factors associated with MFs in thoracolumbar junction OVFs were intravertebral cleft, CM, posterior height loss in CT, and DGOU OF3 fractures. Conclusions: The presence of intravertebral cleft, a difference in posterior height loss between X-rays and CT equal to or lower than 2.4%, higher grades of Genant’s numerical classification, and application of CM instead of PV are predictors of MFs. These findings improve our understanding of the factors involved in the development of MFs, but they need to be validated prospectively.
UAV Data Collection Co-Registration: LiDAR and Photogrammetric Surveys for Coastal Monitoring
Authors: Giordano Carmen Maria , Girelli Valentina Alena , Lambertini Alessandro , Tini Maria Alessandra , Zanutta Antonio
Published: January 2025

When georeferencing is a key point of coastal monitoring, it is crucial to understand how the type of data and object characteristics can affect the result of the registration procedure, and, above all, how to assess the reconstruction accuracy. For this reason, the goal of this work is to evaluate the performance of the iterative closest point (ICP) method for registering point clouds in coastal environments, using a single-epoch and multi-sensor survey of a coastal area (near the Bevano river mouth, Ravenna, Italy). The combination of multiple drone datasets (LiDAR and photogrammetric clouds) is performed via indirect georeferencing, using different executions of the ICP procedure. The ICP algorithm is affected by the differences in the vegetation reconstruction by the two sensors, which may lead to a rotation of the slave cloud. While the dissimilarities between the two clouds can be minimized, reducing their impact, the lack of object distinctiveness, typical of environmental objects, remains a problem that cannot be overcome. This work addresses the use of the ICP method for registering point clouds representative of coastal environments, with some limitations related to the required presence of stable areas between the clouds and the potential errors associated with featureless surfaces.
Predicting Convergence of Per Capita Income in Spain: A Markov and Cluster Approach
Authors: Gálvez-Rodríguez José F. , Manzano-Hidalgo Miguel , García-Luengo Amelia V.
Published: January 2025

In this work we analyze the evolution of productivity, in terms of the convergence of per capita income, of all the Spanish provinces, based on data from the previous decade. On the one hand, a cluster analysis allows us to group the Spanish provinces according to four income levels (low, medium-low, medium-high and high), which can be determined from the quartiles of the distribution, and, on the other hand, Markov chains make it possible to study the long-term evolution of productivity and convergence between the provinces, as well as the speed of convergence towards the equilibrium situation. Moreover, we can obtain the average time to return to an income level in which a province was previously. With the above, predictions of future income levels are made for the provinces, both in the current situation, and if the pandemic caused by COVID-19 had not existed, which leads us to evaluate the impact of the health emergency.
Comparative Analysis of the Corrosion Behavior of Plain and Nanoporous Copper
Authors: Lei Zhen , Mull Ksenya , Dimitrov Nikolay
Published: January 2025

This research investigates the corrosion behavior of copper (Cu) through a comprehensive analysis of both plain and nanoporous Cu thin films. A combination of weight-loss methods for quantitative analysis, along with polarization testing and scanning electron microscopy, is employed for both quantitative and qualitative assessments of Cu corrosion dynamics. The corrosion mechanisms in chloride and nitrate solutions are compared, with an additional discussion on the influence of atmospheric oxygen (O2). The results demonstrate that chloride ions and the presence of O2 create the most severe corrosion conditions, while the concentration of salts has a relatively minor effect on the corrosion behavior. Notably, the comparative study reveals that nanoporous Cu exhibits a greater corrosion tendency, as indicated by more negative corrosion potentials. However, its corrosion rates are lower than those of plain Cu, as determined by corrosion current density measurements.
Load Sensitivity Correlation Factor-Based Steady-State Power Flow Allocation Method for Independent DC Bus Structure Multiport Power Electronic Transformer
Authors: Li Junchi , Wu Junyong , Xiong Fei , Hao Liangliang
Published: January 2025

The independent DC bus structure multiport power electronic transformer (IDBS-MPET) is a novel power electronic transformer designed to integrate multiple DC sources and DC loads. Due to the configuration of DC ports, which are directly constructed by the parallel connection of dual active bridge (DAB) converters, the distribution of DC sources and DC loads among the three phases becomes unbalanced. In cases where the load power at certain ports is too high, this imbalance may lead to the over-modulation of the front-end H-bridge (HB). Since the output power at a certain port in the IDBS-MPET is constrained by the loads at other ports, this paper proposes a multiport steady-state power flow allocation method. This method establishes the load sensitivity correlation factor to enable all the ports to adjust power cooperatively based on it. By applying the proposed steady-state power flow allocation method, iterative calculations continuously update the priority of all the ports and their load sensitivity correlation factors. This process ensures that the power flow converges to a steady-state solution. Simulation results for two different IDBS-MPETs demonstrate that the power flow at all the ports effectively meets load requirements, while the front-end HB avoids over-modulation, ensuring the safe and stable operation of the IDBS-MPET. The results validate the effectiveness of the proposed steady-state power flow allocation method.
PREmbed: Balancing Conditional Generative Models with Embedding Pretraining and Regularization
Authors: Liu Haiyang , Endo Yuki , Lee Jinho , Kamijo Shunsuke
Published: January 2025

Recent advancements in conditional generative models, e.g., Conditional Variational AutoEncoder (CVAE) and Conditional Denoising Diffusion Probabilistic Model (CDDPM), which utilize class-specific embeddings for generating images in specific classes, have demonstrated exceptional capabilities in producing high-quality images on balanced datasets. However, their performance decreases with imbalanced real-world data, affecting the fidelity and diversity of the generated images. This paper discusses the reasons and solutions for the imbalance issue in CVAE and CDDPM. By selectively reweighting the gradients of the embedding layer and main network, we identify the embedding layer’s bias as a critical bottleneck in these models. Motivated by this, we propose Embedding Pretraining and Regularization (PREmbed), a training methodology for addressing biased learning in the embedding layer of these models. PREmbed consists of two key components: (i) Masked Autoencoder pretraining on the original imbalanced dataset to obtain a robust initial embedding, and (ii) an embedding regularization loss to preserve class-level distances during the training phase to improve imbalanced embedding learning. Implementing PREmbed leads to the enhanced convergence of a robust embedding layer. Our experiments on imbalanced CIFAR-10 and CUB-200 datasets demonstrate that PREmbed enhances the performance of CVAE and CDDPM; it outperforms the baseline CVAE by 22.3% (FID 18.63) and the CDDPM by 30.3% (FID 12.70) in imbalanced CIFAR-10; 33.7% (FID 24.08) and 26.5% (FID 13.90) in CUB-200; and 16.4% (FID 49.41) and 15.2% (FID 33.05) in ImageNet-LT (which is where it achieves the state-of-the-art performance in imbalanced conditional image generation task).
Semaphore Recognition Using Deep Learning
Authors: Huan Yan , Yan Weiqi
Published: January 2025

This study explored the application of deep learning models for signal flag recognition, comparing YOLO11 with basic CNN, ResNet18, and DenseNet121. Experimental results demonstrated that YOLO11 outperformed the other models, achieving superior performance across all common evaluation metrics. The confusion matrix further confirmed that YOLO11 exhibited the highest classification accuracy among the tested models. Moreover, by integrating MediaPipe’s human posture data with image data to create multimodal inputs for training, it was observed that the posture data significantly enhanced the model’s performance. Leveraging MediaPipe’s posture data for annotation generation and model training enabled YOLO11 to achieve an impressive 99% accuracy on the test set. This study highlights the effectiveness of YOLO11 for flag signal recognition tasks. Furthermore, it demonstrates that when handling tasks involving human posture, MediaPipe not only enhances model performance through posture feature data but also facilitates data processing and contributes to validating prediction results in subsequent stages.
The Temporal and Spatial Evolution of Flow Heterogeneity During Water Flooding for an Artificial Core Plate Model
Authors: Jiang Chen , Liu Qingjie , Leng Kaiqi , Zhang Zubo , Chen Xu , Wu Tong
Published: January 2025

In the process of reservoir water flooding development, the characteristics of underground seepage field have changed, resulting in increasingly complex oil–water distribution. The original understanding of reservoir physical property parameters based on the initial stage of development is insufficient to guide reservoir development efforts in the extra-high water cut stage. To deeply investigate the spatio-temporal evolution of heterogeneity in the internal seepage field of layered reservoirs during water flooding development, water–oil displacement experimental simulations were conducted based on layered, normally graded models. By combining CT scanning technology and two-phase seepage theory, the variation patterns of heterogeneity in the seepage field of medium-to-high permeability, normally graded reservoirs were analyzed. The results indicate that the effectiveness of water flooding development is doubly constrained by differences in oil–water seepage capacities and the heterogeneity of the seepage field. During the development process, both the reservoir’s flow capacity and the heterogeneity of the seepage field are in a state of continuous change. Influenced by the extra resistance brought about by multiphase flow, the reservoir’s flow capacity drops to 41.6% of the absolute permeability in the extra-high water cut stage. Based on differences in the variation amplitudes of oil–water-phase permeabilities, changes in the heterogeneity of the internal seepage field of the reservoir can be broadly divided into periods of drastic change and relative stability. During the drastic change stage, the fluctuation amplitude of the water-phase permeability variation coefficient is 114.5 times that of the relative stable phase, while the fluctuation amplitude of the oil-phase permeability variation coefficient is 5.2 times that of the stable stage. This study reveals the dynamic changes in reservoir seepage characteristics during the water injection process, providing guidance for water injection development in layered reservoirs.
Methodology for the Automatic Generation of Optimization Models of Systems of Flexible Energy Resources
Authors: Wagner Lukas Peter , Gehlhoff Felix , Reinpold Lasse Matthias , Frey Georg , Jepsen Julian , Fay Alexander
Published: January 2025

The integration of increasing shares of intermittent renewable energy necessitates flexibility in both energy generation and consumption. Typically, the operation of flexible energy resources is orchestrated through optimization models. However, the manual creation of these models is a complex and error-prone task, often requiring the expertise of domain specialists. This work introduces a methodology for the automatic generation of optimization models for systems of flexible energy resources to simplify the modeling process and increase the use of energy flexibility. This methodology utilizes a modular, generic model structure designed to depict systems of flexible energy resources. It incorporates algorithms for model parameter derivation from operational data and an information model that represents the system’s structure and dependencies of resources. The efficacy of this methodology is demonstrated in two case studies, highlighting its relevance and ability to significantly streamline the optimization modeling process by minimizing the need for manual intervention.
Construction and Application of Urban Green Space Ecosystem Service Assessment Indicator System and Assessment Method: A Case Study of Chifeng Central Urban Area, China
Authors: Duan Lingling , Niu Xiang , Wang Bing
Published: January 2025

The assessment of urban green space ecosystem services is an important basis for urban ecosystem management and decision-making. To further enhance the accuracy of this evaluation, this paper refers to the main research results of international urban ecosystem service assessment and puts forward the main principles for the construction of an urban green space ecosystem service assessment index system. Based on this principle, the framework of the assessment indicator system was carried out by adopting the expert consultation method and frequency analysis method. This system includes the functions of leisure and recreation and the landscape premium in cultural services, air purification, noise abatement, carbon sequestration, oxygen release, and precipitation storage in regulatory services, and biodiversity conservation in supply services. The assessment methods for each functional category are chosen for their appropriateness, or the inadequacies of the existing methods are refined and improved. Then, we take the urban center of Chifeng City, China, as an example to carry out an empirical study on the urban green space ecosystem service assessment index system and assessment methods proposed in this paper. This study shows that the total value of green space ecosystem services in the downtown area of Chifeng City is CNY 229.91 million (Chinese Yuan). Among them, cultural services, regulating services, and supporting services accounted for 89.62%, 9.06%, and 1.32% of the total value, respectively. This study has important reference significance for the comprehensive quantitative assessment of the ecological service function value of urban green spaces, revealing the socio-economic value of urban green space resources while providing insights and references for the environmental assessment, planning, construction, and management decision-making of urban green spaces.
Genome-Wide Identification of the Uridine Diphosphate Glucotransferase Gene Family and Expression Profiling Analysis in the Stem Development of Prunus mume
Authors: Zhang Jie , Li Xue , Ma Zhiyuan , Huang Yu , Li Ping , Cheng Tangren , Zheng Tangchun
Published: January 2025

Prunus mume, a traditional ornamental species native to China, is highly valued for both its captivating weeping variety and economic value. The glycosylation of metabolites, which is mediated by UDP-glycosyltransferases (UGTs), is essential for the regulation of secondary metabolic pathways in plants. Here, we systematically identified and analyzed the UGTs in P. mume. A total of 182 PmUGTs were identified using genomic data and categorized into 16 distinct subfamilies (A–P). All PmUGTs were distributed unevenly across the eight chromosomes, with clear evidence of tandem duplication. Additionally, synteny analysis revealed a close evolutionary relationship between P. mume and Prunus persica. A promoter cis-acting element analysis indicated that PmUGTs may respond to light, hormones, and external stresses. A heatmap analysis revealed that PmUGTs had specific expression patterns across different tissues, under various hormone treatments, and in different developmental stages of stem lignification. Notably, qRT-PCR verification showed significant differences in PmUGT163 expression between straight and weeping stems, underscoring its role in regulating plant architecture formation. Taken together, our study elucidates the evolutionary trajectory of PmUGTs and lays the groundwork for the further validation of the candidate genes involved in plant architectural formation.
Effects of Forest Swamp Succession and Soil Depth on Distribution Pattern of Soil Nematode Communities
Authors: Xuan Liqiang , Che Lina , Wan Luhe
Published: January 2025

The forest swamp ecosystem, as a special wetland ecosystem, is a key link in the material cycle and an important carbon sink in the carbon cycle. The global carbon cycle is of great significance, but the impact of forest swamp succession and soil depth on soil active organic matter and nematode community structure and diversity is unclear. This study used the “space instead of time” method to investigate the succession process of forest swamps from grasslands (WC) and shrubs (WG) to forests (WS) in national nature reserves. The results showed that during the forest succession process, the dominant nematode communities in the WC and WG stages were dominated by the genera Apis and Labroidei, while the dominant genera increased in the WS stage. The total abundance of nematodes increased, and the number of groups was ordered WG > WC > WS. The diversity in soil nematode communities according to Shannon–Wiener (H′), Pielou (J), and Trophic diversity (TD) was WS > WG > WC, which is related to vegetation, soil physical and chemical properties, and microbial community structure. The maturity index (MI) was WG > WS > WC. The soil food web was dominated by bacterial channels and had characteristics in forest metabolic activity and regulation ability. At different soil depths, there were significant differences in the community, with species such as the spiny cushioned blade genus being key. The number and group size of nematodes varied from 0–10 cm > 10–20 cm > 20–30 cm. The relative abundance of feeding nematodes changed with depth, while diversity indices such as H′, J, and TD decreased with depth. Ecological function indices such as MI and PPI showed depth variation patterns, while basic indices (BI) and channel indices (CI) showed significant differences. In terms of soil variables, during the forest succession stage, soil organic carbon (SOC), soluble organic nitrogen (DON), easily oxidizable organic carbon (ROC), microbial biomass carbon (MBC), and microbial biomass nitrogen (MBN) showed a gradually increasing trend with WC-WG-WS, while total nitrogen (TN), soluble organic carbon (DOC), soil temperature (ST), and soil moisture (SM) showed opposite changes. There were significant differences in soil ST, SM, and DON values with succession (p < 0.05). At different soil depths, except for DON and ROC, which increased first and then decrease with depth, the values of other physical and chemical factors and active carbon and nitrogen components at depths of 0–10 cm were higher than those at other depths and decreased with depth. An analysis of variance showed significant differences in MBC and MBN values at different soil depths (p < 0.05), which is of great significance for a deeper understanding of the mechanism of soil nematode community construction and its relationship with the environment.
Preliminary Study on the Impact of Ruminal Ciliate Inoculation in Fauna-Free Conditions on the Ruminal Fermentation and Ciliate–Prokaryote Association In Vitro
Authors: Kim Geonwoo , Lee Woohyung , Park Tansol
Published: January 2025

Ruminants rely on the rumen for the anaerobic fermentation of fibrous plant materials, facilitated by a complex microbial community of bacteria, archaea, fungi, and ciliates. Among them, ruminal ciliates significantly influence ruminal fermentation, methane production, nitrogen utilization efficiency, and microbial interactions. This study examined the impact of ciliate inoculation on ruminal fermentation, microbial composition, and functional profiles in fauna-free conditions. Six treatments were tested: control (no ciliates), small entodinia, Epidinium spp., isotrichids, Ophryoscolex spp., and a mixed inoculum. Using QIIME2 to analyze 16S rRNA gene sequences, the study revealed group-specific effects on methane production, volatile fatty acids (VFAs), and microbial diversity. Small entodinia inoculation increased Streptococcus abundance, while isotrichids enriched Megasphaera, enhancing butyrate production. Alpha diversity indices indicated reduced richness in the ciliate-inoculated groups, reflecting predation on prokaryotes. Beta diversity showed distinct microbial and functional profiles among the treatments. Functional analysis highlighted elevated glycerolipid metabolism in isotrichid groups, associated with Bacteroides and Megasphaera, suggesting roles in lipid metabolism and oxidative stress resistance. Despite limited ciliate cell counts, the study emphasizes ciliate-specific interactions and the role of lactic acid-associated bacteria in shaping ruminal fermentation.
A Comparative Analysis of YOLOv9, YOLOv10, YOLOv11 for Smoke and Fire Detection
Authors: Alkhammash Eman H.
Published: January 2025

Forest fires cause extensive environmental damage, making early detection crucial for protecting both nature and communities. Advanced computer vision techniques can be used to detect smoke and fire. However, accurate detection of smoke and fire in forests is challenging due to different factors such as different smoke shapes, changing light, and similarity of smoke with other smoke-like elements such as clouds. This study explores recent YOLO (You Only Look Once) deep-learning object detection models YOLOv9, YOLOv10, and YOLOv11 for detecting smoke and fire in forest environments. The evaluation focuses on key performance metrics, including precision, recall, F1-score, and mean average precision (mAP), and utilizes two benchmark datasets featuring diverse instances of fire and smoke across different environments. The findings highlight the effectiveness of the small version models of YOLO (YOLOv9t, YOLOv10n, and YOLOv11n) in fire and smoke detection tasks. Among these, YOLOv11n demonstrated the highest performance, achieving a precision of 0.845, a recall of 0.801, a mAP@50 of 0.859, and a mAP@50-95 of 0.558. YOLOv11 versions (YOLOv11n and YOLOv11x) were evaluated and compared against several studies that employed the same datasets. The results show that YOLOv11x delivers promising performance compared to other YOLO variants and models.
Combined BPA and DIBP Exposure Induced Intestinal Mucosal Barrier Impairment Through the Notch Pathway and Gut Microbiota Dysbiosis in Mice
Authors: Duan Mengge , Wang Yuting , Chen Shiyu , Lu Jiawen , Dong Ruihong , Yu Qiang , Xie Jianhua , Chen Yi
Published: January 2025

Bisphenol A (BPA) and diisobutyl (DIBP) phthalate are widely used as typical plasticizers in food packaging. Plasticizers can be released from polymers, migrate into food, and be ingested by humans, leading to various health problems. However, little research has investigated the combined toxicity of BPA and DIBP, particularly their intestinal toxicity. Our goal is to analyse the combined toxicity of BPA (50 mg/kg) and DIBP (500 mg/kg) on the intestines of KM mice. Additionally, we tried to find natural products that can inhibit or prevent the combined toxicity of BPA and DIBP. The results indicated that the combination of BPA and DIBP exposure resulted in a reduction of beneficial flora, an increase in D-Lac levels (136 ± 14 μmol/L), an increase in intestinal permeability, activation of the notch pathway, and a decline in intestinal stem cells (ISCs) to goblet cells, compared to single-exposure sources. Nevertheless, Rubus chingii Hu phenolic extract (RHPE) (200, 400 and 600 mg/kg) ameliorated the BPA and DIBP-induced intestinal microbiota disruption and intestinal mucosal barrier impairment by inhibiting the overactivation of the notch pathway. The results of this study highlight the potential risks to human health posed by the combination of BPA and DIBP and may help explain the potential pathways of enterotoxicity caused by combined ingestion.
Metabolomics and Lipidomics Reveal the Metabolic Disorders Induced by Single and Combined Exposure of Fusarium Mycotoxins in IEC-6 Cells
Authors: Wang Xinlu , Xu Yanyang , Yu Haiqi , Lu Yushun , Qian Yongzhong , Wang Meng
Published: January 2025

Deoxynivalenol (DON), fumonisin B1 (FB1), and zearalenone (ZEN) are typical fusarium mycotoxins that occur worldwide in foodstuffs, posing significant health hazards to humans and animals. Single and combined exposure of DON, FB1, and ZEN leads to intestinal toxicity but the toxicology mechanism research is still limited. In this study, we explored the cytotoxicity effects of DON, FB1, ZEN, and their combination in rat intestinal epithelial cell line 6 (IEC-6) cells. Cell viability results showed that the cytotoxicity potency ranking was DON > ZEN > FB1. Furthermore, both DON + FB1 and DON + ZEN presented synergism to antagonism effects based on a combination index (CI)-isobologram equation model. Integrated metabolomics and lipidomics was adopted to explore cell metabolism disorders induced by fusarium mycotoxin exposure. A total of 2011 metabolites and 670 lipids were identified. An overlap of 37 and 62 differential compounds was confirmed after single and combined mycotoxin exposure by multivariate analysis, respectively. Some of the differential compounds were endocellular antioxidants and were significantly downregulated in mycotoxin exposure groups, indicating metabolic disorders as well as antioxidant capacity damage in cells. Pathway enrichment analysis annotated ethanol metabolism production of ROS by CYP2E1 was mainly involved in the disturbance of DON, FB1, and ZEN. The results obtained in this study help to define the toxicity effects of DON, FB1, and ZEN singly and in co-existence, providing an important scientific basis for combined risk recognition of mycotoxin contamination.
Injectable Chitosan Hydrogel Particles as Nasal Packing Materials After Endoscopic Sinus Surgery for Treatment of Chronic Sinusitis
Authors: Yamashita Yusuke , Hosoya Kei , Fujiwara Yukio , Saito Yoichi , Yoshida Masahiro , Matsune Shoji , Okubo Kimihiro , Takei Takayuki
Published: January 2025

After endoscopic sinus surgery (ESS), nasal packing is often used to stop bleeding and promote wound healing. Because maintaining a moist environment is important to enhance wound healing, hydrogel-based wound dressings are effective to promote wound healing. Chitosan is used in the medical field because of its high hemostatic and wound healing properties. We developed a pH-neutral and non-toxic chitosan hydrogel, which was difficult to achieve using conventional methods. In this study, we show in animal experiments that the chitosan hydrogel (hydrogel particles) had higher wound healing properties than a commercially available solid wound dressing (dry state) composed of the same polymer. Additionally, we applied the injectable chitosan hydrogel particles as nasal packing materials to patients with bilateral chronic sinusitis undergoing ESS in a pilot clinical study. Concerning symptom scores, though the results narrowly missed statistical differences (p < 0.05), the average scores of our chitosan hydrogel were superior to those of a commercially available wound dressing (especially p = 0.09 for nasal bleeding). These findings suggest that the injectable chitosan hydrogel could be a viable option as a packing material following ESS.
Compound Heterozygous p.(R124C) (Classic Lattice Corneal Dystrophy) and p.(R124H) (Granular Corneal Dystrophy Type 2) in TGFBI: Phenotype, Genotype, and Treatment
Authors: Min Ji Sang , Kim Tae-im , Jun Ikhyun , Stulting R. Doyle , Rho Changrae , Han Sang Beom , Kim Heeyoung , Choi Jinseok , Han Jinu , Kim Eung Kweon
Published: January 2025

(1) Background: The phenotypes of classic lattice corneal dystrophy (LCD) and granular corneal dystrophy type 2 (GCD2) that result from abnormalities in transforming growth factor β-induced gene (TGFBI) have previously been described. The phenotype of compound heterozygous classic LCD and GCD2, however, has not yet been reported. (2) Case report: A 39-year-old male (proband) presented to our clinic complaining of decreased vision bilaterally. A slit-lamp examination revealed corneal opacities consistent with classic LCD. Contrast sensitivity (CS) was decreased. A genetic analysis performed with commercially available real-time polymerase chain reaction (PCR) showed both homozygous classic LCD and homozygous GCD2. Sanger sequencing performed in our lab suggested compound heterozygosity for c.370C>T and c.371G>A variants, which was confirmed by the TA cloning of exon 4 of TGFBI and sequencing of clones. Phototherapeutic keratectomy (PTK) was performed on the right eye of the proband, and the CS improved. (3) Conclusions: Compound heterozygous classic LCD and GCD2 produces clinical findings like that of severe, classic LCD. PTK can improve VA and CS, delaying the need for keratoplasty.
Coupling Driving Force–Pressure–State–Impact–Response–Management Framework with Hydrochemical Data for Groundwater Management on Sithonia Peninsula, Greece
Authors: Parastatidou Eleni , Ntona Maria Margarita , Kazakis Nerantzis , Pliakas Fotios-Konstantinos
Published: January 2025

Water scarcity in coastal tourist areas constitutes a critical environmental and socioeconomic sustainability issue. Hence, it is crucial to implement an integrated water resource management and protection plan. In this research, the DPSIR framework is coupled with hydrochemical data on groundwater resources in the fractured aquifer of the Sithonia Peninsula in Chalkidiki, North Greece. Geographical and demographic data, together with morphology, geology, hydrology, and groundwater quality data, were collected and evaluated to categorize the hydrosystem’s driving forces, pressures, states, impacts, and responses. The main pressures that affect groundwater quality in the study area are tourism, geological formation, and land use. Based on the analysis of the DPSIR framework, the absence of a landfill site, the inadequate operation of sewage treatment plants and biological wastewater treatment systems, and tourist activity contribute significantly to the degradation of groundwater quality. Additionally, the fractured rock aquifer develops preferential flow paths to pollutants through preexisting faults, which influence groundwater quality. The hydrochemical analysis of groundwater indicates seawater intrusion in the coastal area. The combination of DPSIR analysis and a water quality index based on ion ratios of groundwater samples identifies high-risk areas of seawater intrusion. Thus, it is essential to reinforce groundwater resources by implementing managed aquifer recharge, limiting unnecessary use of groundwater during the tourist season, and storing surface water during the wet period.
Machine Learning Approach to Model Soil Resistivity Using Field Instrumentation Data
Authors: Alam Md Jobair Bin , Gunda Ashish , Ahmed Asif
Published: January 2025

Sub-surface soil hydrological characterization is one of the challenging tasks for engineers and soil scientists, especially the complex hydrological processes that combine key variables such as soil moisture, matric suction, and soil temperature. The ability to infer these variables through a singular measurable soil property, soil resistivity, can potentially improve sub-surface characterization. This research leverages various machine learning algorithms to develop predictive models trained on a comprehensive dataset of sensor-based soil moisture, matric suction, and soil temperature obtained from prototype ET covers, with known resistivity values. Different types of sensors were installed at multiple depths in the ET covers, and resistivity tests were conducted periodically at the same location. Cross-validation and feature selection methods were used to optimize model performance and identify key variables that most significantly impact soil resistivity. Strong inverse correlations between soil moisture and resistivity (r = −0.88) and weak positive correlations with temperature (r = 0.41) and suction (r = 0.34) were observed. Among the machine learning models evaluated, artificial neural networks and support vector machines demonstrated superior predictive performance, achieving a coefficient of determination (R2) above 0.77 and lower root mean square error (RMSE) values (less than 0.14). Linear regression and decision tree models exhibited suboptimal performance because of their limitations in capturing non-linear relationships and overfitting, respectively. Random forest demonstrated superior generalization capabilities compared to decision trees; however, it encountered challenges with mid-range data variability. The findings demonstrate the effectiveness of artificial neural networks in predicting field-scale soil resistivity by utilizing hydrological variables.
Hyperbaric Oxygen Therapy in the Treatment of Crohn’s Disease
Authors: Krstulović Jure , Augustin Goran , Romić Ivan , Tavra Ante , Batinović Franko , Hrgović Zrinka
Published: January 2025

Background/Objectives: Our study describes hyperbaric oxygen therapy (HBOT) as an additional therapy in the conservative treatment of Crohn’s disease (CD) and its benefit in the early postoperative period to prevent surgical complications and improve gastrointestinal motility. Methods: This retrospective study evaluated HBOT in patients hospitalized at the Clinical Hospital Center Split for complications of CD between 2015 and 2020. Patients (N = 61) aged 19 to 67 with perianal fistulas, abscesses, fistulas, obstruction, stenosis, or bleeding were included, excluding those with ulcerative colitis or requiring intensive care. Patients were retrospectively divided into conservatively and surgically treated groups, and HBOT was administered over 15–25 days, with treatment lasting 60 min at 2.2 absolute atmospheres (ATA). We analyzed treatment outcomes between the HBOT-treated surgical and conservative groups and compared patients treated with HBOT to a cohort from the preceding five years who did not receive HBOT. Results: We treated 61 CD patients with HBOT, including 34 conservatively and 27 surgically treated patients. HBOT significantly reduced disease activity indices (311.7 ± 59.1 vs. 114 ± 29.8; 203.6 ± 24.1 vs. 83.8 ± 15, for conservatively treated patients, and 352.8 ± 45.7 vs. 109 ± 22.8; 270.4 ± 19.7 vs. 140.3 ± 10.6 for surgically treated patients) and accelerated bowel peristalsis recovery, with 94.1% of conservatively treated patients achieving remission. Comparison with a historical cohort showed faster recovery and improved outcomes in the HBOT group. Conclusions: HBOT is useful in postponing or avoiding surgical treatment, and in operated patients, it improves postoperative recovery and reduces the rate of postoperative complications.
Spinal Alignment and Pain: An Assessment of Amateur Road Cyclists—A Pilot Study
Authors: Kasperek Wojciech , Kielar Aleksandra , Pasierb Mirosław , Vaskova Monika , Ružbarska Beata , Czarny Wojciech , Drużbicki Mariusz
Published: January 2025

Background: Cycling involves specific body positions that, when maintained for prolonged periods, may affect spinal curvature and increase the risk of pain-related issues. This study aimed to evaluate sagittal spinal curvatures, the prevalence of pain in spinal segments, and their interrelation among amateur road cyclists. Methoods: The research included 30 male participants aged 18–48 years. Pain severity was assessed using the Visual Analog Scale (VAS) and Laitinen scale, while spinal curvature was evaluated with an electronic inclinometer. Results: Results showed no statistically significant differences in spinal curvature angles between cyclists with and without pain complaints (p = 0.056). However, tendencies were noted, such as higher mean VAS scores for lower back pain (4.90) compared to neck pain (3.38), and variations in parameters like Beta, LL, and KGP. Conclusions: While the findings did not confirm clear distinctions, they suggest trends indicating potential links between spinal curvatures and pain occurrence. These results underscore the importance of further studies involving larger cohorts to verify these observations and explore the biomechanical adaptations associated with amateur cycling. Insights from such research could inform strategies for preventing and managing spinal pain among cyclists.
The Investigation of Stefan Luchian Heritage Paintings—A Multi-Analytical Approach
Authors: Oancea Andrei Victor , Simionescu Bogdana , Ursu Laura Elena , Murariu Mioara , Dobromir Marius , Geba Maria , Stratulat Lacramioara , Olaru Mihaela
Published: January 2025

Based on a multi-analytical approach involving mobile techniques and lab-based devices (XPS, portable and micro-Raman spectroscopies, and ATR-FTIR spectroscopy, combined with SEM/EDS and optical microscopy), this study presents the first in-depth investigation of two cultural heritage artworks painted by the famous Romanian artist Ștefan Luchian. The research highlights the artist’s use of a wide range of colors, with his palette including classic pigments such as ochers, lead white, barium white, zinc white, and viridian, as well as contemporary colors such as cobalt purple, alizarin crimson, and the little-known indium yellow. Additionally, attempts are made to characterize the binders used in the paintings, which include linseed oil and animal glue. Beyond identifying the types of pigments and materials used by the artist and assessing the degradation stage of the paintings, this study is the first to provide information regarding the use of In2O3 as a yellow pigment in artwork.
Transcriptome Analysis and Phytohormone Profile Reveal Core Phytohormone Regulating Parthenocarpy in Fingered Citron
Authors: Chen Qianbin , Xu Jinjian , Zou Xinjian , Zhang Yanjun , Zhu Xiaoxian , Zhang Kewei , Chen Wenrong , Liao Fanglei , Guo Weidong
Published: January 2025

Parthenocarpy, the development of fruit without fertilization, is a significant trait in fingered citron (Citrus medica L. var. sarcodactylis Swingle). This study aims to elucidate the regulatory mechanisms underlying parthenocarpy through comparative transcriptome analysis and phytohormone profiling between fingered citron and its non-parthenocarpic counterpart, citron. A total of 66 differentially expressed hormone-related genes were identified, with the auxin pathway emerging as the most prominent in fingered citron. Protein–protein interaction analysis revealed a potential interaction between auxin and abscisic acid (ABA). Phytohormone content analysis indicated that fingered citron exhibited higher levels of indole-3-acetic acid (IAA) and lower levels of ABA compared to citron. A weighted gene co-expression network analysis (WGCNA) suggested that the interplay between auxin and ABA is crucial for triggering parthenocarpy. Virus-induced gene silencing (VIGS) experiments demonstrated that silencing CmsABI5 led to decreased ABA levels, while auxin levels remained unchanged, resulting in disrupted parthenocarpy and increased ethylene levels, indicating a secondary hormonal response. Additionally, gene expression changes associated with failed parthenocarpy showed down-regulation of SAUR50 and up-regulation of PP2C 56, linking these changes to ABA signaling. Our findings highlight the central regulatory role of auxin in parthenocarpy in fingered citron, with ABA acting as a critical modulator. The suppression of ABA alone disrupts parthenocarpy despite stable auxin levels, emphasizing the necessity of balanced hormone interactions. This research underscores the significant role of auxin, rather than gibberellin (GA), in regulating parthenocarpy in fingered citron, contributing valuable insights to the understanding of fruit development mechanisms.
Background and Clinical Features of a Unique and Mysterious Autoinflammatory Disease, Schnitzler Syndrome
Authors: Műzes Györgyi , Sipos Ferenc
Published: January 2025

Schnitzler syndrome is a unique autoinflammatory disease, of which 747 cases have been described worldwide to date. The main features of the syndrome are a triad of recurrent urticaria, monoclonal IgM gammopathy, systemic inflammation associated with recurrent fever, joint and bone pain, and atypical bone remodeling (osteosclerosis). The abnormal activation of the NLRP3 inflammasome produces IL-1, which drives the disease pathology, but it also involves IL-6 and IL-18. Unlike other autoinflammatory diseases, Schnitzler syndrome lacks evidence of the gene divergence causing the abnormal activation of NLRP3. However, mutations in the MEFV and MYD88 genes can be associated with the development of the disease. Due to its rarity, diagnosing the disease can be a challenging task. IL-1 inhibitors (i.e., anakinra, canakinumab, and rilonacept) are prominent in the treatment of the disease, but the IL-6 receptor inhibitor tocilizumab and the Bruton’s tyrosine kinase inhibitor ibrutinib are also promising alternatives. In this summary article, we aim to provide a comprehensive overview of the clinical and molecular background of the disease and potential therapeutic targets, based on the cases reported so far. We diagnosed a patient who, to the best of our knowledge, represents the 748th documented case of this specific pathology. In the context of this patient, we would also like to draw attention to the potential pathogenic role of two novel gene mutations (variants of the MEFV gene “c.2084A>G” and the F2 gene “3′UTR c.*97G>A”).
The Dps Protein Protects Escherichia coli DNA in the Form of the Trimer
Authors: Kovalenko Vladislav , Tereshkina Ksenia , Moiseenko Andrey , Ryzhykau Yury , Kuklin Alexander , Tereshkin Eduard , Zaytsev Petr , Generalova Anastasiya , Persiyantseva Nadezhda , Sokolova Olga , Krupyanskii Yurii , Loiko Nataliya
Published: January 2025

The Dps protein is the major DNA-binding protein of prokaryotes, which protects DNA during starvation by forming a crystalline complex. The structure of such an intracellular DNA-Dps complex is still unknown. However, the phenomenon of a decrease in the size of the Dps protein from 90 Å to 69–75 Å during the formation of a complex with DNA has been repeatedly observed, and no explanation has been given. In this work, we show that during the formation of intracellular DNA–Dps crystals, the protein transitions to another oligomeric form: from a dodecameric (of 12 monomers), which has an almost spherical shape with a diameter of 90 Å, to a trimeric (of three monomers), which has a shape close to a torus-like structure with a diameter of 70 Å and a height of 40 Å. The trimer model was obtained through the molecular dynamic modeling of the interaction of the three monomers of the Dps protein. Placement of the obtained trimer in the electron density of in vitro DNA–Dps crystal allowed for the determination of the lattice parameters of the studied crystal. This crystal model was in good agreement with the SAXS data obtained from intracellular crystals of 2-day-old Escherichia coli cells. The final crystal structure contains a DNA molecule in the through channel of the crystal structure between the Dps trimers. It was discussed that the mechanism of protein transition from one oligomeric form to another in the cell cytoplasm could be regulated by intracellular metabolites and is a simple and flexible mechanism of prokaryotic cell transition from one metabolic state to another.