bluuebunny/crossref_metadata_2025 huggingface dataset:
Advanced Deep Learning Fusion Model for Early Multi-Classification of Lung and Colon Cancer Using Histopathological Images
Authors: Abd El-Aziz A. A. , Mahmood Mahmood A. , Abd El-Ghany Sameh
Published: October 2024

Background: In recent years, the healthcare field has experienced significant advancements. New diagnostic techniques, treatments, and insights into the causes of various diseases have emerged. Despite these progressions, cancer remains a major concern. It is a widespread illness affecting individuals of all ages and leads to one out of every six deaths. Lung and colon cancer alone account for nearly two million fatalities. Though it is rare for lung and colon cancers to co-occur, the spread of cancer cells between these two areas—known as metastasis—is notably high. Early detection of cancer greatly increases survival rates. Currently, histopathological image (HI) diagnosis and appropriate treatment are key methods for reducing cancer mortality and enhancing survival rates. Digital image processing (DIP) and deep learning (DL) algorithms can be employed to analyze the HIs of five different types of lung and colon tissues. Methods: Therefore, this paper proposes a refined DL model that integrates feature fusion for the multi-classification of lung and colon cancers. The proposed model incorporates three DL architectures: ResNet-101V2, NASNetMobile, and EfficientNet-B0. Each model has limitations concerning variations in the shape and texture of input images. To address this, the proposed model utilizes a concatenate layer to merge the pre-trained individual feature vectors from ResNet-101V2, NASNetMobile, and EfficientNet-B0 into a single feature vector, which is then fine-tuned. As a result, the proposed DL model achieves high success in multi-classification by leveraging the strengths of all three models to enhance overall accuracy. This model aims to assist pathologists in the early detection of lung and colon cancer with reduced effort, time, and cost. The proposed DL model was evaluated using the LC25000 dataset, which contains colon and lung HIs. The dataset was pre-processed using resizing and normalization techniques. Results: The model was tested and compared with recent DL models, achieving impressive results: 99.8% for precision, 99.8% for recall, 99.8% for F1-score, 99.96% for specificity, and 99.94% for accuracy. Conclusions: Thus, the proposed DL model demonstrates exceptional performance across all classification categories.
Novel Biomarkers for Early Detection of Hepatocellular Carcinoma
Authors: Attia Abdelrahman M. , Rezaee-Zavareh Mohammad Saeid , Hwang Soo Young , Kim Naomy , Adetyan Hasmik , Yalda Tamar , Chen Pin-Jung , Koltsova Ekaterina K. , Yang Ju Dong
Published: October 2024

Hepatocellular carcinoma (HCC) is a leading cause of cancer mortality globally. Most patients present with late diagnosis, leading to poor prognosis. This narrative review explores novel biomarkers for early HCC detection. We conducted a comprehensive literature review analyzing protein, circulating nucleic acid, metabolite, and quantitative proteomics-based biomarkers, evaluating the advantages and limitations of each approach. While established markers like alpha-fetoprotein (AFP), des-gamma-carboxy prothrombin, and AFP-L3 remain relevant, promising candidates include circulating tumor DNA, microRNAs, long noncoding RNAs, extracellular vesicle, and metabolomic biomarkers. Multi-biomarker panels like the GALAD score, Oncoguard, and Helio liver test show promise for improved diagnostic accuracy. Non-invasive approaches like urine and gut microbiome analysis are also emerging possibilities. Integrating these novel biomarkers with current screening protocols holds significant potential for earlier HCC detection and improved patient outcomes. Future research should explore multi-biomarker panels, omics technologies, and artificial intelligence to further enhance early HCC diagnosis and management.
Early Cervical Cancer Diagnosis with SWIN-Transformer and Convolutional Neural Networks
Authors: Mohammed Foziya Ahmed , Tune Kula Kekeba , Mohammed Juhar Ahmed , Wassu Tizazu Alemu , Muhie Seid
Published: October 2024

Introduction: Early diagnosis of cervical cancer at the precancerous stage is critical for effective treatment and improved patient outcomes. Objective: This study aims to explore the use of SWIN Transformer and Convolutional Neural Network (CNN) hybrid models combined with transfer learning to classify precancerous colposcopy images. Methods: Out of 913 images from 200 cases obtained from the Colposcopy Image Bank of the International Agency for Research on Cancer, 898 met quality standards and were classified as normal, precancerous, or cancerous based on colposcopy and histopathological findings. The cases corresponding to the 360 precancerous images, along with an equal number of normal cases, were divided into a 70/30 train–test split. The SWIN Transformer and CNN hybrid model combines the advantages of local feature extraction by CNNs with the global context modeling by SWIN Transformers, resulting in superior classification performance and a more automated process. The hybrid model approach involves enhancing image quality through preprocessing, extracting local features with CNNs, capturing the global context with the SWIN Transformer, integrating these features for classification, and refining the training process by tuning hyperparameters. Results: The trained model achieved the following classification performances on fivefold cross-validation data: a 94% Area Under the Curve (AUC), an 88% F1 score, and 87% accuracy. On two completely independent test sets, which were never seen by the model during training, the model achieved an 80% AUC, a 75% F1 score, and 75% accuracy on the first test set (precancerous vs. normal) and an 82% AUC, a 78% F1 score, and 75% accuracy on the second test set (cancer vs. normal). Conclusions: These high-performance metrics demonstrate the models’ effectiveness in distinguishing precancerous from normal colposcopy images, even with modest datasets, limited data augmentation, and the smaller effect size of precancerous images compared to malignant lesions. The findings suggest that these techniques can significantly aid in the early detection of cervical cancer at the precancerous stage.
Characteristics of Curious Minds: Evidence from Interviews with Renowned Experts in Five Curiosity-Dominant Fields
Authors: Birenbaum Menucha , Nasser-Abu Alhija Fadia , Shilton Hany , Kimron Helena , Shahor Neria , Rosanski Rovena
Published: October 2024

Semi-structured interviews were conducted with 50 renowned experts from five curiosity-dominant professional fields (scientists, inventors (high-tech entrepreneurs), artists, explorers, and therapeutic professionals). The five-dimensional curiosity framework proposed by Kashdan and colleagues (comprising joyous discovery, deprivation sensitivity, social curiosity, stress (uncertainty) tolerance, and thrill-seeking) was adopted. The purpose was to explore nuances of curiosity manifestations expressed by the subjects in their own words and related personality and contextual attributes. A directed approach to content analysis was applied to code the interview data; qualitative methods were employed for data analysis, complemented by quantitative ones. Insights gained from the findings regarding the curiosity construct, focusing on differences among the groups in regard to aspects of social curiosity and effects of uncertainty tolerance and thrill-thinking, were discussed, followed by implications for cultivating curious minds.
Investigating Students’ Conceptual Knowledge of Quantum Physics to Improve the Teaching and Learning Process
Authors: Nikolaus Patricija , Dželalija Mile , Weber Ivana
Published: October 2024

Research in the field of quantum physics is important for progress in many areas of exploration and development. Quantum computers and other quantum devices are promising technologies with numerous potential applications. On the other hand, understanding, interpreting, teaching, and learning quantum physics as part of an educational process is a major challenge. In the Republic of Croatia, students usually come in contact with the concepts of quantum physics towards the end of their high school education. These concepts are often abstract and represent a remarkable leap from the theories of classical physics. The aim of this study is to test the measurement properties of the instrument used to assess the progress of understanding and knowledge of quantum physics in a sample of Croatian high school students. The quantum physics conceptual survey (QPCS), developed and first tested in 2006 by Wuttiprom et al. at the University of Sydney, was the instrument we used in this study. The test was administered to 76 high school students. The results show that the QPCS test is valid and generally reliable in the context of Croatian secondary education, but for the topics Waves and particles and Uncertainty principle, the reliability needs further investigation. The results of the pretest and posttest were analysed and compared with each other and with previously published results. Quantitative methods were used to analyse the results obtained. We present several possible solutions to improve the teaching process, that we expect will lead to better results, especially for topics that are challenging for students.
Enhancing Arabic Language Acquisition: Effective Strategies for Addressing Non-Native Learners’ Challenges
Authors: Almelhes Sultan
Published: October 2024

The Arabic language has gained significant global recognition, with a growing number of non-Arab individuals learning it as a second language. Despite this trend, learners of Arabic face various challenges that have not been thoroughly examined. This study aimed to investigate the challenges encountered by learners of the Arabic language and to determine the factors that contribute to effective language learning and use. Data from 444 non-native speakers learning Arabic as a second language were analyzed with SPSS 27 using a descriptive approach. The results indicated that Arabic instructors should focus on improving feedback practices, developing customized curricula, and incorporating technology and multimedia resources into their teaching methods. Furthermore, this study highlights the importance of integrating cultural components and accommodating diverse learners in the classroom. To improve speaking proficiency, learners can engage in activities such as listening to radio broadcasts, collaborating with classmates, and building relationships with Arabic-speaking friends. The results of this research provide insights that can assist instructors of Arabic as a second language in supporting learners, improving their abilities to learn and communicate in Arabic.
Multi-Level Sum of Product (SOP) Network Power Optimization Based on Switching Graph
Authors: Kubica Marcin , Kania Dariusz
Published: October 2024

The article presents the methodology of optimization of technology mapping of a multi-output function implemented in the form of sum of product (SOP) networks. The optimization is based on the concept of reducing the switching activity of combinational circuits. The aim of reducing network switching is to limit the consumption of dynamic power. Since dynamic power is one of the components of the total power consumed by digital systems, this leads to an optimization focused on the energy efficiency of digital systems. The basis of the proposed method is the technology mapping using a modified output graph describing the result of minimizing the multi-output function. The modified output graph, in terms of parameters associated with dynamic power, is defined as a switching graph. It was assumed that the key parameter associated with dynamic power is the switching activity of individual nodes of the logic network. The article presents elements of switching graph optimization which lead to the improvement of parameters associated with the dynamic power of the circuit. The essence of the proposed optimization methods is the appropriate movement of products and connections occurring in the logic network. Reducing the number of logic network vertices is also extremely important. The effectiveness of the proposed method was confirmed by the results of experiments performed on selected benchmarks. A significant reduction in the total value of switching activity was obtained for the optimized structures.
DPF-YOLOv8: Dual Path Feature Fusion Network for Traffic Sign Detection in Hazy Weather
Authors: Zhang Yuechong , Liu Haiying , Dong Dehao , Duan Xuehu , Lin Fei , Liu Zengxiao
Published: October 2024

Traffic sign detection plays an integral role in intelligent driving systems. It was found that in real driving scenarios, traffic signs were easily obscured by haze leading to traffic sign detection inaccuracy in assisted driving systems. Therefore, we designed a traffic sign detection model for hazy weather that can effectively help drivers to recognize road signs and reduce the incidence of traffic accidents. A high-precision traffic sign detection network has been designed to address the problem of decreased model recognition performance caused by external factors such as small size of traffic signs and haze obstruction in real-world scenarios. First, the default YOLOv8 was found to have low model detection accuracy in hazy weather occlusion conditions through experimental studies. Therefore, a deeper lightweight and efficient multi-branch CSP (Cross Stage Partial) module was introduced. Second, a dual path feature fusion network was designed to address the problem of insufficient feature fusion due to the small size of traffic signs. Finally, in order to be able to better simulate the real haze weather scene, we added fog to the raw data to enrich the data samples. This was verified through experiments on a public Chinese traffic sign detection dataset after fogging treatment, compared to the default YOLOv8 model. The improved DPF-YOLOv8 algorithm achieved 2.1% and 2.2% improvement in mAP@0.5 and mAP@0.5:0.95 performance metrics to 65.0% and 47.4%, respectively.
Improved YOLOv7 Electric Work Safety Belt Hook Suspension State Recognition Algorithm Based on Decoupled Head
Authors: Xie Xiaona , Chang Zhengwei , Lan Zhongxiao , Chen Mingju , Zhang Xingyue
Published: October 2024

Safety is the eternal theme of power systems. In view of problems such as time-consuming and poor real-time performance in the correct use of seat belt hooks by manual supervision operators in the process of power operation, this paper proposes an improved YOLOv7 seat belt hook suspension state recognition algorithm. Firstly, the feature extraction part of the YOLOv7 backbone network is improved, and the M-Spatial Pyramid Pooling Concurrent Spatial Pyramid Convolution (M-SPPCSPC) feature extraction module is constructed to replace the Spatial Pyramid Pooling Concurrent Spatial Pyramid Convolution (SPPCSPC) module of the backbone network, which reduces the amount of computation and improves the detection speed of the backbone network while keeping the sensory field of the backbone network unchanged. Second, a decoupled head, which realizes the confidence and regression frames separately, is introduced to alleviate the negative impact of the conflict between the classification and regression tasks, consequently improving the network detection accuracy and accelerating the network convergence. Ultimately, a dynamic non-monotonic focusing mechanism is introduced in the output layer, and the Wise Intersection over Union (WioU) loss function is used to reduce the competitiveness of high-quality anchor frames while reducing the harmful gradient generated by low-quality anchor frames, which ultimately improves the overall performance of the detection network. The experimental results show that the mean Average Precision (mAP@0.5) value of the improved network reaches 81.2%, which is 7.4% higher than that of the original YOLOv7, therefore achieving better detection results for multiple-state recognition of hooks.
The Impact of Self-Service Technologies on Cinemagoing Experiences: A Hungarian Case Study
Authors: Szűcs Judit , Guzsvinecz Tibor
Published: October 2024

This study investigates the relationship between self-service technologies (SSTs) and cinemagoing experiences. An online questionnaire was created and filled out by 202 respondents to assess their preferences regarding SSTs in Hungarian cinemas. The analysis was conducted in R based on the following factors: gender, age, place of residence, and cinema attendance frequency. The results showed that 78.43% of males and 79.47% of females preferred hybrid systems combining both human staff and SSTs. There was no significant relationship between gender and SST preference. However, respondents aged 26–35 years and those over 50 years were less likely to prefer SSTs. In addition, people who live in capital cities showed a higher likelihood of preferring SSTs. Despite minor demographic differences, the overall results indicate a strong preference for SSTs across all groups. Predictions using ordinal logistic regression suggest that future cinemagoers will continue to prefer SSTs, with probabilities ranging from 65.58% to 75.90%. These results can help in understanding the growing acceptance of SSTs in cinemas and suggest that their implementation could be well-received by future audiences.
Measurement and Validation of Market Power in China’s Log Import Trade—Empirical Analysis Based on PTM Model and AIDS Model
Authors: Wang Fang , Cheng Baodong , Tian Minghua , Meng Xiao
Published: October 2024

China is the world’s largest importer of logs, possessing the scale to exert significant influence in the international market. This paper uses a fixed-effect variable coefficient Pricing-to-Market panel model to measure China’s market power in log import trade. It also utilizes the Almost Ideal Demand System model from an elasticity perspective to explore the market behavior characteristics of various source countries in China’s log import trade, thereby validating the mechanism of market power. The results indicate that: ① China’s main trading partners can be categorized into four groups according to their market power in the log import trade. Specifically, China holds superlative market power in log imports from Indonesia, Malaysia, and Myanmar; holds strong market power in log imports from Russia, the Democratic Republic of the Congo, and Mozambique; holds weak market power in log imports from Papua New Guinea, Equatorial Guinea, France, Germany, Australia, and New Zealand; and holds no market power in Japan, Cameroon, and the United States. ② As China’s expenditure on log imports increases, there is a tendency to purchase high-quality precious wood and a greater concern for the legality of market transactions. Consequently, China is anticipated to augment its imports from source countries with no or weak market power. ③ The simple price elasticity of log imports from each source country is negative. Source countries with stronger market power tend to increase prices to achieve higher total revenue, while those with weaker market power are more inclined to lower prices to achieve the same. ④ Log products from various source countries are complementary in the Chinese market, indicating that China’s substantial demand for logs relies on the simultaneous supply from multiple countries and diverse wood types. Based on the existence or absence of market power in China’s log import trade, this paper provides targeted insights into enhancing international market power and reducing trade losses.
Developing a New Method to Rapidly Map Eucalyptus Distribution in Subtropical Regions Using Sentinel-2 Imagery
Authors: Tang Chunxian , Jiang Xiandie , Li Guiying , Lu Dengsheng
Published: October 2024

Eucalyptus plantations with fast growth and short rotation play an important role in improving economic conditions for local farmers and governments. It is necessary to map and update eucalyptus distribution in a timely manner, but to date, there is a lack of suitable approaches for quickly mapping its spatial distribution in a large area. This research aims to develop a uniform procedure to map eucalyptus distribution at a regional scale using the Sentinel-2 imagery on the Google Earth Engine (GEE) platform. Different seasonal Senstinel-2 images were first examined, and key vegetation indices from the selected seasonal images were identified using random forest and Pearson correlation analysis. The selected key vegetation indices were then normalized and summed to produce new indices for mapping eucalyptus distribution based on the calculated best cutoff values using the ROC (Receiver Operating Characteristic) curve. The uniform procedure was tested in both experimental and test sites and then applied to the entire Fujian Province. The results indicated that the best season to distinguish eucalyptus forests from other forest types was winter. The composite indices for eucalyptus–coniferous forest separation (CIEC) and for eucalyptus–broadleaf forest separation (CIEB), which were synthesized from the enhanced vegetation index (EVI), plant senescing reflectance index (PSRI), shortwave infrared water stress index (SIWSI), and MERIS terrestrial chlorophyll index (MTCI), can effectively differentiate eucalyptus from other forest types. The proposed procedure with the best cutoff values (0.58 for CIEC and 1.29 for CIEB) achieved accuracies of above 90% in all study sites. The eucalyptus classification accuracies in Fujian Province, with a producer’s accuracy of 91%, user’s accuracy of 97%, and overall accuracy of 94%, demonstrate the strong robustness and transferability of this proposed procedure. This research provided a new insight into quickly mapping eucalyptus distribution in subtropical regions. However, more research is still needed to explore the robustness and transferability of this proposed method in tropical regions or in other subtropical regions with different environmental conditions.
Multi-Source Data Fusion for Vehicle Maintenance Project Prediction
Authors: Chen Fanghua , Shang Deguang , Zhou Gang , Ye Ke , Wu Guofang
Published: October 2024

Ensuring road safety is heavily reliant on the effective maintenance of vehicles. Accurate predictions of maintenance requirements can substantially reduce ownership costs for vehicle owners. Consequently, this field has attracted increasing attention from researchers in recent years. However, existing studies primarily focus on predicting a limited number of maintenance needs, predominantly based solely on vehicle mileage and driving time. This approach often falls short, as it does not comprehensively monitor the overall health condition of vehicles, thus posing potential safety risks. To address this issue, we propose a deep fusion network model that utilizes multi-source data, including vehicle maintenance record data and vehicle base information data, to provide comprehensive predictions for vehicle maintenance projects. To capture the relationships among various maintenance projects, we create a correlation representation using the maintenance project co-occurrence matrix. Furthermore, building on the correlation representation, we propose a deep fusion network that employs the attention mechanism to efficiently merge vehicle mileage and vehicle base information. Experiments conducted on real data demonstrate the superior performance of our proposed model relative to competitive baseline models in predicting vehicle maintenance projects.
Role of Circulating microRNAs in Liver Disease and HCC: Focus on miR-122
Authors: Colaianni Francesco , Zelli Veronica , Compagnoni Chiara , Miscione Martina Sara , Rossi Mario , Vecchiotti Davide , Di Padova Monica , Alesse Edoardo , Zazzeroni Francesca , Tessitore Alessandra
Published: October 2024

miR-122 is the most abundant microRNA (miRNA) in the liver; it regulates several genes mainly involved in cell metabolism and inflammation. Host factors, diet, metabolic disorders and viral infection promote the development of liver diseases, including hepatocellular carcinoma (HCC). The downregulation of miR-122 in tissue is a common feature of the progression of liver injury. In addition, the release of miR-122 in the bloodstream seems to be very promising for the early diagnosis of both viral and non-viral liver disease. Although controversial data are available on the role of circulating miR-122 as a single biomarker, high diagnostic accuracy has been observed using miR-122 in combination with other circulating miRNAs and/or proteins. This review is focused on comprehensively summarizing the most recent literature on the potential role of circulating miR-122, and related molecules, as biomarker(s) of metabolic liver diseases, hepatitis and HCC.
The Mundeck Salt Unit: A Review of Aptian Depositional Context and Hydrocarbon Potential in the Kribi-Campo Sub-Basin (South Cameroon Atlantic Basin)
Authors: Essi Mike-Franck Mienlam , Lee Eun Young , Yem Mbida , Essi Jean Marcel Abate , Atangana Joseph Quentin Yene
Published: October 2024

The Kribi-Campo sub-basin, located in the Gulf of Guinea, constitutes the southeastern segment of the Cameroon Atlantic Margin. Drilling in the Aptian salt unit revealed a sparse hydrocarbon presence, contrasting with modest finds in its counterparts like the Ezanga Salt in Gabon and the Rio Muni Salt in Equatorial Guinea. This discrepancy prompted a reassessment of the depositional context and hydrocarbon potential of the Mundeck salt unit. By integrating 2D seismic reflection and borehole data analysis, this study established the structural and stratigraphic framework of the area, emphasizing the salt unit’s significance. Borehole data indicate a localized salt unit offshore Kribi, with seismic reflection data revealing distinct forms of diapir and pillow. This salt unit displays a substantial lateral extent with thicknesses ranging from 4000 m to 6000 m. The depositional context is linked to the following two major geological events: a significant sea-level drop due to margin uplift during the Aptian and thermodynamic processes driven by transfer faults related to mid-oceanic ridge formation. These events were crucial in forming and evolving the Mundeck Salt. Regarding hydrocarbon prospects, this study identifies the unit as being associated with potential petroleum plays, supported by direct hydrocarbon indicators and fault-related structures. The findings suggest that untapped hydrocarbon resources may still exist, underscoring the need for further exploration and analysis.
Effects of Different Weeding Methods on Soil Physicochemical Properties, Root Morphology, and Fruit Economic Traits in Camellia oleifera Abel. Plantations
Authors: Shi Xueyun , Wu Huaiyuan , Xie Shuangling , Li Hongkui , Wang Yan , Wang Yuman , Liu Huiyun , Cheng Qinhua , Wang Zongde , Hu Dongnan
Published: October 2024

Soil physicochemical properties, root characteristics, and fruit economic traits were determined in Camellia oleifera plantations under spontaneous vegetation + mowing (W1), spontaneous vegetation + glyphosate (W2), and no weeding (CK) treatments. Compared with CK, W1 reduced soil bulk density and increased total nitrogen, total phosphorus, ammonium nitrogen, nitrate nitrogen, and effective potassium content. W2 treatment resulted in higher bulk density than W1 and lower water-holding capacity, total nitrogen, total phosphorus, total potassium, ammonium nitrogen, nitrate nitrogen, and available potassium of the soil. Generally, both W1 and W2 inhibited weed morphological traits while favoring the C. oleifera root system, with the W1 treatment resulting in the greatest increase. Fruit transverse diameter, longitudinal diameter, yield, and oil yield were higher in W1 than in CK and W2 treatments. Weed root systems and C. oleifera root systems ultimately affect oil production and yield by affecting bulk density, ammonium nitrogen, nitrate nitrogen, fruit transverse diameter, seed yield, and seed kernel oil content. In summary, W1 treatment improved the physicochemical properties, root growth, fruit growth, and soil quality in C. oleifera plantations.
The Putative Role of TIM-3 Variants in Polyendocrine Autoimmunity: Insights from a WES Investigation
Authors: Ariolli Andrea , Agolini Emanuele , Mazza Tommaso , Petrizzelli Francesco , Petrini Stefania , D’Oria Valentina , Cudini Annamaria , Nardella Caterina , Pesce Vanessa , Comparcola Donatella , Cappa Marco , Fierabracci Alessandra
Published: October 2024

Autoimmune polyglandular syndrome (APS) comprises a complex association of autoimmune pathological conditions. APS Type 1 originates from loss-of-function mutations in the autoimmune regulator (AIRE) gene. APS2, APS3 and APS4 are linked to specific HLA alleles within the major histocompatibility complex, with single-nucleotide polymorphisms (SNPs) in non-HLA genes also contributing to disease. In general, variability in the AIRE locus and the presence of heterozygous loss-of-function mutations can impact self-antigen presentation in the thymus. In this study, whole-exome sequencing (WES) was performed on a sixteen-year-old female APS3A/B patient to investigate the genetic basis of her complex phenotype. The analysis identified two variants (p.Arg111Trp and p.Thr101Ile) of the hepatitis A virus cell receptor 2 gene (HAVCR2) encoding for the TIM-3 (T cell immunoglobulin and mucin domain 3) protein. These variants were predicted, through in silico analysis, to impact protein structure and stability, potentially influencing the patient’s autoimmune phenotype. While confocal microscopy analysis revealed no alteration in TIM-3 fluorescence intensity between the PBMCs isolated from the patient and those of a healthy donor, RT-qPCR showed reduced TIM-3 expression in the patient’s unfractionated PBMCs. A screening conducted on a cohort of thirty APS patients indicated that the p.Thr101Ile and p.Arg111Trp mutations were unique to the proband. This study opens the pathway for the search of TIM-3 variants possibly linked to complex autoimmune phenotypes, highlighting the potential of novel variant discovery in contributing to APS classification and diagnosis.
Advances and Challenges of Bioassembly Strategies in Neurovascular In Vitro Modeling: An Overview of Current Technologies with a Focus on Three-Dimensional Bioprinting
Authors: Mancuso Salvatore , Bhalerao Aditya , Cucullo Luca
Published: October 2024

Bioassembly encompasses various techniques such as bioprinting, microfluidics, organoids, and self-assembly, enabling advances in tissue engineering and regenerative medicine. Advancements in bioassembly technologies have enabled the precise arrangement and integration of various cell types to more closely mimic the complexity functionality of the neurovascular unit (NVU) and that of other biodiverse multicellular tissue structures. In this context, bioprinting offers the ability to deposit cells in a spatially controlled manner, facilitating the construction of interconnected networks. Scaffold-based assembly strategies provide structural support and guidance cues for cell growth, enabling the formation of complex bio-constructs. Self-assembly approaches utilize the inherent properties of cells to drive the spontaneous organization and interaction of neuronal and vascular components. However, recreating the intricate microarchitecture and functional characteristics of a tissue/organ poses additional challenges. Advancements in bioassembly techniques and materials hold great promise for addressing these challenges. The further refinement of bioprinting technologies, such as improved resolution and the incorporation of multiple cell types, can enhance the accuracy and complexity of the biological constructs; however, developing bioinks that support the growth of cells, viability, and functionality while maintaining compatibility with the bioassembly process remains an unmet need in the field, and further advancements in the design of bioactive and biodegradable scaffolds will aid in controlling cell adhesion, differentiation, and vascularization within the engineered tissue. Additionally, integrating advanced imaging and analytical techniques can provide real-time monitoring and characterization of bioassembly, aiding in quality control and optimization. While challenges remain, ongoing research and technological advancements propel the field forward, paving the way for transformative developments in neurovascular research and tissue engineering. This work provides an overview of the advancements, challenges, and future perspectives in bioassembly for fabricating neurovascular constructs with an add-on focus on bioprinting technologies.
Protective and Detoxifying Effects of Resveratrol on Zearalenone-Mediated Toxicity: A Review
Authors: Lv Qiongxia , Xu Wenjing , Yang Fan , Li Jiahui , Wei Wenjuan , Chen Xiaoguang , Liu Yumei , Zhang Ziqiang
Published: October 2024

Zearalenone (ZEA) is a mycotoxin produced by Fusarium spp. fungi and is widely found in moldy corn, wheat, barley, and other grains. ZEA is distributed to the whole body via blood circulation after metabolic transformation in animals. Through oxidative stress, immunosuppression, apoptosis, autophagy, and mitochondrial dysfunction, ZEA leads to hepatitis, neurodegenerative diseases, cancer, abortion, and stillbirth in female animals, and decreased sperm motility in male animals. In recent years, due to the influence of climate, storage facilities, and other factors, the problem of ZEA pollution in global food crops has become particularly prominent, resulting in serious problems for the animal husbandry and feed industries, and threatening human health. Resveratrol (RSV) is a natural product with therapeutic activities such as anti-inflammatory, antioxidant, and anticancer properties. RSV can alleviate ZEA-induced toxic effects by targeting signaling pathways such as NF-κB, Nrf2/Keap1, and PI3K/AKT/mTOR via attenuating oxidative damage, inflammatory response, and apoptosis, and regulating cellular autophagy. Therefore, this paper provides a review of the protective effect of RSV against ZEA-induced toxicity and its molecular mechanism, and discusses the safety and potential clinical applications of RSV in the search for natural mycotoxin detoxification agents.
Genome-Wide Identification of the Peanut ASR Gene Family and Its Expression Analysis under Abiotic Stress
Authors: Li Jiaxing , Ma Mingxia , Zeng Tuo , Gu Lei , Zhu Bin , Wang Hongcheng , Du Xuye , Zhu Xiu
Published: October 2024

Peanut (Arachis hypogaea L.) is one of the most important oil and food legume crops worldwide. ASR (abscisic acid, stress, ripening) plays extremely important roles in plant growth and development, fruit ripening, pollen development, and stress. Here, six ASR genes were identified in peanut. Structural and conserved motif analyses were performed to identify common ABA/WDS structural domains. The vast majority of ASR genes encoded acidic proteins, all of which are hydrophilic proteins and localized on mitochondria and nucleus, respectively. The cis-element analysis revealed that some cis-regulatory elements were related to peanut growth and development, hormone, and stress response. Under normal growth conditions, AhASR4 and AhASR5 were expressed in all tissues of peanut plants. Quantitative real-time PCR (qRT-PCR) results indicated that peanut ASR genes exhibited complex expression patterns in response to abiotic stress. Notably, under drought and cadmium (Cd) stress, the expression levels of AhASR4 and AhASR5 were significantly upregulated, suggesting that these genes may play a crucial role in the peanut plant’s resistance to such stressors. These results provide a theoretical basis for studying the evolution, expression, and function of the peanut ASR gene family and will provide valuable information in the identification and screening of genes for peanut stress tolerance breeding.
Liquid Biopsy in Pancreatic Ductal Adenocarcinoma: A Review of Methods and Applications
Authors: Dubrovsky Genia , Ross Alison , Jalali Pooya , Lotze Michael
Published: October 2024

Pancreatic ductal adenocarcinoma (PDAC) remains a malignancy with one of the highest mortality rates. One limitation in the diagnosis and treatment of PDAC is the lack of an early and universal biomarker. Extensive research performed recently to develop new assays which could fit this role is available. In this review, we will discuss the current landscape of liquid biopsy in patients with PDAC. Specifically, we will review the various methods of liquid biopsy, focusing on circulating tumor DNA (ctDNA) and exosomes and future opportunities for improvement using artificial intelligence or machine learning to analyze results from a multi-omic approach. We will also consider applications which have been evaluated, including the utility of liquid biopsy for screening and staging patients at diagnosis as well as before and after surgery. We will also examine the potential for liquid biopsy to monitor patient treatment response in the setting of clinical trial development.
Synergistic Proliferation Effects of Xanthohumol and Niflumic Acid on Merkel and Glioblastoma Cancer Cells: Role of Cell Membrane Interactions
Authors: Stompor-Gorący Monika , Włoch Aleksandra , Sengupta Priti , Nasulewicz-Goldeman Anna , Wietrzyk Joanna
Published: October 2024

The objective of our research was to determine the effects of xanthohumol (XN), a flavonoid isolated from hops (Humulus lupulus), and the anti-inflammatory drug niflumic acid (NA), separately and in combination with each other, on the proliferation of human cancer cells. Additionally, so as to understand the mechanism underlying the anticancer properties of the tested compounds, their effects on the biophysical parameters of a model membrane were assessed. The cells were incubated with XN and NA at various concentrations, either individually or in combination with each other. Cell proliferation was quantified using the sulforodamine B (SRB) assay. In addition, the IC50 values for niflumic acid and xanthohumol applied separately were determined by cell proliferation tests for the following human cancer cell lines: 5637 (urinary bladder carcinoma), A-431 (epidermoid carcinoma), UM-SCC-17A (head and neck squamous carcinoma), SK-MEL-3 (melanoma), MCC13 (Merkel cell cancer), and A172 (glioblastoma), in comparison with the mouse normal fibroblasts (BALB/3T3 clone A31). The results show that the two-compound combinations of XN and NA significantly decreased the proliferation of cancer cells in a dose-dependent manner, and the effects were stronger than the additive responses to XN and NA individually. The membrane studies revealed a synergistic effect on the membrane rigidity when using the mixture of XN and NA, which may explain the observed increase in anticancer activity for the combined XN and NA. Our results suggest that NSAIDs, such as niflumic acid, may be a promising strategy for co-application with xanthohumol as anticancer drugs.
Correction: Park et al. Licoricidin, an Active Compound in the Hexane/Ethanol Extract of Glycyrrhiza uralensis, Inhibits Lung Metastasis of 4T1 Murine Mammary Carcinoma Cells. Int. J. Mol. Sci. 2016, 17, 934
Authors: Park So Young , Kwon Soo Jin , Lim Soon Sung , Kim Jin-Kyu , Lee Ki Won , Park Jung Han Yoon
Published: October 2024

In the original publication [...]
A Mini-Review on Gene Therapy in Glaucoma and Future Directions
Authors: Anton Nicoleta , Geamănu Aida , Iancu Raluca , Pîrvulescu Ruxandra Angela , Popa-Cherecheanu Alina , Barac Ramona Ileana , Bandol Geanina , Bogdănici Camelia Margareta
Published: October 2024

Glaucoma is a group of optic neuropathies characterized by the degeneration of retinal ganglion cells and the loss of their axons in the optic nerve. The only approved therapies for the treatment of glaucoma are topical medications and surgical procedures aimed at lowering intraocular pressure. Gene therapy involves the insertion, removal, or modification of genetic material within cells to repair or compensate for the loss of a gene’s function. It describes a process or technology that enables the genetic modification of cells to produce a therapeutic effect. However, changing the genetic material alone does not extend the duration of overexpression of proteins that combat disease, nor does it facilitate the production of new proteins for this purpose. We reviewed the literature concerning the use of gene therapy in the treatment of glaucoma and explored the future directions that this innovation may offer. Three genes associated with glaucoma have been identified within these loci: myocilin/trabecular meshwork glucocorticoid response (TIGR) (GLC1A), optineurin (GLC1E), and WDR36 (GLC1G). Among these, the most extensively studied glaucoma gene is myocilin (a TM-inducible glucocorticoid response gene). Building on previous successes, researchers have begun to apply genetic therapeutic approaches to alleviate or reduce symptoms associated with ocular hypertension (OHT) and glaucoma-like optic neuropathy (GON). It is evident that several therapeutic strategies exist that modulate aqueous humor production and flow, thereby regulating intraocular pressure (IOP) and protecting retinal ganglion cells (RGCs) from apoptosis. With the emergence of gene therapy as a potentially viable approach to preserving vision, new methods for managing glaucoma may soon become available. Genomic therapy is a promising treatment option for glaucoma patients and has significant potential for widespread clinical application.
Effects of Dietary Yeast β-1,3/1,6-D-Glucan on Immunomodulation in RAW 264.7 Cells and Methotrexate-Treated Rat Models
Authors: Son Joohee , Hwang Yeseul , Hong Eun-Mi , Schulenberg Marion , Chai Hyungyung , Jo Hee-Geun , Lee Donghun
Published: October 2024

A new subclass of nutraceuticals, called immunoceuticals, is dedicated to immunological regulation. Although yeast-derived β-1,3/1,6-D-glucan shows promise as an immunoceutical candidate, further studies are needed to define its precise immune-enhancing processes and to standardize its use. Following methotrexate (MTX)-induced immunosuppression in rats, we evaluated the immunomodulatory efficacy of a highly pure and standardized β-1,3/1,6-D-glucan sample (YBG) in RAW 264.7 macrophages. In in vitro and in vivo models, YBG demonstrated remarkable immunomodulatory effects, such as repair of immune organ damage, elevation of blood cytokine levels, and enhanced phagocytosis and nitric oxide production in RAW 264.7 cells. These results are consistent with the established immunostimulatory properties of β-glucan. It is noteworthy that this research indicates the potential of YBG as an immunomodulatory nutraceutical, as it is among the first to demonstrate immunological augmentation in an immunosuppression setting produced by MTX. Based on these observations, further investigation of YBG is warranted, particularly given its potential to emerge as a combination immunoceutical to mitigate immunosuppression and reduce the risk of infection in rheumatoid arthritis (RA) patients receiving long-term MTX therapy.
mTOR in the Development of Hypoxic Pulmonary Hypertension Associated with Cardiometabolic Risk Factors
Authors: Flores Karen , Almeida Carlo , Arriaza Karem , Pena Eduardo , El Alam Samia
Published: October 2024

The pathophysiology of pulmonary hypertension is complex and multifactorial. It is a disease characterized by increased pulmonary vascular resistance at the level due to sustained vasoconstriction and remodeling of the pulmonary arteries, which triggers an increase in the mean pulmonary artery pressure and subsequent right ventricular hypertrophy, which in some cases can cause right heart failure. Hypoxic pulmonary hypertension (HPH) is currently classified into Group 3 of the five different groups of pulmonary hypertensions, which are determined according to the cause of the disease. HPH mainly develops as a product of lung diseases, among the most prevalent causes of obstructive sleep apnea (OSA), chronic obstructive pulmonary disease (COPD), or hypobaric hypoxia due to exposure to high altitudes. Additionally, cardiometabolic risk factors converge on molecular mechanisms involving overactivation of the mammalian target of rapamycin (mTOR), which correspond to a central axis in the development of HPH. The aim of this review is to summarize the role of mTOR in the development of HPH associated with metabolic risk factors and its therapeutic alternatives, which will be discussed in this review.
Circulatory Indicators of Lipid Peroxidation, the Driver of Ferroptosis, Reflect Differences between Relapsing–Remitting and Progressive Multiple Sclerosis
Authors: Stojkovic Ljiljana , Djordjevic Ana , Stefanovic Milan , Stankovic Aleksandra , Dincic Evica , Djuric Tamara , Zivkovic Maja
Published: October 2024

Ferroptosis, a lipid peroxidation- and iron-mediated type of regulated cell death, relates to both neuroinflammation, which is common in relapsing-remitting multiple sclerosis (RRMS), and neurodegeneration, which is prevalent in progressive (P)MS. Currently, findings related to the molecular markers proposed in this paper in patients are scarce. We analyzed circulatory molecular indicators of the main ferroptosis-related processes, comprising lipid peroxidation (malondialdehyde (MDA), 4-hydroxynonenal (4-HNE), and hexanoyl–lysine adduct (HEL)), glutathione-related antioxidant defense (total glutathione (reduced (GSH) and oxidized (GSSG)) and glutathione peroxidase 4 (GPX4)), and iron metabolism (iron, transferrin and ferritin) to estimate their contributions to the clinical manifestation of MS and differences between RRMS and PMS disease course. In 153 patients with RRMS and 69 with PMS, plasma/serum lipid peroxidation indicators and glutathione were quantified using ELISA and colorimetric reactions, respectively. Iron serum concentrations were determined using spectrophotometry, and transferrin and ferritin were determined using immunoturbidimetry. Compared to those with RRMS, patients with PMS had decreased 4-HNE (median, 1368.42 vs. 1580.17 pg/mL; p = 0.03). Interactive effects of MS course (RRMS/PMS) and disease-modifying therapy status on MDA (p = 0.009) and HEL (p = 0.02) levels were detected. In addition, the interaction of disease course and self-reported fatigue revealed significant impacts on 4-HNE levels (p = 0.01) and the GSH/GSSG ratio (p = 0.04). The results also show an association of MS course (p = 0.03) and EDSS (p = 0.04) with GSH levels. No significant changes were observed in the serum concentrations of iron metabolism indicators between the two patient groups (p > 0.05). We suggest circulatory 4-HNE as an important parameter related to differences between RRMS and PMS. Significant interactions of MS course and other clinically relevant parameters with changes in redox processes associated with ferroptosis support the further investigation of MS with a larger sample while taking into account both circulatory and central nervous system estimation.
SSA4 Mediates Cd Tolerance via Activation of the Cis Element of VHS1 in Yeast and Enhances Cd Tolerance in Chinese Cabbage
Authors: Zheng Han , Yuan Chao , Bu Tong , Liu Qun , Li Jingjuan , Wang Fengde , Zhang Yihui , He Lilong , Gao Jianwei
Published: October 2024

Identifying key genes involved in Cadmium (Cd) response pathways in plants and developing low-Cd-accumulating cultivars may be the most effective and eco-friendly strategy to tackle the problem of Cd pollution in crops. In our previous study, Stressseventy subfamily A 4 (SSA4) was identified to be associated with Cd tolerance in yeast. Here, we investigated the mechanism of SSA4 in regulating Cd tolerance in yeast. ScSSA4 binds to POre Membrane 34 (POM34), a key component of nuclear pore complex (NPC), and translocates from the cytoplasm to the nucleus, where it regulates the expression of its downstream gene, Viable in a Hal3 Sit4 background 1 (VHS1), resulting in reduced Cd accumulation in yeast cells. Additionally, we identified a Chinese cabbage SSA4 gene, BrSSA4c, which could enhance the Cd tolerance in Chinese cabbage. This study offers new insights into the regulatory mechanisms of Cd tolerance in yeast, a model organism, and paves the way for the genetic enhancement of Cd tolerance in Chinese cabbage.