bluuebunny/crossref_metadata_2025 huggingface dataset:
Flow Field of Supersonic Oxygen Jet Generated by Various Wear Lengths at the Laval Nozzle Exit
Authors: Liu Fuhai , Lu Songchao , Zeng Sibao , Zhu Rong , Wei Guangsheng , Dong Kai
Published: November 2024

As a main apparatus, the oxygen lance is used to deliver the oxygen element and transfer kinetic energy into the molten bath in the steelmaking process. However, the Laval nozzle exit would be gradually worn out during the service life, which suppresses the performance of the oxygen lance. This paper investigated three different wear length (Lw) conditions at the exit of the Laval nozzle through numerical simulations and high-temperature experiments with various oxygen flow rates. The result showed that the entrainment of the ambient gas was the key factor of the wear phenomenon for the Laval nozzle exit. The maximum total temperature of the gas phase at the Laval nozzle exit formed by the Lw of 0 mm, 2 mm, and 4 mm were 300 K, 959 K, and 1700 K, respectively. Thus, by increasing the Lw value, the total temperature of the gas phase was rapidly improved at the exit of the Laval nozzle, which further accelerated the wear phenomenon at the exit of the Laval nozzle. Besides, axial velocities at the end of the potential core formed by the Lw of 0 mm, 2 mm, and 4 mm were 483.7 m/s, 480.0 m/s, and 478.7 m/s, respectively. As a result, the wear phenomenon reduced the impaction ability of the oxygen jet, which suppressed the impaction depth and radius, resulting in a smaller droplet generation rate.
The Influence of the Plasma Electrolytic Oxidation Parameters of the Mg-AZ31B Alloy on the Micromechanical and Sclerometric Properties of Oxide Coatings
Authors: Niedźwiedź Mateusz , Bara Marek , Korzekwa Joanna , Barylski Adrian , Kaptacz Sławomir
Published: November 2024

This manuscript presents the influence of manufacturing process parameters (peak current density, frequency, process time) on the micromechanical and sclerometric properties of oxide coatings. These parameters were selected based on Hartley’s experimental design, considering three variables at three levels. The coatings were produced on the AZ31B magnesium alloy using the plasma electrolytic oxidation (PEO) method. A trapezoidal voltage waveform and an alkaline, two-component electrolyte were used during the process. The micromechanical and sclerometric properties were assessed by measuring the hardness (HIT) and Young’s modulus (EIT) and determining three critical loads: Lc1 (the critical load at which the first coating damage occurred—Hertz tensile cracks within the scratch), Lc2 (the critical load causing the first cohesive damage to the coating), and Lc3 (the load at which the coating was completely destroyed). Scratch tests were supplemented with profilographometric measurements, which were used to generate isometric images. To identify the relationship between micromechanical and sclerometric properties and the manufacturing parameters, statistical analysis was performed. Research has demonstrated that the plasma electrolytic oxidation (PEO) process improves the micromechanical and adhesive properties of oxide coatings on the AZ31B magnesium alloy. The key process parameters, including peak current density, frequency, and duration, are crucial in determining these enhanced properties.
Antibody–Drug Conjugates: A Start of a New Era in Gynecological Cancers
Authors: Fasih Samir , Welch Stephen , Lohmann Ana Elisa
Published: November 2024

Antibody–drug conjugates (ADCs) are a new class of therapeutic agents designed to target specific antigens on tumor cells, combining the specificity of monoclonal antibodies with the cytotoxicity of chemotherapy agents. ADCs have been available for over a decade, but in gynecological cancers, these agents are relatively new with great promise ahead. More than 80% of ongoing trials in gynecological cancers are evaluating ADCs’ safety and efficacy, of which 40% are early-phase trials. Around twenty ADCs are currently under investigation, either alone or in combination with chemotherapies or immune checkpoint inhibitors. Among them, mirvetuximab soravtansine has been recently approved by the Food and Drug Administration (FDA) in platinum-resistant ovarian cancer with high folate-α receptor expression, as a single agent or in combination. Tisotumab vedotin and trastuzumab deruxtecan are also now approved by the FDA in patients with pre-treated cervical and uterine cancers and further investigation is ongoing. Overall, the toxicity profiles of ADCs are acceptable. Ocular toxicity is one of the specific side effects of some ADCs, but most of the cases are manageable with the use of prophylactic steroids and dose adjustments. This review aims to provide an overview of the fundamental and operational features of ADCs and examine the latest and most promising data, with a particular focus on the Canadian viewpoint.
Traditional Use, Chemical Constituents, and Pharmacological Activity of Maytenus elaeodendroides Stem Bark
Authors: García Trina H. , Spengler Iraida , Fernández Antonio , Rodeiro Idania , Hernández-Balmaseda Ivones , Céspedes Ilianet , Garrido Gabino , dos Santos Lourdes Campaner , Vilegas Wagner , Celano Rita , D’Elia Maria
Published: November 2024

Plants belonging to the genus Maytenus are members of the Celastraceae family. They have been widely used by different peoples as treatment for curing many diseases. The aim of this study was to explore the anti-inflammatory and antioxidant properties of Maytenus elaeodendroides stem bark extracts, an endemic Cuban plant. The antioxidant activity of four extracts (EtOH, EtOAc, n-BuOH, and diethyl ether/petroleum ether 1:1) was determined using DPPH and FRAP methods. Meanwhile, anti-inflammatory effects by the edema method were induced by croton oil in the mouse ear. The investigated extracts showed radical reduction capacity and prevented ear inflammation at doses of 4 mg/ear. In addition, FIA/ESI/IT/MSn was used to determine the qualitative chemical composition of the EtOAc extract and allowed the identification of five flavan-3-ol monomers, four dimers, and other proanthocyanidin oligomers. From this extract three flavan-3-ol compounds (elaeocyanidin and 4′-O-methylgallocatechin), one of them new (2′-hydroxy-4′-methoxy-epigallocatechin), and a proanthocyanidin dimer (afzelechin-(4β→8)-4′-O-methylepigallocatechin) were isolated and identified by the chromatographic method and spectroscopic techniques, mainly ESI-MS and NMR spectroscopic methods.
Aggregate Size Mediated the Changes in Soil Microbial Communities After the Afforestation of a Former Dryland in Northwestern China
Authors: Zhang Deming , Bai Ling , Wang Wei , Wang Yanhe , Chen Tiankun , Yang Quan , Chen Haowen , Kang Shuning , Zhu Yongan , Liu Xiang
Published: November 2024

Although the afforestation of former arable lands is a common global land-use conversion, its impact on soil microbial communities at the aggregate scale has not been adequately addressed. In this study, soil samples were categorized into large macroaggregates (LM, >2 mm), small macroaggregates (SM, 2–0.25 mm), and microaggregates (MI, <0.25 mm) to assess the changes in microbial composition, diversity, network complexity, and network stability within soil aggregates after the afforestation of a former dryland in northwestern China. The results revealed that afforestation enhanced the relative abundance of Actinobacteriota, Chloroflexi, Ascomycota, and Mortierellomycota within the soil aggregates, suggesting that these phyla may have greater advantages in microbial communities post-afforestation. The Shannon–Wiener and Pielou indices for bacterial communities showed no significant differences between land-use types across all aggregate fractions. However, the alpha diversity of fungal communities within the LM and SM significantly increased after afforestation. Bray–Curtis dissimilarity indices showed that afforestation altered bacterial beta diversity within the LM and MI but had a minimal impact on fungal beta diversity across all three aggregate fractions. The topological features of cross-kingdom microbial co-occurrence networks within the soil aggregates generally exhibited a decreasing trend post-afforestation, indicating a simplification of microbial community structure. The reduced robustness of microbial networks within the LM and SM fractions implies that afforestation also destabilized the structure of microbial communities within the macroaggregates. The composition of the soil microbial communities correlated closely with soil carbon and nitrogen contents, especially within the two macroaggregate fractions. The linkages suggests that improved resource conditions could be a key driver behind the shifts in microbial communities within soil aggregates following afforestation. Our findings indicate that the impact of afforestation on soil microbial ecology can be better understood by soil aggregate fractionation.
Utilizing Artificial Intelligence for Microbiome Decision-Making: Autism Spectrum Disorder in Children from Bosnia and Herzegovina
Authors: Bašić-Čičak Džana , Hasić Telalović Jasminka , Pašić Lejla
Published: November 2024

Background/Objectives: The study of microbiome composition shows positive indications for application in the diagnosis and treatment of many conditions and diseases. One such condition is autism spectrum disorder (ASD). We aimed to analyze gut microbiome samples from children in Bosnia and Herzegovina to identify microbial differences between neurotypical children and those with ASD. Additionally, we developed machine learning classifiers to differentiate between the two groups using microbial abundance and predicted functional pathways. Methods: A total of 60 gut microbiome samples (16S rRNA sequences) were analyzed, with 44 from children with ASD and 16 from neurotypical children. Four machine learning algorithms (Random Forest, Support Vector Classification, Gradient Boosting, and Extremely Randomized Tree Classifier) were applied to create eight classification models based on bacterial abundance at the genus level and KEGG pathways. Model accuracy was evaluated, and an external dataset was introduced to test model generalizability. Results: The highest classification accuracy (80%) was achieved with Random Forest and Extremely Randomized Tree Classifier using genus-level taxa. The Random Forest model also performed well (78%) with KEGG pathways. When tested on an independent dataset, the model maintained high accuracy (79%), confirming its generalizability. Conclusions: This study identified significant microbial differences between neurotypical children and children with ASD. Machine learning classifiers, particularly Random Forest and Extremely Randomized Tree Classifier, achieved strong accuracy. Validation with external data demonstrated that the models could generalize across different datasets, highlighting their potential use.
Nash Bargaining-Based Coordinated Frequency-Constrained Dispatch for Distribution Networks and Microgrids
Authors: Zhou Ziming , Wang Zihao , Zhang Yanan , Wang Xiaoxue
Published: November 2024

As the penetration of distributed renewable energy continues to increase in distribution networks, the traditional scheduling model that the inertia and primary frequency support of distribution networks are completely dependent on the transmission grid will place enormous regulatory pressure on the transmission grid and hinder the active regulation capabilities of distribution networks. To address this issue, this paper proposes a coordinated optimization method for distribution networks and microgrid clusters considering frequency constraints. First, the confidence interval of disturbances was determined based on historical forecast deviation data. On this basis, a second-order cone programming model for distribution networks with embedded frequency security constraints was established. Then, microgrids performed economic dispatch considering the reserves requirement to provide inertia and primary frequency support, and a stochastic optimization model with conditional value-at-risk was built to address uncertainties. Finally, a cooperative game between the distribution network and microgrid clusters was established, determining the reserve capacity provided by each microgrid and the corresponding prices through Nash bargaining. The model was further transformed into two sub-problems, which were solved in a distributed manner using the ADMM algorithm. The effectiveness of the proposed method in enhancing the operational security and economic efficiency of the distribution networks is validated through simulation analysis.
A Systematic Review of Techno-Economic, Environmental and Socioeconomic Assessments for Vibration Induced Energy Harvesting
Authors: Gudlaugsson Bjarnhedinn , Bronkema Bethany Marguerite , Stepanovic Ivana , Finger David Christian
Published: November 2024

There is a growing need to ensure the resilience of energy and water systems through digitalization, retrofit these systems for cleaner energy systems, and protect public safety in terms of water quality. This resilience requires a reliable power supply that could be provided by harnessing unexploited energy hidden in the current water infrastructure through the deployment of vortex-induced vibration energy harvesters. Therefore, being able to understand the feasibility of deploying these devices across technical, socioeconomic and environmental scales could further enhance successful deployment and integration of these devices. This paper aims to provide a systematic review investigating the development of energy harvester technologies to understand the key methods used to assess their application feasibility. This study used the PRISMA guidelines, and 139 articles were reviewed and synthesized. The trends were visualized, illustrating the current direction in energy harvesting development and application and methods used to assess the feasibility of these devices and technology. The majority of the reviewed studies focused on technical feasibility, design configuration, limitation, and identification of the most optimal application environment. The results revealed a huge opportunity for energy harvesters, especially as a power supply for monitoring sensors. Nevertheless, the results also identified a knowledge gap when it comes to assessing the overall application feasibility of energy harvesting as most studies currently neglect economic feasibility, environmental impacts, social aspects and energy resilience. Assessment tools will help fill this knowledge gap by identifying the key barriers and benefits gained from integrating this technology into existing energy systems and water systems.
Carbon Footprint of Electric Vehicles—Review of Methodologies and Determinants
Authors: Burchart Dorota , Przytuła Iga
Published: November 2024

The carbon footprint of a product and organization is one of the most important environmental indicators in many sectors, including transport. Consequently, electric vehicles (EV) are being introduced as an alternative to achieve decarbonization targets. This article presents an overview of methodologies for assessing the carbon footprint of electric vehicles, including a review of concepts, methods, standards, and calculation models based on the life cycle of the carbon footprint. The article also includes a systematic review of the results of EV carbon footprint analyses. The analysis of current knowledge on the carbon footprint focuses on road transport vehicles: Battery Electric Vehicles (BEV), Fuel Cell Electric Vehicles (FCEV), Hybrid Electric Vehicles (HEV), and Plug-in Hybrid Electric Vehicles (PHEV). Additionally, a review of factors determining the carbon footprint assessment of electric vehicles, considering their entire life cycle, has been conducted.
Evolution of Regional Innovation Strategies Towards the Transition to Green Energy in Europe 2014–2027
Authors: Pylak Korneliusz , Pizoń Jakub , Łazuka Ewa
Published: November 2024

This paper explores the factors influencing regions’ commitment to the EU’s green energy transition during the 2021–2027 period, with a particular focus on the impact of prior commitments and fossil fuel dependence. Using multimodel regression analysis along with a null classification approach with large language models, we assess how regions’ existing green energy initiatives, their dependence on fossil fuels, and specific energy targets shape their progress towards the EU Green Deal goals. The results confirm path dependency in regional energy policies, where regions with prior investments in decarbonization and energy infrastructure show greater commitment in the current period. Fossil-fuel-dependent regions, on the other hand, face structural barriers slowing their transition to green energy. In addition, the study highlights the selective prioritization of decarbonization and energy efficiency goals, while goals such as consumer empowerment and offshore wind energy remain undervalued. The findings underscore the need for a more comprehensive, sustainable approach to energy transition, particularly in regions with significant dependence on fossil fuels. The paper concludes with a discussion of policy implications for achieving a holistic and equitable energy transition across all EU regions.
Single Well Production Prediction Model of Gas Reservoir Based on CNN-BILSTM-AM
Authors: Gu Daihong , Zheng Rongchen , Cheng Peng , Zhou Shuaiqi , Yan Gongjie , Liu Haitao , Yang Kexin , Wang Jianguo , Zhu Yuan , Liao Mingwei
Published: November 2024

In the prediction of single-well production in gas reservoirs, the traditional empirical formula of gas reservoirs generally shows poor accuracy. In the process of machine learning training and prediction, the problems of small data volume and dirty data are often encountered. In order to overcome the above problems, a single-well production prediction model of gas reservoirs based on CNN-BILSTM-AM is proposed. The model is built by long-term and short-term memory neural networks, convolutional neural networks and attention modules. The input of the model includes the production of the previous period and its influencing factors. At the same time, the fitting production and error value of the traditional gas reservoir empirical formula are introduced to predict the future production data. The loss function is used to evaluate the deviation between the predicted data and the real data, and the Bayesian hyperparameter optimization algorithm is used to optimize the model structure and comprehensively improve the generalization ability of the model. Three single wells in the Daniudi D28 well area were selected as the database, and the CNN-BILSTM-AM model was used to predict the single-well production. The results show that compared with the prediction results of the convolutional neural network (CNN) model, long short-term memory neural network (LSTM) model and bidirectional long short-term memory neural network (BILSTM) model, the error of the CNN-BILSTM-AM model on the test set of three experimental wells is reduced by 6.2425%, 4.9522% and 3.0750% on average. It shows that on the basis of coupling the empirical formula of traditional gas reservoirs, the CNN-BILSTM-AM model meets the high-precision requirements for the single-well production prediction of gas reservoirs, which is of great significance to guide the efficient development of oil fields and ensure the safety of China’s energy strategy.
Case Studies of Battery Energy Storage System Applications in the Brazilian Transmission System
Authors: Falcão Djalma M. , Tao Sun , Taranto Glauco N. , Parreiras Thiago J. Masseran A. , Bento Murilo E. C. , Huanca Dany H. , Muzitano Hugo , Esmeraldo Paulo , Lima Pedro , Monteath Lillian , Brandão Roberto
Published: November 2024

This paper presents the preliminary results of studies aiming to use a battery energy storage system (BESS) in the Brazilian transmission system. The main objective of the BESS is to solve congestion problems caused mainly by the large increase in variable renewable generation in certain system areas. The studies were conducted based on actual forecasted system scenarios using a full representation of the electric grid available from the Brazilian system operator data base. In this work, only the steady-state modeling was considered as this may be the first stage in the assessment of a new technology. A qualitative economic comparison of the BESS application with other possible solutions to the congestion problems is also included.
Empowering Forestry Management and Farmers’ Income Growth Through the Digital Economy—Empirical Evidence from Guizhou Province, China
Authors: Yao Lei , Ma Li , Su Kaiwen , Wang Mengxuan , Duan Wei , Wen Yali
Published: November 2024

Facilitating the sustained and stable growth of farmers’ income is crucial for achieving sustainable development in forest regions. As an emerging driving force, the digital economy has demonstrated substantial potential in enhancing farmers’ income and promoting regional economic prosperity in forest areas. Based on survey data from 1043 households across 10 counties in Guizhou Province, China, this study empirically examined the direct and indirect effects of digital economy participation on income growth among farmers in forest regions. The findings revealed that, first, participation in the digital economy significantly contributed to income growth for these households. This effect remained robust across various estimation methods, restricted sample tests, and when replacing dependent variables. Second, forestry management and its diversification played a mediating role in the relationship between digital economy participation and farmers’ income. Participation in the digital economy indirectly influenced income growth by fostering forestry management activities and their diversification. Third, the heterogeneity analysis indicated that digital economy participation had a significant positive impact on the income growth of pure farming households, part-time farming households, and households that had previously escaped poverty. This discovery underscored the unique role of the digital economy in alleviating poverty and preventing its recurrence. The conclusions of this study provide essential theoretical and practical guidance for empowering forestry development through the digital economy and advancing the digital transformation of the forestry industry. More critically, this research presents a novel pathway for the deep integration of the digital economy with forestry, jointly fostering income growth for farmers in forest regions, which holds significant implications for achieving rural sustainable development.
A 35-Year Analysis of Vegetation Cover in Rare-Earth Mining Areas Using Landsat Data
Authors: Zheng Zhubin , Liu Yuqing , Chen Na , Liu Ge , Lei Shaohua , Xu Jie , Li Jianzhong , Ren Jingli , Huang Chao
Published: November 2024

Fractional vegetation cover (FVC) plays a significant role in assessing ecological quality and protection, as well as soil and water conservation. As a typical rare-earth resource county in China, Dingnan County has experienced rapid development due to rare-earth mining, resulting in significant alterations to vegetation cover. To elucidate the spatio-temporal changes in vegetation within Dingnan County over the past 35 years and the effects of natural and human factors on these changes, the spatial and temporal variations in FVC were analyzed using Landsat-TM/OLI multispectral images taken in 1988, 1995, 1997, 2002, 2006, 2013, 2017, and 2023. The findings indicate that (1) vegetation coverage in Dingnan County decreased from 1988 to 2002, followed by a gradual increase; (2) high vegetation cover is predominantly found in forested areas that maintain their natural state, while the central town and mining areas exhibit generally low coverage; (3) there are regional differences in the relationship between vegetation cover and environmental factors in Dingnan County. This research facilitates the alignment of ion-type rare-earth mining with ecological protection, thereby promoting the sustainable development of the mining area and providing scientific guidance for local governments to formulate more effective management and protection strategies for the mining ecosystem. Additionally, this research offers a scientific foundation for mining areas globally to develop sustainable policies and informed decision-making regarding environmental protection and sustainable development.
An Interval Fuzzy Programming Approach to Solve a Green Intermodal Routing Problem for Timber Transportation Under Uncertain Information
Authors: Sun Yan , Zhang Chen , Sun Guohua
Published: November 2024

This study investigates an intermodal routing problem for transporting wood from a storage yard of the timber harvest area to a timber mill, in which the transfer nodes in the intermodal transportation network have multiple service time windows. To improve the environmental sustainability of timber transportation, a carbon tax policy is employed in the routing to reduce the carbon emissions. Uncertain information on the capacities and carbon emission factors of the transportation activities in the intermodal transportation network is modeled using interval fuzzy numbers to enhance the feasibility of the routing optimization in the actual timber transportation. Based on the above consideration, an interval fuzzy nonlinear optimization model is established to handle the specific routing problem. Model defuzzification and linearization are then conducted to obtain an equivalent formulation that is crisp and linear to make the global optimum solution attainable. A numerical experiment is conducted to verify the feasibility of the proposed model, and it reveals the influence of the optimization level and service time windows on the routing optimization, and it confirms that intermodal transportation is suitable for timber transportation. This experiment also analyzes the feasibility of a carbon tax policy in reducing the carbon emissions of timber transportation, and it finds that the performance of this policy is determined by the optimization level given by the timber mill and is not always feasible in all cases. For the case where a carbon tax policy is infeasible, this study proposes a bi-objective optimization that can use Pareto solutions to balance the economic and environmental objectives as an alternative. The bi-objective optimization further shows the relationship between lowering the transportation costs, reducing the carbon emissions, and enhancing the reliability on capacity and budget by improving the optimization level. The conclusions provide managerial insights that can help the timber mill and intermodal transportation operator organize cost-efficient, low-carbon, and reliable intermodal transportation for timber distribution, and support sustainable forest logistics.
Advancing Additive Manufacturing Through Machine Learning Techniques: A State-of-the-Art Review
Authors: Xiao Shaoping , Li Junchao , Wang Zhaoan , Chen Yingbin , Tofighi Soheyla
Published: November 2024

In the fourth industrial revolution, artificial intelligence and machine learning (ML) have increasingly been applied to manufacturing, particularly additive manufacturing (AM), to enhance processes and production. This study provides a comprehensive review of the state-of-the-art achievements in this domain, highlighting not only the widely discussed supervised learning but also the emerging applications of semi-supervised learning and reinforcement learning. These advanced ML techniques have recently gained significant attention for their potential to further optimize and automate AM processes. The review aims to offer insights into various ML technologies employed in current research projects and to promote the diverse applications of ML in AM. By exploring the latest advancements and trends, this study seeks to foster a deeper understanding of ML’s transformative role in AM, paving the way for future innovations and improvements in manufacturing practices.
Eye Tracking and Human Influence Factors’ Impact on Quality of Experience of Mobile Gaming
Authors: Nawaz Omer , Khatibi Siamak , Sheikh Muhammad Nauman , Fiedler Markus
Published: November 2024

Mobile gaming accounts for more than 50% of global online gaming revenue, surpassing console and browser-based gaming. The success of mobile gaming titles depends on optimizing applications for the specific hardware constraints of mobile devices, such as smaller displays and lower computational power, to maximize battery life. Additionally, these applications must dynamically adapt to the variations in network speed inherent in mobile environments. Ultimately, user engagement and satisfaction are critical, necessitating a favorable comparison to browser and console-based gaming experiences. While Quality of Experience (QoE) subjective evaluations through user surveys are the most reliable method for assessing user perception, various factors, termed influence factors (IFs), can affect user ratings of stimulus quality. This study examines human influence factors in mobile gaming, specifically analyzing the impact of user delight towards displayed content and the effect of gaze tracking. Using Pupil Core eye-tracking hardware, we captured user interactions with mobile devices and measured visual attention. Video stimuli from eight popular games were selected, with resolutions of 720p and 1080p and frame rates of 30 and 60 fps. Our results indicate a statistically significant impact of user delight on the MOS for most video stimuli across all games. Additionally, a trend favoring higher frame rates over screen resolution emerged in user ratings. These findings underscore the significance of optimizing mobile gaming experiences by incorporating models that estimate human influence factors to enhance user satisfaction and engagement.
LINC01614 Promotes Oral Squamous Cell Carcinoma by Regulating FOXC1
Authors: Che Hongze , Zhang Xun , Cao Luo , Huang Wenjun , Lu Qing
Published: November 2024

Background: Long non-coding RNAs (lncRNAs) are pivotal mediators during the development of carcinomas; however, it remains to be investigated whether lncRNAs are implicated in oral squamous cell carcinoma (OSCC). Methods: In this study, quantitative real-time PCR was conducted for detecting the expression of LINC01614 in OSCC cell lines. The biological functions of LINC01614 were assessed by loss- and gain-of-function experiments conducted both in vivo and in vitro. Cellular proliferation, migration, and invasion were investigated herein, and dual luciferase reporter assays were additionally performed to explore the relationships among LINC01614, miR-138-5p, and Forkhead box C1 (FOXC1). Results: The research presented herein revealed that OSCC cells express high levels of LINC01614. Functional experiments employing cellular and animal models demonstrated that LINC01614 knockdown repressed the malignant phenotypes of OSCC cells, including their growth, invasiveness, and migration. Further investigation revealed that LINC01614 absorbs miR-138-5p miRNA by functioning as a competing endogenous RNA to downregulate the abundance of FOXC1. Conclusions: The findings revealed that LINC01614 contributes to the progression of OSCC by targeting the FOXC1 signaling pathway. The study provides insights into a novel mechanistic process to regulate the development of OSCC, and established a possible target for the therapeutic management of OSCC.
Deciphering Carotenoid and Flowering Pathway Gene Variations in Eastern and Western Carrots (Daucus carota L.)
Authors: Cholin Sarvamangala S. , Kulkarni Chaitra C. , Grzebelus Dariusz , Jakaraddi Rashmi , Hundekar Aishwarya , Chandan B. M. , Archana T. S. , Krishnaja Nair R. , Prabhuling G. , Ondrasek Gabrijel , Simon Philipp
Published: November 2024

Background/Objectives: Carrot is a major root vegetable in the Apiaceae owing to its abundant carotenoids, antioxidants, vitamins, and minerals. The modern dark orange western carrot was derived from sequential domestication events from the white-rooted wild form to the pale orange-, purple-, or yellow-rooted eastern carrot. Genetic and molecular studies between eastern and western carrots are meager despite their evolutionary relatedness. Methods: Twelve RNA seq libraries obtained from distinct eastern and western cultivars at vegetative and reproductive developmental stages were utilized to identify differentially expressed genes (DEGs) to decode the key molecular genetic changes in carotenoid and flowering pathways. Results: In the carotenoid pathway, an upregulation of the PSY, CRTISO, and LCYE genes was observed in the western cultivar, while the eastern cultivar exhibited a higher abundance of downstream enzymes, particularly CCD and NCED1. These later enzymes are crucial in linking apocarotenoids and xanthin-mediated ABA signaling. In the flowering pathway, we noted a greater expression of DEGs associated with the photoperiod and vernalization pathways in the western cultivar. In contrast, the eastern cultivar displayed a dominance of genes from the autonomous pathway (FLD, LD, FLK, and PEBP) that function to repress FLC. The experimental validation of 12 key genes through quantitative real-time PCR further confirms their functional role in carrots. Conclusions: The identified key regulatory genes in these major pathways are valuable for designing breeding strategies for manipulating carotenoid content and flowering time while developing climate-specific carrots. The knowledge of carotenoid and flowering pathways is advantageous in producing nutritionally improved roots and seeds in carrots across diverse climates.
Noonan Syndrome: Relation of Genotype to Cardiovascular Phenotype—A Multi-Center Retrospective Study
Authors: Ilic Nikola , Krasic Stasa , Maric Nina , Gasic Vladimir , Krstic Jovana , Cvetkovic Dimitrije , Miljkovic Vesna , Zec Boris , Maver Ales , Vukomanovic Vladislav , Sarajlija Adrijan
Published: November 2024

Background: Noonan syndrome (NS) is a congenital genetic disorder with a prevalence of 1 in 1000 to 2500 live births, and is characterized by distinctive facial features, short stature, chest deformities, and congenital heart disease. This study aims to evaluate the prevalence of specific genetic mutations and their impact on cardiovascular and other outcomes in NS. Methods: We conducted a retrospective clinical study of 25 pediatric patients diagnosed with NS at two institutions: The Mother and Child Health Care Institute of Serbia and the Clinic for Children Diseases, University Clinical Center of the Republic of Srpska. Patients underwent whole-exome sequencing (WES) to identify genetic mutations. Clinical data, including cardiovascular manifestations, psychomotor development, and stature, were analyzed in relation to mutation types. Results: The cohort comprised 60% male and 40% female patients, with a median age at diagnosis of 7.2 years. Cardiovascular abnormalities were present in 88% of patients. Mutations in PTPN11 were most commonly associated with pulmonary valve stenosis (PVS), while RAF1 mutations were prevalent in patients with hypertrophic cardiomyopathy (HCM). No significant association was found between cardiac disease and delayed psychomotor development (p = 0.755), even though the likelihood ratio showed significance in that regard (p = 0.018). Short stature was observed in 48% of patients but was not significantly correlated with genetic type of disease, presence of cardiac disease, or developmental delay. Conclusions: The study confirms the high prevalence of cardiovascular manifestations in NS and highlights genotype–phenotype correlations. While cardiac abnormalities are common, their impact on psychomotor development and stature is less clear. Further research is needed to explore genetic interactions influencing these outcomes and refine clinical management strategies.
Inherited Unbalanced Reciprocal Translocation with 18p11.32p11.21 Tetrasomy and 9q34.3 Trisomy in a Fetus Revealed by Cell-Free Fetal DNA (cffDNA) Testing: Cytogenetic and Cytogenomic Characterization in Prenatal Diagnosis
Authors: Ardisia Carmela , De Falco Luigia , Savarese Giovanni , Ruggiero Raffaella , Suero Teresa , Petrillo Nadia , Ianniello Monica , Sirica Roberto , Mori Alessio , Cino Davide , Barbato Maria , Vitiello Giuseppina , Fico Antonio
Published: November 2024

Background/Objective: Balanced reciprocal translocations are structural chromosomal anomalies that involve a mutual exchange of segments between two non-homologous chromosomes with a consequent 50–80% risk of conceiving fetuses with unbalanced chromosomal anomalies. This study describes a 37-year-old woman, at 13 + 5 weeks of gestation, who is a balanced reciprocal translocation 46,XX,t(9;18)(q34;q11.2) carrier, with a high-risk non-invasive prenatal screening test, NIPT, for chromosome 18 aneuploidy. Methods: The highlighted aneuploidy was characterized with cytogenetic, FISH and SNP-array techniques. Results: Cytogenetic analysis, performed on flask-cultured amniocytes, indicated a 48,XX,+2mar karyotype on 50 metaphases. SNP array analysis showed a 15.3 Mb duplication of chromosome 18p (arr[hg19]18p11.32-p11.21(12,842-15,303,932)x4), consistent with a partial tetrasomy 18p, and a 926 kbp duplication of chromosome 9q (arr[GRCh37]9q34.3(140,118,286-141,044,489)x3), consistent with partial trisomy 9q. FISH analysis with a 9q34.3 probe was performed on flask-cultured amniocytes’ metaphases, highlighting the presence of a third signal on one of the two marker chromosomes (18p11.32-p11.21). Conclusions: The evidence of such partial aneuploidies suggests that different mutational events may be possible at meiotic segregation or probably post-meiotic segregation. The results obtained highlight the high sensitivity of the screening test, NIPT, with massive parallel sequencing, and the usefulness of cytogenetics, cytogenomics and molecular biology techniques, in synergy, to characterize and confirm positive NIPT results.
A Modular Genetic Approach to Newborn Screening from Spinal Muscular Atrophy to Sickle Cell Disease—Results from Six Years of Genetic Newborn Screening
Authors: Bzdok Jessica , Czibere Ludwig , Burggraf Siegfried , Pauly Natalie , Maier Esther M. , Röschinger Wulf , Becker Marc , Durner Jürgen
Published: November 2024

Background/Objectives: Genetic newborn screening (NBS) has already entered the phase of common practice in many countries. In Germany, spinal muscular atrophy (SMA), severe combined immunodeficiency (SCID) and sickle cell disease (SCD) are currently a mandatory part of NBS. Here, we describe the experience of six years of genetic NBS including the prevalence of those three diseases in Germany. Methods: Samples and nucleic acids were extracted from dried blood spot cards, commonly used for NBS. A qPCR assay was used to detect disease-causing variants for SMA and SCD, and the detection of T-cell receptor excision circles (TRECs) was performed for SCID screening. Results: The results of the NBS of over 1 million newborns for SMA, approximately 770,000 for SCID and over 410,000 for SCD are discussed in detail. In these newborns, we have identified 121 cases of SMA, 15 cases of SCID and syndrome-based immunodeficiencies and 77 cases of SCD or β-thalassemia. Conclusions: The flexibility of multiplex qPCR is assessed as an effective tool for incorporating different molecular genetic markers for screening. The processing of dried blood spot (DBS) filter cards for molecular genetic assays and the assays are described in detail; turn-around times and cost estimations are included to give an insight into the processes and discuss further options for optimization. The identified cases are in the range expected for the total number of screened newborns, but present a more exact view on the actual prevalences for Germany.
Accurate Feature Extraction from Historical Geologic Maps Using Open-Set Segmentation and Detection
Authors: Saxton Aaron , Dong Jiahua , Bode Albert , Jaroenchai Nattapon , Kooper Rob , Zhu Xiyue , Kwark Dou Hoon , Kramer William , Kindratenko Volodymyr , Luo Shirui
Published: November 2024

This study presents a novel AI method for extracting polygon and point features from historical geologic maps, representing a pivotal step for assessing the mineral resources needed for energy transition. Our innovative method involves using map units in the legends as prompts for one-shot segmentation and detection in geological feature extraction. The model, integrated with a human-in-the-loop system, enables geologists to refine results efficiently, combining the power of AI with expert oversight. Tested on geologic maps annotated by USGS and DARPA for the AI4CMA DARPA Challenge, our approach achieved a median F1 score of 0.91 for polygon feature segmentation and 0.73 for point feature detection when such features had abundant annotated data, outperforming current benchmarks. By efficiently and accurately digitizing historical geologic map, our method promises to provide crucial insights for responsible policymaking and effective resource management in the global energy transition.
Co-Production Within Academic Constraints: Insights from a Case Study
Authors: Callahan Evelyn , Murtagh Niamh , Pooley Alison , Pannell Jenny , Benzimra Alison
Published: November 2024

Co-production in research offers the potential for multiple benefits, including amplifying the voices of the marginalised, reducing power inequalities between academic researchers and co-researchers outside of academia, increased likelihood of impact, and improvement in the research process. But alongside increased interest in co-production, there is increased awareness of its contextual constraints. Key amongst these are institutional orthodoxies in academia, including time-limited, project-based research and precarious employment for junior researchers. To examine how the potential benefits of co-production can be achieved within the constraints of current academic systems, a case study project was assessed against a documented set of expectations for the co-production of research with older adults. The case study was a research project conducted with seven almshouse communities in England on the topic of social resilience. The wider almshouse communities—staff, trustees, and residents—were involved in co-production. The assessment concluded that co-production led to rich data and deep understanding. Co-production aided the development of skills and experiences of the co-researchers, resulted in changes in practice, and challenged power differentials, albeit in limited ways, but could not ensure the sustainability of relationships or impact. Key elements for effective co-production included the approach to and governance of the project, the formation of a Residents Advisory Group, and planning for the limited commitment that individuals and organisations outside of academia may be able to contribute to research.
Screen Exposure in 4-Year-Old Children: Association with Development, Daily Habits, and Ultra-Processed Food Consumption
Authors: Gomes Gabriela M. D. , Souza Rafaela C. V. , Santos Tamires N. , Santos Luana C.
Published: November 2024

This study aimed to investigate the association between child development, daily habits, and ultra-processed food consumption with screen exposure in 4-year-old children. A cross-sectional study was conducted using a questionnaire that included sociodemographic data, the child’s daily habits, and screenings for child development and eating habits. The daily screen exposure time (cell phone, computer, television, and/or tablet) was measured in minutes and classified as inadequate if >60 min. We conducted bivariate analyses and a generalized linear model. Overall, 362 caregivers–children pairs were investigated. The average screen time per child was 120 min (IQR: 120), and most of the children (71%) showed inadequate screen time for the age group. The longest screen time was associated with the lowest score in child development (β = −0.03; p = 0.01), an increased habit of eating in front of screens (β = 0.34; p < 0.001), and the highest score of ultra-processed foods (UPFs) (β = 0.05; p = 0.001). The sample showed a high prevalence of inadequate screen time, and this has been associated with the lowest score in child development, an increased habit of eating in front of screens, and the highest score of UPFs.
Decentralization Matters: Association of Adherence to Treatment and Distance for the Management of Non-Communicable Diseases in Rural Tanzania
Authors: Belardi Paolo , Bazzanini Noemi , Cera Francesca , Mutalemwa Katunzi , Tognon Francesca , Ndile Emmanuel , Mele Alessandro , Itambu Rehema , Naftali Rhoda , Kakala Bernard , Kayombo Veronica , Mfaume Benjamin , Ndunguru Bruno , Marwa Samwel , Saugo Mario
Published: November 2024

Since March 2019, a non-communicable diseases program has been established at hospital level, with enrollment and clinical reassessment every 6 months. Since July 2023, monthly enrollment and visits have also been conducted at health center level. This study aimed at assessing the adherence to scheduled follow-up visits following the decentralization of the integrated NCDs program from Hospital to Health Center level and investigate factors influencing follow-up adherence. The study was performed in a rural district in Iringa Region, Tanzania. Adherence was measured at both levels. Multivariate regression analysis was conducted to describe socio-demographic and clinical factors influencing attendance at the 6-month hospital-level visit. Among 2198 patients enrolled at the hospital level, weighted adherence over 42 months was 40.8% (95% CI 39.0–42.6%) at the 6-month visit. Multivariate analysis revealed that as the distance from the hospital increased, the probability of attendance decreased (OR 0.17; 95% CI: 0.08–0.39). Among 571 patients enrolled at the residence level, adherence over the first 10 months of program implementation was 91.6% (90.4–92.8%). The findings showed that distance was by far the most important barrier to follow-up adherence and suggested that decentralizing the program from the hospital to peripheral health centers may ensure high follow-up rates.
Cultural and Practical Barriers to Seeking Help for Intimate Partner Violence Among Korean Immigrants: Exploring Gender and Age Differences
Authors: Cho Soon , Choi Y. Joon , Han Jeong-Yeob , Kim Hanyoung , Fife Stephen T.
Published: November 2024

Immigrants in the United States, including Korean immigrants, are more vulnerable to intimate partner violence (IPV), yet they are less likely to seek help than non-immigrants. This qualitative study sought to understand barriers to seeking help for IPV among Korean immigrants and to explore age and gender differences in Korean immigrants’ understanding of these barriers. We conducted four focus groups with 38 adults grouped by age and gender. Thematic analysis was employed to understand Korean immigrants’ perceptions of IPV and barriers to help-seeking. As a result, four prominent themes emerged: (1) differential understanding of IPV, (2) Confucian cultural influences on IPV, (3) cultural barriers to help-seeking, and (4) practical barriers to help-seeking. Women participants showed an in-depth understanding of IPV, recognizing various forms beyond physical violence within the immigrant social context. Younger participants highlighted the intergenerational transmission of IPV. Cultural factors, rooted in Confucianism such as strict gender roles and women’s self-sacrifice, exacerbate IPV. Cultural barriers include shame culture, treating IPV as a private matter, and the emphasis on family unity. Practical barriers are linked to the challenges immigrants face. These insights illustrate the need for targeted IPV interventions tailored to distinct gender and age demographics within the community.