bluuebunny/crossref_metadata_2025 huggingface dataset:
DNA-Protective, Antioxidant and Anti-Carcinogenic Potential of Meadowsweet (Filipendula ulmaria) Dry Tincture
Authors: Andonova Tsvetelina , Muhovski Yordan , Apostolova Elena , Naimov Samir , Mladenova Silviya , Slavov Iliya , Dincheva Ivayla , Georgiev Vasil , Pavlov Atanas , Dimitrova-Dyulgerova Ivanka
Published: October 2024

Nowadays, interest in natural antioxidants (especially phenolics) for the prevention of oxidative stress-related diseases is increasing due to their fewer side effects and more potent activity than some of their synthetic analogues. New chemical and pharmacological studies of well-known herbal substances are among the current trends in medicinal plant research. Meadowsweet (Filipendula ulmaria) is a popular herb used in traditional medicine to treat various diseases (including rheumatic-, inflammatory- and tumor-related disease, etc.). The dry tincture of Filipendulae ulmariae herba, collected from the Bulgarian flora, was analyzed using the HPLC method and bioassayed for antioxidant, antiproliferative and DNA-protective activities against oxidative damage. The HPLC phenolic profile showed 12 phenolics, of which salicylic acid (18.84 mg/g dry extract), rutin (9.97 mg/g de), p-coumaric acid (6.80 mg/g de), quercetin (4.47 mg/g de), rosmarinic acid (4.01 mg/g de) and vanillic acid (3.82 mg/g de) were the major components. The high antioxidant potential of the species was confirmed by using four methods, best expressed by the results of the CUPRAC assay (10,605.91 μM TE/g de). The present study reports for the first time the highly protective activities of meadowsweet dry tincture against oxidative DNA damage and its antiproliferative effect against hepatocellular carcinoma (HepG2 cell line). Meadowsweet dry tincture possesses great potential to prevent diseases caused by oxidative stress.
Innovative Experimental Assessment of Human–Structure Interaction Effects on Footbridges with Accurate Multi-Axial Dynamic Sensitivity Using Real-Time Hybrid Simulation
Authors: Castillo Bryan , Marulanda Johannio , Thomson Peter
Published: October 2024

This study evaluates the dynamic performance of a reference footbridge under human–structure interaction (HSI) effects using real-time hybrid simulation (RTHS). The footbridge, designed with precise multi-axial dynamic sensitivity, is tested under pedestrian gait velocities of 1.20, 1.50, and 1.80 m·s−1. The RTHS framework involves an analytical continuous model of the footbridge as a numerical substructure and real human gait loads as the experimental substructure. The results reveal significant dynamic coupling between pedestrian-induced loads and the responses of the structure. Lateral vibrations exhibit a fundamental frequency of approximately 1.0 Hz, whereas vertical vibrations peaked near 2.0 Hz. Dynamic synchronization, particularly at higher gait velocities, amplified the structural vibrations, with lateral loading increasing by up to 300% in the middle span. Vertical loads show substantial amplification and attenuation depending on gait velocity and footbridge location. Lateral accelerations display a dispersion of approximately 15.0%, whereas vertical accelerations showed higher variability, with dispersions reaching up to 20%. The RTHS technique demonstrates high fidelity and accuracy, with global errors below 2.95% and delays of less than 2.10 ms across all evaluated directions. These results emphasize the critical importance of accounting for HSI effects in the design of pedestrian footbridges because human-induced vibrations can significantly impact structural serviceability and user comfort. This study offers important insights into optimizing footbridge design to mitigate the risks of excessive vibrations and ensure both safety and functionality under typical pedestrian loads.
Text Network Analysis to Develop a Search Strategy for a Systematic Review
Authors: Leem Subeen , Shin Jieun , Kim Jong-Yeup , Shim Sung Ryul
Published: October 2024

Setting the population, intervention, comparison, and outcome (PICO) elements during a search strategy development stage for a systematic review (SR) defines a research question specifically. In contrast to traditional methods that rely on researcher discretion, we propose a text network analysis (TNA) method using the R language to set the correct basis for the PICO. First, we collected 80 related papers from the PubMed database using ‘Health Impact Assessment of arsenic exposure’ as an example topic. Next, we recorded the keywords of each paper into a dataframe and converted the dataframe into an edge list format to create a network. Finally, we confirmed the connectivity and frequency of each keyword through network visualization and the importance of keywords according to three metrics through centrality analysis. As a result, arsenic could be expected to have detrimental effects on the occurrence of heart- and blood-related diseases or on mothers. By setting important keywords as the PICO elements known through a TNA, the reliability of SRs is improved, and this methodology can be equally applied to various topics.
Design and Analysis of a Planar Six-Bar Crank-Driven Leg Mechanism for Walking Robots
Authors: Amine Semaan , Prasad Benrose , Saber Ahmed , Mokhiamar Ossama , Gazo-Hanna Eddie
Published: October 2024

This study presents the design and a thorough analysis of a six-bar crank-driven leg mechanism integrated with a skew pantograph, developed for walking robots. The mechanism’s dimensions were optimized using a rigorous dimensional synthesis process in GIM software (version 2024). Subsequently, a detailed kinematic analysis was performed in GIM to simulate the leg’s motion trajectory, velocity, and acceleration. In parallel, kinematic equations were formulated using the vector loop method, implemented in MATLAB (version R2013-b), and compared with the GIM results for validation, demonstrating the strong agreement between both tools. These results confirm the mechanism’s ability to generate a compact, high-lift foot trajectory while maintaining system stability and energy efficiency. An inverse dynamic analysis was carried out to determine the actuator’s driving torque, ensuring efficient operation under expected load conditions. Furthermore, topology optimization conducted in SOLIDWORKS (version 2021) significantly reduced the weight of the ground-contacting link while preserving its structural integrity. A subsequent stress analysis validated the mechanical viability of the optimized design, supporting its feasibility for real-world implementation. This research provides a robust foundation for the development of a functional prototype. Its potential applications include mobile robots for sectors such as agriculture and all-terrain vehicles, where efficient, reliable, and adaptive locomotion is crucial. The proposed mechanism strikes an optimal balance between mechanical simplicity, cost-effectiveness, and high performance, making it well-suited for challenging operational environments.
Bridging the Vocabulary Gap: Using Side Information for Deep Knowledge Tracing
Authors: Xu Haoxin , Yin Jiaqi , Qi Changyong , Gu Xiaoqing , Jiang Bo , Zheng Longwei
Published: October 2024

Knowledge tracing is a crucial task in personalized learning that models student mastery based on historical data to predict future performance. Currently, deep learning models in knowledge tracing predominantly use one-hot encodings of question, knowledge, and student IDs, showing promising results. However, they face a significant limitation: a vocabulary gap that impedes the processing of new IDs not seen during training. To address this, our paper introduces a novel method that incorporates aggregated features, termed ‘side information’, that captures essential attributes such as student ability, knowledge mastery, and question difficulty. Our approach utilizes side information to bridge the vocabulary gap caused by ID-based one-hot encoding in traditional models. This enables the model, once trained on one dataset, to generalize and make predictions on new datasets with unfamiliar students, knowledge, or questions without the need for retraining. This innovation effectively bridges the vocabulary gap, reduces the dependency on specific data representations, and improves the overall performance of the model. Experimental evaluations on five distinct datasets show that our proposed model consistently outperforms baseline models, using fewer parameters and demonstrating seamless adaptability to new contexts. Additionally, ablation studies highlight that including side information, especially regarding students and questions, significantly improves knowledge tracing effectiveness. In summary, our approach not only resolves the vocabulary gap challenge but also offers a more robust and superior solution across varied datasets.
Modeling the Effect of Climate Change on Evapotranspiration in the Thrace Region
Authors: Deveci Huzur , Konukcu Fatih
Published: October 2024

The aim of this study is to determine the effect of climate change on reference evapotranspiration (ETo) and sunflower and wheat evapotranspiration (ETs and ETw, respectively) in the Trakya Region of Türkiye. ETo Calculator (version 3.2) and CROPWAT 8.0 were used to compute ETo and ET in the reference period (1970–1990), short- (2016–2025), mid- (2046–2055), and long- (2076–2085) terms. Additionally, ETo was tested in 2012 and ETo was simulated for every 1 °C temperature increase up to 5 °C in the reference period. Calculated ETo and ET values for the future were compared with the reference period. For the future, climate data estimated by RegCM3 Regional Climate Model, A2 scenario were used. While the average ETo value of the reference period was 3.3 mm day−1, it was 3.0 mm day−1 in 2012. Compared to the reference period, ETo values change by −3% (3.2 mm day−1), 9% (3.6 mm day−1), and 21% (4.0 mm day−1) in the short-, mid-, and long-term, respectively. The 575 mm ET deficit calculated during the vegetation period of sunflower in the model reference period was forecasted to change by −11% (514 mm), +15% (660 mm), and +25% (721 mm) in the short-, mid-, and long-term, respectively. For wheat, while 59 mm of excess water was calculated in the reference period, it became 193 mm (+227%) in the short-term and a water deficit of 8 mm (−113%) and 6 mm (−110%) in the mid- and long-term, respectively. In addition, it is estimated that there will be an increase of 0.1 mm day−1 (4%) in ETo values for each 1 °C temperature increase compared to the reference period (1970–1990). It was concluded that climate change in the Trakya Region will not significantly affect wheat farming; however, it will cause a serious water deficit in sunflower production.
A Double-Stranded Aptamer for Highly Sensitive Fluorescent Detection of Glutathione S-Transferases
Authors: Cui Wei , Li Suping , Zeng Jiahao , Li Chen , Li Zhaofeng , Wen Xiaohong , Bao Suxia , Mei Yang , Meng Xiangxian , Guo Qiuping
Published: October 2024

Aptamer-based biosensors have been widely constructed and applied to detect diverse targets. Glutathione S-transferase (GST), a pivotal phase II metabolic enzyme, plays a critical role in biotransformation in vivo, and aberrant GST expression is associated with various health risks. Herein, aptamers targeting GST were systematically selected from a randomized single-stranded DNA (ssDNA) library of 79 nucleotides (nt) using a biotinylated GST-immobilized streptavidin agarose (SA) bead SELEX technology. Following rigorous screening across eight rounds, four aptamers with strikingly similar secondary structures emerged. Among these, Seq3 exhibited the highest affinity towards GST and was selected for further optimization. A semi-rational post-SELEX truncation strategy was then employed based on base composition analysis, secondary structure analysis and affinity assessment. This strategy enabled the systematic removal of redundant nucleotides in Seq3 without compromising its affinity, ultimately yielding a truncated aptamer, Seq3-3, which retains its specificity with a compact 39nt length. Building upon Seq3-3, a double-stranded fluorescent aptamer probe was ingeniously designed for the in vitro detection of GST. The detection mechanism hinges on the competitive displacement of the complementary chain from the probe, mediated by the target protein, leading to the separation of the antisense oligonucleotide from the double-stranded complex. This process triggers the restoration of the fluorescence signal, enabling sensitive detection, and the probe exhibits excellent response within a linear range of GST activity ranging from 0 to 1500 U/L. The results show that not only an efficient strategy for screening robust and practicable aptamers but also an ultrahighly sensitive detection platform for GST was established.
The Evolution of Illicit-Drug Detection: From Conventional Approaches to Cutting-Edge Immunosensors—A Comprehensive Review
Authors: Anzar Nigar , Suleman Shariq , Singh Yashda , Kumari Supriya , Parvez Suhel , Pilloton Roberto , Narang Jagriti
Published: October 2024

The increasing use of illicit drugs has become a major global concern. Illicit drugs interact with the brain and the body altering an individual’s mood and behavior. As the substance-of-abuse (SOA) crisis continues to spread across the world, in order to reduce trafficking and unlawful activity, it is important to use point-of-care devices like biosensors. Currently, there are certain conventional detection methods, which include gas chromatography (GC), mass spectrometry (MS), surface ionization, surface-enhanced Raman spectroscopy (SERS), surface plasmon resonance (SPR), electrochemiluminescence (ECL), high-performance liquid chromatography (HPLC), etc., for the detection of abused drugs. These methods have the advantage of high accuracy and sensitivity but are generally laborious, expensive, and require trained operators, along with high sample requirements, and they are not suitable for on-site drug detection scenarios. As a result, there is an urgent need for point-of-care technologies for a variety of drugs that can replace conventional techniques, such as a biosensor, specifically an immunosensor. An immunosensor is an analytical device that integrates an antibody-based recognition element with a transducer to detect specific molecules (antigens). In an immunosensor, the highly selective antigen–antibody interaction is used to identify and quantify the target analyte. The binding event between the antibody and antigen is converted by the transducer into a measurable signal, such as electrical, optical, or electrochemical, which corresponds to the presence and concentration of the analyte in the sample. This paper provides a comprehensive overview of various illicit drugs, the conventional methods employed for their detection, and the advantages of immunosensors over conventional techniques. It highlights the critical need for on-site detection and explores emerging point-of-care testing methods. The paper also outlines future research goals in this field, emphasizing the potential of advanced technologies to enhance the accuracy, efficiency, and convenience of drug detection.
Social Interaction and Online Learning Efficiency for Middle School Students: The Mediating Role of Social Presence and Learning Engagement
Authors: Gao Fangfang , Wang Chunzhen , Xie Han , Hong Jianzhong
Published: October 2024

(1) learning efficiency is recognized as the ultimate goal of online education, as it is related to the quality of online education and the cognitive development of students and is influenced by social interactions. This study explores the mediating roles of social presence and learning engagement in the relationship between social interaction and online learning efficiency, addressing gaps in prior studies that have not yet identified the underlying mechanisms. (2) students from three middle schools (N = 344; Mage = 13.61; 56.68% women) completed self-report questionnaires regarding social interaction, social presence, learning engagement, and learning efficiency. (3) the study findings reveal significant serial mediation effects of social presence and learning engagement in the relationship between learner–instructor and learner–learner interactions and learning efficiency. Specifically, while the indirect effect of learner–instructor interaction through social presence alone (indirect effect = 0.08, 95% CI = [−0.00, 0.17]) was not significant, the pathways through learning engagement (indirect effect = 0.18, 95% CI = [0.11, 0.26]) and the combined mediation through both social presence and learning engagement (indirect effect = 0.06, 95% CI = [0.03, 0.09]) were statistically significant. Similarly, for learner–learner interaction, the indirect effects through social presence (indirect effect = 0.09, 0.17) and learning engagement (indirect effect = 0.17, 95% CI = [0.11, 0.24]) were significant, as was the serial mediation through both mediators (indirect effect = 0.07, 95% CI = [0.04, 0.11]). (4) social presence and learning engagement played crucial mediating roles in the links between social interactions and online learning efficiency, and the predictive efficacy of learner–learner and learner–instructor interactions on online learning efficiency was found to be unequal.
A Systematic Review of Resilience in At-Risk Youth for Psychotic Disorders: An Analysis of Protective and Risk Factors from Recent Literature
Authors: Cojocaru Adriana , Braha Adina , Anastasescu Cătălina Mihaela , Folescu Roxana , Bugi Meda-Ada , Puiu Maria , Zamfir Carmen Lacramioara , Hogea Lavinia , Levai Codrina Mihaela , Bratosin Felix , Danila Alexandra Ioana , Nussbaum Laura
Published: October 2024

Psychotic disorders in youth pose significant challenges for mental health services, necessitating a detailed understanding of the interplay between risk factors and resilience. This systematic review aimed to assess how resilience factors might buffer the adverse effects of risk factors on the development of psychosis among youth, thereby informing targeted interventions. Studies were selected based on criteria including a focus on individuals aged up to 25 years old at risk for psychosis, the examination of both risk factors and resilience, and the use of validated instruments for measuring outcomes. Literature searches were conducted across several databases, such as PubMed, Scopus, and Web of Science. Data extraction emphasized odds ratios (ORs) and hazard ratios (HRs) for risk factors, including familial, developmental, and socio-environmental influences. The review included and analyzed nine studies, encompassing a diverse sample of 140,972 participants. Significant findings indicate that highly supportive familial and community environments significantly reduce the risk of psychosis onset. For instance, children with strong family support and engagement in structured activities demonstrated a 40% lower incidence of developing psychotic symptoms [p < 0.05]. Furthermore, the presence of neurobehavioral deficits, such as impaired verbal memory and attention, emerged as significant predictors of psychosis, with these children exhibiting a threefold increase in risk compared to their peers [OR = 3.2, 95% CI: 2.1–4.8, p < 0.01]. Resilience factors play a critical role in mitigating the impact of psychosocial and neurobiological risks in the development of psychosis among youths. Interventions enhancing resilience could potentially alter the trajectory of psychosis development, emphasizing the need for early and targeted psychosocial interventions to support at-risk populations. This study underscores the importance of fostering resilience through both individual-focused and community-based strategies to prevent the onset of psychotic disorders in vulnerable young populations.
The Usability of Metallurgical Production Waste as a Siliceous Component in Autoclaved Aerated Concrete Technology
Authors: Mészárosová Lenka , Černý Vít , Melichar Jindřich , Ondříčková Pavlína , Drochytka Rostislav
Published: October 2024

The reconstruction of buildings is a complex process that often requires the consideration of the construction load when selecting correct building materials. Autoclaved aerated concrete (AAC)—which has a lower bulk density (compared to traditional masonry materials)—is very beneficial in such applications. A current trend in AAC development is the utilization of secondary raw materials in high-performance AAC, characterized by higher bulk density and compressive strength than regular AAC. The increase in bulk density is achieved by increasing the content of quartz sand in the mixing water. In this study, part of the siliceous component was replaced by ladle slag, foundry sand, furnace lining, and chamotte block powder. These materials are generated as by-products in metallurgy. The substitution rates were 10% and 30%. The samples were autoclaved in a laboratory autoclave for 8 h of isothermal duration at 190 °C with a saturated water vapor pressure of 1.4 MPa. The physical–mechanical parameters were determined, and the microstructure was described by XRD and SEM analyses. The results were compared with traditional AAC, with silica sand being used as the siliceous component. The measurement results show that sand substitution by the secondary raw material is possible, and it does not have a significant impact on the properties of AAC, and in a proper dosage, it can be beneficial for AAC production.
Urban Morphology Classification and Organizational Patterns: A Multidimensional Numerical Analysis of Heping District, Shenyang City
Authors: Liu Shengjun , Zhao Jiaxing , Chen Yijing , Zhang Shengzhi
Published: October 2024

Prior studies have failed to adequately address intangible characteristics and lacked a comprehensive quantification of cultural dimensions. Additionally, such works have not merged supervised and unsupervised classification methodologies. To address these gaps, this study employed multidimensional numerical techniques for precise spatial pattern recognition and urban morphology classification at the block scale. By examining building density, mean floor numbers, functional compositions, and street block mixed-use intensities, alongside historical and contemporary cultural assets within blocks—with assigned weights and entropy calculations from road networks, building vectors, and POI data—a hierarchical categorization of high, medium, and low groups was established. As a consequence, cluster analysis revealed seven distinctive morphology classifications within the studied area, each with unique spatial configurations and evolutionary tendencies. Key findings include the dominance of high-density, mixed-use blocks in the urban core, the persistence of historical morphologies in certain areas, and the emergence of new, high-rise clusters in recently developed zones. The investigation further elucidated the spatial configurations and evolutionary tendencies of each morphology category. These insights lay the groundwork for forthcoming studies to devise morphology-specific management strategies, thereby advancing towards a more scientifically grounded, rational, and precision-focused approach to urban morphology governance.
Probabilistic Loss Assessment for the Typology of Non-Ductile Reinforced Concrete Structures with Flat Slabs, Embedded Beams, and Unreinforced Infill Masonry
Authors: Guamán-Naranjo Mauricio , Poveda-Hinojosa José , Haro-Báez Ana Gabriela
Published: October 2024

Quito, the capital of Ecuador, a development pole, has experienced a population growth of 9% in the last five years. The structural system commonly chosen for housing is reinforced concrete frames with flat slabs, embedded beams, and masonry infill. This typology covers approximately 60% of the residential buildings in the city. Adding to the site’s seismic hazard, this fact results in a city with a high seismic risk. The research presented here is carried out within a probabilistic framework to determine the economic consequences of the main structural typology in the city. The methodology defines the seismic hazard by scaling a database of 200 records to the design spectrum. It models the typology to capture the variability between structures with a solid parametric study. Each capacity curve is analyzed through a nonlinear time history analysis using an equivalent one-degree-of-freedom system. The results show an average annual loss ratio of 0.16%. This metric indicates the vulnerability of the typology and the high repair costs of buildings that will be observed in case of an earthquake. The practical implications of these findings are significant as they contribute to urban planning and policy decisions. Finally, it is observed that the probabilistic method used efficiently generates fragility and vulnerability curves, saving computational time and obtaining expected results.
Epidemiological Study of Adenoid Cystic Carcinoma and Its Outcomes: Insights from the Surveillance, Epidemiology, and End Results (SEER) Database
Authors: Rahouma Mohamed , Khairallah Sherif , Baudo Massimo , Al-Thani Shaikha , Dabsha Anas , Shenouda David , Mohamed Abdelrahman , Dimagli Arnaldo , El Sherbiny Magdy , Kamal Mona , Villena-Vargas Jonathan , Chow Oliver S.
Published: October 2024

Objective: Adenoid cystic carcinoma (ACC) is a rare malignant tumor that mainly arises in the head and neck area. We aimed to compare the long-term survival of patients with ACC based on their geographic regions within the United States using the Surveillance, Epidemiology, and End Results (SEER) registry data. Methods: We queried the SEER database to evaluate the geographic distribution of ACC patients based on inpatient admissions. The states included in the study were divided into four geographical regions (Midwest, Northeast, South, and West) based on the U.S. Census Bureau-designated regions and divisions. Demographic and clinical variables were compared between the groups. Kaplan–Meier curves and Cox regression were used to assess late mortality. Results: A total of 5150 patients were included (4.2% from the Midwest, 17.2% from the Northeast, 22.5% from the South, and 56.1% from the West regions). The median follow-up was 12.3 (95% CI: 11.6–13.1 years). Median overall survival was 11.0 (95% CI: 9.2-NR years), 14.3 (95% CI: 12.4–16.4 years), 11.3 (95% CI: 9.7–14.8 years), and 12.0 (95% CI: 11.3–13.0 years) for Midwest, Northeast, South, and West regions, respectively. In multivariable analysis, older age, male sex, thoracic cancer, the presence of regional and distal disease, receiving chemotherapy, not undergoing surgical resection, and being treated in the West vs. Northeast region were found to be independent predictors of poor survival. We identified a significant survival difference between the different regions, with the West exhibiting the worst survival compared to the Northeast region. Conclusions: In addition to the well-known predictors of late mortality in ACC (tumor location, stage, and treatment modalities), our study identified a lack of social support (being unmarried) and geographic location (West region) as independent predictors of late mortality in multivariable analysis. Further research is needed to explore the causal relationships.
Walnut Shell Biomass Triggered Formation of Fe3C-Biochar Composite for Removal of Diclofenac by Activating Percarbonate
Authors: Zhang Na , Huo Yudong , Pei Chun , Zhang Ying , Xu Lijie , Gan Lu
Published: October 2024

Percarbonate (SPC) as a promising substitute for liquid H2O2 has many advantages in the application of in situ chemical oxidation (ISCO). Developing efficient, cost effective and environmentally friendly catalysts for SPC activation plays the key role in promoting the development of SPC-based ISCO. Herein, the walnut shell biomass was combined with ferric nitrate for the catalytic synthesis of Fe3C@biochar composite (Fe3C@WSB), which demonstrated high efficiency in activating SPC for the removal of diclofenac (DCF). The Fe3C showed average crystallite size of 32.6 nm and the composite Fe3C@WSB demonstrated strong adsorptivity. The prepared Fe3C@WSB could activate both SPC and H2O2 with high efficiency at ca. pH 3 with extremely low leaching of iron, while in a weak acidic condition, higher efficiency of DCF removal was obtained in the Fe3C@WSB/SPC process than in the Fe3C@WSB/H2O2 process. Moreover, the Fe3C@WSB/SPC and Fe3C@WSB/H2O2 processes did not show significant differences when supplied with varying amounts of catalyst or oxidant, but the Fe3C@WSB/SPC process exhibited stronger capability in dealing with relatively highly concentrated DCF solution. Based on quenching experiments and electron spin resonance (ESR) analysis, heterogeneous activation of SPC was assumed as the dominant route for DCF degradation, and both the oxidation by radicals, including •OH, •O2− and CO3•−, combined with electron transfer pathway contributed to DCF degradation in the Fe3C@WSB/SPC process. The cycling experiment results also revealed the stability of Fe3C@WSB. This work may cast some light on the development of efficient catalysts for the activation of SPC.
Small ORFs, Big Insights: Drosophila as a Model to Unraveling Microprotein Functions
Authors: Chanut-Delalande Hélène , Zanet Jennifer
Published: October 2024

Recently developed experimental and computational approaches to identify putative coding small ORFs (smORFs) in genomes have revealed thousands of smORFs localized within coding and non-coding RNAs. They can be translated into smORF peptides or microproteins, which are defined as less than 100 amino acids in length. The identification of such a large number of potential biological regulators represents a major challenge, notably for elucidating the in vivo functions of these microproteins. Since the emergence of this field, Drosophila has proved to be a valuable model for studying the biological functions of microproteins in vivo. In this review, we outline how the smORF field emerged and the nomenclature used in this domain. We summarize the technical challenges associated with identifying putative coding smORFs in the genome and the relevant translated microproteins. Finally, recent findings on one of the best studied smORF peptides, Pri, and other microproteins studied so far in Drosophila are described. These studies highlight the diverse roles that microproteins can fulfil in the regulation of various molecular targets involved in distinct cellular processes during animal development and physiology. Given the recent emergence of the microprotein field and the associated discoveries, the microproteome represents an exquisite source of potentially bioactive molecules, whose in vivo biological functions can be explored in the Drosophila model.
Sunlight-Driven Photodegradation of RB49 Dye Using TiO2-P25 and TiO2-UV100: Performance Comparison
Authors: Zaaboul Fatima , Canle Moisés , Haoufazane Chaimaa , Santaballa Juan Arturo , Hammouti Belkheir , Azzaoui Khalil , Jodeh Shehdeh , Hadjadj Aomar , El Hourch Abderrahim
Published: October 2024

By combining measurements of photocatalysis under solar irradiation with measurements of total organic carbon, we have compared the performance of two TiO2-based photocatalysts in the photodegradation of the dye Reactive Blue 49 (RB49). TiO2-P25 and TiO2-UV100 commercial photocatalysts were tested within a concentration ranging from 0.5 to 4 g/L. The dye solution concentration was varied from 10 to 50 mg/L and its pH was increased from 3 to 9. Extensive characterization of the photocatalysts was performed using Fourier-transform infrared spectroscopy, scanning electron microscopy and X-ray diffraction. TiO2-UV100 proved to be more active in adsorbing RB49 dye than TiO2-P25. At low dye concentrations, the adsorption equilibrium is reached in 15 min. This time increases to 1 h at higher concentrations. The photocatalytic degradation of aqueous RB49 under sunlight was monitored by UV-Vis spectrophotometry. The apparent rate constant of dye photodegradation with TiO2-UV100 is twice that of TiO2-P25. The total organic carbon (TOC) analysis showed a removal of around 98% with TiO2-UV100 and only 85% with TiO2-P25 after 3 h of solar irradiation. Over five photocatalytic cycles of 3 h, TiO2-UV100 maintained a more stable and higher efficient photocatalytic performance. All our results converge toward a better photocatalytic performance of TiO2-UV100 for the photodegradation of RB49 dye and indicate that the most decisive factor is its greater capacity to adsorb the pollutant.
Comparison and Contrast of Calcite vs. Dolomite after Heat Treatment to Enhance Toluidine Blue Removal from Water
Authors: Li Zhaohui , Strommen Jadyn , Garza Aaron , Bowman Anna , Rayniak Angie , Schulz Laura , Allen Lori , Xu Shangping
Published: October 2024

Significant increase in use of color dyes in modern society exerted a great pressure on environmental and water qualities. As such, studies for the removal of color dyes from water have been conducted extensively. In this study, common Earth materials dolomite and calcite were evaluated and contrasted for their removal of toluidine blue (TB), a cationic dye, before and after heat treatment. An increase by a factor of 3 in TB removal capacity from 3.5 to 10 mmol/kg was achieved after dolomite (Dol) was heated to 800 °C (designated as HDol). In contrast, the TB removal capacity increased by more than 100 times from 2 to 220 mmol/kg after calcite (Cal) was heated to 1000 °C (designated as HCal). For Dol and HDol, the TB removal increased as the solution’s pH increased but decreased with increases in the solution’s ionic strength. For Cal and HCal, the influence of the equilibrium solution’s pH and ionic strength on TB removal was negligible. The free energy of TB sorption on Dol, HDol, and Cal were −7 to −15 kJ/mol. The results suggested different removal mechanism for TB by Dol vs. Cal. X-ray diffraction data for Dol showed a slight increase in calcite content after heat treatment. For Cal, CaO was produced after heating, which converted back to calcite after 24 h of mixing with TB solutions. The significant TB removal by HCal could be attributed to its reaction with CaO. Thus, the best solution is to use freshly treated Cal for the removal of TB from solution.
Spray-Deposited TiO2 Layers on Aluminum Foil for Sustainable Water Remediation
Authors: Armaković Sanja J. , Savanović Maria M. , Armaković Stevan
Published: October 2024

In this study, we developed TiO2-coated aluminum (TiO2/Al) surfaces using eco-friendly methods to create efficient and environmentally friendly photoactive materials with the potential to enhance water purification systems. TiO2 particles were deposited onto aluminum foil surfaces via a spray method, followed by heat treatment at 200 °C for 15 min. The morphology of the TiO2/Al surfaces, both before and after photocatalytic treatment, was characterized using scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS). The photocatalytic properties of these modified surfaces were evaluated through the degradation of rhodamine B (RB), methylene blue (MB), and methyl orange (MO) under simulated solar and UV–LED irradiation. Among the dyes tested, MO exhibited the highest degradation, influenced by factors such as absorption maximum, molecular structure, charge, and the number of condensed rings. The computational study of interactions between dye molecules and the combined nanoparticle revealed that the binding was the strongest in the case of MO dye. This study also explored the influence of varying the number of TiO2/Al surfaces in solution (one, five, and ten) on the photodegradation efficiency. The solution with five TiO2/Al surfaces demonstrated optimal performance, achieving a 16% degradation of RB. The reusability of the TiO2/Al surfaces was confirmed through five successive runs of RB degradation. The results indicate that TiO2/Al surfaces are a promising solution for addressing water contamination challenges and advancing sustainable water treatment practices.
Impact of PRECEDE–PROCEED Model Audits in Cancer Screening Programs in Lombardy Region: Supporting Equity and Quality Improvement
Authors: Odelli Stefano , Zeduri Margherita , Schivardi Maria Rosa , Archi Davide , Coppola Liliana , Genco Russo Roberto , Moscheni Maristella , Tettamanzi Elena , Terragni Fabio , Viscardi Michela , Vitale Valentina , Odone Anna , Cereda Danilo , Deandrea Silvia
Published: October 2024

Background: Health disparities related to socio-economic factors impact access to preventive health interventions. The PRECEDE–PROCEED model, a multidimensional approach to health promotion, has been adapted to optimise cancer screening programs in Lombardy, Italy, addressing these disparities. Methods: This study evaluated the application of systemic audits based on the PRECEDE–PROCEED model across Lombardy cancer screening programs. A systematic region-wide audit was performed in 2019, and follow-up audits were performed in 2022–2023. Data were collected using structured analysis methodologies, including epidemiological, behavioural, and organisational assessments. Results: The 2019 audit showed strengths in participation and quality standards but identified challenges in cervical cancer screening coverage and waiting times for assessments. Improvements plans included the digitisation of processes and stakeholder engagement. The 2022–2023 audits reported increased coverage for breast and colorectal screenings, but a slight decline in participation rates and examination coverage. Organisational improvements were noted, yet gaps in training and equity-targeted actions remained. Conclusion: The PRECEDE–PROCEED model audits led to notable improvements in the quality and equity of cancer screening programs in Lombardy. Sustained focus on digital integration, continuous re-training, and targeted equity interventions is essential for further progress.
Assessing Land Use Ecological-Social-Production Functions and Interrelationships from the Perspective of Multifunctional Landscape in a Transitional Zone between Qinghai-Tibet Plateau and Loess Plateau
Authors: Ma Yu , Ji Wenfeng , Meng Qingxiang , Zhang Yali , Li Ling , Liu Mengxue , Wei Hejie
Published: October 2024

Investigating the evolution and drivers of multifunctional land use is essential for sustainable land management and regional biological conservation. This research focuses on the Hehuang Valley, where we developed an “ecological-social-production” evaluation system for assessing land use multifunctionality from the perspective of multifunctional landscape. Leveraging Geographic Information System technologies, we conducted a quantitative analysis of spatiotemporal variations in multifunctional land use across the valley in recently twenty years. Correlation coefficients were employed to identify trade-offs and synergies among various land use functions. Additionally, geographical detector and grey relational analysis models were utilized to pinpoint the factors influencing spatiotemporal changes in land use functions during the specified period. The results showed that: (1) During the period, the overall multifunctionality of land use in the Hehuang Valley exhibited an increasing trend. The economic production function of the land showed the highest growth, while the ecological and social functions showed lower growth. (2) In most areas of the Hehuang Valley, there was a positive correlation between social and economic production functions and a negative correlation between social and ecological functions, as well as between economic production and ecological functions. (3) Natural conditions were the main factors of spatial variation of land use comprehensive functions, but human factors, including land use intensity and the rate of farmland conversion to non-agricultural uses, were the primary drivers of temporal changes in multifunctional land use. The findings provide valuable references and scientific support for policymakers in optimizing land use and multifunctional landscape conservation.
Advances in Theranostic Approaches and Emerging Biomarkers of Diabetes Mellitus
Authors: Aktas Gulali
Published: October 2024

Type 2 diabetes mellitus is one of the most common chronic conditions in the world [...]
Comprehensive Literature Review on Melanoma of Unknown Primary Site Triggered by an Intriguing Case Report
Authors: Bordeanu-Diaconescu Eliza-Maria , Cretu Andrei , Grosu-Bularda Andreea , Andrei Mihaela-Cristina , Hodea Florin-Vlad , Dumitru Catalina-Stefania , Enache Valentin , Creanga Cosmin-Antoniu , Lascar Ioan , Hariga Cristian-Sorin
Published: October 2024

Melanoma is one of the most aggressive forms of skin cancer. While most melanomas have a discernible primary site, a small subset, approximately 3.2%, present as a metastatic disease without an identifiable primary origin, a condition known as melanoma of unknown primary (MUP). Unusual cases of primary melanoma have also been previously reported in the respiratory, gastrointestinal, and urogenital tracts. MUP typically is found in lymph nodes, subcutaneous sites, and visceral organs, with hypotheses about its origin including spontaneous primary tumor regression and ectopic melanocytes. MUP presents unique challenges in diagnosis and treatment due to the absence of a detectable primary tumor. Understanding its genetic and molecular features, epidemiology, prognostic factors, and treatment options is crucial for optimizing patient care and outcomes in this subset of melanoma patients. We conducted an extensive literature review triggered by a case report of a patient with suspected MUP. A 51-year-old woman was transferred from another hospital where an incision was performed for a suspected superinfected hematoma of the left thigh. Since the patient showed high leukocytosis and redness and swelling of the thigh, local debridement, drainage, and excisional biopsy of the tumor mass were performed in our unit in the emergency setting, and the tumor was taken for histopathology evaluation. Intraoperatively, the mass appeared nonspecific. The permanent histopathology report established a diagnosis of melanoma, with tumor proliferation also involving lymphoid tissue, and despite broad clinical and imagistic assessments, the primary melanoma could not be identified. Clinicians must be aware of the varied clinical manifestations of malignant melanoma, especially in cases of occult melanoma where the primary site is not evident.
The Association of Neuroendocrine Differentiation with MicroRNA 21 and MicroRNA let7f Expression and the Clinicopathological Parameters in Primary Invasive Breast Carcinomas with Neuroendocrine Features
Authors: Usul Gamze , Kelten Talu Esra , Yılmaz İsmail , Issın Gizem , Bektaş Sibel , Can Trabulus Didem
Published: October 2024

MiRNAs have been reported as biomarkers with diagnostic, prognostic, and predictive value for many different diseases. Therapeutic agents targeting some miRNAs are currently being developed. We aimed to compare BC-NEFs (carcinoma of the breast with neuroendocrine features) with IDC (invasive ductal carcinoma) cases without neuroendocrine features in terms of the level of miRNA expression known to show the oncogenic (miR-21) and tumor-suppressor effects (miR-let7f) and the clinicopathological features. A total of 29 patients with a diagnosis of BC-NEFs (15 cases with neuroendocrine differentiation >50% of the whole section of tumor and 14 cases with neuroendocrine differentiation 10–50% of the tumor) and 30 patients with a diagnosis of IDC (no neuroendocrine differentiation) were retrospectively re-evaluated. Expression levels of miR-21 and miR-let7f were determined by the qRT-PCR method in paraffin tissue blocks. MiR-21 expression was significantly higher in the IDC group than in the group with BC-NEFs. miR-let7f expression was significantly lower in the group with BC-NEFs compared to the IDC group. A high expression level of miR-21 was found to be associated with progesterone receptor (PR) negativity. Our findings show that the presence of NEFs in breast carcinomas makes a significant difference in the expression levels of the investigated oncogenic (miR-21) and tumor-suppressor (miR-let7f) miRNAs. These findings suggest that miRNAs may be a potential biomarker in BC-NEFs and would benefit from targeted therapy.
Enhancing Anomaly Detection in Maritime Operational IoT Time Series Data with Synthetic Outliers
Authors: Kim Hyunjoo , Joe Inwhee
Published: October 2024

Detecting anomalies in engine and machinery data during ship operations is crucial for maintaining the safety and efficiency of the vessel. We conducted experiments using device data from the maritime industry, consisting of time series records from IoT (Internet of Things) datasets such as cylinder and exhaust gas temperatures, coolant temperatures, and cylinder pressures collected from various sensors on the ship’s equipment. We propose data enrichment and validation techniques by generating synthetic outliers through data degradation and data augmentation with a Transformer backbone, utilizing the maritime operational data. We extract a portion of the input data and replace it with synthetic outliers. The created anomaly data are then used to train the model via a self-supervised learning approach. Synthetic outliers are generated using methods such as the arithmetic mean, geometric mean, median, local scale, global scale, and magnitude warping. With our methodology, we achieved a 17.23% improvement in F1 performance compared to existing state-of-the-art methods across five publicly available datasets and actual maritime operational data collected from the industry.
Toward Dynamic Data-Driven Time-Slicing LSH for Joinable Table Discovery
Authors: Wang Weiwei , Zhu Chunxiang , Yan Han
Published: October 2024

In legacy industrial systems, discovering joinable information between database tables is important for applications such as data integration and data analysis. Locality-Sensitive Hashing-based methods have been proven to be capable of handling chaotic and diverse table relationships, but these methods often rely on an incorrect assumption—that the similarity of table columns in the database directly reflects their joinability, causing problems related to the accuracy of their results. To solve this problem, this study proposes a dynamic data-driven time-slicing Locality-Sensitive Hashing method for joinable table discovery. This method introduces database log information and within different time slices, uses the co-occurrence matrix of data tables to determine their joinability. Specifically, it first performs a MinHash dimensionality reduction on database columns and then uses Locality-Sensitive Hashing to calculate the static similarity. Next, it identifies business modular time slices through database logs, calculates the dynamic similarity of the slice time data, and builds a co-occurrence matrix between tables. Finally, the joinability between data tables is calculated using the static similarity, dynamic similarity, and co-occurrence matrix. The experimental results demonstrate that this method effectively excludes tables that only have similarity but no business relationship for data cleaning, and its accuracy exceeds that of methods that only depend on similarity.