bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of graphene to nano-Ti polymer coating on morphology and anti- corrosion properties
Authors: Wang Bo , Wan Tao , Wei Shicheng C. , Wang Yujiang , Huang Wei , Liang Yi , Li Junqi 
Published: August 2024

Abstract

Corrosion is ubiquitous in life. In order to further improve anti-corrosion of nano-Ti polymer coatings of our previous research, graphene slurry is filled to modify nano-Ti epoxy resin coatings. Structure, anti-permeability, anti-corrosion and anti-wear properties of Nano-Ti polymer functional coatings with different graphene slurry have been investigated systemically by field emission scanning microscopy (FE-SEM), Fourier transform infrared spectroscopy (FT-IR), immersion test, electrochemical measurements and wear test. FE-SEM results showed graphene can disperse well in nano-Ti polymer coating when the content of graphene is 0.5 wt%. Moreover, the results showed that added graphene can enhance the anti-permeability, anti-corrosion, and anti-wear properties of nano-Ti polymer coatings. Nano-Ti polymer/graphene functional coatings showed optimal comprehensive performance and anti-corrosion performance as the graphene content was 0.5 wt%. The diffusion coefficient is 0.44×10− 14 m2·s− 1, the friction coefficient d is only 0.22. In conclusion, the appropriate amount of graphene slurry can effectively improve the anti-corrosion performance of the nano-Ti polymer coating.
Ferroptosis triggers mitochondrial fragmentation via Drp1 activation
Authors: Von Karstedt Silvia , Pedrera Lohans , Clemente Laura Prieto , Dahlhaus Alina , Nasudivar Sara Lotfipour , González Daniel Olmo , Stroh Jenny , Singh Randhwaj Pratap , Grotehans Nils , Langer Thomas , Garcia-Saez Ana 
Published: August 2024

Abstract

Constitutive mitochondrial dynamics ensure quality control and metabolic fitness of cells, and their dysregulation has been implicated in various human diseases. The large GTPase Dynamin-related protein 1 (Drp1) is intimately involved in mediating constitutive mitochondrial fission and has been implicated in mitochondrial cell death pathways. During ferroptosis, a recently identified type of regulated necrosis driven by excessive lipid peroxidation, mitochondrial fragmentation has been observed. Yet, how this is regulated and whether it is involved in ferroptotic cell death has remained unexplored. Here, we provide evidence that Drp1 is activated upon experimental induction of ferroptosis and promotes cell death execution and mitochondrial fragmentation. Using time-lapse microscopy, we found that ferroptosis induced mitochondrial fragmentation and loss of mitochondrial membrane potential, but not mitochondrial outer membrane permeabilization. Importantly, Drp1, the major GTPase involved in steady-state mitochondrial fission, accelerated ferroptotic cell death kinetics. Notably, this function was mediated by regulation of mitochondrial dynamics as overexpression of Mitofusin 2 phenocopied the effect of Drp1 deficiency in delaying ferroptosis cell death kinetics. Mechanistically, we found that Drp1 is phosphorylated and activated after induction of ferroptosis and translocated to mitochondria. Importantly, recruitment to and its further activation at mitochondria through the phosphatase PGAM5 promoted ferroptotic cell death. These data provide the first evidence for a functional role of Drp1 activation in the acceleration of ferroptotic cell death and mitochondrial fragmentation, with important implications for the regulation of mitochondrial dynamics in diseases associated with ferroptosis.
On a Stochastic PDE Model for Epigenetic Dynamics
Authors: Padilla-Longoria Pablo , Sierra Jesus 
Published: August 2024

Abstract

We propose and analyze a stochastic model to investigate epigenetic mutations, i.e., modifications of the genetic information that control gene expression patterns in a cell but do not alter the DNA sequence. Epigenetic mutations are related to environmental fluctuations, which leads us to consider (additive) noise as the driving element for such mutations. We focus on two applications: firstly, cancer immunotherapy involving macrophages' epigenetic modifications that we call tumor microenvironment noise-induced polarizations, and secondly, cell fate determination and mutation of the flower Arabidopsis thaliana. Due to the technicalities involving cancer biology for the first case, we present only a general review of this topic and show the details in a separate manuscript since our principal concerns here are the mathematical results that are important to validate our system as an appropriate epigenetic model; for such results, we rely on the theory of Stochastic PDE, theory of large deviations, and ergodic theory. Moreover, since epigenetic mutations are reversible, a fact currently exploited to develop so-called epi-drugs to treat diseases like cancer, we also investigate an optimal control problem for our system to study the reversal of epigenetic mutations.
Mathematics Subject Classification: 92D10 , 35R60 , 60H15 , 37N25 , 49N90
Mast cell tryptase-PAR2 axis promotes ovarian fibrosis through RNF152-mediated stabilization of Bcl-xL
Authors: Wang Chaojun , Zhang Xiang , Zhang Jun 
Published: August 2024

Abstract

Ovarian fibrosis is a basic histologic feature of premature ovarian insufficiency(POI), which poses a great threat to women of reproductive age. Collagen abundance in ovarian theca-stroma cells contributes to ovarian fibrogenesis. However, the role and mechanism of mast cells in the development of POI have not yet been determined. Our study for the first time found that tryptase secreted by activated mast cells induced COL1A1 and COL1A2 production, two subunits of collagen I in mouse theca–stroma cells by protease-activated receptor-2 signaling. Inhibition of PAR2 or Bcl-xL attenuated the increases of COL1A1 and COL1A2 caused by tryptase. In addition, knockdown of RNF152 reversed the downregulation of collagen production caused by si-Bcl-xL. Clinically, tryptase levels in serum and follicular fluid were higher in both bPOI and POI patients than in controls. Tryptase concentrations in serum and follicular fluid were positively associated with follicle stimulating hormone(FSH) and negatively associated with anti-Müllerian hormone (AMH). Cromolyn sodium, a mast cell stabilizer, reduces collagen I production, but has no effect on hormone synthesis and follicle number in a cisplatin-induced POI mouse model. Our findings shed new insights into the biological function of tryptase in ovarian fibrosis and POI.
Enhancing E-Learning through AI: Advanced Techniques for Optimizing Student Performance
Authors: Mahafdah Rund Fareed , Bouallegue Seifeddine , Bouallegue Ridha 
Published: August 2024

Abstract

The integration of Artificial Intelligence (AI) into e-learning has transformed conventional educational approaches, improving the learning process and maximizing student achievement. This study offers a thorough examination of how artificial intelligence (AI) can be utilized to enhance e-learning results by employing advanced predictive methods and performance optimization strategies. The main goals consist of creating an AI-based framework to monitor and analyze student interactions, evaluating the influence of online learning platforms on student understanding using advanced algorithms, and determining the most efficient methods for blended learning systems. AI algorithms, known for their cognitive ability and capacity to learn, adapt, and make decisions, are employed to analyze and forecast student performance, thereby improving educational quality and outcomes. The practical results obtained by implementing machine learning and deep learning models, such as Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), show substantial enhancements in forecasting different performance metrics. This research highlights the ability of AI to develop adaptable, effective, and successful e-learning environments, promoting enhanced academic achievement and customized learning experiences. The findings demonstrate that CNN outperformed other deep learning and machine learning algorithms in terms of accuracy during the prediction phase, showcasing the advanced capabilities of AI in educational contexts.
Xuebijing Injection Alleviate Sepsis-induced Myocardial Damage by Inhibiting Apoptosis via PI3K/AKT/Foxo3a and MAPK Signaling Pathways
Authors: Liu An-Bu , Tian Na , Feng Ke , Chen Zhong-Wei , Wang Sheng , Liu Jia , Zhang Jun-Fei 
Published: August 2024

Abstract

Background
Xuebijing injections (XBJ) originate from the traditional Chinese medicine (TCM) prescription XuefuZhuyu Decoction. It is composed of five Chinese herbal extracts; Carthami flos, Paeoniae radix rubra, Chuanxiong rhizoma, Salviae miltiorrhizae, and Angelicae Sinensis radix. The China Food and Drug Administration approved XBJ as a TCM preparation for the adjuvant treatment of sepsis. However, the mechanisms underlying the effects of XBJ on sepsis-induced myocardial damage (SIMD) have yet to be fully elucidated. This study explores the potential therapeutic mechanism of XBJ on SIMD.
Methods
In this study, rats were randomly assigned to three groups: Sham group, cecal ligation and puncture (CLP) group, and XBJ group. Echocardiography, myocardial enzymes and hematoxylin-eosin (H&E) were used to detect cardiac function. IL-1β, IL-6 IL-10, TNF-α, SOD and MDA in serum were measured using ELISA kits. The AutoDockTools Vina was utilized for molecular docking to analyze the mechanism of binding of XBJ with PI3K, AKT, Foxo3a, ERK1/2, P38 and JNK protein. Western blotting was conducted to analyze the levels of p-PI3K, PI3K, p-AKT, AKT, p-Foxo3a, Foxo3a, p-ERK1/2, ERK1/2, p-P38, P38, p-JNK, JNK, Bax, Bcl-2, Cleaved-Caspase 3, and Survivin proteins in myocardial tissue. Immunofluorescence staining was utilized to examine the activity levels of PI3K, AKT, Foxo3a, ERK1/2, P38 and JNK in cardiac tissue. Immunohistochemical detection of Bax, Bcl-2 and Cleaved-Caspase 3 expression.
Results
The results of echocardiography, myocardial enzyme and H&E test showed that XBJ could effectively improve the myocardial injury caused by CLP with the increase of treatment time. XBJ decreased IL-1β, IL-6, TNF-α and MDA levels, but increased SOD and IL-10 level in CLP-induced SIMD in ELISA. Molecular docking analysis indicated that there was a strong and stable affinity of XBJ for PI3K/AKT/Foxo3a and MAPK signaling pathways. XBJ treatment led to the downregulation of p-PI3K, p-AKT, p-Foxo3a, Bax, Cleaved-Caspase 3, p-ERK1/2, p-P38 and p-JNK levels, while upregulating Bcl-2, and Survivin protein levels (p < 0.05).
Conclusion
XBJ may alleviate SIMD by suppressing cell apoptosis and inflammation possibly via the PI3K/AKT/Foxo3a and MAPK signaling pathways.
Exploring Morphological and Thermal Characteristics of Chitosan/Starch Blend Films Derived from Natural Sources: Incorporating Thiourea and Urea Coupling Agents with Stearic Acid Plasticizer
Authors: Badr Magd M. , Elsawy Moataz A. , Naguib Hamdy M. , El-Komy Doaa A. , Bekhit Mahmoud , Elmawgoud H. A. 
Published: August 2024

Abstract

In this study, biobased films composed of chitosan and starch polysaccharides were prepared and thoroughly characterized. The coupling of these two polymer components was facilitated using thiourea and urea as crosslinking agents. Chemical interactions were monitored through FTIR and EDX analyses, while the morphological properties were examined using XRD and SEM. The thermal behavior of the films was comprehensively analyzed using DSC, TGA, and DTA measurements. The results indicated that effective film formation between chitosan and starch required the incorporation of a plasticizer, specifically stearic acid, along with thiourea and urea as crosslinking agents. This combination not only enhanced the appearance of the films but also improved their thermodynamic stability. The synthesized biobased polymers demonstrated thermal stability suitable for various applications in agriculture, health, and medicine. The apparent activation energy of starches was determined using several models. Additionally, Fourier transforms infrared spectrometry (FTIR) and TGA-FTIR was employed to investigate the mechanism of the thermal decomposition process. The thermal data were further analyzed using the Coats-Redfern, Friedman, Flynn-Wall-Ozawa (FWO), and Kissinger-Akahira-Sunose (KAS) methods to calculate kinetic parameters.
Stress intensity factors and fracture criteria for an inclined straight-fronted edge crack in round bar with mixed-mode under axial tension
Authors: Xia Weihai , Wang Yuxuan , Peng Guangjian , Huan Yong , Sun Pingping , Zhang Taihua 
Published: August 2024

Abstract

The processing of barbs in sutures introduces cracks, reducing the fracture resistance of the barbed sutures. In this study, an equivalent model was established by analyzing the key features of the barbed suture. A mesh partition method was utilized to define the inclined straight-fronted edge crack region. Then, a three-dimensional finite element model for the barbed suture was constructed. The contour integral method was employed to explore the correlation between cutting parameters and the breaking strength of barbed sutures, elucidating the stress intensity factors under mixed-mode conditions at the crack front. To comprehensively evaluate the effects of the three crack modes on the barbed suture, the equivalent stress intensity factors were calculated according to two fracture criteria. The most susceptible locations, that is, the midpoint of the crack front, for crack propagation were identified. Establishing the relationship between the dimensions, material properties, and equivalent stress intensity factors can provide robust data to achieve the optimal design of cutting angles and cutting depth of barbed sutures. This also gives deep insights into fracture issues in round structures with straight-fronted edge cracks.
Transgenerational plasticity of Elymus nutans was regulated by multiple factors and not directly related to within-generational plasticity
Authors: Jia Cunzhi , Chen Dali , Zhao Xiaohua , Fu Xiuzhen , Hu Xiaowen 
Published: August 2024

Abstract

Background and Aims
Transgenerational plasticity (TGP) have been proven as significant driver of organisms to cope with environmental rapid changes. However, our understanding of key aspects of TGP is limited, especially its influencing factors and relationship to within-generation plasticity (WGP).
Methods
Firstly, we constructed different maternal and offspring environmental backgrounds for five populations of E. nutans through two years of common garden experiments and three years of reciprocal sowing experiments. Subsequently, we examined the influencing factors of TGP of leaf traits and its relationship to WGP.
Results
Maternal environment exerted influences on leaf traits of E. nutans for a minimum of three growing seasons. Progeny plant from low altitude maternal environment had larger and thicker leaves than those from high elevation maternal environment. Morphological traits exhibited higher TGP in high elevation progeny environment, while nutritional traits were higher in low elevation progeny environment. TGP diminished in the third growing season. Remarkably, no clear correlation was identified between TGP and WGP.
Conclusions
Our results revealed the dependence of TGP on trait type, progeny environment, population, and growing season and provided the first evidence that TGP are not correlated with WGP, reflecting the complexity of environmental conditions interactions experienced by the maternal and progeny generations. These findings underscore the importance of accounting for the maternal environment when assessing and utilizing E. nutans. It is advisable to opt for seed sources from environments with similar elevations for the cross regional using of seed sources in ecological restoration.
The fed-batch production of mannosylerythritol lipids by Ustilago maydis DSM 4500 from hydrophilic carbon sources
Authors: Valkenburg André David , Teke George M. , Pott Robert W. M. , Rensburg Eugéne van 
Published: August 2024

Abstract

Glycolipids are a class of widely studied biosurfactants with excellent applicability in cosmetic and pharmaceutical formulations. This class of biosurfactants includes mannosylerythritol lipids (MELs), which have gained particular interest due to their moisturizing and healing activity for dry and damaged human skin, arising from conditions such as eczema. Traditionally, MELs have been produced by growing certain basidiomycetous yeasts of the genus Pseudozyma on vegetable oils. However, oils are a comparatively expensive substrate, which negatively affects the economic performance of MEL production. In addition to this, vegetable oils significantly complicate the downstream processing required to produce a product with the required purity for most applications. To address these challenges, this study investigated MEL-A production exclusively from hydrophilic carbon sources by Ustilago maydis DSM 4500. By implementing a fed-batch production strategy, maximum MEL-A concentration of 0.87 g/L was achieved from glucose exclusively. Also, adding micronutrients (such as MnSO4) to MEL-A production showed a 24.1% increase in the product titer, implying other metabolites are formed, favoring MEL production.
The chlorite adduct of aquacobalamin: contrast with chlorite dismutase
Authors: Lehene Maria , Zagrean-Tuza Cezara , Iancu Stefania D. , Cosma Sergiu-Raul , Branzanic Adrian , Silaghi-Dumitrescu Radu 
Published: August 2024

Abstract

In the reaction of aquacobalamin (aquaCbl) with chlorite, a stable species is detected and assigned as a Co(III)-chlorite complex, Co(III)-OClO−. Its UV-vis spectrum is almost identical to that of aquaCbl, except for some minor differences at ~ 430 nm; cyanide can eliminate and prevent these changes. The 1H-NMR spectra reveal strong influences of chlorite on the B2 and B4 protons of the cobalt-bound dimethyl benzimidazole ligand. Together, the UV-vis and NMR titrations suggest a Kd of 10 mM or higher for chlorite on Cbl. Resonance Raman spectra reveal minor changes in the spectrum of aquaCbl to chlorite – as well as a disappearance of the free chlorite signals, consistent with Cbl-chlorite complex formation. Corroboration for these interpretations is also offered from mass spectrometry and DFT calculations. This Co(III)-OClO− complex would be a stable analogue of the first reaction intermediate in the catalytic cycle of chlorite dismutase, or in the reaction of chlorite with a number of other heme proteins. The differences in reactivity between Co(III) cobalamin and Fe(III) heme towards chlorite are analyzed and rationalized, leading to a reconciliation of experimental and computational data for the latter.
Engine air intake design and evaluation - examples from the Bluecopter™ demonstrator
Authors: Garavello Andrea , Kneish Thomas , Müller Markus , D’Alascio Alessandro 
Published: August 2024

Abstract

The Bluecopter™ demonstrator was developed to prove the feasibility of future eco-friendly rotorcraft by demonstrating significant reduction of CO2 emission, fuel consumption and noise. In this context, several different engine air intake configurations were designed and tested, with the aim of improving engine efficiency and reducing fuel consumption, with minimal to no impact on airframe drag. The present paper summarizes the engine intake design, optimization and testing activities carried out in the frame of the Bluecopter project.
DVTXAI: A Novel Deep Vision Transformer with an Explainable AI-based Framework and its Application in Agriculture
Authors: Kamal Sadia , Sharma Parth , Gupta P.K. , Siddiqui Mohammad Khubeb , Dutt Abhijit , Singh Ankush 
Published: August 2024

Abstract

Agriculture is one of the fundamental components of human civilization, contributing not only to food production but also to economic growth. Early identification of diseases in plants presents a significant challenge, as timely detection is crucial to increasing agricultural production. Incorporating the latest technology, such as artificial intelligence (AI) techniques, in fields can reduce major losses for farmers and also improve productivity. In this paper, we have proposed a Deep Vision transformer and an Explainable AI-based technique to overcome the various diseases in plants. Here, we have used the dataset "Plant Village," as a case study that focuses on two majorly grown crops like: potatoes and tomatoes. Further, we have analyzed nine diseases that affect these crops around the globe, with tomatoes showing six different conditions and potatoes affected by three bacterial diseases. The proposed DVTXAI framework incorporates the Deep vision transforms to detect plant diseases at an early stage. In the experiments, the proposed model achieves an accuracy of 93. 56% for tomatoes and 99.95% for potatoes. Additionally, the model is Explainable AI (XAI), which reveals the transparency mechanism that helps the farmer to make the right decision at an early stage of the crop.
A text mining-based approach for comprehensive understanding of Chinese railway operational equipment failure reports
Authors: Yang Xiaorui , Li Honghui , Xu Yi , Shen Nahao , He Ruiyi 
Published: August 2024

Abstract

Railway operational equipment is crucial for ensuring the safe, smooth, and efficient operation of trains. Comprehensive analysis and mining of historical railway operational equipment failure (ROEF) reports are of significant importance for improving railway safety. Currently, significant challenges in comprehensively analyzing ROEF reports arise due to limitations in text mining technologies. To address this concern, this study leverages advanced text mining techniques to thoroughly analyze these reports. Firstly, real historical failure report data provided by a Chinese railway bureau is used as the data source. The data is preprocessed and an ROEF corpus is constructed according to the related standard. Secondly, based on this corpus, text mining techniques are introduced to build an innovative named entity recognition (NER) model. This model combines bidirectional encoder representations from transformers (BERT), bidirectional long short-term memory (BiLSTM) networks, and conditional random fields (CRF), with an additional entity attention layer to deeply extract entity features. This network architecture is used to classify specific entities in the unstructured data of failure reports. Finally, a knowledge graph (KG) is constructed using the Neo4j database to store and visualize the extracted ROEF-related entities and relationships. The results indicate that by constructing the topological relationships of the ROEF network, this study enables the analysis and visualization of potential relationships of historical failure factors, laying a foundation for failure prediction and ensuring railway safety, while also filling the current gap in the mining and analysis of ROEF reports.