bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimal Weighted Markov Model and Markov Optimal Weighted Combination Model with Their Application in Hunan’s Gross Domestic Product
Authors: Li Dewang , Luo Chingfei , Qiu Meilan
Published: February 2025

In this paper, we mainly establish an optimal weighted Markov model to predict the GDP of Hunan Province from 2017 to 2023. The new model is composed of a fractional grey model and a quadratic function regression model weighted combination and is obtained through Markov correction. First, the optimal order r of the fractional grey model (FGM) is determined by using the particle swarm optimization (PSO) algorithm, and the FGM model is established. Second, a quadratic regression model is established based on the scatter plot of the data. Then, the optimal weighted Markov model (OWMKM) is obtained by combining the above two sub-models (i.e., the optimal weighted combination model (OWM)) and using Markov correction. Finally, the new model is applied to estimate and predict the GDP of Hunan Province from 2017 to 2023. The forecast results show that the four statistical measures of the optimal weighted Markov model, such as MAPE, RMSE, R2, and STD, are superior to the optimal weighted combination model (OWM), the nonlinear auto regressive model (NAR) and the autoregressive integrated moving average model (ARIMA), which indicates that our new model has strong fitting and higher accuracy. We establish the quadratic regression Markov model (QFRMKM), the fractional grey Markov model (FGMKM), and the optimal combination model of these two sub-models (MKMOWM). The effects of the MKMOWM and OWMKM are compared. This research provides a scientifically reliable reference and has significant importance for understanding the development trends of the economy in Hunan Province, enabling governments and companies to make sound and reliable decisions and plans.
On the Relation Between the Domination Number and Edge Domination Number of Trees and Claw-Free Cubic Graphs
Authors: Pan Zhuo , Pan Peng , Tie Chongshan
Published: February 2025

For a connected graph G=(V,E), the dominating set in graph G is a subset of vertices F⊂V such that every vertex of V−F is adjacent to at least one vertex of F. The minimum cardinality of a dominating set of G, denoted by γ(G), is the domination number of G. The edge dominating set in graph G is a subset of edges S⊂E such that every edge of E−S is adjacent to at least one edge of S. The minimum cardinality of an edge dominating set of G, denoted by γ′(G), is the edge domination number of G. In this paper, we characterize all trees and claw-free cubic graphs with equal domination and edge domination numbers, respectively.
Exploring Optimisation Strategies Under Jump-Diffusion Dynamics
Authors: Di Persio Luca , Fraccarolo Nicola
Published: February 2025

This paper addresses the portfolio optimisation problem within the jump-diffusion stochastic differential equations (SDEs) framework. We begin by recalling a fundamental theoretical result concerning the existence of solutions to the Black–Scholes–Merton partial differential equation (PDE), which serves as the cornerstone for subsequent analysis. Then, we explore a range of financial applications, spanning scenarios characterised by the absence of jumps, the presence of jumps following a log-normal distribution, and jumps following a distribution of greater generality. Additionally, we delve into optimising more complex portfolios composed of multiple risky assets alongside a risk-free asset, shedding new light on optimal allocation strategies in these settings. Our investigation yields novel insights and potentially groundbreaking results, offering fresh perspectives on portfolio management strategies under jump-diffusion dynamics.
Traditional Prediction Techniques and Machine Learning Approaches for Financial Time Series Analysis
Authors: Cappello Claudia , Congedi Antonella , De Iaco Sandra , Mariella Leonardo
Published: February 2025

Accurate financial time series forecasting is critical for effective decision making in areas such as risk management, portfolio optimization, and trading. Given the complexity and volatility of financial markets, traditional forecasting methods often fail to capture the underlying dynamics. Recent advances in artificial neural network (ANN) forecasting research indicate that ANNs present a valuable alternative to traditional linear methods, such as autoregressive integrated moving average (ARIMA). However, time series are typically influenced by a combination of factors which require to consider both linear and non-linear characteristics. This paper proposes a new hybrid model that integrates ARIMA and ANN models such as long short-term memory and gated recurrent unit neural network to leverage the distinct strengths of both linear and non-linear modeling. Moreover, the goodness of the proposed model is evaluated through a comparative analysis of the ARIMA, ANN and Zhang hybrid model, using three financial datasets (i.e., Unicredit SpA stock price, EUR/USD exchange rate and Bitcoin closing price). Various absolute and relative error metrics, computed to evaluate the performance of models, can support the use of the proposed approach. The Diebold–Mariano (DM) test is also implemented to asses the significance of the obtained differences of the hybrid model with respect to the other competing models.
Stability of the Comparison Problem for the Spherical Radon Transform
Authors: Li Tian , Wu Longyu , Zhu Quanxin
Published: February 2025

This paper addresses the comparison problem for the spherical Radon transform, which was posed by Koldobsky, Roysdon, and Zvavitch. By applying Fourier analytic techniques, we derive linear stability results for both the affirmative and negative solutions to this problem. Furthermore, we investigate the linear separation in this framework.
RNA Editing Analysis Reveals Methyl Jasmonic Acid Regulation of Fucoxanthin and Fatty Acid Metabolism in Phaeodactylum tricornutum
Authors: Huang Sihui , Liu Hao , Xu Ruihao , Li Wangchang , Yang Han , Bao Xinlei , Hang Yuqing , Gong Yifu , Zhao Yuxiang
Published: February 2025

Phaeodactylum tricornutum is a marine diatom with significant biotechnological potential, particularly in producing high-value bioactive compounds such as fucoxanthin and unsaturated fatty acids, which possess significant pharmaceutical and nutraceutical properties. However, the naturally low yields of these compounds present a major challenge for large-scale production. Methyl jasmonic acid (MeJA), a plant-derived signaling molecule, has been shown to enhance the biosynthesis of these metabolites in P. tricornutum. While transcriptional regulation has been extensively studied, the role of post-transcriptional modifications, such as RNA editing, in mediating MeJA-induced metabolic changes remains largely unexplored. RNA editing can alter nucleotide sequences, leading to functional changes in gene expression and protein activity, thus providing a potential regulatory mechanism for enhanced biosynthesis of target metabolites. In this study, we investigated the role of RNA editing in Phaeodactylum tricornutum under methyl jasmonic acid (MeJA) treatment, focusing on its impact on the accumulation of bioactive compounds such as fucoxanthin and fatty acids. We conducted a comprehensive comparative analysis of RNA editing events across MeJA-treated and control groups. Our findings reveal that MeJA treatment induces significant variations in RNA editing levels, affecting key metabolic pathways. Notably, two genes, Lhcr10 (Phatr3_J16481) and Phatr3_J43665, were identified as potential contributors to increased RNA editing enzyme activity and to energy metabolism and fatty acid biosynthesis under MeJA treatment. These results provide a foundation for the discovery of molecular mechanisms underlying adaptive responses in P. tricornutum and highlight RNA editing as a critical regulatory mechanism in MeJA-induced metabolic reprogramming.
Salicylic Acid Modulates Volatile Organic Compound Profiles During CEVd Infection in Tomato Plants
Authors: Balanzá Marc , Vázquez-Prol Francisco , Rodrigo Ismael , Bellés José María , Vera-Sirera Francisco , López-Gresa Maria Pilar , Lisón Purificación
Published: February 2025

Background:Citrus Exocortis Viroid (CEVd) is a non-coding RNA pathogen capable of infecting a wide range of plant species, despite its lack of protein-coding ability. Viroid infections induce significant alterations in various physiological and biochemical processes, particularly impacting plant metabolism. This study shows the metabolic changes upon viroid infection in tomato plants (Solanum lycopersicum var. ‘MoneyMaker’) exhibiting altered levels of salicylic acid (SA), a key signal molecule involved in the plant defence against this pathogen. Methods: Transgenic RNAi_S5H lines, which have the salicylic acid 5-hydroxylase gene silenced to promote SA accumulation, and NahG lines, which overexpress a salicylate hydroxylase to degrade SA into catechol and prevent its accumulation, were used to establish different SA levels in plants, resulting in varying degrees of resistance to viroid infection. The analysis was performed by using gas chromatography–mass spectrometry (GC-MS) to explore the role of volatile organic compounds (VOCs) in plant immunity against this pathogen. Results: Our results revealed distinct volatile profiles associated with plant immunity, where RNAi_S5H-resistant plants showed significantly enhanced production of monoterpenoids upon viroid infection. Moreover, viroid-susceptible NahG plants emitted a broad range of VOCs, whilst viroid-tolerant RNAi_S5H plants exhibited less variation in VOC emission. Conclusions: This study demonstrates that SA levels significantly influence metabolic responses and immunity in tomato plants infected by CEVd. The identification of differential emitted VOCs upon CEVd infection could allow the development of biomarkers for disease or strategies for disease control.
Transcriptomic Response of Balamuthia mandrillaris to Lippia graveolens Extract Fractions
Authors: Gonzalez-Zuñiga Leobardo Daniel , Gonzalez-Galaviz Jose Reyes , Cruz-Mendívil Abraham , Lares Villa Fernando , Gutiérrez-Grijalva Erick Paul , López-Cervantes Jaime , Sánchez-Machado Dalia I. , Lares-Jiménez Luis Fernando , Rodriguez-Anaya Libia Zulema
Published: February 2025

Balamuthia mandrillaris is a free-living amoeba pathogenic to humans, causing amoebic granulomatous encephalitis (GAE). Due to the associated mortality rates of <95%, the absence of treatments, and a clear understanding of the pathogenesis of this amoeba, Lippia graveolens could be an interesting alternative since it has been used against bacteria, fungi, and other pathogenic protozoa. This study employed RNA sequencing to analyze differentially expressed genes (DEGs), following treatment with two fractionated L. graveolens extracts (concentration: 150 µg/mL) at 48, 96, and 120 h. The DEGs identified are associated with several functions such as stress responses (Prohibitin domain-containing protein), and oxidative damage repair and cell stability (Peroxiredoxin). Genes implicated in virulence and host interaction also showed significant expression changes, such as the ADP ribosylation factor (Arf) GTPase and ephrin type-A receptor, alongside transcription factors involved in the phagocytosis of amoebas. Additionally, the analysis of Gene Ontology categories revealed terms including transmembrane signaling receptor and protein tyrosine activity, DNA replication initiation, the mitotic M phase, and membrane integrity. These results provide valuable insights into the molecular mechanisms utilized by B. mandrillaris to respond to environmental stressors and the repression of genes related to essential functions, which could serve as potential targets for developing novel strategies.
Raman Spectroscopy of Fullerenes: From C60 to Functionalized Derivatives
Authors: Qin Yifan , Xu Jilian , Liang Zhewen , Teng Haijun , Zhan Da , Xu Hai
Published: February 2025

Fullerenes, a unique allotrope of carbon, have captured significant attention in multiple scientific fields. As a non-destructive characterization technique, Raman spectroscopy has proven indispensable for investigating fullerenes and their derivatives, offering detailed insights into their vibrational properties. This review discusses the broad utility of Raman spectroscopy in revealing the structural and physicochemical characteristics of fullerenes—from the iconic C60 molecule to an array of its derivatives—highlighting its capacity to detect functionalization-induced changes in molecular structure and electronic properties, while also assessing environmental influences such as solvent effects and temperature variations. Particular emphasis is placed on advanced Raman-based techniques, including enhanced Raman spectroscopy, surface-enhanced Raman spectroscopy (SERS), and tip-enhanced Raman spectroscopy (TERS), for the characterization of fullerenes and their derivatives. These cutting-edge methods offer high sensitivity and ultra-high spatial resolution, greatly expanding the scope of fullerene research and delivering deeper insights into their structural and functional properties.
Shannon Entropy in Uncertainty Quantification for the Physical Effective Parameter Computations of Some Nanofluids
Authors: Kamiński Marcin , Ossowski Rafał Leszek
Published: February 2025

The main aim of this study is probabilistic computer simulation of the effective physical parameters of fluids containing nanoparticles. A deterministic model following the rule of mixtures and some semi-empirical formulas are employed to calculate effective density, heat conductivity, heat capacity, as well as viscosity for the given nanofluid. This models is randomized here using the Monte-Carlo simulation apparatus for estimation of the Shannon entropy of all these physical parameters, which is the crucial novelty of this study. The volume fraction of the nanoparticles is assumed for this purpose as the Gaussian uncertainty source with the given first two moments. The basic probabilistic characteristics of the nanofluids’ homogenized parameters have also been determined here for some validation of Shannon entropy variations in addition to the statistical disorder of the nanoparticle fraction. These research findings contribute to advancing nanofluidic and microfluidic research, offering robust tools for uncertainty analysis and enhancing the reliability of physical parameter predictions in applications requiring high numerical and/or experimental precision.
Contextual Influence on Pattern Separation During Encoding
Authors: García-Rueda Laura , Poch Claudia , Macedo-Pascual Joaquín , Campo Pablo
Published: February 2025

Pattern separation is considered a crucial process that allows us to distinguish among the highly similar and overlapping experiences that constitute our episodic memory. Not only do different episodes share common features, but it is often the case that they share the context in which they occurred. While there have been a great number of studies investigating pattern separation and its behavioral counterpart, a process known as mnemonic discrimination, surprisingly, research exploring the influence of context on pattern separation or mnemonic discrimination has been less common. The available evidence shows that similar items with similar contexts led to a failure in pattern separation due to high similarity that triggers overlap between events. On the other hand, others have shown that pattern separation can take place even under these conditions, allowing humans to distinguish between events with similar items and contexts, as different hippocampal subfields would play complementary roles in enabling both pattern separation and pattern completion. In the present study, we were interested in testing how stability in context influenced pattern separation. Despite the fact that pattern separation is by definition an encoding computation, the existing literature has focused on the retrieval phase. Here, we used a subsequent memory paradigm in which we manipulated the similarity of context during the encoding of visual objects selected from diverse categories. Thus, we manipulated the encoded context of each object category (four items within a category), so that some categories had the same context and others had a different context. This approach allowed us to test not only the items presented but also to include the conditions that entail the greatest demand on pattern separation. After a 20 min period, participants performed a visual mnemonic discrimination task in which they had to differentiate between old, similar, and new items by providing one of the three options for each tested item. Similarly to previous studies, we found no interaction between judgments and contexts, and participants were able to discriminate between old and lure items at the behavioral level in both conditions. Moreover, when averaging the ERPs of all the items presented within a category, a significant SME emerged between hits and new misses, but not between hits and old false alarms or similar false alarms. These results suggest that item recognition emerges from the interaction with subsequently encoded information, and not just between item memory strength and retrieval processes.
Polyunsaturated Fatty Acids: New Molecular Mechanisms and Nutritional Therapeutic Challenges
Authors: Delmas Dominique , Aires Virginie
Published: February 2025

The scientific exploration of polyunsaturated fatty acids (PUFAs) continues to unveil their profound impact on human health [...]
Eat More Healthily: Nutrition Quality and Nutrition Information of Foods
Authors: Ropero Ana B.
Published: February 2025

Healthy eating is one of the main factors that contribute to reducing the risk of noncommunicable diseases [...]
Dietary Capsaicin Exacerbates Gut Microbiota Dysbiosis and Mental Disorders in Type 1 Diabetes Mice
Authors: Zhang Xiaohui , Hu Houjia , Zhang Yue , Hu Shuting , Lu Jiaqin , Peng Weijie , Luo Dan
Published: February 2025

Background/Objectives: Diabetes mellitus is often accompanied by mental health complications, including anxiety, depression, and cognitive decline. Recent research suggested that capsaicin, the active component of chili peppers, may influence mental health. This study aimed to determine the effect of dietary capsaicin on mental disorders in a type 1 diabetes (T1D) mouse model, while also exploring the potential involvement of the microbiota-gut-brain axis. Methods: We induced T1D in mice using streptozotocin (STZ) and administered a diet supplemented with 0.005% capsaicin for five weeks. Behavioral assessments, including the open field test (OFT), tail suspension test (TST), forced swimming test (FST), elevated plus maze (EPM) test, and Morris water maze (MWM) test, were conducted to evaluate depressive and anxiety-like behaviors as well as cognitive function. Targeted and untargeted metabolomics analyses were performed to assess neurotransmitter levels in the hippocampus and serum metabolites, while 16S rRNA sequencing was utilized to analyze gut microbiota composition. Intestinal barriers were determined using western blot detection of the tight junction proteins ZO-1 and occludin. Results: Dietary capsaicin exacerbated anxiety and depressive-like behaviors along with cognitive declines in T1D mice. Capsaicin reduced gut microbiota diversity and levels of beneficial bacteria, while broad-spectrum antibiotic treatment further intensified anxiety and depression behaviors. Metabolomic analysis indicated that capsaicin disrupted metabolic pathways related to tryptophan and phenylalanine, leading to decreased neuroprotective metabolites, such as kynurenic acid, hippurate, and butyric acid. Additionally, capsaicin diminished the expression of ZO-1 and occludin, indicating increased intestinal permeability. Conclusions: Dietary capsaicin aggravates gut microbiota and metabolic disturbances in diabetic mice, thereby worsening anxiety, depression, and cognitive decline.
Selenium and Episodic Memory: The Moderating Role of Apolipoprotein E ε4
Authors: Kim Shin Gyeom , Keum Musung , Choe Young Min , Suh Guk-Hee , Lee Boung Chul , Kim Hyun Soo , Lee Jun Hyung , Hwang Jaeuk , Yi Dahyun , Kim Jee Wook
Published: February 2025

Background: Selenium (Se), a vital trace element, plays a neuroprotective role by mitigating oxidative stress through selenoproteins and regulating metal balance. The apolipoprotein E ε4 allele (APOE4), a significant genetic risk factor for Alzheimer’s disease (AD), has been linked to reduced Se levels and weakened antioxidant capacity. This research explores the association between serum Se concentrations and cognitive performance, with an emphasis on how APOE4 status influences this relationship. Methods: This study included 196 older adults from community and memory clinic settings, who underwent assessments for episodic memory, global cognition, and non-memory functions using the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) neuropsychological battery, with serum selenium levels analyzed via inductively coupled plasma–mass spectrometry (ICP-MS) and APOE genotyping conducted to determine allele status. Results: Higher serum Se levels were associated with better episodic memory score (EMS) (B = 0.065, 95% CI = 0.020–0.110, p = 0.005) and CERAD total score (TS) (B = 0.119, 95% CI = 0.046–0.193, p = 0.002). However, the interaction between Se and APOE4 status significantly affected EMS (B = −0.074, 95% CI = −0.109 to −0.039, p < 0.001), with significant benefits observed in APOE4-negative participants. Conclusions: This study highlights the genotype-specific impact of Se on cognitive health, emphasizing the need for personalized nutritional interventions targeting Se levels, particularly for APOE4-negative individuals. Future research should further elucidate the mechanisms of Se’s effects and assess its therapeutic potential in aging populations.
The Management of Children with Chronic Health Problems at School from the Perspective of Parents
Authors: Morales Ruíz María del Pilar , Fernández-Medina Isabel María , Alias-Castillo Antonio Javier , Ventura-Miranda María Isabel , Jiménez-Lasserrotte María del Mar , Ruíz-Fernández María Dolores
Published: February 2025

Background: The prevalence of chronic health problems in childhood, such as food and respiratory allergies, as well as endocrine and skin disorders, has increased globally. Parents and children experience difficulties in managing their illness that reduce their quality of life and increase the presence of negative feelings such as fear or anxiety during school hours. Objectives: The aim of this study was to describe and understand the parents’ experiences of the management of children with chronic health problems during school hours. Methods: A qualitative descriptive study design was used. Semi-structured interviews were conducted with 17 parents (1 male and 16 female) who have children with a chronic health problem between September 2022 and June 2023. The data were analyzed with the help of a qualitative data analysis software. The COREQ checklist was used to develop the study. Results: Two categories and four subcategories emerged from the data analysis: (1) Parents’ Perceptions, with the subcategories 1.1., The School Nurse, and 1.2., Educational Environment; and (2) Chronic Pediatric Health Problems, with the subcategories 2.1., Emotional Impact, and 2.2., Lack of Resources. Conclusions: Children with chronic health problems are unprotected during school hours due to the absence of a school nurse. Parents and teachers have to cope with their care without the necessary knowledge, which makes it difficult to manage children with chronic health problems in the school environment.
Utility of 28S Ribosomal RNA Gene Domains for Molecular Classification and Phylogeny of Rhinonyssid Mites
Authors: Sánchez-Carrión Susana A. , Márquez Francisco J. , de Rojas Manuel
Published: February 2025

The family Rhinonyssidae includes endoparasitic, blood-feeding mites that are parasitic on birds and that remain largely unstudied despite their potential role as vectors or reservoirs for various pathogens, like other Dermanyssoidea. Traditionally, the taxonomy of the group has been based on morphometric characteristics, which makes identification very difficult in many groups of closely related species. On the other hand, studies on the phylogenetic relationships within this group of mites have been neglected until the early years of the present century. In this study, twelve species belonging to five different species complexes were identified, and domains D1–D3 28S rRNA of each one were sequenced, for the first time, to investigate the sequence variation and its taxonomic implications for phylogenetic inference. Our data indicate that this molecular marker can effectively differentiate between species within the “motacillae”, “sairae”, “pari”, and “hirsti” complexes of the genus Ptilonyssus and the “melloi” and “columbae” complexes of the genus Tinaminyssus. Furthermore, the phylogenetic tree that can be derived from the domain D1–D3 28S rRNA sequences presented in this study is congruent with the current taxonomy of the Rhinonyssidae. This research calls for a reassessment of the taxonomic status of some group of species.
Enhanced Anti-Babesia Efficacy of Buparvaquone and Imidocarb When Combined with ELQ-316 In Vitro Culture of Babesia bigemina
Authors: Cardillo Natalia M. , Villarino Nicolas F. , Lacy Paul A. , Doggett Joseph S. , Riscoe Michael K. , Suarez Carlos E. , Ueti Massaro W. , Chung Chungwon J.
Published: February 2025

Background/Objectives: B. bigemina is a highly pathogenic and widely distributed tick-borne disease parasite responsible for bovine babesiosis. The development of effective and safe therapies is urgently needed for global disease control. The aim of this study is to compare the effects of endochin-like quinolone (ELQ-316), buparvaquone (BPQ), imidocarb (ID), and the combinations of ID + ELQ-316 and BPQ + ELQ-316, on in vitro survival of B. bigemina. Methods: Parasites at a starting parasitemia level of 2%, were incubated with each single drug and a combination of drugs, ranging from 25 to 1200 nM of concentration over four consecutive days. The inhibitory concentrations, 50% (IC50%) and 99% (IC99%), were estimated. Parasitemia levels were evaluated daily using microscopic examination. Data were statistically compared using the non-parametrical Kruskall–Wallis test. Results: All drugs tested significantly inhibited (p < 0.05) the growth of B. bigemina at 2% parasitemia. The combination of ID + ELQ-316 exhibited a lower mean (IC50%: 9.2; confidence interval 95%: 8.7–9.9) than ID (IC50%: 61.5; confidence interval 95%: 59.54–63.46), ELQ-316 (IC50%: 48.10; confidence interval 95%: 42.76–58.83), BPQ (IC50%: 44.66; confidence interval 95%: 43.56–45.81), and BPQ + ELQ-316 (IC50%: 27.59; confidence interval: N/A). Parasites were no longer viable in cultures treated with the BPQ + ELQ-316 combination, as well as with BPQ alone at a concentration of 1200 nM, on days 2 and 3 of treatment, respectively. Conclusions: BPQ and ID increase the babesiacidal effect of ELQ-316. The efficacy of these combinations deserves to be evaluated in vivo, which could lead to a promising and safer treatment option for B. bigemina.
Preparing a Liposome-Aided Drug Delivery System: The Entrapment and Release Profiles of Doxorubicin and 9-(N-Piperazinyl)-5-methyl-12(H)-quino [3,4-b][1,4]benzothiazinium Chloride with Human Serum Albumin
Authors: Pentak Danuta , Kozik Violetta , Zieba Andrzej , Paździor-Heiske Marlena , Szymczyk Aleksandra , Jampilek Josef , Bak Andrzej
Published: February 2025

Background/Objectives: The principal aim of this work was to prepare a liposomal drug delivery system based on the commercial drug doxorubicin (DOX) and a budding agent with promising anticancer activity, 9-(N-piperazinyl)-5-methyl-12(H)-quino [3,4-b][1,4]benzothiazinium chloride (9-PBThACl). Methods: A spectrophotometric methodology was used to meticulously investigate the drug entrapment and release characteristics of the new liposomal complexes (L) based on dipalmitoylphosphatidylcholine (DPPC) with human serum albumin (HSA) and its defeated analog (dHSA). Results: The impact of the operational parameters (temperature and pH) on the liposome/drug(s)/(d)HSA, namely [LDPPC/9-PBThACl/DOX ]:(d)HSA] systems, as well as the polarity of the phospholipid bilayer, was examined. In order to compare the experimental findings, mathematical models were employed to specify the analytical factors controlling the process of drug release/potential drug release from liposomes. The observed variations in the drug encapsulation and release profiles were due to the combination of liposomal conjugates with human plasma protein. Conclusions: It was proven that changes in the environmental pH directly affect the percentage of drug entrapment in liposomes and the medicine release efficiency. Moreover, the grouping tendency of the liposomal combinations was investigated using a principal component analysis (PCA) and a hierarchical clustering analysis (HCA). Finally, an analysis of variance (ANOVA) confirmed the statistical impact of pH buffering and changing temperature factors on the drug release characteristics of liposomal conjugates.
PLGA-Based Strategies for Intranasal and Pulmonary Applications
Authors: Omidian Hossein , Wilson Renae L.
Published: February 2025

Poly(D,L-lactide-co-glycolide) (PLGA) has emerged as a cornerstone in the development of advanced drug delivery systems, particularly for intranasal and pulmonary routes. Its biodegradability, biocompatibility, and adaptability make it an ideal platform for addressing challenges associated with conventional therapies. By enabling sustained and controlled drug release, PLGA formulations reduce dosing frequency, improve patient compliance, and enhance therapeutic efficacy. These systems demonstrate versatility, accommodating hydrophilic and hydrophobic drugs, biological molecules, and co-delivery of synergistic agents. Moreover, surface modifications and advanced preparation techniques enhance targeting, bioavailability, and stability, expanding PLGA’s applications to treat complex diseases such as tuberculosis, cancer, pulmonary fibrosis, and CNS disorders. This manuscript provides an in-depth review of PLGA’s materials, properties, preparation methods, and therapeutic applications, alongside a critical evaluation of challenges and future opportunities in this field.
Combined Use of Biostimulation and Deficit Irrigation Improved the Fruit Quality in Table Grape
Authors: Zapata-García Susana , Berríos Pablo , Temnani Abdelmalek , Espinosa Pedro J. , Monllor Claudia , Pérez-Pastor Alejandro
Published: February 2025

This study aims to determine the effects of four different biostimulation treatments—composed of microorganisms, seaweed, and plant extracts—on the yield and quality traits of table grapes. Those treatments are compared with an untreated control treatment and tested under two different irrigation schedules: (i) Farmer Irrigation (FI), according to farmer criteria, and (ii) a deficit irrigation program, Precision Irrigation (PI), irrigated as FI, except during the post-veraison period when a 10% soil water depletion was allowed to mitigate the lixiviation. The water inputs in the treatments under PI were reduced by 30% without affecting the total yield but still promoting harvest precocity—an effect that was enhanced by the biostimulated treatments. This deficit irrigation program also stimulated berry growth and a higher maturity index. The different biostimulation treatments led to an improvement in the physical and chemical quality traits of the grapes; under FI, they showed a bigger size and a greater weight than the non-biostimulated treatment, while under PI, they showed a higher soluble sugar concentration and maturity index. Regardless of the irrigation program, the commercial berry color proportion was increased in all the biostimulated treatments, reducing the percentage of green berries. The combined use of biostimulation and PI can promote more efficient and sustainable farming practices, promoting fruit yield precocity and quality of the grapevine in drought-prone regions.
L-Theanine Metabolism in Tea Plants: Biological Functions and Stress Tolerance Mechanisms
Authors: Wang Qianying , Yu Jingbo , Lin Wenchao , Ahammed Golam Jalal , Wang Wenli , Ma Ruihong , Shi Mengyao , Ge Shibei , Mohamed Ahmed S. , Wang Liyuan , Li Qingyun , Li Xin
Published: February 2025

L-theanine, a unique non-protein amino acid predominantly found in tea plants (Camellia sinensis), plays a pivotal role in plant responses to abiotic stress and significantly influences tea quality. In this review, the metabolism and transport mechanisms of L-theanine are comprehensively discussed, highlighting its spatial distribution in tea plants, where it is most abundant in young leaves and less so in roots, stems, and older leaves. The biosynthesis of L-theanine occurs through the enzymatic conversion of glutamate and ethylamine, catalyzed by theanine synthase, primarily in the roots, from where it is transported to aerial parts of the plant for further catabolism. Environmental factors such as temperature, light, drought, elevated CO2, nutrient unavailability, and heavy metals significantly affect theanine biosynthesis and hydrolysis, with plant hormones and transcription factors playing crucial regulatory roles. Furthermore, it has been demonstrated that applying L-theanine exogenously improves other crops’ resistance to a range of abiotic stresses, suggesting its potential utility in improving crop resilience amid climate change. This review aims to elucidate the physiological mechanisms and biological functions of L-theanine metabolism under stress conditions, providing a theoretical foundation for enhancing tea quality and stress resistance in tea cultivation.
Ultraviolet-A Radiation (UVA) as a Stress and the Influence of Provenance and Leaf Age on the Expression of Phenolic Compounds by Eucalyptus camaldulensis ssp. camaldulensis
Authors: Khanal Santosh , Rochfort Simone J. , Steinbauer Martin J.
Published: February 2025

Ultraviolet radiation (UV) represents a significant abiotic stress, affecting green plants. Phenolic compounds have been suggested as components involved in plant photoprotective adaptation. We used a unique combination of experimental (LED lighting and leaf tagging) and analytical (unbiased, or untargeted, metabolomics) approaches to study the effects of high (approximating mid-summer) and low (approximating winter) levels of UVA on the expression of phenolic compounds. These consisted of river red gum (Eucalyptus camaldulensis ssp. camaldulensis) of five provenances. The geographically separated provenances used in our study spanned the lowest and highest latitudes of the range of this subspecies. The concentrations of gallotannins and ellagitannins (i.e., hydrolysable tannins) increased most under high levels of UVA, but responses only differed slightly among provenances. The most substantial changes in the composition of phenolic compounds were associated with leaf age. Overall, 3-month-old (herein, termed ‘young’) leaves had substantially different phenolic compositions to 6- and 12-month-old (‘old’) leaves. Hydrolysable tannins were more abundant in young leaves, whereas pedunculagin, catechin, and kaempferol galloyl glucoses were more abundant in old leaves. High levels of UVA altered the expression of phenolic compounds, but our experimental saplings were unlikely to experience photoinhibition because they were not exposed to high levels of light and low temperatures, nor were they nitrogen-limited. We expect that changes in phenolic compounds would have been more pronounced if we had induced photoinhibition.
The Social Responsibility of Young Professionals Working with Information Systems and Technologies
Authors: Anunciação Pedro , Lemos Filipe , Bumba Mónica
Published: February 2025

Research purpose—Economy digital transformation has had a strong impact on several areas, such as employment, economic organization modus operandi, or the digital modernization of economic agents. Technological innovations, such as artificial intelligence, have resulted in new digital products and services that are smarter, autonomous, and complex. This evolution requires ethics and social responsibility as critical components of economic sustainability. Design/methodology/approach—This article analyzes the relevance of ethics and social responsibility among young information systems professionals. Given the technological specificity of the new generation, it was considered an opportunity to analyze sensitivity to their ethical obligations and responsibilities. A survey was sent to about 40 information systems and technology young professionals, as a convenience sample, to assess several dimensions of ethics and social responsibility, and to identify an opportunity for future studies. Findings—The results show that there is responsibility regarding the social effects of technology on technology users. However, it is noted that there is still a long way to go, because decisions regarding ethical and social responsibilities cannot be left to the discretion of each individual professional. Economic organizations should assume values, policies, and rules appropriated to the new order in the context of the information society. Originality/value/practical implications—The present study aimed to evaluate the relevance of ethics and social responsibility to information systems young professionals, and we expect that these results can encourage them to develop greater sensitivity to this issue, contributing to the change needed and desired.
Copper(II)-Complexed Polyethylenimine-Entrapped Gold Nanoparticles Enable Targeted CT/MR Imaging and Chemodynamic Therapy of Tumors
Authors: He Lingxiu , Liu Na , Pan Risong , Zhu Jingyi
Published: February 2025

Transition-metal ion copper(II) (Cu(II)) has drawn increasing attention as a small-molecular cancer theranostic agent. However, delivering a sufficient dosage of Cu(II) to the tumor site and integrating multiple imaging modalities to achieve precise and effective cancer theranostics remains a critical challenge. Herein, an emerging Cu(II)-based nanocomposite has been synthesized for targeted tumor computed tomography (CT)/magnetic resonance (MR) dual-mode imaging and chemodynamic therapy (CDT). Briefly, 2-picolinic acid (PA-COOH), polyethylene glycol (PEG)-linked folic acid (FA), and fluorescein isothiocyanate (FI) were sequentially conjugated with polyethylenimine (PEI.NH2) and then in situ fabrication of gold nanoparticles (Au NPs) occurred within the PEI.NH2 internal cavity. After acetylation of PEI.NH2 terminal amines and Cu(II) complexation, the Cu(II)-based nanocomposites FA-Au/Cu(II) PENPs with a mean diameter of 2.87 nm were generated. The synthesized FA-Au/Cu(II) PENPs showed favorable stability of colloidal dispersion, sustainable Cu(II) release properties in a pH-dependent manner, and Fenton-like catalytic activity specifically. With the FA-mediated targeting pathway, FA-Au/Cu(II) PENPs can specifically accumulate in cancer cells with high expression of FA receptors. Meanwhile, the complementary CT/MR dual-mode imaging in vitro and in vivo can be afforded by FA-Au/Cu(II) PENPs based on the excellent X-ray attenuation properties of Au NPs and the applicable r1 relaxivity (0.7378 mM−1s−1) of Cu(II). Notably, the Cu(II)-mediated CDT mechanism enables FA-Au/Cu(II) PENPs to elicit the generation of toxic hydroxyl radicals (·OH), depletion of glutathione (GSH), promotion of lipid peroxidation (LPO), and induction of cancer cell apoptosis in vitro, and further demonstrates remarkable anti-tumor efficacy in a xenograft tumor model. With the illustrated targeted theranostic capacity of FA-Au/Cu(II) PENPs towards tumors, this Cu(II)-based nanocomposite paradigm inspires the construction of advanced theranostic nanoplatforms incorporating alternative transition metal ions.
Effects of Guar Gum and Sodium Benzoate on the Properties and Hydrophilicity of Silk Fibroin Hydrogels
Authors: Thonpho Ansaya , Baimark Yodthong , Tanisood Suchai , Srihanam Prasong
Published: February 2025

Silk fibroin (SF)–based hydrogels were prepared by the simple evaporation method. The outcomes of SF–based hydrogels were assessed for consideration in terms of practical and convenient use. Guar gum (GG) and sodium benzoate (SB) are blending reagents to the SF solution and are poured into the petri dish to make the hydrogels. After leaving the mixture solution for three days to solidify, all SF–based hydrogels were peeled off and characterized. The SF–blend guar gum (SF–GG) and SF–GG–blend sodium benzoate (SF–GG–SB) could be constructed, but in different textures and levels of transparency. The SB affected the solid texture and resulted in a higher water contact angle (WCA) value of the prepared SF hydrogel than of the SF–GG. The results from Fourier transform infrared spectroscopy (FTIR) indicated all the main functional groups of substances that were contained in the blending hydrogels. Moreover, some interactions between the functional groups were also detected. A thermogravimetric analyzer (TGA) was used to determine the hydrogel decomposition as a function of temperature. The DTG thermograms, which exhibit the maximum decomposition temperature, revealed that the interaction forces between blending substances and SF, as well as their structure, are the reason for the thermal stability of the SF–based hydrogels. SF–GG–SB hydrogels have higher tensile strength than the SF–GG hydrogels. In conclusion, the appearance, texture, hydrophilicity, thermal stability, and tensile strength of the SF–based hydrogels were affected by the types and concentrations of the blending substances. This suggests that the SF–based hydrogel properties could be designed and adjusted to attain desirable textures for fitting target applications.
Effects of Degassing Treatment on the Dielectric Properties of XLPE Insulation Used in High-Voltage DC Power Cables
Authors: Ding Man , Zheng Qingfeng , Wang Jiahe , He Weifeng , Dai Chao , Wen Dingjun
Published: February 2025

Cross-linked polyethylene power cables are widely used in high-voltage DC transmission lines, owing to their good dielectric and physical–chemical properties. However, the production process of XLPE involves cross-linking and degassing, in which the cross-linking process produces a variety of cross-linking by-products, and the changes in the properties of the cable insulation caused by the degassing process are not well understood. XLPE samples were degassed at 90 °C for 7 and 14 days in this paper, and the main by-products were found to be α-methylstyrene, acetophenone, and cumyl alcohol, the contents of which all declined after the degassing treatment. The results show that the space charge density, the leakage current under a high electric field at different temperatures, and the breakdown strength of the XLPE samples all decreased after the degassing treatment. On the other hand, the XLPE sample after 7 days’ degassing had the lowest conductivity and the highest conductance activation, and the space charge density and the charge decay rate as well as the breakdown strength after 7 days’ degassing differed little from the 14-day treated sample, demonstrating that the 7-day degassing treatment at 90 °C would be enough to achieve superior performance.
Molecular Dynamics Simulation of the Thermal Treatment of the Ara h 6 Peanut Protein
Authors: Smith Andrea , Raghavan Vijaya
Published: February 2025

The Ara h 6 protein is an important allergen found in peanuts (Arachis hypogaea). Ara h 6 represents a significant risk to human health, given its potential to trigger IgE-mediated anaphylaxis. Seeing as peanuts are often heat-processed prior to consumption, understanding the effect heat application has on the Ara h 6 protein’s structure and function is vital. Therefore, the purpose of this study was to explore, through the application of long-timescale 200 ns GROMACS molecular dynamics simulations, the structural changes that occur in the Ara h 6 allergen during thermal processing at 300 K, 350 K, 400 K and 450 K. Larger fluctuations in the Ara h 6 allergen’s secondary structure, RMSD and RMSF were identified at higher processing temperatures. However, observed decreases in Rg and SASA as processing temperature rose from 300 K to 400 K suggested that these observed fluctuations in the structure may be due to a compaction of the protein’s structure. Overall, the Ara h 6 allergen exhibited high thermostability.
Industrial Part Faults Prediction for Nonlinearity and Implied Temporal Sequences
Authors: Zhang Shuyu , Zhang Mengyi , Bo Cuimei , Wang Cunsong
Published: February 2025

The ability to preemptively identify potential failures in industrial parts is crucial for minimizing downtime, reducing maintenance costs and ensuring system reliability and safety. However, challenges such as data nonlinearity, temporal dependencies, and imbalanced datasets complicate accurate fault prediction. In this study, we propose a novel combined approach that integrates the Logistic Model Tree Forest (LMT) with Stacked Long Short-Term Memory (LSTM) networks, addressing these challenges effectively. This hybrid method leverages the decision-making capability of the LMT and the temporal sequence learning ability of Stacked LSTM to improve fault prediction accuracy. Additionally, to tackle the issues posed by imbalanced datasets and noise, we employ the ENN-SMOTE (Edited Nearest Neighbors-Synthetic Minority Over-sampling Technique), a technique for data preprocessing, which enhances data balance and quality. Experimental results show that our approach significantly outperforms traditional methods, achieving a fault prediction accuracy of up to 98.2%. This improvement not only demonstrates the effectiveness of the combined model but also highlights its potential for real-world industrial applications, where high accuracy and reliability are paramount.