bluuebunny/crossref_metadata_2025 huggingface dataset:
Methyl 6,7-Difluoro-2-[(4-fluorobenzyl)sulfanyl]-4-hydroxyquinoline-3-carboxylate
Authors: Potapov Vladimir A. , Novokshonova Irina A. , Musalov Maxim V. , Amosova Svetlana V. , Rakitin Oleg A.
Published: September 2024

A convenient synthesis of a novel fluoroquinolone precursor, methyl 6,7-difluoro-2-[(4-fluorobenzyl)sulfanyl]-4-hydroxyquinoline-3-carboxylate, at a 78% yield starting from 3,4-difluorophenyl isothiocyanate was developed. The structure of the product was established by 1H, 13C, and 19F NMR spectroscopy, mass spectrometry, IR spectroscopy and confirmed by elemental analysis. The title compound, containing the pharmacophoric 4-fluorobenzyl group, will be used in the synthesis of novel fluoroquinolone derivatives.
Bis [4,4′-(1,3-Phenylenebis(azanylylidene))-bis(3,6-di-tert-butyl-2-oxycyclohexa-2,5-dien-1-one)-bis(dimethylsulfoxide)nickel(II)]
Authors: Meshcheryakova Irina N. , Druzhkov Nikolay O. , Yakushev Ilya A. , Arsenyeva Kseniya V. , Klimashevskaya Anastasiya V. , Piskunov Alexandr V.
Published: September 2024

A new cage-like dimeric nickel(II) complex Ni2L2(DMSO)4 based on a ditopic redox-active hydroxy-para-iminobenzoquinone type ligand LH2 (L is 4,4′-(1,3-phenylene-bis(azaneylylidene))-bis(3,6-di-tert-butyl-2-oxycyclohexa-2,5-dien-1-one dianion) was synthesized in DMSO at 120 °C. The molecular structure of the synthesized compound was determined by X-ray diffraction analysis. The complex Ni2L2(DMSO)4 is almost insoluble in all organic solvents, probably due to the presence of a large number of intermolecular contacts in its structure. The electronic spectrum and thermal stability of the crystalline compound have been studied.
Impact of a Bio-Cross-Linking Agent Obtained from Spent Coffee Grounds on the Physicochemical and Thermal Properties of Gelatin/Κ-Carrageenan Hydrogels
Authors: Sapuła Paulina , Zając Paulina , Pielichowski Krzysztof , Raftopoulos Konstantinos N. , Bialik-Wąs Katarzyna
Published: September 2024

Gelatine hydrogels can be prepared using different cross-linking methods, such as enzymatic, physical or chemical. Unfortunately, in the case of chemical cross-linking, the typically utilized synthetic cross-linkers are harmful to human health and the environment. Therefore, in accordance with the principles of green chemistry and sustainable development, we have obtained compounds for the chemical cross-linking of hydrogel polymers from the processing of spent coffee grounds. In this study, gelatin/κ-carrageenan hydrogels are cross-linked using a bio-cross-linking agent from spent coffee grounds. Their physicochemical and thermal properties are compared with those of standard physical gels. The chemical cross-linking was confirmed based on FT-IR spectra, which demonstrated the formation of new covalent bonds between the oxidized polyphenols included in the extract from the spent coffee grounds and the amide groups present in the gelatine structure. Significant differences were also observed in morphology (SEM images) and other physico-chemical characteristics (gel fraction, swelling ability, hardness). The chemically cross-linked hydrogels in comparison to physically ones are characterized by a better developed porous network, a slightly higher gel fraction (64.03 ± 4.52% as compared to 68.15 ± 0.77%), and a lower swelling ratio (3820 ± 45% as compared to 1773 ± 35%), while TGA results show that they have better thermal stability. The research confirmed the possibility of using the developed natural cross-linking agent in the process of obtaining hydrogel materials based on bio-polymers.
A Low-Profile and Ultra-Wideband Pancharatnam–Berry Coding Metasurface for High-Efficiency and Wide-Angle Circular Polarization Anomalous Reflection
Authors: Sun Cuizhen , Gao Junfei , Gao Huanhuan , Ma Xiongwei , Huang Xiaojun
Published: September 2024

The manipulation of electromagnetic waves using metasurfaces is important in areas such as stealth and communication. In this paper, we reported on the use of an element-based polarizer for the first step, which enables the incident electromagnetic waves to integrate into the cross-polarized waves with a relative bandwidth of 88% within 15–37.1 GHz. Then, an eight-element coding metasurface based on the Pancharatnam–Berry phase is presented for circular polarization anomalous reflection. The simulated values show that our work can achieve a high-efficiency (94%) and wide-angle (70°) anomalous reflection under normal incidence. The simulated values present good agreement with the experimental values. Our work reveals the ability to manipulate the waves and electromagnetic stealth.
Tensor Network Space-Time Spectral Collocation Method for Time-Dependent Convection-Diffusion-Reaction Equations
Authors: Adak Dibyendu , Truong Duc P. , Manzini Gianmarco , Rasmussen Kim Ø. , Alexandrov Boian S.
Published: September 2024

Emerging tensor network techniques for solutions of partial differential equations (PDEs), known for their ability to break the curse of dimensionality, deliver new mathematical methods for ultra-fast numerical solutions of high-dimensional problems. Here, we introduce a Tensor Train (TT) Chebyshev spectral collocation method, in both space and time, for the solution of the time-dependent convection-diffusion-reaction (CDR) equation with inhomogeneous boundary conditions, in Cartesian geometry. Previous methods for numerical solution of time-dependent PDEs often used finite difference for time, and a spectral scheme for the spatial dimensions, which led to a slow linear convergence. Spectral collocation space-time methods show exponential convergence; however, for realistic problems they need to solve large four-dimensional systems. We overcome this difficulty by using a TT approach, as its complexity only grows linearly with the number of dimensions. We show that our TT space-time Chebyshev spectral collocation method converges exponentially, when the solution of the CDR is smooth, and demonstrate that it leads to a very high compression of linear operators from terabytes to kilobytes in TT-format, and a speedup of tens of thousands of times when compared to a full-grid space-time spectral method. These advantages allow us to obtain the solutions at much higher resolutions.
Zero-Inflated Binary Classification Model with Elastic Net Regularization
Authors: Xin Hua , Lio Yuhlong , Chen Hsien-Ching , Tsai Tzong-Ru
Published: September 2024

Zero inflation and overfitting can reduce the accuracy rate of using machine learning models for characterizing binary data sets. A zero-inflated Bernoulli (ZIBer) model can be the right model to characterize zero-inflated binary data sets. When the ZIBer model is used to characterize zero-inflated binary data sets, overcoming the overfitting problem is still an open question. To improve the overfitting problem for using the ZIBer model, the minus log-likelihood function of the ZIBer model with the elastic net regularization rule for an overfitting penalty is proposed as the loss function. An estimation procedure to minimize the loss function is developed in this study using the gradient descent method (GDM) with the momentum term as the learning rate. The proposed estimation method has two advantages. First, the proposed estimation method can be a general method that simultaneously uses L1- and L2-norm terms for penalty and includes the ridge and least absolute shrinkage and selection operator methods as special cases. Second, the momentum learning rate can accelerate the convergence of the GDM and enhance the computation efficiency of the proposed estimation procedure. The parameter selection strategy is studied, and the performance of the proposed method is evaluated using Monte Carlo simulations. A diabetes example is used as an illustration.
A Covariance-Free Strictly Complex-Valued Relevance Vector Machine for Reducing the Order of Linear Time-Invariant Systems
Authors: Xie Weixiang , Song Jie
Published: September 2024

Multiple-input multiple-output (MIMO) linear time-invariant (LTI) systems exhibit enormous computational costs for high-dimensional problems. To address this problem, we propose a novel approach for reducing the dimensionality of MIMO systems. The method leverages the Takenaka–Malmquist basis and incorporates the strictly complex-valued relevant vector machine (SCRVM). We refer to this method as covariance-free maximum likelihood (CoFML). The proposed method avoids the explicit computation of the covariance matrix. CoFML solves multiple linear systems to obtain the required posterior statistics for covariance. This is achieved by exploiting the preconditioning matrix and the matrix diagonal element estimation rule. We provide theoretical justification for this approximation and show why our method scales well in high-dimensional settings. By employing the CoFML algorithm, we approximate MIMO systems in parallel, resulting in significant computational time savings. The effectiveness of this method is demonstrated through three well-known examples.
Generalized Shortest Path Problem: An Innovative Approach for Non-Additive Problems in Conditional Weighted Graphs
Authors: Durand Adrien , Watteau Timothé , Ghazi Georges , Botez Ruxandra Mihaela
Published: September 2024

The shortest path problem is fundamental in graph theory and has been studied extensively due to its practical importance. Despite this aspect, finding the shortest path between two nodes remains a significant challenge in many applications, as it often becomes complex and time consuming. This complexity becomes even more challenging when constraints make the problem non-additive, thereby increasing the difficulty of finding the optimal path. The objective of this paper is to present a broad perspective on the conventional shortest path problem. It introduces a new method to classify cost functions associated with graphs by defining distinct sets of cost functions. This classification facilitates the exploration of line graphs and an understanding of the upper bounds on the transformation sizes for these types of graphs. Based on these foundations, the paper proposes a practical methodology for solving non-additive shortest path problems. It also provides a proof of optimality and establishes an upper bound on the algorithmic cost of the proposed methodology. This study not only expands the scope of traditional shortest path problems but also highlights their computational complexity and potential solutions.
Series over Bessel Functions as Series in Terms of Riemann’s Zeta Function
Authors: Tričković Slobodan B. , Stanković Miomir S.
Published: September 2024

Relying on the Hurwitz formula, we find closed-form formulas for the series over sine and cosine functions through the Hurwitz zeta functions, and using them and another summation formula for trigonometric series, we obtain a finite sum for some series over the Riemann zeta functions. We apply these results to the series over Bessel functions, expressing them first as series over the Riemann zeta functions.
Lebesgue Spaces and Operators with Complex Gaussian Kernels
Authors: Negrín E. R. , González B. J. , Maan Jeetendrasingh
Published: September 2024

This paper examines the boundedness properties and Parseval-type relations for operators with complex Gaussian kernels over Lebesgue spaces. Furthermore, this study includes an exploration of the Gauss–Weierstrass semigroup, serving as a particular example within the framework of our analysis.
OCTNet: A Modified Multi-Scale Attention Feature Fusion Network with InceptionV3 for Retinal OCT Image Classification
Authors: Khalil Irshad , Mehmood Asif , Kim Hyunchul , Kim Jungsuk
Published: September 2024

Classification and identification of eye diseases using Optical Coherence Tomography (OCT) has been a challenging task and a trending research area in recent years. Accurate classification and detection of different diseases are crucial for effective care management and improving vision outcomes. Current detection methods fall into two main categories: traditional methods and deep learning-based approaches. Traditional approaches rely on machine learning for feature extraction, while deep learning methods utilize data-driven classification model training. In recent years, Deep Learning (DL) and Machine Learning (ML) algorithms have become essential tools, particularly in medical image classification, and are widely used to classify and identify various diseases. However, due to the high spatial similarities in OCT images, accurate classification remains a challenging task. In this paper, we introduce a novel model called “OCTNet” that integrates a deep learning model combining InceptionV3 with a modified multi-scale attention-based spatial attention block to enhance model performance. OCTNet employs an InceptionV3 backbone with a fusion of dual attention modules to construct the proposed architecture. The InceptionV3 model generates rich features from images, capturing both local and global aspects, which are then enhanced by utilizing the modified multi-scale spatial attention block, resulting in a significantly improved feature map. To evaluate the model’s performance, we utilized two state-of-the-art (SOTA) datasets that include images of normal cases, Choroidal Neovascularization (CNV), Drusen, and Diabetic Macular Edema (DME). Through experimentation and simulation, the proposed OCTNet improves the classification accuracy of the InceptionV3 model by 1.3%, yielding higher accuracy than other SOTA models. We also performed an ablation study to demonstrate the effectiveness of the proposed method. The model achieved an overall average accuracy of 99.50% and 99.65% with two different OCT datasets.
Data Imputation in Electricity Consumption Profiles through Shape Modeling with Autoencoders
Authors: Duarte Oscar , Duarte Javier E. , Rosero-Garcia Javier
Published: September 2024

In this paper, we propose a novel methodology for estimating missing data in energy consumption datasets. Conventional data imputation methods are not suitable for these datasets, because they are time series with special characteristics and because, for some applications, it is quite important to preserve the shape of the daily energy profile. Our answer to this need is the use of autoencoders. First, we split the problem into two subproblems: how to estimate the total amount of daily energy, and how to estimate the shape of the daily energy profile. We encode the shape as a new feature that can be modeled and predicted using autoencoders. In this way, the problem of imputation of profile data are reduced to two relatively simple problems on which conventional methods can be applied. However, the two predictions are related, so special care should be taken when reconstructing the profile. We show that, as a result, our data imputation methodology produces plausible profiles where other methods fail. We tested it on a highly corrupted dataset, outperforming conventional methods by a factor of 3.7.
Compound Optimum Designs for Clinical Trials in Personalized Medicine
Authors: Duarte Belmiro P. M. , Atkinson Anthony C. , Pedrosa David , van Munster Marlena
Published: September 2024

We consider optimal designs for clinical trials when response variance depends on treatment and covariates are included in the response model. These designs are generalizations of Neyman allocation, and commonly employed in personalized medicine where external covariates linearly affect the response. Very often, these designs aim at maximizing the amount of information gathered but fail to assure ethical requirements. We analyze compound optimal designs that maximize a criterion weighting the amount of information and the reward of allocating the patients to the most effective/least risky treatment. We develop a general representation for static (a priori) allocation and propose a semidefinite programming (SDP) formulation to support their numerical computation. This setup is extended assuming the variance and the parameters of the response of all treatments are unknown and an adaptive sequential optimal design scheme is implemented and used for demonstration. Purely information theoretic designs for the same allocation have been addressed elsewhere, and we use them to support the techniques applied to compound designs.
A Comprehensive Analytical Approach for Quality Control of Collagen in Food Supplements
Authors: Kržišnik Nika , Kurent Ema , Roškar Robert
Published: September 2024

Collagen is a popular nutricosmetic ingredient in food supplements due to its anti-aging and other positive effects on the skin. Due to its widespread use and the lack of regulation in this area, appropriate quality control is required to ensure efficacy and safety, with the development of analytical methods playing an important role. Currently, the quantitative determination of collagen is mainly based on time-consuming derivatization-based spectroscopic methods or on complex chromatographic methods with mass spectrometric detection. Therefore, in this study, two new, simple chromatographic methods have been developed. One is intended for the analysis of untreated samples and is characterized by the speed and simplicity of sample preparation. The other method quantifies collagen via the underivatized tripeptide Gly-Pro-Hyp formed by bacterial collagenase hydrolysis and is characterized by its specificity and ability to distinguish between marine and terrestrial collagen. The latter is a novelty in the field of simple methods for collagen analysis and is particularly important in terms of safety. Our comparison with established analytical methods (e.g., via hydroxyproline after complete hydrolysis) for collagen analysis undoubtedly showed the superiority of these new methods for the routine quality control of collagen supplements in terms of specificity, repeatability, sample stability, and simplification in sample preparation. The collagen content in the supplements tested was found to be adequate; however, some discrepancies were found regarding the labeling and origin of the collagen, with possible safety implications.
Direct Extraction of Lipids, β-Carotene, and Polyphenolic Compounds from Wet Microalga Dunaliella salina by Liquefied Dimethyl Ether
Authors: Kanda Hideki , Kusumi Kaito , Zhu Li , Wang Tao
Published: September 2024

Extraction of lipids and high-value products from highly wet microalgae requires significant energy for the drying pretreatment. In this study, we examined the direct extraction of lipids, β-carotene, and polyphenolic compounds from wet Dunaliella salina using liquefied dimethyl ether (DME), which is effective in lipid extraction for biofuel production. The amount of DME-extracted β-carotene was 7.0 mg/g, which was higher than that obtained from the chloroform–methanol extraction. Moreover, the total phenolic content extracted with DME and its antioxidant capacity were slightly higher than those extracted with chloroform–methanol. DME removed almost all the water and extracted 29.2 wt% of total lipids and 9.7 wt% of fatty acids. More lipids were extracted from wet samples by liquefied DME than by chloroform–methanol extraction. The C/N ratio of lipids extracted with DME was 112.0, higher than that of chloroform–methanol. The high C/N ratio suggests that nitrogen-containing phosphatidylcholines may be less easily extracted by liquefied DME and may be highly selective. However, the ratio of saturated fatty acids was 34.8%, lower than that of chloroform–methanol. Na+ and Mg2+ in the culture medium were not extracted using DME. Thus, using the extract with DME has both advantages and disadvantages compared to using the extract with chloroform–methanol; however, it has satisfactory extraction properties. DME is expected to be an environment-friendly alternative solvent because it does not require drying, which is necessary for conventional extraction solvents.
Diversity and Activity of Bacteria Cultured from a Cup—The Sponge Calyx nicaeensis
Authors: Itelson Lynne , Merav Mayan , Haymi Shai , Carmeli Shmuel , Ilan Micha
Published: September 2024

Marine sponges are well-known for hosting rich microbial communities. Sponges are the most prolific source of marine bioactive compounds, which are frequently synthesized by their associated microbiota. Calyx nicaeensis is an endemic Mediterranean sponge with scarce information regarding its (bioactive) secondary metabolites. East Mediterranean specimens of mesophotic C. nicaeensis have never been studied. Moreover, no research has inspected its associated bacteria. Thus, we studied the sponge’s bacterial diversity and examined bacterial interspecific interactions in search of a promising antibacterial candidate. Such novel antimicrobial agents are needed since extensive antibiotic use leads to bacterial drug resistance. Bacteria cultivation yielded 90 operational taxonomic units (OTUs). A competition assay enabled the testing of interspecific interactions between the cultured OTUs. The highest-ranked antagonistic bacterium, identified as Paenisporosarcina indica (previously never found in marine or cold habitats), was mass cultured, extracted, and separated using size exclusion and reversed-phase chromatographic methods, guided by antibacterial activity. A pure compound was isolated and identified as 3-oxy-anteiso-C15-fatty acid-lichenysin. Five additional active compounds await final cleaning; however, they are lichenysins and surfactins. These are the first antibacterial compounds identified from either the C. nicaeensis sponge or P. indica bacterium. It also revealed that the genus Bacillus is not an exclusive producer of lichenysin and surfactin.
Effects of Aging Processes on the Dynamic Impact Mechanical Behavior of Mg-Gd System Alloys
Authors: Ren Yibing , Wang Youqiang , Wang Xuezhao , Xu Ying
Published: September 2024

Exploring the effect of the magnesium alloy aging process on dynamic impact performance could plays an important role in the application of magnesium alloy in automotive lightweighting. In this work, the effects of single-stage, two-stage, and reverse two-stage aging processes on the dynamic mechanical properties of Mg-8.5 Gd-3 Y-0.5 Zr alloy were studied by means of SEM analysis, hardness testing, a quasi-static compression experiment, and SHPB. The results show that the compressive strength of the materials after single-stage, two-stage, and reverse two-stage aging treatments is improved to different degrees compared with that of the alloys in the extruded state. Due to the generation of dynamic precipitation with semi-annular distribution during SHPB, the compressive strength of the reverse two-stage aging alloys reached an excellent 761 MPa, while the two-stage aging alloys had more dynamic precipitation phases at the strain rate of 3500 s−1, resulting in a compressive strength of 730 MPa, which is superior to that of the aluminum alloys used in a wide range of automotive applications. The results of this study can provide a reference for the application of Mg-Gd magnesium alloys under dynamic loading.
The Triaxiality Effect on Damage Evolution in Al-2024 Tensile Samples
Authors: González Álvaro , Celentano Diego , Cruchaga Marcela , Ponthot Jean-Philippe
Published: September 2024

The effect of triaxiality on the evolution of damage in Al-2024 aluminum cylindrical specimens is studied in this work. Uncoupled and coupled damage models, all of them explicitly dependent on triaxiality, are assessed and compared. These models are characterized by tensile tests on cylindrical specimens without notches, to obtain the material parameters for each model. The capability of each model to predict fracture when different positive triaxial conditions evolve is then evaluated through tensile tests on notched cylindrical specimens. In particular, the damage index, evaluated at the fracture strain level, is compared with the experimental results validating the models. Moreover, the triaxiality evolution in the different specimens is studied in order to assess its effect on damage, demonstrating that the fracture strain decreases at greater triaxiality values. Observations through scanning electron microscopy confirm this pattern; i.e., an increase in triaxiality reveals a shift in the fracture mechanism from a more ductile condition in the original specimens to a more brittle one as the notch radius decreases. In addition, bilinear damage evolution is proposed to describe the physical behavior of the material when the Lemaitre coupled model is considered. In such a case, special attention must be devoted to the material characterization since coupling between hardening material parameters and damage affects the results.
Association of Firmicutes/Bacteroidetes Ratio with Body Mass Index in Korean Type 2 Diabetes Mellitus Patients
Authors: Ahmed Kainat , Choi Ha-Neul , Cho Sung-Rae , Yim Jung-Eun
Published: September 2024

Background: The gut microbiome, which is the collection of microorganisms living in the gastrointestinal tract, has been shown to play a significant role in the development of metabolic disorders such as obesity and type 2 diabetes mellitus (T2DM). Studies have found that the ratio of Firmicutes to Bacteroidetes (F/B) is higher in obese individuals compared to lean individuals and tends to decrease with weight loss. However, the relationship between the F/B ratio and T2DM in Korean individuals, with or without obesity, is not fully understood. Objective: The objective of this study is to compare the F/B ratios and metabolic profiles of lean and obese Korean individuals with T2DM. Methods: In this study, 36 individuals with type 2 diabetes mellitus (T2DM) were recruited and classified into four groups (I, II, III, and IV) based on their body mass index (BMI). Group I had a BMI of less than 23.0, group II had a BMI between 23.0 and 24.9, group III had a BMI between 25.0 and 29.9, and group IV had a BMI of 30 kg/m2 or greater. Fecal samples were collected from all participants and sent to Chunlab Inc. (located in Seoul, Republic of Korea) for analysis. The changes in the major microbial phyla within the samples were investigated using quantitative real-time PCR. The collected data were then statistically analyzed using the SPSS program. Results: The levels of triglycerides and alanine transaminase in group I were significantly lower than in the other three groups. The amount of Actinobacteria in group IV was the highest among all four groups. The ratio of Firmicutes to Bacteroidetes increased as BMI increased, and this ratio was positively correlated with AST activity. Conclusions: Our study showed that there is a correlation between the degree of obesity in individuals with diabetes and their gut microbiome. Additionally, the ratio of Firmicutes to Bacteroidetes (F/B ratio) may play a role in the metabolic effects of fatty liver disease, as it may contribute to obesity.
Salicylic Acid and Melatonin Synergy Enhances Boron Toxicity Tolerance via AsA–GSH Cycle and Glyoxalase System Regulation in Fragrant Rice
Authors: Imran Muhammad , Widemann Emilie , Shafiq Sarfraz , Bakhsh Ali , Chen Xiaoyuan , Tang Xiangru
Published: September 2024

Background: Boron is an essential micronutrient for plant growth and productivity, yet excessive boron leads to toxicity, posing significant challenges for agriculture. Fragrant rice is popular among consumers, but the impact of boron toxicity on qualitative traits of fragrant rice, especially aroma, remains largely unexplored. The individual potentials of melatonin and salicylic acid in reducing boron toxicity are less known, while their synergistic effects and mechanisms in fragrant rice remain unclear. Methods: Thus, this study investigates the combined application of melatonin and salicylic acid on fragrant rice affected by boron toxicity. One-week-old seedlings were subjected to boron (0 and 800 µM) and then treated with melatonin and salicylic acid (0 and 100 µM, for 3 weeks). Results: Boron toxicity significantly impaired photosynthetic pigments, plant growth, and chloroplast integrity while increasing oxidative stress markers such as hydrogen peroxide, malondialdehyde, methylglyoxal, and betaine aldehyde dehydrogenase. Likewise, boron toxicity abridged the precursors involved in the 2-acetyl-1-pyrroline (2-AP) biosynthesis pathway. However, individual as well as combined application of melatonin and salicylic acid ameliorated boron toxicity by strengthening the antioxidant defense mechanisms—including the enzymes involved during the ascorbate–glutathione (AsA–GSH) cycle and glyoxalase system—and substantially improved 2-AP precursors including proline, P5C, Δ1-pyrroline, and GABA levels, thereby restoring the 2-AP content and aroma. These findings deduce that melatonin and salicylic acid synergistically alleviate boron toxicity-induced disruptions on the 2-AP biosynthesis pathway by improving the 2-AP precursors and enzymatic activities, as well as modulating the physio-biochemical processes and antioxidant defense system of fragrant rice plants. Conclusions: The findings of this study have the potential to enhance rice productivity and stress tolerance, offering solutions to improve food security and sustainability in agricultural practices, particularly in regions affected by environmental stressors.
Trace Element Geochemical Characteristics of Plants and Their Role in Indicating Concealed Ore Bodies outside the Shizhuyuan W–Sn Polymetallic Deposit, Southern Hunan Province, China
Authors: Ouyang Le , Tan Kaixuan , Li Yongmei , Liu Zhenzhong , Zhou Hao , Li Chunguang , Xie Yanshi , Han Shili
Published: September 2024

To explore the potential of plant trace elements as indicators in the search for concealed deposits within the W–Sn polymetallic mining area of Shizhuyuan, Hunan Province, this study focused on the geochemical characterization of 21 trace elements, including Ag, As, B, Bi, Cd, Mo, Ni, Pb, and U, in the stem and leaf tissues of three predominant plants in the area. A total of 126 plant samples were collected, covering an area of about 10 km2, and analyzed using ICP-MS. The best indicator plants and sampling sites were selected using multiple indicators, including the biological absorption coefficient (XBAC), the enrichment coefficient (KNJ), and the contrast coefficient (KCD). The results showed that plant leaf tissues represent the most effective sampling components for phyto-geochemical surveys in this region. Dicranopteris dichotoma exhibited markedly pronounced geochemical anomalies of Ag (0.137 µg/g), As (86.12 µg/g), Mo (0.963 µg/g), Pb (15.4 µg/g), Sb (2.03 µg/g), and Se (0.547 µg/g) and demonstrated superior absorption capabilities for Ni, Sn, Sb, Pb, and Bi in the soil, with XBAC values of 12.0, 54.2, 23.3, 2.9, and 83.9, respectively. R-type cluster analysis and factor analysis identified four distinct mineralization element combinations: (1) Sn–As, (2) Ag–Cu–Mo, (3) Pb, and (4) Bi–Sb–Se. Consequently, D. dichotoma is a viable indicator plant for the phyto-geochemical detection of concealed Ag, Bi, Mo, Pb, Sb, Se, and Sn mineralization in mining areas. The results demonstrate that using phyto-geochemical methods for mineral prospecting is feasible and has significant application value in the Shizhuyuan mining area, which is characterized by dense vegetation and complex geological conditions.
High-Entropy and Component Stoichiometry Tuning Strategies Boost the Sodium-Ion Storage Performance of Cobalt-Free Prussian Blue Analogues Cathode Materials
Authors: Lin Yuan-Ting , Niu Bai-Tong , Wang Zi-Han , Li Yu-Xi , Xu Yun-Peng , Liu Shi-Wei , Chen Yan-Xin , Lin Xiu-Mei
Published: September 2024

Prussian blue analogs (PBAs) are appealing cathode materials for sodium-ion batteries because of their low material cost, facile synthesis methods, rigid open framework, and high theoretical capacity. However, the poor electrical conductivity, unavoidable presence of [Fe(CN)6] vacancies and crystalline water within the framework, and phase transition during charge–discharge result in inferior electrochemical performance, particularly in terms of rate capability and cycling stability. Here, cobalt-free PBAs are synthesized using a facile and economic co-precipitation method at room temperature, and their sodium-ion storage performance is boosted due to the reduced crystalline water content and improved electrical conductivity via the high-entropy and component stoichiometry tuning strategies, leading to enhanced initial Coulombic efficiency (ICE), specific capacity, cycling stability, and rate capability. The optimized HE-HCF of Fe0.60Mn0.10-hexacyanoferrate (referred to as Fe0.60Mn0.10-HCF), with the chemical formula Na1.156Fe0.599Mn0.095Ni0.092Cu0.109Zn0.105 [Fe(CN)6]0.724·3.11H2O, displays the most appealing electrochemical performance of an ICE of 100%, a specific capacity of around 115 and 90 mAh·g−1 at 0.1 and 1.0 A·g−1, with 66.7% capacity retention observed after 1000 cycles and around 61.4% capacity retention with a 40-fold increase in specific current. We expect that our findings could provide reference strategies for the design of SIB cathode materials with superior electrochemical performance.
Effect of Surface Anions Adsorbed by Rutile TiO2 (001) on Photocatalytic Nitrogen Reduction Reaction: A Density Functional Theory Calculation
Authors: Jiang Xiaoyu , Gao Mengyuan , Li Hongda
Published: September 2024

The adsorption of common anions found in water can have a considerable impact on the surface state and optical characteristics of titanium dioxide (TiO2), which has an important impact on the photocatalytic nitrogen reduction reaction (NRR). This work utilizes density functional theory (DFT) computations to examine the electronic and optical characteristics of the TiO2 (001) surface under various anion adsorptions in order to clarify their influence on the photocatalytic NRR of TiO2. The modifications in the structure, optical, and electronic properties of TiO2 before and after anion adsorption are investigated. In addition, the routes of Gibbs free energy for the NRR are also evaluated. The results indicate that the adsorption of anions modifies the surface characteristics of TiO2 to a certain degree, hence impacting the separating and recombining charge carriers by affecting the energy gap of TiO2. More importantly, the adsorption of anions can increase the energy barriers for the NRR, thereby exerting a detrimental effect on its photocatalytic activity. These findings provide a valuable theoretical contribution to understanding the photocatalytic reaction process of TiO2 and its potential application of NRR in the actual complex water phase.
Evidence of Cooperative Effects for the Fe(phen)2(NCS)2 Spin Crossover Molecular Complex in Polyaniline Plus Iron Magnetite
Authors: Chin Wai Kiat , Tamang Binny , Zaz M. Zaid , Subedi Arjun , Viswan Gauthami , N’Diaye Alpha T. , Lai Rebecca Y. , Dowben Peter A.
Published: September 2024

The spin crossover complex Fe(phen)2(NCS)2 and its composite, Fe(phen)2(NCS)2, combined with the conducting polymer polyaniline (PANI) plus varying concentrations of iron magnetite (Fe3O4) nanoparticles were studied. A cooperative effect is evident from the hysteresis width in the plot of magnetic susceptibility multiplied by temperature versus temperature (χmT versus T) for Fe(phen)2(NCS)2 with PANI plus varying concentrations of Fe3O4 nanoparticles. The hysteresis width in the composites vary no more than 2 K with respect to the pristine Fe(phen)2(NCS)2 spin crossover crystallites despite the fact that there exists a high degree of miscibility of the Fe(phen)2(NCS)2 spin crossover complex with the PANI. The Fe3O4 nanoparticles in the Fe(phen)2(NCS)2 plus PANI composite tend to agglomerate at higher concentrations regardless of the spin state of Fe(phen)2(NCS)2. Of note is that the Fe3O4 nanoparticles are shown to be antiferromagnetically coupled with the Fe(phen)2(NCS)2 when Fe(phen)2(NCS)2 is in the high spin state.
A Descriptive Review of the Antioxidant Effects and Mechanisms of Action of Berberine and Silymarin
Authors: García-Muñoz Ana María , Victoria-Montesinos Desirée , Ballester Pura , Cerdá Begoña , Zafrilla Pilar
Published: September 2024

Oxidative stress is a key factor in the development of chronic diseases such as type 2 diabetes, cardiovascular diseases, and liver disorders. Antioxidant therapies that target oxidative damage show significant promise in preventing and treating these conditions. Berberine, an alkaloid derived from various plants in the Berberidaceae family, enhances cellular defenses against oxidative stress through several mechanisms. It activates the AMP-activated protein kinase (AMPK) pathway, which reduces mitochondrial reactive oxygen species (ROS) production and improves energy metabolism. Furthermore, it boosts the activity of key antioxidant enzymes like superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPx), thus protecting cells from oxidative damage. These actions make berberine effective in managing diseases like type 2 diabetes, cardiovascular conditions, and neurodegenerative disorders. Silymarin, a flavonolignan complex derived from Silybum marianum, is particularly effective for liver protection. It activates the nuclear factor erythroid 2-related factor 2 (Nrf2) pathway, enhancing antioxidant enzyme expression and stabilizing mitochondrial membranes. Additionally, silymarin reduces the formation of ROS by chelating metal ions, and it also diminishes inflammation. This makes it beneficial for conditions like non-alcoholic fatty liver disease (NAFLD) and alcohol-related liver disorders. This review aims to highlight the distinct mechanisms by which berberine and silymarin exert their antioxidant effects.
Electrical Response of Different Crystalline Microregions in Poly(vinylidene fluoride)
Authors: Su Mengyue , Zhou Jun , Chen Yuqing , Wang Yilong , Jin Gan , Wang Haiyang , Zhou Jiacheng , Pang Xiaoyue , Lv Zepeng , Wu Kai
Published: September 2024

The crystal structure has a great influence on the dielectric and piezoelectric performance of poly(vinylidene fluoride) (PVDF). In this work, we prepared PVDF films with two typical crystalline phases (α and β). In situ Kelvin probe force microscopy (KPFM) and Piezoelectric force microscopy (PFM) were employed to investigate the responses of different PVDF crystalline phases to charge mobility, polarization, and piezoelectric properties. We used a homemade Kelvin probe force microscope (KPFM) to inject charges into the two crystalline phases to investigate the differences in the response of different crystalline phases of PVDF to electrical excitation on a microscopic scale. It was found that the α-phase has a lower charge injection barrier and is more susceptible to charge injection and that the α-phase is accompanied by a faster charge dissipation rate, which makes it easier to accumulate charge at the interface between the α-phase and β-phase PVDF. Moreover, the PFM polarization manipulation showed no change in the amplitude and phase diagram of the α-phase under ±10 V bias. In contrast, the β-phase showed a clear polarization reversal phenomenon and a significant increase in piezoelectric amplitude, which is consistent with its polar intrinsic properties. This study provides valuable insights into the multiphase contributions and a reference for designing advanced PVDF dielectrics.
All-Natural Gelatin-Based Nanoemulsion Loaded with TLR 7/8 Agonist for Efficient Modulation of Macrophage Polarization for Immunotherapy
Authors: Goswami Ritabrita , Nabawy Ahmed , Jiang Mingdi , Cicek Yagiz Anil , Hassan Muhammad Aamir , Nagaraj Harini , Zhang Xianzhi , Rotello Vincent M
Published: September 2024

Macrophages are multifunctional immune cells essential for both innate and adaptive immune responses. Tumor-associated macrophages (TAMs) often adopt a tumor-promoting M2-like phenotype, aiding tumor progression and immune evasion. Reprogramming TAMs to a tumoricidal M1-like phenotype is an emerging target for cancer immunotherapy. Resiquimod, a TLR7/8 agonist, can repolarize macrophages from the M2- to M1-like phenotype but is limited by poor solubility. We developed a gelatin nanoemulsion for the loading and delivery of resiquimod, utilizing eugenol oil as the liquid phase and riboflavin-crosslinked gelatin as a scaffold. These nanoemulsions showed high stability, low toxicity, and effective macrophage repolarization, significantly enhancing pro-inflammatory markers and anticancer activity in co-culture models.
Activity of Hydrophilic, Biocompatible, Fluorescent, Organic Nanoparticles Functionalized with Purpurin-18 in Photodynamic Therapy for Colorectal Cancer
Authors: Chkair Rayan , Couvez Justine , Brégier Frédérique , Diab-Assaf Mona , Sol Vincent , Blanchard-Desce Mireille , Liagre Bertrand , Chemin Guillaume
Published: September 2024

Photodynamic therapy (PDT) is a clinically approved, non-invasive therapy currently used for several solid tumors, triggering cell death through the generation of reactive oxygen species (ROS). However, the hydrophobic nature of most of the photosensitizers used, such as chlorins, limits the overall effectiveness of PDT. To address this limitation, the use of nanocarriers seems to be a powerful approach. From this perspective, we have recently developed water-soluble and biocompatible, fluorescent, organic nanoparticles (FONPs) functionalized with purpurin-18 and its derivative, chlorin p6 (Cp6), as new PDT agents. In this study, we aimed to investigate the induced cell death mechanism mediated by these functionalized nanoparticles after PDT photoactivation. Our results show strong phototoxic effects of the FONPs[Cp6], mediated by intracellular ROS generation, and subcellular localization in HCT116 and HT-29 human colorectal cancer (CRC) cells. Additionally, we proved that, post-PDT, the FONPs[Cp6] induce apoptosis via the intrinsic mitochondrial pathway, as shown by the significant upregulation of the Bax/Bcl-2 ratio, the activation of caspases 9, 3, and 7, leading poly-ADP-ribose polymerase (PARP-1) cleavage, and DNA fragmentation. Our work demonstrates the photodynamic activity of these nanoparticles, making them promising candidates for the PDT treatment of CRC.
Associations between Changes in Body Weight Status and High Blood Pressure among Lithuanian Children and Adolescents during the COVID-19 Pandemic: A Retrospective Cohort Study
Authors: Stankute Ieva , Dulskiene Virginija , Kuciene Renata
Published: September 2024

(1) Background: High blood pressure (HBP), overweight, and obesity are common, growing public health problems worldwide. The aim of this study was to evaluate associations between changes in body weight status and HBP among Lithuanian children and adolescents during the COVID-19 pandemic. (2) Methods: In this study, we analysed data on blood pressure and anthropometric measurements of 2430 children and adolescents aged 8–18 years, who participated in both the baseline study conducted before the COVID-19 pandemic (from November 2019 to March 2020) and the follow-up study during the COVID-19 pandemic (from November 2021 to April 2022). Multivariate logistic regression analysis was used to estimate the associations between changes in weight status categories and HBP. (3) Results: At baseline, 17.1% of the subjects had overweight, 5.9% had obesity, 5.6% had abdominal obesity, and 23.7% had HBP, whereas at the follow-up, these percentages increased to 20.1%, 8.2%, 6.8%, and 27.4%, respectively. Compared to schoolchildren who maintained normal weight from baseline to the follow-up period, subjects who newly developed overweight/obesity and those who remained with persistent overweight/obesity had increased odds of HBP, with adjusted odds ratios (aORs) of 1.95 (p < 0.001) and 2.58 (p < 0.001), respectively. In subjects who transitioned from overweight/obesity to normal weight, the odds of HBP were slightly increased, with an aOR of 1.14 (p = 0.598), but the change was not statistically significant (p > 0.05). (4) Conclusions: This study observed an increase in the prevalence of overweight, obesity, and HBP among schoolchildren during the COVID-19 pandemic. The study also suggested that changes from normal body weight status at baseline to overweight/obesity during follow-up, especially persistent overweight/obesity, were associated with higher odds of HBP in Lithuanian children and adolescents during the COVID-19 pandemic.
Green Onion-Derived Exosome-like Nanoparticles Prevent Ferroptotic Cell Death Triggered by Glutamate: Implication for GPX4 Expression
Authors: Yoon Han Jun , Won Jun Pil , Lee Hyuk Gyoon , Seo Han Geuk
Published: September 2024

In recent years, alongside research on mammalian-derived exosomes, there has been increasing interest in the physiological activities of plant-derived exosome-like nanoparticles (PDEN). The biocompatibility, minimal side effects, and diverse bioactive ingredients contained in PDEN make them valuable as potential therapeutic agents for an extensive range of diseases. In this study, we cost-effectively isolated exosome-like nanoparticles from green onion (Allium fistulosum) using polyethylene glycol and examined their biological activity in HT-22 cells exposed to glutamate. The isolated green onion-derived exosome-like nanoparticle (GDEN) had an average diameter of 167.4 nm and a zeta potential of −16.06 mV. GDEN effectively inhibited glutamate-induced Ca2+ influx and lipid peroxidation, thereby preventing ferroptotic cell death in HT-22 mouse hippocampal cells. Additionally, GDEN reduced the intracellular iron accumulation by modulating the expression of proteins associated with iron metabolism, including transferrin receptor 1, ferroportin 1, divalent metal transporter 1, and ferritin. Notably, GDEN upregulated the expression of glutathione peroxidase 4, a potent antioxidant protein involved in ferroptosis, along with an increase in glutathione synthesis. These findings indicate that GDENs have the potential to serve as bioactives from natural sources against glutamate-induced neuronal cell death, like ferroptosis. This study advances the investigation into the potential medical applications of GDEN and may provide a new approach for the utilization of these bioactive components against neuronal disorders.
Cosmological Models within f(T, B) Gravity in a Holographic Framework
Authors: Chokyi Khandro K. , Chattopadhyay Surajit
Published: September 2024

We investigate the cosmological evolution of the universe for a spatially flat FLRW background space within the context of f(T,B) gravity, which is a recently formulated teleparallel theory that connects both f(T) and f(R) gravity under suitable limits. The analysis focuses on four different f(T,B) cosmological models corresponding to various choices of scale factor, namely, emergent, logamediate, and intermediate. In addition to this, we assume a power law-like function of f(T,B) gravity. The reconstruction of f(T,B) gravity considers the Holographic Ricci Dark Energy (HRDE) as the background fluid. We analyze the equation of state parameters and the squared speed of sound for the reconstructed models. Finally, we conduct a thermodynamical analysis for each reconstructed model. The generalized second law of thermodynamics (GSLT) is valid for the four different f(T,B) cosmological models.