bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of Dental Prosthetic Treatment in Patients with Cancer Aged 65 Years and Older after Expanded Health Insurance Coverage: A Retrospective Clinical Study
Authors: Kim Hyo-Jung , Sung Iel-Yong
Published: September 2024

Background and Objectives: With increases in cancer incidence and the number of cancer survivors, the demand for cancer management is growing. However, studies on dental prosthetic treatment for patients with cancer are rare. We aim to investigate the dental prosthetic treatment in patients with cancer aged ≥65 years after expanded health insurance coverage. Materials and Methods: This retrospective study included patients who were treated with implants and removable dentures at Ulsan University Hospital in South Korea between June 2015 and June 2023. Data on age, sex, cancer location, comorbid systemic diseases, number of remaining teeth, dental prosthetic treatment history, type of dental prosthetic treatment, and insurance coverage status were extracted from patient medical records and panoramic radiographs. The influence of multiple variables on dental prosthetic treatment was analyzed using the Chi-square and Fisher’s exact tests. Results: The study included 61 patients with cancer (32 men, 29 women; average age: 70.9 years). Among them, 56 (91.8%) had insurance coverage benefits, and 34 (55.7%) received treatments such as implants, removable partial dentures, or complete dentures for the first time. Treatment types included 37 (60.7%) cases of implant prostheses and 24 (39.3%) conventional removable dentures. No statistical differences were observed in the type of dental prosthetic treatment according to sex, age, cancer location, number of systemic diseases, and dental prosthetic treatment history (p > 0.05). Patients with <10 remaining teeth received treatment with conventional removable dentures, which was statistically significant (p < 0.001). Conclusions: Of the 61 patients, 56 (91.8%) received insurance benefits, and 34 (55.7%) underwent dental prosthetic treatment for the first time. Within the limitations of this retrospective study, the expanded health insurance coverage alleviated the unmet demand for dental prosthetic treatment. As cancer prevalence continues to increase, expanding customized health insurance coverage is crucial to meet this demand.
PREVENT Equation: The Black Sheep among Cardiovascular Risk Scores? A Comparative Agreement Analysis of Nine Prediction Models in High-Risk Lithuanian Women
Authors: Navickas Petras , Lukavičiūtė Laura , Glaveckaitė Sigita , Baranauskas Arvydas , Šatrauskienė Agnė , Badarienė Jolita , Laucevičius Aleksandras
Published: September 2024

Background and Objectives: In the context of female cardiovascular risk categorization, we aimed to assess the inter-model agreement between nine risk prediction models (RPM): the novel Predicting Risk of cardiovascular disease EVENTs (PREVENT) equation, assessing cardiovascular risk using SIGN, the Australian CVD risk score, the Framingham Risk Score for Hard Coronary Heart Disease (FRS-hCHD), the Multi-Ethnic Study of Atherosclerosis risk score, the Pooled Cohort Equation (PCE), the QRISK3 cardiovascular risk calculator, the Reynolds Risk Score, and Systematic Coronary Risk Evaluation-2 (SCORE2). Materials and Methods: A cross-sectional study was conducted on 6527 40–65-year-old women with diagnosed metabolic syndrome from a single tertiary university hospital in Lithuania. Cardiovascular risk was calculated using the nine RPMs, and the results were categorized into high-, intermediate-, and low-risk groups. Inter-model agreement was quantified using Cohen’s Kappa coefficients. Results: The study uncovered a significant diversity in risk categorization, with agreement on risk category by all models in only 1.98% of cases. The SCORE2 model primarily classified subjects as high-risk (68.15%), whereas the FRS-hCHD designated the majority as low-risk (94.42%). The range of Cohen’s Kappa coefficients (−0.09–0.64) reflects the spectrum of agreement between models. Notably, the PREVENT model demonstrated significant agreement with QRISK3 (κ = 0.55) and PCE (κ = 0.52) but was completely at odds with the SCORE2 (κ = −0.09). Conclusions: Cardiovascular RPM selection plays a pivotal role in influencing clinical decisions and managing patient care. The PREVENT model revealed balanced results, steering clear of the extremes seen in both SCORE2 and FRS-hCHD. The highest concordance was observed between the PREVENT model and both PCE and QRISK3 RPMs. Conversely, the SCORE2 model demonstrated consistently low or negative agreement with other models, highlighting its unique approach to risk categorization. These findings accentuate the need for additional research to assess the predictive accuracy of these models specifically among the Lithuanian female population.
Effect of Sintering Temperature on the Microstructure and Mechanical and Tribological Properties of Copper Matrix Composite for Brake Pads
Authors: Zhou Yajun , Zhang Yongzhen , Zhang Xin , Liu Jianxiu , Wang Mingxin
Published: September 2024

Copper-based powder metallurgy materials are frequently utilized in fabricating brake pads for high-speed trains. The preparation process involves mixing, ball milling, pressing, and sintering. Among these steps, hot-pressed sintering stands out as a rapid and efficient method that significantly influences the properties and performance of the products. In this study, four samples (S700/S750/S800/S850) were prepared using hot-pressed sintering at various temperatures, as follows: 700 °C, 750 °C, 800 °C, and 850 °C. The mechanical and physical properties of the four samples were tested, and the microstructure and compositions were investigated using scanning electron microscopy, energy dispersive spectroscopy, and X-ray diffraction. The findings highlighted the close relationship between sintering temperature and the mechanical and physical properties of the samples, as it impacts the porosity and interfacial bonding of the particles. Notably, Sample S800 demonstrated superior mechanical and thermal conductivity. Furthermore, the coefficient of friction (COF), friction heat, and wear rate of the four samples were also tested under different braking speeds ranging from 150 km/h to 350 km/h. The results indicated that the COFs of the four samples remained relatively stable below 300 km/h but decreased notably above 300 km/h due to heat fading. Sample S800 displayed consistent and high COF under varied braking speeds and exhibited the lowest wear rate. The observed wear mechanisms included abrasive wear and oxidation wear. Additionally, the friction test results underscored the close correspondence of the COF curve of S800 with the standard of the Ministry of Railways of the People’s Republic of China.
Efficient Phase Segmentation of Light-Optical Microscopy Images of Highly Complex Microstructures Using a Correlative Approach in Combination with Deep Learning Techniques
Authors: Bachmann Björn-Ivo , Müller Martin , Stiefel Marie , Britz Dominik , Staudt Thorsten , Mücklich Frank
Published: September 2024

Reliable microstructure characterization is essential for establishing process–microstructure–property links and effective quality control. Traditional manual microstructure analysis often struggles with objectivity, reproducibility, and scalability, particularly in complex materials. Machine learning methods offer a promising alternative but are hindered by the challenge of assigning an accurate and consistent ground truth, especially for complex microstructures. This paper introduces a methodology that uses correlative microscopy—combining light optical microscopy, scanning electron microscopy, and electron backscatter diffraction (EBSD)—to create objective, reproducible pixel-by-pixel annotations for ML training. In a semi-automated manner, EBSD-based annotations are employed to generate an objective ground truth mask for training a semantic segmentation model for quantifying simple light optical micrographs. The training masks are directly derived from raw EBSD data using modern deep learning methods. By using EBSD-based annotations, which incorporate crystallographic and misorientation data, the correctness and objectivity of the training mask creation can be assured. The final approach is capable of reproducibly and objectively differentiating bainite and martensite in optical micrographs of complex quenched steels. Through the reduction in the microstructural evaluation to light optical micrographs as the simplest and most widely used method, this way of quantifying microstructures is characterized by high efficiency as well as good scalability.
Study of Intergranular Corrosion Behaviors of Mn-Increased 5083 Al Alloy with Controlled Precipitation States of Al6Mn Formed during Homogenization Annealing
Authors: Zhang Peng , Wang Yue , Zhao Pizhi , Jiang Zhengyi , Tian Yinbao , Yang Yang , Han Jian
Published: September 2024

In this study, as a vital part of the production of Mn-increased 5083 Al alloy, i.e., homogenization annealing before hot rolling, the target states of key Al6Mn precipitation, including the dispersed, initial coarsening and intensive coarsening states, were designed, and the corresponding precipitates formed via the control of the temperature and holding time in the annealing process. By means of metallographic corrosion and nitric acid mass loss tests (NAMLT) for assessing the intergranular corrosion (IGC) resistance, temperatures ranging from 175 °C to 225 °C were determined to induce a transition from sensitization to stabilization for this innovative 5083. At a temperature of 175 °C for a duration of up to 24 h (2 h, 4 h, 8 h, 16 h, 24 h), the results show that when the soak time is 24 h, the sample with initially coarsened Al6Mn phases has a lower degree of sensitization (DOS) compared to the samples with Al6Mn phases in both the dispersed and intensive coarsening states, and its NAMLT is reduced by 11% and 15%, respectively. Subsequently, transmission electron microscopy (TEM) analysis has investigated that for the sample with the best IGC resistance, i.e., that with initially coarsened Al6Mn phases, plate-like Al6Mn particles (200~500 nm) can act as heterogenous nucleation sites for β phases, driving their preferential precipitation on Al6Mn particles and resisting their precipitation along grain boundaries, ultimately improving the IGC resistance of 5083 Al alloy after homogenization annealing.
Identification of Plasma Metabolomic Biomarkers of Juvenile Idiopathic Arthritis
Authors: Kumar Amar , Tatarian Joshua , Shakhnovich Valentina , Chevalier Rachel L. , Sudman Marc , Lovell Daniel J. , Thompson Susan D. , Becker Mara L. , Funk Ryan S.
Published: September 2024

Identification of disease and therapeutic biomarkers remains a significant challenge in the early diagnosis and effective treatment of juvenile idiopathic arthritis (JIA). In this study, plasma metabolomic profiling was conducted to identify disease-related metabolic biomarkers associated with JIA. Plasma samples from treatment-naïve JIA patients and non-JIA reference patients underwent global metabolomic profiling across discovery (60 JIA, 60 non-JIA) and replication (49 JIA, 38 non-JIA) cohorts. Univariate analysis identified significant metabolites (q-value ≤ 0.05), followed by enrichment analysis using ChemRICH and metabolic network mapping with MetaMapp and Cytoscape. Receiver operating characteristic (ROC) analysis determined the top discriminating biomarkers based on area under the curve (AUC) values. A total of over 800 metabolites were measured, consisting of 714 known and 155 unknown compounds. In the discovery cohort, 587 metabolites were significantly altered in JIA patients compared with the reference population (q < 0.05). In the replication cohort, 288 metabolites were significantly altered, with 78 overlapping metabolites demonstrating the same directional change in both cohorts. JIA was associated with a notable increase in plasma levels of sphingosine metabolites and fatty acid ethanolamides and decreased plasma levels of sarcosine, iminodiacetate, and the unknown metabolite X-12462. Chemical enrichment analysis identified cycloparaffins in the form of naproxen and its metabolites, unsaturated lysophospholipids, saturated phosphatidylcholines, sphingomyelins, ethanolamines, and saturated ceramides as the top discriminating biochemical clusters. ROC curve analysis identified 11 metabolites classified as highly discriminatory based on an AUC > 0.90, with the top discriminating metabolite being sphinganine-1-phosphate (AUC = 0.98). This study identifies specific metabolic changes in JIA, particularly within sphingosine metabolism, through both discovery and replication cohorts. Plasma metabolomic profiling shows promise in pinpointing JIA-specific biomarkers, differentiating them from those in healthy controls and Crohn’s disease, which may improve diagnosis and treatment.
A Diboronic Acid-Based Fluorescent Sensor Array for Rapid Identification of Lonicerae Japonicae Flos and Lonicerae Flos
Authors: Bian Ying , Xiang Chenqing , Xu Yi , Zhu Rongping , Qin Shuanglin , Zhang Zhijun
Published: September 2024

Lonicerae japonicae flos (LJF) and Lonicerae flos (LF) are traditional Chinese herbs that are commonly used and widely known for their medicinal properties and edibility. Although they may have a similar appearance and vary slightly in chemical composition, their effectiveness as medicine and their use in clinical settings vary significantly, making them unsuitable for substitution. In this study, a novel 2 × 3 six-channel fluorescent sensor array is proposed that uses machine learning algorithms in combination with the indicator displacement assay (IDA) method to quickly identify LJF and LF. This array comprises two coumarin-based fluorescent indicators (ES and MS) and three diboronic acid-substituted 4,4′-bipyridinium cation quenchers (Q1–Q3), forming six dynamic complexes (C1–C6). When these complexes react with the ortho-dihydroxy groups of phenolic acid compounds in LJF and LF, they release different fluorescent indicators, which in turn causes distinct fluorescence recovery. By optimizing eight machine learning algorithms, the model achieved 100% and 98.21% accuracy rates in the testing set and the cross-validation predictions, respectively, in distinguishing between LJF and LF using Linear Discriminant Analysis (LDA). The integration of machine learning with this fluorescent sensor array shows great potential in analyzing and detecting foods and pharmaceuticals that contain polyphenols.
Polymorph Screening of Core-Chlorinated Naphthalene Diimides with Different Fluoroalkyl Side-Chain Lengths
Authors: de Oliveira Martins Inês , Marchini Marianna , Maini Lucia , Modena Enrico
Published: September 2024

In this work, naphthalenediimide (NDI) derivatives are widely studied for their semiconducting properties and the influence of the side-chain length on the crystal packing is reported, along with the thermal properties of three core-chlorinated NDIs with different fluoroalkyl side-chain lengths (CF3-NDI, C3F7-NDI and C4F9-NDI). The introduction of fluorinated substituents at the imide nitrogen and addition of strong electron-withdrawing groups at the NDI core are used to improve the NDI derivatives air stability. The new compound, CF3-NDI, was deeply analyzed and compared to the well-known C3F7-NDI and C4F9-NDI, leading to the discovery and solution of two different crystal phases, form α and solvate form, and a solid solution of CF3-NDI and CF3-NDI-OH, formed by the decomposition in DMSO.
Modeling UV/Vis Absorption Spectra of Food Colorants in Solution: Anthocyanins and Curcumin as Case Studies
Authors: Gómez Sara , Lafiosca Piero , Giovannini Tommaso
Published: September 2024

We present a comprehensive computational study of UV/Vis absorption spectra of significant food colorants, specifically anthocyanins and curcumin tautomers, dissolved in polar protic solvents, namely water and ethanol. The absorption spectra are simulated using two fully polarizable quantum mechanical (QM)/molecular mechanics (MM) models based on the fluctuating charge (FQ) and fluctuating charge and dipoles (FQFμ) force fields. To accurately capture the dynamical aspects of the solvation phenomenon, atomistic approaches are combined with configurational sampling obtained through classical molecular dynamics (MD) simulations. The calculated QM/FQ and QM/FQFμ spectra are then compared with experiments. Our findings demonstrate that a precise reproduction of the UV/Vis spectra of the studied pigments can be achieved by adequately accounting for configurational sampling, polarization effects, and hydrogen bonding interactions.
Efficient Flotation Separation of Ilmenite and Olivine in a Weak Alkaline Pulp Using a Ternary Combination Collector Centered around Al3+
Authors: Li Jinhui , He Hao , Shao Yanhai , Liu Chenjie , Li Rui , Chen Hongqin , Meng Xiao
Published: September 2024

Due to the similar physical and chemical properties of ilmenite and olivine, separating them is challenging. The flotation process, with the use of collectors, is an effective method. In this study, a ternary collector consisting of aluminum ion (III), benzohydroxamic acid (BHA), and sodium oleate (NaOL) was prepared for the flotation separation of ilmenite and olivine. Through micro-flotation experiments, molecular dynamics simulation (MD), density functional theory (DFT), scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), and time-of-flight secondary ion mass spectrometry (TOF-SIMS) analysis, the synergistic effect between the components of the ternary collector and the adsorption configuration on the surface of ilmenite was investigated. The results revealed that at pH = 8, Al (III), BHA, and NaOL could coordinate and adsorb effectively on the surface of ilmenite, enhancing its floatability for separation from olivine. The adsorption configuration differed from previous reports, showing a co-adsorption of multiple forms on the surface of ilmenite.
Deep Eutectic Solvent-Based Aqueous Two-Phase Systems and Their Application in Partitioning of Phenol Compounds
Authors: Souza Isabela N. , Rodrigues Lucas C. V. , Soares Cleide M. F. , Buarque Filipe S. , Souza Ranyere L. , Lima Álvaro S.
Published: September 2024

This work studies the partition of phenolic compounds, namely caffeic acid, syringic acid, vanillic acid, ferulic acid, and vanillin, in aqueous two-phase systems (ATPSs) formed by acetonitrile and deep eutectic solvents (DESs) based on choline chloride ([Ch]Cl) and carbohydrates (sucrose, d-glucose, d-mannose, arabinose, and d-xylose). The binodal curves built at 25 °C and 0.1 MPa using DES were compared with ATPS composed of [Ch]Cl and the same carbohydrates. The ability to form ATPS depends on the number and kind of hydroxyl groups in DES’s hydrogen-bond donor compound (carbohydrates). ATPS based on DES showed biphasic regions larger than the systems based on [Ch]Cl and carbohydrates alone due to the larger hydrophilicity of DES. The ATPS were used to study the partition of the phenolic compounds. For all the systems, the biomolecules preferentially partitioned to the acetonitrile-rich phase (K > 1), and the best recovery in the top phase ranged between 53.36% (caffeic acid) and 90.09% (vanillin). According to the remarkable results, DES-based ATPS can selectively separate ferulic acid and vanillin for the top phase and syringic, caffeic, and vanillic acids for the bottom phase, achieving a selectivity higher than two.
Thermo-Responsive Hydrogel Based on Lung Decellularized Extracellular Matrix for 3D Culture Model to Enhance Cancer Stem Cell Characteristics
Authors: Chen Lei , Li Fanglu , Li Ruobing , Zheng Ke , Zhang Xinyi , Ma Huijing , Li Kaiming , Nie Lei
Published: September 2024

Cancer stem cells (CSCs) are most likely the main cause of lung cancer formation, metastasis, drug resistance, and genetic heterogeneity. Three-dimensional (3D) ex vivo cell culture models can facilitate stemness improvement and CSC enrichment. Considering the critical role of extracellular matrix (ECM) on CSC properties, the present study developed a thermo-responsive hydrogel using the porcine decellularized lung for 3D cell culture, and the cell-laden hydrogel culturing model was used to explore the CSC characteristics and potential utilization in CSC-specific drug evaluation. Results showed that the lung dECM hydrogel (LEH) was composed of the main ECM components and displayed excellent cellular compatibility. In addition, lung cancer cells 3D cultured in LEH displayed the overexpression of metastasis-related genes and enhanced migration properties, as compared with those in two-dimensional (2D) conditions. Notably, the CSC features, including the expression level of stemness-associated genes, colony formation capability, drug resistance, and the proportion of cancer stem-like cells (CD133+), were also enhanced in 3D cells. Furthermore, the attenuation effect of epigallocatechin gallate (EGCG) on CSC properties in the 3D model was observed, confirming the potential practicability of the 3D culture on CSC-targeted drug screening. Overall, our results suggest that the fabricated LEH is an effective and facile platform for 3D cell culture and CSC-specific drug evaluation.
Evaluation of Adsorption Ability of Lewatit® VP OC 1065 and Diaion™ CR20 Ion Exchangers for Heavy Metals with Particular Consideration of Palladium(II) and Copper(II)
Authors: Wołowicz Anna , Hubicki Zbigniew
Published: September 2024

The adsorption capacities of ion exchangers with the primary amine (Lewatit® VP OC 1065) and polyamine (Diaion™ CR20) functional groups relative to Pd(II) and Cu(II) ions were tested in a batch system, taking into account the influence of the acid concentration (HCl: 0.1–6 mol/L; HCl-HNO3: 0.9–0.1 mol/L HCl—0.1–0.9 mol/L HNO3), phase contact time (1–240 min), initial concentration (10–1000 mg/L), agitation speed (120–180 rpm), bead size (0.385–1.2 mm), and temperature (293–333 K), as well as in a column system where the variable operating parameters were HCl and HNO3 concentrations. There were used the pseudo-first order, pseudo-second order, and intraparticle diffusion models to describe the kinetic studies and the Langmuir and Freundlich isotherm models to describe the equilibrium data to obtain better knowledge about the adsorption mechanism. The physicochemical properties of the ion exchangers were characterized by the nitrogen adsorption/desorption analyses, CHNS analysis, Fourier transform infrared spectroscopy, the sieve analysis, and points of zero charge measurements. As it was found, Lewatit® VP OC 1065 exhibited a better ability to remove Pd(II) than Diaion™ CR20, and the adsorption ability series for heavy metals was as follows: Pd(II) >> Zn(II) ≈ Ni(II) >> Cu(II). The optimal experimental conditions for Pd(II) sorption were 0.1 mol/L HCl, agitation speed 180 rpm, temperature 293 K, and bead size fraction 0.43 mm ≤ f3 < 0.6 mm for Diaion™ CR20 and 0.315–1.25 mm for Lewatit® VP OC 1065. The maximum adsorption capacities were 289.68 mg/g for Lewatit® VP OC 1065 and 208.20 mg/g for Diaion™ CR20. The greatest adsorption ability of Lewatit® VP OC 1065 for Pd(II) was also demonstrated in the column studies. The working ion exchange in the 0.1 mol/L HCl system was 0.1050 g/mL, much higher compared to Diaion™ CR20 (0.0545 g/mL). The best desorption yields of %D1 = 23.77% for Diaion™ CR20 and 33.57% for Lewatit® VP OC 1065 were obtained using the 2 mol/L NH3·H2O solution.
Reaction Rate Rules of Intramolecular H-Migration Reaction Class for RIORIIOO·Radicals in Ether Combustion
Authors: Sun Xiaohui , Li Zerong
Published: September 2024

The intramolecular H-migration reaction of RIORIIOO· radicals constitute a key class of reactions in the low-temperature combustion mechanism of ethers. Despite this, there is a dearth of direct computations regarding the potential energy surface and rate constants specific to ethers, especially when considering large molecular systems and intricate branched-chain structures. Furthermore, combustion kinetic models for large molecular ethers generally utilize rate constants derived from those of structurally similar alcohols or alkane fuels. Consequently, chemical kinetic studies involve the calculation of energy barriers and rate rules for the intramolecular H-migration reaction class of RIORIIOO· radicals, which are systematically conducted using the isodesmic reaction method (IRM). The geometries of the species participating in these reactions are optimized, and frequency calculations are executed using the M06–X method in tandem with the 6–31+G(d,p) basis set by the Gaussian 16 program. Moreover, the M06–2X/6–31+G(d,p) method acts as the low-level ab initio method, while the CBS–QB3 method is utilized as the high-level ab initio method for calculating single-point energies. Rate constants at the high-pressure-limit are computed based on the reaction class transition state theory (RC-TST) by ChemRate program, incorporating asymmetric Eckart tunneling corrections for intramolecular H-migration reactions across a temperature range of 500 to 2000 K. It was found that the isodesmic reaction method gives accurate energy barriers and rate constants, and the rate constants of the H-migration reaction for RIORIIOO· radicals diverge from those of comparable reactions in alkanes and alcohol fuels. There are significant disparities in energy barriers and rate constants across the entire reaction classes of the H-migration reaction for RIORIIOO· radicals, necessitating the subdivision of the H-migration reaction into subclasses. Rate rules are established by averaging the rate constants of representative reactions for each subclass, which is pivotal for the advancement of accurate low-temperature combustion reaction mechanisms for ethers.
Bioactive Properties of Enzymatic Gelatin Hydrolysates Based on In Silico, In Vitro, and In Vivo Studies
Authors: Panjaitan Fenny Crista A. , Shie Sin-Ting , Park Sung Hoon , Sevi Tesalonika , Ko Wen-Ling , Aluko Rotimi E. , Chang Yu-Wei
Published: September 2024

This current study aims to analyze the potential bioactivities possessed by the enzymatic hydrolysates of commercial bovine, porcine, and tilapia gelatins using bioinformatics in combination with in vitro and in vivo studies. The hydrolysate with superior inhibition of angiotensin converting enzyme (ACE) activity was used to treat the D-galactose (DG)-induced amnesic mice. In silico digestion of the gelatins led to the identification of peptide sequences with potential antioxidant, ACE-inhibitory, and anti-amnestic properties. The results of in vitro digestion revealed that the <1 kDa peptide fraction of porcine gelatin hydrolysate obtained after 1 h digestion with papain (PP) (PP1, <1 kDa) potently inhibited ACE, acetylcholinesterase, and prolyl endopeptidase activities at 87.42%, 21.24%, and 48.07%, respectively. Administering the PP1 to DG-induced amnesic mice ameliorated the spatial cognitive impairment and Morris water maze learning abilities. The dentate area morphology in the PP1-treated mice was relatively similar to the control group. In addition, PP1 enhanced the antioxidant capacity in the DG-induced amnesic mice. This study suggests that PP1 could serve as a potential treatment tool against oxidative stress, hypertension, and neurodegenerative diseases.
Sources and Extraction of Biopolymers and Manufacturing of Bio-Based Nanocomposites for Different Applications
Authors: Azadi Elham , Dinari Mohammad , Derakhshani Maryam , Reid Katelyn R. , Karimi Benson
Published: September 2024

In the recent era, bio-nanocomposites represent an emerging group of nanostructured hybrid materials and have been included in a new field at the frontier of materials science, life sciences, and nanotechnology. These biohybrid materials reveal developed structural and functional features of great attention for diverse uses. These materials take advantage of the synergistic assembling of biopolymers with nanometer-sized reinforcements. Conversely, polysaccharides have received great attention due to their several biological properties like antimicrobial and antioxidant performance. They mainly originated in different parts of plants, animals, seaweed, and microorganisms (bacteria, fungi, and yeasts). Polysaccharide-based nanocomposites have great features, like developed physical, structural, and functional features; affordability; biodegradability; and biocompatibility. These bio-based nanocomposites have been applied in biomedical, water treatment, food industries, etc. This paper will focus on the very recent trends in bio-nanocomposite based on polysaccharides for diverse applications. Sources and extraction methods of polysaccharides and preparation methods of their nanocomposites will be discussed.
Single-Layer Metasurface-Based Reflectarray Antenna with H-Shaped Slotted Patch for X-Band Communication
Authors: Ali Jawad , Ahmad Ashfaq , Choi Dong-you
Published: September 2024

In this study, a metasurface-based reflectarray is designed for X-band applications. The unit cells are equipped with an H-shaped slotted patch for additional resonance and phase range. Linear phase variation by altering the length of the patch is realized with a range exceeding 480∘. The reflectarray is designed and fabricated on a thin and high-quality Rogers 5880 substrate. The Finite Element Boundary Integral (FEBI) method is used to simulate a 23×23 element reflectarray and then fabricated to achieve the measured results using an anechoic chamber. The peak gain of the proposed reflectarray is 25.5 dBi recorded with an aperture efficiency of 63.7% at a center frequency of 10 GHz. The cross-polarization and side-lobe levels in the entire band are less than −33 dB and −21 dB, respectively. Moreover, the proposed reflectarray antenna achieves a 20% 1-dB gain bandwidth.
The Light Wavelength, Intensity, and Biasing Voltage Dependency of the Dark and Photocurrent Densities of a Solution-Processed P3HT:PC61BM Photodetector for Sensing Applications
Authors: Jhuma Farjana Akter , Harada Kentaro , Misran Muhamad Affiq Bin , Mo Hin-Wai , Fujimoto Hiroshi , Hattori Reiji
Published: September 2024

The promising possibility of an organic photodetector (OPD) is emerging in the field of sensing applications for its tunable absorption range, flexibility, and large-scale fabrication abilities. In this work, we fabricated a bulk heterojunction OPD with a device structure of glass/ITO/PEDOT:PSS/P3HT:PC61BM/Al using the spin-coating process and characterized the dark and photocurrent densities at different applied bias conditions for red, green, and blue incident LEDs. The OPD photocurrent density exhibited a magnitude up to 2.5–3 orders higher compared to the dark current density at a −1 V bias while it increased by up to 3–4 orders at zero bias conditions for red, green, and blue lights, showing an increasing trend when a higher voltage is applied in the negative direction. Different OPD inner periphery shapes, the OPD to LED distance, and OPD area were also considered to bring the variation in the OPD dark and photocurrent densities, which can affect the on/off ratio of the OPD–LED hybrid system and is a critical phenomenon for any sensing application.
Explainable Encoder–Prediction–Reconstruction Framework for the Prediction of Metasurface Absorption Spectra
Authors: Ouyang Yajie , Zeng Yunhui , Liu Xiaoxiang
Published: September 2024

The correlation between metasurface structures and their corresponding absorption spectra is inherently complex due to intricate physical interactions. Additionally, the reliance on Maxwell’s equations for simulating these relationships leads to extensive computational demands, significantly hindering rapid development in this area. Numerous researchers have employed artificial intelligence (AI) models to predict absorption spectra. However, these models often act as black boxes. Despite training high-performance models, it remains challenging to verify if they are fitting to rational patterns or merely guessing outcomes. To address these challenges, we introduce the Explainable Encoder–Prediction–Reconstruction (EEPR) framework, which separates the prediction process into feature extraction and spectra generation, facilitating a deeper understanding of the physical relationships between metasurface structures and spectra and unveiling the model’s operations at the feature level. Our model achieves a 66.23% reduction in average Mean Square Error (MSE), with an MSE of 2.843 × 10−4 compared to the average MSE of 8.421×10−4 for mainstream networks. Additionally, our model operates approximately 500,000 times faster than traditional simulations based on Maxwell’s equations, with a time of 3×10−3 seconds per sample, and demonstrates excellent generalization capabilities. By utilizing the EEPR framework, we achieve feature-level explainability and offer insights into the physical properties and their impact on metasurface structures, going beyond the pixel-level explanations provided by existing research. Additionally, we demonstrate the capability to adjust absorption by changing the metasurface at the feature level. These insights potentially empower designers to refine structures and enhance their trust in AI applications.
Tribological Properties of Nitrate Graphite Foils
Authors: Morozov Nikolai S. , Demchenko David V. , Bukovsky Pavel O. , Yakovenko Anastasiya A. , Shulyak Vladimir A. , Gracheva Alexandra V. , Chebotarev Sergei N. , Goryacheva Irina G. , Avdeev Viktor V.
Published: September 2024

This study investigates the tribological properties of graphite foils (GF) with densities of 1.0, 1.3, and 1.6 g/cm3, produced from purified natural graphite of different particle sizes (40–80 μm, 160–200 μm, >500 μm). Surface roughness was measured after cold rolling and friction testing at static (0.001 mm/s) and dynamic conditions (0.1 Hz and 1 Hz). Results showed that static friction tests yielded similar roughness values (Sa ≈ 0.5–0.7 μm, Sq ≈ 0.5–1.0 μm) across all densities and particle sizes. Dynamic friction tests revealed increased roughness (Sa from 0.7 to 3.5 μm, Sq from 1.0 to 6.0–7.0 μm). Friction coefficients (µ) decreased with higher sliding speeds, ranging from 0.22 to 0.13. GF with 40–80 μm particles had the lowest friction coefficient (µ = 0.13–0.15), while 160–200 μm particles had the highest (µ = 0.15–0.22). Density changes had minimal impact on friction for the 40–80 μm fraction but reduced friction for the 160–200 μm fraction. Young’s modulus increased with density and decreased with particle size, showing values from 127–274 MPa for 40–80 μm, 104–212 MPa for 160–200 μm, and 82–184 MPa for >500 μm. The stress–strain state in the graphite foil samples was simulated under normal and tangential loads. This makes it possible to investigate the effect of the anisotropy of the material on the stress concentration inside the sample, as well as to estimate the elasticity modulus under normal compression. Structural analyses indicated greater plastic deformation in GF with 40–80 μm particles, reducing coherent-scattering region size from 28 nm to 24 nm. GF samples from 160–200 μm and >500 μm fractions showed similar changes, expanding with density increase from 18 nm to 22 nm. Misorientation angles of GF nanocrystallites decreased from 30° to 27° along the rolling direction (RD). The coherent scattering regions of GF with 40–80 μm particles increased, but no significant changes in the coherent scattering regions were observed for the 160–200 μm and >500 μm fractions during dynamic friction tests. Microstrains and residual macrostresses in GF increased with density for all fractions, expanding under higher friction-induced loads. Higher values of both stresses indicate a higher level of accumulated deformation, which appears to be an additional factor affecting the samples during friction testing. This is reflected in the correlation of the results with the roughness and friction coefficient data of the tested samples.
Enhancing Long-Term Memory in Carbon-Nanotube-Based Optoelectronic Synaptic Devices for Neuromorphic Computing
Authors: Lee Seung Hun , Lee Hye Jin , Jeon Dabin , Kim Hee-Jin , Lee Sung-Nam
Published: September 2024

This study investigates the impact of spin-coating speed on the performance of carbon nanotube (CNT)-based optoelectronic synaptic devices, focusing on their long-term memory properties. CNT films fabricated at lower spin speeds exhibited a greater thickness and density compared to those at higher speeds. These denser films showed enhanced persistent photoconductivity, resulting in higher excitatory postsynaptic currents (EPSCs) and the prolonged retention of memory states after UV stimulation. Devices coated at a lower spin-coating speed of 2000 RPM maintained EPSCs above 70% for 3600 s, outperforming their higher-speed counterparts in long-term memory retention. Additionally, the study demonstrated that the learning efficiency improved with repeated UV stimulation, with fewer pulses needed to achieve the maximum EPSC in successive learning cycles. These findings highlight that optimizing spin-coating speeds can significantly enhance the performance of CNT-based synaptic devices, making them suitable for applications in neuromorphic computing and artificial neural networks requiring robust memory retention and efficient learning.
Absorption Spectra of AlGaN/GaN Terahertz Plasmonic Crystals—Experimental Validation of Analytical Approach
Authors: Dub Maksym , Sai Pavlo , Prystawko Pawel , Knap Wojciech , Rumyantsev Sergey
Published: September 2024

Absorption spectra of AlGaN/GaN grating-gate plasmonic crystals with a period from 1 µm to 2.5 µm were studied experimentally at T = 70 K using Fourier-transform infrared spectrometry. The plasmonic crystals exhibit distinct absorption lines of various plasmon harmonics across the 0.5 to 6 THz frequency range, tunable by gate voltage. Cumbersome and time-consuming electromagnetic simulations are usually needed to interpret or predict the grating-gate crystal spectra. In this work, we examine an analytical model and show that it can successfully describe the majority of existing experimental results. In this way, we demonstrate a new analytical platform for designing plasmonic crystals for THz filters, detectors, and amplifiers.
Nanomaterials for Modified Asphalt and Their Effects on Viscosity Characteristics: A Comprehensive Review
Authors: Huang Hualong , Wang Yongqiang , Wu Xuan , Zhang Jiandong , Huang Xiaohan
Published: September 2024

The application of nanomaterials as modifiers in the field of asphalt is increasingly widespread, and this paper aims to systematically review research on the impact of nanomaterials on asphalt viscosity. The results find that nanomaterials tend to increase asphalt’s viscosity, enhancing its resistance to high-temperature rutting and low-temperature cracking. Zero-dimension nanomaterials firmly adhere to the asphalt surface, augmenting non-bonding interactions through van der Waals forces and engaging in chemical reactions to form a spatial network structure. One-dimensional nanomaterials interact with non-polar asphalt molecules, forming bonds between tube walls, thereby enhancing adhesion, stability, and resistance to cyclic loading. Meanwhile, these bundled materials act as reinforcement to transmit stress, preventing or delaying crack propagation. Two-dimensional nanomaterials, such as graphene and graphene oxide, participate in chemical interactions, forming hydrogen bonds and aromatic deposits with asphalt molecules, affecting asphalt’s surface roughness and aggregate movement, which exhibit strong adsorption capacity and increase the viscosity of asphalt. Polymers reduce thermal movement and compact asphalt structures, absorbing light components and promoting the formation of a cross-linked network, thus enhancing high-temperature deformation resistance. However, challenges such as poor compatibility and dispersion, high production costs, and environmental and health concerns currently hinder the widespread application of nanomaterial-modified asphalt. Consequently, addressing these issues through comprehensive economic and ecological evaluations is crucial before large-scale practical implementation.
The Remarkable and Selective In Vitro Cytotoxicity of Synthesized Bola-Amphiphilic Nanovesicles on Etoposide-Sensitive and -Resistant Neuroblastoma Cells
Authors: Alfei Silvana , Giannoni Paolo , Signorello Maria Grazia , Torazza Carola , Zuccari Guendalina , Athanassopoulos Constantinos M. , Domenicotti Cinzia , Marengo Barbara
Published: September 2024

Neuroblastoma (NB) is a solid tumor occurring in infancy and childhood. Its high-risk form has currently a survival rate <50%, despite aggressive treatments. This worrying scenario is worsened by drug-induced secondary tumorigenesis and the emergency of drug resistance, calling for the urgent development of new extra-genomic treatments. Triphenyl phosphonium salts (TPPs) are mitochondria-targeting compounds that exert anticancer effects, impair mitochondria functions, and damage DNA at the same time. Despite several biochemical applications, TPP-based bola-amphiphiles self-assembling nanoparticles (NPs) in water have never been tested as antitumor agents. Here, with the aim of developing new antitumor devices to also counteract resistant forms of HR-NB, the anticancer effects of a TPP-based bola-amphiphile molecule have been investigated in vitro for the first time. To this end, we considered the previously synthesized and characterized sterically hindered quaternary phosphonium salt (BPPB). It embodies both the characteristics of mitochondria-targeting compounds and those of bola-amphiphiles. The anticancer effects of BPPB were assessed against HTLA-230 human stage-IV NB cells and their counterpart, which is resistant to etoposide (ETO), doxorubicin (DOX), and many other therapeutics (HTLA-ER). Very low IC50 values of 0.2 µM on HTLA-230 and 1.1 µM on HTLA-ER (538-fold lower than that of ETO) were already determined after 24 h of treatment. The very low cell viability observed after 24 h did not significantly differ from that observed for the longest exposure timing. The putative future inclusion of BPPB in a chemotherapeutic cocktail for HR-NB was assessed by investigating in vitro its cytotoxic effects against mammalian cell lines. These included monkey kidney cells (Cos-7, IC50 = 4.9 µM), human hepatic cells (HepG2, IC50 = 9.6 µM), a lung-derived fibroblast cell line (MRC-5, IC50 = 2.8 µM), and red blood cells (RBCs, IC50 = 14.9 µM). Appreciable to very high selectivity indexes (SIs) have been determined after 24 h treatments (SIs = 2.5–74.6), which provided evidence that both NB cell populations were already fully exterminated. These in vitro results pave the way for future investigations of BPPB on animal models and upon confirmation for the possible development of BPPB as a novel therapeutic to treat MDR HR-NB cells.
Gut Microbiota in Patients Receiving Dialysis: A Review
Authors: Lim Xintian , Ooi Lijin , Ding Uzhe , Wu Henry H. L. , Chinnadurai Rajkumar
Published: September 2024

The human gut microbiota constitutes a complex community of microorganisms residing within the gastrointestinal tract, encompassing a vast array of species that play crucial roles in health and disease. The disease processes involved in chronic kidney disease (CKD) and end-stage kidney disease (ESKD) are now increasingly established to result in dysregulation of gut microbiota composition and function. Gut microbiota dysbiosis has been associated with poor clinical outcomes and all-cause mortality in patients with ESKD, particularly individuals receiving dialysis. Prior studies highlighted various factors that affect gut microbiota dysbiosis in CKD and ESKD. These include, but are not limited to, uraemic toxin accumulation, chronic inflammation, immune dysfunction, medications, and dietary restrictions and nutritional status. There is a lack of studies at present that focus on the evaluation of gut microbiota dysbiosis in the context of dialysis. Knowledge on gut microbiota changes in this context is important for determining their impact on dialysis-specific and overall outcomes for this patient cohort. More importantly, evaluating gut microbiota composition can provide information into potential targets for therapeutic intervention. Identification of specific microbial signatures may result in further development of personalised treatments to improve patient outcomes and mitigate complications during dialysis. Optimising gut microbiota through various therapeutic approaches, including dietary adjustments, probiotics, prebiotics, medications, and faecal transplantation, have previously demonstrated potential in multiple medical conditions. It remains to be seen whether these therapeutic approaches are effective within the dialysis setting. Our review aims to evaluate evidence relating to alterations in the gut microbiota of patients undergoing dialysis. A growing body of evidence pointing to the complex yet significant relationship which surrounds gut microbiota and kidney health emphasises the importance of gut microbial balance to improve outcomes for individuals receiving dialysis.
Genomic Insights into Disease Resistance in Sunflower (Helianthus annuus): Identifying Key Regions and Candidate Genes for Verticillium dahliae Resistance
Authors: Yu Yue , Yang Jianfeng , Zhang Jian , Rieseberg Loren H. , Zhao Jun
Published: September 2024

Sunflower (Helianthus annuus) is a globally significant field crop, and disease resistance is crucial for ensuring yield stability and crop quality. Verticillium dahliae is a notorious soilborne pathogen that causes Verticillium Wilt (VW) and threatens sunflower production worldwide. In this study, we conducted a comprehensive assessment of sunflower resistance to V. dahliae across 231 sunflower cultivar lines, from the Sunflower Association Mapping (SAM) population. We employed EMMAX and ridge regression best linear unbiased prediction (rrBLUP) and identified 148 quantitative trait loci (QTLs) and 23 putative genes associated with V. dahliae resistance, including receptor like kinases, cell wall modification, transcriptional regulation, plant stress signalling and defense regulation genes. Our enrichment and quantitative real-time PCR validation results highlight the importance of membrane vesicle trafficking in the sunflower immune system for efficient signaling and defense upon activation by V. dahliae. This study also reveals the polygenic architecture of V. dahliae resistance in sunflowers and provides insights for breeding sunflower cultivars resistant to VW. This research contributes to ongoing efforts to enhance crop resilience and reduce yield losses due to VW, ultimately benefiting sunflower growers and the agricultural sector.