Search Results (6,838)

Human daily physical activity (PA), monitored via wearable devices, provides valuable information for real-time health assessment and disease prevention. However, analyzing time-domain PA data is challenging due to large data volumes and high inter- and intra-individual heterogeneity. Traditional PA analyses often rely on demographics, while advanced methods utilize time-domain summary statistics (e.g., L5, M10) or functional principal component analysis (FPCA). This study presents a data-efficient approach utilizing the Discrete Fourier Transform (DFT) to convert time-domain data into a compact set of frequency-domain variables. Our research suggests that adding these DFT variables can significantly enhance model performance. We demonstrate that incorporating DFT-derived variables substantially improves model performance. Specifically, (1) a small subset of DFT variables effectively captures major PA levels with effective dimensionality reduction; (2) these variables retain known associations with factors like age, sex, and weekday/weekend status; (3) they enhance the performance of classifiers. Mathematical and empirical analyses further confirm the reliability and interpretability of DFT-based features in dimension reduction. Across three mental health studies, these DFT-derived variables successfully capture key PA characteristics while retaining known associations and strengthening model performance. Overall, the proposed DFT-based framework offers a robust and scalable tool for analyzing accelerometer data, with broad applicability in health and behavioral research. Full article

The therapeutic use of non-steroidal anti-inflammatory drugs (NSAIDs) is limited by gastrointestinal and renal adverse effects caused by non-selective COX-1 and COX-2 inhibition. To address this issue, a new series of naproxen–azetidinone hybrids was rationally designed and synthesized to enhance COX-2 selectivity and reduce off-target toxicity. The synthesis involved esterification, hydrazide formation, Schiff base condensation, and intramolecular cyclization with chloroacetyl chloride. Structural characterization was achieved through FT-IR, ¹H NMR, and ¹³C NMR analyses. In silico ADMET profiling confirmed compliance with Lipinski’s rule and predicted favorable gastrointestinal absorption. Molecular docking revealed high COX-2 binding affinities (−11.93 to −9.72 kcal/mol), while MM/GBSA analysis identified compound N4_c (ΔG = −62.27 kcal/mol) as the most stable complex, surpassing meloxicam and naproxen. DFT (B3LYP/6-31G(d,p)) frontier molecular orbital analysis indicated a narrow HOMO–LUMO gap (ΔE = 2.97 eV) for N4_c, suggesting high electronic reactivity and strong enzyme interaction. Molecular dynamics simulations confirmed complex stability. In vivo anti-inflammatory testing using an egg-white-induced rat paw edema model showed that N4_d, N4_e, and N4_f achieved higher inhibition (19.22%, 16.98%, and 16.98%) than naproxen (4.3%). These results highlight 2-azetidinone–naproxen hybrids as promising selective COX-2 inhibitors with enhanced pharmacokinetic and electronic properties. Full article

Dicyanovinyl (DCV) oligothiophenes are interesting materials due to their unique optical and electronic properties. They are relatively easy to prepare using Knoevenagel condensation reactions from the corresponding aldehydes. Understanding their optical and electrochemical characteristics is important for both building structure/property relationships and for optimizing their performance in various applications. We report on the electrochemical and photophysical properties of three oligothiophenes end-capped with dicyanovinyl -CH=C(CN)₂ or DCV groups. The compounds included in this study are DCV-T-DCV (1), DCV-2T-DCV (2), and DCV-3T-DCV (3), where T represents one thiophene unit. Introduction of the DCV groups into oligothiophenes results in unique evolution of their electrochemical and optical behavior. First, new reversible two-electron reduction processes in the series DCV-nT-DCV start to appear with a gradual increase in the reduction potential with an increasing number of thiophene units. This was consistent with the electronic spectroscopic results. These results demonstrate that the DCV groups can be used in molecular design and fine-tuning of the optical and redox properties of oligothiophene and presumably this strategy can be extended to other conjugated organic molecules. We also report on the photophysical and vibrational spectroscopic properties of these compounds. The C=C stretching bands in Raman and IR spectra reveal more quinoidal nature in shorter molecules and more dominant benzoidal character in longer molecules. The DCV-induced modulation of electrochemical, optical, and vibrational properties highlights their potential in diverse optoelectronic applications. Full article

Imidazolium-based ionic liquids bearing a homologous series of oxychlorine anions—1-butyl-3-methylimidazolium chlorite, chlorate, and perchlorate—were synthesized and characterized to relate anion oxygenation to density, thermal expansivity, viscosity, electrical and molar conductivity, ionicity, and antimicrobial performance. Temperature-dependent measurements were carried out from 293.15 to 323.15 K: density and viscosity were recorded and modeled to obtain thermal expansion coefficients; electrical and molar conductivities were measured under identical conditions; and activation parameters were extracted by Arrhenius analysis for viscous flow and for conductivity. Ionicity was assessed from Walden plots and quantified by vertical deviation from the potassium-chloride reference (Angell approach). Complementary DFT calculations provided optimized ion-pair geometries, noncovalent contact patterns, molecular electrostatic potential maps, and frontier-orbital descriptors. In silico ADMET properties were computed to contextualize pharmacokinetic and safety flags. Antimicrobial activity was evaluated by broth microdilution against Escherichia coli, Staphylococcus aureus, Bacillus cereus, and Candida quilliermondii; [Bmim]Cl was included as a comparator to isolate the effect of anion oxygenation. The combined experimental–computational workflow delineates how chlorite, chlorate, and perchlorate shape physicochemical behavior, ionicity, and bioactivity in [Bmim] ionic liquids, providing design guidance for future applications. Full article

Rechargeable sodium-ion batteries (SIBs) have attracted considerable attention owing to the natural abundance and accessibility of sodium. Maricite NaMnPO₄, a phosphate-based cathode material with high theoretical capacity, suffers from blocked sodium-ion diffusion channels. In this study, atomistic simulations using pair potentials and density functional theory (DFT) are employed to investigate intrinsic defect mechanisms, sodium-ion migration pathways, and the role of dopant incorporation at Na, Mn, and P sites in generating Na vacancies and interstitials. Among the intrinsic defects, the Na–Mn anti-site cluster emerges as the most favorable, exhibiting a very low formation energy of 0.12 eV, while the Na Frenkel pair (1.93 eV) is the next most stable defect, indicating that sodium diffusion is primarily facilitated by vacancy formation. Nevertheless, sodium-ion mobility in NaMnPO₄ remains limited, as reflected by the relatively high migration activation energy of 1.28 eV. Among the isovalent substitutions, K is predicted to be the most favorable dopant at the Na site, whereas Ca and Cu are the most favorable at the Mn site. Thallium is identified as a promising dopant at the Mn site for generating Na vacancies that facilitate Na-ion migration, while Ge substitution at the P site is predicted to enhance the sodium content in the material. Full article

This report focuses on the oxalate anion radical (C₂O₄^●−) formed during γ-radiolysis of polycrystalline oxalates: protonated oxalic acid (H₂C₂O₄·2H₂O), caesium oxalate (Cs₂C₂O₄), and potassium oxalate monohydrate (K₂C₂O₄·H₂O). Irradiation at 77 K generates stable radical species, revealed by EPR spectroscopy and supported by DFT calculations. In H₂C₂O₄·2H₂O, the primary axial signal (g_avg = 2.0035) is shown to arise from the structural relaxation of the HC₂O₄∙ radical into the intrinsically stable non-planar (D_2d) conformation, resolving the symmetry conflict with the planar crystal precursor. Numerical deconvolution confirmed the co-existence of this radical with the secondary HCO₂^● species, exhibiting distinct relaxation characteristics. In Cs₂C₂O₄, the broad isotropic signal (g ≈ 2.008) is attributed to the D_2d form. Quantitative analysis proved a sharp, thermodynamically driven structural conversion (D_2d→D_2h) upon annealing above 220 K, where the D₂h conformer (g_avg ≈ 2.011) becomes the dominant species (≈73%). In K₂C₂O₄·H₂O, the C₂O₄^●− radical undergoes rapid decomposition into the CO₂^●− radical (g_avg ≈ 2.0007) due to the kinetic instability of the primary species in that matrix. Our findings underscore the crucial role of computational assistance and quantitative numerical fitting in EPR studies: DFT provided crucial assistance and yielded satisfactory agreement in most cases, while clarifying the structural and kinetic stability governed by the local cationic environment. The stability of the most resistant radical forms persists up to 430 K in the caesium salt. Full article

In this research article, a silicon carbide (SiC) nanocluster has been designed and characterized as an anode electrode for lithium (Li), sodium (Na), potassium (K), beryllium (Be), magnesium (Mg), boron (B), aluminum (Al) and gallium (Ga)-ion batteries through the formation of SiLiC, SiNaC, SiKC, SiBeC, SiMgC, SiBC, SiAlC and SiGaC nanoclusters. A vast study on energy-saving by SiLiC, SiNaC, SiKC, SiBeC, SiMgC, SiBC, SiAlC and SiGaC complexes was probed using computational approaches accompanying density state analysis of charge density differences (CDDs), total density of states (TDOS) and molecular electrostatic potential (ESP) for hybrid clusters of SiLiC, SiNaC, SiKC, SiBeC, SiMgC, SiBC, SiAlC and SiGaC. The functionalization of Li, Na, K, Be, Mg, B, Al and Ga metal/metalloid elements can raise the negative charge distribution of carbon elements as electron acceptors in SiLiC, SiNaC, SiKC, SiBeC, SiMgC, SiBC, SiAlC and SiGaC nanoclusters. Higher Si/C content can increase battery capacity through SiLiC, SiNaC, SiKC, SiBeC, SiMgC, SiBC, SiAlC and SiGaC nanoclusters for energy storage processes and to improve the rate performance by enhancing electrical conductivity. Full article

This study investigates the antioxidant properties of aucubin (AU), an iridoid compound, focusing on its ability to scavenge hydroxyl radicals (^•OH) through its hydroxyl functional groups. Gaussian software was employed to model and validate the underlying antioxidant reaction mechanisms. Three primary pathways were examined: hydrogen atom transfer (HAT), sequential electron transfer-proton transfer (SET-PT), and sequential proton loss–electron transfer (SPLET). All calculations were performed using the M06-2X functional within density functional theory (DFT) at the def2-TZVP level, incorporating Grimme’s D3 dispersion correction and the implicit solvation model based on solute electron density (SMD) for water. Various thermodynamic parameters were determined to analyze and compare the antioxidant reactions, including the O-H bond dissociation energy (BDE), ionization potential (IP), proton dissociation enthalpy (PDE), electron transfer enthalpy (ETE), and proton affinity (PA) of the hydroxy groups. The results indicated that the HAT mechanism is the dominant pathway in the scavenging of ^•OH radicals by AU. The key active sites were identified as the 6-OH group in the aglycone structure and the 6′-OH group in the sugar moiety. Moreover, the polar aqueous environment promoted O-H bond homolysis to enhance the antioxidant activity. Full article

Polycyclic aromatic hydrocarbons (PAHs) play a central role in materials science due to their extended π-conjugated systems, with their stability and reactivity depending critically on their aromatic character. In this work, we systematically investigated the aromaticity and stability of a broad range of linear (acenes, phenacenes, biphenylenes, and cyclobuta-acenes) and belt-like (cyclacenes, cyclophenacenes, and cyclobiphenylenes) PAHs containing five to twelve benzene rings. A diverse set of aromaticity descriptors was employed, including geometric (HOMA), electronic (MCI, FLU) and magnetic (NICS) descriptors, plus the recently developed ${\mathit{Q}}_2$ indices, based on the components of the distributed multipole analysis (DMA) electric quadrupole tensor. These data were complemented by stability analyses using singlet–triplet energy splitting (ΔE_S–T) and fractional occupation number-weighted densities (N_FOD) values. Our results indicate that acenes and phenacenes follow a comparable aromatic trend, with inner rings possessing lower aromaticity and the edge rings showing a more pronounced aromatic character. A subtle difference is observed in the position of the most aromatic ring, which lies slightly closer to the interior in acenes. Phenacenes, however, exhibit greater overall stability, attributed to their armchair edges. For biphenylenes and cyclobuta-acenes, the antiaromatic cyclobutadiene moiety perturbs the aromaticity only in its direct neighborhood and preserves the aromaticity in the remaining chains. In belt-like systems, cyclacenes exhibit strong radical character and low stability, consistent with longstanding synthetic challenges, whereas cyclophenacenes display enhanced aromaticity and stability with extending size. Cyclobiphenylenes combine localized antiaromatic centers with preserved benzene-like aromaticity in rings distant from the cyclobutadiene unit. Full article

N^G, N^G-dimethylarginine (ADMA) is an endogenous compound that acts as a competitive inhibitor of nitric oxide synthase (NOS), thereby reducing nitric oxide (NO) production and contributing to endothelial dysfunction. This dysfunction plays a pivotal role in the development of various pathological conditions, including cardiovascular disease, chronic renal failure, and diabetes. The diminished bioavailability of NO is a critical factor in the progression of these disorders, and alterations in ADMA levels have emerged as significant predictors of cardiovascular events and mortality. In this study, we investigated the molecular characteristics of ADMA using a combined approach of Raman and Fourier Transform Infrared (FT-IR) spectroscopy, complemented by computational simulations with the GaussView 5.0.8 and Gaussian 09 software suite. Experimental Raman and FT-IR spectra were acquired and compared with simulated spectra generated through Density Functional Theory (DFT) calculations. This comparative analysis enabled precise vibrational band assignments and the identification of key molecular vibrational modes, providing valuable insights into ADMA’s structural and vibrational properties. These findings establish a comprehensive spectroscopic reference for ADMA, supporting its potential application as a biomarker in clinical diagnostics. Full article

Background/Objectives: The aim of this study was to evaluate the oral health status of socially vulnerable children and adolescents in Seville and to examine its associations with behavioral and sociodemographic determinants. We hypothesized that greater social vulnerability and suboptimal behaviors would be associated with higher caries experience. Methods: A cross-sectional analytical study was conducted on 250 participants aged 2 to 17 years attending the Luis Séiquer Social Dentistry Foundation between January and March 2025. Clinical examinations followed the WHO Oral Health Surveys: Basic Methods (5th edition, 2013) and were performed by a calibrated dentist. Variables included dental caries indices (dft, DMFT), pulpal treatment needs, and oral hygiene practices. Statistical analyses included Kruskal–Wallis, Mann–Whitney U, Fisher’s exact tests, and multivariate regression models (significance level p < 0.05). Results: Caries prevalence was high across all age groups, particularly in primary dentition (mean dft = 3.05 ± 3.80; DMFT = 2.99 ± 3.66; p < 0.001). Pulp therapy needs were significantly higher among preschoolers (mean = 2.22 ± 2.31). Factors such as low parental education, migrant background, insufficient toothbrushing frequency, and frequent sugar intake were strongly associated with poorer oral health outcomes. Although fluoridated toothpaste use was widespread (>94%), dental floss use remained limited (34.8%). Multivariate analyses confirmed a strong association between social inequalities and oral disease burden. Conclusions: Children and adolescents from vulnerable groups in Seville experience a high prevalence of dental caries and substantial unmet treatment needs. Findings highlight marked oral health disparities linked to socioeconomic status, emphasizing the urgent need for early preventive programs, culturally adapted oral health education, and equitable access to dental care. Full article

Plastic pollution, driven by the durability and widespread use of polyolefins such as polypropylene (PP) and high-density polyethylene (HDPE), poses a formidable environmental challenge. To address this issue, we have developed an integrated multiscale framework that combines thermocatalytic experimentation, process-scale simulation, and molecular-level modeling to optimize the catalytic pyrolysis of PP and HDPE waste. Under the identified optimal conditions (300 °C, 10 wt % HMOR zeolite), liquid-oil yields of 60.8% for PP and 87.3% for HDPE were achieved, accompanied by high energy densities (44.2 MJ/kg, RON 97.5 for PP; 43.7 MJ/kg, RON 115.2 for HDPE). These values significantly surpass those typically reported for uncatalyzed pyrolysis, demonstrating the efficacy of HMOR in directing product selectivity toward valuable liquids. Above 400 °C, the process undergoes a pronounced shift toward gas generation, with gas fractions exceeding 50 wt % by 441 °C, underscoring the critical influence of temperature on product distribution. Gas-phase analysis revealed that PP-derived syngas contains primarily methane (20%) and ethylene (19.5%), whereas HDPE-derived gas features propylene (1.9%) and hydrogen (1.5%), highlighting intrinsic differences in bond-scission pathways governed by polymer architectures. Aspen Plus process simulations, calibrated against experimental data, reliably predict product distributions with deviations below 20%, offering a rapid, cost-effective tool for reactor design and scale-up. Complementary density functional theory (DFT) calculations elucidate the temperature-dependent energetics of C–C bond cleavage and radical formation, revealing that system entropy increases sharply at 500–550 °C, favoring the generation of both liquid and gaseous intermediates. By directly correlating catalyst acidity, molecular reaction mechanisms, and process-scale performance, this study fills a critical gap in plastic-waste valorization research. The resulting predictive platform enables rational design of catalysts and operating conditions for circular economy applications, paving the way for scalable, efficient recovery of fuels and chemicals from mixed polyolefin waste. Full article

This brief review examines the application of various computational approaches to investigate the physicochemical and interfacial properties of nanocomposite systems. Density functional theory (DFT), a quantum-mechanical technique, examines the fundamental properties of nanomaterials. Molecular docking studies have also been explored to show how different biological macromolecules can interact and bind with the nanoparticles (NPs’) surface, along with the molecular dynamics (MDs) simulations, which further strengthen the docking findings. Furthermore, nanotoxicology, a comparatively less explored field, has also been introduced, providing an insight into the interactions between nanomaterials and the environment and biological systems, including the harmful consequences. Full article

Metal-free aminobenzoic acid-derived Schiff bases are attractive antimicrobial leads because their azomethine (–C=N–) functionality enables tunable electronic properties and target engagement. We investigated whether halogenation on the phenolic ring would modulate the redox behavior and enhance antibacterial potency, and hypothesized that heavier halogens would favorably tune physicochemical and electronic descriptors. We synthesized three derivatives (SB-3/Cl, SB-4/Br, and SB-5/I) and confirmed their structures using FTIR, ¹H- and ¹³C-NMR, UV-Vis, and HRMS. For SB-5, single-crystal X-ray diffraction and Hirshfeld analysis verified the intramolecular O–H⋯N hydrogen bond and key packing contacts. Cyclic voltammetry revealed an irreversible oxidation (aminobenzoic ring) and, for the halogenated series, a reversible reduction associated with the imine; peak positions and reversibility trends are consistent with halogen electronic effects and DFT-based MEP/LHS descriptors. Antimicrobial testing showed that SB-5 was selectively potent against Gram-positive aerobes, with low-to-mid micromolar MICs across the panel. Among anaerobes, activity was more substantial: Clostridioides difficile was inhibited at 0.1 µM, and SB-3/SB-5 reduced its sporulation at sub-MICs, while Blautia coccoides was highly susceptible (MIC 0.01 µM). No activity was detected against Gram-negative bacteria at the tested concentrations. In the fungal assay, Botrytis cinerea displayed only a transient fungistatic response without complete growth inhibition. In mammalian cells (HeLa), the compounds displayed clear concentration-dependent behavior. Overall, halogenation, particularly iodination, emerges as a powerful tool to couple redox tuning with selective Gram-positive activity and a favorable cellular tolerance window, nominating SB-5 as a promising scaffold for further antimicrobial optimization. Full article

Most machine learning algorithms operate on vectorized data with Euclidean structures because of the significant mathematical advantages offered by Hilbert space, but improved representational efficiency may offset more involved learning on non-Euclidean structures. Recently, a method that integrates the marginalized graph kernel into the Gaussian process regression framework was used to learn directly on molecular graphs. Here, we describe an implementation of this method for crystalline materials based on effective crystal graph representations: the molecular graphs of 128-atom supercells of body-centered cubic (BCC) iron with periodic boundary conditions. Regressors trained on hundreds of time steps of a density functional theory molecular dynamics (DFT-MD) simulation achieved root mean square errors of less than 5 meV/atom. The mechanical stability of BCC iron was investigated at high pressure and elevated temperature using regressors trained on short DFT-MD runs, including at conditions found in the inner core of the earth. Phonon dispersions obtained from the short runs show that BCC iron is mechanically stable at 360 GPa when the temperature is above 2500 K. Atoms in the super cell were displaced in the direction of the first, second, and third nearest-neighbors from selected configurations that included thermal atomic displacements, and forces exerted on the displaced atoms were computed by numerical differentiation of the regressors. Full article