Search Results (6,822)

The simultaneous HPLC method for quantifying Quercetin (Que), Thymoquinone (Thy), and Pterostilbene (Pte) aims at the precise measurement of these polyphenols alone or in complex mixtures, targeting their therapeutic potential in disorders such as diabetes and epilepsy. The method focuses on quantifying Que, Thy, and Pte, utilizing optimized reversed-phase HPLC conditions as per ICH Q2(R1) standards. Key validation aspects include linearity, specificity, precision, and accuracy, ensuring compliance for quality control in nanomedicine and nutraceuticals, and the method’s applications support pharmacokinetic studies and stability testing, contributing to personalized medicine and addressing pharmaco-resistance. The HPLC method development and validation were performed on a phenyl column using the mobile phase consisting of solvent A (0.1% orthophosphoric acid in HPLC water) and solvent B (acetonitrile) at a ratio of 55:45 in an isocratic elution mode at a flow rate of 1 mL/min and at a column temperature of 35 °C. Ultraviolet detection was measured at 254 nm. Moreover, the method was validated for accuracy, precision, linearity, specificity, and sensitivity. The retention time for tested Que, Thy, and Pte was observed at 4.15 min, 8.70 min, and 10.75 min, respectively. Limits of detection for Que, Thy, and Pte were 1.55 μg/mL, 2.40 μg/mL, and 70.79 µg/mL, whereas limits of quantification were 4.69 μg/mL, 7.28 μg/mL, and 214.52 µg/mL, respectively. Linearity and correlation coefficients for Que, Thy, and Pte were found in the range of 50–250 μg/mL (0.9999), 50–250 μg/mL (0.9999), and 620–3100 μg/mL (0.9996), respectively. A reasonable level of accuracy was indicated by the tested method suggesting extremely high recovery levels (98–102%). The separation of tested compounds was achieved within 11 min. The developed and validated RP-HPLC–UV method was successfully applied for the identification and quantification of Que, Thy, and Pte for their combined estimation in complex formulations. From the validation study, it was found that the tested method is specific, accurate, precise, reliable, and reproducible. Full article

A living organism can be regarded as a dissipative, self-organizing physical system operating far from thermodynamic equilibrium. Such systems can be effectively described within the framework of Markov jump processes subjected to an external driving force that sustains the system away from equilibrium—leading, in the special case of stabilization, to a non-equilibrium steady state (NESS). By combining the Markov formalism with concepts from stochastic thermodynamics, we demonstrate the temporal evolution of entropy in such systems: entropy decreases during growth and development, stabilizes at maturity under NESS conditions, and subsequently increases during aging, death, and decomposition. This characteristic trajectory, which we term the entropy bathtub, highlights the universal thermodynamic structure of living systems. We further show that the system exhibits continuous yet time-dependent positive entropy production, in accordance with fundamental thermodynamic principles. Perturbations of the driving force—whether reversible or irreversible—naturally capture the impact of external stressors, providing a conceptual analogy to pathological processes in biological organisms. Although the model does not introduce fundamentally new elements to the physics of life, it offers a simple tool for exploring entropy-driven mechanisms in living matter. Full article

Reverse engineering (RE) has been increasingly adopted in metal manufacturing to digitize legacy parts, connect “as-is” geometry to mechanical performance, and enable agile repair and remanufacturing. This review consolidates scan-to-simulation workflows that transform 3D measurement data (optical/laser scanning and X-ray computed tomography) into simulation-ready models for structural assessment and manufacturing decisions, with an explicit focus on sustainability. Key steps are reviewed, from acquisition planning and metrological error sources to point-cloud/mesh processing, CAD/feature reconstruction, and geometry preparation for finite-element analysis (watertightness, defeaturing, meshing strategies, and boundary condition transfer). Special attention is given to uncertainty quantification and the propagation of geometric deviations into stress, stiffness, and fatigue predictions, enabling robust accept/reject and repair/replace choices. Sustainability is addressed through a lightweight reporting framework covering material losses, energy use, rework, and lead time across the scan–model–simulate–manufacture chain, clarifying when digitalization reduces scrap and over-processing. Industrial use cases are discussed for high-value metal components (e.g., molds, turbine blades, and marine/energy parts) where scan-informed simulation supports faster and more reliable decision making. Open challenges are summarized, including benchmark datasets, standardized reporting, automation of feature recognition, and integration with repair process simulation (DED/WAAM) and life-cycle metrics. A checklist is proposed to improve reproducibility and comparability across RE studies. Full article

In this study, the nonlinear and non-monotonic behavior of amperometric bienzyme biosensors employing an enzymatic trigger reaction is investigated analytically and computationally using a two-compartment model comprising an enzymatic layer and an outer diffusion layer. The trigger enzymatic reaction is coupled with a cyclic electrochemical–enzymatic conversion (CEC) process. The model is formulated as a system of reaction–diffusion equations incorporating nonlinear Michaelis–Menten kinetics and interlayer partitioning effects. Exact steady-state analytical solutions for substrate and product concentrations, as well as for the output current, are obtained for specific cases of first- and zero-order reaction kinetics. At the transition conditions, biosensor performance is further analyzed numerically using the finite difference method. The CEC biosensor exhibits the highest signal gain when the first enzyme has low activity and the second enzyme has high activity; however, under these conditions, the response time is the longest. When the first enzyme possesses a higher substrate affinity (lower Michaelis constant) than the second, the biosensor demonstrates severalfold higher current and gain compared to the reverse configuration under identical diffusion limitations. Furthermore, increasing external mass transport resistance or interfacial partitioning can enhance the apparent signal gain. Full article

Psychological stress is increasingly investigated as a potentially modifiable factor in male infertility, in part through oxidative stress. This narrative review synthesizes mechanistic and translational evidence linking stress-related neuroendocrine activation and coping behaviors with redox imbalance in the male reproductive tract. Chronic activation of the hypothalamic–pituitary–adrenal axis and sympathetic outflow elevates glucocorticoids and catecholamines. In controlled animal stress paradigms, this is accompanied by suppression of the hypothalamic–pituitary–gonadal axis and by immune and metabolic changes that favor reactive oxygen species generation. The resulting oxidative stress may reduce Leydig cell steroidogenesis, impair testicular and epididymal function, and induce lipid peroxidation, mitochondrial dysfunction, and sperm DNA fragmentation. In such models, these lesions, together with apoptosis of germ and supporting cells, are associated with lower sperm concentration, reduced motility, compromised viability, and diminished fertilizing potential. Overall, preclinical animal studies using defined stress paradigms provide experimental evidence consistent with causal effects of stress on oxidative injury and reproductive impairment in preclinical settings. Human studies linking perceived stress, anxiety/depression, and disturbed sleep to adverse semen parameters and oxidative biomarkers are summarized. However, the human evidence is predominantly associative, and the available studies are cross sectional and remain vulnerable to residual confounding and reverse causality. Potential effect modifiers, including smoking, alcohol use, and circadian disruption, are also discussed as contributors to heterogeneity across clinical studies. Standardized assessment of stress biology and redox status, longitudinal designs aligned with spermatogenic timing, and well-powered intervention trials are needed to define dose–response relationships and support individualized prevention and care. Full article

Facial information carries key personal privacy, and it is crucial to ensure its security through encryption. Traditional encryption for portrait images typically processes the entire image, despite the fact that most regions lack sensitive facial information. This approach is notably inefficient and imposes unnecessary computational burdens. To address this inefficiency while maintaining security, we propose a novel dual-region encryption model for portrait images. Firstly, a Multi-task Cascaded Convolutional Network (MTCNN) was adopted to efficiently segment facial images into two regions: facial and non-facial. Subsequently, given the high sensitivity of facial regions, a robust encryption scheme was designed by integrating a CNN-based key generator, the proposed three-dimensional Multi-module Nonlinear Feedback-coupled Chaotic System (3D-MNFC), DNA encoding, and bit reversal. The 3D-MNFC incorporating time-varying parameters, nonlinear terms and state feedback terms and coupling mechanisms has been proven to exhibit excellent chaotic performance. As for non-facial regions, the Logistic map combined with XOR operations is used to balance efficiency and basic security. Finally, the encrypted image is obtained by restoring the two ciphertext images to their original positions. Comprehensive security analyses confirm the exceptional performance of the regional model: large key space ($2^{536}$) and near-ideal information entropy (7.9995), NPCR and UACI values of 99.6055% and 33.4599%. It is worth noting that the model has been verified to improve efficiency by at least 37.82%. Full article

This study evaluates the partial dealcoholization of red wine using reverse osmosis (ACM3) and nanofiltration (TS80) membranes at 25 and 35 bar, targeting 2% and 4% ethanol reductions. Membrane performance was assessed through fouling analysis and ethanol partitioning, while wine phenolic (flavan-3-ols, anthocyanins) and color characteristics (CIELab parameters) were determined. The 2% reduction process with ACM3 at 25 bar resulted in minimal phenolic changes. The 4% reduction process revealed distinct performance profiles: ACM3 exhibited exceptional stability (3.35–5.30% permeability loss, linear flux decline with R² > 0.93) and ethanol rejection of 17.6–25.5%, while TS80 achieved processing rates three to six times faster with moderate fouling (16.3% loss, 7.7–13.3% rejection). Decreases in flavan-3-ols and anthocyanin concentrations correlated with fouling intensity rather than processing duration. Proanthocyanidin structure remained stable, and color shifts reflected changes in polymeric pigments rather than anthocyanin loss. Reverse osmosis at low transmembrane pressure proved most suitable for quality preservation. The operational trade-off is clear: TS80 offers three to six times faster processing but with greater phenolic loss, while ACM3 requires longer batch times with minimal fouling. Both processes demonstrate that membrane-based dealcoholization without fluid replacement is feasible, providing winemakers with a valuable method to reduce alcohol while preserving quality. Full article

Magnetic resonance imaging (MRI) super-resolution (SR) enables high-resolution reconstruction from low-resolution acquisitions, reducing scan time and easing hardware demands. However, most deep learning-based SR models are large and computationally heavy, limiting deployment in clinical workstations, real-time pipelines, and resource-restricted platforms such as low-field and portable MRI. We introduce CHARMS, a lightweight convolutional–Transformer hybrid with attention regularization optimized for MRI SR. CHARMS employs a Reverse Residual Attention Fusion backbone for hierarchical local feature extraction, Pixel–Channel and Enhanced Spatial Attention for fine-grained feature calibration, and a Multi-Depthwise Dilated Transformer Attention block for efficient long-range dependency modeling. Novel attention regularization suppresses redundant activations, stabilizes training, and enhances generalization across contrasts and field strengths. Across IXI, Human Connectome Project Young Adult, and paired 3T/7T datasets, CHARMS (~1.9M parameters; ~30 GFLOPs for 256 × 256) surpasses leading lightweight and hybrid baselines (EDSR, PAN, W2AMSN-S, and FMEN) by 0.1–0.6 dB PSNR and up to 1% SSIM at ×2/×4 upscaling, while reducing inference time ~40%. Cross-field fine-tuning yields 7T-like reconstructions from 3T inputs with ~6 dB PSNR and 0.12 SSIM gains over native 3T. With near-real-time performance (~11 ms/slice, ~1.6–1.9 s per 3D volume on RTX 4090), CHARMS offers a compelling fidelity–efficiency balance for clinical workflows, accelerated protocols, and portable MRI. Full article

Conflicting data exist regarding the effect of intradetrusor BoNT/A on the incidence of urinary tract infections (UTIs) in patients with neurogenic detrusor overactivity (NDO), contrary to the increase in UTIs noted in patients with idiopathic OAB. Associations between UTIs, chronic inflammation, and bladder overactivity are acknowledged, albeit not fully understood. Chronic bladder inflammation is common in both NDO and OAB patients, and both animal and human studies suggest a beneficial effect of BoNT/A on both urinary and systemic levels of inflammatory markers. To explore whether intradetrusor BoNT/A injections affect the background for the incidence of UTIs in humans, we investigated in parallel the effect of intradetrusor BoNT/A on the incidence of UTIs and on the urine mRNA levels of urinary pathogen-detecting Toll-like receptors TLR2, TLR4, and TLR5 and of factors acting as intermediates of immune response and promoters of inflammatory reactions (IL1β, IL6, TNFα, and PGE₂). For this purpose, we recruited 22 patients with NDO-associated incontinence who received at least one bladder BoNT/A injection. Urine specimens for the study of UTIs were obtained before the procedure and at routine urodynamic follow-ups at 4–6 weeks, 6 and 12 months post-BoNT/A, and at clinical relapse, while urine specimens for the study of biomarkers were collected at the time of BoNT/A injection and at the abovementioned follow-ups thereafter. Urine specimens from 10 adult healthy volunteers with no OAB symptoms served as the control group in the biomarker study. The genes of interest in the urine were studied by RNA isolation, reverse transcription, and real-time PCR. The urine mRNAs of all biomarkers tested appeared to be upregulated in the patients’ samples compared with the controls, albeit only TLR2 and TLR5 mRNA increases were statistically significant. A progressive downregulation of TLR2, TLR5, IL1β, and IL6 urine mRNAs was noted at one and six months post-BoNT/A. TNFα and PGE₂ mRNAs showed a transient increase at one month post-BoNT/A followed by a dramatic drop at the six months’ follow-up. A similar trend for progressive decline was also noticed in the prevalence of both positive urine cultures and symptomatic UTIs in the same timepoints and additionally at 12 months post-treatment in patients who still benefited from the BoNT/A treatment. Upon clinical relapse, the mRNA levels of PGE₂, IL1β, and IL6 increased in parallel with an increase in the prevalence of UTIs, while the levels of TLRs and TNF-α did not follow the same trend. In summary, intradetrusor BoNT/A injections achieved significant decreases in the urine mRNA levels of pathogen-detecting TLRs, immune response, and inflammation mediator cytokines and PGE₂ in our cohort of patients with NDO-associated incontinence. In parallel, decreases were noted in both the incidence of symptomatic UTIs and rates of positive urine cultures. At the time of clinical relapse, the markers of inflammation and immune response, but not TLRs, were upregulated in parallel with the increased incidence of UTIs, suggesting that the studied genes PGE₂, IL1β, and IL6 could be further explored as potential biomarkers for inflammation/immune response and UTIs in the neurogenic population. Full article

Aerospace power systems, including satellites in low earth orbit (LEO) and geostationary earth orbit (GEO), face stringent thermal constraints to minimize size, weight, and power (SWaP). Gallium nitride (GaN) devices offer superior radiation hardness—critical for the harsh space environment—and MHz-level switching capabilities. This high-frequency operation minimizes passive components, particularly magnetics, thereby reducing the overall volume. However, above 10 MHz, magnetic cores become impractical due to material limitations. To address these issues, this article proposes a design methodology for a GaN-based quasi-square-wave (QSW) buck converter integrated with a PCB air-core inductor. First, the impact of the switching frequency and dead time on the zero-voltage switching (ZVS) condition is elaborated. Then, a power loss model accounting for various loss mechanisms is presented. To overcome high GaN body diode reverse conduction loss, an auxiliary diode is employed. Based on the model, a design procedure is developed to optimize the inductor for 10 MHz operation while maximizing efficiency. To validate the design, a 28 V/12 V, 18 W prototype was built and tested. Experimental results demonstrate a peak efficiency of 86.5% at 10 MHz. The auxiliary diode improves efficiency by 4%, verifying reverse conduction loss mitigation. Thermal analysis confirms a full-load case temperature of 62.2 °C, providing a 47.8 °C safety margin compliant with aerospace derating standards. These findings validate the solution for high-frequency, space-constrained aerospace applications. Full article

Cetaceans are artiodactyls adapted to live in the marine environment, and this group includes whales, dolphins, and porpoises. Although mitochondrial nucleotide diversity has been reported separately for many cetacean groups, the proportion of deleterious mutations in these populations is unknown. Furthermore, a comparison of mitogenomic diversities across all cetaceans is also lacking. To investigate this, we conducted a comparative genomic analysis of 2244 mitochondrial genomes from 65 populations across 32 cetacean species. We observed a 78-fold variation in mitogenomic diversity among cetacean populations, suggesting a large difference in genetic diversity. We used the ratio of nonsynonymous-to-synonymous diversities (dN/dS) to measure the proportion of deleterious mutations in the mitochondrial exomes. The dN/dS ratio showed a 22-fold difference between the cetacean population. Based on genetic theories, the large differences observed in the two measures could be attributed to differences in the effective sizes of the cetacean populations. Typically, small populations have low heterozygosity and a high dN/dS ratio, and the reverse is true for large populations. This was further confirmed by the negative correlation observed between heterozygosity and dN/dS ratios of cetacean populations. While our analysis revealed similarities in mitogenomic diversity between the endangered and least-concern cetacean species, the dN/dS ratio of the former was found to be higher than that of the latter. The findings of this study are useful for identifying the relative magnitude of reductions in the population sizes of different cetacean species. This will help conservation management efforts prioritise the use of limited resources, time, and effort to protect the cetacean populations that need immediate attention. Full article

Steel pipes play a vital role in energy and industrial transportation systems, where undetected defects such as cracks and wall thinning may lead to severe safety hazards. Although ultrasonic guided waves enable long-range inspection, their defect imaging performance is often limited by dispersion, multimode interference, and strong noise. In this work, a multi-frequency fusion imaging method integrating time-reversal, topological derivative, and sparse Bayesian learning is proposed for guided wave-based defect detection in steel pipes. Multi-frequency guided waves are employed to enhance defect sensitivity and suppress frequency-dependent ambiguity. Time-reversal focusing is used to concentrate scattered energy at defect locations, while the topological derivative provides a global sensitivity map as physics-guided prior information. These results are further fused within a sparse Bayesian learning framework to achieve probabilistic defect imaging and uncertainty quantification. Dispersion compensation based on the semi-analytical finite element method is introduced to ensure accurate wavefield reconstruction at different frequencies. Domain randomization is also incorporated to improve robustness against uncertainties in material properties, temperature, and measurement noise. Numerical simulation results verify that the proposed method achieves high localization accuracy and significantly outperforms conventional TR-based imaging in terms of resolution, false alarm suppression, and stability. The proposed approach provides a reliable and robust solution for guided wave inspection of steel pipelines and offers strong potential for engineering applications in nondestructive evaluation and structural health monitoring. Full article

Perpetual futures account for approximately 93% of cryptocurrency futures trading volume, yet funding rate dynamics across fragmented markets remain understudied. We construct a high-frequency panel dataset comprising 35.7 million one-minute observations across 26 cryptocurrency exchanges (11 centralized, 15 decentralized) spanning 749 symbols over eight consecutive days. Using time-series econometrics, correlation analysis, and Granger causality tests, we characterize funding rate dynamics, market integration, and information flow. We find evidence of a two-tiered market structure: centralized exchanges (CEX) dominate price discovery with 61% higher integration than decentralized exchanges (DEX), and all significant information flow runs CEX-to-DEX with zero reverse causality. While 17% of observations exhibit economically significant arbitrage spreads (≥20 basis points), only 40% of top opportunities generate positive returns after transaction costs and spread reversals. Delta-neutral portfolio simulations reveal that successful arbitrage requires both high spreads and sufficient duration before inevitable reversals, with forced exits occurring in 95% of opportunities. The findings show that cryptocurrency derivatives markets exhibit a persistent two-tiered structure in which centralized platforms dominate price discovery while transaction costs and spread reversal risks prevent arbitrage from eliminating large mispricings between platforms, resolving the apparent paradox of substantial price fragmentation coexisting with market efficiency. Full article

Numerous research works have tried to evaluate the correlation between inflammation and the onset of prostate cancer. Given the in vitro antioxidant power and the anti-proliferative effects on human prostate cancer cells shown by a Juglans regia L. fresh fruit extract, the aim of this work was the evaluation of its potential in the acute and chronic inflammatory states in vivo, revealing a strong anti-inflammatory activity. In the zymosan-induced edema formation assay, a light and non-significant edema reduction was shown. On the contrary, in the zymosan-induced thermal hyperalgesia assay, the reversion of hyperalgesia after the extract administration was determined. Moreover, in the formalin test, the extract caused a significant decrease in the licking time caused by the aldehyde, especially in the late phase. In silico, quercetin showed the best fit into the enzymatic pocket of AChE (docking score: −11.306 Kcal/mol). Neochlorogenic acid and ellagic acid gave the best docking scores on BChE (−10.292 Kcal/mol and −10.054 Kcal/mol, respectively). Abscisic acid showed a high binding affinity for the glucocorticoid receptor. Finally, quercetin and abscisic acid were quantified to complete the data by HPLC-DAD, giving 0.246 ± 0.003 mg/g of dried extract and 0.036 ± 0.004 mg/g of dried extract, respectively. Full article

Background/Objectives: Preoperative differentiation between oral squamous cell carcinoma (SCC) and minor salivary gland carcinoma (SGC) remains clinically challenging due to overlapping imaging characteristics. This study aimed to develop a diagnostic model based on quantitative dynamic contrast-enhanced MRI (qDCE-MRI) parameters to distinguish SCC from SGC prior to surgery. Methods: Patients with histopathologic confirmed SCC or minor SGC who underwent preoperative 3.0T qDCE-MRI were recruited. Clinical characteristics and pharmacokinetic parameters, including volume transfer constant (K^trans), reverse reflux rate constant (K_ep), volume fraction of extravascular extracellular space (V_e), plasma volume fraction (V_p), time to peak (TTP), maximum concentration (MAXConc), maximal slope (MAXSlope), and area under the concentration-time curve (AUCt), along with the apparent diffusion coefficient (ADC), were extracted. Univariate and multivariable logistic regression analyses were performed to identify independent discriminators. Diagnostic performance was assessed using receiver operating characteristic analysis, and model comparisons were conducted with the DeLong test. Interobserver agreement was evaluated using intraclass correlation coefficients (ICC). Results: All qDCE-MRI parameters demonstrated excellent interobserver agreement (ICC range, 0.82–0.94). Multivariable analysis identified K_ep (OR = 2620.172, p = 0.001), maximal slope (OR = 1.715, p = 0.024), and tumor location (OR = 5.561, p = 0.027) as independent predictors. The qDCE-MRI model achieved superior diagnostic performance compared with the clinical model (AUC: 0.945 vs. 0.747; p = 0.012). Conclusions: A qDCE-MRI–based model incorporating K_ep and MAXSlope was shown to provide excellent accuracy for preoperative differentiation between oral SCC and minor SGC. Full article