Search Results (9,264)

Brachymystax lenok tsinlingensis is an endangered salmonid endemic to China. Traditional trapping methods frequently fail to detect this rare fish in low-density mountain streams, hampering evidence-based conservation. Here, we employed environmental DNA quantitative PCR (eDNA-qPCR) with species-specific primers to assess the spatial biomass distribution of this species in the Zhouzhi Heihe River. Concurrently, we surveyed plankton, benthic macroinvertebrates, and physicochemical water parameters. eDNA detected the target species at 12 of 14 sites, with reliable quantification achieved at 9 sites, suggesting that the method may be more effective than conventional trapping for detecting this species under the studied low-density conditions. eDNA-derived relative biomass exhibited pronounced spatial heterogeneity, ranging from 6.0 × 10⁻⁴ to 1.5 × 10⁻² g/cm³. Water depth showed a significant positive association with biomass (r = 0.5347), whereas phytoplankton Shannon diversity (a measure of species richness and evenness) was significantly negatively correlated (r = −0.5447). Flow velocity displayed a negative trend that did not reach statistical significance (r = −0.5009). Plankton and benthic communities indicated overall ecological conditions but did not directly explain the observed spatial variation in fish biomass. These findings indicate that the spatial pattern of B. lenok tsinlingensis is primarily shaped by local physical habitat structure, with deeper, hydraulically more complex channel units serving as key microhabitats. eDNA-qPCR thus represents an effective, low-disturbance monitoring tool for this endangered cold-water fish and provides a scientific basis for targeted habitat protection and restoration. Full article

Bioelectrical impedance analysis (BIA) is a widely used technique in clinical and research settings because it provides non-invasive estimates of body composition. However, the quality of a measurement depends on more than the perceived accuracy and precision of numbers produced by a BIA device. This review considers BIA through the lens of metrology, defined as the science of measurement. It highlights several key factors that affect measurement quality. These include accuracy, precision, calibration, standardisation, and uncertainty quantification, all of which are essential for meaningful, clinically feasible BIA measurements. Applying prediction equations generated by the device outside their intended context, poor electrode placement, or uncalibrated devices can introduce bias, whereas biological variability can complicate the interpretation of bioimpedance results. The traditional emphasis on using a reference method for validation is considered along with clinical relevance, which is argued to be an equally important benchmark for evaluating measurement utility. We also present best practices and practical guidelines for improving measurement quality, interpretation, and integration into clinical workflows. By adopting a metrological mindset in clinical practice and treating BIA with the same rigour as other diagnostic tools, its utility in areas such as fluid management, nutrition, and preventive health can be further enhanced. Trustworthy decisions depend not only on the data itself but also on how it is measured, interpreted, and used. Full article

This paper presents proprietary, multi-platform software developed in Python for analyzing the electrical and microstructural properties of silicon solar cell metallization. Utilizing a sample set of 20 commercial solar cells, electrical resistivity and contact resistance measurements obtained via the potential difference method were correlated with high-resolution topographic data from AFM, SEM, and CLSM. This process enabled the quantification of how specific features, such as surface roughness and finger height, directly influence electrical performance. The developed algorithms offer high-fidelity predictive capabilities, with relative errors below 4%. This “virtual laboratory” serves as a transformative research and educational tool, allowing for complex materials analysis while avoiding the necessity for destructive testing. Full article

Objectives: Three stability-indicating analytical methods featuring outstanding sensitivity, selectivity, and precision were set up for the quantification of salicylamide (SAD) and ascorbic acid (ASC) in the presence of salicylic acid (SAL), which represents a possible impurity and degradation product of SAD. The aim was to develop sensitive, selective, precise, and eco-friendly assays appropriate for routine quality control of pharmaceuticals. Methods: Method (A) was a spectrophotometric technique of a successive derivative of ratio spectra built upon a two-step derivatization of ratio spectra utilizing double-distilled water as a solvent. SAD was quantified at 247.2 nm and 257.0 nm, and ASC at 251.8 and 259.8 nm, while SAL was quantified at 305.6 nm. Technique (B) relied on ratio spectra for the mean centering analytical process applied via two sequential stages, where the amplitudes derived after the second ratio spectra of the mean centering have been recorded on 291.0, 266.0, and 241.0 nm for SAD, ASC, and SAL, in that order. Method (C) involved TLC densitometric analysis, in which the separation was carried out upon plates of silica gel with chloroform–hexane–methanol–acetone–formic acid (5:3:2:1:0.2, in volumes) as a mobile phase, monitored by densitometric detection at 240 nm. The linear relationships were observed over concentration ranges of (0.2–2 µg/band) for SAD with ASC and (0.1–1 µg/band) for SAL. Validation of the presented techniques was performed in accordance with ICH strategies. Results: These developed techniques have been effectively analyzed for SAD with ASC in pharmaceutical dosage forms with non-interfering ingredients. A statistical comparison with the previously used HPLC technique revealed no considerable difference in terms of accuracy and precision. Greenness assessment using the AGREE platform produced scores of 0.72 for the spectrophotometric approach (benefiting from aqueous solvent) and 0.62 for HPTLC (limited by chloroform). Practical applicability (BAGI = 80 for both spectrophotometry and HPTLC) and overall quality indices (CACI = 83 for spectrophotometry; 80 for HPTLC) supported routine QC suitability. Conclusions: The three developed stability-indicating methods are accurate, precise, and selective for simultaneous assay of SAD and ASC in the presence of SAL and are suitable for quality control use. The spectrophotometric procedures combine high analytical performance with an improved environmental profile, while HPTLC offers comparable analytical reliability with slightly lower greenness due to organic solvent use. Full article

Background/Objectives: Inflammatory and oxidative-stress-related processes contribute to post-myocardial infarction (MI) remodeling and may influence long-term cardiovascular outcomes. Recent findings have highlighted the potential role of non-coding RNAs in regulating these processes. LncRNA MALAT1 acts as a ceRNA that “sponges” miR-146a, reducing its ability to repress downstream targets such as COX-2. The aim of this study was to assess MALAT1 and miR-146a expression in PBMCs and plasma COX-2 in controls and patients six months post-MI. In addition, we investigated whether MALAT1 rs3200401 and miR-146a rs2910164 variants were associated with MI susceptibility, MALAT1 and miR-146a expression, plasma COX-2 levels, and left ventricle (LV) echocardiographic parameters. Methods: The study included 534 patients and 381 controls for genetic analyses, while expression analyses were performed in a subset of 89 patients and 39 controls. TaqMan™ assays were used for genotyping and for quantification of MALAT1 and miR-146a expression. Plasma COX-2 levels were measured using ELISA. Results: Compared to controls, patients had higher MALAT1 expression, whereas lower miR-146a expression was observed only in unadjusted analyses. Plasma COX-2 levels were higher in patients with advanced heart failure (NYHA III–IV) compared with NYHA I-II. The rs3200401 TT genotype was more frequent in patients, whereas rs2910164 genotype distributions were similar between groups. The rs3200401-rs2910164 TG allele combination was associated with increased MI risk. Conclusions: MALAT1 may serve as a potential long-term biomarker of post-MI molecular alterations, whereas the role of miR-146a requires further investigation in larger cohorts. The rs3200401 variant may represent a genetic marker associated with MI susceptibility and adverse LV remodeling. Further studies are needed for confirmation. Full article

The fractional Whitham–Broer–Kaup model governs nonlinear wave propagation in memory-dependent media, including porous structures, viscoelastic fluids, and irregular seabeds, yet the full dynamical spectrum from quasi-periodicity to deterministic chaos, the role of stochastic forcing, and reliable identification from noisy data remains insufficiently explored, particularly how the fractional order $\beta$ influences these regimes. This study addresses these gaps through a comprehensive, multi-method dynamical analysis of a representative nonlinear oscillator embodying key FWBK features. Three-dimensional attractor visualizations, return maps, and surrogate data tests demonstrate a transition from quasi-periodic toroidal attractors to fully developed chaos via torus breakdown, confirming that observed complexity originates from deterministic nonlinearity. Poincaré sections reveal multistability and KAM-type structures, where coexisting attractors depend on initial conditions, while increasing noise progressively disrupts coherent dynamics. The OGY control method effectively stabilizes unstable periodic orbits across chaotic regimes with minimal perturbation, and Lyapunov analysis indicates that stochastic forcing attenuates chaos while enhancing dissipation. The Fokker–Planck framework shows that noise reshapes probability landscapes, driving transitions from unimodal to bimodal distributions. Comparative analysis of SINDy, JMAP and VBA highlights trade-offs in interpretability, computational efficiency, and uncertainty quantification, while an integrated Bayesian–PCE–Sobol approach quantifies parametric uncertainty and reveals time-dependent sensitivity variations. Additionally, the overlapping of soliton solutions extracted via the enhanced modified Sardar sub-equation method reveals structural relationships among soliton families and their stability under interaction. Soliton branches that maintain high overlap under noise correspond to stable regimes, while those losing coherence indicate the onset of chaos. Furthermore, while the reduced dynamics in $\eta$-space are independent of $\beta$, the fractional order controls spatial compression and temporal scaling in physical coordinates, directly influencing observable wave localization. These results imply that fractional effects can modify chaos transitions, support controllability through OGY, and influence noise–instability interactions depending on $\beta$. This framework provides a robust, transferable methodology for analyzing and controlling nonlinear oscillatory systems under deterministic and stochastic conditions, with direct applications to FWBK-based models in coastal engineering, fiber optics, and quantum interference systems. Full article

Background/Objectives: Semaglutide, a long-acting glucagon-like peptide-1 (GLP-1) analog for type 2 diabetes and obesity, requires sensitive and high-throughput bioanalytical methods to support pharmacokinetic studies. However, previously reported liquid chromatography–tandem mass spectrometry (LC–MS/MS) assays have been limited by lengthy run times (~18 min) and suboptimal sensitivity. This study aimed to develop and validate a rapid, sensitive LC–MS/MS method for quantifying semaglutide in plasma. Methods: Plasma samples (50 μL) were prepared by acetone-mediated protein precipitation followed by solid-phase extraction. Chromatographic separation was performed on a Cadenza CD-C18 MF column within 9 min, using positive electrospray ionization in multiple reaction monitoring mode with the transitions m/z 1029.4 → 110.1 for semaglutide and m/z 938.9 → 109.9 for liraglutide (internal standard). Validation followed the U.S. Food and Drug Administration (FDA) bioanalytical guidelines. Results: The assay showed a lower limit of quantification of 1 ng/mL with linearity across 1–500 ng/mL (R² = 0.9999), with sharp peak shape and no carryover. Intra- and inter-day accuracies were 95.69–103.76% and 94.93–100.08%, with precision ≤4.50% and ≤5.88%. Recovery (93.05–107.95%) and matrix effects (96.34–104.12%) were consistent across quality control levels, and the analyte was stable under all tested conditions. The method was successfully applied to a pharmacokinetic study in Sprague–Dawley rats following subcutaneous administration of 50 μg semaglutide. Conclusions: The validated method offers shorter analysis time, improved sensitivity, and reduced sample volume compared with previously reported assays, supporting its application in preclinical pharmacokinetic studies of semaglutide and related GLP-1 analogs. Full article

Essential oils are natural products frequently subject to economically motivated adulteration with cheaper substances like vegetable oils, mineral oils, or organic solvents. This study developed and validated a rapid high-temperature gas chromatography with flame ionization detection (HTGC-FID) method for the simultaneous determination of high-boiling adulterants: triacylglycerides (vegetable oils) and medicinal white oil (mineral oil) in essential oils. The method utilizes on-column injection onto a DB-5 capillary column (30 m × 0.53 mm, 0.88 μm) with a temperature program from 60 to 380 °C and hydrogen carrier gas. Validation parameters demonstrated excellent linearity (R² = 0.9957–0.9978), high repeatability (content RSD < 3%), and sufficient sensitivity (LOQ of 0.03% for triacylglycerides, and 0.63% for medicinal white oil). The method was successfully applied to 20 commercial essential oils. While medicinal white oil was undetected, several samples contained triacylglycerides (up to 3.79%) and other adulterants (up to 52%). Significantly reduced response factors confirmed extensive adulteration in some products. The proposed HTGC-FID method represents a simple, cost-effective, and efficient tool for routine quality control, enabling direct quantification of high-boiling adulterants without tedious sample preparation. Full article

Oncolytic viruses represent a promising class of anticancer therapeutics, and rapid, accurate quantification of viral titers is critical for ensuring both efficacy and safety during clinical development. Conventional viral titering methods, such as 50% cell culture infectious dose (CCID₅₀), are time-consuming and limited in sensitivity, thereby restricting their application in real-time clinical monitoring. This study aimed to develop and validate a rapid titer assay for oHSV2-PD-L1/CD3-BsAb, an oncolytic herpes simplex virus expressing a PD-L1/CD3 bispecific antibody, to support preclinical and clinical monitoring. A dual-reporter cell system was established using Vero-PD-L1-GFP (Vero cells expressing PD-L1 and GFP) cells as target cells and Jurkat-NFAT-Fluc (Jurkat cells expressing NFAT and Fluc) cells as effector cells. Viral infection activates the NFAT signaling pathway, driving Fluc expression, thereby enabling rapid quantification of infectious virus. The assay was evaluated for specificity, limit of detection (LOD), and lower limit of quantification (LLOQ), and compared with the conventional CCID₅₀ method. Its applicability was further assessed using clinical simulation samples, including PBMCs and swabs. The rapid titer assay accurately quantified virus at 10³ CCID₅₀/mL after 8 h of incubation, consistent with CCID₅₀ results, while extending the incubation to 18 h improved the LLOQ to 10^2.5 CCID₅₀/mL, demonstrating enhanced sensitivity. The assay exhibited high reproducibility and stability in both PBMC and swab samples, enabling reliable quantification of low-titer virus in complex biological matrices. Compared with CCID₅₀, the method substantially reduced assay time (from 3–5 days to 8–18 h) while improving sensitivity and specificity. The developed rapid titer assay for oHSV2-PD-L1/CD3-BsAb provides a sensitive and specific platform for viral quantification. It offers a valuable tool for oncolytic virus development, production quality control, and clinical monitoring, facilitating efficient safety evaluation and risk management in ongoing and future clinical applications. Full article

As hen eggs are a primary source of high-quality dietary protein, egg freshness is fundamentally linked to biochemical alterations during storage, including moisture redistribution, protein degradation, and fluctuating chemical profiles. Accurate assessment of these internal changes is paramount for quality control; nonetheless, conventional analytical techniques remain predominantly destructive, rendering them impractical for high-throughput industrial monitoring. While existing literature has explored individual spectroscopic methods, the synergistic potential of multi-sensor integration and advanced artificial intelligence (AI) algorithms remains insufficiently synthesized. This review systematically evaluates recent breakthroughs in integrating AI with diverse spectroscopic modalities for non-destructive freshness quantification, including Visible-Near-Infrared (VIS-NIR), Raman, Fluorescence, and Hyperspectral Imaging (HSI). We elucidate the underlying mechanisms of spectral response to internal quality degradation and discuss the evolution of data-driven modeling from traditional chemometrics to sophisticated deep learning architectures. Furthermore, this work identifies critical bottlenecks in real-time industrial implementation and proposes future research trajectories toward intelligent multi-sensor fusion platforms. Full article

Multi-criteria group decision making (MCGDM) under linguistic uncertainty remains a fundamental challenge in applied mathematics, where decision makers seldom assign crisp numerical evaluations and frequently exhibit heterogeneous risk attitudes shaped by behavioural factors. An integrated mathematical framework, hereafter PLR-3WBC (Probabilistic Linguistic Regret-driven Three-Way Bayesian Consensus), is developed to systematically integrate four methodological components that have each been individually validated in the MCGDM literature: representation of decision information with explicit probability mass on linguistic terms; quantification of decision-maker regret and rejoice psychology under linguistic uncertainty; classification of alternatives into three actionable decision regions rather than a single-valued ranking; and group consensus reaching with credal weight aggregation. Each component has demonstrated its effectiveness in its respective domain; the present framework capitalises on their complementary strengths by embedding them within a single pipeline equipped with formal guarantees, an integration that has not been previously reported. The framework integrates five methodological components: probabilistic linguistic term sets (PLTS) for information representation; the Bayesian best–worst method (BBWM) for credal criterion weighting; a regret–rejoice value function adapted to the linguistic domain for behavioural evaluation; three-way decision (3WD) thresholds derived from a loss-function model for actionable classification; and a distance-based consensus reaching process with feedback mechanism for group convergence. A case study on age-friendliness evaluation of twelve aging urban residential communities under an indicator system of five dimensions and eighteen criteria, with four expert decision makers, demonstrates that PLR-3WBC delivers an actionable three-way classification, recovers a transparent group consensus, and produces rankings broadly consistent with classical TOPSIS, VIKOR, PROMETHEE-II, and BWM-TOPSIS (Spearman rank correlation exceeding 0.97), thereby confirming that the integrated framework preserves the ordinal reliability of these established methods, while additionally delivering three outputs that arise from the methodological integration: an actionable three-way classification enabling discrete budget-aligned decisions, credal weight intervals quantifying the depth of expert agreement on criterion importance, and a behavioural reordering of borderline non-dominated alternatives that reflects the loss-averse psychology of the decision panel and would remain hidden under single-method deployment. Sensitivity analyses with respect to the regret aversion coefficient, the loss function parameters, and the consensus threshold confirm that the qualitative classification is stable across a wide parameter envelope, supporting the practical deployment of PLR-3WBC in age-friendly community renewal programmes. Full article

Human digital twins (HDTs) are patient-specific computational models that combine medical imaging, physiological measurements and predictive algorithms. They are moving from an exciting concept to a realistic clinical opportunity. The key question is no longer whether HDTs can be built. The key question is which methods are mature enough to support clinical decisions and what is still missing for routine use. This systematic review maps the methodological landscape of HDTs and highlights practical bottlenecks that limit clinical translation. A PRISMA 2020 guided search of PubMed, Scopus, IEEE Xplore, and the Cochrane Library, covering publications from 2016 to 2026, identified 151 eligible studies. Bibliometric mapping and thematic synthesis were used to characterize research clusters, computational paradigms, and collaboration patterns. Three dominant application streams were identified: cardiovascular HDTs for hemodynamic simulation and procedural planning, musculoskeletal HDTs for biomechanics-driven orthopedic innovation, and neurological HDTs integrating neuroimaging with computational neuroscience. Across domains, the strongest technical trend is the rise in hybrid pipelines that combine physics-based simulation, including finite element and computational fluid dynamics models, with machine learning for segmentation, parameter identification, reduced-order modeling, and faster inference. However, reporting of verification, validation, uncertainty quantification, and explicit context of use remains uneven and prospective clinical evidence is still limited. Overall, the literature shows rapid progress toward clinically credible HDTs, while highlighting the need for scalable computation, standardized credibility pipelines, and workflow-integrated platforms to support safe and reproducible clinical adoption. Full article

Background/Objectives: Bile acid synthesis disorders (BASDs) represent a distinct category of progressive familiar cholestatic liver disease. A novel targeted mass spectrometry assay was developed for the accurate measurement of the major urinary atypical bile acids and bile alcohols that are biomarkers for HSD3B7, AKR1D1, CYP7B1 and CYP27A1 deficiencies, the four most common BASDs. Methods: Stable-isotope dilution UPLC tandem mass spectrometry was used for the simultaneous quantification of 12 key atypical bile acid biomarkers in urine from patients with BASD. Typical concentration ranges for these metabolites were established from urine samples from patients with biochemically and/or genetically confirmed BASD and compared with non-cholestatic and cholestatic controls. Results: The separation of major 3β-hydroxy-Δ⁵-bile acid sulfates, taurine- and glycine-conjugated 3-oxo-Δ⁴-bile acids, and bile alcohol glucuronides was achieved in a 20 min chromatographic run with intra- and inter-batch imprecisions of <15% for all metabolites. The mean ± SEM urinary concentration of total 3β-sulfated-Δ⁵-cholenoic acids in patients with HSD3B7 deficiency was 704 ± 204 µmol/L (n = 22), approximately 2000-fold higher than in cholestastic patients (n = 168) or non-cholestatic controls (n = 127). Similarly, the concentration of 5β-cholestane-3α,7α,12α,24,25-pentol-glucuronide, the major bile alcohol, in patients with CYP27A1 deficiency was 95 ± 17 µmol/L (n = 12). For CYP7B1 deficiency, two confirmed cases showed elevated levels (average, 7.5 µmol/L) of the glycine conjugate of 3β-sulfooxy-Δ⁵-bile acid. In AKR1D1 deficiency, total 3-oxo-Δ⁴-bile acids in urine were elevated (81 ± 16 µmol/L, n = 48), but concentrations showed overlap with cholestatic and non-cholestatic controls. Conclusions: A novel quantitative tandem mass spectrometry assay is described for the measurement of the major atypical metabolites and biomarkers in urine applicable to the accurate monitoring of treatment responses, and for the first time typical concentration ranges are established for each of these BASDs. Full article

Tire and road wear particles (TRWPs) are major sources of non-exhaust traffic emissions. However, a limited understanding of their generation mechanisms and the lack of efficient collection methods under realistic driving conditions hinder accurate assessment. This study addresses these challenges by developing a vehicle-based methodology for the controlled recovery and characterization of TRWPs in the near-field region, rather than for direct quantification of real-world emissions. An autonomous electric vehicle was employed to ensure stable driving conditions and eliminate exhaust interference. Near-field distribution of TRWPs was visualized using a high-sensitivity optical scattering system. Based on this, a sealed tire enclosure with a high-power on-vehicle vacuum collection system was designed to enhance particle containment and recovery. Controlled circular driving tests were conducted on a dedicated outdoor test track under well-defined and repeatable conditions to enable system-level evaluation of TRWP generation and collection relative to measured tire wear. Particles were analyzed by thermogravimetric analysis, microscopy, scanning electron microscopy–energy-dispersive X-ray spectroscopy, and particle imaging. The results demonstrated stable, reproducible TRWP generation with ~60% collection efficiency relative to tire mass loss. These values are reported as system-dependent recovery indicators rather than precise emission estimates. Additional tests with an expanded recovery protocol indicated that collection efficiency can increase to ~81% (range: 73–91%), highlighting the influence of collection coverage. The collected TRWPs exhibited heterogeneous morphology, bimodal size distribution, and a mixed rubber–mineral composition in the 10–100 μm range. Spatial analysis revealed that TRWPs predominantly accumulated within a narrow zone around the driving lane. While the controlled experimental configuration enables reproducible particle generation and high-efficiency recovery, it represents a simplified driving scenario and may not fully capture the variability of real-world traffic conditions, including straight-line driving and transient maneuvers. Overall, this study demonstrates a technical framework for reproducible and comparative recovery of tire-associated particles under identical, well-defined conditions. The approach is intended to support controlled characterization studies while explicitly acknowledging limitations related to representativeness, particle origin attribution, and quantitative emission relevance, rather than to establish emission factors or mechanistic descriptions of TRWP generation. Full article

Qualitative and quantitative analysis of complex mixtures and structure elucidation is generally impeded by the intrinsic complexity of the NMR spectra and the extensive signal overlap. The conventional approach to characterizing individual metabolites from complex crude extracts of natural products relies on multistep separation workflows employing diverse liquid chromatographic approaches and/or hyphenated techniques, which combine online integration of NMR with separation methods and other forms of spectroscopy. In recent decades, considerable efforts have been devoted to NMR applications in crude extracts without previous separation and isolation of the individual analytes. We present herein a critical overview of several NMR applications using chemical shift ranges of common organic functional groups, which can provide significant resolution advantages under specific experimental conditions. Particular emphasis is placed on: (i) characteristic chemical shift regions of strongly deshielded phenol OH groups, aldehyde CHO groups, hydroperoxide C-O-O-H groups and olefinic protons in conjugated double bonds; (ii) the advantages of using ¹³C chemical shift ranges through 2D ¹H-¹³C HSQC and HMBC experiments of strongly deshielded phenol OH groups, aldehyde CHO groups, hydroperoxide groups, conjugated double bonds, and deshielded aliphatic CH groups; (iii) selective 1D NMR-spin chromatography techniques (1D TOCSY, 1D NOE); (iv) multiple suppression of strong resonances for minor analyte identification and (v) band-selective excitation techniques for minor analyte identification and quantification. The complementary contributions of statistical heterospectroscopy and computational chemical shift prediction are also considered, together with a brief assessment of the NMR experimental parameters and performance characteristics. Full article