Search Results (33,851)

Surface plasmon resonance (SPR) sensors based on photonic crystal fibers (PCFs) hold significant promise for high-precision detection in biochemical and chemical sensing. However, achieving high sensitivity in low-refractive-index (RI) aqueous environments remains a formidable challenge due to weak light-matter interactions. To address this limitation, this paper designs and proposes a novel dual-channel D-shaped PCF-SPR sensor tailored for the refractive index range of 1.34–1.40. The sensor incorporates a dual-layer gold/titanium dioxide film, with gold nanoparticles deposited on the surface to synergistically enhance both propagating and localized surface plasmon resonance effects. Furthermore, a D-shaped polished structure integrated with double-sided microfluidic channels is employed to significantly strengthen the interaction between the guided-mode electric field and the analyte. Finite element method simulations demonstrate that the proposed sensor achieves an average wavelength sensitivity of 5733 nm/RIU and a peak sensitivity of 15,500 nm/RIU at a refractive index of 1.40. Notably, the introduction of gold nanoparticles contributes to an approximately 1.47-fold sensitivity enhancement over conventional structures. This work validates the efficacy of hybrid plasmonic nanostructures and optimized waveguide design in advancing RI sensing performance. Full article

Sodium-pumping NADH: ubiquinone oxidoreductase (Na⁺-NQR) is an important component of the aerobic respiratory chain of Vibrio cholerae. It oxidizes NADH, reduces ubiquinone, and uses the free energy of this redox reaction to move sodium across the cell membrane. The enzyme is a membrane complex of six subunits, two 2Fe−2S centers, and four flavins. Both the oxidized and reduced forms of Na⁺-NQR exhibit EPR signals due to flavin semiquinone radicals. It has been shown that in the oxidized form of the enzyme, the radical is a neutral flavin, while in the NADH-reduced form, the radical is an anionic flavin. Electron Spin Echo Envelope Modulation Spectroscopy (ESEEM) was used to probe the presence of the magnetic nucleus ²³Na in the immediate vicinity of the paramagnetic centers. The contribution of the ²³Na nucleus was observed only in the ESEEM spectra of the anionic flavin semiquinone previously assigned to FMN_NqrB. Analysis shows that the Na⁺ ion is within ~3–4 Å of the flavin radical. This distance is consistent with two models: (i) complexation of the Na⁺ ion with the carbonyl group of CO4; or alternatively, (ii) a “cation-π interaction,” between Na⁺ and the electron-rich π-system of the flavin aromatic rings. Full article

Background: Approximately 20–30% of ultra-high risk (UHR) individuals transition to psychosis within 2–3 years. Neurobiological markers predicting conversion remain critical for precision prevention strategies. Objective: To systematically identify and evaluate structural and functional neuroimaging biomarkers at UHR baseline that predict subsequent conversion to psychosis. Methods: Following PRISMA 2020 guidelines, we searched five databases from January 2000 to February 2025. Two independent reviewers screened studies and assessed quality using the Newcastle–Ottawa Scale. Eligible studies examined baseline neuroimaging measures (structural MRI, functional MRI, diffusion tensor imaging, magnetic resonance spectroscopy) as predictors of psychosis conversion in UHR cohorts. Results: Twenty-five studies comprising 2436 UHR individuals (627 converters, 25.7%) were included (80.0% high quality). Reduced baseline gray matter volume in medial temporal structures (hippocampus: Cohen’s d = −0.45 to −0.68; parahippocampal gyrus: d = −0.52 to −0.71) and prefrontal cortex (d = −0.41 to −0.68) consistently predicted conversion. Progressive gray matter loss in superior temporal gyrus distinguished converters (d = −0.72). Reduced prefrontal–temporal functional connectivity predicted conversion (AUC = 0.73–0.82). Compromised white matter integrity in uncinate fasciculus (fractional anisotropy: d = −0.47 to −0.71) and superior longitudinal fasciculus predicted transition. Elevated striatal glutamate predicted conversion (d = 0.52–0.76). Thalamocortical dysconnectivity showed large effects (Hedges’ g = 0.66–0.88). Multimodal imaging models achieved 78–85% classification accuracy. Conclusions: Neuroimaging biomarkers, particularly medial temporal and prefrontal structural alterations, functional dysconnectivity, and white matter abnormalities, demonstrate moderate-to-large effect sizes in predicting UHR conversion. Multimodal approaches combining structural, functional, and neurochemical measures show promise for individualized risk prediction and early intervention targeting in precision prevention strategies. Full article

Determining RNA secondary structures is a fundamental challenge in computational biology and molecular sensing. Experimental techniques such as X-ray crystallography, nuclear magnetic resonance, and cryo-electron microscopy can reveal RNA structures with atomic precision, but their high cost and time consuming nature limit large-scale applications. To address this issue, we introduce the Structure-Sensing Nucleotide Attention Learning framework (NTFold), a virtual sensing framework based on deep learning for accurate RNA secondary structure prediction. NTFold integrates a Nucleotide Attention Module (NAM) to explicitly model dependencies among nucleotides, thereby capturing fine-grained sequence correlations. The resulting correlation map is subsequently refined by a Structural Refinement Module (SRM), which preserves hierarchical spatial information and enforces structural consistency. Through this two stage learning paradigm, NTFold produces high-precision contact maps that enable reliable RNA secondary structure reconstruction. Extensive experiments demonstrate that NTFold outperforms existing deep learning-based predictors, highlighting its capability to learn both local and global nucleotide interactions in an sensor inspired manner. This study provides a new direction for integrating attention driven correlation modeling with structure-sensing refinement toward efficient and scalable RNA structural sensing. Full article

This article presents a systematic review on methods for quantifying three-dimensional, time-resolved (3D+t) deformation and motion of human arteries from Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched Scopus, Web of Science, IEEE Xplore, Google Scholar, and PubMed on 19 December 2025 for in vivo, patient-specific CT or MRI studies reporting motion or deformation of large human arteries. We included studies that quantified arterial deformation or motion tracking and excluded non-vascular tissues, in vitro or purely computational work. Thirty-five studies were included in the qualitative synthesis; most were small, single-centre observational cohorts. Articles were analysed qualitatively, and results were synthesised narratively. Across the 35 studies, the most common segmentation approaches are active contours and threshold, while temporal motion is tracked using either voxel registration or surface methods. These kinematic data are used to compute metrics such as circumferential and longitudinal strain, distensibility, and curvature. Several studies also employ inverse methods to estimate wall stiffness. The findings consistently show that arterial strain decreases with age (on the order of 20% per decade in some cases) and in the presence of disease, that stiffness correlates with geometric remodelling, and that deformation is spatially heterogeneous. However, insufficient data prevents meaningful comparison across methods. Full article

Background: Trypanosoma cruzi, the causative agent of Chagas disease, remains a major public health concern, and there is a continued need for new antitrypanosomal agents. Thiosemicarbazone (TSC) derivatives have emerged as a promising class of compounds with potential antiparasitic activity. Objectives: This study aimed to report the synthesis, characterization, and biological profiling of a novel series of thiosemicarbazone derivatives as antitrypanosomal agents against Trypanosoma cruzi. Methods: Fourteen new compounds and six previously described analogues were prepared and characterized by ¹H/¹³C nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS). As a preliminary in vitro screen, activity was assessed by direct parasite counting in epimastigote and bloodstream trypomastigote forms, as tractable models of replicative and infective stages sharing core metabolic targets with intracellular amastigotes. Epimastigote potency was quantified as half-maximal effective concentrations (EC₅₀) derived from dose–response curves, whereas trypomastigote response was evaluated as percent viability after treatment at a fixed concentration of 20 µM. Mechanistic profiling included inhibition assays against the cysteine protease cruzipain (CZP) and selected redox defense enzymes, complemented by in silico similarity clustering and binding-pose affinity scoring. Results: A nitro-methoxy-substituted TSC showed potent CZP inhibition but limited trypomastigote efficacy, whereas brominated analogues displayed dual-stage activity independent of CZP inhibition. Tanimoto similarity analysis identified distinct structure–activity clusters, linking nitro-methoxy substitution to epimastigote selectivity and brominated scaffolds to broader antiparasitic profiles, with hydrophobicity and steric complementarity as key determinants. Enzymatic assays revealed no significant inhibition of cytosolic tryparedoxin peroxidase (cTXNPx) or glutathione peroxidase type I (TcGPx-I), suggesting redox disruption is not a primary mode of action. In vitro and in silico analyses showed low or no non-specific cytotoxicity under the tested conditions, supporting further optimization of these derivatives as antitrypanosomal preliminary hits. Key hits included derivative 3e (epimastigote EC₅₀ = 0.36 ± 0.02 µM) and brominated analogues 2c and 2e (epimastigote EC₅₀ = 3.92 ± 0.13 and 4.36 ± 0.10 µM, respectively), while docking supported favorable binding-pose affinity (e.g., ΔG_S-pose = −20.78 ± 2.47 kcal/mol for 3e). Conclusions: These results support further optimization of the identified thiosemicarbazone derivatives as preliminary antitrypanosomal hits and provide insight into structure–activity relationships and potential mechanisms of action. Full article

In the eddy current testing (ECT) of magnetized ferromagnetic pipelines, permeability perturbations near defects cause magnetic distortion that primarily modulates the imaginary part of the ECT sensor’s impedance, leading to confusion between inner and outer wall defect signals. To address this interference, this study thoroughly analyzes the modulation mechanism of permeability changes on impedance and investigates the feasibility of detecting solely the real part to enhance discrimination reliability. This understanding leads to the proposal of a solution employing an LC resonant circuit, capitalizing on its characteristic of zero imaginary part impedance at the resonant frequency, to effectively suppress the permeability-related signal interference. Experimental results demonstrate the effectiveness of the proposed approach: the magnetization response test confirms the insensitivity of the LC sensor to permeability perturbations, and the defect discrimination experiment shows that the sensor achieves a standard deviation ratio of 2.25 and a peak-to-peak ratio of 4.42 between inner and outer wall defect signals. The findings indicate that the LC resonant sensor can reliably distinguish between inner and outer wall defects through simple amplitude thresholding, thereby improving the reliability of inspections for magnetized pipelines in industrial applications. Full article

Cardiac magnetic resonance (CMR) imaging has been considered crucial in non-ischemic cardiomyopathy (NICM). This study aims to evaluate the role of CMR in identifying risk factors for life-threatening events in patients with NICM and reduced left ventricular ejection fraction (LVEF). Methods: We analysed 57 (mean age 62.5 ± 11.4 years, 68.4% male) first-diagnosed NICM patients with reduced LVEF (mean 42 ± 9%). CMR assessments evaluated LVEF, right ventricular ejection fraction (RVEF), cardiac T1 mapping, extracellular volume (ECV), and the presence/extension of late gadolinium enhancement (LGE). Patients were monitored for a composite endpoint including sudden cardiac death (SCD), major ventricular arrhythmic events, and hospitalization for heart failure (HHF). Results During a median follow-up lasting 543 days, 18 patients (31%) experienced cardiovascular events. A higher native T1 mapping value (1076 (1025–1120) ms vs. 999 (990–1037) ms, p < 0.001), a higher ECV (34 ± 6% vs. 28 ± 4,% p < 0.001) and a reduced RVEF (52 ± 13% vs. 60 ± 9%, p < 0.03) proved to be significantly correlated to an increased HHF, arrhythmic and SCD risk. Additionally, a native T1 mapping value exceeding 1018 ms demonstrated an increased risk (HR: 6.285; 95% CI: 2.044–19.326, p = 0.001) as well as an ECV greater than 28% (HR: 19.752; 95% CI: 2.622–148.817, p = 0.004) for composite endpoint. Conclusion In NICM patients, elevated native T1 mapping and ECV values identified a high-risk subgroup for arrhythmic events while LVEF, and RVEF provide further risk stratification for the composite endpoint. CMR assessment may optimize risk stratification in NICM patients. Full article

Brain magnetic resonance imaging (MRI) is highly susceptible to motion artifacts that degrade fine structural details and undermine quantitative analysis. Conventional U-Net-based deep learning approaches for motion artifact reduction typically operate only in the image domain and are often trained on data with simplified motion patterns, thereby limiting physical plausibility and generalization. We propose Sim-DDNet, a simulation-data-based dual-domain network that combines k-space-based motion simulation with a joint image-k-space reconstruction architecture. Motion-corrupted data were generated from T2-weighted Alzheimer’s Disease Neuroimaging Initiative brain MR scans using a k-space replacement scheme with three to five random rotational and translational events per volume, yielding 69,283 paired samples (49,852/6969/12,462 for training/validation/testing). Sim-DDNet integrates a real-valued U-Net-like image branch and a complex-valued k-space branch using cross attention, FiLM-based feature modulation, soft data consistency, and composite loss comprising L1, structural similarity index measure (SSIM), perceptual, and k-space-weighted terms. On the independent test set, Sim-DDNet achieved a peak signal-to-noise ratio of 31.05 dB, SSIM of 0.85, and gradient magnitude similarity deviation of 0.077, consistently outperforming U-Net and U-Net++ across all three metrics while producing less blurring, fewer residual ghost/streak artifacts, and reduced hallucination of non-existent structures. These results indicate that dual-domain, data-consistency-aware learning, which explicitly exploits k-space information, is a promising approach for physically plausible motion artifact correction in brain MRI. Full article

We employ the Dynamical Projective Operatorial Approach (DPOA) to investigate the ultrafast optical excitations of germanium under intense, ultrashort pump pulses. The method has very low resource demand relative to many other available approaches and enables detailed calculation of the residual electron and hole populations induced by the pump pulse. It provides direct access to the energy distribution of excited carriers and to the total energy transferred to the system. By decomposing the response into contributions from different multi-photon resonant processes, we systematically study the dependence of excited-carrier density and absorbed energy on key pump-pulse parameters: duration, amplitude, and photon energy. Our results reveal a complex interplay between these parameters, governed by resonant Rabi-like dynamics and competition between different multi-photon absorption channels. For the studied germanium setup, we find that two-photon processes are generally dominant, while one- and three-photon channels become significant under specific conditions of pump-pulse frequency, duration, and intensity. This comprehensive analysis offers practical insights for optimizing ultrafast optical control in semiconductors by targeting specific multi-photon pathways. Full article

Plastic pollution raises concerns for health and the environment. Plastics are not biodegradable but gradually erode to microplastic and nanoplastic particles spreading almost everywhere. Nanoplastics exhibit colloidal behavior. Thereby, their analysis can be accomplished by refractometry, preferably by an on-chip tool. We present a study of such colloids using a microfabricated Fabry–Pérot cavity with curved mirrors, which holds a capillary micro-tube used both for fluid handling and light collimation, resulting in an optically stable microresonator. Despite the numerous scatterers within the sample, the sub-millimeter scale cavity provides the advantages of reduced interaction length while maintaining light confinement. This significantly reduces optical loss and hence keeps resonance modes with quality factors (resonant frequency/bandwidth) above 1100. Therefore, small quantities of colloids can be measured by the interference spectral response through the shift in resonant wavelengths. The particles’ Brownian motion potentially causing perturbations in the spectra can be overcome either by post-measurement cross-correlation analysis or by avoiding it entirely by taking the measurements at once by a wideband source and a spectrum analyzer. The effective refractive index of solutions with solid contents down to 0.34% could be determined with good agreement with theoretical predictions. Even lower detection capabilities might be attained by slightly altering the technique to cause particle aggregation achieved solely by light. Full article

Inspired by the well-known experimental connections between $X\left(3872\right)$, $Z_{cs}\left(4220\right)$, and $Y\left(4620\right)$, we systematically study the recently reported strange partner of $T_{cc}$, the $1^{+}$$cc\overline{q}\overline{s}$ system, and its orbital excitation state $1^{-}$$cc\overline{q}\overline{s}$. A chiral quark model incorporating SU(3) symmetry is considered to study these two systems. To better investigate their spatial structure, we introduce a precise few-body calculation method, the Gaussian Expansion Method (GEM). In our calculations, we include all possible physical channels, including molecular states and diquark structures, and consider channel coupling effects. To identify the stable structures in the system (bound states and resonance states) we employ a powerful resonance search method, the Real-Scaling Method (RSM). According to our results, in the $1^{+}$$cc\overline{q}\overline{s}$ system, we obtain two bound states with energies of 3890 MeV and 3940 MeV, as well as two resonance states with energies of 3975 MeV and 4090 MeV. The decay channels of these two resonance states are $D{D}_s^{\ast }$ and $D^{\ast }{D}_s$, respectively. In the $1^{-}$$cc\overline{q}\overline{s}$ system, we obtain only one resonance state, with an energy of 4570 MeV, and two main decay channels: $D{D}_{s1}^{\ast }$ and $D^{\ast }{D}_{s1}^{\prime }$. We strongly suggest that experimental groups use our predictions to search for these stable structures. Full article

Gliomas are a significant health problem with a lot of imaging challenges. The role of imaging is no longer limited to only providing anatomic details, but with the advancement of Magnetic Resonance Imaging (MRI) techniques, it now permits the assessment of the freedom of water molecule movement, the microvascular structure, the hemodynamic characteristics, and the chemical makeup of certain metabolites of lesions. These advanced imaging techniques include diffusion-weighted imaging, diffusion tensor imaging, dynamic contrast-enhanced MRI, Magnetic Resonance (MR) perfusion, MR angiography, and magnetic resonance spectroscopy. their role in the diagnosis, classification, and post-treatment follow-up of gliomas, as well as their application in radiogenomics and glioma analysis with the aid of artificial intelligence, is presented and discussed. Full article

Background/Objectives: Trace metals, including copper (Cu) and zinc, are associated with the development and prognosis of hepatocellular carcinoma (HCC). However, their interference with magnetic resonance imaging (MRI) limits their use as potential biomarkers. This study investigated the usefulness of Synchrotron Radiation–excited X-ray Fluorescence (SR-XRF) imaging in studying the distribution of trace metals in HCC. Methods: This case–control study analyzed 33 specimens from 32 patients with HCC who underwent surgical resection (n = 29) or biopsy (n = 3) at Kobe University Hospital between December 1999 and November 2002. The findings of SR-XRF were compared with those of MRI and histopathology. Results: SR-XRF provided two-dimensional mapping of trace metal distribution with high spatial resolution (1.0 µm). The mean tumor-to-liver ratio (TLR) of Cu content was significantly higher in well-differentiated HCCs than in moderately and poorly differentiated HCCs (p < 0.05). Moreover, the mean TLRs of Cu content were significantly higher in high-intensity lesions than in iso- or low-intensity lesions on T1-weighted imaging (p < 0.05). Conclusions: This study supports previous evidence of the involvement of Cu in HCC development, suggesting its potential as a clinical biomarker for diagnosis and disease progression. Additionally, the results demonstrate that SR-XRF has potential for clinical application due to its ability to map trace metal distribution at high resolution. These findings suggest, rather than demonstrate, the association among Cu accumulation, tumor differentiation, and MRI signal characteristics. Full article

Background: Differentiating hypophysitis from non-functioning pituitary macroadenomas (NFPMA) remains a clinical and radiological challenge. Both entities present as sellar masses with overlapping features but require distinct therapeutic approaches. Accurate preoperative identification is necessary to avoid unnecessary surgery in inflammatory forms. This review aims to compare the clinical, endocrine, and imaging characteristics of hypophysitis and NFPMA, incorporating recent findings and evaluating the performance of three diagnostic scoring systems currently in use. Methods: A comprehensive narrative literature review was conducted using original articles, clinical series, radiological studies, and systematic reviews retrieved from international databases. The analysis focused on demographic characteristics, clinical presentation, hormonal profiles, magnetic resonance imaging (MRI) features, and the comparative evaluation of the three published diagnostic scoring systems designed to differentiate hypophysitis from NFPMA. Results: Hypophysitis predominantly affects women, particularly during late pregnancy or the postpartum period, and is frequently associated with autoimmune diseases. Corticotropic deficiency and central diabetes insipidus (CDI) are disproportionately frequent in hypophysitis, whereas somatotropic deficiency is more characteristic of NFPMA. Radiologically, hypophysitis typically appears as a smaller, symmetric, and homogeneous mass with intense, uniform contrast enhancement, associated with pituitary stalk thickening and loss of the posterior pituitary bright spot. In contrast, NFPMA generally present as larger, asymmetric, and heterogeneous lesions, frequently invading the cavernous sinus and compressing the optic chiasm. Analysis of the three diagnostic scores indicates that combining clinical, hormonal, and imaging data improves accuracy compared to relying on single features. The most recent score includes hormonal markers, which significantly enhance sensitivity and specificity, emphasizing the importance of integrated assessment. Conclusions: No single clinical, hormonal, or imaging feature is pathognomonic. However, integrating clinical context, endocrine profile, imaging characteristics, and validated diagnostic scores significantly enhances preoperative diagnostic accuracy. The systematic use of composite scores may help optimize therapeutic decision-making and reduce unnecessary surgical interventions in patients with hypophysitis. Full article