High-resolution Detection Research Articles

Label-free 3D optical angiography via time-frequency domain analysis of focal modulated dynamic blood flow

Accurate three-dimensional (3D) blood flow imaging with high spatiotemporal resolution and significant detection depth is essential for studying vascular structure-related diseases. In this Letter, we introduce a label-free 3D optical angiography technique via time-frequency domain analysis (TFDA) of focal modulated dynamic blood flow. First, a low-magnification telecentric lens is used for sparse axial sampling within a large depth-of-field range to obtain a coarse estimate of vascular depth. Then, based on the frequency-depth characteristics of dynamic blood flow signals, a TFDA-based focusing evaluation function is established in combination with Lambert–Beer's law, achieving a mean absolute percentage error of 2.06%. Finally, validation on a 3-day-old chicken embryo demonstrated a lateral spatial resolution of 2.95 μm and imaging time of 11.5 s for a 4.95 × 4.95 × 0.7 mm3 sample. Our method provides effective blood flow depth localization by assessing focal modulation intensity relative to focal plane and blood flow position, offering promising support for vascular disease research.

Identification of α-galactosylceramide as an endogenous mammalian antigen for iNKT cells.

Invariant natural killer T (iNKT) cells are unconventional T cells recognizing lipid antigens in a CD1d-restricted manner. Among these lipid antigens, α-galactosylceramide (α-GalCer), which was originally identified in marine sponges, is the most potent antigen. Although the presence of α-anomeric hexosylceramide and microbiota-derived branched α-GalCer is reported, antigenic α-GalCer has not been identified in mammals. Here, we developed a high-resolution separation and detection system, supercritical fluid chromatography tandem mass spectrometry (SFC/MS/MS), that can discriminate hexosylceramide diastereomers (α-GalCer, α-GlcCer, β-GalCer, or β-GlcCer). The B16 melanoma tumor cell line does not activate iNKT cells; however, ectopic expression of CD1d was sufficient to activate iNKT cells without adding antigens. B16 melanoma was unlikely to generate iNKT cell antigens; instead, antigen activity was detected in cell culture serum. Activity-based purification and SFC/MS/MS identified dihydrosphingosine-based saturated α-GalCer as an antigenic component in serum, bile, and lymphoid tissues. These results show the first evidence for the presence of potent antigenic α-GalCer in mammals.

Comparison of Single Atoms vs. Sub-Nanoclusters as Co-Catalysts in Perovskites and Metal Oxides for Photocatalytic Technologies

Adatoms as co-catalysts may play a key role in photocatalysis, yet control of their exact configuration remains challenging. Specifically, there is converging evidence that ultra-small structures may be optimal as co-catalysts; however, a comprehensive distinction between single atoms (SAs), sub-nanoclusters (SNCs), and quantum-sized small particles (QSSPs) has yet to be established. Herein, we present a critical review addressing these distinctions, along with challenges related to the controlled synthesis of SAs, SNCs, and QSSPs; their detection methods; and their functional benefits in photocatalysis. Our discussion focuses on perovskite oxides (e.g., such as ABO3, where A and B are cations) and metal oxides (MxOy, where M is a metal) decorated with adatoms, which demonstrate superior photocatalytic performance compared to their unmodified counterparts. Finally, we highlight cases of misinterpretation between SA, SNC, and QSSP configurations emerging from limitations in high-resolution detection techniques and synthesis methods.

Nanopore-Based High Resolution Detection of Multiple Post-Translational Modifications in Proteins.

Protein post-translational modifications (PTMs) play crucial roles in various cellular processes. Despite their significance, only a few PTMs have been extensively studied at the proteome level, primarily due to the scarcity of reliable, convenient, and low-cost sensing methods. Here, we present a straightforward and effective strategy for detecting PTMs on short peptides through host-guest interaction-assisted nanopore sensing. Our results demonstrate that the identity of 13 types of PTMs in a specific position of a phenylalanine-containing peptide could be determined via current blockage during translocation of the peptide through α-hemolysin nanopores in the presence of cucurbit[7]uril. Furthermore, we extend this strategy by incorporating a short peptide into the probe, enabling the discrimination of various PTMs, positional isomers, and even multiple PTMs on the target peptide. With ongoing improvements, our method holds promise for practical applications in sensing PTMs in biologically relevant samples, offering an efficient alternative to traditional mass spectrometry approaches.

Nanopore‐Based High Resolution Detection of Multiple Post‐Translational Modifications in Proteins

Protein post‐translational modifications (PTMs) play crucial roles in various cellular processes. Despite their significance, only a few PTMs have been extensively studied at the proteome level, primarily due to the scarcity of reliable, convenient, and low‐cost sensing methods. Here, we present a straightforward and effective strategy for detecting PTMs on short peptides through host‐guest interaction‐assisted nanopore sensing. Our results demonstrate that the identity of 13 types of PTMs in a specific position of a phenylalanine‐containing peptide could be determined via current blockage during translocation of the peptide through α‐hemolysin nanopores in the presence of cucurbit[7]uril. Furthermore, we extend this strategy by incorporating a short peptide into the probe, enabling the discrimination of various PTMs, positional isomers, and even multiple PTMs on the target peptide. With ongoing improvements, our method holds promise for practical applications in sensing PTMs in biologically relevant samples, offering an efficient alternative to traditional mass spectrometry approaches.

Design and analysis of optical devices with ultra-high quality factor based on a plasmonic photonic hybrid structure

Abstract In the present paper, the design of a tunable, high transmitting, and optical ultra-narrow band-pass filter using a plasmonic-photonic hybrid structure comprised of a multilayer stack of dielectrics and a thin sheet of silver is proposed. This current design can create more energy coupling, thus having a higher transmission peak in comparison to prior studies. To obtain a filtering operation, two different topologies are designed to achieve better performance specifications. The materials used in the structure include silicon, silicon-dioxide, and silver. The Drude model is employed for the silver. It has been shown that the geometrical parameters are sensitive to choose such that transmission properties and resonance wavelengths are arbitrarily tunable. The structure's design enables a single-mode as well as a multi-mode spectrum for each topology. We have achieved a maximum quality factor of 432.87 with an ultra-small full-width-at-half-maximum bandwidth of 1.43 nm, while the maximum transmission values are greater than 75%. Most of the various advantages include adjustability, high detection resolution, and integration at the nanoscale for optical applications owing to the basic merits of the hybrid structures of plasmonic and photonic crystals.

Electrocardiography with high resolution and digital processing for the non-invasive detection of low amplitude potentials

Cardiovascular diseases represent the primary cause of mortality in contemporary society. However, the majority of these conditions can be effectively diagnosed at an early stage through the use of Electrocardiography (ECG). ECG with high resolution, recorded from the body’s surface, has the capability to detect subtle intracardiac potentials with low amplitude, thereby reducing the need for invasive diagnostic procedures. Enhanced resolution in ECG acquisition enables the generation of more detailed signals, which increases the potential for identifying additional features compared to conventional methods. This study introduces a platform employing a 24-bit analog-to-digital converter for real-time acquisition of ECG signals. These signals are transmitted to a web-based system for subsequent processing and analysis. The research aims to validate the technological feasibility of acquiring ECG signals at 24-bit resolution, facilitating immediate clinical interventions and providing a foundation for future investigations. A prototype device was tested by capturing patient ECG signals, which were processed using advanced filters to identify key areas of clinical relevance.

Nanopore-based random genomic sampling for intraoperative molecular diagnosis

BackgroundCentral nervous system tumors are among the most lethal types of cancer. A critical factor for tailored neurosurgical resection strategies depends on specific tumor types. However, it is uncommon to have a preoperative tumor diagnosis, and intraoperative morphology-based diagnosis remains challenging. Despite recent advances in intraoperative methylation classifications of brain tumors, accuracy may be compromised by low tumor purity. Copy number variations (CNVs), which are almost ubiquitous in cancer, offer highly sensitive molecular biomarkers for diagnosis. These quantitative genomic alterations provide insight into dysregulated oncogenic pathways and can reveal potential targets for molecular therapies.MethodsWe develop iSCORED, a one-step random genomic DNA reconstruction method that enables efficient, unbiased quantification of genome-wide CNVs. By concatenating multiple genomic fragments into long reads, the method leverages low-pass sequencing to generate approximately 1–2 million genomic fragments within 1 h. This approach allows for ultrafast high-resolution CNV analysis at a genomic resolution of 50 kb. In addition, concurrent methylation profiling enables brain tumor methylation classification and identifies promoter methylation in amplified oncogenes, providing an integrated diagnostic approach.ResultsIn our retrospective cohort of 26 malignant brain tumors, iSCORED demonstrated 100% concordance in CNV detection, including chromosomal alterations and oncogene amplifications, when compared to clinically validated assays such as Next-Generation Sequencing and Chromosomal Microarray. Furthermore, we validated iSCORED’s real-time applicability in 15 diagnostically challenging primary brain tumors, achieving 100% concordance in detecting aberrant CNV detection, including diagnostic chromosomal gains/losses and oncogene amplifications (10/10). Of these, 14 out of 15 brain tumor methylation classifications aligned with final pathological diagnoses. This streamlined workflow—from tissue arrival to automatic generation of CNV and methylation reports—can be completed within 105 min.ConclusionsThe iSCORED pipeline represents the first method capable of high-resolution CNV detection within the intraoperative timeframe. By combining CNV detection and methylation classification, iSCORED provides a rapid and comprehensive molecular diagnostic tool that can inform rapid clinical decision. The integrated approach not only enhances the accuracy of tumor diagnosis but also optimizes surgical planning and identifies potential molecular therapies, all within the critical intraoperative timeframe.

Fast 3D Transmission Tower Detection Based on Virtual Views

Advanced remote sensing technologies leverage extensive synthetic aperture radar (SAR) satellite data and high-resolution airborne light detection and ranging (LiDAR) data to swiftly capture comprehensive 3D information about electrical grid assets and their surrounding environments. This facilitates in-depth scene analysis for target detection and classification, allowing for the early recognition of potential hazards near transmission towers (TTs). These innovations present a groundbreaking strategy for the automated inspection of electrical grid assets. However, traditional 3D target detection techniques, which involve searching the entire 3D space, are marred by low accuracy and high computational demands. Although deep learning-based 3D target detection methods have significantly improved detection precision, they rely on a large volume of 3D target samples for training and are sensitive to point cloud data density. Moreover, these methods demonstrate low detection efficiency, constraining their application in the automated monitoring of electricity networks. This paper proposes a fast 3D target detection method using virtual views to overcome these challenges related to detection accuracy and efficiency. The method first utilizes cutting-edge 2D splatting technology to project 3D point clouds with diverse densities from a specific viewpoint, generating a 2D virtual image. Then, a novel local–global dual-path feature fusion network based on YOLO is applied to detect TTs on the virtual image, ensuring efficient and accurate identification of their positions and types. Finally, by leveraging the projection transformation between the virtual image and the 3D point cloud, combined with a 3D region growing algorithm, the 3D points belonging to the TTs are extracted from the whole 3D point cloud. The effectiveness of the proposed method in terms of target detection rate and efficiency is validated through experiments on synthetic datasets and outdoor LiDAR point clouds.

A method for diagnosing the implosion symmetry in inertial confinement fusion with wide-angle VISAR

Abstract A method for diagnosing implosion symmetry in inertial confinement fusion(ICF) with wide-angle velocity interferometer system for any reflector(VISAR)was proposed in this study. The method considers the object-image relationship of the wide-angle VISAR, characteristics of the fringe pattern, and the symmetry theory; the fringe pattern must be continuous in space to apply this method. Hydrodynamic calculations showed that the radiation-temperature distribution on the surface of capsule was spatially continuous, indirectly proving the applicability of the method. The evolution of P2 asymmetry at different positions of the capsule was examined through an eight-beam laser indirect-drive experiment at a 10 kJ-level laser facility, proving the feasibility of the method. The application of wide-angle VISAR for the diagnosis of implosion symmetry in ICF was more accurate and intuitive and demonstrated high spatiotemporal resolution and wide detection range. This method can provide reference data for the micro-mechanism study of hydrodynamic instability and radiation-driven asymmetry, as well as support for optimizing the implosion compression process to achieve efficient and stable ignition.

Highly Fluorescent Bio-Synthesized Carbon Quantum Dots for Latent Fingerprint Detection.

This study introduces an innovative approach to high-resolution latent fingerprint detection using carbon quantum dots (CQDs) biosynthesized from spent coffee grounds, enhanced with nitrogen doping. Conventional fingerprinting methods frequently use hazardous chemicals and are costly, highlighting the need for eco-friendly, affordable alternatives that preserve detection quality. The biosynthesized nitrogen-doped CQDs exhibit strong photoluminescence and high stability, offering a sustainable, effective alternative for fingerprint imaging. Using a one-step hydrothermal synthesis method, nitrogen-doped CQDs were developed, displaying intense cyan fluorescence under UV light at 365nm. The quantum yield was measured to be 19.73%. Characterization through UV-Visible and photoluminescence spectroscopy, FTIR, XRD and TEM confirmed the morphology, surface properties, optical properties and stability. The average particle size diameter was calculated to be around 8.71 ± 0.14nm. These CQDs were tested on various non-porous surfaces including marble, glass, aluminium, and metal where they provided detailed visualization of fingerprint ridge patterns, sweat pores, and minutiae with high fluorescence. Notably, the CQDs demonstrated excellent adherence and sustained fluorescence, maintaining photostability for up to 60 days under dark storage conditions at 2-8°C. This sustainable synthesis method thus produces nitrogen-doped CQDs with robust fluorescent properties, establishing a promising, eco-friendly solution for high-resolution latent fingerprint detection in forensic investigations.

Characterization of main degradation products from dendrobine under stress conditions by multistage cleavage of UPLC-ESI-IT-TOF.

Dendrobine is a sesquiterpene alkaloid primarily used in the treatment of inflammatory diseases, immune system disorders, and conditions related to oxidative stress. To understand the possible degradation pathways of dendrobine for its quality control, we conducted an in-depth investigation of its degradation products using forced degradation methods. The separation of dendrobine and its degradation products was achieved on a Shim-pack XR-ODS III (75 mm × 2 mm, 1.6 µm) column with a methanol-water mixture as the mobile phase under isocratic conditions, the isolated compounds were examined in positive ion mode with an ion trap-time of flight mass spectrometer (IT-TOF). In order to obtain in-depth structural information about the degradation products, mass spectrometry was performed using a five-stage fragmentation approach. This method allowed for thorough structural clarification via several rounds of selective fragmentation and high-resolution detection. System control and data acquisition were managed using LCMSsolution 3.81 software. The results showed that dendrobine undergoes significant degradation under oxidative, acidic, hydrolytic and thermal conditions, resulting in the formation of several degradation products with notable structural changes. Under oxidative conditions, dendrobine primarily generates two degradation products with mass increases of 16 Da and 32 Da, indicating mono-oxidation and di-oxidation reactions. Acidic degradation led to the identification of three degradation products, including a novel compound with an 18 Da mass increase, suggesting potential hydrolysis or dehydration reactions. Hydrolytic and thermal conditions resulted in the formation of two and three degradation products, respectively, with structural changes indicating possible molecular cleavage and reorganization mechanisms. In contrast, dendrobine exhibited strong stability under alkaline and photolytic conditions, with no significant degradation products detected. Detailed characterization of the degradation products via multi-stage mass spectrometry revealed key reaction pathways and mechanisms involved in dendrobine's degradation, providing critical insights for assessing its chemical stability and optimizing storage conditions.

Detecting copy-number alterations from single-cell chromatin sequencing data by AtaCNA.

Single-cell assay of transposase-accessible chromatin sequencing (scATAC-seq) unbiasedly profiles genome-wide chromatin accessibility in single cells. In single-cell tumor studies, identification of normal cells or tumor clonal structures often relies on copy-number alterations (CNAs). However, CNA detection from scATAC-seq is difficult due to the high noise, sparsity, and confounding factors. Here, we describe AtaCNA, a computational algorithm that accurately detects high-resolution CNAs from scATAC-seq data. We benchmark AtaCNA using simulation and real data and find AtaCNA's superior performance. Analyses of 10 scATAC-seq datasets show that AtaCNA could effectively distinguish malignant from non-malignant cells. In glioblastoma, endometrial, and ovarian cancer samples, AtaCNA identifies subclones at distinct cellular states, suggesting an important interplay between genetic and epigenetic plasticity. Some tumor subclones only differ in small-scale (10-20 Mb) CNAs, demonstrating the importance of high-resolution CNA detection. These data show that AtaCNA can aid in integrative analysis to understand the complex heterogeneity in cancer.

Ion Pair Chromatography for Endogenous Metabolite LC-MS Analysis in Tissue Samples Following HGH Resolution Untargeted Acquisition.

A protocol for the preparation of tissue extracts for the targeted analysis ca. 150 polar metabolites, including those involved in central carbon metabolism, is described, using a reversed phase ion pair U(H)PLC-MS method. Data collection enabled in high-resolution mass spectrometry detection provides highly specific and sensitive acquisition of metabolic intermediates with wide range physicochemical properties and pathway coverage. Technical aspects are discussed for method transfer along with the basic principles of sample sequence setup, data analysis, and validation. At last general comments are given to help the assessment of data quality and system performance.

Simplified Eye-safe Pulsed ToF LiDAR with Modified Newtonian Telescope for Long-Distance High-Resolution Detection in Rain Atmosphere

Simplified Eye-safe Pulsed ToF LiDAR with Modified Newtonian Telescope for Long-Distance High-Resolution Detection in Rain Atmosphere

Injection-Locked-Oscillation-Based Active Sensor on Folded SIW Dual Re-entrant Cavities Resonator for High-Resolution Detection to VOC Concentration

Injection-Locked-Oscillation-Based Active Sensor on Folded SIW Dual Re-entrant Cavities Resonator for High-Resolution Detection to VOC Concentration

A Comparative Study of Ground-Based and Drone-Based GPR: Opportunities, Challenges, and Applications in Bromo, Indonesia

A drone-based GPR offers improved mobility and accessibility for subsurface exploration while delivering high-resolution detection of objects and soil layers, particularly in challenging areas. This study compares the performance and limitations of ground-based and drone-based GPR by analyzing their responses to surface condition using GPR radargrams. Data were collected from the Bromo-Tengger Caldera, East Java, Indonesia, using a 150 MHz antenna for drone-based GPR and a 500 MHz antenna for ground-based GPR. Data processing included filters like static correction, bandpass, gain, background removal, FK-filter, and time-to-depth conversion, with additional steps like time cut and trace editing for drone-based GPR. The results of ground-based GPR data appeared more random, with less distinct reflectors due to surface conditions like vegetation and rough terrain, despite noise filtering. Drone-based GPR faced challenges such as greater static correction due to higher altitude, and deviations from planned paths caused by GPS errors. The study concludes that both methods have unique strengths and weaknesses, and the choice between them should be based on the survey area’s conditions and project goals.

Organic Manganese Halides with Near-Unity Quantum Efficiency for High-Resolution and Flexible X-Ray Detection and Imaging.

In this paper, two new organic manganese halides (pe-ted)2MnX4 (pe-ted+ = ethylphenyltriethylenediamine cation, X = Cl, Br) are synthesized, exhibiting green luminescence with near-unity photoluminescence quantum efficiency. (pe-ted)2MnBr4 shows good linear response to X-ray dose rate, with a high light yield of ≈62 000photonsMeV-1 and low detection limit of 1.376µGys-1. Flexible scintillator film is prepared by blending with polydimethylsiloxane for high-resolution imaging, with a low detection limit (5.173µGys-1), an excellent X-ray imaging spatial resolution (18.0lpmm-1) and an impressive X-ray irradiation switching stability (3.6mGys-1). WLED of high color rendering index hasalso been fabricated. These findings represent an example of shapeable X-ray scintillators, providing new possibilities for curved and 3D X-ray imaging.

Design of unexploded ordnance detection sensor based on frequency-domain electromagnetic method

ABSTRACT Detecting underground metal targets (e.g. unexploded ordnance) using simple devices and seeking to improve the detection accuracy and depth is a hot issue in electromagnetic detection in recent years. Electromagnetic detection based on the frequency-domain method has a simple excitation method, a wide excitation range, and high detection resolution and frequency flexibility. However, the primary field generated by the excitation coil and the secondary field generated by the unexploded ordnance exist at the same time, which has a large impact on the effective signal; and the current detection accuracy is not high, and the effective eigenvalues are less. To address these situations, in this paper, we use the analytical solution of the rectangular coil and finite element simulation to design a new type of electromagnetic sensor with differential multi-component reception, and the influence of the primary field can be eliminated with the help of its coupling characteristics. Based on the unique sensor structure, we propose a four-quadrant fast horizontal localisation as well as a method for target identification and a method for depth fixing of the target by SNR eigenvalue fitting. In a laboratory environment with 10 V low-power excitation, the sensor has a farthest detection depth of about 1.2 m and a positioning error of about 14.43 mm within a depth of 0.9 m, and it can be detected as far as 0.6 m in an outdoor environment.

High-resolution and instability-driven image reconstruction based on wave localization in azobenzene polymer

Transverse modulation instability (MI) has been proved useful for reconstructing noisy images. However, the signal-noise resonances for high-frequency modes are always suppressed during the generation of instability, resulting in the blurring of output images. By controlling of photo-birefringence and isomerization of azobenzene-derivative polymer, we proposed an instability-driven reconstruction by re-growing high-frequency modes via localizing wave response. The agreement between the experimental results and numerical simulations proves its effectiveness. This work provides a general and flexible way for high-resolution target detection.