Limited Resolution Research Articles

Discovery of lipid binding sites in a ligand-gated ion channel by integrating simulations and cryo-EM.

Ligand-gated ion channels transduce electrochemical signals in neurons and other excitable cells. Aside from canonical ligands, phospholipids are thought to bind specifically to the transmembrane domain of several ion channels. However, structural details of such lipid contacts remain elusive, partly due to limited resolution of these regions in experimental structures. Here, we discovered multiple lipid interactions in the channel GLIC by integrating cryo-electron microscopy and large-scale molecular simulations. We identified 25 bound lipids in the GLIC closed state, a conformation where none, to our knowledge, were previously known. Three lipids were associated with each subunit in the inner leaflet, including a buried interaction disrupted in mutant simulations. In the outer leaflet, two intrasubunit sites were evident in both closed and open states, while a putative intersubunit site was preferred in open-state simulations. This work offers molecular details of GLIC-lipid contacts particularly in the ill-characterized closed state, testable hypotheses for state-dependent binding, and a multidisciplinary strategy for modeling protein-lipid interactions.

Synthetic Fourier Domain Optical Coherence Tomography

A novel approach for image formation in optical coherence tomography (OCT) and microscopy is presented. The depth resolution of OCT, including recently developed nanosensitive OCT (nsOCT), is limited by the spectral bandwidth of the light source used for illumination. The proposed approach, synthetic OCT (synOCT), permits label‐free, depth‐resolved quantitative visualization of the subwavelength‐sized structures with nanosensitivity. Using synOCT it is possible to estimate the contribution of axial Fourier components of an object's structure in image formation at each small volume within the image. The size of such areas can be smaller than the resolution limit of the imaging system that provides potential for super‐resolution imaging. Visualization of the subwavelength periodic structures and quantitative visualization of the subwavelength internal structures of highly scattering biological samples, within voxels smaller than resolution limit of the imaging system, are demonstrated. In contrast to nsOCT, the trade‐off between spectral and spatial resolution is removed which results in dramatic improvement of both spectral and spatial resolution in synOCT relative to nsOCT.

Microscopic moisture localisation in unsaturated materials using nuclear magnetic resonance relaxometry

Due to the detrimental effects of moisture in the built environment, there is a continuous interest in non-destructive experimental techniques that quantify and/or localise moisture in materials. Most existing experimental techniques, however, typically focus on macroscopic moisture contents in samples rather than the microscopic distribution of water in the individual pores of building materials. For the latter, a popular method such as X-ray computed tomography is not readily applicable, due to the gap between its spatial resolution limit and the typical pore sizes of building materials. Nuclear magnetic resonance (NMR) relaxometry is capable of measuring water in pores of both the nanometer and micrometer scale and is therefore an interesting possibility. While most NMR research focusses on water-saturated materials or overall moisture contents, this study determines the size distributions of the water islands in unsaturated materials with NMR, and compares results to X-ray computed tomography (XCT) images and pore network model (PNM) simulations. Results on unsaturated materials show that NMR focusses on the biggest water islands (i.e. in capillary filled pores) and disregards the hydrogen nuclei in smaller water islands (i.e. stored in pore corners). NMR relaxometry is therefore only adept at providing very rough estimates of the size of water-filled pores, especially since post-processing of the NMR experiments to obtain these water island size distributions involves a lot of uncertainty.

A Community Detection and Graph-Neural-Network-Based Link Prediction Approach for Scientific Literature

This study presents a novel approach that synergizes community detection algorithms with various Graph Neural Network (GNN) models to bolster link prediction in scientific literature networks. By integrating the Louvain community detection algorithm into our GNN frameworks, we consistently enhanced the performance across all models tested. For example, integrating the Louvain model with the GAT model resulted in an AUC score increase from 0.777 to 0.823, exemplifying the typical improvements observed. Similar gains were noted when the Louvain model was paired with other GNN architectures, confirming the robustness and effectiveness of incorporating community-level insights. This consistent increase in performance—reflected in our extensive experimentation on bipartite graphs of scientific collaborations and citations—highlights the synergistic potential of combining community detection with GNNs to overcome common link prediction challenges such as scalability and resolution limits. Our findings advocate for the integration of community structures as a significant step forward in the predictive accuracy of network science models, offering a comprehensive understanding of scientific collaboration patterns through the lens of advanced machine learning techniques.

Non-invasive evaluation of endometrial microvessels via in vivo intrauterine photoacoustic endoscopy

The endometrium microvessel system, responsible for supplying oxygen and nutrients to the embryo, holds significant importance in evaluating endometrial receptivity (ER). Visualizing this system directly can significantly enhance ER evaluation. Currently, clinical methods like Narrow-band hysteroscopy and Color Doppler ultrasound are commonly used for uterine blood vessel examination, but they have limitations in depth or resolution. Endoscopic Photoacoustic Imaging (PAE) has proven effective in visualizing microvessels in the digestive tract, while its adaptation to uterine imaging faces challenges due to the uterus's unique physiological characteristics. This paper for the first time that uses high-resolution PAE in vivo to capture a comprehensive network of endometrial microvessels non-invasively. Followed by continuous observation and quantitative analysis in the endometrial injury model, we further corroborated that PAE detection of endometrial microvessels stands as a valuable indicator for evaluating ER. The PAE system showcases its promising potential for integration into reproductive health assessments.

A 3D printable gelatin methacryloyl/chitosan hydrogel assembled with conductive PEDOT for neural tissue engineering

In neural tissue engineering, biomaterial scaffolds that have high conductivity and customized structures are crucial in promoting nerve regeneration. Poly(3,4-ethylenedioxythiophene) (PEDOT) has emerged as a promising conductive polymer with excellent chemical stability and biocompatibility. However, traditional three-dimensional (3D) printing of PEDOT-based conductive scaffolds faces challenges in limited printing resolution, poor solubility, and brittleness of conductive materials. Herein, digital light processing (DLP) printing was used to fabricate complex hydrogel structures using gelatin methacryloyl (GelMA) and chitosan (CS) while incorporating PEDOT nanoparticles through interfacial polymerization to create conducting pathways within a hydrogel structure. The integration of PEDOT significantly enhanced the electrical conductivity and mechanical properties of the GelMA/CS hydrogel while preserving printed details. The GelMA/CS-PEDOT hydrogel promoted cell proliferation and facilitated axon outgrowth of PC12 cells and Schwann cells during in vitro culture. Moreover, in vitro direct current electrical stimulation promoted axon elongation of PC12 cells cultured on a conductive substrate. In vivo studies used a conductive nerve conduit to repair a 10-mm rat sciatic nerve defect, validating the efficacy of GelMA/CS-PEDOT scaffold in peripheral nerve injury repair. These findings highlight the significant potential of conductive GelMA/CS-PEDOT hydrogel in the field of neural tissue engineering.

Radial basis function neural network optimization algorithm based on dynamic inertial weight particle swarm optimization for separating overlapping peaks in ion mobility spectrometry.

Ion mobility spectrometry (IMS), as a promising analytical tool, has been widely employed in the structural characterization of biomolecules. Nevertheless, the inherent limitation in the structural resolution of IMS frequently results in peak overlap during the analysis of isomers exhibiting comparable structures. The radial basis function (RBF) neural network optimization algorithm based on dynamic inertial weight particle swarm optimization (DIWPSO) was proposed for separating overlapping peaks in IMS. The RBF network structure and parameters were optimized using the DIWPSO algorithm. By extensively training using a large dataset, an adaptive model was developed to effectively separate overlapping peaks in IMS data. This approach successfully overcomes issues related to local optima, ensuring efficient and precise separation of overlapping peaks. The method's performance was evaluated using experimental validation and analysis of overlapping peaks in the IMS spectra of two sets of isomers: 3'/6'-sialyllactose; fructose-6-phosphate, glucose-1-phosphate, and glucose-6-phosphate. A comparative analysis was conducted using other algorithms, including the sparrow search algorithm, DIWPSO algorithm, and multi-objective dynamic teaching-learning-based optimization algorithm. The comparison results show that the DIWPSO-RBF algorithm achieved remarkably low maximum relative errors of only 0.42%, 0.092%, and 0.41% for ion height, mobility, and half peak width, respectively. These error rates are significantly lower than those obtained using the other three algorithms. The experimental results convincingly demonstrate that this method can adaptively, rapidly, and accurately separate overlapping peaks of multiple components, improving the structural resolution of IMS.

Nonstationary time-frequency characteristics of vehicle suspension systems based on evolutionary power spectral density

Improving the ride comfort for vehicles that travel at varying speeds is a nonstationary problem and has been an increasingly important topic for suspension system research. Accurate identification of frequencies associated with the resonant responses is needed for effective design of active suspension control strategies. However, traditional time-frequency (TF) methods have resolution limitations in either the time domain or the frequency domain. This paper proposes a new methodology to employ the evolutionary power spectral density (EPSD) to describe the responses of vehicles in the time-frequency domain. The key to calculate the responses in nonstationary cases is to derive the nonuniform modulation function which is obtained by the pseudo excitation method. To illustrate the applicability of the proposed method, an example of a seven-degree-of-freedom vehicle model is investigated in which the nonstationary excitations acting on the wheels are computed by the nonuniform modulation function and a precise integration method. Results show that resolutions obtained by the EPSD are more precise than the traditional TF methods with less than 0.2 Hz of bandwidth in both the lower frequency range at the first natural frequency of 1 Hz and in the higher frequency around 10 Hz. Moreover, the changing of the resonant frequency with varying speeds provides the insights, from the perspective of human body’s sensitivity to frequencies of vibration, to improve the ride comfort for vehicles under nonstationary driving conditions.

Innovative super-resolution in spatial transcriptomics: a transformer model exploiting histology images and spatial gene expression.

Spatial transcriptomics technologies have shed light on the complexities of tissue structures by accurately mapping spatial microenvironments. Nonetheless, a myriad of methods, especially those utilized in platforms like Visium, often relinquish spatial details owing to intrinsic resolution limitations. In response, we introduce TransformerST, an innovative, unsupervised model anchored in the Transformer architecture, which operates independently of references, thereby ensuring cost-efficiency by circumventing the need for single-cell RNA sequencing. TransformerST not only elevates Visium data from a multicellular level to a single-cell granularity but also showcases adaptability across diverse spatial transcriptomics platforms. By employing a vision transformer-based encoder, it discerns latent image-gene expression co-representations and is further enhanced by spatial correlations, derived from an adaptive graph Transformer module. The sophisticated cross-scale graph network, utilized in super-resolution, significantly boosts the model's accuracy, unveiling complex structure-functional relationships within histology images. Empirical evaluations validate its adeptness in revealing tissue subtleties at the single-cell scale. Crucially, TransformerST adeptly navigates through image-gene co-representation, maximizing the synergistic utility of gene expression and histology images, thereby emerging as a pioneering tool in spatial transcriptomics. It not only enhances resolution to a single-cell level but also introduces a novel approach that optimally utilizes histology images alongside gene expression, providing a refined lens for investigating spatial transcriptomics.

Electromagnetic tomographic cerebral angiography

World Health Organization stated that “Cardiovascular diseases (CVDs) are the leading cause of death globally. Angiography is an important method in diagnostic of CVD. Standard-of-Care methods of angiography, such as X-Ray or CT- or MRI- angiography methods, being accurate and widely adopted in clinical practice, are bulky, expensive and energy in-efficient. X-ray and CT- angiography methods are also potentially hazardous as techniques require the use of ionizing contrast agents. Electromagnetic tomography (EMT) is an emerging medical imaging modality. EMT is applicable for safe functional imaging but suffers from a limited spatial resolution because of relatively large wavelength of electromagnetic radiation as compared to sizes of biological targets of particular interest, such as, for example blood vessels. Novel approach and method, presented in the study is capable to overcome such limitations and provide a mean for a dynamic, on-line EMT angiography. New method of EMT angiography was presented in application to cerebral angiography. Achieved imaging results clearly demonstrate applicability of the method for detecting small cerebral vessels of the diameter as small as 1.3 mm and to distinguish vessels with different dimensions. The technical challenges in the development of angiography capable EMT systems are assessed and discussed.

Probing the multi-disordered nanoscale alloy at the interface of lateral heterostructure of MoS2–WS2

Abstract Transition metal dichalcogenide (TMDs) heterostructure, particularly the lateral heterostructure of two different TMDs, is gaining attention as ultrathin photonic devices based on the charge transfer (CT) excitons generated at the junction. However, the characteristics of the interface of the lateral heterostructure, determining the electronic band structure and alignment at the heterojunction region, have rarely been studied due to the limited spatial resolution of nondestructive analysis systems. In this study, we investigated the confined phonons resulting from the phonon-disorder scattering process involving multiple disorders at the lateral heterostructure interface of MoS2–WS2 to prove the consequences of disorder-mediated deformation in the band structure. Moreover, we directly observed variations in the metal composition of the multi-disordered nanoscale alloy Mo1−x W x S2, consisting of atomic vacancies, crystal edges, and distinct nanocrystallites. Our findings through tip-enhanced Raman spectroscopy (TERS) imply that a tens of nanometer area of continuous TMDs alloy forms the multi-disordered interface of the lateral heterostructure. The results of this study could present the way for the evaluation of the TMDs lateral heterostructure for excitonic applications.

A seismic prediction method of reservoir brittleness based on mineral composition and pore structure

The Lucaogou Formation, a typical fine-grained mixed formation in the Jimusaer Sag of the Junggar Basin, exhibits considerable potential for hydrocarbon exploration. Accurate brittle prediction is a crucial factor in determining hydraulic fracturing effectiveness. However, the area features complex lithological characteristics, including carbonate rocks, clastic rocks, volcanic rocks, and gypsum interbeds, along with thin layering and sporadic sweet spots. Traditional prediction methods offer limited resolution and there is an urgent need for a seismic brittle prediction method tailored to this complex geological environment. This paper presents a multi-mineral composition equivalent model for complex lithologies that enables the accurate calculation of Vp and Vs These ratios serve as the foundation for pre-stack elastic parameter predictions, which include Poisson’s ratio and Young’s modulus. By comparing the predicted parameters with well-logging measurements, the prediction accuracy is improved to 82%, with particularly high conformity in intervals characterized by high organic matter and clay content. Additionally, a three-dimensional brittle modeling approach reveals that the brittleness of the reservoir exceeds that of the surrounding rock, showing a gradual improvement in brittleness with increasing burial depth from southeast to northwest. The central area exhibits relatively good brittleness, with a stable, blocky distribution pattern.

Quantitative ultrasound image assessment of the optic nerve subarachnoid space during 90-day head-down tilt bed rest

The elevation in the optic nerve sheath (ONS) pressure (ONSP) due to microgravity-induced headward fluid shift is the primary hypothesized contributor to SANS. This longitudinal study aims to quantify the axial plane of the optic nerve subarachnoid space area (ONSSA), which is filled with cerebrospinal fluid (CSF) and expands with elevated ONSP during and after head-down tilt (HDT) bed rest (BR). 36 healthy male volunteers (72 eyes) underwent a 90-day strict 6° HDT BR. Without obtaining the pre-HDT data, measurements were performed on days 30, 60, and 90 during HDT and at 6 recovery time points extended to 180-days (R + 180) in a supine position. Portable B-scan ultrasound was performed using the 12 MHz linear array probe binocularly. The measurements of the ONS and the calculation of the ONSSA were performed with ImageJ 1.51 analysis software by two experienced observers in a masked manner. Compared to R + 180, the ONSSA on HDT30, HDT60, and HDT90 exhibited a consistently significant distention of 0.44 mm2 (95% CI: 0.13 to 0.76 mm2, P = 0.001), 0.45 mm2 (95% CI: 0.15 to 0.75 mm2, P = 0.001), and 0.46 mm2 (95% CI: 0.15 to 0.76 mm2, P < 0.001), respectively, and recovered immediately after HDT on R + 2. Such small changes in the ONSSA were below the lateral resolution limit of ultrasound (0.4 mm) and may not be clinically relevant, possibly due to ONS hysteresis causing persistent ONS distension. Future research can explore advanced quantitative portable ultrasound-based techniques and establish comparisons containing the pre-HDT measurements to deepen our understanding of SANS.

Multi- and Gray-Scale Thermal Lithography of Silk Fibroin as Water-Developable Resist for Micro and Nanofabrication.

Silk fibroin (SF) is a natural material with polymorphic structures that determine its water solubility and biodegradability, which can be altered by exposing it to heat. Here, a hybrid thermal lithography method combining scalable microscale laser-based patterning with nanoscale patterning based on thermal scanning probe lithography is developed. The latter enables in addition grayscale patterns to be made. The resolution limit of the writing in silk fibroin is studied by using a nanoscale heat source from a scanned nanoprobe. The heat thereby induces local water solubility change in the film, which can subsequently be developed in deionized water. Nanopatterns and grayscale patterns down to 50nm lateral resolution are successfully written in the silk fibroin that behaves like a positive tone resist. The resulting patterned silk fibroin is then applied as a mask for dry etching of SiO2 to form a hard mask for further nano-processing. A very high selectivity of 42:1 between SiO2 and silk fibroin is obtained allowing for high-aspect ratio structure to be fabricated. The fabricated nanostructures have very low line edge roughness of 5±2nm. The results demonstrate the potential of silk fibroin as a water-soluble resist for hybrid thermal lithography and precise micro/nanofabrication.

Design of ultra-wide-field scanning laser fundus imaging system with cascaded conicoid mirrors.

We propose and design a multi-stage cascaded scanning laser ophthalmoscope (SLO) for ultra-wide field (UWF), which uses conicoid mirrors, constructed by conjugation of pupil plane. The vergence uniformity and the angular magnification of a cascaded conicoid mirrors (CCM) system are analyzed recursively and optimized preliminarily to achieve high quality imaging with UWF, and the optimal system with the model eye are obtained by simulation and optimization. Two-stage and three-stage cascaded systems are designed with this method, and the formulas of beam vergence and angular magnification are obtained by theoretical derivation. As compared to the two-stage CCM system, the proposed three-stage cascaded UWF SLO has superior performance in imaging quality. Its average RMS radius of spot diagram is calculated to be 26.372 µm, close to the diffractive limit resolution. The image resolution of human retina can be up to 30 µm with 135° FOV in theory. The three-stage cascaded SLO is more suitable for UWF fundus imaging. This study will be helpful for early screening and accurate diagnosis of various diseases in the peripheral retina.

One-Shot Dual-Detection-Based Single-Molecule Super-Resolution Imaging Method for Real-Time Observation of Spatiotemporal Catalytic Activity Variations on the Plasmonic Gold Nanoparticle Surface.

Understanding the relationship between the surface properties of a single plasmonic nanoparticle and its catalytic performance is critical for developing highly efficient nanocatalysts. In this study, a one-shot dual-detection-based single-molecule super-resolution imaging method in the evanescent field was developed to observe real-time spatiotemporal catalytic activity on a single plasmonic gold nanoparticle (AuNP) surface. The scattering intensity of AuNPs and the fluorescence of resorufin molecules produced on the AuNP surface were obtained simultaneously to investigate the relationship between nanoparticles and catalytic reactions at a single-molecule level. Chemisorbed adsorbates (i.e., catalytic product and resorufin) changed the electron density of individual AuNPs throughout the catalytic cycle, resulting in the fluctuation of the scattering intensity of individual AuNPs, which was attributed to the electron transfer between reactant resazurin molecules and AuNPs. The increase in the electron density of individual AuNPs affected the catalytic reaction rate. Furthermore, sequential mapping of individual catalytic events at the subdiffraction limit resolution was completed for real-time surface dynamics and spatiotemporal activity variations on the single AuNP surface. The developed method can aid in understanding surface-property-dependent catalytic kinetics and facilitate the development of nanoparticle-based heterogeneous catalysts at subdiffraction limit resolution.

Thermally Activated Delayed Fluorescence (TADF)-active Coinage-metal Sulfide Clusters for High-resolution X-ray Imaging.

The study of facile-synthesis and low-cost X-ray scintillators with high light yield, low detection limit and high X-ray imaging resolution plays a vital role in medical and industrial imaging fields. However, the optimal balance between X-ray absorption, decay lifetime and excitonic utilization efficiency of scintillators to achieve high-resolution imaging is extremely difficult due to the inherent contradiction. Here two thermally activated delayed fluorescence (TADF)-actived coinage-metal clusters M6 S6 L6 (M=Ag or Cu) were synthesized by simple solvothermal reaction, where the cooperation of heavy atom-rich character and TADF mechanism supports strong X-ray absorption and rapid luminescent collection of excitons. Excitingly, Ag6 S6 L6 (SC-Ag) displays a high photoluminescence quantum yield of 91.6 % and scintillating light yield of 17420 photons MeV-1 , as well as a low detection limit of 208.65 nGy s-1 that is 26 times lower than the medical standard (5.5 μGy s-1 ). More importantly, a high X-ray imaging resolution of 16 lp/mm based on SC-Ag screen is demonstrated. Besides, rigid core skeleton reinforced by metallophilicity endows clusters M6 S6 L6 strong resistance to humidity and radiation. This work provides a new view for the design of efficient scintillators and opens the research door for silver clusters in scintillation application.

Phantom evaluation of electrical conductivity mapping by MRI: Comparison to vector network analyzer measurements and spatial resolution assessment.

To evaluate the performance of various MR electrical properties tomography (MR-EPT) methods at 3 T in terms of absolute quantification and spatial resolution limit for electrical conductivity. Absolute quantification as well as spatial resolution performance were evaluated on homogeneous phantoms and a phantom with holes of different sizes, respectively. Ground-truth conductivities were measured with an open-ended coaxial probe connected to a vector network analyzer (VNA). Four widely used MR-EPT reconstruction methods were investigated: phase-based Helmholtz (PB), phase-based convection-reaction (PB-cr), image-based (IB), and generalized-image-based (GIB). These methods were compared using the same complex images from a 1 mm-isotropic UTE sequence. Alternative transceive phase acquisition sequences were also compared in PB and PB-cr. In large homogeneous phantoms, all methods showed a strong correlation with ground truth conductivities (r > 0.99); however, GIB was the best in terms of accuracy, spatial uniformity, and robustness to boundary artifacts. In the resolution phantom, the normalized root-mean-squared error of all methods grew rapidly (>0.40) when the hole size was below 10 mm, with simplified methods (PB and IB), or below 5 mm, with generalized methods (PB-cr and GIB). VNA measurements are essential to assess the accuracy of MR-EPT. In this study, all tested MR-EPT methods correlated strongly with the VNA measurements. The UTE sequence is recommended for MR-EPT, with the GIB method providing good accuracy for structures down to 5 mm. Structures below 5 mm may still be detected in the conductivity maps, but with significantly lower accuracy.

Imaging privacy threats from an ambient light sensor.

Embedded sensors in smart devices pose privacy risks, often unintentionally leaking user information. We investigate how combining an ambient light sensor with a device display can capture an image of touch interaction without a camera. By displaying a known video sequence, we use the light sensor to capture reflected light intensity variations partially blocked by the touching hand, formulating an inverse problem similar to single-pixel imaging. Because of the sensors' heavy quantization and low sensitivity, we propose an inversion algorithm involving an ℓp-norm dequantizer and a deep denoiser as natural image priors, to reconstruct images from the screen's perspective. We demonstrate touch interactions and eavesdropping hand gestures on an off-the-shelf Android tablet. Despite limitations in resolution and speed, we aim to raise awareness of potential security/privacy threats induced by the combination of passive and active components in smart devices and promote the development of ways to mitigate them.

Quantitative Label-Free Chemical Imaging of PLGA Nanoparticles in Cells and Tissues with Single-Particle Sensitivity.

Nanomedicine has brought significant advancements to healthcare by utilizing nanotechnology in medicine. Despite much promise, the further development of nanocarriers for clinical use has been hindered by a lack of understanding and visualization of nano-bio interactions. Conventional imaging methods have limitations in resolution, sensitivity, and specificity. This study introduces a label-free optical approach using stimulated Raman scattering (SRS) microscopy to image poly(lactic-co-glycolic acid) (PLGA) nanocarriers, the most widely used polymeric nanocarrier for delivery therapeutic agents, with single-particle sensitivity and quantification capabilities. A unique Raman peak was identified for PLGA ester, enabling generalized bio-orthogonal bond imaging. We demonstrated quantitative SRS imaging of PLGA nanocarriers across different biological systems from cells to animal tissues. This label-free imaging method provides a powerful tool for studying this prevalent nanocarrier and quantitatively visualizing their distribution, interaction, and clearance in vivo.