Motion Of Probe Research Articles

Applications of scanning ion conductance microscope in biomedical fields

AbstractScanning ion conductance microscopy (SICM) is a scanning probe technique to reflect the surface morphology of the sample with the probe's motion trajectory through measuring the current between the probe and the surface of the sample. Since the surface of the sample can be scanned noncontact and the morphological characteristics of the living cell can be obtained under physiological conditions, SICM is particularly important in the field of biomedicine. SICM has strong potentials in various applications, such as the real‐time and high‐resolution imaging of living cells, monitoring the volume and movements of living cells. In addition, SICM combines with various technologies such as patch clamp and nanopipette to study the physical properties of cells. Furthermore, using SICM to observe cell and tissue structure provides more directions for studying the mechanism of disease. This review briefly introduces the principles and imaging modes of SICM and outlines the recent applications and development of SICM in biomedical research. We also introduce the limitations of the existing SICM technology and make a perspective on its future development.

Dynamics of a spherical self-propelled tracer in a polymeric medium: interplay of self-propulsion, stickiness, and crowding.

We employ computer simulations to study the dynamics of a self-propelled spherical tracer particle in a viscoelastic medium, made of a long polymer chain. Here, the interplay between viscoelasticity, stickiness, and activity (self-propulsion) brings additional complexity to the tracer dynamics. Our simulations show that on increasing the stickiness of the tracer particle to the polymer beads, the dynamics of the tracer particle slows down as it gets stuck to the polymer chain and moves along with it. But with increasing self-propulsion velocity, the dynamics gets enhanced. In the case of increasing stickiness as well as activity, the non-Gaussian parameter (NGP) exhibits non-monotonic behavior, which also shows up in the re-scaled self part of the van-Hove function. Non-Gaussianity results owing to the enhanced binding events and the sticky motion of the tracer along with the chain with increasing stickiness. On the other hand, with increasing activity, initially non-Gaussianity increases as the tracer moves through the heterogeneous polymeric environment but for higher activity, the tracer escapes resulting in a negative NGP. For higher values of stickiness, the trapping time distributions of the passive tracer particle broaden and have long tails. On the other hand, for a given stickiness with increasing self-propulsion force, the trapping time distributions become narrower and have short tails. We believe that our current simulation study will be helpful in elucidating the complex motion of activity-driven probes in viscoelastic media.

Microrheology near jamming.

The jamming transition is a nonequilibrium critical phenomenon, which governs characteristic mechanical properties of jammed soft materials, such as pastes, emulsions, and granular matters. Both experiments and theory of jammed soft materials have revealed that the complex modulus measured by conventional macrorheology exhibits a characteristic frequency dependence. Microrheology is a new type of method to obtain the complex modulus, which transforms the microscopic motion of probes to the complex modulus through the generalized Stokes relation (GSR). Although microrheology has been applied to jammed soft materials, its theoretical understanding is limited. In particular, the validity of the GSR near the jamming transition is far from obvious since there is a diverging length scale lc, which characterizes the heterogeneous response of jammed particles. Here, we study the microrheology of jammed particles by theory and numerical simulation. First, we develop a linear response formalism to calculate the response function of the probe particle, which is transformed to the complex modulus via the GSR. Then, we apply our formalism to a numerical model of jammed particles and find that the storage and loss modulus follow characteristic scaling laws near the jamming transition. Importantly, the observed scaling law coincides with that in macrorheology, which indicates that the GSR holds even near the jamming transition. We rationalize this equivalence by asymptotic analysis of the obtained formalism and numerical analysis on the displacement field of jammed particles under a local perturbation.

Structural Anomaly in Glasses: Molecular Dynamics Study of Organic Radical in Dibutylphthalate at Different Temperatures

Understanding the heterogeneous nano/microscopic structures of various organic glasses is fundamental and necessary for many applications. Recently, unusual structural phenomena have been observed experimentally in various organic glasses near their glass transition temperatures (Tg), including dibutyl phthalate (DBP). In particular, the librational motion of radical probe in the glass is progressively suppressed upon temperature increase. In this work, we report in-depth molecular dynamics studies of structural anomalies in DBP glass, that revealed insights into the general mechanism of these phenomena. In particular, we have evidenced that the two types of solvation within alkyl chains coexist, allowing only small-angle wobbling of the solute molecule (TEMPO radical), and another favouring large-angle rotations. The former solvation assumes constrained location of the solute near carboxyl groups of DBP, while the latter is coupled to the concerted movement of butyl chains. Remarkably, excellent qualitative and quantitative agreement with previous experimental results were obtained. As such, we are certain that the above-mentioned dynamic phenomena explain the intriguing structural anomalies observed in DBP and some other glasses in the vicinity of Tg.

Augmented Reality and Robotic Systems for Assistance in Percutaneous Nephrolithotomy Procedures: Recent Advances and Future Perspectives

Percutaneous nephrolithotomy is the gold standard for the treatment of renal stones larger than 20 mm in diameter. The treatment outcomes of PCNL are highly dependent on the accuracy of the puncture step, in order to achieve a suitable renal access and reach the stone with a precise and direct path. Thus, performing the puncturing to get the renal access is the most crucial and challenging step of the procedure with the steepest learning curve. Many simulation methods and systems have been developed to help trainees achieve the requested competency level to achieve a suitable renal access. Simulators include human cadavers, animal tissues and virtual reality simulators to simulate human patients. On the other hand, the availability of pre-operative information (e.g., computed tomography or magnetic resonance imaging) and of intra-operative images (e.g., ultrasound images) has allowed the development of solutions involving augmented reality and robotic systems to assist the surgeon during the operation and to help a novel surgeon in strongly reducing the learning curve. In this context, the real-time awareness of the 3D position and orientation of the considered anatomical structures with reference to a common frame is fundamental. Such information must be accurately estimated by means of specific tracking systems that allow the reconstruction of the motion of the probe and of the tool. This review paper presents a survey on the leading literature on augmented reality and robotic assistance for PCNL, with a focus on existing methods for tracking the motion of the ultrasound probe and of the surgical needle.

Cationic molecular probes based on aggregation-induced emission for fluorescent sensing and super-resolution imaging of insulin fibrosis

Amyloid fibrosis of protein is one of protein-related essential issues, which provides the critical information for the diagnosis and therapy of degenerative diseases. Insulin possesses the determined structure and relatively low molecular weight, which is often used as the main model protein to study amyloid fibrosis. Here, we have designed and synthesized three hydrophilic cationic aggregation-induced emission (AIE) probes with different aromatic ketone structures through geminal cross-coupling (GCC) reaction. Cationic AIE molecular probes can bind to insulin fibrils with negative charge at pH = 9.0 through electrostatic interaction, which constrains the intramolecular motion of probes and enhances the fluorescence. The detection limit of probes for insulin fibrils is as low as 0.64 nM. The random and sparse lighting of cationic molecular probes can be realized to enable the super-resolution imaging through the reversible electrostatic association-dissociation interaction between the negative insulin fibrils and positive molecular probes. The fine structure of the fibrils is observed, and full-width at half maximum (FWHM) for assessing the resolution can reach 35 nm, which is of great significance for the development of high-performance super-resolution imaging probes based on aggregation-induced emission and their optical nanoscale visualization applications in the exploration of amyloid fibrillation and related diseases.

Observation of conformational changes that underlie the catalytic cycle of Xrn2.

Nuclear magnetic resonance (NMR) methods that quantitatively probe motions on molecular and atomic levels have propelled the understanding of biomolecular processes for which static structures cannot provide a satisfactory description. In this work, we studied the structure and dynamics of the essential 100-kDa eukaryotic 5′→3′ exoribonuclease Xrn2. A combination of complementary fluorine and methyl-TROSY NMR spectroscopy reveals that the apo enzyme is highly dynamic around the catalytic center. These observed dynamics are in agreement with a transition of the enzyme from the ground state into a catalytically competent state. We show that the conformational equilibrium in Xrn2 shifts substantially toward the active state in the presence of substrate and magnesium. Finally, our data reveal that the dynamics in Xrn2 correlate with the RNA degradation rate, as a mutation that attenuates motions also affects catalytic activity. In that light, our results stress the importance of studies that go beyond static structural information.

Orbital Stability and Invariant Manifolds on Distant Retrograde Orbits around Ganymede and Nearby Higher-Period Orbits

In the past few years, distant retrograde orbits (DROs) have become increasingly popular due to their conspicuous stability. Nevertheless, it is this characteristic that results in the challenge to the design of transfer orbits into/out of DROs. This paper investigates the DROs around Ganymede in order to utilize their dynamical characteristics for Jupiter system exploration. In particular, the DRO family is calculated by numerical integration and numerical continuation, higher-period orbits near the DROs are detected using bifurcation theory, and characteristics including orbital stability and invariant manifolds of these orbits are investigated through stability indices and manifold theory. The stability of DROs and the higher-period orbits are first investigated in the circular restricted three-body problem and are then verified in a third-body gravitation perturbation model. The results show that the strong stability of DROs makes it possible to observe the Galilean moons for long periods and that the higher-period orbits that bifurcate from the DROs offer additional insight into the motion of probes approaching/departing from the vicinities of the DROs. Further investigation of the invariant manifolds around higher-period orbits reveals the feasibility of utilizing the DRO family and the nearby unstable structures for multi-target exploration and low-energy transfer between the Galilean moons.

Linear viscoelasticity of nanocolloidal suspensions from probe rheology molecular simulations

We use molecular dynamics (MD) simulations in conjunction with the probe rheology technique to investigate the linear viscoelasticity of nanocolloidal suspensions. A particulate model of the solvent is used in which the hydrodynamics is governed by interparticle interactions. Active and passive probe rheology molecular simulations are performed on the colloidal suspensions of different volume fractions ranging from 0.30 to 0.45 to determine the linear viscoelastic properties of these systems. The viscoelastic modulus of the suspensions is obtained by analyzing the probe motion using continuum mechanics. In active rheology, the distribution of colloid particles around the probe is observed to be symmetric indicating that the system is in the linear regime at all conditions investigated. In passive rheology, the mean-squared displacement of the probe covers the range of motion from ballistic to diffusive regimes. The dynamic modulus and the reduced complex viscosity values obtained from probe rheology simulations are in good agreement with the results from the oscillatory nonequilibrium MD (NEMD) simulations and the literature theoretical predictions. At low frequency values, accounting for artificial hydrodynamic interactions between the probe and its periodic images improves the quantitative accuracy of the modulus values obtained from simulations. Simulations carried out using probes of different sizes indicate that only the probes that are larger than the colloids yield viscoelastic modulus values that are in good agreement with the NEMD values at all volume fractions investigated.

Design and testing of drift free force probe experiments with absolute distance control

After almost 35 years of truly successful and transformative advancements, Atomic Force Microscopy (AFM) and, in general, scanning probe microscopy still have a fundamental limitation. This is constant drift and uncontrolled motion of probe and tested surface structures with respect to each other. This is inherently linked to the currently accepted design principle-only forces are measured, and distances are inferred from force measurements and piezo motions. Here, we demonstrate and test a new setup, which combines advantages of AFM and the surface forces apparatus, where absolute distances are measured by Multiple Beam White Light Interferometry (MBI). The novel and unique aspect of this apparatus consists of a synergistic combination of white light interferometric measurement of the absolute distance by direct reflection from an AFM cantilever and a fast distance clamping and drift correction using an IR-laser Fabry-Pérot interferometry-based approach (FPI). We demonstrate the capabilities of the system by force/distance measurements, benchmarking of distance control by direct comparison of MBI and FPI, and discuss potential applications of the system. This novel setup has the potential to form, monitor, and stress a single molecule or ligand/receptor bond on the molecular hook with sub-nanometer control of molecular distances over in principle infinite times.

High-Pressure ESR Spectroscopy: On the Rotational Motion of Spin Probes in Pressurized Ionic Liquids.

We report high-pressure (up to 50 MPa) ESR-spectroscopic investigations on the rotational correlation times of the nitroxide radicals 2,2,6,6-tetramethylpiperidine 1-oxyl (TEMPO), 4-hydroxy-2,2,6,6-tetramethylpiperidine 1-oxyl (TEMPOL), and 4-amino-2,2,6,6-tetramethylpiperidine 1-oxyl (ATEMPO) in the ionic liquids 1-ethyl-3-methylimidazolium tetrafluoroborate (emimBF4), 1-butyl-3-methylimidazolium hexafluorophosphate (bmimPF6), 1-butyl-3-methylimidazolium tetrafluoroborate (bmimBF4), 1-methyl-3-octylimidazolium tetrafluoroborate (omimBF4), and 1-methyl-3-octylimidazolium hexafluorophosphate (omimPF6). The activation volumes (38.5–56.6 Å3) determined from pressure dependent rotational diffusion coefficients agree well with the pressure dependent viscosities of the ionic liquids. Experimentally, the fractional exponent of the generalized Stokes–Einstein–Debye relation is found to be close to one.

Endoscopic en-face optical coherence tomography and fluorescence imaging using correlation-based probe tracking.

Forward-viewing endoscopic optical coherence tomography (OCT) provides 3D imaging in vivo, and can be combined with widefield fluorescence imaging by use of a double-clad fiber. However, it is technically challenging to build a high-performance miniaturized 2D scanning system with a large field-of-view. In this paper we demonstrate how a 1D scanning probe, which produces cross-sectional OCT images (B-scans) and 1D fluorescence T-scans, can be transformed into a 2D scanning probe by manual scanning along the second axis. OCT volumes are assembled from the B-scans using speckle decorrelation measurements to estimate the out-of-plane motion along the manual scan direction. Motion within the plane of the B-scans is corrected using image registration by normalized cross correlation. En-face OCT slices and fluorescence images, corrected for probe motion in 3D, can be displayed in real-time during the scan. For a B-scan frame rate of 250 Hz, and an OCT lateral resolution of approximately , the approach can handle out-of-plane motion at speeds of up to 4 mm/s.

USPoint: Self-Supervised Interest Point Detection and Description for Ultrasound-Probe Motion Estimation During Fine-Adjustment Standard Fetal Plane Finding.

Ultrasound (US)-probe motion estimation is a fundamental problem in automated standard plane locating during obstetric US diagnosis. Most recent existing recent works employ deep neural network (DNN) to regress the probe motion. However, these deep regressionbased methods leverage the DNN to overfit on the specific training data, which is naturally lack of generalization ability for the clinical application. In this paper, we are back to generalized US feature learning rather than deep parameter regression. We propose a self-supervised learned local detector and descriptor, named USPoint, for US-probe motion estimation during the fine-adjustment phase of fetal plane acquisition. Specifically, a hybrid neural architecture is designed to simultaneously extract a local feature, and further estimate the probe motion. By embedding a differentiable USPoint-based motion estimation inside the proposed network architecture, the USPoint learns the keypoint detector, scores and descriptors from motion error alone, which doesn't require expensive human-annotation of local features. The two tasks, local feature learning and motion estimation, are jointly learned in a unified framework to enable collaborative learning with the aim of mutual benefit. To the best of our knowledge, it is the first learned local detector and descriptor tailored for the US image. Experimental evaluation on real clinical data demonstrates the resultant performance improvement on feature matching and motion estimation for potential clinical value. A video demo can be found online: https://youtu.be/JGzHuTQVlBs.

Multimodal-GuideNet: Gaze-Probe Bidirectional Guidance in Obstetric Ultrasound Scanning.

Eye trackers can provide visual guidance to sonographers during ultrasound (US) scanning. Such guidance is potentially valuable for less experienced operators to improve their scanning skills on how to manipulate the probe to achieve the desired plane. In this paper, a multimodal guidance approach (Multimodal-GuideNet) is proposed to capture the stepwise dependency between a real-world US video signal, synchronized gaze, and probe motion within a unified framework. To understand the causal relationship between gaze movement and probe motion, our model exploits multitask learning to jointly learn two related tasks: predicting gaze movements and probe signals that an experienced sonographer would perform in routine obstetric scanning. The two tasks are associated by a modality-aware spatial graph to detect the co-occurrence among the multi-modality inputs and share useful cross-modal information. Instead of a deterministic scanning path, Multimodal-GuideNet allows for scanning diversity by estimating the probability distribution of real scans. Experiments performed with three typical obstetric scanning examinations show that the new approach outperforms single-task learning for both probe motion guidance and gaze movement prediction. Multimodal-GuideNet also provides a visual guidance signal with an error rate of less than 10 pixels for a 224 × 288 US image.

Follow the Curve: Robotic Ultrasound Navigation With Learning-Based Localization of Spinous Processes for Scoliosis Assessment

The scoliosis progression in adolescents requires close monitoring to timely take treatment measures. Ultrasound imaging is a radiation-free alternative in scoliosis assessment to X-ray, which is typically used in clinical practice. However, ultrasound images are prone to speckle noise, making it challenging for sonographers to detect bony features and follow the spinal curvature. This study introduces a novel robotic ultrasound approach for spinous process localization and automatic spinal curvature tracking for scoliosis assessment. The positions of the spinous processes are computed using a fully connected network with a deconvolutional head. A 5-fold cross-validation was performed on a dataset of ultrasound images from 25 human subjects with scoliosis. The resulting percentage of correct keypoints of the spinous process is 0.966±0.027 with a mean distance error of 1.0±0.99 mm. We use this machine learning-based method to guide the motion of the robot-held ultrasound probe and to follow the spinal curvature while capturing ultrasound images. We present a new force-driven controller that automatically adjusts the pose and orientation of the probe relative to the skin surface, which ensures a good acoustic coupling between the probe and skin. We extended the network architecture to additionally perform classification of the spine into its regions, i.e., sacrum, lumbar, and thoracic, which are used to adjust the probe’s orientation to account for the varying curvature along the spine. After the autonomous scanning, the acquired data is used to reconstruct the coronal spinal image, where the deformity of the scoliosis spine can be assessed and measured. The proposed learning-based method for anatomical landmarks localization was compared to conventional methods based on phase symmetry and image intensity. The learning-based method proved to be more precise for spinous process localization while processing images at a faster rate, which is advantageous for real-time scoliosis scanning. To evaluate the performance of our robotic method, we conducted an experimental study with human scoliosis subjects where deviations of the spinous process from the image center can be compared to those appearing in a manual scan. Our results show that the robotic approach reduces the mean error of spinal curvature following for mild scoliosis from 4.6±4.6mm (manual scanning) to 1.0±0.8mm (robotic scanning); For moderate scoliosis from 4.3±3.9mm (manual scanning) to 2.8±1.8mm (robotic scanning). The angles of spinal deformity measured on spinal reconstruction images were similar for both methods, implying that they equally reflect human anatomy. The spinal region-specific moment-based probe orientation control showed to improve the scanning performance. An ablation study was performed to investigate the importance of each component of the proposed system.

The confined Generalized Stokes-Einstein relation and its consequence on intracellular two-point microrheology

Two-point microrheology (TPM) is used to infer material properties of complex fluids from the correlated motion of hydrodynamically interacting probes embedded in the medium. The mechanistic connection between probe motion and material properties is propagation of disturbance flows, encoded in current TPM theory for unconfined materials. However, confined media e.g. biological cells and particle-laden droplets, require theory that encodes confinement into the flow propagator (Green’s function). To test this idea, we use Confined Stokesian Dynamics simulations to explicitly represent many-body hydrodynamic couplings between colloids and with the enclosing cavity at arbitrary concentration and cavity size. We find that previous TPM theory breaks down in confinement, and we identify and replace the underlying key elements. We put forth a Confined Generalized Stokes-Einstein Relation and report the viscoelastic spectrum. We find that confinement alters particle dynamics and increases viscosity, owing to hydrodynamic and entropic coupling with the cavity. The new theory produces a master curve for all cavity sizes and concentrations and reveals that for colloids larger than 0.005 times the enclosure size, the new model is required.

Mobile Ultrasound Tracking and Magnetic Control for Long‐Distance Endovascular Navigation of Untethered Miniature Robots against Pulsatile Flow

Long‐distance endovascular navigation of miniature robots under the guidance of medical imaging modalities is essential for microrobotic targeted delivery in the human body. Herein, a scheme on this topic based on mobile ultrasound (US) tracking and magnetic control is proposed. Considering the narrow 2D imaging of a US probe and the fast decay of the magnetic field, the US probe is integrated with three electromagnetic coils for simultaneous long‐distance tracking and control of untethered miniature robots. To enable robust tracking with pulsatile flow, a tracking strategy consisting of tracking in and perpendicular to the image plane is designed. In the image plane, an iterative statistics‐based strategy is proposed to extract the position and orientation of the robot from the US imaging. For the direction perpendicular to the US image plane, the probe motion is automatically adjusted according to the tracking quality. Based on the real‐time tracking result, demanded rotating fields are generated by the mobile coils for helical propulsion. The proposed scheme is implemented on a full‐scale silicone phantom of human iliac and aorta arteries with blood‐mimicking fluid and pulsatile flow. Experimental results validate the robustness and the effectiveness of the proposed scheme.

An application of symplectic integration for general relativistic planetary orbitography subject to non-gravitational forces

Spacecraft propagation tools describe the motion of near-Earth objects and interplanetary probes using Newton’s theory of gravity supplemented with the approximate general relativistic n-body Einstein–Infeld–Hoffmann equations of motion. With respect to the general theory of relativity and the long-standing recommendations of the International Astronomical Union for astrometry, celestial mechanics and metrology, we believe modern orbitography software is now reaching its limits in terms of complexity. In this paper, we present the first results of a prototype software titled General Relativistic Accelerometer-based Propagation Environment (GRAPE). We describe the motion of interplanetary probes and spacecraft using extended general relativistic equations of motion which account for non-gravitational forces using end-user supplied accelerometer data or approximate dynamical models. We exploit the unique general relativistic quadratic invariant associated with the orthogonality between four-velocity and acceleration and simulate the perturbed orbits for Molniya, Parker Solar Probe and Mercury Planetary Orbiter-like test particles subject to a radiation-like four-force. The accuracy of the numerical procedure is maintained using a 5-stage, 10^mathrm{th}-order structure-preserving Gauss collocation symplectic integration scheme. GRAPE preserves the norm of the tangent vector to the test particle worldline at the order of 10^{-32}.

Language of transducer manipulation 2.0: continuing to codify terms for effective teaching

ObjectivesAccurate communication is an integral component of ultrasound education. In light of the recent global pandemic, this has become even more crucial as many have moved to virtual education out of necessity. Several studies and publications have sought to establish common terminology for cardinal ultrasound probe motions. To date, no studies have been performed to determine which of these terms have been adopted by the ultrasound community at large.MethodsA survey was developed which asked respondents to describe videos of six common probe motions in addition to providing basic demographic and training data. The survey was disseminated electronically across various academic listservs and open access resources.ResultsData were collected over a 6-week period and yielded 418 unique responses. Responses demonstrated significant variation in terminology related to all 6 cardinal probe motions. While some degree of difference in response can be accounted for by discipline of training, inter-group variation still exists in terminology to describe common probe motions. Of the survey respondents, 57.5% felt that inconsistent probe motion terminology made teaching ultrasound more difficult.ConclusionsThe results demonstrate that despite efforts to codify probe motions, variation still exists between ultrasound practitioners and educators in the description of cardinal probe motions. This lack of consensus can contribute to challenges in both virtual and in-person ultrasound education.

Rheological properties of phase transitions in polydisperse and monodisperse colloidal rod systems

AbstractRheological modifiers are added to formulations to tune rheology, enable function and drive phase changes requiring an understanding of material structure and properties. We characterize two colloidal rod systems during phase transitions using multiple particle tracking microrheology, which measures the Brownian motion of probes embedded in a sample. These systems include a colloid (monodisperse polyamide or polydisperse hydrogenated castor oil), surfactant (linear alkylbenzene sulfonate [LAS]), and nonabsorbing polymer (polyethylene oxide [PEO]) which drives gelation by depletion interactions. Phase transitions are characterized at all concentrations using time‐cure superposition. We determine that rheological evolution depends onLAS:colloid. The critical PEO concentration required to form a gel,cc/c*, is independent ofLAS:colloid, critical relaxation exponent,n, is dependent onLAS:colloid, and both are independent of colloid polydispersity.nindicates the material structure at the phase transition. AtLAS:colloid > 16, the scaffold is a tightly associated network and atLAS:colloid = 16 a loosely associated network.