Model-free robust motion control for biological optical microscopy using time-delay estimation with an adaptive RBFNN compensator.

The field of large numerical aperture microscopy has witnessed significant advancements in spatial and temporal resolution, as well as improvements in optical microscope imaging quality. However, these advancements have concurrently raised the demand for enhanced precision, extended range, and increased load-bearing capacity in objective motion carrier (OMC). To address this challenge, this study introduces an innovative OMC that employs a ball screw mechanism as its primary driving component. Furthermore, a robust nonlinear motion control strategy has been developed, which integrates fast nonsingular terminal sliding mode, experimental estimation techniques, and adaptive radial basis neural network, to mitigate the impact of nonlinear friction within the ball screw mechanism on motion precision. The stability of the closed-loop control system has been rigorously demonstrated through Lyapunov theory. Compared with other enhanced sliding mode control strategies, the maximum error and root mean square error of this controller are improved by 33% and 34% respectively. The implementation of the novel OMC has enabled the establishment of a high-resolution bio-optical microscope, which has proven its effectiveness in the microscopic imaging of retinal organoids.

Distributed observer-based finite-time control of moving target tracking for UAV formation.

This paper disseminated two formation control strategies for multiple unmanned aerial vehicles (multi-UAV) system of moving target tracking in a windy environment. The communication among UAVs is modeled by a directed graph. The first control strategy proposes a distributed dynamic error observer and a guidance law to make the system global uniform asymptotic stability when the wind disturbance is a known constant. The second control strategy employs a distributed fixed-time observer and a finite-time stable guidance law to make the system globally finite-time stable with unknown wind disturbances. The stability of both formation control strategies is rigorous demonstrated mathematically. Finally, the excellent performance and reliability of the proposed guidance law for target tracking in a windy environment are verified through several simulation examples.

NeuWS: Neural wavefront shaping for guidestar-free imaging through static and dynamic scattering media.

Diffraction-limited optical imaging through scattering media has the potential to transform many applications such as airborne and space-based imaging (through the atmosphere), bioimaging (through skin and human tissue), and fiber-based imaging (through fiber bundles). Existing wavefront shaping methods can image through scattering media and other obscurants by optically correcting wavefront aberrations using high-resolution spatial light modulators-but these methods generally require (i) guidestars, (ii) controlled illumination, (iii) point scanning, and/or (iv) statics scenes and aberrations. We propose neural wavefront shaping (NeuWS), a scanning-free wavefront shaping technique that integrates maximum likelihood estimation, measurement modulation, and neural signal representations to reconstruct diffraction-limited images through strong static and dynamic scattering media without guidestars, sparse targets, controlled illumination, nor specialized image sensors. We experimentally demonstrate guidestar-free, wide field-of-view, high-resolution, diffraction-limited imaging of extended, nonsparse, and static/dynamic scenes captured through static/dynamic aberrations.

Corrigendum: Integration: gospel for immune bioinformatician on epitope-based therapy.

[This corrects the article DOI: 10.3389/fimmu.2023.1075419.].

Softness enhanced macrophage-mediated therapy of inhaled apoptotic-cell-inspired nanosystems for acute lung injury.

Engineered nanosystems offer a promising strategy for macrophage-targeted therapies for various diseases, and their physicochemical parameters including surface-active ligands, size and shape are widely investigated for improving their therapeutic efficacy. However, little is known about the synergistic effect of elasticity and surface-active ligands. Here, two kinds of anti-inflammatory N-acetylcysteine (NAC)-loaded macrophage-targeting apoptotic-cell-inspired phosphatidylserine (PS)-containing nano-liposomes (PSLipos) were constructed, which had similar size and morphology but different Young's modulus (E) (H, ~ 100 kPa > Emacrophage vs. L, ~ 2 kPa < Emacrophage). Interestingly, these PSLipos-NAC showed similar drug loading and encapsulation efficiency, and in vitro slow-release behavior of NAC, but modulus-dependent interactions with macrophages. Softer PSLipos-L-NAC could resist macrophage capture, but remarkably prolong their targeting effect period on macrophages via durable binding to macrophage surface, and subsequently more effectively suppress inflammatory response in macrophages and then hasten inflammatory lung epithelial cell wound healing. Especially, pulmonary administration of PSLipos-L-NAC could significantly reduce the inflammatory response of M1-like macrophages in lung tissue and promote lung injury repair in a bleomycin-induced acute lung injury (ALI) mouse model, providing a potential therapeutic approach for ALI. The results strongly suggest that softness may enhance ligand-directed macrophage-mediated therapeutic efficacy of nanosystems, which will shed new light on the design of engineered nanotherapeutics.

Roadmap on Deep Learning for Microscopy.

Through digital imaging, microscopy has evolved from primarily being a means for visual observation of life at the micro- and nano-scale, to a quantitative tool with ever-increasing resolution and throughput. Artificial intelligence, deep neural networks, and machine learning are all niche terms describing computational methods that have gained a pivotal role in microscopy-based research over the past decade. This Roadmap is written collectively by prominent researchers and encompasses selected aspects of how machine learning is applied to microscopy image data, with the aim of gaining scientific knowledge by improved image quality, automated detection, segmentation, classification and tracking of objects, and efficient merging of information from multiple imaging modalities. We aim to give the reader an overview of the key developments and an understanding of possibilities and limitations of machine learning for microscopy. It will be of interest to a wide cross-disciplinary audience in the physical sciences and life sciences.

Assembly of Clay Nanotubes on Cotton Fibers Mediated by Biopolymer for Robust and High-Performance Hemostatic Dressing.

Uncontrollable bleeding from military conflicts, accidents, and surgical procedures is a major life-threatening factor. Rapid, safe, and convenient hemostasis is critical to the survival of bleeding patients in prehospital care. However, the peel-off of hemostats such as kaolinite sheets from the cotton fibers often poses a risk of distal thrombosis. Here, an efficient clay hemostat of halloysite nanotubes is tightly bound onto commercial cotton fibers, which is capillary mediated by biopolymer alginate with Ca2+ crosslinking. The robust clay nanotube dressing materials maintain high procoagulant activity after harsh water treatment, and only a few residuals of halloysite exist in the wound area. Compared with commercial hemostat QuikClot Combat gauze, halloysite-alginate-cotton composite dressing exhibits hemostatic properties both in vivo and in vitro with high safety. The hemostatic mechanism of the dressing is attributed to activating platelets, locally concentrating clotting components in the nanoclay, halloysite coagulation factors, and alginate cross-linked with Ca2+ . This work inspires robust self-assembly of clay nanotubes on textile fibers and offers a hemostatic material with balanced high hemostatic activity, minimal ingredient loss, and biocompatibility. The robust dressing based on halloysite tightly bounded cotton shows great potential for military, medical, and civil bleeding control with low health risks.

RTPN method for cooperative interception of maneuvering target by gun-launched UAV.

According to the actual situation of gun-launched UAV intercepting "Low-slow-small" target and the specific maneuverability of gun-launched UAV, an enhanced real proportion guidance law (RTPN) guidance interception method is designed. The traditional RTPN method does not consider the saturation overload limit and the capture region of arbitrary maneuvering target. In addition, aiming at the measurement error and the dynamic response delay of the gun-launched UAV during the interception, the EKF data fusion track prediction algorithm is proposed. Simulation results show that the proposed method can effectively solve the problem.

Event-triggered observer-based H∞ sliding mode control of nonlinear systems.

The problem of sliding mode control for a class of Takagi-Sugeno fuzzy model-based nonlinear one-sided Lipschitz systems is investigated in the paper. Due to the state components are not available, a state observer is designed based on an event-triggering mechanism. Meanwhile, the output measurements transmitted through the communication channels suffer from signal delays. Based on the estimated state, an integral sliding surface is proposed. Then, the sliding mode dynamics is obtained by virtue of equivalent control principle. Further, by constructing appropriate sliding mode controller, the finite-time reachability of predefined sliding surface is surely guaranteed. Moreover, the stability with an H∞ performance analysis of sliding mode dynamics is undertaken via Lyapunov function theory and the criteria are established in terms of LMI. Finally, numerical examples are provided to demonstrate the effectiveness of the proposed method.

Composite proportional-integral sliding mode control with feedforward control for cell puncture mechanism with piezoelectric actuation.

This paper presents a novel control strategy to compensate hysteretic nonlinearity and achieve precise positioning control of a cell puncture mechanism driven by a piezoelectric actuator (PEA). A dynamic model of the cell puncture mechanism is developed based on the Bouc-Wen model. Parameters of the nonlinear model are identified by particle swarm optimization. The strategy of feedforward (FF) control and sliding mode feedback (FB) control based on the Bouc-Wen inverse model is further developed to position the cell puncture mechanism. Zebrafish embryo is used as the validation object, wherein a cell micropuncture experiment is successfully performed. Proportional-integral sliding mode FB control plus FF control has a simple structure and exhibits excellent performance. Thus, this method can be easily extended to other micro-or nanopositioning mechanisms based on PEAs and adopted in practical applications.

Spatial Distribution Patterns and Driving Factors of Plant Biomass and Leaf N, P Stoichiometry on the Loess Plateau of China.

Understanding the geographic patterns and potential drivers of leaf stoichiometry and plant biomass is critical for modeling the biogeochemical cycling of ecosystems and to forecast the responses of ecosystems to global changes. Therefore, we studied the spatial patterns and potential drivers of leaf stoichiometry and herb biomass from 15 sites spanning from south to north along a 500 km latitudinal gradient of the Loess Plateau. We found that leaf N and P stoichiometry and the biomass of herb plants varied greatly on the Loess Plateau, showing spatial patterns, and there were significant differences among the four vegetation zones. With increasing latitude (decreasing mean annual temperature and decreasing mean precipitation), aboveground and belowground biomass displayed an opening downward parabolic trend, while the root-shoot ratio gradually decreased. Furthermore, there were significant linear relationships between the leaf nitrogen (N) and phosphorus (P) contents and latitude and climate (mean annual rainfall and mean annual temperature). However, the leaf N/P ratio showed no significant latitudinal or climatic trends. Redundancy analysis and stepwise regression analysis revealed herb biomass and leaf N and P contents were strongly related to environmental driving factors (slope, soil P content and latitude, altitude, mean annual rainfall and mean annual temperature). Compared with global scale results, herb plants on the Loess Plateau are characterized by relatively lower biomass, higher N content, lower P content and a higher N/P ratio, and vegetative growth may be more susceptible to P limitation. These findings indicated that the remarkable spatial distribution patterns of leaf N and P stoichiometry and herb biomass were jointly regulated by the climate, soil properties and topographic properties, providing new insights into potential vegetation restoration strategies.

Roles of visual and non-visual information in the perception of scene-relative object motion during walking.

Perceiving object motion during self-movement is an essential ability of humans. Previous studies have reported that the visual system can use both visual information (such as optic flow) and non-visual information (such as vestibular, somatosensory, and proprioceptive information) to identify and globally subtract the retinal motion component due to self-movement to recover scene-relative object motion. In this study, we used a motion-nulling method to directly measure and quantify the contribution of visual and non-visual information to the perception of scene-relative object motion during walking. We found that about 50% of the retinal motion component of the probe due to translational self-movement was removed with non-visual information alone and about 80% with visual information alone. With combined visual and non-visual information, the self-movement component was removed almost completely. Although non-visual information played an important role in the removal of self-movement-induced retinal motion, it was associated with decreased precision of probe motion estimates. We conclude that neither non-visual nor visual information alone is sufficient for the accurate perception of scene-relative object motion during walking, which instead requires the integration of both sources of information.

Vernier effect of two cascaded in-fiber Mach-Zehnder interferometers based on a spherical-shaped structure.

The Vernier effect of two cascaded in-fiber Mach-Zehnder interferometers (MZIs) based on a spherical-shaped structure has been investigated. The envelope based on the Vernier effect is actually formed by a frequency component of the superimposed spectrum, and the frequency value is determined by the subtraction between the optical path differences of two cascaded MZIs. A method based on band-pass filtering is put forward to extract the envelope efficiently; strain and curvature measurements are carried out to verify the validity of the method. The results show that the strain and curvature sensitivities are enhanced to -8.47 pm/µÎµ and -33.70 nm/m-1 with magnification factors of 5.4 and -5.4, respectively. The detection limit of the sensors with the Vernier effect is also discussed.

Out-of-Plane Rotation Control of Biological Cells With a Robot-Tweezers Manipulation System for Orientation-Based Cell Surgery.

In many cell surgery applications, cell must be oriented properly such that the microsurgery tool can access the target components with minimum damage to the cell. In this paper, a scheme for out of image plane orientation control of suspended biological cells using robotic controlled optical tweezers is presented for orientation-based cell surgery. Based on our previous work on planar cell rotation using optical tweezers, the dynamic model of cell out-of-plane orientation control is formulated by using the T-matrix approach. Vision-based algorithms are developed to extract the cell out of image plane orientation angles, based on 2-D image slices obtained under an optical microscope. A robust feedback controller is then proposed to achieve cell out-of-plane rotation. Experiments of automated out of image plane rotational control for cell nucleus extraction surgery are performed to demonstrate the effectiveness of the proposed approach. This approach advances robot-aided single cell manipulation and produces impactful benefits to cell surgery applications such as nucleus transplantation and organelle biopsy in precision medicine.

Achieving Automated Organelle Biopsy on Small Single Cells Using a Cell Surgery Robotic System.

Single cell surgery such as manipulation or removal of subcellular components or/and organelles from single cells is increasingly used for the study of diseases and their causes in precision medicine. This paper presents a robotic surgery system to achieve automated organelle biopsy of single cells with dimensions of less than 20 µm in diameter. The complexity of spatial detection of the organelle position is reduced by patterning the cells using a microfluidic chip device. A sliding mode nonlinear controller is developed to enable extraction of organelles, such as the mitochondria and the nucleus, from single cells with high precision. An image processing algorithm is also developed to automatically detect the position of the desired organelle. The effectiveness of the proposed robotic surgery system is demonstrated experimentally with automated extraction of mitochondria and nucleus from human acute promyelocytic leukemia cells and human fibroblast cells. Extraction is followed by biological tests to indicate the functionality of biopsied mitochondria as well as the cell viability after removal of mitochondria. The results presented here have revealed that the proposed approach of automated organelle biopsy on single small cells is feasible.

Manipulation of Biological Cells Using a Robot-Aided Optical Tweezers System.

This article reviews the autonomous manipulation strategies of biological cells utilizing optical tweezers, mainly including optical direct and indirect manipulation strategies. The typical and latest achievements in the optical manipulation of cells are presented, and the existing challenges for autonomous optical manipulation of biological cells are also introduced. Moreover, the integrations of optical tweezers with other manipulation tools are presented, which broadens the applications of optical tweezers in the biomedical manipulation areas and will also foster new developments in cell-based physiology and pathology studies, such as cell migration, single cell surgery, and preimplantation genetic diagnosis (PGD).

Predictors for nephrology outpatient care and recurrence of acute kidney injury (AKI) after an in-hospital AKI episode.

Acute kidney injury (AKI) is associated with increased long-term risk of end-stage kidney disease (ESKD) and mortality. Nephrology care following discharge from hospital may improve survival through prevention of recurrent AKI events. In this study, we examined the factors that were associated with outpatient nephrology follow-up after the development of AKI on patients who had a nephrology in-hospital consultation and were discharged from McGill University Health Centre between January 1, 2006 and December 31, 2010. The associated factors for AKI-free survival postdischarge were assessed applying multivariate Cox hazard proportional models. Of 170 patients, only 22% of the AKI admissions studied were booked with nephrology follow-up after discharge. The unadjusted hazard ratio (HR) of outpatient nephrology care postdischarge was 1.82 (95% confidence interval [CI] 0.93-3.56) for AKI-free survival postdischarge. The adjusted HR was 2.04 (95% CI 1.01-4.12) when we adjusted for follow-up with other medical clinics, significant stage 4 and stage 5 chronic kidney disease and diabetes status. Patients with less comorbidities and higher serum creatinine on discharge received outpatient nephrology care. Nephrology outpatient care is associated with decreased risk of recurrence of AKI after discharge from hospital.

Influence of carbon nanotubes microstructures inside composites on the loading role of nanotubes bore.

To fully utilize the extraordinary mechanical properties of carbon nanotubes (CNTs) in composites, great attention has been paid to prepare CNTs based composites with uniformly dispersion and strong interfacial adhesion. With the help of micro-Raman spectroscopy, herein, we study the influence of nanotube microstructures (e.g., dispersion and orientation) on the loading role of nanotubes bore. By using the same batch of composite solutions, two types of composite materials with different nanotube morphologies were prepared by electrospun and solution casting methods. Raman results have revealed that the loading-role of nanotubes bore in the electrospun nonwoven mats is much stronger than that of regular composite films owing to its uniformly dispersion as well as high orientation.