Microswarms face challenges in precise delivery within dynamic biological fluids due to fluid disturbances and limited operational intuitiveness. Current approaches insufficiently utilize the operator’s perceptual awareness and interactive decision-making capabilities, particularly in complex tasks that require a balance between flexibility and precision. In this study, we propose a haptic-assisted magnetic actuation control strategy, establishing a human-in-the-loop control framework. The haptic perception system provides the operator with haptic feedback reflecting the interactions between the microswarm and the environment. A real-time tracking system monitors the position and pattern of the controlled microswarm in remote environments, and transmits this information to the control system for decision-making. After characterizing the magnetic field parameters and magnetic nanoparticles, we have achieved real-time navigation and morphology modulation of the microswarm in dynamic flow conditions and three-dimensional (3D) space. Comparative experiments under various flow rate conditions demonstrate that the haptic-assisted strategy enhances microswarm control stability and precision across different flow regimes. Moreover, the human-machine collaboration mechanism improves delivery success rates (97%) under sudden disturbances compared to preprogrammed automated control and purely manual control, validating its potential for applications in complex biomedical scenarios. Our work provides a haptic-assisted microswarm control method in dynamic conditions, expanding an adaptive microswarm control strategy in complex biomedical environments.

Photothermal therapy represents a promising therapeutic approach due to its non-invasiveness and spatiotemporal controllability. However, conventional nanoparticle-based systems are limited by low conversion efficiency, quick heat dissipation, and the high dosages required for sufficient therapeutic hyperthermia. Although micro/nanorobotic platforms improve targeting, they still face challenges in achieving adequate localized heat safely, often requiring high material concentrations that risk vascular complications. To address these limitations, this work introduces a strategy leveraging magnetically regulated swarming dynamics to amplify photothermal conversion. With designed magnetic actuation, building blocks are organized into the reconfigurable microswarm, achieving localized densification that minimizes heat dissipation and achieves photothermal amplification under near-infrared (NIR) light. Compared with the dispersive state, the microswarm exhibits a 23 ̊C enhancement owing to its boosted photothermal conversion efficiency and great thermal stability across variable scales, effectively overcoming rapid heat dissipation in dynamic environments. Besides, magnetically controlled reconfiguration allows tunable heating areas, balancing spatial coverage and therapeutic intensity. Compared with dispersive systems, a 7-fold improvement in the cancer cell-killing efficiency of the microswarm can be achieved via photothermal amplification. This work establishes a photothermal amplification strategy to overcome limitations of passive diffusion and dosage dependence, pioneering a versatile nanorobotic platform for precision photothermal-based treatment.

Endovascular embolization is one of the core techniques in minimally invasive interventional medicine. It allows catheters to be accurately delivered to target blood vessels under image guidance for the implantation of embolic materials to achieve vascular occlusion. Although this technique has become increasingly mature, it still faces major challenges in precise delivery due to the limitations of embolic-agent properties and design concepts, restricting further improvement of the embolization therapeutic efficacy. Driven by continuous breakthroughs in materials science and control engineering, as well as the inevitable trend of medical development toward miniaturization, precision, and intelligence, microrobots show broad application prospects in precision disease treatment. They present advantages in accurate embolization and remote control in endovascular embolization, which can effectively improve embolization outcomes and reduce the risk of ectopic embolism. Taking the embolic microrobot system as the research focus, this paper systematically elaborates the design strategies, validation models, and practical applications of magnetically actuated embolic microrobots, comprehensively evaluates various imaging systems, and summarizes the supporting magnetic actuation technologies. It concludes the multimodule collaboration and adaptation framework of embolic microrobot systems. Finally, it analyzes the current limitations and potential translational challenges and presents a systematic prospect of its future development trends.

Microrobotic swarms, through their collective and reconfigurable behaviours, can flexibly adapt to various targeted delivery and navigation tasks. However, achieving autonomous navigation and obstacle avoidance in unknown environments remains a challenge. Here we propose a reinforcement-learning-based control strategy for swarm navigation under partial observation. To bridge the gap between simulation and reality, we introduce a generalized sim-to-real transfer method, enabling the simulation-trained swarm to effectively explore in unknown environments. Our model combines temporally extended attention with multi-level domain randomization of the environment, perception, actuation and dynamics, allowing the policy to use current sensory inputs and historical context to select magnetic actuation commands. Our model efficiently performs autonomous navigation and obstacle avoidance through benchmarking against human operators in simulated environments. The proposed strategy enables swarm navigation and dynamic obstacle avoidance, cargo transportation, moving target tracking and recovery from temporary vision loss, and hovering by its partial sensing and decision-making. Analysis of action sequences and attention scores reveals that the swarm makes task-priority-based decisions, optimizing trajectories towards the target in unknown environments.

Magnetic actuation is a promising approach in the robotic manipulation field, enabling wireless manipulation for small-scale operations. However, selective three-dimensional (3D) manipulation of multiple magnetic microrobots under global magnetic fields remains a challenge. This paper presents a dynamic magnetic modeling and vision-guided control strategy to realize 3D manipulation of magnetic microrobots, including patch-robot-assisted collective delivery and microrobot screening. An impedance regulation-based position control method is proposed, leveraging theoretical analysis of electromagnetic forces and fluid drag to accommodate microrobots with diverse morphologies. Through trajectory motion experiments, our control strategy ensures that the mean absolute errors (MAE) of the microrobots are consistently below 200 μm. By utilizing patch robot adhesion and differential magnetic responses among the microrobots, this strategy enables selective manipulation and collective sorting in a 3D space. Applications in patch-robot-assisted delivery, collective sorting and screening are validated. The proposed approach advances magnetic microrobot control by enabling spatially selective operations critical for biomedical tasks.

Microrobotic swarms have gained considerable attention due to their ability to adapt and collaborate for complex tasks. However, achieving precise control over their collective behavior for both autonomous navigation and on-demand pattern transformation, especially in the context of manipulation, remains a critical challenge. Here, we introduce a hierarchical framework that integrates Transformer-based reinforcement learning to enable a microrobotic swarm to autonomously navigate, avoid obstacles, and adjust its pattern configuration. By incorporating domain randomization, our approach allows direct transfer from simulation to real-world deployment without requiring additional fine-tuning. Through experiment validation, we demonstrate that the swarm can not only navigate through complex and dynamic environments but also adapt its formation for efficient cargo transportation, even when the tasks were not part of the training data. This work offers a scalable solution for deploying microrobotic swarms that can autonomously perform both targeted navigation and on-demand pattern control, making them suitable for a wide range of applications in constrained environments.

Magnetic microrobots hold great promise for biomedical applications. However, achieving flexible magnetic field adjustment with a magnetic actuation system (MAS) to actuate diverse microrobots remains a significant challenge. In this work, we propose an Electromagnetic-Permanent Magnet Actuation (EPMA) system that generates controllable magnetic field variations to enable microrobot actuation for diverse tasks, including microrobotic actuation, microswarm pattern transformation and targeted delivery. Automatic ellipsoid calibration of the Hall sensors enables real-time magnetic field orientation measurement with an error under 3? Experimental results demonstrate the microrobot's actuation performance in four distinct scenarios, with a rotation frequency of 0.5 Hz. Furthermore, by adjusting the dynamic magnetic field, we achieve microswarm pattern reconfiguration under static conditions as well as targeted delivery in fluidic environments at a flow speed of 52 mm/s and a rotation frequency of 4 Hz. This study presents a hybrid MAS for the microrobotic actuation in diverse environments by controllable dynamic magnetic fields.

Magnetic actuation is a promising approach in the robotic manipulation field, enabling wireless manipulation for small-scale operations. However, selective three-dimensional (3D) manipulation of multiple magnetic microrobots under global magnetic fields remains a challenge. This paper presents a dynamic magnetic modeling and vision-guided control strategy to realize 3D manipulation of magnetic microrobots, including patch-robot-assisted collective delivery and microrobot screening. An impedance regulation-based position control method is proposed, leveraging theoretical analysis of electromagnetic forces and fluid drag to accommodate microrobots with diverse morphologies. Through trajectory motion experiments, our control strategy ensures that the mean absolute errors (MAE) of the microrobots are consistently below 200 mu m. By utilizing patch robot adhesion and differential magnetic responses among the microrobots, this strategy enables selective manipulation and collective sorting in a 3D space. Applications in patch-robot-assisted delivery, collective sorting and screening are validated. The proposed approach advances magnetic microrobot control by enabling spatially selective operations critical for biomedical tasks.

Wearable microfluidic sensors represent a promising advancement in the field of noninvasive health monitoring, providing continuous and personalized insights into the physiological status of an individual. With all-in-one wearable devices, human sweat can be collected, transported, and analyzed noninvasively through a large number of biochemical biomarkers in human sweat including glucose, lactate, uric acid, cortisol, and various ions. In this review, the state-of-art wearable microfluidic noninvasive sensors for biomarker monitoring in sweat are classified into four subtopics according to the sweat analysis method: electrochemical sweat analysis, colorimetric sweat analysis, fluorometric and plasmonic sweat analysis, and hybrid sweat analysis. In addition, the research trend of wearable microfluidic noninvasive sensors for sweat analysis is outlooked.

Magnetic continuum robots (MCRs) have garnered substantial attention as a new class of flexible robotic systems capable of navigating complex and confined spaces with remarkable dexterity. By combining continuous, deformable structures with remotely applied magnetic fields, MCRs achieve contactless, remote manipulation, making them well-suited for medical applications. This review introduces recent advances in MCR research, focusing on design principles, structural configurations, and control strategies. Various MCR designs and structures, including those integrated with permanent magnets, magnetic matter, ferromagnetic sphere, and micro coil, are discussed. Furthermore, different magnetic actuation platforms are introduced, and the level of MCR automation is classified based on control strategies. Key intelligent manipulation capabilities of MCRs, including navigation, delivery, printing, grasping, imaging, and sensing are explored. Finally, future development priorities and directions are identified to provide insights for advancing intelligent robotic systems.

Antibiotic residues in food and the environment pose significant risks to public health and safety, necessitating the development of rapid, portable, and efficient detection methods. Ofloxacin (OFL), a widely used antibiotic, is of particular concern due to its potential for contamination in milk and surface water. Current detection methods often require expensive instrumentation and complex procedures, limiting their applicability for on-site testing. This work addresses the critical need for a cost-effective, portable approach to reliably detect OFL residues. We developed a novel personal glucose meter (PGM)-based aptasensor utilizing a porous spherical cerium-based metal-organic framework (Ce-MOF) as a loading platform for glucose oxidase (GOx) and oligonucleotide sequences (Ce-MOF-GOx-cDNA). The hybrid probe, formed by conjugating Ce-MOF-GOx-cDNA with aptamer-modified magnetic beads, enabled specific recognition of OFL through nucleobase pairing. The sensor exhibited a detection range of 50 pg/mL to 500 ng/mL with a detection limit of 40 pg/mL under optimal conditions. The process showed excellent selectivity, stability, and reproducibility. Real-sample testing in spiked milk and surface water demonstrated recovery rates of 99.5% - 108%, with relative standard deviations of less than 4.7%. This study presents a portable and efficient strategy for detecting OFL residues using a PGM-based aptasensor. The method combines simplicity, rapid detection, and high sensitivity, offering significant potential for on-site applications in food and environmental safety monitoring.

Breaking through cell membrane barriers is a crucial step for intracellular drug delivery in antitumor chemotherapy. Hereby, a magnetic nanorobot, capable of exerting mechanical agitation on cellular membrane to promote intracellular drug delivery, was developed. The main body of the nanorobots was composed of nano-scaled gold nanospikes that were deposited with Ni and Ti nanolayers for magnetic activation and biocompatibility, responsively. The nanorobots can be precisely navigated to target cancer cells under external magnetic field control. By virtue of the sharp nanospike structures, the magnetically powered rotation behavior of the nanorobots can impose mechanical agitation on the living cell membrane and thus improve the membrane permeability, leading to promoted transmembrane cargo delivery. Coarse-grained molecular dynamics simulation revealed that the mechanism of mechanical intervention regulated permeability of the bilayer lipid membrane, allowing for enhanced transmembrane diffusion of small cargo molecules. An in vitro study demonstrated that these nanorobots can markedly enhance the efficiency of drug entry into tumor cells, thus improving the effectiveness of tumor therapy under magnetic activation in vivo. This work paves a new way for overcoming cell membrane barriers for intracellular drug delivery by using a magnetic nanorobotic system, which is expected to promote further application of magnetically controlled nanorobot technology in the field of precision medicine.

Introducing the inherent genetic diversity of wild species into cultivars has become one of the hot topics in crop genetic breeding and genetic resource research. Fiber- and seed-related traits, which are critical to the global economy and people’s livelihoods, are the principal focus of cotton breeding. Here, the wild cotton species Gossypium tomentosum was used to broaden the genetic basis of G. hirsutum and identify QTLs for fiber- and seed-related traits. A population of 559 chromosome segment substitution lines (CSSLs) was established with various chromosome segments from G. tomentosum in a G. hirsutum cultivar background. Totals of 72, 89, and 76 QTLs were identified for three yield traits, five fiber quality traits, and six cottonseed nutrient quality traits, respectively. Favorable alleles of 104 QTLs were contributed by G. tomentosum. Sixty-four QTLs were identified in two or more environments, and candidate genes for three of them were further identified. The results of this study contribute to further studies on the genetic basis of the morphogenesis of these economic traits, and indicate the great breeding potential of G. tomentosum for improving the fiber- and seed-related traits in G. hirsutum.

Magnetic microrobots are showing great potential in micromanipulation due to the capability of motion control under external fields. However, achieving selective control of magnetic microrobots in three-dimensional (3D) space using global magnetic fields still presents a challenge. In this work, we propose a selective control strategy based on a movable electromagnetic coil system, incorporating a mass-spring-damping model to achieve precise control of cell microrobots in 3D space. By combining theoretical analysis with vision-based feedback, experiments are demonstrated in different scenarios, including step climbing and ring traversal, validating the control capability in different environments. Furthermore, by utilizing the differences in magnetic responses among cell microrobots, this strategy enables selective manipulation of multiple cell microrobots, demonstrating real-time sorting manipulation in a 3D space. Our work presents a strategy that can be applied to selectively manipulate magnetic microrobots in complex environments.

Tendon repair remains challenging owing to the limited capacity for endogenous repair. Vasoactive intestinal peptide (VIP) promotes bone tissue regeneration; however, its role in tendon repair remains unclear. In the present study, we demonstrated that VIP stimulated M2 polarization of macrophages and facilitated tendon regeneration by regulating immune homeostasis and maintaining the function of tendon stem/progenitor cells (TSPCs). Additionally, we established GelMa-loaded VIP@PLGA@ZIF-8 (VPZ) nanoparticles (VPZG) to enable the sustained and localized release of VIP at the site of patellar tendon injury in SD rats. The results of the in vitro experiments demonstrated that VPZG regulated the homeostasis of macrophage polarization by downregulating the NF-κB axis. VPZG also promoted efferocytosis and suppressed the release of proinflammatory factors. Additionally, VPZG enhanced the tenogenic differentiation of TSPCs when cocultured with macrophages. In vivo, we implanted VPZG at the site of patellar tendon injury, where it released VIP sustainably and slowly to promote tendon regeneration. This effect was achieved through the downregulation of the expression levels of various inflammatory factors, as well as the regulation of local immune homeostasis. In conclusion, our results demonstrated that VPZG facilitated tendon injury repair by regulating immune homeostasis and enhancing TSPC function. These findings suggest that VPZG is a promising avenue for the clinical improvement of tendon injury treatment.

A porous, small-sized Ce-based metal-organic framework (Ce-UiO-66) was synthesized using a simple and mild method. By integrating this material with an Mg2+-driven DNAzyme signal amplification strategy, a targeted responsive release system was developed for electrochemical aptasensors, enabling sensitive and selective detection of ofloxacin (OFL). Ce-UiO-66 served as an intelligent controlled-release platform, with cleavable hairpin DNA (HP) acting as a gating element to encapsulate methylene blue (MB) within its pores. In the presence of OFL, the aptamer-DNAzyme complex transitioned from a stable to a dissociated state, releasing DNAzyme to the electrode interface, where it recognized the enzyme cleavage site on HP, initiating a catalytic cleavage cycle and releasing substantial amounts of MB. To further enhance aptasensor performance, AuPt NPs/PEI-rGO was employed as the electrode modification material, significantly improving the conductivity and increasing the electrode's surface area, thereby providing more binding sites for the released MB. Under optimized conditions, the aptasensor achieved a detection limit of 0.058 pg/mL and a broad detection range from 1 x 10-7 to 1 mu g/mL. This study offers new insights into the design of targeted responsive release systems and expands their potential applications, particularly in rapid food safety detection, demonstrating both practicality and sensitivity.

NIN-like proteins (NLPs) are evolutionarily conserved transcription factors that play a key role in regulating plant physiological responses to changes in external nitrogen levels. Although NLP genes have been extensively studied in various plant species, a comprehensive analysis of the NLP gene family in cotton (Gossypium spp.) remains lacking. In this study, 65 NLP genes were identified across four cotton species (G. raimondii, G. barbadense, G. arboreum, and G. hirsutum) and were classified into three groups. Analyses of protein characteristics, phylogeny, gene structure, conserved motifs, and gene expression were conducted. Gene family expansion of GhNLPs was primarily driven by fragment duplication. RNA-seq and qRT-PCR analyses showed that GhNLP2.1 was significantly upregulated by nitrogen treatments in cotton roots. Its expression level increased in response to higher nitrogen concentrations. Overexpression of GhNLP2.1 in Arabidopsis resulted in improved growth and enhanced activities of nitrogen metabolism-related enzymes under low nitrogen conditions compared to sufficient nitrogen conditions. Silencing of GhNLP2.1 through virus-induced gene silencing significantly impaired nitrogen accumulation and utilization in cotton. This study enhances our understanding of GhNLP genes, highlights their role in regulating nitrogen use efficiency in upland cotton, and provides a foundation for future research on GhNLP2.1 function.

Magnetic microrobots (MMRs), driven by electromagnetic actuation systems, offer promise for biomedical uses such as targeted drug delivery and minimally invasive therapy, but their motion control is hindered by environmental and system constraints. We propose a magnetic trap strategy to guide MMRs. Earnshaw’s theorem confirms that stable 3D magnetic traps are impossible, so we constrain the Z-axis to form 2D traps in the X–Y plane. Experiments achieved control with errors below 2 mm at 1,024 of 1,331 test points, demonstrating feasibility under constraints. This work provides theoretical insight and practical, robust guidance for controlling MMRs with an electromagnetic actuation system in biomedical scenarios.

Collective microrobots enable controlled batch delivery, showing promising application in the biomedical field. However, significant challenges remain in achieving long-distance delivery of collective microrobots in dynamic environments. This study proposes a magnetic actuation strategy for delivering collective cell microrobots in flowing conditions. A magnetic actuation method is developed, and a mobile actuation system with multiple coils coordination is designed to generate spatially isotropic magnetic fields. Experiments of delivering collective microrobots are conducted in flowing conditions, including downstream and upstream with an average flow velocity up to 8.84 mm/s. Results demonstrate that the proposed actuation strategy enhances driving performance in dynamic environments, achieving long-distance delivery of collective microrobots (over 548 mm). The final access rate of microrobots reaches 90.63% and 94.79% in upstream and downstream conditions, respectively. Our strategy provides an efficient control method for delivering collective microrobots, showing potential for targeted delivery in biomedical applications.