A Multidrug Delivery Microrobot for the Synergistic Treatment of Cancer.

Multidrug combination therapy provides an effective strategy for malignant tumor treatment. This paper presents the development of a biodegradable microrobot for on-demand multidrug delivery. By combining magnetic targeting transportation with tumor therapy, it is hypothesized that loading multiple drugs on different regions of a single magnetic microrobot can enhance a synergistic effect for cancer treatment. The synergistic effect of using two drugs together is greater than that of using each drug separately. Here, a 3D-printed microrobot inspired by the fish structure with three hydrogel components: skeleton, head, and body structures is demonstrated. Made of iron oxide (Fe3 O4 ) nanoparticles embedded in poly(ethylene glycol) diacrylate (PEGDA), the skeleton can respond to magnetic fields for microrobot actuation and drug-targeted delivery. The drug storage structures, head, and body, made by biodegradable gelatin methacryloyl (GelMA) exhibit enzyme-responsive cargo release. The multidrug delivery microrobots carrying acetylsalicylic acid (ASA) and doxorubicin (DOX) in drug storage structures, respectively, exhibit the excellent synergistic effects of ASA and DOX by accelerating HeLa cell apoptosis and inhibiting HeLa cell metastasis. In vivo studies indicate that the microrobots improve the efficiency of tumor inhibition and induce a response to anti-angiogenesis. The versatile multidrug delivery microrobot conceptualized here provides a way for developing effective combination therapy for cancer.

Distributed tracking control for multiple Euler-Lagrange systems with communication delays and input saturation.

This study mainly investigates the problem of distributed tracking control for time-varying delay existing multiple Euler-Lagrange systems considering full-state constraints and input saturation under the directed graph. Specifically, the system under consideration consists of system uncertainties and external disturbances. In the control law design, a distributed observer is first designed that the followers can obtain the leader's time-varying information. Then the barrier Lyapunov function technique is used to make sure the system errors can converge to a certain range while the anti-windup method is utilized to overcome the influence of control input saturation. Further, in order to prevent chattering, an adaptive law is given. Numerical simulations are given to verify the proposed algorithms.

Automated In Vivo Navigation of Magnetic-Driven Microrobots Using OCT Imaging Feedback.

OBJECTIVE: The application of in vivo microrobot navigation has received considerable attention from the field of precision therapy, which uses microrobots in living organisms. METHODS: This study investigates the navigation of microrobots in vivo using optical coherence tomography (OCT) imaging feedback. The electromagnetic gradient field generated by a home-made electromagnetic manipulation system is magnetically modeled. With this model, the magnetic force acting on the microrobot is calculated, and the relationship between this force and the velocity of the microrobot is characterized. RESULTS: Results are verified through in vitro experiments wherein microrobots are driven in three types of fluid, namely, normal saline, gastric juice, and mouse urine. In vivo experiments are performed to navigate the microrobot in a mouse portal vein in which the OCT imaging system tracks the microrobot in vivo. CONCLUSIONS: Experimental results demonstrate the effectiveness of the proposed approach. The microrobots can be magnetically driven in the in vivo environment using the OCT imaging feedback. SIGNIFICANCE: The significance of this study lies in providing a new method of driving microrobots in vivo.