Sharp nanothorn-equipped ionogel microrobots for targeted periodontitis therapy

Dongqing He; Zhaolei Zou; Dongdong Jin; Zichang Guo; Yinuo Song; Qiannan Hu; Muqiao Yu; Jingyi Lu; Juan Fang; Qianqian Wang; Chengqi Xu; Wenjun Chen; Zhi Wang; Xing Ma

doi:10.1126/sciadv.aeb6882

. 2026 Aug 5;12(32):eaeb6882. doi: 10.1126/sciadv.aeb6882

Sharp nanothorn-equipped ionogel microrobots for targeted periodontitis therapy

Dongqing He ^1,^2,^†, Zhaolei Zou ^3,^†, Dongdong Jin ^2,^*, Zichang Guo ², Yinuo Song ², Qiannan Hu ³, Muqiao Yu ³, Jingyi Lu ³, Juan Fang ³, Qianqian Wang ⁴, Chengqi Xu ⁵, Wenjun Chen ², Zhi Wang ^3,^*, Xing Ma ^1,^2,^*

PMCID: PMC13440429 PMID: 42555738

Abstract

Periodontitis necessitates targeted therapy due to its high prevalence, progressive tissue destruction, and systemic disease links. Conventional mechanical debridement and pharmacological treatments are limited by complex periodontal barriers, including viscous crevicular fluid and resilient biofilms, which impede bacterial eradication and drug delivery. Here, we engineered magnetically actuated microrobots with gold nanothorns for disrupting biofilms and penetrating mucus barriers. Fabricated by encapsulating curcumin in antibacterial ionogel microspheres with asymmetric magnetic deposition and nanothorn functionalization, these microrobots enabled precise magnetic navigation in viscous media, while penetrating a biomimetic mucus analog, enhancing periodontal retention, and mechanically dislodging biofilms. Furthermore, ethanol-responsive release of curcumin enhanced its bioavailability, thereby scavenging free radicals and modulating macrophage phenotypes to alleviate inflammation. Guided by a toothbrushing-inspired handheld magnetic controller, microrobots evaluated using in vivo murine models demonstrated reduced inflammation, inhibited bone resorption, improved tissue health, and oral microbiota remodeling toward ecological balance, showing promise for targeted periodontitis therapy.

Nanothorned magnetic microrobots penetrate a high-viscosity surrogate mucus, disrupt biofilms, and improve murine periodontitis.

INTRODUCTION

Periodontitis, a highly prevalent chronic inflammatory disease affecting over 50% of adults globally, originates from dysbiotic bacterial biofilms that trigger progressive destruction of periodontal structures (1). Characterized initially by gingival erythema and edema, this pathology advances to irreversible degradation of periodontal ligaments, cementum, and alveolar bone, ultimately culminating in tooth loss (2). Critically, sustained periodontal inflammation propagates systemic ramifications via hematogenous dissemination of pathogens and inflammatory mediators, establishing confirmed associations with gastrointestinal disorders, diabetes mellitus, carcinogenesis, and adverse cardiovascular outcomes (3, 4). Consequently, effective therapeutic intervention necessitates comprehensive elimination of pathogenic biofilms, suppression of local inflammation, and ultimately restoration of periodontal tissue homeostasis, objectives fundamental to halting disease progression and mitigating systemic health impacts (3, 5).

Current clinical paradigms predominantly rely on mechanical debridement (e.g., ultrasonic scaling) and adjunctive pharmacotherapy, yet both approaches confront substantial limitations imposed by the complex periodontal microenvironment (5, 6). Mechanical instrumentation suffers from restricted physical access to deep periodontal pockets and anatomical intricacies, often resulting in incomplete biofilm removal that perpetuates inflammatory cascades and impedes tissue regeneration (7). Meanwhile, conventional drug delivery is critically compromised by multilevel biological barriers: continuous salivary secretion rapidly clears administered agents (8); the highly viscous gingival crevicular fluid/mucus within pockets severely retards passive drug diffusion (9); the complex and mechanically stable architecture of biofilms hinders antibacterial drugs from reaching and eliminating internal bacteria (10); and the dense mucosal barrier further obstructs drug penetration into deeper infected tissues (11). These collective barriers profoundly diminish therapeutic efficacy against subgingival biofilms and periodontitis (12).

Micro/nanorobots, defined as miniaturized devices capable of converting intrinsic chemical energy or extrinsic physical stimuli into autonomous motility (13–15), offer transformative potential for biomedical applications. Their unique advantages, including microscale navigation capability, controllable propulsion, and force-generating capacity, enable precise operations within confined biological spaces (16, 17). To date, micro/nanorobots have demonstrated versatile functionalities in targeted drug delivery (18), biological imaging (19), embolization and thrombolysis therapy (20, 21), and biosensing (14). Particularly relevant to infectious diseases, they exhibit promising antibiofilm capabilities (22, 23) through multiple mechanisms, such as catalytic generation of antibacterial species [e.g., reactive oxygen species (ROS)] (24, 25), spatially controlled antibiotic release (26), and photothermal ablation (27, 28). Notably, their active propulsion allows penetration through formidable biological barriers (29–31), including hemorheological barrier (32), gastrointestinal mucus (33), and cellular membranes (34). Currently, several studies have advanced the application of micro/nanorobots in the treatment of oral diseases (6, 9, 24, 35–40), represented by periodontitis (table S1). While these advances have revolutionized superficial biofilm management in accessible anatomical sites [e.g., magnetically steered microrobots for catheter decontamination (41) and enzyme-powered nanoswarms for wound biofilm disruption (42)], their application against periodontitis faces exceptional challenges. The deeply entrenched biofilms within anatomically tortuous gingival sulci, typically measuring <3 mm in width (3), coupled with the viscoelastic resistance of periodontal biobarriers, critically impair micro/nanorobots’ targeting accuracy and motility efficiency. Overcoming these constraints represents a pivotal frontier in advancing precision periodontitis therapy.

In this work, we propose magnetically driven microrobots featuring nanothorns for targeted periodontitis treatment (Fig. 1). The microrobots were fabricated using antibacterial ionogel microspheres as carriers for the hydrophobic drug curcumin, followed by asymmetric deposition of magnetic nanolayers and surface modification with sharp gold nanothorns. This unique design facilitated precise control and targeted navigation of both individual microrobot and swarms under magnetic actuation, enabling penetration through a high-viscosity surrogate mucus analog (used to simulate the salivary and periodontal mucus barrier). Simultaneously, the mechanical force generated by the nanothorns effectively removed the bacterial biofilms entrenched in confined gingival sulci. Moreover, the nanothorns substantially enhanced microrobot anchoring at targeted gingival tissue sites. Consequently, the drug curcumin embedded in microrobots with controlled ethanol-responsive release property performed enhanced bioavailability, while scavenging free radicals and modulating macrophage phenotype, thereby alleviating inflammation. Inspired by daily toothbrushing, we further designed a handheld magnetic controller for activating microrobotic therapeutic platform within the complex periodontal microenvironment. As demonstrated in murine models, although direct quantitative evidence of microrobot penetration across all native tissue layers is not provided, periodontitis-induced inflammation was effectively alleviated following treatment, accompanied by inhibition of pathological bone resorption and improvement in periodontal tissue health. Furthermore, the oral microbiota was remodeled, promoting ecological balance within the periodontal microenvironment. Therefore, this magnetically driven microrobotic platform may inform future development of noninvasive, targeted strategies for periodontitis therapy.

RESULTS

Preparation and characterization of magnetic ionogel-based microrobots

Ionogels, polymeric networks immobilizing ionic liquids (ILs), have emerged as advanced functional materials due to their exceptional environmental stability, intrinsic self-healing capability, and tunable ionic conductivity (43, 44). Their unique matrix architecture facilitates controlled uptake/release of therapeutic cargoes (45, 46) (e.g., drug molecules), positioning them as ideal platforms for multifunctional microrobots. Capitalizing on these properties, we engineered magnetic ionogel-based microrobots through sequential fabrication steps (Fig. 1). Bulk ionogel was first synthesized by codissolving poly(lactic-co-glycolic acid) (PLGA) and 1-butyl-3-methylimidazolium hexafluorophosphate ([BMIM]PF₆) in a cosolvent followed by solvent volatilization (Fig. 2, A and B). Notably, the solvent evaporation method enables morphological control via template-directed assembly (47). Specifically, curcumin drug-loaded ionogel microspheres (∼10 μm diameter, fig. S1) were generated through emulsion solvent evaporation, using emulsion droplets as soft templates. Subsequently, a 200-nm Fe layer and 20-nm Pt layer were deposited asymmetrically on the microspheres via electron-beam evaporation, endowing them with magnetic responsiveness and catalytic functionality. The synthetic yield and the cost of Pt electron-beam evaporation were analyzed in fig. S2. Furthermore, Au nanothorns were catalytically grown on the Pt surface using our previously established protocol (48, 49), equipping the microrobots with dual capabilities: mechanical biofilm disruption via sharp nanostructures and enhanced propulsion in viscous oral environments.

Comprehensive morphological characterization confirmed successful structural engineering. Scanning electron microscopy (SEM) images in Fig. 2 (C and D) revealed distinct Janus architectures before and after nanothorn modification. Unmodified microrobots exhibited clear hemispheric contrast attributable to asymmetric metal coating (Fig. 2C), while nanothorn-decorated counterparts displayed densely arrayed protrusions with ∼60-nm base diameters (Fig. 2D and high-resolution image in fig. S3). Atomic force microscopy (AFM) topographic analysis (Fig. 2E) quantified surface roughness evolution: average roughness (Ra) increased dramatically from ∼2 (bare) to ∼140 nm (nanothorn-modified) in Fig. 2F. Elemental composition and distribution were verified by x-ray photoelectron spectroscopy (XPS) and energy-dispersive spectroscopy (EDS). XPS survey spectra confirmed the presence of C, O, N, F, P, Fe, Pt, and Au in fig. S4, while EDS mapping (Fig. 2G and fig. S5) spatially resolved the metal/nonmetal Janus configuration.

Chemical fingerprinting and surface properties were systematically investigated. Fourier transform infrared (FTIR) spectroscopy in Fig. 2H identified key functional groups: C═O stretching vibration in PLGA (1751 cm⁻¹), [BMIM]⁺ vibration (1575 cm⁻¹), and P─F vibrations in PF₆⁻ (838 cm⁻¹ for stretching and 559 cm⁻¹ for bending). The characteristic peak at 1512 cm⁻¹ corresponded to the aromatic skeleton vibration of curcumin (43), collectively confirming that ionogel microspheres loaded with curcumin drug were successfully prepared. Zeta potential evolution tracked surface modifications during fabrication (Fig. 2I): PLGA (−1.73 mV) → ionogels (−11.6 mV) → ionogels@Fe (−13.5 mV) → ionogels@Fe@Pt (−12.2 mV) → ionogels@Fe@Pt@Au nanothorns (+3.31 mV). This progressive shift validates successful layer-by-layer assembly. Last, vibrating sample magnetometer (VSM) measurements conducted in Fig. 2J confirmed paramagnetic behavior of microrobots. While nanothorn modification slightly reduced saturation magnetization (attributable to increased nonmagnetic mass), the microrobots retained rapid magnetic responsiveness to external fields (Fig. 2J, inset), enabling precise actuation control in periodontal environments.

Magnetically actuated motion behavior of ionogel microrobots

The motion kinematics of microrobots were characterized using a triaxial Helmholtz coil system capable of generating programmable rotating magnetic fields (fig. S6). Under uniform field strength (e.g., 2 mT), microrobots executed two fundamental motion modes: directional rolling (Fig. 3A and movie S1) and axial rotation (Fig. 3B and movie S2). Quantitative analysis revealed frequency-dependent velocity profiles: both translational (v) and angular (ω) velocities exhibited bell-shaped curves peaking at approximately 12 Hz (v_max = 20.2 μm/s; ω_max = 47.8 rad/s for nanothorn-modified microrobots). This characteristic “step-out” behavior (50) originates from the competition between magnetic torque and viscous resistance. Beyond critical frequency, viscous drag exceeds magnetic alignment capability, causing progressive desynchronization. Notably, the achieved velocities correspond to 2.02 body lengths per second, substantially surpassing the passive diffusion of conventional drug carriers.

Fig. 3. — (A) Schematic diagrams and time-lapse images of the rolling motions of the microrobots within 4 s (with magnetic field strength of 2 mT). Scale bar, 20 μm. (B) Schematic diagrams and time-lapse images of the rotating motions of the microrobots (with magnetic field strength of 2 mT). Diameter of microrobots: 10 μm. (C) Effects of nanothorn modification on the translational velocity and angular velocity of microrobots under the magnetic field with different frequencies (with magnetic field strength of 2 mT). (D and E) Translational velocity and angular velocity of nanothorn-modified microrobots as a function of the magnetic field parameters. (F) Translational velocity and angular velocity of nanothorn-modified microrobots under different viscosity conditions (with magnetic field strength of 8 mT and magnetic field frequency of 16 Hz). (G) Motion trajectory of a single microrobot navigated by external magnetic field (with magnetic field strength of 2 mT and magnetic field frequency of 5 Hz). Scale bar, 20 μm. (H) Heatmap of swarm motion velocity based on the panning velocity of the robotic arm and rotating velocity of magnet (with magnetic field strength of 30 mT). (I) Swarm motion velocity as a function of magnetic field strength in the systems with different viscosities (with robotic arm panning velocity of 0.4 mm/s and magnet rotating velocity of 15 r/s). (J) Motion trajectory of the swarm (with robotic arm panning velocity of 0.4 mm/s and magnet rotating velocity of 15 r/s, and magnetic field strength of 30 mT). Scale bar, 5 mm. Error bars indicate SD (N = 5).

Surface topology engineering profoundly impacted locomotion efficiency (51). The influence of Au nanothorns on microrobots’ motion behaviors was studied in Fig. 3C. In directional rolling motion, Au-nanothorn modification enhanced the translational velocities of microrobots by 158.9% (7.8 μm/s versus 20.2 μm/s at 12 Hz, 2 mT). This augmentation stems from increased surface roughness (Ra increased from 2 to 140 nm) generating asymmetric friction gradients during surface contact. Conversely, nanothorns increased axial rotational resistance, reducing step-out frequency from 12 to 10 Hz, and ω_max from 73.2 to 60.6 rad/s (17.2% decrease). Subsequently, the effects of magnetic field strength on the rolling and rotation behaviors of nanothorn-modified microrobots were investigated in Fig. 3 (D and E). Both studies demonstrated a positive correlation between field strength and translational/angular motion due to enhanced magnetic torque, while step-out frequencies increased almost proportionally.

To assess clinical translational potential, motion performance of microrobots was systematically evaluated in physiologically relevant viscous environments mimicking saliva and gingival crevicular fluid (5 to 10 cP) (52). As demonstrated in Fig. 3F and fig. S7, both rolling and rotational velocities exhibited progressive attenuation with increasing medium viscosity. Crucially, this velocity decay plateaued substantially when viscosity exceeded 20 cP, a critical threshold corresponding to the viscoelastic transition point of periodontal mucus where elastic modulus dominates viscous response. In real saliva, the microrobots maintained effective propulsion with the rolling and rotational velocities of 15.3 μm/s and 50.7 rad/s, respectively (magnetic field: 8 mT, 16 Hz). This robust performance confirms their capacity to navigate the oral salivary environment. Furthermore, the locomotion capability of microrobots on bacterial biofilms was further evaluated. As shown in fig. S8A, the motion speed of the microrobots in the biofilm is slightly lower than that in the ideal medium, which is attributed to the increased viscous resistance. From fig. S8B, it can be seen that the mean square deviation curves in both the ideal medium and the biofilm exhibit an upward parabolic trend, indicating that the microrobots perform active and directional motion under the action of a magnetic field. Spatial controllability of the microrobots in ideal media (Fig. 3G and movie S3) and bacterial biofilm (fig. S9A and movie S4) was further validated through on-demand path-following trials. The corresponding instantaneous velocity distributions were also statistically analyzed (figs. S9B and S10), with the results indicating that the motion velocity of the magnetically actuated microrobot is relatively stable. Microrobots precisely tracked polygonal trajectories (rectangular and triangular for instance) with directional error <4.3% of path length, demonstrating real-time maneuverability essential for accessing subgingival niches.

For practical periodontitis therapy, coordinated operation of microrobot collectives is imperative. We established swarm control (movie S5) using a custom magnetic manipulation system comprising a robotic arm and a spherical permanent magnet mounted on a rotating motor as shown in fig. S11. Swarm velocity regulation was achieved by synchronizing the panning velocity of robotic arm and the rotational velocity of magnet. As illustrated in Fig. 3H, swarm velocity increased positively with the panning velocity of robotic arm, but exhibited pronounced hysteresis during an excessive panning velocity, manifesting as swarm fragmentation due to insufficient magnetic retention force. Concurrently, the enhancement of magnet rotational velocity amplified hydrodynamic entrainment, elevating the swarm velocity to 0.59 mm/s at optimal parameters. Environmental adaptability tests (Fig. 3I) confirmed swarm functionality across viscosity gradients (10 to 40 cP, as well as real saliva), with velocity profiles mirroring single-robot trends. The motion trajectory of swarm could also be precisely controlled, as shown in Fig. 3J and movie S5. Crucially, the swarm executed precision curvilinear navigation along 50.2 mm circular paths (radius of curvature: 8 mm) with <8.3% positional deviation, validating deployment and manipulation feasibility of microrobots within the viscoelastic environment of tortuous gingival sulci (3). Furthermore, we evaluated the motion performance of the microrobotic swarm in a flow chamber. Under magnetic actuation, the swarm navigated against fluid flow and withstood flow velocities up to ∼1 cm/s (fig. S12 and movie S6), demonstrating its feasibility for dynamic environments. It should be noted that this represents a simplified in vitro model and does not fully replicate the spatially heterogeneous, and inflammation-dependent nature of gingival crevicular fluid outflow in an inflamed periodontal pocket.

Mucus barrier penetration and tissue adhesion performance of ionogel microrobots in vitro and in vivo

Oral mucus, primarily constituted by mucin glycoproteins, forms a viscoelastic cross-linked network that acts as a physical barrier to severely impedes drug penetration (especially macromolecular or granular drugs) (8). Therefore, a biomimetic gingival mucus model with a viscosity of 104 cP was first prepared by dissolving mucin, collagen, and salivary amylase in phosphate-buffered saline (PBS) solution to evaluate the in vitro barrier breakthrough performance of microrobots (fig. S13). It should be noted that the model was an artificial composite serving as a rheology-informed surrogate, not a reconstruction of native gingival tissue or authentic crevicular mucus. Under the actuation of a rotating permanent magnet, microrobots executed mechanical drilling penetration into the biomimetic gingival mucus (Fig. 4A). Confocal laser scanning microscopy (CLSM) was used to monitor the penetration process of microrobots (Fig. 4B), where red fluorescence corresponded to the biomimetic gingival mucus stained with rhodamine B, while the green fluorescence from the loaded curcumin drug indicated the position of microrobots. As shown in Fig. 4C, in the absence of magnetic actuation, passive diffusion of microrobots achieved negligible penetration within the biobarrier model. In contrast, when magnetic activation was applied for 30 min, microrobots could effectively penetrate into the biomimetic gingival mucus, achieving a maximal penetration depth of ∼487.4 μm (the depth within the in vitro surrogate mucus analog). Crucially, this depth was 1.49-fold greater than that achieved by microrobots without nanothorns. To maintain microrobots in periodontal region under practical application scenarios, we dispersed microrobots in a starch hydrogel with the viscosity of 100 cP, and then injected them into the periodontal pockets. The viscosity of starch hydrogel is higher than the that of most oral mucus (53), constituting a firmer physical barrier to microrobotic drug delivery. As shown in fig. S14, the nanothorn-modified microrobots can also penetrate this viscous physical barrier under magnetic actuation. Such enhancement in penetration performance is mechanistically attributed to nanothorn-generated shear forces during rotation, which disrupt polymer chain entanglement of the surrogate mucus analog and reduce penetration resistance through shear-thinning effects (54). It is worth noting that the biomimetic mucus model recapitulates the viscoelastic resistance of gingival crevicular fluid but does not incorporate the continuous outward flow that occurs in a real inflamed periodontal pocket.

Fig. 4. — (A) Schematic diagram of microrobots breaking through biomimetic mucus model (an engineered surrogate mucus analog). (B and C) CLSM images, penetration depth of microrobots in the biomimetic mucus model. Scale bar, 200 μm. Error bars indicate SD (N = 20). a: microrobots without nanothorns, b: microrobots with nanothorns, c: microrobots without nanothorns under magnetic field activation, and d: microrobots with nanothorns under magnetic field activation. (D) Schematic diagram of the test showing microrobots’ capability of adhesion on HGEC layer. (E and F) CLSM images, relative adhesion area of microrobots on HGEC layer. Scale bar, 200 μm. Error bars indicate SD (N = 5). a: microrobots without nanothorns, b: microrobots with nanothorns, c: microrobots without nanothorns under magnetic field activation, and d: microrobots with nanothorns under magnetic field activation. (G) In vivo fluorescence images of microrobots residing in mouse periodontium. Scale bar, 1 cm. (H) SEM images of mouse periodontal tissue treated with various groups. (I) Immunofluorescence analysis of frozen sections of mouse periodontal mucosa treated with various groups. Scale bar, 100 μm. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001.

Sustainable residence of microrobots at targeted lesion site minimizes drug loss while enhancing local drug concentration, which is paramount for improving drug delivery across the dense mucosal barrier into deeper infected tissues (55). Using an in vitro human gingival epithelial cell (HGEC) model, the tissue adhesion ability of microrobots toward periodontium was quantified by surface coverage area of microrobots, defined as the percentage of green fluorescence area within the entire field of view (Fig. 4D). The fluorescence images of microrobots adhered to HGEC layer after PBS rinse are depicted in Fig. 4E, and the quantitative surface coverage area is plotted in Fig. 4F. After 30-min magnetic actuation, nanothorn-modified microrobots achieved ∼2.29-fold greater adhesion versus nonthorned counterparts. Notably, magnetic actuation enhanced interfacial contact through forced microrobot-substrate interactions, whereas nonactuated samples exhibited progressive detachment (2.36-fold decrease after 30 min).

Translating to in vivo murine models, the directional locomotion of the microrobots within the periodontal region was monitored through endoscopy (fig. S15 and movie S7), and real-time fluorescence imaging was employed to track the periodontal residence of microrobots in the oral environment (Fig. 4G). No fluorescence signal was detected in the oral cavity of mouse injected with PBS only as control group. High-intensity signal could be observed in the central part of the mouse oral cavity when PBS-dispersed microrobots were injected, which, however, decreased rapidly over time. This was mainly due to gingival crevicular fluid pressure and salivary washout. To address this, microrobots were embedded in injectable starch hydrogel (fig. S16), a shear-thinning carrier that maintained magnetic maneuverability of microrobots as aforementioned while resisting washout. This carrier enzymatically degraded via salivary amylase (fig. S17), accompanied by a rapid decrease in its internal ethanol concentration (fig. S18), causing no damage to living periodontal tissue. After 30 min, in the absence of magnetic actuation, the fluorescence intensity in the periodontium of the mouse was notably lower than the initial value due to the loss of microrobots. In contrast, sustained fluorescence intensity in the group treated with magnetic actuation for 30 min confirmed the retention of microrobots (>95.1% of initial signal, Fig. 4G and fig. S19). Figure 4H shows that a substantial accumulation of microrobots guided by magnetic fields can be observed deep within the gingiva, indicating that magnetically actuated microrobots enabled effective targeted delivery and stable residence. Upon field termination, the attenuation in fluorescence intensity at 120 min reflected the sustained release of curcumin drug from microrobots. Furthermore, as shown in fig. S20, the microrobots still remain in the mouse periodontal region after 48 hours of treatment, proving that magnetically actuated microrobots achieved long-term residency on the periodontium of the mouse. Further histological validation via immunofluorescence of periodontal mucosa in Fig. 4I revealed that magnetically guided microrobots formed discrete aggregations, with a subset of these microrobots successfully anchoring to the mucosa. Nonactuated controls showed negligible retention in oral cavity. Although without direct quantitative evidence across all native tissue layers, this demonstrated that magnetically driven microrobots could overcome salivary/crevicular washout, improve local retention, and achieve mucosal anchoring within the living periodontal environment, which is a critical prerequisite for targeted antimicrobial delivery in periodontitis treatment.

Mechanical removal of bacterial biofilm via active motion of ionogel microrobots

Bacterial biofilms within deep periodontal pockets pose formidable treatment challenges due to their extracellular polymeric substance (EPS)–shielded architecture, which impedes penetration of antibacterial drugs to kill internal bacteria (10, 27). Thus, efficient removal of bacterial biofilm is critically important for targeted drug therapy of periodontitis. To achieve this, we engineered microrobots with ultrasharp gold nanothorns capable of mechanically disrupting biofilms (Fig. 5A). Using Streptococcus mutans (a typical Gram-positive facultative anaerobic bacterium), a primary cariogenic pathogen dominating subgingival plaque (56, 57), we established mature biofilms for evaluation. The CLSM images of bacterial biofilms under various treatment conditions were collected and analyzed in Fig. 5B. The live/dead bacteria are pre-stained with SYTOX9 (green fluorescence) and propidium iodide (red fluorescence), respectively. For untreated control group, intact and dense biofilm comprised of living bacteria labeled with green fluorescence. In contrast, magnetic actuation of nanothorn-modified microrobot contributed to the destruction of whole biofilms. Quantitative analysis in Fig. 5 (B to D) revealed 74.1% decrease in viable bacteria (green fluorescence) and 88.2% decrease in biofilm thickness after nanothorn-modified microrobot treatment under magnetic actuation, with characteristic removal tracks visible in fig. S21. Critically, nanothorn modification enhanced biofilm removal by 1.62-fold compared to smooth microrobots, attributed to the effective EPS lacerations by ultrasharp nanothorns during high-speed rotation. Moreover, the magnetically actuated nanothorn-modified microrobots also exhibited excellent clearance efficacy against both single-species bacterial biofilms composed of Porphyromonas gingivalis (a typical gram-negative anaerobic bacterium) (fig. S22) and Fusobacterium nucleatum (a typical gram-negative anaerobic bacterium) (fig. S23), as well as ecologically complex multispecies composite bacterial biofilms (fig. S24). We further performed biofilm regeneration assays following its removal. Compared with other groups, after treatment with the nanothorn-modified microrobots, the residual bacteria were unable to reestablish the biofilm (fig. S25), suggesting that the nanothorn structures effectively achieved mechanical sterilization within the biofilm. Next, to evaluate the structural integrity of the biofilm matrix, we performed SYPRO Ruby staining, which specifically binds to the proteinaceous components of the EPS (58). Fluorescence signal intensity analysis (figs. S26 and S27) demonstrated that, the magnetically actuated microrobots, particularly those functionalized with nanothorns, effectively dismantle the protective protein scaffolding of biofilms, offering a robust and multifaceted strategy for biofilm eradication.

The mechanical bactericidal ability of microrobots was further investigated by SEM observation (Fig. 5E). The morphology of bacteria remained almost unchanged after being treated with static microrobot. Meanwhile, the bacterial biofilm treated with magnetically actuated nonthorned microrobot exhibited evident removal traces, yet the bacterial morphology still remained unaffected. In contrast, nanothorn-modified microrobots under magnetic actuation effectively disrupted biofilm, generating bacterial debris as indicated by the yellow arrows. This proved the necessity of nanothorns on microrobots for mechanical removal of bacterial biofilm, whose ultrasharp structures were capable of cutting and destroying the cellular structures of small-sized bacteria. As shown in fig. S28, after biofilm removal by the microrobots, the detached bacteria primarily adhered to the nanothorns, whereas regions without nanothorns had almost no bacterial adhesion. These results indicate that the nanothorn structure not only facilitates bacterial biofilm clearance but also maintains its structural integrity throughout the process. In addition, following 48 hours of immersion in saliva (fig. S29), the nanothorn structure on the microrobots remained largely unchanged, further confirming its stability under physiological conditions.

To facilitate effective control of microrobots in realistic clinical scenarios, we developed a handheld magnetic controller inspired by electric toothbrushes (Fig. 5F). Its core module integrated a neodymium magnet (surface field: ∼100 mT) rotated by a direct current motor (0 to 100 Hz) whose parameters could be controlled by the printed circuit board, generating rotating magnetic fields with tunable strength, direction, and rotating frequency. Then a 3D-printed ex vivo human periodontal model (fig. S30) was established, in which, bacterial biofilm stained with rhodamine B was implanted on the inner surface to mimic the clinical conditions of periodontal pocket environment. Actuated by the handheld magnetic controller, microrobotic swarm were magnetically navigated through simulated pockets (movie S8), achieving precise biofilm eradication via swarm rotation-translation coupling. We anticipated that the portability of the handheld magnetic controller, combined with its ability to drive microrobots for bacterial biofilm removal, enables the development of complementary products, such as toothpaste infused with microrobots, for the treatment and prevention of periodontitis.

To evaluate the destructive stress exerted by nanothorns on bacterial biofilms, we analyzed the mechanics of microrobots under magnetic field actuation. The magnetic force exerted by a single microrobot in the magnetic field of a permanent magnet was calculated (Fig. 5G), revealing a quantitative value of 172 pN along field direction, at the field strength of 20 mT and field gradient of 10 T/m (a common magnetic field configuration for actuating microrobots with rotating permanent magnet in our work). After rough statistics, the number of nanothorns on a single microrobot was ∼22,000, so the magnetic force exerted by a single nanothorn was ∼7.82 × 10⁻¹⁵ N (details can be found in the text S1). On the basis of nanothorn dimensions, the contact areas between a single Au nanothorn and a bacterium were estimated as 19.6 nm² at the tip and 15,000 nm² at the side. Consequently, the corresponding stresses exerted by a single nanothorn during bacterial penetration and cutting were ∼400 and 0.52 Pa, respectively (fig. S31), which are sufficient to disrupt biofilms (37, 59). Furthermore, nano-indentation and nanoscratch tests demonstrated that the nanothorn tips and sides withstand loads of ∼0.012 and 0.226 mN (fig. S32), respectively. These values substantially exceed the magnetic force applied during operation, confirming the structural robustness of gold nanothorns for biofilm removal. In addition, COMSOL Multiphysics simulations analyzed stress distribution on microrobot surfaces during rotational motion, along with surface/ambient fluid velocity profiles. Figure 5H showed that stress concentration occurred on the microrobots’ nanothorns, with the maximum stress value reaching ∼0.75 Pa on the nanothorn tips. In contrast, the stress on the surface without nanothorns remained comparable to ambient environment, confirming that the anchored nanothorns on microrobot enhance mechanical stress application for biofilm disruption. Meanwhile, flow velocity peaked at the equatorial region of microrobot due to maximal linear velocity during rotation. Nanothorns enhanced shear forces, generating ∼400 μm/s velocities near equatorial thorns. This induced elevated velocities in surrounding fluid, confirming rotational nanothorn-induced shear thinning and their critical role in biofilm destruction via high shear stresses. In summary, the mechanical force exerted by microrobots under magnetic field activation was sufficient for breaking through the physical barrier of bacterial biofilms, while the modification of ultrasharp nanothorns further contributed to the destruction of internal bacterial cellular structures, paving the foundation of thorough antibacterial treatment in targeted periodontitis therapy.

Controlled drug release of ionogel microrobots for synergistic bacterial killing and inflammation elimination

The limited bioavailability of highly potent antibacterial drugs often stems from their hydrophobic nature (60), underscoring the need for delivery systems capable of effective loading and controlled release of such cargo molecules. Curcumin, a representative hydrophobic drug with broad biological activities including anti-inflammatory, antioxidant, anticancer, and antibacterial effects (61), is widely used in periodontitis therapy (62). Furthermore, as a natural product, curcumin exhibits high safety and biocompatibility, aligning with the current pursuit for green and sustainable biomaterials. Consequently, we used curcumin as a model drug, loaded into the ionogel microrobots via an emulsion-solvent evaporation-based encapsulation process. As demonstrated in Fig. 6A, the excellent solubility of curcumin in ILs (fig. S33) enabled the IL-containing microrobots to achieve a drug loading capacity of 38.8 μg/mg when the added drug mass fraction was 6 weight % (wt %). This represents a 1.76-fold increase compared to microrobots fabricated without ILs. Notably, the microrobots exhibited ethanol-responsive drug release property. This behavior is attributed to ethanol-induced swelling of the ionogel networks. Penetrating ethanol molecules disrupt the weak interactions between the ILs and the polymer networks, facilitating the leakage of ILs containing the dissolved drug molecules (45). Figure 6B shows that near-complete drug release was achieved within 200 min under 50 wt % ethanol conditions. The release process was concurrently monitored by the decreasing fluorescence intensity of the encapsulated curcumin (Fig. 6B, inset). Furthermore, microrobots containing ILs demonstrated a faster release rate than those without ILs. The drug release rate could also be modulated by adjusting the ethanol concentration (Fig. 6C), and a sustained release profile is maintained even in ethanol-free system, enabling controlled drug delivery.

Effective eradication of pathogenic bacteria is crucial to prevent inflammation exacerbation and recurrence in periodontitis treatment. We evaluated the chemical antibacterial activity of the microrobots using bacterial colony counting and biofilm formation assays. P. gingivalis, a primary pathogen strongly associated with periodontitis (63), was selected for testing. Figure 6 (D and E) presents the inhibitory effects on P. gingivalis under different treatments. Biofilm formation inhibition aligned with colony count results. PLGA microspheres exhibited negligible antibacterial efficacy (inhibition rate <7%), while ionogels showed a slight improvement (inhibition rate ∼33%), attributable to the inherent antibacterial properties of imidazolium-based ILs that can disrupt bacterial membrane structures (64). Thus, microrobots constructed with ILs also demonstrated notable antibacterial properties, achieving an inhibition rate of ∼48%, representing a further enhancement over plain ionogels. This improvement is likely due to the disruptive effect of the sharp Au nanothorns on bacterial membranes during cocultivation, reducing bacterial activity (65). Moreover, ethanol stimulation triggered substantial curcumin release, markedly boosting the microrobots’ bacterial inhibition rate to ∼90%, leveraging curcumin’s inherent antibacterial capability (61). Given the polymicrobial nature of periodontitis, we further assessed the microrobots’ activity against S. mutans and F. nucleatum, common periodontitis-related pathogens (66). The microrobots demonstrated excellent antibacterial performance against these strains (fig. S34), with inhibition rates of ∼96 and ∼89% respectively, indicating broad-spectrum efficacy against various oral bacteria.

Before intracellular immune regulation studies, we evaluated the cytotoxicity of the microrobots (Fig. 6F). Coculturing gingival epithelial cells with microrobots at varying concentrations resulted in cell survival rates exceeding 80%, as measured by the CCK-8 assay. Notably, even under magnetic actuation (less than 50 mT), the treated gingival epithelial cells maintained high viability (>80%; fig. S35), with negligible impact on their morphology, inflammatory factor expression, or transendothelial electrical resistance (figs. S36 to S38). Safety was further corroborated by hemolysis and coagulation assays (figs. S39 and S40), indicating no notable damage to red blood cells (RBCs) or interference with coagulation. In addition, the microrobots demonstrated self-degradability in a salivary environment (fig. S41), confirming their overall suitability for oral applications. These results indicated good biocompatibility of the microrobots, and curcumin itself also showed no substantial toxicity to healthy cells. During inflammation, activated immune cells produce excessive free radicals and ROS, inducing oxidative stress. This triggers pro-inflammatory cytokine release, intensifies inflammation, and damages healthy tissues (67, 68). Scavenging free radicals is thus essential to restore redox balance, alleviate oxidative stress and cell damage at inflammatory sites, and create a favorable microenvironment for repair (69). As shown in Fig. 6G and fig. S42, the free radical scavenging capacity of the microrobots against various species, including 2,2′-azinobis(3-ethylbenzothiazoline-6-sulfonic acid) radical cation (ABTS·), 2,2-diphenyl-1-picrylhydrazyl radical (DPPH·), hydroxyl radical (OH·), and superoxide anion (·O₂⁻), was evaluated in solution. Drug-loaded microrobots (100 μg/ml) exhibited high scavenging rates of ∼99, ∼90, ∼70, and ∼65% for these radicals, respectively, primarily attributed to the released curcumin. Drug-free microrobots still showed weak scavenging activity, which might be attributed to their metallic components undergoing valence state changes (fig. S43) (70). Furthermore, the microrobots’ ability to scavenge intracellular ROS was validated at the cellular level (Fig. 6, H and I). Fluorescent labeling with a ROS probe revealed that the intracellular ROS fluorescence intensity in cells treated with drug-releasing microrobots was notably lower than that in the control group, as quantified by flow cytometry. Therefore, the microrobots exhibit potent free radical and ROS scavenging capabilities, mediated predominantly by the released curcumin.

Macrophages dynamically polarize into distinct phenotypes (M1/M2) in response to environmental signals. While M1 macrophages exacerbate inflammation via endogenous immunomodulatory pathways (12), M2 macrophages promote tissue repair by releasing anti-inflammatory and proregenerative factors (71). We assessed the microrobots’ effect on macrophage polarization using immunofluorescence staining for M1 (CD86) and M2 (CD206) markers (6). Flow cytometry quantification of CD86⁺ and CD206⁺ cells confirmed the phenotypes. As shown in Fig. 6 (J to M), compared to the control group, the microrobots, via released curcumin acting on cellular transcription factors, inhibited M1 macrophage polarization and promoted polarization toward the M2 phenotype. Subsequent quantitative polymerase chain reaction (qPCR) analysis (fig. S44) revealed that microrobot treatment following drug release down-regulated pro-inflammatory cytokines interleukin-1 beta (IL-1β), IL-6, and tumor necrosis factor–α (TNF-α), while up-regulating anti-inflammatory cytokines IL-10 and transforming growth factor-β1 (TGF-β1). The increased M2 macrophage population generated more anti-inflammatory cytokines to resolve inflammation, thereby establishing a more favorable immune microenvironment conducive to tissue regeneration and repair. Collectively, these results demonstrate that the microrobots eliminate inflammation through a synergistic therapeutic mechanism combining effective bacterial inhibition, potent free radical/ROS scavenging, and targeted immunomodulation of macrophage polarization.

Therapeutic efficacy of ionogel microrobots against periodontitis in vivo

Subsequently, we comprehensively evaluated the in vivo therapeutic efficacy of the magnetically actuated microrobots with gold nanothorns against periodontitis. The experimental timeline is outlined in Fig. 7A, with corresponding photographs of the treatment procedure provided in fig. S45. After establishing the periodontitis model by ligating the maxillary second molars of mice, the microrobots were injected into the periodontal pockets surrounding the second molars at 2-day intervals. Each injection was followed by a 30-min magnetic field treatment applied using the self-developed handheld magnetic controller. Following a 2-week treatment period, maxilla samples were harvested for analysis. Micro–computed tomography (micro-CT) analysis of the treated alveolar bone (Fig. 7B) revealed that bone loss was mitigated, accompanied by elevated bone volume per tissue volume (BV/TV) and trabecular number (Tb.N), alongside reduced trabecular separation (Tb.Sp) (Fig. 7, C to F), indicating enhanced osteogenic activity and attenuated bone resorption. Group (e) (injecting nanothorn-modified microrobots dispersed in a starch hydrogel carrier and subjected to magnetic field treatment for 30 min) demonstrated the most notable restoration of bone microarchitecture. Histomorphometric analyses further corroborated these findings (Fig. 7, G to J). Hematoxylin and eosin (H&E) and Masson’s trichrome staining of periodontal tissues highlighted reduced alveolar bone loss [quantitatively assessed by measuring the vertical distance between the alveolar bone crest (ABC) and cementoenamel junction (CEJ)], robust collagen deposition, and diminished inflammatory cell infiltration in group (e). Tartrate-resistant acid phosphatase (TRAP) staining confirmed a notable decrease in osteoclast infiltration within group (e), corroborating the observed attenuation of bone resorption. The therapeutic efficacy of the platform was further substantiated by rigorous safety evaluations. Histological analysis confirmed that the periodontal tissues remained intact without observable damage following magnetically actuated treatment (fig. S46), and systemic coagulation function remained unaffected (fig. S47). Regarding the metabolic fate of the microrobots, in vivo monitoring revealed a transient increase in Fe and Au ion levels in the gingival tissue and saliva within the first 6 hours post-treatment, which returned to baseline within 24 hours (figs. S48 and S49). No notable metal accumulation was detected in major organs (heart, liver, spleen, lung, and kidney), blood, or saliva upon completion of the treatment cycle (figs. S50 and S51). Furthermore, H&E staining of major organs revealed no detectable pathological abnormalities or toxicity (fig. S52), underscoring the excellent biocompatibility of the treatment regimen.

Fig. 7. — (A) Schematic illustration of periodontitis treatment process by using microrobots. The figure was created using BioRender (https://BioRender.com/7vix0ao). (B) 3D/2D reconstruction and images of the maxillary molars with different treatments by micro-CT. Scale bar, 500 μm. (C to F) The quantitation of bone loss, BV/TV, Tb.N, and Tb.Sp of the alveolar bone. (G) H&E, Masson, and TRAP staining images of periodontal tissue treated with various groups. Scale bar, 200 μm. (H to J) The corresponding quantitative evaluation of distance between ABC and CEJ, collagen deposition and TRAP⁺ cell. a: control, b: starch gel, c: curcumin@gel, d: microrobots@gel, and e: microrobots@gel with magnetic field. Error bars indicate SD (N = 5). *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001.

Collectively, these in vivo results demonstrate that the released curcumin effectively mitigates the progression of periodontitis by inhibiting inflammation, eliminating bacterial infection and suppressing pathological bone resorption, underscoring its potential as an ideal therapeutic agent for periodontitis owing to its high safety profile and multifaceted pharmacological activities. The relatively low bioavailability of curcumin that limits therapeutic application is well addressed by our developed microrobotic platform. The incorporation of ILs in microrobots substantially improved the solubility of curcumin and enhanced drug bioavailability through sustained release, while magnetic field treatment amplified therapeutic potency of microrobots through targeted delivery and enhanced capability in local retention and mucosal anchoring.

Anti-inflammatory mechanism and microbiota regulation of ionogel microrobots in vivo

To further elucidate the in vivo anti-inflammatory mechanisms of microrobots, we assessed the expression of pro-inflammatory cytokines (IL-1β, IL-6, and TNF-α) in gingival tissues via immunohistochemistry (IHC). Immunostaining revealed markedly reduced infiltration of IL-1β, IL-6, and TNF-α in the gingival tissues of groups (d) (injecting nanothorn-modified microrobots dispersed in a starch hydrogel carrier without magnetic field treatment) and (e) compared to the control group (Fig. 8, A to D), demonstrating potent anti-inflammatory efficacy of ionogel microrobots in vivo. Corroborating this, immunofluorescence analysis showed a notable decrease in pro-inflammatory M1 macrophages (CD86⁺/F4/80⁺) and a concurrent increase in anti-inflammatory M2 macrophages (CD206⁺/F4/80⁺) within groups (d) and (e) (Fig. 8, E to G), suggesting that modulation of macrophage polarization contributed to inflammation suppression. These findings collectively demonstrate the capability of the microrobots as a drug delivery system to achieve controlled drug release, maintain effective local drug concentrations, and, under external magnetic field actuation, precisely target inflammatory sites to effectively regulate the macrophage microenvironment.

Fig. 8. — (A) IHC staining of IL-1β, IL-6, and TNF-α in the periodontal tissue after different treatments. Scale bar, 50 μm. (B to D) The corresponding quantitative evaluation of inflammatory factors in local periodontal tissue (IL-1β, IL-6, and TNF-α). Error bars indicate SD (N = 5). (E) Immunofluorescence analysis of M1 macrophages (CD86⁺/F4/80⁺) and M2 macrophages (CD206⁺/F4/80⁺). Scale bar, 50 μm. (F and G) The corresponding quantitative evaluation of M1 and M2 cells. Error bars indicate SD (N = 5). (H) Venn plot of the specific genus in different groups. (I) Microbiota constitution of mice’s oral cavity with different treatment groups in phylum level. (J and K) Relative abundance of *Proteobacteria* and *Firmicutes* after treatment in different groups. Error bars indicate SD (N = 3). (L) PCA in different groups. (M) Circos diagram of the association between treatment groups. (N) LEfSe analysis of groups a and e. a: control, b: starch gel, c: curcumin@gel, d: microrobots@gel, and e: microrobots@gel with magnetic field. *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001.

Using 16S rDNA gene sequencing, we comprehensively investigated the microbial mechanisms underlying the therapeutic benefits conferred by the microrobots in periodontitis. A Venn diagram depicting genus-level distributions revealed pronounced alterations in the relative diversity of the subgingival microbiota across treatment groups compared to the control (Fig. 8H). Although group (c) (injecting curcumin dispersed in a starch hydrogel carrier) exhibited the most pronounced alterations, these changes potentially risked ecological imbalance. Moreover, groups (d) and (e) shared considerable microbiota similarity, indicating overlapping treatment effects. At the phylum level, groups (d) and (e) displayed a reduced relative abundance of Firmicutes and an elevated relative abundance of Proteobacteria compared to control group (Fig. 8, I to K, and fig. S53). Furthermore, a substantial decline in the abundance of Acinetobacter at the genus level was observed in group (e) (fig. S54), indicating a favorable shift toward a healthier microbiota composition and effective inhibition of potential pathogens. Principal components analysis (PCA) evaluated the overall structural differences of microbiota, showing clear separation of control group from the treatment groups (Fig. 8L), signifying substantial treatment-induced restructuring of the microbiota. A Circos diagram further illustrates the associations between treatment groups and microbiota composition across taxonomic levels (Fig. 8M). Linear discriminant analysis effect size (LEfSe) identified Ligilactobacillus and Limosilactobacillus as dominant genera in the control group (a), whereas Enterococcus and Gordonibacter were enriched in group (e) (Fig. 8N). LEfSe also identified specific microbial communities enriched in group (e) relative to other treatments (fig. S55). These findings underscore the ability of the microrobots to reshape the dysbiotic oral microbiome and modulate host immune responses, thereby alleviating periodontitis-associated inflammation. In addition, the mechanical forces generated by the magnetically actuated microrobots may affect microbial interactions (including competition and cooperation), potentially contributing to the observed compositional shifts. Investigating the impact of such mechanical forces on microbiota represents a promising avenue for developing novel microbiome-modulating strategies.

DISCUSSION

In summary, we have designed and fabricated magnetically actuated ionogel microrobots featuring nanothorns for targeted periodontitis therapy. Owing to the enhanced motility provided by the nanothorn structure, these microrobots effectively penetrate a high-viscosity surrogate mucus analog in vitro and anchor to the dense mucosa layer in vivo, notably promoting targeted drug delivery within confined periodontal pockets. Furthermore, magnetically activated microrobots generate localized, high stress via their sharp nanothorns, enabling the mechanical removal of biofilm and effective destruction of internal bacterial. Following the ethanol-responsive release of the hydrophobic drug curcumin, the microrobots effectively eliminate inflammation through synergistic bacterial killing, free radical/ROS scavenging, and macrophage polarization regulation. Last, we developed an integrated, clinically promising periodontitis therapeutic strategy, realized through a handheld magnetic controller for precise microrobot manipulation. In vivo studies demonstrated that microrobot treatment substantially improved inflammation resolution, tissue health, and microenvironmental homeostasis in periodontitis.

Although this study proposed and verified the feasibility of magnetically driven ionogel microrobots for targeted periodontitis therapy, the animal experiments were still limited in both scale and duration, which may not fully capture the stability and effectiveness of long-term application in complex clinical environments. The barrier-penetration experiments were performed using a surrogate mucus analog that does not replicate the full biochemical, structural, and dynamic complexity of the native periodontal barrier. Therefore, the measured penetration performance should not be interpreted as direct evidence that the microrobots can traverse the complete sequence of physiological periodontal barriers in vivo. Future studies should aim to directly quantify microrobot penetration across native tissue layers under in vivo conditions. The oral microenvironment exhibits considerable individual variability, including differences in gingival crevicular fluid composition, microbial diversity, and the dynamic progression of inflammation. These factors may affect the motility, anchoring efficiency, and drug release patterns of microrobots in vivo, thereby necessitating systematic validation in large animal models and preclinical trials. Future research may be directed toward several aspects. First, the development of control systems that integrate multimodal imaging and intelligent navigation will be essential to achieve real-time monitoring and adaptive regulation of microrobotic motion and drug release, thus improving operational precision in complex oral environments. Second, multifunctional integration should be explored, enabling microrobots not only perform drug delivery and biofilm removal but also to respond to external stimuli such as acoustic, optical, or electrical triggers, creating more controllable and personalized therapeutic strategies. Third, interdisciplinary collaboration among pharmaceutics, periodontology, and materials science should be strengthened to establish standardized clinical evaluation systems for systematically assessing safety, efficacy, and applicability across different subtypes and stages of periodontitis. By continuously addressing these challenges, the proposed platform holds great promise for bridging the gap from laboratory research to clinical practice and for advancing precision therapies for oral diseases.

MATERIALS AND METHODS

Materials

[BMIM]PF₆ (99%), curcumin (98%), poly(vinyl alcohol) 1788 (PVA, GR), dichloromethane (CH₂Cl₂, 99.8%), glycerol (C₃H₈O₃, 99%), ethanol anhydrous (EtOH, 99.5%), acetic acid (C₂H₄O₂, 99.5%) were purchased from Shanghai Macklin Biochemical Co. Ltd. PLGA (75:25, M_w ∼38000) was obtained from Jinan Daigang Biomaterial Co. Ltd. PBS (pH 7.2) was purchased from Thermo Fisher Scientific Inc. Starch soluble (GR), hydrogen peroxide (H₂O₂, 30 wt %, GR), gold chloride trihydrate (HAuCl₄·3H₂O, 99.9%), silver nitrate (AgNO₃, AR), rhodamine B (RhB, AR), α-amylase (BR), nitrotetrazolium blue chloride (NBT; 98%), riboflavin (C₁₇H₂₀N₄O₆, 98%), dl-methionine (C₅H₁₁NO₂S, 99%), terephthalic acid (TA, 99%), 2,2′-azinobis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS, 98%), 1,1-diphenyl-2-picrylhydrazyl (DPPH, 97%), potassium persulfate (KPS, AR) were purchased from Shanghai Aladdin Biochemical Technology Co. Ltd. All of the reagents and solvents were used as received without further purification.

Preparation of drug loaded ionogel microrobots

First, 1.0 g of PVA was dissolved in 50 ml of deionized water as the aqueous phase, while the oil phase was formed by dissolving 0.45 g of PLGA, 0.5 g of [BMIM]PF₆ and 0.06 g of curcumin (with the mass fraction of curcumin as 6 wt %) in 20 ml of CH₂Cl₂ under ultrasonication. Next, the aqueous phase and the oil phase were charged into a flask and stirred continuously at 1000 rpm to form a stable emulsion. The reaction system was then heated to 40°C and kept for 24 hours under stirring to completely evaporate CH₂Cl₂. The drug loaded ionogel microspheres were obtained after centrifugation and washing with 10 wt % acetic acid and distilled water several times, followed by freeze-drying at −40°C under vacuum for 12 hours.

Subsequently, the prepared drug loaded ionogel microspheres were sonically dispersed into deionized water at a concentration of 5 mg/ml and added dropwise with a pipette onto the glass slide pre-treated with plasma. After the sample dried naturally, the ionogel microspheres formed a monolayer structure on the surface of glass slide. A 200-nm-thick Fe layer and a 20-nm-thick Pt layer were sequentially deposited on the glass slide surface via electron beam evaporation and ion beam sputtering techniques, yielding the ionogel@Fe@Pt microspheres (i.e., microrobots without gold nanothorns).

Last, 2 mg of ionogel@Fe@Pt was dispersed into 108 μl of deionized water, and HAuCl₄ solution (60 μl, 40 mM), AgNO₃ solution (12 μl, 10 mM), and H₂O₂ solution (60 μl, 2 wt %) were added successively. After oscillating for 100 s, the nanothorn-modified microrobots were obtained by washing with distilled water for four times, followed by freeze-drying at −40°C under vacuum for 12 hours.

Preparation of curcumin@gel and microrobots@gel

In brief, 25 g of water-soluble starch was dissolved in 10 ml of distilled water by continuously stirring at 70°C. The starch hydrogel (100 cP) was obtained through the process of natural cooling the reaction system to room temperature.

One microgram of curcumin was dissolved in 1 ml of ethanol, and the solution was added to 9 ml of the above starch hydrogel and mixed evenly to obtain curcumin@gel (100 μg/ml).

Twenty micrograms of microrobots was dispersed in 9 ml of the above starch hydrogel by ultrasonication, then 1 ml of ethanol was added into the gel and mixed evenly to obtain microrobots@gel (2 mg/ml).

Cell lines, bacterial strains, and culture

HGECs and Human acute monocytic leukemia (THP-1) cells were purchased from American Type Culture Collection (ATCC). HGECs were cultured in Dulbecco’s minimum essential medium supplemented with 10% fetal bovine serum (FBS) at 37°C and 5% CO₂. THP-1 were cultured in RPMI-1640 supplemented with 10% FBS at 37°C and 5% CO₂. P. gingivalis (ATCC 33277) was grown in brain heart infusion (BHI) broth medium supplemented with vitamin K1 (0.5 μg/ml) and hemin (5 μg/ml) in an anaerobic system (oxygen concentration <0.16%). F. nucleatum (ATCC 25586) and S. mutans (ATCC 700610) was cultured at 37°C in BHI broth medium.

Experiment of microrobots drilling to overcome simulated mucus

The collagen-mucin composites and starch gel stained with rhodamine B was paved on the confocal dishes to construct simulated mucus. Microrobots with or without nanothorns were added to the surface of the simulated mucus and a magnetic field was applied (20 mT, 10 r/s). Observation of the drilling depth of microrobots at different times by 3D CLSM.

Adhesion of microrobots assay

For in vitro detection, HGECs were cultured in 24-well plates until confluent as previously article described (72). Microrobots with or without nanothorns (100 μg/ml) were added and a magnetic field was applied (20 mT, 10 r/s). Un-adherent microrobots were gently washed with PBS, imaged with fluorescence microscope. Five fields of view were taken each time to calculate the percentage of adherent area of microrobots, and analyzed by ImageJ.

For in vivo assays, C57BL/6J mice were oral given PBS, microrobots@PBS, and microrobots@gel (2 mg/ml) solution (50 μl). Magnetic field was applied for 30 min in microrobots@gel + magnetic field group. The fluorescence intensity of the residual adherent microrobots in the mouse oral cavity was detected by in vivo imaging at determined time. Then, the oral mucosal tissues of mice were collected, and frozen sections were prepared. The nuclei were stained with DAPI and visualized by fluorescence microscopy.

Mechanical removal of bacterial biofilm assay

S. mutans suspension (10⁶ CFU/ml) containing 1 wt % sucrose was cultured in 15-mm confocal dishes to form bacterial biofilm. Post-biofilm formation, microrobots with or without nanothorns (100 μg/ml) were added. For the magnetic field group, a 30-min magnetic field exposure was applied (20 mT, 10 r/s). The bacterial biofilms were then rinsed three times with ddH₂O and stained in the dark for 15 min using the LIVE/DEAD BacLight Bacterial Viability Kit (Invitrogen, L7012), containing an equimolar mixture of SYTOX9 and propidium iodide. To evaluate the structural integrity and proteinaceous components of the EPS matrix, the biofilms were also stained with SYPRO Ruby (Invitrogen, S12000). Bacterial biofilms were visualized using a Zeiss LSM 980 confocal microscope. Image analysis was performed using ImageJ with the COMSTAT plugin. The removal of multispecies composite bacterial biofilms was performed using a mature, 72-hour biofilm model. This composite biofilm was formed by culturing a mixed suspension of P. gingivalis, F. nucleatum, and S. mutans at a ratio of 1:1:1 under strict anaerobic conditions, followed by the identical treatment and analysis procedures described for the single-species model.

Removal of bacterial biofilm within the periodontal model. First, the periodontal model was obtained through 3D printing technology, followed by polishing process. The polished 3D-printed periodontal model was sterilized in an autoclave for 20 min at 121°C, and subsequently used for biofilm formation. Fifty microliters of S. mutans suspension (10⁶ CFU/ml) containing 1 wt % sucrose was cultured in the periodontal model to form bacterial biofilm. Then the bacterial biofilm was stained with rhodamine B for easy observation. Last, the swarm of the microrobots (0.5 mg) was controlled by a handheld magnetic controller to remove bacterial biofilm within the periodontal model.

Simulation methodology

The simulation studies were conducted using COMSOL Multiphysics 6.1 software to investigate the fluid flow induced by the rotating motion of microrobot. In a typical simulation, the rotating magnetic field acting on the microrobot was set to be strength of 8 mT and frequency of 16 Hz, and the corresponding rotating velocity of the microrobot is 50.7 rad/s. The simulations were based on a laminar flow model, governed by the Navier-Stokes equations (73).

ρ_{l} \nabla \cdot {\vec{u}}_{l} = 0

(1)

ρ_{l} ({\vec{u}}_{l} \cdot \nabla) {\vec{u}}_{l} = - \nabla \cdot \{- p_{l} I + η_{l} [\nabla {\vec{u}}_{l} + {(\nabla {\vec{u}}_{l})}^{T}]\}

(2)

where $ρ_{l}$ , $η_{l}$ , $p_{l}$ , and ${\vec{u}}_{l}$ were the density, dynamic viscosity, pressure, and velocity of liquid, respectively, and I was the identity matrix. The rotational motion of microrobot was implemented on the basis of the dynamic mesh method of rotating domain in COMSOL. Besides, the flow and pressure distribution on microrobot were simulated with a three-dimensional Rotating Machinery module. The fluid density and viscosity were set as 1.04 × 10³ kg m⁻³ and 1.0 × 10⁻³ Pa·s, respectively. The results could be obtained after the whole model reaching the equilibrium state.

Evaluation of drug loading and release

In brief, drug curcumin was dissolved in CH₂Cl₂, and a series of concentrations was prepared to facilitate the construction of its standard curve by ultraviolet-visible (UV-vis) spectrophotometry. Drug-loaded microrobots (0.1 g) was dissolved in 10 ml of CH₂Cl₂, and the maximum absorbance of the supernatant was measured using a UV-vis spectrometer. The drug loading was determined by inputting the absorbance value into the standard curve formula.

Drug loaded microrobots (0.1 g) was dispersed into 10 ml of aqueous solutions with different ethanol contents, and incubated on a shaker at 37°C. At each time point, the absorbance values of supernatant in the system were measured. The absorbance values were analyzed to assess drug release.

Antibacterial activity

P. gingivalis, F. nucleatum, and S. mutans as the typical bacteria of periodontitis, were selected to characterize the antibacterial activities of microrobots by the plate colony-counting method. The bacterial suspension (10⁶ CFU/ml) was cocultured with microrobots (100 μg/ml) for 24 hours using a standardized bacterial coculture assay. After the coculture, the 100 μl of S. mutans, F. nucleatum, and P. gingivalis suspensions (diluted 10,000 times) were plated on BHI agar or BHI blood agar plates, respectively, and incubated at 37°C for 24 hours. The viability of bacteria was determined by counting the number of colonies formed.

Bacterial biofilm formation test

Crystal violet staining was used to examine the effect of microrobots on bacterial biofilm formation. In brief, overnight cultures of S. mutans, F. nucleatum, and P. gingivalis with containing microrobots were inoculated anaerobically at 37°C for 24 hours. Then, the culture medium and unbound bacteria were carefully aspirated, and the wells were rinsed three times with PBS. Subsequently, methanol was added to fix the biofilms for 15 min at room temperature. After air-drying for 30 min, biofilms were stained with 0.1% crystal violet for 15 min. Unbound dye was removed by gentle rinsing under tap water. Retained dye was solubilized in 95% ethanol with 30-min shaking, and absorbance was measured at 595 nm.

Cell viability assay

Cell viability was measured using the CCK-8 assay. Five thousand human gingival endothelial cells were plated in a 96-well plate with F12 medium (10% FBS). After 72 hours of treatment with microrobots, the cells were washed with PBS, and 10 μl of CCK-8 reagent in 100 μl of medium was added. After 2 hours of incubation at 37°C in the dark, absorbance at 450 nm was determined using a microplate reader.

Hemolysis test

Blood samples were collected from C57BL/6J mice. RBCs were separated by centrifugation for preparation of RBC suspension. Then, microrobots were added into RBC suspension at different concentrations. PBS and ddH₂O were added as negative and positive control, respectively. After 1 hour, supernatants were collected after centrifugation and absorbance at 540 nm was measured using a microplate reader.

Free radical scavenging assay

The antioxidant property of microrobots was estimated by analyzing its activity for scavenging free radicals, including ABTS·, DPPH·, OH·, and ·O₂⁻.

For ABTS· scavenging assay, 3 mg of ABTS was dissolved in 0.735 ml of PBS buffer to obtain ABTS stock solution; 1 mg KPS was dissolved in 1.43 ml PBS buffer to obtain KPS stock solution; 0.2 ml each of ABTS and KPS stock solutions were mixed and incubated in the dark for 12 hours. The mixture was then diluted with PBS buffer to an absorbance of ∼0.7 (UV-vis) to obtain the ABTS· test solution. Microrobots were dispersed in anhydrous ethanol, and a calculated volume of the sample solution was added to the ABTS· test solution. After stirring at 37°C for 2 hours, UV-vis measurements were performed to evaluate the ABTS· inhibition rate.

For DPPH· scavenging assay, 1 mg of DPPH was dissolved in ethanol to obtain the DPPH· test solution (with UV-vis absorbance of ∼0.7). Microrobots were dispersed in anhydrous ethanol, and a calculated volume of the sample solution was added to the DPPH· test solution. After stirring at 37°C for 2 hours, UV-vis measurements were performed to evaluate the DPPH· inhibition rate.

For OH· scavenging assay, the OH· test solution was prepared with PBS containing terephthalic acid (0.5 mM) and H₂O₂ (10 mM). Microrobots were dispersed in anhydrous ethanol, and a calculated volume of the sample solution was added to the OH· test solution. After stirring at 37°C for 2 hours, fluorescence spectroscopy measurements (with an excitation wavelength of 315 nm) were performed to evaluate the OH· inhibition rate.

For ·O₂⁻ scavenging assay, the ·O₂⁻ test solution was prepared with PBS containing riboflavin (20 μM), dl-methionine (0.013 M), and NBT (75 μM), following by illuminating under UV for 1 hour. Microrobots were dispersed in anhydrous ethanol, and a calculated volume of the sample solution was added to the ·O₂⁻ test solution. After stirring at 37°C for 2 hours, UV-vis measurements were performed to evaluate the ·O₂⁻ inhibition rate.

Intracellular ROS-scavenging in vitro

Cellular ROS scavenging activity was detected using ROS assay kit (Beyotime, S0033). The HGECs were inoculated in 12-well culture plates. Microrobots (100 μg/ml) and 5% EtOH were added for coculture, and then treated with 200 μM of H₂O₂ and incubated for 24 hours. The cells were then stained with DCFH-DA (10 μM) for 20 min. After removing the excess probe, the mean fluorescence intensity of ROS was measured by flow cytometry.

Anti-inflammation assay

THP-1 cells were first seeded into six-well plate and then induced as M0 by of phorbol 12-myristate 13-acetate (100 ng/ml) stimulation for 48 hours. Microrobots (100 μg/ml) and 5% ethanol were then added for coculture. M1 was further induced by lipopolysaccharide (100 ng/ml) and interferon-γ (20 ng/ml), and M2 was induced by IL-4 (20 ng/ml) and interleukin-13 (20 ng/ml).

For flow cytometry, cells were collected and incubated with fluorescein isothiocyanate anti-CD86 (eBioscience, 2527187) or PE anti-CD206 (eBioscience, 2344972) antibodies for 1 hour at 4°C. All cells were analyzed using BD LSRFFortessa (BD Biosciences).

For quantitative real-time PCR (RT-PCR), total RNAs were extracted using RNA-Quick Purification Kit (ESscience, RN001). The RNAs (1 μg) were then converted into cDNA using PrimeScript RT Master Mix (Takara, RR036A). AceQ Universal SYBR qPCR Master Mix (Vazyme, Q511-02) were used to perform RT-qPCR. After normalization to glyceraldehyde-3-phosphate dehydrogenase (GAPDH) expression, the expression of the target gene was quantified by the 2−ΔΔCt method. Primers include: IL-1β forward: CTCGCCAGTGAAATGAT; IL-1β reverse: AAGCCCTTGCTGTAGTG; TNF-α forward: CGAGTGACAAGCCTGTAGCC; TNF-α reverse: TGAAGAGGACCTGGGAGTAGAT; IL-6 forward: GCTGCTCCTGGTGTTG; IL-6 reverse: CCTCTTTGCTGCTTTCA; IL-10 forward: TGAGAACCAAGACCCAGAC; IL-10 reverse: TTCACAGGGAAGAAATCG; TGF-β1 forward: CTGTGGCTACTGGTGCTGAC; TGF-β1 reverse: CATAGATTTCGTTGTGGGTTTC; GAPDH forward: AATCCCATCACCATCTTCC; and GAPDH reverse: GAGTCCTTCCACGATACCAA.

Treatment of periodontitis in mice

The typical ligature-induced periodontitis mice model was performed. All animal study protocols were performed under the guidelines of the Institutional Animal Care and Use Committee of Sun Yat-Sen University (SYSU-IACUC-2024-002181). Twenty male C57BL/6 mice (4 weeks old, 20 to 25 g) were randomly divided into the following five groups: periodontitis control group, starch gel (with 10% ethanol), curcumin@gel, microrobots@gel, and microrobots@gel + magnetic field. Periodontitis was induced by tying a 5-0 silk ligature in the cervical region of the maxillary bilateral second molars. The ligatures were examined every other day to ensure that they remained in place during the experimental period.

After 1 week, animals in the control group were treated with PBS (50 μl), and animals in starch gel (50 μl), curcumin@gel (100 μg/ml, 50 μl), microrobots@gel (2 mg/ml, 50 μl), and microrobots@gel (2 mg/ml, 50 μl) + magnetic field groups were injected into the periodontal pockets with starch gel. Then, the microrobots@gel + magnetic field group mouse was treated with a portable handheld magnetic controller for 30 min each. The operation was performed every 2 days. After 2 weeks, the mice were executed to collect tissues to assess the treatment effect.

Micro–computed tomography analysis

Mouse maxillary jaws were scanned using micro-CT (Scano Medical AG) to assess alveolar bone loss and bone density. The 3D images were reconstructed using Mimics Research 21.0 (Materialise). The distance between the CEJ and the ABC was measured on the mesial root surface of the second molars to evaluate the level of bone loss. Trabecular morphometry was determined by measuring bone volume/tissue volume ratio (BV/TV), number of trabeculae (Tb.N), and spacing of trabeculae (Tb.Sp).

Histological analysis

Mouse heart, liver, spleen, lung, and kidney tissues were excised, embedded in paraffin, and sectioned. Sections were stained with H&E for pathologic analysis to assess in vivo safety.

Isolated mouse maxillae were collected, fixed in 10% formalin for 24 hours, decalcified in EDTA slow decalcification solution (Servicebio) for 4 weeks, dehydrated and embedded in paraffin. Then, 4-μm slices were prepared. The slices were then stained with H&E to examine histological alterations. Masson staining was performed to detect collagen formation during the healing process.

TRAP staining was used to assess the number of osteoclasts, using a TRAP staining kit (Sigma-Aldrich, 387A). The numbers of TRAP cells were counted on each TRAP-stained section by two independent investigators.

IHC was carried out in the following steps: dewaxing, rehydrated in graded alcohol, 3% hydrogen peroxide closure, high-temperature antigen repair, and antigen closure. Next slices were incubated with anti–IL-1β (Affinity, AF5103), TNF-α (Abiowell, AWA10207), and IL-6 (Abiowell, AWA46788) antibodies, respectively, overnight at 4°C. After treatment with horseradish peroxidase–conjugated goat anti-rabbit secondary antibody, slides were stained with 3,3-diaminobenzidine. The stained slides were then scanned using an Aperio AT2 scanner (Leica). H score and percentage of positive cells were quantified by background subtraction using the Aperio eSlide Manager quantification software. The threshold for scanning of different positive cells was set according to the standard control slices provided by Aperio (74).

To assess macrophage infiltration, maxillae sections from mice were incubated overnight at 4°C with primary antibodies against F4/80 (eBioscience, 14-4801-85), CD86 (Cell Signaling Technology, 91882), or CD206 (Cell Signaling Technology, 24595). Following primary antibody incubation, sections were treated with Alexa Fluor 488– or Alexa Fluor 594–conjugated secondary antibodies. Nonspecific binding was blocked using an aqueous blocking buffer, and coverslips were mounted. Fluorescence imaging was taken and analyzed using an Olympus fluorescence microscope.

16S rDNA sequence

Microbial DNA was obtained from the oral gingiva of C57BL/6 mice using the FastDNA Spin Kit. 16S rDNA gene sequencing was performed by Cosmos Wisdom Co. Ltd. (Hangzhou, China). The quality and quantity of the extracted DNA were determined by a NanoDrop2000. 16S rDNA genes (V3 + V4 region) were amplified using universal primers (338F 5′-ACTCCTACGGGAGGCAGCAG-3′ and 806R 5′-GGACTACHVGGGTWTCTAAT-3′) that contained adapter and barcode sequences. All PCRs were carried out with FastPfu Polymerase. Sequencing libraries were generated using the NEXTFLEX Rapid DNA-Seq Kit. The library was sequenced using the Illumina PE250 platform. The raw sequencing reads were filtered using fastp (75). Then, cutadapt (76) was used to identify and remove primer sequences, yielding clean reads devoid of primer regions. Subsequently, the DADA2 method (77) within QIIME2 (78) was used for denoising (generating denoised reads), merging paired-end sequences (producing merged reads), and removing chimeric sequences, ultimately resulting in high-quality nonchimeric reads as the final effective data. The resulting amplicon sequence variants (ASVs) were taxonomically annotated using the Naive Bayesian classifier in QIIME2, referencing the Silva 138.1 database (79), to assign taxonomic classifications (phylum to species) to each ASV. Community composition across samples was analyzed at all taxonomic levels, and QIIME2-generated abundance tables were used for downstream visualization. Bioinformatic analysis was performed using the OmicStudio tools at https://omicstudio.cn/tool (80).

Characterization techniques

FTIR spectroscopy was performed on a Thermo Nicolet NEXUS-470 spectrometer using potassium bromide pellet technique. The zeta potential was measured by dynamic light scattering with Zetasizer Nano ZEP. AFM measurements were performed on Bruker Dimension Icon with NanoScope. SEM images and EDS were captured by Carl Zeiss Microscopy GmbH Gemini SEM 300 and Oxford instruments X-Max, respectively. Transmission electron microscopy images were captured by a Hitachi JEM-2100 (JEOL) electron microscope. CLSM micrographs and fluorescence images were taken with a Nikon A1r and Leica inverted optical microscope (DMi8), respectively. XPS was conducted via an Axis Ultra DLD (Kratos) spectrometer with an Al Kα radiation under ultrahigh vacuum condition. The magnetic properties were evaluated at 300 K using a PPMS Model 6000 Quantum Design VSM.

Statistical analysis

All statistical analyses were implemented with GraphPad Prism 8.0. Unpaired two-tailed Student’s t test for two groups was used. Analysis of variance (ANOVA) was performed on multiple groups, followed by Dunnett’s multiple comparison test or Tukey’s multiple comparison test. Results are expressed as mean ± standard deviation (SD) from at least three independent experiments. *P < 0.05 was considered statistically significant.

Acknowledgments

Funding:

This work is supported by the National Natural Science Foundation of China (U22A20315) (Z.W.), Shenzhen Medical Research Fund (A2403068) (D.J.), and National Science Fund for Distinguished Young Scholars (82325013) (Z.W.). The authors also thank the support from National Natural Science Foundation of China (52202347) (W.C.) and (52472280) (D.J.); Guangdong Special Support Program for Outstanding Youth Talent (2024TQ08C855) (D.J.); Shenzhen Science and Technology Program (RCJC20231211090000001, GXWD20231129101105001) (X.M.), (JCYJ20250604145629040) (D.H.), (GXWD20231129105757003) (W.C.), (KJZD20231023100302006) (D.J.); and Macau Foundation for Development of Science and Technology (0008/2024/RIA1) (X.M.).

Author contributions:

Conceptualization: X.M., Z.W., D.J., D.H., and Q.W. Resources: X.M. and D.J. Methodology: D.H., Z.Z., D.J., and X.M. Investigation: D.H., Z.Z., X.M., W.C., and M.Y. Validation: X.M., D.H., Z.Z., D.J., Q.H., M.Y., J.L., C.X., and W.C. Data curation: D.H., Z.Z., Z.G., and J.F. Formal analysis: D.H., Z.G., Y.S., Q.H., W.C., and J.F. Software: Y.S. Visualization: D.H. and D.J. Funding acquisition: X.M., D.H., and D.J. Supervision: X.M., Z.W., Q.W., and D.J. Writing–original draft: D.H. and X.M. Writing–review and editing: Z.Z., X.M., Z.W., Q.W., W.C., and D.J. Project administration: X.M. and D.J.

Competing interests:

The authors declare that they have no competing interests.

Data, code, and materials availability:

All data and code needed to evaluate and reproduce the results in the paper are present in the paper and/or the Supplementary Materials. The raw sequencing data that support the findings of this study have been deposited in the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) under BioProject accession no. PRJNA1472985. The ionogel, drug-loaded ionogel microspheres, and nanothorn-modified ionogel microrobots, are available from the corresponding author X.M. (maxing@hit.edu.cn) upon reasonable request. Detailed preparation procedures are described in Materials and Methods.

Supplementary Materials

The PDF file includes:

Supplementary Text S1

Figs. S1 to S55

Table S1

Legends for movies S1 to S8

sciadv.aeb6882_sm.pdf^{(4.8MB, pdf)}

Other Supplementary Material for this manuscript includes the following:

Movies S1 to S8

sciadv.aeb6882_movies_s1_to_s8.zip^{(25MB, zip)}

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Text S1

Figs. S1 to S55

Table S1

Legends for movies S1 to S8

sciadv.aeb6882_sm.pdf^{(4.8MB, pdf)}

Movies S1 to S8

sciadv.aeb6882_movies_s1_to_s8.zip^{(25MB, zip)}

Data Availability Statement

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PERMALINK

Sharp nanothorn-equipped ionogel microrobots for targeted periodontitis therapy

Dongqing He

Zhaolei Zou

Dongdong Jin

Zichang Guo

Yinuo Song

Qiannan Hu

Muqiao Yu

Jingyi Lu

Juan Fang

Qianqian Wang

Chengqi Xu

Wenjun Chen

Zhi Wang

Xing Ma

Roles

Abstract

INTRODUCTION

Fig. 1. Schematic of the synthetic procedure and periodontitis therapy of microrobots.

RESULTS

Preparation and characterization of magnetic ionogel-based microrobots

Fig. 2. Fabrication and characterization of the ionogel microrobots.

Magnetically actuated motion behavior of ionogel microrobots

Fig. 3. Magnetically controlled motion behavior of the microrobots and their swarm.

Mucus barrier penetration and tissue adhesion performance of ionogel microrobots in vitro and in vivo

Fig. 4. Mucus barrier penetration and tissue adhesion performance of the microrobots in vitro and in vivo.

Mechanical removal of bacterial biofilm via active motion of ionogel microrobots

Fig. 5. Active motion–enabled mechanical removal of bacterial biofilm by magnetically actuated microrobots.

Controlled drug release of ionogel microrobots for synergistic bacterial killing and inflammation elimination

Fig. 6. The antibacterial and anti-inflammatory properties of curcumin drug-loaded microrobots.

Therapeutic efficacy of ionogel microrobots against periodontitis in vivo

Fig. 7. Evaluations of the therapeutic efficacy of microrobots for periodontitis treatment in vivo.

Anti-inflammatory mechanism and microbiota regulation of ionogel microrobots in vivo

Fig. 8. Immune regulation mechanism and oral microbiota regulation of microrobots in vivo.

DISCUSSION

MATERIALS AND METHODS

Materials

Preparation of drug loaded ionogel microrobots

Preparation of curcumin@gel and microrobots@gel

Cell lines, bacterial strains, and culture

Experiment of microrobots drilling to overcome simulated mucus

Adhesion of microrobots assay

Mechanical removal of bacterial biofilm assay

Simulation methodology

Evaluation of drug loading and release

Antibacterial activity

Bacterial biofilm formation test

Cell viability assay

Hemolysis test

Free radical scavenging assay

Intracellular ROS-scavenging in vitro

Anti-inflammation assay

Treatment of periodontitis in mice

Micro–computed tomography analysis

Histological analysis

16S rDNA sequence

Characterization techniques

Statistical analysis

Acknowledgments

Funding:

Author contributions:

Competing interests:

Data, code, and materials availability:

Supplementary Materials

The PDF file includes:

Other Supplementary Material for this manuscript includes the following:

REFERENCES

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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