Wireless bioelectronic interfaces are increasingly used to control tissue-engineered, muscle-powered biohybrid robotic systems. However, a unifying engineering framework linking device design to system-level control remains underdeveloped. Here, we formulate wireless control in biohybrid robotics as a coupled co-design problem integrating signal delivery, spatial selectivity, scalability, sensing and feedback, controller implementation, biological life support, and interface stability. We analyze three representative actuation and control strategies—wireless electrical stimulation, wireless optoelectronic stimulation, and neuromuscular integration—which operate in distinct regimes with characteristic trade-offs. Across these modalities, the tissue–device interface emerges as a key constraint governing the interplay among electrical or optical signal delivery, circuit performance, sensing, and biomechanical response. We outline practical design principles spanning electromagnetic field distribution, circuit architecture, actuator mechanics, multi-actuator addressing, and closed-loop control. Rather than treating neural organoids as an inevitable end point, we compare conventional electronic controllers, neuronal culture–silicon interfaces, and organoid–microelectrode array systems as alternative trajectories toward closed-loop autonomy. This system-level perspective provides design guidelines for stable, scalable, and application-driven biohybrid robotic systems.
Closed-loop control over bladder function, for conditions such as neurogenic bladder dysfunction, requires real-time monitoring of bladder state. Here, we assessed the ability of a novel recording and analysis technique to extract neural activity from awake rats as a quasi-real-time feedback biomarker of bladder fullness in normal and chronic cystitis models. Adult male rats (n = 12) were implanted with a four-electrode planar array and the bladder instrumented for continuous-flow cystometry over 2 weeks. In three rats, bladder inflammation was induced using cyclophosphamide (CYP, 75-100 mg/kg, i.p.). Neural recordings were made during awake cystometry, and extracted Aδ afferent activity was correlated with bladder pressure. In control rats (n = 9), there was a strong, stable correlation of integrated Aδ activity with bladder pressure during filling at 1 week (R 2: 0.55 ± 0.04) and 2 weeks (R 2: 0.57 ± 0.04; p > 0.05). In CYP-cystitis rats (days 9, 11, and 14), there was no difference in this correlation (week 2: 0.54 ± 0.031; p > 0.05). Taken together, data suggest the recording and analysis technology remained stable in awake, freely moving normal rats and during 2 weeks of chronic implantation. Furthermore, data show potential that abnormal activation of nociceptive afferents in cystitis rats, which causes an increase in baseline activity, does not weaken correlation of Aδ activity with bladder pressure. In conclusion, this feasibility study is a promising first study step for the translation of closed-loop technology for bladder control for neurogenic bladder dysfunction.
Currently, preclinical research on colorectal cancer (CRC) lacks effective tumor models. In recent years, 3D bioprinted models have shown great potential in tumor model construction. This study used 3D bioprinting technology to establish a CRC extracellular matrix (ECM) model. Gradient concentrations of laminin/entactin complex combined with photocurable gelatin methacrylate (GelMA) hydrogel were used to prepare 3D bioprinting bioinks with biomimetic ECM properties. Biocompatibility was assessed by calcein-AM and propidium iodide staining. Proliferation was evaluated using the CellTiter-Glo® Luminescent Cell Viability Assay Kit in SW620 cells and primary CRC cells. A “sandwich structure” model with inner and outer layers of GelMA or GelMA + LE2 was constructed to observe cell invasion. Mechanical properties of GelMA + LE2 were characterized. Total RNA was extracted from cells in 3D bioprinted models constructed with GelMA and GelMA + LE2 for transcriptome sequencing. Finally, chemotherapeutic drug tests were performed on the 3D bioprinted models. A 3D bioprinted CRC organoid model based on GelMA + LE2 was successfully established. This model exhibited good biocompatibility and the ability to promote tumor cell proliferation and invasion. These characteristics were independent of the model's mechanical properties. Instead, they originated from LE2 activating the ErbB/Wnt signaling pathway and gap junction-mediated intercellular communication. Additionally, a significant correlation was observed between the clinical treatment outcomes of CRC patients and the drug test results of the 3D bioprinted models. The 3D bioprinted CRC organoid constructed in this study provides a biomimetic and high-throughput research platform for precision medicine.
Endovascular coiling is a minimally invasive therapeutic option for intracranial aneurysm (IA). This technique involves occluding the aneurysmal sac with one or more metallic coils to decrease perfusion of the dilated arterial wall. Although coil deployment has proven to be generally effective, clinical outcomes are difficult to predict, with aneurysms reopening occurring in approximately 20% of cases. The purpose of this study is to use in silico modeling combined with statistical analysis and machine learning to predict the biomechanical outcomes of coiling by studying the relationship between IA morphology and post-coiling quantitative parameters. First, a clinical database of IAs was parametrized based on a set of geometrical features. and 500 synthetic sac geometries were virtually generated. Simulations of coil deployment were then performed for each of these geometries, and the resulting reaction force, elastic energy, and contact pressure were used to train a predictive machine learning algorithm. The surrogate model demonstrated strong predictive performance for the reaction force (R2 = 0.74 and MAPE = 4.56%) and moderate performance for the elastic energy stored by the deformed coil (R2 = 0.68 and MAPE = 26.95%). Morphological factors such as aneurysm sac volume, surface, and height showed a good correlation with simulation parameters using Spearman analysis. As a preliminary proof-of-concept study, this methodology represents a first step toward the development of an in silico tool aimed at enhancing pre-operative planning for endovascular coil procedures. This has the potential to improve the stratification of patients at higher risk of complications and the identification of borderline IAs that may not be suitable for endovascular coiling.
