Microcatheters have enabled diverse minimally invasive endovascular operations and notable health benefits compared with open surgeries. However, with tortuous routes far from the arterial puncture site, the distal vascular regions remain challenging for safe catheter access. Therefore, we propose a wireless stent-shaped magnetic soft robot to be deployed, actively navigated, used for medical functions, and retrieved in the example M4 segment of the middle cerebral artery. We investigate shape-adaptively controlled locomotion in phantoms emulating the physiological conditions here, where the lumen diameter shrinks from 1.5 mm to 1 mm, the radius of curvature of the tortuous lumen gets as small as 3 mm, the lumen bifurcation angle goes up to 120°, and the pulsatile flow speed reaches up to 26 cm/s. The robot can also withstand the flow when the magnetic actuation is turned off. These locomotion capabilities are confirmed in porcine arteries ex vivo. Furthermore, variants of the robot could release the tissue plasminogen activator on-demand locally for thrombolysis and function as flow diverters, initiating promising therapies towards acute ischemic stroke, aneurysm, arteriovenous malformation, dural arteriovenous fistulas, and brain tumors. These functions should facilitate the robot’s usage in new distal endovascular operations.

Neural interfaces are the fundamental tools to understand the brain and cure many nervous-system diseases. For proper interfacing, seamless integration, efficient and safe digital-to-biological signal transduction, and long operational lifetime are required. Here, we devised a wireless optoelectronic pseudocapacitor converting the optical energy to safe capacitive currents by dissociating the photogenerated excitons in the photovoltaic unit and effectively routing the holes to the supercapacitor electrode and the pseudocapacitive electrode–electrolyte interfacial layer of PEDOT:PSS for reversible faradic reactions. The biointerface showed high peak capacitive currents of ∼3 mA·cm –2 with total charge injection of ∼1 μC·cm –2 at responsivity of 30 mA·W –1 , generating high photovoltages over 400 mV for the main eye photoreception colors of blue, green, and red. Moreover, modification of PEDOT:PSS controls the charging/discharging phases leading to rapid capacitive photoresponse of 50 μs and effective membrane depolarization at the single-cell level. The neural interface has a device lifetime of over 1.5 years in the aqueous environment and showed stability without significant performance decrease after sterilization steps. Our results demonstrate that adopting the pseudocapacitance phenomenon on organic photovoltaics paves an ultraefficient, safe, and robust way toward communicating with biological systems.

Light activated modulation of neural activity is an emerging field for the basic investigation of neural systems and development of new therapeutic methods such as artificial retina. Colloidal inorganic nanocrystals have great potential for neural interfaces due to their adjustable optoelectronic properties via high-level structural, compositional, and size control. However, toxic heavy metal content (e.g., cadmium, mercury), electrochemical coupling to the cells and low photon-to-current efficiency limit their effective use. Here, we introduce the use of aluminum antimonide (AlSb) nanocrystals as the cell interfacing layer for capacitive neural stimulation in the blue spectrum. We demonstrate successful photostimulation of primary hippocampal neurons below ocular safety limits. In addition, our device shows high biocompatibility in vitro and passive accelerated ageing tests indicate a functional lifetime over 3 years showing their feasible use for chronic implants. We demonstrate that nanocrystal biointerfaces hold high promise for future bioelectronics and protheses.

Optoelectronic biointerfaces have made a significant impact on modern science and technology from understanding the mechanisms of the neurotransmission to the recovery of the vision for blinds. They are based on the cell interfaces made of organic or inorganic materials such as silicon, graphene, oxides, quantum dots, and 𝝅-conjugated polymers, which are dry and stiff unlike a cell/tissue environment. On the other side, wet and soft hydrogels have recently been started to attract significant attention for bioelectronics because of its high-level tissue-matching biomechanics and biocompatibility. However, it is challenging to obtain optimal opto-bioelectronic devices by using hydrogels requiring device, heterojunction, and hydrogel engineering. Here, an optoelectronic biointerface integrated with a poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate), PEDOT:PSS, hydrogel that simultaneously achieves efficient, flexible, stable, biocompatible, and safe photostimulation of cells is demonstrated. Besides their interfacial tissue-like biomechanics, ≈34 kPa, and high-level biocompatibility, hydrogel-integration facilitates increase in charge injection amounts sevenfolds with an improved responsivity of 156 mA W −1 , stability under mechanical bending , and functional lifetime over three years. Finally, these devices enable stimulation of individual hippocampal neurons and photocontrol of beating frequency of cardiac myocytes via safe charge-balanced capacitive currents. Therefore, hydrogel-enabled optoelectronic biointerfaces hold great promise for next-generation wireless neural and cardiac implants.

Neural photostimulation has high potential to understand the working principles of complex neural networks and develop novel therapeutic methods for neurological disorders. A key issue in the light-induced cell stimulation is the efficient conversion of light to bioelectrical stimuli. In photosynthetic systems developed in millions of years by nature, the absorbed energy by the photoabsorbers is transported via nonradiative energy transfer to the reaction centers. Inspired by these systems, neural interfaces based on biocompatible quantum funnels are developed that direct the photogenerated charge carriers toward the bionanojunction for effective photostimulation. Funnels are constructed with indium-based rainbow quantum dots that are assembled in a graded energy profile. Implementation of a quantum funnel enhances the generated photoelectrochemical current 215% per unit absorbance in comparison with ungraded energy profile in a wireless and free-standing mode and facilitates optical neuromodulation of a single cell. This study indicates that the control of charge transport at nanoscale can lead to unconventional and effective neural interfaces.

Light-activated biointerfaces provide a non-genetic route for effective control of neural activity. InP quantum dots (QDs) have a high potential for such biomedical applications due to their uniquely tunable electronic properties, photostability, toxic-heavy-metal-free content, heterostructuring, and solution-processing ability. However, the effect of QD nanostructure and biointerface architecture on the photoelectrical cellular interfacing remained unexplored. Here, we unravel the control of the photoelectrical response of InP QD-based biointerfaces via nanoengineering from QD to device-level. At QD level, thin ZnS shell growth (∼0.65 nm) enhances the current level of biointerfaces over an order of magnitude with respect to only InP core QDs. At device-level, band alignment engineering allows for the bidirectional photoelectrochemical current generation, which enables light-induced temporally precise and rapidly reversible action potential generation and hyperpolarization on primary hippocampal neurons. Our findings show that nanoengineering QD-based biointerfaces hold great promise for next-generation neurostimulation devices.

In vivo confocal microscopy (IVCM) is a noninvasive, reproducible, and inexpensive diagnostic tool for corneal diseases. However, widespread and effortless image acquisition in IVCM creates serious image analysis workloads on ophthalmologists, and neural networks could solve this problem quickly. We have produced a novel deep learning algorithm based on generative adversarial networks (GANs), and we compare its accuracy for automatic segmentation of subbasal nerves in IVCM images with a fully convolutional neural network (U-Net) based method. Methods:We have collected IVCM images from 85 subjects. U-Net and GAN-based image segmentation methods were trained and tested under the supervision of three clinicians for the segmentation of corneal subbasal nerves. Nerve segmentation results for GAN and U-Net-based methods were compared with the clinicians by using Pearson's R correlation, Bland-Altman analysis, and receiver operating characteristics (ROC) statistics. Additionally, different noises were applied on IVCM images to evaluate the performances of the algorithms with noises of biomedical imaging. Results:The GAN-based algorithm demonstrated similar correlation and Bland-Altman analysis results with U-Net. The GAN-based method showed significantly higher accuracy compared to U-Net in ROC curves. Additionally, the performance of the U-Net deteriorated significantly with different noises, especially in speckle noise, compared to GAN. Conclusions:This study is the first application of GAN-based algorithms on IVCM images. The GAN-based algorithms demonstrated higher accuracy than U-Net for automatic corneal nerve segmentation in IVCM images, in patient-acquired images and noise applied images. This GAN-based segmentation method can be used as a facilitating diagnostic tool in ophthalmology clinics.Translational Relevance: Generative adversarial networks are emerging deep learning models for medical image processing, which could be important clinical tools for rapid segmentation and analysis of corneal subbasal nerves in IVCM images.

Optoelectronic photoelectrodes based on capacitive charge-transfer offer an attractive route to develop safe and effective neuromodulators. Here, we demonstrate efficient optoelectronic photoelectrodes that are based on the incorporation of quantum dots (QDs) into poly(3-hexylthiophene-2,5-diyl) (P3HT) and [6,6]-Phenyl-C61-butyric acid methyl ester (PCBM) bulk heterojunction. We control the performance of the photoelectrode by the blend ratio, thickness, and nanomorphology of the ternary bulk heterojunction. The optimization led to a photocapacitor that has a photovoltage of 450 mV under a light intensity level of 20 mW.cm−2 and a responsivity of 99 mA/W corresponding to the most light-sensitive organic photoelectrode reported to date. The photocapacitor can facilitate action potential generation by hippocampal neurons via burst waveforms at an intensity level of 20 mW.cm−2. Therefore, the results point to an alternative direction in the engineering of safe and ultra-light-sensitive neural interfaces.