Customizable, wireless and implantable neural probe design and fabrication via 3D printing

Advances in gut-brain organ chips

The brain and gut are sensory organs responsible for sensing, transmitting, integrating, and responding to signals from the internal and external environment. In-depth analysis of brain-gut axis interactions is important for human health and disease prevention. Current research on the brain-gut axis primarily relies on animal models. However, animal models make it difficult to study disease mechanisms due to inherent species differences, and the reproducibility of experiments is poor because of individual animal variations, which leads to a significant limitation of real-time sensory responses. Organ-on-a-chip platforms provide an innovative approach for disease treatment and personalized research by replicating brain and gut ecosystems in vitro. This enables a precise understanding of their biological functions and physiological responses. In this article, we examine the history and most current developments in brain, gut, and gut-brain chips. The importance of these systems for understanding pathophysiology and developing new drugs is emphasized throughout the review. This article also addresses future directions and present issues with the advancement and application of gut-brain-on-a-chip technologies.

Special Section Guest Editorial: Open-source neurophotonic tools for neuroscience

The editorial completes the Neurophotonics special series on open-source neurophotonic tools for neuroscience.

Body-temperature softening electronic ink for additive manufacturing of transformative bioelectronics via direct writing

Mechanically transformative electronic systems (TESs) built using gallium have emerged as an innovative class of electronics due to their ability to switch between rigid and flexible states, thus expanding the versatility of electronics. However, the challenges posed by gallium's high surface tension and low viscosity have substantially hindered manufacturability, limiting high-resolution patterning of TESs. To address this challenge, we introduce a stiffness-tunable gallium-copper composite ink capable of direct ink write printing of intricate TES circuits, offering high-resolution (~50 micrometers) patterning, high conductivity, and bidirectional soft-rigid convertibility. These features enable transformative bioelectronics with design complexity akin to traditional printed circuit boards. These TESs maintain rigidity at room temperature for easy handling but soften and conform to curvilinear tissue surfaces at body temperature, adapting to dynamic tissue deformations. The proposed ink with direct ink write printing makes TES manufacturing simple and versatile, opening possibilities in wearables, implantables, consumer electronics, and robotics.

Printable devices for neurotechnology

Printable electronics for neurotechnology is a rapidly emerging field that leverages various printing techniques to fabricate electronic devices, offering advantages in rapid prototyping, scalability, and cost-effectiveness. These devices have promising applications in neurobiology, enabling the recording of neuronal signals and controlled drug delivery. This review provides an overview of printing techniques, materials used in neural device fabrication, and their applications. The printing techniques discussed include inkjet, screen printing, flexographic printing, 3D printing, and more. Each method has its unique advantages and challenges, ranging from precise printing and high resolution to material compatibility and scalability. Selecting the right materials for printable devices is crucial, considering factors like biocompatibility, flexibility, electrical properties, and durability. Conductive materials such as metallic nanoparticles and conducting polymers are commonly used in neurotechnology. Dielectric materials, like polyimide and polycaprolactone, play a vital role in device fabrication. Applications of printable devices in neurotechnology encompass various neuroprobes, electrocorticography arrays, and microelectrode arrays. These devices offer flexibility, biocompatibility, and scalability, making them cost-effective and suitable for preclinical research. However, several challenges need to be addressed, including biocompatibility, precision, electrical performance, long-term stability, and regulatory hurdles. This review highlights the potential of printable electronics in advancing our understanding of the brain and treating neurological disorders while emphasizing the importance of overcoming these challenges.

3D Printed Integrated Sensors: From Fabrication to Applications-A Review

The integration of 3D printed sensors into hosting structures has become a growing area of research due to simplified assembly procedures, reduced system complexity, and lower fabrication cost. Embedding 3D printed sensors into structures or bonding the sensors on surfaces are the two techniques for the integration of sensors. This review extensively discusses the fabrication of sensors through different additive manufacturing techniques. Various additive manufacturing techniques dedicated to manufacture sensors as well as their integration techniques during the manufacturing process will be discussed. This review will also discuss the basic sensing mechanisms of integrated sensors and their applications. It has been proven that integrating 3D printed sensors into infrastructures can open new possibilities for research and development in additive manufacturing and sensor materials for smart goods and the Internet of Things.

3D Printed Customizable Microsampling Devices for Neuroscience Applications

Multifunctional devices that incorporate chemical or physical measurements combined with ways to manipulate brain tissue via drug delivery, electrical stimulation, or light for optogenetics are desired by neuroscientists. The next generation in vivo brain devices will likely utilize the extensive flexibility and rapid processing of 3D printing. This Perspective demonstrates how close we are to this reality for advanced neuroscience measurements. 3D printing provides the opportunity to improve microsampling-based devices in ways that have not been previously available. Not only can 3D printing be used for actual device creation, but it can also allow printing of peripheral objects necessary to assemble functional devices. The most probable 3D printing set up for microsampling devices with appropriate nm to μm feature size will likely require 2-photon polymerization-based printers. This Perspective describes the advantages and challenges for 3D printing of microsampling devices as an initial step to meet the next generation device needs of neuroscientists.

Conducting polymer-based nanostructured materials for brain-machine interfaces

As scientists discovered that raw neurological signals could translate into bioelectric information, brain-machine interfaces (BMI) for experimental and clinical studies have experienced massive growth. Developing suitable materials for bioelectronic devices to be used for real-time recording and data digitalizing has three important necessitates which should be covered. Biocompatibility, electrical conductivity, and having mechanical properties similar to soft brain tissue to decrease mechanical mismatch should be adopted for all materials. In this review, inorganic nanoparticles and intrinsically conducting polymers are discussed to impart electrical conductivity to systems, where soft materials such as hydrogels can offer reliable mechanical properties and a biocompatible substrate. Interpenetrating hydrogel networks offer more mechanical stability and provide a path for incorporating polymers with desired properties into one strong network. Promising fabrication methods, like electrospinning and additive manufacturing, allow scientists to customize designs for each application and reach the maximum potential for the system. In the near future, it is desired to fabricate biohybrid conducting polymer-based interfaces loaded with cells, giving the opportunity for simultaneous stimulation and regeneration. Developing multi-modal BMIs, Using artificial intelligence and machine learning to design advanced materials are among the future goals for this field. This article is categorized under: Therapeutic Approaches and Drug Discovery > Nanomedicine for Neurological Disease.