Commonly Overlooked Factors in Biocompatibility Studies of Neural Implants

Creating ionic current pathways: A non-implantation approach to achieving cortical electrical signals for brain-computer interface

This study introduces a novel method for acquiring brain electrical signals comparable to intracranial recordings without the health risks associated with implanted electrodes. We developed a technique using ultrasonic tools to create micro-holes in the skull and insert hollow implants, preventing natural healing. This approach establishes an artificial ionic current path (AICP) using tissue fluid, facilitating signal transmission from the cortex to the scalp surface. Experiments were conducted on pigs to validate the method's effectiveness. We synchronized our recordings with perforated electrocorticography (ECoG) for comparison. The AICP method yielded signal quality comparable to implanted ECoG in the low-frequency range, with a significant improvement in signal-to-noise ratio for evoked potentials. Our results demonstrate that this non-invasive technique can acquire high-quality brain signals, offering potential applications in neurophysiology, clinical research, and brain-computer interfaces. This innovative approach of utilizing tissue fluid as a natural conduction path opens new avenues for brain signal acquisition and analysis.

Flexible Neural Interface From Non-Transient Silk Fibroin With Outstanding Conformality, Biocompatibility, and Bioelectric Conductivity

Silk fibroin (SF) with good biocompatibility can enable an efficient and safe implementation of neural interfaces. However, it has been difficult to achieve a robust integration of patterned conducting materials (multichannel electrodes) on flexible SF film substrates due to the absence of some enduring interactions. In this study, a thermo-assisted pattern-transfer technique is demonstrated that can facilely transfer a layer of pre-set poly(3,4-ethylenedioxythiophene) (PEDOT) onto the flexible SF substrate through an interpenetrating network of 2 polymer chains, achieving a desired substrate/conductor intertwined interface with good flexibility (≈33 MPa), conductivity (386 S cm-1) and stability in liquid state over 4 months simultaneously. Importantly, this technique can be combined with ink-jet printing to prepare a multichannel SF-based neural interface for the electrocorticogram (ECoG) recording and inflammation remission in rat models. The SF-based neural interface with satisfied tissue conformability, biocompatibility, and bioelectric conductivity is a promising ECoG acquisition tool, where the demonstrated approach can also be useful to develop other SF-based flexible bioelectronics.

Smart zwitterionic coatings with precise pH-responsive antibacterial functions for bone implants to combat bacterial infections

Hydrophilic antifouling coatings based on zwitterionic polymers have been widely applied for the surface modification of bone implants to combat biofilm formation and reduce the likelihood of implant-related infections. However, their long-term effectiveness is significantly limited by the lack of effective and precise antibacterial activity. Here, a pH-responsive smart zwitterionic antibacterial coating (PSB/GS coating) was designed and robustly fabricated onto titanium-base bone implants by using a facile two-step method. First, dopamine (DA) and a poly(sulfobetaine methacrylate-co-dopamine methacrylamide) (PSBDA) copolymer were deposited on implants via mussel-inspired surface chemistry, resulting in a hydrophilic base coating with abundant catechol residues. Next, an amino-rich antibiotic, gentamicin sulfate (GS), was covalently linked to the coating through the formation of acid-sensitive Schiff base bonds between the amine groups of GS and the catechol residues present in both the zwitterionic polymer and the DA component. During the initial implantation period, the hydrophilic zwitterionic polymers demonstrated the desired anti-fouling properties that could effectively reduce protein and bacterial adhesion by over 90%. With time, the bacterial proliferation led to a decrease in the microenvironment pH value, resulting in the hydrolysis of the acid-sensitive Schiff base bonds, thereby releasing GS on demand and effectively enhancing the anti-biofilm properties of coatings. Benefiting from this synergistic antifouling and smart antibacterial activities, the PSB/GS coating exerted an excellent anti-infective activity in both in vivo preoperative and postoperative infection rat models. This proposed facile yet effective coating strategy is expected to provide a promising solution to combat bone implant-related infections.

Towards detection of cancer biomarkers in human exhaled air by transfer-learning-powered analysis of odor-evoked calcium activity in rat olfactory bulb

Detection of volatile organic compounds in exhaled air is a promising approach to non-invasive and scalable gastric cancer screening. This work proposes a new approach for the detection of volatile organic compounds by analyzing odor-evoked calcium responses in the rat olfactory bulb. We estimate the feasibility of gastric cancer biomarker detection added to the exhaled air of healthy participants. Our detector consists of a convolutional encoder and a similarity-based classifier over encoder outputs. To minimize overfitting on a small available training set, we involve a pre-training where the encoder is trained on synthetic data representing spatiotemporal patterns similar to real calcium responses in the olfactory bulb. We estimate the classification accuracy of exhaled air samples by matching their encodings with encodings of calibration samples of two classes: 1) exhaled air and 2) a mixture of exhaled air with the cancer biomarker. On our data, the accuracy increased from 0.68 on real data up to 0.74 if pre-training on synthetic data is involved. Our work is focused on proving the feasibility of proposed new approach rather than on comparing its efficiency with existing methods. Such detection is often performed with an electronic nose, but its output becomes unstable over time due to a sensor drift. In contrast to the electronic nose, rats can robustly detect low concentrations of biomarkers over lifetime. The feasibility of gastric cancer biomarker detection in exhaled air by bio-hybrid system is shown. Pre-training of neural models for images analysis increases the accuracy of detection.