Advanced capabilities in electrical recording are essential for the treatment of heart-rhythm diseases. The most advanced technologies use flexible integrated electronics; however, the penetration of biological fluids into the underlying electronics and any ensuing electrochemical reactions pose significant safety risks. Here, we show that an ultrathin, leakage-free, biocompatible dielectric layer can completely seal an underlying layer of flexible electronics while allowing for electrophysiological measurements through capacitive coupling between tissue and the electronics, and thus without the need for direct metal contact. The resulting current-leakage levels and operational lifetimes are, respectively, four orders of magnitude smaller and between two and three orders of magnitude longer than those of any other flexible-electronics technology. Systematic electrophysiological studies with normal, paced and arrhythmic conditions in Langendorff hearts highlight the capabilities of the capacitive-coupling approach. Our technology provides a realistic pathway towards the broad applicability of biocompatible, flexible electronic implants.

Materials that can serve as long-lived barriers to biofluids are essential to the development of any type of chronic electronic implant. Devices such as cardiac pacemakers and cochlear implants use bulk metal or ceramic packages as hermetic enclosures for the electronics. Emerging classes of flexible, biointegrated electronic systems demand similar levels of isolation from biofluids but with thin, compliant films that can simultaneously serve as biointerfaces for sensing and/or actuation while in contact with the soft, curved, and moving surfaces of target organs. This paper introduces a solution to this materials challenge that combines (i) ultrathin, pristine layers of silicon dioxide (SiO2) thermally grown on device-grade silicon wafers, and (ii) processing schemes that allow integration of these materials onto flexible electronic platforms. Accelerated lifetime tests suggest robust barrier characteristics on timescales that approach 70 y, in layers that are sufficiently thin (less than 1 μm) to avoid significant compromises in mechanical flexibility or in electrical interface fidelity. Detailed studies of temperature- and thickness-dependent electrical and physical properties reveal the key characteristics. Molecular simulations highlight essential aspects of the chemistry that governs interactions between the SiO2 and surrounding water. Examples of use with passive and active components in high-performance flexible electronic devices suggest broad utility in advanced chronic implants.

The spontaneous conversion of asparagine residues to aspartic acid or iso-aspartic acid, via deamidation, is a major pathway of protein degradation and is often seriously disruptive to biological systems. Deamidation has been shown to negatively affect both in vitro stability and in vivo biological function of diverse classes of proteins. During protein therapeutics development, deamidation liabilities that are overlooked necessitate expensive and time-consuming remediation strategies, sometimes leading to termination of the project. In this paper, we apply machine learning to a large (n = 776) liquid chromatographytandem mass spectrometry (LC-MS/MS) dataset of monoclonal antibody peptides to create computational models for the posttranslational modification asparagine deamidation, using the random decision forest method. We show that our categorical model predicts antibody deamidation with nearly 5% increased accuracy and 0.2 MCC over the best currently available models. Surprisingly, our model also paces or outperforms advanced and conventional models on an independent non-antibody dataset. In addition to deamidation probability, we are able to accurately predict deamidation rate (R 2 = 0.963 and Q2 = 0.822), a capability with no peer in current models. This method should enable significant improvement in protein candidate selection, especially in biopharmaceutical development, and can be applied with similar accuracy to enzymes, monoclonal antibodies, next-generation formats, vaccine component antigens, and gene therapy vectors such as adenoassociated virus.

No abstract

Gibberellins (GAs) are a class of phytohormones, important for plant growth, and very difficult to distinguish because of their similarity in chemical structures. Herein, we develop the first nanosensors for GAs by designing and engineering polymer-wrapped single-walled carbon nanotubes (SWNTs) with unique corona phases that selectively bind to bioactive GAs, GA3 and GA4, triggering near-infrared (NIR) fluorescence intensity changes. Using a new coupled Raman/NIR fluorimeter that enables self-referencing of nanosensor NIR fluorescence with its Raman G-band, we demonstrated detection of cellular GA in Arabidopsis, lettuce, and basil roots. The nanosensors reported increased endogenous GA levels in transgenic Arabidopsis mutants that overexpress GA and in emerging lateral roots. Our approach allows rapid spatiotemporal detection of GA across species. The reversible sensor captured the decreasing GA levels in salt-treated lettuce roots, which correlated remarkably with fresh weight changes. This work demonstrates the potential for nanosensors to solve longstanding problems in plant biotechnology.