An In Silico Model for Predicting the Efficacy of Edge-to-Edge Repair for Mitral Regurgitation.

In recent years, transcatheter edge-to-edge repair (TEER) has been widely adopted as an effective treatment for mitral regurgitation (MR). The aim of this study is to develop a personalized in silico model to predict the effect of edge-to-edge repair in advance to the procedure for each individual patient. For this purpose, we propose a combination of a valve deformation model for computing the mitral valve (MV) orifice area (MVOA) and a lumped parameter model for the hemodynamics, specifically mitral regurgitation volume (RVol). Although we cannot obtain detailed information on the three-dimensional flow field near the mitral valve, we can rapidly simulate the important medical parameters for the clinical decision support. In the present method, we construct the patient-specific pre-operative models by using the parameter optimization and then simulate the postoperative state by applying the additional clipping condition. The computed preclip MVOAs show good agreement with the clinical measurements, and the correlation coefficient takes 0.998. In addition, the MR grade in terms of RVol also has good correlation with the grade by ground truth MVOA. Finally, we try to investigate the applicability for the predicting the postclip state. The simulated valve shapes clearly show the well-known double orifice and the improvement of the MVOA, compared with the preclip state. Similarly, we confirmed the improved reverse flow and MR grade in terms of RVol. A total computational time is approximately 8 h by using general-purpose PC. These results obviously indicate that the present in silico model has good capability for the assessment of edge-to-edge repair.

Self-assembled GA-Repeated Peptides as a Biomolecular Scaffold for Biosensing with MoS2 Electrochemical Transistors.

Biosensors with two-dimensional materials have gained wide interest due to their high sensitivity. Among them, single-layer MoS2 has become a new class of biosensing platform owing to its semiconducting property. Immobilization of bioprobes directly onto the MoS2 surface with chemical bonding or random physisorption has been widely studied. However, these approaches potentially cause a reduction of conductivity and sensitivity of the biosensor. In this work, we designed peptides that spontaneously align into monomolecular-thick nanostructures on electrochemical MoS2 transistors in a non-covalent fashion and act as a biomolecular scaffold for efficient biosensing. These peptides consist of repeated domains of glycine and alanine in the sequence and form self-assembled structures with sixfold symmetry templated by the lattice of MoS2. We investigated electronic interactions of self-assembled peptides with MoS2 by designing their amino acid sequence with charged amino acids at both ends. Charged amino acids in the sequence showed a correlation with the electrical properties of single-layer MoS2, where negatively charged peptides caused a shift of threshold voltage in MoS2 transistors and neutral and positively charged peptides had no significant effect on the threshold voltage. The transconductance of transistors had no decrease due to the self-assembled peptides, indicating that aligned peptides can act as a biomolecular scaffold without degrading the intrinsic electronic properties for biosensing. We also investigated the impact of peptides on the photoluminescence (PL) of single-layer MoS2 and found that the PL intensity changed sensitively depending on the amino acid sequence of peptides. Finally, we demonstrated a femtomolar-level sensitivity of biosensing using biotinylated peptides to detect streptavidin.

Designable peptides on graphene field-effect transistors for selective detection of odor molecules.

Gas sensing based on graphene field-effect transistors (GFETs) has gained broad interest due to their high sensitivity. Further progress in gas sensing with GFETs requires to detection of various odor molecules for applications in the environmental monitoring, healthcare, food, and cosmetic industries. To develop the ubiquitous odor-sensing system, establishing an artificial sense of smell with electronic devices by mimicking olfactory receptors will be key. Although the application of olfactory receptors to GFETs is straightforward for odor sensing, synthetic molecules with a similar function to olfactory receptors would be desirable to realize the robust performance of sensing. In this work, we designed three new peptides consisting of two domains: a bio-probe to the target molecules and a molecular scaffold. These peptides were rationally designed based on a motif sequence in olfactory receptors and self-assembled into a molecular thin film on GFETs. Limonene, methyl salicylate, and menthol were employed as representative odor molecules of plant flavors to demonstrate the biosensing of odor molecules. The conductivity change of GFETs against the binding to odor molecules with various concentrations and the dynamic response revealed a distinct signature of three different peptides against individual species of the target molecules. The kinetic response of each peptide exhibited characteristic time constants in the adsorption and desorption process, also supported by the principal component analysis. Our demonstration of the graphene odor sensors with the designed peptides opens a way to establish future peptide-array sensors with multi-sequence of peptide, realizing an odor sensing system with higher selectivity.

De novo designed peptides form a highly catalytic ordered nanoarchitecture on a graphite surface.

Here we demonstrate that short peptides, de novo designed from first principles, self-assemble on the surface of graphite to produce a highly robust and catalytic nanoarchitecture, which promotes peroxidation reactions with activities that rival those of natural enzymes in both single and multi-substrate reactions. These designable peptides recapitulate the symmetry of the underlying graphite surface and act as molecular scaffolds to immobilize hemin molecules on the electrode in a hierarchical self-assembly manner. The highly ordered and uniform hybrid graphite-peptide-hemin nanoarchitecture shows the highest faradaic efficiency of any hybrid electrode reported. Given the explosive growth of the types of chemical reactions promoted by self-assembled peptide materials, this new approach to creating complex electrocatalytic assemblies will yield highly efficient and practically applicable electrocatalysts.

Cosolvents Restrain Self-Assembly of a Fibroin-Like Peptide on Graphite.

Controllable self-assembly of peptides on solid surfaces has been investigated for establishing functional bio/solid interfaces. In this work, we study the influence of organic solvents on the self-assembly of a fibroin-like peptide on a graphite surface. The peptide has been designed by mimicking fibroin proteins to have strong hydrogen bonds among peptides enabling their self-assembly. We have employed cosolvents of water and organic solvents with a wide range of dielectric constants to control peptide self-assembly on the surface. Atomic force microscopy has revealed that the peptides self-assemble into highly ordered monolayer-thick linear structures on graphite after incubation in pure water, where the coverage of peptides on the surface is more than 85%. When methanol is mixed, the peptide coverage becomes zero at a threshold concentration of 30% methanol on graphite and 25% methanol on MoS2. The threshold concentration in ethanol, isopropanol, dimethyl sulfoxide, and acetone varies depending on the dielectric constant with restraining self-assembly of the peptides, and particularly low dielectric-constant protic solvents prevent the peptide self-assembly significantly. The observed phenomena are explained by competitive surface adsorption of the organic solvents and peptides and the solvation effect of the peptide assembly.