Galvanic Replacement Synthesis of VOx@EGaIn-PEG Core-Shell Nanohybrids for Peroxidase Mimics.

The development of high-performance biosensors is a key focus in the nanozyme field, but the current limitations in biocompatibility and recyclability hinder their broader applications. Herein, we address these challenges by constructing core-shell nanohybrids with biocompatible poly(ethylene glycol) (PEG) modification using a galvanic replacement reaction between orthovanadate ions and liquid metal (LM) (VOx@EGaIn-PEG). By leveraging the excellent charge transfer properties and the low band gap of the LM surface oxide, the VOx@EGaIn-PEG heterojunction can effectively convert hydrogen peroxide into hydroxyl radicals, demonstrating excellent peroxidase-like activity and stability (Km = 490 µM, vmax = 1.206 µM/s). The unique self-healing characteristics of LM further enable the recovery and regeneration of VOx@EGaIn-PEG nanozymes, thereby significantly reducing the cost of biological detection. Building upon this, we developed a nanozyme colorimetric sensor suitable for biological systems and integrated it with a smartphone to create an efficient quantitative detection platform. This platform allows for the convenient and sensitive detection of glucose in serum samples, exhibiting a good linear relationship in the range of 10-500 µM and a detection limit of 2.35 µM. The remarkable catalytic potential of LM, combined with its biocompatibility and regenerative properties, offers valuable insights for applications in catalysis and biomedical fields.

Enzyme-Driven, Switchable Catalysis Based on Dynamic Self-Assembly of Peptides.

Covalent regulatory systems of enzymes are widely used to modulate biological enzyme activities. Inspired by the regulation of reactive-site phosphorylation in organisms, we developed peptide-based catecholase mimetics with switchable catalytic activity and high selectivity through the co-assembly of nanofibers comprising peptides and copper ions (Cu2+ ). Through careful design and modification of the peptide backbone structure based on the change in the free energy of the system, we identified the peptide with the most effective reversible catalytic activity. Kinase/phosphatase switches were used to control the reversible transition of nanofiber formation and depolymerization, as well as to modulate the active-site microenvironment. Notably, the self-assembly and disassembly processes of nanofibers were simulated using coarse-grained molecular dynamics. Furthermore, theoretical calculations confirmed the coordination of the peptide and Cu2+ , forming a zipper-like four-ligand structure at the catalytically active center of the nanofibers. Additionally, we conducted a comprehensive analysis of the catalytic mechanism. This study opens novel avenues for designing biomimetic enzymes with ordered structures and dynamic catalytic activities.

Multicomponent structural color membrane based on soft lithography array for high-sensitive Raman detection.

Inspired by ordered photonic crystals and structural color materials in nature, we successfully prepared hydroxypropyl cellulose (HPC) photonic films with ordered surface arrays by double-imprint soft lithography. Then we introduced another important material of the cellulose family, cellulose nanocrystals (CNC), which has liquid crystal nature and birefringent properties of the particles, into the system to realize the single-point shrinkage of the film array and the control of structural color. Through multi-component doping and concentration control, we further optimized the multi-scale structure of the materials, and obtained HPC/CNCs composite photonic films with excellent properties in color, stability and flexibility, whose elastic modulus and tensile properties are significantly higher than those of single-component. Further loading of SiO2@PDA enhances the color saturation and realizes the in-situ reduction of metal ions on the film surface. This plasma film can track a variety of substances with high sensitivity and long-term stability, showing potential application prospects in the field of surface-enhanced Raman scattering (SERS), which provides a potential possibility for chiral structures to be used in the field of biosensor detection and circularly polarized luminescence.

Rethreading Design of Ratiometric roGFP2 Mimetic Peptide for Hydrogen Peroxide Sensing.

Reconstruction of the miniaturized peptide to mimic the tailored functions of protein has been attractive but challenging. Herein, initialized from the crystal structure of redox-sensitive green fluorescent protein-2 (roGFP2), we propose a practical approach to construct the roGFP2 mimetic peptide by rethreading the aromatic residues adjacent to the chromophore fragment. By fine-tuning the residues of peptides, a mini tetrapeptide (Cys-Phe-Phe-His) was designed, which can act as a hydrogen peroxide sensor using its ratiometric fluorescence. The roGFP2 mimetic tetrapeptide is biocompatible and photostable and has competitive fluorescent properties with roGFP2 by the virtue of its assembly induced emissions. We expand the ratiometric tetrapeptide for sensing hydrogen peroxide in acidic chambers. The results provide a promising approach for the artificial design of miniaturized peptides with the desired function.

Enzymatic polymerization of enantiomeric L-3,4-dihydroxyphenylalanine into films with enhanced rigidity and stability.

L-3,4-dihydroxyphenylalanine is an important molecule in the adhesion of mussels, and as an oxidative precursor of natural melanin, it plays an important role in living system. Here, we investigate the effect of the molecular chirality of 3,4-dihydroxyphenylalanine on the properties of the self-assembled films by tyrosinase-induced oxidative polymerization. The kinetics and morphology of pure enantiomers are completely altered upon their co-assembly, allowing the fabrication of layer-to-layer stacked nanostructures and films with improved structural and thermal stability. The different molecular arrangements and self-assembly mechanisms of the L+D-racemic mixtures, whose oxidation products have increased binding energy, resulting in stronger intermolecular forces, which significantly increases the elastic modulus. This study provides a simple pathway for the fabrication of biomimetic polymeric materials with enhanced physicochemical properties by controlling the chirality of monomers.

Self-Guided Optimization Semi-Supervised Method for Joint Segmentation of Macular Hole and Cystoid Macular Edema in Retinal OCT Images.

Macular hole (MH) and cystoid macular edema (CME) are two common retinal pathologies that cause vision loss. Accurate segmentation of MH and CME in retinal OCT images can greatly aid ophthalmologists to evaluate the relevant diseases. However, it is still challenging as the complicated pathological features of MH and CME in retinal OCT images, such as the diversity of morphologies, low imaging contrast, and blurred boundaries. In addition, the lack of pixel-level annotation data is one of the important factors that hinders the further improvement of segmentation accuracy. Focusing on these challenges, we propose a novel self-guided optimization semi-supervised method termed Semi-SGO for joint segmentation of MH and CME in retinal OCT images. Aiming to improve the model's ability to learn the complicated pathological features of MH and CME, while alleviating the feature learning tendency problem that may be caused by the introduction of skip-connection in U-shaped segmentation architecture, we develop a novel dual decoder dual-task fully convolutional neural network (D3T-FCN). Meanwhile, based on our proposed D3T-FCN, we introduce a knowledge distillation technique to further design a novel semi-supervised segmentation method called Semi-SGO, which can leverage unlabeled data to further improve the segmentation accuracy. Comprehensive experimental results show that our proposed Semi-SGO outperforms other state-of-the-art segmentation networks. Furthermore, we also develop an automatic method for measuring the clinical indicators of MH and CME to validate the clinical significance of our proposed Semi-SGO. The code will be released on Github 1,2.

Graph Attention U-Net for Retinal Layer Surface Detection and Choroid Neovascularization Segmentation in OCT Images.

Choroidal neovascularization (CNV) is a typical symptom of age-related macular degeneration (AMD) and is one of the leading causes for blindness. Accurate segmentation of CNV and detection of retinal layers are critical for eye disease diagnosis and monitoring. In this paper, we propose a novel graph attention U-Net (GA-UNet) for retinal layer surface detection and CNV segmentation in optical coherence tomography (OCT) images. Due to retinal layer deformation caused by CNV, it is challenging for existing models to segment CNV and detect retinal layer surfaces with the correct topological order. We propose two novel modules to address the challenge. The first module is a graph attention encoder (GAE) in a U-Net model that automatically integrates topological and pathological knowledge of retinal layers into the U-Net structure to achieve effective feature embedding. The second module is a graph decorrelation module (GDM) that takes reconstructed features by the decoder of the U-Net as inputs, it then decorrelates and removes information unrelated to retinal layer for improved retinal layer surface detection. In addition, we propose a new loss function to maintain the correct topological order of retinal layers and the continuity of their boundaries. The proposed model learns graph attention maps automatically during training and performs retinal layer surface detection and CNV segmentation simultaneously with the attention maps during inference. We evaluated the proposed model on our private AMD dataset and another public dataset. Experiment results show that the proposed model outperformed the competing methods for retinal layer surface detection and CNV segmentation and achieved new state of the arts on the datasets.

Bioinspired porphyrin-peptide supramolecular assemblies and their applications.

Inspired by the hierarchical chiral assembly of porphyrin-proteins in photosynthetic systems, the hierarchical self-assembly of porphyrin-amino acids/peptides provides a novel strategy for constructing functional materials. How to artificially simulate the assembly of porphyrins, proteins, and other cofactors in the photosynthesis system to obtain persistent strong light capture, charge separation and catalytic reactions has become an important concern in the construction of biomimetic photosynthesis systems. This paper summarizes the different assembly strategies adopted in recent years, the effects of driving forces on self-assembly, and the application of porphyrin-peptides in catalysis and biomedicine, and briefly discusses the challenges and prospects for future research.

Coordination-Induced Self-Assembly of a Dipeptide into Multifunctional Chiral Nanostructures.

Short peptides could be used as chiral motifs to self-assemble into various artificial nanostructures with supramolecular or nanoscale chirality, but their applications still need to be expanded. Here, under the mediation of metal ions, the ferrocene-diphenylalanine (Fc-LFLF) peptide can self-assemble into various chiral nanostructures, including right-handed helical microflowers mediated by Cu2+, left-handed nanofibers mediated by Ag+, and right-handed nanofibers mediated by Zn2+ and Cd2+. Meanwhile, the gold nanoparticles could be mineralized and deposited on Cu2+/Fc-LFLF microflowers to form AuNPs@Cu2+/Fc-LFLF, which showed significantly improved catalytic activity. The Ag+ could be further mineralized on the peptide nanofibers to form AgNPs@Fc-LFLF, showing an excellent antibacterial effect. Overall, this study provides new insights into the chiral self-assembly of short peptides and demonstrates that the chiral peptide-metal assemblies may have broad prospects in the fields of biocatalysis and antimicrobials.

AFENet: Attention Fusion Enhancement Network for Optic Disc Segmentation of Premature Infants.

Retinopathy of prematurity and ischemic brain injury resulting in periventricular white matter damage are the main causes of visual impairment in premature infants. Accurate optic disc (OD) segmentation has important prognostic significance for the auxiliary diagnosis of the above two diseases of premature infants. Because of the complexity and non-uniform illumination and low contrast between background and the target area of the fundus images, the segmentation of OD for infants is challenging and rarely reported in the literature. In this article, to tackle these problems, we propose a novel attention fusion enhancement network (AFENet) for the accurate segmentation of OD in the fundus images of premature infants by fusing adjacent high-level semantic information and multiscale low-level detailed information from different levels based on encoder-decoder network. Specifically, we first design a dual-scale semantic enhancement (DsSE) module between the encoder and the decoder inspired by self-attention mechanism, which can enhance the semantic contextual information for the decoder by reconstructing skip connection. Then, to reduce the semantic gaps between the high-level and low-level features, a multiscale feature fusion (MsFF) module is developed to fuse multiple features of different levels at the top of encoder by using attention mechanism. Finally, the proposed AFENet was evaluated on the fundus images of preterm infants for OD segmentation, which shows that the proposed two modules are both promising. Based on the baseline (Res34UNet), using DsSE or MsFF module alone can increase Dice similarity coefficients by 1.51 and 1.70%, respectively, whereas the integration of the two modules together can increase 2.11%. Compared with other state-of-the-art segmentation methods, the proposed AFENet achieves a high segmentation performance.

Rational Design of Chiral Nanohelices from Self-Assembly of Meso-tetrakis (4-Carboxyphenyl) Porphyrin-Amino Acid Conjugates.

In this article, meso-tetrakis (4-carboxyphenyl) porphyrins modified with different amino acids were designed, synthesized, and researched. The chiral self-assembly behavior of these porphyrin-amino acid molecules can be precisely controlled by adjusting the pH, constituent amino acids, and temperature, thereby giving rise to chiral nanostructures with precisely tailored helical pitch and handedness. This research provides a certain reference for the design and preparation of chiral nanomaterials and has potential application prospects in chiral resolution and chiral catalysis.

Colorful Pigments for Hair Dyeing Based on Enzymatic Oxidation of Tyrosine Derivatives.

Melanin exists widely in nature and can afford a variety of colors from black to brown and red according to chemical structure differences and specific mixtures. Inspired by nature, this work reports that tyrosine derivatives with different protecting groups at its N- or C-terminal can be enzymatically oxidized into melanin-like pigments with a wide range of colors. The emergence of colorful pigments can be attributed to the incomplete enzymatic oxidation and polymerization caused by the chemical premodification of the tyrosine molecule. The pigments can be deposited on the surface of the hair to obtain a series of colorful and saturated hair dye effects. Moreover, after the pigments were coated on the hair, we can further deposit silver nanoparticles through in situ reduction, making these coatings have anti-inflammatory and antibacterial potential, thereby expanding their potential use for people with low immunity or those who work in hospitals. This work proposes a green and effective way to synthesize colorful pigments with great potential applications in the hair dying and cosmetic industries.

Self-Assembled Bio-Organometallic Nanocatalysts for Highly Enantioselective Direct Aldol Reactions.

Supramolecular nanocatalysts were designed for asymmetric reactions through the self-assembly process of a bio-organometallic molecule, ferrocene-l-prolinamide (Fc-CO-NH-P). Fc-CO-NH-P could self-assemble into versatile nanostructures in water, including nanospheres, nanosheets, nanoflowers, and pieces. In particular, the self-assembled nanoflowers exhibited a superior specific surface area, high stability, and delicate three-dimensional (3D) chiral catalytic active sites. The nanoflowers could serve as heterogeneous catalysts with an excellent catalytic performance toward direct aldol reactions in aqueous solution, achieving both high yield (>99%) and stereoselectivity (anti/syn = 97:3, ee% >99%). This study proposed a significant strategy to fabricate supramolecular chiral catalysts, serving as a favorable template for designing new asymmetric catalysts.