Identification of Molecular Profile of Cell Membrane via Magnetic Plasmonic Nanoprobe.

Cell membranes are primarily composed of lipids, membrane proteins, and carbohydrates, and the related studies of membrane components and structures at different stages of disease development, especially membrane proteins, are of great significance. Here, we investigate the chemical signature profiles of cell membranes as biomarkers for cancer cells via label-free surface-enhanced Raman scattering (SERS). A magnetic plasmonic nanoprobe was proposed by decorating magnetic beads with silver nanoparticles, allowing self-driven cell membrane-targeted accumulation within 5 min. SERS profiles of three types of breast cells were achieved under the plasmon enhancement effect of these nanoprobes. Membrane fingerprint spectra from breast cell lines were further classified with the convolutional neural network model, which perfectly distinguished between two breast cancer subtypes. We further tested various clinical samples using this method and obtained fingerprint spectra from primary cells and frozen slices. This study presents a practical, user-friendly approach for label-free and in situ analysis of cell membranes, which can work for early tumor screening and treatment assessment for tumors reliant on the Molecular profiles of cell membranes. Additionally, this method can be applied universally to explore cell membrane components of other cells, thus assisting Human Cell Atlas.

Nanozyme-Based Microfluidic Chip System for pH-Regulated Pretreatment and Sensitive Sensing.

Nanozymes, possessing nanomaterial properties and catalytic activities, offer great opportunities to design sensitive analytical detection systems. However, the low interference resistance of nanozymes poses a significant limitation on the precise detection of target substances. Herein, a nanozyme-based microfluidic chip system for pH-regulated pretreatment and sensitive sensing of cysteine (Cys) is reported. The copper metal-organic framework (Cu MOF) exhibits good cysteine oxidase-like activity at pH 7.0, while demonstrating excellent laccase-like activity at pH 8.0. Taking advantage of the pH-regulated enzyme-like activity, the integrated microfluidic device involving the immobilization of Cu MOF eliminates the interference of dopamine (DA) and accurately detects the target Cys. Compared with the untreated reaction system, the developed nanozyme system shows a significantly improved accuracy in detecting Cys, with an R2 value of 0.9914. This work provides an efficient method to enhance the interference resistance of nanozymes and broadens the application in sample pretreatment.

In Situ Defect Engineering of Fe-MIL for Self-Enhanced Peroxidase-Like Activity.

Defect engineering is an effective strategy to enhance the enzyme-like activity of nanozymes. However, previous efforts have primarily focused on introducing defects via de novo synthesis and post-synthetic treatment, overlooking the dynamic evolution of defects during the catalytic process involving highly reactive oxygen species. Herein, a defect-engineered metal-organic framework (MOF) nanozyme with mixed linkers is reported. Over twofold peroxidase (POD)-like activity enhancement compared with unmodified nanozyme highlights the critical role of in situ defect formation in enhancing the catalytic performance of nanozyme. Experimental results reveal that highly active hydroxyl radical (•OH) generated in the catalytic process etches the 2,5-dihydroxyterephthalic acid ligands, contributing to electronic structure modulation of metal sites and enlarged pore sizes in the framework. The self-enhanced POD-like activity induced by in situ defect engineering promotes the generation of •OH, holding promise in colorimetric sensing for detecting dichlorvos. Utilizing smartphone photography for RGB value extraction, the resultant sensing platform achieves the detection for dichlorvos ranging from 5 to 300 ng mL-1 with a low detection limit of 2.06 ng mL-1. This pioneering work in creating in situ defects in MOFs to improve catalytic activity offers a novel perspective on traditional defect engineering.

An atomic force microscopy and total internal reflection fluorescence microscopy correlated system (AFM-TIRF) for fluorescence imaging and spectroscopy of a single particle.

Combining atomic force microscopy (AFM) with other optical microscopic techniques is pivotal in nanoscale investigations, particularly leveraging the surface-sensitive properties of total internal reflection fluorescence microscopy (TIRF). A novel design that integrates AFM with a multi-wavelength TIRF is displayed, providing simultaneous fluorescence imaging and spectral acquisition capabilities. We elaborate on the considerations in the instrument design process and demonstrate the performance and potential applications of the instrument through fluorescence imaging and spectroscopy testing of individual nanoparticles. This AFM and TIRF correlated system (AFM-TIRF) emerges as a promising option for single-molecule fluorescence studies, enabling simultaneous manipulation and detection of fluorescence from individual molecules.

Grain-Boundary-Rich Ceria Metallene Nanozyme with Abundant Metal Site Pairs Boosts Phosphatase-like Activity.

Natural phosphatases featuring paired metal sites inspire various advanced nanozymes with phosphatase-like activity as alternatives in practical applications. Numerous efforts to create point defects show limited metal site pairs, further resulting in insufficient activity. However, it remains a grand challenge to accurately engineer abundant metal site pairs in nanozymes. Herein, we report a grain-boundary-rich ceria metallene nanozyme (GB-CeO2) with phosphatase-like activity. Grain boundaries acting as the line or interfacial defects can effectively increase the content of Ce4+/Ce3+ site pairs to 72.28%, achieving a 49.28-fold enhancement in activity. Furthermore, abundant grain boundaries optimize the band structure to assist the photoelectron transfer under irradiation, which further increases the content of metal site pairs to 88.96% and finally realizes a 114.39-fold enhanced activity over that of CeO2 without irradiation. Given the different inhibition effects of pesticides on catalysts with and without irradiation, GB-CeO2 was successfully applied to recognize mixed toxic pesticides.

In-droplet multiplex immunoassays for hypoxia-induced single-cell cytokines.

Cytokine expression is an important biomarker in understanding hypoxia microenvironments in tumor growth and metastasis. In-droplet-based immunoassays performed above the target cell membrane were employed to track the cytokines of single cells with the aid of three types of immuno-nanoprobes (one capture nanoprobe and two reporter nanoprobes). Single cells and nanoprobes were co-packaged in water-in-oil microdroplets (about 100 µm in diameter) using a cross-shaped microfluidic chip. In each droplet, capture nanoprobes would be first fixed to the cell surface by linking to membrane proteins that have been streptavidinized. Then, the capture nanoprobes can collect cell-secreted cytokines (VEGF and IL-8) by the antibodies, followed by two reporter nanoprobes that emit distinguishable fluorescence. Fluorescence imaging was utilized to record the signal outputs of two reporter probes, which reflect cytokine expressions secreted by a single tumor cell. The cytokine levels at different degrees of hypoxia induction were assessed. Multiple chemometric methods were adopted to distinguish differences in the secretion of two cytokines and the results demonstrated a positive correlation. This study developed an in-droplet, dual-target, simultaneous biosensing strategy for a single cell, which is helpful for understanding the impacts of hypoxia microenvironments on cell cytokines that are vital for assessing early cancer diagnosis and prognosis.

Artificial-Cofactor-Mediated Hydrogen and Electron Transfer Endows AuFe/Polydopamine Superparticles with Enhanced Glucose Oxidase-Like Activity.

Various applications related to glucose catalysis have led to the development of functional nanozymes with glucose oxidase (GOX)-like activity. However, the unsatisfactory catalytic activity of nanozymes is a major challenge for their practical applications due to their inefficient hydrogen and electron transfer. Herein, we present the synthesis of AuFe/polydopamine (PDA) superparticles that exhibit photothermal-enhanced GOX-like activity. Experimental investigations and theoretical calculations reveal that the glucose oxidation process catalyzed by AuFe/PDA follows an artificial-cofactor-mediated hydrogen atom transfer mechanism, which facilitates the generation of carbon-centered radical intermediates. Rather than depending on charged Au surfaces for thermodynamically unstable hydride transfer, Fe(III)-coordinated PDA with abundant amino and phenolic hydroxyl groups serves as cofactor mimics, facilitating both hydrogen atom and electron transfer in the catalytic process. Finally, leveraging the photothermal-enhanced GOX-like and catalase-like activities of AuFe/PDA, we establish a highly sensitive and accurate point-of-care testing blood glucose determination with exceptional anti-jamming capabilities.

Deep learning-based pathological prediction of lymph node metastasis for patient with renal cell carcinoma from primary whole slide images.

BACKGROUND: Metastasis renal cell carcinoma (RCC) patients have extremely high mortality rate. A predictive model for RCC micrometastasis based on pathomics could be beneficial for clinicians to make treatment decisions. METHODS: A total of 895 formalin-fixed and paraffin-embedded whole slide images (WSIs) derived from three cohorts, including Shanghai General Hospital (SGH), Clinical Proteomic Tumor Analysis Consortium (CPTAC) and Cancer Genome Atlas (TCGA) cohorts, and another 588 frozen section WSIs from TCGA dataset were involved in the study. The deep learning-based strategy for predicting lymphatic metastasis was developed based on WSIs through clustering-constrained-attention multiple-instance learning method and verified among the three cohorts. The performance of the model was further verified in frozen-pathological sections. In addition, the model was also tested the prognosis prediction of patients with RCC in multi-source patient cohorts. RESULTS: The AUC of the lymphatic metastasis prediction performance was 0.836, 0.865 and 0.812 in TCGA, SGH and CPTAC cohorts, respectively. The performance on frozen section WSIs was with the AUC of 0.801. Patients with high deep learning-based prediction of lymph node metastasis values showed worse prognosis. CONCLUSIONS: In this study, we developed and verified a deep learning-based strategy for predicting lymphatic metastasis from primary RCC WSIs, which could be applied in frozen-pathological sections and act as a prognostic factor for RCC to distinguished patients with worse survival outcomes.

Nanozyme Metabolism Controls Air Pollution over an Atomic Potassium Cyano Site.

Increasing threats of air pollution prompt the design of air purification systems. As a promising initiative defense strategy, nanocatalysts are integrated to catalyze the detoxification of specific pollutants. However, it remains a grand challenge to tailor versatile nanocatalysts to cope with diverse pollutants in practice. Here, we report a nanozyme metabolism system to realize broad-spectrum protection from air pollution. Atomic K-modified carbon nitride featuring flavin oxidase-like and peroxidase-like activities was synthesized to initiate nanozyme metabolism. In situ experiments and theoretical investigations collectively show that K sites optimize the geometric and electronic structure of cyano sites for both enzyme-like activities. As a proof of concept, the nanozyme metabolism was applied to the mask against volatile organic compounds, persistent organic pollutants, reactive oxygen species, bacteria, and so on. Our finding provides a thought to tackle global air pollution and deepens the understanding of nanozyme metabolism.

Bifunctional enzyme-mimicking metal-organic frameworks for sensitive acetylcholine analysis.

The development of nanomaterials with multi-enzyme-like activity is crucial for addressing challenges in multi-enzyme-based biosensing systems, including cross-talk between different enzymes and the complexities and costs associated with detection. In this study, Pt nanoparticles (Pt NPs) were successfully supported on a Zr-based metal-organic framework (MOF-808) to create a composite catalyst named MOF-808/Pt NPs. This composite catalyst effectively mimics the functions of acetylcholinesterase (AChE) and peroxidase (POD). Leveraging this capability, we replaced AChE and POD with MOF-808/Pt NPs and constructed a biosensor for sensitive detection of acetylcholine (ACh). The MOF-808/Pt NPs catalyze the hydrolysis of ACh, resulting in the production of acetic acid. The subsequent reduction in pH value further enhances the POD-like activity of the MOFs, enabling signal amplification through the oxidation of a colorimetric substrate. This biosensor capitalizes on pH variations during the reaction to modulate the different enzyme-like activities of the MOFs, simplifying the detection process and eliminating cross-talk between different enzymes. The developed biosensor holds great promise for clinical diagnostic analysis and offers significant application value in the field.