Laser-Shock-Driven In Situ Evolution of Atomic Defect and Piezoelectricity in Graphitic Carbon Nitride for the Ionization in Mass Spectrometry

Piezoelectric Amyloid Fibril for Energy Harvesting, Reactive Oxygen Species Generation, and Wireless Cell Therapy

Biomolecular piezoelectric materials are envisioned for advanced biomedical applications for their robust piezoelectricity, biocompatibility, and flexibility. Here, we report the piezoelectric property of amyloid fibrils derived from three distinct proteins: lysozyme, insulin, and amyloid-β. We found that piezoelectric properties are dependent on the extent of the β-sheet structure and the extent of fibril anisotropy. We have observed the piezoelectric constant value in the range of 24-42 pm/V for fibrils made of lysozyme/insulin/amyloid-β, and for the sheet/bundle-like structure of lysozyme aggregates, the value becomes 62 pm/V. These piezoelectric constant values are 4-10 times higher than the native lysozyme/insulin/amyloid proteins. Computational studies show that extension of the β-sheet structure produces an asymmetric arrangement of charges (in creating dipole moment) and mechanical stress induces an aligned orientation of these dipoles that results in a piezoelectric effect. It is shown that these piezoelectric fibrils can harvest mechanical as well as ultrasound-based energy to produce a voltage of up to 1 V and a current of up to 13 nA. These fibrils are employed for reactive oxygen species (ROS) generation under ultrasound exposure and utilized for ultrasonic degradation of organic pollutants or killing of cancer cells via intracellular ROS generation under ultrasound exposure. Our findings demonstrate that the piezoelectric property of protein fibrils has potential for wireless therapeutic applications and may have physiological roles that are yet to be explored.

Inhibiting Protein Aggregation Using Cellulose Nanocrystal in MALDI-TOF MS Analysis: Improving the Sensitivity and Repeatability of Intact Protein in Pueraria

Protein aggregation can induce low sensitivity and poor repeatability of matrix-assisted laser desorption/ionization time-of-fight mass spectrometry (MALDI-TOF MS) analysis for intact protein. Herein, we introduced a strategy to decrease protein aggregation in the sample solution by using cellulose nanocrystal (CNC). The results indicated that protein granule size was effectively reduced by adding CNC to the sample solution. Through MALDI-TOF MS analysis, the signal-to-noise ratio of [M + H]+ peak increased 2-fold, and the detection of limit was <10 μg/mL for intact protein. The CNC also contributed to excellent point-to-point repeatability for MALDI-TOF MS analysis with the coefficient of variation (CV) of 10.0% with CNC vs 48.9% without CNC in Hb solution. Also, the repeatability of Pueraria protein ion signals was improved by using CNC, and the CV with and without CNC was 16.1% and 39.6%, respectively. Moreover, protein ion intensity exhibited great linear relationship (y = 53.04x - 3.474, R2 = 0.9936) with the concentrations (ranging from 0.1 to 10 mg/mL) when using CNC. Further investigation revealed that m/z 19,000 and m/z 21,000 peaks of Pueraria could be used for the adulteration analysis and post-translational modification research, demonstrating our method has the potential for broad applications.

Multifunctional carbon nitride nanoarchitectures for catalysis

Catalysis is at the heart of modern-day chemical and pharmaceutical industries, and there is an urgent demand to develop metal-free, high surface area, and efficient catalysts in a scalable, reproducible and economic manner. Amongst the ever-expanding two-dimensional materials family, carbon nitride (CN) has emerged as the most researched material for catalytic applications due to its unique molecular structure with tunable visible range band gap, surface defects, basic sites, and nitrogen functionalities. These properties also endow it with anchoring capability with a large number of catalytically active sites and provide opportunities for doping, hybridization, sensitization, etc. To make considerable progress in the use of CN as a highly effective catalyst for various applications, it is critical to have an in-depth understanding of its synthesis, structure and surface sites. The present review provides an overview of the recent advances in synthetic approaches of CN, its physicochemical properties, and band gap engineering, with a focus on its exclusive usage in a variety of catalytic reactions, including hydrogen evolution reactions, overall water splitting, water oxidation, CO2 reduction, nitrogen reduction reactions, pollutant degradation, and organocatalysis. While the structural design and band gap engineering of catalysts are elaborated, the surface chemistry is dealt with in detail to demonstrate efficient catalytic performances. Burning challenges in catalytic design and future outlook are elucidated.

Designed Concave Octahedron Heterostructures Decode Distinct Metabolic Patterns of Epithelial Ovarian Tumors

Epithelial ovarian cancer (EOC) is a polyfactorial process associated with alterations in metabolic pathways. A high-performance screening tool for EOC is in high demand to improve prognostic outcome but is still missing. Here, a concave octahedron Mn₂ O₃ /(Co,Mn)(Co,Mn)₂ O₄ (MO/CMO) composite with a heterojunction, rough surface, hollow interior, and sharp corners is developed to record metabolic patterns of ovarian tumors by laser desorption/ionization mass spectrometry (LDI-MS). The MO/CMO composites with multiple physical effects induce enhanced light absorption, preferred charge transfer, increased photothermal conversion, and selective trapping of small molecules. The MO/CMO shows ≈2-5-fold signal enhancement compared to mono- or dual-enhancement counterparts, and ≈10-48-fold compared to the commercialized products. Subsequently, serum metabolic fingerprints of ovarian tumors are revealed by MO/CMO-assisted LDI-MS, achieving high reproducibility of direct serum detection without treatment. Furthermore, machine learning of the metabolic fingerprints distinguishes malignant ovarian tumors from benign controls with the area under the curve value of 0.987. Finally, seven metabolites associated with the progression of ovarian tumors are screened as potential biomarkers. The approach guides the future depiction of the state-of-the-art matrix for intensive MS detection and accelerates the growth of nanomaterials-based platforms toward precision diagnosis scenarios.