Self-Assembly of Luminescent Gold Nanoparticles with Sensitive pH-Stimulated Structure Transformation and Emission Response toward Lysosome Escape and Intracellular Imaging.

Ultrasmall luminescent gold nanoparticles (AuNPs, d < 3.0 nm) with distinct optical properties and good biocompatibilities hold enormous promise for advanced disease theranostics. However, ultrasmall AuNPs generally show low cellular interaction and are hardly ever transported into the specific subcellular compartments, hampering their further biomedical use in cellular delivery and intracellular tracking. Using a conventional cationic polymer chitosan (CS) with the isoelectric point of 6.5 as a template, ultrasmall luminescent AuNPs can be easily formed into self-assembled nanostructures (AuNPs@CS) with significantly enhanced cellular interaction capability and sensitive emission response toward subcellular location. The self-assembled AuNPs@CS become compacted nanostructures (∼23.5 nm) with high luminescence at low pH values (e.g., pH < 6.5) but reversibly transform to swelled structures with weak luminescence at high pH values (e.g., pH 7.4). The self-assembly of AuNPs not only improves the emission properties but also alters the surface charge and assembly size, resulting in both enhanced cellular internalization and effective endosomal escape capability. More importantly, the sensitive luminescence response of the AuNPs@CS from the acidic organelle lysosome to the neutral cytoplasm demonstrates the great potential in optical intracellular tracking.

Intelligent perceptual textiles based on ionic-conductive and strong silk fibers.

Endowing textiles with perceptual function, similar to human skin, is crucial for the development of next-generation smart wearables. To date, the creation of perceptual textiles capable of sensing potential dangers and accurately pinpointing finger touch remains elusive. In this study, we present the design and fabrication of intelligent perceptual textiles capable of electrically responding to external dangers and precisely detecting human touch, based on conductive silk fibroin-based ionic hydrogel (SIH) fibers. These fibers possess excellent fracture strength (55 MPa), extensibility (530%), stable and good conductivity (0.45 S·m-1) due to oriented structures and ionic incorporation. We fabricated SIH fiber-based protective textiles that can respond to fire, water, and sharp objects, protecting robots from potential injuries. Additionally, we designed perceptual textiles that can specifically pinpoint finger touch, serving as convenient human-machine interfaces. Our work sheds new light on the design of next-generation smart wearables and the reshaping of human-machine interfaces.

Carbon-Based Flexible Devices for Comprehensive Health Monitoring.

Traditional public health systems suffer from incomprehensive, delayed, and inefficient medical services. Convenient and comprehensive health monitoring has been highly sought after recently. Flexible and wearable devices are attracting wide attention due to their potential applications in wearable human health monitoring and care systems. Using carbon materials with overall superiorities can facilitate the development of wearable and flexible devices with various functions and excellent performance, which can comprehensively and real-time monitor human health status and prevent diseases. Herein, the latest advances in the rational design and controlled fabrication of carbon materials for applications in health-related flexible and wearable electronics are reviewed. The fabrication strategies, working mechanism, performance, and applications in health monitoring of carbon-based flexible devices, including electromechanical sensors, temperature/humidity sensors, chemical sensors, and flexible conductive wires/electrodes, are reviewed. Furthermore, integrating multiple carbon-based devices into multifunctional wearable systems is discussed. Finally, the existing challenges and future opportunities in this field are also proposed.

A synergistic interfacial and topological strategy for reinforcing aramid nanofiber films.

While nanomaterials possess impressive mechanical properties at the microscale level, their macroscopic assemblies usually exhibit inferior properties due to ineffective stress transfer among individual nanomaterials. This issue is addressed in this work by achieving strong interfacial interactions between aramid nanofibers and graphene oxide nanosheets through a neutralization reaction in a dipolar solvent and regulating the topological properties using polymer micelles to form a compact structure, leading to the formation of a super-strong and super-tough nanofiber film. The film was prepared through a sol-gel-film transition process and possesses a nacre-like microstructure that deflects microcracks and prevents them from propagating straight through the film. Remarkably, it demonstrates a tensile strength of 599.0 MPa and a toughness of 37.7 MJ m-3, which are 491.0% and 1094.5% that of a pristine aramid nanofiber film, respectively. In addition, it exhibits excellent tolerance to extreme temperatures (-196 to 300 °C) and fatigue resistance to folding 10 000 times. Overall, this study presents a synergistic interfacial and topological enhancement strategy for constructing nanomaterial-based composites with inherited properties from the nanoscale building blocks to the macroscale structural material.

Monitoring blood pressure and cardiac function without positioning via a deep learning-assisted strain sensor array.

Continuous and reliable monitoring of blood pressure and cardiac function is of great importance for diagnosing and preventing cardiovascular diseases. However, existing cardiovascular monitoring approaches are bulky and costly, limiting their wide applications for early diagnosis. Here, we developed an intelligent blood pressure and cardiac function monitoring system based on a conformal and flexible strain sensor array and deep learning neural networks. The sensor has a variety of advantages, including high sensitivity, high linearity, fast response and recovery, and high isotropy. Experiments and simulation synergistically verified that the sensor array can acquire high-precise and feature-rich pulse waves from the wrist without precise positioning. By combining high-quality pulse waves with a well-trained deep learning model, we can monitor blood pressure and cardiac function parameters. As a proof of concept, we further constructed an intelligent wearable system for real-time and long-term monitoring of blood pressure and cardiac function, which may contribute to personalized health management, precise and early diagnosis, and remote treatment.