Congcong Zhang

Neural stem cell (NSC) transplantation holds great potential for Alzheimer's disease (AD) therapy; however, its efficacy is severely compromised by the oxidative microenvironment, which impairs mitochondrial function and promotes aberrant glial differentiation. To overcome this barrier, lysosome‐responsive EGCG–lysine nanoparticles (EL NPs) were developed. Upon endo‐lysosomal disassembly, EL NPs release active components that scavenge reactive oxygen species (ROS) and restore mitochondrial bioenergetics via AMPK signaling. This metabolic rescue activates a Ca ^{2 +} ‐dependent MAPK pathway, driving commitment to the GABAergic neuronal lineage. Under oxidative stress, EL NPs enhanced neuronal differentiation efficiency by 2.5–3.0‐fold compared with spontaneous differentiation while suppressing astroglial activation. In an AD mouse model, transplantation of EL NP‐loaded NSCs promoted in situ neurogenesis, attenuated neuroinflammation, and restored cognitive performance to ∼89%–90% of wild‐type levels. These results present a translatable strategy to augment NSC‐based repair by modulating intracellular responses to oxidative stress and promoting neuronal differentiation.

Chronic skin wounds remain difficult to treat because infection, oxidative stress, vascular insufficiency, matrix dysfunction, and persistent inflammation reinforce one another and trap repair in a nonhealing state. Tannic acid and bioactive metal ions are increasingly combined to address this problem, yet the literature is often fragmented between TA‐centered formulations, free‐ion strategies, and multifunctional TA–metal assemblies. This review examines these three therapeutic logics in parallel and asks not only what each platform can do but also what wound bottleneck it is actually designed to solve. The discussion first clarifies what TA alone has contributed before TA–metal systems emerged, then evaluates the biological power and formulation risk of free metal ions, and finally analyzes how coordination chemistry enables retention, controlled ion presentation, redox balance, adhesion, and microenvironmental modulation in TA–metal biomaterials. Representative studies are re‐read through wound problems, material format, evidence depth, and translational meaning rather than as a simple catalog of positive outcomes. Particular attention is given to immune microenvironment remodeling, macrophage‐centered claims, stage‐adaptive design, and the distinction between established evidence and attractive but still inferential mechanistic narratives. By integrating material design logic with biological interpretation and translational criteria, this review provides a practical framework for selecting, evaluating, and advancing TA–metal biomaterials for skin repair.

MicroRNAs, as pivotal post-transcriptional regulators of gene expression, are closely associated with major diseases. Precise detection of their expression abnormalities is of paramount importance for disease prevention and control. Although graphene field-effect transistors (GFETs) exhibit significant advantages in miRNA sensing, liquid-gate structures suffer from suboptimal stability, while back-gate structures are constrained by limited sensitivity, making it challenging to achieve simultaneous optimization of both. To address this issue, our study has innovatively constructed a biosensing platform that synergizes field-effect regulation with DNA walker-based signal amplification. This platform achieves directional immobilization of DNA walkers on GFETs via Au-S bonds. It utilizes target miRNA-141 to trigger cascade strand displacement reactions, and combines field-effect modulation with a DNA walker-driven signal cascade amplification mechanism. Additionally, it leverages a T7 exonuclease-assisted target recycling regeneration mechanism to realize a three-stage coordinated process of "target recognition-chain displacement-signal amplification". This platform achieves high sensitivity with an impressively low detection limit of 12.6 fM in the range of 0.1 pM to 1 μM for miRNA-141 detection, with signal output unrestricted by Debye length limitations. This design successfully resolves the inherent conflict between sensitivity and stability in GFETs, providing an innovative solution that combines high reliability with ultrasensitivity for clinical nucleic acid biomarker detection.

Central nervous system (CNS) injury can cause devastating neurological dysfunction in patients, permanently impairing their ability to take care of themselves and reducing their quality of life. At present, neural tissue engineering is the most promising way to treat this disease. However, there are still many challenges and obstacles in the process of correctly structuring tissue engineering. The successful development of tissue engineering relies on three key components: biological scaffold materials, seed cells, and various growth factors. In summary, this review provides a systematic analysis of scaffold materials differentiation strategies for inducing diverse stem cells into neuro‐like cells. The synthesized findings not only accelerate regenerative medicine approaches but also provide the critical solutions for CNS injury treatment and advance therapeutic development, offering important references for future research and clinical translation.

In recent years, tissue engineering has emerged as a cutting‐edge approach for the treatment of spinal cord injury (SCI) owing to its remarkable capabilities. It can create living tissues with robust vitality, achieve maximal tissue repair with minimal cell usage, and facilitate seamless reconstruction with unmatched plasticity, all while addressing immune rejection issues. Among these advancements, one‐dimensional (1D) materials have garnered significant attention. Their morphology closely resembles the extracellular matrix environment, thereby fostering the elongation of dendrites and axons on neurons and greatly enhancing the prospects for SCI repair. With a keen focus on the latest advancements in the application of 1D nanomaterials in nerve tissue engineering for spinal nerve repair, this review delves into several key aspects. Firstly, it explores the “bottom‐up” approach to synthesizing 1D nanomaterials. Secondly, it examines the mechanisms by which these nanomaterials influence neural tissue engineering. Thirdly, it presents various cutting‐edge strategies aimed at optimizing the morphology and performance of 1D materials, thereby enhancing the efficiency of nerve tissue injury repair. Lastly, it discusses the current challenges and future prospects facing this fascinating field. We aspire that this comprehensive review will provide a profound understanding of the development of 1D materials in neural tissue engineering and inspire a wider audience with its potential.

With excellent feature representation capabilities, deep autoencoder networks have attracted attention in process monitoring. However, it cannot take into account the quality indicators to identify whether the faults are quality-relevant. To address this issue, an orthogonal feature separation autoencoder (OFSAE) method is developed for quality-relevant fault monitoring. The proposed OFSAE mainly consists of the quality-relevant encoder network, quality-irrelevant encoder network, decoder network, and regression network. Through parallel learning and orthogonal projection for process variables, quality-relevant and quality-irrelevant variations can be isolated while maintaining good prediction performance. Finally, in comparison with conventional monitoring methods, the superiority of OFSAE is validated by the Tennessee Eastman process.

Automatic guidance soft target vehicle is widely used in intelligent vehicle active safety test., and trajectory tracking is its main function. By analyzing the high speed working condition and path tracking of soft guided vehicle., the objective function was established., the tracking error model and model constraint conditions were designed., and the trajectory tracking controller based on MPC was established. Finally, the Carsim-Simulink co-simulation platform was constructed. By importing vehicle parameters into Carsim software., and using s-function function in matlab software to create model predictive control code. The simulation results show that the trajectory tracking controller has good tracking effect.