Hepatocellular carcinoma (HCC) was characterized as being hypervascular. In the present study, we generated a single-cell spatial transcriptomic landscape of the vasculogenic etiology of HCC and illustrated overexpressed Golgi phosphoprotein 73 (GP73) HCC cells exerting cellular communication with vascular endothelial cells with high pro-angiogenesis potential via multiple receptor–ligand interactions in the process of tumor vascular development. Specifically, we uncovered an interactive GP73-mediated regulatory network coordinated with c-Myc, lactate, Janus kinase 2/signal transducer and activator of transcription 3 (JAK2/STAT3) pathway, and endoplasmic reticulum stress (ERS) signals in HCC cells and elucidated its pro-angiogenic roles in vitro and in vivo. Mechanistically, we found that GP73, the pivotal hub gene, was activated by histone lactylation and c-Myc, which stimulated the phosphorylation of downstream STAT3 by directly binding STAT3 and simultaneously enhancing glucose-regulated protein 78 (GRP78)-induced ERS. STAT3 potentiates GP73-mediated pro-angiogenic functions. Clinically, serum GP73 levels were positively correlated with HCC response to anti-angiogenic regimens and were essential for a prognostic nomogram showing good predictive performance for determining 6-month and 1-year survival in patients with HCC treated with anti-angiogenic therapy. Taken together, the aforementioned data characterized the pro-angiogenic roles and mechanisms of a GP73-mediated network and proved that GP73 is a crucial tumor angiogenesis niche gene with favorable anti-angiogenic potential in the treatment of HCC.

Dipeptidyl peptidase-IV (DPP-4) enzyme inhibitors are a promising category of diabetes medications. Bioactive peptides, particularly those derived from bovine milk proteins, play crucial roles in inhibiting the DPP-4 enzyme. This study describes a comprehensive strategy for DPP-4 inhibitory peptide discovery and validation that combines machine learning and virtual proteolysis techniques. Five machine learning models, including GBDT, XGBoost, LightGBM, CatBoost, and RF, were trained. Notably, LightGBM demonstrated superior performance with an AUC value of 0.92 ± 0.01. Subsequently, LightGBM was employed to forecast the DPP-4 inhibitory potential of peptides generated through virtual proteolysis of milk proteins. Through a series of in silico screening process and in vitro experiments, GPVRGPF and HPHPHL were found to exhibit good DPP-4 inhibitory activity. Molecular docking and molecular dynamics simulations further confirmed the inhibitory mechanisms of these peptides. Through retracing the virtual proteolysis steps, it was found that GPVRGPF can be obtained from β-casein through enzymatic hydrolysis by chymotrypsin, while HPHPHL can be obtained from κ-casein through enzymatic hydrolysis by stem bromelain or papain. In summary, the integration of machine learning and virtual proteolysis techniques can aid in the preliminary determination of key hydrolysis parameters and facilitate the efficient screening of bioactive peptides.

Photochromic polymer is defined as a series of materials based on photochromic units in polymer chains, which produces reversible color changes under irradiation with a particular wavelength. Currently, as the research progresses, it shows increasing potential applications in various fields, such as anti-counterfeiting, information storage, super-resolution imaging, and logic gates. However, there is a paucity of published reviews on the topic of photochromic polymers. Herein, this review discusses and summarizes the research progress and prospects of such materials, mainly summarizing the basic mechanisms, classification, and applications of azobenzene, spiropyran, and diarylethene photochromic polymers. Moreover, 3-dimensional (3D) printable photochromic polymers are worthy to be summarized specifically because of its innovative approach for practical application; meanwhile, the developing 3D printing technology has shown increasing potential opportunities for better applications. Finally, the current challenges and future directions of photochromic polymer materials are summarized.

Vehicle skin is the key component in maintaining the aerodynamic shape of the vehicle. A deformable high-speed vehicle needs to adjust its shape in real time to realize optimum aerodynamic efficiency and to withstand extreme heat flow induced by high-speed flight, which requires the skin to possess large strain and high-temperature resistance. Traditional vehicle skin cannot satisfy both of the requirements. Biomimetic flexible skin for deformable high-speed vehicles (DHSV-bio-FS) combines flexible material fabrication with transpiration cooling technology, which can simulate human skin sweat cooling, and has the characteristics of large strain and high-temperature resistance. The thermal protection performance of the prepared prototype of DHSV-bio-FS was evaluated by simulation and wind tunnel experiments at 40% tensile strain with liquid water as coolant. Simulation results suggest that the surface temperature of the DHSV-bio-FS at 40% tensile strain is consistent with the temperature of the coolant (350 K) in a 3,000 K high-temperature gas environment. In addition, the prepared prototype DHSV-bio-FS survived for 1,200 s in a high-temperature gas environment of 200 kW/m² in wind tunnel experiments. This paper verifies the reliability of DHSV-bio-FS in a high-temperature gas environment and can be deployed in applications of flexible skin for deformable high-speed vehicles (DHSV-FS).

Short-chain fatty acids (SCFAs) have been increasingly evidenced to be important bioactive metabolites of the gut microbiota and transducers in controlling diverse psychiatric or neurological disorders via the microbiota–gut–brain axis. However, the precise mechanism by which brain SCFAs extert multiple beneficial effects is not completely understood. Our previous research has demonstrated that the acetyl-coenzyme A synthetase short-chain family member 2 (ACSS2) is a novel target of the rapid and long-lasting antidepressant responses. Here, we show that micromolar SCFAs significantly augment both total cellular and nuclear ACSS2 to trigger tryptophan hydroxylase 2 (TPH2) promoter histone acetylation and its transcription in SH-SY5Y cells. In chronic-restraint-stress-induced depression mice, neuronal ACSS2 knockdown by stereotaxic injection of adeno-associated virus in the hippocampus abolished SCFA-mediated improvements in depressive-like behaviors of mice, supporting that ACSS2 is required for SCFA-mediated antidepressant responses. Mechanistically, the peroxisome-proliferator-activated receptor gamma (PPARγ) is identified as a novel partner of ACSS2 to activate TPH2 transcription. Importantly, PPARγ is also responsible for SCFA-mediated antidepressant-like effects via ACSS2–TPH2 axis. To further support brain SCFAs as a therapeutic target for antidepressant effects, d-mannose, which is a naturally present hexose, can significantly reverse the dysbiosis of gut microbiota in the chronic-restraint-stress-exposure mice and augment brain SCFAs to protect against the depressive-like behaviors via ACSS2–PPARγ–TPH2 axis. In summary, brain SCFAs can activate ACSS2–PPARγ–TPH2 axis to play the antidepressive-like effects, and d-mannose is suggested to be an inducer of brain SCFAs in resisting depression.

Recent years have witnessed numerous technical breakthroughs in connected and autonomous vehicles (CAVs). On the one hand, these breakthroughs have significantly advanced the development of intelligent transportation systems (ITSs); on the other hand, these new traffic participants introduce more complex and uncertain elements to ITSs from the social space. Digital twins (DTs) provide real-time, data-driven, precise modeling for constructing the digital mapping of physical-world ITSs. Meanwhile, the metaverse integrates emerging technologies such as virtual reality/mixed reality, artificial intelligence, and DTs to model and explore how to realize improved sustainability, increased efficiency, and enhanced safety. More recently, as a leading effort toward general artificial intelligence, the concept of foundation model was proposed and has achieved significant success, showing great potential to lay the cornerstone for diverse artificial intelligence applications across different domains. In this article, we explore the big models embodied foundation intelligence for parallel driving in cyber-physical-social spaces, which integrate metaverse and DTs to construct a parallel training space for CAVs, and present a comprehensive elucidation of the crucial characteristics and operational mechanisms. Beyond providing the infrastructure and foundation intelligence of big models for parallel driving, this article also discusses future trends and potential research directions, and the “6S” goals of parallel driving.

Due to the breaking of time-reversal and parity symmetries and the presence of non-conservative microscopic interactions, active spinner fluids and solids respectively exhibit nondissipative odd viscosity and nonstorage odd elasticity, engendering phenomena unattainable in traditional passive or active systems. Here, we study the effects of odd viscosity and elasticity on phase behaviors of active spinner systems. We find the spinner fluid under a simple shear experiences an anisotropic gas–liquid phase separation driven by the odd-viscosity stress. This phase separation exhibits equilibrium-like behavior, with both binodal-like and spinodal curves and critical point. However, the formed dense liquid phase is unstable, since the odd elasticity instantly takes over the odd viscosity to condense the liquid into a solid-like phase. The unusual phase behavior essentially arises from the competition between thermal fluctuations and the odd response-induced effective attraction. Our results demonstrate that the cooperation of odd viscosity and elasticity can lead to exotic phase behavior, revealing their fundamental roles in phase transition.

Soft crawling robots have been widely studied and applied because of their excellent environmental adaptability and flexible movement. However, most existing soft crawling robots typically exhibit a single-motion mode and lack diverse capabilities. Inspired by Drosophila larvae, this paper proposes a compact soft crawling robot (weight, 13 g; length, 165 mm; diameter, 35 mm) with multimodal locomotion (forward, turning, rolling, and twisting). Each robot module uses 4 sets of high-power-density shape memory alloy actuators, endowing it with 4 degrees of motion freedom. We analyze the mechanical characteristics of the robot modules through experiments and simulation analysis. The plug-and-play modules can be quickly assembled to meet different motion and task requirements. The soft crawling robot can be remotely operated with an external controller, showcasing multimodal motion on various material surfaces. In a narrow maze, the robot demonstrates agile movement and effective maneuvering around obstacles. In addition, leveraging the inherent bistable characteristics of the robot modules, we used the robot modules as anchoring units and installed a microcamera on the robot’s head for pipeline detection. The robot completed the inspection in horizontal, vertical, curved, and branched pipelines, adjusted the camera view, and twisted a valve in the pipeline for the first time. Our research highlights the robot’s superior locomotion and application capabilities, providing an innovative strategy for the development of lightweight, compact, and multifunctional soft crawling robots.

Helicobacter pylori colonizes over 50% of people worldwide. Biofilm formation through penetrating gastric mucus and resistance acquired by H. pylori markedly reduces the efficacy of traditional antibiotics. The present triple therapy and bismuth-based quadruple therapy inevitably causes intestinal flora disturbance and fails to address the excessive H. pylori-triggered inflammatory response. Herein, a mucus-permeable therapeutic platform (Cu-MOF@NF) that consists of copper-bearing metal-organic framework (Cu-MOF) loaded with nitrogen-doped carbon dots and naturally active polysaccharide fucoidan is developed. The experimental results demonstrate that Cu-MOF@NF can penetrate the mucus layer and hinder H. pylori from adhering on gastric epithelial cells of the stomach. Notably, released Cu²⁺ can degrade the polysaccharides in the biofilm and interfere with the cyclic growing mode of “bacterioplankton ↔ biofilm”, thereby preventing recurrent and persistent infection. Compared with traditional triple therapy, the Cu-MOF@NF not only possesses impressive antibacterial effect (even include multidrug-resistant strains), but also improves the inflammatory microenvironment without disrupting the balance of intestinal flora, providing a more efficient, safe, and antibiotic-free new approach to eradicating H. pylori.