It is crucial to monitor the real-time and accurate status of an electric drive system and understand its interaction with driving behavior in order to meet the higher requirements for vehicle safety and reliability in the era of autonomous driving. Traditional wired sensors have limitations in system integration and energy autonomy. This study proposes a triboelectric nanogenerator (TENG) based on the centrifugal-force-enhanced contact mechanism, which can be directly integrated into the transmission shaft of electric vehicles to construct an intelligent self-powered monitoring system. This design effectively overcomes the bottleneck of unstable signals and insufficient durability of traditional rotating TENGs at high speeds by coupling centrifugal force and spring pre-tension and outputs stable and high signal-to-noise ratio sensing signals. On this basis, this study not only achieved high-precision real-time perception of the driving system speed but also further explored the rich information embedded in the centrifugal-force-enhanced contact TENG signal and extended it to the intelligent recognition of driving behavior and road conditions. Based on signal processing and the convolutional neural network and bidirectional long short-term memory model, the system has achieved fault diagnosis of key transmission component bearings in the transmission system with an accuracy rate of up to 96.1%. At the same time, the system can effectively recognize driving behaviors such as sudden acceleration and deceleration (recognition accuracy of 84%), as well as typical road conditions such as flat, slippery, and speed bumps (recognition accuracy of 89.9%), providing key information for automatic driving algorithm calibration and driving safety improvement. The self-powered embedded sensing technology developed in this study provides a new technological path for the efficient energy management and predictive maintenance system of intelligent connected vehicles and is a key sensing node for building future autonomous transportation systems.

Liver fibrosis shows limited treatment efficacy, driven by metabolic reprogramming and epigenetics, while the role of lactate-mediated lactylation in hepatic microenvironment remains unclear. Here, through integrative analysis of public databases and human cirrhotic liver tissues, we identified a pathogenic FSP1⁺ (fibroblast specific protein 1) macrophage subset as a key therapeutic target. We uncovered a novel FSP1–glycolysis–lactylation axis that drives fibrotic progression through metabolic–immune crosstalk. Expanded FSP1⁺ macrophage infiltration was observed in human cirrhotic liver tissues and myeloid-specific Fsp1 knockout markedly attenuates inflammation and fibrosis. Mechanistic investigations reveal that FSP1 physically interacts with pyruvate kinase M2 (PKM2) in macrophages, inhibiting its ubiquitin–proteasome degradation to stabilize the enzyme. This FSP1–PKM2 interaction enhances glycolytic flux and lactate production, which in turn promotes KAT2B-dependent lactylation of phosphoglycerate kinase 1 (PGK1) at lysine 353 (K353). The posttranslational modification creates a positive feedback loop by concurrently activating PGK1 and pyruvate dehydrogenase kinase 1, which blocks mitochondrial pyruvate metabolism, thereby amplifying glycolysis and PGK1 lactylation. Notably, we developed a cell-penetrating peptide targeting PGK1-K353 lactylation that effectively attenuates the progression of liver fibrosis. Our findings establish lactate-mediated lactylation of PGK1 as a critical node in fibrotic metabolism and reveal a previously unrecognized FSP1–glycolysis axis that sustains the pro-fibrotic microenvironment. Targeting PGK1-K353 lactylation represents a promising therapeutic strategy for chronic liver diseases.

Osteoporosis is a systemic skeletal disorder characterized by reduced bone mass, impaired microarchitecture, and increased fracture risk, primarily resulting from dysregulated bone remodeling. Increasing evidence highlights a close interaction between bone metabolism and the gut microbiota. Alterations in bone mineral density can influence gut microbial composition. Conversely, microbial dysbiosis disrupts bone homeostasis through multiple pathways, including microbial metabolites, immune regulation, and neuroendocrine signaling. Short-chain fatty acids suppress osteoclast differentiation and enhance intestinal calcium absorption, while gut dysbiosis promotes bone loss by impairing intestinal barrier integrity and increasing proinflammatory cytokines such as tumor necrosis factor-α and interleukin-6. The gut–brain–bone axis represents an important regulatory network linking the central nervous system, gut-derived signals, and skeletal remodeling. Chronic stress and neurodegenerative conditions activate the hypothalamic–pituitary–adrenal axis and bone-derived extracellular vesicle signaling, thereby favoring bone resorption. Estrogen deficiency further disrupts the receptor activator of nuclear factor κΒ ligand/osteoprotegerin signaling pathway and alters gut microbial composition, contributing to postmenopausal bone loss. Therapeutic strategies targeting this axis, including probiotics, prebiotics, fecal microbiota transplantation, dietary fiber supplementation, and pharmacological or natural compounds, show potential in restoring microbial balance and improving bone metabolism. Future studies integrating multiomics approaches and well-designed clinical trials are needed to clarify microbiome–bone interactions and support the development of targeted interventions for osteoporosis.

As silicon anodes approach their theoretical capacity limits in lithium-ion batteries, the exploration of materials with even higher energy storage potential becomes imperative. Here, we demonstrate that silicon–carbon composites can deliver ultrahigh capacities exceeding 6,500 mAh g⁻¹, benefiting from the abundant internal defects within the composite. At a charge–discharge rate of 0.1 C (0.42 A g⁻¹), the initial discharge specific capacity reaches 6,694.21 mAh g⁻¹, with a Coulombic efficiency (CE) of 74.71%, markedly exceeding the theoretical capacity limit of silicon. By further optimizing lithium battery electrolyte, the initial discharge specific capacity is 5,294.88 mAh g⁻¹ and CE is increased to 90.96%. Moreover, an artificial intelligence-assisted framework combining a multilayer perceptron with a constrained genetic algorithm predicts a theoretical maximum initial discharge capacity of 7,789.55 mAh g⁻¹. These results provide compelling evidence that silicon–carbon composites hold great promise for substantially enhancing the energy density of next-generation lithium-ion batteries.

Non-small-cell lung cancer (NSCLC) with brain metastases poses formidable therapeutic challenges due to acquired resistance and the inherent pharmacokinetic defects of traditional delivery. We developed an innovative lipoic acid-based self-assembled nanodrug (dabrafenib, trametinib, and lipoic acid self-assembly [DTL]) system, whose rational design was guided by a novel machine learning platform to overcome high-cost, empirical screening bottlenecks. Multifunctional lipoic acid, serving as a universal self-assembling molecule, enabled DTL’s robust assembly and enhanced penetration across mucosal and solid tumor barriers via its unique thiol-mediated exchange mechanism while simultaneously exerting distinct antitumor efficacy. Intranasal administration of DTL achieved efficient dual-targeted delivery to both primary NSCLC and established intracranial metastases. Furthermore, compared to conventional targeted combination therapies, DTL induced diverse, multimodal tumor cell death (apoptosis, pyroptosis, and ferroptosis) and profoundly remodeled the immune microenvironment. In vivo, DTL markedly inhibited tumor growth with reduced toxicity, offering a clinically translatable strategy for advanced NSCLC.

Large momentum effective theory (LaMET) provides a general framework for computing the multi-dimensional partonic structure of the proton from first principles using lattice quantum chromodynamics (QCD). In this effective field theory approach, LaMET predicts parton distributions through a power expansion and perturbative matching of a class of Euclidean observables—quasi-distributions—evaluated at large proton momenta. Recent advances in lattice renormalization, such as the hybrid scheme with leading renormalon resummation, together with improved matching kernel that incorporates higher-loop corrections and resummations, have enhanced both the perturbative and power accuracy of LaMET, enabling a reliable quantification of theoretical uncertainties. Moreover, the Coulomb-gauge correlator approach further simplifies lattice analyses and improves the precision of transverse-momentum-dependent structures, particularly in the non-perturbative region. State-of-the-art LaMET calculations have already yielded certain parton observables with important phenomenological impact. In addition, the recently proposed kinematically enhanced lattice interpolation operators promise access to unprecedented proton momenta with greatly improved signal-to-noise ratios, which will extend the range of LaMET prediction and further suppress the power corrections. The remaining challenges, such as controlling excited-state contamination in lattice matrix elements and extracting gluonic distributions, are expected to benefit from emerging lattice techniques for ground-state isolation and noise reduction. Thus, lattice QCD studies of parton physics have entered an exciting stage of precision control and systematic improvement, which will have a broader impact for nuclear and particle experiments.

Vascular scaffolds are fundamental devices in treating vascular occlusions, aneurysms, and hemodialysis access. However, their long-term efficacy is often compromised by 2 major pathophysiological responses: acute thrombosis and intimal hyperplasia, underscoring the need for effective antithrombotic treatment and intensive surveillance. This review highlights the emerging approaches used to address such challenges in vascular scaffolds: surface biofunctionalization and intelligent monitoring systems. We first introduce the leading biodegradable elastic polymers for vascular scaffolds, followed by a comprehensive overview of surface biofunctionalization techniques for preventing thrombosis and promoting endothelialization. The review further explores the cutting-edge advances in integrating flexible bioelectronics with cardiovascular implants for intelligent real-time monitoring of hemodynamics, thrombosis, and restenosis. It concludes with a discussion of the remaining challenges and future perspectives, thereby promoting the development of more effective cardiovascular therapies and their clinical applications.

The tumor microenvironment is a central determinant of cancer progression, metastatic spread, and therapeutic resistance. Once considered passive scaffolds, stromal cells are now recognized as heterogeneous, active regulators of tumor behavior. Recent single-cell and spatial multiomics studies have resolved functionally distinct stromal subtypes, each defined by characteristic molecular programs and spatial niches, with specialized roles in extracellular matrix remodeling, immune evasion, and angiogenesis. This review synthesizes evidence for bidirectional stromal–tumor cross-talk in which cytokine networks (e.g., transforming growth factor-beta, interleukin-6, and C-X-C motif chemokine ligand 12/C-X-C chemokine receptor 4) coordinate epithelial–mesenchymal transition, stemness, chemotaxis, and vascular remodeling. Building on these insights, this review also argues for subtype-specific biomarkers and multimodal therapeutic strategies to overcome stromal-mediated resistance. Integrating stromal heterogeneity into precision-oncology workflows through standardized, lineage-resolved profiling and real-time biomarker guidance will be essential for diagnostic refinement and personalized treatment.

Polyamines are ancient metabolites that serve critical functions in maintaining epithelial integrity, regulating immune response, and supporting healthy aging. The gut microbiota actively synthesizes and converts polyamines, while host factors such as inflammation, barrier function, and nutritional status dynamically modulate this metabolic network. Disruption of this host–microbiota axis reduces polyamine availability, impairs barrier function, and exacerbates inflammation. In contrast, polyamines exert protective effects by promoting epithelial repair, modulating macrophage and T-cell responses, and enhancing autophagy-mediated tissue renewal and longevity. Recent advances in engineered probiotics, microbial small RNAs, and postbiotics further highlight the therapeutic potential of precisely modulating polyamine metabolism in clinical contexts such as inflammatory bowel disease, metabolic syndrome, and neurodegenerative conditions associated with aging.

Electroactive microbes are uniquely capable of aggressively corroding metals like stainless steel that were once thought immune to microbial attack. This activity has been attributed to microbial destruction of the protective chromium oxide passive film on the stainless steel surface that protects the underlying Fe⁰ from corrosive agents, allowing the microbes to establish direct electrical contact with the Fe⁰ and extract electrons to support anaerobic respiration. We show here that the electroactive microbe Geobacter sulfurreducens, despite its high corrosive activity, is unable to physically breach the passive film. Instead, it enables biologically mediated electron transfer across an intact chromium oxide-rich layer that remains sufficiently insulating to block abiotic proton reduction. These findings challenge the prevailing assumption that electroactive microbes must directly contact Fe⁰ for corrosion and provide new guidance for the design of corrosion-resistant metals.