As pivotal drivers of smart cities, mega-mobility systems integrate large-scale transportation networks, communication nodes, and energy circuits into a coupled multinetwork system. Urban megasystems epitomize the grand challenge of “organized complexity”, exhibiting characteristic features such as adaptive openness, nonlinear dynamics, hierarchical organization, and emergent properties. Analytical investigations, constrained by the rigid separation of macro- and microlevel paradigms, struggle to capture the nonlinear interdependencies across levels that define mega-mobility systems. In this review, we systematically advance macro–micro integration with feedback (MMIF) as a transformative paradigm for analyzing urban mega-mobility systems, synthesizing the state-of-the-art developments in typical constituent subsystems under this unified perspective. The MMIF paradigm bridges the gap between theoretical abstraction and empirical practice, contributing to scientifically sound urban development by harmonizing emergent patterns with granular behavioral dynamics. Building upon this paradigm, we investigate the key methods and technologies empowered by artificial intelligence that enable MMIF and critically analyze the enduring challenges and prospective research directions. As urban mobility systems increasingly serve as test beds for complexity science, the MMIF paradigm using artificial intelligence promises to reshape interdisciplinary collaboration, offering a blueprint for building intelligent, adaptive, and human-centric cities.

Stroke-induced motor and cognitive impairments substantially reduce the quality of life in elderly populations, driving the need for rehabilitation strategies that integrate neural plasticity and functional recovery. In this 4.5-year longitudinal study, we evaluated the efficacy of brain–computer interface combined with functional electrical stimulation (BCI-FES) versus FES only and conventional care (control) in 100 stroke survivors (60 to 90 years; 4,172 total screened, with 24 chronic-stage patients [>1 year post-onset] completing long-term follow-up). We integrated clinical metrics (Fugl-Meyer assessment [FMA], modified Barthel index [MBI], and Montreal Cognitive Assessment [MoCA]) with electroencephalography-based neurophysiological profiling to dissect recovery mechanisms. BCI-FES yielded superior and sustained improvements across all domains: motor function (FMA Δ = 4.5 ± 1.2 points, Cohen’s d = 1.2) versus FES (Δ = 1.7 ± 0.8, d = 0.4) and control (Δ = 0.9 ± 0.6, d = 0.2), functional independence (MBI Δ = 5.4 ± 1.5, d = 1.1) exceeding FES (Δ = 2.2 ± 1.1, d = 0.4) and control (Δ = 1.3 ± 0.5, d = 0.5), and cognitive function (MoCA Δ = 1.6 ± 0.5, d = 0.8 at 4 months), although cognitive gains declined to near baseline by 4.5 years. Hemorrhagic stroke patients showed exceptional BCI-FES responses, while ischemic patients exhibited higher variability. Neurophysiologically, BCI-FES induced theta (Cz and C4) and alpha (FC3 and CP3) power increases, with theta power at Cz strongly predicting FMA gains (r = 0.68), and enhanced theta/alpha band functional connectivity (clustering coefficient +22%, local efficiency +18%, and small-world index +15%). Predictive modeling identified that an optimal treatment window (3 to 12 months post-onset with 10 to 15 weeks of therapy) maximizes recovery via peak neuroplasticity, and a responder profile (stroke duration <23 months) includes patients with residual plasticity (age <70, baseline MBI >40), predicting 76% of favorable outcomes. These findings establish BCI-FES as a transformative rehabilitation tool, driving dual-phase recovery via early cortical plasticity and sustained network coherence while highlighting the need for age-tailored cognitive maintenance strategies. This work redefines precision stroke care by merging clinical outcomes with mechanistic insights, positioning BCI-FES as the standard of care for diverse stroke subtypes.

The absence of distinct biomarkers for oral squamous cell carcinoma (OSCC) hampers clinical diagnosis and treatment. Previous studies have demonstrated that sialylated immunoglobulin G (SIA-IgG) is up-regulated in a variety of epithelial-derived tumors and plays an important biological role. However, the function of SIA-IgG in OSCC progression is yet to be clarified. The expression characteristics and clinical significance of SIA-IgG were investigated using immunohistochemistry, western blot, and bioinformatics analysis. The biological functions of SIA-IgG were evaluated in vitro and in vivo. The underlying mechanisms of SIA-IgG in OSCC were elucidated using immunoprecipitation, mass spectrometry, and proteomic profiling. Furthermore, we explored the inhibitory effects of an exogenously added SIA-IgG-specific monoclonal antibody, RP215, on OSCC. An elevated level of SIA-IgG was observed in OSCC, and this was linked to poor survival among OSCC patients. Meanwhile, the up-regulation of SIA-IgG and valosin-containing protein (VCP) promoted the malignant progression of OSCC by activating the oxidative phosphorylation pathway. Moreover, SIA-IgG showed potential as a marker of OSCC cancer stem cells. Mechanistically, SIA-IgG enhanced the interaction between VCP and NADH:ubiquinone oxidoreductase subunit B6 (NDUFB6), thereby inhibiting the ubiquitin–proteasome-pathway-mediated degradation of NDUFB6 and sustaining the activation of the oxidative phosphorylation pathway. This inhibitory effect was abrogated by the overexpression of VCP. Furthermore, the SIA-IgG-specific antibody RP215 suppressed the malignant progression of OSCC, both in vitro and in vivo.

The 5-HT_1A receptor is a critical target in the treatment of depression and anxiety. Bufotenine derivatives, such as 5-methoxy-N,N-dimethyltryptamine (5-MeO-DMT), 5-hydroxy-N,N-dimethyltryptamine (5-OH-DMT), and 5-hydroxy-N,N,N-dimethyltryptamine—derived from traditional Chinese medicine—have shown antidepressant potential. However, the structural basis of their interaction with 5-HT_1A and their pharmacological profiles remain incompletely understood. This study investigated bufotenine derivatives acting on multiple serotonin receptors, highlighting 5-HT_1A as a key mediator of antidepressant effects while recognizing 5-HT_2A as primarily responsible for hallucinogenic outcomes, to identify candidates with therapeutic efficacy but reduced hallucinogenic liability. We determined the cryo-electron microscopy structures of 5-HT_1A bound to selected bufotenine derivatives. Functional assays in mice, including behavioral tests and receptor activation studies, were used to evaluate the antidepressant of each compound. Structural analysis revealed that all bufotenine derivatives engage conserved motifs within the 5-HT_1A binding pocket, with 5-OH-DMT displaying a distinct interaction pattern. Behavioral assays showed that 5-OH-DMT and 5-MeO-DMT retained strong antidepressant and anxiolytic effects. These pharmacological differences correlate with their unique receptor binding conformation. This study delineated the structural pharmacology of bufotenine derivatives at the 5-HT_1A receptor, identifying 5-OH-DMT and 5-MeO-DMT as promising antidepressant and anxiolytic candidates. The findings establish a molecular framework for the development of next-generation nonhallucinogenic therapeutics aimed at 5-HT_1A.

As an essential branch of smart materials, shape memory polymer materials (SMPs) have made substantial advances in fabrication strategies, microstructure design, and response methods. Shape memory polymer porous materials (SMPPMs), combining the advantages of SMPs and porous materials, feature lightweight properties, tunable micro/nanostructures, large specific surface areas, and programmable shapes, which have attracted important attention across a wide range of applications. This study focuses on 2 types of SMPPMs: shape memory foams and shape memory aerogels. This review systematically examines the fabrication strategies for SMPPMs, including gas foaming, template, freeze-drying, and 4-dimensional printing methods, deeply analyzes the impact of fabrication strategies on their micro/nanostructures, and summarizes their latest applications in areas such as smart thermal protection systems for aerospace, minimally invasive biomedical devices, and high-sensitivity smart sensors. This review analyzes the current state of research and future trends in SMPPMs from multiple perspectives, including material design, structural design, and response strategies. The design of SMPPMs requires integration with actual application needs, achieved through appropriate selection of polymer matrices and optimized micro/nanostructure designs to improve material performance. Furthermore, the review also introduces current challenges and development trends related to SMPPMs, including advanced, sophisticated, large-scale preparation strategies, and efficient, rapid, precise driving methods, as well as applications that integrate multiple disciplines and fields.

This study overcomes 2 critical barriers to the clinical translation of nano-adsorbents for sepsis blood purification: the weakening of adsorption function caused by nanoparticle biofouling and the limitations in clinical translation of recovery devices. We pioneer electrically neutral phosphocholine zwitterions as selective lipopolysaccharide (LPS) ligands. Their precise charge orientation resolves the core conflict between anti-fouling efficacy and LPS capture via differential dipole realignment upon LPS binding, enabling unprecedented selective LPS capture capacity with minimal protein adsorption. To address the persistent challenges of nano-adsorbent retrieval from blood, and clinical incompatibility of existing retrieval devices with blood purification systems, we developed a discretely assembled magnetic nanocomposite platform (PCAPAN-Fe) and an extracorporeal LPS-targeting magnetic array system (ELMAS), eliminating key risks inherent in monolithic designs while ensuring complete nanoparticle harvest. In septic rabbit models, the integrated platform exhibited 100% survival with early intervention, 84.7% LPS clearance (versus 20% survival and 45.6% LPS clearance for commercial adsorbents), and marked reduction of key proinflammatory cytokines. Crucially, the therapy achieved 82.2% LPS clearance efficacy in progressive sepsis, extending survival to 40% (versus 0% for commercial adsorbents). By ingeniously integrating molecular-level ligand design with a clinically viable device, this work pioneers a paradigm shifts in sepsis nanotherapeutic, resolving the performance–biosafety paradox in blood purification.

Organonitrogen chemicals with C=N bonds are one of the most important groups of chemicals with broad applications, but their synthesis via reductive coupling remains a great challenge, because of the favorable hydrogenation of C=N bonds into C–N bonds. In this study, a nitrogen-doped carbon-supported β-MoO₃ catalyst with abundant oxygen vacancies (O_v) was discovered to be robust in the reductive coupling of nitro compounds with biomass-derived alcohols toward the synthesis of organonitrogen chemicals, including imines and N-heterocycles with C=N bonds. The O_v in β-MoO₃ serves a crucial role in the adsorption and activation of substrates via the electronic interaction between the negatively charged oxygen atoms in these substrates and the O_v sites in β-MoO₃. The presence of O_v greatly lowers the energy barriers of the reductive coupling reaction, and the electron transfer from alcohols to nitro compounds is mediated by the Mo⁵⁺/Mo⁶⁺ redox cycle. Our method demonstrates excellent selectivity to C=N bonds and is effective for a wide substrate scope including the highly inert methanol and ethanol. This study highlights the use of non-noble metal oxides as alternatives to traditional metal nanoparticles for various challenging organic transformations.

Achieving stable n-type conductivity in diamond has remained a central challenge due to the deep donor levels and compensation associated with conventional dopants. Here, we show that oxygen-assisted B–N codoping during microwave plasma chemical vapor deposition activates shallow BN₂ donors within a narrow thermal window ~(1,020 K), yielding reproducible electron conduction. First-principles calculations identify the BN₂ complex—stabilized via oxygen-mediated regulation of N site occupancy that suppresses deeper N-related defects—as a shallow and strain-tolerant donor, consistent with the experimentally optimized growth window for BN₂ codoping. The resulting films exhibit electron concentrations above 10¹⁹ cm⁻³ with a mobility of 4.05 cm²/(V·s) and a shallow activation energy of ~21.1 meV, confirming effective n-type transport. Integration with p-type 2H-MoTe₂ yields a diamond-based pn junction with clear rectifying behavior. While device performance is presently limited by interface states, these findings establish BN₂ codoping as a viable strategy for n-type diamond and highlight interface quality as the decisive frontier for diamond electronics, opening opportunities for high-frequency, high-power, and radiation-hard device platforms.

Chemoresistance is a primary cause of cancer treatment failure, due to the lack of specific regulatory strategies arising from unclear mechanisms. Here, we uncover the pivotal role of the PRMT1/SOX2 axis in regulating cancer stemness, a key factor contributing to cancer chemoresistance. In light of this, we construct a DNA nanomachine (DNM) to overcome chemoresistance by reversing cancer stemness. This DNM is constructed using a programmable DNA origami framework, incorporating CD44-targeting aptamers and glutathione (GSH)-responsive stemness inhibitors (DCLX069) as functional components. The DNM exhibits a specific affinity toward CD44-overexpressing tumor cells, enabling the effective delivery of the loaded cisplatin (CDDP) to the tumor cells. Upon entering the tumor cells, DCLX069 is rapidly released from the DNM due to high intracellular GSH levels, leading to swift regulation of the PRMT1/SOX2 axis. In contrast, CDDP exhibits a gradual enzymatic release profile. This temporally programmed release enables the reversal of cancer stemness before chemotherapy initiation, resulting in a substantial improvement in CDDP chemosensitivity and a significant increase in the median survival of tumor-bearing mice from 27 to over 56 d with DNM assistance. This study highlights the promising potential of this DNA nanotechnology-empowered therapy in addressing chemoresistance in malignant tumors.

Large-scale proteomics enables the identification of biomarkers and undulations in metabolic aging. This study aimed to develop a metabolic age (MA) and identify proteomic biomarkers and their undulating changes during metabolic aging. Using UK Biobank data, MA was developed from mortality-associated metabolomic profiles (nuclear magnetic resonance platform) in 203,491 participants. Associations between 2,923 plasma proteins (Olink Explore 3072 platform) and metabolic aging phenotypes, including MA, telomere length, frailty index, incident type 2 diabetes, cardiovascular disease, and mortality, were examined in 24,920 participants via Cox proportional hazards or linear models. Differential expression–sliding window analysis captured protein waves during metabolic aging in 7,092 participants. MA improved the predictions of mortality, cardiovascular disease, and type 2 diabetes beyond conventional risk factors (C-index up to 0.786) and correlated strongly with chronological age (Spearman’s r: 0.876). Sixty proteins were associated with all metabolic aging phenotypes. Among them, growth differentiation factor 15 (GDF15), urokinase plasminogen activator surface receptor (PLAUR), tumor necrosis factor receptor superfamily member 10A (TNFRSF10A), tumor necrosis factor receptor superfamily member 10B (TNFRSF10B), gamma-interferon-inducible lysosomal thiol reductase (IFI30), hepatocyte growth factor (HGF), WAP 4-disulfide core domain protein 2 (WFDC2), collagen alpha-3(VI) chain (COL6A3), polymeric immunoglobulin receptor (PIGR), insulin-like growth factor-binding protein 4 (IGFBP4), and tumor necrosis factor receptor superfamily member 27 (EDA2R) ranked within the top 20 for at least 4 phenotypes based on P values. Pathway analysis highlighted symbiont entry into host cell and cytokine–cytokine receptor interaction in metabolic aging. Proteins showed undulating changes during metabolic aging, with 3 peaks at 44, 51, and 63 years. MA–protein trajectories clustered into 3 groups. Groups 1 and 3 exhibited linear increases with MA, whereas group 2 showed nonlinear increases. In conclusion, the identification of plasma proteomic biomarkers and their undulating changes in metabolic aging provides a critical foundation for developing clinical markers and precision interventions to prevent accelerated metabolic aging.