Low tumor immunogenicity and limited immune-cell infiltration remain major barriers to effective breast cancer immunotherapy. Although sonodynamic therapy (SDT) offers a noninvasive strategy for deep-tissue tumor treatment, its efficacy is often restricted by insufficient reactive oxygen species (ROS) generation and the immunosuppressive tumor microenvironment. Here, we report a sonosensitizer-functionalized polymetallic nanozyme, Pd@PtBi₂-Ce6@HA (PPBCH), as a multifunctional theranostic platform for photoacoustic imaging-guided sonodynamic cancer immunotherapy. Upon ultrasound (US) activation, PPBCH exhibits catalase-, peroxidase-, and glutathione oxidase-like activities, thereby enabling O₂ generation, ROS amplification, and intracellular glutathione depletion. This coordinated redox disruption induces mitochondrial dysfunction, lipid peroxidation, and GPX4 downregulation, leading to severe oxidative damage, ferroptotic stress, and subsequent immunogenic cell death. PPBCH also elicits canonical hallmarks of immunogenic cell death, including calreticulin exposure, HMGB1 release, and extracellular ATP secretion, thereby promoting dendritic cell maturation and antitumor immune activation. In parallel, the polymetallic framework enables photoacoustic imaging for monitoring tumor accumulation and guiding treatment timing in vivo. More importantly, PPBCH-mediated SDT remodels the immunosuppressive tumor microenvironment, enhances CD8⁺ T-cell infiltration, promotes M1-like macrophage polarization, and markedly improves the therapeutic efficacy of anti-PD-L1 immunotherapy. This work establishes a polymetallic nanozyme strategy that integrates catalytic sonodynamic amplification, imaging-guided intervention, and immunomodulation for precise cancer immunotherapy.

Machine vision systems in real-world applications require devices capable of adapting to multiple operational modes, including high-sensitivity photodetection, neuromorphic synaptic behavior, and optical memory. However, integrating these distinct optoelectronic functionalities into a single device presents a challenge due to their conflicting requirements for photoresponse time and retention. Here, a gate-programmable multifunctional transistor based on a MoS₂/MAPbBr₃ van der Waals (vdW) heterostructure is fabricated. By using the gate field to tune the interfacial electric field and trapping/release kinetics associated with shallow- and deep-level states, the device can be programmed to operate as a photodetector, synaptic transistor, and gate-bias-assisted multilevel optical memory. Under a positive gate voltage (V_G), a pronounced photogating effect enables photodetection with responsivity (R) of ∼2397 A/W. At V_G = –20 V, the device switches to synaptic mode. At a more negative gate bias, the device enters a gate-bias-assisted optical-memory mode under sustained gate bias. To illustrate the utility of this programmable multifunctionality, frequency-encoded image recognition is demonstrated with 96.4% accuracy. In addition, a device-enabled reservoir-computing (RC) scheme with software-assisted readout improves classification accuracy by ~20% through deep delay-based processing. This work demonstrates a multimodal transistor architecture that integrates multiple optoelectronic functions in a single device and suggests a compact hardware route toward adaptive in-sensor optical information processing.

Engineering inorganic matrices with optimized photon absorption and interfacial energy transfer is pivotal for advancing laser desorption/ionization mass spectrometry (LDI-MS) toward high-fidelity metabolomic analysis. Here, we developed a metal-organic framework (MOF)-derived porous iron oxide (pFO) nanomatrix for LDI-MS-based metabolomics. The pFO exhibits strong UV absorption at 355 nm, a high specific surface area (59.7 m²/g), and a uniform mesoporous structure, which collectively afford low background noise, enhanced analyte signal intensity, and high analytical reproducibility (coefficient of variation < 9.2%). Using this platform, metabolic fingerprints were rapidly acquired from 269 tobacco leaf samples. Integrated with Random Forest, the approach achieved accurate discrimination of leaf stalk position (AUC = 0.962) and reliable differentiation between southwestern and southeastern production regions (AUC > 0.944). Furthermore, eight representative m/z features were identified to construct a reduced classification panel, which maintained robust predictive performance in the test set (AUC > 0.913). This study establishes MOF-derived pFO as a high-performance inorganic matrix for LDI-MS metabolomics and establishes a rapid and reproducible analytical strategy for digital classification and quality traceability of agricultural products.

Sodium-ion batteries (SIBs) are promising for low-temperature applications compared with commercial lithium-ion batteries, because of the weaker solvation and higher conductivity of Na⁺ in electrolytes. However, the large size of Na⁺ leads to slow ionic transport and sluggish reaction kinetics in the electrodes, which is more severe after the lattice shrinks under low temperatures. Herein, a conjugated coordination polymer (CCP) is reported as a cathode for low-temperature SIBs, by using naphthazarin (DHNQ) as the ligands and Ni²⁺ as the metal centers. Benefiting from the π-d conjugation, the Ni-DHNQ exhibits a high electrical conductivity of 69.7 mS/m and maintains both structural integrity and efficient electron and ion transport even at −40°C. These characteristics collectively enhance the reaction kinetics and cycling stability. The Ni-DHNQ cathode enables ultrafast charging to 52% state-of-charge (SOC) in 90 s and exhibits an ultralow capacity decay rate of 0.0028% per cycle over 5000 cycles. When paired with an organic anode, the pouch full-cell could reach 87% of its SOC even at −40°C, far higher than the commercial lithium-ion batteries (12%) and reported alkali-metal-ion batteries. This work demonstrates the promise of CCPs for high-performance sustainable energy storage under extreme conditions.