Science Bulletin最新文献

Immunotherapy is increasingly reshaping the therapeutic landscape of clinical oncology by inducing effective tumor regression and durable responses in various types of human cancers. However, a substantial fraction of patients resist immunotherapy, or even experience relapse after an initial response. Clinically, the conventional biomarkers often exhibit limited predictive accuracy and poor transferability across tumor types. These limitations highlight the urgent need for more robust, data-driven strategies to decipher tumor-immune dynamics and guide personalized treatment. Recently, artificial intelligence (AI) has emerged as a transformative paradigm in immuno-oncology, offering scalable solutions to decode high-dimensional and heterogeneous biomedical data. The evolution of AI can be broadly divided into six key stages: early machine learning (ML) classifiers, unsupervised representation learning, graph-based modeling of cell-cell interactions, multimodal foundation and biomedical language models, reinforcement and active learning paradigms, and AI virtual cells. At the molecular level, AI facilitates the integration of genomics, transcriptomics, proteomics, and spatially resolved single-cell omics, supporting fine-grained reconstruction of the tumor immune microenvironment (TIME). At the clinical interface, the application of deep learning (DL) in liquid biopsy, digital pathology, and radiologic imaging has advanced response prediction, biomarker discovery, and early detection of immune-related adverse events (irAEs), driving personized immunotherapy. This review synthesizes recent progress in AI-guided precision immunotherapy across molecular, cellular, and phenotypic area. By outlining key methodological advances and translational opportunities, we highlight that multimodal AI frameworks can pave the way toward the more interpretable, robust, and individualized immunotherapy strategies for cancer treatment.

Mesenchymal stem/stromal cells (MSCs) continue to drive innovation in regenerative medicine, yet the field is undergoing a critical evolution from the early concept of cellular engraftment to complex paracrine-mediated tissue repair. This review systematically evaluates the core scientific questions defining this transition, highlighting the latest advancements in MSC biology and the rapidly expanding therapeutic frontier of MSC-derived extracellular vesicles (MSC-EVs). We critically appraise recent progress in decoding MSC therapeutic mechanisms, specifically their profound capacity for immune modulation and microenvironmental remodeling. By synthesizing current findings across diverse and challenging clinical applications-encompassing oral tissue regeneration, osteoarthritis, and complex immune disorders-we provide expert insights into the discrepancies between promising preclinical data and variable clinical outcomes. Crucially, we address persistent translational bottlenecks, including inherent donor heterogeneity, manufacturing scalability, and the lack of standardized potency assays. It is our perspective that overcoming these limitations demands a strategic pivot towards precise cell-free MSC-EV therapies and advanced bioengineering strategies. Ultimately, this review highlights key directions for future research. By connecting basic mechanistic insights with clinical demands, we aim to accelerate the translation of effective MSC-based therapies.

In frustrated Ising magnets, classical spin liquids (CSLs) with macroscopic ground-state degeneracy can survive against conventional magnetic order. Here we report the discovery of a high-field route toward spin liquids in a bilayer triangular lattice antiferromagnet, Rb₂Co₂(SeO₃)₃. We demonstrate that field-controlled dilution of dimers gives rise to a cascade of candidate CSLs within an intermediate temperature regime. These states are characterized by correlated Ising dimers and are found to exhibit a macroscopic residual entropy of 1/2(1-M/M_s)Rln2, originating from doubly degenerate spin configurations. Owing to the interplay of intra- and inter-layer interactions, these CSLs are stabilized by lattice symmetry breaking, precursory to the low-temperature fractional magnetization plateaus. Such field-induced spin liquids can be understood as a consequence of generalized ice rules. In particular, the 5/6-plateau phase may host a quantum spin liquid ground state. Our results thereby establish a new pathway for exploring diverse spin liquid states across both classical and quantum regimes.

Superconductivity has been discovered in a variety of heterostructures, yet the general principles governing interface superconductivity remain elusive. Superfluid density, or superfluid stiffness, is a key parameter for characterizing the superconducting state, and its relation to the transition temperature T_c is central to understanding the superconducting mechanism. Measuring the superfluid stiffness of interface superconductors is, however, technically challenging because the signal arises from an extremely small volume near the interface. Here, we overcome this challenge by developing a highly sensitive two-coil mutual inductance technique compatible with a dilution refrigerator, enabling systematic measurements of the superfluid stiffness ρ_s in LaAlO₃/KTaO₃(111) (LAO/KTO(111)) heterostructures. Under electrostatic gating, the diamagnetic transition temperature T_c^MI first increases in proportion to ρ_s, then saturates beyond a threshold and becomes independent of ρ_s, signaling a crossover from Bose-Einstein-condensate-like to Bardeen-Cooper-Schrieffer-like behavior. We propose that these results arise from emergent granular superconductivity, an interpretation further supported by the observation of a paramagnetic Meissner effect under small applied magnetic fields.

The partial oxidation of methane (POM) is hampered by the high kinetic barrier of C-H bond activation, which demands high operating temperatures, and catalyst surface oxidation induces detrimental deactivation. This paper describes that the dual role of molybdenum carbide (MoC_x) enables facile methane activation and imparts oxidation resistance to Ni-based catalysts. We found that MoC_x modifies the reaction mechanism by altering oxygen adsorption, becoming the preferred site for oxygen activation and thereby protecting the Ni surface. In situ spectroscopy, transient and steady-state kinetics, and density functional theory calculations reveal the formation of a metastable C-Mo-O/Ni interface under reaction conditions. This interface provides a mechanism of O*-assisted C-H bond activation pathway instead of direct oxidation or combustion and reforming POM mechanism, lowering its activation energy. Concurrently, MoC_x maintains Ni in electron-deficient metallic state, effectively suppressing its oxidation. It achieves ∼94% CH₄ conversion and 99% syngas selectivity during a 75-h stability test at 720 °C. This work underscores the role of transition metal carbides as functional oxygen regulators, where the formation of oxycarbide intermediates dictates catalytic performance. The philosophy for anti-oxidation stability could generate broader implications for heterogeneous catalyst design.

Aqueous zinc-ion batteries (AZIBs) are promising candidates for large-scale energy storage owing to their safety, low cost, and material abundance. However, their practical deployment is hindered by interfacial failure of Zn metal anodes. While these issues have been widely investigated from kinetic, structural, and transport perspectives, the underlying thermodynamic driving forces remain less explored. This review re-examines the failure mechanisms of aqueous Zn metal anodes through the lens of interfacial thermodynamics. A fundamental thermodynamic asymmetry is proposed between the entropy-penalized Zn deposition and entropy-favored parasitic reactions including hydrogen evolution and corrosion. The structured electric double layer is further hypothesized to act as a low-entropy interfacial region that amplifies this imbalance. Re-evaluating prevailing stabilization strategies within this framework reveals their shared role in rebalancing the interfacial enthalpy-entropy landscape. This review aims to complement kinetic and structural analyses, offering a unified thermodynamic narrative to guide the design of more reversible Zn anodes.