Advanced Science最新文献

B. K. Kim, S. Jee, Y. Ahn, et al. “Seedless One-Pot Synthesis of Colloidal InAs Quantum Dots Enabling a High-Accuracy Photoplethysmography Oximeter.” Advanced Science 13, no. 38 (2026): e24375. https://doi.org/10.1002/advs.202524375

We have just noticed that one of the grant numbers in the Acknowledgements section was entered incorrectly. The grant number was published as RS-2025-24563595, whereas the correct number is RS-2025-24523595.

Nevertheless, as accurate funding information is important, we would be very grateful if you could kindly consider correcting the Acknowledgements section as follows:

“This work was supported by Korea Research Institute for Defense Technology Planning and Advancement (KRIT)  Grant funded by Defense Acquisition Program Administration (DAPA) (KRIT-CT-23-031); the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT, RS-2025-24523595, RS-2025-02316659); the Korea Research Institute of Standards and Science (KRISS-JP2026-0052, KRISS-GP2026-0001); and by the Ministry of Trade, Industry and Energy (MOTIE) and Korea Institute for Advancement of Technology (KIAT) through the International Cooperative R&D program (P0028887).”

We apologize for this error.

Direct reprogramming, which converts somatic cells from one lineage to another without passing through a pluripotent state, represents a promising therapeutic strategy for regenerative medicine. Recent advancements in identifying reprogramming factors and understanding molecular barriers have enabled efficient generation of therapeutically relevant cells. Yet, the clinical application of in vitro-derived reprogrammed cells is hampered by the immature phenotype, hostile microenvironments, low engraftment, and poor survival after transplantation. In vivo direct reprogramming of tissue-resident cells within their native tissue microenvironment offers a compelling alternative to overcome these barriers. Harnessing biochemical and biophysical cues of the tissue microenvironment, this approach facilitates the acquisition of molecular and functional features resembling endogenous cells. This review summarizes the current understanding of in vivo direct reprogramming, covering mechanisms, key reprogramming factors, and delivery strategies, and explores therapeutic applications across organ systems. Finally, key challenges such as delivery efficiency, incomplete understanding of tissue cues, and limited mechanistic insights, along with emerging strategies, are discussed.

Visualizing Hidden Periodontal Pathogen Activity

Hidden within the periodontal pocket, Porphyromonas gingivalis, a major periodontal pathogen, secretes Arg-specific gingipain. This protease cleaves peptides immobilized on CaCO₃ microspheres to release a chromogenic dye, transforming an invisible bacterial activity into a visible color signal for on-site detection. More details can be found in the Research Article by Yuki Hiruta, Jesse V. Jokerst, and co-workers (DOI: 10.1002/advs.77102).

Exposomics provides a systems-level framework to characterize the environmental exposures experienced across the life course and their biological consequences, offering critical insights into tumor initiation and precision prevention. Advances in sensing technologies, intelligent materials, and data science now enable continuous acquisition of external exposures alongside endogenous molecular and phenotypic responses. In this emerging paradigm, exposure is conceptualized not as an isolated variable statistically associated with disease, but as a temporally structured driver embedded within multiscale biological processes. By integrating multimodal monitoring with AI-enabled causal modeling, exposomics moves cancer risk assessment beyond population averages toward individualized, dynamically updated exposure-informed risk assessment. This Perspective highlights key technological directions in external-internal monitoring integration, intelligent sensing ecosystems, and causal data fusion, and outlines a translational framework aimed at supporting precision cancer prevention and early risk management.

Brain organoids are self-organizing 3D aggregates derived from pluripotent stem cells and thus mirror many aspects of human brain development, including gene expression programs, spatial organization, and neuron subtype specification. As a result, these organoids have been used to emulate neurodevelopmental, neuropsychiatric, and neurodegenerative diseases. Yet, their maturation remains fundamentally constrained by diffusion-limited necrosis, incomplete vascularization, limited visualization, and the absence of large-scale circuit integration, which collectively prevent progression beyond the fetal stage. These intrinsic limitations have catalyzed a convergence across microfluidics, biofabrication, imaging, and ethical frameworks, giving rise to a multidisciplinary movement aimed at enhancing organoid viability, reproducibility, and physiological relevance. This perspective examines how these technologies are transforming brain organoids from developmental models into experimentally robust, functional platforms.

Wearable and implantable microfluidic systems have progressed from laboratory prototypes toward translational clinical deployment, enabling continuous, minimally invasive sampling of dynamic biomarkers across sweat, saliva, tears, and interstitial fluid. However, existing reviews often address materials chemistry or device fabrication in isolation, obscuring the systemic path to clinical translation. This review establishes a cohesive, translation-focused linear trajectory starting from foundational functional biomaterials and advanced fabrication techniques, transitioning into a performance benchmarking of diagnostics-oriented systems and closed-loop theranostic platforms. Through these vectors, we systematically evaluate how microfluidic transport, multiplexed molecular analytics, and autonomous therapeutic integration collectively drive the shift from passive tracking to adaptive intervention. Beyond physical hardware, we decode the integration of artificial intelligence (AI) across three precise pathways: sensor self-calibration, multiplexed molecular decoding, and on-device autonomous decision-making. Finally, we critically examine the socio-technical barriers to clinical translation, with a focus on how biofluid data heterogeneity and population baseline disparities propagate algorithmic bias. We propose that robust hardware interfaces, standardized validation benchmarks, and alignment with emerging regulatory frameworks are prerequisites for achieving equitable, responsible digital health protection.

This study revisits oxygen-free, all-nitride glasses as a distinct class of high-performance materials, originally reported three decades ago by Grande, Holloway, McMillan, and Angell. A novel glass family at the time, such glass systems have remained unreplicated, largely due to the highly specialized experimental conditions required for their synthesis. With contemporary advances, such constraints are no longer prohibitive. Rather, in light of the persistent challenges in enhancing the performance of conventional glass systems, all-nitride glasses are reconsidered herein as a potentially viable class of processable materials that combine the formability of glasses with ceramic-level performance–without compromising optical transparency. Building upon progress in the modeling and computational evaluation of glass properties, a thermodynamic and semi-empirical framework is established to delineate the accessible chemical space and to estimate key properties, including liquidus temperature, density, elastic modulus, and refractive index. This approach enables assessment of the attainable property realm, which is shown to far surpass that of oxide glasses, consistent with experimental trends observed in oxynitride systems. Prospective processing routes, functionalization strategies, and high-performance applications are discussed in light of overcoming supply chain risks associated with materials in current use.

Targeted protein degradation (TPD) redirects endogenous protein-disposal pathways to selectively eliminate therapeutically relevant proteins. Over the past two decades, this field has progressed from proteolysis-targeting chimeras (PROTACs) to an expanding repertoire of proteasomal and lysosomal degradation strategies. Recent studies indicate that supramolecular strategies are emerging in TPD, with dynamic noncovalent interactions and ordered assembly shaping degrader construction, delivery, functional integration, or intracellular assembly or activation. Here we organize recent advances into four major modes of supramolecular involvement, encompassing noncovalent modular decoupling of degrader components, delivery-oriented single-component self-assembly, multicomponent co-assembly for functional integration, and intracellular in situ assembly that generates either persistent local architectures or active degraders following cellular entry. We discuss their applications across proteasomal, endosomal-lysosomal, and autophagy-lysosomal degradation pathways. Finally, we discuss translational challenges and emerging opportunities for advancing supramolecular degraders, spanning modular design, strategy diversification, indication selection, systemic biodistribution, intracellular trafficking, safety assessment, and the prospective use of artificial intelligence (AI)-assisted modeling.

Electroforming-Free, Self-Rectifying Selector-Only Memory

Electroforming-free, self-rectifying switching with polarity-dependent threshold modulation is realized in selector-only memory through Cu-ion migration in a bilayer stacked dual functional materials. The cover visualizes diffusive Cu-ion migration and transient filament dynamics in a bilayer selector-only memory, together with a three-SR-SOM full-adder architecture demonstrating compact logic-in-memory operation. More details can be found in the Research Article by Jea-Gun Park, Jinsub Park, and co-workers (DOI: 10.1002/advs.77423).