Game theory problems are widely applied in many research areas such as computer science and finance, with the key issue being how to quickly make decisions. Here, we present a novel quantum algorithm for game theory problems based on a continuous quantum walk. Our algorithm exhibits quantum advantage compared to classical game algorithms. Furthermore, we exploit the analogy between the wave function of the Schrödinger equation and the voltage in Kirchhoff’s law to effectively translate the design of quantum game trees into classical circuit networks. We have theoretically simulated the quantum game trees and experimentally validated the quantum functionality speedup on classical circuit networks. Due to the robust scalability and stability inherent in classical circuit networks, quantum game trees implemented within this framework hold promise for addressing more intricate application scenarios.

Hydrologic reconstructions from North America are largely unknown for the Middle Miocene. Examination of fungal palynomorph assemblages coupled with traditional plant-based palynology permits delineation of local, as opposed to regional, climate signals and provides a baseline for study of ancient fungas. Here, the Fungi in a Warmer World project presents paleoecology and paleoclimatology of 351 fungal morphotypes from 3 sites in the United States: the Clarkia Konservat-Lagerstätte site (Idaho), the Alum Bluff site (Florida), and the Bouie River site (Mississippi). Of these, 83 fungi are identified as extant taxa and 41 are newly reported from the Miocene. Combining new plant-based paleoclimatic reconstructions with funga-based paleoclimate reconstructions, we demonstrate cooling and hydrologic changes from the Miocene climate optimum to the Serravallian. In the southeastern United States, this is comparable to that reconstructed with pollen and paleobotany alone. In the northwestern United States, cooling is greater than indicated by other reconstructions and hydrology shifts seasonally, from no dry season to a dry summer season. Our results demonstrate the utility of fossil fungi as paleoecologic and paleoclimatic proxies and that warmer than modern geological time intervals do not match the “wet gets wetter, dry gets drier” paradigm. Instead, both plants and fungi show an invigorated hydrological cycle across mid-latitude North America.

Background: The mechanisms underlying social dysfunction caused by repeated sevoflurane in early life remain unclear. Whether the gut microbiota–metabolite–brain axis is involved in the mechanism of sevoflurane developmental neurotoxicity still lacks report. Methods: Mice received 3% sevoflurane at postnatal day (PND) 6, 7, and 8 for 2 h per day. Metagenomic sequencing and untargeted metabolomic analysis were applied to investigate the effects of sevoflurane on gut microbiota and metabolism. The animal social behavior and the synaptic development were analyzed during PND 35. Subsequently, fecal microbiota transplantation (FMT) from the control group and bile acid administration were performed to see the expected rescuing effect on socially related behaviors that were impaired by repeated sevoflurane exposure in the mice. Results: In the 3-chamber test, sevoflurane-exposed mice spent less time with stranger mice compared with the control group. The density of both the apical and basal spine decreased in mice exposed to sevoflurane. In addition, repeated sevoflurane exposure led to a notable alteration in the gut microbiota and metabolite synthesis, particularly bile acid. FMT reduced the production of intestinal bile acid and attenuated the effect of sevoflurane exposure on social function and synaptic development. Cholestyramine treatment mimics the protective effects of FMT. Conclusions: The gut microbiota–metabolite–brain axis underlies social dysfunction caused by sevoflurane exposure in early age, and bile acid regulation may be a promising intervention to this impairment.

Advanced sensing devices based on metasurfaces have emerged as a revolutionary platform for innovative label-free biosensors, holding promise for early diagnostics and the detection of low-concentration analytes. Here, we developed a chip-based ultrasensitive terahertz (THz) metasensor, leveraging a quasi-bound state in the continuum (q-BIC) to address the challenges associated with intricate operations in trace biochemical detection. The metasensor design features an open-ring resonator metasurface, which supports magnetic dipole q-BIC combining functionalized gold nanoparticles (AuNPs) bound with a specific antibody. The substantial enhancement in THz–analyte interactions, facilitated by the potent near-field enhancement enabled by the q-BICs, results in a substantial boost in biosensor sensitivity by up to 560 GHz/refractive index units. This methodology allows for the detection of conjugated antibody–AuNPs for cardiac troponin I at concentrations as low as 0.5 pg/ml. These discoveries deliver valuable insight for AuNP-based trace biomolecule sensing and pave the path for the development of chip-scale biosensors with profound light–matter interactions.

Microneedles have shown considerable potential in treating ocular diseases, yet enhancing their architecture and functionality to improve therapeutic efficacy poses marked challenges. Here, inspired by the antioxidant strategy of blueberries and the wet adhesive mechanism of clingfish, we construct hierarchical and multifunctional microneedles. These microneedles possess both wet adhesive and antioxidant properties, making them highly effective for ocular wound healing. Constructed using polyacrylic acid-N-hydroxysuccinimide-based hydrogel with hexagonal structures, these generated microneedles ensure strong adhesion in wet environments. Furthermore, by incorporating proanthocyanidins (pAc) into the tips, the microneedle is imparted with excellent competence to scavenge reactive oxygen species (ROS). In the rat model of ocular alkali burns, the designed microneedle not only exhibited robust adhesion and desirable antioxidant properties in the moist ocular environment but also facilitated sustained drug release and effective treatment. These results suggest that our bioinspired microneedles with multifunctional properties offer substantial advancement over conventional approaches, positioning them as promising candidates for versatile wound healing applications.

Melting and solidification of lunar regolith are pivotal for comprehending the evolutionary dynamics of lunar volcanism, geology, and impact history. Additionally, insights gained from these processes can contribute to the advancement of in situ resource utilization technologies, for instance additive manufacturing and resource extraction systems. Herein, we conduct the direct observation of the melting and rapid solidification of lunar particles returned by the Chang’E 5 mission. The melting temperature and melting sequence were obtained. Bubble generation, growth, and release were clearly observed, with a maximum bubble diameter of 5 µm, which is supposed to be according to the release of volatiles that embedded in the particles. During the solidification process, evident crystallization occurred with incremental crystal growth rate approximately of 27 nm/s. Scanning electron microscopy and energy-dispersive x-ray spectroscopy results verified that the Fe-rich mineral crystalizes first. These results would improve the understanding of the evolution of lunar volcanism, geology, and impact history.

Understanding protein corona composition is essential for evaluating their potential applications in biomedicine. Relative protein abundance (RPA), accounting for the total proteins in the corona, is an important parameter for describing the protein corona. For the first time, we comprehensively predicted the RPA of multiple proteins on the protein corona. First, we used multiple machine learning algorithms to predict whether a protein adsorbs to a nanoparticle, which is dichotomous prediction. Then, we selected the top 3 performing machine learning algorithms in dichotomous prediction to predict the specific value of RPA, which is regression prediction. Meanwhile, we analyzed the advantages and disadvantages of different machine learning algorithms for RPA prediction through interpretable analysis. Finally, we mined important features about the RPA prediction, which provided effective suggestions for the preliminary design of protein corona. The service for the prediction of RPA is available at http://www.bioai-lab.com/PC_ML.

Immune checkpoint therapy, such as programmed cell death protein 1/programmed death-ligand 1 (PD-1/PD-L1) blockade, has achieved remarkable results in treating various tumors. However, most cancer patients show a low response rate to PD-1/PD-L1 blockade, especially those with microsatellite stable/mismatch repair-proficient colorectal cancer subtypes, which indicates an urgent need for new approaches to augment the efficacy of PD-1/PD-L1 blockade. Cholesterol metabolism, which involves generating multifunctional metabolites and essential membrane components, is also instrumental in tumor development. In recent years, inhibiting proprotein convertase subtilisin/kexin type 9 (PCSK9), a serine proteinase that regulates cholesterol metabolism, has been demonstrated to be a method enhancing the antitumor effect of PD-1/PD-L1 blockade to some extent. Mechanistically, PCSK9 inhibition can maintain the recycling of major histocompatibility protein class I, promote low-density lipoprotein receptor-mediated T-cell receptor recycling and signaling, and modulate the tumor microenvironment (TME) by affecting the infiltration and exclusion of immune cells. These mechanisms increase the quantity and enhance the antineoplastic effect of cytotoxic T lymphocyte, the main functional immune cells involved in anti-PD-1/PD-L1 immunotherapy, in the TME. Therefore, combining PCSK9 inhibition therapy with anti-PD-1/PD-L1 immunotherapy may provide a novel option for improving antitumor effects and may constitute a promising research direction. This review concentrates on the relationship between PCSK9 and cholesterol metabolism, systematically discusses how PCSK9 inhibition potentiates PD-1/PD-L1 blockade for cancer treatment, and highlights the research directions in this field.

Layered structure oxides have emerged as highly promising cathode materials for lithium-ion batteries. In these cathode materials, volume variation related to anisotropic lattice strain during Li⁺ insertion/extraction, however, can induce critical structural instability and electrochemical degradation upon cycling. Despite extensive research efforts, solving the issues of lattice strain and mechanical fatigue remains a challenge. This perspective aims to establish the “structure–property relationship” between the degradation mechanism of the layered oxide cathode due to lattice strain and the structural evolution during cycling. By addressing these issues, we aim to guide the improvement of electrochemical performance, thereby facilitating the widespread adoption of these materials in future high-energy density lithium-ion batteries.

Colloidal molecules, ordered structures assembled from micro- and nanoparticles, serve as a valuable model for understanding the behavior of real molecules and for constructing materials with tunable properties. In this work, we introduce a universal strategy for assembling colloidal molecules consisting of a central active particle surrounded by several passive particles as ligands. During the assembly process, active particles attract the surrounding passive particles through phoresis and osmosis resulting from the chemical reactions on the surface of the active particles, while passive particles repel each other due to the electric polarization induced by an alternating current (AC) electric field. By carefully selecting particles of varying structures and sizes, we have assembled colloidal molecules of symmetric and asymmetric dimers, trimers, and multimers. Furthermore, the coordination number of these colloidal molecules can be regulated in real time and in situ by tuning the interaction forces between the constituent particles. Brownian dynamics simulations reproduced the formation of the colloidal molecules and validated that the self-assembly arises from chemically induced attraction and electrical dipolar repulsion. This strategy for reconfigurable colloidal assemblies poses the potential for designing adaptive micro-nanomachines.