Thermoelectric (TE) materials have garnered widespread research interest owing to their capability for direct heat-to-electricity conversion. Binary indium-based chalcogenides (In–X, X = Te, Se, S) stand out in inorganic materials by virtue of their relatively low thermal conductivity. For example, In₄Se_2.35 shows a low thermal conductivity of 0.74 W m⁻¹ K⁻¹ and an impressive zT value of 1.48 along the b–c plane at 705 K, as a result of structural anisotropy. Here, we review the structural features and recent research progress in the TE field for In–X materials. It begins by presenting the characteristics of crystal structure, electronic band structure, and phonon dispersion, aiming to microscopically understand the similarity/dissimilarity among these In–X compounds, notably the role of unconventional bonds (such as In–In) in modulating the band structures and lattice vibrations. Furthermore, TE optimization strategies of such materials were classified and discussed, including defect engineering, crystal orientation engineering, nanostructuring, and grain size engineering. The final section provides an overview of recent progress in optimizing TE properties of indium tellurides, indium selenides, and indium sulfides. An outlook is also presented on the major challenges and opportunities associated with these material systems for future TE applications. This Review is expected to provide critical insights into the development of new strategies to design binary indium-based chalcogenides as promising TE materials in the future.

Ultrasound localization microscopy (ULM) is a novel imaging technique that overcomes the diffraction limit to achieve super-resolution imaging at the 10-μm scale. Despite its remarkable progress, challenges persist in enhancing the precision of microbubble tracking and fulfilling the requirements for high frame rates in practical circumstances, especially in moving organs. To address these issues, an enhanced ULM approach (shorten as vc-Kalman) integrating rapid motion compensation was developed to achieve excellent image quality. Unlike traditional methods relying on observed bubble positions, the proposed algorithm combined statistical information derived from historical data with Kalman-filter-predicted positions to enable more accurate bubble localization. Meanwhile, microbubble brightness in adjacent frames was incorporated as multidimensional feature to further improve the matching efficacy. Furthermore, velocity constraint was applied to minimize possible erroneous traces and enhance the contrast-to-noise ratio of ULM images, while ensuring the continuity of vascular reconstruction and the accuracy of the blood flow analysis to generate a reduced normalized root mean square error in velocity estimation, even at a relatively low frame rate of 146 Hz. More important, to effectively suppress the impact of physiological movements in moving organs like kidneys, this algorithm fulfilled subpixel displacement vector identification through parabolic fitting and expedited motion compensation via dynamic programming-based cross-correlation search. The results indicated that this advanced vc-Kalman method substantially boosted both the robustness and accuracy of ULM imaging, thereby opening more opportunities for clinical applications of super-resolution ULM technology.

In heavy-ion collisions at relativistic energies, the incident nuclei travel at nearly the speed of light. These collisions deposit kinetic energy into the overlap region and create a high-temperature environment where hadrons “melt” into deconfined quarks and gluons. The spectator nucleons, which do not undergo scatterings, generate an ultraintense electromagnetic field—on the order of 10¹⁸ G at the Relativistic Heavy Ion Collider and 10¹⁹ G at the Large Hadron Collider. These powerful electromagnetic fields have a substantial impact on the produced particles, not only complicating the study of particle interactions but also inducing novel physical phenomena. To explore the nature of these fields and their interactions with deconfined quarks, we provide a detailed overview, encompassing theoretical estimations of their generation and evolution, as well as experimental efforts to detect them. We also provide physical interpretations of the discovered results and discuss potential directions for future investigations.

Ferroptosis has promising potential for augmenting antitumor effects, but monotherapy with ferroptosis inducers in vivo has been reported to have limited efficacy in tumor management. The development of synergistic strategies with targeted capabilities is crucial for enhancing the antitumor efficacy of ferroptosis inducers. In this study, we designed and characterized a novel self-assembled nanomedicine by mixing ferrous ions (Fe²⁺) and epigallocatechin gallate (EGCG) in a controllable manner and encapsulating the ferroptosis inducer RSL3, named Fe-EGCG@RSL3. This multifunctional nanomedicine effectively induces ferroptosis and growth inhibition in bladder cancer cells and patient-derived organoids. In vivo, Fe-EGCG@RSL3 was enriched in the subcutaneous tumors of allogenic and xenograft mouse models, thereby substantially overcoming RSL3 resistance. Intravesical instillation of Fe-EGCG@RSL3 controls orthotopic bladder tumor progression. Furthermore, nanomedicine potentiates the therapeutic effect of anti-programmed cell death protein 1 (PD1) immunotherapy by increasing the cytotoxicity of CD8⁺ T cells to cancer cells and modulating the proportions of both T-cell and myeloid cell subpopulations within the tumor immune microenvironment. Overall, Fe-EGCG@RSL3 has dual functions as a multifaceted nanomedicine that integrates ferroptosis induction with immunomodulation, offering a novel and clinically translatable strategy for bladder cancer therapy.

There is remarkable demand for bio-based specialty resins such as benzoxazine thermosets, but they are brittle and difficult to process. This study reports the synthesis of a processable bio-based polybenzoxazine resin via the copolymerization of rigid and soft benzoxazine dimers synthesized from bio-based phenols. The polybenzoxazine copolymer demonstrated excellent thermoplasticity and a tunable toughness in the range of 9.0 to 24.1 MJ/m³. The incorporation of soft segments and dynamic ester bonds in the polybenzoxazine notably improved its thermoplasticity compared with traditional thermosetting benzoxazine resins. The polybenzoxazine copolymer also demonstrated a dielectric constant of 2.99 and a dielectric loss of 0.019 at 3 GHz, as well as a high breakdown voltage of 27.2 kV/mm. This research highlights the promising mechanical and thermal properties of the resulting bio-based resin, as well as its tunable dielectric properties, making it a competitive candidate for various high-performance applications in the polymer industry.

The first challenge in building a living robotic system inspired by life evolution is how to replicate the original form of life—the cell. However, current microrobots mimic cell motion control but fail to replicate the functional biological activities of cellular systems. Here, we propose a strategy that programs microparticle swarms encapsulated in droplets at an air/liquid interface to create cell-mimetic droplet microrobots with vitality by employing alternating magnetic fields. Through the design of algorithms and spontaneous interface waves, our collective system embodies reversible transitions between gas, chain, array, and disk-like collective modes, and emulates various complex activities of living cells in nature, including division and exocytosis. Based on these 2 capabilities learned from living cells, the cell-mimetic microrobots navigate the bile duct to the gallbladder under the guidance and control of magnetic fields, completing the drug release task. This cell-mimetic microrobots may provide a fundamental understanding of cellular life and pave the way for the construction of artificial living systems. Furthermore, they hold substantial potential for medical and environmental applications.

Understanding the impacts of anthropogenic activities on groundwater is crucial for its management and utilization. However, predicting anthropogenic impacts on groundwater remains challenging due to their complexity. As any anthropogenic activity generates carbon emissions, we employed carbon emissions to characterize the intensity of anthropogenic activities to predict groundwater storage variations. Carbon emission–groundwater machine learning models indicate that groundwater storage will increase in Rhine Valley (7.3% ± 1.9%), the Great Lakes Basin (6.7% ± 4.3%), and Pearl River catchments (1.8% ± 1.5%) in the next 3 decades, but it will continue to decline in Yangtze River catchments (−13.7% ± 3.4%), with R² ranging from 0.916 to 0.995. Furthermore, the existing groundwater protection measures of Yangtze River catchments will not be sufficient to compensate for future declines in groundwater storage caused by anthropogenic activities (5.9% ± 4% decrease in 2050), indicating the necessity of more effective measures. This study developed a method to predict the impacts of anthropogenic activities on groundwater, thus overcoming an important obstacle in predicting groundwater behavior, which is crucial for the utilization and management of groundwater resources. The methodology developed in this study for predicting the impacts of anthropogenic activities on groundwater will raise awareness of the link between anthropogenic activities and groundwater and lead to in-depth research on anthropogenically driven groundwater prediction studies. This will overcome substantial barriers to predicting groundwater behavior, which is critical for groundwater resource use and management.

Advancing targeted cancer immunotherapy is pivotal for overcoming distant metastasis and tumor relapse. The recent study in Nature Cancer by Sanlorenzo et al. demonstrates a breakthrough strategy combining systemic type I interferon with topical Toll-like receptor 7/8 agonists, where oral imiquimod primes plasmacytoid dendritic cells (DCs) to produce type I interferon, thereby sensitizing conventional DCs in tumors to local Toll-like receptor 7 activation. This approach triggers c-Jun-dependent IL-12 production and CCL2-mediated plasmacytoid DC recruitment, enabling localized and systemic tumor suppression. Importantly, the therapy synergizes with PD-1 blockade to prevent recurrence, representing a significant advance in DC-targeted cancer immunotherapy.

Opioid use disorders (OUDs) pose a substantial global health burden, with methadone maintenance treatment (MMT) widely adopted as an intervention; however, MMT is associated with immunosuppression, metabolic disturbances, and dysbiosis of the gut microbiota. Despite the potential of acupuncture in reducing methadone dosages and opioid addiction, the underlying biological mechanisms remain unclear. Therefore, we aimed to integrate clinical trial data with multi-omics analysis, including single-cell sequencing, transcriptomics, metabolomics, and metagenomics, to evaluate the effects of acupuncture in patients undergoing MMT. We collected peripheral blood mononuclear cells, plasma, and fecal samples from 48 MMT participants in a randomized, placebo-controlled trial. Participants were divided into acupuncture (n = 25) and sham-acupuncture (n = 23) groups. After 8 weeks of intervention, 84% of patients in the acupuncture group achieved ≥20% reduction in methadone dosage, compared to 39% in the sham-acupuncture group (P < 0.01). Our findings revealed that acupuncture may activate the defense response to viruses, with altered immune cell functions in classical monocytes correlating with clinical responses to reduced methadone doses. Acupuncture might ameliorate intestinal microbial disruptions caused by OUD by up-regulating Bilophila and modulating bile acid metabolism. Furthermore, acupuncture up-regulated galectin-9 (LGALS9)-mediated intercellular communication between classical monocytes and other immune subsets. To further validate the mechanistic link between bile acid metabolism and immune regulation, we conducted in vitro experiments using THP-1 monocytes treated with cholic acid. The results showed that bile acid exposure suppressed galectin-9 and IFN-γ expression, while low-dose bile acid (simulating acupuncture effects) partially reversed this effect. These findings support a bile acid–galectin–interferon axis that may be modulated by acupuncture in OUD. Collectively, our results provide clinical and mechanistic evidence supporting acupuncture as a potential adjunct therapy to mitigate the adverse effects of long-term opioid use.

Advanced haptic feedback interfaces are essential for human–machine interaction, particularly in assistive technologies that offer versatile commands, simplify navigation, and enhance emotional interactions for individuals with visual and hearing impairments. Current systems, primarily reliant on Braille and mechanical announcements, fall short of addressing these needs. Existing haptic interfaces, while providing various haptic feedback modes, still face challenges including rigid, strong current, or high-voltage stimulation, limiting their applicability and long-term safety for widespread use. Here, the work demonstrates a flexible, integrable, and programmable haptic interface based on elastomer actuators that utilize a unique forming process to create customized local stiffness in a multilayer elastomer by varying the cross-linking density of elastomers. Complemented by tailored software, the system delivers a 4-dimensional haptic experience within a safe voltage of less than 50 V and a frequency range of 50 to 450 Hz, enabling high-fidelity emotional and navigational feedback. Demonstrations of this system achieve an average accuracy rate of 64.6% in emotional interactions without prior training, improving to 95.8% with learning mode, along with an average accuracy rate of 94.2% for 9 directional commands in navigation interactions.