The detection of gravitational waves from extreme-mass-ratio inspirals (EMRIs) in space-based antennas like Taiji and Laser Interferometer Space Antenna promises deep insights into strong-field gravity and black hole physics. However, the complex, highly degenerate, and nonconvex likelihood landscapes characteristic of EMRI parameter spaces pose severe challenges for conventional Markov chain Monte Carlo (MCMC) methods. Under realistic instrumental noise and broad priors, these methods demand impractical computational costs but are prone to becoming trapped in local maxima, leading to biased and unreliable parameter estimates. To address these challenges, we introduce flow-matching MCMC (FM-MCMC), a novel Bayesian framework that integrates continuous normalizing flows (CNFs) with parallel tempering MCMC (PTMCMC). By generating high-likelihood regions via CNFs and refining them through PTMCMC, FM-MCMC enables robust exploration of the nontrivial parameter spaces, achieves orders-of-magnitude improvement in computational efficiency, and, more importantly, ensures statistically unbiased inference. By enabling real-time, unbiased parameter inference, FM-MCMC could unlock the full scientific potential of EMRI observations, and would serve as a scalable pipeline for precision gravitational-wave astronomy.

Organic piezoelectric materials have garnered increasing interest for biomechanical applications; however, their practical appeal has been limited by low piezoelectricity and low mechanical compliance. Recently, liquid–liquid interface polar engineering has emerged as a promising strategy to overcome these limitations. By utilizing polarity asymmetry at the liquid–liquid interface, this strategy enables precise control over molecular assembly and phase separation, thereby inducing high piezoelectric polarization of organic materials while maintaining their intrinsic mechanical compliance. This breakthrough paves the way for developing organic piezoelectric materials that exhibit both high piezoelectricity and high mechanical compliance, advancing their potential in biomechanical sensing, actuating, and energy harvesting.

The ferromagnetic (FM) properties of the van der Waals charge transfer insulator CrGeTe3 provide a promising avenue for concurrently controlling magnetic and electrical characteristics. This enables the potential integration of devices using nanoscale materials. In this research, we have effectively produced highly stable CrGeTe3 nanosheets by utilizing a Cr2Te3 template. Additionally, we show that the magnetic and electrical characteristics of CrGeTe3 single crystals can be continuously adjusted through the application of pressure. Electrical transport measurements reveal that CrGeTe3 transitions from an insulator under ambient conditions to a metallic state at 6.02 GPa. After reaching 25.33 GPa, CrGeTe3 undergoes a phase transition from the FM state to the Néel antiferromagnetic state at 30 K. This transition highlights the important impact of pressure on exchange interactions, corroborating density functional theory calculations. Micromagnetic simulation shows that the high-pressure topological Hall effect above 25.33 GPa originates from the Néel-type skyrmion. The interaction observed between magnetic couplings and high pressure provides crucial insights into the novel topological transport phenomena and their underlying physics, which is valuable for advancing spintronics devices and other emerging electronic technologies.

Aging, caused by a variety of exogenous stimuli and internal factors, leads to a gradual and irreversible decline in the function of the organism. The aging process involves complex gene regulation, in which transcription factors may play a key role as core regulatory elements. In this study, the single-cell transcriptome of skin revealed homeobox C10 (HOXC10) as a core element in the transcription factor regulatory network associated with skin aging. In vivo and vitro, the expression of HOXC10 was down-regulated in senescent fibroblasts and aging tissues, and overexpressed HOXC10 delayed cell senescence and skin aging. Mechanistically, HOXC10 targeted the promoter region of frizzled 6 (FZD6) to reduce its expression and therefore activated the Wnt/β-catenin signaling pathway to delay aging. Finally, by using the Connectivity Map approach, we explored simvastatin as a functional mimic of HOXC10 and demonstrated its antiaging ability in vitro and vivo. In conclusion, our results establish the role of HOXC10/FZD6/Wnt signals in skin aging and identify simvastatin as a potential therapeutic strategy to delay aging.

Aging has important impacts on both the function and structure of the brain, yet the interplay between these changes remains unclear. Here, we present a unified framework including both single-modal and multimodal age predictions using a large UK Biobank dataset (27,793 healthy subjects, 49 to 76 years) to identify and validate brain functional network connectivity (FNC) and gray matter volume (GMV) changes associated with aging, then propose a novel analysis method to reveal various joint aging patterns, and finally investigate the association between joint function–structure changes and cognitive declines. Multimodality outperforms single modality in the age prediction, underscoring the significance of multimodal aging-related changes. Aging primarily induces synergistic changes, with both FNC and GMV decreased in the cerebellum, frontal pole, paracingulate gyrus, and precuneus cortex, indicating consistent degeneration in motor control, sensory processing, and emotional regulation, and contradictory changes with increased FNC magnitude but decreased GMV in the occipital pole, lateral occipital cortex, and frontal pole, acting as a compensatory mechanism as one ages to preserve visual acuity, cognitive ability, and behavioral modulation. Particularly, joint changes, with both FNC and GMV decreased in the crus I cerebellum and the paracingulate gyrus, show a strong Pearson correlation with the reaction time. In summary, our study unveils diverse joint function–structure changes, providing strong evidence for understanding distinct cognitive deteriorations during aging.

Aging is characterized by a gradual decline in the functionality of all the organs and tissues, leading to various diseases. As the global population ages, the urgency to develop effective anti-aging strategies becomes increasingly critical due to the growing severity of associated health problems. Immunotherapy offers novel and promising approaches to combat aging by utilizing approaches including vaccines, antibodies, and cytokines to target specific aging-related molecules and pathways. In this review, we summarize the recent advancements of immunotherapies to eliminate senescence cells and senescence-associated secretory phenotypes (SASPs). Next, we describe immunotherapies against age-related diseases containing neurodegenerative diseases, vascular pathologies, type 2 diabetes (T2D), arthritis, osteoporosis, chronic obstructive pulmonary disease (COPD), fibrosis, skin aging, and cancer, detailing the targets, corresponding manipulations, and clinical trials. Related problems including immunosenescence, serious adverse effects, the duality of function of senescent cells and SASPs, and inherent problems of immunotherapy are also discussed, suggesting directions for improvement. In addition to recent development and challenges in the field, we describe a blueprint of personalized aging immunotherapy by multi-omics, Big Data, artificial intelligence (AI), and nanobots in the future, aiming to inspire the development of novel strategies for healthy aging.

Retinal degenerative disorders pose critical challenges for vision restoration, with traditional prosthetics limited by spectral sensitivity and invasive surgeries. In recent work published in Science, revolutionary tellurium nanowire networks converted broadband visible to near-infrared-II (up to 1,550 nm) light into electrical signals without external bias, restoring functional vision in blind animal models.

Sustainable habitation systems are critical to enabling deep-space exploration on Mars, where challenges such as low gravity, extreme thermal fluctuations, and resource constraints demand advanced structural innovations. This study introduces Zhuque Base, a habitat concept inspired by terrestrial cave-dwelling principles, optimized through finite element analysis via COMSOL Multiphysics. Three arch-based configurations—the eggshell, catenary, and 2-centered arch—were systematically evaluated by parameterizing geometric variables. The study demonstrated that eggshell arches significantly outperformed 2-centered and catenary arches in mechanical properties, reducing vertical displacement of critical points such as sidewalls by 53% and 44%, respectively. In terms of thermal efficiency, the optimal catenary arch showed 5.5% and 6.7% lower heat loss than eggshell and 2-centered arches. Furthermore, the implementation of optimal parameters (span: 3.2 m, height: 1.25 or 1.45 m) limits the peak compressive stress to 195.72 to 203.38 kPa, while the cross-sectional area can be increased by 14% to maximize the available internal space. These findings establish a parameter-driven framework for in situ Mars habitat optimization, emphasizing the trade-off between mechanical robustness and thermal efficiency in extraterrestrial structural design.

Multimodal sentiment analysis (MSA) aims to assess emotional states by integrating information from text, audio, and video. However, the heterogeneous nature of these modalities presents substantial challenges for accurate sentiment prediction. Existing approaches typically align pairs of modalities using attention mechanisms or contrastive learning, which are computationally expensive. Additionally, they often rely on a single granularity of alignment, either by averaging features over all time steps or aligning features at each individual time step. These approaches overlook the fact that emotional expression can vary across individuals and contexts, requiring multiple granularities to capture emotion effectively. To address these challenges, we propose a novel framework, Retrieve, Rank, and Reconstruction with Different Granularities (R3DG). R3DG segments the audio and video modalities into multiple representations at varying granularities based on their temporal durations. It then selects the most relevant representations that align closely with the text modality. To preserve the original information, R3DG reconstructs the audio and video data using the selected representations. Finally, the fused audio, video, and text features are aligned and combined for sentiment prediction, reducing the need for multiple alignment steps. Extensive experiments on 5 benchmark MSA datasets demonstrate that R3DG outperforms existing methods and achieves substantial reductions in computational time. Code is available at https://github.com/YetZzzzzz/R3DG.

Successful restoration of blood supply still follows with serious secondary brain injury in cerebral ischemia reperfusion injury (CIRI). However, conventional management after CIRI exhibits numerous limitations.Transcranial low-intensity ultrasound stimulation (TLUS) has been extensively utilized in the field of neuromodulation owing to its characteristics of zero potential side effects, noninvasiveness, deep tissue penetration, and precise spatial targeting capability. Here, we develop a smart multifunctional ultrasound-responsive delivery system to regulate CIRI. Briefly, curcumin, a well-documented safe neuroprotective monomer derived from traditional Chinese medicine, is encapsulated into self-assembled liposomal nanocarriers (RRP@Lipo-Cur). These nanocarriers are modified with reactive oxygen species- and ultrasound-responsive functional elements, as well as neuron-targeting peptides, enabling targeted accumulation in ischemic penumbra and stimuli-responsive drug release. In the mouse model of middle cerebral artery occlusion/reperfusion (MCAO/r), the synergistic treatment of RRP@Lipo-Cur and TLUS significantly facilitated the polarization of microglia from the M1 to the M2 phenotype via the intracellular mitogen-activated protein kinase (MAPK) and nuclear factor κB signaling (NF-κB) pathways, which effectively promoted the establishment of an anti-inflammatory microenvironment in the ischemic penumbra, thereby providing neuroprotection for the damaged neurons. Furthermore, in comparison to single nanomaterial or TLUS interventions, synergistic treatment can optimally modulate neuroinflammation, safeguard injured neurons, and enhance the recovery of neurological function.