Science Bulletin最新文献

Protecting, managing, and restoring freshwater ecosystems in the Anthropocene is essential to tackling the triple planetary crises of biodiversity loss, pollution, and climate change. However, conventional restoration frameworks often struggle to account for the rapid and nonlinear dynamics that characterize ecological transitions today. In this review, we synthesize emerging insights from freshwater restoration research and propose a novel bivariate framework that integrates both the rate and magnitude of change from a long-term, evolutionary perspective. By examining multidecadal to centennial trajectories and dynamics using paleoenvironmental records, our framework offers a more nuanced classification of ecosystem status along a degradation continuum. Specifically, we categorize four ecosystem types based on their state (from minimally disturbed to highly degraded) and their rate of change (from slow to fast). Each type is associated with distinct system dynamics, restoration potentials, and strategic considerations. To demonstrate practical utility, we apply the framework to a representative Anthropocene lake undergoing severe ecological degradation. While centered on freshwater systems, the framework offers broader relevance for understanding and guiding restoration in other ecosystem types. We conclude by identifying key knowledge gaps and future research directions needed to enhance ecosystem resilience and inform adaptive management in a rapidly changing world.

We report the high-purity identification of cosmic-ray (CR) protons and a precise measurement of their energy spectrum from 0.15 to 12 PeV using the Large High Altitude Air Shower Observatory (LHAASO). Abundant event statistics, combined with the simultaneous detection of electrons/photons, muons, and Cherenkov light in air showers, enable spectroscopic measurements with statistical and systematic precision comparable to satellite data at lower energies. The proton spectrum shows significant hardening relative to low-energy extrapolations, culminating at 3 PeV, followed by sharp softening. This distinct spectral structure closely aligned with the knee in the all-particle spectrum points to the emergence of a new CR component at PeV energies that might be linked to the dozens of PeVatrons recently discovered by LHAASO, and offers crucial clues to the origin of Galactic cosmic rays.

ST-elevation myocardial infarction (STEMI) remains a leading cause of cardiovascular morbidity and mortality worldwide, and accurate early risk stratification is critical for implementing precision therapies in clinical practice. However, existing clinical risk scores and manually derived imaging biomarkers have limited accuracy in predicting post-STEMI outcomes. To address this gap, we developed DeepSTEMI, an end-to-end deep learning system that integrates multi-sequence cardiac magnetic resonance (CMR) images with clinical parameters for predicting 2-year major adverse cardiovascular events (MACE). The system comprised two key algorithmic modules: a U-Net module that automatically segments heart regions from raw CMR images and a Transformer-based module that predicted future cardiovascular events. DeepSTEMI was developed using a multicenter dataset (n = 610; 20,618 images) from STEMI patients enrolled in the EARL-MYO-CMR registry (NCT03768453), with external validation performed in 334 patients (9944 images) from three independent cardiac centers. In external validation, DeepSTEMI demonstrated superior predictive performance compared to conventional clinical risk scores and manual CMR parameters (AUC 0.894, 95% CI: 0.823-0.965; overall accuracy 94.3%). The model identified high-risk patients who exhibited a 20-fold MACE risk compared to low-risk counterparts (HR 20.43, log-rank P < 0.001). SHapley Additive exPlanations (SHAP) analysis revealed that DeepSTEMI's predictive power stems from clinical-imaging synergy, enabling it to capture complex pathological patterns. DeepSTEMI achieved consistently superior performance over the Eitel score across all subgroups, with the greatest benefit observed in women (NRI 1.597) and in patients imaged 4-7 d post-STEMI (NRI 1.442). Overall, DeepSTEMI serves as an automated, scalable, and interpretable clinical copilot, which advances post-STEMI risk stratification beyond the limitations of current paradigms.

Fast radio bursts (FRBs) remain one of the most puzzling astrophysical phenomena. While most FRBs are detected only once or sporadically, we present the identification of FRB 20190520B as the first persistently active source over a continuous span of ∼4 years. This rare long-term activity enabled a detailed investigation of its dispersion measure (DM) evolution. We also report that FRB 20190520B exhibits a substantial decrease in DM at a global rate of (-12.4±0.3) pc cm^-3yr^-1, exceeding previous FRB's DM variation measurements by a factor of three and surpassing those observed in pulsars by orders of magnitude. The magnitude and consistency of the DM evolution, along with a high host DM contribution, strongly indicate that the source resides in a dense, expanding ionized medium, likely a young supernova remnant (SNR).

Glacial lake outburst floods (GLOFs) are among the most severe cryospheric hazards in the Himalaya. While previous studies have primarily focused on the characteristics and causes of GLOFs, strategies for mitigating their disaster impacts remain underexplored. This study introduces China's Glacial Lake Management System (GLMS) and evaluates its potential for regional replication in reducing damage caused by GLOFs. We find that while GLOF frequency shows a statistically insignificant decrease from 1990 to 2023, downstream damage has intensified, yet appears relatively mitigated within China across the Himalaya following the implementation of the GLMS. Further hydrodynamic modelling suggests that glacial lakes will continue to expand in the future, with total growth expected to triple relative to the 2000-2020 period. These expansions could increase GLOF exposure by over 27% for high-risk lakes and by more than 40% in regions outside China without targeted interventions. However, implementing GLMS engineering measures could reduce the intensity of future floods by 24%, with even greater reductions outside China-29% compared to 21% within China. Building on China's lake management experience and recognizing the transboundary nature of GLOFs, the comprehensive framework we propose for region-wide glacial lake risk reduction across the Himalaya integrates engineering measures, early warning systems, and community responses. This framework addresses the urgent need for proactive and coordinated mitigation strategies in densely populated high-mountain regions.

Mutations in cytoplasmic DNA-degrading enzymes can lead to the accumulation of cytoplasmic DNA (cytoDNA), which excessively activates DNA-sensing pathways and exacerbates inflammatory aging. Reducing cytoDNA levels to suppress DNA-sensing mechanisms is therefore critical for treating elderly-onset rheumatoid arthritis (EORA). In this study, we constructed Trex1 mRNA loaded lipid nanoparticles (LNPs) via microfluidics and prepared DNase I loaded polydopamine (PDA) nanoparticles through oxidative polymerization. These two components were co-encapsulated into methacrylated hyaluronic acid (HAMA) microspheres using microfluidic photopolymerization. The LNPs incorporate cationic lipids to facilitate mRNA loading and promote endosomal escape, enabling efficient translation of TREX1 and subsequent recognition and degradation of cytoDNA. Meanwhile, cationic mesoporous polydopamine electrostatically adsorbs and degrades extracellular DNA. The microspheres function as a reservoir for sustained nanoparticles release, enabling synergistic inhibition of DNA sensing pathways. This microsphere based vaccine upregulates TREX1 expression in antigen presenting cells (APCs) and reduces cytoDNA levels, thereby suppressing overactivation of the cGAS-STING signaling axis and promoting immune tolerance. It also attenuates the differentiation of CD4⁺ T cells into Th1, Th2, Th17, and Treg subsets. In an aged rat model of rheumatoid arthritis, vaccination significantly attenuated soft tissue edema, synovial inflammation, and articular cartilage and bone destruction. By clearing excess cytoDNA and restraining DNA-sensing hyperactivation, this vaccine induces cellular immune tolerance and represents a promising therapeutic strategy for rheumatoid arthritis in the elderly.