Circulating concentrations of low-density lipoprotein cholesterol (LDL-C) and triglyceride-rich lipoproteins are leading risk factors for atherosclerotic cardiovascular disease1. Despite several approved lipid-lowering medications, most patients fail to achieve target lipid levels under the chronic care treatment model2,3. Here, we describe a potential single-course treatment in which an infusion of guide RNA and mRNA encoding a CRISPR adenine base editor—encapsulated within a GalNAc–lipid nanoparticle—leads to durable, liver-selective inactivation of angiopoietin-like 3 (ANGPTL3), a known driver of increased LDL-C and triglyceride concentrations. Analyses in human liver cells in vitro confirmed that the base editor introduces a DNA base-pair change at the target ANGPTL3 locus with no detectable off-target editing at any of approximately 3000 candidate sites or treatment-related structural variants. Targeted ANGPTL3 inactivation in nonhuman primates was well-tolerated and led to a > 90% mean reduction in circulating ANGPTL3 protein, with durability confirmed out to 3 years following a single dose. In mouse and nonhuman primate models of hyperlipidemia, gene inactivation was associated with reductions of approximately 40 to 50% in LDL-C and 50 to 70% in triglycerides. These results provided the scientific foundation for initiation of an ongoing first-in-human clinical trial in patients with refractory hyperlipidemia syndromes.
The Intergovernmental Panel on Climate Change recommended 1.5°C carbon reduction target, requiring powerful enforcement from major economies. China, the largest CO2 emitter, is facing severe difficulties for both variable renewable accommodation and decarbonization of hard-to-abate sectors. Hydrogen, as a critical green energy carrier bridging renewable to end-users, faces significant obstacles in real-world deployment such as costly transportation, storage and fuel-cell adoption. Affordable and coordinated hydrogen deployment plan to accelerate the carbon-neutral transition remains ambiguous. Here, we present cost-effective carbon-neutral transition pathways for entire energy economy of China emphasizing the significant role of hydrogen and derivatives as green energy carriers, considering high-resolution renewable deployments, hourly power system operations in 29 provincial regions, over 46,000 rail/road/marine/pipeline transfer routing of hydrogen derivatives, process-level fuel adoption strategies in all end-use sectors. Results show that incorporating hydrogen and derivatives can reduce the overall transition cost by $ 10.7 trillion compared with renewable and electrification pathways, achieving negative carbon abatement costs ($-6.15/ton), eliminating external oil import expenses, equivalent to over 50% of China trade surplus (2023 level)1, significantly boosting employment and economic growth. Hydrogen derivative based transition pathway offers a vital direction for affordable and secure decarbonization for China and beyond under volatile international energy markets.
Glioblastoma is incurable and resistant to therapy despite genomic stability under treatment1–8, suggesting that non-genetic cellular plasticity is a central driver of progression. Whether such plasticity reflects stochastic state switching or is governed by predictable gene regulation has remained unclear9–13. Here we introduce scDORI (single-cell deep multi-omic regulatory inference)—a deep-learning framework that infers enhancer-driven gene-regulatory networks at single-cell resolution—and apply it to single-nucleus multiome profiles of more than one million cells from primary glioblastomas. Integrating computational inference with systematic perturbation screens across patient-derived models, we show that a structured regulatory program with an asymmetric interplay of activators and repressors governs cellular plasticity in glioblastoma. The resulting transition landscape is hierarchical and predictable, but permits cross-lineage trajectories that are absent from normal neurodevelopment. Within this landscape, low-plasticity states such as the neuronal-like state are not stable differentiation end points but actively maintained configurations, stabilized by a network of safeguard repressors that silence alternative fates. We identify MYT1L as the dominant member of this network, and show that it binds to and represses master regulators of every alternative state to consolidate neuronal-like identity. MYT1L restricted plasticity even under standard-of-care therapy and suppressed tumour growth and invasion in vivo. Conversely, loss of MYT1L reactivated plasticity and accelerated malignant features, indicating that low-plasticity identity requires continuous repression. These findings reframe malignant cell state stability as a balance between activation and continuous repression, and nominate safeguard repressors as candidate therapeutic targets that are distinct from differentiation-inducing activators, with potential relevance across cancers in which phenotypic switching drives therapy resistance. Multi-omic analyses of cells from patients with glioblastoma (GB) provide insight into the role of non-genetic cellular plasticity in disease progression, showing that state stability in GB cells is controlled by a network of interacting activators and repressors.
