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Charge-switching ionizable lipids lower the toxicity of lipid nanoparticles

Nature Nanotechnology, Published online: 08 September 2026; doi:10.1038/s41565-026-02262-6

Charge-switching S-lipids generate S-lipid nanoparticles that are neutral or negative at physiological pH but become cationic in acidic endosomes, enabling nucleic acid delivery with reduced inflammation compared with conventional LNPs.
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Advances in understanding the mechanisms underlying acquired resistance to third-generation tyrosine kinase inhibitors in non-small cell lung cancer

Front Cell Dev Biol. 2026 Aug 24;14:1867246. doi: 10.3389/fcell.2026.1867246. eCollection 2026.

ABSTRACT

Acquired resistance to third-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) presents a formidable challenge in the treatment of non-small cell lung cancer (NSCLC). Despite the remarkable efficacy of these agents, resistance inevitably develops, typically within approximately 10 months of treatment initiation. This review elucidates the multifaceted mechanisms driving this resistance, broadly categorized into on-target EGFR-dependent alterations and off-target EGFR-independent bypass pathway activations. On-target mechanisms include the emergence of tertiary EGFR mutations, most notably C797S, which disrupts TKI binding. Off-target mechanisms encompass the activation of alternative signaling pathways such as MET and HER2/HER3 amplification, as well as histological transformations and complex changes within the tumor microenvironment. Furthermore, recent discoveries highlight the role of epigenetic dysregulation and metabolic reprogramming in fostering resistance. To counter this pervasive adaptability, advanced diagnostic methodologies, including liquid biopsy and high-resolution omics technologies, are crucial for real-time molecular profiling. The field is actively exploring emerging combination therapeutic strategies to circumvent these diverse resistance pathways, aiming to prolong clinical benefits and improve patient outcomes. The persistent emergence of resistance underscores that current targeted therapies, while revolutionary, are primarily disease-modifying rather than curative, necessitating continuous innovation to overcome the inherent biological challenge of tumor adaptability and heterogeneity.

PMID:42707604 | PMC:PMC13547778 | DOI:10.3389/fcell.2026.1867246

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Author Correction: Inactivating <i>SnRK1Ξ²1A</i> promotes broad-spectrum disease resistance in rice

Nature, Published online: 20 May 2026; doi:10.1038/s41586-026-10659-5

Author Correction: Inactivating SnRK1Ξ²1A promotes broad-spectrum disease resistance in rice
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DriveDreamer-Policy: A Geometry-Grounded World-Action Model for Unified Generation and Planning

arXiv:2604.01765v1 Announce Type: cross Abstract: Recently, world-action models (WAM) have emerged to bridge vision-language-action (VLA) models and world models, unifying their reasoning and instruction-following capabilities and spatio-temporal world modeling. However, existing WAM approaches often focus on modeling 2D appearance or latent representations, with limited geometric grounding-an essential element for embodied systems operating in the physical world. We present DriveDreamer-Policy, a unified driving world-action model that integrates depth generation, future video generation, and motion planning within a single modular architecture. The model employs a large language model to process language instructions, multi-view images, and actions, followed by three lightweight generators that produce depth, future video, and actions. By learning a geometry-aware world representation and using it to guide both future prediction and planning within a unified framework, the proposed model produces more coherent imagined futures and more informed driving actions, while maintaining modularity and controllable latency. Experiments on the Navsim v1 and v2 benchmarks demonstrate that DriveDreamer-Policy achieves strong performance on both closed-loop planning and world generation tasks. In particular, our model reaches 89.2 PDMS on Navsim v1 and 88.7 EPDMS on Navsim v2, outperforming existing world-model-based approaches while producing higher-quality future video and depth predictions. Ablation studies further show that explicit depth learning provides complementary benefits to video imagination and improves planning robustness.
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Inactivating <i>SnRK1Ξ²1A</i> promotes broad-spectrum disease resistance in rice

Nature, Published online: 25 March 2026; doi:10.1038/s41586-026-10273-5

SnRK1Ξ²1A in rice promotes susceptibility to multiple fungal diseases, and disrupting this infection-inducible gene confers broad-spectrum resistance without compromising growth or yield under normal field conditions.
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