Nature Biomedical Engineering

Nature Biomedical Engineering, Published online: 30 April 2026; doi:10.1038/s41551-026-01677-9 STRAIGHT-IN Dual enables allele-specific integration of two DNA constructs into hiPSCs within 1 week. The system was used to programme hiPSCs into distinct cell types and for tunable expression of different transcription factors within the same cell.

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Nature Biomedical Engineering, Published online: 01 May 2026; doi:10.1038/s41551-026-01653-3 GSCo is a Generalist–Specialist Collaboration that combines the generalizability of generalist foundation models with the domain-specific benefits of specialist models. GSCo remains efficient and scalable while excelling at diverse medical tasks.

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Nature Biomedical Engineering, Published online: 24 April 2026; doi:10.1038/s41551-026-01667-x DeepDrugDiscovery is an AI-powered screening platform incorporating ADMET and blood–brain barrier penetrability predictions to successfully identify mTOR-independent autophagy enhancers that can cross the blood–brain barrier for Alzheimer’s disease therapy.

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Nature Biomedical Engineering, Published online: 27 April 2026; doi:10.1038/s41551-026-01664-0 Embedding cortical geometric eigenmodes into the EEG/MEG inverse problem enables precise, biologically grounded reconstructions of whole-brain activity, enhancing mapping of dynamics, connectivity and clinical targets.

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Nature Biomedical Engineering, Published online: 24 April 2026; doi:10.1038/s41551-026-01662-2 The OCTCube models integrate optical coherence tomography and other imaging modalities to achieve state-of-the-art performance in predicting retinal diseases with strong generalizability across cohorts, devices and modalities.

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Nature Biomedical Engineering, Published online: 05 May 2026; doi:10.1038/s41551-026-01672-0 A transferrin receptor-associating polyplex formed by complexing mRNA with modified polyethylenimine enables monocyte trafficking and lymph node targeting for potent and selective cancer vaccination.

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Nature Biomedical Engineering, Published online: 26 March 2026; doi:10.1038/s41551-026-01638-2 A video-based deep-learning system was trained to understand the spectrum of human cardiovascular disease by the self-supervised method of contrastive learning, using pairs of cardiac MRI scans and their corresponding text reports that are generated as part of routine clinical practice.

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Nature Biomedical Engineering, Published online: 25 March 2026; doi:10.1038/s41551-026-01637-3 A transformer-based vision system for cardiac MRI offers a generalizable and data-efficient system for diverse tasks in cardiology, offering clear advantages for contextualizing human cardiovascular disease and diagnosing disease.

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Nature Biomedical Engineering, Published online: 31 March 2026; doi:10.1038/s41551-026-01642-6 A multiplexed RNA detection method exploits crRNA-dependent variability in Cas13a activity on RNA targets for kinetic barcoding and can be used to distinguish among SARS-CoV-2 variants in clinical samples.

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Nature Biomedical Engineering, Published online: 30 March 2026; doi:10.1038/s41551-026-01634-6 BioMedAgent is a self-evolving LLM multi-agent framework that learns to use various bioinformatics tools and chain them into executable workflows for autonomously carrying out diverse biomedical data tasks initiated by natural-language prompts.

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Nature Biomedical Engineering, Published online: 07 April 2026; doi:10.1038/s41551-026-01639-1 BUSGen is a foundation generative model designed for analysing breast ultrasound images that supports diverse tasks and improves breast cancer screening, diagnosis and prognosis.

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Nature Biomedical Engineering, Published online: 07 April 2026; doi:10.1038/s41551-026-01650-6 Prime editing using non-canonical prime editing guide RNAs, where the reverse transcription template and primer binding site is integrated within the single guide RNA loops rather than attached to the 3′ ends of CRISPR–Cas guide RNAs, increases editing efficiency.

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Nature Biomedical Engineering, Published online: 06 April 2026; doi:10.1038/s41551-026-01647-1 A large-scale prime editing study elucidates the functional roles of almost all possible single amino acid variants of the ligand-binding domain of the androgen receptor and has important implications in prostate cancer treatment.

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