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Biology subjects

Ahn, C. H.

Publications and source records attributed to Ahn, C. H..

2 recordsLinked to original sources

Implantable Living Materials Autonomously Deliver Therapeutics from Contained Engineered Bacteria

Microbes are increasingly utilized as living therapeutic vehicles, yet their uncontrolled dissemination in the body has long remained a roadblock to clinical development. Physical containment, while widely used for mammalian cells, remains largely unattainable due to eventual bacteria escape. Here, we present an implantable material platform that encapsulates and confines bacteria, wherein synthetically engineered microbes produce therapeutic payloads from within. To prevent microbial escape, we developed a hydrogel scaffold with dual mechanical features: high stiffness to regulate bacterial proliferation and high toughness to resist material fracture under physiological stress. This design achieved complete bacterial containment for over six months and withstood multiple forms of mechanical loading that otherwise caused catastrophic material failure. By genetically engineering embedded bacteria, we endowed the material with environmental sensing and on-demand therapeutic release capabilities and demonstrated autonomous treatment in a murine prosthetic joint infection model. This multimodal strategy provides a safe and generalizable framework for deploying microbial medicines in vivo and supports their use as autonomous drug depots across a range of disease settings.

bioengineering↗

Translating clinical gene sequencing into a foundational representation of tumor subtype

While gene sequencing is routine in cancer care, translating sequences into treatment decisions remains a challenge. Here we introduce MutationProjector, an AI foundation model that transforms tumor mutation profiles into a compact representation of cancer subtype, with broad implications for diagnosis and therapy. MutationProjector is pre-trained by integrating genomic alterations from >30,000 tumors with extensive molecular knowledge, yielding a model that accurately reconstructs held-out genetic profiles (demonstrating strong generalization) and determines subtype representations from altered molecular pathways (enabling model interpretability). We evaluate MutationProjector in independent tasks related to prediction of immunotherapy response, prediction of chemotherapy response, and classification of metastasis, recording leading performance in all areas. Each task identifies key biomarkers of interest, including KMT2A and KRAS-STK11 alterations which govern immunotherapy response.

systems biology↗