Following publication of this article, the authors noticed that the WB bands of c-Myc in Figure 7D were inadvertently misplaced [1]. After carefully checking the original data, the authors confirmed the error occurred during figure assembly. This error does not affect the conclusions of this article. The figure has been corrected in the original HTML and PDF, and Fig. 7D is provided below. The authors would like to apologize for any inconvenience caused.
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Making the internet better for AI agents might make it worse for everyone else
Millions of AI agents are descending on a web built for humans. Websites are trying to keep them out, but the arrival of these new visitors could transform the internet.
A New Study Links GLP-1s to a Rare Vision-Loss Condition—Here’s What Doctors Want You to Know
Experts explain the real risk.
Nanopore sequencing of cell-free DNA
Cell-free DNA is generally fragmented and present in low abundance, making its detection and characterization challenging. In this Primer, Korabečná et al. discuss the use of nanopore sequencing for cell-free analysis from blood samples, as well as associated technical challenges.
Light Addresses Single Molecular Qubits
System exploiting organic carbene molecules might be exploited in quantum networks.
Spatial Proteomics for Precision Oncology
Tumors are complex cellular ecosystems in which cancer cell phenotypes, their spatial organization, and their interactions with immune and stromal compartments determine disease progression and therapy response. To resolve this complexity, the use of highly multiplexed Imaging Mass Cytometry™ (IMC™) together with multiomic profiling and artificial intelligence (AI) can identify clinically relevant features of the tumor microenvironment, providing a rich framework for patient stratification and targeted therapy in precision oncology.
In this GEN webinar, Bernd Bodenmiller, PhD (University of Zürich), illustrates this integrated approach through two recent examples. In a study of 323 epithelial ovarian cancers, tumors with more diverse cell phenotypes and spatial organization recurred faster. His lab also identified a therapy-resistant tumor cell phenotype (TUBB3+/pRB+) associated with recurrence and poor response to standard therapy. Spatial transcriptomics and ex vivo drug screening of 3D sphere models and patient samples showed that these cells resist standard-of-care agents but are sensitive to specific inhibitors. In 498 clear cell renal cell carcinomas, the use of AI revealed three survival ecotypes that predict survival better than basic clinical data and molecular stratification models. Each ecotype has its own genomic and metabolic features and is predictive of treatment outcome. Deep learning predicted the ecotypes directly from routine H&E slides, and the findings were validated across five cohorts comprising more than 2,500 patients.
Webinar attendees will learn how integrating spatial single-cell proteomics by IMC with multiomics and AI identifies therapy-resistant cell populations and prognostic tumor ecosystems. This approach provides a detailed framework for patient stratification and targeted therapy in precision oncology.
Antibody-drug conjugates control rhabdomyosarcoma cells in mice
An antibody that recognizes the protein FGFR4 delivers anticancer drugs directly to cancer cells, slowing or stopping tumor growth in mice.
OpenAI’s Greg Brockman Says AI Will Allow Death To Become A Choice, Echoing Elon Musk’s Take That “Longevity Or Semi-Immortality Is An Extremely Solvable Problem”
Elon Musk made the claim in January 2026, then declared in October that “longevity is coming,” a view that OpenAI’s Brockman now echoes.
An AI-native experimental laboratory for autonomous biomolecular operations
China built an AI that runs an entire biology lab on it’s own.
Researchers from Shangha published a paper that feels like a massive leap toward artificial scientists.
They built AutoDNA, an “AI-native experimental laboratory”
Until now, if you asked an AI to design a biology experiment, it could give you a great protocol. But a human still had to walk into a lab, hold the pipettes, run the thermal cyclers, and tweak the process when things inevitably went wrong.
AutoDNA removes the human.
You just type a natural language prompt, and a swarm of specialized AI agents takes over.
Here’s how wild this multi-agent architecture is:
Scientists spot elusive particle decay in search for ‘Zeptoverse’
Scientists have found evidence for a rare particle decay occurring once in 10 billion particles at the LHCb experiment at CERN.