Alpha1 Record ID: 7C425A20
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Pai, V. P.; Traer, J. A.; Sperry, M. M.; Zeng, Y.; Levin, M.
Synthetic living constructs, which lack the long histories of selection in ecological contexts that shape behaviors of conventional organisms, offer an important complement to traditional studies of learning. Could novel biobots exhibit sensing and memory of experiences? Here, we investigated the effects of chemical stimuli on basal Xenobots - autonomously motile entities derived from Xenopus embryonic ectodermal explants (with no additional sculpting or bioengineering). We quantified and characterized the coordinated ciliary activity that generates fluid flow fields guiding the trajectory of Xenobot motion. We also show distinct and specific changes in Xenobot behavior after brief exposure to Xenopus embryonic cell extract and to ATP. These two experiences produced distinct, long-term, stimulus-specific memories, detectable through both transcriptional and physiological signatures. Exposure to specific environmental stimuli induced alterations in the spatiotemporal patterns of calcium signaling across Xenobots. Together, these data lay a foundation for characterizing the capabilities of synthetic cellular collectives to sense and discriminate among stimuli, as well as store functional information in a non-neural context. Understanding behavioral competencies in novel, non-neural systems have broad implications across evolutionary biology, behavioral science, bioengineering, and bio/hybrid robotics.
Imagine a blob of frog skin with no brain that can still "remember" things. These "xenobots" use weird calcium waves to store memories of chemical hits for days. It’s basically a biological hard drive made of lab-grown slime—proving you don't actually need a brain to have a memory.
Sparked massive hype among synthetic biologists and roboticists, posted by Michael Levin (@drmichaellevin) with 21 replies debating non-neural cognition
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CD4⁺ T cells confer transplantable rejuvenation via Rivers of telomeres
Lanna, A.; Valvo, S.; Dustin, M.; Rinaldi, F.
Using a GPT-5-driven autonomous lab to optimize the cost and titer of cell-free protein synthesis
Smith, A. A.; Wong, E. L.; Donovan, R. C.; Chapman, B. A.; Harry, R.; Tirandazi, P.; Kanigowska, P.; Gendreau, E. A.; Dahl, R. H.; Jastrzebski, M.; Cortez, J. E.; Bremner, C. J.; Hemuda, J. C. M.; Dooner, J.; Graves, I.; Karandikar, R.; Lionetti, C.; Christopher, K.; Consiglio, A. L.; Tran, A.; McCusker, W.; Nguyen, D. X.; Nunes da Silva, I. B.; Bautista-Ayala, A. R.; McNerney, M. P.; Atkins, S.; McDuffie, M.; Serber, W.; Barber, B. P.; Thanongsinh, T.; Nesson, A.; Lama, B.; Nichols, B.; LaFrance, C.; Nyima, T.; Byrn, A.; Thornhill, R.; Cai, B.; Ayala-Valdez, L.; Wong, A.; Che, A. J.; Thavaraj
A Single-Cell and Spatial 3D Multi-omic Atlas of Developing Human Basal Ganglia and Inhibitory Neurons
Heffel, M. G.; Xu, H.; Pastor-Alonso, O.; Li, X.; Baig, M. S.; Irfan Ghoor, R.; Li, R.; Kern, C.; Kum, J.; Zhang, Y.; Paino, J.; Tsai, M. J.; Tai, C.-Y.; Tucker, G.; Zhao, Z.; Hou, A.; von Behren, Z.; Bhade, M.; Li, S.; Sandoval, K.; Scholes, J.; Codrea, F.; Calimlim, J.; Liao, E. K.; Leung, G.; Kim, J.; Eskin, E.; Flint, J.; Cotter, J. A.; Pasaniuc, B.; Bintu, B.; Zhu, Q.; Mukamel, E. A.; Ernst, J.; Paredes, M. F.; Luo, C.
Prediction of transformative breakthroughs in biomedical research
Davis, M. T.; Busse, B. L.; Arabi, S.; Meyer, P.; Hoppe, T. A.; Meseroll, R. A.; Hutchins, B. I.; Willis, K. A.; Santangelo, G. M.