Georgia Tech researchers are exploring new frontiers in neuroethics: to ensure that emerging neurotechnologies can be used for the good of all and to ensure that we won’t inadvertently relinquish crucial human rights which have yet to be legally defined.
As neuroscience and neurotechnology accelerate, Georgia Tech researchers are examining what a neuro-connected future could mean for society and for humanity itself.
Tonsil-derived fibroblasts support B cell activation and proliferation in response to stimulation in ex vivo 3D co-culture. However, when rendered senescent using bleomycin, tonsil-derived fibroblast…
Gliogenesis is a multistep process in which glial progenitors are specified into migrating and proliferating precursor cells that subsequently differentiate into mature astrocytes and oligodendrocytes. How these developmental processes are coordinated to generate the diverse glial lineages across gray matter (GM) and white matter (WM) remains poorly understood. Here, we show that the basic-helix-loop-helix (bHLH) transcription factor ASCL1 serves as a direct mechanistic link between these processes in the dorsal forebrain. Notably, ASCL1 is dynamically expressed in glial progenitor cells, initiating in the ventricular zone (VZ), peaking in the intermediate zone (IZ), but is downregulated once glial cells enter the cortical plate. Lineage tracing of ASCL1+ progenitors demonstrates that they subsequently co-express OLIG2 to generate both astrocytes and oligodendrocytes in an “outside-in” pattern starting from the upper cortex inward to the corpus callosum, the opposite pattern of neurogenesis. ASCL1 gain-of-function combined with OLIG2 loss-of-function reveals that sustained levels of ASCL1 are essential to induce sufficient levels of OLIG2 required to specify oligodendrocyte precursor cell (OPC) fate. Interestingly, a persistent ASCL1 expression also maintains OPCs in an undifferentiated, pre-neoplastic state into postnatal stages, in part by suppressing their differentiation into postmitotic oligodendrocytes. Together, these findings establish ASCL1 as a key regulator of the spatiotemporal order of glial lineage diversity in cortical GM and callosal WM, and highlight ASCL1 dysregulation as an underlying developmental mechanism in the pathogenesis of gliomas.
Significance statement The brain relies on macroglia to form the blood-brain-barrier, insulate nerve fibers, and regulate neuronal signaling; yet how these cell types are generated remains poorly understood. This study shows that the timing and levels of two key regulatory proteins, ASCL1 and OLIG2, function together to guide immature glial cells through distinct stages of development. Notably, we show that brief ASCL1 activity followed by sustained ASCL1 and OLIG2 levels coordinate when glial cells form, the cell type they become, and where they migrate to reside in the cerebral cortex. By revealing the developmental program underlying the generation of glial cell diversity, this study provides a framework for understanding how glial-related neurological diseases and cancer arise in the brain.
Three people going blind got one injection designed to make their old eye cells young again. Eight weeks later, two of them could see better. These are the first human results from age-reversal gene therapy.
In this episode of Health Longevity Secrets, Robert Lufkin MD breaks down the first-in-human data for ER-100, Life Biosciences’ epigenetic reprogramming therapy for glaucoma, presented October 8, 2026. You’ll learn how the OSK (Yamanaka factor) genes reset old retinal cells, what the safety data showed, what a 4-decibel visual field gain really means, how the therapy guards against cancer, and why three patients with no placebo group is a first step, not proof.
CHAPTERS: 00:00 — Introduction: First Human Results of Age Reversal. 00:28 — Recap: Human Age Reversal Has Begun. 00:44 — Glaucoma: Why Lost Vision Can’t Be Restored Today. 00:59 — Harvard 2020: OSK Genes Restore Vision in Old Mice. 01:29 — ER-100 Phase 1 Trial: First Human Results. 02:05 — ER-100 Safety Data Through Day 56 02:28 — 2 of 3 Glaucoma Patients Improved Their Vision. 02:48 — What a 4 dB Visual Field Gain Really Means. 03:42 — Does Cellular Reprogramming Cause Cancer? 04:17 — Will Age Reversal Arrive in Our Lifetime? 04:40 — Beyond Glaucoma: Macular Degeneration and Other Diseases. 04:59 — Honest Caveats: 3 Patients, No Placebo, Learning Effect. 06:04 — The Takeaway: The Race to Reverse Aging.
KEY TAKEAWAYS: • ER-100 is the first therapy built to reverse cellular aging to be tested in people: 3 glaucoma patients, one eye injection at the lowest dose, plus doxycycline as the on-switch for 8 weeks. • Safety was clean through day 56: no dose-limiting toxicities and no serious adverse events attributed to the gene therapy. • 2 of 3 patients improved on the Humphrey visual field test, with at least 28% of tested points improving by more than 4 dB (about 2.5x dimmer light detected). • An independent safety board approved tripling the dose for the next patients. • The therapy leaves out c-Myc, a known cancer gene, and has an off switch; patients will be followed until about 2032. • Big caveats: 3 patients, no placebo, open-label, a noisy test with a known learning effect, and a company presentation rather than a peer-reviewed paper.
STUDIES & SOURCES MENTIONED: • Life Biosciences — First-in-human data from the ongoing Phase 1 trial of ER-100 (Oct 8, 2026) — https://www.lifebiosciences.com/life–… • Lu et al., Nature 2020 — Reprogramming to recover youthful epigenetic information and restore vision — https://pubmed.ncbi.nlm.nih.gov/33268… • ClinicalTrials.gov NCT07290244 — Evaluating ER-100 for Safety in Optic Neuropathies — https://clinicaltrials.gov/study/NCT0… • Gillespie et al., Invest Ophthalmol Vis Sci 2003 — CIGTS visual field test-retest variability — https://pubmed.ncbi.nlm.nih.gov/12766… • Business Insider — Silicon Valley billionaires and cellular reprogramming (Oct 2026) — https://www.businessinsider.com/billi… • Previous episode — Human Age Reversal Has Begun — • Human Age Reversal Has Begun.
This video is for educational purposes only and is not medical advice.
Quantum computing has turned into a phrase that the tech industry will sprinkle on almost anything to help raise funds and generate sales. As a result, there is a tsunami of hype about what quantum computers are going to revolutionise. Join leading quantum computing specialist Scott Aaronson as he challenges the hype and tells us what is really going on.
AI can now imitate the great artists so well that we often can’t tell the difference. But imitation is not creation. Philosopher of aesthetics Derek Matravers argues that a painting without intention is not art at all. When we engage with a painting merely for its beauty, the maker’s identity might not matter. But art does more: it connects us to another mind, to an artist’s deliberate creation of meaning. A human artist stakes something on each decision; an AI stakes nothing, merely averaging out its training data. It might make some beautiful objects, but they are empty of the meaning that we seek in art.
Can AI produce art? The question is not as simple as it might seem. Certainly, AI has played a large part in the production of works of art. The Turkish-American artist, Refik Anadol, has won international acclaim for some spectacular pieces of visual art generated by AI. But was it Anadol who produced these using AI akin to Titian producing his paintings using a paintbrush? Or was it AI who produced these? If consciousness is necessary for creativity, and AI lacks consciousness, then AI lacks creativity. And if creativity is necessary to produce art, then AI could not have produced the works and those works still be art. These and other questions are generating a rich and interesting debate in universities and academic journals across the world.
Where one stands on these matters will depend on where one stands on the broader issues that structure the debate. There is no point in asking whether AI can produce art if one does not know what art is. The same might be true for other concepts that feature in the debate, such as intentions, creativity, meaning and so on. It also helps to know about how the various systems (in particular, the image-generating systems such as DALL-E, Midjourney, and Stable Diffusion) work. I am going to start at a rather more practical level. AI can produce works that have the appearance of works of art in all media. It can produce complex narrative works, complex musical works, and complex images. Judged purely on qualities associated with the medium (say, narrative, musical, or visual complexity) some of these works are above the quality most of us could achieve if we tried it ourselves.
You want to reprogram a cell to heal a disease, but you don’t know what instructions it has already received. Throughout their lives, cells constantly receive chemical signals from their environment that tell them what to do and what to become. If scientists want to manipulate these cells for medical treatments, they first need to decode their “signal history.” However, reading this history inside living, developing tissues has been incredibly difficult—until now. https://www.nature.com/articles/s41592-026-03213-8
To solve this, researchers created a clever two-step workaround. First, in the lab, they exposed human stem cells to thousands of different chemical signals, creating a massive “dictionary” of how cells physically react to specific instructions. Next, they trained an artificial intelligence program named IRIS to memorize this dictionary, teaching it to recognize the unique “fingerprints” that different signals leave behind on a cell.
Once IRIS was trained, the researchers let it act as a detective on real, living mouse embryos. By looking at the current state of the embryo’s single cells, IRIS successfully reconstructed their past. It figured out exactly which chemical signals the cells had experienced to become the specific types they are today, revealing hidden differences between seemingly identical cells and tracing the exact chemical journey cells take as they develop.
Ultimately, this breakthrough reveals that cells across different types share a common, universal language of chemical signals. By giving scientists a scalable, highly accurate tool to map out how cells communicate and develop in the living body, this technology paves the way for designing highly targeted medical therapies and precisely engineering cell behavior.
IRIS learns conserved signaling representations from in vitro perturbation data to reconstruct signaling states and histories across diverse in vivo cellular contexts.
