Windows into the past: Genetic analysis of Deep Maniot Greeks reveals a unique genetic time capsule in the Balkans
Peer-Reviewed Publication
This month, we’re focusing on artificial intelligence (AI), a topic that continues to capture attention everywhere. Here, you’ll find the latest research news, insights, and discoveries shaping how AI is being developed and used across the world.
Updates every hour. Last Updated: 7-May-2026 05:16 ET (7-May-2026 09:16 GMT/UTC)
A new genetic study has revealed that the people of Deep Mani, who inhabit one of the remotest regions of mainland Greece, represent one of the most genetically distinctive populations in Europe, shaped by more than a millennium of isolation. The findings, published today (4 February) in Communications Biology, reveal that many lineages can be traced back to the Bronze Age, Iron Age and Roman period of Greece.
Researchers at the Technion – Israel Institute of Technology, in collaboration with MIT, Harvard University, Johns Hopkins University, and the University of Massachusetts, have developed a self-regulating, implantable “living” technology that could one day eliminate the need for daily insulin injections in people with diabetes.
Led by Assistant Professor Shady Farah of the Technion’s Faculty of Chemical Engineering, the study presents a cell-based implant that functions as an autonomous artificial pancreas. Once implanted, the system continuously senses blood-glucose levels, produces insulin within the implant, and releases precisely the amount needed—without external pumps, injections, or patient intervention.
A key innovation is a novel “crystalline shield” that protects the implant from immune rejection, allowing it to function reliably for years. The technology has demonstrated effective glucose regulation in mice and long-term cell viability in non-human primates.
Beyond diabetes, the platform may be adapted for treating other chronic conditions requiring continuous delivery of biological therapeutics, potentially transforming long-term disease management.
Electrocatalysis sits at the heart of clean hydrogen production, fuel cells, and carbon dioxide conversion, yet progress toward scalable, high-performance catalysts has remained frustratingly slow. A growing body of research now suggests that artificial intelligence (AI) may be key to breaking this bottleneck—but only if it is used wisely. By reviewing three decades of AI applications in electrocatalysis, researchers reveal how the field has shifted from isolated data analysis toward end-to-end, data-driven discovery. The work highlights a critical turning point: AI is no longer just accelerating experiments, but beginning to reshape how electrocatalysts are designed, evaluated, and understood at a fundamental level.
Researchers from King Abdullah University of Science and Technology (KAUST) have developed deepBlastoid, the first deep-learning platform specifically designed for the high-throughput, automated classification of human stem cell-derived embryo models (blastoids). By leveraging a ResNet-18 architecture and a novel Confidence Rate metric, the model achieves up to 97% accuracy and processes images 1,000 times faster than human experts. This tool facilitates large-scale drug screening and basic research into early human development by providing a standardized, objective evaluation framework.