Fun fact. Tarantulas can regenerate lost legs during the molting process. If a leg is lost or injured, a new, smaller, and less hairy leg will appear in its place after the next molt. Within one or two subsequent molts, the leg usually returns to its normal size.

A new protein-based gel can regenerate tooth enamel. For generations, dental patients have accepted a hard truth: once your tooth enamel is gone, it is gone for good. However, a major scientific breakthrough has shattered this limitation. An international research team, led by scientists at the University of Nottingham, has developed a revolutionary biomimetic gel capable of repairing and regenerating damaged tooth enamel. Published in the journal Nature Communications, this fluoride-free treatment uses lab-engineered proteins to mimic the natural processes of enamel development during infancy. When applied to the teeth, it creates a microscopic scaffold that captures calcium and phosphate ions from the patient's saliva, systematically growing a new mineral layer that seamlessly integrates with the tooth's original structure. This innovative gel offers a painless, drill-free alternative to traditional fillings and crowns, which only mask damage rather than healing it. Clinical trials for the biocompatible gel are slated to begin this year, and the development team is already collaborating with spin-off company Mintech-Bio with the goal of releasing their first commercial product as early as next year. By offering a permanent, easy-to-apply solution for acid erosion and early-stage cavities, this regenerative technology could fundamentally change routine dental care and spare millions of patients the discomfort of the dental drill. source: Hasan, A., et al.. Biomimetic supramolecular protein matrix restores structure and properties of human dental enamel. Nature Communications, 16(1), 9434.

Scientists are using extracts from sheep's wool to regenerate bone tissue in living animals. Researchers at King’s College London have unlocked a highly sustainable breakthrough in regenerative medicine by turning ordinary sheep’s wool into advanced bone-healing scaffolds. The team extracted keratin, the tough structural protein that gives wool its strength, and developed it into thin, biomimetic membranes. In laboratory trials, these membranes successfully supported the growth of human bone cells. When tested in living animal models with severe, non-healing skull injuries, the wool-derived scaffolds guided the growth of new bone directly across the damaged areas, demonstrating the immense clinical potential of this abundant agricultural byproduct. What makes this discovery particularly remarkable is the quality of the regenerated tissue. While collagen has long been the gold-standard scaffold in orthopedics, it often suffers from poor structural strength and rapid degradation. The new wool-based keratin scaffolds, however, produced bone that was far more organized, stable, and structurally similar to healthy natural bone than tissue grown with conventional collagen. Because wool is a renewable resource often discarded as farming waste, this technology offers a scalable, eco-friendly, and cost-effective alternative that could soon challenge the long-standing medical reliance on expensive, animal-derived collagen. source: Gamea, S., Kaabi, H., Elredah, I., Aljohani, H., Horamee, S., Abu Shaqrah, H. J. N., Lu, E. M.-C., Hodgkinson, T., Balto, H., Sharpe, P. T., & Elsharkawy, S. (2026). Bone regeneration of rat calvarial defect using biomimetic keratin-based membranes. Biomaterials Advances, 184, 214806.

Ever fix one slide and watch the agent regenerate the whole deck and break everything? This work solves that with hierarchical memory plus local revision 🗂️ Title: MemSlides: A Hierarchical Memory Driven Agent Framework for Personalized Slide Generation with Multi-turn Local Revision URL: ❓ What's new? 💡 It gives a slide-generation agent a hierarchical memory that cleanly separates persistent preferences (user profile), session-level working memory, and reusable tool experience. It also edits only the target slides instead of regenerating the full deck. ❓ How does it keep local edits from drifting? 💡 A Plan–Act–Guard loop. Plan turns a request into an explicit "execution contract" (target paths, active rules, coverage requirements); Act picks tools like batch CSS over shared selectors or patch operations; Guard binds patches to content hashes and blocks premature finalization until all targets are covered. ❓ Do one-off instructions leak into permanent preferences? 💡 No — at job end, intent-aware consolidation writes back only stable signals, preventing transient "just this round" requests from becoming persistent preferences. ❓ Does it work? 💡 In blind review, personalization beats DeepPresenter on every dimension (e.g. Visual +1.66). With tool memory, closed-loop completion hits 0.963 and time-to-first-correct-edit drops 609.5s → 242.5s (~60% faster). Designing agent memory by role rather than one flat store feels broadly useful for multi-turn editing tasks. #AIAgents# #LLM#

Scottish scientists are at the forefront of MS research using tiny fish that can regenerate their nervous systems. But Britain’s post-EU reality is creating bottlenecks for breakthroughs. 🔗

Dependabot now supports version updates for Agent Package Manager (APM). • Opens PRs to update git dependencies in and regenerate • Available on all GitHub plans and coming to GitHub Enterprise Server 3.24