EXCLUSIVE: Sunshine Biopharma ($SBFM) updated its K1.1 mRNA cancer program, with preclinical work showing tumor-suppressing activity in liver cancer models. Next, it plans to test K1.1 mRNA with a cancer vaccine for non-small cell lung cancer.

An AI model just rediscovered Kepler's law from latent space, with zero knowledge of orbital mechanics. And the same core architecture spans molecular dynamics, cell prediction, and even generating cancer treatment hypotheses. Title: JEPA-Anything: Learning Predictive Models across Different Worlds URL: In one sentence: it decomposes a target's representation into K orthogonal subspaces, each with its own dedicated predictor — "Orthogonal Predictive Factorization" (OPF) — and applies this single mechanism across radically different domains, from vision and biology to clinical data, control, and molecular dynamics. 🔭 Highlight 1: Rediscovering a physical law from latent space Trained only on orbital motion data, its latent frequency modes recovered Kepler's law f=(2π)⁻¹a⁻³/². The fitted slope was -1.4991 against a theoretical -1.5, with R²=0.9999999. 🧬 Highlight 2: Generating and validating a cancer treatment hypothesis Factor analysis on liver cancer data proposed combining IL-18 and CD73 blockade, which then showed the strongest tumor cell killing in actual patient-derived organoids. ⚛️ Highlight 3: Consistently strong across molecular dynamics and cell prediction It achieved the lowest error across 100-step molecular simulations of water, quartz, paracetamol, and benzene, and also beat prior methods on single-cell perturbation prediction. It's striking that one core architecture spans such wildly different scientific domains this well. #WorldModels# #AIforScience#

Every living thing on Earth like bacteria, trees, you writes its instructions in the same four-letter code. A, T, C, G. Four letters, every organism, no exceptions, for billions of years. Scientists at UC San Diego just added 4 made-up letters & the enzyme that reads DNA handled them anyway. 🧬 Here's why that's strange. DNA isn't useful on its own. An enzyme has to crawl along it to copy it out & that enzyme has spent billions of years seeing only those four letters. Show it something new & it should choke. It didn't. It read the synthetic letters as accurately as the real ones. They took atomic-level pictures to find out why & the answer is that the enzyme isn't only checking for the specific chemistry of the natural pairs. A synthetic pair that fits, trips the same recognition machinery. Right shape, it copies. Never mind that nothing in nature has ever looked like this. The second paper is the stranger one. They used synthetic letters built without the chemical bonds every textbook says hold DNA pairs to their partners. The enzyme worked on those too. So life's alphabet has four letters not because four is the limit, but because that's what it started with. Turns out the machinery was always capable of more. This was purified enzyme in a test tube, not inside a living cell. That's the next problem & it's a hard one. What it's for, eventually? DNA with extra letters can be designed to do things natural DNA can't. Earlier work built synthetic DNA that latches onto liver cancer cells. This is the step that makes running that kind of thing inside a living organism plausible.

🎤 This week’s Hello! Sta: Morning Musume。’25, OCHA NORMA, Juice=Juice, Tsubaki Factory 📺 #MorningMusume25# #TsubakiFactory# #JuiceJuice# #OCHANORMA# #JPop# #HelloProject# #IdolPerformance# #LiveConcert# #MVBehindTheScenes# #MusicShow# #JapaneseMusic# #JapanIdols#