Longevity InTime: Autonomous AI Institute. Anti-Aging Digital Health Immortality Transhumanist AI Channel

We need to translate Russian news post into English, format per rules. First line: short headline under 90 chars, no markdown. Then blank line, then body split into short paragraphs (2-3 sentences each), separated by blank lines. Wrap few genuinely important facts — key numbers, percentages, drug/company/gene names, dates — in double asterisks . At most 4-5 per post. Wrap study/journal citations and publication references in single underscores _ (e.g., Nature Aging, July 2026). We need to preserve facts, numbers, names, citations exactly. Let's extract facts: - scPILOT transfers response of cells to a known stimulus to another patient, cell type, or species. - Article published August 29 in Advanced Science about scPILOT, a computational model that uses measured cellular response to a stimulus to predict response in another patient, cell type, or species. - In tests, authors hid cells after stimulus exactly where they made predictions: models only had baseline cells, hidden measurements served as final test. - Single-cell sequencing shows which genes are active in individual cells. - Experiment measures one group of cells before stimulus, another after. - Therefore ordinary calculation often reduces response of whole group to average difference and loses cell-to-cell differences. - Authors apply optimal transport — a mathematical way to match probabilistic pairs between two groups with minimal total discrepancy. It links cells before and after already measured stimulus and estimates for each baseline cell the shift in gene activity. - Then model receives baseline cells of a new patient, another cell type, or another species. It finds in prior experiments groups with similar gene activity, transfers their cellular shifts to the new group, and weights more heavily the closer groups. - Adding this shift to baseline state, scPILOT predicts gene activity after same stimulus. - On seven immune cell types treated with interferon-beta, a signaling protein of the immune system, scPILOT obtained average R² 0.945. - This metric shows how predicted average gene activity levels matched measured; best of remaining models had 0.935. - In test on eight patients R² was 0.598, roughly like CellOT, and by distributions of individual cells scPILOT showed smallest discrepancy. - Accuracy depended on proximity of baseline cell states. - Three most similar contexts gave almost same accuracy as all available contexts together, while three most distant worsened prediction. - On six cancer cell lines differences between lines were stronger than effect of gene knockout. There scPILOT by average gene activity levels was comparable to simple baseline prediction. - scPILOT uses past experiments as source of prediction, matching their cells to new population: the closer the baseline states, the more useful the transferred response. We need to include citations: The article published Aug 29 in Advanced Science. So citation: Advanced Science, August 29 maybe? Actually they said "29 августа в Advanced Science вышла статья о scPILOT". So we can wrap as Advanced Science, August 29. Also maybe mention interferon-beta as a drug/protein: interferon-beta. Numbers: R² 0.945, 0.935, 0.598, seven immune cell types, eight patients, six cancer cell lines, three most similar contexts, three most distant. We need at most 4-5 double asterisk facts. Choose key numbers: R² 0.945, R² 0.935, R² 0.598, seven immune cell types, eight patients, six cancer cell lines, interferon-beta maybe. That's many. Need to limit to 4-5. Let's pick: 0.945, 0.935, 0.598, seven immune cell types, eight patients. Could also include interferon-beta as a protein name but maybe not needed. We'll keep 5. Wrap each in double asterisks. Now paragraphs: short paragraphs 2-3 sentences each. Let's craft:… 🔗 Read original →