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

We need to translate the Russian news post into natural English, format according to rules: - First line: short headline under 90 chars, no markdown, no # prefix. - Then a 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, never a whole sentence. - Wrap study/journal citations and publication references in single underscores _ (e.g., Nature Aging, July 2026). - Preserve all facts, numbers, names, citations exactly. No added commentary. - No source link. We need to identify important facts to bold: numbers like 12,779 genes, 28 August, Cell, 33.4 million cells, 21.99 million cells, 11,527 suppressed genes, 2,035,311 significant pairs, nine regulators, 12 independently tested links, ten statistically significant, etc. Also dates: 28 August, maybe mention Cell publication date. Also gene names: IL10, IL21, mTORC1, SUMO. Also study: OneK1K with 782 participants, validated on 199. Also mention Gladstone Institutes release. We need to limit bold to at most 4-5 per post. So we need to select maybe 4-5 key facts. Let's pick: 12,779 genes, 33.4 million cells, 21.99 million cells, 11,527 suppressed genes, 2,035,311 significant pairs. That's 5 bold items. Ensure not bold whole sentences. We also need to wrap study/journal citations in single underscores: The work published in Cell on August 28 -> Cell, August 28. Also maybe mention OneK1K study -> OneK1K. Also Gladstone Institutes release maybe not a journal citation; but could be just text. We need to ensure we don't bold whole sentences; only wrap the specific numbers/names. Let's craft headline: something like "Perturb‑seq maps state‑dependent gene effects in human CD4+ T cells". Count characters: Let's count: "Perturb‑seq maps state‑dependent gene effects in human CD4+ T cells". Characters: Let's count roughly: P(1) e2 r3 t4 u5 r6 b7 ‑ (maybe counts as one) 8 s9 e10 q11 (space)12 m13 a14 p15 s16 (space)17 s18 t19 a20 t21 e22 ‑23 d24 e25 p26 e27 n28 d29 e30 n31 t32 (space)33 g34 e35 n36 e37 (space)38 e39 f40 f41 e42 c43 t44 s45 (space)46 i47 n48 (space)49 h50 u51 m52 a53 n54 (space)55 C56 D57 4 58 + 59 (space)60 T61 (space)62 c63 e64 l65 l66 s67. That's about 67 chars, okay under 90. Now body paragraphs: We need short paragraphs 2-3 sentences each. Let's break content: Paragraph 1: Introduce study: On August 28, Cell published work on CD4+ T cells measuring effects of suppressing 12,779 genes in primary human T cells. Team took blood from four healthy donors, partially knocked down each gene one at a time, and read responses at rest, 8h, and 48h after restimulation. Paragraph 2: Explain Perturb-seq method: They used CRISPRi with guide RNAs to partially suppress a gene, then measured which other genes became more or less active. After QC, from 33.4 million cells they kept 21.99 million with unambiguous guide assignments. For 11,527 suppressed genes they evaluated changes and found 2,035,311 significant gene‑pair links, each tied to a specific T‑cell state. Paragraph 3: Validation: Nine known and novel regulators of IL10 and IL21 were tested with two independent guides, RNA readout and protein measurement. In all 12 tested links the effect direction matched the main experiment; ten were statistically significant. The same suppressed gene gave different effects in three cell states. Paragraph 4: Temporal patterns: At 8h after stimulation they saw early gene clusters linked to calcium‑mediated signaling; at 48h they saw late clusters linked to cell division and genome maintenance. This state‑dependence turns a “virtual cell” into a testable problem: a computer model must predict the measured response from cell state and perturbation.… 🔗 Read original →