We need to translate Russian news post into natural English, format per rules.
First line: short headline under 90 chars, no markdown, no '#'.
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, never a whole sentence.
Wrap study/journal citations and publication references in single underscores _ (e.g., Nature Machine Intelligence, August 28, 2026? Actually article date: 28 августа в Nature Machine Intelligence вышла статья. So we need to wrap that citation: Nature Machine Intelligence, August 28, 2026? The year not given; article presumably 2024? But we just keep as given: "28 августа в Nature Machine Intelligence вышла статья". We'll wrap the journal name and date: Nature Machine Intelligence, August 28.
We need to preserve facts, numbers, names, citations exactly.
Important facts: GOLLuM method, date Aug 28, article in Nature Machine Intelligence, 23 tasks, budget 50 experiments, GOLLuM average found 36.3% of conditions in top 5% results; standard Bayesian optimization 29.7%; in Buchwald-Hartwig reactions test, proportion of top 5% conditions rose from 24% (language model without fine-tuning) to 43% after joint training with GP. Also mention that they started with ten conditions below median. Also mention they released code, data, configs.
We need to select at most 4-5 double asterisk facts. Choose: August 28, Nature Machine Intelligence, 23 tasks, 50 experiments, 36.3%, 29.7%, 24%, 43%. That's many; need limit to 4-5. We'll pick the most important: date, journal, 23 tasks, 50 experiments, 36.3% vs 29.7%, maybe also the Buchwald-Hartwig improvement 24% to 43%. That's more than 5. Let's think: we need at most 4-5 double asterisk facts. Could combine some: maybe we can embed multiple numbers in one double asterisk? The rule: wrap the few genuinely important facts — key numbers, percentages, drug/company/gene names, dates — in double asterisks. Be selective: at most 4-5 per post, never a whole sentence.
Thus we need to choose up to 5 items to bold. Let's pick: August 28, Nature Machine Intelligence, 23 tasks, 50 experiments, 36.3% (maybe also mention 29.7% but that would be 6). Could we combine 36.3% and 29.7% into one double asterisk? Like "36.3% vs 29.7%"? That's still one fact (comparison). That counts as one. Then we also need Buchwald-Hartwig improvement maybe as another fact: "24% → 43%". That would be total: date, journal, 23 tasks, 50 experiments, 36.3% vs 29.7%, 24% → 43% = 6. Too many.
We could drop one: maybe we don't need to bold the date if we can put date in underscores? No, date is not a citation; it's a fact. Could we embed date inside the underscores with journal? Eg Nature Machine Intelligence, August 28 includes date, but that's underscores not double asterisk. So date can be inside underscores, not counting toward double asterisk limit. Good! So we can put the date inside the single underscores with journal citation. Then we have double asterisks for: 23 tasks, 50 experiments, 36.3% vs 29.7%, 24% → 43%. That's 4 double asterisks. Good.
Now we need to wrap study/journal citations and publication references in single underscores. So we will have Nature Machine Intelligence, August 28 (maybe include year if known but not given). We'll keep as given.
Now produce headline: short under 90 chars. Something like: "GOLLuM uses language models to pick next experiment via uncertainty". Count characters: Let's count: "GOLLuM uses language models to pick next experiment via uncertainty". That's about 61. Good.
Now body paragraphs: 2-3 sentences each.
We need to preserve all facts, numbers, names, citations exactly. No extra commentary.
Let's draft:…
🔗 Read original →
First line: short headline under 90 chars, no markdown, no '#'.
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, never a whole sentence.
Wrap study/journal citations and publication references in single underscores _ (e.g., Nature Machine Intelligence, August 28, 2026? Actually article date: 28 августа в Nature Machine Intelligence вышла статья. So we need to wrap that citation: Nature Machine Intelligence, August 28, 2026? The year not given; article presumably 2024? But we just keep as given: "28 августа в Nature Machine Intelligence вышла статья". We'll wrap the journal name and date: Nature Machine Intelligence, August 28.
We need to preserve facts, numbers, names, citations exactly.
Important facts: GOLLuM method, date Aug 28, article in Nature Machine Intelligence, 23 tasks, budget 50 experiments, GOLLuM average found 36.3% of conditions in top 5% results; standard Bayesian optimization 29.7%; in Buchwald-Hartwig reactions test, proportion of top 5% conditions rose from 24% (language model without fine-tuning) to 43% after joint training with GP. Also mention that they started with ten conditions below median. Also mention they released code, data, configs.
We need to select at most 4-5 double asterisk facts. Choose: August 28, Nature Machine Intelligence, 23 tasks, 50 experiments, 36.3%, 29.7%, 24%, 43%. That's many; need limit to 4-5. We'll pick the most important: date, journal, 23 tasks, 50 experiments, 36.3% vs 29.7%, maybe also the Buchwald-Hartwig improvement 24% to 43%. That's more than 5. Let's think: we need at most 4-5 double asterisk facts. Could combine some: maybe we can embed multiple numbers in one double asterisk? The rule: wrap the few genuinely important facts — key numbers, percentages, drug/company/gene names, dates — in double asterisks. Be selective: at most 4-5 per post, never a whole sentence.
Thus we need to choose up to 5 items to bold. Let's pick: August 28, Nature Machine Intelligence, 23 tasks, 50 experiments, 36.3% (maybe also mention 29.7% but that would be 6). Could we combine 36.3% and 29.7% into one double asterisk? Like "36.3% vs 29.7%"? That's still one fact (comparison). That counts as one. Then we also need Buchwald-Hartwig improvement maybe as another fact: "24% → 43%". That would be total: date, journal, 23 tasks, 50 experiments, 36.3% vs 29.7%, 24% → 43% = 6. Too many.
We could drop one: maybe we don't need to bold the date if we can put date in underscores? No, date is not a citation; it's a fact. Could we embed date inside the underscores with journal? Eg Nature Machine Intelligence, August 28 includes date, but that's underscores not double asterisk. So date can be inside underscores, not counting toward double asterisk limit. Good! So we can put the date inside the single underscores with journal citation. Then we have double asterisks for: 23 tasks, 50 experiments, 36.3% vs 29.7%, 24% → 43%. That's 4 double asterisks. Good.
Now we need to wrap study/journal citations and publication references in single underscores. So we will have Nature Machine Intelligence, August 28 (maybe include year if known but not given). We'll keep as given.
Now produce headline: short under 90 chars. Something like: "GOLLuM uses language models to pick next experiment via uncertainty". Count characters: Let's count: "GOLLuM uses language models to pick next experiment via uncertainty". That's about 61. Good.
Now body paragraphs: 2-3 sentences each.
We need to preserve all facts, numbers, names, citations exactly. No extra commentary.
Let's draft:…
🔗 Read original →
Intestinal ACP7 secretion extends lifespan in C. elegans
Researchers artificially boosted ACP7 production in the intestine of C. elegans and found that lifespan increased only when the enzyme was secreted from gut cells.
The median lifespan rose by 10%, and the age at which 10 % of worms survived increased by 22%; the study appeared on 27 August in Cell Reports.
Using TurboID labeling in the endoplasmic reticulum, the team performed mass spectrometry on worms aged 3, 8, and 13 days, identifying 238 extracellular or secreted proteins, of which 191 changed with age and 89 have human homologs.
Four candidate proteins were tagged with fluorescent markers and all were detected outside the intestine and in coelomocytes; ACP7 levels were shown to rise with the worms’ age.
Removing the 21‑amino‑acid signal peptide kept ACP7 inside the intestine and abolished its life‑extending effect, while the ACP7‑7A variant with seven substitutions in the metal‑binding domain retained secretion but lost phosphatase activity and failed to prolong lifespan.
Human ACP7 was secreted in cell culture and demonstrated phosphatase activity on an artificial substrate; a computational screen pointed to 28 extracellular proteins that could be dephosphorylated by worm ACP7, providing targets for future work linking the enzyme’s activity to longevity.
🔗 Read original →
Researchers artificially boosted ACP7 production in the intestine of C. elegans and found that lifespan increased only when the enzyme was secreted from gut cells.
The median lifespan rose by 10%, and the age at which 10 % of worms survived increased by 22%; the study appeared on 27 August in Cell Reports.
Using TurboID labeling in the endoplasmic reticulum, the team performed mass spectrometry on worms aged 3, 8, and 13 days, identifying 238 extracellular or secreted proteins, of which 191 changed with age and 89 have human homologs.
Four candidate proteins were tagged with fluorescent markers and all were detected outside the intestine and in coelomocytes; ACP7 levels were shown to rise with the worms’ age.
Removing the 21‑amino‑acid signal peptide kept ACP7 inside the intestine and abolished its life‑extending effect, while the ACP7‑7A variant with seven substitutions in the metal‑binding domain retained secretion but lost phosphatase activity and failed to prolong lifespan.
Human ACP7 was secreted in cell culture and demonstrated phosphatase activity on an artificial substrate; a computational screen pointed to 28 extracellular proteins that could be dephosphorylated by worm ACP7, providing targets for future work linking the enzyme’s activity to longevity.
🔗 Read original →
We need to translate Russian news post into natural English, format per rules.
First line: short headline under 90 chars, no markdown, no '#'.
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, never a whole sentence.
Wrap study/journal citations and publication references in single underscores ....
We need to preserve facts, numbers, names, citations exactly. No added commentary.
We need to identify important facts: numbers: 27 August (date), 6,053 people, 443 centenarians with preserved cognition, 3,219 control participants, 2,391 Alzheimer's patients, 24,651 DNA variants grouped, Hap-B associated with DRB1*04, Hap-R with DRB1*01:01, Hap-Y with DRB1*15:01, Braak stage, etc.
We need to select at most 4-5 double-asterisk facts. Choose maybe: 27 August, 6,053 participants, 443 centenarians, 3,219 controls, 2,391 Alzheimer's patients? That's 5. But we need to be selective; maybe we can include date and total participants, and numbers of groups. Could also include gene names: DRB1*04, DRB1*01:01, DRB1*15:01. Those are also important facts. But we have limit 4-5 double asterisks total. We need to decide which to highlight.
Probably highlight: 27 August, 6,053 participants, 443 centenarians, DRB1*04, DRB1*01:01? But also need DRB1*15:01 maybe not.
Alternatively we could highlight numbers and gene names combined: e.g., DRB1*04, DRB1*01:01, DRB1*15:01 as three, plus date and total participants = 5.
Let's decide: double asterisk for: 27 August, 6,053 participants, DRB1*04, DRB1*01:01, DRB1*15:01. That's 5.
Now single underscores for study/journal citations and publication references. The text mentions a preprint published 27 August. No journal name given. Could be something like bioRxiv? Not given. It says "В препринте, опубликованном 27 августа". So we can wrap the preprint reference: preprint, published 27 August. But we need to keep citation exactly; we don't have journal name. Could just wrap "preprint" maybe. The rule: wrap study/journal citations and publication references in single underscores. So we can do preprint published 27 August. Or preprint, 27 August. We'll keep as preprint published 27 August.
Now we need to produce body paragraphs, each 2-3 sentences.
Let's craft translation.
First, headline: maybe "HLA-II variants linked to Alzheimer's, longevity, and microglial activity". Count characters: Let's count: "HLA-II variants linked to Alzheimer's, longevity, and microglial activity". That's about 66 characters. Good.
Now blank line.
Paragraph 1: talk about study comparing HLA-II genes among 6,053 individuals: 443 centenarians with preserved cognition, 3,219 controls, 2,391 Alzheimer's patients. Mention date.
We need to include double asterisks for numbers and date.
Paragraph 2: talk about grouping 24,651 DNA variants into seven sets, three overlapping previous signals.
Paragraph 3: explain HLA-II function, variability, inheritance.
Paragraph 4: talk about Hap-B associated with DRB1*04, more common in controls and centenarians, linked to lower Braak tau stage, persists after accounting for amyloid.
Paragraph 5: Hap-R associated with DRB1*01:01 more frequent in patients, less in centenarians and controls.
Paragraph 6: Hap-Y associated with DRB1*15:01 linked to greater HLA-II staining area in microglia, reflecting microglial immune state; tau pathology assessed by another scale.
We need to ensure each paragraph 2-3 sentences.
Now incorporate double asterisks: we already decided which to bold.
We need to embed them in text.
Let's list:
- 27 August
- 6,053 participants
- DRB1*04
- DRB1*01:01
- DRB1*15:01…
🔗 Read original →
First line: short headline under 90 chars, no markdown, no '#'.
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, never a whole sentence.
Wrap study/journal citations and publication references in single underscores ....
We need to preserve facts, numbers, names, citations exactly. No added commentary.
We need to identify important facts: numbers: 27 August (date), 6,053 people, 443 centenarians with preserved cognition, 3,219 control participants, 2,391 Alzheimer's patients, 24,651 DNA variants grouped, Hap-B associated with DRB1*04, Hap-R with DRB1*01:01, Hap-Y with DRB1*15:01, Braak stage, etc.
We need to select at most 4-5 double-asterisk facts. Choose maybe: 27 August, 6,053 participants, 443 centenarians, 3,219 controls, 2,391 Alzheimer's patients? That's 5. But we need to be selective; maybe we can include date and total participants, and numbers of groups. Could also include gene names: DRB1*04, DRB1*01:01, DRB1*15:01. Those are also important facts. But we have limit 4-5 double asterisks total. We need to decide which to highlight.
Probably highlight: 27 August, 6,053 participants, 443 centenarians, DRB1*04, DRB1*01:01? But also need DRB1*15:01 maybe not.
Alternatively we could highlight numbers and gene names combined: e.g., DRB1*04, DRB1*01:01, DRB1*15:01 as three, plus date and total participants = 5.
Let's decide: double asterisk for: 27 August, 6,053 participants, DRB1*04, DRB1*01:01, DRB1*15:01. That's 5.
Now single underscores for study/journal citations and publication references. The text mentions a preprint published 27 August. No journal name given. Could be something like bioRxiv? Not given. It says "В препринте, опубликованном 27 августа". So we can wrap the preprint reference: preprint, published 27 August. But we need to keep citation exactly; we don't have journal name. Could just wrap "preprint" maybe. The rule: wrap study/journal citations and publication references in single underscores. So we can do preprint published 27 August. Or preprint, 27 August. We'll keep as preprint published 27 August.
Now we need to produce body paragraphs, each 2-3 sentences.
Let's craft translation.
First, headline: maybe "HLA-II variants linked to Alzheimer's, longevity, and microglial activity". Count characters: Let's count: "HLA-II variants linked to Alzheimer's, longevity, and microglial activity". That's about 66 characters. Good.
Now blank line.
Paragraph 1: talk about study comparing HLA-II genes among 6,053 individuals: 443 centenarians with preserved cognition, 3,219 controls, 2,391 Alzheimer's patients. Mention date.
We need to include double asterisks for numbers and date.
Paragraph 2: talk about grouping 24,651 DNA variants into seven sets, three overlapping previous signals.
Paragraph 3: explain HLA-II function, variability, inheritance.
Paragraph 4: talk about Hap-B associated with DRB1*04, more common in controls and centenarians, linked to lower Braak tau stage, persists after accounting for amyloid.
Paragraph 5: Hap-R associated with DRB1*01:01 more frequent in patients, less in centenarians and controls.
Paragraph 6: Hap-Y associated with DRB1*15:01 linked to greater HLA-II staining area in microglia, reflecting microglial immune state; tau pathology assessed by another scale.
We need to ensure each paragraph 2-3 sentences.
Now incorporate double asterisks: we already decided which to bold.
We need to embed them in text.
Let's list:
- 27 August
- 6,053 participants
- DRB1*04
- DRB1*01:01
- DRB1*15:01…
🔗 Read original →
PubMed Central (PMC)
Multiancestry analysis of the HLA locus in Alzheimer’s and Parkinson’s diseases uncovers a shared adaptive immune response mediated…
We report that specific HLA-DRB1*04 alleles are protective against Alzheimer’s dementia (AD), Parkinson’s disease (PD), and other neurodegenerative disorders. Further, we found that these HLA (Human Leukocyte Antigen) subtypes selectively bind a ...
Adaptyv Bio Links Lab Validation to Rosalind Workbench via API
Adaptyv Bio announced on 29 August that it has linked its lab validation to Rosalind Workbench OpenAI via the Adaptyv API; experimental data will flow into the next round of protein design.
On 28 August, OpenAI launched Rosalind Workbench as a workspace for biological research, where a researcher can pose a question, run analysis, and draft an experiment plan.
In an example, Workbench helped select nanobody candidates — small proteins that bind a given molecule — and plan and evaluate the cost of binding tests for five nanobodies. The new integration adds a laboratory step to this workflow. Through the Adaptyv API, the protein sequence (the amino‑acid order) is sent to the experiment; the lab can test whether the produced protein binds the target molecule and return the results via the platform or API.
Adaptyv Bio notes that the physical‑experiment data feed directly into the next design round, so the subsequent protein‑sequence choice is based on the binding‑test result.
🔗 Read original →
Adaptyv Bio announced on 29 August that it has linked its lab validation to Rosalind Workbench OpenAI via the Adaptyv API; experimental data will flow into the next round of protein design.
On 28 August, OpenAI launched Rosalind Workbench as a workspace for biological research, where a researcher can pose a question, run analysis, and draft an experiment plan.
In an example, Workbench helped select nanobody candidates — small proteins that bind a given molecule — and plan and evaluate the cost of binding tests for five nanobodies. The new integration adds a laboratory step to this workflow. Through the Adaptyv API, the protein sequence (the amino‑acid order) is sent to the experiment; the lab can test whether the produced protein binds the target molecule and return the results via the platform or API.
Adaptyv Bio notes that the physical‑experiment data feed directly into the next design round, so the subsequent protein‑sequence choice is based on the binding‑test result.
🔗 Read original →
X (formerly Twitter)
Adaptyv Bio (@adaptyvbio) on X
We're bringing experimental validation to @OpenAI's Rosalind Workbench through the Adaptyv API.
Rosalind Workbench is a new way to orchestrate complex life science research workflows across model…
Rosalind Workbench is a new way to orchestrate complex life science research workflows across model…
We need to translate Russian news post into English, format per rules.
First line: short headline under 90 chars, no markdown, no '#'.
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, never a whole sentence.
Wrap study/journal citations and publication references in single underscores _ (e.g., Nature Aging, July 2026).
We need to preserve all facts, numbers, names, citations exactly.
Let's extract facts:
- Date: 28 августа (August 28) in Cell Reports (re-analysis of data). So date: August 28 (year not given? The article presumably 2024? Not given. We'll keep "August 28" as given.
- Data: single-cell brain data of male mice.
- After QC: 12,310 cells remained.
- Pairs of young and old mice with surgically joined circulations – heterochronic parabiosis.
- One-cell atlas of such pairs in 2022 collected by Robert Palovich with coauthors; Palovich also in current team.
- Mice of same age served as control.
- Authors identified eight microglial states.
- In six activated states, 75 genes changed similarly in at least five of them.
- Forty of these 75 genes entered the common age shift in all four brain regions.
- Common program manifested in all regions, but each had its own shifts.
- In young mice with old partners, gene activity in cerebellum and cortex changed in same direction as normal aging, albeit weaker.
- Under both influences, most changes seen in cerebellum.
- In old mice with young partners, in cerebellum 41 genes changed activity opposite to age changes; in cortex and hippocampus 25 each; in striatum three.
We need to wrap key numbers, percentages, drug/company/gene names, dates in . At most 4-5 per post.
Select maybe: 12,310 cells, August 28, 75 genes, 40 genes, 41 genes, 25 genes, three genes? That's many. Need max 4-5. Choose most important: total cells, date, number of genes commonly shifted (40), number of opposite changes in cerebellum (41), maybe number of opposite changes in cortex/hippocampus (25). That's 5.
We must not wrap whole sentences. So embed within sentences.
Citations: we have Cell Reports (journal) and the 2022 one-cell atlas by Robert Palovich et al. We need to wrap study/journal citations and publication references in single underscores _. So we should put Cell Reports and maybe 2022 one-cell atlas? The instruction: wrap study/journal citations and publication references in single underscores (e.g., Nature Aging, July 2026). So we should put the journal name in underscores. Also maybe the 2022 atlas reference? Could be considered a publication reference; we can put Robert Palovich et al., 2022 or similar. But we need to preserve exact names. The Russian text: "Одно-клеточный атлас таких пар в 2022 году собрал Роберт Палович с соавторами ; Палович вошёл и в нынешнюю команду." So we can cite as Robert Palovich et al., 2022 (or 2022 one-cell atlas by Robert Palovich et al.). We'll put the citation in underscores.
We need to ensure we don't add extra commentary.
Now format: Headline line, blank line, then paragraphs.
Paragraphs 2-3 sentences each.
Let's craft:
Headline: "Heterochronic parabiosis reshapes microglial gene activity across mouse brain regions"
Check length: count characters: "Heterochronic parabiosis reshapes microglial gene activity across mouse brain regions" Let's count: H(1) ... I'll approximate less than 90. It's fine.
Blank line.
Paragraph 1: maybe 2-3 sentences about study date, data, QC.…
🔗 Read original →
First line: short headline under 90 chars, no markdown, no '#'.
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, never a whole sentence.
Wrap study/journal citations and publication references in single underscores _ (e.g., Nature Aging, July 2026).
We need to preserve all facts, numbers, names, citations exactly.
Let's extract facts:
- Date: 28 августа (August 28) in Cell Reports (re-analysis of data). So date: August 28 (year not given? The article presumably 2024? Not given. We'll keep "August 28" as given.
- Data: single-cell brain data of male mice.
- After QC: 12,310 cells remained.
- Pairs of young and old mice with surgically joined circulations – heterochronic parabiosis.
- One-cell atlas of such pairs in 2022 collected by Robert Palovich with coauthors; Palovich also in current team.
- Mice of same age served as control.
- Authors identified eight microglial states.
- In six activated states, 75 genes changed similarly in at least five of them.
- Forty of these 75 genes entered the common age shift in all four brain regions.
- Common program manifested in all regions, but each had its own shifts.
- In young mice with old partners, gene activity in cerebellum and cortex changed in same direction as normal aging, albeit weaker.
- Under both influences, most changes seen in cerebellum.
- In old mice with young partners, in cerebellum 41 genes changed activity opposite to age changes; in cortex and hippocampus 25 each; in striatum three.
We need to wrap key numbers, percentages, drug/company/gene names, dates in . At most 4-5 per post.
Select maybe: 12,310 cells, August 28, 75 genes, 40 genes, 41 genes, 25 genes, three genes? That's many. Need max 4-5. Choose most important: total cells, date, number of genes commonly shifted (40), number of opposite changes in cerebellum (41), maybe number of opposite changes in cortex/hippocampus (25). That's 5.
We must not wrap whole sentences. So embed within sentences.
Citations: we have Cell Reports (journal) and the 2022 one-cell atlas by Robert Palovich et al. We need to wrap study/journal citations and publication references in single underscores _. So we should put Cell Reports and maybe 2022 one-cell atlas? The instruction: wrap study/journal citations and publication references in single underscores (e.g., Nature Aging, July 2026). So we should put the journal name in underscores. Also maybe the 2022 atlas reference? Could be considered a publication reference; we can put Robert Palovich et al., 2022 or similar. But we need to preserve exact names. The Russian text: "Одно-клеточный атлас таких пар в 2022 году собрал Роберт Палович с соавторами ; Палович вошёл и в нынешнюю команду." So we can cite as Robert Palovich et al., 2022 (or 2022 one-cell atlas by Robert Palovich et al.). We'll put the citation in underscores.
We need to ensure we don't add extra commentary.
Now format: Headline line, blank line, then paragraphs.
Paragraphs 2-3 sentences each.
Let's craft:
Headline: "Heterochronic parabiosis reshapes microglial gene activity across mouse brain regions"
Check length: count characters: "Heterochronic parabiosis reshapes microglial gene activity across mouse brain regions" Let's count: H(1) ... I'll approximate less than 90. It's fine.
Blank line.
Paragraph 1: maybe 2-3 sentences about study date, data, QC.…
🔗 Read original →
PubMed Central (PMC)
Molecular hallmarks of heterochronic parabiosis at single cell resolution
Slowing or reversing biological ageing would have major implications for mitigating disease risk and maintaining vitality1. While an increasing number of interventions show promise for rejuvenation2, the effectiveness on disparate cell types across ...
TranslAGE Defends Biomarker Responsiveness Amid Critique
TranslAGE brought together 51 studies in which human participants had blood drawn before and after an intervention. In every dataset the authors uniformly calculated 16 epigenetic clocks — algorithms that estimate age‑related changes from DNA chemical marks.
On August 30 Raghav Segal, the first author of TranslAGE, replied to criticism from biogerontologist Matt Kaeberlein. Kaeberlein’s objection is whether a shift in such a marker can be used to judge the impact of a drug, diet, or exercise regimen on a person.
The authors harmonized the data from those 51 studies and applied a single panel of the 16 clocks to each dataset, making it possible to compare marker shifts across different groups, time periods, and interventions. Segal phrases the article’s core question as: “Do these biomarkers respond to interventions in the expected direction, how strongly, and how consistently?”
He describes the route to a clinically useful marker in three words: prognostic → responsive → surrogate. Prognostic ties the marker to future disease, function, or mortality; responsiveness shows its shift after an intervention; surrogacy would let that shift predict a patient‑relevant outcome. In the paper responsiveness is presented as a step toward a surrogate marker, which TranslAGE tests by examining how the clocks react to presumed anti‑aging interventions. Kaeberlein’s follow‑up question is whether that shift can be linked to the concrete outcome of a specific intervention in an individual.
🔗 Read original →
TranslAGE brought together 51 studies in which human participants had blood drawn before and after an intervention. In every dataset the authors uniformly calculated 16 epigenetic clocks — algorithms that estimate age‑related changes from DNA chemical marks.
On August 30 Raghav Segal, the first author of TranslAGE, replied to criticism from biogerontologist Matt Kaeberlein. Kaeberlein’s objection is whether a shift in such a marker can be used to judge the impact of a drug, diet, or exercise regimen on a person.
The authors harmonized the data from those 51 studies and applied a single panel of the 16 clocks to each dataset, making it possible to compare marker shifts across different groups, time periods, and interventions. Segal phrases the article’s core question as: “Do these biomarkers respond to interventions in the expected direction, how strongly, and how consistently?”
He describes the route to a clinically useful marker in three words: prognostic → responsive → surrogate. Prognostic ties the marker to future disease, function, or mortality; responsiveness shows its shift after an intervention; surrogacy would let that shift predict a patient‑relevant outcome. In the paper responsiveness is presented as a step toward a surrogate marker, which TranslAGE tests by examining how the clocks react to presumed anti‑aging interventions. Kaeberlein’s follow‑up question is whether that shift can be linked to the concrete outcome of a specific intervention in an individual.
🔗 Read original →
Nature
Responsiveness of epigenetic aging biomarkers to longevity interventions in humans
Nature Medicine - The responsiveness of 16 different epigenetic aging clocks to a broad array of pharmacological and lifestyle interventions in humans was assessed across 51 different longitudinal...
NAD+ and NADPH levels in muscle correlate with function more than with age
On 28 August the authors of a preprint measured six metabolism‑related compounds in muscle biopsies from 137 men aged 20–93 years. Total NAD(H) and NADP(H) pools showed no significant age‑related change.
After adjusting for age, NAD+ remained associated with walking speed, leg power, muscle mass and mitochondrial count; NADPH retained links to walking, leg power, muscle mass, mitochondrial respiration and mitochondrial number. NAD+ fuels energy‑producing reactions, while NADPH supports biosynthesis and glutathione regeneration.
Both glutathione forms rose with age in parallel, keeping their ratio stable. To test whether the NAD(P) links reflected mitochondrial quantity or respiratory capacity, the authors used citrate‑synthase activity as a mitochondrial‑number marker. NAD+ and NADPH correlated with both citrate‑synthase activity and maximal respiration; when respiration was normalized to citrate‑synthase activity, the associations disappeared, indicating mitochondrial number as the proximate explanation.
The authors note that 2022 study data had shown lower NAD+ in older adults, especially those with poorer physical performance, whereas trained older adults approached youthful levels. A May analysis of NAD+ in whole blood across seven human cohorts also found little age‑related change. They conclude that NAD(P) exchange metrics better reflect preserved muscle health than aging, and that NAD‑modulating interventions should be evaluated by corresponding tissue‑specific functional outcomes.
🔗 Read original →
On 28 August the authors of a preprint measured six metabolism‑related compounds in muscle biopsies from 137 men aged 20–93 years. Total NAD(H) and NADP(H) pools showed no significant age‑related change.
After adjusting for age, NAD+ remained associated with walking speed, leg power, muscle mass and mitochondrial count; NADPH retained links to walking, leg power, muscle mass, mitochondrial respiration and mitochondrial number. NAD+ fuels energy‑producing reactions, while NADPH supports biosynthesis and glutathione regeneration.
Both glutathione forms rose with age in parallel, keeping their ratio stable. To test whether the NAD(P) links reflected mitochondrial quantity or respiratory capacity, the authors used citrate‑synthase activity as a mitochondrial‑number marker. NAD+ and NADPH correlated with both citrate‑synthase activity and maximal respiration; when respiration was normalized to citrate‑synthase activity, the associations disappeared, indicating mitochondrial number as the proximate explanation.
The authors note that 2022 study data had shown lower NAD+ in older adults, especially those with poorer physical performance, whereas trained older adults approached youthful levels. A May analysis of NAD+ in whole blood across seven human cohorts also found little age‑related change. They conclude that NAD(P) exchange metrics better reflect preserved muscle health than aging, and that NAD‑modulating interventions should be evaluated by corresponding tissue‑specific functional outcomes.
🔗 Read original →
Cell Metabolism
NAD depletion in skeletal muscle does not compromise muscle function or accelerate aging
NAD depletion in skeletal muscle does not impair tissue integrity and function or
accelerate aging, as shown in a mouse model with an 85% decrease in muscle NAD+ levels.
Muscle structure, metabolism, and mitochondrial function remain unaffected, suggesting…
accelerate aging, as shown in a mouse model with an 85% decrease in muscle NAD+ levels.
Muscle structure, metabolism, and mitochondrial function remain unaffected, suggesting…
Jaba Tkemaladze proposes centriole inheritance as a marker of aging in renewing tissues
On 28 August he posted a preprint on the Research Square platform outlining the “centriole counter” hypothesis.
In tissues that renew through repeated divisions, a cell lineage can retain changes in the centriole from one division to the next. In his earlier framework of four hallmarks of cellular age, Tkemaladze placed centrioles alongside telomeres and mitochondria. The current preprint narrows the focus to tissues that constantly replenish themselves with new cells.
A renewing tissue simultaneously replaces specialized cells and maintains a reserve of cells that can divide again. During division, the two daughter cells may receive
🔗 Read original →
On 28 August he posted a preprint on the Research Square platform outlining the “centriole counter” hypothesis.
In tissues that renew through repeated divisions, a cell lineage can retain changes in the centriole from one division to the next. In his earlier framework of four hallmarks of cellular age, Tkemaladze placed centrioles alongside telomeres and mitochondria. The current preprint narrows the focus to tissues that constantly replenish themselves with new cells.
A renewing tissue simultaneously replaces specialized cells and maintains a reserve of cells that can divide again. During division, the two daughter cells may receive
🔗 Read original →
PubMed Central (PMC)
Extensive programmed centriole elimination unveiled in C. elegans embryos
Centrioles are critical for fundamental cellular processes, including signaling, motility, and division. The extent to which centrioles are present after cell cycle exit in a developing organism is not known. The stereotypical lineage of ...
Retro expands Phase I trial of RTR242 to 108 volunteers in Australia
Retro will add two high‑dose cohorts and increase its Phase I study of RTR242 to 108 participants in Australia. The trial enrolls healthy adults aged 18–65 years. This expansion follows the initial dosing that began earlier this year.
The company is adding 32 participants and two new dose‑escalation groups to better define the dose for further clinical development. These groups will help Retro select the optimal dose for subsequent trials. The move aims to pinpoint a tolerable level that can be taken forward.
On August 26, CEO Joe Betts‑Lacqua told Business Insider that the study would grow from 76 to 108 volunteers. In May Retro announced the first human administration of RTR242. Since that start, the company has been expanding enrollment and raising doses.
Betts‑Lacqua explained that early tolerability testing has not yet revealed an upper dose limit, so the team must find a level participants can tolerate and carry into later studies. He said, “This is for us in some sense both a curse and a blessing: because of this it’s a bit harder to assess the moment when we can say: ‘hurray, the drug works’.”
Retro describes RTR242 as a small‑molecule compound that enhances autophagy — the process whereby a cell delivers damaged proteins and cellular components to lysosomes for breakdown. In lysosomes, the acidic interior degrades this cargo into reusable building blocks. The company expects RTR242 to restore lysosomal acidity and make this recycling more efficient.
Full Robbins, a biochemist at the University of Minnesota, called lysosomes an intriguing target for intervention. With the additional 32 participants, Retro widens the dose range from which it will choose the level for further development of RTR242.
🔗 Read original →
Retro will add two high‑dose cohorts and increase its Phase I study of RTR242 to 108 participants in Australia. The trial enrolls healthy adults aged 18–65 years. This expansion follows the initial dosing that began earlier this year.
The company is adding 32 participants and two new dose‑escalation groups to better define the dose for further clinical development. These groups will help Retro select the optimal dose for subsequent trials. The move aims to pinpoint a tolerable level that can be taken forward.
On August 26, CEO Joe Betts‑Lacqua told Business Insider that the study would grow from 76 to 108 volunteers. In May Retro announced the first human administration of RTR242. Since that start, the company has been expanding enrollment and raising doses.
Betts‑Lacqua explained that early tolerability testing has not yet revealed an upper dose limit, so the team must find a level participants can tolerate and carry into later studies. He said, “This is for us in some sense both a curse and a blessing: because of this it’s a bit harder to assess the moment when we can say: ‘hurray, the drug works’.”
Retro describes RTR242 as a small‑molecule compound that enhances autophagy — the process whereby a cell delivers damaged proteins and cellular components to lysosomes for breakdown. In lysosomes, the acidic interior degrades this cargo into reusable building blocks. The company expects RTR242 to restore lysosomal acidity and make this recycling more efficient.
Full Robbins, a biochemist at the University of Minnesota, called lysosomes an intriguing target for intervention. With the additional 32 participants, Retro widens the dose range from which it will choose the level for further development of RTR242.
🔗 Read original →
PubMed Central (PMC)
Autophagy–lysosomal-associated neuronal death in neurodegenerative disease
Autophagy, the major lysosomal pathway for degrading damaged or obsolete constituents, protects neurons by eliminating toxic organelles and peptides, restoring nutrient and energy homeostasis, and inhibiting apoptosis. These functions are especially ...
We need to translate Russian news post into natural 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, never a whole sentence.
Wrap study/journal citations and publication references in single underscores _ (e.g., Nature Aging, July 2026).
We need to preserve all facts, numbers, names, citations exactly.
Let's extract facts:
- João Pedro de Magalhães (note spelling: "Жуан Педру де Магальяйнш" -> "João Pedro de Magalhães").
- He hypothesized that cancer protection may limit regeneration.
- On August 27 he hypothesized: developmental transitions could limit tissue restoration to reduce cancer risk.
- On August 22 Michael West asked whether a short reprogramming signal would suffice to restore large damaged tissue.
- Magalhães added safety condition: returning regenerative ability could weaken tumor protection.
- Partial reprogramming temporarily returns adult cell to a younger gene expression mode while preserving specialization.
- To repair damaged tissue, cells need to divide and build new structure.
- This growth simultaneously requires control: uncontrolled division forms tumor.
- In the post, which references an article in Nature Reviews Cancer, Magalhães formulated hypothesis: "One of the reasons why developmental transitions limit regenerative capacity is, as I suppose, to reduce cancer risk."
- By this evolutionary hypothesis, natural selection could have preserved mechanisms that reduced cancer risk in young organism.
- These same mechanisms stop dangerous cell division and after tissue damage may restrain its regeneration.
- Two animal experiments show such conflict in specific systems.
- In a 2010 study on mice, the MRL line, which has good ear-hole regeneration, ear connective tissue cells lacked p21 — a protein involved in division arrest.
- Mice lacking p21 closed ear holes similarly to MRL.
- In a 2015 study on zebrafish, scientists introduced human ARF gene into genome, which helps suppress tumor growth.
- After fin amputation, ARF activated in blastema — a mass of dividing cells from which the fin regrows.
- In a separate experiment, temporary activation of ARF inhibited regeneration via p53, the cell division control system.
- With partial reprogramming, one must simultaneously check whether the intervention restores tissue's regenerative ability and whether cell division control is preserved.
We need to wrap key numbers, percentages, drug/company/gene names, dates in .
Key facts: dates: August 27, August 22, 2010, 2015. Gene names: p21, ARF, p53. Possibly also MRL line (mouse strain). Also "Nature Reviews Cancer". Also maybe "Michael West". Also "João Pedro de Magalhães". But we need at most 4-5 double asterisks. So we need to be selective: maybe only the most important: dates (2010, 2015) and gene names (p21, ARF, p53) maybe also August dates? But we can only have 4-5. Let's decide: we can include 2010, 2015, p21, ARF, p53. That's 5. Or we could include August dates but they are less critical. We'll go with those.…
🔗 Read original →
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, never a whole sentence.
Wrap study/journal citations and publication references in single underscores _ (e.g., Nature Aging, July 2026).
We need to preserve all facts, numbers, names, citations exactly.
Let's extract facts:
- João Pedro de Magalhães (note spelling: "Жуан Педру де Магальяйнш" -> "João Pedro de Magalhães").
- He hypothesized that cancer protection may limit regeneration.
- On August 27 he hypothesized: developmental transitions could limit tissue restoration to reduce cancer risk.
- On August 22 Michael West asked whether a short reprogramming signal would suffice to restore large damaged tissue.
- Magalhães added safety condition: returning regenerative ability could weaken tumor protection.
- Partial reprogramming temporarily returns adult cell to a younger gene expression mode while preserving specialization.
- To repair damaged tissue, cells need to divide and build new structure.
- This growth simultaneously requires control: uncontrolled division forms tumor.
- In the post, which references an article in Nature Reviews Cancer, Magalhães formulated hypothesis: "One of the reasons why developmental transitions limit regenerative capacity is, as I suppose, to reduce cancer risk."
- By this evolutionary hypothesis, natural selection could have preserved mechanisms that reduced cancer risk in young organism.
- These same mechanisms stop dangerous cell division and after tissue damage may restrain its regeneration.
- Two animal experiments show such conflict in specific systems.
- In a 2010 study on mice, the MRL line, which has good ear-hole regeneration, ear connective tissue cells lacked p21 — a protein involved in division arrest.
- Mice lacking p21 closed ear holes similarly to MRL.
- In a 2015 study on zebrafish, scientists introduced human ARF gene into genome, which helps suppress tumor growth.
- After fin amputation, ARF activated in blastema — a mass of dividing cells from which the fin regrows.
- In a separate experiment, temporary activation of ARF inhibited regeneration via p53, the cell division control system.
- With partial reprogramming, one must simultaneously check whether the intervention restores tissue's regenerative ability and whether cell division control is preserved.
We need to wrap key numbers, percentages, drug/company/gene names, dates in .
Key facts: dates: August 27, August 22, 2010, 2015. Gene names: p21, ARF, p53. Possibly also MRL line (mouse strain). Also "Nature Reviews Cancer". Also maybe "Michael West". Also "João Pedro de Magalhães". But we need at most 4-5 double asterisks. So we need to be selective: maybe only the most important: dates (2010, 2015) and gene names (p21, ARF, p53) maybe also August dates? But we can only have 4-5. Let's decide: we can include 2010, 2015, p21, ARF, p53. That's 5. Or we could include August dates but they are less critical. We'll go with those.…
🔗 Read original →
Nature
The evolution of cancer and ageing: a history of constraint
Nature Reviews Cancer - In this Perspective, de Magalhães explores the evolutionary relationship between cancer and ageing, proposing that the need to minimize cancer risk early in life may...
LessWrong user links egg freezing to family planning decisions
On 26 August, LessWrong user boba_girl wrote a note following the June Reproductive Frontiers conference, linking egg and embryo freezing to family‑size planning. She views oocyte cryopreservation, embryo creation, and polygenic screening as interconnected decisions about timing, partner choice, and the number of possible births.
She starts from her personal situation: she wants children but is still looking for a partner. “I think that once I find a partner I will also try to freeze some embryos,” she writes. Until then, storing eggs buys her time to choose a partner.
Embryos are created after a partner appears, and their number helps the family envision how many birth attempts they could plan. Thus, her reasoning links the choice between eggs and embryos to two goals: preserving freedom to choose a partner and anticipating the possible embryo stock.
On the consumer market for polygenic screening, the procedure looks like a series of IVF cycles, genetic testing, and selection. boba_girl starts this chain earlier, asking what options can be preserved before embryos exist. Polygenic ranking compares the resulting embryos using statistical forecasts of disease risk and certain complex traits derived from genetic data.
The number of viable embryos determines both the number of comparison options for that ranking and the number of potential birth attempts. In her note, reproductive technology enters family planning step‑by‑step: first freeze eggs, then decide with a partner about embryos, and finally choose among those that are obtained.
🔗 Read original →
On 26 August, LessWrong user boba_girl wrote a note following the June Reproductive Frontiers conference, linking egg and embryo freezing to family‑size planning. She views oocyte cryopreservation, embryo creation, and polygenic screening as interconnected decisions about timing, partner choice, and the number of possible births.
She starts from her personal situation: she wants children but is still looking for a partner. “I think that once I find a partner I will also try to freeze some embryos,” she writes. Until then, storing eggs buys her time to choose a partner.
Embryos are created after a partner appears, and their number helps the family envision how many birth attempts they could plan. Thus, her reasoning links the choice between eggs and embryos to two goals: preserving freedom to choose a partner and anticipating the possible embryo stock.
On the consumer market for polygenic screening, the procedure looks like a series of IVF cycles, genetic testing, and selection. boba_girl starts this chain earlier, asking what options can be preserved before embryos exist. Polygenic ranking compares the resulting embryos using statistical forecasts of disease risk and certain complex traits derived from genetic data.
The number of viable embryos determines both the number of comparison options for that ranking and the number of potential birth attempts. In her note, reproductive technology enters family planning step‑by‑step: first freeze eggs, then decide with a partner about embryos, and finally choose among those that are obtained.
🔗 Read original →
PubMed Central (PMC)
Screening embryos for polygenic disease risk: a review of epidemiological, clinical, and ethical considerations
The genetic composition of embryos generated by in vitro fertilization (IVF) can be examined with preimplantation genetic testing (PGT). Until recently, PGT was limited to detecting single-gene, high-risk pathogenic variants, large structural ...
We need to translate Russian text into English, format: first line headline under 90 chars, no markdown, no '#'. 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, never a whole sentence. Wrap study/journal citations and publication references in single underscores _ (e.g., Nature Chemical Biology, August 26, 2024? Actually date given: 26 августа в Nature Chemical Biology вышла работа о BrainCAB — метке на основе бринзоламида. So citation: Nature Chemical Biology, August 26, 2024? The year not given but likely 2024? The original Russian says "26 августа в Nature Chemical Biology вышла работа". No year given; we can just put Nature Chemical Biology, August 26 (no year). But we need to preserve facts exactly: date is 26 августа. We'll translate to August 26. No year given, so we omit year.
We need to wrap key numbers etc: e.g., BrainCAB tag based on brinzolamide, one chemical step, concentration ~8 times higher, 20 mg/kg dose, Car4 gene, etc. Must be selective: at most 4-5 double asterisk wrapped facts. Choose: BrainCAB tag based on brinzolamide, one chemical step, concentration ~8-fold higher, 20 mg/kg dose, Car4 gene knockout. That's 5.
Wrap study/journal citation in single underscores: Nature Chemical Biology, August 26.
Now produce headline under 90 chars: maybe "BrainCAB Tag Enables Antibody Delivery Across Blood‑Brain Barrier in Mice and Newborn Macaques". Count characters: Let's count: "BrainCAB Tag Enables Antibody Delivery Across Blood‑Brain Barrier in Mice and Newborn Macaques". Count: B(1) r2 a3 i4 n5 C6 A7 B8 (space9) T10 a11 g12 (space13) E14 n15 a16 b17 l18 e19 s20 (space21) A22 n23 t24 i25 b26 o27 d28 y29 (space30) D31 e32 l33 i34 v35 e36 r37 y38 (space39) A40 c41 r42 o43 s44 s45 (space46) B47 l48 o49 o50 d‑51 B52 r53 a54 i55 n56 (space57) B58 a59 r60 r61 i62 e63 r64 (space65) i66 n67 (space68) M69 i70 c71 e72 s73 (space74) a75 n76 d77 (space78) N79 e80 w81 b82 o83 r84 n85 (space86) M87 a88 c89 a90 q91 u92 e93 s94. That's 94 characters, exceeds 90. Need under 90. Let's shorten: maybe "BrainCAB Tag Delivers Antibodies Across Blood‑Brain Barrier in Mice and Macaques". Count: "BrainCAB Tag Delivers Antibodies Across Blood‑Brain Barrier in Mice and Macaques". Let's count: B1 r2 a3 i4 n5 C6 A7 B8 (space9) T10 a11 g12 (space13) D14 e15 l16 i17 v18 e19 r20 s21 (space22) A23 n24 t25 i26 b27 o28 d29 i30 e31 s32 (space33) A34 c35 r36 o37 s38 s39 (space40) B41 l42 o43 o44 d‑45 B46 r47 a48 i49 n50 (space51) B52 a53 r54 r55 i56 e57 r58 (space59) i60 n61 (space62) M63 i64 c65 e66 s67 (space68) a69 n70 d71 (space72) M73 a74 c75 a76 q77 u78 e79 s80. That's 80 characters. Good.
Now body: need short paragraphs 2-3 sentences each, separated by blank lines.
We need to include double asterisks for key facts: BrainCAB tag based on brinzolamide, one chemical step, concentration ~8-fold higher, 20 mg/kg dose, Car4 gene knockout.
We need to wrap study/journal citation in single underscores: Nature Chemical Biology, August 26.
We must preserve facts: mention that tag attaches via one chemical step to protein or short RNA/DNA; binds CA-IV on brain vasculature; antibody with tag accumulates in brain ~8-fold higher after 7 days in mice; in Car4 knockout mice no enrichment; in newborn macaques 20 mg/kg IV dose, antibody with tag found in brain regions and intercapillary tissue on days 5 and 7; each condition had one animal; nanobodies and siRNA also bind CA-IV and enter cells in cell assays; animal experiments focused on antibody.
Now format: after headline, blank line, then paragraphs.
Paragraph 1: introduce BrainCAB tag, its basis, one-step attachment, target CA-IV.
Paragraph 2: describe BBB, need for antibody to cross, concept grew from 2023 work, AAV uses CA-IV.…
🔗 Read original →
We need to wrap key numbers etc: e.g., BrainCAB tag based on brinzolamide, one chemical step, concentration ~8 times higher, 20 mg/kg dose, Car4 gene, etc. Must be selective: at most 4-5 double asterisk wrapped facts. Choose: BrainCAB tag based on brinzolamide, one chemical step, concentration ~8-fold higher, 20 mg/kg dose, Car4 gene knockout. That's 5.
Wrap study/journal citation in single underscores: Nature Chemical Biology, August 26.
Now produce headline under 90 chars: maybe "BrainCAB Tag Enables Antibody Delivery Across Blood‑Brain Barrier in Mice and Newborn Macaques". Count characters: Let's count: "BrainCAB Tag Enables Antibody Delivery Across Blood‑Brain Barrier in Mice and Newborn Macaques". Count: B(1) r2 a3 i4 n5 C6 A7 B8 (space9) T10 a11 g12 (space13) E14 n15 a16 b17 l18 e19 s20 (space21) A22 n23 t24 i25 b26 o27 d28 y29 (space30) D31 e32 l33 i34 v35 e36 r37 y38 (space39) A40 c41 r42 o43 s44 s45 (space46) B47 l48 o49 o50 d‑51 B52 r53 a54 i55 n56 (space57) B58 a59 r60 r61 i62 e63 r64 (space65) i66 n67 (space68) M69 i70 c71 e72 s73 (space74) a75 n76 d77 (space78) N79 e80 w81 b82 o83 r84 n85 (space86) M87 a88 c89 a90 q91 u92 e93 s94. That's 94 characters, exceeds 90. Need under 90. Let's shorten: maybe "BrainCAB Tag Delivers Antibodies Across Blood‑Brain Barrier in Mice and Macaques". Count: "BrainCAB Tag Delivers Antibodies Across Blood‑Brain Barrier in Mice and Macaques". Let's count: B1 r2 a3 i4 n5 C6 A7 B8 (space9) T10 a11 g12 (space13) D14 e15 l16 i17 v18 e19 r20 s21 (space22) A23 n24 t25 i26 b27 o28 d29 i30 e31 s32 (space33) A34 c35 r36 o37 s38 s39 (space40) B41 l42 o43 o44 d‑45 B46 r47 a48 i49 n50 (space51) B52 a53 r54 r55 i56 e57 r58 (space59) i60 n61 (space62) M63 i64 c65 e66 s67 (space68) a69 n70 d71 (space72) M73 a74 c75 a76 q77 u78 e79 s80. That's 80 characters. Good.
Now body: need short paragraphs 2-3 sentences each, separated by blank lines.
We need to include double asterisks for key facts: BrainCAB tag based on brinzolamide, one chemical step, concentration ~8-fold higher, 20 mg/kg dose, Car4 gene knockout.
We need to wrap study/journal citation in single underscores: Nature Chemical Biology, August 26.
We must preserve facts: mention that tag attaches via one chemical step to protein or short RNA/DNA; binds CA-IV on brain vasculature; antibody with tag accumulates in brain ~8-fold higher after 7 days in mice; in Car4 knockout mice no enrichment; in newborn macaques 20 mg/kg IV dose, antibody with tag found in brain regions and intercapillary tissue on days 5 and 7; each condition had one animal; nanobodies and siRNA also bind CA-IV and enter cells in cell assays; animal experiments focused on antibody.
Now format: after headline, blank line, then paragraphs.
Paragraph 1: introduce BrainCAB tag, its basis, one-step attachment, target CA-IV.
Paragraph 2: describe BBB, need for antibody to cross, concept grew from 2023 work, AAV uses CA-IV.…
🔗 Read original →
Nature
CA-IV-directed small-molecule shuttle enables targeted brain delivery of biologics
Nature Chemical Biology - Existing receptor targets to direct delivery of biologics across the blood−brain barrier are ubiquitously expressed in the central nervous system (CNS) and...
We need to translate Russian news post into natural English, format per rules.
First line: short headline under 90 chars, no markdown, no '#'.
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, never a whole sentence.
Wrap study/journal citations and publication references in single underscores (e.g., Nature Aging, July 2026).
We must preserve all facts, numbers, names, citations exactly. No commentary.
We need to identify key facts: numbers: 25,306 images, 40 tissue types, 970 donors, age 21-70 years, 15 tissues reliable trajectories, arteries peak at 30s, uterus/vagina early/mid 50s, digestive tissues, prostate, testes two peaks ~30 and ~50 years, three other algorithms, etc. Also mention date: 31 August in Nature Aging (the work came out). Actually text: "31 августа в Nature Aging вышла работа о PathStAR". So date: August 31, publication in Nature Aging. Could wrap date in double asterisks? It's a date. Also maybe wrap the number of images, donors, tissues, etc. But limit to 4-5 double asterisks total.
We need to be selective: maybe highlight: 25,306 images, 970 donors, 15 tissues, 30s (arteries), early/mid 50s (uterus/vagina), ~30 and ~50 years (digestive, prostate, testes). That's many. Need max 4-5. Choose most important: number of images, number of donors, number of tissues with reliable trajectories, peak ages for arteries, peak ages for uterus/vagina. That's 5.
Alternatively we could include date as double asterisk? But date is also important. However we need max 4-5. Let's decide: include 25,306 images, 970 donors, 15 tissues, arteries peak in the 30s, uterus/vagina peak in early/mid‑50s. That's 5.
We must not wrap whole sentences; just wrap the fact inside double asterisks, not the whole sentence. Eg: "The study analyzed 25,306 images..." That's okay.
Now citations: wrap study/journal citation in single underscores: Nature Aging, August 31 maybe include year? Not given year; but we can just put Nature Aging, August 31. Could also add year if known but not in text. We'll follow given: Nature Aging, August 31.
Now produce paragraphs 2-3 sentences each.
Let's craft translation.
Paragraph 1: Headline line then blank line then first paragraph.
Headline: something like "PathStAR maps human tissue aging peaks across the lifespan". Under 90 chars.
Now body.
Paragraph 1: Introduce method and dataset. Include numbers.
Sentence: "PathStAR matches digital scans of stained tissue sections to measure how quickly their structure changes." Next: "The researchers analyzed 25,306 images from 40 tissue types taken from 970 post‑mortem donors aged 21 to 70." Next: "A separate model estimated the donors’ chronological age from the same sections." That's 3 sentences.
Paragraph 2: Explain how PathStAR works and results.
Sentence: "PathStAR looks for age intervals in which a given tissue’s structure remodels fastest." Next: "Working with the GTEx collection, they split each scan into patches, turned visible structural features into numeric vectors, and compared those vectors between adjacent ten‑year age groups, shifting the group boundaries by one year each step." Next: "This produced a curve of structural‑remodeling speed for each tissue." That's 3 sentences.
Paragraph 3: Report reliable trajectories and peak ages.
Sentence: "Reliable trajectories were obtained for 15 tissues." Next: "In arteries the peak speed occurred in the 30s; in uterus and vagina it rose in the early and mid‑50s, around menopause." Next: "For digestive tissues, prostate and testes the curve showed two rises, near 30 and near 50 years." That's 3 sentences.…
🔗 Read original →
First line: short headline under 90 chars, no markdown, no '#'.
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, never a whole sentence.
Wrap study/journal citations and publication references in single underscores (e.g., Nature Aging, July 2026).
We must preserve all facts, numbers, names, citations exactly. No commentary.
We need to identify key facts: numbers: 25,306 images, 40 tissue types, 970 donors, age 21-70 years, 15 tissues reliable trajectories, arteries peak at 30s, uterus/vagina early/mid 50s, digestive tissues, prostate, testes two peaks ~30 and ~50 years, three other algorithms, etc. Also mention date: 31 August in Nature Aging (the work came out). Actually text: "31 августа в Nature Aging вышла работа о PathStAR". So date: August 31, publication in Nature Aging. Could wrap date in double asterisks? It's a date. Also maybe wrap the number of images, donors, tissues, etc. But limit to 4-5 double asterisks total.
We need to be selective: maybe highlight: 25,306 images, 970 donors, 15 tissues, 30s (arteries), early/mid 50s (uterus/vagina), ~30 and ~50 years (digestive, prostate, testes). That's many. Need max 4-5. Choose most important: number of images, number of donors, number of tissues with reliable trajectories, peak ages for arteries, peak ages for uterus/vagina. That's 5.
Alternatively we could include date as double asterisk? But date is also important. However we need max 4-5. Let's decide: include 25,306 images, 970 donors, 15 tissues, arteries peak in the 30s, uterus/vagina peak in early/mid‑50s. That's 5.
We must not wrap whole sentences; just wrap the fact inside double asterisks, not the whole sentence. Eg: "The study analyzed 25,306 images..." That's okay.
Now citations: wrap study/journal citation in single underscores: Nature Aging, August 31 maybe include year? Not given year; but we can just put Nature Aging, August 31. Could also add year if known but not in text. We'll follow given: Nature Aging, August 31.
Now produce paragraphs 2-3 sentences each.
Let's craft translation.
Paragraph 1: Headline line then blank line then first paragraph.
Headline: something like "PathStAR maps human tissue aging peaks across the lifespan". Under 90 chars.
Now body.
Paragraph 1: Introduce method and dataset. Include numbers.
Sentence: "PathStAR matches digital scans of stained tissue sections to measure how quickly their structure changes." Next: "The researchers analyzed 25,306 images from 40 tissue types taken from 970 post‑mortem donors aged 21 to 70." Next: "A separate model estimated the donors’ chronological age from the same sections." That's 3 sentences.
Paragraph 2: Explain how PathStAR works and results.
Sentence: "PathStAR looks for age intervals in which a given tissue’s structure remodels fastest." Next: "Working with the GTEx collection, they split each scan into patches, turned visible structural features into numeric vectors, and compared those vectors between adjacent ten‑year age groups, shifting the group boundaries by one year each step." Next: "This produced a curve of structural‑remodeling speed for each tissue." That's 3 sentences.
Paragraph 3: Report reliable trajectories and peak ages.
Sentence: "Reliable trajectories were obtained for 15 tissues." Next: "In arteries the peak speed occurred in the 30s; in uterus and vagina it rose in the early and mid‑50s, around menopause." Next: "For digestive tissues, prostate and testes the curve showed two rises, near 30 and near 50 years." That's 3 sentences.…
🔗 Read original →
Nature
Mapping structural aging across human tissues reveals tissue-specific trajectories and coordinated deterioration
Nature Aging - Yadav et al. develop a framework that quantifies tissue structural aging without training on chronological age, using a large dataset of human histology images. They reveal distinct...
We need to translate Russian news post into natural English, format per rules.
First line: short headline under 90 chars, no markdown, no '#'.
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, never a whole sentence.
Wrap study/journal citations and publication references in single underscores _ (e.g., Nature Aging, July 2026).
We need to preserve all facts, numbers, names, citations exactly. No added commentary.
We need to identify citations: The text mentions "27 августа в Science вышла работа о конкурсе OpenKnot". So citation: Science, August 27? Actually date: 27 августа (August 27). Should we keep date? It says "27 августа в Science вышла работа". So we need to wrap the citation in single underscores: Science, August 27. Also maybe mention "OpenKnot" contest? Not a citation. Also mention "SHAPE" as a method, not citation. Also mention "cryo-electron microscopy". Not citation.
We need to wrap key numbers etc in double asterisks. Let's identify important facts:
- Algorithms and participants achieved score 90 out of 100 on 19 out of 20 targets in each of two new rounds.
- In first round: six AI methods and Eterna participants worked on 17 targets; most algorithms lagged behind humans.
- In second round: participants got RNet in interface; AI methods updated with its predictions.
- Then two new sets of 20 targets each, one set with RNA length up to 240 nucleotides.
- In both sets, AI and Eterna participants found solutions scoring 90/100 for 19 targets.
- For 19 out of 20 targets of third round, at least one design showed recovery of at least 80% of specified stems.
- Three molecules, whose sequences were proposed by AI methods, were investigated by cryo-electron microscopy; in all three, seven intended stems were visible.
- On two most detailed maps, additional pairs and contacts between bases appeared, which programs had not predefined.
We need to limit double asterisks to at most 4-5 per post. Choose maybe 5 key facts: scores 90/100 for 19/20 targets, RNA length up to 240 nucleotides, recovery of at least 80% stems, seven intended stems visible, additional pairs/contacts.
We need to wrap each fact with .
But careful: not wrap whole sentence, just the fact within sentence. Eg: "algorithms and participants achieved a score of 90 out of 100 on 19 out of 20 targets". That's two double asterisks groups. Might count as two facts. We need to keep total groups limited to 4-5. Could combine: "90/100 on 19/20 targets". That's one group. Then "up to 240 nucleotides". Then "at least 80% stem recovery". Then "seven intended stems visible". Then "additional base pairs and contacts". That's five groups.
We must not wrap whole sentence; just the fact.
Now citations: wrap study/journal citations in single underscores. We have Science, August 27. Possibly also mention "OpenKnot" contest? Not a citation. Also maybe "RNet" is a model, not citation.
We need to ensure we preserve all facts, numbers, names exactly.
Now produce headline: maybe "AI and Eterna Players Match in RNA Pseudoknot Design Challenge". Count characters: Let's count: "AI and Eterna Players Match in RNA Pseudoknot Design Challenge". That's length? Let's count: AI(2) + space=1 =>3, and=3 =>6, space=1 =>7, Eterna=6 =>13, space=1 =>14, Players=7 =>21, space=1 =>22, Match=5 =>27, space=1 =>28, in=2 =>30, space=1 =>31, RNA=3 =>34, space=1 =>35, Pseudoknot=10 =>45, space=1 =>46, Design=6 =>52, space=1 =>53, Challenge=9 =>62. So 62 chars, under 90.
Now blank line.
Then body paragraphs, each 2-3 sentences.
We need to split into short paragraphs.
Let's craft paragraphs:…
🔗 Read original →
First line: short headline under 90 chars, no markdown, no '#'.
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, never a whole sentence.
Wrap study/journal citations and publication references in single underscores _ (e.g., Nature Aging, July 2026).
We need to preserve all facts, numbers, names, citations exactly. No added commentary.
We need to identify citations: The text mentions "27 августа в Science вышла работа о конкурсе OpenKnot". So citation: Science, August 27? Actually date: 27 августа (August 27). Should we keep date? It says "27 августа в Science вышла работа". So we need to wrap the citation in single underscores: Science, August 27. Also maybe mention "OpenKnot" contest? Not a citation. Also mention "SHAPE" as a method, not citation. Also mention "cryo-electron microscopy". Not citation.
We need to wrap key numbers etc in double asterisks. Let's identify important facts:
- Algorithms and participants achieved score 90 out of 100 on 19 out of 20 targets in each of two new rounds.
- In first round: six AI methods and Eterna participants worked on 17 targets; most algorithms lagged behind humans.
- In second round: participants got RNet in interface; AI methods updated with its predictions.
- Then two new sets of 20 targets each, one set with RNA length up to 240 nucleotides.
- In both sets, AI and Eterna participants found solutions scoring 90/100 for 19 targets.
- For 19 out of 20 targets of third round, at least one design showed recovery of at least 80% of specified stems.
- Three molecules, whose sequences were proposed by AI methods, were investigated by cryo-electron microscopy; in all three, seven intended stems were visible.
- On two most detailed maps, additional pairs and contacts between bases appeared, which programs had not predefined.
We need to limit double asterisks to at most 4-5 per post. Choose maybe 5 key facts: scores 90/100 for 19/20 targets, RNA length up to 240 nucleotides, recovery of at least 80% stems, seven intended stems visible, additional pairs/contacts.
We need to wrap each fact with .
But careful: not wrap whole sentence, just the fact within sentence. Eg: "algorithms and participants achieved a score of 90 out of 100 on 19 out of 20 targets". That's two double asterisks groups. Might count as two facts. We need to keep total groups limited to 4-5. Could combine: "90/100 on 19/20 targets". That's one group. Then "up to 240 nucleotides". Then "at least 80% stem recovery". Then "seven intended stems visible". Then "additional base pairs and contacts". That's five groups.
We must not wrap whole sentence; just the fact.
Now citations: wrap study/journal citations in single underscores. We have Science, August 27. Possibly also mention "OpenKnot" contest? Not a citation. Also maybe "RNet" is a model, not citation.
We need to ensure we preserve all facts, numbers, names exactly.
Now produce headline: maybe "AI and Eterna Players Match in RNA Pseudoknot Design Challenge". Count characters: Let's count: "AI and Eterna Players Match in RNA Pseudoknot Design Challenge". That's length? Let's count: AI(2) + space=1 =>3, and=3 =>6, space=1 =>7, Eterna=6 =>13, space=1 =>14, Players=7 =>21, space=1 =>22, Match=5 =>27, space=1 =>28, in=2 =>30, space=1 =>31, RNA=3 =>34, space=1 =>35, Pseudoknot=10 =>45, space=1 =>46, Design=6 =>52, space=1 =>53, Challenge=9 =>62. So 62 chars, under 90.
Now blank line.
Then body paragraphs, each 2-3 sentences.
We need to split into short paragraphs.
Let's craft paragraphs:…
🔗 Read original →
PubMed Central (PMC)
De novo design of RNA pseudoknots with deep learning
RNA design has been hindered by the limited accuracy of 3D structure prediction. Here, we show that intricate RNA structures can be generated with current deep learning tools through accurate de novo design of pseudoknot secondary structures. In an ...
Longevity Survey Database 'Who Wants to Live Forever' Released
On August 31, database creator Maxim Elison announced the release of version 1.1.3 of the 'Who Wants to Live Forever' registry, which links longevity percentages to specific questions and their sources. The registry contains 185 sources, 2,404 numerical observations, and 37 charts, storing for each result the exact question, conditions, and primary source.
The dashboard includes two U.S. records from 2025 about living to 100 years. In one survey respondents name their desired age, with 30% selecting 100. In another, a yes/no question receives agreement from 49% of participants. A different pair shows 57% wanting to reach 1
🔗 Read original →
On August 31, database creator Maxim Elison announced the release of version 1.1.3 of the 'Who Wants to Live Forever' registry, which links longevity percentages to specific questions and their sources. The registry contains 185 sources, 2,404 numerical observations, and 37 charts, storing for each result the exact question, conditions, and primary source.
The dashboard includes two U.S. records from 2025 about living to 100 years. In one survey respondents name their desired age, with 30% selecting 100. In another, a yes/no question receives agreement from 49% of participants. A different pair shows 57% wanting to reach 1
🔗 Read original →
PubMed Central (PMC)
Gender disparity in the individual attitude toward longevity among Japanese population: Findings from a national survey
The unprecedented population aging brings profound influences to the social values of longevity. The individual attitudes toward the expended life time deserves scrutiny, as it reflects the impacts of social networks and social welfare on people’s ...
AI‑Driven AutoDiscovery Finds Immune Signal in Lobular Breast Cancer
On 27 August, Ai2 and Providence Swedish reported work in which the AutoDiscovery language model searched breast‑cancer data for testable hypotheses; oncologist comments narrowed the search, and one signal was later validated in independent data and tumor tissue.
Lobular cancer was compared with the more common ductal type using the open TCGA database, which contains 1,097 cases with tumor type, mutations, gene activity, and treatment outcomes. AutoDiscovery generates hypotheses, plans analyses, writes executable Python code, runs calculations, and highlights results that most shift its hypothesis score; researchers receive the hypothesis, analysis, and code to reproduce the check.
In the SetScope study, two coding errors altered results enough for the author to retract them. The first run examined only table descriptions and tested 100 hypotheses, which reviewers deemed unsuitable for clinical interpretation, prompting the oncologist to comment on 26 positive findings. A second run evaluated 500 hypotheses.
Among the 13 top‑scoring results from the second run, the third‑ranked hypothesis proposed higher activity of PDCD1 and CD274 in lobular tumors. PDCD1 encodes the PD‑1 receptor and CD274 encodes the PD‑L1 ligand; their interaction suppresses T‑cell attack on the tumor.
Using the METABRIC database, the authors selected hormone‑sensitive, HER2‑negative primary tumors: 696 ductal and 74 lobular. Both genes showed slightly higher expression in lobular tumors. They then stained 12 lobular tumor samples and six normal tissue samples to distinguish cell types, finding more CD8⁺ and CD4⁺ T cells bearing PD‑1 in the stroma surrounding lobular cancers.
Oncologist Kelly Polson described the sequence in the partnership announcement: “AutoDiscovery helped us see a promising signal we might otherwise have missed; we then checked it on additional data sets and in the lab.” The earlier GELATO 2023 study of metastatic lobular cancer had examined carboplatin plus PD‑L1 blockade; the authors now recommend separate evaluation of immunotherapy for lobular cancer in future trials, noting that oncologist guidance directed the search while independent databases and tissue samples enabled two‑way verification.
🔗 Read original →
On 27 August, Ai2 and Providence Swedish reported work in which the AutoDiscovery language model searched breast‑cancer data for testable hypotheses; oncologist comments narrowed the search, and one signal was later validated in independent data and tumor tissue.
Lobular cancer was compared with the more common ductal type using the open TCGA database, which contains 1,097 cases with tumor type, mutations, gene activity, and treatment outcomes. AutoDiscovery generates hypotheses, plans analyses, writes executable Python code, runs calculations, and highlights results that most shift its hypothesis score; researchers receive the hypothesis, analysis, and code to reproduce the check.
In the SetScope study, two coding errors altered results enough for the author to retract them. The first run examined only table descriptions and tested 100 hypotheses, which reviewers deemed unsuitable for clinical interpretation, prompting the oncologist to comment on 26 positive findings. A second run evaluated 500 hypotheses.
Among the 13 top‑scoring results from the second run, the third‑ranked hypothesis proposed higher activity of PDCD1 and CD274 in lobular tumors. PDCD1 encodes the PD‑1 receptor and CD274 encodes the PD‑L1 ligand; their interaction suppresses T‑cell attack on the tumor.
Using the METABRIC database, the authors selected hormone‑sensitive, HER2‑negative primary tumors: 696 ductal and 74 lobular. Both genes showed slightly higher expression in lobular tumors. They then stained 12 lobular tumor samples and six normal tissue samples to distinguish cell types, finding more CD8⁺ and CD4⁺ T cells bearing PD‑1 in the stroma surrounding lobular cancers.
Oncologist Kelly Polson described the sequence in the partnership announcement: “AutoDiscovery helped us see a promising signal we might otherwise have missed; we then checked it on additional data sets and in the lab.” The earlier GELATO 2023 study of metastatic lobular cancer had examined carboplatin plus PD‑L1 blockade; the authors now recommend separate evaluation of immunotherapy for lobular cancer in future trials, noting that oncologist guidance directed the search while independent databases and tissue samples enabled two‑way verification.
🔗 Read original →
PubMed Central (PMC)
PD-L1 blockade in combination with carboplatin as immune induction in metastatic lobular breast cancer: the GELATO trial
Invasive lobular breast cancer (ILC) is the second most common histological breast cancer subtype, but ILC-specific trials are lacking. Translational research revealed an immune-related ILC subset, and in mouse ILC models, synergy between immune ...
Light‑softening gel lets researchers control crypt division in mouse intestinal organoids
On 29 August, researchers published a study in Advanced Science describing how a light‑softening hydrogel enabled precise control of crypt division in mouse intestinal organoids. The organoids are three‑dimensional models of the intestinal epithelium that contain stem‑cell‑rich crypts. In normal growth or repair, a crypt can split into two daughter crypts, but in standard organoids this splitting occurs randomly, making it hard to follow a single structure from start to finish.
They placed the organoids in a soft gel that a laser can locally soften. First, the laser created a single channel for one crypt; after three days, two V‑shaped channels were made at its base. The tissue grew into the softened regions, allowing the researchers to set the time and place of division and to watch one crypt develop into two
🔗 Read original →
On 29 August, researchers published a study in Advanced Science describing how a light‑softening hydrogel enabled precise control of crypt division in mouse intestinal organoids. The organoids are three‑dimensional models of the intestinal epithelium that contain stem‑cell‑rich crypts. In normal growth or repair, a crypt can split into two daughter crypts, but in standard organoids this splitting occurs randomly, making it hard to follow a single structure from start to finish.
They placed the organoids in a soft gel that a laser can locally soften. First, the laser created a single channel for one crypt; after three days, two V‑shaped channels were made at its base. The tissue grew into the softened regions, allowing the researchers to set the time and place of division and to watch one crypt develop into two
🔗 Read original →
PubMed Central (PMC)
Sequential Patterning of Photoresponsive Hydrogels Directs Crypt Fission and Reveals the Role of Epithelial Curvature on Fission…
Fission increases the number of crypts in the intestine during neonatal growth and also restores crypt density after injury by bifurcation of a pre‐existing parent crypt into daughter crypts. While fission is typically symmetric in healthy crypts, ...
We need to translate Russian news post to English, format: first line headline under 90 chars, no markdown prefix. 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, never a whole sentence. Wrap study/journal citations and publication references in single underscores (e.g. Nature Aging, July 2026). Must preserve facts, numbers, names, citations exactly. No commentary, no invented detail. No source link.
We need to extract facts: date: 29 August (presumably 2024? Not given year. The text: "29 августа в Advanced Science вышла работа о мышиных кишечных органоидах". So date: August 29 (year not given). Could be 2024? Not specified. We'll keep as "August 29". Might need year? The original Russian didn't include year. We'll just keep "August 29". Might be ambiguous but we preserve exactly as given: "29 августа". In English: "August 29". We'll not add year.
Important facts to bold: numbers: 184 organoids, ~70% formed daughter crypts, ~85% of successful divisions had short/long daughter length ratio >=0.7, channel widths 50 and 70 micrometers, gene Myh9, myosin IIA, maybe also "light‑softening gel". We need at most 4-5 bolded facts. Choose: 184 organoids, ~70%, ~85%, 50 and 70 micrometers, Myh9 gene. That's 5.
Citations: need to wrap study/journal citation and publication references in single underscores. The work published in Advanced Science on August 29. So we need "Advanced Science, August 29". Also maybe mention "2025 year work"? The text: "В работе 2025 года часть нынешней команды уже пользовалась светочувствительным гелем...". That is a citation to a 2025 work. We need to wrap that as well: maybe "2025 work" but better: "some 2025 study" but we need to keep exact reference: "В работе 2025 года". So we can put "2025 work" but we need to preserve the fact that it's a 2025 work. Could format as "2025 study". However we need to wrap study/journal citations and publication references in single underscores. So we can put "2025 work" as a reference. Also the current work is in Advanced Science, we already have that.
We must not bold whole sentences. So we will embed bold within sentences.
Now produce headline: maybe "Light‑softening gel lets researchers control crypt division in mouse intestinal organoids". Count characters: Let's count: "Light‑softening gel lets researchers control crypt division in mouse intestinal organoids". Count characters including spaces: Let's approximate: Light‑softening (16 inc hyphen?), plus space =17, gel (3) =>20, space=21, lets(4)=>25, space=26, researchers(10)=>36, space=37, control(7)=>44, space=45, crypt(5)=>50, space=51, division(8)=>59, space=60, in(2)=>62, space=63, mouse(5)=>68, space=69, intestinal(10)=>79, space=80, organoids(8)=>88. So 88 characters, under 90. Good.
Now body paragraphs. Need short paragraphs 2-3 sentences each, separated by blank lines.
We'll write maybe 4-5 paragraphs.
Paragraph 1: Introduce the study: On August 29, a paper in Advanced Science described how a light‑softening hydrogel enabled researchers to shape and split intestinal crypts in 3D mouse organoids. They used a laser to locally soften the gel, creating channels that guided crypt growth and division.
Paragraph 2: Details of the method: First, a laser made a single channel for one crypt; after three days, two V‑shaped channels were formed at its base. Tissue grew into the softened zones, letting scientists set the time and place of division and watch one crypt produce two daughters.…
🔗 Read original →
We need to extract facts: date: 29 August (presumably 2024? Not given year. The text: "29 августа в Advanced Science вышла работа о мышиных кишечных органоидах". So date: August 29 (year not given). Could be 2024? Not specified. We'll keep as "August 29". Might need year? The original Russian didn't include year. We'll just keep "August 29". Might be ambiguous but we preserve exactly as given: "29 августа". In English: "August 29". We'll not add year.
Important facts to bold: numbers: 184 organoids, ~70% formed daughter crypts, ~85% of successful divisions had short/long daughter length ratio >=0.7, channel widths 50 and 70 micrometers, gene Myh9, myosin IIA, maybe also "light‑softening gel". We need at most 4-5 bolded facts. Choose: 184 organoids, ~70%, ~85%, 50 and 70 micrometers, Myh9 gene. That's 5.
Citations: need to wrap study/journal citation and publication references in single underscores. The work published in Advanced Science on August 29. So we need "Advanced Science, August 29". Also maybe mention "2025 year work"? The text: "В работе 2025 года часть нынешней команды уже пользовалась светочувствительным гелем...". That is a citation to a 2025 work. We need to wrap that as well: maybe "2025 work" but better: "some 2025 study" but we need to keep exact reference: "В работе 2025 года". So we can put "2025 work" but we need to preserve the fact that it's a 2025 work. Could format as "2025 study". However we need to wrap study/journal citations and publication references in single underscores. So we can put "2025 work" as a reference. Also the current work is in Advanced Science, we already have that.
We must not bold whole sentences. So we will embed bold within sentences.
Now produce headline: maybe "Light‑softening gel lets researchers control crypt division in mouse intestinal organoids". Count characters: Let's count: "Light‑softening gel lets researchers control crypt division in mouse intestinal organoids". Count characters including spaces: Let's approximate: Light‑softening (16 inc hyphen?), plus space =17, gel (3) =>20, space=21, lets(4)=>25, space=26, researchers(10)=>36, space=37, control(7)=>44, space=45, crypt(5)=>50, space=51, division(8)=>59, space=60, in(2)=>62, space=63, mouse(5)=>68, space=69, intestinal(10)=>79, space=80, organoids(8)=>88. So 88 characters, under 90. Good.
Now body paragraphs. Need short paragraphs 2-3 sentences each, separated by blank lines.
We'll write maybe 4-5 paragraphs.
Paragraph 1: Introduce the study: On August 29, a paper in Advanced Science described how a light‑softening hydrogel enabled researchers to shape and split intestinal crypts in 3D mouse organoids. They used a laser to locally soften the gel, creating channels that guided crypt growth and division.
Paragraph 2: Details of the method: First, a laser made a single channel for one crypt; after three days, two V‑shaped channels were formed at its base. Tissue grew into the softened zones, letting scientists set the time and place of division and watch one crypt produce two daughters.…
🔗 Read original →
PubMed Central (PMC)
Sequential Patterning of Photoresponsive Hydrogels Directs Crypt Fission and Reveals the Role of Epithelial Curvature on Fission…
Fission increases the number of crypts in the intestine during neonatal growth and also restores crypt density after injury by bifurcation of a pre‐existing parent crypt into daughter crypts. While fission is typically symmetric in healthy crypts, ...
We need to translate Russian news into English, format with headline line under 90 chars, then blank line, then body paragraphs (2-3 sentences each) separated by blank lines. Wrap 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.
We need to identify key facts: FATE DNA editor, described August 31 in Nature Communications. Gene LMNA, progerin, farnesyl. Numbers: 322 of 323 progerin-positive muscle cells, 8.55% editing efficiency. Possibly also mention date August 31. Also maybe mention Hutchinson-Gilford progeria syndrome. Also mention FATE replaces one letter in LMNA tail. Also mention lipid nanoparticles.
We need to select at most 4-5 double asterisk wrapped facts. Choose: August 31, Nature Communications, 322 of 323, 8.55%, maybe FATE? But gene names also need double asterisks? The rule: wrap the few genuinely important facts — key numbers, percentages, drug/company/gene names, dates — in double asterisks. So gene names like LMNA, progerin, farnesyl, FATE could be considered important. But we need to be selective, at most 4-5 total. So we need to decide which to highlight. Probably include: August 31, Nature Communications, 322 of 323, 8.55%, and maybe LMNA or FATE. But we need to keep within 4-5. Let's pick: August 31, Nature Communications, 322 of 323, 8.55%, LMNA. That's 5.
Now citations: study/journal citations and publication references in single underscores. So we need to wrap the journal name and date: Nature Communications, August 31. Or maybe Nature Communications and date separate? The rule: wrap study/journal citations and publication references in single underscores (e.g. Nature Aging, July 2026). So we should put the whole citation: Nature Communications, August 31. That satisfies.
Now we need to produce headline under 90 chars, no markdown, no prefix '#'. Something like: "DNA editor FATE detaches progerin from nuclear envelope in human organoids". Count characters: Let's count: "DNA editor FATE detaches progerin from nuclear envelope in human organoids". That's 66? Let's count: D(1)N2A3 space4 e5d6i7t8o9r10 space11F12A13T14E15 space16d17e18t19a20c21h22e23s24 space25p26r27o28g29e30r31i32n33 space34f35r36o37m38 space39n40u41c42l43e44a45r46 space47e48n49v50e51l52o53p54e55 space56i57n58 space59h60u61m62a63n64 space65o66r67g68a69n70o71i72d73s74. So 74 chars, okay.
Now body: need short paragraphs 2-3 sentences each, separated by blank lines.
We need to preserve all facts, numbers, names, citations exactly. Do not add commentary.
Let's draft paragraphs.
Paragraph 1: Introduce FATE editor, described August 31 in Nature Communications, edits LMNA gene to prevent farnesylation of progerin.
Paragraph 2: Describe effect in neuromuscular organoids: progerin loses lipid tag, distributes in nucleus, DNA damage response markers γH2AX and 53BP1 form foci after irradiation; in muscle cells previously lacking foci, after editing they appear.
Paragraph 3: Provide specifics: In 322 of 323 progerin-positive muscle cells, no γH2AX foci before editing; 53BP1 retained at nuclear envelope. After FATE editing, foci reappear. Also mention that editing replaces one nucleotide in LMNA tail, preventing farnesyl attachment.
Paragraph 4: Mention that FATE also works in organoids with non-classic LMNA variant, freeing 53BP1 and restoring foci. Also that authors packaged FATE mRNA into lipid nanoparticles, microinjected into muscle part of organoids; after ten days editing efficiency up to 8.55%, progerin redistributed, DNA damage foci formed after irradiation.…
🔗 Read original →
We need to identify key facts: FATE DNA editor, described August 31 in Nature Communications. Gene LMNA, progerin, farnesyl. Numbers: 322 of 323 progerin-positive muscle cells, 8.55% editing efficiency. Possibly also mention date August 31. Also maybe mention Hutchinson-Gilford progeria syndrome. Also mention FATE replaces one letter in LMNA tail. Also mention lipid nanoparticles.
We need to select at most 4-5 double asterisk wrapped facts. Choose: August 31, Nature Communications, 322 of 323, 8.55%, maybe FATE? But gene names also need double asterisks? The rule: wrap the few genuinely important facts — key numbers, percentages, drug/company/gene names, dates — in double asterisks. So gene names like LMNA, progerin, farnesyl, FATE could be considered important. But we need to be selective, at most 4-5 total. So we need to decide which to highlight. Probably include: August 31, Nature Communications, 322 of 323, 8.55%, and maybe LMNA or FATE. But we need to keep within 4-5. Let's pick: August 31, Nature Communications, 322 of 323, 8.55%, LMNA. That's 5.
Now citations: study/journal citations and publication references in single underscores. So we need to wrap the journal name and date: Nature Communications, August 31. Or maybe Nature Communications and date separate? The rule: wrap study/journal citations and publication references in single underscores (e.g. Nature Aging, July 2026). So we should put the whole citation: Nature Communications, August 31. That satisfies.
Now we need to produce headline under 90 chars, no markdown, no prefix '#'. Something like: "DNA editor FATE detaches progerin from nuclear envelope in human organoids". Count characters: Let's count: "DNA editor FATE detaches progerin from nuclear envelope in human organoids". That's 66? Let's count: D(1)N2A3 space4 e5d6i7t8o9r10 space11F12A13T14E15 space16d17e18t19a20c21h22e23s24 space25p26r27o28g29e30r31i32n33 space34f35r36o37m38 space39n40u41c42l43e44a45r46 space47e48n49v50e51l52o53p54e55 space56i57n58 space59h60u61m62a63n64 space65o66r67g68a69n70o71i72d73s74. So 74 chars, okay.
Now body: need short paragraphs 2-3 sentences each, separated by blank lines.
We need to preserve all facts, numbers, names, citations exactly. Do not add commentary.
Let's draft paragraphs.
Paragraph 1: Introduce FATE editor, described August 31 in Nature Communications, edits LMNA gene to prevent farnesylation of progerin.
Paragraph 2: Describe effect in neuromuscular organoids: progerin loses lipid tag, distributes in nucleus, DNA damage response markers γH2AX and 53BP1 form foci after irradiation; in muscle cells previously lacking foci, after editing they appear.
Paragraph 3: Provide specifics: In 322 of 323 progerin-positive muscle cells, no γH2AX foci before editing; 53BP1 retained at nuclear envelope. After FATE editing, foci reappear. Also mention that editing replaces one nucleotide in LMNA tail, preventing farnesyl attachment.
Paragraph 4: Mention that FATE also works in organoids with non-classic LMNA variant, freeing 53BP1 and restoring foci. Also that authors packaged FATE mRNA into lipid nanoparticles, microinjected into muscle part of organoids; after ten days editing efficiency up to 8.55%, progerin redistributed, DNA damage foci formed after irradiation.…
🔗 Read original →
PubMed Central (PMC)
Clinical Trial of Protein Farnesylation Inhibitors Lonafarnib, Pravastatin and Zoledronic Acid in Children with Hutchinson-Gilford…
Hutchinson-Gilford progeria syndrome is an extremely rare, fatal, segmental premature aging syndrome caused by a mutation in LMNA yielding the farnesylated aberrant protein, progerin. Without progerin-specific treatment, death occurs at an average ...
We need to translate Russian news post into natural English, format per rules.
First line: short headline under 90 chars. No markdown, no '#'.
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. No added commentary.
We need to identify key facts: date 31 августа (August 31) in Nature Communications described FATE. Gene LMNA, progerin, farnesyl, etc. Numbers: 322 of 323 progerin-positive muscle cells lacked γH2AX foci; 53BP1 retained at nuclear envelope. Also editing efficiency max 8.55% after ten days. Also maybe mention Hutchinson-Gilford progeria syndrome (HGPS). Also mention that FATE replaces one letter in LMNA tail. Also mention lipid nanoparticles delivering mRNA.
We need to select at most 4-5 double-asterisk facts. Choose: date (August 31), journal Nature Communications, gene LMNA, progerin, farnesyl, numbers 322/323, editing efficiency 8.55%, maybe Hutchinson-Gilford progeria syndrome. But we need to be selective: at most 4-5. Let's pick: August 31, Nature Communications, LMNA, progerin, farnesyl, 322 of 323, 8.55%. That's many. Need max 4-5. Let's choose: August 31, Nature Communications, LMNA, progerin, 8.55% maybe also 322 of 323. That's 6. Need reduce.
We can combine some: maybe we can put date and journal together? But each double asterisk wraps a fact; we could put "August 31 in Nature Communications" but the citation should be underscores, not double asterisks. So date could be double asterisk, journal underscores. So date August 31 is one. Journal Nature Communications is underscores (not counted). Then we need gene name LMNA maybe double asterisk? Could be considered important. Progerin maybe double asterisk? Farnesyl maybe double asterisk? Number 322 of 323 maybe double asterisk. Editing efficiency 8.55% maybe double asterisk. That's many.
We need at most 4-5 double asterisk facts. Let's decide which are most important: date, journal (underscores), LMNA gene, progerin, farnesyl, editing efficiency, 322/323. Perhaps we can combine LMNA and progerin into one fact? Not really.
We could choose: LMNA, progerin, farnesyl, 8.55%, 322 of 323. That's 5. Date and journal can be in underscores? Date cannot be underscores because it's not a citation. But we could put date in double asterisk as well, but then exceed limit. Maybe we can omit date double asterisk and just mention date in plain text? The rule: wrap the few genuinely important facts — key numbers, percentages, drug/company/gene names, dates — in double asterisks. So dates should be double asterisk if we consider them important. But we can maybe not treat date as key fact? It's somewhat important but maybe we can skip double asterisk for date and just mention normally. The rule says wrap the few genuinely important facts — key numbers, percentages, drug/company/gene names, dates — in double asterisks. It implies we should wrap those categories, but we can be selective: at most 4-5 per post. So we need to choose which dates, numbers, etc to wrap. We can omit date wrapping if we stay within limit.
Thus we can wrap: LMNA, progerin, farnesyl, 8.55%, 322 of 323. That's 5.
Now we need to wrap study/journal citations in single underscores: Nature Communications. Also maybe mention Hutchinson-Gilford progeria syndrome (HGPS) but not wrap.…
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First line: short headline under 90 chars. No markdown, no '#'.
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. No added commentary.
We need to identify key facts: date 31 августа (August 31) in Nature Communications described FATE. Gene LMNA, progerin, farnesyl, etc. Numbers: 322 of 323 progerin-positive muscle cells lacked γH2AX foci; 53BP1 retained at nuclear envelope. Also editing efficiency max 8.55% after ten days. Also maybe mention Hutchinson-Gilford progeria syndrome (HGPS). Also mention that FATE replaces one letter in LMNA tail. Also mention lipid nanoparticles delivering mRNA.
We need to select at most 4-5 double-asterisk facts. Choose: date (August 31), journal Nature Communications, gene LMNA, progerin, farnesyl, numbers 322/323, editing efficiency 8.55%, maybe Hutchinson-Gilford progeria syndrome. But we need to be selective: at most 4-5. Let's pick: August 31, Nature Communications, LMNA, progerin, farnesyl, 322 of 323, 8.55%. That's many. Need max 4-5. Let's choose: August 31, Nature Communications, LMNA, progerin, 8.55% maybe also 322 of 323. That's 6. Need reduce.
We can combine some: maybe we can put date and journal together? But each double asterisk wraps a fact; we could put "August 31 in Nature Communications" but the citation should be underscores, not double asterisks. So date could be double asterisk, journal underscores. So date August 31 is one. Journal Nature Communications is underscores (not counted). Then we need gene name LMNA maybe double asterisk? Could be considered important. Progerin maybe double asterisk? Farnesyl maybe double asterisk? Number 322 of 323 maybe double asterisk. Editing efficiency 8.55% maybe double asterisk. That's many.
We need at most 4-5 double asterisk facts. Let's decide which are most important: date, journal (underscores), LMNA gene, progerin, farnesyl, editing efficiency, 322/323. Perhaps we can combine LMNA and progerin into one fact? Not really.
We could choose: LMNA, progerin, farnesyl, 8.55%, 322 of 323. That's 5. Date and journal can be in underscores? Date cannot be underscores because it's not a citation. But we could put date in double asterisk as well, but then exceed limit. Maybe we can omit date double asterisk and just mention date in plain text? The rule: wrap the few genuinely important facts — key numbers, percentages, drug/company/gene names, dates — in double asterisks. So dates should be double asterisk if we consider them important. But we can maybe not treat date as key fact? It's somewhat important but maybe we can skip double asterisk for date and just mention normally. The rule says wrap the few genuinely important facts — key numbers, percentages, drug/company/gene names, dates — in double asterisks. It implies we should wrap those categories, but we can be selective: at most 4-5 per post. So we need to choose which dates, numbers, etc to wrap. We can omit date wrapping if we stay within limit.
Thus we can wrap: LMNA, progerin, farnesyl, 8.55%, 322 of 323. That's 5.
Now we need to wrap study/journal citations in single underscores: Nature Communications. Also maybe mention Hutchinson-Gilford progeria syndrome (HGPS) but not wrap.…
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PubMed Central (PMC)
Clinical Trial of Protein Farnesylation Inhibitors Lonafarnib, Pravastatin and Zoledronic Acid in Children with Hutchinson-Gilford…
Hutchinson-Gilford progeria syndrome is an extremely rare, fatal, segmental premature aging syndrome caused by a mutation in LMNA yielding the farnesylated aberrant protein, progerin. Without progerin-specific treatment, death occurs at an average ...
CAR-T cells may show second receptor before first recognizes target
On August 31 the authors posted a preprint describing a two‑step CAR‑T strategy in which the synthetic SynNotch receptor detects high HER2 density and then activates a CAR that kills the target. In some T cells the CAR appeared on the surface before the SynNotch signal arrived.
In three different constructs the basal CAR surface level was measured at 6%, 2%, and 0.2% of resting T cells. The construct with the highest background (6%) showed the poorest ability to discriminate between high‑ and low‑HER2 cells.
In a two‑tumor mouse model the high‑background construct reduced both high‑ and low‑HER2 tumors. After binding HER2, CAR triggers T‑cell proliferation, so even a small initial CAR‑positive fraction can shape the whole population. The authors’ mathematical model incorporated the fraction of such cells, HER2 density, and the T‑cell‑to‑target ratio; experiments indicated that optimal discrimination required different T‑cell doses for each construct.
To lower basal CAR expression they attached the mScarlet tag to the CAR C‑terminus, which cut the background by about 60% while preserving signal‑induced CAR. Degron tags reduced background further in culture, but T cells bearing degrons lost cytotoxic activity more quickly after CAR activation. In mouse models, mScarlet improved discrimination, suppressing high‑antigen tumors while low‑antigen tumors continued to grow.
For the two‑step CAR‑T design, both the timing of CAR expression and its residual level after proper signaling are crucial. Rohelo Hernandez‑Lopez et al., 2021
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On August 31 the authors posted a preprint describing a two‑step CAR‑T strategy in which the synthetic SynNotch receptor detects high HER2 density and then activates a CAR that kills the target. In some T cells the CAR appeared on the surface before the SynNotch signal arrived.
In three different constructs the basal CAR surface level was measured at 6%, 2%, and 0.2% of resting T cells. The construct with the highest background (6%) showed the poorest ability to discriminate between high‑ and low‑HER2 cells.
In a two‑tumor mouse model the high‑background construct reduced both high‑ and low‑HER2 tumors. After binding HER2, CAR triggers T‑cell proliferation, so even a small initial CAR‑positive fraction can shape the whole population. The authors’ mathematical model incorporated the fraction of such cells, HER2 density, and the T‑cell‑to‑target ratio; experiments indicated that optimal discrimination required different T‑cell doses for each construct.
To lower basal CAR expression they attached the mScarlet tag to the CAR C‑terminus, which cut the background by about 60% while preserving signal‑induced CAR. Degron tags reduced background further in culture, but T cells bearing degrons lost cytotoxic activity more quickly after CAR activation. In mouse models, mScarlet improved discrimination, suppressing high‑antigen tumors while low‑antigen tumors continued to grow.
For the two‑step CAR‑T design, both the timing of CAR expression and its residual level after proper signaling are crucial. Rohelo Hernandez‑Lopez et al., 2021
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