We need to translate Russian news to 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.
Let's extract facts:
- NovaGo Therapeutics (Swiss biotech) announced closing of financing round on 24 million Swiss francs, or $30 million. Date: 2 September (presumably 2025? Not specified but article says "2 сентября швейцарская биотехнологическая компания NovaGo Therapeutics объявила о закрытии раунда финансирования". Likely 2025? Not given; we keep as "2 September". No year given; we can keep just date.
- Funds intended for study of antibody NG004 in 120 people with acute spinal cord injury in Germany, Spain, Switzerland.
- Participants to be randomly assigned to groups, allocation concealed from patients and investigators (double-blind).
- Acute spinal cord injury damages nerve pathways that brain uses to send commands to body; in CNS such fibers poorly regrow, making recovery of movement and sensation difficult.
- NovaGo links NG004 to one of molecular obstacles to such recovery.
- Nogo-A — protein described as brake on nerve fiber regrowth and remodeling of nerve connections after injury.
- NG004 — antibody designed to block Nogo-A.
- Developers expect blockade will allow surviving pathways to form new connections.
- In international clinical trial registry ClinicalTrials.gov, entry last updated February 2025, described first phase of NG004: first-in-human administration to people with acute incomplete cervical spinal cord injury.
- Protocol of this phase envisages dose escalation and assessment of safety, tolerability, pharmacokinetics — how antibody behaves in body.
- With these funds NovaGo plans to move from early testing of dosing regimen to 120-patient NG004 study.
We need to wrap key numbers, percentages, drug/company/gene names, dates in double asterisks. At most 4-5 per post.
Select important facts: $30 million, 24 million Swiss francs, 2 September, 120 patients, Nogo-A, NG004, ClinicalTrials.gov, February 2025, maybe acute spinal cord injury.
But we must limit to 4-5 double asterisk wrappings. Let's choose: $30 million, 24 million Swiss francs, 2 September, 120 patients, Nogo-A, NG004, ClinicalTrials.gov, February 2025 – that's 8, too many. Need max 4-5.
We can combine some: maybe only wrap numbers and key names: $30 million, 120 patients, Nogo-A, NG004, ClinicalTrials.gov (that's 5). Dates maybe not wrapped? But date is important fact; we could wrap 2 September instead of one of others. Need to be selective.
Let's decide: wrap $30 million, 120 patients, Nogo-A, NG004, ClinicalTrials.gov. That's 5. Dates not wrapped; but we could incorporate date in sentence without wrapping.
Alternatively, we could wrap 2 September instead of one. But we need to keep key numbers: financing amount, patient count, protein name, antibody name, registry. That seems good.…
🔗 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.
Let's extract facts:
- NovaGo Therapeutics (Swiss biotech) announced closing of financing round on 24 million Swiss francs, or $30 million. Date: 2 September (presumably 2025? Not specified but article says "2 сентября швейцарская биотехнологическая компания NovaGo Therapeutics объявила о закрытии раунда финансирования". Likely 2025? Not given; we keep as "2 September". No year given; we can keep just date.
- Funds intended for study of antibody NG004 in 120 people with acute spinal cord injury in Germany, Spain, Switzerland.
- Participants to be randomly assigned to groups, allocation concealed from patients and investigators (double-blind).
- Acute spinal cord injury damages nerve pathways that brain uses to send commands to body; in CNS such fibers poorly regrow, making recovery of movement and sensation difficult.
- NovaGo links NG004 to one of molecular obstacles to such recovery.
- Nogo-A — protein described as brake on nerve fiber regrowth and remodeling of nerve connections after injury.
- NG004 — antibody designed to block Nogo-A.
- Developers expect blockade will allow surviving pathways to form new connections.
- In international clinical trial registry ClinicalTrials.gov, entry last updated February 2025, described first phase of NG004: first-in-human administration to people with acute incomplete cervical spinal cord injury.
- Protocol of this phase envisages dose escalation and assessment of safety, tolerability, pharmacokinetics — how antibody behaves in body.
- With these funds NovaGo plans to move from early testing of dosing regimen to 120-patient NG004 study.
We need to wrap key numbers, percentages, drug/company/gene names, dates in double asterisks. At most 4-5 per post.
Select important facts: $30 million, 24 million Swiss francs, 2 September, 120 patients, Nogo-A, NG004, ClinicalTrials.gov, February 2025, maybe acute spinal cord injury.
But we must limit to 4-5 double asterisk wrappings. Let's choose: $30 million, 24 million Swiss francs, 2 September, 120 patients, Nogo-A, NG004, ClinicalTrials.gov, February 2025 – that's 8, too many. Need max 4-5.
We can combine some: maybe only wrap numbers and key names: $30 million, 120 patients, Nogo-A, NG004, ClinicalTrials.gov (that's 5). Dates maybe not wrapped? But date is important fact; we could wrap 2 September instead of one of others. Need to be selective.
Let's decide: wrap $30 million, 120 patients, Nogo-A, NG004, ClinicalTrials.gov. That's 5. Dates not wrapped; but we could incorporate date in sentence without wrapping.
Alternatively, we could wrap 2 September instead of one. But we need to keep key numbers: financing amount, patient count, protein name, antibody name, registry. That seems good.…
🔗 Read original →
PR Newswire
NovaGo Therapeutics Closes USD 30 Million Series B Financing to Advance Proof-of-Concept Study in Acute Spinal Cord Injury
/PRNewswire/ -- NovaGo Therapeutics AG, a clinical-stage biotechnology company developing anti-Nogo-A biologics for diseases of the central nervous system,...
OpenAI warns chain‑of‑thought tracking of Astra is fragile amid depth limits
On 2 September, chief scientist Jakub Pachocki of OpenAI said that the sequential computation depth of the advanced model Astra stays within twice the depth of GPT‑4. He noted that this limit reflects the current frontier of the model’s reasoning steps.
AI safety researcher Ryan Greenblatt asked whether developers could quickly raise the number of internal steps the model takes. OpenAI tracks the model’s chain‑of‑thought text—the written trace of its reasoning—to see how training‑learned behavior rules appear on new tasks.
Pachocki called this monitoring method fragile and said it is moving in an unfavorable direction. In earlier descriptions he portrayed Astra as a system for long‑term research that can modify code, run experiments, and report results.
Greenblatt considers the current disclosure of depth useful and defines sequential depth as the number of computation stages the model passes through one after another before answering. He wonders whether Astra has an adjustable parameter that could increase repetitions, how easy it would be to scale, whether it would boost capabilities, and if a small amount of fine‑tuning could sharply raise the repetition
🔗 Read original →
On 2 September, chief scientist Jakub Pachocki of OpenAI said that the sequential computation depth of the advanced model Astra stays within twice the depth of GPT‑4. He noted that this limit reflects the current frontier of the model’s reasoning steps.
AI safety researcher Ryan Greenblatt asked whether developers could quickly raise the number of internal steps the model takes. OpenAI tracks the model’s chain‑of‑thought text—the written trace of its reasoning—to see how training‑learned behavior rules appear on new tasks.
Pachocki called this monitoring method fragile and said it is moving in an unfavorable direction. In earlier descriptions he portrayed Astra as a system for long‑term research that can modify code, run experiments, and report results.
Greenblatt considers the current disclosure of depth useful and defines sequential depth as the number of computation stages the model passes through one after another before answering. He wonders whether Astra has an adjustable parameter that could increase repetitions, how easy it would be to scale, whether it would boost capabilities, and if a small amount of fine‑tuning could sharply raise the repetition
🔗 Read original →
X (formerly Twitter)
Jakub Pachocki (@merettm) on X
I want to prevent a race into unmonitorability kicked off by confused reporting. The depth of the computation graph for our present frontier models, including Astra, is within a factor of two of G…
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 must preserve all facts, numbers, names, citations exactly. No added commentary.
We need to identify important facts: numbers: 2 September (date), Nature journal, 105,502 gene activity profiles, 10 donors with MS and 10 controls, maybe percentages? Not given. Gene names: CFH, Cfh, C3, SCR20, mHDM-FH. Also maybe mention "oxidative damage", "lipid peroxidation". But we need to limit double asterisks to at most 4-5. Choose key numbers/dates: 2 September, Nature, 105,502, CFH, Cfh, C3, SCR20, mHDM-FH maybe too many. Need max 4-5. Let's pick: 2 September, Nature, 105,502, CFH, Cfh? That's 5. Could also include C3 but that would be 6. Maybe we can combine some: we need to keep key facts but limited. Perhaps we can include 2 September, Nature, 105,502, CFH/Cfh, C3? That's still 5 if we treat CFH/Cfh as one? But they are separate names. Could we wrap gene names in double asterisks only when they appear first time? Might exceed limit. Let's think: The instruction: "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 4-5 items to bold. Likely we can bold: 2 September, Nature, 105,502, CFH, C3. That's 5. Or we could bold CFH, Cfh, C3, SCR20, mHDM-FH (5 gene names) but then we lose date/journal. Probably date and journal are important. Let's choose: 2 September, Nature, 105,502, CFH, C3. That covers date, journal, sample size, key gene, complement gene.
We'll need to ensure we don't bold whole sentences. Just wrap those specific tokens.
Now citations: we have only one citation: article published in Nature on 2 September. So we wrap that in single underscores: Nature maybe with date? The rule: wrap study/journal citations and publication references in single underscores (e.g., Nature Aging, July 2026). So we should put Nature, 2 September maybe. The original Russian: "В опытах на клетках и мышах фактор H защищал нейроны от воспалительного повреждения 2 сентября в журнале Nature вышла статья о факторе H". So citation: Nature, 2 September. We'll wrap that as Nature, 2 September.
Now body: need short paragraphs 2-3 sentences each.
Let's outline translation:
Paragraph 1: In experiments on cells and mice, factor H protected neurons from inflammatory damage. A paper published in Nature, 2 September describes factor H — a protein that normally acts extracellularly as a regulator of the innate immune system. In human post‑mortem tissue, the CFH gene encoding this protein was more active in more resilient neurons.
Paragraph 2: The authors tested how factor H works inside neurons using cell cultures and mice. Protection was provided by its SCR20 domain, which reduced oxidative damage to membranes. Retinal ganglion cells — neurons whose axons form the optic nerve — were isolated from the macula of ten donors with multiple sclerosis and ten control donors; after quality control, 105,502 gene‑expression profiles were analysed.…
🔗 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 added commentary.
We need to identify important facts: numbers: 2 September (date), Nature journal, 105,502 gene activity profiles, 10 donors with MS and 10 controls, maybe percentages? Not given. Gene names: CFH, Cfh, C3, SCR20, mHDM-FH. Also maybe mention "oxidative damage", "lipid peroxidation". But we need to limit double asterisks to at most 4-5. Choose key numbers/dates: 2 September, Nature, 105,502, CFH, Cfh, C3, SCR20, mHDM-FH maybe too many. Need max 4-5. Let's pick: 2 September, Nature, 105,502, CFH, Cfh? That's 5. Could also include C3 but that would be 6. Maybe we can combine some: we need to keep key facts but limited. Perhaps we can include 2 September, Nature, 105,502, CFH/Cfh, C3? That's still 5 if we treat CFH/Cfh as one? But they are separate names. Could we wrap gene names in double asterisks only when they appear first time? Might exceed limit. Let's think: The instruction: "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 4-5 items to bold. Likely we can bold: 2 September, Nature, 105,502, CFH, C3. That's 5. Or we could bold CFH, Cfh, C3, SCR20, mHDM-FH (5 gene names) but then we lose date/journal. Probably date and journal are important. Let's choose: 2 September, Nature, 105,502, CFH, C3. That covers date, journal, sample size, key gene, complement gene.
We'll need to ensure we don't bold whole sentences. Just wrap those specific tokens.
Now citations: we have only one citation: article published in Nature on 2 September. So we wrap that in single underscores: Nature maybe with date? The rule: wrap study/journal citations and publication references in single underscores (e.g., Nature Aging, July 2026). So we should put Nature, 2 September maybe. The original Russian: "В опытах на клетках и мышах фактор H защищал нейроны от воспалительного повреждения 2 сентября в журнале Nature вышла статья о факторе H". So citation: Nature, 2 September. We'll wrap that as Nature, 2 September.
Now body: need short paragraphs 2-3 sentences each.
Let's outline translation:
Paragraph 1: In experiments on cells and mice, factor H protected neurons from inflammatory damage. A paper published in Nature, 2 September describes factor H — a protein that normally acts extracellularly as a regulator of the innate immune system. In human post‑mortem tissue, the CFH gene encoding this protein was more active in more resilient neurons.
Paragraph 2: The authors tested how factor H works inside neurons using cell cultures and mice. Protection was provided by its SCR20 domain, which reduced oxidative damage to membranes. Retinal ganglion cells — neurons whose axons form the optic nerve — were isolated from the macula of ten donors with multiple sclerosis and ten control donors; after quality control, 105,502 gene‑expression profiles were analysed.…
🔗 Read original →
Nature
Intracellular complement factor H protects neurons during CNS inflammation
Nature - CFH is a key mediator of neuronal resilience across the central nervous system in mice and humans.
We need to translate Russian news post into natural English, format per rules.
First line: headline under 90 chars, no markdown. Then blank line, then body paragraphs (2-3 sentences each) separated by blank lines.
We need to 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). There's no explicit journal citation in the text, but we have "III фазы INTerpath-001" and "III фазы" etc. Possibly we can treat the study as a citation? The instruction: wrap study/journal citations and publication references in single underscores. We have no explicit journal name, but we could treat "III фазы INTerpath-001" as a study reference? Might be considered a study. Could put INTerpath-001? But they said e.g. Nature Aging, July 2026. So we need to wrap study/journal citations and publication references. The text mentions "III фазы INTerpath-001". That's a trial name. Could be considered a study reference. We'll wrap it in single underscores: INTerpath-001. Also maybe "III фазы" is not needed. We'll just underscore the trial name.
We need to wrap key numbers, percentages, drug/company/gene names, dates in double asterisks. At most 4-5 per post.
Important facts: dates: 2 сентября (September 2), 19 августа (August 19). Drug/company/gene names: MAGE-A3, pембролизумаб (pembrolizumab), intismeran autogene (personalized mRNA therapy), Merck, Moderna. Also maybe "IIB–IV" stages. Also "III фазы". Also maybe "персональная мРНК-терапии intismeran autogene". Also "пембролизумаб". Also "MAGE-A3". Also "Merck and Moderna". Also "INTerpath-001". Also "IIB–IV". Also "September 2" and "August 19". Need to pick at most 4-5 double asterisk items. Let's select: September 2, August 19, MAGE-A3, pembrolizumab, INTerpath-001 (or Merck and Moderna). But we need to keep at most 4-5. Let's do 5: September 2, August 19, MAGE-A3, pembrolizumab, INTerpath-001. Also we could include Merck and Moderna but that would be extra. We'll stick to 5.
Now we need to ensure we don't wrap whole sentences. Just wrap those specific tokens.
Now produce headline: maybe "Essay explains how tumor mutations lead to personalized cancer vaccines". Under 90 chars.
Let's count: "Essay explains how tumor mutations lead to personalized cancer vaccines" length: count characters: E(1) ... Let's approximate: "Essay explains how tumor mutations lead to personalized cancer vaccines" = 58? Actually let's count: Essay(5) + space=1 =>6, explains(7)=>13, space=1=>14, how(3)=>17, space=1=>18, tumor(5)=>23, space=1=>24, mutations(9)=>33, space=1=>34, lead(4)=>38, space=1=>39, to(2)=>41, space=1=>42, personalized(12)=>54, space=1=>55, cancer(6)=>61, space=1=>62, vaccines(7)=>69. So 69 chars, okay.
Now blank line, then body paragraphs.
We need to split into short paragraphs 2-3 sentences each.
Let's craft paragraphs:
Paragraph 1: Introduce essay, author, date, topic.
Sentence: On September 2, machine‑learning engineer Abhishek Mahajan at biotech company published an essay on therapeutic cancer vaccines. He contrasted early attempts to target shared tumor antigens with personalized mRNA drugs made for each patient. Researchers have long sought proteins present in tumors across individuals, such as MAGE‑A3, which was tested in phase III trials for melanoma and non‑small‑cell lung cancer but failed to improve disease‑free survival.
We need to wrap MAGE‑A3 with double asterisks, September 2 with double asterisks. Also maybe "phase III" not needed. Also "September 2" we already have.
Paragraph 2: Explain how T cells recognize peptides via MHC, process to select neoantigens.…
🔗 Read original →
First line: headline under 90 chars, no markdown. Then blank line, then body paragraphs (2-3 sentences each) separated by blank lines.
We need to 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). There's no explicit journal citation in the text, but we have "III фазы INTerpath-001" and "III фазы" etc. Possibly we can treat the study as a citation? The instruction: wrap study/journal citations and publication references in single underscores. We have no explicit journal name, but we could treat "III фазы INTerpath-001" as a study reference? Might be considered a study. Could put INTerpath-001? But they said e.g. Nature Aging, July 2026. So we need to wrap study/journal citations and publication references. The text mentions "III фазы INTerpath-001". That's a trial name. Could be considered a study reference. We'll wrap it in single underscores: INTerpath-001. Also maybe "III фазы" is not needed. We'll just underscore the trial name.
We need to wrap key numbers, percentages, drug/company/gene names, dates in double asterisks. At most 4-5 per post.
Important facts: dates: 2 сентября (September 2), 19 августа (August 19). Drug/company/gene names: MAGE-A3, pембролизумаб (pembrolizumab), intismeran autogene (personalized mRNA therapy), Merck, Moderna. Also maybe "IIB–IV" stages. Also "III фазы". Also maybe "персональная мРНК-терапии intismeran autogene". Also "пембролизумаб". Also "MAGE-A3". Also "Merck and Moderna". Also "INTerpath-001". Also "IIB–IV". Also "September 2" and "August 19". Need to pick at most 4-5 double asterisk items. Let's select: September 2, August 19, MAGE-A3, pembrolizumab, INTerpath-001 (or Merck and Moderna). But we need to keep at most 4-5. Let's do 5: September 2, August 19, MAGE-A3, pembrolizumab, INTerpath-001. Also we could include Merck and Moderna but that would be extra. We'll stick to 5.
Now we need to ensure we don't wrap whole sentences. Just wrap those specific tokens.
Now produce headline: maybe "Essay explains how tumor mutations lead to personalized cancer vaccines". Under 90 chars.
Let's count: "Essay explains how tumor mutations lead to personalized cancer vaccines" length: count characters: E(1) ... Let's approximate: "Essay explains how tumor mutations lead to personalized cancer vaccines" = 58? Actually let's count: Essay(5) + space=1 =>6, explains(7)=>13, space=1=>14, how(3)=>17, space=1=>18, tumor(5)=>23, space=1=>24, mutations(9)=>33, space=1=>34, lead(4)=>38, space=1=>39, to(2)=>41, space=1=>42, personalized(12)=>54, space=1=>55, cancer(6)=>61, space=1=>62, vaccines(7)=>69. So 69 chars, okay.
Now blank line, then body paragraphs.
We need to split into short paragraphs 2-3 sentences each.
Let's craft paragraphs:
Paragraph 1: Introduce essay, author, date, topic.
Sentence: On September 2, machine‑learning engineer Abhishek Mahajan at biotech company published an essay on therapeutic cancer vaccines. He contrasted early attempts to target shared tumor antigens with personalized mRNA drugs made for each patient. Researchers have long sought proteins present in tumors across individuals, such as MAGE‑A3, which was tested in phase III trials for melanoma and non‑small‑cell lung cancer but failed to improve disease‑free survival.
We need to wrap MAGE‑A3 with double asterisks, September 2 with double asterisks. Also maybe "phase III" not needed. Also "September 2" we already have.
Paragraph 2: Explain how T cells recognize peptides via MHC, process to select neoantigens.…
🔗 Read original →
Deleting the Ghr gene in mice at 12 months of age using a tamoxifen‑inducible Cre system extended lifespan in females. The animals received tamoxifen for five days, while controls got peanut oil. This lowered circulating IGF-1 while raising growth hormone levels, indicating reduced tissue sensitivity to the signal.
Female mice lived longer: median lifespan rose by +8%, and the maximum recorded lifespan increased by +12%. Male mice did not show a significant shift in survival curves.
In males, after adjusting for lean body mass, performance on the rotarod and grip‑strength test improved, and vertebral trabecular bone structure was better preserved. Liver single‑nucleus profiling showed hepatocyte gene programs shifting toward a more female‑like pattern.
The work was published 5 September and shows that attenuating GH signaling after midlife can still influence aging, with sex‑specific effects on survival and liver metabolism.
🔗 Read original →
Female mice lived longer: median lifespan rose by +8%, and the maximum recorded lifespan increased by +12%. Male mice did not show a significant shift in survival curves.
In males, after adjusting for lean body mass, performance on the rotarod and grip‑strength test improved, and vertebral trabecular bone structure was better preserved. Liver single‑nucleus profiling showed hepatocyte gene programs shifting toward a more female‑like pattern.
The work was published 5 September and shows that attenuating GH signaling after midlife can still influence aging, with sex‑specific effects on survival and liver metabolism.
🔗 Read original →
PubMed Central (PMC)
Midlife Growth Hormone Receptor Ablation Extends Healthy Lifespan and Induces Sex‐Specific Hepatic Transcriptional Changes at Single‐Cell…
Suppression of growth hormone (GH) signaling is known to be effective to extend lifespan in mammals, yet most models rely on congenital disruption of the GH/insulin‐like growth factor‐1 (IGF‐1) axis. Whether modulation of this pathway later in life ...
We need to translate Russian news post into English, format: first line short headline under 90 chars, no markdown. Then blank line, then body split into short paragraphs (2-3 sentences each), separated by blank lines. Wrap few genuinely important facts — key numbers, percentages, drug/company/gene names, dates — in double asterisks . At most 4-5 per post. Wrap study/journal citations and publication references in single underscores _ (e.g., Nature Aging, July 2026). Must preserve facts, numbers, names, citations exactly. No commentary.
We need to identify key facts: date "4 сентября" (September 4) on Research Square preprint. Twelve artificial condensates. Three proteins: hnRNPA1, tau, FUS. Concentration inside droplets >50-fold. Notable fiber growth delayed. Stress granule definition. RNASEK excess circular RNAs turning stress granules into toxic aggregates. Authors worked with hnRNPA1, tau, FUS. Condensates sequestered soluble molecules. Optical slices and EM showed fibers mainly outside droplets and at boundary. Fiber elongation by adding single protein molecules; when fewer outside, growth slows. At boundary, low external concentration leads to nucleation at boundary; higher leads to nucleation in surrounding solution. Authors added hnRNPA1 variant lacking segment that initiates fiber assembly; this variant reduced protein density at boundary without changing condensate viscosity, and expectation of growth became longer. Viscoelastic property: internal protein-RNA network flows but resists deformation. More viscoelastic condensates slower released one of the studied hnRNPA1 variants outward. Outside fibers had less protein for elongation, thus grew later. Starting point was 2025 work about simple condensate from hnRNPA1 segment: interior retained protein, boundary could accelerate fiber nucleation. New preprint tested this scheme in twelve multi-component systems, then got same direction of effect in condensates from G3BP1 and polyA RNA, and in granules from cell lysate. In human cells authors measured mechanical properties of granules; amyloid fiber growth tracked in reconstructed systems and lysate granules. In these models fiber fate determined by protein location, its density at boundary, and exchange rate between droplet and surrounding solution.
We need to pick at most 4-5 key facts to bold. Likely: date September 4, twelve artificial condensates, >50-fold concentration, three proteins hnRNPA1, tau, FUS, maybe viscoelastic property effect. Also maybe mention G3BP1 and polyA RNA. But limit to 4-5.…
🔗 Read original →
We need to identify key facts: date "4 сентября" (September 4) on Research Square preprint. Twelve artificial condensates. Three proteins: hnRNPA1, tau, FUS. Concentration inside droplets >50-fold. Notable fiber growth delayed. Stress granule definition. RNASEK excess circular RNAs turning stress granules into toxic aggregates. Authors worked with hnRNPA1, tau, FUS. Condensates sequestered soluble molecules. Optical slices and EM showed fibers mainly outside droplets and at boundary. Fiber elongation by adding single protein molecules; when fewer outside, growth slows. At boundary, low external concentration leads to nucleation at boundary; higher leads to nucleation in surrounding solution. Authors added hnRNPA1 variant lacking segment that initiates fiber assembly; this variant reduced protein density at boundary without changing condensate viscosity, and expectation of growth became longer. Viscoelastic property: internal protein-RNA network flows but resists deformation. More viscoelastic condensates slower released one of the studied hnRNPA1 variants outward. Outside fibers had less protein for elongation, thus grew later. Starting point was 2025 work about simple condensate from hnRNPA1 segment: interior retained protein, boundary could accelerate fiber nucleation. New preprint tested this scheme in twelve multi-component systems, then got same direction of effect in condensates from G3BP1 and polyA RNA, and in granules from cell lysate. In human cells authors measured mechanical properties of granules; amyloid fiber growth tracked in reconstructed systems and lysate granules. In these models fiber fate determined by protein location, its density at boundary, and exchange rate between droplet and surrounding solution.
We need to pick at most 4-5 key facts to bold. Likely: date September 4, twelve artificial condensates, >50-fold concentration, three proteins hnRNPA1, tau, FUS, maybe viscoelastic property effect. Also maybe mention G3BP1 and polyA RNA. But limit to 4-5.…
🔗 Read original →
Researchsquare
An error has occurred
Research Square is a preprint platform that makes research communication faster, fairer, and more useful.
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.
We need to identify key facts: date: 4 September (article in Science Advances). Gene: Polg, variant POLG D257A. Mutation load: at nine months about half compared to whole-body POLG mutant. Activity of complex I and IV reduced about a quarter (~25%). Fractional shortening reduced similarly. At 12-16 months, contractility continues weakening; by 16 months mutation load reaches level of nine-month whole-body mutant. Collagen deposits observed. Interferon signals and antigen presentation increased with higher mutation load. More immune cells, especially dendritic.
We need to limit double asterisks to at most 4-5. Choose key numbers: date, mutation load half, activity reduction quarter (~25%), fractional shortening reduction quarter, mutation load reaches level at 16 months. That's 5 maybe. Also maybe gene name POLG D257A? That's a name but maybe not needed as double asterisk? Could be considered important. But we must limit to 4-5. Let's pick: 4 September, about half, about a quarter, about a quarter (maybe combine?), by 16 months. That's 4? Actually we have date, half, quarter (complex activity), quarter (fractional shortening), 16 months. That's 5. Good.
We need to wrap study/journal citation: article in Science Advances on 4 September. So we need Science Advances, 4 September maybe. Use single underscores.
Now produce headline: maybe "Mitochondrial DNA errors in mouse heart cells weaken contraction and trigger immune remodeling". Count characters: Let's count: "Mitochondrial DNA errors in mouse heart cells weaken contraction and trigger immune remodeling". Count: M(1) ... Let's approximate: It's likely under 90. We'll ensure.
Now body paragraphs: 2-3 sentences each.
Paragraph 1: describe model and findings at nine months.
Paragraph 2: describe progression to 12-16 months, collagen deposits, etc.
Paragraph 3: describe immune signaling and dendritic cells, link to respiratory chain defects.
Make sure to wrap numbers in double asterisks.
We need to keep the citation: Science Advances, 4 September maybe.
Let's craft.
Paragraph 1: "Researchers created a mouse line in which a proof‑defective POLG variant (POLG D257A) is expressed only in cardiomyocytes. By nine months the mitochondrial DNA mutation load in heart cells was about half that seen in mice with the defective POLG throughout the body, while body and organ weights remained normal. Activity of respiratory‑chain complexes I and IV fell by about a quarter, and fractional shortening — the proportion of left‑ventricular systolic reduction — dropped by a similar about a quarter."
Check double asterisks: we have nine months, about half, about a quarter, about a quarter (that's 4). Good.
Paragraph 2: "Between 12 and 16 months contractile force continued to decline, and by 16 months the mitochondrial mutation burden reached the level of the nine‑month whole‑body POLG mutant. Histology showed collagen deposits — areas of fibrous tissue — in these hearts, and the loss of respiratory‑chain subunits varied across different cardiac regions."
Double asterisks: we have 12 and 16 months, 16 months (that's 2 more, total now 6 > limit). Need to reduce. We must keep at most 4-5 total. So we need to be selective.…
🔗 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.
We need to identify key facts: date: 4 September (article in Science Advances). Gene: Polg, variant POLG D257A. Mutation load: at nine months about half compared to whole-body POLG mutant. Activity of complex I and IV reduced about a quarter (~25%). Fractional shortening reduced similarly. At 12-16 months, contractility continues weakening; by 16 months mutation load reaches level of nine-month whole-body mutant. Collagen deposits observed. Interferon signals and antigen presentation increased with higher mutation load. More immune cells, especially dendritic.
We need to limit double asterisks to at most 4-5. Choose key numbers: date, mutation load half, activity reduction quarter (~25%), fractional shortening reduction quarter, mutation load reaches level at 16 months. That's 5 maybe. Also maybe gene name POLG D257A? That's a name but maybe not needed as double asterisk? Could be considered important. But we must limit to 4-5. Let's pick: 4 September, about half, about a quarter, about a quarter (maybe combine?), by 16 months. That's 4? Actually we have date, half, quarter (complex activity), quarter (fractional shortening), 16 months. That's 5. Good.
We need to wrap study/journal citation: article in Science Advances on 4 September. So we need Science Advances, 4 September maybe. Use single underscores.
Now produce headline: maybe "Mitochondrial DNA errors in mouse heart cells weaken contraction and trigger immune remodeling". Count characters: Let's count: "Mitochondrial DNA errors in mouse heart cells weaken contraction and trigger immune remodeling". Count: M(1) ... Let's approximate: It's likely under 90. We'll ensure.
Now body paragraphs: 2-3 sentences each.
Paragraph 1: describe model and findings at nine months.
Paragraph 2: describe progression to 12-16 months, collagen deposits, etc.
Paragraph 3: describe immune signaling and dendritic cells, link to respiratory chain defects.
Make sure to wrap numbers in double asterisks.
We need to keep the citation: Science Advances, 4 September maybe.
Let's craft.
Paragraph 1: "Researchers created a mouse line in which a proof‑defective POLG variant (POLG D257A) is expressed only in cardiomyocytes. By nine months the mitochondrial DNA mutation load in heart cells was about half that seen in mice with the defective POLG throughout the body, while body and organ weights remained normal. Activity of respiratory‑chain complexes I and IV fell by about a quarter, and fractional shortening — the proportion of left‑ventricular systolic reduction — dropped by a similar about a quarter."
Check double asterisks: we have nine months, about half, about a quarter, about a quarter (that's 4). Good.
Paragraph 2: "Between 12 and 16 months contractile force continued to decline, and by 16 months the mitochondrial mutation burden reached the level of the nine‑month whole‑body POLG mutant. Histology showed collagen deposits — areas of fibrous tissue — in these hearts, and the loss of respiratory‑chain subunits varied across different cardiac regions."
Double asterisks: we have 12 and 16 months, 16 months (that's 2 more, total now 6 > limit). Need to reduce. We must keep at most 4-5 total. So we need to be selective.…
🔗 Read original →
PubMed Central (PMC)
Cardiomyocyte-intrinsic somatic mtDNA mutations induce an OXPHOS-dependent immune response and promote progressive heart failure
Mitochondrial DNA (mtDNA) mutations accumulate with age, but their mechanistic contribution to aging remains unclear. The classical mtDNA mutator mouse expresses a proofreading-deficient mtDNA polymerase (POLGD257A) and accumulates mtDNA mutations ...
We need to translate Russian news post into natural English, format per rules.
We need a short headline under 90 chars, first line 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. No commentary.
We need to identify key facts: date: 4 сентября (September 4) in Science Advances. Also mention 2018 year. Also mention drug: doxorubicin (доксорубицин). Genes: Sod2, ACO2, SLC25A1, ACLY, H3K27Ac, H3K9Ac. Also mention mice. Possibly numbers: not many numbers. Could include "4 September" as date. Also maybe "Science Advances". Also "2018". Also "doxorubicin". Also "Sod2". Also "ACO2". Also "SLC25A1". Also "ACLY". Also "H3K27Ac". Also "H3K9Ac". That's many; we need to limit to 4-5 double asterisks. Choose most important: date, drug, gene names maybe. But we need to wrap key numbers, percentages, drug/company/gene names, dates. So we can wrap each gene name? That would be many. We need to be selective: at most 4-5 per post. So choose maybe: September 4, Science Advances, doxorubicin, Sod2, ACO2? That's 5. Or we could include SLC25A1, ACLY, but limit.
We need to wrap study/journal citations in single underscores: e.g., Science Advances, September 4? Actually citation: "4 сентября в Science Advances вышла работа о мышах". So we can wrap the journal name and date in single underscores: Science Advances, September 4. Also mention 2018 work: maybe 2018 study? But we can just wrap the citation.
We need to ensure we don't wrap whole sentences. So we need to embed double asterisks around specific facts within sentences, not whole sentence.
We need to produce short paragraphs 2-3 sentences each.
Let's craft translation.
First line headline: maybe "Mitochondrial stress in embryos confers lasting heart protection in mice". Count characters: Let's count: "Mitochondrial stress in embryos confers lasting heart protection in mice". That's 66 characters approx. Under 90.
Now blank line.
Now body paragraphs.
Paragraph 1: talk about study published September 4 in Science Advances; embryos had transient oxidative stress via Sod2 suppression; after birth Sod2 restored; adult hearts partially protected from doxorubicin damage.
We need to embed double asterisks for key facts: maybe September 4, Science Advances, doxorubicin, Sod2. That's 4.
We need to embed single underscores for citation: maybe Science Advances, September 4 (but we already used double asterisks for date and journal; we need to follow rule: wrap study/journal citations and publication references in single underscores. So the citation should be underscores, not double asterisks. So we need to decide: either we use double asterisks for key numbers/drug/gene names, and single underscores for citations. So we cannot double asterisk the journal name if we also need to underscore it. So we need to choose: either we underscore the citation, and double asterisk other facts like drug, gene names, date maybe. But date is part of citation; maybe we can underscore the whole citation Science Advances, September 4 and double asterisk other facts like doxorubicin, Sod2, ACO2, SLC25A1? That's 4 double asterisks.
Let's do: double asterisks for doxorubicin, Sod2, ACO2, SLC25A1 (or ACLY). Choose 4.
Single underscores for citation: Science Advances, September 4.
Also maybe we need to underscore the 2018 work: could be 2018 study but not necessary.
We need to ensure we don't overdo double asterisks.…
🔗 Read original →
We need a short headline under 90 chars, first line 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. No commentary.
We need to identify key facts: date: 4 сентября (September 4) in Science Advances. Also mention 2018 year. Also mention drug: doxorubicin (доксорубицин). Genes: Sod2, ACO2, SLC25A1, ACLY, H3K27Ac, H3K9Ac. Also mention mice. Possibly numbers: not many numbers. Could include "4 September" as date. Also maybe "Science Advances". Also "2018". Also "doxorubicin". Also "Sod2". Also "ACO2". Also "SLC25A1". Also "ACLY". Also "H3K27Ac". Also "H3K9Ac". That's many; we need to limit to 4-5 double asterisks. Choose most important: date, drug, gene names maybe. But we need to wrap key numbers, percentages, drug/company/gene names, dates. So we can wrap each gene name? That would be many. We need to be selective: at most 4-5 per post. So choose maybe: September 4, Science Advances, doxorubicin, Sod2, ACO2? That's 5. Or we could include SLC25A1, ACLY, but limit.
We need to wrap study/journal citations in single underscores: e.g., Science Advances, September 4? Actually citation: "4 сентября в Science Advances вышла работа о мышах". So we can wrap the journal name and date in single underscores: Science Advances, September 4. Also mention 2018 work: maybe 2018 study? But we can just wrap the citation.
We need to ensure we don't wrap whole sentences. So we need to embed double asterisks around specific facts within sentences, not whole sentence.
We need to produce short paragraphs 2-3 sentences each.
Let's craft translation.
First line headline: maybe "Mitochondrial stress in embryos confers lasting heart protection in mice". Count characters: Let's count: "Mitochondrial stress in embryos confers lasting heart protection in mice". That's 66 characters approx. Under 90.
Now blank line.
Now body paragraphs.
Paragraph 1: talk about study published September 4 in Science Advances; embryos had transient oxidative stress via Sod2 suppression; after birth Sod2 restored; adult hearts partially protected from doxorubicin damage.
We need to embed double asterisks for key facts: maybe September 4, Science Advances, doxorubicin, Sod2. That's 4.
We need to embed single underscores for citation: maybe Science Advances, September 4 (but we already used double asterisks for date and journal; we need to follow rule: wrap study/journal citations and publication references in single underscores. So the citation should be underscores, not double asterisks. So we need to decide: either we use double asterisks for key numbers/drug/gene names, and single underscores for citations. So we cannot double asterisk the journal name if we also need to underscore it. So we need to choose: either we underscore the citation, and double asterisk other facts like drug, gene names, date maybe. But date is part of citation; maybe we can underscore the whole citation Science Advances, September 4 and double asterisk other facts like doxorubicin, Sod2, ACO2, SLC25A1? That's 4 double asterisks.
Let's do: double asterisks for doxorubicin, Sod2, ACO2, SLC25A1 (or ACLY). Choose 4.
Single underscores for citation: Science Advances, September 4.
Also maybe we need to underscore the 2018 work: could be 2018 study but not necessary.
We need to ensure we don't overdo double asterisks.…
🔗 Read original →
PubMed Central (PMC)
Mitochondrial superoxide–induced mitohormesis is mediated by citrate and cardioprotective
Mitohormesis, whereby transient mitochondrial stress induces adaptive signaling, promotes organismal resilience and longevity in invertebrates, but how this operates in mammals and the underlying metabolic signals involved remain unclear. Using a ...
Spatial-ATAC-Hi-C maps DNA folding and accessibility in tissue slices
In Nature Methods published September 1, researchers presented Spatial-ATAC-Hi-C, a method that simultaneously measures DNA contacts and chromatin accessibility at each point of a tissue slice. DNA in the nucleus is packed into chromatin that forms loops, bringing distant regulatory elements near genes; open chromatin is accessible to regulatory proteins, and assigning coordinates to these two dimensions is essential because neighboring cells can belong to different types and follow distinct gene programs.
The tissue is fixed on a glass slide, DNA fragments that interacted in nuclei are ligated, and two perpendicular series of microchannels with barcodes—50 horizontal and 50 vertical channels—create up to 2,500 points; each point occupies a 50 × 50 µm square and typically contains 3–21 cells. After sequencing, barcodes return both DNA contacts and accessible regulatory regions to each point.
Validation against independent Hi‑C and ATAC‑seq on adjacent mouse brain slices showed the protocol preserves both signals, and the map distinguished chromatin loops characteristic of different neuron types and brain areas. In astrocytoma and glioblastoma samples Spatial-ATAC-Hi-C detected copy‑number changes and structural rearrangements of genomic fragments, which matched whole‑genome sequencing of neighboring slices.
In one glioblastoma specimen spatially segregated groups of points with distinct copy‑number profiles displayed concordant contact and accessibility maps. In aged tissue the approach can test whether changes in DNA accessibility, long‑range genome contacts, and cellular composition coincide within the same zones.
🔗 Read original →
In Nature Methods published September 1, researchers presented Spatial-ATAC-Hi-C, a method that simultaneously measures DNA contacts and chromatin accessibility at each point of a tissue slice. DNA in the nucleus is packed into chromatin that forms loops, bringing distant regulatory elements near genes; open chromatin is accessible to regulatory proteins, and assigning coordinates to these two dimensions is essential because neighboring cells can belong to different types and follow distinct gene programs.
The tissue is fixed on a glass slide, DNA fragments that interacted in nuclei are ligated, and two perpendicular series of microchannels with barcodes—50 horizontal and 50 vertical channels—create up to 2,500 points; each point occupies a 50 × 50 µm square and typically contains 3–21 cells. After sequencing, barcodes return both DNA contacts and accessible regulatory regions to each point.
Validation against independent Hi‑C and ATAC‑seq on adjacent mouse brain slices showed the protocol preserves both signals, and the map distinguished chromatin loops characteristic of different neuron types and brain areas. In astrocytoma and glioblastoma samples Spatial-ATAC-Hi-C detected copy‑number changes and structural rearrangements of genomic fragments, which matched whole‑genome sequencing of neighboring slices.
In one glioblastoma specimen spatially segregated groups of points with distinct copy‑number profiles displayed concordant contact and accessibility maps. In aged tissue the approach can test whether changes in DNA accessibility, long‑range genome contacts, and cellular composition coincide within the same zones.
🔗 Read original →
Nature
Spatial chromatin architecture and accessibility co-profiling of mammalian tissues
Nature Methods - Spatial-ATAC-Hi-C enables the profiling of both chromatin accessibility and organization in a spatially resolved manner, as demonstrated on mouse brain and human glioblastoma and...
Ray Kurzweil Joins Subsense as Advisor on Brain‑Nanoparticle Interface
On September 3, Ray Kurzweil became a product and vision advisor to the California startup Subsense. The company says it will introduce two types of nanoparticles through the nose to interface with the brain, using a wearable device to read and stimulate neuronal activity.
According to Subsense, plasmonic particles would scatter near‑infrared light differently in the presence of a local electric field, allowing the wearable to read signals. Magnetoelectric particles would convert an external magnetic field into a local electric effect to stimulate neurons. The system must deliver particles to the target brain area, retain them, read the signal, and induce a local effect.
At the September 3 event, Kurzweil described the ultimate goal: “Ultimately we want to merge smartphone with brain.” A Science Advances 2021 study showed a related step: magnetoelectric particles injected into specific mouse brain areas were exposed to static and alternating magnetic fields. The combination of particles and both fields increased c‑Fos‑positive neurons and altered gait parameters in mice, confirming local stimulation.
Kurzweil will advise Subsense on product development, with the company’s first focus on neurological diseases. Subsense plans pilot clinical trials for 2027–2029.
🔗 Read original →
On September 3, Ray Kurzweil became a product and vision advisor to the California startup Subsense. The company says it will introduce two types of nanoparticles through the nose to interface with the brain, using a wearable device to read and stimulate neuronal activity.
According to Subsense, plasmonic particles would scatter near‑infrared light differently in the presence of a local electric field, allowing the wearable to read signals. Magnetoelectric particles would convert an external magnetic field into a local electric effect to stimulate neurons. The system must deliver particles to the target brain area, retain them, read the signal, and induce a local effect.
At the September 3 event, Kurzweil described the ultimate goal: “Ultimately we want to merge smartphone with brain.” A Science Advances 2021 study showed a related step: magnetoelectric particles injected into specific mouse brain areas were exposed to static and alternating magnetic fields. The combination of particles and both fields increased c‑Fos‑positive neurons and altered gait parameters in mice, confirming local stimulation.
Kurzweil will advise Subsense on product development, with the company’s first focus on neurological diseases. Subsense plans pilot clinical trials for 2027–2029.
🔗 Read original →
Science Advances
Nonresonant powering of injectable nanoelectrodes enables wireless deep brain stimulation in freely moving mice
Wireless powering of magnetoelectric nanoelectrodes is used for deep brain stimulation in freely moving and transgene-free mice.
Starr Foundation Funds $37M Brown Aging Research Alliance
On September 3, Brown University announced the Starr Healthspan Innovation Alliance, a five‑year program backed by a $37 million grant from the Starr Foundation to link its Center for Biology of Aging with clinical trials run by Brown University Health. The initiative aims to translate laboratory discoveries into human studies by providing the researchers, trial teams, and participants needed for clinical testing.
Funds will cover laboratory work, the hiring of new researchers, and the expansion of the clinical research network. In addition, the grant will create two new endowed professorships in geroscience and support the recruitment of specialist staff.
Brown University Health currently conducts about 500 clinical trials in Rhode Island, with roughly two‑thirds focused on aging and related diseases. These trials provide a substantial platform for testing interventions that emerge from the Center for Biology of Aging.
The alliance will pay for specialists, participant recruitment and support through local communities, and will foster partnerships with scientific groups and industry. It builds on an organizational foundation established in 2
🔗 Read original →
On September 3, Brown University announced the Starr Healthspan Innovation Alliance, a five‑year program backed by a $37 million grant from the Starr Foundation to link its Center for Biology of Aging with clinical trials run by Brown University Health. The initiative aims to translate laboratory discoveries into human studies by providing the researchers, trial teams, and participants needed for clinical testing.
Funds will cover laboratory work, the hiring of new researchers, and the expansion of the clinical research network. In addition, the grant will create two new endowed professorships in geroscience and support the recruitment of specialist staff.
Brown University Health currently conducts about 500 clinical trials in Rhode Island, with roughly two‑thirds focused on aging and related diseases. These trials provide a substantial platform for testing interventions that emerge from the Center for Biology of Aging.
The alliance will pay for specialists, participant recruitment and support through local communities, and will foster partnerships with scientific groups and industry. It builds on an organizational foundation established in 2
🔗 Read original →
PubMed Central (PMC)
NIA Translational Geroscience Network: An Infrastructure to Facilitate Geroscience-Guided Clinical Trials
AI system Astra drafts five NIH R01 grant proposals in under an hour
On September 6, Lokseyl posted on X that he asked Astra to read his published works, identify new directions, and prepare five drafts of R01 grant applications for the US National Institutes of Health. He noted that the task took about an hour and required roughly about $20 of computational resources.
One attached draft page poses a question about how cancer cell metabolism responds to enzyme inhibition when nutrient availability shifts, aiming to pinpoint which enzyme sets the reaction rate under those conditions. The draft builds on prior lab results to formulate a hypothesis that cellular nutrition, chemical state, and energy demand determine which step of glucose processing becomes rate‑limiting.
The first aim proposes varying nutrient conditions and the activity of three enzymes to see which step begins to limit flux. The second aim calls for comparing multiple mechanistic explanations with measurements and constructing a simplified model of the observed changes. The third aim requires pre‑registering predictions for new nutrient combinations and cell cultures, then testing them experimentally.
Lokseyl wrote that Astra “well reproduced this logic,” turning his existing work into questions, hypotheses, and experiments that would seem familiar and justified to an expert review panel. He judged all five drafts to be “quite reasonable,” grounded in his research and resembling a grant he himself might have written.
🔗 Read original →
On September 6, Lokseyl posted on X that he asked Astra to read his published works, identify new directions, and prepare five drafts of R01 grant applications for the US National Institutes of Health. He noted that the task took about an hour and required roughly about $20 of computational resources.
One attached draft page poses a question about how cancer cell metabolism responds to enzyme inhibition when nutrient availability shifts, aiming to pinpoint which enzyme sets the reaction rate under those conditions. The draft builds on prior lab results to formulate a hypothesis that cellular nutrition, chemical state, and energy demand determine which step of glucose processing becomes rate‑limiting.
The first aim proposes varying nutrient conditions and the activity of three enzymes to see which step begins to limit flux. The second aim calls for comparing multiple mechanistic explanations with measurements and constructing a simplified model of the observed changes. The third aim requires pre‑registering predictions for new nutrient combinations and cell cultures, then testing them experimentally.
Lokseyl wrote that Astra “well reproduced this logic,” turning his existing work into questions, hypotheses, and experiments that would seem familiar and justified to an expert review panel. He judged all five drafts to be “quite reasonable,” grounded in his research and resembling a grant he himself might have written.
🔗 Read original →
Gene activity entropy varies with age and cancer across tissues
Researchers analyzed RNA from over 25 000 human and mouse tissue samples, computing Shannon entropy to measure whether gene activity is concentrated in few genes or spread across many. They first asked whether this entropy changes with age uniformly across the body. After adjusting for available sample characteristics, entropy decreased in brain, stomach, and blood; it increased in salivary gland, heart, skin, fat, and skeletal muscle; and remained stable in other tissues.
The age‑related pattern therefore differs by organ. To separate intracellular changes from shifts in cell‑type composition, the authors estimated cellular makeup mathematically; the entropy rise seen in skin and skeletal muscle persisted after this correction. In single‑cell data from liver cancer and melanoma, tumor cells often showed higher entropy even among cells of the same type.
In matched tumor‑normal pairs, primary tumors of most types had higher entropy than adjacent normal tissue. For melanoma, entropy rose from non‑sun‑exposed skin through primary tumor to late metastases, using skin and tumor data from separate cohorts. In 5 out of 6 paired melanoma samples that acquired therapy resistance, entropy increased.
Among cancer types where the link to overall survival was significant, high entropy accompanied worse survival in roughly ~70% of cases. In cellular reprogramming experiments, a less successful chemical protocol yielded higher entropy than a more successful one. The same entropy calculation reflects both cellular state and tissue composition, and its meaning depends on the specific organ and sample makeup. Aging Cell, 4 September
🔗 Read original →
Researchers analyzed RNA from over 25 000 human and mouse tissue samples, computing Shannon entropy to measure whether gene activity is concentrated in few genes or spread across many. They first asked whether this entropy changes with age uniformly across the body. After adjusting for available sample characteristics, entropy decreased in brain, stomach, and blood; it increased in salivary gland, heart, skin, fat, and skeletal muscle; and remained stable in other tissues.
The age‑related pattern therefore differs by organ. To separate intracellular changes from shifts in cell‑type composition, the authors estimated cellular makeup mathematically; the entropy rise seen in skin and skeletal muscle persisted after this correction. In single‑cell data from liver cancer and melanoma, tumor cells often showed higher entropy even among cells of the same type.
In matched tumor‑normal pairs, primary tumors of most types had higher entropy than adjacent normal tissue. For melanoma, entropy rose from non‑sun‑exposed skin through primary tumor to late metastases, using skin and tumor data from separate cohorts. In 5 out of 6 paired melanoma samples that acquired therapy resistance, entropy increased.
Among cancer types where the link to overall survival was significant, high entropy accompanied worse survival in roughly ~70% of cases. In cellular reprogramming experiments, a less successful chemical protocol yielded higher entropy than a more successful one. The same entropy calculation reflects both cellular state and tissue composition, and its meaning depends on the specific organ and sample makeup. Aging Cell, 4 September
🔗 Read original →
PubMed Central (PMC)
Tissue‐Level Transcriptomic Entropy Reveals Organ‐Specific Aging Patterns and Predicts Cancer Progression
Although aging and cancer share complex molecular mechanisms, distinguishing causative factors from byproducts remains challenging. Here, we investigated the role of tissue transcriptomic entropy—a measure of transcriptional disorder—in aging and ...
Body‑Channel Communication Enables High‑Bandwidth Wireless Neural Implants
The main problem with modern wireless neuroimplants is the tight limits on bandwidth, power consumption, and heating: a high‑resolution microelectrode array (MEA) with 1000‑channel MEA generates a data stream exceeding 300 Mbps. Radio‑frequency transmission of this volume produces too much heat, inevitably damaging brain tissue.
The EU‑funded IoN (Intranet of Neurons) project tackled this with a two‑stage wireless architecture that uses body‑channel communication (BCC), treating the body’s tissues as a wire and abandoning
🔗 Read original →
The main problem with modern wireless neuroimplants is the tight limits on bandwidth, power consumption, and heating: a high‑resolution microelectrode array (MEA) with 1000‑channel MEA generates a data stream exceeding 300 Mbps. Radio‑frequency transmission of this volume produces too much heat, inevitably damaging brain tissue.
The EU‑funded IoN (Intranet of Neurons) project tackled this with a two‑stage wireless architecture that uses body‑channel communication (BCC), treating the body’s tissues as a wire and abandoning
🔗 Read original →
TMP-316 improves hind‑limb weight bearing in rats after spinal cord injury
A preprint posted on bioRxiv, September 4 describes TMP-316, a compound that simultaneously inhibits four related branches of the AGC‑kinase family.
The authors started from RO48, which had shown spinal‑cord‑injury benefit in mice but also acted on the cardiac hERG channel and had short cerebrospinal‑fluid half‑life. They generated 371 analogues, screened them for neurite outgrowth and activity against S6K1 and ROCK2, and identified TMP-316 as the lead.
In neuronal cultures, inhibition of S6K1 and ROCK2 promoted neurite extension, and adding blockade of PKCγ or PKX further increased growth. All four kinases share an ATP‑binding pocket that modeling predicted TMP-316 could occupy.
In the animal study, male rats were randomly assigned to three groups (vehicle, ~0.3 mg/kg, or ~1 mg/kg TMP-316; n = 12‑13 per group). The compound was injected into the lumbar cerebrospinal‑fluid space immediately before a C5‑C6 contusion, and investigators assessing locomotion were blinded to treatment.
At the ~1 mg/kg dose, a composite gait score began to differ from controls on day 14, with the greatest divergence occurring between days 28 and 42. Motion analysis showed that the injured fore‑paw bore more weight and that bipedal support returned during stance.
🔗 Read original →
A preprint posted on bioRxiv, September 4 describes TMP-316, a compound that simultaneously inhibits four related branches of the AGC‑kinase family.
The authors started from RO48, which had shown spinal‑cord‑injury benefit in mice but also acted on the cardiac hERG channel and had short cerebrospinal‑fluid half‑life. They generated 371 analogues, screened them for neurite outgrowth and activity against S6K1 and ROCK2, and identified TMP-316 as the lead.
In neuronal cultures, inhibition of S6K1 and ROCK2 promoted neurite extension, and adding blockade of PKCγ or PKX further increased growth. All four kinases share an ATP‑binding pocket that modeling predicted TMP-316 could occupy.
In the animal study, male rats were randomly assigned to three groups (vehicle, ~0.3 mg/kg, or ~1 mg/kg TMP-316; n = 12‑13 per group). The compound was injected into the lumbar cerebrospinal‑fluid space immediately before a C5‑C6 contusion, and investigators assessing locomotion were blinded to treatment.
At the ~1 mg/kg dose, a composite gait score began to differ from controls on day 14, with the greatest divergence occurring between days 28 and 42. Motion analysis showed that the injured fore‑paw bore more weight and that bipedal support returned during stance.
🔗 Read original →
bioRxiv
AGC kinase homology requires and enables co-targeting for CNS regeneration
Axon regrowth in the central nervous system (CNS) is constrained by robust regulatory networks. Here we show that optimal neurite outgrowth in rodent and human CNS neurons is achieved by co-inhibition of kinases across four closely related clades within the…
Fruit Fly Connectome Data Used to Simulate 'Bad Apple' Touhou Track
Researchers took recently published connectome data from adult male fruit flies and fed it into a neural simulation. They then translated the simulated neural activity into the melody of the Touhou song 'Bad Apple'.
The motion‑detecting neurons in the simulation directly controlled a virtual fly, making it move to the music. Looking ahead, one could imagine a digital copy of a person being forced to play internet meme tracks—a darkly humorous take on transhumanism.
🔗 Source: @solid_state_humanity
Researchers took recently published connectome data from adult male fruit flies and fed it into a neural simulation. They then translated the simulated neural activity into the melody of the Touhou song 'Bad Apple'.
The motion‑detecting neurons in the simulation directly controlled a virtual fly, making it move to the music. Looking ahead, one could imagine a digital copy of a person being forced to play internet meme tracks—a darkly humorous take on transhumanism.
🔗 Source: @solid_state_humanity
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Solid State Humanity
Кто-то использовал недавно опубликованные данные о коннектоме взрослых самцов плодовых мушек в симуляции, а затем превратил их нейронную активность в... трек из Touhou "Bad Apple".
Отображённые нейроны движения буквально управляли виртуальной мухой. А теперь…
Отображённые нейроны движения буквально управляли виртуальной мухой. А теперь…
FishNAP screen identifies seven reversible blood‑brain barrier‑opening molecules
On September 4, researchers at Rutgers University released version 2 of a preprint describing the FishNAP assay, a zebrafish‑larvae screen for molecules that transiently increase blood‑brain barrier permeability. The assay first measures behavioral changes caused by loperamide entry into the brain, then quantifies leakage of a fluorescent tracer into brain tissue. FishNAP preprint, Rutgers University, version 2, September 4
They screened 2,320 FDA‑approved small molecules and found 11 that repeatedly altered larval behavior; direct tracer measurements confirmed seven compounds with pronounced passage of the smallest marker into the brain. All seven showed reversible barrier opening, with function restored within 24 hours after compound removal.
The three selected molecules—calcitriol, lovastatin, sunitinib—were tested in adult mice, where each increased tracer and albumin accumulation in brain tissue; calcitriol and lovastatin also allowed IgG entry. In cortical tissue, levels of CLDN5 and MFSD2A decreased while CAV1 increased, indicating loosened tight junctions and enhanced transcellular transport.
The authors link this protein pattern to weakened endothelial tight junctions and heightened vesicular transport, noting that FishNAP selects for small molecules that transiently alter vascular wall permeability. The method’s usefulness depends on the size of the intended cargo and which barrier property the hit compound modifies.
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On September 4, researchers at Rutgers University released version 2 of a preprint describing the FishNAP assay, a zebrafish‑larvae screen for molecules that transiently increase blood‑brain barrier permeability. The assay first measures behavioral changes caused by loperamide entry into the brain, then quantifies leakage of a fluorescent tracer into brain tissue. FishNAP preprint, Rutgers University, version 2, September 4
They screened 2,320 FDA‑approved small molecules and found 11 that repeatedly altered larval behavior; direct tracer measurements confirmed seven compounds with pronounced passage of the smallest marker into the brain. All seven showed reversible barrier opening, with function restored within 24 hours after compound removal.
The three selected molecules—calcitriol, lovastatin, sunitinib—were tested in adult mice, where each increased tracer and albumin accumulation in brain tissue; calcitriol and lovastatin also allowed IgG entry. In cortical tissue, levels of CLDN5 and MFSD2A decreased while CAV1 increased, indicating loosened tight junctions and enhanced transcellular transport.
The authors link this protein pattern to weakened endothelial tight junctions and heightened vesicular transport, noting that FishNAP selects for small molecules that transiently alter vascular wall permeability. The method’s usefulness depends on the size of the intended cargo and which barrier property the hit compound modifies.
🔗 Read original →
bioRxiv
In vivo discovery of blood-brain barrier opening small molecules with FishNAP
The blood-brain barrier (BBB) is crucial for neural homeostasis, tightly regulating molecular exchange between the circulation and brain. However, this selective protection also greatly limits drug delivery to the central nervous system, posing a major challenge…
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 "статья с промежуточными данными регистра MASTRR: в десяти центрах США устройства Myriad применили у 411 пациентов с 474 сложными дефектами мягких тканей." No explicit journal name. Might be a study article but not given. We may need to wrap any citation like "статья" but we don't have journal name. Possibly we can treat "MASTRR" as registry name, not citation. No explicit journal citation given. So maybe we don't need any underscores. However we could still wrap the registry name? The rule: "Wrap study/journal citations and publication references in single underscores". If none present, we skip.
We need to wrap key numbers, percentages, drug/company/gene names, dates in double asterisks. At most 4-5 per post.
Important facts: 411 patients, 474 defects, 10 US centers, Myriad device, made from sheep rumen extracellular matrix, median follow-up 27.1 weeks, 50 patients (12.2%) had 59 adverse events, superficial infection 2.9%, deep infection 0.7%, skin reaction (likely related) led to removal of 40% of scaffold, antihistamines, split-thickness skin graft, registry ongoing, planned size 800 participants, primary endpoint proportion with adverse events over three years, article published September 3 (maybe date). Also "почти 60% дефектов сохранялись больше месяца" (almost 60% defects persisted >1 month). Also participants often had type 2 diabetes and vascular diseases.
We need to select at most 4-5 double asterisk wrapped items. Choose the most important: number of patients (411), number of defects (474), median follow-up (27.1 weeks), percentage with adverse events (12.2%), planned registry size (800). Also maybe date Sept 3. But we have limit 4-5. Let's pick: 411 patients, 474 defects, 27.1 weeks, 12.2%, 800 participants. That's 5.
We need to ensure we don't wrap whole sentence. Just wrap those numbers/percentages.
Also need to wrap drug/company/gene names: Myriad is a device name; could be considered a company/device name; we could wrap it but that would increase count. We already have 5 items; maybe we replace one with Myriad? But we need to keep numbers. The rule says "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". So we can include drug/company names as part of the limited count. We need to decide which to include. Probably include Myriad as it's important. But we also need numbers. Let's see if we can fit 5 items: Myriad, 411 patients, 27.1 weeks, 12.2%, 800 participants. That's 5. Could also include 474 defects but we would exceed. Maybe we can combine "411 patients with 474 defects" as one phrase? But that would be a whole sentence? Not exactly; we could wrap "411 patients" and "474 defects" separately but that's two. Could we wrap "411 patients, 474 defects" as one? That includes two numbers but still one wrapped segment. The rule says wrap few genuinely important facts — key numbers, percentages, drug/company/gene names, dates. It doesn't forbid wrapping a phrase containing multiple numbers. So we could wrap "411 patients with 474 defects" as one item. That counts as one. Then we have Myriad, 27.1 weeks, 12.2%, 800 participants = total 5. Good.…
🔗 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 "статья с промежуточными данными регистра MASTRR: в десяти центрах США устройства Myriad применили у 411 пациентов с 474 сложными дефектами мягких тканей." No explicit journal name. Might be a study article but not given. We may need to wrap any citation like "статья" but we don't have journal name. Possibly we can treat "MASTRR" as registry name, not citation. No explicit journal citation given. So maybe we don't need any underscores. However we could still wrap the registry name? The rule: "Wrap study/journal citations and publication references in single underscores". If none present, we skip.
We need to wrap key numbers, percentages, drug/company/gene names, dates in double asterisks. At most 4-5 per post.
Important facts: 411 patients, 474 defects, 10 US centers, Myriad device, made from sheep rumen extracellular matrix, median follow-up 27.1 weeks, 50 patients (12.2%) had 59 adverse events, superficial infection 2.9%, deep infection 0.7%, skin reaction (likely related) led to removal of 40% of scaffold, antihistamines, split-thickness skin graft, registry ongoing, planned size 800 participants, primary endpoint proportion with adverse events over three years, article published September 3 (maybe date). Also "почти 60% дефектов сохранялись больше месяца" (almost 60% defects persisted >1 month). Also participants often had type 2 diabetes and vascular diseases.
We need to select at most 4-5 double asterisk wrapped items. Choose the most important: number of patients (411), number of defects (474), median follow-up (27.1 weeks), percentage with adverse events (12.2%), planned registry size (800). Also maybe date Sept 3. But we have limit 4-5. Let's pick: 411 patients, 474 defects, 27.1 weeks, 12.2%, 800 participants. That's 5.
We need to ensure we don't wrap whole sentence. Just wrap those numbers/percentages.
Also need to wrap drug/company/gene names: Myriad is a device name; could be considered a company/device name; we could wrap it but that would increase count. We already have 5 items; maybe we replace one with Myriad? But we need to keep numbers. The rule says "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". So we can include drug/company names as part of the limited count. We need to decide which to include. Probably include Myriad as it's important. But we also need numbers. Let's see if we can fit 5 items: Myriad, 411 patients, 27.1 weeks, 12.2%, 800 participants. That's 5. Could also include 474 defects but we would exceed. Maybe we can combine "411 patients with 474 defects" as one phrase? But that would be a whole sentence? Not exactly; we could wrap "411 patients" and "474 defects" separately but that's two. Could we wrap "411 patients, 474 defects" as one? That includes two numbers but still one wrapped segment. The rule says wrap few genuinely important facts — key numbers, percentages, drug/company/gene names, dates. It doesn't forbid wrapping a phrase containing multiple numbers. So we could wrap "411 patients with 474 defects" as one item. That counts as one. Then we have Myriad, 27.1 weeks, 12.2%, 800 participants = total 5. Good.…
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PubMed Central (PMC)
The Role and Efficacy of NovoSorb Biodegradable Temporizing Matrix in Complex Reconstructive Wounds: A Systematic Review
Managing complex wounds with exposed bone, tendons, metalware, or irradiated tissue is challenging. NovoSorb Biodegradable Temporizing Matrix (BTM) offers an alternative by promoting vascularization and neodermis formation. This review assessed the ...
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). There's no citation in the text except maybe Post Bulletin? It's a news source, not a study/journal. So we may not need underscores unless we treat Post Bulletin as a publication reference? The rule says wrap study/journal citations and publication references in single underscores. Post Bulletin is a publication, so we can wrap it: Post Bulletin. But it's a news source; still a publication reference. We'll do that.
We need to preserve all facts, numbers, names, citations exactly.
Important facts: United Therapeutics, completed facility in Stuartville on September 1, cost $110 million, facility designed for 150 genetically edited pigs, organs for human transplantation, xenotransplantation definition, facility size 65,000 sq ft, about 25 employees, labs, veterinary clinic, two surgical blocks, Rodney Lamb (technical operations head of xenoprogram) compared clean zone to "building within a building", internal clean zone separated, staff work with animals in protective suits, equipment and materials sterilized with hydrogen peroxide before entry, these procedures maintain conditions for pigs to become donors for patients, adjacent to completed center company purchased 207 acres for future swine organ production complexes, first center now ready to accept animals.
We need to bold at most 4-5 key facts: maybe the date, cost, number of pigs, facility size, acres purchased. That's 5.
We need to bold them with double asterisks. Ensure not bold whole sentence.
We'll embed bold around the numbers/dates etc.
Let's craft headline: "United Therapeutics Completes $110 Million Pig‑Organ Facility in Stuartville". Count characters: Let's count: United(6) + space=1 =>7, Therapeutics(12)=>19, space=20, Completes(9)=>29, space=30, $110(4)=>34, space=35, Million(7)=>42, space=43, Pig‑Organ(9 inc hyphen?) Let's count: Pig‑Organ (P i g ‑ O r g a n) that's 9 inc hyphen? Actually "Pig‑Organ": 3+1+6=10? Let's just approximate. We'll be under 90.
Now blank line.
Paragraph 1: mention completion date Sept 1, cost $110M, facility for 150 genetically edited pigs, purpose xenotransplantation. We'll bold date, cost, number of pigs.
Paragraph 2: definition of xenotransplantation, mention facility size 65,000 sq ft, about 25 employees, labs, vet clinic, two surgical blocks. Bold facility size maybe.
Paragraph 3: quote Rodney Lamb, description of clean zone as "building within a building", internal clean zone separated, staff wear protective suits, equipment sterilized with hydrogen peroxide. Possibly bold nothing else.
Paragraph 4: mention adjacent purchase of 207 acres for future complexes, first center now ready to accept animals. Bold acres.
We need to ensure at most 4-5 bolded items total. Let's choose: September 1, $110 million, 150 genetically edited pigs, 65,000 square feet, 207 acres. That's 5.
We need to wrap them in double asterisks exactly.
Now ensure we don't bold whole sentence; just those phrases.
Now need to wrap study/journal citations and publication references in single underscores. We have Post Bulletin as a publication reference. We'll wrap that.
Now produce final output.
Check formatting: first line headline, then blank line, then paragraphs separated by blank lines.
Paragraphs: 2-3 sentences each.
Let's craft.…
🔗 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). There's no citation in the text except maybe Post Bulletin? It's a news source, not a study/journal. So we may not need underscores unless we treat Post Bulletin as a publication reference? The rule says wrap study/journal citations and publication references in single underscores. Post Bulletin is a publication, so we can wrap it: Post Bulletin. But it's a news source; still a publication reference. We'll do that.
We need to preserve all facts, numbers, names, citations exactly.
Important facts: United Therapeutics, completed facility in Stuartville on September 1, cost $110 million, facility designed for 150 genetically edited pigs, organs for human transplantation, xenotransplantation definition, facility size 65,000 sq ft, about 25 employees, labs, veterinary clinic, two surgical blocks, Rodney Lamb (technical operations head of xenoprogram) compared clean zone to "building within a building", internal clean zone separated, staff work with animals in protective suits, equipment and materials sterilized with hydrogen peroxide before entry, these procedures maintain conditions for pigs to become donors for patients, adjacent to completed center company purchased 207 acres for future swine organ production complexes, first center now ready to accept animals.
We need to bold at most 4-5 key facts: maybe the date, cost, number of pigs, facility size, acres purchased. That's 5.
We need to bold them with double asterisks. Ensure not bold whole sentence.
We'll embed bold around the numbers/dates etc.
Let's craft headline: "United Therapeutics Completes $110 Million Pig‑Organ Facility in Stuartville". Count characters: Let's count: United(6) + space=1 =>7, Therapeutics(12)=>19, space=20, Completes(9)=>29, space=30, $110(4)=>34, space=35, Million(7)=>42, space=43, Pig‑Organ(9 inc hyphen?) Let's count: Pig‑Organ (P i g ‑ O r g a n) that's 9 inc hyphen? Actually "Pig‑Organ": 3+1+6=10? Let's just approximate. We'll be under 90.
Now blank line.
Paragraph 1: mention completion date Sept 1, cost $110M, facility for 150 genetically edited pigs, purpose xenotransplantation. We'll bold date, cost, number of pigs.
Paragraph 2: definition of xenotransplantation, mention facility size 65,000 sq ft, about 25 employees, labs, vet clinic, two surgical blocks. Bold facility size maybe.
Paragraph 3: quote Rodney Lamb, description of clean zone as "building within a building", internal clean zone separated, staff wear protective suits, equipment sterilized with hydrogen peroxide. Possibly bold nothing else.
Paragraph 4: mention adjacent purchase of 207 acres for future complexes, first center now ready to accept animals. Bold acres.
We need to ensure at most 4-5 bolded items total. Let's choose: September 1, $110 million, 150 genetically edited pigs, 65,000 square feet, 207 acres. That's 5.
We need to wrap them in double asterisks exactly.
Now ensure we don't bold whole sentence; just those phrases.
Now need to wrap study/journal citations and publication references in single underscores. We have Post Bulletin as a publication reference. We'll wrap that.
Now produce final output.
Check formatting: first line headline, then blank line, then paragraphs separated by blank lines.
Paragraphs: 2-3 sentences each.
Let's craft.…
🔗 Read original →
We need to translate Russian news post into natural fluent 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 important facts: dates: "4 сентября авторы препринта описали SniffCell." => September 4 (year not given). Could be 2024? Not given. We'll keep date as September 4.
Numbers: average accuracy 80.38%; 16 physically sorted fractions; 83 of 92 DNA sites; 172 donors; median proportion 29.2% for neuronal events and 66.7% for oligodendrocytic events; atlas of methylation 2023 gathered 39 cell groups from 205 healthy samples; SniffCell expanded atlas for eight tissues.
Also key names: SniffCell method; T- and B-cell receptors; tandem repeats; GAA triplet; frontal cortex; neurons and oligodendrocytes; somatic variant.
We need to select at most 4-5 double asterisk facts. Choose maybe: September 4, 80.38%, 172 donors, 29.2%, 66.7%. That's 5.
But also maybe include "83 of 92 sites". Could replace one. Let's decide: we need at most 4-5. Choose 5: September 4, 80.38%, 172 donors, 29.2%, 66.7%.
Wrap each in double asterisks.
Now citations: The text mentions "атлас метилирования 2023 года , который собрал 39 групп клеток из 205 здоровых образцов." That's a reference; we need to wrap study/journal citations and publication references in single underscores. This is not a journal citation but a dataset/reference. We'll treat as methylation atlas 2023 maybe. The instruction: wrap study/journal citations and publication references in single underscores. So we can put methylation atlas 2023 (or 2023 methylation atlas). Also maybe "препринт SniffCell" is a preprint; not a journal citation. We'll just underscore the atlas reference.
Also maybe "обзор о геномной мозаике" is a review; we could underscore that as genomic mosaic review. But we need to be selective; maybe just one underscore.
We'll include methylation atlas 2023 as the citation.
Now produce translation.
First line headline: something like "SniffCell method links DNA methylation to cell types and finds repeat expansions in neurons". Count characters: Let's count: "SniffCell method links DNA methylation to cell types and finds repeat expansions in neurons". Count characters including spaces: Let's count: S(1)n2i3f4f5C6e7l8l9 (space10)m11e12t13h14o15d16 (space17)l18i19n20k21s22 (space23)D24N25A26 (space27)m28e29t30h31y32l33a34t35i36o37n38 (space39)t40o41 (space42)c43e44l45l46 (space47)t48y49p50e51s52 (space53)a54n55d56 (space57)f58i59n60d61s62 (space63)r64e65p66e67a68t69 (space70)e71x72p73a74n75s76i77o78n79s80 (space81)i82n83 (space84)n85e86u87r88o89n90s91. That's 91 characters, okay under 90? Actually 91 > 90. Need under 90. Let's shorten: "SniffCell links DNA methylation to cell types, finds neuronal repeat expansions". Count: S1n2i3f4f5C6e7l8l9 (space10)m11e12t13h14o15d16 (space17)l18i19n20k21s22 (space23)D24N25A26 (space27)m28e29t30h31y32l33a34t35i36o37n38 (space39)t40o41 (space42)c43e44l45l46 (space47)t48y49p50e51s52, (space53)f54i55n56d57s58 (space59)n60e61u62r63o64n65a66l67 (space68)r69e70p71e72a73t74 (space75)e76x77p78a79n80s81i82o83n84s85. That's 85 characters. Good.
Now blank line.
Now body paragraphs.
We need to preserve facts. Let's craft paragraphs 2-3 sentences each.…
🔗 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 important facts: dates: "4 сентября авторы препринта описали SniffCell." => September 4 (year not given). Could be 2024? Not given. We'll keep date as September 4.
Numbers: average accuracy 80.38%; 16 physically sorted fractions; 83 of 92 DNA sites; 172 donors; median proportion 29.2% for neuronal events and 66.7% for oligodendrocytic events; atlas of methylation 2023 gathered 39 cell groups from 205 healthy samples; SniffCell expanded atlas for eight tissues.
Also key names: SniffCell method; T- and B-cell receptors; tandem repeats; GAA triplet; frontal cortex; neurons and oligodendrocytes; somatic variant.
We need to select at most 4-5 double asterisk facts. Choose maybe: September 4, 80.38%, 172 donors, 29.2%, 66.7%. That's 5.
But also maybe include "83 of 92 sites". Could replace one. Let's decide: we need at most 4-5. Choose 5: September 4, 80.38%, 172 donors, 29.2%, 66.7%.
Wrap each in double asterisks.
Now citations: The text mentions "атлас метилирования 2023 года , который собрал 39 групп клеток из 205 здоровых образцов." That's a reference; we need to wrap study/journal citations and publication references in single underscores. This is not a journal citation but a dataset/reference. We'll treat as methylation atlas 2023 maybe. The instruction: wrap study/journal citations and publication references in single underscores. So we can put methylation atlas 2023 (or 2023 methylation atlas). Also maybe "препринт SniffCell" is a preprint; not a journal citation. We'll just underscore the atlas reference.
Also maybe "обзор о геномной мозаике" is a review; we could underscore that as genomic mosaic review. But we need to be selective; maybe just one underscore.
We'll include methylation atlas 2023 as the citation.
Now produce translation.
First line headline: something like "SniffCell method links DNA methylation to cell types and finds repeat expansions in neurons". Count characters: Let's count: "SniffCell method links DNA methylation to cell types and finds repeat expansions in neurons". Count characters including spaces: Let's count: S(1)n2i3f4f5C6e7l8l9 (space10)m11e12t13h14o15d16 (space17)l18i19n20k21s22 (space23)D24N25A26 (space27)m28e29t30h31y32l33a34t35i36o37n38 (space39)t40o41 (space42)c43e44l45l46 (space47)t48y49p50e51s52 (space53)a54n55d56 (space57)f58i59n60d61s62 (space63)r64e65p66e67a68t69 (space70)e71x72p73a74n75s76i77o78n79s80 (space81)i82n83 (space84)n85e86u87r88o89n90s91. That's 91 characters, okay under 90? Actually 91 > 90. Need under 90. Let's shorten: "SniffCell links DNA methylation to cell types, finds neuronal repeat expansions". Count: S1n2i3f4f5C6e7l8l9 (space10)m11e12t13h14o15d16 (space17)l18i19n20k21s22 (space23)D24N25A26 (space27)m28e29t30h31y32l33a34t35i36o37n38 (space39)t40o41 (space42)c43e44l45l46 (space47)t48y49p50e51s52, (space53)f54i55n56d57s58 (space59)n60e61u62r63o64n65a66l67 (space68)r69e70p71e72a73t74 (space75)e76x77p78a79n80s81i82o83n84s85. That's 85 characters. Good.
Now blank line.
Now body paragraphs.
We need to preserve facts. Let's craft paragraphs 2-3 sentences each.…
🔗 Read original →
medRxiv
Cell-type-resolved somatic variant discovery from bulk long-read sequencing
Somatic mutations arise throughout life, with functional consequences tied to the cell populations in which they occur. Genome-wide studies measure somatic variations in bulk tissue, whereas single-cell approaches resolve cell identity but provide limited…
VisionECG builds 3D left‑ventricle model from ECG
On September 4, researchers posted a preprint on medRxiv preprint, September 4 describing VisionECG, a model trained on 71,132 ECG‑MRI pairs from the UK Biobank. The model learns to generate a sequence of 50 successive 3‑D surfaces of the left ventricle from a standard 12‑lead ECG and eight basic subject characteristics.
For 5,000 patients with both ECG and echocardiography, the model‑derived ejection fraction was compared to ultrasound measurements. From the reconstructed ventricular motion the model can compute volume, mass, wall thickness, ejection fraction and myocardial strain.
On an external test set of 2,000 participants the median relative error of volume over the cardiac cycle was 8.34%, and wall‑thickness error was 9.54%. When the individual ECG was replaced by the cohort average, the volume error in dilated cardiomyopathy rose from 12.59% to 20.29%, showing the model relies on person‑specific electrical activity.
Ejection fraction — the fraction of blood expelled by the left ventricle each beat — was able to distinguish reduced function at thresholds of 50%, 45% and 35% with AUC values ranging from 0.79–0.81. AUC measures how well the model separates groups.
In a follow‑up cohort of 17,566 subjects, the same features yielded a five‑year heart‑failure forecast with a C‑index of 0.76, compared with 0.63 for a forecast based on conventional ECG parameters. A single predicted ventricular‑motion sequence thus provides both anatomical measurements and risk prediction.
🔗 Read original →
On September 4, researchers posted a preprint on medRxiv preprint, September 4 describing VisionECG, a model trained on 71,132 ECG‑MRI pairs from the UK Biobank. The model learns to generate a sequence of 50 successive 3‑D surfaces of the left ventricle from a standard 12‑lead ECG and eight basic subject characteristics.
For 5,000 patients with both ECG and echocardiography, the model‑derived ejection fraction was compared to ultrasound measurements. From the reconstructed ventricular motion the model can compute volume, mass, wall thickness, ejection fraction and myocardial strain.
On an external test set of 2,000 participants the median relative error of volume over the cardiac cycle was 8.34%, and wall‑thickness error was 9.54%. When the individual ECG was replaced by the cohort average, the volume error in dilated cardiomyopathy rose from 12.59% to 20.29%, showing the model relies on person‑specific electrical activity.
Ejection fraction — the fraction of blood expelled by the left ventricle each beat — was able to distinguish reduced function at thresholds of 50%, 45% and 35% with AUC values ranging from 0.79–0.81. AUC measures how well the model separates groups.
In a follow‑up cohort of 17,566 subjects, the same features yielded a five‑year heart‑failure forecast with a C‑index of 0.76, compared with 0.63 for a forecast based on conventional ECG parameters. A single predicted ventricular‑motion sequence thus provides both anatomical measurements and risk prediction.
🔗 Read original →
medRxiv
Reconstructing synthetic hearts from ECG using flow matching
Cardiac imaging enables quantitative assessment of cardiac structure and function but remains constrained by cost, infrastructure and specialist expertise. In contrast, electrocardiogram (ECG) is widely accessible yet underexploited, despite encoding latent…