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.…

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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.

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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.…

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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.…

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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.…

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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.

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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.

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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

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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.

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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

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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

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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.

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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