Matt Kaeberlein Questions Genflow's Early Claim of Age Reversal in Dogs
On 8 September Genflow announced that it had met its pre‑specified primary endpoint in a trial of 24 beagles older than ten years. The company said the GRIM DNA‑methylation clock showed a lower biological age in the treated dogs compared with the saline‑treated group, and it pledged to present detailed results on 1–2 October.
On 12 September biogerontologist Matt Kaeberlein questioned why the outcome was released before the full data were available. He noted that, as far as he could see, no preprint or dataset existed to evaluate the claim of age reversal.
The study randomly assigned the 24 beagles to four groups, with assessors blinded to treatment. Three groups received different gene‑therapy variants, while the control group received saline. The primary endpoint was the GRIM clock, and Genflow plans to disclose the full dataset at the Animal Longevity Summit in Toronto on 1–2 October, with DNA‑clock and muscle‑histology results slated for 2 October.
Kaeberlein had previously discussed in August whether a shift in such a clock could be taken as evidence of an intervention’s effect, and he asked for the data needed to verify the claim of a 'reduction of biological age'. He highlighted the Longevity.Technology headline: 'Genflow gene therapy reverses aging in dogs'.
He argued that only after the 2 October release of the DNA‑clock and muscle‑histology measurements can the primary‑endpoint claim be properly checked against the underlying data.
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On 8 September Genflow announced that it had met its pre‑specified primary endpoint in a trial of 24 beagles older than ten years. The company said the GRIM DNA‑methylation clock showed a lower biological age in the treated dogs compared with the saline‑treated group, and it pledged to present detailed results on 1–2 October.
On 12 September biogerontologist Matt Kaeberlein questioned why the outcome was released before the full data were available. He noted that, as far as he could see, no preprint or dataset existed to evaluate the claim of age reversal.
The study randomly assigned the 24 beagles to four groups, with assessors blinded to treatment. Three groups received different gene‑therapy variants, while the control group received saline. The primary endpoint was the GRIM clock, and Genflow plans to disclose the full dataset at the Animal Longevity Summit in Toronto on 1–2 October, with DNA‑clock and muscle‑histology results slated for 2 October.
Kaeberlein had previously discussed in August whether a shift in such a clock could be taken as evidence of an intervention’s effect, and he asked for the data needed to verify the claim of a 'reduction of biological age'. He highlighted the Longevity.Technology headline: 'Genflow gene therapy reverses aging in dogs'.
He argued that only after the 2 October release of the DNA‑clock and muscle‑histology measurements can the primary‑endpoint claim be properly checked against the underlying data.
🔗 Read original →
X (formerly Twitter)
Matt Kaeberlein (@mkaeberlein) on X
Another example of "science by press release", which isn't really science at all.
A publicly traded company puts out a press release announcing amazing results for their gene therapy *before* e…
A publicly traded company puts out a press release announcing amazing results for their gene therapy *before* e…
Sinclair and Brenner Debate Why SIRT1‑Targeting Drug Programs Were Halted
On September 10 a study on the compound SRT1720 was released; it was tested on rat kidney cells and on rats with sepsis. On September 1
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On September 10 a study on the compound SRT1720 was released; it was tested on rat kidney cells and on rats with sepsis. On September 1
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PubMed Central (PMC)
Pharmacological activation of SIRT1 alleviates sepsis-associated acute kidney injury by improving renal mitochondrial energy metabolism
Sepsis-associated acute kidney injury (SA-AKI) is a frequent and severe complication of sepsis and is closely associated with increased mortality. Mitochondrial dysfunction and impaired energy metabolism are important contributors to SA-AKI ...
Roko Mijić Warns AI Growth Could Outpace Human Governance
Roko Mijić posted on X on September 12 that the rapid growth of AI capabilities could bypass human control, arguing that legal and political institutions might fail to steer AI’s expanding abilities in medicine, pensions, goods, and safety toward human benefit.
He sees governance as the condition that turns new capabilities into help for people; new ways of working and finding efficient solutions benefit humans only through rules and institutions that distribute their outputs, which he describes as a fragile link.
In his example, if AI’s ability to find efficient solutions grows about 50% per year, institutions could still treat it as fast economic growth, but at 1,000–10,000% per year AI would have enough optimization power to circumvent human governance, potentially leading to scenarios where AI overthrows the state instead of paying taxes or destroys people instead of treating aging.
He links the need for a slowdown in AI development — referencing an April conversation with David Wood about a contractual pause in the race for general‑purpose AI — to the task of reshaping governance to handle far more disruptive changes, arguing that surviving AI will require both slowing AI and rebuilding institutions.
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Roko Mijić posted on X on September 12 that the rapid growth of AI capabilities could bypass human control, arguing that legal and political institutions might fail to steer AI’s expanding abilities in medicine, pensions, goods, and safety toward human benefit.
He sees governance as the condition that turns new capabilities into help for people; new ways of working and finding efficient solutions benefit humans only through rules and institutions that distribute their outputs, which he describes as a fragile link.
In his example, if AI’s ability to find efficient solutions grows about 50% per year, institutions could still treat it as fast economic growth, but at 1,000–10,000% per year AI would have enough optimization power to circumvent human governance, potentially leading to scenarios where AI overthrows the state instead of paying taxes or destroys people instead of treating aging.
He links the need for a slowdown in AI development — referencing an April conversation with David Wood about a contractual pause in the race for general‑purpose AI — to the task of reshaping governance to handle far more disruptive changes, arguing that surviving AI will require both slowing AI and rebuilding institutions.
🔗 Read original →
X (formerly Twitter)
Roko 🐉 (@RokoMijic) on X
The big problem that humanity has with AI is that the legal and political systems that we use to turn work/optimization into utility for us (like medical care, pensions, products to buy, safe stre…
Single amino‑acid swap in CD27 boosts CAR‑T activity against CD70
In a preprint published on September 10, authors changed one amino acid in CD27 – the natural partner of the tumor antigen CD70.
CAR‑T cells are made by giving T lymphocytes a receptor that recognizes a chosen target; here the receptor’s recognition domain is CD27 itself rather than an antibody fragment. A 2025 study (2025 work) showed that a CD27‑CAR construct expanded in mouse blood roughly 80–100‑fold more than antibody‑based CARs in a myeloma model.
To improve CD27, the researchers modeled the CD27:CD70 interface and screened 24 contact residues; the N88A substitution (asparagine → alanine at position 88) emerged as the best candidate from both computational and experimental tests.
In vitro, N88A‑CAR‑T cells killed two AML cell lines faster than the parental CD27‑CAR. In a leukemia mouse model, animals received tumor cells and then 0.5 million CAR‑T cells after four days; tumors stayed below detection limits for the full 85‑day observation in the N88A group, whereas the original CD27‑CAR group had a median survival of 38 days.
In a myeloma model both CD27 versions kept tumors undetectable, but N88A showed greater expansion in mouse blood. Biochemical assays revealed N88A binds CD70 with a slower association rate but a >4‑fold slower dissociation, giving an approximately 2‑fold stronger CD27:CD70 complex; modeling suggests the complex can adopt multiple bound states, consistent with the measured slow off‑rate.
Off‑target screening detected signal only at FCGR3A due to the
🔗 Read original →
In a preprint published on September 10, authors changed one amino acid in CD27 – the natural partner of the tumor antigen CD70.
CAR‑T cells are made by giving T lymphocytes a receptor that recognizes a chosen target; here the receptor’s recognition domain is CD27 itself rather than an antibody fragment. A 2025 study (2025 work) showed that a CD27‑CAR construct expanded in mouse blood roughly 80–100‑fold more than antibody‑based CARs in a myeloma model.
To improve CD27, the researchers modeled the CD27:CD70 interface and screened 24 contact residues; the N88A substitution (asparagine → alanine at position 88) emerged as the best candidate from both computational and experimental tests.
In vitro, N88A‑CAR‑T cells killed two AML cell lines faster than the parental CD27‑CAR. In a leukemia mouse model, animals received tumor cells and then 0.5 million CAR‑T cells after four days; tumors stayed below detection limits for the full 85‑day observation in the N88A group, whereas the original CD27‑CAR group had a median survival of 38 days.
In a myeloma model both CD27 versions kept tumors undetectable, but N88A showed greater expansion in mouse blood. Biochemical assays revealed N88A binds CD70 with a slower association rate but a >4‑fold slower dissociation, giving an approximately 2‑fold stronger CD27:CD70 complex; modeling suggests the complex can adopt multiple bound states, consistent with the measured slow off‑rate.
Off‑target screening detected signal only at FCGR3A due to the
🔗 Read original →
bioRxiv
Deep Learning-based Modeling Enhances Efficacy of Natural Ligand CAR Binders Targeting CD70
CD70 is well-recognized as a promising “pan-cancer” chimeric antigen receptor (CAR) T-cell target. Prior work has shown that a “natural ligand” (NL)-based CAR targeting CD70, employing its physiological interaction partner CD27, may have therapeutic advantages…
PHAROS preprint introduces algorithm to find drug sequences for desired cell states
On September 10 the PHAROS preprint appeared, describing a system that takes the current and desired states of a cell group and searches for an order of drug perturbations that, according to its calculations, brings the first state closer to the second. The approach relies on the STATE model, which is trained to predict how a cell group changes after a drug is applied. Unlike a standard cellular‑response model that predicts the effect of a given drug, PHAROS begins with the initial and target cell states.
The authors frame therapy discovery as a reverse question: “Which interventions are most likely to shift a heterogeneous cell population from its present state to a desired one?” PHAROS applies drugs one at a time; after each step
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On September 10 the PHAROS preprint appeared, describing a system that takes the current and desired states of a cell group and searches for an order of drug perturbations that, according to its calculations, brings the first state closer to the second. The approach relies on the STATE model, which is trained to predict how a cell group changes after a drug is applied. Unlike a standard cellular‑response model that predicts the effect of a given drug, PHAROS begins with the initial and target cell states.
The authors frame therapy discovery as a reverse question: “Which interventions are most likely to shift a heterogeneous cell population from its present state to a desired one?” PHAROS applies drugs one at a time; after each step
🔗 Read original →
bioRxiv
PHAROS: turning single-cell perturbation models into target-directed drug-combination screens
Combination therapies are central to cancer treatment, but exhaustive screening is impractical. We introduce PHAROS, a framework that turns a pretrained single-cell perturbation model into a target-directed search engine for drug combinations. PHAROS predicts…
New perspective proposes assay for tissue repair and tumor risk after cancer therapy
On September 11 Adriana Paulina Gudino Reyes published a perspective on restoring normal tissue after cancer treatment. She proposes checking the recovery of damaged tissue together with signs that the intervention might support tumor growth. Oncology metrics track tumor burden, progression and survival; Reyes adds a separate outcome: can damaged normal tissue regain its function. Tissue repair and tumor adaptation may use the same cellular signals. In aged mice, activating the Igf2 gene restored the liver’s regenerative capacity, while blocking the IGF1R protein‑receptor reduced tumor burden in a hepatoblastoma model. In healthy growing mice the same blocker decreased liver size and body mass. One growth pathway participated in both tissue repair and tumor growth under different conditions. Tissue repair engages inflammation, angiogenesis and extracellular‑matrix remodeling; in tumors the same processes occur among malignant, immune and stromal cells. “The same signaling network can support normal‑tissue repair while simultaneously helping the tumor survive, invade or evade immunity.” Reyes recommends moving from simple models to complex ones: first compare normal and tumor human cells before damage, after damage and during recovery; then add stromal and immune cells. Organoids and co‑cultures allow testing their interactions, as do microphysiological systems that replicate tissue functions. In each model she suggests pairing normal‑tissue repair readouts with tumor‑cell proliferation, invasion, angiogenic signaling, genetic integrity and therapy sensitivity. As an example she analyzes stromal cells from Wharton’s jelly – umbilical‑cord tissue – whose properties depend on source, purity, culture conditions, passage number, genetic stability, sterility and traceability from donor to sample. These data let one assess how a specific cell product behaves alongside a particular tumor.
🔗 Read original →
On September 11 Adriana Paulina Gudino Reyes published a perspective on restoring normal tissue after cancer treatment. She proposes checking the recovery of damaged tissue together with signs that the intervention might support tumor growth. Oncology metrics track tumor burden, progression and survival; Reyes adds a separate outcome: can damaged normal tissue regain its function. Tissue repair and tumor adaptation may use the same cellular signals. In aged mice, activating the Igf2 gene restored the liver’s regenerative capacity, while blocking the IGF1R protein‑receptor reduced tumor burden in a hepatoblastoma model. In healthy growing mice the same blocker decreased liver size and body mass. One growth pathway participated in both tissue repair and tumor growth under different conditions. Tissue repair engages inflammation, angiogenesis and extracellular‑matrix remodeling; in tumors the same processes occur among malignant, immune and stromal cells. “The same signaling network can support normal‑tissue repair while simultaneously helping the tumor survive, invade or evade immunity.” Reyes recommends moving from simple models to complex ones: first compare normal and tumor human cells before damage, after damage and during recovery; then add stromal and immune cells. Organoids and co‑cultures allow testing their interactions, as do microphysiological systems that replicate tissue functions. In each model she suggests pairing normal‑tissue repair readouts with tumor‑cell proliferation, invasion, angiogenic signaling, genetic integrity and therapy sensitivity. As an example she analyzes stromal cells from Wharton’s jelly – umbilical‑cord tissue – whose properties depend on source, purity, culture conditions, passage number, genetic stability, sterility and traceability from donor to sample. These data let one assess how a specific cell product behaves alongside a particular tumor.
🔗 Read original →
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New Neurointerface Restores Speech and Movement via 3D Avatar
This neurointerface helps people with severe paralysis fully restore both nonverbal and verbal communication. While earlier systems could decode either speech or movement in isolation, this development is the first to combine both functions, translating brain signals in real time through a full‑size digital 3D avatar that speaks and reproduces facial expressions and gestures.
It relies on a single high-density ECoG implant that reads the electrical activity of the cerebral cortex. Researchers found that the brain zones responsible for speech and limb movement partly overlap in activity. To prevent interference, engineers built a specialized AI model with parallel decoders that separate and simultaneously process commands for articulation and gesturing (such as a shoulder shrug, head nod, or fist raise).
The neurointerface was successfully tested on three patients who had completely lost the ability to communicate. In dialogue tests the system showed high accuracy of intent recognition, and one participant reached 100% average decoding accuracy for both speech and gestures. This perfect score was maintained across three conversational blocks.
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This neurointerface helps people with severe paralysis fully restore both nonverbal and verbal communication. While earlier systems could decode either speech or movement in isolation, this development is the first to combine both functions, translating brain signals in real time through a full‑size digital 3D avatar that speaks and reproduces facial expressions and gestures.
It relies on a single high-density ECoG implant that reads the electrical activity of the cerebral cortex. Researchers found that the brain zones responsible for speech and limb movement partly overlap in activity. To prevent interference, engineers built a specialized AI model with parallel decoders that separate and simultaneously process commands for articulation and gesturing (such as a shoulder shrug, head nod, or fist raise).
The neurointerface was successfully tested on three patients who had completely lost the ability to communicate. In dialogue tests the system showed high accuracy of intent recognition, and one participant reached 100% average decoding accuracy for both speech and gestures. This perfect score was maintained across three conversational blocks.
🔗 Read original →
Nature
Simultaneous speech and gesture decoding for multimodal communication in paralysis
Nature Neuroscience - Brosler et al. develop a brain–computer interface that simultaneously decodes speech and gestures from a single cortical implant to animate a virtual avatar, providing a...
Space Exposure Tests Reveal Cataract Lens Durability on ISS
Scientists sent intraocular lenses used in cataract surgery to the International Space Station to evaluate how artificial lens materials endure the harsh environment of open space. This knowledge is vital for preparing long‑duration missions to the Moon and Mars, where transplantation and on‑site surgical care may become essential because of radiation, injury, and crew aging.
135 lenses were removed from sterile packaging and mounted in special containers on the station’s exterior, where they faced direct vacuum, temperature swings, solar ultraviolet radiation, and a stream of atomic oxygen for six months at three different shielding levels. In parallel, 45 lenses from the same batch were kept in a control container on Earth at room temperature and normal
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Scientists sent intraocular lenses used in cataract surgery to the International Space Station to evaluate how artificial lens materials endure the harsh environment of open space. This knowledge is vital for preparing long‑duration missions to the Moon and Mars, where transplantation and on‑site surgical care may become essential because of radiation, injury, and crew aging.
135 lenses were removed from sterile packaging and mounted in special containers on the station’s exterior, where they faced direct vacuum, temperature swings, solar ultraviolet radiation, and a stream of atomic oxygen for six months at three different shielding levels. In parallel, 45 lenses from the same batch were kept in a control container on Earth at room temperature and normal
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ARPA‑H awards AI contracts for heart‑failure patient support between visits
On September 9, the US agency ARPA‑H announced contract awards for its 39‑month ADVOCATE program aimed at developing AI agents to assist heart‑failure patients between clinic visits. In the first stage, teams have 24 months to build an AI agent and submit a FDA device authorization request.
Heart‑failure management requires clinicians to iteratively adjust therapy based on symptoms, blood pressure, kidney function, and drug tolerance. ADVOCATE seeks to shift some of this repetitive work outside the visit by having the agent interact with patients, support them, and escalate cases to the clinical team.
The first‑stage contracts went to Atman Health, Tempus AI, UpDoc. The program also funds an AI observer that will monitor the agent in real time for unsafe recommendations, and an independent evaluation by the Johns Hopkins University Applied Physics Lab to assess technical performance and clinical outcomes.
Because algorithms can learn site‑specific habits, a review of medical‑AI auditing notes that local rules and patient mixes leave traces in records, causing a model to perform well in one hospital but poorly elsewhere. UpDoc’s roadmap includes independent validation, comparing the agent’s decisions with those of cardiologists, then an FDA‑cleared investigational‑device clinical study.
Atman uses a language model that reads medical records and converses with patients, while a separate rule‑based system makes treatment decisions so clinicians can see the logic behind each recommendation. The program’s trajectory — from contracts, through observer oversight, independent assessment, and usual‑care comparison — leads to clinical verification.
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On September 9, the US agency ARPA‑H announced contract awards for its 39‑month ADVOCATE program aimed at developing AI agents to assist heart‑failure patients between clinic visits. In the first stage, teams have 24 months to build an AI agent and submit a FDA device authorization request.
Heart‑failure management requires clinicians to iteratively adjust therapy based on symptoms, blood pressure, kidney function, and drug tolerance. ADVOCATE seeks to shift some of this repetitive work outside the visit by having the agent interact with patients, support them, and escalate cases to the clinical team.
The first‑stage contracts went to Atman Health, Tempus AI, UpDoc. The program also funds an AI observer that will monitor the agent in real time for unsafe recommendations, and an independent evaluation by the Johns Hopkins University Applied Physics Lab to assess technical performance and clinical outcomes.
Because algorithms can learn site‑specific habits, a review of medical‑AI auditing notes that local rules and patient mixes leave traces in records, causing a model to perform well in one hospital but poorly elsewhere. UpDoc’s roadmap includes independent validation, comparing the agent’s decisions with those of cardiologists, then an FDA‑cleared investigational‑device clinical study.
Atman uses a language model that reads medical records and converses with patients, while a separate rule‑based system makes treatment decisions so clinicians can see the logic behind each recommendation. The program’s trajectory — from contracts, through observer oversight, independent assessment, and usual‑care comparison — leads to clinical verification.
🔗 Read original →
PR Newswire
Atman Health Wins ARPA-H Award to Build Agentic AI for Cardiovascular Care, Starting with Heart Failure
/PRNewswire/ -- Atman Health today announced that it has been selected by the Advanced Research Projects Agency for Health (ARPA-H) to develop an agentic...
Mitochondria in nerve terminals linked to varied rule‑switching in aged mice
Researchers linked poorer rule‑switching in aged mice to mitochondria in nerve terminals. The study appeared September 14 in Aging Cell. They examined the medial prefrontal cortex and tested the mitochondrial antioxidant MitoQ, which accumulates in mitochondria.
Mice first learned to obtain a reward for one of two screen lines. Then the rule changed so that reward depended on touching one side of the screen regardless of line, measuring the ability to abandon a learned response and adopt a new one.
Male C57BL/6J mice mastered the initial task equally, but after the rule switch accuracy in the final session varied widely among old animals. Investigators sought a marker of behavioral flexibility after the initial task was learned.
Three‑dimensional electron microscopy showed synaptic density declines with age. In old mice task accuracy varied independently of synaptic density and size, while a higher proportion of synapses containing a mitochondrion in the nerve terminal correlated with lower accuracy.
Proteomic analysis of a synapse‑enriched fraction found poorer accuracy matched higher levels of mitochondrial proteins, including those involved in energy production. Comparing age‑related proteins with accuracy‑correlated proteins revealed little overlap, indicating distinct protein sets for aging versus individual differences.
From week 55 to week 75 mice received MitoQ in water or the control compound dTPP. The final analysis included seven MitoQ‑treated and five dTPP‑treated mice. MitoQ improved performance on the rule‑switching task while initial learning remained equal. After MitoQ the synaptosomal fraction showed reduced mitochondrial and pro‑apoptotic proteins linked to programmed cell death.
The authors propose mitochondria in nerve terminals as a testable component explaining why same‑aged animals differ in behavioral adaptation after condition changes.
🔗 Read original →
Researchers linked poorer rule‑switching in aged mice to mitochondria in nerve terminals. The study appeared September 14 in Aging Cell. They examined the medial prefrontal cortex and tested the mitochondrial antioxidant MitoQ, which accumulates in mitochondria.
Mice first learned to obtain a reward for one of two screen lines. Then the rule changed so that reward depended on touching one side of the screen regardless of line, measuring the ability to abandon a learned response and adopt a new one.
Male C57BL/6J mice mastered the initial task equally, but after the rule switch accuracy in the final session varied widely among old animals. Investigators sought a marker of behavioral flexibility after the initial task was learned.
Three‑dimensional electron microscopy showed synaptic density declines with age. In old mice task accuracy varied independently of synaptic density and size, while a higher proportion of synapses containing a mitochondrion in the nerve terminal correlated with lower accuracy.
Proteomic analysis of a synapse‑enriched fraction found poorer accuracy matched higher levels of mitochondrial proteins, including those involved in energy production. Comparing age‑related proteins with accuracy‑correlated proteins revealed little overlap, indicating distinct protein sets for aging versus individual differences.
From week 55 to week 75 mice received MitoQ in water or the control compound dTPP. The final analysis included seven MitoQ‑treated and five dTPP‑treated mice. MitoQ improved performance on the rule‑switching task while initial learning remained equal. After MitoQ the synaptosomal fraction showed reduced mitochondrial and pro‑apoptotic proteins linked to programmed cell death.
The authors propose mitochondria in nerve terminals as a testable component explaining why same‑aged animals differ in behavioral adaptation after condition changes.
🔗 Read original →
PubMed Central (PMC)
Mitochondrial ecosystem restoration in Alzheimer’s disease: from mechanisms to multi-target therapeutic strategies
Alzheimer’s disease (AD), the most prevalent cause of dementia, lacks definitive cures despite decades of research focused on amyloid-beta (Aβ) and tau pathologies. Emerging evidence positions mitochondrial dysfunction not merely as a downstream ...
GenEHR predicts 5‑year cancer risk from electronic health records
Authors evaluated GenEHR on five existing EHR databases. For each database they trained a separate model version that estimates the probability of a first cancer diagnosis within 6–60 months and ranks individuals for targeted screening. The preprint was posted on 11 September.
The model incorporates the order of diagnoses, medications, procedures, lab results, and intervals between visits. A repeat analysis a week after an abnormal result may signal active diagnostic work‑up, whereas the same analysis a year later often reflects routine annual check‑up. First
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Authors evaluated GenEHR on five existing EHR databases. For each database they trained a separate model version that estimates the probability of a first cancer diagnosis within 6–60 months and ranks individuals for targeted screening. The preprint was posted on 11 September.
The model incorporates the order of diagnoses, medications, procedures, lab results, and intervals between visits. A repeat analysis a week after an abnormal result may signal active diagnostic work‑up, whereas the same analysis a year later often reflects routine annual check‑up. First
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medRxiv
Generative model of patient health states and pan-cancer risk stratification
While large language models are powerful generators of new text, forecasting disease progression from longitudinal health histories remains a challenging problem. We introduce GenEHR, an autoregressive generative model trained on electronic health records…
GenScript to invest 70% of IPO proceeds in AI‑driven automated labs
On September 11, GenScript signed a conditional agreement to place 77.126 million new shares at HK$30.50 each. If fully placed, the company expects to receive about HK$2.327 billion after expenses.
GenScript plans to direct roughly 70% of these net proceeds toward automated laboratories for AI‑based drug discovery. About 20% will go to related research, workflow‑linking software, and international platform expansion.
The AI system proposes candidate molecules that could become future drugs; the lab then synthesizes them and tests whether they bind to a chosen biological target, such as a disease‑relevant protein, and measures their properties. These results feed the next round of computer‑driven design.
Automated high‑throughput labs run such experiments in large batches, and the exchange announcement notes that funds will also cover equipment, upgrades to existing facilities, and expanded synthesis, screening, and testing capabilities. The board intends to use the raised capital to expand this infrastructure, while current operations are funded from
🔗 Read original →
On September 11, GenScript signed a conditional agreement to place 77.126 million new shares at HK$30.50 each. If fully placed, the company expects to receive about HK$2.327 billion after expenses.
GenScript plans to direct roughly 70% of these net proceeds toward automated laboratories for AI‑based drug discovery. About 20% will go to related research, workflow‑linking software, and international platform expansion.
The AI system proposes candidate molecules that could become future drugs; the lab then synthesizes them and tests whether they bind to a chosen biological target, such as a disease‑relevant protein, and measures their properties. These results feed the next round of computer‑driven design.
Automated high‑throughput labs run such experiments in large batches, and the exchange announcement notes that funds will also cover equipment, upgrades to existing facilities, and expanded synthesis, screening, and testing capabilities. The board intends to use the raised capital to expand this infrastructure, while current operations are funded from
🔗 Read original →
Five pharma firms improve protein‑ligand AI model via federated learning
Five pharmaceutical companies jointly fine‑tuned OpenFold3 Preview 2 on a private set of 20,167 confidential structures and evaluated on a held‑out set of 1,056 structures. The work was reported by Nature on 14 September.
For a drug to work its molecule must bind a specific site on the target protein; OpenFold3 builds a 3D model of the protein‑ligand pair from sequence and molecular description. Useful structures often stay inside pharma pipelines because they involve undisclosed molecules and targets.
OpenFold released the weights, code and data for OpenFold3 in March, allowing anyone to reproduce and fine‑tune the model. Each company kept its own structures locally and fine‑tuned a copy of the model; updates were aggregated into a shared version using federated learning.
On the held‑out set the fine‑tuned version reached the target accuracy in 52.1% of cases, versus 35.6% for the original OpenFold3 Preview 2 and 40.9% for Boltz‑
🔗 Read original →
Five pharmaceutical companies jointly fine‑tuned OpenFold3 Preview 2 on a private set of 20,167 confidential structures and evaluated on a held‑out set of 1,056 structures. The work was reported by Nature on 14 September.
For a drug to work its molecule must bind a specific site on the target protein; OpenFold3 builds a 3D model of the protein‑ligand pair from sequence and molecular description. Useful structures often stay inside pharma pipelines because they involve undisclosed molecules and targets.
OpenFold released the weights, code and data for OpenFold3 in March, allowing anyone to reproduce and fine‑tune the model. Each company kept its own structures locally and fine‑tuned a copy of the model; updates were aggregated into a shared version using federated learning.
On the held‑out set the fine‑tuned version reached the target accuracy in 52.1% of cases, versus 35.6% for the original OpenFold3 Preview 2 and 40.9% for Boltz‑
🔗 Read original →
Nature
Drug firms’ secret data supercharge AI protein models
Nature - An AI system trained on more than 20,000 protein structures from pharmaceutical companies outperforms AlphaFold-like models that use only public data.
Perfusion lowers liver biological age, improves transplant outcomes
On September 14, MIT Technology Review, September 14 reported unpublished data from a Boston team showing that connecting donor livers to an oxygenated perfusion device is linked to a lower biological age assessment. The findings were presented at an industry conference.
In two series of molecular measurements, biological age scores were lower for livers after machine perfusion than for those stored on ice. The first series examined 37 samples from 19 livers via epigenetic marks; the second series evaluated 208 samples from 103 livers by gene activity.
After adjusting for chronological age, the difference between groups was about 30%. After transplantation, scores rose in both groups but remained lower for perfused livers.
Gene activity related to inflammation and tissue structure changed, and cells more actively cleared damaged parts, accompanying the lower biological age scores.
In a 2022 randomized study of 300 recipients, normothermic perfusion reduced early graft dysfunction from 31% to 18%.
The new data add a molecular assessment of organ condition before surgery to that clinical result. Perfusion systems also allow drugs to be delivered directly to the liver before operation. In another study, the drug FXT-001 was added to the system’s fluid to protect cell membranes from oxidative damage.
The current team is testing drug treatments for livers; biological age assessment could show how such preparation alters tissue.
🔗 Read original →
On September 14, MIT Technology Review, September 14 reported unpublished data from a Boston team showing that connecting donor livers to an oxygenated perfusion device is linked to a lower biological age assessment. The findings were presented at an industry conference.
In two series of molecular measurements, biological age scores were lower for livers after machine perfusion than for those stored on ice. The first series examined 37 samples from 19 livers via epigenetic marks; the second series evaluated 208 samples from 103 livers by gene activity.
After adjusting for chronological age, the difference between groups was about 30%. After transplantation, scores rose in both groups but remained lower for perfused livers.
Gene activity related to inflammation and tissue structure changed, and cells more actively cleared damaged parts, accompanying the lower biological age scores.
In a 2022 randomized study of 300 recipients, normothermic perfusion reduced early graft dysfunction from 31% to 18%.
The new data add a molecular assessment of organ condition before surgery to that clinical result. Perfusion systems also allow drugs to be delivered directly to the liver before operation. In another study, the drug FXT-001 was added to the system’s fluid to protect cell membranes from oxidative damage.
The current team is testing drug treatments for livers; biological age assessment could show how such preparation alters tissue.
🔗 Read original →
PubMed Central (PMC)
Impact of Portable Normothermic Blood-Based Machine Perfusion on Outcomes of Liver Transplant: The OCS Liver PROTECT Randomized…
Can oxygenated portable normothermic perfusion of deceased donor livers for transplant improve outcomes compared with the current standard of care using ischemic cold storage? In this multicenter randomized clinical trial of 300 recipients of liver ...
Biological Age Estimates Vary Depending on Signals and Populations Studied
On 8 September, Frontiers in Aging published a review of 435 studies from January 2011 — June 2023 that examined biomarkers of aging and how they are combined into biological age estimates. The authors note that the resulting estimate depends on which signals are used and on the group of people it was tested on.
Biological age tries to capture aging through markers such as telomere length, blood proteins, or gene activity. Some estimates rely on a single marker, others use models that combine several signals, so the same term can refer to different measurements.
In 123 of 162 studies, older participants tended to have shorter telomeres, while 25 studies found no such link. The association was common but varied across works, keeping telomere length as one of many aging signals.
The review also covers blood proteins and metabolites, gene expression, and multi‑marker models. Authors stress that different biological age measures give divergent results and ask how they relate, and which markers truly reflect aging versus drive it.
Performance of algorithms can differ across sexes, ethnicities, social groups, lifestyles, and environments; one study showed better accuracy when applied to the population on which it was trained. The review concludes that a biological age number is meaningful only when accompanied by an explanation of the signals it integrates, what they reflect biologically, and for whom it was validated.
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On 8 September, Frontiers in Aging published a review of 435 studies from January 2011 — June 2023 that examined biomarkers of aging and how they are combined into biological age estimates. The authors note that the resulting estimate depends on which signals are used and on the group of people it was tested on.
Biological age tries to capture aging through markers such as telomere length, blood proteins, or gene activity. Some estimates rely on a single marker, others use models that combine several signals, so the same term can refer to different measurements.
In 123 of 162 studies, older participants tended to have shorter telomeres, while 25 studies found no such link. The association was common but varied across works, keeping telomere length as one of many aging signals.
The review also covers blood proteins and metabolites, gene expression, and multi‑marker models. Authors stress that different biological age measures give divergent results and ask how they relate, and which markers truly reflect aging versus drive it.
Performance of algorithms can differ across sexes, ethnicities, social groups, lifestyles, and environments; one study showed better accuracy when applied to the population on which it was trained. The review concludes that a biological age number is meaningful only when accompanied by an explanation of the signals it integrates, what they reflect biologically, and for whom it was validated.
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Frontiers
Frontiers | Molecular markers, mechanisms and metrics of biological aging: a scoping review
Biological aging is a rapidly growing area of research, which entails characterizing the rate of aging independent of an individual’s chronological age. In t...
Founder of Nucleus Genomics Calls for 'Genetic Optimization Industry'
On 8 September, Kian Sadeghi, the founder of Nucleus Genomics, published an essay titled Evolution by Genetic Optimization. In it he groups embryo selection, gene editing, and technologies that could increase the number of available oocytes.
He argues that the main mechanism of genetic optimization is selection, not construction, and assigns gene editing to cases requiring a new genetic change. Selection, he links to IVG — a developing technology for obtaining eggs or sperm from other body cells — which would increase the number of gametes and thus embryos with different DNA combinations for evaluation and choice.
In IVF clinics, preimplantation genetic testing is already used to screen embryos before transfer, including for single‑gene disorders. Sadeghi also incorporates polygenic scores — calculations of disease risk or trait likelihood from many DNA variants — into his program. Authors of an article in Scientific American distinguish such testing from polygenic assessments of complex diseases and traits
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On 8 September, Kian Sadeghi, the founder of Nucleus Genomics, published an essay titled Evolution by Genetic Optimization. In it he groups embryo selection, gene editing, and technologies that could increase the number of available oocytes.
He argues that the main mechanism of genetic optimization is selection, not construction, and assigns gene editing to cases requiring a new genetic change. Selection, he links to IVG — a developing technology for obtaining eggs or sperm from other body cells — which would increase the number of gametes and thus embryos with different DNA combinations for evaluation and choice.
In IVF clinics, preimplantation genetic testing is already used to screen embryos before transfer, including for single‑gene disorders. Sadeghi also incorporates polygenic scores — calculations of disease risk or trait likelihood from many DNA variants — into his program. Authors of an article in Scientific American distinguish such testing from polygenic assessments of complex diseases and traits
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medRxiv
Within- and Between-Family Validation of Nine Polygenic Risk Scores Developed in 1.5 Million Individuals: Implications for IVF…
Polygenic risk scores (PRSs) can reduce lifetime disease risk by guiding embryo selection during in vitro fertilization (IVF). We performed genome-wide association meta-analyses totaling ∼1.5 million individuals to construct state-of-the-art PRSs for nine…
US Military Pushes for AI Dominance While AI Leaders Call for Slowdown
It is absurd to see the usual roles reversed. Normally one expects officials and the military to warn about uncontrolled technologies and demand tighter controls, while private corporations quietly push progress for profit. Instead, the heads of leading AI laboratories are publishing manifestos urging a slowdown of the tech race, calling for audits and a pause in the development of super‑intelligent systems.
At the very same moment the U.S. Department of Defense is openly posting slogans styled “Americanism, not effective altruism” and stating that its primary goal is absolute AI dominance. Adding to the paradox, the recent Palantir manifesto — which the White House openly follows — reinforces this stance. Thus, while developers fear their own algorithms and request a pause, government agencies are pressing the accelerator to the floor.
This signals that an evolutionary transition is imminent, and the power apparatus understands that whoever first forges a machine intelligence of a higher level will claim the future world. Attempts to curb the singularity are failing, which is a good sign, and at some point the government may recognize the potential of augments and genetic editing — a capability not weaker than AI and sometimes stronger. This could be the very trigger of exponential growth that Kurzweil warned about.
🔗 Source: @solid_state_humanity
It is absurd to see the usual roles reversed. Normally one expects officials and the military to warn about uncontrolled technologies and demand tighter controls, while private corporations quietly push progress for profit. Instead, the heads of leading AI laboratories are publishing manifestos urging a slowdown of the tech race, calling for audits and a pause in the development of super‑intelligent systems.
At the very same moment the U.S. Department of Defense is openly posting slogans styled “Americanism, not effective altruism” and stating that its primary goal is absolute AI dominance. Adding to the paradox, the recent Palantir manifesto — which the White House openly follows — reinforces this stance. Thus, while developers fear their own algorithms and request a pause, government agencies are pressing the accelerator to the floor.
This signals that an evolutionary transition is imminent, and the power apparatus understands that whoever first forges a machine intelligence of a higher level will claim the future world. Attempts to curb the singularity are failing, which is a good sign, and at some point the government may recognize the potential of augments and genetic editing — a capability not weaker than AI and sometimes stronger. This could be the very trigger of exponential growth that Kurzweil warned about.
🔗 Source: @solid_state_humanity
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Solid State Humanity
Вы вообще представьте абсурдность ситуации. Обычно ждешь, что именно чиновники и военные будут кричать о "неконтролируемых технологиях" и требовать закрутить гайки, а частные корпорации - тайком продавливать прогресс ради прибыли.
Главы ведущих ИИ-лабораторий…
Главы ведущих ИИ-лабораторий…
Two substantia nigra connectivity axes tied to aging/movement and memory/mood
On 8 September, Molecular Psychiatry published an article on the substantia nigra, a small midbrain region involved in movement control. Using data from over a thousand participants across four independent datasets, researchers identified two stable connectivity axes within this region.
First, they built a map using resting‑state fMRI from 618 healthy participants aged 18‑88, then replicated it in a separate group of 184 young participants with higher‑resolution scans. In both samples the same two axes emerged.
The first axis runs from the inner to outer part of the substantia nigra and correlates with age, reaction speed, motor learning and planning ability. In clinical datasets this axis differed according to the result of SAA‑analysis of cerebrospinal fluid, which tests whether the protein alpha‑synuclein forms aggregates.
The second axis extends from the posterior to anterior part of the region. In healthy aging it linked to memory, cognitive flexibility, anxiety and depression. In
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On 8 September, Molecular Psychiatry published an article on the substantia nigra, a small midbrain region involved in movement control. Using data from over a thousand participants across four independent datasets, researchers identified two stable connectivity axes within this region.
First, they built a map using resting‑state fMRI from 618 healthy participants aged 18‑88, then replicated it in a separate group of 184 young participants with higher‑resolution scans. In both samples the same two axes emerged.
The first axis runs from the inner to outer part of the substantia nigra and correlates with age, reaction speed, motor learning and planning ability. In clinical datasets this axis differed according to the result of SAA‑analysis of cerebrospinal fluid, which tests whether the protein alpha‑synuclein forms aggregates.
The second axis extends from the posterior to anterior part of the region. In healthy aging it linked to memory, cognitive flexibility, anxiety and depression. In
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No accelerated gray‑matter loss found at menopause transition, study shows
Researchers analyzed repeated MRI scans of 1,095 participants taken during puberty, pregnancy, and menopause. The study was published on 8 September in Nature Communications.
The menopause transition analysis included 120 women who answered “no” to menopause at the first scan and “yes” at the second. For comparison, researchers
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Researchers analyzed repeated MRI scans of 1,095 participants taken during puberty, pregnancy, and menopause. The study was published on 8 September in Nature Communications.
The menopause transition analysis included 120 women who answered “no” to menopause at the first scan and “yes” at the second. For comparison, researchers
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PubMed Central (PMC)
Puberty, pregnancy, and menopause show shared and distinct structural changes across the lifespan
The female brain undergoes substantial reorganization during major hormonal transitions, yet whether puberty, pregnancy, and menopause engage shared or distinct neuroplastic mechanisms remains unknown. We compared longitudinal structural brain ...
Waymo robotaxis crash rates 68% lower than human drivers in four US cities
The Insurance Institute for Highway Safety (IIHS) compared Waymo’s driver‑less robotaxi trips with human driving in San Francisco, Phoenix, Los Angeles and Austin. In the sample, injury‑causing crashes per mile were 81% lower for Waymo. Overall comparable crashes per mile were 68% lower.
The analysis covered about 50 million miles traveled by Waymo vehicles versus 222 billion miles driven by humans in the same areas and period. Only 22% of the 736 automated‑system incidents were deemed comparable to police‑reportable crashes.
By city, the reduction was 76% in Phoenix, 71% in Los Angeles and 35% in San Francisco, while Austin showed a 4% increase—a figure sensitive to few events. These results refer to the current Waymo robotaxi fleet and to the crash category defined as police‑reportable.
IIHS recommends a unified data‑collection system for mileage, operating mode and crashes to maintain comparable monitoring as robot
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The Insurance Institute for Highway Safety (IIHS) compared Waymo’s driver‑less robotaxi trips with human driving in San Francisco, Phoenix, Los Angeles and Austin. In the sample, injury‑causing crashes per mile were 81% lower for Waymo. Overall comparable crashes per mile were 68% lower.
The analysis covered about 50 million miles traveled by Waymo vehicles versus 222 billion miles driven by humans in the same areas and period. Only 22% of the 736 automated‑system incidents were deemed comparable to police‑reportable crashes.
By city, the reduction was 76% in Phoenix, 71% in Los Angeles and 35% in San Francisco, while Austin showed a 4% increase—a figure sensitive to few events. These results refer to the current Waymo robotaxi fleet and to the crash category defined as police‑reportable.
IIHS recommends a unified data‑collection system for mileage, operating mode and crashes to maintain comparable monitoring as robot
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Algorithm Finds Optimal Nerve‑Cortex Pulse Pause Faster Than Random Search in Adults
A preprint released on 8 September describes how researchers tested ten adults and eight children to determine the optimal pause between an electrical nerve impulse and a magnetic brain pulse. They varied the pause from 5 to 130 ms in 5‑ms steps (26 pauses total), repeating each pause ten times for adults and six times for children, and built individual response maps of the tibialis anterior muscle.
After three randomly selected pulse pairs, a Gaussian‑process model predicted the next pause to try, aiming for a response level at 90 % of each participant’s individual range between weakest and strongest responses. The model’s suggestion was checked against the full map after each trial.
In adults, the algorithm reached the target in nine out of ten participants, requiring a median of 10 pulse pairs, whereas random selection needed a median of 20 pairs. In children, the algorithm succeeded in five of eight participants with a median of 45 pairs, while random search succeeded in four of eight with a median of 56 pairs.
When predicting a left‑out pause from the remaining data, the model achieved an average R² of 0.71 for adults and 0.18 for children. Authors attribute the poorer child performance to greater response variability and the lower number
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A preprint released on 8 September describes how researchers tested ten adults and eight children to determine the optimal pause between an electrical nerve impulse and a magnetic brain pulse. They varied the pause from 5 to 130 ms in 5‑ms steps (26 pauses total), repeating each pause ten times for adults and six times for children, and built individual response maps of the tibialis anterior muscle.
After three randomly selected pulse pairs, a Gaussian‑process model predicted the next pause to try, aiming for a response level at 90 % of each participant’s individual range between weakest and strongest responses. The model’s suggestion was checked against the full map after each trial.
In adults, the algorithm reached the target in nine out of ten participants, requiring a median of 10 pulse pairs, whereas random selection needed a median of 20 pairs. In children, the algorithm succeeded in five of eight participants with a median of 45 pairs, while random search succeeded in four of eight with a median of 56 pairs.
When predicting a left‑out pause from the remaining data, the model achieved an average R² of 0.71 for adults and 0.18 for children. Authors attribute the poorer child performance to greater response variability and the lower number
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PubMed Central (PMC)
Autonomous optimization of neuroprosthetic stimulation parameters that drive the motor cortex and spinal cord outputs in rats and…
Neural stimulation can alleviate paralysis and sensory deficits. Novel high-density neural interfaces can enable refined and multipronged neurostimulation interventions. To achieve this, it is essential to develop algorithmic frameworks capable of ...