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Category: bioengineering

AI + Synthetic Biology: The Most Transformative Technology in Human History | Ben Lamm (Colossal)

This episode was filmed at the 2026 Abundance360 Summit.

This interview explores the groundbreaking work of Colossal in synthetic biology, de-extinction, and AI integration. Colossal CEO Ben Lamm explains how the company is revolutionizing biodiversity preservation, tackling plastic pollution, and creating living products with immense potential.

Get access to metatrends 10+ years before anyone else — https://qr.diamandis.com/metatrends.

Ben Lamm is Co-founder and CEO of Colossal Biosciences

Peter H. Diamandis, MD, is the Founder of XPRIZE, Singularity University, ZeroG, and A360.

Chapters:

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Compact CRISPR system unlocks targeted in-body gene editing, with up to 90% efficiency

A research team has discovered an enhanced CRISPR gene-editing system that could enable targeted delivery inside the human body—a key step toward broader clinical use. Researchers identified a naturally occurring enzyme, Al3Cas12f, that is small enough to fit into adeno-associated virus vectors, a leading targeted delivery method for gene therapies. They then engineered an enhanced version that dramatically improved gene-editing performance in human cells.

The advance addresses a major limitation in CRISPR technology. Commonly used gene-editing proteins are too large for targeted delivery systems, restricting clinical applications to cells modified outside the body, such as blood and bone marrow.

“Smart delivery of gene editing systems is a powerful notion with broad clinical implications, and this basic science finding takes us a significant step toward that future,” said Erica Brown, Ph.D., acting director of NIH’s National Institute of General Medical Sciences (NIGMS).

Non-Stationary Load Extrapolation over Long Horizons Based on a Frequency-Consistent Diffusion Model

【】 Full article: (Authored by Yu Bai and Fei Meng, from University of Shanghai for Science and Technology, China.)

Engineering load signals support durability analysis because they reflect real service conditions. Long-duration load histories are essential for fatigue-life prediction and reliability assessment. However, long-term field measurements are often costly and difficult to obtain. Therefore, extending short measurements into representative long histories is practically important. This study proposes a frequency-consistent diffusion_model (FCDM) for long-horizon extrapolation of non-stationary bearing load signals under turning conditions. load_extrapolation.

Abstract

This study proposes a frequency-consistent diffusion model (FCDM) for long-horizon extrapolation of non-stationary bearing load signals. Condition tokens and spectral-consistency constraints are introduced to preserve spectral and fatigue-related characteristics during tenfold extrapolation. The generated signals are evaluated using PSD, band-energy proportion, Range-Mean distribution, and unit pseudo-damage. Compared with DDPM, FCDM better preserves dominant frequencies, harmonic structure, and band-energy allocation. The dominant frequency error is 1.02%, and the mean harmonic error is 0.52%. FCDM also shows smaller band-energy allocation errors across all frequency bands. In addition, it reproduces the bimodal clustering pattern in the Range-Mean distribution more accurately. The unit pseudo-damage is 1.0978 for FCDM and 1.1280 for DDPM. These results indicate that FCDM improves spectral fidelity and fatigue-related consistency in long-sequence load extrapolation.

Diffusion Model, Load Extrapolation, Frequency-Consistency

Hackers meet their match: New DNA encryption protects engineered cells from within

Engineered cells are a high-value genetic asset that is key to many fields, including biotechnology, medicine, aging, and stem cell research, with the global market projected to reach $8.0 trillion USD by 2035. Yet the only ways to keep the cells safe are strong locks and watchful guards.

In Science Advances, a team of U.S. researchers present a new approach to genetically securing precious biological material. They created a genetic combination lock in which the locking or encryption process scrambled the DNA of a cell so that its important instructions were non-functional and couldn’t be easily read or used.

The unlocking, or decryption, process involves adding a series of chemicals in a precise order over time—like entering a password—to activate recombinases, which then unscramble the DNA to their original, functional form.

Scientists Discover Dual Treatment for Lung Cancer and Muscle Wasting

Researchers at Oregon State University have pioneered a transformative approach for simultaneously targeting lung cancer and the debilitating muscle-wasting syndrome known as cachexia—a condition that plagues many lung cancer patients. Their groundbreaking work employs lipid nanoparticles (LNPs) as a delivery vehicle for messenger RNA (mRNA) therapeutics, addressing critical challenges in precision drug delivery for aggressive tumors deep within the lung tissue.

Lipid nanoparticles, microscopic carriers composed of fatty compounds like lipids, have revolutionized drug delivery with their ability to ferry genetic material directly into cells. In this study, the OSU team engineered LNPs comprised of DC-cholesterol and a specialized ionizable lipid, 113-O12B, which exhibited a remarkable ability to bind a blood serum protein called vitronectin. This binding triggers the formation of a protein corona on the nanoparticles, a dynamic interface that actively guides the LNPs to lung tissue, and more importantly, lung tumor microenvironments.

Vitronectin’s recruitment is no coincidence. It interacts with integrin receptors—cellular docking proteins highly expressed on lung cancer cells. These integrins act as biological gateways, facilitating enhanced uptake of the therapeutic nanoparticles by tumor cells while sparing healthy tissue. This receptor-mediated targeting marks a significant advance over conventional LNPs, which commonly accumulate in the liver, limiting their therapeutic index against lung malignancies.

10 Enhanced Super-human Types in Frank Herbert’s Dune

Frank Herbert’s Dune saga which has six books in its expanse is no doubt one of the most popular and most influential books in Science fiction. Dune is really about how putting all your hope into a hero or a “chosen one” and then to a set of beliefs can go awry wrong in a big terrifying way. The story shows how easily large groups of people can be influenced by ideas, especially when religion and politics get mixed together, it shows the great game of power on a galactic scale. It showcases how humanity would evolve and transform in the future, some which are familiar while others totally alien in appearance. Then the overall idea of a long “Golden Path” that is meant to ensure the survival of humanity becomes the overarching theme of the saga and along the way, different human types emerge in the storyline, some enhanced by genetic engineering, others by cloning and selective breeding. So, here in this video we will take a look at 10 of these enhanced or superhuman types in the canon Dune works.

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Physics-Informed LSTM for Fatigue Life Prediction of Rubber Isolators under Thermo-Mechanical Coupling

【】 Full article: (Authored by Shen Liu and Fei Meng, from University of Shanghai for Science and Technology, China.)

Rubber supports are essential in automotive, heavy machinery, and aerospace engineering. They offer excellent hyper elasticity, viscoelastic dissipation, and noise reduction. However, their fatigue evolution under coupled thermo-mechanical loading is exceptionally complex. This study develops an LSTM-Physics-Informed Neural Network (PINN) framework that integrates prior physical knowledge transfer with Partial Differential Equation (PDE) constraints, to address the challenge of predicting the fatigue life of rubber_isolators under thermo-mechanical-damage coupling.

Abstract

Rubber supports are ubiquitous in modern vibration isolation systems. Their fatigue evolution under coupled thermo-mechanical loading is exceptionally complex. Traditional life prediction methods rely heavily on empirical formulas. These methods often lack accuracy and extrapolation capabilities under varying temperatures. To address this, we propose a novel LSTM-PINN architecture. This framework integrates physical constitutive relations and temperature effects into a neural network. We used transfer learning to extract baseline physical data across wide temperature ranges. Long Short-Term Memory (LSTM) layers capture sequential loading features. We embedded partial differential equations (PDEs) into the loss function. These PDEs are based on strain energy density (SED) and Arrhenius thermodynamics. This approach ensures strict adherence to physical laws. Results demonstrate that LSTM-PINN achieves high precision even with small datasets. It also exhibits superior out-of-distribution (OOD) generalization. This framework provides a new paradigm for evaluating the reliability of rubber components.

Rubber Isolator, Fatigue Life, PINN, LSTM, Thermo–Mechanical Coupling

We are already gene editing humans

You just haven’t noticed.

George Church, Harvard geneticist and Human Genome Project pioneer, explains why CRISPR wasn’t the real breakthrough, how multiplex gene editing unlocked organ transplants and de-extinction, and why aging will likely require rewriting many genes at once.

Hosted by Mgoes → https://twitter.com/m_goes_distance
Brought to you by SuperHuman Fund → https://superhuman.fund/

0:00 — Gene Editing Mammals → Humans
8:36 — Germline vs Somatic
14:56 — Modified Humans Are Already Here
18:50 — Enhancing Healthy Humans
25:00 — Aging Therapies vs Cognitive Enhancement
30:20 — Embryo Selection
38:10 — Is US Losing To UAE?
42:33 — Biotech Failures
49:31 — Next Dire Wolf Moment
54:21 — AI x Science
1:02:07 — Synthetizing Entire Genomes.

The Accelerate Bio Podcast explores the future of humanity in the age of Artificial Intelligence. Subscribe for deep-dive conversations with founders, scientists, and investors shaping AI, biotechnology, and human progress.

This episode discusses George Church, gene editing, CRISPR, human enhancement, longevity, aging, embryo selection, synthetic biology, multiplex editing, AI biotech.

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The scientist using AI to hunt for antibiotics just about everywhere

When he was just a teenager trying to decide what to do with his life, César de la Fuente compiled a list of the world’s biggest problems. He ranked them inversely by how much money governments were spending to solve them. Antimicrobial resistance topped the list.

Twenty years on, the problem has not gone away. If anything, it’s gotten worse. Infections caused by bacteria, fungi, and viruses that have evolved ways to evade treatments are now associated with more than 4 million deaths per year, and a recent analysis, published in the Lancet, predicts that number could surge past 8 million by 2050. In a July 2025 essay in Physical Review Letters, de la Fuente, now a bioengineer and computational biologist, and synthetic biologist James Collins warned of a looming “postantibiotic” era in which infections from drug-resistant strains of common bacteria like Escherichia coli or Staphylococcus aureus, which can often still be treated by our current arsenal of medications, become fatal. “The antibiotic discovery pipeline remains perilously thin,” they wrote, “impeded by high development costs, lengthy timelines, and low returns on investment.”

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