Lifeboat Foundation: Safeguarding Humanity
Toggle light / dark theme

Blog

Category: biological – Page 11

Introducing Anthropic’s AI for Science Program

Today, we’re launching Anthropic’s AI for Science program – a new initiative designed to accelerate scientific research and discovery through access to our API. This program will provide free API credits to support researchers working on high-impact scientific projects, with a particular focus on biology and life sciences applications.

Why AI for Science? At Anthropic, we believe that AI has the potential to significantly accelerate scientific progress. Advanced AI reasoning and language capabilities can help researchers analyze complex scientific data, generate hypotheses, design experiments, and communicate findings more effectively. By reducing the time and resources needed for scientific discovery, we can help address some of humanity’s most pressing challenges.

Anthropic is an AI safety and research company that’s working to build reliable, interpretable, and steerable AI systems.

Natural enzyme capable of cleaving cellulose could transform biofuel production

The deconstruction of cellulose is essential for the conversion of biomass into fuels and chemicals. But cellulose, the most abundant renewable polymer on the planet, is extremely recalcitrant to biological depolymerization. Although composed entirely of glucose units, its crystalline microfibrillar structure and association with lignin and hemicelluloses in plant cell walls make it highly resistant to degradation.

As a result, its degradation in nature is slow and requires complex enzymatic systems. The deconstruction of cellulose, which could, among other things, significantly increase the production of ethanol from sugarcane, has been a major technological challenge for decades.

Researchers from the Brazilian Center for Research in Energy and Materials (CNPEM), in partnership with colleagues from other institutions in Brazil and abroad, have just obtained an enzyme that could revolutionize the process of deconstructing cellulose, allowing, among other technological applications, the large-scale production of so-called second-generation ethanol, derived from agro-industrial waste such as sugarcane bagasse and corn straw. The study was published in the journal Nature.

Active Fluids Solve Icy “Six-Vertex” Model

Researchers demonstrate an active-fluid system whose behaviors map directly to predictions of the six-vertex model—an exactly solvable model that was originally developed to explain the behavior of ice.

Active fluids—collections of self-propelled agents such as bacteria, cells, or colloids—consume energy to move, flowing without being pushed [1]. These materials break the conventional rules of fluid dynamics, as they can flow spontaneously, switch direction without apparent cause, and organize into complex patterns with no external control. Active fluids were initially studied to understand the collective dynamics observed in biological systems. Now they offer a rich playground for exploring nonequilibrium physics. Yet, in the ever-expanding universe of active-fluid physics, it is rare to find an experimental system that maps precisely onto a mathematically exact model.

Mapping memory: Protein tracking technique reveals synaptic changes during learning

A team of Harvard researchers have unveiled a way to map the molecular underpinnings of how learning and memories are formed, a new technique expected to offer insights that may pave the way for new treatments for neurological disorders such as dementia.

“This technique provides a lens into the synaptic architecture of memory, something previously unattainable in such detail,” said Adam Cohen, professor of chemistry and and of physics and senior co-author of the research paper, published in Nature Neuroscience.

Memory resides within a dense network of billions of neurons within the brain. We rely on synaptic plasticity—the strengthening and modulation of connections between these neurons—to facilitate learning and memory.

Digital technologies

Digital transformation is blurring the lines between the physical, digital and biological spheres. From cloud computing, to Artificial Intelligence (AI) and Big Data, technologies of the Fourth Industrial Revolution (4IR) are shaping every aspect of our lives.

In the oil and gas industry, digital transformation is revolutionizing how we supply energy to the world. By deploying a range of 4IR technologies across our business, we aim to meet the world’s energy needs while enhancing productivity, reducing CO2 emissions, and creating next-generation products and materials.

Novel AI model inspired by neural dynamics from the brain

MIT CSAIL researchers developed “linear oscillatory state-space models” to leverage harmonic oscillators. Capturing the stability and efficiency of biological neural systems and translating these principles into a machine learning framework, the LinOSS approach can help predict complex systems.

Programmable double-network gels: Interspecies interactions dictate structure, resilience and adaptability

A new study uncovers how fine-tuning the interactions between two distinct network-forming species within a soft gel enables programmable control over its structure and mechanical properties. The findings reveal a powerful framework for engineering next-generation soft materials with customizable behaviors, inspired by the complexity of biological tissues.

The study, titled “Inter-Species Interactions in Dual, Fibrous Gels Enable Control of Gel Structure and Rheology,” is published in Proceedings of the National Academy of Sciences.

The study uses simulations to investigate how varying the strength and geometry of interactions between two colloidal species impacts network formation and rheological performance. By controlling separately interspecies stickiness and tendency to bundle, researchers discovered that tuning these inter-species interactions allows over whether the networks that they form remain separate, overlap, or intertwine.

Manta ray group formations reveal how collective swimming affects propulsion efficiency

From bird flocking to fish schooling, many biological systems exhibit some type of collective motion, often to improve performance and conserve energy. Compared to other swimmers, manta rays are particularly efficient, and their large aspect ratio is useful for creating large lift compared to drag. These properties make their collective motion especially relevant to complex underwater operations.

To understand how their affect their propulsion, researchers from Northwestern Polytechnical University (NPU) and the Ningbo Institute of NPU, in China, modeled the motions of groups of , which they present in Physics of Fluids.

“As underwater operation tasks become more complex and often require multiple underwater vehicles to carry out group operations, it is necessary to take inspiration from the group swimming of organisms to guide formations of underwater vehicles,” said author Pengcheng Gao. “Both the shape of manta rays and their propulsive performance are of great value for biomimicry.”

Quantum effects in proteins: How tiny particles coordinate energy transfer inside cells

Protons are the basis of bioenergetics. The ability to move them through biological systems is essential for life. A new study in Proceedings of the National Academy of Sciences shows for the first time that proton transfer is directly influenced by the spin of electrons when measured in chiral biological environments such as proteins. In other words, proton movement in living systems is not purely chemical; it is also a quantum process involving electron spin and molecular chirality.

The quantum process directly affects the small movements of the biological environment that support . This discovery suggests that energy and information transfer in life is more controlled, selective, and potentially tunable than previously believed, bridging with biological chemistry and opening new doors for understanding life at its deepest level—and for designing technologies that can mimic or control biological processes.

The work, led by a team of researchers from the Hebrew University of Jerusalem collaborating with Prof. Ron Naaman from Weizmann Institute of Science and Prof. Nurit Ashkenasy from Ben Gurion University, reveals a surprising connection between the movement of electrons and protons in biological systems.