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Category: biological

Scientists crack ancient salt crystals to unlock secrets of 1.4 billion-year-old air

More than a billion years ago, in a shallow basin across what is now northern Ontario, a subtropical lake much like modern-day Death Valley evaporated under the sun’s gentle heat, leaving behind crystals of halite—rock salt.

It was a very different world than the one we know today. Bacteria were the dominant form of life. Red algae had only just appeared on the evolutionary scene. Complex multicellular life like animals and plants wouldn’t show up for another 800 million years.

As the water evaporated into brine, some of it became trapped in tiny pockets within the crystals, effectively frozen in time. Those trapped fluid inclusions contained air bubbles revealing, in fine detail, the composition of early Earth’s atmosphere. The crystals were buried in sediment, effectively sealed off from the rest of the world for 1.4 billion years, their secrets unknown.

A molecular switch for green hydrogen: Catalyst changes function based on how it’s assembled

Hydrogen production through water electrolysis is a cornerstone of the clean energy transition, but it relies on efficient and stable catalysts that work under acidic conditions—currently dominated by precious metals like iridium and platinum.

A research team from the Singular Center for Research in Biological Chemistry and Molecular Materials (CiQUS) in Spain, led by María Giménez-López, has made a fundamental advance toward Earth-abundant alternatives. Their work, published in the journal Advanced Materials, shows that a single molecular compound can act as a catalytic “switch,” toggling between oxygen and hydrogen production.

From Decoherence to Coherent Intelligence: A Framework for the Emergence of AI Structure through Recursive Reasoning

This paper develops a thermodynamic framework for understanding the coherence of both biological and artificial cognition. We formalize thermodynamic coherence as an expression of information processing constrained by entropy and temperature, establishing a quantitative link between physical energy states and cognitive stability. Building on foundational concepts from statistical mechanics, quantum biology, and information theory, we argue that intelligence emerges as an ordered process, one that locally resists entropy through orderly reasoning work that generates coherent structure. The resulting framework is applied to wave function collapse, consciousness models, and machine reasoning, showing that coherence serves as a universal condition for stable cognition across domains.

To flexibly organize thought, the brain makes use of space

In Current Biology, the Miller Lab at MIT provides new evidence that the brain recruits and controls ad hoc groups of neurons for cognitive tasks by applying brain waves to patches of the cortex.

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In a new study, MIT researchers tested their theory of Spatial Computing, which holds that the brain recruits and controls ad hoc groups of neurons for cognitive tasks by applying brain waves to patches of the cortex.

Reining In a Chaotic Fluid

Fluid flows mimicking biological flows can be controlled in the lab using a feedback system, which could be useful in robotics and other technologies.

Ordinary fluids can flow when driven by pressure or gravity, but biological fluids, such as those inside cells, generate complex flows through internal sources of chemical energy. Flows of such “active fluids” could be extremely useful in robotics and other areas of engineering, but controlling them remains difficult. Now researchers have demonstrated a method of control that maintains a constant fluid speed despite changing conditions [1]. They hope that the approach can be used to stabilize active-matter flows in future technologies.

Life depends on biochemical processes that respond to many situations while maintaining fixed chemical conditions despite external and internal disruptions. Inspired by this impressive stability, researchers have been developing analogous artificial systems by assembling active fluids from key biochemical components akin to those inside cells. For example, they have created fluids that can generate their own bulk contractions or undergo spontaneous flows. Although these rudimentary designs mimic some features of living matter, researchers have so far failed to demonstrate techniques that keep properties such as fluid flow speeds stable over time.

A third path to explain consciousness: Biological computationalism

Right now, the debate about consciousness often feels frozen between two entrenched positions. On one side sits computational functionalism, which treats cognition as something you can fully explain in terms of abstract information processing: get the right functional organization (regardless of the material it runs on) and you get consciousness.

On the other hand is biological naturalism, which insists that consciousness is inseparable from the distinctive properties of living brains and bodies: biology isn’t just a vehicle for cognition, it is part of what cognition is. Each camp captures something important, but the stalemate suggests that something is missing from the picture.

In our new paper, we argue for a third path: biological computationalism. The idea is deliberately provocative but, we think, clarifying. Our core claim is that the traditional computational paradigm is broken or at least badly mismatched to how real brains operate.

On biological and artificial consciousness: A case for biological computationalism

The rapid advances in the capabilities of Large Language Models (LLMs) have galvanised public and scientific debates over whether artificial systems might one day be conscious. Prevailing optimism is often grounded in computational functionalism: the assumption that consciousness is determined solely by the right pattern of information processing, independent of the physical substrate. Opposing this, biological naturalism insists that conscious experience is fundamentally dependent on the concrete physical processes of living systems. Despite the centrality of these positions to the artificial consciousness debate, there is currently no coherent framework that explains how biological computation differs from digital computation, and why this difference might matter for consciousness.

Living cells may generate electricity from motion

Cells may generate their own electrical signals through microscopic membrane motions. Researchers show that active molecular processes can create voltage spikes similar to those used by neurons. These signals could help drive ion transport and explain key biological functions. The work may also guide the design of intelligent, bio-inspired materials.

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