Plant DNA has become a frontier for artificial intelligence, with large language models turning genetic sequences into interpretable content for researchers. These tools treat bases like words, revealing hidden patterns that once eluded traditional methods.
A study published by Dr. Meiling Zou from Hainan University describes how language-based models interpret extensive plant genomes with remarkable precision.
Trees get most of the love, but diatoms, a group of photosynthetic microalgae, produce 20% of Earth’s oxygen and are the foundation of aquatic food webs. The prevalence and diversity of diatoms have made them highly successful, suggesting the evolutionary history of diatoms is worth understanding as an important piece of the larger puzzle of life on Earth.
A new study led by researchers from the U of A found that diatoms evolved slowly for the first 100 million years of their existence. Then, 170 million years ago, they reached an inflection point characterized by a burst of rapid speciation orders of magnitude faster than anything that had preceded it. This included changes to their shape, size and mode of reproduction, as well as repeated movements from oceans into freshwater systems, a typically difficult barrier for aquatic species to cross.
With an estimated 100,000 species, diatoms are now one of the most diverse groups of microalgae. They are small enough that dozens could fit on the head of a pin and are found almost anywhere there is water and sunlight.
The researchers are especially interested in how our bodies maintain balance. Metabolic homeostasis, the fancy term for it, may have shaped more traits than we realize.
And as diets continue to change today, our ancient genetic choices could still be nudging us in new directions.
The study is published in the journal Cell Genomics.
Researchers led by Hiroshi Ohno at the RIKEN Center for Integrative Medical Sciences (IMS) in Japan have discovered a new way to reduce obesity. Their study shows that supplying the gut with extra acetate reduces fat and liver mass in both normal and obese mice, as long as bacteria of the Bacteroides species are also present in the gut.
When both these conditions are met, gut bacteria can eliminate more sugars from the gut and promote the burning of fats for energy in the host. The findings were published in Cell Metabolism.
Affecting hundreds of millions of people around the world, obesity constitutes a global epidemic. It is linked to eating too much sugar and starchy foods and is known to increase the risk of heart disease, type-2 diabetes, and cancer. At the same time, studies show that eating fiber reduces the risk of these very same diseases—even though it cannot be digested directly by mammals.
Beta-glucan fibre molecules are found in oats Alamy/PA A new study suggests that eating a fibre supplement found naturally in oats, barley and rye before
People who follow a MIND diet, even if started later in life, were significantly less likely to develop Alzheimer’s disease or related forms of dementia, according to new research.
The MIND diet stands for “Mediterranean-DASH Intervention for Neurodegenerative Delay” and combines many elements of the Mediterranean diet and DASH (“Dietary Approaches to Stop Hypertension”). It emphasizes brain-healthy foods like leafy greens, berries, nuts and olive oil.
The study, being presented Monday at the American Society for Nutrition’s annual meeting, analyzed data from nearly 93,000 U.S. adults aged 45 to 75 starting in the 1990s.
Swiss scientists have created a new plastic-like material that’s flexible, biodegradable, and even edible. The secret? It’s still alive.
The material, which was created by a team from Empa in Switzerland, manages to balance biodegradability with toughness and versatility – a feat that is far from easy in materials science.
The researchers processed fibers from the mycelium (the root-like part) of the split-gill mushroom (Schizophyllum commune) into a liquid mixture, without actually killing them off or destroying their natural biological functions.
In a discovery three decades in the making, scientists at Rutgers and Brookhaven National Laboratory have acquired detailed knowledge about the internal structures and mode of regulation for a specialized protein and are proceeding to develop tools that can capitalize on its ability to help plants combat a wide range of diseases.
The work, which exploits a natural process where plant cells die on purpose to help the host plant stay healthy, is expected to have wide applications in the agricultural sector, offering new ways to protect major food crops from a variety of devastating diseases, the scientists said.
In a study published in Nature Communications, a team led by Eric Lam at Rutgers University-New Brunswick and Qun Liu at Brookhaven National Laboratory in New York reported that advanced crystallography and computer modeling techniques have enabled them to obtain the best picture yet of a pivotal plant protease, a protein enzyme that cuts other proteins, known as metacaspase 9.
Learning and motivation are driven by internal and external rewards. Many of our day-to-day behaviours are guided by predicting, or anticipating, whether a given action will result in a positive (that is, rewarding) outcome. The study of how organisms learn from experience to correctly anticipate rewards has been a productive research field for well over a century, since Ivan Pavlov’s seminal psychological work. In his most famous experiment, dogs were trained to expect food some time after a buzzer sounded. These dogs began salivating as soon as they heard the sound, before the food had arrived, indicating they’d learned to predict the reward. In the original experiment, Pavlov estimated the dogs’ anticipation by measuring the volume of saliva they produced. But in recent decades, scientists have begun to decipher the inner workings of how the brain learns these expectations. Meanwhile, in close contact with this study of reward learning in animals, computer scientists have developed algorithms for reinforcement learning in artificial systems. These algorithms enable AI systems to learn complex strategies without external instruction, guided instead by reward predictions.
The contribution of our new work, published in Nature (PDF), is finding that a recent development in computer science – which yields significant improvements in performance on reinforcement learning problems – may provide a deep, parsimonious explanation for several previously unexplained features of reward learning in the brain, and opens up new avenues of research into the brain’s dopamine system, with potential implications for learning and motivation disorders.
Reinforcement learning is one of the oldest and most powerful ideas linking neuroscience and AI. In the late 1980s, computer science researchers were trying to develop algorithms that could learn how to perform complex behaviours on their own, using only rewards and punishments as a teaching signal. These rewards would serve to reinforce whatever behaviours led to their acquisition. To solve a given problem, it’s necessary to understand how current actions result in future rewards. For example, a student might learn by reinforcement that studying for an exam leads to better scores on tests. In order to predict the total future reward that will result from an action, it’s often necessary to reason many steps into the future.
From river-clogging plants to disease-carrying insects, the direct economic cost of invasive species worldwide has averaged about $35 billion a year for decades, researchers said Monday.
Since 1960, damage from non-native plants and animals expanding into new territory has cost society more than $2.2 trillion, more than 16 times higher than previous estimates, they reported in the journal Nature Ecology & Evolution.
The accelerating spread of invasive species —from mosquitoes to wild boar to tough-to-eradicate plants—blights agriculture, spreads disease and drives the growing pace of species extinction.