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Category: robotics/AI

MIT Mined Bacteria for the Next CRISPR—and Found Hundreds of Potential New Tools

Now, MIT scientists have released an AI called DefensePredictor that can root out new bacterial defense systems in five minutes, instead of weeks or months. As proof of concept, DefensePredictor churned through hundreds of thousands of proteins in multiple strains of Escherichia coli (E. coli). Over 600 proteins not previously linked to immune defense popped up. Added to a vulnerable strain of bacteria, a subset of these protected them against attack.

“E. coli harbors a much broader landscape of antiphage defense than previously realized, expanding the likely number of systems by multiple orders of magnitude,” wrote the team.

These systems might hold secrets about how immunity evolved. And because the proteins may work in different ways, they could be a goldmine for next-generation precision molecular tools.

A generative AI framework unifies human multi-omics to model aging, metabolic health, and intervention response

Circadian rhythms are predictable biological patterns that recur about every 24 h and, in mammals such as humans, are entrained to daylight by the hypothalamic suprachiasmatic nucleus (SCN). Although light is a potent zeitgeber for the SCN, cells outside of the SCN can synchronize to daily nutrient and metabolic cues. In these tissues, nutrient metabolic processes are regulated by the molecular clock in anticipation of food availability or scarcity. Furthermore, nutrients and metabolic processes themselves may act upon members of the molecular clock to regulate their expression and activity. These interactions maintain synchrony between the SCN and food-entrainable clocks when activity and nutrient intake align. However, the light-entrainable SCN and food-entrainable clocks can become desynchronized, particularly in modern society where humans are commonly exposed to shift work and jet lag. Therefore, the mechanisms for sensing nutrients at specific times of day are critical components of circadian timekeeping and organismal homeostasis. In the following narrative review, we aim to synthesize current evidence on time-of-day-dependent nutrient sensing in mammalian systems, examine how nutrient-derived signals and metabolic processes interact with molecular clock mechanisms across cellular and tissue levels, and evaluate the integration of central and peripheral clocks in regulating gene expression, energy utilization, and organismal homeostasis, including the impacts of feeding cycles and circadian disruption. While previous reviews have discussed circadian nutrient metabolism, this review provides conceptual support for the role of nutrients as time-of-day signaling mechanisms.

Malaria rebound spurs AI-driven hunt for parasite genes linked to deadly cases

Despite decades of efforts to combat it, malaria remains a major global health threat. According to the World Health Organization’s (WHO) 2025 World Malaria Report, about 282 million cases and approximately 610,000 deaths were recorded worldwide in 2024. Recently, there has been a slight rise in the number of cases again. Children under the age of 5 in sub-Saharan Africa are particularly affected.

While many millions of lives have been saved since 2000, progress is slowing down. Reasons for this include drug and insecticide resistance, the effects of climate change, and weak health systems. The WHO stresses that increased international efforts and innovative approaches are urgently needed to curb malaria in the long term.

“For over 100 years, the Bernhard Nocht Institute for Tropical Medicine has been dedicated to researching and combating malaria,” says Prof. Jürgen May, Chairman of the BNITM Board. “In view of stagnating progress and new challenges, it is clear how important new scientific approaches are. A key factor here is the use of modern data analysis.

Big Data Approach to Assessment of an Aldosterone-Renin Ratio for Detection of Potential Surgical Cases of Primary Aldosteronism

RESEARCH ARTICLE:

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A humanoid robot sprints past the human half-marathon world record in Beijing race

The winner from Honor, a Chinese smartphone maker, completed the 21-kilometer (13-mile) race in 50 minutes and 26 seconds, according to a WeChat post by the Beijing Economic-Technological Development Area, also known as Beijing E-Town, where the race kicked off.

That was faster than the human world record holder, Uganda’s Jacob Kiplimo, who finished the same distance in about 57 minutes in March at the Lisbon road race.

The performance by the robot marked a significant step forward from last year’s inaugural race, during which the winning robot finished in 2 hours, 40 minutes and 42 seconds.

How Automation and AI Are Transforming Organoid Research

The life sciences are in the midst of a crucial shift, driven by the emergence of organoid-based models and the power of automation. Organoids—three-dimensional cell cultures that mimic human tissue architecture and function—are enabling researchers to ask and answer questions that were once beyond reach. Paired with advances in automation, robotics, and artificial intelligence (AI), these models are transforming drug discovery and preclinical testing, offering a more human-relevant alternative to outdated 2D cell cultures and animal models. This revolution is reshaping the pharmaceutical industry, while also holding the potential to accelerate progress in personalized medicine.

Beyond 2D: The Rise of Organoids

For decades, preclinical research has relied on 2D cell cultures, single-cell-type 3D spheroid models, and animal models, despite their limitations in replicating human biology. Organoids, which are derived from stem cells, offer a more accurate representation of human tissues, recapitulating complex biological processes such as organ-specific functionality and cellular interactions. These miniature self-organizing biological systems are being used to model diseases, test drug efficacy and toxicity, and even explore regenerative medicine.

How tiny voids could make fusion targets more stable under powerful shockwaves

Picture two materials sandwiched together. The boundary between them may appear flat, but, in reality, it is full of tiny bumps and dents. Suddenly, the materials are hit with a shockwave. If that wave hits a bump in the material interface, it slows down. If it hits a dent, it accelerates forward. This imbalance creates fast, narrow jets of material—called the Richtmyer-Meshkov (RM) instability.

In a recent paper, published in Physical Review Letters, researchers from Lawrence Livermore National Laboratory (LLNL), Imperial College London and their collaborators used AI to optimize and 3D printing to create a target that effectively negates the RM instability.

“Our target reshapes the shockwave, in both space and time, as it travels through the material,” said first author Jergus Strucka, now at the European XFEL. “Instead of a single shock hitting the surface, we introduce voids to break it up into a sequence of smaller pressure pulses that arrive at slightly different times.”

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