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XP140BR: 6-year-old girl with XP-J

This issue’s cover features companion papers that exemplify how understanding a rare disease can inform treatment strategies in other conditions.

Fassihi et al. and Nakazawa et al. report on the C-terminal deletion of transcription factor TFIIH-p52 subunit as a cause of xeroderma pigmentosum.

The cover art was created using PyMOL; TFIIH-p52 subunit (blue; C-terminus in white). Image credit: Keiko Itano.

https://www.jci.org/articles/view/195731 https://www.jci.org/articles/view/195732


1National Xeroderma Pigmentosum Service, Rare Disease Centre, Guy’s and St Thomas’ NHS Trust, London, United Kingdom.

2Department of Molecular Genetics, Nagoya University Graduate School of Medicine, Nagoya, Japan.

Physicists reveal a new quantum state where electrons run wild

Electrons can freeze into strange geometric crystals and then melt back into liquid-like motion under the right quantum conditions. Researchers identified how to tune these transitions and even discovered a bizarre “pinball” state where some electrons stay locked in place while others dart around freely. Their simulations help explain how these phases form and how they might be harnessed for advanced quantum technologies.

Biotech solves for best-in-class ADC formula with $120M fundraise

A San Diego biotech has set out to solve the formula for best-in-class antibody-drug conjugates, raising $120 million with support from Big Pharma Merck & Co. to fuel its efforts.

Solve Therapeutics’ new fundraise was led by oncology-focused VC Yosemite, with participation from new investors Abingworth and Merck, plus existing investors Alexandria Venture Investments and Citadel’s Surveyor Capital, among others.

The simulated Milky Way: 100 billion stars using 7 million CPU cores

Researchers have successfully performed the world’s first Milky Way simulation that accurately represents more than 100 billion individual stars over the course of 10 thousand years. This feat was accomplished by combining artificial intelligence (AI) with numerical simulations. Not only does the simulation represent 100 times more individual stars than previous state-of-the-art models, but it was produced more than 100 times faster.

Published in Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis, the study represents a breakthrough at the intersection of astrophysics, high-performance computing, and AI. Beyond astrophysics, this new methodology can be used to model other phenomena such as and .

Species in crisis: Critically endangered penguins are directly competing with fishing boats

A new study led by the University of St Andrews has found that critically endangered African penguins (Spheniscus demersus) are significantly more likely to forage in the same areas as commercial fishing vessels during years of low fish abundance, increasing competition for food and adding pressure to a species already in crisis.

Published in the Journal of Applied Ecology, the research introduces a novel metric called “overlap intensity” which for the first time measures not just the extent of shared space between and fishing vessels, but how many penguins are actually affected by this overlap.

The African penguin population has plummeted by nearly 80% in the past three decades, in part due to competition with the local fishery targeting sardines and anchovies, a key prey for the penguins.

MIT Neuroscientist Proposes Brain Waves are the Hidden Engine Behind Thought and Consciousness

When it comes to understanding the mystery of human consciousness, scientists have long sought the hidden mechanism that transforms mere neural firing into the rich experience of thought.

Now, a leading MIT neuroscientist believes he’s found a clue that suggests the brain’s electrical waves don’t just reflect our thoughts, but actually create them.

At the Society for Neuroscience’s annual meeting on November 15, Dr. Earl K. Miller, a professor at MIT’s Picower Institute for Learning and Memory, will unveil a provocative proposal: that cognition and consciousness emerge from the fast, flexible organization of the brain’s cortex—powered by analog computations performed by traveling brain waves.

In other words, the rhythm of the brain may be more than background noise—it may be the very pulse of thought itself.

“The brain uses these oscillatory waves to organize itself,” Dr. Miller said in a press statement. “Cognition is large-scale neural self-organization. The brain has got to organize itself to perform complex behaviors. Brain waves are the patterns of excitation and inhibition that organize the brain, and this leads to consciousness because consciousness is this organized knitting together of the cortex.”

Dr. Miller’s theory revives the concept of analog computation. Unlike digital computers, which rely on discrete binary bits, analog systems process continuous information—waves interacting to produce a vast range of possible values.

Dr. Miller argues that the brain’s natural oscillations—electrical waves generated by millions of neurons—function as analog computers, sculpting information in a fast, flexible, and energy-efficient way.

MAKER: Large Language Models (LLMs) have achieved remarkable breakthroughs in reasoning, insight generation, and tool use

They can plan multi-step actions, generate creative solutions, and assist in complex decision-making. Yet these strengths fade when tasks stretch over long, dependent sequences. Even small per-step error rates compound quickly, turning an impressive short-term performance into complete long-term failure.

That fragility poses a fundamental obstacle for real-world systems. Most large-scale human and organizational processes – from manufacturing and logistics to finance, healthcare, and governance – depend on millions of actions executed precisely and in order. A single mistake can cascade through an entire pipeline. For AI to become a reliable participant in such processes, it must do more than reason well. It must maintain flawless execution over time, sustaining accuracy across millions of interdependent steps.

Apple’s recent study, The Illusion of Thinking, captured this challenge vividly. Researchers tested advanced reasoning models such as Claude 3.7 Thinking and DeepSeek-R1 on structured puzzles like Towers of Hanoi, where each additional disk doubles the number of required moves. The results revealed a sharp reliability cliff: models performed perfectly on simple problems but failed completely once the task crossed about eight disks, even when token budgets were sufficient. In short, more “thinking” led to less consistent reasoning.

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