The case for fixing everything

The handsome new book Maintenance: Of Everything, Part One, by the tech industry legend Stewart Brand, promises to be the first in a series offering “a comprehensive overview of the civilizational importance of maintenance.” One of Brand’s several biographers described him as a mainstay of both counterculture and cyberculture, and with Maintenance, Brand wants us to understand that the upkeep and repair of tools and systems has profound impact on daily life. As he puts it, “Taking responsibility for maintaining something—whether a motorcycle, a monument, or our planet—can be a radical act.”

Radical how? This volume doesn’t say. In an outline for the overall work, Brand says his goal is to “end with the nature of maintainers and the honor owed them.”

The idea that maintainers are owed anything, much less honor, might surprise some readers. Actually, maintenance and repair have been hot topics in academia since the mid-2010s. I played some role in that movement as a cofounder of the Maintainers, a global, interdisciplinary network dedicated to the study of maintenance, repair, care, and all the work that goes into keeping the world going.

Brand is right, too, that maintainers haven’t gotten the laurels they deserve. Over the past few decades, scholars have shown that work from oiling tools to replacing worn parts to updating code bases all tends to be lower in status than “innovation.” Maintenance gets neglected in many organizational and social settings. (Just look at some American infrastructure!) And as the right-to-­repair movement has shown, companies in pursuit of greater profits have frequently locked us out of being able to do repairs or greatly reduced the maintainable life of their products. It’s hard to think of any other reason to put a computer in the door of a refrigerator.

Some of Brand’s earlier work helped inspire those insights. But his new book makes me think he doesn’t see things that way. For Brand, maintenance seems to be a solitary act, profound but more about personal success and fulfillment than tending to a shared world or making it better.


Born in 1938, Brand is 87 years old. A sense hangs over the book—with its battles against corrosion, rust, and decay, with its attempts to keep things going even as they inevitably falter—of someone looking over life and pondering its end. Maintenance: Of Everything connects to every stage of Brand’s life. It’s worth reviewing where it falls in that arc. Brand has always been interested in tools and fixing things, but rarely has he focused on the systems that need the most care. 

More than a half-century ago, Brand was a member of the Merry Pranksters, a countercultural, LSD-centered hippie collective famously led by Ken Kesey, the author of One Flew Over the Cuckoo’s Nest. In 1966, Brand co-produced the Trips Festival, where bands like the Grateful Dead and Big Brother and the Holding Company performed for thousands amid psychedelic light shows.

Brand’s Whole Earth Catalog had a vision that might feel progressive, but its libertarian, rugged-individualist philosophy of remaking civilization alone stood in contrast to more collective social change movements.

In some ways, the Trips Festival set a paradigm for the rest of his life’s work. Brand’s biographers have described him as a network celebrity—someone who got ahead by bringing people together, building coalitions of influential figures who could boost his signal. As Kesey put it in 1980, “Stewart recognizes power. And cleaves to it.” 

Brand applied this network logic to the undertaking he will always be best remembered for: the Whole Earth Catalog. First published in 1968 and aimed at hippies and members of the nascent back-to-the-land movement, the publication had the motto “Access to tools.” Its pages were full of Quonset huts, geodesic domes, solar panels, well pumps, water filters, and other technologies for life off the grid. It was a vision that might feel progressive or left-leaning, but the libertarian, rugged-individualist philosophy of eschewing corrupt systems and remaking civilization alone stood in contrast to the more collective movements pushing for deep social change at the time—like civil rights, feminism, and environmentalism.

That vision also led straight to the empowerment that came with new digital tools, and to Silicon Valley. In 1985, Brand published the Whole Earth Software Catalog, the last of the series, and also cofounded the WELL—the Whole Earth ’Lectronic Link, a pioneering online community famous for, among other things, facilitating the trade of Grateful Dead bootlegs. He also wrote a hagiographic book about the MIT Media Lab, known for its corporate-sponsored research into new communications tech. “The Lab would cure the pathologies of technology not with economics or politics but with technology,” Brand wrote. Again, not collective action, not policymaking: tools. And Brand then cofounded the Global Business Network, a group of pricey consulting futurists that further connected him to MIT, Stanford, and the Valley. Brand had literally helped bring about the modern digital revolution.

His attention then turned toward its upkeep. Brand’s 1994 book, How Buildings Learn: What Happens After They’re Built, argued against high-modernist architectural ideas. Nearly all buildings eventually get remade, he argued, but he especially favored cheap, simple structures that inhabitants could easily retool to suit changing needs. In some ways, Brand was recapitulating the liberated—or libertarian—philosophy of the Whole Earth Catalog: People can remake their world, if they have access to tools. In a chapter titled “The Romance of Maintenance,” he asked readers to see the beauty, value, and occasional pleasures of fixer-uppers of all kinds.

This chapter was a touchstone for many of us in the academic subfield of maintenance studies. Researchers in disciplines like history, sociology, and anthropology, as well as artists and practitioners in fields like libraries, IT, and engineering, all started trying to understand the realities and, yes, romance of maintenance and repair. Brand joined and contributed to Listservs, attended conferences, chatted with intellectual leaders. So it’s a bit uncharitable when he writes that his new book is “the first to look at maintenance in general.” He knows better. The real question, though, is what his work has to teach us that others have not said before. In this first volume, the answer is unclear.


Maintenance: Of Everything, Part One is an odd book. If so much of Brand’s thinking has been about access to tools, he now asks, in a more extended way: How are our tools maintained? But where Brand began his career with a catalogue, in this volume we get … what? A digest? An almanac? An encyclopedia? Its form and riotous variety fit no genre easily. 

The book has two chapters. The first, “The Maintenance Race,” recounts the story of three men who took part in the Golden Globe, a round-the-world race for solo sailors held in 1968. Each of the sailors, Brand explains, had a different philosophy of maintenance. One neglected it and hoped for the best. He died. Another thought of and prepared for everything in advance, and while he didn’t win the race, he completed it and once held the record for the “world’s longest recorded nonstop solo sailing voyage.” The final sailor won and did so through heroic acts of perseverance; his style was “Whatever comes, deal with it,” Brand explains. Structured like a fairy tale and unremittingly romantic, the story—like most of the anecdotes in the book—focuses on the derring-do of vigorous white guys. The strategy is no secret. Brand’s outline explains: “Start with a dramatic contest of maintenance styles under life-critical conditions—a true story told as a fable.” This myth is meant to inspire. 

The second chapter, “Vehicles (and Weapons),” is over 150 pages long. It has five sections, multiple subsections, five subsections designated “digressions,” one called a “subdigression,” two “postscripts,” and several “footnotes” that are not footnotes in a formal sense but, rather, further addenda. At times, it all feels like notes for a future work. Brand makes no apology for the book’s woolliness. “All I can offer here,” he writes, “is to muse across a representative of maintenance domains and see what emerges.” Perhaps the most charitable reading of the potpourri is that it represents the return of a Merry Prankster, offering us a riotous varied light show. It’s a good book to leave on a table and occasionally open to a random page for entertainment. But it often seems as if it does not know what it wants to say or be. 

“Vehicles (and Weapons)” begins by paraphrasing two famous works of maintenance philosophy, Robert M. Pirsig’s Zen and the Art of Motorcycle Maintenance and Matthew B. Crawford’s Shop Class as Soulcraft. Maintenance involves both “problem finding” and “problem solving.” While much repair work is marked by anxiety, impatience, and boredom, it also offers positive values and outcomes. “Motorcycle maintainers take heart from what they repair for—the glory of the ride,” Brand writes. 

The beauty and triumph of cheapness is a running theme throughout the work, harking back to How Buildings Learn. Henry Ford’s Model T won out over early electric vehicles and hugely expensive luxury vehicles like Rolls-Royce’s Silver Ghost because it was cheap and easier to maintain. The three most popular cars in human history—the Ford Model T, the Volkswagen Bug, and the Lada “Classic” from Russia—all privileged cheapness, “retained their basic design for decades, and … invited repair by the owner.” Or, to be fair, maybe demanded it? For every hobbyist who delighted in being able to self-reliantly keep a VW running, there must have been thousands who appreciated how cheap it was and hated that it broke a lot. Brand never points to social research, like surveys, that might help us know people’s feelings on such matters.

Other sections recount how Americans created interchangeable parts (enabling not only cheap mass production but also easy maintenance), examine how maintenance works with assault rifles and in war, and track the history of technical manuals from the early modern period to the age of YouTube. These stories are solid, but they’re also well known to students of technology, and nearly all are recycled from the work of others, featuring many large block quotes. The volume breaks little new ground. 

Brand treats maintenance as an unalloyed good. But the field of maintenance studies has moved on, burrowing into the domain’s ironies, complexities, and difficulties. A simple example: In most cases, it is environmentally far better to retire and recycle an internal-combustion vehicle and buy an electric one than to keep the polluting beast going forever. Maintaining a gas-guzzler or a coal-­burning power plant isn’t a radical act but a regressive one. Also, maintenance can become a life-breaking burden on the poor, and it falls inequitably on the shoulders of women and people of color. Keeping existing systems going can be a way of avoiding tough, necessary change—like making technological systems more accessible for people with disabilities. In this volume, Brand is uninterested in such difficult trade-offs. He avoids any question of how politics shapes these issues, or how they shape politics.

This avoidance comes out most clearly in a section of “Vehicles (and Weapons)” that talks about Elon Musk—a character of “unique mastery,” Brand informs us. He tells us that Bill Gates once shorted Tesla’s stock, only to lose $1.5 billion. The lesson is clear: Elon won. 

In what political and social vision is money the best way to keep the score? Brand rightly points out that electric vehicles have fewer moving parts and, in that sense, are more maintainable than internal-combustion vehicles. He celebrates Musk most of all because his products “have all proven to be game changers in part because they combine ingenious design with surprisingly low cost.” Again, it’s Brand’s “cheap, available tools” hypothesis. But there’s a real superficiality and lack of follow-through in thinking here: Teslas remain luxury vehicles whose sales have slumped since federal tax subsidies disappeared. The company has faced several right-to-repair lawsuits; there’s even a law review article on the topic. Musk is in no sense a maintenance hero. Yet Brand writes that with his companies, “Musk may have done more practical world saving than any other business leader of his time.” By the time Brand was writing this book, the controversies surrounding Musk for at least flirting with antisemitism, racism, sexism, authoritarianism, and more were quite clear. About this, the book says not a word.

book cover
Maintenance: Of Everything, Part One
Stewart Brand
STRIPE PRESS, 2026

For sure, Brand needn’t agree with Musk’s critics, but failing to even broach the subject is tone deaf and out of touch. Others have argued that Silicon Valley’s “Move fast and break things” mentality undermines healthy maintenance. Brand doesn’t raise the idea—even to dismiss it. 

It could be that with Maintenance: Of Everything, Part One Brand is just getting going; that in subsequent volumes he’ll have something more coherent to say; that he’ll raise really hard questions and try to answer them. But given his track record, we might reasonably doubt it. Kesey said Brand cleaves to power; he certainly doesn’t question it. 

Lee Vinsel is an associate professor of science, technology, and society at Virginia Tech and host of Peoples & Things, a podcast about human life with technology.

Cerebral blood flow and functional connectivity immediate changes following intradermal acupuncture in major depressive disorder

BackgroundAcupuncture has been increasingly applied as an adjunctive treatment for major depressive disorder (MDD), yet its central neurobiological mechanisms remain insufficiently understood. Cerebral blood flow (CBF) and functional connectivity strength (FCS) provide complementary perspectives on regional metabolic activity and large-scale functional integration, and their coupling may reflect neurovascular coordination relevant to depression.MethodsTwenty patients with MDD and twenty matched healthy controls (HC) underwent resting-state MRI. Patients received intradermal acupuncture (IA) and were scanned before and immediately after stimulation, while healthy controls were scanned once. Voxel-wise analyses of CBF, FCS, and their ratio (CBF/FCS) were performed to characterize acupuncture-related changes in neurovascular coupling. Group comparisons and pre–post acupuncture effects were assessed at the whole gray matter level.ResultsAcupuncture induced significant alterations in CBF/FCS coupling across widespread brain regions, including the bilateral precuneus, postcentral gyrus, superior temporal pole, superior frontal gyrus, occipital cortex, and cerebellum. These regions are primarily involved in sensorimotor processing, cognitive control, and emotional regulation. Overall, IA was associated with an immediate increase in CBF/FCS coupling, suggesting enhanced coordination between cerebral perfusion and functional network integration.ConclusionThis study provides evidence that intradermal acupuncture modulates neurovascular coupling in patients with MDD, offering neuroimaging-based insights into its antidepressant mechanisms. The findings support the notion that acupuncture may facilitate more efficient brain function by optimizing the balance between neural activity and metabolic supply.

Brain Gene Variations Help Explain Neurological and Psychiatric Sex Differences

Thousands of genes are expressed differently in the brains of men and women, researchers have discovered.

The findings could help explain differences in neurodevelopmental, psychiatric, and neurodegenerative disorders between the sexes.

While men are more likely to experience schizophrenia, attention deficit hyperactivity disorder, and Parkinson’s disease, women are more prone to mood disorders and Alzheimer’s disease.

The U.S. study, in Science, is the first systemic single-cell survey of sex differences in gene expression across multiple regions of the human brain.

“Together, these findings provide a comprehensive map of molecular sex differences in the human brain and offer initial insight into their underlying mechanisms and potential functional consequences,” Alex DeCasien, PhD, from the National Institute of Mental Health in Bethesda, Maryland, told Inside Precision Medicine.

DeCasien and co-workers conducted a high-resolution analysis of gene expression in tissue samples from the brains of 15 men and 15 women using single-nucleus RNA sequencing.

They then used data from earlier large neuroimaging studies to select six cortical regions to sample, four of which showed sex-related differences in grey matter volume and two in which no such differences were found.

The team found subtle but widespread differences in gene activity between men and women. Biological sex explained very little of the variance in gene expression across the brain, at less than 1%, but differences were widespread—with more than 3000 genes showing different expression according to sex in at least one cortical region.

The greatest sex-related differences in gene expression were on the sex chromosomes. However, most of the genes showing sex-related variations in expression were autosomal—carried on one of the 22 numbered non-sex chromosomes.

The predominant driver for sex-biased expression of genes on these autosomal chromosomes were sex steroid hormones such as estrogen and testosterone.

Surprisingly, more than half the X chromosome genes in women were expressed in both alleles for at least one cell type. This indicated that many had escaped X chromosome inactivation—a female phenomenon in which one of the two X chromosomes is switched off early in development to stop women producing double the number of X-linked gene products to men.

“That finding has implications for understanding sex-biased disease susceptibility because several genes implicated in neurodevelopmental disorders reside on the X chromosome,” commented Jessica Tollkuhn, PhD, from Cold Spring Harbor Laboratory, and S Marc Breedlove, from Michigan State University, in an accompanying Perspective article.

They noted that autosomal genes showing sex-biased expression were substantially enriched for extracellular matrix components, hormone signaling pathways, and metabolic processes. “Genes with greater expression in women were enriched for mitochondrial and synaptic functions, whereas male-biased genes were associated with metabolic and structural pathways,” the editorialists added.

“By pinpointing these sexually differentiated processes, the data provide a treasure trove for the discovery of biomarkers of and/or therapeutic targets for differential disease risk in men and women.”

DeCasien and team added: “These findings raise the possibility that sex differences in gene expression modulate the magnitude of genetic effects at risk loci, contributing to differences in disease vulnerability and to reduced portability of polygenic risk prediction across sexes.”

The post Brain Gene Variations Help Explain Neurological and Psychiatric Sex Differences appeared first on Inside Precision Medicine.

AACR 2026 Chairs Identify Themes and Highlights from the Conference

The American Association for Cancer Research (AACR) Annual Meeting kicks off this weekend in San Diego. A whirlwind of sessions, keynotes, fireside chats, posters, and exhibitors, the meeting is THE annual event for the cancer community.

Before the conference, GEN spoke with AACR program chairs Paul S. Mischel, MD, Professor and Vice Chair for Research for the Department of Pathology at Stanford Medicine of Stanford University and Alice T. Shaw, MD, PhD, Chair of the Department of Medical Oncology and the Chief of Strategic Partnerships at Dana-Farber. In this interview, they share their perspectives on the event, what attendees should be looking out for, and what they, personally, are most looking forward to.

This interview has been edited for length and clarity.

 

GEN: What did you feel were some of the most important themes to include in the conference program?

Shaw: First of all, it’s been such an honor for me to work with Paul as well as our president, Lillian Siu, MD. We had an expert program committee and incredible staff at AACR who all helped shape the program.

This year’s annual meeting feels more meaningful than ever, because of everything going on in the world, including funding challenges, challenging geopolitics, and everything else. It has felt even more important that we have this time to bring together our global community of cancer researchers and investigators.

When Paul and I met last summer, we felt strongly that this meeting was not just about designing an incredibly strong scientific program to showcase the science and all of the innovation, but we wanted to make a point to demonstrate to the audience, and the world, the tangible benefits of scientific research to patients with cancer, and to highlight how all the research we do is done with an eye toward improving the lives of patients with cancer.

We intentionally planned a scientific program with patients and patient impact front and center and have tried to incorporate the patient perspective and even patient voices in some sessions—to emphasize that science drives impact for patients.

Mischel: When we started about a year ago, our conviction—that there probably has never been a more important year for an AACR meeting—grew over the year. This organization is a beacon of light at a time in which there’s been extraordinary progress in cancer, and [there is] the potential to really make a difference in patients’ lives at the face of some very major headwinds. What we’re seeing is a level of enthusiasm and engagement in coming together in the community that’s saying: we won’t be stopped in making a difference for patients with cancer. And there were a number of themes that were central to this meeting.

For example, precision—that you can use information about patients to identify what’s gone wrong and how to develop therapies based upon deep molecular knowledge. Partnership—The growing recognition of how we work together to make a difference for patients. It’s not a winner-take-all strategy. It’s not a race to the top for individuals. It’s a race to the top for people with cancer. And we do it effectively by joining hands to make a difference for patients. And global work—another major theme that we’re really talking about this year, because together we can make a real difference for people with cancer.

We work together with people that span an enormous range of disciplines and expertise. A number of themes came front and center during the year. The technologies to interrogate what’s happening in human beings, whether it’s in their tissue, their blood, or their images—it’s nothing short of breathtaking. The ability to either forestall cancer by detecting if it’s going to happen, or catch it early, or monitor our most effective treatments is really changing the game. New modalities for developing treatments. We’ve heard a lot about harnessing the immune system and about the development of small molecules. There’s all kinds of new chemistry, molecular glues and degraders that are leading the way. And they’re tied to deep investigations into the fundamental biology.

AI is changing the game as well. We are very excited that we’ve brought together perhaps the most interesting AI sessions that you can imagine, that talk about all of the ways that AI can be used—not like an oracle but actually in partnership with helping make a difference for patients, whether it be in the diagnostics or the development of therapeutics. AI is only beginning to be tapped to help us think about how to integrate knowledge across all of these domains. And it goes beyond that because it’s not only about the molecular composition of a person’s tumor, it’s about a human being, what they eat, where they live, what they do, and various other social determinants of health that might increase risks of cancer. A lot of attention is paid in the meeting to that aspect of it as well. So, I think we’re in for an incredibly interesting meeting.

Shaw: One of the themes that came right out from everyone on the program committee was how important it was to highlight AI; I think everyone believes that AI is going to be transformative and it’s going to impact all aspects of cancer research and clinical care in the coming years. We had a number of AI experts on our program committee. They really helped embed AI topics throughout the scientific and also the educational program.

In fact, when Paul and I were planning the opening plenary session, we really wanted one of the opening plenary speakers to be able to speak on AI. So, we have Regina Barzilay, PhD, from MIT, who’s going to speak on her work in the AI space, both in terms of drug discovery and all the way out to clinical applications. We also have an AI-focused plenary session all unto itself as well, to drive home the importance of AI tools and technologies. It is incredible how AI is already being used in terms of foundational discovery and in terms of real-world, clinical data mining and implementation. And Paul already mentioned genomics, precision medicine, biomarker discovery, histopathology, radiology, all of which are already being impacted by AI.

Mischel: One of the things that is perhaps most stunning is this idea that you might be able to prevent cancer. We already see real world examples of that with things like HPV vaccines. The work is advancing so quickly that it might be possible to build vaccines against [something] that might prevent people who are at high risk of developing cancer from getting those cancers. Our colleague and AACR President Lillian Siu, MD, has a presidential symposium focused on that. What I hope that we’re getting across is the real scale and power of the work that’s being presented and the way that it crosses so many disciplines at this meeting.

Shaw: We are going to have a large focus, as we usually do, on molecularly targeted therapies. We have several sessions on the basic research side, but also in the clinical trial sessions around targeting RAS. RAS, of course, is the most commonly mutated oncogene in human cancer and has been undruggable for decades.

In the last five to 10 years, we now finally have small molecule therapies that can target different RAS mutations. In fact, you may have just heard the news about a new RAS inhibitor, daraxonrasib from Revolution Medicines, and pivotal Phase III trial data in previously treated pancreatic cancer. This was an incredibly positive study, doubling overall survival. Not even knowing those results, though, we already had planned quite a lot around RAS.

In that context of precision therapies, I also want to mention that I’m excited about one of our discovery science plenaries on Saturday that is going to focus on minimal residual disease (MRD) in solid tumors. Here the question is, if we have such incredibly effective targeted therapies for oncogene-driven cancers like RAS, EGFR, and ALK, why aren’t we curing more patients who have these types of cancers? We believe that a lot of the reason is because we can’t eliminate every cancer cell. And if we could just understand what allows those residual cells to survive, perhaps we could eradicate those and then be on the road to curing patients who have advanced disease. So, this whole plenary will focus on the science around MRD and how that then leads to clinical applications as well.

Mischel: Fundamental science is deeply central to this process. We frame a lot of things in terms of what it means for patients’ lives. I think an important part of this meeting is also integrating how those discoveries really flow from the work in fundamental science. For example, in the opening plenary, we’re going to be hearing about how tumors change their stripes effectively to become resistant to treatments, the lineage plasticity, this idea that they adopt new states to become resistant. And then what can you do about it?

When people used to be diagnosed with terminal cancer, it meant that they were going to die soon, and now people can be diagnosed with terminal cancer and live for years. That’s stunning. And that is happening because of cancer research and the integration of cancer research all the way from the most mechanistic to the most applied. One of the deepest themes of this meeting comes into this concept of partnership, that we highlight the critical nature of each component and the integration of those components, all the way from fundamental discovery to translation to patients.

 

GEN: What are some of the biggest scientific challenges you’re seeing right now in cancer biology that you think people will be discussing at the meeting?

Mischel: Cancer is hard because it is evolution on steroids. The mechanism that I study—extrachromosomal DNA, the ability of cancer cells and tumors to change quickly to resist treatment—is all about that. And it comes from us; it’s our cells that have gone bad. We have to find ways to show how they’re different and target those differences. We’re getting better at it through our understanding of science.

Shaw:  I am someone who sits between basic research and the clinic, so I do a lot of translational research. What the AACR meeting does well is gets at this key challenge around how we translate basic discoveries into the clinic. We all just want better cancer therapies for our patients. There are many aspects that really make the translation of discoveries difficult, and these will come out in various forms at the meeting. We’ve been talking about how hard it is to understand the biology, and to identify and validate new targets for drug discovery, for cancer treatments in the future.

I have spent some time on the industry side, so I also recognize how challenging it is, even when you have what you think is a perfect target, to drug that target. At the annual meeting, we’re going to talk a lot about different modalities, ways of thinking about going after what we believe are important targets, be it a small molecule or maybe it’s a new degrader or maybe it’s some other very complicated biologic.

I want to emphasize that to use or to identify the optimal modality requires that we understand the biology and the science behind it. The other challenge that I’ve seen in the translational space is around identifying which patients are going to benefit from a new therapy. A good example of where we’ve seen struggles is immunotherapy and identifying novel immunotherapy combinations and which ones have robust activity. But we can’t tell exactly which patients are deriving that benefit. Oftentimes with no biomarker to guide us, we can’t move forward with what could be a promising combination. At the annual meeting, we try to highlight a lot of these correlative or translational biomarker studies from early phase clinical trials.

The last thing I’ll mention is around how we use preclinical models most effectively to predict what’s going to be a promising new therapy. Often, these models are just models; they’re simpler than human cancers. They can’t recapitulate the complexity of human biology, and they can lead us the wrong way. For example, to overestimate how effective a therapy may be. Fine-tuning our models and making them as predictive as possible is a key challenge.

Mischel: Data seems to suggest that very often you might need to combine agents to make differences for patients. And that of course makes enormous sense from a biological standpoint, but it’s much harder to do when you start thinking about how you design the trials to do that. It’s a slow process. And so, there is increasing recognition of the need to figure out how to combine agents and hopefully ways to figure out how practically to begin to test them more effectively and in a more cost-effective fashion.

 

GEN: What have been some of the biggest advances since the last meeting?

Mischel: I just keep coming back to RAS because it’s such a big deal. An undruggable target that we’re now seeing a huge change in. It’s a huge deal.

Shaw: I would agree with that. And it’s not simply the RAS inhibitor itself. Many of us believe that that is just the start of how we most effectively treat RAS-driven cancers. We need the best RAS inhibitor to serve as an anchor and then we will build these combinations around that which will hopefully be even more effective and allow us to maximally cytoreduce or debulk cancers and then allow us to take in other even higher order combinations.

We have sessions this year all around RAS-mutant cancers. We have a designated session just focused on pancreatic cancer biology, because understanding that biology well is going to be critical to developing these types of combination approaches.

The other thing that’s exciting—and this space is always evolving—is a plenary session on innovative new therapeutic modalities. This session will focus on a couple key modalities that are already transforming the space. Antibody-drug conjugates (ADC), for example. They are basically entering every therapeutic space that we have in cancer [and] understanding of the biology around how you’re targeting certain tumor-selective antigens.

Also, the design of the ADC itself can be very, very sophisticated and can be tweaked to further enhance activity. We’ll have some great talks around the next generation of ADCs that are going to be even more effective and even safer than what we currently have.

And in that same session around innovative modalities, we’ll also have talks around immune cell engagers; also, new data and next generation immune cell engagers that have built upon the early data with the first-generation immune cell engagers. The other very innovative new therapy that we will highlight, even in more detail than last year, is around radioligand therapies—a way to selectively target tumor cells with radiation. Unlike ADCs where the payload is chemotherapy, here the payload is radiation therapy. We’ve already seen really that these radioligand therapies are incredibly important for patients; they are coming out in all different therapeutic spaces. We thought it was important to highlight the latest advances in radioligand therapies, and we also have some education sessions so that physicians and scientists understand the basics around this innovative and exciting modality.

Mischel: The concepts of glues and degraders open the therapeutic landscape in a very different way. In many ways, the landscape has been limited to enzymes that you can inhibit, and not all good cancer targets are going to be enzymes that you can inhibit, and these glues and degraders change what you can do, whether it’s getting rid of them, moving them, giving them new functions. It’s a very powerful technology that is getting ready to make an enormous difference in clinic.

Shaw:  In the opening plenary session, George Winter will speak on glues and degraders. I also wanted to highlight the “New Drugs on the Horizon” sessions. We do this every year at the annual meeting. I love these sessions because they are first time disclosures of novel cancer therapies that have just entered the clinic or they’re about to enter the clinic. These talks go deep into the biology of the disease and how the drug was discovered and developed into early clinical plans. Several talks in this session this year are going to feature molecular glue degraders. That will be a nice way to tie together this theme around the degraders and the power of this new modality.

Mischel: One other thing I want to squeeze in is why on Earth are younger people getting cancer, particularly colorectal cancer? That’s really disturbing. We have sessions that are data rich that go right at that, and the answers are interesting.

 

GEN: Will there be any programming at the meeting that addresses the current state of funding?

Shaw:  We’re fortunate that Tony Letai, MD, PhD, the NCI director, is attending and speaking at the meeting in our opening ceremony on Sunday. He’s also participating in a workshop that we’re holding on grant writing and the scientific review process. On Monday, he will give an NCI director’s address and participate in a fireside chat where I’m sure he’s going to get a lot of questions around funding.

There are also sessions within the science and health policy track at the meeting that are going to focus on federal funding of grants. There is even a researcher town hall that’s really going to talk a lot about this.

 

GEN: Do you have any advice for young cancer researchers that may be attending AACR for the first time?

Mischel: I have two bits of advice. One of them is to know that what you’re doing is incredibly important. You are welcome. You’re one of us, you’re important. Do what you need and go forward because the work that you’re doing is going to matter an enormous amount. The second thing is do not be afraid. Do not think that the senior people at the meeting, the “bigwigs,” are too busy for you. Do not think they do not want to meet you, because they do. You’re the future. Go up, introduce yourself, say hello, tell us who you are.

 

GEN: What are things you are looking forward to outside of the sessions? 

Shaw:  I love the AACR annual meeting because it’s such an opportunity not just to learn, but to network and reconnect with friends and collaborators who you may not have seen in a while. I also think it’s a great venue for many of us to have formal sit-down meetings with industry partners and talk through the latest data that were just presented and discuss new collaborations. I personally am looking forward to the 5K race that Paul and I are speaking at. I’m going to try to run the race! One of my sons runs marathons and I thought, well, the least I can do is try and run a 5K.

Mischel: I’m looking forward to having a drink with Alice after the meeting ends and debriefing on putting this meeting together, which has been an absolute pleasure. I wish I were running the 5K race. I’m doing an education session at that time. I’m looking forward to meeting the students. There are these brilliant young people from all around the world and they’re just at the start of their career and they draw inspiration from this meeting, and I really enjoy it when they come up to me and I get to meet them. You see the brilliance and excitement in these people’s faces. And I’m looking forward to that.

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Landmark Pancreatic Cancer Trial Highlights Promise of RAS-Targeting Daraxonrasib

Earlier this week, Revolution Medicines reported positive results from a global Phase III trial of its RAS‑targeting inhibitor daraxonrasib (RMC-6236) in metastatic pancreatic ductal adenocarcinoma (PDAC). In the RASolute 302 trial, patients receiving daraxonrasib achieved longer progression‑free survival (PFS) and overall survival (OS) than those on standard cytotoxic chemotherapy.

The RASolute 302 trial enrolled patients with pancreatic tumors harboring a wide range of RAS variants, including those with RAS G12 mutations (such as G12D, G12V, and G12R), as well as those without an identified RAS mutation. The primary endpoints of the trial were PFS and OS in patients with tumors harboring RAS G12 mutations. Secondary endpoints assessed PFS and OS in all enrolled patients (the intent-to-treat population), including those with tumors with and without (wild type) an identified RAS mutation.

Daraxonrasib patients achieved a median OS of 13.2 months versus 6.7 months for chemotherapy. The drug was generally well tolerated, with a manageable safety profile and with no new safety signals.

“With these unprecedented results, daraxonrasib has the potential to achieve our goal of bending the mortality curve in pancreatic cancer. Unlike chemotherapy, daraxonrasib is a RAS-targeted medicine that targets RAS in its active ‘ON’ state, shutting down a key signaling pathway that drives aggressive tumor growth. This is especially important in pancreatic cancer, which is among the most RAS-driven cancers, with more than 90% of tumors harboring a RAS mutation that is the driver of the cancer,” asserted Mark A. Goldsmith, MD, PhD, CEO and chairman of Revolution Medicines.

Pancreatic cancer carries one of the highest mortality rates of any solid tumor, a consequence of late-stage diagnosis and resistance to standard chemotherapy. In the United States, recent estimates point to roughly 60,000 new cases and nearly 50,000 deaths each year. With most PDAC tumors driven by RAS alterations, the early success of emerging RAS‑targeted strategies hints at how much more may be possible as this therapeutic space continues to expand.

RAS is the key oncogenic driver of pancreatic cancer. Nearly all RAS mutations occur at KRAS position G12, but RAS mutations in other isoforms and at KRAS positions G13 and Q61 are also observed. Daraxonrasib works by suppressing RAS signaling through inhibition of the interaction between both wild-type and mutant RAS(ON) proteins and their downstream effectors.

Pancreatic cancer is the most RAS-addicted of all major cancers, with more than 90% of patients harboring tumors driven by mutations in RAS proteins. These mutations span a range of RAS variants that fuel aggressive tumor behavior. Daraxonrasib, a multi-selective inhibitor of RAS(ON) proteins, is the first investigational agent in a novel class of RAS inhibitors designed to address a diverse and broad spectrum of oncogenic RAS drivers.

“For patients with metastatic pancreatic cancer, new treatment options are urgently needed to increase survival time and improve quality of life,” said Brian M. Wolpin, MD, MPH, professor of medicine at Harvard Medical School, director of the Hale Family Center for Pancreatic Cancer Research at Dana-Farber Cancer Institute, and principal investigator for the RASolute 302 trial. “The widely anticipated results of this study indicate that daraxonrasib provides a clear and highly meaningful step forward for patients with pancreatic cancer who have experienced progression on prior treatment, typically chemotherapy. I believe that this new approach is a very important advance for the field that I expect will be practice-changing for physicians and improve the care for patients with previously treated metastatic pancreatic cancer.”

Revolution Medicines now intends to submit the drug for approval by regulatory authorities, including the U.S. Food and Drug Administration as part of a future New Drug Application, and for presentation at the 2026 American Society of Clinical Oncology Annual Meeting. 

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Treating enterprise AI as an operating layer

There’s a fault line running through enterprise AI, and it’s not the one getting the most attention. The public conversation still tracks foundation models and benchmarks—GPT versus Gemini, reasoning scores, and marginal capability gains. But in practice, the more durable advantage is structural: who owns the operating layer where intelligence is applied, governed, and improved. One model treats AI as an on-demand utility; the other embeds it as an operating layer—the combination of operation software, data capture, feedback loops and governance that sits between models and real work—that compounds with use.

Model providers like OpenAI and Anthropic sell intelligence as a service: you have a problem, you call an API, you get an answer. That intelligence is general-purpose, largely stateless, and only loosely connected to the day-to-day operations where decisions are made. It’s highly capable and increasingly interchangeable. The distinction that matters is whether intelligence resets on every prompt or accumulates over time.

Incumbent organizations, by contrast, can treat AI as an operating layer: instrumentation across operations, feedback loops from human decisions, and governance that turns individual tasks into reusable policy. In that setup, every exception, correction, and approval becomes a chance to learn—and intelligence can improve as the platform absorbs more of the organization’s work. The organizations most likely to shape the enterprise AI era are those that can embed intelligence directly into operational platforms and instrument those platforms so work generates usable signals.

The prevailing narrative says nimble startups will out-innovate incumbents by building AI-native from scratch. If AI is primarily a model problem, that story holds. But in many enterprise domains, AI is a systems problem—integrations, permissions, evaluation, and change management—where advantage accrues to whomever already sits inside high-volume, high-stakes operations and converts that position into learning and automation.

The inversion: AI executes, humans adjudicate

Traditional services organizations are built on a simple architecture: humans use software to do expert work. Operators log into systems, navigate operations, make decisions, and process cases. Technology is the medium. Human judgment is the product.

An AI-native platform inverts this. It ingests a problem, applies accumulated domain knowledge, executes autonomously what it can with high confidence, and routes targeted sub-tasks to human experts when the situation demands judgment that the system can’t yet reliably provide.

But inverting human-AI interaction isn’t just a UI redesign—it requires raw material. It’s only possible when the platform is built on a foundation of domain expertise, behavioral data, and operational knowledge accumulated over years.

The three compounding assets incumbents already own

AI-native startups begin with a clean architectural slate and can move quickly. What they can’t easily manufacture is the raw material that makes domain AI defensible at scale:

  • Proprietary operational data
  • A large workforce of domain experts whose day-to-day decisions generate training signals
  • Accumulated tacit knowledge about how complex work actually gets done

Services companies already have all three. But these ingredients aren’t moats on their own. They become an advantage only when a company can systematically convert messy operations into AI-ready signals and institutional knowledge—then feed the results back into operations so the system keeps improving.

Codifying expertise into reusable signals

In most services organizations, expertise is tacit and perishable. The best operators know things they cannot easily articulate: heuristics developed over the years, edge-case intuitions, and pattern recognition that operate below the level of conscious reasoning.

At Ensemble, the strategy for addressing this challenge is knowledge distillation. The systematic conversion of expert judgment and operational decisions into machine-readable training signals.

In health-care revenue cycle management, for example, systems can be seeded with explicit domain knowledge and then deepen their coverage through structured daily interaction with operators. In Ensemble’s implementation, the system identifies gaps, formulates targeted questions, and cross-checks answers across multiple experts to capture both consensus and edge-case nuance. It then synthesizes these inputs into a living knowledge base that reflects the situational reasoning behind expert-level performance.

Turning decisions into a learning flywheel

Once a system is constrained enough to be trusted, the next question is how it gets better without waiting for annual model upgrades. Every time a skilled operator makes a decision, they generate more than a completed task. They generate a potential labeled example—context paired with an expert action (and sometimes an outcome). At scale, across thousands of operators and millions of decisions, that stream can power supervised learning, evaluation, and targeted forms of reinforcement—teaching systems to behave more like experts in real conditions.

For example, if an organization processes 50,000 cases a week and captures just three high-quality decision points per case, that’s 150,000 labeled examples every week without creating a separate data-collection program.

A more advanced human-in-the-loop design places experts inside the decision process, so systems learn not just what the right answer was, but how ambiguity gets resolved. Practically, humans intervene at branch points—selecting from AI-generated options, correcting assumptions, and redirecting operations. Each intervention becomes a high-value training signal. When the platform detects an edge case or a deviation from the expected process, it can prompt for a brief, structured rationale, capturing decision factors without requiring lengthy free-form reasoning logs.

Building toward expertise amplification

The goal is to permanently embed the accumulated expertise of thousands of domain experts—their knowledge, decisions, and reasoning—into an AI platform that amplifies what every operator can accomplish. Done well, this produces a quality of execution that neither humans nor AI achieve independently: higher consistency, improved throughput, and measurable operational gains. Operators can focus on more consequential work, supported by an AI that has already completed the analytical groundwork across thousands of analogous prior cases.

The broader implication for enterprise leaders is straightforward. Advantages in AI won’t be determined by access to general-purpose models alone. It will come from an organization’s ability to capture, refine, and compound what it knows, its data, decisions, and operational judgment, while building the controls required for high-stakes environments. As AI shifts from experimentation to infrastructure, the most durable edge may belong to the companies that understand the work well enough to instrument it and can turn that understanding into systems that improve with use.

This content was produced by Ensemble. It was not written by MIT Technology Review’s editorial staff.

Spatial evolution in temporal dynamics of hemodynamic response function in human superior colliculi with ultra-high-resolution MRI at 9.4T

The superior colliculus (SC) plays a crucial role in multisensory integration, visual information processing, saccadic target selection, visual selective attention, and decision making. In particular, the SC has a key role in oculomotor coordination, following a rostro-caudal organization. The rostral SC, which corresponds to foveal representation, is linked to fixation, microsaccades, smooth pursuit, and vergence adjustments. In contrast, the caudal SC, representing more peripheral visual field, is associated with the large gaze shifts (saccades). However, evidence regarding whether this functional gradient is preserved in the human SC remains limited. In this study, we employed a sequence-following visual-motor task to specifically engage SC activity. We measured blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI) responses to brief neural activity, known as hemodynamic response function (HRF). We showed a spatial gradient of the BOLD positive HRFs (pHRF) along the rostro-caudal axis of the SC. The pHRF was primarily located in the rostral SC, and it gradually weakened toward the caudal SC, where negative HRF (nHRF) was often observed. The systematic rostro-caudal evolution of HRFs were consistent both within and across subjects, consistent with results from previous electrophysiological studies. Our work showed the feasibility of using ultra-high-field fMRI to non-invasively examine neurovascular dynamics in a small and deeply located subcortical structures of the human brain.

The noise we make is hurting animals. Can we learn to shut up?

When the covid-19 pandemic started, Jennifer Phillips thought about the songs of the sparrows.

They were easier to hear, because the world had suddenly become quieter. Car traffic plummeted as people sheltered at home and shifted to remote work. Air travel collapsed. Cities—normally filled with the honking, screeching, engine-gunning riot of transportation—became as silent as tombs.

For years, Phillips has studied how animals react to “anthropogenic noise,” or the racket created by human activity. Most animals really don’t like it, she and her colleagues have learned. Animals constantly listen to the world around them: They’re on the alert for the rustle of approaching predators, or a mating call from a member of their species. As human society has expanded—with sprawling cities, industrial mines, and roads crisscrossing the world—it has gotten noisier too, and animals have trouble hearing one another.

Noise is invisible; there’s no billowing smokestack, no soiled waterway. We just got used to it as it vibrated in the background.

Phillips and her colleagues had spent time in the 2010s in San Francisco recording the sound of white-crowned sparrows in the Presidio. It’s a park that is half peaceful nature and half automobile noise, since it’s filled with thick clumps of trees and grassy fields but also has two highways that slice through it, feeding onto the Golden Gate Bridge. In past recordings, starting in the 1950s, sparrows had sung with complex and lower-pitched melodies and three major “dialects.” But by the 2010s, traffic in the Presidio had exploded, and the hubbub was so loud that the birds began to sing with faster trills—and at a higher pitch—so their fellows could hear them. The two quietest dialects were either dead or on their way to extinction.

They’re “screaming at the top of their lungs,” says Phillips. “They really can’t hear the lower frequencies when the traffic noise is present.” Urban noise can even change birds’ bodies; they get thinner and more stressed out. Their mating calls aren’t as effective, because female birds, as researchers have found, generally don’t enjoy high-pitched, high-volume shouting. (It makes them wonder if the males are unhealthy.) The noise can increase bird-on-bird conflict, because when birds can’t hear warning cries they accidentally stumble into enemy territory. Perhaps worst of all, in situations like these biodiversity takes a hit: Entire species that can’t handle urban clamor simply head out of town and never come back.

But as the sudden, eerie silence of the pandemic descended, Phillips sat at home thinking, It’s really quiet. And then she wondered: Would the Presidio birds now be able to hear each other better?

She raced over to the park and started recording. Sure enough, the park was seven decibels quieter—a huge drop. (That’s like the difference between the noise of the average home and whispering.)

And remarkably, the researchers found that the songs of the white-crowned sparrows had transformed. They were singing more quietly, with a richer range of frequencies. A bird could be heard twice as far as before. And the mating calls had gotten more sultry.

“They could sing a higher performance, basically a sexier song, but not have to scream it so loud,” Phillips says. 

It was as if time had been reversed and all the damage abruptly repaired. And it proved what Phillips and her peers have been increasingly documenting: that anthropogenic noise is the newest form of pollution we need to tackle. The noise of our relentlessly on-the-move industrial society affects all life on Earth, wildlife and humans, in ways we’re just beginning to grasp. Yet strategies such as electrification and clever urban design could help. As the Presidio showed, noise can vanish overnight—once we figure out how to shut up.

Hidden impacts

Many forms of pollution are obvious to us humans. Dumping toxic goo into lakes? Sure, that’s bad. Coal smokestacks pumping soot and carbon dioxide, plastic bags and sea nets choking whales—we now understand that these, too, are problems. Even an idea as gauzy as light pollution has penetrated the public consciousness to some extent, since it’s why city dwellers can’t see many stars, and we’ve heard it confuses migratory birds.

But noise, mostly from transportation, took longer to hit our radar. This is partly because it’s invisible; there’s no billowing smokestack, no soiled waterway. We just got used to it as it vibrated in the background.

sparrow perched on a branch, singing
Sparrows in San Francisco’s Presidio began to sing with faster trills—and at a higher pitch—so their fellows could hear them over the noise of nearby traffic.
GETTY IMAGES
hummingbird in flight
The black-chinned hummingbird seems to prefer noisy areas, fledging more chicks than the same species does in quieter areas.
MDF/WIKIMEDIA COMMONS

There were a few studies in the ’70s and ’80s showing that animals were upset by our noise. But the field really began to take off in the ’00s, in part because digital technology made it easier to record long swathes of sound out in nature and analyze them. One early salvo came from the biologist Hans Slabbekoorn, who was studying doves in the city of Leiden and irritatedly noticed that he could rarely get a clean recording because of the background noise. Sometimes he’d see the doves’ throats moving as they cooed but couldn’t hear them. “If I’m having difficulty hearing them,” he thought, “what about them?”

So he and a colleague started recording ambient sound levels in different parts of Leiden. Some were quiet residential areas, which registered a soothing 42 decibels, and others were noisy intersections or areas near highways, which reached 63 decibels, about as loud as background music. Sure enough, he found that birds in the noisy areas were singing at a higher pitch.

Over the next two decades, research in the field bloomed. Noise, the scientists found, has a few common ill effects on animals. It disrupts communication, certainly. But it also generally stresses them, reducing everything from their body weight to their receptivity to mating calls. If an animal nests closer to a road, its reproduction rates can go down; eastern bluebirds, for example, produce fewer fledglings. Truly cacophonous noise—like planes taking off at a nearby airport—can cause hearing loss in birds. And animals can wind up becoming less aware of threats from predators. They’ll wander closer to danger, because they can’t hear it coming. (And sometimes they’ll do the opposite: They’ll develop a rageaholic hair-­trigger temper, because they’re constantly on high alert and regard everything as a threat.) 

Even in deep rural areas, where things are normally pretty quiet, highways can disrupt wildlife—the noise carries far into the fields nearby. Fraser Shilling, a biologist at the University of California, Davis, has stood up to half a mile from rural highways and recorded sound as loud as 60 decibels, which is at least 20 decibels higher than you’d typically find in the wilderness. “The motorcycles and the 18-wheelers are really the ones that project a lot of noise,” he told me. 

Above 55 decibels, many skittish animals get into a fight-or-flight panic. The prevalence of bobcats—an endangered species famously rattled by noise—“starts dropping off the cliff,” says Shilling. Above 65, “you’re really starting to exclude almost all wildlife.”

And that’s not even the upper limit of what wildlife is exposed to. There are roughly a half-million natural-gas wells around the US, and piercingly loud compressors are used to shoot water down into most of them. Up close, the compressors can kick out 95 decibels, a sound as loud as a subway train; at one Wyoming gas well the sound still registered around 48 decibels nearly a quarter-mile away.

Historically, it wasn’t always easy to prove that noise was causing whatever problems the animals were experiencing. Maybe it was other factors; maybe animal populations reduce near a road because some are hit by vehicles? 

But several clever experiments have proved that noise—and noise alone—can disrupt wildlife. One was the “phantom road” experiment by the conservation scientist Jesse Barber and his team, then at Boise State University. They went out to a quiet, uninhabited area of the Boise foothills in Idaho, far away from any roads. In this valley in the mountains, thousands of migratory birds stop on their way south each year; they’ll gorge themselves on cherry bushes, gaining weight for the next days of flying. The researchers strapped 15 pairs of speakers to Douglas fir trees, in a half-kilometer line. Then they blasted recordings of highway noise. They played the noise for four days and then turned it off for four days. Then they observed thousands of birds, capturing many to measure their body mass.

The noise truly rattled the birds. When the sound was turned on, nearly a third left the area. Those that stuck around ate less: While birds should be heavier after a day of foraging, these ones didn’t gain much. The noise seemed to have so interrupted their feeding that they weren’t packing on the weight needed for their migratory trip.

Other, similarly nifty A/B tests followed. One was led by David Luther, a biologist at George Mason University (who also worked with Phillips on the covid-19 study in San Francisco). In 2015, these researchers took 17 white-crowned sparrows at birth and raised them in a lab. To teach them their species’ songs, they played the nestlings recordings of adult sparrows singing, at low and high pitches. Six of the nestlings heard the songs without any interference; with the other half, the researchers played the sounds of city noise at the same time.

The results were stark. The lucky birds that were spared the traffic noise learned to perform the quieter, sweeter, more complex songs. But the birds that had traffic noise blasted learned only the higher, faster, more stressed-out songs. From the cradle, noise changed the way they communicated.

Humans hate noise too

You can’t pull the same experiment with humans, raising them in a lab to see how noise affects them. (Not ethically, anyway.) But if we could, we’d likely find the same thing. We, too, are animals—and it appears that we suffer in similar ways from anthropogenic noise, even though we’re the ones creating it.

The sound of traffic is correlated with lousy sleep, higher blood pressure, more heart disease, and higher stress.

Stacks of research in the last few decades have found that noise—most often, as with wildlife, the sound of traffic—is correlated with lousy sleep, higher blood pressure, more heart disease, and higher stress. A Danish study followed almost 25,000 nurses for years and found that an additional 10 decibels hit them hard; over a 23-year period they had an 8% higher rate of death, plus higher rates of nearly every bad thing that could happen to you: cancers, psychiatric problems, strokes. (They controlled for other malign health influences.) As you’d probably predict by now, children fare badly too. When Barcelona researchers followed almost 3,000 elementary school kids for a year, they found that those in noisier schools performed worse on assessments of working memory and ability to pay attention.

“We think of ourselves as being ‘used to it,’” says Gail Patricelli, a professor of evolution and ecology at the University of California, Davis. “We’re not as used to it as we think we are.”

It’s also true that there’s a trade-off. Many people understand that noise from cities and highways is aggravating, but we tolerate it because we get benefits along with the hassles. Cities are crammed with jobs and connections and dating opportunities; cars and trucks bring us the things we need and increase our personal mobility.

It turns out that animals make a similar calculus. Some species appear to benefit in certain ways from proximity to noise, so they move toward it. 

Clinton Francis, a biologist at California Polytechnic State University, and a team studied bird populations near noisy gas wells in rural New Mexico. Most species avoided the riot of the well pumps. But Francis was surprised to find that some hummingbirds and finches preferred it, and by one important measure they thrived: They were nesting more in the noisy areas than in the quieter areas. Additionally, several species had more success at fledging chicks in noisier locations.

What was going on? It’s likely that the noise makes it harder for predators to hear the birds and hunt down their nests. “It’s essentially a predator shield,” Francis says. Since his research found that predators can cause as much as 76% of failures of eggs to produce healthy offspring, that’s a significant survival advantage.

Cities can offer the same protections to certain species. Consider the case of Flaco, a Eurasian eagle-owl that escaped from the Central Park Zoo in February of 2023 and found he was in a terrific place to hunt. The incessant traffic ought to have caused him trouble. “An owl like this is among the most vulnerable species to intrusions from noise pollution. They’re listening for extremely faint signals or cues that their prey provide,” Francis notes. But New York has its compensations, because prey animals abound. They’re also naïve and unguarded, never expecting an owl with a six-foot wingspan to swoop down and devour them.

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Granted, these upsides don’t cancel out the negatives. Human noise may shield some birds from predators, but in other ways it leaves them faintly miserable, with high levels of stress hormones and lower weight. 

Worse, the species that manage to thrive in cities or near highways are often the same ones all over the country.  And they represent only a minority of species; most are driven further away, with less and less land to live on as civilization spreads ever outward. 

“Overall, it’s kind of a nightmare for diversity,” says Luther.

How to silence the world

In the early ’00s, the village of Alverna in the Netherlands began to get louder. A major intercity road cut straight through the town, and traffic had gone up by two-thirds in the previous decade. Facing complaints about the din, the town offered to put up some 13-foot walls on either side of the route. Residents hated the idea. Who wants to look out the window at massive walls?

So instead town planners redesigned the road in subtle ways. They lowered it by half a meter, slightly blocking the tire sounds. They built wedges that rise up three feet on either side, and surfaced them with attractive antique stone; that blocked even more sound. They planted sound-absorbing trees. And as a final coup de grâce, they reduced the speed limit from about 50 to 30 miles per hour. When a car is moving slowly, the engine is producing most of the roar—but once it’s going 45 mph or faster, the rumble of tires on the pavement takes over and is much louder. Each intervention had only a small effect, but cumulatively they made the road a blessed 10 decibels quieter.

This tale illustrates one curious upside of noise. Compared with other forms of pollution, it can be ended quickly. Toxic pollutants or CO2 can hang around for tens of thousands of years; the microplastics in your pancreas are probably never coming out. But with noise, the instant you reduce the source, the benefits are immediate. 

Plus, most of what works is “not rocket science,” Shilling says. A tall wall at the side of a highway will cut noise by 10 decibels; fill a double-sided wall with rubble and it’s even better. That could cut the traffic noise to below 55 decibels, he notes, which would help particularly skittish forms of wildlife. Walls can block animal movement, though, so in animal-heavy areas it’s better to build berms—small hills on either side of a highway. Areas of high ecological importance could be prioritized to keep costs down. 

“If there’s a great chunk of wetland habitat and it’s the only one around for 50 miles in any direction? Well, then we should build noise walls around it,” he says. We should also build overpasses and underpasses to help animals get around. And to quiet the din of gas wells out in the countryside, states could require companies to build walls around them. (They’ll likely only do that, though, when human neighbors complain or launch lawsuits; animals don’t have lawyers.)

Cities, too, can learn to shut up, as Alverna proved. At the most ambitious, some have buried noisy highways that once cut through the downtown core. Boston put a massive elevated highway underground in its “Big Dig”; in Slabbekoorn’s hometown of Amstelveen—a suburb of Amsterdam—they’re currently enclosing the A9 highway in a tunnel and turning the surface into a verdant park with new buildings. “That’s amazing, getting back a lot of the space as well,” he says. 

Granted, this sort of reengineering can be brutally expensive, which is why politicians blanch when they’re asked to reduce road noise. The Big Dig cost $15 billion, and with interest up to $24 billion. When I mentioned cost to Shilling, he sighed. “It’s not as expensive as a B-1 bomber or tax cuts for rich people,” he says. “Environmental stuff is considered expensive just because our expectations are low, not because we can’t afford to do it.”

There are cheaper and more politically palatable fixes, though. Reducing urban speed limits is one; Paris recently cut the top speed on its ring roads from 70 to 50 kilometers per hour (43 to 31 mph), and noise at night went down by an average 2.7 decibels—a noticeable drop. Planting more trees and vegetation all around roads and cities can cut a few decibels more, and residents love it. 

Growing adoption of electricity would also bring down the volume. “Electric vehicles of all kinds have the potential to make a big difference,” Patricelli says; when the light turns green and an EV next to you accelerates away, it’s up to 13 decibels quieter than a comparable gas-­powered vehicle. These benefits won’t be felt as much on highways, because EVs still make tire noise at high speeds. But in the slower stop-and-go traffic of urban life, they are far more pleasant to the ears, both animal and human. Indeed, the electrification of everything that currently uses a gas-powered motor will make urban life quieter. Cities like Alameda, California, and Alexandria, Virginia, are increasingly banning gas-powered leaf blowers and lawn mowers, which operate at hair-raising volume while electric ones whisper along. 

We’ve engineered a civilization that roars, but the next phase is making it purr. The animals will thank us. 

Clive Thompson is a science and technology journalist based in New York City.

No one’s sure if synthetic mirror life will kill us all

For four days in February 2019, some 30 synthetic biologists and ethicists hunkered down at a conference center in Northern Virginia to brainstorm high-risk, cutting-­edge, irresistibly exciting ideas that the National Science Foundation should fund. By the end of the meeting, they’d landed on a compelling contender: making “mirror” bacteria. Should they come to be, the lab-created microbes would be structured and organized like ordinary bacteria, with one important exception: Key biological molecules like proteins, sugars, and lipids would be the mirror images of those found in nature. DNA, RNA, and many other components of living cells are chiral, which means they have a built-in rotational structure. Their mirrors would twist in the opposite direction. 

Researchers thrilled at the prospect. “Everybody—everybody—thought this was cool,” says John Glass, a synthetic biologist at the J. Craig Venter Institute in La Jolla, California, who attended the 2019 workshop and is a pioneer in developing synthetic cells. It was “an incredibly difficult project that would tell us potentially new things about how to design and build cells, or about the origin of life on Earth.” The group saw enormous potential for medicine, too. Mirror microbes might be engineered as biological factories, producing mirror molecules that could form the basis for new kinds of drugs. In theory, such therapeutics could perform the same functions as their natural counterparts, but without triggering unwelcome immune responses. 

After the meeting, the biologists recommended NSF funding for a handful of research groups to develop tools and carry out preliminary experiments, the beginnings of a path through the looking glass. The excitement was global. The National Natural Science Foundation of China funded major projects in mirror biology, as did the German Federal Ministry of Research, Technology, and Space.

By five years later, in 2024, many researchers involved in that NSF meeting had reversed course. They’d become convinced that in the worst of all possible futures, mirror organisms could trigger a catastrophic event threatening every form of life on Earth; they’d proliferate without predators and evade the immune defenses of people, plants, and animals. 

“I wish that one sunny afternoon we were having coffee and we realized the world’s about to end, but that’s not what happened.”

Kate Adamala, synthetic biologist, University of Minnesota

Over the past two years, they’ve been ringing alarm bells. They published an article in Science in December 2024, accompanied by a 299-page technical report addressing feasibility and risks. They’ve written essays and convened panels and cofounded the Mirror Biology Dialogues Fund (MBDF), a broadly funded nonprofit charged with supporting work on understanding and addressing the risk. The issue has received a blaze of media attention and ignited dialogues among not only chemists and synthetic biologists but also bioethicists and policymakers.  

What’s received less attention, however, is how we got here and what uncertainties still remain about any potential threat. Creating a mirror-life organism would be tremendously complicated and expensive. And although the scientific community is taking the alarm seriously, some scientists doubt whether it’s even possible to create a mirror organism anytime soon. “The hypothetical creation of mirror-­image organisms lies far beyond the reach of present-day science,” says Ting Zhu, a molecular biologist at Westlake University, in China, whose lab focuses on synthesizing mirror-image peptides and other molecules. He and others have urged colleagues not to let speculation and anxiety guide decision-making and argued that it’s premature to call for a broad moratorium on early-stage research, which they say could have medical benefits. 

But the researchers who are raising flags describe a pathway, even multiple pathways, to bringing mirror life into existence—and they say we urgently need guardrails to figure out what kinds of mirror-biology research might still be safe. That means they’re facing a question that others have encountered before, multiple times over the last several decades and with mixed results—one that doesn’t have a neat home in the scientific method. What should scientists do when they see the shadow of the end of the world in their own research? 

Looking-glass life

The French chemist and microbiologist Louis Pasteur was the first to recognize that biological molecules had built-in handedness. In the late 19th century, he described all living species as “functions of cosmic asymmetry.” What would happen, he mused, if one could replace these chiral components with their mirror opposites? 

Scientists now recognize that chirality is central to life itself, though no one knows why. In humans, 19 of the 20 so-called “standard” amino acids that make up proteins are chiral, and all in the same way. (The outlier, glycine, is symmetrical.) The functions of proteins are intricately tied to their shapes, and they mostly interact with other molecules through chiral structures. Almost all receptors on the surface of a cell are chiral. During an infection, the immune system’s sentinels use chirality to detect and bind to antigens—substances that trigger an immune response—and to start the process of building antibodies. 

By the late 20th century, researchers had begun to explore the idea of reversing chirality. In 1992, one team reported having synthesized the first mirror-image protein. That, in turn, set off the first clarion call about the risk: In response to the discovery, chemists at Purdue University pointed out, briefly, that mirror-life organisms, if they escaped from a lab, would be immune to any attack by “normal” life. A 2010 story in Wired highlighting early findings in the area noted that if a such a microbe developed the ability to photosynthesize, it could obliterate life as we know it. 

The synthetic biology community didn’t seriously weigh those threats then, says David Relman, a specialist who bridges infectious disease and microbiology at Stanford University and a trailblazer in studying the gut and oral microbiomes. The idea of a mirror microbe seemed too far beyond the actual progress on proteins. “This was almost a solely theoretical argument 20 years ago,” he says. 

Now the research landscape has changed. 

Scientists are quickly making progress on mirror images of the machinery cells use to make proteins and to self-replicate. Those components include DNA, which encodes the recipes for proteins; DNA polymerases, which help copy genetic material; and RNA, which carries recipes to ribosomes, the cell’s protein factories. If researchers could make self-replicating mirror ribosomes, then they would have an efficient way to produce mirror proteins. That could be used as a biological manufacturing method for therapeutics. But embedded in a self-­replicating, metabolizing synthetic cell, all these pieces could give rise to a mirror microbe. 

When synthetic biologists convened in Northern Virginia in 2019, they didn’t recognize how quickly the technology was advancing, and if they saw a threat at all, it may have been obscured by the blinding appeal of pushing the science forward. What’s become apparent now, says Glass, is that scientists in different disciplines, all related to mirror life, were largely unaware of what other scientists had been doing. Chemists didn’t know that synthetic biologists had made so much progress on creating mirror cells with natural chirality from scratch. Biologists didn’t appreciate that chemists were building ever-larger mirror macromolecules. “We tend to be siloed,” Glass says. And nobody, he says, had thought to seriously examine the immune system concerns that had already been raised in response to earlier work. “There was not an immunologist or an infectious disease person in the room,” Glass says, reflecting on the 2019 meeting. “I may have come closest, given that I work with pathogenic bacteria and viruses,” he adds, but his work doesn’t address how they cause infections in their hosts.

on the left, a hand with petri dish and the same image inverted on the right

GETTY IMAGES

These scientists also didn’t know that around the same time as their meeting, another conversation about mirror life was happening—a darker dialogue that was as focused on danger as it was on discovery. Starting around 2016, researchers with a nonprofit called Open Philanthropy had begun compiling research files on catastrophic biological risks. The organization, which rebranded as Coefficient Giving in 2025, funds projects across a range of focus areas; it adheres to a divisive philanthropic philosophy called effective altruism, which advocates giving money to projects with the highest potential benefit to the most people. While that might not sound objectionable, critics point out that the metrics devotees use to gauge “effectiveness” can prioritize long-term solutions while neglecting social injustices or systemic problems. 

Someone in Open Philanthropy’s bio­security group had suggested looking into the risks posed by mirror life. In 2019 the organization began funding research by Kevin Esvelt, who leads the Sculpting Evolution group at the MIT Media Lab, on biosecurity issues, including mirror life. He began reading up to see whether mirror life was something to worry about.

Esvelt made waves in 2013 for pioneering the use of CRISPR to develop a gene drive, a technology that could spread genetic changes introduced into a living organism through a whole population. Researchers are exploring its use, for example, to make mosquitoes hostile to the parasite that causes malaria—and, as a result, lower their chance of spreading it to humans. But almost immediately after he developed the tool, Esvelt argued against using it for profit, at least until proper safeguards could be set and its use in fighting malaria had been established. “Do you really have the right to run an experiment where if you screw up, it affects the whole world?” he asked, in this magazine, in 2016. At the Media Lab, Esvelt leads efforts to safely develop gene drives that can be deployed locally but prevented from spreading globally. 

Esvelt says he’s often thinking about the security risks posed by self-sustaining genetically engineered technologies, and research led him to suspect that the threat of mirror organisms hadn’t been seriously interrogated. The more he learned about microbial growth rates, predator-prey and microbe-microbe interactions, and immunology, the more he began to worry that mirror organisms, if impervious to the innate defenses of natural ones, could cause unstoppable infections in the event that they escaped the lab. 

Even if the first experimental iteration of such a germ were too fragile to survive in the environment or a human body, Esvelt says, it would be a light lift to genetically engineer new, more resilient versions with existing technology. Even worse, he says, the results could be weaponized. The possible path from 2019 to global annihilation seemed almost too direct, he found. 

But he wasn’t an expert in all the scientific fields involved in research on mirror life, so he started making calls. He first described his concerns to Relman one night in February 2022, at a restaurant outside Washington, DC. Esvelt hoped Relman would tell him he was wrong, that he’d missed something over the years of gathering data. Instead, he was troubled. 

The concern spreads

When Relman returned to California, he read more about the technology, the risks, and the role of chirality in the immune system and the environment. And he consulted experts he knew well—ecologists, other microbiologists, immunologists, all of them leaders in their fields—in an attempt to assuage his concerns. “I was hoping that they’d be able to say, I’ve thought about this, and I see a problem with your logic. I see that it’s really not so bad,” he says. “At every turn, that did not happen. Something about it was new to every person.” 

The concern spread. Relman worked with Jack Szostak, a professor of chemistry at the University of Chicago, and a group of researchers to see if it was possible to make an argument that mirror life wasn’t going to wipe out humanity. Included in that group was Kate Adamala, a synthetic biologist at the University of Minnesota. She was a natural choice: Adamala had shared the initial grant from the NSF, in 2019, to explore mirror-life technologies. 

She also became convinced the risk was real—and was dumbfounded that she hadn’t seen it earlier. “I wish that one sunny afternoon we were having coffee and we realized the world’s about to end, but that’s not what happened,” she says. “I’m embarrassed to admit that I wasn’t even the one that brought up the risks first.” Through late 2023 and early 2024, the endeavor began to take on the form of a rigorous scientific investigation. Experts were presented with a hypothesis—namely, that if mirror cells were built, they would pose an existential threat—and asked to challenge it. The goal was to falsify the hypothesis. “It would be great if we were wrong,” says Vaughn Cooper, a microbiologist at the University of Pittsburgh and president-elect of the American Society for Microbiology. 

Relman says that as the chemists and biologists learned more about one another’s work and began to understand what immunologists know about how living things defend themselves, they started to connect the dots and see an emerging picture of an unstoppable synthetic threat.

Some scientists have pushed back against the doomsday scenario, suggesting that the case against mirror life offers an “inflated view of the danger.”

Timothy Hand, an immunologist at the University of Pittsburgh who hadn’t participated in the 2019 NSF meeting, wasn’t initially worried when he heard about mirror life, in 2024. “The mammalian immune system has this incredible capability to make antibodies against any shape,” he says. “Who cares if it’s a mirror?” But when he took a closer look at that process, he could see a cascade of potential problems far upstream of antibody production. Start with detection: Macrophages, which are cells the immune system uses to identify and dispatch invaders, use chiral sensing receptors on their surfaces. The proteins they use to grab on to those invaders, too, are chiral. That suggests the possibility that an organism could be infected with a mirror organism but not be able to detect it or defend against it. “The lack of innate immune sensing is an incredibly dangerous circumstance for the host,” Hand says.

By early 2024, Glass had become concerned as well. Relman and James Wagstaff, a structural biologist from Open Philanthropy, visited him at the Venter Institute to talk about the possibility of using synthetic cell technology—Glass’s specialty—to build mirror life. “At first I thought, This can’t be real,” Glass says. They walked through arguments and counterarguments. “The more this went on, the more I started feeling ill,” he says. “It made me realize that work I had been doing for much of the last 20 years could be setting the world up for this incredible catastrophe.” 

In the second half of 2024, the growing group of scientists assembled the report and wrote the policy forum for Science. Relman briefed policymakers at the White House, members of the defense community, and the National Security Agency. Researchers met with the National Institutes of Health and the National Science Foundation. “We briefed the United Nations, the UK government, the government of Singapore, scientific funding organizations from Brazil,” says Glass. “We’ve talked to the Chinese government indirectly. We were trying to not blindside anybody.” 

A year and a half on, the push has had an impact. UNESCO has recommended a precautionary global moratorium on creating mirror-life cells, and major philanthropic organizations that fund science, including the Alfred P. Sloan Foundation, have announced they will not finance research leading to a mirror microorganism. The Bulletin of the Atomic Scientists highlighted considerations about mirror life in its most recent report on the Doomsday Clock. In March, the United Nations Secretary-General’s Scientific Advisory Board issued a brief highlighting the risks—noting, for example, that recent progress on building mirror molecules could reduce the cost of creating a mirror microbe. 

“I think no one really believes at this stage that we should make mirror life, based on the evidence that’s available,” says James Smith, the scientist who leads the MBDF, the nonprofit focused on assessing the risks of mirror life, which is funded by Coefficient Giving, the Sloan Foundation, and other organizations. The challenge now, Smith says, is for scientists to work with policymakers and bioethicists to figure out how much research on mirror life should be permitted—and who will enforce the rules.

Drawing the line

Not everyone is convinced that mirror organisms pose an existential threat. It’s difficult to verify predictions about how mirror microbes would fare in the immune system—or the larger world—without running experiments on them. Some scientists have pushed back against the doomsday scenario, suggesting that the case against mirror life offers an “inflated view of the danger.” Others have noted that carbohydrates called glycans already exist in both left- and right-handed forms—even in pathogens—and the immune system can recognize both of them. Experiments focused on interactions between the immune system and mirror molecules, they say, could help clarify the risks of mirror organisms and reduce uncertainty. 

Even among those convinced that the worst-case scenario is possible, researchers still disagree over where to draw the line. What inquiries should be allowed and what should be prohibited?

Andy Ellington, a biotechnologist and synthetic biologist at the University of Texas at Austin, doesn’t think mirror organisms will come to fruition anytime soon. Even if they do, he isn’t sure they will pose a threat. “If there is going to be harm done to the human race, this is about position 382 on my list,” he says. But at the same time, he says it’s a complicated issue worth studying more, and he wants to see the conversations continue: “We’re operating in a space where there’s so much unknown that it’s very difficult for us to do risk assessment.” 

Even among those convinced that the worst-case scenario is possible, researchers still disagree over where to draw the line. What inquiries should be allowed and what should be prohibited? 

Adamala, of the University of Minnesota, and others see a natural line at ribosomes, the cellular factories that transform chains of amino acids into proteins. These would be a critical ingredient in creating a self-replicating organism, and Adamala says the path to getting there once mirror ribosomes are in place would be pretty straightforward. But Zhu, at Westlake, and others counter that it’s worth developing mirror ribosomes because they could possibly produce medically useful peptides and proteins more efficiently than traditional chemical methods. He sees a clear distinction, and a foundational gap, between that kind of technology and the creation of a living synthetic organism. “It is crucial to distinguish mirror-image molecular biology from mirror-image life,” he says. That said, he points out that many synthetic molecules and organisms containing unnatural components, including but not limited to the mirror-image subset, might pose health risks. Researchers, he says, should focus on developing holistic guidelines to cover such risks—not just those from mirror molecules. 

Even if the exact risk remains uncertain, Esvelt remains more convinced than ever that the work should be paused, perhaps indefinitely. No one has taken a meaningful swing at the hypothesis that mirror life could wipe out everything, he says. The primary uncertainties aren’t around whether mirror life is dangerous, he points out; they have more to do with identifying which bacterium—including what genes it encodes, what it eats, how it evades the immune system’s sentinels—could lead to the most serious consequences. “The risk of losing everything, like the entire future of humanity integrated over time, is not worth any small fraction of the economy. You just don’t muck around with existential risk like that,” he says. 

In some ways, scientists have been here before, working out rules and limits for research. Two years after the start of the covid-19 pandemic, for example, the World Health Organization published guidelines for managing risks in biological research. But the history is much deeper: Horrific episodes of human experimentation led to the establishment of institutional review boards to provide ethical oversight. In the early 1970s, in response to concerns over lab-acquired infections and growing use of biological warfare, the US Centers for Disease Control and Prevention established biohazard safety levels (BSLs), which govern work on potentially dangerous biological experiments.

And in 1975—at the dawn of recombinant DNA research, which allows researchers to put genetic material from one organism into another—geneticists met at the Asilomar conference center in Pacific Grove, California, to hammer out rules governing the work. There were concerns over what would happen if some virus or bacterium, genetically engineered to have traits that would make it particularly dangerous for people, escaped from a lab. Scientists agreed to self-imposed restrictions, like a moratorium on research until new safety guidelines were in place. As a result of the meeting, in June 1976 the NIH issued rules that, among other things, categorized the risks associated with rDNA experiments and aligned them with the newly adopted BSL system.

Asilomar is often hailed as a successful model for scientific self-governance. But that perception reflects a tendency to recall the meeting through a nostalgic haze. “In fact, it was incredibly messy and human,” says Luis Campos, a historian of science at Rice University. Equally brilliant Nobelists argued on either side of the question of whether to rein in rDNA research. Technical discussions dominated; talks about who would be affected by the technology were missing. The meeting didn’t start establishing guidelines, says Campos, until the lawyers mentioned liability and lab leaks. 

For now it’s unclear whether these examples of self-­governance, which arose from the demonstrated risks of existing technologies, hold useful lessons for the mirror-life community. Three competing images of the future are coming into focus: Mirror life might not be possible, it might be possible but not threatening, or it might be possible and capable of obliterating all life on Earth. 

Scientists may be censoring themselves out of fear and speculation. To some, shutting down the work seems necessary and urgent; to others, it is unnecessarily limiting. What’s clear is that the question of what to do about mirror life has been both illuminating and disorienting, pushing scientists to interrogate not only their current research but where it might lead. This is uncharted territory. 

Stephen Ornes is a science writer based in Nashville, Tennessee.

A calibration-aware hierarchical CNN-SWIN fusion framework for robust Cross-Dataset brain MRI analysis

IntroductionDeep learning approaches have become central to brain MRI analysis; however, their reliability under dataset shift remains a critical barrier to safe and scalable deployment in neuroscience and clinical research. While convolutional neural networks (CNNs) provide strong locality-driven inductive biases for robust feature extraction, they lack global contextual awareness. Conversely, transformer-based architectures capture long-range dependencies but often exhibit reduced robustness and miscalibrated confidence when applied to heterogeneous medical imaging data, particularly in Cross-Dataset settings.MethodsIn this work, we propose a calibration-aware hierarchical CNN-Transformer fusion framework designed for robust brain MRI analysis under dataset shift. The architecture integrates a pretrained multi-scale CNN backbone with a hierarchical transformer branch and performs scale-aligned fusion through cross-attention mechanisms. By allowing local convolutional features to selectively query global contextual representations, the proposed design maintains stable feature contributions during fusion and mitigates overconfident reliance on transformer features when generalization degrades across datasets. The framework is evaluated using a strict Cross-Dataset protocol, where models are trained on one dataset and tested on a distinct dataset.ResultsExperimental results demonstrate that the proposed fusion model achieves competitive classification performance while substantially improving probabilistic calibration relative to both CNN-only and transformer-only baselines. Specifically, the model attains an average accuracy of 99.20% and achieves lower Expected Calibration Error (ECE = 0.0041), Brier score (0.0028), and Negative Log-Likelihood (NLL = 0.0277) compared to a standalone Swin Transformer and a strong ResNet50 baseline.DiscussionThese findings demonstrate that calibration-aware hierarchical CNN-Transformer fusion enhances both predictive reliability and robustness under Cross-Dataset evaluation. By improving the alignment between predictive confidence and empirical correctness, the proposed method supports safer large-scale analysis of heterogeneous brain MRI data, with important implications for multi-center neuroscience studies and trustworthy clinical decision support.