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.

The post AACR 2026 Chairs Identify Themes and Highlights from the Conference appeared first on GEN – Genetic Engineering and Biotechnology News.

STAT+: Researchers behind GLP-1 obesity drugs advance new approach: Drop GLP-1 as a target

The scientists whose work spurred the development of powerful obesity drugs like Eli Lilly’s Zepbound are now raising a provocative hypothesis: Perhaps targeting the GLP-1 hormone is actually not necessary to achieve effective weight loss.

A group of researchers led by Richard DiMarchi and Matthias Tschöp has created an experimental drug that activates receptors of the GIP and glucagon hormones. They propose — based on rodent and monkey studies — that this kind of molecule, when administered at high enough doses, may result in weight loss comparable to the weight loss seen with drugs that include GLP-1 as a target, and without the tolerability issues like nausea and vomiting that often come with the approved treatments, according to a peer-reviewed draft paper published this week.

The research, funded by a biotech called BlueWater Biosciences, would still need to be confirmed in humans; oftentimes results seen in animals don’t translate in the clinic. But the proposed approach, outlined in the journal Molecular Metabolism by some of the most well-known scientists in the field, is likely to stir controversy, as it challenges a central notion underpinning not just the development of approved obesity products but also next-generation versions. 

Continue to STAT+ to read the full story…

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. 

The post Landmark Pancreatic Cancer Trial Highlights Promise of RAS-Targeting Daraxonrasib appeared first on GEN – Genetic Engineering and Biotechnology News.

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Making AI operational in constrained public sector environments

The AI boom has hit across industries, and public sector organizations are facing pressure to accelerate adoption. At the same time, government institutions face distinct constraints around security, governance, and operations that set them apart from their business counterparts. For this reason, purpose-built small language models (SLMs) offer a promising path to operationalize AI in these environments.  

A Capgemini study found that 79 percent of public sector executives globally are wary about AI’s data security, an understandable figure given the heightened sensitivity of government data and the legal obligations surrounding its use. As Han Xiao, vice president of AI at Elastic, says, “Government agencies must be very restricted about what kind of data they send to the network. This sets a lot of boundaries on how they think about and manage their data.”

The fundamental need for control over sensitive information is one of many factors complicating AI deployment, particularly when compared against the private sector’s standard operational assumptions.

Unique operational challenges

When private-sector entities expand AI, they typically assume certain conditions will be in place, including continuous connectivity to the cloud, reliance on centralized infrastructure, acceptance of incomplete model transparency, and limited restrictions on data movement. For many state institutions, however, accepting these conditions could be anything from dangerous to impossible. 

Government agencies must ensure that their data stays under their control, that information can be checked and verified, and that operational disruptions are kept to an absolute minimum. At the same time, they often have to run their systems in environments where internet connectivity is limited, unreliable, or unavailable. These complexities prevent many promising public sector AI pilots from moving beyond experimentation. “Many people undervalue the operating challenge of AI,” Xiao says. “The public sector needs AI to perform reliably on all kinds of data, and then to be able to grow without breaking. Continuity of operations is often underestimated.” An Elastic survey of public sector leaders found that 65 percent struggle to use data continuously in real time and at scale. 

Infrastructure constraints compound the problem. Government organizations may also struggle to obtain the graphics processing units (GPUs) used to train and access complex AI models. As Xiao points out, “Government doesn’t often purchase GPUs, unlike the private sector—they’re not used to managing GPU infrastructure. So accessing a GPU to run the model is a bottleneck for much of the public sector.” 

A smaller, more practical model

The many nonnegotiable requirements in the public sector make large language models (LLMs) untenable. But SLMs can be housed locally, offering greater security and control. SLMs are specialized AI models that typically use billions rather than hundreds of billions of parameters, making them far less computationally demanding than the largest LLMs.

The public sector does not need to build ever-larger models housed in offsite, centralized locations. An empirical study found that SLMs performed as well or better than LLMs. SLMs allow sensitive information to be used effectively and efficiently while avoiding the operational complexity of maintaining large models. Xiao puts it this way: “It is easy to use ChatGPT to do proofreading. It’s very difficult to run your own large language models just as smoothly in an environment with no network access.” 

SLMs are purpose-built for the needs of the department or agency that will use them. The data is stored securely outside the model, and is only accessed when queried. Carefully engineered prompts ensure that only the most relevant information is retrieved, providing more accurate responses. Using methods such as smart retrieval, vector search, and verifiable source grounding, AI systems can be built that cater to public sector needs. 

Thus, the next phase of AI adoption in the public sector may be to bring the AI tool to the data, rather than sending the data out into the cloud. Gartner predicts that by 2027, small, specialized AI models will be used three times more than LLMs.

Superior search capabilities

“When people in the public sector hear AI, they probably think about ChatGPT. But we can be much more ambitious,” says Xiao. “AI can revolutionize how the government searches and manages the large amounts of data they have.”

Looking beyond chatbots reveals one of AI’s most immediate opportunities: dramatically improved search. Like many organizations, the public sector has mountains of unstructured data—including technical reports, procurement documents, minutes, and invoices. Today’s AI, however, can deliver results sourced from mixed media, like readable PDFs, scans, images, spreadsheets, and recordings, and in multiple languages. All of this can be indexed by SLM-powered systems to provide tailored responses and to draft complex texts in any language, while ensuring outputs are legally compliant. “The public sector has a lot of data, and they don’t always know how to use this data. They don’t know what the possibilities are,” says Xiao.

Even more powerful, AI can help government employees interpret the data they access. “Today’s AI can provide you with a completely new view of how to harness that data,” says Xiao. A well-trained SLM can interpret legal norms, extract insights from public consultations, support data-driven executive decision-making, and improve public access to services and administrative information. This can contribute to dramatic improvements in how the public sector conducts its operations.

The small-language promise

Focusing on SLMs shifts the conversation from how comprehensive the model can be to how efficient it is. LLMs incur significant performance and computational costs and require specialized hardware that many public entities cannot afford. Despite requiring some capital expenses, SLMs are less resource-intensive than LLMs, so they tend to be cheaper and reduce environmental impact. 

Public sector agencies often face stringent audit requirements, and SLM algorithms can be documented and certified as transparent. Some countries, particularly in Europe, also have privacy regulations such as GDPR that SLMs can be designed to meet.

Tailored training data produces more targeted results, reducing errors, bias, and hallucinations that AI is prone to. As Xiao puts it, “Large language models generate text based on what they were trained on, so there is a cut-off date when they were trained. If you ask about anything after that, it will hallucinate. We can solve this by forcing the model to work from verified sources.”

Risks are also minimized by keeping data on local servers, or even on a specific device. This isn’t about isolation but about strategic autonomy to enable trust, resilience, and relevance.

By prioritizing task-specific models designed for environments that process data locally, and by continuously monitoring performance and impact, public sector organizations can build lasting AI capabilities that support real-world decisions. “Do not start with a chatbot; start with search,” Xiao advises. “Much of what we think of as AI intelligence is really about finding the right information.”

This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff. It was researched, designed, and written by human writers, editors, analysts, and illustrators. This includes the writing of surveys and collection of data for surveys. AI tools that may have been used were limited to secondary production processes that passed thorough human review.

The Download: cyberscammers’ banking bypasses, and carbon removal troubles

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology.

Cyberscammers are bypassing banks’ security with illicit tools sold on Telegram 

Inside a money-laundering center in Cambodia, an employee opens a banking app on his phone. It asks for a photo linked to the account, so he uploads a picture of a 30-something Asian man. 

The app then requests a video “liveness” check. The scammer holds up a static image of a woman who doesn’t match the account. After 90 seconds, he’s in. 

The exploit relies on illicit hacking services sold on Telegram that break “Know Your Customer” (KYC) facial scans. MIT Technology Review found 22 channels and groups advertising these services. This is what we discovered

—Fiona Kelliher 

Is carbon removal in trouble? 

—Casey Crownhart 

Last week, news emerged that Microsoft was pausing carbon removal purchases. It was a bombshell—Microsoft effectively is the carbon removal market, single-handedly purchasing around 80% of all contracted carbon removal. 

The report sparked fear across the industry, raising questions about the future of carbon removal and the role of Big Tech. Read the full story

This story is from The Spark, our weekly newsletter exploring the technology that could combat the climate crisis. Sign up to receive it in your inbox every Wednesday. 

The quest to measure our relationship with nature 

—Emma Marris 

Humans have done some destructive things to the ecosystems around us. But conservationists are learning that we can also be a force for good. 

To understand how we work best with nature, a group of scientists, authors, and philosophers have developed new measurements of human-nonhuman relationships. Now, a team in the United Nations is continuing the work. Find out why—and what they hope to achieve

This story is from the next issue of our print magazine, which is all about nature. Subscribe now to read it when it lands on Wednesday, April 22.  

The must-reads 

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology. 

1 Ukraine says Russian troops have surrendered to robots  
They claim a fully automated attack captured army positions for the first time in history. (404 Media
+ Europe’s vision for future wars is full of drones. (MIT Technology Review
 
2 Monkeys with BCIs are navigating virtual worlds using only their thoughts 
The research could help people with paralysis. (New Scientist)  
+ But these implants still face a critical test. (MIT Technology Review
 
3 NASA wants to put nuclear reactors on the Moon 
They could power lunar bases and extend spaceflight. (Wired $) 
+ NASA is also building a nuclear-powered spacecraft. (MIT Technology Review

4 Plans for online age verification in the US are raising red flags 
Experts warn of compliance issues and potential data breaches. (NBC News
+ In the EU, an age verification app is about to launch. (Reuters $) 

5 An AI chip boom just pushed Taiwan’s stock market past the UK’s 
It’s risen past $4 trillion to become the world’s seventh largest. (FT $) 
+ Future AI chips could be built on glass. (MIT Technology Review

6 The public backlash against data centers is intensifying in the US 
Protests and litigation are blocking projects. (CNBC
+ One potential solution? Putting them in space. (MIT Technology Review

7 Five-minute EV charging is becoming a reality 
China’s BYD has started rolling it out. (Gizmodo)  
+ “Extended-range electric vehicles” are about to hit US streets. (Atlantic $) 

8 Stealth signals are bypassing Iran’s internet blackout  
Files hidden in satellite TV broadcasts keep information flowing. (IEEE
 
9 Shoe brand Allbirds made a shock pivot to AI, sending stock up 700%  
No bubble to see here, folks. (CNBC)  
+ What even is the AI bubble? (MIT Technology Review

10 The largest ever map of the universe is complete  
It captures 47 million galaxies and quasars. (Space.com

Quote of the day 

“I like the internet as much as anybody, but we’ve got to go on an internet diet. We don’t need to pay for corporations to do their internet stuff.” 

 —Sylvia Whitt, a 78-year-old retiree based in Virginia, tells the Washington Post why they’re protesting against data centers.  

One More Thing 

a collage of hands and suggestive body shapes

ISRAEL VARGAS

AI and the future of sex 

Some Republican lawmakers want to criminalize porn and arrest its creators. But what if porn is wholly created by an algorithm? In that case, whether it’s obscene, ethical, or safe becomes a secondary issue. The primary concern will be what it means for porn to be “real”—and what the answer demands from all of us. 

Technological advances could even remove the “messy humanity” from sex itself. The rise of AI-generated porn may be a symptom of a new synthetic sexuality, not the cause. Read the full story

—Leo Herrera 

We can still have nice things 

A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line.) 

+ An animator turned his son’s drawings into epic anime characters. 
+ Hundreds of baby green sea turtles made a spectacular first journey to the ocean. 
+ You can now track rocket launches from take-off to orbit in real time. 
+ These musical mistakes prove that even the classics aren’t perfect. 

Role of TRPC1 in the pathogenesis of depression induced by traumatic brain injury

BackgroundTraumatic brain injury (TBI) is one of the leading causes of mortality and disability, with many patients developing long-term sequelae. Depression is among the most common psychiatric complications following TBI, yet its underlying mechanisms remain unclear. Transient receptor potential canonical 1 (TRPC1) has been implicated in neurological disorders, but its role in post-TBI depression is not well understood.MethodsA controlled cortical impact (CCI) model was used to induce moderate TBI in mice. At 4 weeks post-injury, depressive-like behaviors were assessed using the tail suspension test (TST), forced swim test (FST), and sucrose preference test (SPT). Subsequently, reactive astrocytes and microglia were quantified, along with the expression of inflammatory cytokines, in the ipsilateral hippocampus. Synaptic function was also evaluated.ResultsBehavioral tests revealed that TBI mice exhibited significant depressive- and anxiety-like behaviors at 4 weeks post-injury. Concurrently, TRPC1 expression was downregulated in the ipsilateral hippocampus, accompanied by reduced levels of synaptic-associated proteins, elevated pro-inflammatory cytokines, and increased reactive astrocytes and microglia. Further experiments demonstrated that TRPC1 overexpression attenuated neuroinflammation, restored synaptic function, and ameliorated depressive-like behaviors in TBI mice.ConclusionThis study suggests that TBI may trigger depression by downregulating TRPC1, thereby promoting neuroinflammation and synaptic dysfunction. Conversely, TRPC1 overexpression mitigates these effects, highlighting its potential as a therapeutic target for post-TBI depression.

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.

Diffusion tensor imaging-functional MRI fusion reveals disrupted white matter structure–function coupling in HIV-associated asymptomatic neurocognitive impairment

ObjectiveConventionally, blood oxygen level-dependent (BOLD) signals derived from resting-state functional magnetic resonance imaging (rs-fMRI) are attributed to gray matter, but recent evidence confirms stable low-frequency oscillations within white matter. While structure–function coupling is pivotal in neuropsychiatry, it remains underexplored in HIV-associated neurocognitive disorders (HAND). Focusing on Asymptomatic Neurocognitive Impairment (ANI), the earliest stage of HAND, this study establishes a white matter skeleton-based fusion framework integrating diffusion tensor imaging (DTI) and rs-fMRI to investigate underlying mechanisms.MethodsWe enrolled 47 patients with ANI and 48 matched healthy controls. Fractional anisotropy (FA) images from DTI and BOLD signals derived from rs-fMRI were projected onto a unified white matter skeleton to achieve structure–function spatial alignment. FA, skeleton-based white matter amplitude of low-frequency fluctuations (SWALFF), and its dynamic variability (dSWALFF) were calculated. Group differences in white matter structure and function were assessed, with structure–function coupling examined in regions showing overlapping FA-SWALFF and FA-dSWALFF alterations. Additionally, a novel White Matter Dys-coupling Index (WDI) was proposed to quantify the deviation between structural integrity and functional activity and evaluate its clinical relevance.ResultsCompared to controls, ANI patients exhibited widespread FA reductions and increased mean diffusivity (MD) and radial diffusivity (RD), indicating diffuse demyelination. Functionally, a spatial dissociation emerged: SWALFF was reduced in posterior occipital pathways (left vertical occipital fasciculus, forceps major), whereas SWALFF and dSWALFF were elevated in prefrontal pathways (forceps minor). Overlapping regions revealed complex coupling patterns, ranging from concordant decline to compensatory upregulation and decoupling. The interaction between FA and dSWALFF further highlighted instability in dynamic regulation. The WDI was significantly correlated with infection duration, immune status, and cognitive domain scores.ConclusionThis study identifies a characteristic “coupling imbalance” in the white matter of ANI patients, defined by the coexistence of structural degeneration and functional reorganization. We propose the WDI as a quantitative metric for this deviation. Its significant associations with clinical and cognitive metrics suggest its potential as a neuroimaging biomarker for the early identification and mechanistic understanding of HAND.

Integrating evidence-based health approaches in U.S. healthcare settings: addressing the syndemics of poverty, health, and violence

Health disparities in the United States are not produced by single risk factors but by interacting social and biological conditions that cluster within structurally marginalized communities. Poverty, violence, and poor physical and mental health form a reinforcing system of disadvantage that traditional healthcare models—organized around isolated diseases—are poorly equipped to address. This perspective examines these dynamics through a syndemic framework, which conceptualizes co-occurring conditions as mutually interacting epidemics intensified by social inequality. Drawing on interdisciplinary evidence from public health, medicine, and social science, we describe how poverty-related stressors such as housing instability, food insecurity, and barriers to healthcare intersect with exposure to interpersonal and structural violence to amplify risks for depression, posttraumatic stress disorder, chronic disease, and premature mortality. These interactions produce compounded health burdens that are disproportionately experienced by marginalized populations. Despite increasing attention to social determinants of health, current healthcare responses remain fragmented. Health systems frequently identify risks through screening for social needs or trauma exposure but lack the institutional infrastructure, reimbursement mechanisms, and cross-sector partnerships required to address them effectively. We argue that advancing health equity requires moving beyond additive models of care coordination toward syndemic-informed healthcare systems that intervene simultaneously on clustered conditions and their shared upstream drivers. We outline key priorities for practice, policy, and research, including linking screening to actionable care pathways, strengthening partnerships between healthcare and social service systems, and expanding workforce training to include structural and syndemic competency.