Health Innovation West Midlands (HIWM) has helped local NHS organisations secure a share of the £85m national investment in obesity care.
Sheffield first council to oppose NHS FDP Palantir contract
Sheffield City Council has become the first local authority to approve a motion formally opposing Palantir’s involvement in the NHS FDP.
CAR T Cells Simultaneously Target Glioblastoma and Immune Cells
Scientists have identified a new molecular target for CAR T-cell immunotherapy to attack both glioblastoma cells and tumor-supporting macrophages at once. A study published today in Nature shows promising preclinical results that could allow this approach to overcome the limitations of previous attempts to target glioblastoma with CAR T cells.
“Our approach targets both the tumor and the environment that allows it to thrive,” said Sheila K. Singh, MD, PhD, professor of neuro-oncology and neurosurgery at King’s College London and McMaster University. “Instead of treating glioblastoma as only a mass of cancer cells, we need to think of it as a connected tumor-immune ecosystem. By going beyond the cancer cells alone, we are also targeting immune cells that help shield the tumor from treatment.”
Glioblastoma is an aggressive and lethal form of brain cancer where current treatments, including surgery, radiation and chemotherapy, only provide temporary benefits and are rarely able to prevent recurrence. Past attempts to develop CAR T therapies for glioblastoma have failed to produce sustained responses due to a number of challenges such as heterogeneous antigen expression, antigen loss, and microenvironmental barriers that treatments solely focusing on targeting the tumor cells have not been able to surmount.
In particular, tumor-associated macrophages have been shown to be key contributors to glioblastoma progression. While macrophages normally play an important role in the immune response against infections, glioblastoma can recruit and reprogram these immune cells to promote tumor growth, suppress the immune system, and resist treatment.
“CAR T therapy has been effective in some blood cancers, but translating that success to brain tumors has been difficult,” said Shan Grewal, an MD/PhD candidate at McMaster and co-lead author of the study. “Most approaches have focused on killing cancer cells alone. Our work suggests we may also need to dismantle the immune support system that helps glioblastoma survive.”
Using patient tumor samples, Singh’s team conducted multi-omic profiling studies that led to the identification of a promising target present both in glioblastoma cells and tumor-associated macrophages, called glycoprotein non-metastatic melanoma protein B (GPNMB). By engineering CAR T cells to target GPNMB, the researchers were able to attack glioblastoma tumors on two fronts and show potent antitumor activity in several preclinical models including patient-derived xenografts.
While more work will be needed before this strategy can be evaluated in clinical trials, the study introduces a new framework to identify immunotherapy targets that could potentially be applied to a wide range of solid tumors beyond glioblastoma.
Supporting this concept, a team at the University of Calgary has simultaneously published results in Nature Cancer from a first-in-human study using a similar approach in relapsed alveolar soft-part sarcoma (ASPS) and translocation renal cell carcinoma, two types of cancer that stably express GPNMB. In these patients, a CAR T-cell therapy directed against GPNMB was found to be safe and induced stable disease for up to three months, providing early clinical evidence supporting the feasibility of this therapeutic approach.
The post CAR T Cells Simultaneously Target Glioblastoma and Immune Cells appeared first on Inside Precision Medicine.
A Recap of the Inaugural Youth Mental Health Hub at SXSW London
In early June, SXSW London returned for its second year, gathering thousands of creatives, enthusiasts, entrepreneurs, and investors into the city to celebrate film, music, tech, and culture. As part of this year’s festival, the Child Mind Institute, in partnership with Wellcome, proudly presented the inaugural Youth Mental Health Hub – a week of programming dedicated to advancing solutions to one of the defining challenges of our time: the global youth mental health crisis. Through six thought-provoking sessions, leaders in clinical care, science, technology, policy, and media came together to explore how to strengthen prevention, improve early identification, reduce stigma, and build systems that meet young people where they are.
Here’s a look back at the inspiring conversations that took place throughout the week.
Beyond the Average: Understanding Vulnerability in the Digital Childhood Era
As artificial intelligence rapidly transforms the experience of childhood, experts explored how AI can both support and challenge young people’s mental health. The panelists discussed when and under what conditions young people may be most vulnerable as well as what systems we need to support them.
Moderator
Gary Wilson, Director of Research, Huo Family Foundation
Speakers
Catherine Sebastian, PhD, Head of Evidence for Mental Health, Wellcome
John Pickavance, PhD, Principal Data Scientist, Born in Bradford
Georgia Turner, Postdoctoral Research Associate, University of Cambridge
Michael Milham, MD, PhD, Chief Science Officer, Child Mind Institute
AI Is Already Shaping Childhood. Who Is Shaping AI? Balancing Innovation, Evidence, and Safety in Youth Mental Health
Youth are experiencing the impacts of AI earlier and more intensely than any previous generation has. This session explored the role of public leadership in anticipating harm before it becomes systemic — establishing guardrails, fostering digital resilience, and ensuring that innovation advances hand in hand with youth mental health and well-being.
Moderator
Sarah Aguiar-Borges, PhD, University of Cambridge
Speakers
Julia Gillard, former Prime Minister of Australia; Chair, Wellcome
Kanishka Narayan, UK Minister for AI and Online Safety
Giovanni Salum, MD, PhD, SVP, Global Programs, Child Mind Institute.
Youth Mental Health After Conflict: Healing, Resilience, and Rebuilding Systems
Experts shared insights on the unique mental health challenges facing children affected by war, displacement, and humanitarian crises. This session explored how societies can implement youth-centered systems grounded in prevention and use early identification to position youth mental health as a cornerstone of long-term recovery and resilience.
Moderator
Krupa Padhy, BBC Radio 4
Speakers
Dr. Mark Jordans, professor, Centre for Global Mental Health, King’s College London; Director of Research & Development, War Child
Emma Ferguson, mental health policy and advocacy specialist, UNICEF
Mohamed Ali, Director, Iftin Global
Dyslexia: Changing the Story
In a timely discussion, experts explored how dyslexia is currently understood in society, challenging current language and misperceptions that can impact a child’s confidence and mental health. Through a blend of personal experience and clinical expertise, the conversation focused on the need for evidence-based support and strengths-based approaches to help children and their families thrive.
Moderator
Kate Griggs, Founder, Made By Dyslexia
Speakers
Maggie Aderin, PhD, space scientist & educator; dyslexia advocate
Harold S. Koplewicz, MD, President and Medical Director, Child Mind Institute
Connection Continuum: Preventing Suicide and Combating Loneliness
Suicide is one of the leading causes of death among young people globally. This session gathered community, clinical, and digital leaders to explore what a more connected system of support looks like in practice. The panelists also discussed the important of recognizing warning signs, expanding access to evidence-based care, and prioritizing early intervention to help prevent youth suicide.
Moderator
Krupa Padhy, BBC Radio 4
Speakers
Victoria Hornby, CEO, Mental Health Innovations
Dean Perryman, Empty Chairs
Michael Milham, MD, PhD, Chief Science Officer, Child Mind Institute
Does Mental Health Science Funding Need a New Paradigm in the Age of AI?
With technology evolving faster than the science designed to understand it, experts examined how research, philanthropy, and clinical leaders can work together to build the evidence, safeguards, and infrastructure needed to protect children’s mental health in the digital age.
Moderator
Chelsea Clinton, Vice Chair, Clinton Global Initiative
Speakers
Miranda Wolpert, Director of Mental Health, Wellcome
Margaret Laws, President & CEO, HopeLab
Daria Bukhman, Co-Founder and Chair, Bukhman Philanthropies
Harold S. Koplewicz, MD, President & Medical Director, Child Mind Institute
The post A Recap of the Inaugural Youth Mental Health Hub at SXSW London appeared first on Child Mind Institute.
Boys, Masculinity, and the Looksmaxxing Trend
By now, you’ve probably heard of the term looksmaxxing. Think pieces about the trend have popped up all over the internet. And in a recent episode of Saturday Night Live, comedians poked fun at lookmaxxing influencers obsessed with having the perfect male physique.
While this new social media craze may seem silly, it’s impacting more boys than you might think. In a study conducted last year that surveyed over 3,000 young men (ages 16–25) from the United States, United Kingdom, and Australia, nearly two-thirds of participants were regularly engaging with masculinity influencers.
Teen boys are being encouraged to change the way they look in order to fit a certain standard of attraction. The growing amount of looksmaxxing content they see online can have real effects on their self-esteem and mental health.
What is looksmaxxing?
Looksmaxxing originated nearly a decade ago in incel forums where men blamed their lack of romantic partners on the belief that female sexual selection is primarily based on physical qualities. So men who aren’t born with traits desirable to women are doomed to fail romantically. While traditional incels wallow in this fate, looksmaxxers seek to enhance their appearance to become more attractive. Their community claims that there is a universal standard for what the ideal man (and woman) should look like.
This is determined by a rating system called the PSL scale — the name being an amalgamation of three prominent misogynistic incel forums of the 2010s. There are many factors that go into the scaling, such as eye shape, jaw size, nose angle, and body fat percentage. Along this scale, you can land in four categories: subhuman, normie, Chadlite, and Chad (the ultimate catch).
During the pandemic, looksmaxxing went mainstream, merging with “manosphere” content on social media platforms like TikTok and Instagram. The trend became less about the ability to attract women and more of a competition among boys and men as they engaged in mog-offs — online contests where people have their faces analyzed and compared by facial recognition software to determine who’s better looking.
Self-improvement practices have gained popularity among boys. Some are considered to be softmaxxing, like developing skincare routines or eating high-protein diets, and others to be hardmaxxing, like using growth hormones or getting cosmetic surgery.
Prominent young influencers like Clavicular represent the extreme side of looksmaxxing. He practices bonesmashing (using a hammer on facial bones to try to form more angular features), injects himself with testosterone, and takes meth to maintain a low body fat percentage while still having a muscular physique.
Looksmaxxing and new beauty standards
The rise of looksmaxxing seems to have a caused a ripple effect among teen boys. While the ideal look has centered on big muscles and washboard abs for decades, there’s now an added pressure on facial beauty that’s typically been reserved for girls.
“With some of the teen boys I work with, most of whom already have self-esteem issues, I think there is a lot more concern about how they look,” observes Alnardo Martinez, LMHC, director of the Pediatric OCD Intensive Program and a mental health counselor at the Child Mind Institute. “They want to have the strong jaw, really big muscles, clear skin, and a perfect haircut.”
However, Martinez notes that it sometimes take a while for boys to admit that they feel this pressure. They may insist that they don’t really care about that stuff. “But then, maybe a few months later, it comes out that there is a lot of comparison. They’re spending a lot of time in front of the mirror or in the bathroom trying to create this perfect image,” he observes.
What teen boys think about looksmaxxing and self-improvement
We talked to young men who were critical of Clavicular and the impact looksmaxxing can have on teens but were positive about engaging in some form of physical self-improvement.
Wyatt, now 19, remembers comparing his jawline to his peers’ when he was in 7th grade. “I just felt like they had really sharp jawlines. And I was just like, ‘Oh, I want to get closer to that.’” He would also come across TikToks advertising rubber chewing blocks and chin exercises meant to strengthen the jawline.
And so, Wyatt began to do jaw exercises he’d found online, reciting the alphabet while stretching out the muscles. “I would go through my Zoom classes throughout the day and then after that was done, I’d just go into the bathroom and go through the whole exercise. It would take like an hour sometimes,” he recalls. “It turned into more like a self-care, self-improvement session. I would do that every day after my classes. I didn’t feel like I was done with school until I finished my jawline routine.” He took photos to document his progress.
Wyatt feels like the routine had a positive effect, because he was able to see an improvement. “I felt more satisfied with myself, a little more confident.”
Lev, now 19, remembers wanting to have some control over his body when going through puberty in high school. “Puberty is not a straightforward process. It’s not all peaches and cream. Your body changes, and it can be uncomfortable,” he explains. “But with lifting and strength training, it was very exciting to see this, you know, man energy that came out of it. I wanted to harness that and really take it by the reins. Have some agency as a man.”
And while he rejects the extreme parts of looksmaxxing, Lev does regularly practice self-improvement through weight lifting, skin care routines, and taking GLP-1 weight loss medication.
How looksmaxxing can impact boys’ mental health
Since looksmaxxing places such a strong emphasis on achieving a very specific look, clinicians are concerned about its influence on teens. “Self-esteem is pretty fragile during puberty,” Martinez says. “There’s already a ton of comparison and perceived flaws that teens don’t love about themselves.”
These insecurities can be exacerbated by the type of content teens engage with online, Martinez explains. Along with ChatGPT bots specifically designed to judge aesthetics, Reddit threads such as r/Mewing and websites like Looksmaxxing Forum encourage boys to post pictures of their faces and bodies to get rated by their peers. Boys as young as 13 visit these forums, posting pictures and asking for tips on how to improve their looks.
“These are generally places where people are already pretty harsh and critical. These boys are receiving a lot more ‘confirmation’ around the perceived things that are wrong with them or that they need to change,” Martinez says. “And it just feeds into the already present negative self-image and self-talk.”
He explains that this type of social media engagement can also compound underlying mental health issues like depression and social anxiety. “They might be less likely to go out and talk to people because they’re thinking, ‘Everyone is going to see this one thing that everyone else has told me is wrong with me. So now I can’t go out,’”he says.
Martinez is also concerned that online content can negatively affect teens with body dysmorphic disorder (BDD). “If they think they have a big nose, for example, they might go on these Reddits and ask, ‘What does my nose look like? Is it too big?’ There are trolls out there. Someone is going to say yes and then that’s going to make the BDD symptoms even worse.”
When behaviors might be concerning
In some ways, teen boys taking part in more self-improvement practices could be seen as a good thing. They’re exercising, taking care of their skin, and eating more balanced diets. The issues begin when these types of practices turn into obsession. And given the underlying ideology of looksmaxxing and the nature of social media, things can become unhealthy.
According to Martinez, there are some changes in behavior to look out for that indicate you might want to step in.
One clear change, he says, is a noticeable shift in the amount of time they’re spending on grooming themselves. “Maybe they were someone who would typically just get up and run out the door without washing their face,” he says. “But now they’re spending a lot more time in the bathroom and asking a lot of questions about how they look.”
Another warning sign can be a big change in personality. “Irritability is a big one that we’ll see a lot,” he says. “They’re unhappy with how they look, so this increases a general level of irritation.”
These behaviors paired with an unusual uptick in time spent on social media, Martinez explains, can be a sign that something’s wrong and support is needed.
How to support your child
If you’re worried that your child might be engaging in looksmaxxing-related behaviors to an unhealthy degree, says Martinez, there are a few things you can do:
- Open communication. Martinez suggests approaching your child with curiosity. “You could start the conversation by saying something like, ‘So have you heard about this? What do you think about it? Have you ever had any thoughts yourself about how you look or desires to change your body or face?’ And then give them some space to be open and vulnerable about it. Validate their experience.”
- Find out where your child is getting their information. “Read it together, talk about it, and see what your child thinks about it,” Martinez advises. “And if it’s promoting something dangerous, then you can talk to them about how those practices can be harmful and what could actually happen if they do some of those things.”
- Encourage male role models. “There’s a patient I work with now who doesn’t have a present dad,” Martinez explains. “His mom tries to talk to him about things like body image, but he feels like she doesn’t understand and can’t relate. So having someone that he can talk to and be open about this stuff with, especially someone who can also share their own struggles, can be really helpful.”
- Seek help from a mental health professional. This is especially important if you find out that your child has been engaging in extreme forms of looksmaxxing such as bonesmashing or starvemaxxing. Martinez recommends looking for a clinician who specializes in body image or body dysmorphic disorder.
A lot of parenting comes down to open communication around what your kids are seeing and what they’re feeling. We all have things about our bodies that we might not like and wish we could change, says Martinez, and it can help to normalize those feelings. “And then you can discuss how they can make changes in healthy ways,” he suggests. “Go over what’s a realistic change and what’s a dangerous change.”
The post Boys, Masculinity, and the Looksmaxxing Trend appeared first on Child Mind Institute.
Michael Antonov: From Virtual Worlds to Real-World Drug Discovery
AI is often portrayed as either a technology that will revolutionize healthcare and cure disease or an overhyped force that could stifle science—but the reality is far more nuanced. While AI is already transforming biomedical research, meaningful advances in medicine require much more than powerful algorithms. That complexity is the focus of this conversation with Michael Antonov, co-founder of Oculus, who turned to biology and drug discovery after pioneering virtual reality.
To do so, he co-founded the computational drug discovery company Deep Origin. Rather than relying on AI alone, Antonov believes progress depends on integrating machine learning with physics-based molecular simulations, mechanistic models, and rigorous experimental validation. This philosophy has been fundamental for shaping Deep Origin’s AI-native platform to improve virtual drug screening, predict toxicity, and help researchers develop safer, more effective therapies.
In this episode of Behind the Breakthroughs, Anotonov examines how AI is changing drug discovery and the pharmaceutical industry’s opportunities and limitations, taking a pragmatic approach to claims that AI alone can improve human health from larger models and more computing power. This conversation offers a glimpse into biomedical innovation’s future for those interested in where AI is truly changing medicine and where human expertise and experimental science remain vital.
This interview has been edited for length and clarity.
IPM: Does virtual reality (VR) have a role in medicine and healthcare?
Antonov: VR is predominantly a visualization device, so it’s good for training and various other areas in terms of actual treatments. When VR has been used and is actually FDA approved, as far as I know, it presents modified images to each eye and kind of trains your brain to treat them both simultaneously. Similarly, it’s been used for PTSD treatments and some of the areas where you can maybe handle fears. I haven’t personally experimented with that.
On the visualization side, for displayed molecules, there’s a company that has done a great job of allowing you to look at the molecules, and this could be useful for research. That said, it just gives you more spatial perception. It doesn’t actually solve the problem for you.
On the training side, there are potentially huge benefits, even though you would then have to require investing a lot in software to make it actually perform well. Now, one good example is, I have invested in this company called Osso VR, which does training for knee replacement surgery, and they actually practiced it, and they did a study where their surgeons trained with their knee replacement and got 230% more proficiency.
Given the time and the accuracy of a procedure and the speed of how they learn. But to me, that felt actually very incredible that it’s actually being used. I think they also do nursing trade trainings and such. Those are probably the top areas that will probably be more brain-oriented cognitive things you could do. It would just take time to explore it.
IPM: What will AI’s impact be on medicine and healthcare?
Antonov: I think that there is still a lot of uncertainty. The system is overloaded. There’s a whole spectrum, and the challenge is that there are hundreds of different companies and projects with a whole different range of funding.
For pharma, it would be a big job to sift through what is actually good and what will help me take my target forward. That’s a challenge because there’s a lot more noise and there are some really good companies, but there are also many me-too, not-so-great ones. There are also certain fundamental areas that haven’t been solved yet, like toxicity and other issues, although there has been progress in some areas. There are like dozens of predictors, but they’re not necessarily super great, though they’re better than nothing. It’s hard to tell where it’s going. The biggest thing is to see what you actually prove in the lab.
The other thing is that there is a range of medicinal chemists and other knowledgeable people who haven’t been exposed to the breakthroughs or effects we might see on our side. AI may surprise us in certain biological parts of the name for certain problems. Now, more holistically at Deep Origin, our plan is to support the discovery process for small molecule drugs and have predictable outcomes.
IPM: How will AI drive the future of precision medicine?
Antonov: The super exciting way it could look in 20 years in that type of timeframe is that we are starting to get personalized medicine. You’re really combining the patient and the system model so that whenever you have a disease, if you have maybe a novel genomic mutation or if you have a new virus, you can literally put the data into the system.
Here is basically experimental data about whatever you collect from the virus. I don’t know if you get the structure of its protease from crystallography. I will even tell you here are the steps you need to take and which lab to run them in. But once you provide it, the system will be able to decompose the pathways and targets it’s affecting and then identify the specific concentrations you might need for these patients.
Essentially, you can provide a target in just a few months. You have good candidates, and these candidates have a much higher probability of not being toxic and having good admin properties. Let’s say we are moving from 90% failure rate to maybe 60%. That would be a huge job. That’s what the toxicity models enable, though they are hard because they need both experimental and data collection. But actually, even things like physics can help with counter screening, asking, what are all these things we should not bind to? Go and check them computationally. This whole stack basically gives you data on how to run your trial. That’s ten years. But then you level it up with populations and the individual.
This is a 2030 year outlook because then you’re pulling in the genomics data, maybe various things, and this is where the industry really becomes much more powerful and individualized. To do that, you really need these more detailed models.
IPM: Do you have a prediction about a current AI trend that will be around for a while?
Antonov: One of the hot topics right now is the idea of AI scientists. In our case, we have an AI discovery engine. We actually did this earlier, which is this area grant from the U.K. for picking up the disease, which can be fully drugged by AI.
We ran our AI scientist system to pick a target for endometriosis. It uses our tools to come up with a molecule. It’s currently in progress, and it did a very detailed breakdown and analysis of hundreds of targets based on very specific criteria, and I picked a particular one with all the reasons.
It’s interesting to make those kinds of tools and this whole pipeline available to almost everyday people because then, much like some genomics tools, an available AI system, which can support the full path of drug development, can in fact let a patient or an interest group just come in and take lots of steps in the direction of saying, “Here’s either maybe an RNA or a gene therapy or a drug that can serve.”
That would be a huge step toward democratizing it. It doesn’t mean that AI will do all the steps for us, but it doesn’t mean that it can do a lot of the known steps, which have been done many times and can help us along the way. Of course, the real scientist will still be very critical to all the parts.
For general accessibility, this automation that is happening and these kinds of simulation tools and large language models in general are incredible. They’ve got a little bit of a long-winded thing, but I wanted to reflect on what you said.
IPM: What are the pros and cons of building Deep Origin in the U.S. or China?
Antonov: Some of the more recent wisdom that I’ve heard is that if you want to survive in the U.S. or more expensive countries, you need to be taking bigger risks, and you need to be more innovative in how you approach the type of modalities and things. So that’s one line of thinking.
Another way is to be distributed. In our case, a big part of our AI/ML team is in Armenia. My co-founder is Armenian. We have 40 people there. I have just come from spending a week and a half with the team there for model building and science. There is an AI, and there are definitely people in all of the areas. Automated labs could also probably be in any country.
In terms of the actual trials, it depends on the situation. There are certain things that it’s probably wiser to do in China for this time being, but also maybe India will be up and coming, and if there are certain scenarios where there are more rare diseases, it’s probably okay to also not stay in the States.
There’s no perfect answer. We have a challenging environment. At the end of the day, you have to have something really valuable and novel to keep going forward. They have really great scientific research there too. We have to be careful and just really go at it hard.
IPM: Where does China stand out from the United States in terms of pharmaceutical research and development?
Antonov: If I were to pick one area, it’s the cost of clinical trials and the way we select just all the aspects of this. And to be honest, I’m not an expert in this. And clearly there’s a lot of progress in China right now. Everybody talks about how it’s much more cost-effective and quicker to do things there. There are a lot of “right to try” opportunities that are helping.
That said, I believe that we can have a lot better kinds of social programs around this to make it like easier for people to participate and maybe take more highly educated guesses and risks. There’s software infrastructure to simplify and reduce the cost. That would be amazing. In some of those areas, AI also can help, and the models actually can help.
IPM: If you could work on anything, what would it be?
Antonov: I would say focusing on aging as a disease. If you look at the funding, things could shake up the type of research that the NIH and the National Institute on Aging (NIA) do, which is really fundamental to our biology because it drives the majority of diseases and has 3% of the budget, whereas oncology and Alzheimer’s have huge budgets. There’s probably more impact in aging than probably some other well-funded areas if we look at the fundamental parts. That would be a big area where you can have a multiplier effect just from the research side.
To really build an ecosystem of better computational and AI models, maybe creating some way to actually incentivize people to contribute to them, because that’s the challenge right now. You can publish a research paper, or you can build your model to make your proprietary hidden drug. But we need scientists to share those in an integrated way. How do we do that?
Maybe it’ll take some big AI companies to jump into it and do something there. But it’s not going to be solved with just a model. It really needs to be a true experiment-grounded framework where researchers can contribute their part and have it be a part of a whole.
The post Michael Antonov: From Virtual Worlds to Real-World Drug Discovery appeared first on Inside Precision Medicine.
NHS Greater Glasgow and Clyde rolls out digital triage system
NHS Greater Glasgow and Clyde (NHSGGC) has begun rolling out a digital triage system across its emergency departments.
The Download: Anthropic launches Claude Science, and California’s carbon manure math
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.
Claude Science is Anthropic’s newest flagship product
At an event for pharmaceutical executives, biotech founders, and researchers yesterday, Anthropic announced Claude Science, a major new product intended to support scientific research like Claude Code supports software engineering.
Like Claude Code, Claude Science can autonomously carry out meaningful work from concise, high-level instructions, with tools for computational biology and drug development. The launch signals that Anthropic is doubling down on AI for science, and the company will also use the product in its own research into drugs for rare, neglected diseases.
Discover why Anthropic is betting big on AI for scientific research.
—Grace Huckins
Why California’s carbon manure math doesn’t add up
Something stinks in California’s climate policies.
Years ago, the state set up a system that pays cattle farmers to turn the methane emitted from cattle manure into natural gas. It’s become wildly popular because the subsidies are extremely lucrative. But research suggests the program exposes the shortcomings of carbon offsetting and trading schemes.
Instead of forcing industries to directly cut their pollution or pay for it as a cost of doing business, legislators have opted for incentives that swap climate responsibilities between parties and regions. The system could ultimately lock in more warming.
Read the full story on California’s dubious carbon calculations.
—James Temple
This story is from The Spark, our weekly climate tech newsletter. Sign up to receive it in your inbox every Wednesday.
Watch now: longevity’s next frontier—“reprogramming” your body
Billions of dollars are pouring into efforts to reverse aging as scientists investigate ways to return cells to a younger state. But how close are these experimental treatments? And are they likely to work?
At a recent virtual Roundtables event, MIT Technology Review explored the answers with science editor Mary Beth Griggs and senior biotechnology reporter Jessica Hamzelou. Subscribers can now watch the full recording of the fascinating discussion.
MIT Technology Review Narrated: the search for dark matter has been blown wide open
For decades, physicists have hunted for weakly interacting massive particles (WIMPs), a leading candidate for dark matter. But their search has run into a new problem: neutrinos.
These tiny particles from the sun and other stars can create a “neutrino fog” that drowns out any signal of dark matter. Hitting the neutrino fog does not, however, mean an end to the search. Researchers just have to shift the focus of their hunt.
They’re now casting a much wider net. New proposals include quantum sensors, liquid-helium detectors, and even searches in Jupiter’s atmosphere.
—Dan Garisto
This is our latest story to be turned into an MIT Technology Review Narrated podcast, which we publish each week on Spotify and Apple Podcasts. Just navigate to MIT Technology Review Narrated on either platform, and follow us to get all our new content as it’s released.
The must-reads
I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.
1 The US has lifted restrictions on Anthropic’s Mythos and Fable models
Anthropic said it would begin restoring access today. (NYT $)
+ The US had imposed controls over security concerns. (Bloomberg $)
+ It lifted the restrictions after lengthy talks with Anthropic. (BBC)
+ But the crackdown has already opened doors for Chinese AI rivals. (CNBC)
2 The most detailed survey of the universe ever is now underway
It’s using the largest digital camera on Earth. (New Scientist $)
+ The project is based at the Vera C. Rubin Observatory in Chile. (NYT $)
+ It aims to transform our view of the cosmos. (MIT Technology Review)
3 Tech talent is fleeing the US due to H1-B visa chaos
They’re eyeing relocation to Canada, the UK, or the Gulf. (Rest of World)
+ While China is poaching AI talent from the US. (CNBC)
+ Visa rules are also affecting young scientists. (MIT Technology Review)
4 Trump raked in more than $1 billion from crypto businesses in 2025
He reported $635 million in royalties from a Trump meme coin. (BBC)
+ The rest largely came from his World Liberty Financial venture. (The Hill)
5 The UN warns that the rapid spread of AI may worsen global inequality
It’s proposed a shared framework for responsible AI development. (Guardian)
6 Companies are making LLMs talk like a caveman to curb AI spending
A senior OpenAI employee contributed to the “caveman” project. (404 Media)
7 Babies are born with the neural foundations for math
Brain recordings have identified the mechanisms. (New Scientist $)
8 An independent studio has bought the OpenAI movie Amazon dropped
Neon has purchased “Artificial,” which focuses on Sam Altman. (NYT $)
+ Amazon had dumped it after investing in OpenAI. (Gizmodo)
+ The depiction of Altman is reportedly unsympathetic. (Variety)
9 AI has re-created Gene Wilder’s voice for a new “Willy Wonka” series
Wilder’s wife said his estate is “delighted” with the new show. (NBC News)
+ Netflix partnered with AI company ElevenLabs on the project. (The Verge)
10 NASA aims to send a spare Mars rover—and soccer ball—to the moon
The nuclear-powered “Promise” may help establish a lunar base. (NYT $)
Quote of the day
“Caveman save you token, save you money.”
—The GitHub repository for the “caveman” plugin explains how the project curbs AI spending by turning verbose LLM outputs into concise text.
One More Thing
SELMAN DESIGN
AI is dreaming up drugs that no one has ever seen. Now we’ve got to see if they work.
On average, it takes more than 10 years and billions of dollars to develop a new drug. A growing number of startups are betting that AI can make the process faster and cheaper.
By predicting how potential drugs might behave in the body and discarding dead-end compounds before they leave the computer, machine-learning models can cut down on the need for painstaking lab work.
Yet it is still early days for AI drug discovery. A lot of AI companies are making claims they can’t back up—and the technology is not a panacea. But the technology is beginning to move from promise to practice.
Find out how AI is speeding up drug discovery.
—Will Douglas Heaven
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.)
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+ Focus your mind or unwind with over 80 custom albums of ambient instrumental electronic music on Caught In Joy.
Freed: ‘We throw away money on digital bets’
Benefits from digital are there for the taking, suggests James Freed, deputy director of the NHS Digital Academy.
Dose–response relationship of exercise interventions on sleep quality in patients with depression: a systematic review and meta-analysis
BackgroundThis meta-analysis aimed to systematically evaluate the effects of exercise interventions on sleep quality in patients with depression and to explore the dose–response relationships of key intervention parameters.MethodsA comprehensive search was conducted in PubMed, Web of Science, Embase, Scopus, and the Cochrane Library to identify randomized controlled trials (RCTs). Standardized mean differences (SMDs) and 95% confidence intervals (CIs) were calculated using a random-effects model. Subgroup and sensitivity analyses were performed to examine potential dose–response relationships.ResultsA total of 17 publications, including 19 randomized controlled trial comparisons and 1,457 participants, were included in this systematic review and meta-analysis. Pooled estimates indicated that exercise interventions significantly improved sleep quality [SMD = −0.37, 95% CI: −0.48 to −0.27]. Dose–response modeling suggested that exercise doses around 312.75 MET·min/week may be associated with greater improvements [Hedges’ g = −0.51, 95% CI: −0.71 to −0.31]. Subgroup analyses suggested that mind–body exercise [SMD = −0.49, 95% CI: −0.63 to −0.35], durations of 9–12 weeks [SMD = −0.49, 95% CI: −0.74 to −0.24], fewer than two sessions per week [SMD = −0.47, 95% CI: −0.65 to −0.29], and sessions longer than 90 minutes [SMD = −0.42, 95% CI: −0.66 to −0.18] may be associated with favorable changes.ConclusionsExercise interventions may improve sleep quality in individuals with depression, with potential benefits at low doses. These findings support individualized exercise prescriptions, but larger multicenter RCTs with long-term follow-up are needed to confirm the dose–response pattern and subgroup findings.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD420251105568, identifier PROSPERO (CRD420251105568).