IntroductionAction Over Inertia (AOI) is a recovery-oriented intervention designed to promote occupational engagement and support personal recovery through changes in everyday activity patterns. While AOI has been examined in Western contexts, its applicability and clinical adaptation in East Asian settings remain underexplored. This study used a mixed-methods approach to examine the feasibility and cultural adaptation of a group-based AOI program in Japan.MethodsA mixed-methods pilot feasibility design was used. The quantitative component was a single-arm repeated-measures pilot study conducted across four psychiatric daycare facilities in Japan. Outcomes were assessed at baseline, post-intervention, and 1-month follow-up in 12 participants with serious mental illness using the Recovery Assessment Scale (RAS), Temple University Community Participation Measure-Japanese version (TUCP-J), and Social Functioning Scale (SFS), alongside symptom severity assessed with the Brief Psychiatric Rating Scale (BPRS). These measures were used as exploratory clinical outcomes to describe preliminary patterns of change and to inform future controlled studies, rather than to determine intervention effectiveness. The qualitative component involved semi-structured interviews with occupational therapists who delivered the intervention, to contextualize the quantitative findings and identify implementation barriers and adaptations. The quantitative intervention study was approved by the Research Ethics Committee of the Graduate School of Medicine, Nagoya University, Japan (2023-0209), and registered with the UMIN Clinical Trials Registry (UMIN000045392). The qualitative interview study was approved by the Ethics Review Committee for Research Involving Human Participants, Nihon Fukushi University, Japan (23-041-03).ResultsNo significant improvements were observed in the exploratory outcomes of recovery, participation, or social functioning. Although BPRS showed a significant overall time effect, post-hoc comparisons between time points were not significant, and this change cannot be causally attributed to AOI because of the single-arm design. In an exploratory observation, participants with higher symptom severity appeared to show lower community participation. Qualitative findings suggested that the intervention dose, participant–program fit, readiness for activity change, and group-based delivery conditions may need further optimization within Japanese psychiatric daycare settings.DiscussionThe findings suggest that group-based AOI may be feasible to implement in Japanese psychiatric daycare settings, but further cultural and clinical adaptation is needed before effectiveness can be evaluated in controlled trials. Adaptation may require preserving AOI’s theoretical foundations while making the intervention less exposing, less abstract, and more accessible in group-based settings. Future studies should use controlled designs, longer follow-up periods, and broader outcome indicators to examine the effectiveness and implementation of culturally adapted AOI.Clinical trial registrationUMIN Clinical Trials Registry https://www.umin.ac.jp/ctr/, identifier UMIN000045392.
Social anxiety but not callous-unemotional traits predicts shame coping in conduct disorder
IntroductionConduct disorders are characterized by emotional dysregulation. Both callous-unemotional traits and social anxiety are heightened in conduct disorder patients and are associated with different mechanisms of emotion regulation. Previous evidence has proposed that secondary emotions, such as shame, might also be affected in conduct disorder and that callous-unemotional traits and social anxiety might be related to shame as well as to shame coping. Therefore, the current study investigated links between callous-unemotional traits, social anxiety, shame proneness, and shame coping in adolescent inpatients with conduct disorder.MethodsForty adolescent inpatients with conduct disorders (M = 12.4, SD = 1.4) filled in questionnaires on callous-unemotional traits, social anxiety, shame proneness, and shame coping. Correlational and regression analyses, as well as mediation analyses were performed.ResultsCallous-unemotional traits were not associated with any other construct. Social anxiety showed positive correlations with shame proneness and internalizing as well as externalizing shame coping. Social anxiety was also a significant predictor of internalizing shame coping while controlling for shame proneness and callous-unemotional traits. No predictors emerged for externalizing shame coping. Mediation analyses confirmed that neither shame proneness nor social anxiety mediated the relationship between CU traits and shame coping, as CU traits were not significantly associated with either variable.DiscussionThe findings suggest that social anxiety plays a key role in internalizing shame coping in conduct disorder patients. CU traits appear to be unrelated to shame proneness and shame coping, either directly or indirectly, in conduct disorder.
Spatial CRISPR screens map total RNA in tissue
Nature Biotechnology, Published online: 11 June 2026; doi:10.1038/s41587-026-03126-z
A method for spatial CRISPR perturbation screening reveals how genetic changes alter coding and non-coding RNA in a native tissue context, including the tumor microenvironment.
Large-scale, spatially resolved panoramic CRISPR screening in native tissue environments using Perturb-DBiT
Nature Biotechnology, Published online: 11 June 2026; doi:10.1038/s41587-026-03127-y
In vivo CRISPR genetic perturbations are spatially mapped at scale.
Clinical Profile and Genomic Characterization of the 2026 Bundibugyo Virus Index Case in Uganda
Nature Medicine, Published online: 11 June 2026; doi:10.1038/s41591-026-04510-7
Clinical Profile and Genomic Characterization of the 2026 Bundibugyo Virus Index Case in Uganda
STAT+: Enliven Therapeutics’ leukemia drug shows promise in new study
A targeted drug from Enliven Therapeutics induced molecular responses in nearly half of patients with advanced leukemia, including higher response rates in patients treated at an earlier stage of their disease.
The updated early-stage study results reported Thursday for the Enliven drug, ELVN-001, compare favorably to a current blockbuster medicine sold by Novartis and an upstart experimental drug recently bought by Merck.
At 24 weeks, an 80 mg, once-daily dose of ELVN-001 achieved a major molecular response in 48% of patients with chronic myeloid leukemia, or CML, a slow-growing cancer that starts in myeloid cells.
STAT+: ‘Synthetic lethality’ could trigger another round of biotech M&A
This story first appeared in Adam’s Biotech Scorecard, a subscriber-only newsletter. STAT+ subscribers can sign up here to get it delivered to their inbox.
Never before have I covered so much positive news about pancreatic cancer in such a short period of time. What happens next? Could Revolution Medicines buy Tango Therapeutics? Or, perhaps Bristol Myers Squibb goes all out and acquires Revolution Medicines?
To be clear, neither of these deals has been announced, or even rumored. I’m just playing the biotech M&A speculation game. But a strong case for something to happen can be made in the wake of Monday’s exciting report from Tango. In an early-stage clinical trial, patients with advanced pancreatic cancer benefited more from a combination of two targeted drugs — a PRMT5 inhibitor from Tango and Revolution’s pan-RAS inhibitor — than they might from each drug on its own.
HHS responds coolly to paper on alcohol risk
Get your daily dose of health and medicine every weekday with STAT’s free newsletter Morning Rounds. Sign up here.
Good morning. Today we’ve got an item from STAT’s new AAAS media fellow Lauren Chan. She’ll be reporting with us this summer. Scroll down to read her report on a sugary soda study.
Google DeepMind is worried about what happens when millions of agents start to interact
Google DeepMind is funding research into the potential dangers of situations where millions of different AI agents interact with each other online.
According to Rohin Shah, who directs the company’s AGI safety and alignment research, the mass-market arrival of agents that can carry out tasks without human oversight and follow instructions given to them by other agents creates a whole new class of risk.
In an effort to address this, Google DeepMind—which made agent-based tools a centerpiece of Google I/O last month—has teamed up with several other organizations to announce a $10 million funding pot for researchers to study the behavior of multi-agent systems and come up with ways to prevent unsafe scenarios. Joining Google DeepMind are Schmidt Sciences, a philanthropic foundation set up by Eric and Wendy Schmidt; ARIA, the UK government’s moonshot agency; the Cooperative AI foundation, a UK-based nonprofit research outfit; and Google’s charitable arm, Google.org.
I asked Shah and James Fox, who leads the Science of Trustworthy AI program at Schmidt Sciences, what they hope to achieve with that $10 million. It’s no small sum, but it’s dwarfed by the budgets commanded by Google DeepMind’s own research teams.
The aim is to kick-start research outside tech companies, says Shah: “The strength of academia is that it can look really quite far into the future and do the kind of work that isn’t top of mind at industry labs.”
“The main issue is that there just isn’t really a field of research for multi-agent safety yet,” he adds. “And we would like there to be.”
The concern is that as more and more AI agents get deployed and begin working together, we could hit a tipping point where imagined scenarios become real. “We see this with humanity, too,” says Shah. “Our institutions can accomplish things that no individual human can.”
Shah thinks that we have a few more months to go before agents are deployed throughout the economy in numbers that make potential risks a real concern. He wants to get ahead of that moment.
Risky business
What risks are we talking about, exactly? The possibilities that Shah and Fox have in mind mostly boil down to supercharged versions of bad things that happen on the internet already: scams, prompt injections (where an AI agent is fed malicious instructions, turning it into a self-guiding piece of malware), other forms of cyberattack. We look at what humans do now and ask what the agent version of that would be, says Shah.
“We’ve got this digital commons that is integral to how society works, and you really want to ensure that this doesn’t descend into just absolute anarchy,” says Fox.
(I asked Shah if they were considering any worst-case scenarios more on the doomer end of the spectrum, such as widespread economic collapse. “Certainly not if we’re talking by the end of the year,” he said. That’s only six months away! He laughed. “Okay, a while after that.”)
Shah and Fox both think that the only way to understand what might happen when large numbers of multi-agent systems interact with each other is to run realistic simulations. They want researchers to drop AI agents into sandboxes and study what they do.
You can’t predict what’s going to happen by studying single agents, or even small groups of agents, in isolation. You can’t assume that AI agents underpinned by LLMs will always act rationally, says Fox. And the complexity comes from having huge numbers of interactions at once.
Some researchers, including a team at Google DeepMind, have argued that artificial general intelligence (if possible at all) could come not from a single super-smart model but from a kind of agent hive mind, where the capabilities of the whole add up to more than the sum of its parts.
Lack of trust
Google DeepMind is not the only top AI firm warning about the risks of the technology it is building. A couple of weeks ago, Anthropic published guidelines for deploying AI agents based on an approach to cybersecurity known as zero trust, which starts with the assumption that a computer system is vulnerable, an agent is an attacker, and a breach will happen.
Refael Angel, cofounder and CTO of Akeyless, a cybersecurity firm based in Tel Aviv, agrees that understanding the new risks introduced by agent-based systems is crucial.
Every approach to security in the past has assumed that the machine in question was software written by a human, doing fixed things on fixed paths, says Angel: “An agent breaks all of those assumptions. It reasons, it improvises, and it can be hijacked by a single sentence buried in a document it was asked to read.”
Angel welcomes this new funding. “No single lab should author the safety standards everyone else has to trust,” he says. But he cautions that safety researchers can overlook boring problems that are already here in favor of more exotic hypothetical ones.
And yet, Fox notes, risks that were hypothetical a few years ago are now very real: “The future’s come more quickly than perhaps expected.”
Why China is betting on big nuclear reactors
It’s a tale of two nuclear industries.
In China, large reactors are coming together at a stunning pace. The country has nearly doubled its nuclear fleet since 2016, reaching nearly 60 gigawatts of total power capacity. The new facilities are nearly all gigawatt-scale pressurized-water reactors.
Meanwhile, the US has built just two reactors in that time—Unit 3 and Unit 4 at Plant Vogtle in Georgia. Smaller reactors are attracting a lot of excitement and investment, though. A microreactor developer just saw its reactor reach criticality in a new Department of Energy pilot program.
The world is racing to meet rising electricity demand, and many countries are interested in energy sources, like nuclear power, that don’t come with greenhouse-gas emissions. The key question: Which of these strategies will really pay off in terms of getting electrons on the grid quickly?
Today, the US and France are known as leaders in the nuclear industry. The US has the world’s largest fleet, with France coming in second. France is heavily dependent on nuclear for its grid—about two-thirds of the country’s power comes from nuclear reactors.
But they have hardly added any new reactors to their fleets in recent years. The US can point only to Vogtle, and France connected its latest reactor to the grid in December 2024—the first in over 20 years.
It’s incredibly difficult to build the massive projects that dominate the nuclear industry today. Up-front investment can run well into the billions, so investors need to wait decades to break even. Designs are complex and can often change during the regulatory process, tacking on cost and time.
Many are hoping that the key to turning things around in these countries could be smaller reactors.
The idea is that shrinking the footprint of a reactor cuts down the initial investment needed to prove out the new technology. The reactors could even be put together in a factory rather than being built on-site, allowing for a lower price over time.
These smaller reactors are the target of tons of interest and investment in the US, including a new Department of Energy pilot program. The department set a goal last year of having three test reactors reach criticality by July 4, 2026, the nation’s 250th anniversary. (Criticality is the point at which a reactor achieves a self-sustaining chain reaction that can release energy.)
Last week, California-based Antares hit the milestone with its Mark-0 reactor.
The company plans to eventually build microreactors, designed to produce between 100 kilowatts and 1 megawatt of electricity (large reactors on the grid today are at least 1,000 times that size). The core design is a sodium-cooled reactor, and it uses TRISO fuel, self-contained graphite-coated spheres of a more concentrated fuel than what most reactors use today.
But there is still a long way to go before it can actually produce power—the Mark-0 doesn’t have any power conversion or heat removal systems. The company plans to produce electricity in late 2027 and deploy in the field by 2028, CEO Jordan Bramble told the Associated Press.
The private sector is interested—and invested—too. Big Tech companies are throwing money at new reactors they hope can help power data centers.
But look to the other side of the globe, and others are sticking with the established blueprint: China is absolutely churning out large nuclear reactors. Construction started on six new reactors there in 2025, and two more got underway in the first five months of 2026. The country is on course to overtake both the US and the European Union in installed nuclear capacity by 2030.
The speed here is staggering. As of 2024, the average time to build a new reactor in China came in at between five and seven years. The global average is about nine years, and the two most recent reactors in the US took about 15 years.
One key to this speed is standardization: China has set up a uniform project management system to design, license, and build new reactors. They’re built in batches of six or more to take advantage of economies of scale.
It’s one of the ideas meant to give the edge to smaller reactors, but China is working to realize the same benefits for larger projects. A huge amount of government investment is certainly helping.
Larger reactors generally provide more electricity to the grid for a lower price, a key consideration in view of China’s steeply increasing electricity demand. While smaller reactors require less up-front investment than larger ones because of their size, they’ll actually be more expensive per unit of electricity produced.
That’s not to say China is exclusively focused on big reactors: the country is also expected to see its first operational small modular reactor, the Linglong-1, start sending power to the grid this year.
But looking ahead, it’ll be interesting to see if smaller reactors can help the West keep building new nuclear power. At the moment, with China’s quick progress, it’s looking as if bigger might just be better.
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