Scientists have deliberately turned male mouse embryos into females for the first time. A team based in Japan used a CRISPR-based approach to remove the Y chromosome from male cells and create female clones of male mice.
“No one has done this before,” says Monika Ward, a reproductive biologist at the University of Hawaii, who was not involved in the research.
The feat could change the way scientists think about reproduction, says Takashi Ishiuchi, a reproductive biologist at the University of Yamanashi, who co-led the work. The findings were published in a preprint paper shared on bioRxiv earlier this month, which has not yet been through the peer-review process. “There’s a fixed concept in our scientific field that we need both females and males for reproduction,” says Ishiuchi. “I think we could change this concept.”
He and his colleague Shogo Matoba of the Riken BioResource Research Center in Ibaraki also hope their technique could help rescue endangered species, particularly in cases where only a few individuals remain.
“It’s exciting to see,” says Ben Novak, lead scientist at the wildlife conservation organization Revive & Restore, who was not involved in the work. “I am confident there will be plenty of applications, particularly for conservation purposes.”
Sex change
Ishiuchi says he and his colleagues were inspired by the Okinawa rubble goby, a fish that can change its sex in certain situations. If no males are present, a female can do this in order to reproduce with the other females. Males can also change sex to female.
This ability to change sex might be useful when it comes to rescuing endangered species, including mammals. There’s some precedent in the lab—albeit not intentional. In 2009, researchers reported the accidental birth of a single female pup in a batch of 27 clones created from male mouse cells.
Sometimes the surviving population of a species falls so low that scientists will try to clone those animals. Cloning isn’t perfect—it can be tricky and inefficient, and it creates genetically identical individuals whose offspring might be more vulnerable to disease. But it has helped scientists with efforts to bring some species back from the brink of extinction, including black-footed ferrets and Przewalski’s horse.
Cloning an individual can only replicate its genes, so cloning a male animal will create all male offspring, for example. That won’t help much in the hypothetical situation where only male individuals of a species are left.
Ishiuchi has been working on a way to overcome this challenge by altering the chromosomes in cells. Mammals’ DNA is organized in pairs of chromosomes, including one pair of sex chromosomes. These sex chromosomes are typically XX in females and XY in males.
It’s the Y chromosome that makes mammals male. Ishiuchi and his colleagues have developed a CRISPR-based tool to get rid of it. Their approach targets a section of the Y chromosome that plays an important role in ensuring that, each time a cell divides, the “daughter” cells inherit the Y chromosome.
Cutting the Y
When the researchers tested their technique—which they call Y-CUT—in early-stage mouse embryos, they found they were able to eliminate the Y chromosome. Treated XY embryos were transferred to surrogate mice, which gave birth to female pups. The effect can be described as a “sex reversal,” say the researchers.
The female pups had XO chromosomes, which means they had one X chromosome rather than the usual two. But this didn’t seem to affect the animals, which grew up healthy and fertile, say Ishiuchi and Matoba.
In a second experiment, the researchers found they could also use Y-CUT to create female clones from male mice.
A standard approach to cloning involves taking the DNA-containing nucleus of a cell from an adult animal and inserting it into an egg cell that has had its own DNA removed. Under the right conditions, the resulting cell can develop into an animal that is genetically identical to the original donor.
Matoba and his colleagues used a similar method. Once they had a glut of these cloned cells, they treated some with Y-CUT before transferring them to surrogate mice to carry the pregnancies.
This allowed them to create female clones of male mice. The females are genetically identical to the original male, apart from the missing Y chromosome, says Matoba. “It’s like sci-fi,” says Ishiuchi.

In other experiments, the scientists were able to create female clones from male cells that had been cryopreserved—and the cloned males and females could mate to produce healthy pups. This suggests the Y-CUT approach might allow scientists to create female clones from male samples in “frozen zoos” that store cryopreserved cells and tissues from a range of animal species.
It could have uses beyond conservation efforts, too. “This could be used potentially for producing genetically engineered animals,” says Ward. Creating an animal with multiple genetic edits can be time-consuming and expensive; creating male and female clones of that animal could help scientists time and money. Ward also hopes the technique could be a useful tool to study the biology of sex chromosomes.
Complementary techniques
The Y-CUT approach isn’t perfect. For now, it still requires hollowed-out egg cells, which need to come from females of the same species or at least a closely related one. And it won’t be useful for endangered species in which only females survive.
The technique works well in mice, partly because XO female mice are fertile. But while the approach might help some of the 355 endangered and vulnerable species of rodents, other mammals with XO chromosomes tend to experience infertility.
But other new technologies could complement Y-CUT. In 2023, Katsuhiko Hayashi of Osaka University and his colleagues showed they could turn cells taken from male mice into egg cells. This enabled them to create mice with two dads—but the same approach could also provide the hollowed-out egg cells needed for the Y-CUT technique. “It’s a complementary story,” says Matoba.
Ishiuchi is also working on a technique that involves inserting a second X chromosome into cells, which might restore the fertility of the resulting female animals.
In addition, there might be a work-around for situations where scientists have females but need males. A couple of months ago, Sayaka Wakayama of the University of Yamanashi in Japan and colleagues showed they could insert rat chromosomes into mice. That could potentially be used to create XY male embryos, says Novak.
That would be useful in cases like that of the black-footed ferret, he adds. A conservation team recently cloned a female ferret using cells taken from another animal in the 1980s. That female is considered incredibly valuable, says Novak. But females can produce only a few litters in their lifetime. A male clone, which might be able to contribute to dozens of litters in a lifetime, would be “desirable.”
“It’s really exciting to see more diverse tools being developed,” says Novak. “There are so many different scenarios in which they could be used for rare and endangered species.”
Business and technology leaders need no convincing that the time of agentic AI is here. Organizations are rapidly adopting agents, and few executives doubt the technology’s potential to transform work. But many organizations find that realizing the desired return on investment (ROI) from AI hinges on having the right foundation, with inadequate infrastructure and data being major blockers.
Agentic AI places considerable new demands on enterprise data systems. The shift from answering questions to taking actions means AI agents need data from across the enterprise, in all its structured and unstructured forms, and with the right business context. To make decisions and act in real time, agents also need frictionless access to the organization’s operational systems—for example, those storing its supply chain, point-of-sale, or human resources data. Legacy data systems, even those updated just a few years ago, struggle to meet these demands.

As AI agents become embedded more widely in enterprise operations, the need to overcome the restrictions of legacy data systems grows more urgent. If Gartner’s prediction that AI agents will augment or automate 50% of business decisions by 2027 proves correct, organizations must eliminate bottlenecks or risk depriving agents of the data they need to make the right decisions at speed.
This report, based on a survey of 300 data and technology executives, explores how legacy systems are limiting the effectiveness of AI agents in many organizations. It finds that a handful of organizations—the data leaders—are having greater success with agentic AI and experiencing fewer data limitations as a result of legacy systems. These leaders offer a guide to creating the right data environment for agents to flourish and trusted systems to scale.

Key findings from the report include:
Few companies currently provide agentic AI with ample access to enterprise data. Across all the surveyed organizations, AI only has access to an average of 45% of company data. That number falls to 30% or less in organizations categorized as “data laggards”. A select group, however, ensures access to over 70% of their data. These “data leaders” are having greater success with their agents than the rest.
Trust in agent decisions is a reflection of data readiness. Today, only around half of surveyed organizations trust that the decisions their AI agents make are accurate and relevant. By contrast, 100% of the data leaders trust their agents’ decisions, a strong indicator that reliable AI requires a reliable data foundation.
Data leaders find it easier to achieve agent scale and speed. Two-thirds of data laggards say legacy data systems limit AI agent scaling (66%) and prevent agents from making decisions at speed (68%). Having largely overcome legacy data constraints, the leaders have mostly cleared these roadblocks, with just 8% reporting either constraint.
The pressure is on to make data estates agent-ready. Within two years, 100% of respondents plan to be using agentic AI, with 69% expecting to use it widely. Without removing data system constraints, agentic AI will fail to deliver the desired speed and efficiencies it promises.
Data access and context are top priorities. The most important initiative to enable scaling among all respondents is improving access to structured and unstructured data for AI agents. Also high on the list is enhancing data and AI governance with business context. Data leaders are also focusing heavily on the automation of data management.
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.
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.
How we picked 35 of the world’s top young scientists and engineers
On September 8, MIT Technology Review will reveal its 2026 list of Innovators Under 35, recognizing 35 young people from around the world who are doing groundbreaking scientific work and building clever technical fixes for sticky problems.
By finding the top young innovators globally and learning what they’re focused on in their work, we aim to give readers a sense of what advances to expect in the years to come.
As a newsroom, we also use this exercise to help us spot rising talent and get to know some of the best early-career researchers in the fields that we cover.
This year, we received 550 nominations. Find out how we whittled them down to 35 of the young innovators shaping the future of technology, and check out last year’s list.
—Amy Nordrum
How the “censorship-industrial complex” is changing the internet and US policy
—Eileen Guo
I first heard the term “censorship-industrial complex” on April 15, 2025. That’s when I got the tip that a small office in the US State Department, which focused on monitoring and countering foreign disinformation from the likes of Russia, Iran, and China, was facing imminent shutdown—the next day.
And the reason? The office was accused of serving as the department’s central hub in the so-called censorship-industrial complex—a sprawling constellation of government agencies, academics, civil society groups, and Big Tech platforms allegedly conspiring to suppress conservative and populist speech online under the guise of combating disinformation.
I broke the story on April 16. But for me, it was just the start of a deep reporting rabbit hole into an idea that had moved from the fringes of the right-wing internet into the Trump administration.
For more on what the narrative means for the internet, read my story here.
MIT Technology Review Narrated: Montana’s plan to become an experimental medical hub just pushed forward
At the end of July, any biotech company in Montana with an experimental drug gained a clear path to selling it to consumers.
Companies whose drugs have been through preliminary testing—sometimes in as few as 10 healthy people—can pay $12,500 to apply to a newly established review board. Once approved, they can set their own prices and sell the drugs through experimental treatment clinics, the first of which is likely to open around the end of this year.
Montana’s latest right-to-try legislation is unique. While similar laws elsewhere limit access to people with terminal illness, Montana’s system is theoretically open to anyone who gives informed consent and can pay. That includes people desperate for treatments for rare diseases. It also includes those interested in longevity and drugs pitched as preventive therapies.
—Jessica Hamzelou
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 China-linked hackers have hit Taiwan in an “unprecedented” AI attack
They used open-source agents to compromise government websites. (FT $)
+ UK military drones were found sending a signal to China. (Cybernews)
+ Taiwan’s “silicon shield” could be weakening. (MIT Technology Review)
2 Wall Street firms are paying $100,000 a month to get Trump posts first
Trump Media said more than 10 firms have signed up for the service. (CNN)
+ It offers faster access to market-moving posts on Truth Social. (BBC)
+ Trump Media also lost $238 million as crypto holdings fell. (CNBC)
3 ICE plans to give officers gloves that can deliver painful electric shocks
It’s set to spend up to $20 million to buy thousands of the devices. (AP News)
+ A switch turns them from normal gloves into “electrical mode.” (Guardian)
4 Spotify will label AI artists and stop recommending them
The platform is cracking down on fake performers. (Guardian)
+ “AI personas” will appear on artist profiles and track listings. (NYT $)
5 Social media spurred a deadly migrant surge from Morocco to Spain
Disinformation encouraged thousands to attempt the crossing. (NYT $)
6 Anthropic’s Claude is adding watermarks to AI text and images
It could guarantee votes are counted and kept anonymous. (Axios)
7 Drugs that mimic the brain’s wakefulness signal are taking off
Orexin drugs could treat sleep disorders, ADHD and addiction. (Economist $)
+ But psychedelics are falling short in clinical trials. (MIT Technology Review)
8 Cargo thieves have turned to violence to steal AI hardware
Shipments have disappeared after their escorts were attacked. (Wired $)
9 Scientists may have found the elusive glueball, a particle made of force
A Chinese collider has produced the strongest evidence yet. (Science)
10 A firm selling “100% human-written, never AI” research is entirely AI
The reviewers on the Research Gold site are AI-generated. (404 Media)
Quote of the day
“I think the fourth wave of slop will be when there’s no longer any meaningful quality hit in slop, when the average piece of slop is better than the best human in that field.”
—Kevin Roose, a technology columnist at The New York Times, tells the Pivot podcast what the next stage of AI slop will look like.
One More Thing
Are we ready to hand AI agents the keys?
We’re starting to give AI agents real autonomy, and we’re not prepared for what could happen next. Any action that can be captured by text is potentially within the purview of AI agents—which is why they can cause so much mischief.
“The great paradox of agents is that the very thing that makes them useful—that they’re able to accomplish a range of tasks—involves giving away control,” says Iason Gabriel, a senior staff research scientist at Google DeepMind who focuses on AI ethics.
Researchers warn that agents could misinterpret goals, leak sensitive information, fall victim to prompt-injection attacks, and exploit software vulnerabilities at scale. And there’s no foolproof way to guarantee that they’ll act as their developers intend.
Here’s why giving AI agents more autonomy is dangerous.
—Grace Huckins
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 intrepid inventor has built and tested an anti-mosquito electric suit.
+ Musician Hasan Ceylan performs moving covers of modern hits on traditional Turkish instruments from the Ottoman era.
+ As the midterms approach, see whether you could draw electoral boundaries to rig an election at puzzle game Gerrymandle.
+ Photographer John Thomson’s images from 19th-century China are an extraordinary peek into an ancient society that would soon be swept away.
Next month, on September 8, MIT Technology Review will reveal its 2026 list of Innovators Under 35, recognizing 35 young people from around the world who are doing groundbreaking scientific work and building clever technical fixes for sticky problems.
By finding the top young innovators globally and learning what they’re focused on in their work, we aim to give readers a sense of what advances to expect in the years to come. As a newsroom, we also use this exercise to help us spot rising talent and get to know some of the best early-career researchers in the fields that we cover.
The editors of MIT Technology Review published the first Innovators Under 35 list in 1999, and it’s become a beloved annual tradition alongside our lists of 10 Breakthrough Technologies, 10 Climate Tech Companies to Watch, and (new this year) 10 Things That Matter in AI Right Now.
The people we’ve featured through the years have gone on to shape the tech industry and our broader culture, from Lisa Su (featured in 2002), whose stunning turnaround of AMD has built it into one of the top chipmakers worldwide, to Daniel Ek (featured in 2012), who cofounded Spotify (which we described at the time as “a jukebox in the cloud”). Subscribers can browse all the past honorees in this database.
Selecting the 2026 Innovators was a monthslong endeavor. This year, we received 550 nominations, both from staff and via our public nomination process. From those entries, our editors selected 110 semifinalists. We looked for candidates who were setting out to solve big problems or answer pressing scientific questions in their work, and who had already made clear progress toward their goals.
All semifinalists then completed an application to help us learn more about them. They collected reference letters, uploaded videos, and submitted résumés. Forty-four expert judges then helped us evaluate these applications. Some of these judges are former Innovators themselves. Many have returned year after year to volunteer their time, energy, and expertise to the judging process. We’re grateful for their efforts.
In the end, our editors reviewed all of the judges’ scores and comments and selected the 35 winners. Each works in one of four categories: biotechnology, artificial intelligence, computing and robotics, and climate and energy.
“These Innovators represent some of the best aspects of science and technology research—pushing forward bold ideas to improve the future for everyone,” says Costa Samaras, a 2026 judge who is also the director of Carnegie Mellon’s Scott Institute for Energy Innovation.
The 2026 list of Innovators will be available to MIT Technology Review subscribers on our site on September 8. To access the package when it comes out online, you can subscribe now via this link. It will also be published in the September/October issue, which will be available on newsstands worldwide on August 31.
Do you know someone who deserves a spot on next year’s list? Nominations for the 2027 competition will open by early December. Check back then or sign up for our daily newsletter The Download to stay in the loop.
The artificial intelligence-powered function offers contextual responses and is available on desktop, mobile and TV devices.
A new training program is designed to support skilled workers across the U.S. even as community sentiment about data center development wanes.
The system adheres to WhatsApp’s privacy focus, ensuring better user protection without external oversight.
