James' World 2

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A small, unassuming fern-like plant has something massive lurking within: the largest genome ever discovered, outstripping the human genome by more than 50 times.

The plant (Tmesipteris oblanceolata) contains a whopping 160 billion base pairs, the units that make up a strand of DNA. That’s 11 billion more than the previous record holder, the flowering plant Paris japonica, and 30 billion more than the marbled lungfish (Protopterus aethiopicus), which has the largest animal genome. The findings were published today in iScience.

Study co-author Jaume Pellicer, an evolutionary biologist at the Botanical Institute of Barcelona in Spain who also co-discovered P. japonica’s gargantuan genome, had thought that the earlier discovery was close to the genome size limit. “But the evidence has once again surpassed our expectations,” he says.

Genomic giants

The world’s genomic champion, which is native to New Caledonia and neighboring archipelagos in the South Pacific, is a species of plant called a fork fern. Its colossal number of base pairs raises questions as to how the plant manages its genetic material. Only a small proportion of DNA is made of protein-coding genes, leading study co-author Ilia Leitch, an evolutionary biologist at London’s Royal Botanic Gardens, Kew, to wonder how the plant’s cellular machinery accesses those bits of the genome “amongst this huge morass of DNA. It’s like trying to find a few books with the instructions for how to survive in a library of millions of books — it’s just ridiculous.”

There’s also the question of how and why an organism evolved to have so many base pairs. Generally, having more base pairs leads to higher demand for the minerals that comprise DNA and for energy to duplicate the genome with every cell division, Leitch says. But if the organism lives in a relatively stable environment with little competition, a gargantuan genome might not come with a high cost, she adds.

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Welcome to The Twilight Zone. Not some ­science fiction fantasy, but a real place where up to 90 percent of us spend the majority of our waking lives.

We have built a world that hides us from daylight in dimly-lit offices, and then illuminates the night. We talk of burning the candle at both ends. The midnight oil. There not being enough hours in the day. We depend on night shift workers to mend our roads and staff our hospitals.

Small wonder, then, that a third of us are ­struggling to sleep. Finally, though, the degree to which we’ve been playing a dangerous game with our biology is being understood. 

Until recently, sleep science was ­often synonymous with circadian science, but the latter is now emerging out of the shadows. The 2017 Nobel Prize in Physiology or Medicine was awarded to three scientists in the field of circadian rhythm. As a result of theirs and others’ breakthroughs, we’re waking up to the power of the body’s internal biological clock. 

Like plants and animals, we too are preprogrammed to do certain activities at specific times of the day. Our ­circadian rhythms are controlled by circadian clocks, present in every organ and every cell, and these clocks tell our brain when to sleep, tell our gut when to digest our food optimally, tell our heart to pump more blood, and when to slow down.

The health risks associated with a disrupted circadian rhythm

Ignore them at your peril. In the short term, you may feel lethargic, ­suffer insomnia, and weight gain. One report showed that 57 percent of junior doctors have had a crash, or near miss, on the way back from a night shift. 

And the long-term effects? Chronic disease, such as type 2 diabetes, Alzheimer’s, and cancer, have been linked to disruption of our circadian rhythm. The impact of disrupting our circadian sleep rhythm is such that night-shift workers have a higher mortality rate. The 24-hour society comes with a high price tag.

For Dr Satchin Panda, one of the scientists at the forefront of the circadian science revolution, the challenge for humanity is to rethink the world which we have built over the past 100 years. 

“It’s an asbestos moment,” he says. “We figured out asbestos was harmful in the Seventies, and we’re still removing it now. We’re going through that moment with circadian disruption, but it will take a generation to implement change.”

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China has landed on the moon’s mysterious far side — again.

The robotic Chang’e 6 mission touched down inside Apollo Crater, within the giant South Pole-Aitken basin, at 6:23 a.m. Beijing Time on Sunday (June 2) , according to Chinese space officials. It was 6:23 p.m. EDT (2223 GMT) on June 1 at the time of the landing. The probe “successfully landed in the pre-selected area,” China’s space agency said.

The China National Space Administration (CNSA) now has two far-side landings under its belt — this one and Chang’e 4, which dropped a lander-rover combo onto the gray dirt in January 2019. No other country has done it once.

And Chang’e 6 will make further history for China, if all goes according to plan: The mission aims to scoop up samples and send them back to Earth, giving researchers their first-ever up-close looks at material from this part of the moon.

“The Chang’e-6 mission is the first human sampling and return mission from the far side of the moon,” CNSA officials said in a translated statement. (To be clear: Chang’e 6 is a robotic, not crewed, mission.) “It involves many engineering innovations, high risks, and great difficulty.”

Sampling a new environment

Chang’e 6 launched on May 3 with a bold and unprecedented task: haul home samples from the moon’s far side, which always faces away from us. (The moon is tidally locked to Earth, completing one rotation on its axis in roughly the same amount of time it takes to orbit our planet. So observers here on Earth always see the same side of our natural satellite.)

Every lunar surface mission before Chang’e 4 targeted the near side, largely because that area is easier to explore. It’s harder to communicate with robots operating on the far side, for example; doing so generally requires special relay orbiters, which China launched ahead of both Chang’e 4 and Chang’e 6. China’s newest moon relay satellite, called Queqiao-2, aided the Chang’e 6 landing, CNSA officials said.

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Of course, the camera buffs are all over it, but serious and casual creators from other genres have paused their usual programming to rave about how it transcends amateur vlogging pursuits, whether you’re filming a wedding or self-shooting a scene for a Sundance-hopeful short film.

Some of us at The Verge are excited, too: Vjeran liked it enough to call it his favorite gadget of 2023, and Sean just bought one after using it to elevate his Today I’m Toying With videos.

I felt tingles about the $519 Osmo Pocket 3 when DJI first announced it, but it wasn’t until I purchased a Creator Combo that I fully understood the hype. The video quality often comes close to my full-frame Sony mirrorless (although I can’t get all the same shots) and is very noticeably better than my phone.

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Kris Hansen had worked as a chemist at the 3M Corporation for about a year when her boss, an affable senior scientist named Jim Johnson, gave her a strange assignment. 3M had invented Scotch Tape and Post-it notes; it sold everything from sandpaper to kitchen sponges. But on this day, in 1997, Johnson wanted Hansen to test human blood for chemical contamination.

Several of 3M’s most successful products contained man-made compounds called fluorochemicals. In a spray called Scotchgard, fluorochemicals protected leather and fabric from stains. In a coating known as Scotchban, they prevented food packaging from getting soggy. In a soapy foam used by firefighters, they helped extinguish jet-fuel fires. Johnson explained to Hansen that one of the company’s fluorochemicals, PFOS—short for perfluorooctanesulfonic acid—often found its way into the bodies of 3M factory workers. Although he said that they were unharmed, he had recently hired an outside lab to measure the levels in their blood. The lab had just reported something odd, however. For the sake of comparison, it had tested blood samples from the American Red Cross, which came from the general population and should have been free of fluorochemicals. Instead, it kept finding a contaminant in the blood.

Johnson asked Hansen to figure out whether the lab had made a mistake. Detecting trace levels of chemicals was her specialty: she had recently written a doctoral dissertation about tiny particles in the atmosphere. Hansen’s team of lab technicians and junior scientists fetched a blood sample from a lab-supply company and prepped it for analysis. Then Hansen switched on an oven-size box known as a mass spectrometer, which weighs molecules so that scientists can identify them.

As the lab equipment hummed around her, Hansen loaded a sample into the machine. A graph appeared on the mass spectrometer’s display; it suggested that there was a compound in the blood that could be PFOS. That’s weird, Hansen thought. Why would a chemical produced by 3M show up in people who had never worked for the company?

Hansen didn’t want to share her results until she was certain that they were correct, so she and her team spent several weeks analyzing more blood, often in time-consuming overnight tests. All the samples appeared to be contaminated. When Hansen used a more precise method, liquid chromatography, the results left little doubt that the chemical in the Red Cross blood was PFOS.

Hansen now felt obligated to update her boss. Johnson was a towering, bearded man, and she liked him: he seemed to trust her expertise, and he found something to laugh about in most conversations. But, when she shared her findings, his response was cryptic. “This changes everything,” he said. Before she could ask him what he meant, he went into his office and closed the door.

This was not the first time that Hansen had found a chemical where it didn’t belong. A wiry woman who grew up skiing competitively, Hansen had always liked to spend time outdoors; for her chemistry thesis at Williams College, she had kayaked around the former site of an electric company on the Hoosic River, collecting crayfish and testing them for industrial pollutants called polychlorinated biphenyls (PCBs). Her research, which showed that a drainage ditch at the site was leaking the chemicals, prompted a news story and contributed to a cleanup effort overseen by the Massachusetts Department of Environmental Protection. At 3M, Hansen assumed that her bosses would respond to her findings with the same kind of diligence and care.

Hansen stayed near Johnson’s office for the rest of the day, anxiously waiting for him to react to her research. He never did. In the days that followed, Hansen sensed that Johnson had notified some of his superiors. She remembers his boss, Dale Bacon, a paunchy fellow with gray hair, stopping by her desk and suggesting that she had made a mistake. “I don’t think so,” she told him. In subsequent weeks, Hansen and her team ordered fresh blood samples from every supplier that 3M worked with. Each of the samples tested positive for PFOS.

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Bird flu has been behaving very strangely lately. A strain of the highly pathogenic avian influenza virus (H5N1) has been spreading in dairy cows in at least nine U.S. states. Infected cows have very high levels of virus in their milk, and early reports indicate that it is being spread by contaminated milking equipment, although other methods of transmission are also possible. Several cats that drank raw milk from infected cows developed neurological symptoms and died. Pasteurizing milk appears to effectively neutralize the H5N1 virus.

In recent weeks, three human infections with the virus have been confirmed—all in dairy workers who had contact with sick cows. All three developed symptoms of eye infections known as conjunctivitis. The latest case, reported in Michigan this week, also involved respiratory symptoms more typical of a flu infection. The workers were most likely exposed to the virus in contaminated milk—by getting it on their hands and then touching their eyes, for example, or via milk droplets (or even microscopic particles called aerosols) from a cow’s udder or milking equipment.

“It is really surprising how widespread this thing got over a few months’ time and how this virus seems to be spreading through the milking machines from udder to udder,” says Ron Fouchier, deputy head of the viroscience department at Erasmus University Medical Center Rotterdam in the Netherlands. “This is a completely new situation for all of us, and it’s surprising and a little bit worrying because of the enormous amounts of virus that can be in raw milk.”

But why is H5N1 causing eye infections in humans? And is there a risk the virus could spread more widely and potentially cause a pandemic?

In fact, cases of avian flu causing conjunctivitis are not that rare. There was a large outbreak of H7N7 avian flu in poultry in the Netherlands in 2003, which led to 89 confirmed human cases. Of these, 78 people had conjunctivitis; five had both conjunctivitis and flulike illness and two had only flulike illness. One person developed pneumonia and respiratory distress and died, according to a 2004 study by Fouchier and his colleagues.

“We’ve seen this [conjunctivitis] also before with … H7N7 viruses quite a lot and a little bit less with H5 bird flu viruses,” Fouchier says. (The latter is the type now spreading in cows.) “But we know that these bird flu viruses can cause conjunctivitis rather easily.”

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Matthew Ludak/The Washington Post via Getty Images

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When Google announced it was rolling out its artificial-intelligence-powered search feature earlier this month, the company promised that “Google will do the googling for you.” The new feature, called AI Overviews, provides brief, AI-generated summaries highlighting key information and links on top of search results.

Unfortunately, AI systems are inherently unreliable. Within days of AI Overviews’ release in the US, users were sharing examples of responses that were strange at best. It suggested that users add glue to pizza or eat at least one small rock a day, and that former US president Andrew Johnson earned university degrees between 1947 and 2012, despite dying in 1875. 

On Thursday, Liz Reid, head of Google Search, announced that the company has been making technical improvements to the system to make it less likely to generate incorrect answers, including better detection mechanisms for nonsensical queries. It is also limiting the inclusion of satirical, humorous, and user-generated content in responses, since such material could result in misleading advice.

But why is AI Overviews returning unreliable, potentially dangerous information? And what, if anything, can be done to fix it?

How does AI Overviews work?

In order to understand why AI-powered search engines get things wrong, we need to look at how they’ve been optimized to work. We know that AI Overviews uses a new generative AI model in Gemini, Google’s family of large language models (LLMs), that’s been customized for Google Search. That model has been integrated with Google’s core web ranking systems and designed to pull out relevant results from its index of websites.

Most LLMs simply predict the next word (or token) in a sequence, which makes them appear fluent but also leaves them prone to making things up. They have no ground truth to rely on, but instead choose each word purely on the basis of a statistical calculation. That leads to hallucinations. It’s likely that the Gemini model in AI Overviews gets around this by using an AI technique called retrieval-augmented generation (RAG), which allows an LLM to check specific sources outside of the data it’s been trained on, such as certain web pages, says Chirag Shah, a professor at the University of Washington who specializes in online search.

Once a user enters a query, it’s checked against the documents that make up the system’s information sources, and a response is generated. Because the system is able to match the original query to specific parts of web pages, it’s able to cite where it drew its answer from—something normal LLMs cannot do.

One major upside of RAG is that the responses it generates to a user’s queries should be more up-to-date, more factually accurate, and more relevant than those from a typical model that just generates an answer based on its training data. The technique is often used to try to prevent LLMs from hallucinating. (A Google spokesperson would not confirm whether AI Overviews uses RAG.)

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Sarah Rogers/MITTR

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