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Tackling long-haul diseases | MIT Technology Review

Diane Davis

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Tal, who has been obsessed with infectious disease since losing an uncle to HIV/AIDS and a cousin to meningococcal meningitis, wondered what this striking diversity could reveal about our immune response to infection. According to one hypothesis, the wide array of these receptors is the result of an evolutionary arms race between disease-causing microbes and the immune system. Think of the receptor as a lock, and the “Nothing to see here” message as a key. Pathogens might evolve to produce their own chemical mimics of this key, effectively hiding from the immune system in plain sight. In response, the human population has developed a wide range of locks to frustrate any given impostor key. 

Wanting to test this hypothesis, Tal found herself walking the halls of Stanford, asking colleagues, “Who’s got a cool bug?” Someone gave her Borrelia burgdorferi, the bacterium that causes Lyme disease. Previous research from Tal’s collaborator Jenifer Coburn, a microbiologist now at the Medical College of Wisconsin, had established that Lyme bacteria sport a special protein crucial for establishing a lasting infection. Knock this protein out, and the immune system swiftly overwhelms the bugs. The big question, however, was what made this protein so essential. So Tal used what’s known as a high-affinity probe as bait—and caught the Borrelia’s mimic of our “Don’t eat me” signal binding to it. In other words, she confirmed that the bacteria’s sneakyprotein was, as predicted, a close match for a healthy cell’s signal.  

Sex differences in Lyme infection

Until then, Tal says, she had never given Lyme disease much thought. But the more she learned, the more disturbed she grew. Even after timely antibiotic treatment, roughly 10% of all Lyme patients go on to develop chronic symptoms that can include crushing pain, debilitating fatigue, and cognitive changes that make basic tasks a struggle.  

This confocal micrograph depicts Borrelia burgdorferi bacteria, which cause Lyme disease when transmitted to humans by ticks. These Borrelia were genetically engineered to produce a green fluorescent protein.

COURTESY OF THE TAL RESEARCH GROUP

Perhaps even more alarming than the disease has been the medical community’s response to it. “I realized that there’s this public health debacle around Lyme, and it’s, for lack of a better word, obscene,” Tal says. Chronic Lyme patients skew female, and for decades, clinicians have dismissed their symptoms as signs of mental illness. The medical establishment has “done nothing but call them crazy,” Tal says, “instead of admitting that they just don’t understand what’s going on.” 

Today, there is no objective way to diagnose chronic Lyme, and no medically accepted therapy. For some patients, lengthy treatments with high doses of antibiotics can ease symptoms, but these come with their own serious risks. (They can, for example, damage the microbiome, leading to significant negative effects on health.) And because the antibiotic used currently only prevents bacteria from replicating, Tal notes, it’s up to the immune system to actually kill off the invaders. If immune cells can’t tell friend from foe, the utility of antibiotics may be limited. 

Chronic Lyme patients skew female, and for decades, the medical establishment has “done nothing but call them crazy,” Tal says, “instead of admitting that they just don’t understand what’s going on.”

For Tal, these revelations were electrifying. She dove into the immunology of Lyme disease, focusing in particular on sex differences. In one mouse experiment, she discovered that Lyme bacteria “completely disfigured” the uterus. Yet after delving through decades of Lyme research, she could find only one other study that even documented uterine infection. 

This shortfall mirrors larger problems in medical research. “We’ve let men dictate the direction of research funding for so long,” Tal says. Traditionally, studies focused on male subjects, and a 1977 FDA policy barred women from participating in most clinical trials in the US in the wake of birth defects caused by thalidomide. It wasn’t until 1993 that federal law required studies to include women and minorities. This, coupled with other sex- and gender-based medical biases, means that many female-dominated diseases remain under-researched. “So much of this research is being done on males, male mice—male, male, male,” Tal says. “And I’m like, no.” 

Tal suspects that the sex disparities seen in chronic Lyme and other pathogen-­triggered chronic diseases might come down to the fact that men mount a more robust response to acute infection. This no-holds-barred approach is risky—“Your immune system has the power to kill you,” she notes—but it may mean that men, on average, can kill off more viruses or bacteria in the critical first week of infection. After that window closes, the immune system largely settles back down, Tal says. Pathogens that escaped the initial blitz could take up long-term residence in the body, potentially causing persistent symptoms. And women have a higher chance of chronic illness.

Technology & Innovation

This self-driving startup is using generative AI to predict traffic

Diane Davis

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A diptych view of the same image via camera and LiDAR.

While autonomous driving has long relied on machine learning to plan routes and detect objects, some companies and researchers are now betting that generative AI — models that take in data of their surroundings and generate predictions — will help bring autonomy to the next stage. Wayve, a Waabi competitor, released a comparable model last year that is trained on the video that its vehicles collect. 

Waabi’s model works in a similar way to image or video generators like OpenAI’s DALL-E and Sora. It takes point clouds of lidar data, which visualize a 3D map of the car’s surroundings, and breaks them into chunks, similar to how image generators break photos into pixels. Based on its training data, Copilot4D then predicts how all points of lidar data will move. Doing this continuously allows it to generate predictions 5-10 seconds into the future.

Waabi is one of a handful of autonomous driving companies, including competitors Wayve and Ghost, that describe their approach as “AI-first.” To Urtasun, that means designing a system that learns from data, rather than one that must be taught reactions to specific situations. The cohort is betting their methods might require fewer hours of road-testing self-driving cars, a charged topic following an October 2023 accident where a Cruise robotaxi dragged a pedestrian in San Francisco. 

Waabi is different from its competitors in building a generative model for lidar, rather than cameras. 

“If you want to be a Level 4 player, lidar is a must,” says Urtasun, referring to the automation level where the car does not require the attention of a human to drive safely. Cameras do a good job of showing what the car is seeing, but they’re not as adept at measuring distances or understanding the geometry of the car’s surroundings, she says.

Though Waabi’s model can generate videos showing what a car will see through its lidar sensors, those videos will not be used as training in the company’s driving simulator that it uses to build and test its driving model. That’s to ensure any hallucinations arising from Copilot4D do not get taught in the simulator.

The underlying technology is not new, says Bernard Adam Lange, a PhD student at Stanford who has built and researched similar models, but it’s the first time he’s seen a generative lidar model leave the confines of a research lab and be scaled up for commercial use. A model like this would generally help make the “brain” of any autonomous vehicle able to reason more quickly and accurately, he says.

“It is the scale that is transformative,” he says. “The hope is that these models can be utilized in downstream tasks” like detecting objects and predicting where people or things might move next.

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Technology & Innovation

Methane leaks in the US are worse than we thought

Diane Davis

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Methane leaks in the US are worse than we thought

Methane emissions are responsible for nearly a third of the total warming the planet has experienced so far. While there are natural sources of the greenhouse gas, including wetlands, human activities like agriculture and fossil-fuel production have dumped millions of metric tons of additional methane into the atmosphere. The concentration of methane has more than doubled over the past 200 years. But there are still large uncertainties about where, exactly, emissions are coming from.

Answering these questions is a challenging but crucial first step to cutting emissions and addressing climate change. To do so, researchers are using tools ranging from satellites like the recently launched MethaneSAT to ground and aerial surveys. 

The US Environmental Protection Agency estimates that roughly 1% of oil and gas produced winds up leaking into the atmosphere as methane pollution. But survey after survey has suggested that the official numbers underestimate the true extent of the methane problem.  

For the sites examined in the new study, “methane emissions appear to be higher than government estimates, on average,” says Evan Sherwin, a research scientist at Lawrence Berkeley National Laboratory, who conducted the analysis as a postdoctoral fellow at Stanford University.  

The data Sherwin used comes from one of the largest surveys of US fossil-fuel production sites to date. Starting in 2018, Kairos Aerospace and the Carbon Mapper Project mapped six major oil- and gas-producing regions, which together account for about 50% of onshore oil production and about 30% of gas production. Planes flying overhead gathered nearly 1 million measurements of well sites using spectrometers, which can detect methane using specific wavelengths of light. 

Sherwin et al., Nature

Here’s where things get complicated. Methane sources in oil and gas production come in all shapes and sizes. Some small wells slowly leak the gas at a rate of roughly one kilogram of methane an hour. Other sources are significantly bigger, emitting hundreds or even thousands of kilograms per hour, but these leaks may last for only a short period.

The planes used in these surveys detect mostly the largest leaks, above roughly 100 kilograms per hour (though they catch smaller ones sometimes, down to around one-tenth that size, Sherwin says). Combining measurements of these large leak sites with modeling to estimate smaller sources, researchers estimated that the larger leaks account for an outsize proportion of emissions. In many cases, around 1% of well sites can make up over half the total methane emissions, Sherwin says.

But some scientists say that this and other studies are still limited by the measurement tools available. “This is an indication of the current technology limits,” says Ritesh Gautam, a lead senior scientist at the Environmental Defense Fund.

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Technology & Innovation

The Download: What social media can teach us about AI

Diane Davis

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The Download: What social media can teach us about AI

June 2023

Astronomy should, in principle, be a welcoming field for blind researchers. But across the board, science is full of charts, graphs, databases, and images that are designed to be seen.

So researcher Sarah Kane, who is legally blind, was thrilled three years ago when she encountered a technology known as sonification, designed to transform information into sound. Since then she’s been working with a project called Astronify, which presents astronomical information in audio form. 

For millions of blind and visually impaired people, sonification could be transformative—opening access to education, to once unimaginable careers, and even to the secrets of the universe. Read the full story.

—Corey S. Powell

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

+ It’s time to get into metal detecting (no really, it is!)
+ Meanwhile, over on Mars
+ A couple in the UK decided to get married on a moving train, because why not?
+ Even giant manta rays need a little TLC every now and again.


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