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Looking to space to cure osteoarthritis

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knee research image


In 1976, Alan Grodzinsky ’71, ScD ’74, was feeling a little frustrated. 

He had spent two years teaching a basic course on semiconductor physics and circuits in MIT’s Department of Electrical Engineering and Computer Science, learning the material in the fast-moving field as he went along. That didn’t leave him any time for research. Then a golden opportunity arose.

With the help of the late Irving London, founder of the Harvard-MIT Program in Health Sciences and Technology, Grodzinsky won a sabbatical at Boston Children’s Hospital under the mentorship of the late Mel Glimcher, chief of orthopedic surgery and a pioneering researcher on the biology of human bones and collagen.

Glimcher wanted to start a research project on cartilage, the tough matrix of fibers that lines the joints, and on osteoarthritis, the chronic, painful disease that breaks that cartilage down.

It was a perfect fit for the 29-year-old Grodzinsky, who had earned his ScD studying the electrical properties of collagen, one of the constituents of cartilage. By year’s end, he was on the path he has followed ever since: trying to find effective treatments for osteoarthritis, the leading cause of chronic pain and disability around the world. It affects more than 30 million Americans, and hundreds of millions globally.

“It’s a huge financial burden and disability burden. And while it’s not fatal, it certainly contributes to loss of quality of life,” says Joseph Buckwalter, an orthopedic surgeon and osteoarthritis expert based in Iowa, who has known Grodzinsky for decades. “The costs of total joint replacements, mainly knees and hips, is one of our major health expenditures.”

No plan for pain

The US Food and Drug Administration has not approved any disease-modifying medications for osteoarthritis—drugs that treat the underlying condition rather than just the symptoms. The most sufferers can hope for, Grodzinsky says, are pain relievers like Motrin, occasional injections of steroids, and eventually joint replacement surgery. More than a million knee and hip replacements are done in the US each year, and the number is expected to soar as the population ages.

While older people are most susceptible to osteoarthritis, Grodzinsky has focused much of his research on younger people, particularly female athletes, who often develop the condition after knee injuries.

Tens of thousands of young women suffer injuries to the anterior cruciate ligaments of their knees each year. “When I teach my course at MIT related to biomechanics,” Grodzinsky says, “I ask about ACL injuries, and just as many hands go up today as in the past. I taught a Harvard Medical School course recently, and of the 20 students in the class, four women had suffered ACL tears, and one was on her third surgery.”

Doctors can fix these tears, he says, but both men and women who suffer joint injuries are still at high risk of developing osteoarthritis in subsequent years. And while knee replacements can counteract the effects of osteoarthritis, doctors are reluctant to perform such surgery on younger people because it will probably need to be repeated after the first artificial joint wears out.

A knee implant can last years, says Buckwalter, but “I would have nightmares doing it in someone under 40, because the odds are almost overwhelming that they’ll need another one.”

Nanoparticle Rx

Researchers have identified existing drugs that might alleviate the onset of osteoarthritis, but they are hampered by the fact that cartilage does not have a natural blood supply, Grodzinsky says. When doctors inject a steroid in the knee joint to reduce inflammation, the body clears most of the medication before it can get into the cartilage.

To tackle this problem, his lab has pioneered research involving nanoparticles, human cadaver knees, and even missions to the International Space Station.

Six days after an arthritic knee was treated with nanoparticles containing insulin-like growth factor 1 (blue), the particles have penetrated through the cartilage of the knee joint.

BRETT GEIGER AND JEFF WYCKOFF

Starting with that sabbatical more than four decades ago, Grodzinsky learned a vital fact about cartilage. While the tissue fibers themselves provide some of the support for our joints, much of its strength comes from its electrostatic properties. “It turns out about half the compressive mechanical stiffness of our cartilage is due to electrostatic repulsive interactions between negatively charged sugar chains,” he says.

This negatively charged tissue matrix also offers a way to deliver drugs directly into the tissue: by loading them into positively charged nanoparticles. Grodzinsky’s team has been able to show in human cadaver knee cartilage that such particles can counteract the early inflammation and damage caused by injuries. 

The initial nanoparticle work was started several years ago by Grodzinsky’s former doctoral student Ambika Bajpayee, MNG ’07, PhD ’15, now a professor at Northeastern University. Bajpayee then collaborated with Paula Hammond, head of MIT’s chemical engineering department, who had pioneered the use of nanoparticles to deliver drugs to cancerous tumors. 

In the Grodzinsky lab, the drug-­containing nanoparticles are injected into animals’ joints, just as they would be in human patients, he says, and “once they’re inside, if they’re used at the right concentration, they can stay inside for many weeks,” nestled in the fibrous matrix. 

The group has concentrated on delivering two medications that are already approved for human use. 

One is the anti-inflammatory dexamethasone, which also has been used successfully to treat breathing problems in some hospitalized covid-19 patients. The other is insulin-like growth factor 1 (IGF-1), a hormone that promotes growth of bone and cartilage tissue and has been used in children born smaller than normal.

The dexamethasone lessens the breakdown of cartilage after an injury, Grodzinsky says, while IGF-1 can promote tissue repair.

Animal studies using IGF-1 have been done in a collaboration with Hammond, and Grodzinsky’s lab has extended this experimental treatment to human tissues as well, relying on samples from dead people. So far, the lab has been able to obtain pieces of knee bone, cartilage, and synovial joint capsule from 45 donors, says Garima Dwivedi, a postdoctoral researcher in the lab. 

Dwivedi and her colleagues put the samples in wells built into plastic plates and keep them metabolically active. Then they apply a mechanical impact that mimics what happens in a knee injury. That releases inflammatory molecules known as cytokines and begins a process similar to what happens in osteoarthritis.

Outer space

In this work, the researchers put the nanoparticles in the culture medium that bathes the tissue samples—a technique they could also use in future experiments on the space station, which has become a magnet for researchers studying diseases of aging.

Scientists have known for years that human tissues age more quickly in low Earth orbit than on Earth, though the reasons are somewhat mysterious. One analysis estimated that astronauts’ muscles and bones atrophy 10 times faster in microgravity. 

Figuring out how to repair joint damage may be crucial for future long- term space missions.

With funding from the NIH and NASA, Grodzinsky’s lab sent samples of knee cartilage-bone plugs and synovium tissues to the ISS in 2019 and 2020. They hoped to determine whether osteoarthritis-like disease could be initiated “in a dish” to simulate what happens in humans after a knee injury—using the microgravity environment to explore and eliminate the mechanical processes at work—and to try treating it with dexamethasone and IGF-1. 

Preliminary results have been encouraging, he says. On the most recent trip to the ISS, the lab found that both drugs reduced damage in the many of the cartilage samples. 

“Since most researchers these days stress that there will not likely be a single magic bullet, we believe the ability to test combinations of drugs in vitro is an important step forward,” Grodzinsky says.

The work in microgravity may also pay dividends for future space missions, Dwivedi says. Astronauts, who exercise intensively in space to counteract the atrophy that muscles and bones tend to suffer in weightless conditions, are three times more likely to get impact injuries than people on Earth, she says, so figuring out how to repair joint damage may be crucial for future long-term space missions.

Compassionate mentorship

Grodzinsky always seemed destined to find a home at MIT.

Growing up on Long Island, where he attended public schools in the booming postwar suburb of East Meadow, he sometimes visited his older brother, Stephen Grodzinsky ’65, SM ’67, at Burton House. He remembers thinking, “This looks great to me.”

He went on to get his ScD under the late James Melcher, director of the school’s Laboratory for Electromagnetic and Electronic Systems. But soon a recession hit, and the only positions he was offered were a postdoc in icy Saskatchewan and an assistant professorship in music and engineering in Brazil. His mentors—including Ioannis Yannas, best known for inventing artificial skin—encouraged him to stick around, offering him a teaching position in electrical engineering. He has been at the Institute ever since.

In 1995, MIT set up the Center for Biomedical Engineering to advance research in what was then a new field. Three years later, Grodzinsky was named to his current post as its director. At that time, his faculty affiliation changed to the newly formed Department of Biological Engineering, with joint appointments in EECS and mechanical engineering.

Grodzinsky believes any research success he has achieved has been the direct result of the “tremendous PhD students and postdocs we were able to get at MIT.” They in turn have prospered under his compassionate mentorship.

“It has been a pleasure to work with him, primarily because he gives you a lot of independence for your own ideas to develop,” says postdoc Dwivedi. “And no matter who you are and what stage of career you’re in, he listens to you with utmost attention and respect.”

Professor Gropdzinsky and wife Gail
Grodzinsky and his wife, Gail, now a pediatric neuropsychologist at Boston Children’s Hospital, met playing chamber music.

WEBB CHAPPELL

She also appreciates his personal support. When her parents in India contracted covid in April, he “gave me completely free time to help take care of them,” she says. 

Grodzinsky himself has managed to avoid osteoarthritis, even though, at age 74, he is in a prime risk category for the disease. 

Maybe, he muses, it’s because his avocation as a musician has kept him limber. After years of piano lessons at the Third Street Music School Settlement in New York, he became the principal violist of the MIT Symphony Orchestra as an undergraduate. He also played in freelance string quartets after finishing his ScD and met his wife, Gail, playing chamber music.

After officially setting foot on campus as a student at age 18, he says with a smile, “somehow, I’ve never been able to find a way to leave.”

Tech

Why I became a TechTrekker

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group jumps into the air with snowy mountains in the background


My senior spring in high school, I decided to defer my MIT enrollment by a year. I had always planned to take a gap year, but after receiving the silver tube in the mail and seeing all my college-bound friends plan out their classes and dorm decor, I got cold feet. Every time I mentioned my plans, I was met with questions like “But what about school?” and “MIT is cool with this?”

Yeah. MIT totally is. Postponing your MIT start date is as simple as clicking a checkbox. 

Sofia Pronina (right) was among those who hiked to the Katla Glacier during this year’s TechTrek to Iceland.

COURTESY PHOTO

Now, having finished my first year of classes, I’m really grateful that I stuck with my decision to delay MIT, as I realized that having a full year of unstructured time is a gift. I could let my creative juices run. Pick up hobbies for fun. Do cool things like work at an AI startup and teach myself how to create latte art. My favorite part of the year, however, was backpacking across Europe. I traveled through Austria, Slovakia, Russia, Spain, France, the UK, Greece, Italy, Germany, Poland, Romania, and Hungary. 

Moreover, despite my fear that I’d be losing a valuable year, traveling turned out to be the most productive thing I could have done with my time. I got to explore different cultures, meet new people from all over the world, and gain unique perspectives that I couldn’t have gotten otherwise. My travels throughout Europe allowed me to leave my comfort zone and expand my understanding of the greater human experience. 

“In Iceland there’s less focus on hustle culture, and this relaxed approach to work-life balance ends up fostering creativity. This was a wild revelation to a bunch of MIT students.”

When I became a full-time student last fall, I realized that StartLabs, the premier undergraduate entrepreneurship club on campus, gives MIT undergrads a similar opportunity to expand their horizons and experience new things. I immediately signed up. At StartLabs, we host fireside chats and ideathons throughout the year. But our flagship event is our annual TechTrek over spring break. In previous years, StartLabs has gone on TechTrek trips to Germany, Switzerland, and Israel. On these fully funded trips, StartLabs members have visited and collaborated with industry leaders, incubators, startups, and academic institutions. They take these treks both to connect with the global startup sphere and to build closer relationships within the club itself.

Most important, however, the process of organizing the TechTrek is itself an expedited introduction to entrepreneurship. The trip is entirely planned by StartLabs members; we figure out travel logistics, find sponsors, and then discover ways to optimize our funding. 

two students soaking in a hot spring in Iceland

COURTESY PHOTO

In organizing this year’s trip to Iceland, we had to learn how to delegate roles to all the planners and how to maintain morale when making this trip a reality seemed to be an impossible task. We woke up extra early to take 6 a.m. calls with Icelandic founders and sponsors. We came up with options for different levels of sponsorship, used pattern recognition to deduce the email addresses of hundreds of potential contacts at organizations we wanted to visit, and all got scrappy with utilizing our LinkedIn connections.

And as any good entrepreneur must, we had to learn how to be lean and maximize our resources. To stretch our food budget, we planned all our incubator and company visits around lunchtime in hopes of getting fed, played human Tetris as we fit 16 people into a six-person Airbnb, and emailed grocery stores to get their nearly expired foods for a discount. We even made a deal with the local bus company to give us free tickets in exchange for a story post on our Instagram account. 

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The Download: spying keyboard software, and why boring AI is best

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🧠


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 ubiquitous keyboard software puts hundreds of millions of Chinese users at risk

For millions of Chinese people, the first software they download onto devices is always the same: a keyboard app. Yet few of them are aware that it may make everything they type vulnerable to spying eyes. 

QWERTY keyboards are inefficient as many Chinese characters share the same latinized spelling. As a result, many switch to smart, localized keyboard apps to save time and frustration. Today, over 800 million Chinese people use third-party keyboard apps on their PCs, laptops, and mobile phones. 

But a recent report by the Citizen Lab, a University of Toronto–affiliated research group, revealed that Sogou, one of the most popular Chinese keyboard apps, had a massive security loophole. Read the full story. 

—Zeyi Yang

Why we should all be rooting for boring AI

Earlier this month, the US Department of Defense announced it is setting up a Generative AI Task Force, aimed at “analyzing and integrating” AI tools such as large language models across the department. It hopes they could improve intelligence and operational planning. 

But those might not be the right use cases, writes our senior AI reporter Melissa Heikkila. Generative AI tools, such as language models, are glitchy and unpredictable, and they make things up. They also have massive security vulnerabilities, privacy problems, and deeply ingrained biases. 

Applying these technologies in high-stakes settings could lead to deadly accidents where it’s unclear who or what should be held responsible, or even why the problem occurred. The DoD’s best bet is to apply generative AI to more mundane things like Excel, email, or word processing. Read the full story. 

This story is from The Algorithm, Melissa’s weekly newsletter giving you the inside track on all things AI. Sign up to receive it in your inbox every Monday.

The ice cores that will let us look 1.5 million years into the past

To better understand the role atmospheric carbon dioxide plays in Earth’s climate cycles, scientists have long turned to ice cores drilled in Antarctica, where snow layers accumulate and compact over hundreds of thousands of years, trapping samples of ancient air in a lattice of bubbles that serve as tiny time capsules. 

By analyzing those cores, scientists can connect greenhouse-gas concentrations with temperatures going back 800,000 years. Now, a new European-led initiative hopes to eventually retrieve the oldest core yet, dating back 1.5 million years. But that impressive feat is still only the first step. Once they’ve done that, they’ll have to figure out how they’re going to extract the air from the ice. Read the full story.

—Christian Elliott

This story is from the latest edition of our print magazine, set to go live tomorrow. Subscribe today for as low as $8/month to ensure you receive full access to the new Ethics issue and in-depth stories on experimental drugs, AI assisted warfare, microfinance, and more.

The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 How AI got dragged into the culture wars
Fears about ‘woke’ AI fundamentally misunderstand how it works. Yet they’re gaining traction. (The Guardian
+ Why it’s impossible to build an unbiased AI language model. (MIT Technology Review)
 
2 Researchers are racing to understand a new coronavirus variant 
It’s unlikely to be cause for concern, but it shows this virus still has plenty of tricks up its sleeve. (Nature)
Covid hasn’t entirely gone away—here’s where we stand. (MIT Technology Review)
+ Why we can’t afford to stop monitoring it. (Ars Technica)
 
3 How Hilary became such a monster storm
Much of it is down to unusually hot sea surface temperatures. (Wired $)
+ The era of simultaneous climate disasters is here to stay. (Axios)
People are donning cooling vests so they can work through the heat. (Wired $)
 
4 Brain privacy is set to become important 
Scientists are getting better at decoding our brain data. It’s surely only a matter of time before others want a peek. (The Atlantic $)
How your brain data could be used against you. (MIT Technology Review)
 
5 How Nvidia built such a big competitive advantage in AI chips
Today it accounts for 70% of all AI chip sales—and an even greater share for training generative models. (NYT $)
The chips it’s selling to China are less effective due to US export controls. (Ars Technica)
+ These simple design rules could turn the chip industry on its head. (MIT Technology Review)
 
6 Inside the complex world of dissociative identity disorder on TikTok 
Reducing stigma is great, but doctors fear people are self-diagnosing or even imitating the disorder. (The Verge)
 
7 What TikTok might have to give up to keep operating in the US
This shows just how hollow the authorities’ purported data-collection concerns really are. (Forbes)
 
8 Soldiers in Ukraine are playing World of Tanks on their phones
It’s eerily similar to the war they are themselves fighting, but they say it helps them to dissociate from the horror. (NYT $)
 
9 Conspiracy theorists are sharing mad ideas on what causes wildfires
But it’s all just a convoluted way to try to avoid having to tackle climate change. (Slate $)
 
10 Christie’s accidentally leaked the location of tons of valuable art 🖼📍
Seemingly thanks to the metadata that often automatically attaches to smartphone photos. (WP $)

Quote of the day

“Is it going to take people dying for something to move forward?”

—An anonymous air traffic controller warns that staffing shortages in their industry, plus other factors, are starting to threaten passenger safety, the New York Times reports.

The big story

Inside effective altruism, where the far future counts a lot more than the present

" "

VICTOR KERLOW

October 2022

Since its birth in the late 2000s, effective altruism has aimed to answer the question “How can those with means have the most impact on the world in a quantifiable way?”—and supplied methods for calculating the answer.

It’s no surprise that effective altruisms’ ideas have long faced criticism for reflecting white Western saviorism, alongside an avoidance of structural problems in favor of abstract math. And as believers pour even greater amounts of money into the movement’s increasingly sci-fi ideals, such charges are only intensifying. Read the full story.

—Rebecca Ackermann

We can still have nice things

A place for comfort, fun and distraction in these weird times. (Got any ideas? Drop me a line or tweet ’em at me.)

+ Watch Andrew Scott’s electrifying reading of the 1965 commencement address ‘Choose One of Five’ by Edith Sampson.
+ Here’s how Metallica makes sure its live performances ROCK. ($)
+ Cannot deal with this utterly ludicrous wooden vehicle
+ Learn about a weird and wonderful new instrument called a harpejji.



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Why we should all be rooting for boring AI

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Why we should all be rooting for boring AI


This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here.

I’m back from a wholesome week off picking blueberries in a forest. So this story we published last week about the messy ethics of AI in warfare is just the antidote, bringing my blood pressure right back up again. 

Arthur Holland Michel does a great job looking at the complicated and nuanced ethical questions around warfare and the military’s increasing use of artificial-intelligence tools. There are myriad ways AI could fail catastrophically or be abused in conflict situations, and there don’t seem to be any real rules constraining it yet. Holland Michel’s story illustrates how little there is to hold people accountable when things go wrong.  

Last year I wrote about how the war in Ukraine kick-started a new boom in business for defense AI startups. The latest hype cycle has only added to that, as companies—and now the military too—race to embed generative AI in products and services. 

Earlier this month, the US Department of Defense announced it is setting up a Generative AI Task Force, aimed at “analyzing and integrating” AI tools such as large language models across the department. 

The department sees tons of potential to “improve intelligence, operational planning, and administrative and business processes.” 

But Holland Michel’s story highlights why the first two use cases might be a bad idea. Generative AI tools, such as language models, are glitchy and unpredictable, and they make things up. They also have massive security vulnerabilities, privacy problems, and deeply ingrained biases.  

Applying these technologies in high-stakes settings could lead to deadly accidents where it’s unclear who or what should be held responsible, or even why the problem occurred. Everyone agrees that humans should make the final call, but that is made harder by technology that acts unpredictably, especially in fast-moving conflict situations. 

Some worry that the people lowest on the hierarchy will pay the highest price when things go wrong: “In the event of an accident—regardless of whether the human was wrong, the computer was wrong, or they were wrong together—the person who made the ‘decision’ will absorb the blame and protect everyone else along the chain of command from the full impact of accountability,” Holland Michel writes. 

The only ones who seem likely to face no consequences when AI fails in war are the companies supplying the technology.

It helps companies when the rules the US has set to govern AI in warfare are mere recommendations, not laws. That makes it really hard to hold anyone accountable. Even the AI Act, the EU’s sweeping upcoming regulation for high-risk AI systems, exempts military uses, which arguably are the highest-risk applications of them all. 

While everyone is looking for exciting new uses for generative AI, I personally can’t wait for it to become boring. 

Amid early signs that people are starting to lose interest in the technology, companies might find that these sorts of tools are better suited for mundane, low-risk applications than solving humanity’s biggest problems.

Applying AI in, for example, productivity software such as Excel, email, or word processing might not be the sexiest idea, but compared to warfare it’s a relatively low-stakes application, and simple enough to have the potential to actually work as advertised. It could help us do the tedious bits of our jobs faster and better.

Boring AI is unlikely to break as easily and, most important, won’t kill anyone. Hopefully, soon we’ll forget we’re interacting with AI at all. (It wasn’t that long ago when machine translation was an exciting new thing in AI. Now most people don’t even think about its role in powering Google Translate.) 

That’s why I’m more confident that organizations like the DoD will find success applying generative AI in administrative and business processes. 

Boring AI is not morally complex. It’s not magic. But it works. 

Deeper Learning

AI isn’t great at decoding human emotions. So why are regulators targeting the tech?

Amid all the chatter about ChatGPT, artificial general intelligence, and the prospect of robots taking people’s jobs, regulators in the EU and the US have been ramping up warnings against AI and emotion recognition. Emotion recognition is the attempt to identify a person’s feelings or state of mind using AI analysis of video, facial images, or audio recordings. 

But why is this a top concern? Western regulators are particularly concerned about China’s use of the technology, and its potential to enable social control. And there’s also evidence that it simply does not work properly. Tate Ryan-Mosley dissected the thorny questions around the technology in last week’s edition of The Technocrat, our weekly newsletter on tech policy.

Bits and Bytes

Meta is preparing to launch free code-generating software
A version of its new LLaMA 2 language model that is able to generate programming code will pose a stiff challenge to similar proprietary code-generating programs from rivals such as OpenAI, Microsoft, and Google. The open-source program is called Code Llama, and its launch is imminent, according to The Information. (The Information

OpenAI is testing GPT-4 for content moderation
Using the language model to moderate online content could really help alleviate the mental toll content moderation takes on humans. OpenAI says it’s seen some promising first results, although the tech does not outperform highly trained humans. A lot of big, open questions remain, such as whether the tool can be attuned to different cultures and pick up context and nuance. (OpenAI)

Google is working on an AI assistant that offers life advice
The generative AI tools could function as a life coach, offering up ideas, planning instructions, and tutoring tips. (The New York Times)

Two tech luminaries have quit their jobs to build AI systems inspired by bees
Sakana, a new AI research lab, draws inspiration from the animal kingdom. Founded by two prominent industry researchers and former Googlers, the company plans to make multiple smaller AI models that work together, the idea being that a “swarm” of programs could be as powerful as a single large AI model. (Bloomberg)

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