Shoot for the Moon: Its Surface Contains a Pot of Gold
Here's a riddle: What do the Moon, nuclear weapons, clean energy of the future, terrorism, and lung disease all have in common?
One goal of India's upcoming space probe is to locate deposits of helium-3 that are worth trillions of dollars.
The answer is helium-3, a gas that's extremely rare on Earth but 100 million times more abundant on the Moon. This past October, the Lockheed Martin corporation announced a concept for a lunar landing craft that may return humans to the Moon in the coming decade, and yesterday China successfully landed the Change-4 probe on the far side of the Moon. Landing inside the Moon's deepest crater, the Chinese achieved a first in space exploration history.
Meanwhile, later this month, India's Chandrayaan-2 space probe will also land on the lunar surface. One of its goals is to locate deposits of helium-3 that are worth trillions of dollars, because it could be a fuel for nuclear fusion energy to generate electricity or propel a rocket.
The standard way that nuclear engineers are trying to achieve sustainable fusion uses fuels that are more plentiful on Earth: deuterium and tritium. But MIT researchers have found that adding small amounts of helium-3 to the mix could make it much more efficient, and thus a viable energy source much sooner that once thought.
Even if fusion is proven practical tomorrow, any kind of nuclear energy involves long waits for power plant construction measured in decades. However, mining helium-3 could be useful now, because of its non-energy applications. A major one is its ability to detect neutrons coming from plutonium that could be used in terrorist attacks. Here's how it works: a small amount of helium-3 is contained within a forensic instrument. When a neutron hits an atom of helium-3, the reaction produces tritium, a proton, and an electrical charge, alerting investigators to the possibility that plutonium is nearby.
Ironically, as global concern about a potential for hidden nuclear material increased in the early 2000s, so did the supply of helium-3 on Earth. That's because helium-3 comes from the decay of tritium, used in thermonuclear warheads (H-bombs). Thousands of such weapons have been dismantled from U.S. and Russian arsenals, making helium-3 available for plutonium detection, research, and other applications--including in the world of healthcare.
Helium-3 can help doctors diagnose lung diseases, since it enables imaging of the lungs in real time.
Helium-3 dramatically improves the ability of doctors to image the lungs in a range of diseases including asthma, chronic obstructive pulmonary disease and emphysema, cystic fibrosis, and bronchopulmonary dysplasia, which happens particularly in premature infants. Specifically, helium-3 is useful in magnetic resonance imaging (MRI), a procedure that creates images from within the body for diagnostic purposes.
But while a standard MRI allows doctors to visualize parts of the body like the heart or brain, it's useless for seeing the lungs. Because lungs are filled with air, which is much less dense than water or fat, effectively no signals are produced that would enable imaging.
To compensate for this problem, a patient can inhale gas that is hyperpolarized –meaning enhanced with special procedures so that the magnetic resonance signals from the lungs are finally readable. This gas is safe to breathe when mixed with enough oxygen to support life. Helium-3 is one such gas that can be hyperpolarized; since it produces such a strong signal, the MRI can literally see the air inside the lungs and in all of the airways, revealing intricate details of the bronchopulmonary tree. And it can do this in real time
The capability to show anatomic details of the lungs and airways, and the ability to display functional imaging as a patient breathes, makes helium-3 MRI far better than the standard method of testing lung function. Called spirometry, this method tells physicians how the lungs function overall, but does not home in on particular areas that may be causing a problem. Plus, spirometry requires patients to follow instructions and hold their breath, so it is not great for testing young children with pulmonary disease.
In recent years, the cost of helium-3 on Earth has skyrocketed.
Over the past several years, researchers have been developing MRI for lung testing using other hyperpolarized gases. The main alternative to helium-3 is xenon-129. Over the years, researchers have learned to overcome certain disadvantages of the latter, such as its potential to put patients to sleep. Since helium-3 provides the strongest signal, though, it is still the best gas for MRI studies in many lung conditions.
But the supply of helium-3 on Earth has been decreasing in recent years, due to the declining rate of dismantling of warheads, just as the Department of Homeland Security has required more and more of the gas for neutron detection. As a result, the cost of the gas has skyrocketed. Less is available now for medical uses – unless, of course, we begin mining it on the moon.
The question is: Are the benefits worth the 239,000-mile trip?
A new type of cancer therapy is shrinking deadly brain tumors with just one treatment
Few cancers are deadlier than glioblastomas—aggressive and lethal tumors that originate in the brain or spinal cord. Five years after diagnosis, less than five percent of glioblastoma patients are still alive—and more often, glioblastoma patients live just 14 months on average after receiving a diagnosis.
But an ongoing clinical trial at Mass General Cancer Center is giving new hope to glioblastoma patients and their families. The trial, called INCIPIENT, is meant to evaluate the effects of a special type of immune cell, called CAR-T cells, on patients with recurrent glioblastoma.
How CAR-T cell therapy works
CAR-T cell therapy is a type of cancer treatment called immunotherapy, where doctors modify a patient’s own immune system specifically to find and destroy cancer cells. In CAR-T cell therapy, doctors extract the patient’s T-cells, which are immune system cells that help fight off disease—particularly cancer. These T-cells are harvested from the patient and then genetically modified in a lab to produce proteins on their surface called chimeric antigen receptors (thus becoming CAR-T cells), which makes them able to bind to a specific protein on the patient’s cancer cells. Once modified, these CAR-T cells are grown in the lab for several weeks so that they can multiply into an army of millions. When enough cells have been grown, these super-charged T-cells are infused back into the patient where they can then seek out cancer cells, bind to them, and destroy them. CAR-T cell therapies have been approved by the US Food and Drug Administration (FDA) to treat certain types of lymphomas and leukemias, as well as multiple myeloma, but haven’t been approved to treat glioblastomas—yet.
CAR-T cell therapies don’t always work against solid tumors, such as glioblastomas. Because solid tumors contain different kinds of cancer cells, some cells can evade the immune system’s detection even after CAR-T cell therapy, according to a press release from Massachusetts General Hospital. For the INCIPIENT trial, researchers modified the CAR-T cells even further in hopes of making them more effective against solid tumors. These second-generation CAR-T cells (called CARv3-TEAM-E T cells) contain special antibodies that attack EFGR, a protein expressed in the majority of glioblastoma tumors. Unlike other CAR-T cell therapies, these particular CAR-T cells were designed to be directly injected into the patient’s brain.
The INCIPIENT trial results
The INCIPIENT trial involved three patients who were enrolled in the study between March and July 2023. All three patients—a 72-year-old man, a 74-year-old man, and a 57-year-old woman—were treated with chemo and radiation and enrolled in the trial with CAR-T cells after their glioblastoma tumors came back.
The results, which were published earlier this year in the New England Journal of Medicine (NEJM), were called “rapid” and “dramatic” by doctors involved in the trial. After just a single infusion of the CAR-T cells, each patient experienced a significant reduction in their tumor sizes. Just two days after receiving the infusion, the glioblastoma tumor of the 72-year-old man decreased by nearly twenty percent. Just two months later the tumor had shrunk by an astonishing 60 percent, and the change was maintained for more than six months. The most dramatic result was in the 57-year-old female patient, whose tumor shrank nearly completely after just one infusion of the CAR-T cells.
The results of the INCIPIENT trial were unexpected and astonishing—but unfortunately, they were also temporary. For all three patients, the tumors eventually began to grow back regardless of the CAR-T cell infusions. According to the press release from MGH, the medical team is now considering treating each patient with multiple infusions or prefacing each treatment with chemotherapy to prolong the response.
While there is still “more to do,” says co-author of the study neuro-oncologist Dr. Elizabeth Gerstner, the results are still promising. If nothing else, these second-generation CAR-T cell infusions may someday be able to give patients more time than traditional treatments would allow.
“These results are exciting but they are also just the beginning,” says Dr. Marcela Maus, a doctor and professor of medicine at Mass General who was involved in the clinical trial. “They tell us that we are on the right track in pursuing a therapy that has the potential to change the outlook for this intractable disease.”
Since the early 2000s, AI systems have eliminated more than 1.7 million jobs, and that number will only increase as AI improves. Some research estimates that by 2025, AI will eliminate more than 85 million jobs.
But for all the talk about job security, AI is also proving to be a powerful tool in healthcare—specifically, cancer detection. One recently published study has shown that, remarkably, artificial intelligence was able to detect 20 percent more cancers in imaging scans than radiologists alone.
Published in The Lancet Oncology, the study analyzed the scans of 80,000 Swedish women with a moderate hereditary risk of breast cancer who had undergone a mammogram between April 2021 and July 2022. Half of these scans were read by AI and then a radiologist to double-check the findings. The second group of scans was read by two researchers without the help of AI. (Currently, the standard of care across Europe is to have two radiologists analyze a scan before diagnosing a patient with breast cancer.)
The study showed that the AI group detected cancer in 6 out of every 1,000 scans, while the radiologists detected cancer in 5 per 1,000 scans. In other words, AI found 20 percent more cancers than the highly-trained radiologists.
Scientists have been using MRI images (like the ones pictured here) to train artificial intelligence to detect cancers earlier and with more accuracy. Here, MIT's AI system, MIRAI, looks for patterns in a patient's mammograms to detect breast cancer earlier than ever before. news.mit.edu
But even though the AI was better able to pinpoint cancer on an image, it doesn’t mean radiologists will soon be out of a job. Dr. Laura Heacock, a breast radiologist at NYU, said in an interview with CNN that radiologists do much more than simply screening mammograms, and that even well-trained technology can make errors. “These tools work best when paired with highly-trained radiologists who make the final call on your mammogram. Think of it as a tool like a stethoscope for a cardiologist.”
AI is still an emerging technology, but more and more doctors are using them to detect different cancers. For example, researchers at MIT have developed a program called MIRAI, which looks at patterns in patient mammograms across a series of scans and uses an algorithm to model a patient's risk of developing breast cancer over time. The program was "trained" with more than 200,000 breast imaging scans from Massachusetts General Hospital and has been tested on over 100,000 women in different hospitals across the world. According to MIT, MIRAI "has been shown to be more accurate in predicting the risk for developing breast cancer in the short term (over a 3-year period) compared to traditional tools." It has also been able to detect breast cancer up to five years before a patient receives a diagnosis.
The challenges for cancer-detecting AI tools now is not just accuracy. AI tools are also being challenged to perform consistently well across different ages, races, and breast density profiles, particularly given the increased risks that different women face. For example, Black women are 42 percent more likely than white women to die from breast cancer, despite having nearly the same rates of breast cancer as white women. Recently, an FDA-approved AI device for screening breast cancer has come under fire for wrongly detecting cancer in Black patients significantly more often than white patients.
As AI technology improves, radiologists will be able to accurately scan a more diverse set of patients at a larger volume than ever before, potentially saving more lives than ever.