The Meat Industry Is Polluting the Planet. Bug Burgers Could Save It.
Agriculture in the 21st century is not as simple as it once was. With a population seven billion strong, a climate in crisis, and sustainability in farming practices on everyone's radar, figuring out how to feed the masses without destroying the Earth is a pressing concern.
Tufts scientists argue that insect cells may be better suited to lab-created meat protein than traditional farm animal cells.
In addition to low-emission cows and drone pollinators, there's a promising new solution on the table. How does "lab-grown insect meat" grab you?
Writing in Frontiers in Sustainable Food Systems, researchers at Tufts University say insects that are fed plants and genetically modified for maximum growth, nutrition, and flavor could be the best, greenest alternative to our current livestock farming practices. This lab-grown protein source could produce high volume, nutritious food without the massive resources required for traditional animal agriculture.
"Due to the environmental, public health, and animal welfare concerns associated with our current livestock system, it is vital to develop more sustainable food production methods," says lead author Natalie Rubio. Could insect meat be the key?
Next Up
New sustainable food production includes what's called "cellular agriculture," an emerging industry and field of study in which meat and dairy are produced via cells in a lab instead of whole animals. So far, scientists have primarily focused on bovine, porcine, and avian cells to create this "cultured meat."
But the Tufts scientists argue that insect cells may be better suited to lab-created meat protein than traditional farm animal cells.
"Compared to cultured mammalian, avian, and other vertebrate cells, insect cell cultures require fewer resources and less energy-intensive environmental control, as they have lower glucose requirements and can thrive in a wider range of temperature, pH, oxygen, and osmolarity conditions," reports Rubio.
"Alterations necessary for large-scale production are also simpler to achieve with insect cells, which are currently used for biomanufacturing of insecticides, drugs, and vaccines," she adds.
They still have some details to hash out, however, including how to make cultured insect meat more like the steak and chicken we're all familiar with.
"Despite this immense potential, cultured insect meat isn't ready for consumption," says Rubio. "Research is ongoing to master two key processes: controlling development of insect cells into muscle and fat, and combining these in 3D cultures with a meat-like texture." They are currently experimenting with mushroom-derived fiber to tackle the latter.
People would still be able to eat meat—it would just come from a different source.
Open Questions
As the report points out, one thing that makes cellular agriculture an attractive alternative to high-density animal farming is that it doesn't require consumers to change their behaviors. People would still be able to eat meat—it would just come from a different source.
But the big question remains: How will lab-grown insect meat taste? Will the buggers really taste as good as burgers?
And, of course, there's the "ew" factor. Meat alternatives have proven to work for some people—Tofurky is still in business, after all—but it may be a hard sell to get the masses to jump on board with eating bugs. Consuming creepy crawlies sounds simply unpalatable to many, and the term "lab-grown, cellular insect meat" doesn't help much. Perhaps an entirely new nomenclature is in order.
Another question is whether or not folks will trust such scientifically-created food. People already use the term "frankenfood" to refer to genetic modification -- even though the vast majority of the corn and soybeans planted in the U.S. today are genetically engineered, and other major crops with GM varieties include potatoes, apples, squash, and papayas. Still, combining GM technology with eating insects may be a hard sell.
However, we're all going to have to get used to trying new things if we want to leave a habitable home for our children. If a lab-grown bug burger can save the planet, maybe it's worth a shot.
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.