Iconic Neuroscientist Eric Kandel Shares This Advice for Combating Memory Loss
Kira Peikoff was the editor-in-chief of Leaps.org from 2017 to 2021. As a journalist, her work has appeared in The New York Times, Newsweek, Nautilus, Popular Mechanics, The New York Academy of Sciences, and other outlets. She is also the author of four suspense novels that explore controversial issues arising from scientific innovation: Living Proof, No Time to Die, Die Again Tomorrow, and Mother Knows Best. Peikoff holds a B.A. in Journalism from New York University and an M.S. in Bioethics from Columbia University. She lives in New Jersey with her husband and two young sons. Follow her on Twitter @KiraPeikoff.
Eric Kandel, 88, is a living legend. A specialist in the neurobiology of learning and memory, he received a Nobel Prize in 2000 for his work on the physiological basis of memory storage. Kandel is the Director of the Kavli Institute for Brain Science and Co-Director of the Mortimer B. Zuckerman Mind Brain Behavior Institute at Columbia University, where he has taught and conducted research for 44 years.
"If you walk two or three miles a day, you will release sufficient osteocalcin from your bones to combat non-Alzheimer's age-related memory loss."
And he's still going strong. Leapsmag Editor-in-Chief Kira Peikoff recently caught up with Dr. Kandel about his latest research, his advice for fellow seniors, and his opinions on some of the biggest challenges in neuroscience today.
What are working on these days?
I'm working on three problems: one is age-related memory loss, the second is post-traumatic stress disorder, and the third is the beholder's share: how a viewer responds to works of art. The beholder's share is a term that Alois Riegl created. He said there are two shares to a painting: the painter creates it, but it's not meaningful until somebody responds to it: the viewer, the beholder.
That's fascinating. As far as age-related memory loss, what are you learning in that area?
I'm learning that there are two forms of age-related memory loss. One is Alzheimer's disease, which we've known about for a long time. But the second is a more benign form which I call just age-related memory loss, which begins actually somewhat earlier and has a very different anatomical locus in the brain. It is caused by a different anatomical defect and responds to different therapeutic measures. It critically involves an area in the hippocampus called the dentate gyrus and it responds to a hormone released by bone called osteocalcin.
It therefore seems likely that one very effective way of combatting age-related memory loss is walking. If you walk two or three miles a day, you are likely to release sufficient osteocalcin from your bones to combat non-Alzheimer's age-related memory loss. In collaboration with Gerard Karsenty at Columbia, my lab at Columbia has been exploring this over the last year and a half.
Have you published anything about this yet?
We are just getting ready to do so.
"I think at the moment we should stick with trying to just reverse abnormalities."
Another question I have is about brain-computer interfaces to help cure disease or even provide cognitive enhancements. What do you think of companies like Kernel and Neuralink that are trying to push this new technology?
I think if it works it would be very nice. We have to see some direct evidence first, but it's certainly an encouraging approach. I think there are a number of directions we could take. The one I think at the moment is most profitable is to try to use the brain as it is and try to enhance it, restore it, refurbish it, make it function better from its age-related condition.
You mean, without some kind of machine interface?
Without necessarily introducing anything from the outside world. Although I have no objection whatsoever to introducing ancillary aids if they're beneficial and not harmful.
Do you have any opinion on whether neuroscience and technology should aim to provide an enhancement to the brain or just return it to baseline and cure disease?
I would be perfectly satisfied if we just cured diseases. I think at the moment we should stick with trying to just reverse abnormalities, but certainly … having the capability of becoming more intelligent, more attentive, capable of remembering things better than normal, that would be nice.
What do you think is the most important challenge facing the field of neuroscience today?
It's hard to say. I think the biology of consciousness is one fantastic problem. Trying to understand and successfully reverse some of the abnormalities of the brain, like age-related memory loss, schizophrenia, depression, manic depressive illness would be wonderful.
To be able to reverse memory loss, to allow people in their 70s, 80s, and 90s to live free and independent lives, is a major challenge for brain science.
Absolutely. Is there anything else you'd like to share with our readers about your research or the field more broadly?
I'd emphasize that brain science is a relatively young discipline but it's moving ahead in a very responsible and a very effective fashion, making progress in a number of areas, and is clearly sensitive to, and responsive to, the demands of the social situation. Right now, number one, the population is aging dramatically. In 1900, the average life expectancy was 50, and now the average life expectancy is 78 for men, and 82 for women.
So people are living longer and therefore are having age-related diseases, including memory loss. To be able to reverse it, to allow people in their 70s, 80s, and 90s to live free and independent lives, is a major challenge for brain science in both its basic and its clinically applied fashion. I think this is very important and serious effort should be put into this.
Kira Peikoff was the editor-in-chief of Leaps.org from 2017 to 2021. As a journalist, her work has appeared in The New York Times, Newsweek, Nautilus, Popular Mechanics, The New York Academy of Sciences, and other outlets. She is also the author of four suspense novels that explore controversial issues arising from scientific innovation: Living Proof, No Time to Die, Die Again Tomorrow, and Mother Knows Best. Peikoff holds a B.A. in Journalism from New York University and an M.S. in Bioethics from Columbia University. She lives in New Jersey with her husband and two young sons. Follow her on Twitter @KiraPeikoff.
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.