For today's podcast episode, Leaps.org talks with Sara Mednick, author of The Power of the Downstate, a book about the science of relaxation - why it's so important, the best ways to get more of it, and the time of day when our bodies are biologically suited to enjoy it the most.
Show notes
3:10 – The definition of “upstates” and “downstates”
5:50 – The power of 6 slow, deep breaths per minute to balance the nervous system
9:05 – Watching out for mouth breathing and email apnea
13:30 – Different ways of breathing for different goals
16:35 – Body rhythms – what is heart rate variability and why is it so important?
21:05 – Are you naturally a morning or night person? Nature vs nurture
27:10 – The perfect storm that gets in the way of following our circadian rhythms
29:15 – The evolution of our pre-bedtime downstates – why it's important to check in with your cave mates
30:10 – The culture shift needed for more people to follow their circadian rhythms and improve their health
35:10 – Employers and communities can build downstates into daily work and life
38:15 – Choosing how we react to the world
41:00 – Being smarter about peak performance
45:09 – The science of pacing yourself for long-term productivity
49:42 – The science of light exposure for circadian rhythms
52:20 – Where to learn more about Sara Mednick’s research and writing
Links:
Sara Mednick’s website https://www.saramednick.com/ and her Twitter
Mednick’s recent book - The Power of the Downstate
Mednick’s book on the benefits of napping - Take a Nap! Change Your Life
The blue light blocking glasses recommended in Mednick’s book https://www.amazon.com/dp/B019C3O2UE?psc=1&ref=ppx_yo2ov_dt_b_product_details
An app for measuring heart rate variability - Elite HRV app https://elitehrv.com/
Thorne take-home Melatonin test
A recent study in The Lancet Oncology showed that AI found 20 percent more cancers on mammogram screens 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.