Podcasts about Mayo Clinic

When a child is critically ill and answers are elusive, every day can feel like an eternity. This week on Tomorrow's Cure from Mayo Clinic, host Cathy Wurzer talks with pediatric geneticist Whitney Thompson, M.D., from Mayo Clinic, genomic medicine pioneer Stephen Kingsmore, M.D., DSc, from Rady Children's Institute for Genomic Medicine, and Sean George, Ph.D., CEO of Inflection Medicine, about how rapid whole genome sequencing is transforming care for the youngest patients. Together, they explore how clinicians are shortening the “diagnostic odyssey,” pairing sequencing with artificial intelligence to identify potential treatments, and redefining what is possible for rare diseases through programs like Mayo Clinic Children's BabyFORce. You will also hear powerful patient stories, including children whose lives changed after a genomic diagnosis opened the door to targeted therapies, and a candid discussion about cost, access, and ethics as this technology moves toward wider adoption. Tune in to learn how today's breakthroughs in pediatric genomics could shape the future of medicine for all of us. How to listen and stay connected:• Subscribe to Tomorrow's Cure on your favorite podcast app and follow the show so you never miss an episode.• Get the latest health information from Mayo Clinic's experts—subscribe to Mayo Clinic's newsletter for free today: ⁠https://mayocl.in/3EcNPNc⁠ Connect with Mayo Clinic:• Like Mayo Clinic on Facebook: https://www.facebook.com/mayoclinic/⁠Follow • Mayo Clinic on Instagram: ⁠https://www.instagram.com/mayoclinic/⁠Follow • Mayo Clinic on X (formerly Twitter): ⁠https://x.com/MayoClinic⁠Follow • Mayo Clinic on Threads: ⁠https://www.threads.net/@mayoclinic

Leadless Pacemakers and Extravascular ICDs   Guest: Alan M. Sugrue, M.B., B.Ch., B.A.O. Host: Sharonne Hayes, M.D.   This episode of “Interviews With the Experts” explores how leadless pacemakers and extravascular ICDs are redefining device therapy by minimizing lead- and pocket-related complications while expanding options for patients with complex anatomy or infection risk. Listeners will learn how these systems differ from traditional transvenous technologies, review key data on safety and efficacy, and understand which patient profiles are best suited for each approach.   Topics Discussed: How do leadless pacemakers differ from traditional transvenous systems in terms of technology, complication profile, and clinical outcomes? In which patient populations should leadless pacing be considered as a first-line option? What are the key design and functional differences between extravascular and subcutaneous ICDs? What advantages and limitations should clinicians understand when deciding between these two systems?   Connect with Mayo Clinic's Cardiovascular Continuing Medical Education online at https://cveducation.mayo.edu or on Twitter @MayoClinicCV and @MayoCVservices. LinkedIn: Mayo Clinic Cardiovascular Services Cardiovascular Education App: The Mayo Clinic Cardiovascular CME App is an innovative educational platform that features cardiology-focused continuing medical education wherever and whenever you need it. Use this app to access other free content and browse upcoming courses. Download it for free in Apple or Google stores today! No CME credit offered for this episode.   Podcast episode transcript found here.   Recorded 21-October-2025

What are the differences in black and white comedians and the audiences they draw? I had an interesting experience opening for DL Hughly. He was a huge star and I was an open mic comic. It didn't go well for me. Here's the quick story and the lesson I learned.  https://www.TheWorkLady.com  Jan McInnis is a top change management keynote speaker, comedian, and funny motivational speaker who helps organizations use humor to handle change, build resilience, and strengthen leadership skills. With her laugh-out-loud stories and practical tips, Jan shows audiences how humor isn't just entertainment—it's a business skill that drives communication, connection, and stress relief.   A conference keynote speaker, Master of Ceremonies, and comedy writer, Jan has written material for The Tonight Show with Jay Leno as well as radio, TV, and syndicated cartoon strips. She's the author of two books—Finding the Funny Fast and Convention Comedian—and her insights on humor in business have been featured in The Wall Street Journal, The Washington Post, and The Huffington Post. For over 25 years, she has been helping leaders and teams discover how to bounce back from setbacks, embrace change, and connect through comedy.   Jan has delivered keynote speeches at thousands of events nationwide, from the Federal Reserve Banks to the Mayo Clinic, for industries that include healthcare, finance, government, education, women's leadership events, technology, and safety & disaster management. Her client list features respected organizations such as: Healthcare: Mayo Clinic, Kaiser Permanente, Abbott Pharmaceuticals, Health Information Management Associations, Assisted Living Associations Finance: Federal Reserve Banks, Merrill Lynch, Transamerica Insurance, BDO Accounting, American Institute of CPAs, credit unions, banking associations Government: U.S. Air Force, Social Security Administration, International Institute of Municipal Clerks, National League of Cities, public utilities, correctional associations Women's Leadership Events: Toyota Women's Conference, Go Red for Women, Speaking of Women's Health, Soroptimists, Women in Insurance & Financial Services Education: State superintendent associations, community college associations, Head Start associations, National Association of Elementary and Middle School Principals Safety & Disaster: International Association of Emergency Managers, Disney Emergency Management, Mid-Atlantic Safety Conference, risk management associations   Her background as a Washington, D.C. marketing executive gives her a unique perspective that blends business acumen with stand-up comedy. Jan was also honored with the Greater Washington Society of Association Executives "Excellence in Education" Award. Along with her podcast Finding the Funny: Leadership Tips from a Comedian, Jan also produces Comedian Stories: Tales From the Road in Under 5 Minutes. Whether she's headlining a major convention, hosting a leadership retreat, or teaching resilience at a safety conference, Jan's programs give audiences the tools to laugh, learn, and lead.  

This episode features two guests from the ISAPP board of directors who led the recently published consensus definition of gut health: Prof. Maria Marco PhD from UC Davis (USA), and Prof. Eamonn Quigley MD from Houston Methodist Hospital (USA). In the paper, the group defines gut health as: “a state of normal gastrointestinal function without active gastrointestinal disease and gut-related symptoms that affect quality of life”. Gut health is a commonly used term that previously had no scientific definition. Initially the group of experts (both scientists and physicians) that met to discuss it had a lot of skepticism, but they became more enthusiastic and engaged as the discussion proceeded and were finally able to reach consensus. The group identified 6 distinct domains that are encompassed under gut health: gut microbiome, gut barrier, gastrointestinal physiology (primarily intestinal secretions and motility), gut-brain axis, immune function, and metabolism. The group hopes it will provide clarity over time about which aspect(s) of gut health are being assessed in a given study (as it's not realistic to look at all aspects in a single study). One difficulty is that some of the tests available to measure these domains are quite limited and/or invasive. Nor do consistent correlations exist between symptoms and objective measures of the 6 domains. Determinants of gut health are also discussed in the paper, with diet being important among these. Episode abbreviations and links: Gut health consensus definition paper: The International Scientific Association for Probiotics and Prebiotics (ISAPP) consensus statement on the definition and scope of gut health Earlier publication on gut health by Bischoff: ‘Gut health’: a new objective in medicine? About Prof. Maria Marco PhD: Dr. Maria Marco PhD, is President of ISAPP's board of directors and Professor in the Department of Food Science and Technology at the University of California, Davis. She earned her PhD in microbiology at the University of California, Berkeley. Prof. Marco started her lactic acid bacteria and gut health laboratory at UC Davis in 2008 and has built an internationally-recognized, NIH, USDA, and NSF funded research program on probiotics, fermented foods, and dietary modulation of the gut microbiome. She is currently a fellow in the American Academy of Microbiology. About Prof. Eamonn Quigley MD: Dr. Eamonn M M Quigley MD FRCP FACP MACG FRCPI MWGO is David M Underwood Chair of Medicine in Digestive Disorders and Chief of the Division of Gastroenterology and Hepatology at Houston Methodist Hospital. A native of Cork, Ireland, he graduated in medicine from University College Cork. He trained in internal medicine in Glasgow, completed a two-year research fellowship at the Mayo Clinic, and training in gastroenterology in Manchester, UK. He joined the University of Nebraska Medical Center in 1986 where he rose to become Chief of Gastroenterology and Hepatology. Returning to Cork in 1998 he served as Dean of the Medical School and a PI at the Alimentary Pharmabiotic Center. He served as president of the American College of Gastroenterology and the WGO and as editor-in-chief of the American Journal of Gastroenterology.

Ben Lindbergh and Meg Rowley banter about a video of Brandon Marsh’s hair-wetting, the Phillies’ latest therapy, the Red Sox “home whites” non-disparagement saga, a former team exec’s proposals to promote competitive balance, and the best candidates among MLB players to pit against each other in a “Who ya got?” debate, then preview the 2026 Toronto Blue Jays (55:43) with The Athletic’s Mitch Bannon, and the 2026 Tampa Bay Rays (1:42:53) with MLB.com’s Adam Berry. 2026 EW Season Preview Series ALBALCHWATHBOSCLEHOUNYYDETLAATBRKCRSEATORMINTEX NLATLCHCARIMIACINCOLNYMMILLADPHIPITSDPWSNSTLSFG .intro-team, .intro-team td { font-family: lato, Arial, Arial, Helvetica, sans-serif; font-size: 13px; margin-bottom: 20px; } .intro-team .intro-header { /*display: none;*/ text-align: center; } .team-lg { text-align: center; width: 100%; } /* [class^="team-box-"] > div { display: inline-block; width: 48%; } [class^="team-box-"] > div table { width: 100%; border-collapse: collapse; } [class^="team-box-"] > div td { background-color: #efefef; border: 1px solid #ccc; line-height: 2; text-align: center; cursor: default; } [class^="team-box-"] > div a { color: #000; text-decoration: none; display: block; width: 100% } [class^="team-box-"] > div a:hover { color: #50ae26; } [class^="team-box-"] > div a.link-inactive { color: #aaa; } */ Audio intro: The Spaghettis, “Effectively Wild Theme” Audio interstitial 1: Jonathan Crymes, “Effectively Wild Theme” Audio interstitial 2: Ian H., “Effectively Wild Theme” Audio outro: Nate Emerson, “Effectively Wild Theme” Link to Steele tweet Link to Marsh video Link to Jake on Marsh’s hair routine Link to Baumann on Crawford Link to hyperbaric oxygen therapy article 1 Link to hyperbaric oxygen therapy article 2 Link to Mayo Clinic on hyperbaric oxygen therapy Link to research on efficacy Link to Red Sox jersey change Link to story on changing statements Link to side-by-side statements Link to @RedSox reply Link to Ball on competitive balance Link to Moneyball scene Link to BP on competitive balance Link to Ben on Machado vs. Arenado Link to Ben on Correa vs. Seager Link to Baumann on Conforto vs. Judge Link to Machado vs. Arenado, rest of 2015 Link to Machado vs. Arenado, 2016 on Link to Correa vs. Seager, 2018 on Link to Conforto vs. Judge, start of 2017 Link to Conforto vs. Judge, rest of 2017 Link to Conforto vs. Judge, 2018 on Link to team payrolls page Link to Blue Jays offseason tracker Link to Blue Jays depth chart Link to 2025 team FRV Link to team SP projections Link to Rogers Centre renovations Link to “Toronto” pronunciation Link to Return of the Jedi scene Link to bagged milk Link to Happ on bagged milk Link to Sloan’s website Link to Mitch’s author archive Link to Mitch’s podcast Link to Rays offseason tracker Link to Rays depth chart Link to Dolinar data 1 Link to Dolinar data 2 Link to three-team-trades stat Link to Statcast park factors Link to team WAR projections Link to Shane scene Link to ballpark renderings Link to trial delay Link to Adam’s author archive Link to spring training Opening Day Sponsor Us on Patreon Give a Gift Subscription Email Us: podcast@fangraphs.com Effectively Wild Subreddit Effectively Wild Wiki Apple Podcasts Feed Spotify Feed YouTube Playlist Facebook Group Bluesky Account Twitter Account Get Our Merch! var SERVER_DATA = Object.assign(SERVER_DATA || {}); Source

S1E10: Disaster Recovery Is Dead. Long Live Technology Resilience! On this episode, host Steven Hajny is joined by Heather Costa, Director of Technology Resilience at Mayo Clinic, to unpack what “resilience” really means in modern healthcare IT, especially when cyber disruption is the clear and present danger. Heather champions for moving beyond traditional “disaster recovery” thinking and instead prioritizing business workflows (the minimum viable hospital) over recovering hundreds of Tier 1 apps. Together they explore why recovery timelines always “depend,” why honest planning beats rosy assumptions, and how Zero Trust-era identity systems have become ground zero when everything goes sideways. To stream our Station live 24/7 visit www.HealthcareNOWRadio.com or ask your Smart Device to “….Play Healthcare NOW Radio”. Find all of our network podcasts on your favorite podcast platforms and be sure to subscribe and like us. Learn more at www.healthcarenowradio.com/listen

Episode Topic: Innovation AI with the Mayo Clinic (https://think.nd.edu/bq/healthai-2/ )Discover how Mayo Clinic is pioneering the future of healthcare. Go beyond the technology to see how AI is amplifying their historic, compassion-driven mission, freeing caregivers to focus on what truly matters: the patient. Emily Godsey, Administrator of Innovation & Digital Transformation for the Mayo Clinic, and Scott Helgeson, Doctor of Medicine and Assistant Professor at the Mayo Clinic, reveal a powerful vision for a more human-centered and proactive model of medicine.Featured Speakers:-Emily Godsey, MSHA, FACHE, Mayo Clinic-Scott Helgeson, M.D., Mayo ClinicRead this episode's recap over on the University of Notre Dame's open online learning community platform, ThinkND: https://go.nd.edu/30ec36.This podcast is a part of the ThinkND Series titled Health AI Forum. (https://go.nd.edu/090c52)Thanks for listening! The ThinkND Podcast is brought to you by ThinkND, the University of Notre Dame's online learning community. We connect you with videos, podcasts, articles, courses, and other resources to inspire minds and spark conversations on topics that matter to you — everything from faith and politics, to science, technology, and your career. Learn more about ThinkND and register for upcoming live events at think.nd.edu. Join our LinkedIn community for updates, episode clips, and more.

The New Discourses Podcast with James Lindsay, Ep. 193 As we encounter both the material in the infamous Epstein Files and revelations from some of Epstein's associates, not to mention the advances in AI and robotics, we're confronted with what seemed like dystopian science fiction just a few years ago: transhumanism. Tech futurists, however, have been predicting it and working toward it for decades, including the curious figure of "Martine" Rothblatt, creator of SiriusXM Radio and board member at the Mayo Clinic. Rothblatt is trans and has written at least two very odd books about sex and gender, The Apartheid of Sex: A Manifesto on the Freedom of Gender (https://www.amazon.com/Apartheid-Sex-Manifesto-Freedom-Gender/dp/051759997X/) (1996) and an updated version called From Transgender to Transhuman: A Manifesto on the Freedom of Form (https://www.amazon.com/Transgender-Transhuman-Manifesto-Freedom-Form/dp/0615489427/) (2011). In this latter book, Rothblatt explains, perhaps ironically now, that the same arguments that justify "transgender" also justify transhuman: ultimately that who we really are does not depend on our physical body at all. In this creepy episode of the New Discourses Podcast, host James Lindsay presents some of this troubling book to you. You will not want to miss this. Latest from New Discourses Press! The Queering of the American Child: https://queeringbook.com/ Support New Discourses: https://newdiscourses.com/support Follow New Discourses on other platforms: https://newdiscourses.com/subscribe Follow James Lindsay: https://linktr.ee/conceptualjames © 2026 New Discourses. All rights reserved. #NewDiscourses #JamesLindsay #Transhumanism

Rick Hill defeated terminal cancer in 1974 after walking out of the Mayo Clinic — and 51 years later he's medication-free. The weapon? Diet, B17 laetrile, and pancreatic enzymes. The same hospital that told Rick he had months to live sent him home with white bread, Jell-O, and pasta. That's not an accident. That's the system. What Rick did instead — and what Steve Jobs never knew about — is exactly what the MAHA movement is finally starting to wake people up to. Carbs feed cancer. Sugar is the fuel. And the treatment that saved Rick's life was suppressed by the U.S. government for decades. This episode will make you rethink everything you've been told about food, medicine, and who actually profits from your diagnosis. Chapters:0:00 - Intro: Carbs Are the Enemy2:24 - Rick Hill's Terminal Cancer Diagnosis at the Mayo Clinic10:29 - How Sugar Literally Feeds Cancer Cells18:21 - The Steve Jobs Objection: Natural vs. Western Medicine20:08 - B17, Enzymes & Government Suppression of Alternative Treatment28:16 - The MAHA Movement & Gen Z Waking Up to Food as Medicine32:08 - Where to Get B17, Enzymes & Rick's Free Resources34:01 - Outro Studio Sponsor: ⁠Cardio Miracle⁠ - "Unlock the secret to a healthier heart, increased energy levels, and transform your cardiovascular fitness like never before.": ⁠CardioMiracle.com/TBNS⁠ LINKS:RNC Store (B17 laetrile & pancreatic enzymes, 10% off with code RICK10): ⁠RNCstore.com⁠Free Book — "Too Young to Die" by Rick Hill: ⁠b17works.com⁠Free Book — "World Without Cancer" by G. Edward Griffin (Chapters 5–7): ⁠myworldwithoutcancer.com⁠ Order ⁠Cardio Miracle⁠ (⁠CardioMiracle.com/TBNS⁠) for 15% off and take a step towards better heart health and overall well-being! WATCH The Brian Nichols Show on ⁠YouTube⁠ & ⁠Rumble⁠. Follow Brian on social media: X.com/Twitter ⁠(https://www.briannicholsshow.com/twitter⁠) & Facebook (⁠https://www.briannicholsshow.com/facebook⁠) LIKE, SHARE, and SUBSCRIBE to ⁠The Brian Nichols Show ⁠for a BRAND NEW episode airing every THURSDAY at 9pm EST! Email Listener Questions to ⁠brian@briannicholsshow.com⁠! Learn more about your ad choices. Visit megaphone.fm/adchoices

Rick Hill defeated terminal cancer in 1974 after walking out of the Mayo Clinic — and 51 years later he's medication-free. The weapon? Diet, B17 laetrile, and pancreatic enzymes.The same hospital that told Rick he had months to live sent him home with white bread, Jell-O, and pasta. That's not an accident. That's the system. What Rick did instead — and what Steve Jobs never knew about — is exactly what the MAHA movement is finally starting to wake people up to.Carbs feed cancer. Sugar is the fuel. And the treatment that saved Rick's life was suppressed by the U.S. government for decades. This episode will make you rethink everything you've been told about food, medicine, and who actually profits from your diagnosis. Chapters: 0:00 - Intro: Carbs Are the Enemy 2:24 - Rick Hill's Terminal Cancer Diagnosis at the Mayo Clinic 10:29 - How Sugar Literally Feeds Cancer Cells (The White Bread & Jell-O Scandal) 18:21 - The Steve Jobs Objection: Natural Medicine vs. Western Medicine 20:08 - B17, Pancreatic Enzymes & the Government Suppression of Alternative Cancer Treatment 28:16 - The MAHA Movement & Why Gen Z Is Waking Up to Food as Medicine 32:08 - Where to Get B17, Enzymes & Rick's Free Resources 34:01 - Outro Studio Sponsor: Cardio Miracle - "Unlock the secret to a healthier heart, increased energy levels, and transform your cardiovascular fitness like never before.": CardioMiracle.com/TBNS .LINKS SECTION RNC Store (B17 laetrile & pancreatic enzymes, 10% off with code RICK10): RNCstore.com Free Book — "Too Young to Die" by Rick Hill: b17works.com Free Book — "World Without Cancer" by G. Edward Griffin (Chapters 5–7): myworldwithoutcancer.com ❤️ Order Cardio Miracle (CardioMiracle.com/TBNS) for 15% off and take a step towards better heart health and overall well-being!

In recent years, mounting scientific evidence has shown a connection between our mental health and our heart health. Articles published by Harvard, the Mayo Clinic and the American Heart Association, have all provided evidence that a poor mental mindset can negatively affect your heart and lead to heart disease. For more than 5 decades, Brian Clement, Ph.D., L.N. has been at the forefront of the progressive health movement. An author of several books, he has long been a proponent of a holistic, proactive approach to healthcare and disease prevention. He is also the co-director of the renowned Hippocrates (pronounced Hip-Pah-Cruh-Tees) Wellness retreat in West Palm Beach, Florida. Now celebrating its 70th year, Hippocrates Wellness has become one of the world's leading wellness retreats for those seeking health and longevity through education, nutritional counseling, therapies and lectures. In recognition of Heart Health Month, Brian Clement, Ph.D., L.N. will discuss the mind-heart connection, provide tips for cultivating a heart-healthy mindset and how things like the right foods can be the best prescription for a healthier heart.Become a supporter of this podcast: https://www.spreaker.com/podcast/arroe-collins-like-it-s-live--4113802/support.

Rick Hill defeated terminal cancer in 1974 after walking out of the Mayo Clinic — and 51 years later he's medication-free. The weapon? Diet, B17 laetrile, and pancreatic enzymes. The same hospital that told Rick he had months to live sent him home with white bread, Jell-O, and pasta. That's not an accident. That's the system. What Rick did instead — and what Steve Jobs never knew about — is exactly what the MAHA movement is finally starting to wake people up to. Carbs feed cancer. Sugar is the fuel. And the treatment that saved Rick's life was suppressed by the U.S. government for decades. This episode will make you rethink everything you've been told about food, medicine, and who actually profits from your diagnosis. Chapters:0:00 - Intro: Carbs Are the Enemy2:24 - Rick Hill's Terminal Cancer Diagnosis at the Mayo Clinic10:29 - How Sugar Literally Feeds Cancer Cells18:21 - The Steve Jobs Objection: Natural vs. Western Medicine20:08 - B17, Enzymes & Government Suppression of Alternative Treatment28:16 - The MAHA Movement & Gen Z Waking Up to Food as Medicine32:08 - Where to Get B17, Enzymes & Rick's Free Resources34:01 - Outro Studio Sponsor: ⁠Cardio Miracle⁠ - "Unlock the secret to a healthier heart, increased energy levels, and transform your cardiovascular fitness like never before.": ⁠CardioMiracle.com/TBNS⁠ LINKS:RNC Store (B17 laetrile & pancreatic enzymes, 10% off with code RICK10): ⁠RNCstore.com⁠Free Book — "Too Young to Die" by Rick Hill: ⁠b17works.com⁠Free Book — "World Without Cancer" by G. Edward Griffin (Chapters 5–7): ⁠myworldwithoutcancer.com⁠ Order ⁠Cardio Miracle⁠ (⁠CardioMiracle.com/TBNS⁠) for 15% off and take a step towards better heart health and overall well-being! WATCH The Brian Nichols Show on ⁠YouTube⁠ & ⁠Rumble⁠. Follow Brian on social media: X.com/Twitter ⁠(https://www.briannicholsshow.com/twitter⁠) & Facebook (⁠https://www.briannicholsshow.com/facebook⁠) LIKE, SHARE, and SUBSCRIBE to ⁠The Brian Nichols Show ⁠for a BRAND NEW episode airing every THURSDAY at 9pm EST! Email Listener Questions to ⁠brian@briannicholsshow.com⁠! Learn more about your ad choices. Visit megaphone.fm/adchoices

When a two-year-old boy suffered a catastrophic injury that severed the connection between his skull and spine, doctors across Europe told his family there was no hope. His spinal cord was completely severed, and the injury was not considered survivable. But University of Chicago neurosurgeon Mohamad Bydon saw a possibility.In this episode of Big Brains, Dr. Bydon walks us through the extraordinary, multi-stage surgery at UChicago that not only saved the boy's life but helped him regain the ability to breathe, talk and move his fingers and toes. He examines the future of surgery for spinal cord injury patients—from minimally invasive surgery techniques to robotic surgery and AI to stem cell therapy—is even helping some paralyzed patients regain movement and even walk again after their injuries. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

It's YOUR time to #EdUp with Karolyn Pearson, Senior Executive Vice President Operations, EducationDynamics, Matt Harris, Sr. Director of Communications, & Scott Bacon, Senior Vice President for External Affairs, Jacksonville UniversityIn this episode, recorded Live from the 2026 InsightsEDU Conference in Fort Lauderdale, Florida, February 17-19,YOUR host is ⁠⁠Dr. Joe SallustioHow does AI create feedback loops for crisis comms by writing coverage in both positive & negative light to prepare for multiple scenarios?Why use AI as thought partner to craft narratives around financial challenges when media members are using AI too?What makes strategic PR shift narrative from lazy financial challenge coverage to addressing workforce needs with Mayo Clinic & Baptist Health partnerships?Listen in to #EdUpThank YOU so much for tuning in. Join us on the next episode for YOUR time to EdUp!Connect with YOUR EdUp Team - ⁠⁠⁠⁠⁠ ⁠⁠⁠⁠⁠Elvin Freytes⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠& ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Dr. Joe Sallustio⁠⁠⁠⁠⁠● Join YOUR EdUp community at ⁠The EdUp Experience⁠We make education YOUR business!P.S. Want to get early, ad-free access & exclusive leadership content to help support the show? Become an #EdUp Premium Member today!

In this episode of “Answers From the Lab,” host Bobbi Pritt, M.D., chair of the Division of Clinical Microbiology at Mayo Clinic, is joined by William Morice II, M.D., Ph.D., president and CEO of Mayo Clinic Laboratories, to discuss recent industry news and how collaborations are helping drive transformation in clinical diagnostics. Together, they explore:Protecting Access to Medicare Act (PAMA) delay (01:09): Dr. Morice shares what the latest delay of PAMA means for laboratories.FDA guidance on wearables (02:23): Learn about recent FDA guidance that allows more non‑invasive wearables to be classified as wellness devices. Collaboration as a driver of innovation (06:20): Discover why collaboration is critical to advancement in clinical diagnostics.Note: Information in this post was accurate at the time of its posting.ResourcesGroundbreaking collaborationsMary Jo Williamson offers four steps to maximize collaboration benefitsDr. Bill Morice shares how a platform for collaboration transforms diagnostics“Answers From the Lab” podcast: “Forging Collaborations That Deliver Better Outcomes”

Dr. Earl J. Campazzi is board certified and has trained and practiced at some of the finest medical institutions in the country. At the Mayo Clinic in Rochester, Minnesota, Dr. Campazzi spent several years on staff providing medical care and teaching resident physicians. He completed his medical training at The Johns Hopkins University and served as chief resident. He earned his medical doctorate from the University of Pittsburgh School of Medicine. Dr. Campazzi holds additional postgraduate degrees including a Master of Public Health with emphasis in Health Care Policy and Management and a Master of Health Sciences with emphasis in Immunology and Infectious Diseases, both from The Johns Hopkins University Bloomberg School of Public Health. In 2020, he completed The Stanford Genetics and Genomics Certificate program at Stanford University. Dr. Campazzi also earned his Master of Business Administration with Health Services Management concentration from Duke University Fuqua School of Business. He completed his Bachelor of Arts at The Johns Hopkins University.Support the show

Eric is a strategist focused on designing experiences people genuinely desire. Over nearly 20 years, he's worked across hospitality, transportation, and member-based communities—domains where brand, environment, and service design meet. His portfolio includes global experience strategy for Hilton's luxury brands, premium mobility design at Uber, and the member experience vision for NeueHouse. That same foundation has made Eric a trusted partner in health and well-being, where the stakes are high and the details matter. At Cactus, he leads strategy for a high-touch longevity startup in the Middle East and has helped reimagine care delivery and environment design for Canyon Ranch, Mayo Clinic, and more. An anthropologist by training, Eric blends cultural insight with business logic and spatial storytelling. He works closely with CEOs, product leaders, and architects to shape offerings from the ground up. In this episode of the Podcast, brand strategist Eric Matis explores how lessons from consumer brands can transform healthcare experiences. Drawing on his years at Red Scout, Cactus and his multidisciplinary background, Matis discusses brand strategy as the art of finding focus through intention and how those principles apply to patient empowerment, service design, and cultural change in healthcare. Hear how healthcare can move beyond compliance toward engagement, respect, and desirability—from oncology clinics to digital health tools.

Automation is quietly reshaping what happens before, during, and after a medical visit, and for many patients it is almost invisible. In this episode of Tomorrow's Cure, host Cathy Wurzer talks with Mayo Clinic physician leader Dr. Anjali Bhagra and human centered AI expert Dr. Ravi Bapna about how automation and artificial intelligence are changing the way care teams work, how patients access care, and what it takes to keep people at the center of these advances. They share real stories from clinic and hospital settings, including tools that automatically generate notes from complex visits, systems that help triage patients more quickly around the world, and AI that supports earlier diagnosis. The conversation also tackles the hard questions around trust, bias, and burnout. Listeners will hear how thoughtful automation can free up time for human connection and why the future of healthcare is people and technology working together in new ways. How to listen and stay connected:• Subscribe to Tomorrow's Cure on your favorite podcast app and follow the show so you never miss an episode.• Get the latest health information from Mayo Clinic's experts—subscribe to Mayo Clinic's newsletter for free today: ⁠https://mayocl.in/3EcNPNc⁠ Connect with Mayo Clinic:• Like Mayo Clinic on Facebook: https://www.facebook.com/mayoclinic/⁠Follow • Mayo Clinic on Instagram: ⁠https://www.instagram.com/mayoclinic/⁠Follow • Mayo Clinic on X (formerly Twitter): ⁠https://x.com/MayoClinic⁠Follow • Mayo Clinic on Threads: ⁠https://www.threads.net/@mayoclinic

Host: Darryl S. Chutka, M.D.  Guest: Hema Narayanasamy, M.B.B.S.  Pericardial disease represents a spectrum of both inflammatory and non-inflammatory disorders which involve the pericardium, with acute pericarditis being the most common disorder. Although not often seen in a primary care practice, we still need to consider pericarditis as it can masquerade several other more commonly seen conditions. It's important to recognize pericardial disease early and decide who needs an urgent referral or hospitalization for appropriate treatment. What are some of the more common causes of pericardial disease? What are the most commonly encountered symptoms, physical exam findings, imaging results, and lab abnormalities? What are the potential complications? The topic for today's podcast is pericardial disease, and my guest is Dr. Hema Narayanasamy, from the Department of Cardiovascular Disease from the Arizona campus of the Mayo Clinic.  Mayo Clinic Talks: Heart Health | Mayo Clinic School of Continuous Professional Development  Connect with us! Mayo Clinic Talks Podcast Season 6 | Mayo Clinic School of Continuous Professional Development 

Laura Hanley, licensed therapist and workplace consultant at Big Picture Companies, joins The Manufacturing Employer to unpack generational diversity on the shop floor. Drawing from her clinical background at the Mayo Clinic and VA, Laura explains why communication and occupational empathy are key skills in today's manufacturing environment. She breaks down why older and younger workers often talk past each other, how wiring, motivation, and stress responses play into team dynamics, and why leadership rooted in empathy and data-driven insight is essential.

In this special series on Metabolic-Dysfunction Associated Steatotic Liver Disease (MASLD) and Metabolic Dysfunction-associated steatohepatitis (MASH) our host, Dr. Neil Skolnik will discuss diagnosis and treatment of MASH using a case-based approach with two master clinicians, one a hepatologist and the other a primary care physician. This special episode is supported by an independent educational grant from Boehringer Ingelheim. Presented by: Neil Skolnik, M.D., Professor of Family and Community Medicine, Sidney Kimmel Medical College, Thomas Jefferson University; Associate Director, Family Medicine Residency Program, Abington Jefferson Health Alina M. Allen, M.D. Associate Professor of Medicine at Mayo Clinic in Rochester, Minnesota, where she serves as the Director of Hepatology and Director of the MASLD Clinic. Susan Kuchera, M.D. - Program Director of the Jefferson Health Abington Family Medicine Residency Program, Clinical Associate Professor of Family and Community Medicine in the Sidney Kimmel Medical College of Thomas Jefferson University Selected references: Metabolic Dysfunction–Associated Steatotic Liver Disease (MASLD) in People With Diabetes: The Need for Screening and Early Intervention. A Consensus Report of the American Diabetes Association. Diabetes Care 2025;48(7):1057–1082  

Translating the DGA Into Real-World Cardiometabolic Care   Guest: Stephen L. Kopecky, M.D. Host: Kyla M. Lara-Breitinger, M.D., M.H.S.   In this third episode roundtable, Dr. Lara Breitinger and Dr. Steve Kopecky examine what the DGAs get right—and where they fall short—for cardiovascular risk, from their emphasis on whole-food patterns to ongoing gaps around food processing, nutrient oversimplification, and sustainability messaging. They share how they translate the guidelines into real-world cardiometabolic care, including the evidence-based principles they use in clinic and when to individualize beyond national recommendations. Looking ahead, they explore the future of nutrition guidance—food as medicine, precision cardiometabolic care, and outcomes-driven recommendations—reminding listeners that the DGA is a starting point and to focus on "one bite at a time."   Topics Discussed: The mismatch between guidelines and patients What the DGA gets right—and wrong—for CV risk How you counsel patients today Where nutrition guidance needs to go next   Connect with Mayo Clinic's Cardiovascular Continuing Medical Education online at https://cveducation.mayo.edu or on Twitter @MayoClinicCV and @MayoCVservices. LinkedIn: Mayo Clinic Cardiovascular Services Cardiovascular Education App: The Mayo Clinic Cardiovascular CME App is an innovative educational platform that features cardiology-focused continuing medical education wherever and whenever you need it. Use this app to access other free content and browse upcoming courses. Download it for free in Apple or Google stores today! No CME credit offered for this episode.   Podcast episode transcript found here.   Recorded on: 10-February-2026

Dr. Dawn Mussallem is a Mayo Clinic oncologist who survived stage 4 cancer at 26, heart failure, and a heart transplant—then became the first person to run a marathon within a year of receiving a new heart. This conversation explores the integrative approach to cancer treatment, why exercise might be as powerful as chemotherapy, the self-flagellation patients feel despite doing everything right, and the profound role of mindset in survival. Typically, my guests fall into two buckets—incredible story or incredible expertise. I don't know that I've ever had a guest who inhabits both worlds the way Dawn does. Her story is super inspirational, and the information is equally impactful. Enjoy! ⁠Show notes + MORE⁠ ⁠Watch on YouTube⁠ ⁠Newsletter Sign-Up⁠ Today's Sponsors: Noble Mobile: The first phone carrier that pays you to use your phone less. Try it for just $10 with code RICHROLL

 In this episode, Praneetha Elugunti of Mayo Clinic explores how health care leaders can balance innovation with human-centered care. She shares insights on leveraging AI responsibly, investing in workforce development, and creating connected, personalized care experiences across physical, digital, and virtual environments.

 In this episode of Your Checkup, we explore a new study from the Mayo Clinic examining whether menopause hormone therapy enhances weight loss outcomes in postmenopausal women taking tirzepatide. Menopause is a major metabolic turning point — with rising visceral fat, declining muscle mass, and increasing cardiovascular risk. Researchers found that women using hormone therapy while on tirzepatide lost significantly more weight — nearly 5% more total body weight — and experienced additional cardiometabolic improvements compared to women not using hormones. We break down what this means, why estrogen may play a synergistic role, what the study does not prove, and how to think about personalized obesity treatment during midlife. Send us a message with this link, we would love to hear from you. Standard message rates may apply.Support the showProduction and Content: Edward Delesky, MD, DABOM & Nicole Aruffo, RN Artwork Rebrand and Avatars: Vantage Design Works (Vanessa Jones) Website: https://www.vantagedesignworks.com/ Instagram: https://www.instagram.com/vantagedesignworks?igsh=aHRuOW93dmxuOG9m&utm_source=qr Original Artwork Concept: Olivia Pawlowski

Breast cancer screening fails most often where access is constrained: limited appointments, geographic gaps, dense breast tissue, and reliance on self-exams that depend entirely on human touch. Awareness alone doesn't close those gaps.In this episode, Dr. Karny Ilan, co-founder and CEO of Feminai, shares how physician-led product design, multidisciplinary collaboration, and rigorous clinical trials shaped a new model for breast screening access. The conversation explores a shift in how breast health is managed—from episodic screening to continuous, individualized monitoring. Rather than relying on infrequent appointments alone, it examines tools designed to track changes over time, at home, while remaining connected to clinical decision-making. Timestamps(00:11) Breast cancer risk shaped by genetics and lived exposure(08:37) Limits of traditional self-breast exams(09:09) Personal experience shaping breast health urgency(10:15) How at-home breast scanning detects change over time(12:42) Designing screening tools for dense breast tissue(17:03) Addressing breast size, shape, and post-surgical variation(18:31) Clinical trials revealing real-world usability gaps(20:13) Why ease of use affects screening reliability(29:29) Access gaps amplified by pandemic-era screening delays(38:09) Broad inclusion across age, risk, and body types Guest BioDr. Karny Ilan — Co-Founder and CEO, FeminaiDr. Karny Ilan is a general surgery resident at Sheba Medical Center and the co-founder and CEO of Feminai, a breast health company developing an AI-enabled disposable wearable patch and app for at-home breast exams. With a strong family history of breast cancer, she brings clinical experience and patient-centered design to building scalable screening tools that expand access and personalization.LinkedIn: https://www.linkedin.com/in/karny-ilan/Key PointsAccess constraints drive missed detection: Feminai targets screening gaps caused by geography, capacity, and avoidance.Physician-led design builds trust: Clinical credibility accelerated adoption with providers and investors.Dense breast tissue is a priority use case: The technology is designed to perform well where mammography often struggles.Personalized baselines change detection logic: Each scan is compared against the user's own prior data.Usability directly affects accuracy: Instructions, fit, and behavior shape downstream AI performance.Deep Dives1. At-home breast exams as infrastructureDesigned for frequent, low-friction useComplements rather than replaces imaging2. Patch and app workflowRisk stratification via medical questionnaireBluetooth-enabled scan uploads to secure cloudAI analysis with physician review3. Designing for every bodyStretch materials accommodate size variationDense tissue explicitly accounted forAdditional sizes planned as rollout expands4. Clinical trials beyond performance metricsUsability drove multiple design iterationsInstruction format affected adherenceShape changes required algorithm updates5. Personalized longitudinal trackingEach woman compared only to herselfChanges flagged based on deviation, not population averages6. Leadership and multidisciplinary teamsEngineers exposed to clinical sitesPatient stories shared to reinforce missionStability in leadership communication protected executionLinks & ReferencesBreast cancer screening beyond mammography (Mayo Clinic): https://www.mayoclinic.org/tests-procedures/mammogram/in-depth/breast-cancer/art-20047233Breast cancer screening recommendations (USPSTF): https://www.uspreventiveservicestaskforce.org/uspstf/recommendation/breast-cancer-screening

In this episode, Praneetha Elugunti of Mayo Clinic explores how health care leaders can balance innovation with human-centered care. She shares insights on leveraging AI responsibly, investing in workforce development, and creating connected, personalized care experiences across physical, digital, and virtual environments.

Human beings can't truly multitask. You can only focus on one thing at a time—and at the deepest level, that's either love or fear. In this episode, Dr. Alex Loyd and Harry explore: The neuroscience of attention (you can only focus on 1-3 things consciously) Mayo Clinic's proof: fear-based thinking creates disease, love-based thinking creates health Why 80% of people lean toward fear The Parable of the Sower: how "cares of the world" fragment you How to stop treating God like a vending machine The Hidden Treasure parable: going all in on what matters most Episode Highlights: → Intention (subconscious) vs. Attention (conscious) - and the will that connects them → Your unconscious processes 1,000-3,000 things at once (that's why dreams are weird) → The prayer shift that changed everything for Dr. Alex → Why you can't serve two masters New episodes every 2nd, 3rd & 4th Wednesday. Subscribe now!

Julia and Drew are back in the studio to discuss Season 10, Episode 2 of Summer House. The girls crack open an ice cold Loverboy and dish about Kyle and Amanda's drama vortex, Bad Bunny's incredible Super Bowl performance, Lexi Wood's new talent agency, chewing gum as jaw-defining practicum, and an investigative report into David's new line of "protein fish." XOXO, Girls Room.Follow Girls Room on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠TikTok⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.Follow Drew on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Twitter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.Follow Julia on ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Twitter⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ and ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Instagram⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠.

What if lasting energy and better health didn't require complicated routines or constant stress? In this episode, Dr. Debbie Ozment, DDS, shares her refreshingly simple approach to enhancing vitality, preventing disease, and creating sustainable wellness habits that truly work. As the host of the Vitality Made Simple podcast, Dr. Ozment focuses on early detection, prevention, and practical strategies that help people feel their best at every stage of life. With decades of experience in dentistry and integrative health, she highlights how oral health, inflammation, toxins, and emotional stress can quietly drain energy and impact long-term wellbeing — and what you can do about it. In this conversation, we explore: ·       How small, consistent lifestyle changes can extend your vitality span ·       The connection between oral health, inflammation, and chronic disease prevention ·       Simple, stress-free ways to support mental, emotional, and physical wellness Dr. Ozment has been in private dental practice since 1985 and is a graduate of the University of Oklahoma College of Dentistry. She later earned a Master's degree in Metabolic and Nutritional Medicine from the University of South Florida Morsani College of Medicine and is a Diplomate of the American Academy of Anti-Aging Medicine. Trained at the Mayo Clinic and certified as a National Board-Certified Health and Wellness Coach, she brings a truly integrative perspective to modern health. Follow Dr. Ozment on Instagram @drdebbieozment to stay up to date with her latest insights and resources. Episode also available on Apple Podcasts: https://apple.co/38oMlMr  Keep up with Debbie Ozment socials here: Facebook: https://www.facebook.com/drdebbieozment/ Youtube: https://www.youtube.com/@drdebbieozment

JU Nursing Professors Dr. Lindsay Wolf & Joseph Fitzgerald discuss programs for non-nursing background students to admit directy into Bachelor in Nursing and Master's in Nursing degree programs, including NCLEX exam eligibility, with an emphasis on bedside care and serving patients in the local community. Visit WWW.JU.EDU/NURSING to learn more.

Many serious medical illnesses are associated with some degree of serum electrolyte abnormality, renal impairment, or both. The neurologist must determine if the patient's neurologic symptoms are related to the renal and electrolyte disturbances or whether a concurrent primary neurologic process is at play. In this episode, Casey Albin, MD, speaks with Eelco F. M. Wijdicks, MD, PhD, FAAN, FACP, FNCS, author of the article "Neurologic Manifestations of Renal and Electrolyte Disorders" in the Continuum® February 2026 Neurology of Systemic Disease issue. Dr. Albin is a Continuum® Audio interviewer, associate editor of media engagement, and an assistant professor of neurology and neurosurgery at Emory University School of Medicine in Atlanta, Georgia. Dr. Wijdicks is a professor of neurology and attending neurointensivist for the Neurosciences Intensive Care Unit at Mayo Clinic in Rochester, Minnesota. Additional Resources Read the article: Neurologic Manifestations of Renal and Electrolyte Disorders Subscribe to Continuum®: shop.lww.com/Continuum Earn CME (available only to AAN members): continpub.com/AudioCME Continuum® Aloud (verbatim audio-book style recordings of articles available only to Continuum® subscribers): continpub.com/Aloud More about the American Academy of Neurology: aan.com Social Media facebook.com/continuumcme @ContinuumAAN Host: @caseyalbin Guest: @EWijdicks Full episode transcript available here

For a century, Mayo Clinic Proceedings has captured the evolution of modern medicine, from pioneering cortisone therapy to today's breakthroughs in artificial intelligence and digital diagnostics. In this episode of Tomorrow's Cure from Mayo Clinic, host Cathy Wurzer talks with Editor in Chief Dr. Karl Nath and hematologist and longtime contributor Dr. Vincent Rajkumar about the journal's origins, its global influence, and how it helps physicians turn complex science into practical care.​ They explore innovations such as AI enabled ECGs that can reveal hidden heart rhythm problems, voice biomarkers that may flag cardiovascular disease from a simple speech sample, stem cell approaches for spinal cord injury, and novel therapies that emerged from Mayo Clinic Proceedings and went on to reshape clinical practice.Listen to hear how Mayo Clinic Proceedings is preparing for its second century as a trusted guide to evidence based medicine. How to listen and stay connected:• Subscribe to Tomorrow's Cure on your favorite podcast app and follow the show so you never miss an episode.• Get the latest health information from Mayo Clinic's experts—subscribe to Mayo Clinic's newsletter for free today: ⁠https://mayocl.in/3EcNPNc⁠ Connect with Mayo Clinic:• Like Mayo Clinic on Facebook: https://www.facebook.com/mayoclinic/⁠Follow • Mayo Clinic on Instagram: ⁠https://www.instagram.com/mayoclinic/⁠Follow • Mayo Clinic on X (formerly Twitter): ⁠https://x.com/MayoClinic⁠Follow • Mayo Clinic on Threads: ⁠https://www.threads.net/@mayoclinic

Host: Darryl S. Chutka, M.D.  Guest: Stephen Kopecky, M.D.  We have a variety of pharmacologic options and lifestyle changes we recommend to our patients to reduce their cardiovascular risks. One frequent recommendation is participation in a regular exercise program. One specific type of exercise is high intensity interval training. It's been shown to improve a variety of metabolic parameters. What does high intensity interval training consist of? What are the specific metabolic benefits? Can all patients participate in this type of exercise? What's the recommended duration and frequency of training and how good is patient adherence to interval training? The topic for this podcast is “High Intensity Interval Training and Reducing Cardiovascular Risk” and my guest is Dr. Stephen Kopecky, a preventive cardiologist in the Department of Cardiovascular Disease at the Mayo Clinic.  Connect with us! Mayo Clinic Talks Podcast Season 6 | Mayo Clinic School of Continuous Professional Development 

Episode SummaryWhat happens when a systems girl has a heart and actually cares about people. This one starts with negative twenty one degrees and ends with an absolute mic drop on service, strategy, and building a business that does not eat your identity alive. Rachel Traxler brings the rare combo of warmth and tactical clarity, and Miles and Jared go right where photographers actually live: the tension between art, family, ambition, burnout, and the pressure to do it all.If you have ever thought “I just need more inquiries,” Rachel lovingly corrects you. If you have ever felt the hat switching guilt spiral, she names it. If you have ever wanted a simpler way to set goals that actually get finished, she lays out the framework.Why toxic positivity is a turnoff and how Rachel stays upbeat without becoming fluffThe real issue most photographers have is not visibility, it is conversionHow to use your conversion rate to set realistic inquiry goalsWhy creatives avoid goals and how vague goals secretly protect our excusesThe quarterly sprint method: treat Q1 like the whole year and build momentum fastCapacity, prioritizing, and the uncomfortable truth that you cannot crush every hat at the same timeStreamlining life outside of business to protect your bandwidth (yes, even grocery delivery)Vendor referrals versus social inquiries and why quality leads matter more than quantityLeaving a stable job to chase photography and why “plan B” is not always requiredIdentity and work: when your job becomes who you are, the roller coaster gets brutalThe gratitude reset and why your best life metrics are rarely gear or numbersRachel's background at Mayo Clinic working with women facing ovarian cancer and how it shaped her perspectiveThe mic drop moment: service as the foundation that makes systems actually meaningfulMore inquiries is not always the answer. Sometimes you have enough leads and your conversion is the leakIf your goal is one wedding a month and your conversion is 25 percent, you only need four solid inquiriesDo not build marketing systems until you know your numbers and your actual goalsQuarterly goals beat vague yearly dreams. Short sprints create real tractionYour business should serve your life, not replace your identityJoin PHOTOCO Membership (monthly trainings, exclusive guest experts, community): https://thephotographiccollective.comPHOTOCO Podcast: https://thephotographiccollective.com/podcastPHOTOCO AfterCast and member exclusives: https://thephotographiccollective.comMiles Witt Boyer on Instagram: https://instagram.com/mileswittboyerRachel Traxler on Instagram: https://instagram.com/racheltraxlerStrategy is serving. Systems are not cold. They are how you love people better.If you loved this episode, send it to a photographer friend who keeps saying “I just need more inquiries.” Then go look at your conversion rate like an adult.If you thought this episode was good, the AfterCast is where it gets dangerous.In the public episode we talk big ideas: goals, capacity, conversion, and building a business that does not eat your life.In the AfterCast we get specific.We pull the curtain back on what to actually do next, how to think about your numbers, and how to build systems that do not feel robotic or fake.If you are tired of listening to inspiration and still not knowing what to change on Monday morning, you want the AfterCast.Join PHOTOCO for less than $50 a month and get access to the AfterCast, member only trainings, guest experts, and a community of photographers who are building the same thing right alongside you.Come for the episode.Stay for the blueprint.

Applications of the New DGA   Guest: Tara Schmidt, RDN, LD Host: Kyla Lara-Breitinger, M.D., M.H.S.   Every five years, new dietary guidelines for Americans are put out by the U.S. Department of Health and Human Services (HHS) and U.S. Department of Agriculture (USDA). The Dietary Guidelines for Americans, 2025-2030 (10th edition) was recently published in early 2026 and has sparked some controversy with not only its visual icon, but some of its emphases as well. In this second episode reviewing the new DGA, Dr. Kyla-Lara Breitinger and Tara Schmidt, RDN, LD review what the new guidelines advise and what may be confusing for consumers.     Topics Discussed: Do you want to share a bit of history around the DGAs? What recommendations from the new DGAs align with longstanding nutrition science? Are there elements of the new guidelines that raise any concern? What should be some key nutritional focuses for Americans, given what we know about their health status?   Connect with Mayo Clinic's Cardiovascular Continuing Medical Education online at https://cveducation.mayo.edu or on Twitter @MayoClinicCV and @MayoCVservices. LinkedIn: Mayo Clinic Cardiovascular Services Cardiovascular Education App: The Mayo Clinic Cardiovascular CME App is an innovative educational platform that features cardiology-focused continuing medical education wherever and whenever you need it. Use this app to access other free content and browse upcoming courses. Download it for free in Apple or Google stores today! No CME credit offered for this episode.   Podcast episode transcript found here.   Recorded on: 05-February-2026

Dr. Dawn Mussallem shares her inspiring journey of overcoming significant health challenges, including a battle with stage four cancer. She discusses the importance of a supportive community, the role of spirituality in her healing process, and the lessons learned from adversity. Dr. Mussallem emphasizes the significance of nutrition and healthy living, advocating for both women's and men's health, and the need for personalized medical care. Her story is a testament to resilience, love, and the power of human connection. Kimberly and Dawn Mussallem discuss the importance of nutrition for healthy aging, emphasizing the need to eliminate processed foods and increase fiber intake. They explore the significance of protein, particularly plant-based sources, and debunk myths surrounding soy consumption. Dawn shares her transition from the Mayo Clinic to Fountain Life, focusing on advanced diagnostics and personalized wellness strategies.Chapters00:00 Introduction and Background03:02 Overcoming Adversity: Dawn's Health Journey05:51 The Impact of Cancer Diagnosis09:02 Navigating Treatment and Finding Meaning11:59 Spirituality and Connection in Healing15:01 The Role of Support and Community17:49 Life After Cancer: Motherhood and Challenges21:09 Advanced Heart Failure and Resilience23:59 The Gift of Life and Family28:40 The Unexpected Loss31:41 Men's Health Advocacy35:44 Integrating Lifestyle and Medicine39:42 Food as Medicine47:57 The Path to Healthy Aging52:58 Navigating Food Safety and Additives53:54 Plant-Based Proteins and Dining Out56:24 Debunking Soy Myths and Breast Cancer58:47 The Role of Soy in Cancer Prevention01:00:38 Red Meat vs. Plant Proteins01:02:26 Healthy Eating Guidelines for Families01:04:35 The Importance of Whole Foods01:07:44 Innovations in Plant-Based Proteins01:10:38 Dawn's Transition to Fountain LifeSponsors: LMNTOFFER: Right now, for my listeners LMNT is offering a free sample pack with any LMNT drink mix purchase at DrinkLMNT.com/FEELGOOD. That's 8 single serving packets FREE with any LMNT any LMNT drink mix purchase. This deal is only available through my link so. Also try the new LMNT Sparkling — a bold, 16-ounce can of sparkling electrolyte water.USE LINK: DrinkLMNT.com/FEELGOODFATTY15 OFFER: Fatty15 is on a mission to replenish your C15 levels and restore your long-term health. You can get an additional 15% off their 90-day subscription Starter Kit by going to fatty15.com/KIMBERLY and using code KIMBERLY at checkout.USE LINK: fatty15.com/KIMBERLY Dr. Dawn Mussallem Resources: Website: fountainlife.com Instagram: @drdawnmussallem Bio: Dr. Dawn Mussallem is a distinguished consultant in the Division of Hematology Oncology at Mayo Clinic, where she has served as a clinician for over 20 years, and an Assistant Professor of Medicine.She is also a board-certified lifestyle medicine breast specialist at The Robert and Monica Jacoby Center for Breast Health and founded the Integrative Medicine and Breast Health Program at Mayo Clinic Florida.A stage IV cancer survivor diagnosed three months into medical school, Dr. Mussallem's personal journey is a testament to resilience and determination.In 2021, she underwent a heart transplant and remarkably became the first person to run a marathon one year post-transplant. Internationally recognized for her work in cancer prevention and integrative oncology, she is a prolific speaker and author. Her dedication to patient care and innovative approaches align perfectly with IM8's mission, making her an invaluable addition to the Medical Advisory Board.See Privacy Policy at https://art19.com/privacy and California Privacy Notice at https://art19.com/privacy#do-not-sell-my-info.

Midlife health decisions rarely fail because women “don't know what to do.” They fail because the stakes change overnight, the calendar stays overloaded, and the system you used to rely on stops working.This conversation sits at the intersection of two realities: breast cancer can show up even without family history, and the perimenopause to menopause transition forces a new level of precision around hormones, bone health, fatigue, and what you put on your skin.In this episode, Sally Mueller, co-founder of Womaness, speak candidly from lived experience—diagnosis timelines, treatment tradeoffs, dense breast screening gaps, and the unglamorous but decisive habits that actually keep women on track.Timestamps(03:16) Following instincts as an early prevention strategy (11:18) Clean, hormone-free formulations and long-term exposure risk (12:58) Hereditary versus environmental drivers of breast cancer (20:20) Dense breast tissue and proactive screening strategies (27:31) Vitamin D deficiency and systemic fatigue signals (28:49) Supplement consistency versus reactive use (32:32) Why steady supplementation outperforms short-term fixes (36:18) Bone health through impact, resistance, and movement variety (40:07) Exercise variation as a stimulus for bone remodeling (41:47) Treating exercise like a non-negotiable meeting Guest BioSally Mueller — Co-Founder and CEO, WomanessSally Mueller is the co-founder of Womaness, a women's wellness brand focused on perimenopause and menopause solutions across skin, body, supplements, and sexual wellness.LinkedIn: https://www.linkedin.com/in/sally-mueller/Key PointsMidlife health breakdown is often a systems failure, not a motivation problem: Delayed screenings, inconsistent supplements, and deprioritized movement compound risk over time.Early detection depends on follow-through, not awareness: Dense breast tissue, hormone shifts, and missed baselines create blind spots when care is delayed.Consistency beats intensity in supplements and exercise: Vitamin D, bone-loading movement, and simple routines outperform sporadic “health resets.”Clean inputs matter more after cancer, but should start earlier: What women put on and in their bodies becomes more consequential during hormonal transition.Exercise functions as prevention infrastructure, not lifestyle garnish: Impact, resistance, and aerobic movement materially affect recurrence risk, bone density, and fatigue.Deep DivesDelayed care as a compounding risk factorMissed appointments increase exposure windowsDelays often happen during peak hormonal volatilityDense breast tissue and the screening gapMammograms alone can miss early signalsUltrasound and MRI baselines improve detectionVitamin D deficiency as a hidden performance drainFatigue and joint pain can signal depletionWinter and low sun accelerate declineSupplement discipline versus reactive useInconsistent intake reduces benefitFewer supplements taken regularly outperform complex stacksBone health beyond medicationImpact and resistance stimulate bone remodelingMovement variety matters more than volumeExercise as a protective interventionAerobic activity reduces systemic disease riskStrength work supports bone and joint resilienceClean formulations and cumulative exposureHormone-free products reduce added loadTransparency matters more during midlife transitionsWhy midlife routines collapse firstCaregiving, careers, and stress convergeHealth behaviors are usually the first to dropTreating exercise like a meetingScheduled movement increases adherenceNon-negotiable time blocks protect consistencyPrevention as an operating modelMidlife health requires durable systemsShort-term fixes fail under long timelinesLinks & ReferencesBreast cancer screening beyond mammography (Mayo Clinic): https://www.mayoclinic.org/tests-procedures/mammogram/in-depth/breast-cancer/art-20047233Vitamin D deficiency, symptoms, and testing (National Institutes of Health): https://ods.od.nih.gov/factsheets/VitaminD-Consumer/Exercise and bone health in midlife and beyond (International Osteoporosis Foundation): https://www.osteoporosis.foundation/health-professionals/prevention/exercise

From Palantir and Two Sigma to building Goodfire into the poster-child for actionable mechanistic interpretability, Mark Bissell (Member of Technical Staff) and Myra Deng (Head of Product) are trying to turn “peeking inside the model” into a repeatable production workflow by shipping APIs, landing real enterprise deployments, and now scaling the bet with a recent $150M Series B funding round at a $1.25B valuation.In this episode, we go far beyond the usual “SAEs are cool” take. We talk about Goodfire's core bet: that the AI lifecycle is still fundamentally broken because the only reliable control we have is data and we post-train, RLHF, and fine-tune by “slurping supervision through a straw,” hoping the model picks up the right behaviors while quietly absorbing the wrong ones. Goodfire's answer is to build a bi-directional interface between humans and models: read what's happening inside, edit it surgically, and eventually use interpretability during training so customization isn't just brute-force guesswork.Mark and Myra walk through what that looks like when you stop treating interpretability like a lab demo and start treating it like infrastructure: lightweight probes that add near-zero latency, token-level safety filters that can run at inference time, and interpretability workflows that survive messy constraints (multilingual inputs, synthetic→real transfer, regulated domains, no access to sensitive data). We also get a live window into what “frontier-scale interp” means operationally (i.e. steering a trillion-parameter model in real time by targeting internal features) plus why the same tooling generalizes cleanly from language models to genomics, medical imaging, and “pixel-space” world models.We discuss:* Myra + Mark's path: Palantir (health systems, forward-deployed engineering) → Goodfire early team; Two Sigma → Head of Product, translating frontier interpretability research into a platform and real-world deployments* What “interpretability” actually means in practice: not just post-hoc poking, but a broader “science of deep learning” approach across the full AI lifecycle (data curation → post-training → internal representations → model design)* Why post-training is the first big wedge: “surgical edits” for unintended behaviors likereward hacking, sycophancy, noise learned during customization plus the dream of targeted unlearning and bias removal without wrecking capabilities* SAEs vs probes in the real world: why SAE feature spaces sometimes underperform classifiers trained on raw activations for downstream detection tasks (hallucination, harmful intent, PII), and what that implies about “clean concept spaces”* Rakuten in production: deploying interpretability-based token-level PII detection at inference time to prevent routing private data to downstream providers plus the gnarly constraints: no training on real customer PII, synthetic→real transfer, English + Japanese, and tokenization quirks* Why interp can be operationally cheaper than LLM-judge guardrails: probes are lightweight, low-latency, and don't require hosting a second large model in the loop* Real-time steering at frontier scale: a demo of steering Kimi K2 (~1T params) live and finding features via SAE pipelines, auto-labeling via LLMs, and toggling a “Gen-Z slang” feature across multiple layers without breaking tool use* Hallucinations as an internal signal: the case that models have latent uncertainty / “user-pleasing” circuitry you can detect and potentially mitigate more directly than black-box methods* Steering vs prompting: the emerging view that activation steering and in-context learning are more closely connected than people think, including work mapping between the two (even for jailbreak-style behaviors)* Interpretability for science: using the same tooling across domains (genomics, medical imaging, materials) to debug spurious correlations and extract new knowledge up to and including early biomarker discovery work with major partners* World models + “pixel-space” interpretability: why vision/video models make concepts easier to see, how that accelerates the feedback loop, and why robotics/world-model partners are especially interesting design partners* The north star: moving from “data in, weights out” to intentional model design where experts can impart goals and constraints directly, not just via reward signals and brute-force post-training—Goodfire AI* Website: https://goodfire.ai* LinkedIn: https://www.linkedin.com/company/goodfire-ai/* X: https://x.com/GoodfireAIMyra Deng* Website: https://myradeng.com/* LinkedIn: https://www.linkedin.com/in/myra-deng/* X: https://x.com/myra_dengMark Bissell* LinkedIn: https://www.linkedin.com/in/mark-bissell/* X: https://x.com/MarkMBissellFull Video EpisodeTimestamps00:00:00 Introduction00:00:05 Introduction to the Latent Space Podcast and Guests from Goodfire00:00:29 What is Goodfire? Mission and Focus on Interpretability00:01:01 Goodfire's Practical Approach to Interpretability00:01:37 Goodfire's Series B Fundraise Announcement00:02:04 Backgrounds of Mark and Myra from Goodfire00:02:51 Team Structure and Roles at Goodfire00:05:13 What is Interpretability? Definitions and Techniques00:05:30 Understanding Errors00:07:29 Post-training vs. Pre-training Interpretability Applications00:08:51 Using Interpretability to Remove Unwanted Behaviors00:10:09 Grokking, Double Descent, and Generalization in Models00:10:15 404 Not Found Explained00:12:06 Subliminal Learning and Hidden Biases in Models00:14:07 How Goodfire Chooses Research Directions and Projects00:15:00 Troubleshooting Errors00:16:04 Limitations of SAEs and Probes in Interpretability00:18:14 Rakuten Case Study: Production Deployment of Interpretability00:20:45 Conclusion00:21:12 Efficiency Benefits of Interpretability Techniques00:21:26 Live Demo: Real-Time Steering in a Trillion Parameter Model00:25:15 How Steering Features are Identified and Labeled00:26:51 Detecting and Mitigating Hallucinations Using Interpretability00:31:20 Equivalence of Activation Steering and Prompting00:34:06 Comparing Steering with Fine-Tuning and LoRA Techniques00:36:04 Model Design and the Future of Intentional AI Development00:38:09 Getting Started in Mechinterp: Resources, Programs, and Open Problems00:40:51 Industry Applications and the Rise of Mechinterp in Practice00:41:39 Interpretability for Code Models and Real-World Usage00:43:07 Making Steering Useful for More Than Stylistic Edits00:46:17 Applying Interpretability to Healthcare and Scientific Discovery00:49:15 Why Interpretability is Crucial in High-Stakes Domains like Healthcare00:52:03 Call for Design Partners Across Domains00:54:18 Interest in World Models and Visual Interpretability00:57:22 Sci-Fi Inspiration: Ted Chiang and Interpretability01:00:14 Interpretability, Safety, and Alignment Perspectives01:04:27 Weak-to-Strong Generalization and Future Alignment Challenges01:05:38 Final Thoughts and Hiring/Collaboration Opportunities at GoodfireTranscriptShawn Wang [00:00:05]: So welcome to the Latent Space pod. We're back in the studio with our special MechInterp co-host, Vibhu. Welcome. Mochi, Mochi's special co-host. And Mochi, the mechanistic interpretability doggo. We have with us Mark and Myra from Goodfire. Welcome. Thanks for having us on. Maybe we can sort of introduce Goodfire and then introduce you guys. How do you introduce Goodfire today?Myra Deng [00:00:29]: Yeah, it's a great question. So Goodfire, we like to say, is an AI research lab that focuses on using interpretability to understand, learn from, and design AI models. And we really believe that interpretability will unlock the new generation, next frontier of safe and powerful AI models. That's our description right now, and I'm excited to dive more into the work we're doing to make that happen.Shawn Wang [00:00:55]: Yeah. And there's always like the official description. Is there an understatement? Is there an unofficial one that sort of resonates more with a different audience?Mark Bissell [00:01:01]: Well, being an AI research lab that's focused on interpretability, there's obviously a lot of people have a lot that they think about when they think of interpretability. And I think we have a pretty broad definition of what that means and the types of places that can be applied. And in particular, applying it in production scenarios, in high stakes industries, and really taking it sort of from the research world into the real world. Which, you know. It's a new field, so that hasn't been done all that much. And we're excited about actually seeing that sort of put into practice.Shawn Wang [00:01:37]: Yeah, I would say it wasn't too long ago that Anthopic was like still putting out like toy models or superposition and that kind of stuff. And I wouldn't have pegged it to be this far along. When you and I talked at NeurIPS, you were talking a little bit about your production use cases and your customers. And then not to bury the lead, today we're also announcing the fundraise, your Series B. $150 million. $150 million at a 1.25B valuation. Congrats, Unicorn.Mark Bissell [00:02:02]: Thank you. Yeah, no, things move fast.Shawn Wang [00:02:04]: We were talking to you in December and already some big updates since then. Let's dive, I guess, into a bit of your backgrounds as well. Mark, you were at Palantir working on health stuff, which is really interesting because the Goodfire has some interesting like health use cases. I don't know how related they are in practice.Mark Bissell [00:02:22]: Yeah, not super related, but I don't know. It was helpful context to know what it's like. Just to work. Just to work with health systems and generally in that domain. Yeah.Shawn Wang [00:02:32]: And Mara, you were at Two Sigma, which actually I was also at Two Sigma back in the day. Wow, nice.Myra Deng [00:02:37]: Did we overlap at all?Shawn Wang [00:02:38]: No, this is when I was briefly a software engineer before I became a sort of developer relations person. And now you're head of product. What are your sort of respective roles, just to introduce people to like what all gets done in Goodfire?Mark Bissell [00:02:51]: Yeah, prior to Goodfire, I was at Palantir for about three years as a forward deployed engineer, now a hot term. Wasn't always that way. And as a technical lead on the health care team and at Goodfire, I'm a member of the technical staff. And honestly, that I think is about as specific as like as as I could describe myself because I've worked on a range of things. And, you know, it's it's a fun time to be at a team that's still reasonably small. I think when I joined one of the first like ten employees, now we're above 40, but still, it looks like there's always a mix of research and engineering and product and all of the above. That needs to get done. And I think everyone across the team is, you know, pretty, pretty switch hitter in the roles they do. So I think you've seen some of the stuff that I worked on related to image models, which was sort of like a research demo. More recently, I've been working on our scientific discovery team with some of our life sciences partners, but then also building out our core platform for more of like flexing some of the kind of MLE and developer skills as well.Shawn Wang [00:03:53]: Very generalist. And you also had like a very like a founding engineer type role.Myra Deng [00:03:58]: Yeah, yeah.Shawn Wang [00:03:59]: So I also started as I still am a member of technical staff, did a wide range of things from the very beginning, including like finding our office space and all of this, which is we both we both visited when you had that open house thing. It was really nice.Myra Deng [00:04:13]: Thank you. Thank you. Yeah. Plug to come visit our office.Shawn Wang [00:04:15]: It looked like it was like 200 people. It has room for 200 people. But you guys are like 10.Myra Deng [00:04:22]: For a while, it was very empty. But yeah, like like Mark, I spend. A lot of my time as as head of product, I think product is a bit of a weird role these days, but a lot of it is thinking about how do we take our frontier research and really apply it to the most important real world problems and how does that then translate into a platform that's repeatable or a product and working across, you know, the engineering and research teams to make that happen and also communicating to the world? Like, what is interpretability? What is it used for? What is it good for? Why is it so important? All of these things are part of my day-to-day as well.Shawn Wang [00:05:01]: I love like what is things because that's a very crisp like starting point for people like coming to a field. They all do a fun thing. Vibhu, why don't you want to try tackling what is interpretability and then they can correct us.Vibhu Sapra [00:05:13]: Okay, great. So I think like one, just to kick off, it's a very interesting role to be head of product, right? Because you guys, at least as a lab, you're more of an applied interp lab, right? Which is pretty different than just normal interp, like a lot of background research. But yeah. You guys actually ship an API to try these things. You have Ember, you have products around it, which not many do. Okay. What is interp? So basically you're trying to have an understanding of what's going on in model, like in the model, in the internal. So different approaches to do that. You can do probing, SAEs, transcoders, all this stuff. But basically you have an, you have a hypothesis. You have something that you want to learn about what's happening in a model internals. And then you're trying to solve that from there. You can do stuff like you can, you know, you can do activation mapping. You can try to do steering. There's a lot of stuff that you can do, but the key question is, you know, from input to output, we want to have a better understanding of what's happening and, you know, how can we, how can we adjust what's happening on the model internals? How'd I do?Mark Bissell [00:06:12]: That was really good. I think that was great. I think it's also a, it's kind of a minefield of a, if you ask 50 people who quote unquote work in interp, like what is interpretability, you'll probably get 50 different answers. And. Yeah. To some extent also like where, where good fire sits in the space. I think that we're an AI research company above all else. And interpretability is a, is a set of methods that we think are really useful and worth kind of specializing in, in order to accomplish the goals we want to accomplish. But I think we also sort of see some of the goals as even more broader as, as almost like the science of deep learning and just taking a not black box approach to kind of any part of the like AI development life cycle, whether that. That means using interp for like data curation while you're training your model or for understanding what happened during post-training or for the, you know, understanding activations and sort of internal representations, what is in there semantically. And then a lot of sort of exciting updates that were, you know, are sort of also part of the, the fundraise around bringing interpretability to training, which I don't think has been done all that much before. A lot of this stuff is sort of post-talk poking at models as opposed to. To actually using this to intentionally design them.Shawn Wang [00:07:29]: Is this post-training or pre-training or is that not a useful.Myra Deng [00:07:33]: Currently focused on post-training, but there's no reason the techniques wouldn't also work in pre-training.Shawn Wang [00:07:38]: Yeah. It seems like it would be more active, applicable post-training because basically I'm thinking like rollouts or like, you know, having different variations of a model that you can tweak with the, with your steering. Yeah.Myra Deng [00:07:50]: And I think in a lot of the news that you've seen in, in, on like Twitter or whatever, you've seen a lot of unintended. Side effects come out of post-training processes, you know, overly sycophantic models or models that exhibit strange reward hacking behavior. I think these are like extreme examples. There's also, you know, very, uh, mundane, more mundane, like enterprise use cases where, you know, they try to customize or post-train a model to do something and it learns some noise or it doesn't appropriately learn the target task. And a big question that we've always had is like, how do you use your understanding of what the model knows and what it's doing to actually guide the learning process?Shawn Wang [00:08:26]: Yeah, I mean, uh, you know, just to anchor this for people, uh, one of the biggest controversies of last year was 4.0 GlazeGate. I've never heard of GlazeGate. I didn't know that was what it was called. The other one, they called it that on the blog post and I was like, well, how did OpenAI call it? Like officially use that term. And I'm like, that's funny, but like, yeah, I guess it's the pitch that if they had worked a good fire, they wouldn't have avoided it. Like, you know what I'm saying?Myra Deng [00:08:51]: I think so. Yeah. Yeah.Mark Bissell [00:08:53]: I think that's certainly one of the use cases. I think. Yeah. Yeah. I think the reason why post-training is a place where this makes a lot of sense is a lot of what we're talking about is surgical edits. You know, you want to be able to have expert feedback, very surgically change how your model is doing, whether that is, you know, removing a certain behavior that it has. So, you know, one of the things that we've been looking at or is, is another like common area where you would want to make a somewhat surgical edit is some of the models that have say political bias. Like you look at Quen or, um, R1 and they have sort of like this CCP bias.Shawn Wang [00:09:27]: Is there a CCP vector?Mark Bissell [00:09:29]: Well, there's, there are certainly internal, yeah. Parts of the representation space where you can sort of see where that lives. Yeah. Um, and you want to kind of, you know, extract that piece out.Shawn Wang [00:09:40]: Well, I always say, you know, whenever you find a vector, a fun exercise is just like, make it very negative to see what the opposite of CCP is.Mark Bissell [00:09:47]: The super America, bald eagles flying everywhere. But yeah. So in general, like lots of post-training tasks where you'd want to be able to, to do that. Whether it's unlearning a certain behavior or, you know, some of the other kind of cases where this comes up is, are you familiar with like the, the grokking behavior? I mean, I know the machine learning term of grokking.Shawn Wang [00:10:09]: Yeah.Mark Bissell [00:10:09]: Sort of this like double descent idea of, of having a model that is able to learn a generalizing, a generalizing solution, as opposed to even if memorization of some task would suffice, you want it to learn the more general way of doing a thing. And so, you know, another. A way that you can think about having surgical access to a model's internals would be learn from this data, but learn in the right way. If there are many possible, you know, ways to, to do that. Can make interp solve the double descent problem?Shawn Wang [00:10:41]: Depends, I guess, on how you. Okay. So I, I, I viewed that double descent as a problem because then you're like, well, if the loss curves level out, then you're done, but maybe you're not done. Right. Right. But like, if you actually can interpret what is a generalizing or what you're doing. What is, what is still changing, even though the loss is not changing, then maybe you, you can actually not view it as a double descent problem. And actually you're just sort of translating the space in which you view loss and like, and then you have a smooth curve. Yeah.Mark Bissell [00:11:11]: I think that's certainly like the domain of, of problems that we're, that we're looking to get.Shawn Wang [00:11:15]: Yeah. To me, like double descent is like the biggest thing to like ML research where like, if you believe in scaling, then you don't need, you need to know where to scale. And. But if you believe in double descent, then you don't, you don't believe in anything where like anything levels off, like.Vibhu Sapra [00:11:30]: I mean, also tendentially there's like, okay, when you talk about the China vector, right. There's the subliminal learning work. It was from the anthropic fellows program where basically you can have hidden biases in a model. And as you distill down or, you know, as you train on distilled data, those biases always show up, even if like you explicitly try to not train on them. So, you know, it's just like another use case of. Okay. If we can interpret what's happening in post-training, you know, can we clear some of this? Can we even determine what's there? Because yeah, it's just like some worrying research that's out there that shows, you know, we really don't know what's going on.Mark Bissell [00:12:06]: That is. Yeah. I think that's the biggest sentiment that we're sort of hoping to tackle. Nobody knows what's going on. Right. Like subliminal learning is just an insane concept when you think about it. Right. Train a model on not even the logits, literally the output text of a bunch of random numbers. And now your model loves owls. And you see behaviors like that, that are just, they defy, they defy intuition. And, and there are mathematical explanations that you can get into, but. I mean.Shawn Wang [00:12:34]: It feels so early days. Objectively, there are a sequence of numbers that are more owl-like than others. There, there should be.Mark Bissell [00:12:40]: According to, according to certain models. Right. It's interesting. I think it only applies to models that were initialized from the same starting Z. Usually, yes.Shawn Wang [00:12:49]: But I mean, I think that's a, that's a cheat code because there's not enough compute. But like if you believe in like platonic representation, like probably it will transfer across different models as well. Oh, you think so?Mark Bissell [00:13:00]: I think of it more as a statistical artifact of models initialized from the same seed sort of. There's something that is like path dependent from that seed that might cause certain overlaps in the latent space and then sort of doing this distillation. Yeah. Like it pushes it towards having certain other tendencies.Vibhu Sapra [00:13:24]: Got it. I think there's like a bunch of these open-ended questions, right? Like you can't train in new stuff during the RL phase, right? RL only reorganizes weights and you can only do stuff that's somewhat there in your base model. You're not learning new stuff. You're just reordering chains and stuff. But okay. My broader question is when you guys work at an interp lab, how do you decide what to work on and what's kind of the thought process? Right. Because we can ramble for hours. Okay. I want to know this. I want to know that. But like, how do you concretely like, you know, what's the workflow? Okay. There's like approaches towards solving a problem, right? I can try prompting. I can look at chain of thought. I can train probes, SAEs. But how do you determine, you know, like, okay, is this going anywhere? Like, do we have set stuff? Just, you know, if you can help me with all that. Yeah.Myra Deng [00:14:07]: It's a really good question. I feel like we've always at the very beginning of the company thought about like, let's go and try to learn what isn't working in machine learning today. Whether that's talking to customers or talking to researchers at other labs, trying to understand both where the frontier is going and where things are really not falling apart today. And then developing a perspective on how we can push the frontier using interpretability methods. And so, you know, even our chief scientist, Tom, spends a lot of time talking to customers and trying to understand what real world problems are and then taking that back and trying to apply the current state of the art to those problems and then seeing where they fall down basically. And then using those failures or those shortcomings to understand what hills to climb when it comes to interpretability research. So like on the fundamental side, for instance, when we have done some work applying SAEs and probes, we've encountered, you know, some shortcomings in SAEs that we found a little bit surprising. And so have gone back to the drawing board and done work on that. And then, you know, we've done some work on better foundational interpreter models. And a lot of our team's research is focused on what is the next evolution beyond SAEs, for instance. And then when it comes to like control and design of models, you know, we tried steering with our first API and realized that it still fell short of black box techniques like prompting or fine tuning. And so went back to the drawing board and we're like, how do we make that not the case and how do we improve it beyond that? And one of our researchers, Ekdeep, who just joined is actually Ekdeep and Atticus are like steering experts and have spent a lot of time trying to figure out like, what is the research that enables us to actually do this in a much more powerful, robust way? So yeah, the answer is like, look at real world problems, try to translate that into a research agenda and then like hill climb on both of those at the same time.Shawn Wang [00:16:04]: Yeah. Mark has the steering CLI demo queued up, which we're going to go into in a sec. But I always want to double click on when you drop hints, like we found some problems with SAEs. Okay. What are they? You know, and then we can go into the demo. Yeah.Myra Deng [00:16:19]: I mean, I'm curious if you have more thoughts here as well, because you've done it in the healthcare domain. But I think like, for instance, when we do things like trying to detect behaviors within models that are harmful or like behaviors that a user might not want to have in their model. So hallucinations, for instance, harmful intent, PII, all of these things. We first tried using SAE probes for a lot of these tasks. So taking the feature activation space from SAEs and then training classifiers on top of that, and then seeing how well we can detect the properties that we might want to detect in model behavior. And we've seen in many cases that probes just trained on raw activations seem to perform better than SAE probes, which is a bit surprising if you think that SAEs are actually also capturing the concepts that you would want to capture cleanly and more surgically. And so that is an interesting observation. I don't think that is like, I'm not down on SAEs at all. I think there are many, many things they're useful for, but we have definitely run into cases where I think the concept space described by SAEs is not as clean and accurate as we would expect it to be for actual like real world downstream performance metrics.Mark Bissell [00:17:34]: Fair enough. Yeah. It's the blessing and the curse of unsupervised methods where you get to peek into the AI's mind. But sometimes you wish that you saw other things when you walked inside there. Although in the PII instance, I think weren't an SAE based approach actually did prove to be the most generalizable?Myra Deng [00:17:53]: It did work well in the case that we published with Rakuten. And I think a lot of the reasons it worked well was because we had a noisier data set. And so actually the blessing of unsupervised learning is that we actually got to get more meaningful, generalizable signal from SAEs when the data was noisy. But in other cases where we've had like good data sets, it hasn't been the case.Shawn Wang [00:18:14]: And just because you named Rakuten and I don't know if we'll get it another chance, like what is the overall, like what is Rakuten's usage or production usage? Yeah.Myra Deng [00:18:25]: So they are using us to essentially guardrail and inference time monitor their language model usage and their agent usage to detect things like PII so that they don't route private user information.Myra Deng [00:18:41]: And so that's, you know, going through all of their user queries every day. And that's something that we deployed with them a few months ago. And now we are actually exploring very early partnerships, not just with Rakuten, but with other people around how we can help with potentially training and customization use cases as well. Yeah.Shawn Wang [00:19:03]: And for those who don't know, like it's Rakuten is like, I think number one or number two e-commerce store in Japan. Yes. Yeah.Mark Bissell [00:19:10]: And I think that use case actually highlights a lot of like what it looks like to deploy things in practice that you don't always think about when you're doing sort of research tasks. So when you think about some of the stuff that came up there that's more complex than your idealized version of a problem, they were encountering things like synthetic to real transfer of methods. So they couldn't train probes, classifiers, things like that on actual customer data of PII. So what they had to do is use synthetic data sets. And then hope that that transfer is out of domain to real data sets. And so we can evaluate performance on the real data sets, but not train on customer PII. So that right off the bat is like a big challenge. You have multilingual requirements. So this needed to work for both English and Japanese text. Japanese text has all sorts of quirks, including tokenization behaviors that caused lots of bugs that caused us to be pulling our hair out. And then also a lot of tasks you'll see. You might make simplifying assumptions if you're sort of treating it as like the easiest version of the problem to just sort of get like general results where maybe you say you're classifying a sentence to say, does this contain PII? But the need that Rakuten had was token level classification so that you could precisely scrub out the PII. So as we learned more about the problem, you're sort of speaking about what that looks like in practice. Yeah. A lot of assumptions end up breaking. And that was just one instance where you. A problem that seems simple right off the bat ends up being more complex as you keep diving into it.Vibhu Sapra [00:20:41]: Excellent. One of the things that's also interesting with Interp is a lot of these methods are very efficient, right? So where you're just looking at a model's internals itself compared to a separate like guardrail, LLM as a judge, a separate model. One, you have to host it. Two, there's like a whole latency. So if you use like a big model, you have a second call. Some of the work around like self detection of hallucination, it's also deployed for efficiency, right? So if you have someone like Rakuten doing it in production live, you know, that's just another thing people should consider.Mark Bissell [00:21:12]: Yeah. And something like a probe is super lightweight. Yeah. It's no extra latency really. Excellent.Shawn Wang [00:21:17]: You have the steering demos lined up. So we were just kind of see what you got. I don't, I don't actually know if this is like the latest, latest or like alpha thing.Mark Bissell [00:21:26]: No, this is a pretty hacky demo from from a presentation that someone else on the team recently gave. So this will give a sense for, for technology. So you can see the steering and action. Honestly, I think the biggest thing that this highlights is that as we've been growing as a company and taking on kind of more and more ambitious versions of interpretability related problems, a lot of that comes to scaling up in various different forms. And so here you're going to see steering on a 1 trillion parameter model. This is Kimi K2. And so it's sort of fun that in addition to the research challenges, there are engineering challenges that we're now tackling. Cause for any of this to be sort of useful in production, you need to be thinking about what it looks like when you're using these methods on frontier models as opposed to sort of like toy kind of model organisms. So yeah, this was thrown together hastily, pretty fragile behind the scenes, but I think it's quite a fun demo. So screen sharing is on. So I've got two terminal sessions pulled up here. On the left is a forked version that we have of the Kimi CLI that we've got running to point at our custom hosted Kimi model. And then on the right is a set up that will allow us to steer on certain concepts. So I should be able to chat with Kimi over here. Tell it hello. This is running locally. So the CLI is running locally, but the Kimi server is running back to the office. Well, hopefully should be, um, that's too much to run on that Mac. Yeah. I think it's, uh, it takes a full, like each 100 node. I think it's like, you can. You can run it on eight GPUs, eight 100. So, so yeah, Kimi's running. We can ask it a prompt. It's got a forked version of our, uh, of the SG line code base that we've been working on. So I'm going to tell it, Hey, this SG line code base is slow. I think there's a bug. Can you try to figure it out? There's a big code base, so it'll, it'll spend some time doing this. And then on the right here, I'm going to initialize in real time. Some steering. Let's see here.Mark Bissell [00:23:33]: searching for any. Bugs. Feature ID 43205.Shawn Wang [00:23:38]: Yeah.Mark Bissell [00:23:38]: 20, 30, 40. So let me, uh, this is basically a feature that we found that inside Kimi seems to cause it to speak in Gen Z slang. And so on the left, it's still sort of thinking normally it might take, I don't know, 15 seconds for this to kick in, but then we're going to start hopefully seeing him do this code base is massive for real. So we're going to start. We're going to start seeing Kimi transition as the steering kicks in from normal Kimi to Gen Z Kimi and both in its chain of thought and its actual outputs.Mark Bissell [00:24:19]: And interestingly, you can see, you know, it's still able to call tools, uh, and stuff. It's um, it's purely sort of it's it's demeanor. And there are other features that we found for interesting things like concision. So that's more of a practical one. You can make it more concise. Um, the types of programs, uh, programming languages that uses, but yeah, as we're seeing it come in. Pretty good. Outputs.Shawn Wang [00:24:43]: Scheduler code is actually wild.Vibhu Sapra [00:24:46]: Yo, this code is actually insane, bro.Vibhu Sapra [00:24:53]: What's the process of training in SAE on this, or, you know, how do you label features? I know you guys put out a pretty cool blog post about, um, finding this like autonomous interp. Um, something. Something about how agents for interp is different than like coding agents. I don't know while this is spewing up, but how, how do we find feature 43, two Oh five. Yeah.Mark Bissell [00:25:15]: So in this case, um, we, our platform that we've been building out for a long time now supports all the sort of classic out of the box interp techniques that you might want to have like SAE training, probing things of that kind, I'd say the techniques for like vanilla SAEs are pretty well established now where. You take your model that you're interpreting, run a whole bunch of data through it, gather activations, and then yeah, pretty straightforward pipeline to train an SAE. There are a lot of different varieties. There's top KSAEs, batch top KSAEs, um, normal ReLU SAEs. And then once you have your sparse features to your point, assigning labels to them to actually understand that this is a gen Z feature, that's actually where a lot of the kind of magic happens. Yeah. And the most basic standard technique is look at all of your d input data set examples that cause this feature to fire most highly. And then you can usually pick out a pattern. So for this feature, If I've run a diverse enough data set through my model feature 43, two Oh five. Probably tends to fire on all the tokens that sounds like gen Z slang. You know, that's the, that's the time of year to be like, Oh, I'm in this, I'm in this Um, and, um, so, you know, you could have a human go through all 43,000 concepts andVibhu Sapra [00:26:34]: And I've got to ask the basic question, you know, can we get examples where it hallucinates, pass it through, see what feature activates for hallucinations? Can I just, you know, turn hallucination down?Myra Deng [00:26:51]: Oh, wow. You really predicted a project we're already working on right now, which is detecting hallucinations using interpretability techniques. And this is interesting because hallucinations is something that's very hard to detect. And it's like a kind of a hairy problem and something that black box methods really struggle with. Whereas like Gen Z, you could always train a simple classifier to detect that hallucinations is harder. But we've seen that models internally have some... Awareness of like uncertainty or some sort of like user pleasing behavior that leads to hallucinatory behavior. And so, yeah, we have a project that's trying to detect that accurately. And then also working on mitigating the hallucinatory behavior in the model itself as well.Shawn Wang [00:27:39]: Yeah, I would say most people are still at the level of like, oh, I would just turn temperature to zero and that turns off hallucination. And I'm like, well, that's a fundamental misunderstanding of how this works. Yeah.Mark Bissell [00:27:51]: Although, so part of what I like about that question is you, there are SAE based approaches that might like help you get at that. But oftentimes the beauty of SAEs and like we said, the curse is that they're unsupervised. So when you have a behavior that you deliberately would like to remove, and that's more of like a supervised task, often it is better to use something like probes and specifically target the thing that you're interested in reducing as opposed to sort of like hoping that when you fragment the latent space, one of the vectors that pops out.Vibhu Sapra [00:28:20]: And as much as we're training an autoencoder to be sparse, we're not like for sure certain that, you know, we will get something that just correlates to hallucination. You'll probably split that up into 20 other things and who knows what they'll be.Mark Bissell [00:28:36]: Of course. Right. Yeah. So there's no sort of problems with like feature splitting and feature absorption. And then there's the off target effects, right? Ideally, you would want to be very precise where if you reduce the hallucination feature, suddenly maybe your model can't write. Creatively anymore. And maybe you don't like that, but you want to still stop it from hallucinating facts and figures.Shawn Wang [00:28:55]: Good. So Vibhu has a paper to recommend there that we'll put in the show notes. But yeah, I mean, I guess just because your demo is done, any any other things that you want to highlight or any other interesting features you want to show?Mark Bissell [00:29:07]: I don't think so. Yeah. Like I said, this is a pretty small snippet. I think the main sort of point here that I think is exciting is that there's not a whole lot of inter being applied to models quite at this scale. You know, Anthropic certainly has some some. Research and yeah, other other teams as well. But it's it's nice to see these techniques, you know, being put into practice. I think not that long ago, the idea of real time steering of a trillion parameter model would have sounded.Shawn Wang [00:29:33]: Yeah. The fact that it's real time, like you started the thing and then you edited the steering vector.Vibhu Sapra [00:29:38]: I think it's it's an interesting one TBD of what the actual like production use case would be on that, like the real time editing. It's like that's the fun part of the demo, right? You can kind of see how this could be served behind an API, right? Like, yes, you're you only have so many knobs and you can just tweak it a bit more. And I don't know how it plays in. Like people haven't done that much with like, how does this work with or without prompting? Right. How does this work with fine tuning? Like, there's a whole hype of continual learning, right? So there's just so much to see. Like, is this another parameter? Like, is it like parameter? We just kind of leave it as a default. We don't use it. So I don't know. Maybe someone here wants to put out a guide on like how to use this with prompting when to do what?Mark Bissell [00:30:18]: Oh, well, I have a paper recommendation. I think you would love from Act Deep on our team, who is an amazing researcher, just can't say enough amazing things about Act Deep. But he actually has a paper that as well as some others from the team and elsewhere that go into the essentially equivalence of activation steering and in context learning and how those are from a he thinks of everything in a cognitive neuroscience Bayesian framework, but basically how you can precisely show how. Prompting in context, learning and steering exhibit similar behaviors and even like get quantitative about the like magnitude of steering you would need to do to induce a certain amount of behavior similar to certain prompting, even for things like jailbreaks and stuff. It's a really cool paper. Are you saying steering is less powerful than prompting? More like you can almost write a formula that tells you how to convert between the two of them.Myra Deng [00:31:20]: And so like formally equivalent actually in the in the limit. Right.Mark Bissell [00:31:24]: So like one case study of this is for jailbreaks there. I don't know. Have you seen the stuff where you can do like many shot jailbreaking? You like flood the context with examples of the behavior. And the topic put out that paper.Shawn Wang [00:31:38]: A lot of people were like, yeah, we've been doing this, guys.Mark Bissell [00:31:40]: Like, yeah, what's in this in context learning and activation steering equivalence paper is you can like predict the number. Number of examples that you will need to put in there in order to jailbreak the model. That's cool. By doing steering experiments and using this sort of like equivalence mapping. That's cool. That's really cool. It's very neat. Yeah.Shawn Wang [00:32:02]: I was going to say, like, you know, I can like back rationalize that this makes sense because, you know, what context is, is basically just, you know, it updates the KV cache kind of and like and then every next token inference is still like, you know, the sheer sum of everything all the way. It's plus all the context. It's up to date. And you could, I guess, theoretically steer that with you probably replace that with your steering. The only problem is steering typically is on one layer, maybe three layers like like you did. So it's like not exactly equivalent.Mark Bissell [00:32:33]: Right, right. There's sort of you need to get precise about, yeah, like how you sort of define steering and like what how you're modeling the setup. But yeah, I've got the paper pulled up here. Belief dynamics reveal the dual nature. Yeah. The title is Belief Dynamics Reveal the Dual Nature of Incompetence. And it's an exhibition of the practical context learning and activation steering. So Eric Bigelow, Dan Urgraft on the who are doing fellowships at Goodfire, Ekt Deep's the final author there.Myra Deng [00:32:59]: I think actually to your question of like, what is the production use case of steering? I think maybe if you just think like one level beyond steering as it is today. Like imagine if you could adapt your model to be, you know, an expert legal reasoner. Like in almost real time, like very quickly. efficiently using human feedback or using like your semantic understanding of what the model knows and where it knows that behavior. I think that while it's not clear what the product is at the end of the day, it's clearly very valuable. Thinking about like what's the next interface for model customization and adaptation is a really interesting problem for us. Like we have heard a lot of people actually interested in fine-tuning an RL for open weight models in production. And so people are using things like Tinker or kind of like open source libraries to do that, but it's still very difficult to get models fine-tuned and RL'd for exactly what you want them to do unless you're an expert at model training. And so that's like something we'reShawn Wang [00:34:06]: looking into. Yeah. I never thought so. Tinker from Thinking Machines famously uses rank one LoRa. Is that basically the same as steering? Like, you know, what's the comparison there?Mark Bissell [00:34:19]: Well, so in that case, you are still applying updates to the parameters, right?Shawn Wang [00:34:25]: Yeah. You're not touching a base model. You're touching an adapter. It's kind of, yeah.Mark Bissell [00:34:30]: Right. But I guess it still is like more in parameter space then. I guess it's maybe like, are you modifying the pipes or are you modifying the water flowing through the pipes to get what you're after? Yeah. Just maybe one way.Mark Bissell [00:34:44]: I like that analogy. That's my mental map of it at least, but it gets at this idea of model design and intentional design, which is something that we're, that we're very focused on. And just the fact that like, I hope that we look back at how we're currently training models and post-training models and just think what a primitive way of doing that right now. Like there's no intentionalityShawn Wang [00:35:06]: really in... It's just data, right? The only thing in control is what data we feed in.Mark Bissell [00:35:11]: So, so Dan from Goodfire likes to use this analogy of, you know, he has a couple of young kids and he talks about like, what if I could only teach my kids how to be good people by giving them cookies or like, you know, giving them a slap on the wrist if they do something wrong, like not telling them why it was wrong or like what they should have done differently or something like that. Just figure it out. Right. Exactly. So that's RL. Yeah. Right. And, and, you know, it's sample inefficient. There's, you know, what do they say? It's like slurping feedback. It's like, slurping supervision. Right. And so you'd like to get to the point where you can have experts giving feedback to their models that are, uh, internalized and, and, you know, steering is an inference time way of sort of getting that idea. But ideally you're moving to a world whereVibhu Sapra [00:36:04]: it is much more intentional design in perpetuity for these models. Okay. This is one of the questions we asked Emmanuel from Anthropic on the podcast a few months ago. Basically the question, was you're at a research lab that does model training, foundation models, and you're on an interp team. How does it tie back? Right? Like, does this, do ideas come from the pre-training team? Do they go back? Um, you know, so for those interested, you can, you can watch that. There wasn't too much of a connect there, but it's still something, you know, it's something they want toMark Bissell [00:36:33]: push for down the line. It can be useful for all of the above. Like there are certainly post-hocVibhu Sapra [00:36:39]: use cases where it doesn't need to touch that. I think the other thing a lot of people forget is this stuff isn't too computationally expensive, right? Like I would say, if you're interested in getting into research, MechInterp is one of the most approachable fields, right? A lot of this train an essay, train a probe, this stuff, like the budget for this one, there's already a lot done. There's a lot of open source work. You guys have done some too. Um, you know,Shawn Wang [00:37:04]: There's like notebooks from the Gemini team for Neil Nanda or like, this is how you do it. Just step through the notebook.Vibhu Sapra [00:37:09]: Even if you're like, not even technical with any of this, you can still make like progress. There, you can look at different activations, but, uh, if you do want to get into training, you know, training this stuff, correct me if I'm wrong is like in the thousands of dollars, not even like, it's not that high scale. And then same with like, you know, applying it, doing it for post-training or all this stuff is fairly cheap in scale of, okay. I want to get into like model training. I don't have compute for like, you know, pre-training stuff. So it's, it's a very nice field to get into. And also there's a lot of like open questions, right? Um, some of them have to go with, okay, I want a product. I want to solve this. Like there's also just a lot of open-ended stuff that people could work on. That's interesting. Right. I don't know if you guys have any calls for like, what's open questions, what's open work that you either open collaboration with, or like, you'd just like to see solved or just, you know, for people listening that want to get into McInturk because people always talk about it. What are, what are the things they should check out? Start, of course, you know, join you guys as well. I'm sure you're hiring.Myra Deng [00:38:09]: There's a paper, I think from, was it Lee, uh, Sharky? It's open problems and, uh, it's, it's a bit of interpretability, which I recommend everyone who's interested in the field. Read. I'm just like a really comprehensive overview of what are the things that experts in the field think are the most important problems to be solved. I also think to your point, it's been really, really inspiring to see, I think a lot of young people getting interested in interpretability, actually not just young people also like scientists to have been, you know, experts in physics for many years and in biology or things like this, um, transitioning into interp, because the barrier of, of what's now interp. So it's really cool to see a number to entry is, you know, in some ways low and there's a lot of information out there and ways to get started. There's this anecdote of like professors at universities saying that all of a sudden every incoming PhD student wants to study interpretability, which was not the case a few years ago. So it just goes to show how, I guess, like exciting the field is, how fast it's moving, how quick it is to get started and things like that.Mark Bissell [00:39:10]: And also just a very welcoming community. You know, there's an open source McInturk Slack channel. There are people are always posting questions and just folks in the space are always responsive if you ask things on various forums and stuff. But yeah, the open paper, open problems paper is a really good one.Myra Deng [00:39:28]: For other people who want to get started, I think, you know, MATS is a great program. What's the acronym for? Machine Learning and Alignment Theory Scholars? It's like the...Vibhu Sapra [00:39:40]: Normally summer internship style.Myra Deng [00:39:42]: Yeah, but they've been doing it year round now. And actually a lot of our full-time staff have come through that program or gone through that program. And it's great for anyone who is transitioning into interpretability. There's a couple other fellows programs. We do one as well as Anthropic. And so those are great places to get started if anyone is interested.Mark Bissell [00:40:03]: Also, I think been seen as a research field for a very long time. But I think engineering... I think engineers are sorely wanted for interpretability as well, especially at Goodfire, but elsewhere, as it does scale up.Shawn Wang [00:40:18]: I should mention that Lee actually works with you guys, right? And in the London office and I'm adding our first ever McInturk track at AI Europe because I see this industry applications now emerging. And I'm pretty excited to, you know, help push that along. Yeah, I was looking forward to that. It'll effectively be the first industry McInturk conference. Yeah. I'm so glad you added that. You know, it's still a little bit of a bet. It's not that widespread, but I can definitely see this is the time to really get into it. We want to be early on things.Mark Bissell [00:40:51]: For sure. And I think the field understands this, right? So at ICML, I think the title of the McInturk workshop this year was actionable interpretability. And there was a lot of discussion around bringing it to various domains. Everyone's adding pragmatic, actionable, whatever.Shawn Wang [00:41:10]: It's like, okay, well, we weren't actionable before, I guess. I don't know.Vibhu Sapra [00:41:13]: And I mean, like, just, you know, being in Europe, you see the Interp room. One, like old school conferences, like, I think they had a very tiny room till they got lucky and they got it doubled. But there's definitely a lot of interest, a lot of niche research. So you see a lot of research coming out of universities, students. We covered the paper last week. It's like two unknown authors, not many citations. But, you know, you can make a lot of meaningful work there. Yeah. Yeah. Yeah.Shawn Wang [00:41:39]: Yeah. I think people haven't really mentioned this yet. It's just Interp for code. I think it's like an abnormally important field. We haven't mentioned this yet. The conspiracy theory last two years ago was when the first SAE work came out of Anthropic was they would do like, oh, we just used SAEs to turn the bad code vector down and then turn up the good code. And I think like, isn't that the dream? Like, you know, like, but basically, I guess maybe, why is it funny? Like, it's... If it was realistic, it would not be funny. It would be like, no, actually, we should do this. But it's funny because we know there's like, we feel there's some limitations to what steering can do. And I think a lot of the public image of steering is like the Gen Z stuff. Like, oh, you can make it really love the Golden Gate Bridge, or you can make it speak like Gen Z. To like be a legal reasoner seems like a huge stretch. Yeah. And I don't know if that will get there this way. Yeah.Myra Deng [00:42:36]: I think, um, I will say we are announcing. Something very soon that I will not speak too much about. Um, but I think, yeah, this is like what we've run into again and again is like, we, we don't want to be in the world where steering is only useful for like stylistic things. That's definitely not, not what we're aiming for. But I think the types of interventions that you need to do to get to things like legal reasoning, um, are much more sophisticated and require breakthroughs in, in learning algorithms. And that's, um...Shawn Wang [00:43:07]: And is this an emergent property of scale as well?Myra Deng [00:43:10]: I think so. Yeah. I mean, I think scale definitely helps. I think scale allows you to learn a lot of information and, and reduce noise across, you know, large amounts of data. But I also think we think that there's ways to do things much more effectively, um, even, even at scale. So like actually learning exactly what you want from the data and not learning things that you do that you don't want exhibited in the data. So we're not like anti-scale, but we are also realizing that scale is not going to get us anywhere. It's not going to get us to the type of AI development that we want to be at in, in the future as these models get more powerful and get deployed in all these sorts of like mission critical contexts. Current life cycle of training and deploying and evaluations is, is to us like deeply broken and has opportunities to, to improve. So, um, more to come on that very, very soon.Mark Bissell [00:44:02]: And I think that that's a use basically, or maybe just like a proof point that these concepts do exist. Like if you can manipulate them in the precise best way, you can get the ideal combination of them that you desire. And steering is maybe the most coarse grained sort of peek at what that looks like. But I think it's evocative of what you could do if you had total surgical control over every concept, every parameter. Yeah, exactly.Myra Deng [00:44:30]: There were like bad code features. I've got it pulled up.Vibhu Sapra [00:44:33]: Yeah. Just coincidentally, as you guys are talking.Shawn Wang [00:44:35]: This is like, this is exactly.Vibhu Sapra [00:44:38]: There's like specifically a code error feature that activates and they show, you know, it's not, it's not typo detection. It's like, it's, it's typos in code. It's not typical typos. And, you know, you can, you can see it clearly activates where there's something wrong in code. And they have like malicious code, code error. They have a whole bunch of sub, you know, sub broken down little grain features. Yeah.Shawn Wang [00:45:02]: Yeah. So, so the, the rough intuition for me, the, why I talked about post-training was that, well, you just, you know, have a few different rollouts with all these things turned off and on and whatever. And then, you know, you can, that's, that's synthetic data you can kind of post-train on. Yeah.Vibhu Sapra [00:45:13]: And I think we make it sound easier than it is just saying, you know, they do the real hard work.Myra Deng [00:45:19]: I mean, you guys, you guys have the right idea. Exactly. Yeah. We replicated a lot of these features in, in our Lama models as well. I remember there was like.Vibhu Sapra [00:45:26]: And I think a lot of this stuff is open, right? Like, yeah, you guys opened yours. DeepMind has opened a lot of essays on Gemma. Even Anthropic has opened a lot of this. There's, there's a lot of resources that, you know, we can probably share of people that want to get involved.Shawn Wang [00:45:41]: Yeah. And special shout out to like Neuronpedia as well. Yes. Like, yeah, amazing piece of work to visualize those things.Myra Deng [00:45:49]: Yeah, exactly.Shawn Wang [00:45:50]: I guess I wanted to pivot a little bit on, onto the healthcare side, because I think that's a big use case for you guys. We haven't really talked about it yet. This is a bit of a crossover for me because we are, we are, we do have a separate science pod that we're starting up for AI, for AI for science, just because like, it's such a huge investment category and also I'm like less qualified to do it, but we actually have bio PhDs to cover that, which is great, but I need to just kind of recover, recap your work, maybe on the evil two stuff, but then, and then building forward.Mark Bissell [00:46:17]: Yeah, for sure. And maybe to frame up the conversation, I think another kind of interesting just lens on interpretability in general is a lot of the techniques that were described. are ways to solve the AI human interface problem. And it's sort of like bidirectional communication is the goal there. So what we've been talking about with intentional design of models and, you know, steering, but also more advanced techniques is having humans impart our desires and control into models and over models. And the reverse is also very interesting, especially as you get to superhuman models, whether that's narrow superintelligence, like these scientific models that work on genomics, data, medical imaging, things like that. But down the line, you know, superintelligence of other forms as well. What knowledge can the AIs teach us as sort of that, that the other direction in that? And so some of our life science work to date has been getting at exactly that question, which is, well, some of it does look like debugging these various life sciences models, understanding if they're actually performing well, on tasks, or if they're picking up on spurious correlations, for instance, genomics models, you would like to know whether they are sort of focusing on the biologically relevant things that you care about, or if it's using some simpler correlate, like the ancestry of the person that it's looking at. But then also in the instances where they are superhuman, and maybe they are understanding elements of the human genome that we don't have names for or specific, you know, yeah, discoveries that they've made that that we don't know about, that's, that's a big goal. And so we're already seeing that, right, we are partnered with organizations like Mayo Clinic, leading research health system in the United States, our Institute, as well as a startup called Prima Menta, which focuses on neurodegenerative disease. And in our partnership with them, we've used foundation models, they've been training and applied our interpretability techniques to find novel biomarkers for Alzheimer's disease. So I think this is just the tip of the iceberg. But it's, that's like a flavor of some of the things that we're working on.Shawn Wang [00:48:36]: Yeah, I think that's really fantastic. Obviously, we did the Chad Zuckerberg pod last year as well. And like, there's a plethora of these models coming out, because there's so much potential and research. And it's like, very interesting how it's basically the same as language models, but just with a different underlying data set. But it's like, it's the same exact techniques. Like, there's no change, basically.Mark Bissell [00:48:59]: Yeah. Well, and even in like other domains, right? Like, you know, robotics, I know, like a lot of the companies just use Gemma as like the like backbone, and then they like make it into a VLA that like takes these actions. It's, it's, it's transformers all the way down. So yeah.Vibhu Sapra [00:49:15]: Like we have Med Gemma now, right? Like this week, even there was Med Gemma 1.5. And they're training it on this stuff, like 3d scans, medical domain knowledge, and all that stuff, too. So there's a push from both sides. But I think the thing that, you know, one of the things about McInturpp is like, you're a little bit more cautious in some domains, right? So healthcare, mainly being one, like guardrails, understanding, you know, we're more risk adverse to something going wrong there. So even just from a basic understanding, like, if we're trusting these systems to make claims, we want to know why and what's going on.Myra Deng [00:49:51]: Yeah, I think there's totally a kind of like deployment bottleneck to actually using. foundation models for real patient usage or things like that. Like, say you're using a model for rare disease prediction, you probably want some explanation as to why your model predicted a certain outcome, and an interpretable explanation at that. So that's definitely a use case. But I also think like, being able to extract scientific information that no human knows to accelerate drug discovery and disease treatment and things like that actually is a really, really big unlock for science, like scientific discovery. And you've seen a lot of startups, like say that they're going to accelerate scientific discovery. And I feel like we actually are doing that through our interp techniques. And kind of like, almost by accident, like, I think we got reached out to very, very early on from these healthcare institutions. And none of us had healthcare.Shawn Wang [00:50:49]: How did they even hear of you? A podcast.Myra Deng [00:50:51]: Oh, okay. Yeah, podcast.Vibhu Sapra [00:50:53]: Okay, well, now's that time, you know.Myra Deng [00:50:55]: Everyone can call us.Shawn Wang [00:50:56]: Podcasts are the most important thing. Everyone should listen to podcasts.Myra Deng [00:50:59]: Yeah, they reached out. They were like, you know, we have these really smart models that we've trained, and we want to know what they're doing. And we were like, really early that time, like three months old, and it was a few of us. And we were like, oh, my God, we've never used these models. Let's figure it out. But it's also like, great proof that interp techniques scale pretty well across domains. We didn't really have to learn too much about.Shawn Wang [00:51:21]: Interp is a machine learning technique, machine learning skills everywhere, right? Yeah. And it's obviously, it's just like a general insight. Yeah. Probably to finance too, I think, which would be fun for our history. I don't know if you have anything to say there.Mark Bissell [00:51:34]: Yeah, well, just across the science. Like, we've also done work on material science. Yeah, it really runs the gamut.Vibhu Sapra [00:51:40]: Yeah. Awesome. And, you know, for those that should reach out, like, you're obviously experts in this, but like, is there a call out for people that you're looking to partner with, design partners, people to use your stuff outside of just, you know, the general developer that wants to. Plug and play steering stuff, like on the research side more so, like, are there ideal design partners, customers, stuff like that?Myra Deng [00:52:03]: Yeah, I can talk about maybe non-life sciences, and then I'm curious to hear from you on the life sciences side. But we're looking for design partners across many domains, language, anyone who's customizing language models or trying to push the frontier of code or reasoning models is really interesting to us. And then also interested in the frontier of modeling. There's a lot of models that work in, like, pixel space, as we call it. So if you're doing world models, video models, even robotics, where there's not a very clean natural language interface to interact with, I think we think that Interp can really help and are looking for a few partners in that space.Shawn Wang [00:52:43]: Just because you mentioned the keyword

Dr. Bill Morice is the President and CEO of Mayo Clinic Laboratories and the former longtime Chair of Lab Medicine and Pathology at Mayo. This week Dr. Morice gets into the specifics of Guillain-Barre syndrome (also known as Acute Inflammatory Demyelinating Polyneuropathy) and Shingles. The Christopher Gabriel Program ----------------------------------------------------------- Please Like, Comment and Follow 'The Christopher Gabriel Program' on all platforms: The Christopher Gabriel Program is available on the KMJNOW app, Apple Podcasts, Spotify, YouTube or wherever else you listen to podcasts. --- The Christopher Gabriel Program | Website | Facebook | X | Instagram | --- Everything KMJ KMJNOW App | Podcasts | Facebook | X | Instagram See omnystudio.com/listener for privacy information.

Host: Darryl S. Chutka, M.D.  Guest: George Wang, M.D.  Bicuspid aortic valve is a relatively common congenital heart disease. It can be associated with other genetic disorders such as Turner's Syndrome or exist as an isolated entity. In most cases, patients with a bicuspid aortic valve are initially asymptomatic; however later in the course, they may develop symptoms related to a subsequent aortic stenosis or regurgitation. It's also associated with a dilated ascending aorta with potential rupture if unrecognized. Therefore, it's in the patient's best interest to diagnose the condition as early as possible. What are the early symptoms and when should we suspect the patient may have a bicuspid aortic valve? What type of surveillance should be performed and when is surgery indicated? These are some of the questions I'll be asking my guest, Dr. George Wang, a cardiologist in the Department of Cardiovascular Medicine at the Arizona Campus of the Mayo Clinic as we discuss “Bicuspid Aortic Valve Disease”.  Mayo Clinic Talks: Heart Health | Mayo Clinic School of Continuous Professional Development  Connect with us! Mayo Clinic Talks Podcast Season 6 | Mayo Clinic School of Continuous Professional Development 

In this episode of “Answers From the Lab,” host Bobbi Pritt, M.D., chair of the Division of Clinical Microbiology at Mayo Clinic, is joined by William Morice II, M.D., Ph.D., president and CEO of Mayo Clinic Laboratories, to discuss Protecting Access to Medicare Act (PAMA) reform and celebrate an exciting milestone for Dr. Pritt's “Creepy Dreadful Wonderful Parasites” blog. Later in the episode, Dr. Pritt welcomes Angie Reese-Davis, Mayo Clinic Laboratories' director of operations, to explore how proactive monitoring, shipping workflows, teamwork, and ongoing process improvements all contribute to a resilient lab logistics system. PAMA reform update (00:34): Get the latest on PAMA delays and the new Reforming and Enhancing Sustainable Updates to Laboratory Testing Services (RESULTS) Act.Creepy Dreadful Wonderful Parasites (04:24): Go behind the scenes of the 800 parasite cases Dr. Pritt has featured on her long-running blog.Logistics at Mayo Clinic Laboratories (08:09): Learn how the team manages and tracks the 40,000 samples that arrive each day.Process improvement and resiliency (12:49): Discover how the logistics team continues to innovate and evolve to support clients more efficiently and effectively.Note: Information in this post was accurate at the time of its posting.

In this episode, Lyell K. Jones Jr, MD, FAAN, speaks with Aaron L. Berkowitz, MD, PhD, FAAN, who served as the guest editor of the February 2026 Neurology of Systemic Disease issue. They provide a preview of the issue, which publishes on February 2, 2026. Dr. Jones is the editor-in-chief of Continuum: Lifelong Learning in Neurology® and is a professor of neurology at Mayo Clinic in Rochester, Minnesota. Dr. Berkowitz is a Continuum® Audio interviewer and a professor of neurology in the Department of Neurology at the University of California, San Francisco, in San Francisco, California. Additional Resources Read the issue: continuum.aan.com Subscribe to Continuum®: shop.lww.com/Continuum Continuum® Aloud (verbatim audio-book style recordings of articles available only to Continuum® subscribers): continpub.com/Aloud More about the American Academy of Neurology: aan.com Social Media facebook.com/continuumcme @ContinuumAAN Host: @LyellJ Guest: @AaronLBerkowitz Full episode transcript available here Dr Jones: The human nervous system is so complex. You can spend your whole career studying it and still have plenty to learn. But the human brain does not exist in isolation. It's intricately connected with and reliant on other bodily systems. When those systems go awry, sometimes the first sign is in the nervous system. Today we will speak with Dr Aaron Berkowitz, an expert on the neurology of systemic disease, and learn a little about how these disorders can present and what we can do about it. Dr Jones: This is Dr Lyell Jones, Editor-in-Chief of Continuum. Thank you for listening to Continuum Audio. Be sure to visit the links in the episode notes for information about subscribing to the journal, listening to verbatim recordings of the articles, and exclusive access to interviews not featured on the podcast. Dr Jones: This is Dr Lyell Jones, Editor-in-Chief of Continuum: Lifelong Learning in Neurology. Today, I'm interviewing Dr Aaron Berkowitz, who is Continuum's guest editor for our latest issue of Continuum on the neurology of systemic disease. Dr Berkowitz is a professor of clinical neurology at the University of California, San Francisco, and he has an active practice as a neurohospitalist and in outpatient general neurology---and, importantly, as a clinician educator. In addition to numerous teaching awards, Dr Berkowitz has published several books and also serves on our editorial board for Continuum. Dr Berkowitz, welcome. Thank you for joining us. Why don't you introduce yourself to our listeners?  Dr Berkowitz: Thanks, Lyell. As you mentioned, I'm a general neurologist and neurohospitalist here in San Francisco, California at UCSF and very involved in resident education as well. And I was honored, flattered and a little bit frightened when I received the invitation to guest edit this massive issue on the neurology of systemic disease. But I've learned a ton, and it's been great to work with you and the incredible authors we recruited to write for us. And I'm excited to have the issue out in the world.  Dr Jones: Yeah, me too. And you and I have talked about it before: you're one of a very small group of people who have guest edited multiple issues on different topics, right?  Dr Berkowitz: That's right. I did the neuroinfectious disease issue in… was it 2020? 2021? Something like that.  Dr Jones: Yeah. So, congratulations, more people have walked on the moon than done what you've done. And I'm looking forward to chatting, Aaron, and really grateful for your work putting together a fantastic issue. I think our listeners will appreciate that the nervous system does not function in isolation. It's important to understand the neurologic manifestations of diseases that originate within the brain, spinal cord, nerves, muscles, etc., but also the manifestations of diseases that begin in other systems and, you know, may masquerade as a primary neurologic disorder. So, it's obviously an important topic for neurologists, since many of these patients are receiving care in another setting, perhaps from another specialist. I almost think of this issue of Continuum as a handbook for the consultant neurologist, inpatient or outpatient. I don't know. Do you think that's a fair characterization of the topic? Dr Berkowitz: Absolutely. I completely agree with you. I think, yeah, many of us go into neurology interested in our primary diseases, whether it's stroke or Parkinson's or neuropathy or particular interest in neurologic symptoms, whether they're cognitive, motor, sensory, visual. And we quickly learn in residency, right? As you said, a lot of what we see is neurologic manifestations of primary diseases. So, I don't know how similar this is to other training programs. But it seemed like, if I'm remembering correctly, my first year of residency was mostly on primary neurology services, general stroke, ICU. And we moved into the consultant role more in the PGY-3 year the next year. And I remember explaining to students rotating with us on the consult services, this is actually much more complex in a way, because the patient has some type of symptom in a much broader and much more complicated context of multiple things going on. And I call it "neurology in the wild." There's, like, neurology of, this patient's had a stroke and we know they have a stroke and we're trying to figure out why and treat it. That's all interesting. But our question here, is there a stroke needle buried in this haystack of all of these medical or surgical complications? And learning what I call neurology of X, which is really what this issue is; as you said, that there's a neurology of everything. There's a neurology of cardiac disease. There's a neurology of the peripartum. There's a neurology of rheumatologic disease. There's every new treatment that comes out in oncology has a neurology we learn, right? There's a neurology of everything.  Dr Jones: There's a lot of axes, right? There's the heart-brain axis and the kidney-brain axis. And… I think we cover everything except the spleen-brain axis, which maybe that's a thing, maybe not. I'll probably hear from all the spleen fans out there. So, I want to do a little bit of an experiment. We're going to do something new today on the podcast. Before we get into the questions, we're going to start with a Continuum Audio trivia question. So, this will be a first time ever. Dr Berkowitz, we all know that chronic hyperglycemia, or diabetes, can lead to many neurologic and systemic complications and that optimal glucose control is our goal. For our listeners, here's the question: what neurologic complication can occur from correcting hyperglycemia too quickly? What neurologic complication can occur from correcting hyperglycemia too quickly? Stick around to the end of our interview for the answer. So, Aaron, let's get right to it. You had a chance to review all the articles in this issue on the neurology of systemic disease. What do you think in all of those is the most exciting recent development for patients who fit into this category? Dr Berkowitz: Yeah, that's a great question. I think we talked about when we were putting this issue together, right, a lot of the Continuum subspecialty topics; there should have been updates on particular disease diagnostics, treatments, new phenotypes. Whereas here probably a lot less has changed in primary heart disease, primary cancer. As I'd like to say to our students trying to excite them about neurology, most specialties have new treatments, but I can name a large number of new diseases, right, that have been discovered since we've been out of training. So, a lot of the primary medicine stays the same, and the neurologic complications stay the same. But probably the thing that many readers will want to keep handy and will probably be much in need of update again in three years are the neurologic complications of all the new cancer treatments. So, if we think back to I finished training just over ten years ago when a lot of the fill-in-the-blank-umabs were coming out, CAR T therapy, and we were starting to see a lot of neurology, I remember, related to these and telling the oncologists and they said, oh, you just wait. We are seeing at the conferences that there's a lot of neurology to these. And I feel like that is always a moving target. And I think we are seeing a lot of those and it's hard to keep up with which treatments can cause which complications, which syndromes and which severities require holding the treatment when you can rechallenge longer-term complications of CAR T cell therapies now that we've learned more about the acute complications. So, Amy Pruitt from Penn has written us a fantastic article for this issue that covers a lot of the updates there. And I learned a lot from that. I feel like that's the one that just like every time the carnioplastic diseases are reviewed in Continuum, it seems like the table is another page longer from your colleagues there in Rochester teaching us about new antibodies. And I feel like, for this issue, that's one of the areas that felt like there was a lot of very new content to keep up with since last time.  Dr Jones: That's good news, right? It's good that we have new immunotherapies for cancer, but it does lead to neurologic catastrophes sometimes, and it is a moving target, really rapid. So, you mentioned that just over ten years ago you finished your training and now we see a lot more of these complex immunotherapy-related neurologic complications. What about in the other direction? Are there any things that you see less commonly now in your practice than you might have seen ten years ago right when you were finishing training?  Dr Berkowitz: I would say no, I think. I think we're seeing a lot of new stuff, and we're still seeing a high volume of the classic consults we tend to get, whether that's altered mental status in a patient who's systemically ill; weakness or difficulty reading from the ventilator in a patient who's critically ill; patient has endocarditis and has a stroke hemorrhage or mycotic aneurysm, what do we do? Yeah, one of the parts that was really fun and educational editing this issue is, I really wanted to ask the experts the questions I find that are really troubling and challenging and make sure we could understand their perspective on things like the endocarditis consult, which I always feel like each time there's some twist that even though the question is what do we do about this stroke and/or hemorrhage and/or aneurysm and is surgery safe? It seems like each time I always feel like I'm reinventing the wheel, trying to really sort out how to think about this. And we have a great article from Alvin Doss at Beth Israel and Steve Feskey from Boston Medical Center. It covers a lot of cardiology, as you know, in that article about a great section on endocarditis where every time it came back for review, I would say, but what about this? This comes up. What about this? Can you explain how you think about this for our readers? I don't know. I'd be curious to hear your perspective. It sounds like we agree on what has become more common. I don't think anything in neurology seems to become less… Dr Jones: Well, no, I guess we haven't really solved anything, I guess we haven't cured any problem. But that's okay, right? I mean, it's building on an established foundation of experience and history in our field. And you know, we mentioned earlier that in many ways this issue is kind of like a neurology consultant's handbook. We did something a little different with it in that sense. In addition to you serving as the guest editor, you have authored an article in the issue. It touches on something that we've talked about a couple of times, and I'd be interested to hear you talk through it with our listeners a little bit on how to approach the neurologic consultation. Tell us a little more about that and your article and how you approached it.  Dr Berkowitz: Oh, yeah, thanks. Well, thanks first of all for inviting me to think about a sort of introductory article to this issue. And I was trying to think about what to write about because, as you've said and we've been talking about, no one could know every neurologic complication of every medical disease, treatment, surgery, hospital context. Probably many of us don't even know all the muscle diseases, right, within neurology. So how could we know all this stuff? And we need some type of manual from our colleagues that can explain, okay, I know this patient has inflammatory bowel disease and they've had a stroke. Is that- are these related? Are these unrelated? And I thought the articles kind of answer all of these questions. What would I say beyond this patient has disease X and is on drug Y? Well, look up in this issue disease X and see what the neurology can be, common and rare and how often it's associated, how often it's the presenting feature, how often it means the treatment is failing, etc. I thought, I'm not sure there's much to say there. That's about a paragraph. And I thought, well, let's think even more broadly about neurologic consultation. And as you know, I like to think about diagnostic reasoning and clinical reasoning. And we talk a lot about framing bias right? And I think that is very common in consultative neurology because we'll be told in the consult or in the page or E-consult or whatever it is, this is a blank-year-old blank with a history of blank on treatment blank. And right away your mind is starting to say, oh, well, the patient just had heart disease, or, the patient is nine months pregnant, or, the patient is on an immune checkpoint inhibitor. And whether you want to do it or not, your mind is associating the patient's neurology with that. And it's- even if we know we're framing or anchoring, it's hard to kind of pull away from that. And most of the time, common things being common, a patient with cancer develops new neurology, It's probably the cancer, the treatment, or sometimes a paraneoplastic syndrome. But I've definitely found if you do a lot of inpatient neurology and a lot of consults that you're seeing so much and you have no choice but to apply these heuristics, because you're seeing a lot of volume quickly and the patients are in the hospital or they're being closely followed and outpatient setting by another specialist. You presume if you didn't get it quite right the first time, it's going to come back to you. And there's a little bit of difficulty figuring out, this is a case, actually, of all the altered mental status in acutely ill patients I got today, this is the one I should dig deeper in that I think this could turn out to be a stroke or encephalitis as opposed to delirium. I felt like that I really haven't approached that except knowing that it's easy to fall into traps. And so, I started to think about framing bias. You know, we talked about if we become aware of our biases, right, we're better at not falling prey to them. But it's subconscious. So, we might be applying it without even realizing, or even saying, I might be framing this case the wrong way, you can go right on framing it the wrong way. So, I want to kind of get a little more granular on what types of framing biases actually are relevant, specifically, to the console setting. And so, I tried to come up with a few more specific examples and try to think about ways that we could at least have a quick, if our knee-jerk is to associate primary disease X that the patient has or primary treatment X with neurologic symptom Y, what's at least a quick counter-knee jerk to say, what if it could be something else? So, for example, one of them I call "low signal-to-noise ratio bias." Altered mental status in the acutely ill hospitalized patient. What would you say, Lyell? 99 out of 100- 99.9 out of 100, it's not a primary neurologic disease. Is that fair to say? Dr Jones: Very high, yep. I agree. Dr Berkowitz: Yeah. But could it be a stroke? Could it be non-convulsive status epilepticus, meningitis encephalitis? So, how do we sort of counteract low signal-to-noise ratio bias, acknowledging it exists, acknowledging most of the time there is a low signal-to-noise, that it's not going to be neurology---to just for example, use the time course. This is pretty acute. Have I convinced myself this is not a stroke or a seizure or an acute neurologic infection? And if I'm not sure at the bedside, should I err on the side of more testing? Or the "curbside bias," as I call when your colleague just sends you a text message on your phone, No need to even open the chart, Dr Jones. Patient had a cerebellar stroke. Incidental. They're here for something else. Aspirin, right? Just like a super tentorial stroke. And you might reply thumbs up. And then imagine you open the CT scan and it's a huge cerebellar stroke with fourth ventricular compression- and patient can hide a lot of stroke back there, might just have a little ataxia. You were curbsided and that framed you to think, oh, they asked me, is aspirin okay for a cerebellar stroke and I said yes, without realizing actually the question should have been posed is, how do you manage a huge stroke with mass effect in the posterior fossa? So, these types of biases, I come up with five of them, I won't go through all of them. I'm in the article to sort of acknowledge for the reader, most of the time it's going to be what you look up in this issue, but how to think about the times where it might not be and how to be more precise about what framing is and different types of framing that occur specifically in the consultant arena. Dr Jones: And I think the longer we practice, the more of those low-frequency exceptions that you see. And, you know, and then it sticks in our mind and sometimes the bias swings the other way; people, you know, think primarily about the low frequency. And so, it's tricky. And what I really enjoyed about that article, we started talking about this probably more than a year ago, and more than a year ago, I would say relatively few clinicians were using a now widely popular large language model for clinical decision-making; we won't name the model. And now I think most clinicians are using it almost every day, right? And I think it puts a premium on how to think and how to engage with the patient, and less about the facts and the lists that a lot of conventional medical education really is derived from. So, I really appreciate that article. We can pat ourselves in the back. We had some foresight to put it in the issue, and I think it's a great addition to it. Dr Berkowitz: Thank you. Dr Jones: So, the list of potential topics when we think about the neurologic manifestations of systemic disease, we tend to break it down by organ systems, right? But the amount of things that could end up in the issue is almost infinite. Is there anything that, when you were putting this issue together---either in terms of the topics or editing the articles---is there anything that you wanted to include, but we just didn't have room? Dr Berkowitz: I certainly won't say we covered everything, but I will say we were able to recruit a fantastic team of authors. And as you and I also talked about at the beginning, although you could say, we're doing the movement disorders issue, let's find all the top movement disorders folks who are expert specialists in this field, there's not really a neurohematologist or a neurogastroenterologist out here. So, you and I put our heads together to think of phenomenal general neurologists in most cases, some subspecialists who know a lot about this but were also excited to read a lot more about it and assemble the existing knowledge by the practicing neurologist for the practicing neurologist. And I think with that approach and letting folks have kind of, you know, I asked some specific questions. These are topics I hope you'll cover. These are vexing questions in this area. I hope you'll find some answers to how often can this neurology be the primary feature of this rheumatologic disease with no systemic manifestations and when should we look or as we mentioned, the complicated endocarditis consult. I won't say we covered everything. This could be, and is, textbook-sized, and there are textbooks on this topic. But I think on the contrary, authors came back and had sections on things that I might not have thought to ask- to cover. Dr Sarah LaHue, my colleague here at UCSF, I asked for an article, as traditionally in this issue, on the neurology of pregnancy in the postpartum state and included, I think probably for the first time in Continuum, a fantastic review of neurologic considerations in patients in menopause, which I'm not sure has been covered before. So, things that I wouldn't have even thought to ask for. Our authors came back with some fantastic stuff. And the ICU article by Dr Shivani Ghoshal, instead of focusing just on altered mental status in the ICU, weakness in the ICU---those are all in there---I also asked her to discuss complications of procedures in the ICU. How often do procedures in the ICU cause local neuropathies or vascular injury, these types of things. Dr Jones: Yeah, me too. And I guess that's a great advertisement, that there probably are things that we didn't cover, but if there are, we can't think of them. We've done as best as we can. So now let's come back to our Continuum Audio trivia question for our listeners. And I'll repeat the question: what neurologic complication can occur from correcting hyperglycemia too quickly? And I actually think there might be two correct answers to this one. Dr Berkowitz, what do you think? Dr Berkowitz: Yeah, I was thinking of two things. I hope these are the things you're thinking of as well. One is what I think used to be referred to as insulin neuritis, sort of an acute painful small fiber neuropathy from after the initiation of insulin, I think also called treatment-induced diabetic neuropathy or something of that nature. And then the other one described, defined and classified by your colleagues there in Rochester, the diabetic lumbosacral radiculoplexis neuropathy or Bruns-Garland syndrome or a diabetic amyotropy, I think, can also---if I'm not mistaken---also occur in this context; you should have weight loss in association with diet treatment of diabetes. But how did I do? Dr Jones: Yeah, you win the prize, the first-ever prize. There's no monetary value to the prize, but pride, I think, is a good one. Yeah, those were the two I was thinking of. The treatment-induced neuropathy of diabetes is really nicely covered in Dr Rafid Mustafa's article on the neurologic complications of endocrine disorders. It's a rare condition characterized by the acute/subacute onset of diffuse neuropathic pain and some usually some autonomic dysfunction. And it occurs when you have rapid and substantial reductions in blood glucose levels. And you can almost map it out. There was a study from 2015 which is referenced in the article, which found that a drop in hemoglobin A1c of 2 to 3% over three months confers about a 20% absolute risk of developing this treatment-induced neuropathy of diabetes, and a drop of more than 4%, more than 80% risk. So, very substantial. And then in the other---we see this commonly in patients with diabetic lumbosacral radiculoplexis neuropathy---they have the subacute onset of usually asymmetric pain and weakness in the lower limbs that tends to occur more frequently in patients who have had recent better control of their sugar. We can also see it in the upper limbs too. So, you get a perfect score. Dr Berkowitz, well done. Again, I want to thank you. I want to thank you for such a great issue, a great article to kick off the issue, and a great discussion of the neurology of systemic disease. Today I learned a lot talking today, I learned a lot reading the issue. Really grateful for your leadership of putting it together, pulling together a really great author panel, and I think it will come in handy not just for our junior readers and listeners, but also our more experienced subscribers as well. Dr Berkowitz: Thank you so much. Like I said, it was a big honor to be invited to guest edit this issue. I've read it every three years since I started residency. It's always one of my favorite issues. As you said, a manual for consultative neurology, and I learned a ton from our authors and really appreciate the opportunity to work with you and the amazing Continuum team to bring this from an idea, as you said, probably over a year ago to a printed issue. So, thanks again, Lyell. Dr Jones: Thank you. And again, we've been speaking with Dr Aaron Berkowitz, guest editor of Continuum's most recent issue on the neurology of systemic disease. Please check it out, and thank you to our listeners for joining today. Dr Monteith: This is Dr Teshamae Monteith, Associate Editor of Continuum Audio. If you've enjoyed this episode, you'll love the journal, which is full of in-depth and clinically relevant information important for neurology practitioners. Use the link in the episode notes to learn more and subscribe. Thank you for listening to Continuum Audio.

Cardiovascular disease remains the leading cause of death in the United States, yet new science and smarter systems are changing what is possible for patients and families. In this episode of Tomorrow's Cure, host Cathy Wurzer talks with three leaders who are reshaping how we prevent, understand, and treat heart disease and obesity. Mayo Clinic gastroenterologist Dr. Andres Acosta explains why obesity is not “one size fits all” and how phenotype based, precision treatments can double weight loss success and reduce cardiovascular risk. American Heart Association CEO Nancy Brown explores why heart disease still claims so many lives, how social and economic forces drive risk, and what it will take to improve health for every community. Dr. Kevin Volpp, scientific lead of the AHA Food is Medicine initiative, shares how medically tailored meals and behavioral economics could cut costly hospital readmissions and make healthy eating more affordable. Listen to hear personal stories, practical takeaways, and a hopeful look at the future of heart health. How to listen and stay connected: Subscribe to Tomorrow's Cure on your favorite podcast app and follow the show so you never miss an episode. Get the latest health information from Mayo Clinic's experts—subscribe to Mayo Clinic's newsletter for free today: https://mayocl.in/3EcNPNc Connect with Mayo Clinic: Like Mayo Clinic on Facebook: https://www.facebook.com/mayoclinic/ Follow Mayo Clinic on Instagram: https://www.instagram.com/mayoclinic/ Follow Mayo Clinic on X (formerly Twitter): https://x.com/MayoClinic Follow Mayo Clinic on Threads: https://www.threads.net/@mayoclinic

Are all ultra-processed foods bad for your health? New science says no — and the details may surprise you. In this episode of The Exam Room Podcast, host Chuck Carroll is joined by Dr. Hana Kahleova, director of clinical research at the Physicians Committee for Responsible Medicine, to break down a comprehensive review of more than 300 studies examining ultra-processed foods, diabetes, heart disease, and mortality. The findings challenge common assumptions and reveal that not all processed foods impact health the same way. In this episode, you'll learn: - Which ultra-processed foods are most strongly linked to diabetes and heart disease - Why meat and processed meat are the primary drivers of harm - How some breads, cereals, and plant-based processed foods may actually be protective - The role fiber plays in processed foods and metabolic health - Why current dietary guidelines may be oversimplifying processed foods

Host: Darryl S. Chutka, M.D.  Guest: Julie Rosenthal, M.D.  Cardiac amyloidosis is not a common condition, but it is important for primary care clinicians to recognize it in our patients. It's commonly underdiagnosed as the symptoms are often assumed to be due to other, more common cardiac problems. Early recognition is important since this can result in improved treatment options and better patient outcomes. So how do we recognize cardiac amyloidosis? What are the presenting symptoms and what's the best way to establish an accurate diagnosis? I'll be asking my guest these questions as we discuss cardiac amyloidosis. My guest for tis podcast is Dr. Julie Rosenthal, a cardiologist in the Department of Cardiovascular Medicine at the Arizona campus of the Mayo Clinic.   Mayo Clinic Talks: Heart Health | Mayo Clinic School of Continuous Professional Development  Connect with us! Mayo Clinic Talks Podcast Season 6 | Mayo Clinic School of Continuous Professional Development 

Defying 1974 Terminal Diagnosis Without Chemo – B17, Nutrition Choices, and How New Guidelines Validate Real Food Over Processed Poison Streaming live today on Dangerous Dames: Hosts Courtenay Turner and Dr. Lee Merritt welcome Rick Hill, a 51-year cancer survivor, author, and Oasis of Hope ambassador who turned a grim 1974 Mayo Clinic stage 3 embryonal cell carcinoma diagnosis into a legacy of hope. Rick defied conventional paths—no chemo or radiation—choosing metabolic therapy, targeted nutrition including B17, and strict anti-sugar/real food protocols that kept him thriving for decades. 'I'm Alive Today Because I Didn't Follow the Old Guidelines,' Rick shares, critiquing 1970s low-fat/high-carb disasters while celebrating how today's federal shifts finally echo what saved him: avoid ultra-processed poisons, protect metabolism, eat real food. This episode connects personal proof to policy headlines, challenging Big Sugar influences and exploring transparency in cancer prevention/treatment choices. Inspiring for anyone facing adversity or questioning mainstream narratives. Support natural approaches at https://rncstore.com/dangerous – use code 'dangerous' for discounts on Rick's prevention bundles, B17 products, and more. Tune in for dangerous truths that empower real healing! Too hot for YouTube — live at 5pm Central on Rumble.Read the accompanying article to this episode, here: https://courtenayturner.substack.com/p/dangerous-dames-ep86-battling-big Replay & archives at https://thedangerousdames.comSupport the show (code “dangerous” at affiliates) and subscribe — the map is being redrawn this week.Let's get dangerous. ▶Support our show by supporting your health & wealth!
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Episode#327-Taped January 21, 2026 We talk about behavior lifestyle change and how it starts with a positive mindset. Lifestyle change starts in the mind and not in the gym. According to the Mayo Clinic, studies show that personality traits such as optimism and pessimism can affect many areas of your health and well-being. Joining us is Jonathan Boulware, a lifestyle behavior change specialist and creator of the 432 Playbook  and author of his free e-book, “Take control of your body before it takes control of you”. He will discuss with us his personal health journey, the core principles behind the 432 Playbook and what we need to do to have sustainable lifestyle change and transformation. Find out more about Jonathan Boulware and his programs. Youcanbeatobesity.com It's All About Health & Fitness-Vicki Doe Fitness podcast Ranked #5 on the Top 25 Midwest Fitness Podcasts to Listen to… with additional national recognition as #53 on the Top 100 US fitness podcast. Rate This Podcast Give us a 5-star review.  We appreciate you! Take this quick audience survey. Thank you! FREE Metabolic Makeover Masterclass Webinar Replay! Learn how to reset your metabolism, boost energy, and support sustainable weight loss using simple, science-backed strategies. Enroll in the Vicki Doe Fitness Academy to get instant access to the replay and begin your healthy living journey today. Vicki Doe Fitness-STORE Discover the Vicki Doe Fitness-STORE—your destination for stylish apparel, fitness gear, and wellness essentials like yoga mats, water bottles, candles, and premium supplements. Shop now and elevate your health journey! Resources *Note: Some of the resources below may be affiliate links, meaning Vicki Doe Fitness receives a commission (at no extra cost to you) if you use the link to make a purchase. Thank you for your support! Herbs and spices are the keys to delicious, flavorful, and sophisticated meals! FREE DOWNLOAD- Herbs and Spices Cheatsheet Let's get ECO-friendly.  Try ECOLunchbox.com ECOlunchbox specializes in stainless steel bento boxes, artisan fair trade lunch bags, napkins, snack sacks, and other eco-friendly lunchware. They are a certified green business.  ECOlunchbox is a consumer products company started by an eco mom in the San Francisco Bay Area. ECOLunchbox.com Go to our Resources page-   For the most recommended tools, you need to succeed on your healthy living journey!! Listen and share our podcast show- “It's All About Health & Fitness-” Vicki Doe Fitness Subscribe to Apple Podcast Subscribe on Stitcher Or on any of the platforms that you listen to your podcast! Watch & Subscribe on YouTube! Catch our latest health & wellness videos on YouTube at Vicki Haywood Doe – Vicki Doe FitnessSubscribe now and join the movement!

January 29, 2026: Your daily rundown of health and wellness news, in under 5 minutes. Today's top stories: Sword Health acquires Kaia Health for $285M, expanding AI Care platform into Germany's 70M+ person reimbursement system Flo Health and Mayo Clinic study finds U.S. women lag behind UK, Canada, and Australia in recognizing perimenopause symptoms Life Biosciences receives FDA clearance for first human trial of partial cellular reprogramming, targeting glaucoma using gene therapy More from Fitt: Fitt Insider breaks down the convergence of fitness, wellness, and healthcare — and what it means for business, culture, and capital. Subscribe to our newsletter → insider.fitt.co/subscribe Work with our recruiting firm → https://talent.fitt.co/ Follow us on Instagram → https://www.instagram.com/fittinsider/ Follow us on LinkedIn → linkedin.com/company/fittinsider Reach out → insider@fitt.co

You don't need another diet. You need a system that lasts. In this powerful episode of The Exam Room Podcast, host Chuck Carroll sits down with body recomposition expert and Forever Fit author Maxime Sigouin to reveal how you can build muscle, burn fat, and stay strong for life — at any age. Whether you're 40, 60, or even 80+, your body is still capable of transformation. In this episode you'll learn: • Why most diets fail long-term • The difference between fat loss and body recomposition • How to reverse diet and avoid rebound weight gain • Why strength training is essential as we age • The mindset that drives lifelong success • How daily movement burns more calories than gym workouts