『LEVELS – A Whole New Level』のカバーアート

LEVELS – A Whole New Level

LEVELS – A Whole New Level

著者： Levels
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Levels helps you understand your metabolic health with personalized data, expert guidance, and tools that connect your daily choices to measurable changes in your body. Our goal is to help you make better decisions about food, exercise, sleep, and long-term health. Connect with us: Become a Member: https://levels.link/wnl YouTube: https://youtube.com/@levels Instagram: https://instagram.com/levels Twitter: https://twitter.com/levels LinkedIn: https://linkedin.com/company/levels TikTok: https://tiktok.com/@levelsLevels 衛生・健康的な生活
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  • #311 - Can Your Blood Predict Your Future Health? | Dr. Tony Wyss-Coray & Mike Haney

    #311 - Can Your Blood Predict Your Future Health? | Dr. Tony Wyss-Coray & Mike Haney
    2026/09/17
    From a single blood sample, new proteomic tools can now measure thousands of proteins at once. Dr. Tony Wyss-Coray’s lab is using that flood of data, together with machine learning, to build a much higher-resolution picture of what’s happening throughout the body and where someone’s health may be headed.The early signals are striking. In one analysis of people who appeared healthy by conventional measures, every additional 4.1 years of estimated heart age was associated with nearly 2.5 times the risk of heart failure over the following 15 years. Wyss-Coray sees this kind of measurement eventually becoming a “health compass”: something that could show which parts of the body are changing fastest, then help track whether an intervention is actually moving them in the right direction.Free course: Improve your metabolic healthGet our free email course on how glucose, nutrition, exercise, sleep, and measurement can help you build habits that support better energy and long-term health: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://levels.link/wnl⁠What We Cover:How a drop of blood can now reveal information from thousands of proteinsWhy aging appears to happen in waves rather than at a steady rateWhy one part of the body may age faster than the restWhat young-blood experiments in mice taught Wyss-Coray about proteins and brain agingHow the work is moving from whole organs down to individual cell typesWhy the field’s biggest constraint may now be data collection rather than better AI🎙️ About the Guest:Dr. Tony Wyss-Coray is the D.H. Chen Distinguished Professor of Neurology and Neurological Sciences at Stanford University and director of the Phil and Penny Knight Initiative for Brain Resilience.📍What Dr. Tony Wyss-Coray & Mike Haney discussed:04:03 Proteins 101: the building blocks hiding information about your health05:09 How one blood sample can measure thousands of proteins09:07 Using machine learning to find patterns in the proteome12:17 Can blood reveal what’s happening inside the brain?13:11 What happened when young blood was given to old mice19:45 Why aging may happen in waves rather than at a steady rate29:24 How stable are protein measurements over time?32:37 Can proteins predict disease years before it appears?40:35 Why one part of your body may age faster than the rest46:31 The missing test: does an intervention actually change the measurement?51:04 Going from whole organs to individual cell types54:10 Why more data, not better AI, is the current bottleneck57:18 A future “health compass” for the body🔗 Helpful Links:Organ aging signatures in the plasma proteome track health and disease (Nature, 2023)PaperThe foundational organ-aging work discussed in the episode, using plasma proteins to estimate aging across 11 organs.Plasma proteomic signatures of cellular aging predict human disease (Nature Medicine, 2026)PaperThe newer study extending the approach to more than 40 cell types using over 7,000 plasma proteins.Undulating changes in human plasma proteome profiles across the lifespan (Nature Medicine, 2019)PaperYoung blood reverses age-related impairments in cognitive function and synaptic plasticity in mice (Nature Medicine, 2014)PaperUK Biobank Research resourceThe large longitudinal cohort used for much of the disease-prediction work discussed in the episode.Watch the conversation: https://youtu.be/1dfMBAZiP8oFind us on YouTube: ⁠⁠⁠⁠⁠⁠⁠⁠⁠https://youtube.com/levelshealth?sub_confirmation=1⁠⁠⁠⁠⁠⁠⁠⁠📲 Connect:Connect with Dr. Tony Wyss-Coray at Stanford 👋 Who we are:Levels helps you understand your metabolic health with personalized data, expert guidance, and tools that connect your daily choices to measurable changes in your body. Our goal is to help you make better decisions about food, exercise, sleep, and long-term health.Look for new shows every month on A Whole New Level, where we have in-depth conversations with thought leaders about metabolic health.
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  • #310 - Can We Measure Aging Well Enough to Treat It? | Dr. Nir Barzilai & Mike Haney

    #310 - Can We Measure Aging Well Enough to Treat It? | Dr. Nir Barzilai & Mike Haney
    2026/09/10
    Aging science has gotten much better at describing who appears to be aging faster or slower. What medicine still lacks is a reliable feedback loop: a way to tell whether something we do is actually changing the biology that drives age-related disease.Dr. Nir Barzilai argues that solving that measurement problem could turn geroscience from an interesting field of research into something doctors can actually use: measure where you are, intervene, measure again, and learn what works.Free course: Improve your metabolic healthGet our free email course on how glucose, nutrition, exercise, sleep, and measurement can help you build habits that support better energy and long-term health: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://levels.link/wnl⁠What We Cover:What centenarians reveal about living longer and spending less time sickWhy changing one hallmark of aging can affect several othersHow TAME was designed to test metformin as an anti-aging drug and to convince the FDA to treat aging itself as an endpoint—and why it failed to get off the groundWhy metformin, SGLT2 inhibitors, GLP-1 agonists, and some osteoporosis drugs are being studied as potential gerotherapeutics, or anti-aging drugsHow FAST is searching existing clinical trials for biomarkers that change when an intervention affects aging biologyWhether aging needs continuous monitoring or can be meaningfully tracked a few times a year🎙️ About the Guest:Dr. Nir Barzilai is the Ingeborg and Ira Leon Rennert Chair in Aging Research and a professor of medicine and genetics at Albert Einstein College of Medicine, where he directs the Institute for Geroscience. 📍What Dr. Nil Barzilai & Mike Haney discussed:05:10 - Aging is a condition, not just a label05:59 - Why aging is what drives disease08:19 - Should we call aging a disease?10:20 - Why the species may have a ceiling around 11514:34 - Why changing one hallmark of aging changes the others23:08 - Metformin was anti-aging before it was a diabetes drug31:55 - Centenarians live longer and spend less time sick40:12 - How TAME tried to make aging an FDA endpoint48:17 - Metformin, SGLT2s, GLP-1s, and osteoporosis drugs as gerotherapeutics52:26 - FAST: finding biomarkers that actually change with treatment56:49 - Whether aging needs continuous monitoring, or a few checks a year1:01:16 - Where behavior still fits once we have anti-aging drugs🔗 Helpful Links:Hallmarks of Aging: An Expanding Universe (Cell, 2023) PaperCompression of Morbidity Is Observed Across Cohorts with Exceptional Longevity (JAGS, 2016) PaperMetformin as a Tool to Target Aging (Cell Metabolism, 2016) PaperGeroscience-Guided Repurposing of FDA-Approved Drugs to Target Aging (Aging Cell, 2022) PaperBiomarkers of Aging for the Identification and Evaluation of Longevity Interventions (Cell, 2023) PaperFAST: Finding Aging Biomarkers by Searching Existing Trials FAST InitiativeARPA-H PROSPR / FAST award ARPA-H FAST projectWatch the conversation: https://youtu.be/HbeGjwCw6vkFind us on YouTube: ⁠⁠⁠⁠⁠⁠⁠⁠https://youtube.com/levelshealth?sub_confirmation=1⁠⁠⁠⁠⁠⁠⁠📲 Connect:Connect with Dr. Nil Barzilai on X: https://x.com/NirBarzilaiMD👋 Who we are:Levels helps you understand your metabolic health with personalized data, expert guidance, and tools that connect your daily choices to measurable changes in your body. Our goal is to help you make better decisions about food, exercise, sleep, and long-term health.Look for new shows every month on A Whole New Level, where we have in-depth conversations with thought leaders about metabolic health.
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  • #309 - What AI Sees That Doctors Can’t | Dr. Ziad Obermeyer & Mike Haney

    #309 - What AI Sees That Doctors Can’t | Dr. Ziad Obermeyer & Mike Haney
    2026/09/03
    Medical AI is already getting good at doing things doctors do. Dr. Ziad Obermeyer thinks the bigger opportunity is using AI to discover things medicine doesn’t yet know.His work shows both sides of that future: algorithms can amplify bad assumptions when trained on the wrong targets, but they can also uncover signals in medical data that humans miss. Obermeyer argues that as more health data is collected outside the hospital, AI could turn it into a continuous picture of health rather than a series of isolated snapshots.Free course: Improve your metabolic healthGet our free email course on how glucose, nutrition, exercise, sleep, and measurement can help you build habits that support better energy and long-term health: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://levels.link/wnl⁠What We Cover:Why AI should learn from patients and outcomes, not just doctorsHow an ECG model found hidden risk of sudden cardiac deathWhy medical data access is still a major bottleneckHow more measurement could actually mean fewer unnecessary testsWhy healthcare may be entering a “mainframe to PC” transition🎙️ About the Guest:Dr. Ziad Obermeyer is an emergency medicine physician and an Associate Professor at the UC Berkeley School of Public Health. He also co-founded Dandelion Health and the non-profit Nightingale Open Science. 📍What Dr. Ziad Obermeyer & Mike Haney discussed:02:43 Why better data is fundamental to medical AI05:54 The problem: There’s no variable called “get sick”09:27 Algorithms optimize exactly what you tell them to23:03 Why teaching AI to copy doctors limits what it can discover26:28 How AI could create a new science of medicine28:40 Could AI predict sudden cardiac death before it happens?34:14 Can an algorithm teach us what it sees?36:50 Medicine’s biggest AI bottleneck: access to data49:00 Healthcare’s “mainframe to PC” transition55:08 Why more measurement could actually mean fewer tests58:46 Why medical AI is aiming too low1:02:13 What the next generation of wearables needs to measure🔗 Helpful Links:Dissecting Racial Bias in an Algorithm Used to Manage the Health of Populations (Science, 2019)https://www.science.org/doi/10.1126/science.aax2342An Algorithmic Approach to Reducing Unexplained Pain Disparities in Underserved Populations (Nature Medicine, 2021)https://www.nature.com/articles/s41591-020-01192-7An ECG Biomarker for Sudden Cardiac Death Discovered with Deep Learning (Nature, 2026)https://www.nature.com/articles/s41586-026-10674-6Predicting the Future — Big Data, Machine Learning, and Clinical Medicine (NEJM, 2016)https://www.nejm.org/doi/full/10.1056/NEJMp1606181Nightingale Open Sciencehttps://www.nightingalescience.org/Dandelion Healthhttps://dandelionhealth.ai/Watch the conversation: https://youtu.be/WDo-iL6O5nUFind us on YouTube: ⁠⁠⁠⁠⁠⁠⁠https://youtube.com/levelshealth?sub_confirmation=1⁠⁠⁠⁠⁠⁠📲 Connect:Connect with Dr. Ziad Obermeyer on https://ziadobermeyer.com/👋 Who we are:Levels helps you understand your metabolic health with personalized data, expert guidance, and tools that connect your daily choices to measurable changes in your body. Our goal is to help you make better decisions about food, exercise, sleep, and long-term health.Look for new shows every month on A Whole New Level, where we have in-depth conversations with thought leaders about metabolic health.
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    1 時間 6 分
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