Dave Feldman sits down with Chris MacAskill to unpack the Keto-CTA study: owning key mistakes, dissecting plaque progression metrics, and charting the path forward in lipid research. Along the way, they explore observational data limits, AI-guided imaging, and the role of community and social media in driving scientific discovery. Chapters 00:00 Intro & Study Context 00:04 Acknowledging Mistakes & Team Dynamics 01:03 Figure 1A Graphical vs Numerical Error 03:09 Importance of Table 3 & Endpoint Inclusion 05:00 Heterogeneity in Non-Calcified Plaque Progression 07:47 Observational Data & Causation Debate 11:13 What Is Percent Atheroma Volume (PAV)? 15:00 Semi-Quantitative vs Quantitative Metrics 16:15 Cohort-Wide 50 % Increase in PAV 18:06 Biology vs Algorithm in AI Readings 20:59 Comparison with Miami Heart Cohort 25:30 Why a Control Group Was Challenging 30:00 Sources of Saturated Fat & LDL Impact 34:00 Lean Mass Hyper-Responder Physiology 40:00 Protein Shake Rate-of-Change Analogy 44:...