Episode
[SPECIAL EDITION] 🍭 The Metabolic Hijack: Algorithmic Engineering of Modern Disease
- Podcast
- AI Unraveled: Latest AI News, ChatGPT, Gemini, Claude, DeepSeek, Gen AI, LLMs, Agents, Ethics, Bias
- Published
- May 27, 2026
- Duration seconds
- 1460
- Processing state
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- https://rss.com/podcasts/djamgatech/2841205
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Summary
🎧 Listen ADS-FREE: https://podcasts.apple.com/us/channel/djamgamind/id6760446113 Visit our Research Hub at https://djamgamind.com Subscribe to our Newsletter at https://enoumen.substack.com #DJAMGAMIND #AIRIA Summary: In this special investigative edition, we deconstruct the modern chronic disease engine. We analyze the pioneering clinical work of Dr. David Unwin, who translated the glycemic load of foods into "teaspoon of sugar" equivalents to reverse Type 2 diabetes. We dive into the pathophysiology of Non-Alcoholic Fatty Liver Disease (NAFLD) and how fructose acts as a silent data sink. We explore the neurochemical hijack of food addiction and the molecular links between glucose and oncogenesis. Finally, we expose the algorithmic arms race: how Big Food uses AI to design hyper-palatable foods, and how health tech is deploying machine learning to restore metabolic health. Itemized Important Topics: The Teaspoon Metric: Dr. David Unwin's framework showing a healthy adult has only 4 grams (one teaspoon) of circulating blood glucose. The Silent Data Sink: How dietary fructose bypasses peripheral circulation, driving hepatic lipogenesis and fatty liver disease. The Neurochemical Hijack: The 5 clinical stages of food addiction caused by ultra-processed foods downregulating dopamine D2 receptors. The Sugar-Cancer Nexus: How chronic sugar consumption triggers the Warburg Effect and activates the PI3K/Akt signaling cascade to fuel tumor growth. The Algorithmic Arms Race: Big Food conglomerates using machine learning (like Gastrograph AI) to map flavor profiles, contrasted with health tech using deep learning on Continuous Glucose Monitors. Macroeconomic Signals: The financial burden of metabolic failure, costing US employers $1.43 trillion annually in lost productivity. 🔗 RE…