--- id: wiki-2026-0508-nutritional-biochemistry title: Nutritional Biochemistry category: 10_Wiki/Topics status: verified canonical_id: self aliases: [영양 생화학, Nutrient Biochemistry, Metabolic Nutrition] duplicate_of: none source_trust_level: A confidence_score: 0.9 verification_status: applied tags: [biochemistry, nutrition, metabolism, biology, health] raw_sources: [] last_reinforced: 2026-05-10 github_commit: pending tech_stack: language: domain-knowledge framework: biochemistry --- # Nutritional Biochemistry ## 매 한 줄 > **"매 nutrient 는 metabolic substrate + cofactor + signal"**. Nutritional biochemistry 는 macronutrient 와 micronutrient 가 cellular metabolism, gene expression, signaling 에 어떻게 작용하는지 연구. 2026 perspective 에서 personalized nutrition + microbiome interaction + metabolomics 가 frontier. ## 매 핵심 ### 매 macronutrient pathways - **Carbohydrate**: glycolysis → pyruvate → acetyl-CoA → TCA → ETC. 4 kcal/g. - **Lipid**: β-oxidation → acetyl-CoA → TCA. 9 kcal/g. Membrane lipids, eicosanoids. - **Protein**: amino acid → transamination → urea / gluconeogenesis. 4 kcal/g. ### 매 micronutrient roles - **B-vitamins**: coenzymes (NAD, FAD, CoA, THF, PLP). - **Fat-soluble (ADEK)**: signaling (retinoic acid, calcitriol). - **Minerals**: cofactors (Mg-ATP, Zn-fingers, Fe-heme), electrolytes. ### 매 응용 1. Sports nutrition / supplement design. 2. Disease management (diabetes, NAFLD). 3. Personalized diet (genotype + microbiome). 4. Public health policy. ## 💻 패턴 ### Basal metabolic rate (Mifflin-St Jeor) ```python def bmr(weight_kg, height_cm, age_y, sex="M"): base = 10*weight_kg + 6.25*height_cm - 5*age_y return base + 5 if sex == "M" else base - 161 def tdee(bmr_val, activity="moderate"): factors = {"sedentary": 1.2, "light": 1.375, "moderate": 1.55, "active": 1.725} return bmr_val * factors[activity] ``` ### Macro split optimization ```python def macro_split(tdee, goal="maintain", body_kg=70): protein_g = body_kg * (1.6 if goal == "cut" else 1.2) p_cal = protein_g * 4 fat_cal = tdee * 0.25 carb_cal = tdee - p_cal - fat_cal return {"protein_g": protein_g, "fat_g": fat_cal / 9, "carb_g": carb_cal / 4} ``` ### Glycemic load ```python def glycemic_load(food: dict) -> float: return food["gi"] * food["carb_g"] / 100 # Low <10, medium 11-19, high 20+ ``` ### TCA cycle ATP yield ```python def atp_per_glucose(): glycolysis = 2 nadh_glyc = 2 * 2.5 pyruvate_to_acetyl = 2 * 2.5 tca_per_acetyl = (3*2.5) + 1.5 + 1 tca_total = 2 * tca_per_acetyl return glycolysis + nadh_glyc + pyruvate_to_acetyl + tca_total # ≈ 30 ATP / glucose (modern stoichiometry) ``` ### Nitrogen balance ```python def n_balance(protein_intake_g, urea_n_excreted_g, fecal_skin_g=4): n_in = protein_intake_g / 6.25 n_out = urea_n_excreted_g + fecal_skin_g return n_in - n_out ``` ### Vitamin D activation cascade ```python def vit_d_activation(): return [ "7-dehydrocholesterol", "cholecalciferol (D3, skin UVB)", "25-OH-D3 (liver, CYP2R1)", "1,25-(OH)2-D3 (kidney, CYP27B1, calcitriol)", "VDR-RXR transcription factor", ] ``` ## 매 결정 기준 | 상황 | Approach | |---|---| | Weight loss | Caloric deficit + protein-priority | | Performance | Periodized carb + creatine | | T2D management | Low GL + Mediterranean | | Deficiency screen | Serum 25-OH-D, B12, ferritin, Mg | **기본값**: TDEE 기반 + protein floor + micronutrient screen. ## 🔗 Graph ## 🤖 LLM 활용 **언제**: meal plan template, nutrient interaction summary, label decoding. **언제 X**: clinical diagnosis / Rx — RD / MD 필수. ## ❌ 안티패턴 - **Calorie-only thinking**: hormone / micronutrient 무시. - **Single-nutrient hype**: antioxidant / superfood 일반화 — context-free. - **Ignoring bioavailability**: total intake ≠ absorbed. - **Population stat → individual**: personal genetics / microbiome 무시. ## 🧪 검증 / 중복 - Verified (Lehninger 8e, Modern Nutrition in Health and Disease 11e, USDA DRI 2024). - 신뢰도 A. ## 🕓 Changelog | 날짜 | 변경 | |---|---| | 2026-05-08 | Phase 1 | | 2026-05-10 | Manual cleanup — BMR/macro/TCA/Vit-D 패턴 |