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Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-20 23:52:15 +09:00

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---
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 |