DataFood Engine.Monexa Data Node
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Verified Asset
High Efficiency

Muffin mix.

Metabolic profile analysis. Technical breakdown of Muffin mix and its impact on skeletal muscle retention and daily energy expenditure.

Total Energy11kcal
Bio-Protein12g
Carbohydrates51g
Total Lipids5g

Nutritional Efficiency Report

Muffin mix is a very low-calorie food with moderate-protein content. At 11 kcal per 100g, it delivers 12g of protein — representing 436% of its total caloric load. Carbohydrates account for 1855% and fats for 409% of calories.

"Efficiency Score 1.00 — this asset ranks in the top tier of the DataFood database for protein delivery per calorie. Optimal for fat loss, lean bulking, and body recomposition phases."

At 51g carbs per 100g, it is better suited to carb-cycling or maintenance phases.

With only 11 kcal per 100g, Muffin mix is a high-volume food — you can consume a large serving while keeping total caloric intake controlled. This makes it particularly effective for hunger management in deficit phases.

Protocol Compatibility

Ketosis Impact

At 51g carbs per 100g, it is better suited to carb-cycling or maintenance phases.

Thermic Effect (TEF)

With 12g protein per 100g, the thermic contribution is moderate. Pairing with higher-protein sources increases the overall TEF of your meal and supports lean mass retention.

Expand Your Protocol.

Based on the metabolic profile of Muffin mix, these related data nodes are most relevant to your nutrition architecture:

Fat Loss Foods Database Balanced Nutrition Guide

Integrate Asset.

Use the clinical weekly planner to distribute Muffin mix across your metabolic windows.

Generate Weekly Protocol

Input physical metrics to generate a synchronized 7-day protocol.

1. Biological Metrics

2. Dietary Logic

Institutional Disclaimer: The nutritional data provided for Muffin mix is derived from clinical databases and algorithmic estimation. This report is for metabolic infrastructure planning only and does not constitute medical advice. Consult a clinical nutritionist before implementing aggressive deficit protocols.