```json
{
  "sym_variables": [
    ("x0", "grams of fat"),
    ("x1", "milligrams of vitamin C"),
    ("x2", "milligrams of iron"),
    ("x3", "milligrams of vitamin B3")
  ],
  "objective_function": "4*x0 + 5*x1 + 5*x2 + 2*x3",
  "constraints": [
    "7*x1 + 6*x2 >= 15",
    "7*x0 + 6*x1 >= 8",
    "6*x1 + 5*x3 >= 8",
    "7*x0 + 5*x3 >= 8",
    "6*x1 + 6*x2 + 5*x3 >= 18",
    "7*x0 + 6*x1 + 6*x2 + 5*x3 >= 18",
    "3*x1 + 8*x2 >= 11",
    "8*x2 + 10*x3 >= 19",
    "1*x0 + 3*x1 >= 15",
    "3*x1 + 8*x2 + 10*x3 >= 25",
    "1*x0 + 3*x1 + 8*x2 + 10*x3 >= 25",
    "6*x1 + 3*x3 >= 23",
    "8*x0 + 6*x1 >= 19",
    "6*x1 + 9*x2 >= 23",
    "8*x0 + 9*x2 + 3*x3 >= 22",
    "8*x0 + 6*x1 + 9*x2 + 3*x3 >= 22",
    "6*x0 + 3*x3 >= 21",
    "3*x1 + 3*x3 >= 16",
    "6*x0 + 3*x1 + 6*x2 + 3*x3 >= 16",
    "9*x0 + 7*x1 >= 16",
    "9*x0 + 7*x1 + 2*x2 + 7*x3 >= 16",
    "10*x1 - 7*x2 >= 0",
    "-9*x0 + 7*x1 >= 0",
    "6*x2 + 5*x3 <= 25",
    "8*x2 + 10*x3 <= 88",
    "1*x0 + 10*x3 <= 84",
    "9*x2 + 3*x3 <= 77",
    "8*x0 + 3*x3 <= 46",
    "9*x0 + 7*x3 <= 20",
    "2*x2 + 7*x3 <= 35",
    "7*x1 + 2*x2 <= 23",
    "7*x1 + 7*x3 <= 50",
    "9*x0 + 7*x1 + 2*x2 <= 76",
    "9*x0 + 2*x2 + 7*x3 <= 50",
    "7*x1 + 2*x2 + 7*x3 <= 60",
    "x0 integer",
    "x1 integer"

  ]
}
```

```python
import gurobipy as gp

# Create a new model
m = gp.Model("nutrition_optimization")

# Create variables
fat = m.addVar(vtype=gp.GRB.INTEGER, name="fat")
vitamin_c = m.addVar(vtype=gp.GRB.INTEGER, name="vitamin_c")
iron = m.addVar(vtype=gp.GRB.CONTINUOUS, name="iron")
vitamin_b3 = m.addVar(vtype=gp.GRB.CONTINUOUS, name="vitamin_b3")


# Set objective function
m.setObjective(4*fat + 5*vitamin_c + 5*iron + 2*vitamin_b3, gp.GRB.MINIMIZE)

# Add constraints
m.addConstr(7*vitamin_c + 6*iron >= 15)
m.addConstr(7*fat + 6*vitamin_c >= 8)
m.addConstr(6*vitamin_c + 5*vitamin_b3 >= 8)
m.addConstr(7*fat + 5*vitamin_b3 >= 8)
m.addConstr(6*vitamin_c + 6*iron + 5*vitamin_b3 >= 18)
m.addConstr(7*fat + 6*vitamin_c + 6*iron + 5*vitamin_b3 >= 18)
m.addConstr(3*vitamin_c + 8*iron >= 11)
m.addConstr(8*iron + 10*vitamin_b3 >= 19)
m.addConstr(1*fat + 3*vitamin_c >= 15)
m.addConstr(3*vitamin_c + 8*iron + 10*vitamin_b3 >= 25)
m.addConstr(1*fat + 3*vitamin_c + 8*iron + 10*vitamin_b3 >= 25)
m.addConstr(6*vitamin_c + 3*vitamin_b3 >= 23)
m.addConstr(8*fat + 6*vitamin_c >= 19)
m.addConstr(6*vitamin_c + 9*iron >= 23)
m.addConstr(8*fat + 9*iron + 3*vitamin_b3 >= 22)
m.addConstr(8*fat + 6*vitamin_c + 9*iron + 3*vitamin_b3 >= 22)
m.addConstr(6*fat + 3*vitamin_b3 >= 21)
m.addConstr(3*vitamin_c + 3*vitamin_b3 >= 16)
m.addConstr(6*fat + 3*vitamin_c + 6*iron + 3*vitamin_b3 >= 16)
m.addConstr(9*fat + 7*vitamin_c >= 16)
m.addConstr(9*fat + 7*vitamin_c + 2*iron + 7*vitamin_b3 >= 16)
m.addConstr(10*vitamin_c - 7*iron >= 0)
m.addConstr(-9*fat + 7*vitamin_c >= 0)
m.addConstr(6*iron + 5*vitamin_b3 <= 25)
m.addConstr(8*iron + 10*vitamin_b3 <= 88)
m.addConstr(1*fat + 10*vitamin_b3 <= 84)
m.addConstr(9*iron + 3*vitamin_b3 <= 77)
m.addConstr(8*fat + 3*vitamin_b3 <= 46)
m.addConstr(9*fat + 7*vitamin_b3 <= 20)
m.addConstr(2*iron + 7*vitamin_b3 <= 35)
m.addConstr(7*vitamin_c + 2*iron <= 23)
m.addConstr(7*vitamin_c + 7*vitamin_b3 <= 50)
m.addConstr(9*fat + 7*vitamin_c + 2*iron <= 76)
m.addConstr(9*fat + 2*iron + 7*vitamin_b3 <= 50)
m.addConstr(7*vitamin_c + 2*iron + 7*vitamin_b3 <= 60)



# Optimize model
m.optimize()

# Print solution
if m.status == gp.GRB.OPTIMAL:
    print('Obj: %g' % m.objVal)
    print('Fat: %g' % fat.x)
    print('Vitamin C: %g' % vitamin_c.x)
    print('Iron: %g' % iron.x)
    print('Vitamin B3: %g' % vitamin_b3.x)
elif m.status == gp.GRB.INFEASIBLE:
    print('Model is infeasible')
else:
    print('Optimization ended with status %d' % m.status)
```