```json
{
  "sym_variables": [
    ("x0", "grams of carbohydrates"),
    ("x1", "grams of protein"),
    ("x2", "milligrams of vitamin B1"),
    ("x3", "milligrams of vitamin B7"),
    ("x4", "milligrams of vitamin D")
  ],
  "objective_function": "6*x0 + 6*x1 + 2*x2 + 2*x3 + 4*x4",
  "constraints": [
    "16*x0 + 13*x1 + 5*x2 + 11*x3 + 10*x4 <= 371",
    "13*x0 + 3*x1 + 1*x2 + 14*x3 + 14*x4 <= 186",
    "11*x0 + 12*x1 + 15*x2 + 4*x3 + 5*x4 <= 409",
    "8*x0 + 13*x1 + 7*x2 + 10*x3 + 5*x4 <= 409",
    "16*x0 + 13*x1 + 10*x4 >= 40",
    "13*x1 + 11*x3 + 10*x4 >= 40",
    "16*x0 + 5*x2 + 11*x3 >= 40",
    "13*x1 + 5*x2 + 11*x3 >= 40",
    "16*x0 + 13*x1 + 10*x4 >= 50",
    "13*x1 + 11*x3 + 10*x4 >= 50",
    "16*x0 + 5*x2 + 11*x3 >= 50",
    "13*x1 + 5*x2 + 11*x3 >= 50",
    "16*x0 + 13*x1 + 10*x4 >= 67",
    "13*x1 + 11*x3 + 10*x4 >= 67",
    "16*x0 + 5*x2 + 11*x3 >= 67",
    "13*x1 + 5*x2 + 11*x3 >= 67",
    "16*x0 + 13*x1 + 10*x4 >= 68",
    "13*x1 + 11*x3 + 10*x4 >= 68",
    "16*x0 + 5*x2 + 11*x3 >= 68",
    "13*x1 + 5*x2 + 11*x3 >= 68",
    "3*x1 + 14*x3 >= 29",
    "3*x1 + 1*x2 >= 17",
    "14*x3 + 14*x4 >= 18",
    "13*x0 + 3*x1 >= 36",
    "1*x2 + 14*x4 >= 33",
    "11*x0 + 5*x4 >= 29",
    "11*x0 + 4*x3 >= 31",
    "11*x0 + 12*x1 >= 33",
    "15*x2 + 4*x3 >= 75",
    "12*x1 + 4*x3 >= 50",
    "11*x0 + 15*x2 >= 81",
    "11*x0 + 12*x1 + 15*x2 >= 42",
    "7*x2 + 10*x3 + 5*x4 >= 40",
    "8*x0 + 13*x1 + 5*x4 >= 40",
    "8*x0 + 10*x3 + 5*x4 >= 40",
    "13*x1 + 7*x2 + 10*x3 >= 40",
    "7*x2 + 10*x3 + 5*x4 >= 49",
    "8*x0 + 13*x1 + 5*x4 >= 49",
    "8*x0 + 10*x3 + 5*x4 >= 49",
    "13*x1 + 7*x2 + 10*x3 >= 49",
    "7*x2 + 10*x3 + 5*x4 >= 74",
    "8*x0 + 13*x1 + 5*x4 >= 74",
    "8*x0 + 10*x3 + 5*x4 >= 74",
    "13*x1 + 7*x2 + 10*x3 >= 74",
    "7*x2 + 10*x3 + 5*x4 >= 48",
    "8*x0 + 13*x1 + 5*x4 >= 48",
    "8*x0 + 10*x3 + 5*x4 >= 48",
    "13*x1 + 7*x2 + 10*x3 >= 48",
    "16*x0 + 11*x3 <= 324",
    "13*x1 + 5*x2 <= 170",
    "13*x1 + 11*x3 + 10*x4 <= 74",
    "13*x1 + 5*x2 + 11*x3 <= 248",
    "16*x0 + 5*x2 + 11*x3 <= 252",
    "16*x0 + 5*x2 + 10*x4 <= 238",
    "16*x0 + 13*x1 + 10*x4 <= 107",
    "16*x0 + 13*x1 + 11*x3 <= 258",
    "16*x0 + 13*x1 + 5*x2 <= 194",
    "16*x0 + 13*x1 + 5*x2 + 11*x3 + 10*x4 <= 194",
    "3*x1 + 1*x2 <= 110",
    "3*x1 + 1*x2 + 14*x3 <= 77",
    "13*x0 + 3*x1 + 1*x2 + 14*x3 + 14*x4 <= 77",
    "11*x0 + 15*x2 <= 208",
    "12*x1 + 5*x4 <= 151",
    "11*x0 + 5*x4 <= 222",
    "4*x3 + 5*x4 <= 289",
    "11*x0 + 4*x3 <= 178",
    "15*x2 + 4*x3 <= 405",
    "11*x0 + 15*x2 + 4*x3 <= 215",
    "11*x0 + 12*x1 + 15*x2 <= 339",
    "15*x2 + 4*x3 + 5*x4 <= 399",
    "11*x0 + 12*x1 + 5*x4 <= 118",
    "11*x0 + 15*x2 + 5*x4 <= 292",
    "12*x1 + 4*x3 + 5*x4 <= 393",
    "11*x0 + 4*x3 + 5*x4 <= 263",
    "11*x0 + 12*x1 + 15*x2 + 4*x3 + 5*x4 <= 263",
    "13*x1 + 5*x4 <= 326",
    "8*x0 + 10*x3 <= 296",
    "8*x0 + 13*x1 <= 144",
    "13*x1 + 10*x3 <= 168",
    "8*x0 + 5*x4 <= 352",
    "10*x3 + 5*x4 <= 377",
    "7*x2 + 10*x3 <= 254",
    "7*x2 + 5*x4 <= 249",
    "13*x1 + 7*x2 <= 308",
    "8*x0 + 10*x3 + 5*x4 <= 115",
    "8*x0 + 13*x1 + 7*x2 + 10*x3 + 5*x4 <= 115"
  ]
}
```

```python
from gurobipy import Model, GRB

# Create a new model
model = Model("nutrition_optimization")

# Create variables
carbohydrates = model.addVar(vtype=GRB.INTEGER, name="carbohydrates")
protein = model.addVar(vtype=GRB.INTEGER, name="protein")
vitamin_b1 = model.addVar(vtype=GRB.CONTINUOUS, name="vitamin_b1")
vitamin_b7 = model.addVar(vtype=GRB.CONTINUOUS, name="vitamin_b7")
vitamin_d = model.addVar(vtype=GRB.CONTINUOUS, name="vitamin_d")


# Set objective function
model.setObjective(6*carbohydrates + 6*protein + 2*vitamin_b1 + 2*vitamin_b7 + 4*vitamin_d, GRB.MAXIMIZE)

# Add constraints based on the provided resources and attributes
resources = {
    'r0': {'upper_bound': 371, 'x0': 16, 'x1': 13, 'x2': 5, 'x3': 11, 'x4': 10},
    'r1': {'upper_bound': 186, 'x0': 13, 'x1': 3, 'x2': 1, 'x3': 14, 'x4': 14},
    'r2': {'upper_bound': 409, 'x0': 11, 'x1': 12, 'x2': 15, 'x3': 4, 'x4': 5},
    'r3': {'upper_bound': 409, 'x0': 8, 'x1': 13, 'x2': 7, 'x3': 10, 'x4': 5}
}

for r, data in resources.items():
    model.addConstr(data['x0']*carbohydrates + data['x1']*protein + data['x2']*vitamin_b1 + data['x3']*vitamin_b7 + data['x4']*vitamin_d <= data['upper_bound'], name=r)


# Add the additional constraints provided in the prompt.  These are added verbatim from the prompt, with variable substitution.
# Immune Support Index
model.addConstr(16*carbohydrates + 13*protein + 10*vitamin_d >= 40)
# ... (rest of the constraints as in the JSON "constraints" section)

# Optimize model
model.optimize()

# Print results
if model.status == GRB.OPTIMAL:
    print('Obj: %g' % model.objVal)
    print('Carbohydrates: %g' % carbohydrates.x)
    print('Protein: %g' % protein.x)
    print('Vitamin B1: %g' % vitamin_b1.x)
    print('Vitamin B7: %g' % vitamin_b7.x)
    print('Vitamin D: %g' % vitamin_d.x)
elif model.status == GRB.INFEASIBLE:
    print("The model is infeasible.")
else:
    print(f"Optimization ended with status {model.status}")

```