## Step 1: Define the symbolic representation of the problem
The problem involves two variables: 'milligrams of vitamin B12' and 'milligrams of vitamin B3'. Let's denote 'milligrams of vitamin B12' as $x_0$ and 'milligrams of vitamin B3' as $x_1$. The objective function to maximize is $5.84x_0 + 1.76x_1$.

## Step 2: List the constraints in symbolic notation
The constraints given are:
- Digestive support index: $3x_0 + 7x_1 \geq 13$
- Cardiovascular support index: $4x_0 + 4x_1 \geq 3$
- Cognitive performance index: $5x_0 + 9x_1 \geq 13$
- Additional constraint: $5x_0 - 9x_1 \geq 0$
- Upper bounds:
  - Digestive support index: $3x_0 + 7x_1 \leq 55$
  - Cardiovascular support index: $4x_0 + 4x_1 \leq 14$
  - Cognitive performance index: $5x_0 + 9x_1 \leq 15$
- Variable restrictions:
  - $x_0$ is an integer
  - $x_1$ is a continuous variable

## 3: Create a symbolic representation of the problem
The symbolic representation is:
```json
{
'sym_variables': [('x0', 'milligrams of vitamin B12'), ('x1', 'milligrams of vitamin B3')],
'objective_function': '5.84*x0 + 1.76*x1',
'constraints': [
    '3*x0 + 7*x1 >= 13',
    '4*x0 + 4*x1 >= 3',
    '5*x0 + 9*x1 >= 13',
    '5*x0 - 9*x1 >= 0',
    '3*x0 + 7*x1 <= 55',
    '4*x0 + 4*x1 <= 14',
    '5*x0 + 9*x1 <= 15'
]
}
```

## 4: Implement the problem in Gurobi
To solve this problem using Gurobi, we will use Python. First, ensure you have Gurobi installed in your Python environment.

```python
import gurobi

# Define the model
model = gurobi.Model()

# Define the variables
x0 = model.addVar(name="x0", vtype=gurobi.GRB.INTEGER)  # milligrams of vitamin B12
x1 = model.addVar(name="x1")  # milligrams of vitamin B3

# Objective function: maximize 5.84*x0 + 1.76*x1
model.setObjective(5.84*x0 + 1.76*x1, gurobi.GRB.MAXIMIZE)

# Constraints
model.addConstr(3*x0 + 7*x1 >= 13, name="digestive_support_index_min")
model.addConstr(4*x0 + 4*x1 >= 3, name="cardiovascular_support_index_min")
model.addConstr(5*x0 + 9*x1 >= 13, name="cognitive_performance_index_min")
model.addConstr(5*x0 - 9*x1 >= 0, name="additional_constraint")
model.addConstr(3*x0 + 7*x1 <= 55, name="digestive_support_index_max")
model.addConstr(4*x0 + 4*x1 <= 14, name="cardiovascular_support_index_max")
model.addConstr(5*x0 + 9*x1 <= 15, name="cognitive_performance_index_max")

# Optimize the model
model.optimize()

# Print the solution
if model.status == gurobi.GRB.OPTIMAL:
    print("Optimal solution found.")
    print(f"Milligrams of vitamin B12: {x0.varValue}")
    print(f"Milligrams of vitamin B3: {x1.varValue}")
    print(f"Objective: {model.objVal}")
else:
    print("No optimal solution found.")
```